Planet Neuroscience

arXiv:2502.14337v1 Announce Type: new Abstract: Although individual neurons and neural populations exhibit the phenomenon of representational drift, perceptual and behavioral outputs of many neural circuits can remain stable across time scales over which representational drift is substantial. These observations motivate a dynamical systems framework for neural network activity that focuses on the concept of \emph{latent processing units,} core elements for robust coding and computation embedded in collective neural dynamics. Our theoretical treatment of these latent processing units yields five key attributes of computing through neural network dynamics. First, neural computations that are low-dimensional can nevertheless generate high-dimensional neural dynamics. Second, the manifolds defined by neural dynamical trajectories exhibit an inherent coding redundancy as a direct consequence of the universal computing capabilities of the underlying dynamical system. Third, linear readouts or decoders of neural population activity can suffice to optimally subserve downstream circuits controlling behavioral outputs. Fourth, whereas recordings from thousands of neurons may suffice for near optimal decoding from instantaneous neural activity patterns, experimental access to millions of neurons may be necessary to predict neural ensemble dynamical trajectories across timescales of seconds. Fifth, despite the variable activity of single cells, neural networks can maintain stable representations of the variables computed by the latent processing units, thereby making computations robust to representational drift. Overall, our framework for latent computation provides an analytic description and empirically testable predictions regarding how large systems of neurons perform robust computations via their collective dynamics.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-02-21 05:00:00 UTC.

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Beyond Performance Scores: Directed Functional Connectivity as a Brain-Based Biomarker for Motor Skill Learning and Retention

arXiv:2502.14731v1 Announce Type: new Abstract: Motor skill acquisition in fields like surgery, robotics, and sports involves learning complex task sequences through extensive training. Traditional performance metrics, like execution time and error rates, offer limited insight as they fail to capture the neural mechanisms underlying skill learning and retention. This study introduces directed functional connectivity (dFC), derived from electroencephalography (EEG), as a novel brain-based biomarker for assessing motor skill learning and retention. For the first time, dFC is applied as a biomarker to map the stages of the Fitts and Posner motor learning model, offering new insights into the neural mechanisms underlying skill acquisition and retention. Unlike traditional measures, it captures both the strength and direction of neural information flow, providing a comprehensive understanding of neural adaptations across different learning stages. The analysis demonstrates that dFC can effectively identify and track the progression through various stages of the Fitts and Posner model. Furthermore, its stability over a six-week washout period highlights its utility in monitoring long-term retention. No significant changes in dFC were observed in a control group, confirming that the observed neural adaptations were specific to training and not due to external factors. By offering a granular view of the learning process at the group and individual levels, dFC facilitates the development of personalized, targeted training protocols aimed at enhancing outcomes in fields where precision and long-term retention are critical, such as surgical education. These findings underscore the value of dFC as a robust biomarker that complements traditional performance metrics, providing a deeper understanding of motor skill learning and retention.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-02-21 05:00:00 UTC.

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Explanations of Deep Language Models Explain Language Representations in the Brain

arXiv:2502.14671v1 Announce Type: cross Abstract: Recent advances in artificial intelligence have given rise to large language models (LLMs) that not only achieve human-like performance but also share computational principles with the brain's language processing mechanisms. While previous research has primarily focused on aligning LLMs' internal representations with neural activity, we introduce a novel approach that leverages explainable AI (XAI) methods to forge deeper connections between the two domains. Using attribution methods, we quantified how preceding words contribute to an LLM's next-word predictions and employed these explanations to predict fMRI recordings from participants listening to the same narratives. Our findings demonstrate that attribution methods robustly predict brain activity across the language network, surpassing traditional internal representations in early language areas. This alignment is hierarchical: early-layer explanations correspond to the initial stages of language processing in the brain, while later layers align with more advanced stages. Moreover, the layers more influential on LLM next-word prediction$\unicode{x2014}$those with higher attribution scores$\unicode{x2014}$exhibited stronger alignment with neural activity. This work establishes a bidirectional bridge between AI and neuroscience. First, we demonstrate that attribution methods offer a powerful lens for investigating the neural mechanisms of language comprehension, revealing how meaning emerges from preceding context. Second, we propose using brain alignment as a metric to evaluate the validity of attribution methods, providing a framework for assessing their biological plausibility.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-02-21 05:00:00 UTC.

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A Relativistic Theory of Consciousness (shortened version)

arXiv:2502.07247v3 Announce Type: replace Abstract: This paper is a shortened version of the full paper that was published in the journal Frontiers of Psychology in May 2022. In recent decades, the scientific study of consciousness has significantly increased our understanding of this elusive phenomenon. Yet, despite critical development in our understanding of the functional side of consciousness, we still lack a fundamental theory regarding its phenomenal aspect. The phenomenal aspect of consciousness is the first-person answer to what it is like question, and it has thus far proved recalcitrant to direct scientific investigation. The question of how the brain, or any cognitive system, can create conscious experience out of neural representations poses a great conundrum to science. Naturalistic dualists argue that it is composed of a primitive, private, nonreductive element of reality. Illusionists, on the other hand, argue that it is merely a cognitive illusion. We contend that both the dualist and illusionist positions are flawed because they tacitly assume consciousness to be an absolute property that does not depend on the observer. We developed a conceptual and a mathematical argument for a relativistic theory of consciousness in which a system either has or does not have phenomenal consciousness with respect to some observer. According to the theory, Phenomenal consciousness is neither private nor delusional, just relativistic. In the frame of reference of the cognitive system, it will be observable (first-person perspective) and in other frame of reference it will not (third-person perspective). These two cognitive frames of reference are both correct, just as in the case of an observer that claims to be at rest while another will claim that the observer has constant velocity. Neither observer position can be privileged, as they both describe the same underlying reality.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-02-21 05:00:00 UTC.

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Emergence of the Primacy Effect in Structured State-Space Models

arXiv:2502.13729v2 Announce Type: replace-cross Abstract: Human and animal memory for sequentially presented items is well-documented to be more accurate for those at the beginning and end of the sequence, phenomena known as the primacy and recency effects, respectively. By contrast, artificial neural network (ANN) models are typically designed with a memory that decays monotonically over time. Accordingly, ANNs are expected to show the recency effect but not the primacy effect. Contrary to this theoretical expectation, however, the present study reveals a counterintuitive finding: a recently developed ANN architecture, called structured state-space models, exhibits the primacy effect when trained and evaluated on a synthetic task that mirrors psychological memory experiments. Given that this model was originally designed for recovering neuronal activity patterns observed in biological brains, this result provides a novel perspective on the psychological primacy effect while also posing a non-trivial puzzle for the current theories in machine learning.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-02-21 05:00:00 UTC.

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Dynamic Activation with Knowledge Distillation for Energy-Efficient Spiking NN Ensembles

arXiv:2502.14023v1 Announce Type: cross Abstract: While foundation AI models excel at tasks like classification and decision-making, their high energy consumption makes them unsuitable for energy-constrained applications. Inspired by the brain's efficiency, spiking neural networks (SNNs) have emerged as a viable alternative due to their event-driven nature and compatibility with neuromorphic chips. This work introduces a novel system that combines knowledge distillation and ensemble learning to bridge the performance gap between artificial neural networks (ANNs) and SNNs. A foundation AI model acts as a teacher network, guiding smaller student SNNs organized into an ensemble, called Spiking Neural Ensemble (SNE). SNE enables the disentanglement of the teacher's knowledge, allowing each student to specialize in predicting a distinct aspect of it, while processing the same input. The core innovation of SNE is the adaptive activation of a subset of SNN models of an ensemble, leveraging knowledge-distillation, enhanced with an informed-partitioning (disentanglement) of the teacher's feature space. By dynamically activating only a subset of these student SNNs, the system balances accuracy and energy efficiency, achieving substantial energy savings with minimal accuracy loss. Moreover, SNE is significantly more efficient than the teacher network, reducing computational requirements by up to 20x with only a 2% drop in accuracy on the CIFAR-10 dataset. This disentanglement procedure achieves an accuracy improvement of up to 2.4% on the CIFAR-10 dataset compared to other partitioning schemes. Finally, we comparatively analyze SNE performance under noisy conditions, demonstrating enhanced robustness compared to its ANN teacher. In summary, SNE offers a promising new direction for energy-constrained applications.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-02-21 05:00:00 UTC.

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Position: Graph Learning Will Lose Relevance Due To Poor Benchmarks

arXiv:2502.14546v1 Announce Type: cross Abstract: While machine learning on graphs has demonstrated promise in drug design and molecular property prediction, significant benchmarking challenges hinder its further progress and relevance. Current benchmarking practices often lack focus on transformative, real-world applications, favoring narrow domains like two-dimensional molecular graphs over broader, impactful areas such as combinatorial optimization, relational databases, or chip design. Additionally, many benchmark datasets poorly represent the underlying data, leading to inadequate abstractions and misaligned use cases. Fragmented evaluations and an excessive focus on accuracy further exacerbate these issues, incentivizing overfitting rather than fostering generalizable insights. These limitations have prevented the development of truly useful graph foundation models. This position paper calls for a paradigm shift toward more meaningful benchmarks, rigorous evaluation protocols, and stronger collaboration with domain experts to drive impactful and reliable advances in graph learning research, unlocking the potential of graph learning.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-02-21 05:00:00 UTC.

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Multi-Class Imbalanced Learning with Support Vector Machines via Differential Evolution

arXiv:2502.14597v1 Announce Type: cross Abstract: Support vector machine (SVM) is a powerful machine learning algorithm to handle classification tasks. However, the classical SVM is developed for binary problems with the assumption of balanced datasets. Obviously, the multi-class imbalanced classification problems are more complex. In this paper, we propose an improved SVM via Differential Evolution (i-SVM-DE) method to deal with it. An improved SVM (i-SVM) model is proposed to handle the data imbalance by combining cost sensitive technique and separation margin modification in the constraints, which formalize a parameter optimization problem. By using one-versus-one (OVO) scheme, a multi-class problem is decomposed into a number of binary subproblems. A large optimization problem is formalized through concatenating the parameters in the binary subproblems. To find the optimal model effectively and learn the support vectors for each class simultaneously, an improved differential evolution (DE) algorithm is applied to solve this large optimization problem. Instead of the validation set, we propose the fitness functions to evaluate the learned model and obtain the optimal parameters in the search process of DE. A series of experiments are carried out to verify the benefits of our proposed method. The results indicate that i-SVM-DE is statistically superior by comparing with the other baseline methods.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-02-21 05:00:00 UTC.

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Multi-scale Topology Optimization using Neural Networks

arXiv:2404.08708v2 Announce Type: replace Abstract: A long-standing challenge is designing multi-scale structures with good connectivity between cells while optimizing each cell to reach close to the theoretical performance limit. We propose a new method for direct multi-scale topology optimization using neural networks. Our approach focuses on inverse homogenization that seamlessly maintains compatibility across neighboring microstructure cells. Our approach consists of a topology neural network that optimizes the microstructure shape and distribution across the design domain as a continuous field. Each microstructure cell is optimized based on a specified elasticity tensor that also accommodates in-plane rotations. The neural network takes as input the local coordinates within a cell to represent the density distribution within a cell, as well as the global coordinates of each cell to design spatially varying microstructure cells. As such, our approach models an n-dimensional multi-scale optimization problem as a 2n-dimensional inverse homogenization problem using neural networks. During the inverse homogenization of each unit cell, we extend the boundary of each cell by scaling the input coordinates such that the boundaries of neighboring cells are combined. Inverse homogenization on the combined cell improves connectivity. We demonstrate our method through the design and optimization of graded multi-scale structures.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-02-21 05:00:00 UTC.

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Integrated Scheduling Model for Arrivals and Departures in Metroplex Terminal Area

arXiv:2502.12196v2 Announce Type: replace Abstract: In light of the rapid expansion of civil aviation, addressing the delays and congestion phenomena in the vicinity of metroplex caused by the imbalance between air traffic flow and capacity is crucial. This paper first proposes a bi-level optimization model for the collaborative flight sequencing of arrival and departure flights in the metroplex with multiple airports, considering both the runway systems and TMA (Terminal Control Area) entry/exit fixes. Besides, the model is adaptive to various traffic scenarios. The genetic algorithm is employed to solve the proposed model. The Shanghai TMA, located in China, is used as a case study, and it includes two airports, Shanghai Hongqiao International Airport and Shanghai Pudong International Airport. The results demonstrate that the model can reduce arrival delay by 51.52%, departure delay by 18.05%, and the runway occupation time of departure flights by 23.83%. Furthermore, the model utilized in this study significantly enhances flight scheduling efficiency, providing a more efficient solution than the traditional FCFS (First Come, First Served) approach. Additionally, the algorithm employed offers further improvements over the NSGA II algorithm.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-02-21 05:00:00 UTC.

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Increasingly efficient chromatin binding of cohesin and CTCF supports chromatin architecture formation during zebrafish embryogenesis

Nature Communications, Published online: 21 February 2025; doi:10.1038/s41467-025-56889-5

Using single-molecule tracking of cohesin and CTCF during zebrafish embryogenesis, the molecular kinetics underlying chromatin architecture formation was revealed and gradual emergence of chromatin structure recapitulated by polymer simulations.

in Nature Communications on 2025-02-21 00:00:00 UTC.

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Heparan sulfate regulates myofibroblast heterogeneity and function to mediate niche homeostasis during alveolar morphogenesis

Nature Communications, Published online: 21 February 2025; doi:10.1038/s41467-025-57163-4

The alveoli of the lung are formed through the coordination of multiple cell types to yield a large surface area for gas exchange. Here they show that heparan sulfate plays essential roles in lung myofibroblasts to maintain MAPK signaling and the alveolar niche.

in Nature Communications on 2025-02-21 00:00:00 UTC.

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Vacancies in sulfides facilitate fluid-induced solid-state diffusion and critical metals accumulation

Nature Communications, Published online: 21 February 2025; doi:10.1038/s41467-025-57171-4

Vacancies in sulfides facilitate fluid-induced solid-state diffusion at rates nearly two orders of magnitude faster than traditional lattice diffusion, promoting critical metal accumulation during ore formation.

in Nature Communications on 2025-02-21 00:00:00 UTC.

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Entanglement growth from squeezing on the MPS manifold

Nature Communications, Published online: 21 February 2025; doi:10.1038/s41467-025-56959-8

Recent work explored the connection between quantum thermalization in closed many-body systems and classical chaos by projecting quantum dynamics onto classical dynamics. Here the authors further this understanding by analytically linking entanglement growth to the Lyapunov spectrum.

in Nature Communications on 2025-02-21 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 224: Corticolimbic Structural Deficits in Violent Patients with Schizophrenia

Brain Sciences, Vol. 15, Pages 224: Corticolimbic Structural Deficits in Violent Patients with Schizophrenia

Brain Sciences doi: 10.3390/brainsci15030224

Authors: Maria Athanassiou Alexandre Dumais Inès Zouaoui Alexandra Fortier Luigi de Benedictis Olivier Lipp Andràs Tikàsz Stéphane Potvin

Background/Objectives: Violent behaviors are uncommon in patients with schizophrenia (Sch), but when present, exacerbate stigma and challenge treatment. The following study aimed to identify the structural abnormalities associated with violent behaviors in Sch by implementing a validated tool specifically designed to evaluate violent behaviors in psychiatric populations, as well as by performing region-of-interest neuroimaging analyses, focused on areas commonly associated with the neurobiology of violence and aggression. Methods: Eighty-three participants were divided into three groups: Sch with violent behaviors (Sch+V, n = 34), Sch without violent behaviors (Sch-V, n = 28), and healthy controls (HC, n = 21). Structural neuroimaging analyses were performed across groups to assess gray matter volume (GMV) and cortical thickness (CT) differences in regions previously implicated in aggressive behaviors. Results: The data revealed significant reductions in GMV in the right amygdala and diminished cortical thickness (CT) in the bilateral dorsolateral prefrontal cortices (dlPFC) in patients with Sch+V compared to patients with Sch-V and HCs. Right amygdalar volume also demonstrated a negative correlational trend with hostility scores in patients with Sch+V. Conclusions: These findings underscore disruptions in the structural integrity of the dlPFC&mdash;responsible for inhibitory control&mdash;and the amygdala&mdash;central to emotional processing in violent patients with Sch. Future research should aim to investigate potential functional interactions at a network level to gain a deeper understanding of the neurobiological underpinnings of violent behaviors in this population.

in Brain Sciences on 2025-02-21 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 223: Clinical Aspects of Mental Imagery in Alzheimer’s Disease-Related Dementia: A Review of Cognitive, Motor, and Emotional Interventions

Brain Sciences, Vol. 15, Pages 223: Clinical Aspects of Mental Imagery in Alzheimer’s Disease-Related Dementia: A Review of Cognitive, Motor, and Emotional Interventions

Brain Sciences doi: 10.3390/brainsci15030223

Authors: Anna Christakou Marousa Pavlou George Stranjalis Vasiliki Sakellari

The present review describes the use and effectiveness of mental imagery in Alzheimer&rsquo;s disease-related dementia. Six databases were thoroughly searched from January 2010 to December 2024. Different types of studies were retrieved and reviewed for imagery of the motor, cognitive, and emotional states and quality of life of the elderly with dementia. Although the scarce results showed the positive effect of mental imagery to the every-day life of older adults with dementia, more research should be conducted with larger homogenous samples and more valid tools. Future recommendations are provided.

in Brain Sciences on 2025-02-21 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 222: Quantifying the Multidimensionality of Abstract Concepts: An Italian Database

Brain Sciences, Vol. 15, Pages 222: Quantifying the Multidimensionality of Abstract Concepts: An Italian Database

Brain Sciences doi: 10.3390/brainsci15030222

Authors: Virginia Maria Borsa Maria Arioli Riccardo Verni Nicola Canessa Stefano F. Cappa Eleonora Catricalà

Background: The embodied cognition approach, as applied to concrete knowledge, is centred on the role of the perceptual and motor aspects of experience. To extend the embodied framework to abstract knowledge, some studies have suggested that further dimensions, such as affective or social experiences, are relevant for the semantic representations of abstract concepts. The objective of this study is to develop a measure that can quantitatively capture the multidimensional nature of abstract concepts. Methods: We used dimension-rating methods, known to be suitable, to account for the semantic representations of abstract concepts, to develop a new database of 964 Italian words, rated by 542 participants. Besides classical psycholinguistic variables (i.e., concreteness, imageability, familiarity, age of acquisition, semantic diversity) and affective norms (i.e., valence, arousal), we collected ratings on selected dimensions characterizing the semantic representations of abstract concepts, i.e., introspective, mental state, quantitative, spatial, social, moral, theoretical, and economic dimensions. The measure of exclusivity was incorporated to quantify the number of dimensions, and the respective relevance, for each concept. Concepts with a high value of exclusivity rely on only one/a few dimension/s with high value on the respective rating scale. Results: A multidimensional representation characterized most abstract concepts, with two robust major clusters. The first was characterized by dense intersections among introspective, mental state, social, and moral dimensions; the second, less interconnected, cluster revolved around quantitative, spatial, theoretical, and economic dimensions. Quantitative, theoretical, and economic concepts obtained higher exclusivity values. Conclusions: The present study contributes to the investigation of the semantic organization of abstract words and supports a controlled selection and definition of stimuli for clinical and research settings.

in Brain Sciences on 2025-02-21 00:00:00 UTC.

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Deciphering Compromised Speech-in-Noise Intelligibility in Older Listeners: The Role of Cochlear Synaptopathy

Speech intelligibility declines with age and sensorineural hearing damage (SNHL). However, it remains unclear whether cochlear synaptopathy (CS), a recently discovered form of SNHL, significantly contributes to this issue. CS refers to damaged auditory-nerve synapses that innervate the inner hair cells and there is currently no go-to diagnostic test available. Furthermore, age-related hearing damage can comprise various aspects (e.g., hair cell damage, CS) that each can play a role in impaired sound perception. To explore the link between cochlear damage and speech intelligibility deficits, this study examines the role of CS for word recognition among older listeners. We first validated an envelope-following response (EFR) marker for CS using a Budgerigar model. We then applied this marker in human experiments, while restricting the speech material’s frequency content to ensure that both the EFR and the behavioral tasks engaged similar cochlear frequency regions. Following this approach, we identified the relative contribution of hearing sensitivity and CS to speech intelligibility in two age-matched (65-year-old) groups with clinically normal (n = 15, 8 females) or impaired audiograms (n = 13, 8 females). Compared to a young normal-hearing control group (n = 13, 7 females), the older groups demonstrated lower EFR responses and impaired speech reception thresholds. We conclude that age-related CS reduces supra-threshold temporal envelope coding with subsequent speech coding deficits in noise that cannot be explained based on hearing sensitivity alone.

in eNeuro on 2025-02-20 17:30:22 UTC.

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MicroRNA-155 Inhibition Activates Wnt/{beta}-Catenin Signaling to Restore Th17/Treg Cell Balance and Protect against Acute Ischemic Stroke

Acute ischemic stroke (AIS) is a severe neurological disease associated with Th17/Treg cell imbalance and dysregulation of the Wnt/β-catenin signaling pathway. This study investigates whether miR-155 inhibition can activate Wnt/β-catenin signaling, improve Th17/Treg balance, and provide neuroprotection against stroke. We conducted a multilevel experimental design, including high-throughput sequencing, bioinformatics analysis, in vivo mouse models, and in vitro cell experiments. High-throughput sequencing revealed significant differential gene expression between the miR-155 antagomir–treated and control groups (BioProject: PRJNA1152758). Bioinformatics analysis identified key genes linked to Wnt/β-catenin signaling and Th17/Treg imbalance. In vitro experiments confirmed that miR-155 inhibition activated Wnt/β-catenin signaling and improved Th17/Treg ratios. In vivo studies demonstrated that miR-155 antagomir treatment provided significant neuroprotection against AIS. These findings suggest that targeting miR-155 could be a promising therapeutic strategy for stroke by modulating immune balance and key signaling pathways.

in eNeuro on 2025-02-20 17:30:22 UTC.

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Community preparedness for earthquake disasters: A preliminary assessment of awareness and disaster infrastructure response in Cianjur, West Java-Indonesia [version 3; peer review: 1 approved, 1 approved with reservations]

Background The danger of earthquakes poses a serious threat to people worldwide. One of the most significant challenges is preparing communities to cope effectively with this disaster. Therefore, understanding earthquake hazards is critically important for preparedness, mitigation, and an effective response to this threat. This report aims to observe and conduct a preliminary assessment of the degree to which community preparedness for earthquake disasters has been implemented. Methods Empirical data were obtained from survey respondents and interviews. The respondents were members of a community affected by the Cianjur earthquake, which occurred on November 21, 2022. The data were analysed using the mean range approach, based on Likert scales. Additionally, the Spearman correlation method was employed to indicate the relationship between community awareness and infrastructure readiness. Result Based on empirical evidence and preliminary analysis, it is evident that the preparedness of the community to respond effectively to earthquake catastrophes is inadequate. An apparent lack of readiness is observed in the inadequate construction of housing that fails to meet disaster standards, and the absence of disaster response facilities is notable. Conclusions Based on our initial assumption, it appears that knowledge related to disaster resilience in this area has not been adequately disseminated or socialized. However, this premise requires further investigation.

in F1000Research on 2025-02-20 14:57:02 UTC.

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Case Report: Managing Odontoma and Molar-Incisor-Hypomineralization Challenges in Orthodontics [version 2; peer review: 1 approved with reservations]

This report presents the successful orthodontic management of a case of odontoma associated with impaction of the mandibular right permanent canine and Molar-incisor-hypomineralization (MIH). Although case studies have reported the management of odontomas and MIH as separate entities, there is a lack of evidence regarding the comprehensive management of patients presenting with a combination of odontoma, dental impaction, and MIH. A 15-year, 7-month-old female patient complained of the appearance of her smile and the delayed eruption of her mandibular right permanent canine. She was diagnosed with Angle’s Class I molar relationship and Class II canine relationship with the maxillary permanent right lateral incisor in a lingual crossbite. Furthermore, she had mandibular right permanent canine impaction, retained mandibular right primary canine, and MIH in the permanent anterior teeth and first molars. The management involved the removal of the odontoma to allow for orthodontic traction of the lower permanent right canine. After that, the esthetic appearance of the teeth was improved through restorative treatment.

in F1000Research on 2025-02-20 14:54:02 UTC.

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Through restful waters and deep commotion: A study on burnout and health impairment of Italian seafarers from the JD-R model perspective. [version 2; peer review: 1 approved, 2 approved with reservations]

Background The work experience of seafarers differs significantly from other land-based occupations due to several factors, particularly remoteness and the restricted work environment. This study seeks to examine the impact of burnout and health impairment in the maritime industry, using the Job Demand-Resources theory as a framework. Methods To investigate these phenomena, an online questionnaire was sent to 629 Italian seafarers and we conducted analysis on a valid sample of 239 respondents (94.6% men, Mage = 39.44, SD = 12.8). We tested a mediated Structural Equation Model (SEM) aimed at predicting negative health outcomes. Results The results show that burnout plays a mediating role between job demands (such as workload and cognitive strain) and health impairment (such as sleep quality and physical well-being) (Total Indirect Effect = 0.443, p < .0001) as well as between job resources (such as social support and transformational leadership) and health impairment (Total Indirect Effect = -0.249, p < .0001). Furthermore, the findings highlight the direct influence of occupational resources on seafarers’ health. Conclusions The discussion highlights the urgent need for more research in the field of organisational psychology in the maritime industry and the discrepancies between these findings, which are consistent with the existing maritime literature, and other studies that do not include seafarers in their sample groups.

in F1000Research on 2025-02-20 14:51:35 UTC.

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All-cause mortality according to COVID-19 vaccination status: An analysis of the UK office for National statistics public data [version 2; peer review: 1 approved, 1 approved with reservations]

Background The mass vaccination campaign against COVID-19 has been commonly considered the best response to the global COVID-19 pandemic crisis. However, assessment of its real-world effect can be performed by analysis of all-cause mortality by vaccination status. The UK is perhaps the only country which has made publicly available all-cause mortality data by vaccination status. Methods Data from April 2021 to May 2023 published by the UK Office for National Statistics (ONS) were retrospectively analyzed by age groups and vaccination status; the standardized mortality ratio (SMR) for all-cause and non-COVID-19 mortality was calculated against the corresponding unvaccinated groups. Results We found that across all age groups, all-cause mortality SMRs increased from a certain date, dependent on the age group. Across all age groups, all-cause mortality SMRs were initially much lower than 1. However, due to their increase, by a certain date for the 18-39, 80-89 and 90+ age groups they exceeded the reference value. For the other age groups, the date at which the SMR would reach 1 can be predicted, provided the trend is maintained. Non-COVID-19 SMRs’ trends were very similar. Their initial values much lower than 1 are suggestive of significant biases in the ONS dataset, leading to underestimate the risks for the vaccinated people, as it is implausible that COVID-19 vaccines protect against non-COVID-19 deaths. Conclusions The increase over time in all-cause death SMRs in vaccinated people compared to unvaccinated, and their excess from the reference values for certain age groups, should be carefully considered to understand the underlying factors. Furthermore, since the initial values of the SMRs are much lower than 1, we assume the presence of significant biases in the ONS dataset, leading to understimate the risks for the vaccinated people, as it is implausible that COVID-19 vaccines protect against non-COVID-19 deaths. It would be desirable for other major countries to systematically collect all-cause mortality by vaccination status and, in the meantime, a pending indepth investigations, much greater caution should be exercised in promoting mass vaccination campaigns.

in F1000Research on 2025-02-20 14:35:57 UTC.

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Resilience of mobility network to dynamic population response across COVID-19 interventions: Evidences from Chile

by Pasquale Casaburi, Lorenzo Dall’Amico, Nicolò Gozzi, Kyriaki Kalimeri, Anna Sapienza, Rossano Schifanella, Tiziana Di Matteo, Leo Ferres, Mattia Mazzoli

The COVID-19 pandemic highlighted the importance of non-traditional data sources, such as mobile phone data, to inform effective public health interventions and monitor adherence to such measures. Previous studies showed how socioeconomic characteristics shaped population response during restrictions and how repeated interventions eroded adherence over time. Less is known about how different population strata changed their response to repeated interventions and how this impacted the resulting mobility network. We study population response during the first and second infection waves of the COVID-19 pandemic in Chile and Spain. Via spatial lag and regression models, we investigate the adherence to mobility interventions at the municipality level in Chile, highlighting the significant role of wealth, labor structure, COVID-19 incidence, and network metrics characterizing business-as-usual municipality connectivity in shaping mobility changes during the two waves. We assess network structural similarities in the two periods by defining mobility hotspots and traveling probabilities in the two countries. As a proof of concept, we simulate and compare outcomes of an epidemic diffusion occurring in the two waves. While differences exist between factors associated with mobility reduction across waves in Chile, underscoring the dynamic nature of population response, our analysis reveals the resilience of the mobility network across the two waves. We test the robustness of our findings recovering similar results for Spain. Finally, epidemic modeling suggests that historical mobility data from past waves can be leveraged to inform future disease spatial invasion models in repeated interventions. This study highlights the value of historical mobile phone data for building pandemic preparedness and lessens the need for real-time data streams for risk assessment and outbreak response. Our work provides valuable insights into the complex interplay of factors driving mobility across repeated interventions, aiding in developing targeted mitigation strategies.

in PLoS Computational Biology on 2025-02-20 14:00:00 UTC.

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Macrophage invasion into the Drosophila brain requires JAK/STAT-dependent MMP activation in the blood–brain barrier

by Bente Winkler, Dominik Funke, Christian Klämbt

The central nervous system is well-separated from external influences by the blood–brain barrier. Upon surveillance, infection or neuroinflammation; however, peripheral immune cells can enter the brain where they often cause detrimental effects. To invade the brain, immune cells not only have to breach cellular barriers, but they also need to traverse associated extracellular matrix barriers. Neither in vertebrates nor in invertebrates is it fully understood how these processes are molecularly controlled. We recently established Drosophila melanogaster as a model to elucidate peripheral immune cell invasion into the brain. Here, we show that neuroinflammation leads to the expression of Unpaired cytokines that activate the JAK/STAT signaling pathway in glial cells of the blood–brain barrier. This in turn triggers the expression of matrix metalloproteinases enabling remodeling of the extracellular matrix enclosing the fly brain and a subsequent invasion of immune cells into the brain. Our study demonstrates conserved mechanisms underlying immune cell invasion of the nervous system in invertebrates and vertebrates and could, thus, further contribute to understanding of JAK/STAT signaling during neuroinflammation.

in PLoS Biology on 2025-02-20 14:00:00 UTC.

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Evaluating the Efficacy of Gelatin-Chitosan-Tetraethyl Orthosilicate Calcium Hydroxide Composite as a Dental Pulp Medicament on COX-2, PGP 9.5, TNF-α Expression and Neutrophil number [version 3; peer review: 1 approved, 1 approved with reservations, 1 no

Introduction Calcium hydroxide (Ca(OH)2) is the material of choice for pulp therapy. However, Ca(OH)2 has drawbacks such as toxicity, poor sealing, and tunnel defect formation. Alternative materials have been developed to provide more biocompatible materials with better dentin formation ability. The objective of this study was to evaluate the effect of composites containing gelatin (G), chitosan (CH), tetraethyl orthosilicate (TEOS), and Ca(OH)2, namely G-CH-TEOS-Ca (OH)2 (Extended data) on inflammation of the dental pulp (expression of COX-2, PGP 9.5, TNF-α, and neutrophil number). Materials and methods A total of 16 Wistar rat models of acute pulp injury were prepared and divided into two groups, treatment and control, 8 with each. In the treatment group, we applied a pulp-capping material using G-CH-TEOS-Ca (OH)2 and Ca(OH)2. On the 1st and 3rd days, rats were sacrificed. Tissue samples from 4 rats in each group were processed for histological preparation. COX-2, PGP 9.5, and TNF-α were observed using immunohistochemical (IHC) staining, and neutrophil numbers were observed using hematoxylin-eosin staining. Image analysis of COX-2, PGP 9.5, and TNF-α expression was performed using ImageJ software. Results The results showed a decrease significantly in COX-2 expression while PGP 9.5 and TNF-α expression were significantly higher than those in the control group. Neutrophil numbers were lower in the treatment group than in the control group, but the difference was not statistically significant. Conclusion The G-CH-TEOS-Ca (OH)2 composite material may have potential as an exposed pulp medicament by reducing mediator of inflammation (COX-2 expression) and increasing the regeneration factor (TNF-α expression) and nerve (PGP 9.5 expression).

in F1000Research on 2025-02-20 10:47:10 UTC.

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Case Report: Hymenolepis diminuta in an asymptomatic Ecuadorian child. [version 3; peer review: 1 approved, 2 approved with reservations]

Background The cestode Hymenolepis diminuta is a cosmopolitan parasite, which in the adult stage is usually found in the small intestine of rats and accidentally in humans. Case report We describe the finding of eggs of this parasite in an asymptomatic 3-year-old child. The child had extremely high IgE values of 1,376 IU/ml. After receiving treatment with Albendazole suspension 400mg/20mL, on the 10th day post-treatment, he showed no H. diminuta eggs in his fecal matter Conclusions Detailed morphological review of Hymenolepis nana-like eggs is recommended to distinguish them from H. diminuta eggs.

in F1000Research on 2025-02-20 10:01:01 UTC.

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Ligand-induced receptor multimerization achieves specificity enhancement of kinetic proofreading without associated costs

Author(s): Duncan Kirby and Anton Zilman

This paper investigates models of two mechanisms used by cells to enhance specificity of signaling pathways. In the kinetic proofreading mechanism, the ligand-bound receptor must pass through a sequence of states before reaching the signaling state. In the multimeric receptor signaling mechanism, receptor subunits are bound by a multivalent ligand to form a signaling complex. A key result of this paper is that the multimeric receptor is capable of achieving the same maximum specificity as the kinetic proofreading receptor.

[Phys. Rev. E 111, 024408] Published Thu Feb 20, 2025

in Physical Review E: Biological physics on 2025-02-20 10:00:00 UTC.

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Magnitude and Factors Associated with Research Misconduct at a Public University in Ethiopia: A Cross-Sectional Survey [version 2; peer review: 2 approved with reservations]

Background Research integrity, essential for ethical scientific research, has been inadequately addressed in Ethiopia, resulting in gaps in addressing misconduct like plagiarism, falsification and fabrication. The aim of this study was to assess the magnitude and factors associated with research misconduct at a public university in Ethiopia. Methods An institutional-based cross-sectional study was conducted on a random sample of researchers. Data were collected via a self-administered, structured questionnaire, which was adapted from a similar study. The collected data were analysed using descriptive, bivariate, and multivariable logistic regression. Result A total of 244 researchers participated in the study, resulting in an 82% response rate. In our study, 37.7% of participants reported engaging in at least one form of misconduct, 95% CI [31.6%, 44.1%]. Authorship misconduct was the most common form of self-reported misconduct (47.5%), 95% CI [41.1%, 54.0%], followed by fabrication and falsification (40.6%), 95% CI [34.4%, 47.0%]. Publication pressure was significantly associated with research misconduct (AOR = 3.18; 95% CI: [1.02, 9.95]). Conclusion This study highlights the prevalence of research misconduct and questionable research practices among academic researchers, with authorship misconduct, fabrication, falsification, and plagiarism being the most commonly reported types. Attitudes toward research misconduct and self-reported involvement were influenced by academic position, research experience, and publication pressure, with junior researchers being more likely to report engaging in misbehavior. While ethics training has occasionally been associated with reduced rates of research misconduct, its effectiveness remains uncertain, as institutional culture, supervision, and mentorship may play a more significant role. Addressing research misconduct requires a comprehensive approach that extends beyond ethical instruction, incorporating targeted support for early-career researchers, open dialogue, and institutional policy reforms.

in F1000Research on 2025-02-20 09:27:37 UTC.

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Influence of Iron Deficiency Anaemia on Glycated Haemoglobin in Non-diabetics [version 1; peer review: awaiting peer review]

Background Glycated hemoglobin (HbA1C) is a valuable marker in the management of Diabetes Mellitus, aiding in screening and diagnosis, and as a predictor of complications. Iron deficiency anaemia in developing countries has been found to affect the blood levels of HbA1C, decreasing its sensitivity. This study was undertaken to analyse the influence of iron deficiency anaemia on HbA1c levels, and thereby assess the reliability of A1C as a diagnostic marker for diabetes mellitus in iron deficient patients Methods This cross-sectional observational case-control study was conducted in a single tertiary care center. A total of 164 patients were recruited, 82 each from the case and control groups. The groups were matched for age and sex. Cases were nondiabetics with iron deficiency, and controls were nondiabetics without iron deficiency Results Age and sex were matched between cases and controls. The median ferritin levels were 5.9 ng/dl (n= 82) and 144 ng/dl (n= 82) among cases and controls. Transferrin saturation was distributed among cases, with a median of 3.4% for males (n= 36) and 3.2% for females (n= 46). Median hemoglobin levels were compared among each age group, with more severe anemia being seen as age increased. HbA1C was also compared age -wise, with results being statistically significant across each category. There was a statistically significant difference between HbA1C levels in cases and controls (p<0.0001), with some cases having A1C in the diabetic range, without any signs and symptoms of diabetes, and normal fasting and post prandial glucose Conclusion The results of our study suggest that although HbA1C is a diagnostic marker for type 2 diabetes mellitus, it loses its reliability when there is a co-existing iron deficiency anaemia. Hence certain amount of vigilance is mandated to confirm diabetes mellitus based on HbA1C, when the patient also has iron deficiency.

in F1000Research on 2025-02-20 09:00:39 UTC.

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Erratum for the Research Article “Building materials could store more than 16 billion tonnes of CO2 annually” by Van Roijen et al.

Science, Volume 387, Issue 6736, February 2025.

in Science on 2025-02-20 08:00:00 UTC.

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Quantum computing requires high-performance software

Science, Volume 387, Issue 6736, February 2025.

in Science on 2025-02-20 08:00:00 UTC.

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The perils of labor

Science, Volume 387, Issue 6736, Page 832-832, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Morality in a more-than-human world

Science, Volume 387, Issue 6736, Page 833-833, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Magnetic modulation of keyhole instability during laser welding and additive manufacturing

Science, Volume 387, Issue 6736, Page 864-869, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Neuronal FAM171A2 mediates α-synuclein fibril uptake and drives Parkinson’s disease

Science, Volume 387, Issue 6736, Page 892-900, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Visible light–triggered depolymerization of commercial polymethacrylates

Science, Volume 387, Issue 6736, Page 874-880, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Spiro-C(sp3)-atom transfer: Creating rigid three-dimensional structures with Ph2SCN2

Science, Volume 387, Issue 6736, Page 885-892, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Nickel promotes selective ethylene epoxidation on silver

Science, Volume 387, Issue 6736, Page 869-873, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Interfacial bonding enhances thermoelectric cooling in 3D-printed materials

Science, Volume 387, Issue 6736, Page 845-850, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Material-like robotic collectives with spatiotemporal control of strength and shape

Science, Volume 387, Issue 6736, Page 880-885, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Comic relief

Science, Volume 387, Issue 6736, Page 902-902, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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In Other Journals

Science, Volume 387, Issue 6736, Page 838-839, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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An innate drive to save a life

Science, Volume 387, Issue 6736, Page 827-828, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Enabling evolvability to evolve

Science, Volume 387, Issue 6736, Page 825-826, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Connecting the dots for cooling

Science, Volume 387, Issue 6736, Page 826-827, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Evaluating animal consciousness

Science, Volume 387, Issue 6736, Page 822-824, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Airport plan imperils South Korea’s tidal flat

Science, Volume 387, Issue 6736, Page 834-835, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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COP30’s hypocritical cruise ship lodging plan

Science, Volume 387, Issue 6736, Page 835-835, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Military base threatens Galápagos Islands

Science, Volume 387, Issue 6736, Page 834-834, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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News at a glance

Science, Volume 387, Issue 6736, Page 808-809, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Mass firings decimate U.S. science agencies

Science, Volume 387, Issue 6736, Page 810-811, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Researchers seek lessons from animals’ growing pains

Science, Volume 387, Issue 6736, Page 812-813, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Sodium batteries power up

Science, Volume 387, Issue 6736, Page 813-814, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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A new origin story for the highest energy cosmic rays

Science, Volume 387, Issue 6736, Page 814-815, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Crop research hit by U.S. foreign aid freezes

Science, Volume 387, Issue 6736, Page 816-816, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Cutting AI down to size

Science, Volume 387, Issue 6736, Page 818-821, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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High-performance computing at a crossroads

Science, Volume 387, Issue 6736, Page 829-831, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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In Science Journals

Science, Volume 387, Issue 6736, Page 837-839, February 2025.

in Science on 2025-02-20 06:59:17 UTC.

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Rapid estrogen signaling drives binge drinking

Sex hormones shape behavior through diverse mechanisms. In a recent study, Zallar et al. have uncovered a rapid, nongenomic estrogen signaling pathway mediating binge drinking in female mice via membrane-associated estrogen receptor α (ERα) in the bed nucleus of the stria terminalis (BNST). These findings reveal sex-specific neurobiological underpinnings of alcohol use linked to naturally circulating hormone levels.

in Trends in Neurosciences: In press on 2025-02-20 00:00:00 UTC.

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A KIF1C-CNBP motor-adaptor complex for trafficking mRNAs to cell protrusions

Moissoglu et al. study the mechanisms of mRNA targeting to mammalian cell protrusions. They show that the RNA-binding protein CNBP binds 3′ UTR GA-rich sequences in protrusion-localized mRNAs and recruits the KIF1C kinesin for mRNA trafficking on microtubules. This work reveals a new motor-adaptor complex for microtubule-based mRNA transport.

in Cell Reports: Current Issue on 2025-02-20 00:00:00 UTC.

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Restraint of inflammasome-driven cytokine responses through the mRNA stability protein TTP

O’Keefe et al. determined that inflammasome agonists, working through the mitochondria, rapidly inactivate ERK1/2. They further show that the ERK substrate, TTP, is also inactivated, leading to increased cytokine responses.

in Cell Reports: Current Issue on 2025-02-20 00:00:00 UTC.

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Defining the molecular identity and morphology of glia limitans superficialis astrocytes in vertebrates

Hasel et al. show that molecularly and morphologically specialized astrocytes make up the brain and spinal cord surface, thereby creating the glia limitans superficialis. These astrocytes selectively express the gene Myocilin, and their cell bodies create the brain surface and have processes that reach into the parenchyma.

in Cell Reports: Current Issue on 2025-02-20 00:00:00 UTC.

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Computational functions of precisely balanced neuronal microcircuits in an olfactory memory network

Meissner-Bernard et al. combined experiments and modeling to analyze specific functions of inhibition in a memory network. Inhibition was found to be important not only to stabilize overall activity levels but also to maintain activity patterns in an informative regime, consistent with models assuming balanced, non-random connectivity between assemblies of neurons.

in Cell Reports: Current Issue on 2025-02-20 00:00:00 UTC.

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NUCLEAR RNA POLYMERASE D1 is essential for tomato embryogenesis and desiccation tolerance in seeds

Feng et al. examine the role of RNA-dependent DNA methylation in plant embryogenesis using a multi-omic method. They discover that 21/22-nt sRNA rises in response to decreased CHH methylation. After being harvested, the mutant embryos do not survive desiccation due to abnormal WOX/auxin signaling.

in Cell Reports: Current Issue on 2025-02-20 00:00:00 UTC.

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Non-ionotropic signaling through the NMDA receptor GluN2B carboxy-terminal domain drives dendritic spine plasticity and reverses fragile X phenotypes

Barnes et al. used an assay of spine plasticity in hippocampal slices to study non-ionotropic NMDA-receptor signaling. Signaling is initiated via the GluN2B carboxy-terminal domain and modulates spine morphology, protein synthesis, and protein-synthesis-dependent synaptic plasticity. Augmenting GluN2B signaling reverses core phenotypes in the mouse model of fragile X syndrome.

in Cell Reports: In press on 2025-02-20 00:00:00 UTC.

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Structural dynamics of human fatty acid synthase in the condensing cycle

Nature, Published online: 20 February 2025; doi:10.1038/s41586-025-08782-w

Structural dynamics of human fatty acid synthase in the condensing cycle

in Nature on 2025-02-20 00:00:00 UTC.

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Author Correction: The genetic origin of the Indo-Europeans

Nature, Published online: 20 February 2025; doi:10.1038/s41586-025-08789-3

Author Correction: The genetic origin of the Indo-Europeans

in Nature on 2025-02-20 00:00:00 UTC.

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Rare genetic disorder treated in womb for the first time

Nature, Published online: 20 February 2025; doi:10.1038/d41586-025-00534-0

The child, who is now almost three years old, shows no signs of the often fatal motor neuron disease.

in Nature on 2025-02-20 00:00:00 UTC.

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Snapshots of acyl carrier protein shuttling in human fatty acid synthase

Nature, Published online: 20 February 2025; doi:10.1038/s41586-025-08587-x

Using cryo-electron microscopy, the structures of mammalian fatty acid synthase reveal how the acyl carrier protein dynamically shuttles intermediates between selected active sites.

in Nature on 2025-02-20 00:00:00 UTC.

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Trump’s siege of science: how the first 30 days unfolded and what’s next

Nature, Published online: 20 February 2025; doi:10.1038/d41586-025-00525-1

The breakneck pace and devastating impact of the administration’s policy changes has shocked researchers.

in Nature on 2025-02-20 00:00:00 UTC.

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How leading a postdoc network boosted my career prospects

Nature, Published online: 20 February 2025; doi:10.1038/d41586-025-00207-y

Tracy Wietecha says the experience swallowed up evenings and weekends, but taught her budgeting, networking and conflict-management skills.

in Nature on 2025-02-20 00:00:00 UTC.

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AI tool diagnoses diabetes, HIV and COVID from a blood sample

Nature, Published online: 20 February 2025; doi:10.1038/d41586-025-00528-y

‘One-shot’ approach that uses machine learning to screen immune cells could help to detect conditions with overlapping symptoms.

in Nature on 2025-02-20 00:00:00 UTC.

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Revealed: NIH research grants still frozen despite lawsuits challenging Trump order

Nature, Published online: 20 February 2025; doi:10.1038/d41586-025-00540-2

The Trump administration is exploiting a loophole to keep a funding freeze in place, leaving researchers in limbo.

in Nature on 2025-02-20 00:00:00 UTC.

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Author Correction: Ultrafast intrinsic optical-to-electrical conversion dynamics in a graphene photodetector

Nature Photonics, Published online: 20 February 2025; doi:10.1038/s41566-025-01646-9

Author Correction: Ultrafast intrinsic optical-to-electrical conversion dynamics in a graphene photodetector

in Nature Photomics on 2025-02-20 00:00:00 UTC.

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Full-field Brillouin microscopy based on an imaging Fourier-transform spectrometer

Nature Photonics, Published online: 20 February 2025; doi:10.1038/s41566-025-01619-y

A Fourier-transform imaging spectrometer enables two-dimensional spectral Brillouin imaging at a throughput of up to 40,000 spectra per second over a 300 × 300 µm² field of view.

in Nature Photomics on 2025-02-20 00:00:00 UTC.

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Genetically encoded biosensor for fluorescence lifetime imaging of PTEN dynamics in the intact brain

Nature Methods, Published online: 20 February 2025; doi:10.1038/s41592-025-02610-9

A first-in-class fluorescence lifetime-based FRET sensor for phosphatase and tensin homolog (PTEN) enables the dynamic monitoring of PTEN activity in cultured cells and in vivo with high spatiotemporal resolution.

in Nature Methods on 2025-02-20 00:00:00 UTC.

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Chimpanzees adapt their exploration to key properties of the environment

Nature Communications, Published online: 20 February 2025; doi:10.1038/s41467-025-57022-2

Exploration helps reduce uncertainty in daily life, but the evolutionary roots of adaptive exploration are unclear. Here, the authors show that chimpanzees, like humans, tailor their exploration depending on their environment.

in Nature Communications on 2025-02-20 00:00:00 UTC.

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A neural implementation model of feedback-based motor learning

Nature Communications, Published online: 20 February 2025; doi:10.1038/s41467-024-54738-5

How the brain adapts our movements to new conditions remains unclear. Here, the authors show that a recurrent neural network that controls its output using error-based feedback can learn to counteract a persistent perturbation using a biologically plausible plasticity rule, recapitulating key neural and behavioural features of motor adaptation.

in Nature Communications on 2025-02-20 00:00:00 UTC.

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Expanding protected area coverage for migratory birds could improve long-term population trends

Nature Communications, Published online: 20 February 2025; doi:10.1038/s41467-025-57019-x

Populations of many migratory taxa have been declining over recent decades. This study examines how well protected areas in Europe cover the dynamic distributions of migratory birds throughout their annual cycles and finds that many species are inadequately protected, especially farmland birds, and that higher protected area coverage correlates with more positive long-term population trends.

in Nature Communications on 2025-02-20 00:00:00 UTC.

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Warming-induced retreat of West Antarctic glaciers weakened carbon sequestration ability but increased mercury enrichment

Nature Communications, Published online: 20 February 2025; doi:10.1038/s41467-025-57085-1

This study reveals that Holocene warming and glacial retreat in West Antarctica reduced carbon sequestration but enhanced mercury burial in Ross Sea sediments, suggesting future warming could further accelerate carbon loss and mercury accumulation.

in Nature Communications on 2025-02-20 00:00:00 UTC.

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Publisher Correction: Land system changes of terrestrial tipping elements on Earth under global climate pledges: 2000–2100

Scientific Data, Published online: 20 February 2025; doi:10.1038/s41597-025-04648-y

Publisher Correction: Land system changes of terrestrial tipping elements on Earth under global climate pledges: 2000–2100

in Nature scientific data on 2025-02-20 00:00:00 UTC.

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APEC climate center multi-model ensemble dataset for seasonal climate prediction

Scientific Data, Published online: 20 February 2025; doi:10.1038/s41597-025-04643-3

APEC climate center multi-model ensemble dataset for seasonal climate prediction

in Nature scientific data on 2025-02-20 00:00:00 UTC.

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Specialized metabolome and transcriptome atlas of developing Arabidopsis thaliana seed under warm temperatures

Scientific Data, Published online: 20 February 2025; doi:10.1038/s41597-025-04563-2

Specialized metabolome and transcriptome atlas of developing Arabidopsis thaliana seed under warm temperatures

in Nature scientific data on 2025-02-20 00:00:00 UTC.

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High-quality genome assembly and annotation of Thalassiosira rotula (synonym of Thalassiosira gravida)

Scientific Data, Published online: 20 February 2025; doi:10.1038/s41597-025-04634-4

High-quality genome assembly and annotation of Thalassiosira rotula (synonym of Thalassiosira gravida)

in Nature scientific data on 2025-02-20 00:00:00 UTC.

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A chromosome-scale reference assembly of Vigna radiata enables delineation of centromeres and telomeres

Scientific Data, Published online: 20 February 2025; doi:10.1038/s41597-025-04436-8

A chromosome-scale reference assembly of Vigna radiata enables delineation of centromeres and telomeres

in Nature scientific data on 2025-02-20 00:00:00 UTC.

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Using a units ontology to annotate pre-existing metadata

Scientific Data, Published online: 20 February 2025; doi:10.1038/s41597-025-04587-8

Using a units ontology to annotate pre-existing metadata

in Nature scientific data on 2025-02-20 00:00:00 UTC.

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FaultSeg: A Dataset for Train Wheel Defect Detection

Scientific Data, Published online: 20 February 2025; doi:10.1038/s41597-025-04557-0

FaultSeg: A Dataset for Train Wheel Defect Detection

in Nature scientific data on 2025-02-20 00:00:00 UTC.

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A dataset for monitoring agricultural drought in Europe

Scientific Data, Published online: 20 February 2025; doi:10.1038/s41597-024-04199-8

A dataset for monitoring agricultural drought in Europe

in Nature scientific data on 2025-02-20 00:00:00 UTC.

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Multiplexed Lectin-PAINT super-resolution microscopy enables cell glycotyping

Communications Biology, Published online: 20 February 2025; doi:10.1038/s42003-025-07626-7

A super-resolution method for single-molecule detection and tracking of glycans on the surface of living cells is developed. Glycan’s abundance and mobility are used to explore differences in glycosylation at single-cell level.

in Nature communications biology on 2025-02-20 00:00:00 UTC.

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Automatic engagement of limbic and prefrontal networks in response to food images reflects distinct information about food hedonics and inhibitory control

Communications Biology, Published online: 20 February 2025; doi:10.1038/s42003-025-07704-w

Representational similarity analysis reveals distinct networks of prefrontal and limbic brain regions that automatically encode healthfulness and hedonic value, guiding food consumption.

in Nature communications biology on 2025-02-20 00:00:00 UTC.

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Learning to operate an imagined speech Brain-Computer Interface involves the spatial and frequency tuning of neural activity

Communications Biology, Published online: 20 February 2025; doi:10.1038/s42003-025-07464-7

Training to operate a brain-computer interface for decoding imagined speech from non-invasive EEG improves control performance and induces dynamic changes in brain oscillations crucial for speech processing.

in Nature communications biology on 2025-02-20 00:00:00 UTC.

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mGluR5-mediated astrocytes hyperactivity in the anterior cingulate cortex contributes to neuropathic pain in male mice

Communications Biology, Published online: 20 February 2025; doi:10.1038/s42003-025-07733-5

mGluR5-mediated astrocytic hyperactivity in the ACC drives neuropathic pain in male mice by increasing extracellular glutamate and synaptic transmission, highlighting a key role of astrocyte-neuron interactions in chronic pain.

in Nature communications biology on 2025-02-20 00:00:00 UTC.

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Regulation of chromatin modifications through coordination of nucleus size and epithelial cell morphology heterogeneity

Communications Biology, Published online: 20 February 2025; doi:10.1038/s42003-025-07677-w

Cell morphology heterogeneity in epithelial tissues, driven by asymmetric cell division, correlates with nucleus morphology and impacts chromatin state diversity through histone modifications.

in Nature communications biology on 2025-02-20 00:00:00 UTC.

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Developmental phylotranscriptomics in grapevine suggests an ancestral role of somatic embryogenesis

Communications Biology, Published online: 20 February 2025; doi:10.1038/s42003-025-07712-w

A phylotranscriptomic study in grapevine suggests that somatic embryogenesis represents a primordial embryogenic program in plants, showing stronger evolutionary system-level analogies to animal development than zygotic embryogenesis.

in Nature communications biology on 2025-02-20 00:00:00 UTC.

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The histone demethylase dLsd1 regulates organ size by silencing transposable elements

Communications Biology, Published online: 20 February 2025; doi:10.1038/s42003-025-07724-6

Genetic experiments coupled with genomic analysis reveal the role of the histone demethylase dLsd1 in regulating organ size via the repression of transposable elements’ transcription and mobilization in the model organism Drosophila melanogaster.

in Nature communications biology on 2025-02-20 00:00:00 UTC.

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Differences in HIV-1 reservoir size, landscape characteristics, and decay dynamics in acute and chronic treated HIV-1 Clade C infection

Persisting HIV reservoir viruses in resting CD4 T cells and other cellular subsets are a barrier to cure efforts. Early antiretroviral therapy (ART) enables post-treatment viral control in some cases, but mechanisms remain unclear. We hypothesised that ART initiated before peak viremia impacts HIV-1 subtype C reservoirs. We studied 35 women at high risk of infection from Durban, South Africa, identified with hyperacute HIV by twice-weekly HIV-RNA testing. Participants included 11 starting ART at a median of 456 (297–1203) days post-onset of viremia (DPOV) and 24 at 1 (1–3) DPOV. Peripheral blood mononuclear cells (PBMCs) were used to measured total HIV-1 DNA by droplet digital PCR (ddPCR) and sequence viral reservoir genomes by full-length proviral sequencing (FLIP-seq). ART during hyperacute infection blunted peak viremia (p<0.0001), but contemporaneous total HIV-1 DNA did not differ (p=0.104). Over 1 year, a decline of total HIV-1 DNA was observed in early treated persons (p=0.0004), but not late treated. Among 697 viral genome sequences, the proviral genetic landscape differed between untreated, late treated, and early treated groups. Intact genomes after 1 year were higher in untreated (31%) versus late treated (14%) and early treated (0%). Treatment in both late and early infection caused more rapid decay of intact (13% and 51% per month) versus defective (2% and 35%) viral genomes. However, intact genomes persisted 1 year post chronic treatment but were undetectable with early ART. Early ART also reduced phylogenetic diversity of intact genomes and limited cytotoxic T lymphocyte immune escape variants in the reservoir. Overall, ART initiated in hyperacute HIV-1 subtype C infection did not impact reservoir seeding but was associated with rapid intact viral genome decay, reduced genetic complexity, and limited immune escape, which may accelerate reservoir clearance in combination with other interventional strategies.

in eLife on 2025-02-20 00:00:00 UTC.

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To be, or not to be, part-time in academia

Part-time working can be beneficial for individual academics, and also for academia as a whole. In addition to improving work-life balance and well-being, the benefits of part-time working include increased motivation, reduced burnout, and workplaces that are more diverse and inclusive. Here, six researchers who have experience of working part-time discuss what individuals, employers and funders can do to promote and support part-time working in academia.

in eLife on 2025-02-20 00:00:00 UTC.

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Systems genomics of salinity stress response in rice

Populations can adapt to stressful environments through changes in gene expression. However, the fitness effect of gene expression in mediating stress response and adaptation remains largely unexplored. Here, we use an integrative field dataset obtained from 780 plants of Oryza sativa ssp. indica (rice) grown in a field experiment under normal or moderate salt stress conditions to examine selection and evolution of gene expression variation under salinity stress conditions. We find that salinity stress induces increased selective pressure on gene expression. Further, we show that trans-eQTLs rather than cis-eQTLs are primarily associated with rice’s gene expression under salinity stress, potentially via a few master-regulators. Importantly, and contrary to the expectations, we find that cis-trans reinforcement is more common than cis-trans compensation which may be reflective of rice diversification subsequent to domestication. We further identify genetic fixation as the likely mechanism underlying this compensation/reinforcement. Additionally, we show that cis- and trans-eQTLs are under balancing and purifying selection, respectively, giving us insights into the evolutionary dynamics of gene expression variation. By examining genomic, transcriptomic, and phenotypic variation across a rice population, we gain insights into the molecular and genetic landscape underlying adaptive salinity stress responses, which is relevant for other crops and other stresses.

in eLife on 2025-02-20 00:00:00 UTC.

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Robust variability of grid cell properties within individual grid modules enhances encoding of local space

Although grid cells are one of the most well-studied functional classes of neurons in the mammalian brain, whether there is a single orientation and spacing value per grid module has not been carefully tested. We analyze a recent large-scale recording of medial entorhinal cortex to characterize the presence and degree of heterogeneity of grid properties within individual modules. We find evidence for small, but robust, variability and hypothesize that this property of the grid code could enhance the encoding of local spatial information. Performing analysis on synthetic populations of grid cells, where we have complete control over the amount heterogeneity in grid properties, we demonstrate that grid property variability of a similar magnitude to the analyzed data leads to significantly decreased decoding error. This holds even when restricted to activity from a single module. Our results highlight how the heterogeneity of the neural response properties may benefit coding and opens new directions for theoretical and experimental analysis of grid cells.

in eLife on 2025-02-20 00:00:00 UTC.

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Reduced discrimination between signals of danger and safety but not overgeneralization is linked to exposure to childhood adversity in healthy adults

Childhood adversity is a strong predictor of developing psychopathological conditions. Multiple theories on the mechanisms underlying this association have been suggested which, however, differ in the operationalization of ‘exposure.’ Altered (threat) learning mechanisms represent central mechanisms by which environmental inputs shape emotional and cognitive processes and ultimately behavior. 1402 healthy participants underwent a fear conditioning paradigm (acquisition training, generalization), while acquiring skin conductance responses (SCRs) and ratings (arousal, valence, and contingency). Childhood adversity was operationalized as (1) dichotomization, and following (2) the specificity model, (3) the cumulative risk model, and (4) the dimensional model. Individuals exposed to childhood adversity showed blunted physiological reactivity in SCRs, but not ratings, and reduced CS+/CS- discrimination during both phases, mainly driven by attenuated CS+ responding. The latter was evident across different operationalizations of ‘exposure’ following the different theories. None of the theories tested showed clear explanatory superiority. Notably, a remarkably different pattern of increased responding to the CS- is reported in the literature for anxiety patients, suggesting that individuals exposed to childhood adversity may represent a specific sub-sample. We highlight that theories linking childhood adversity to (vulnerability to) psychopathology need refinement.

in eLife on 2025-02-20 00:00:00 UTC.

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Combined forces of hydrostatic pressure and actin polymerization drive endothelial tip cell migration and sprouting angiogenesis

Cell migration is a key process in the shaping and formation of tissues. During sprouting angiogenesis, endothelial tip cells invade avascular tissues by generating actomyosin-dependent forces that drive cell migration and vascular expansion. Surprisingly, endothelial cells (ECs) can still invade if actin polymerization is inhibited. In this study, we show that endothelial tip cells employ an alternative mechanism of cell migration that is dependent on Aquaporin (Aqp)-mediated water inflow and increase in hydrostatic pressure. In the zebrafish, ECs express aqp1a.1 and aqp8a.1 in newly formed vascular sprouts in a VEGFR2-dependent manner. Aqp1a.1 and Aqp8a.1 loss-of-function studies show an impairment in intersegmental vessels formation because of a decreased capacity of tip cells to increase their cytoplasmic volume and generate membrane protrusions, leading to delayed tip cell emergence from the dorsal aorta and slower migration. Further inhibition of actin polymerization resulted in a greater decrease in sprouting angiogenesis, indicating that ECs employ two mechanisms for robust cell migration in vivo. Our study thus highlights an important role of hydrostatic pressure in tissue morphogenesis.

in eLife on 2025-02-20 00:00:00 UTC.

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Impact of liver-specific survival motor neuron (SMN) depletion on central nervous system and peripheral tissue pathology

Spinal muscular atrophy (SMA) is caused by mutations in the Survival Motor Neuron 1 (SMN1) gene. While traditionally viewed as a motor neuron disorder, there is involvement of various peripheral organs in SMA. Notably, fatty liver has been observed in SMA mouse models and SMA patients. Nevertheless, it remains unclear whether intrinsic depletion of SMN protein in the liver contributes to pathology in the peripheral or central nervous systems. To address this, we developed a mouse model with a liver-specific depletion of SMN by utilizing an Alb-Cre transgene together with one Smn^2B allele and one Smn1 exon 7 allele flanked by loxP sites. Initially, we evaluated phenotypic changes in these mice at postnatal day 19 (P19), when the severe model of SMA, the Smn^2B/- mice, exhibit many symptoms of the disease. The liver-specific SMN depletion does not induce motor neuron death, neuromuscular pathology or muscle atrophy, characteristics typically observed in the Smn^2B/- mouse at P19. However, mild liver steatosis was observed, although no changes in liver function were detected. Notably, pancreatic alterations resembled that of Smn^2B/-mice, with a decrease in insulin-producing β-cells and an increase in glucagon-producingα-cells, accompanied by a reduction in blood glucose and an increase in plasma glucagon and glucagon-like peptide (GLP-1). These changes were transient, as mice at P60 exhibited recovery of liver and pancreatic function. While the mosaic pattern of the Cre-mediated excision precludes definitive conclusions regarding the contribution of liver-specific SMN depletion to overall tissue pathology, our findings highlight an intricate connection between liver function and pancreatic abnormalities in SMA.

in eLife on 2025-02-20 00:00:00 UTC.

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Rare missense variants of the leukocyte common antigen related receptor (LAR) display reduced activity in transcellular adhesion and synapse formation

The leukocyte common antigen related receptor (LAR) is a member of the LAR receptor protein tyrosine phosphatase (RPTP) family of synaptic adhesion molecules that contribute to the proper alignment and specialization of synaptic connections in the mammalian brain. LAR-RPTP members have been genetically associated with neuropsychiatric disorders, but the molecular consequences of genetic perturbations of LAR remain unstudied. Using exome sequencing data from psychiatric patients and controls, we identify rare missense variants of LAR that render the extracellular domain (ECD) unstable and susceptible to proteolytic cleavage. Using recombinant and cellular systems, we describe three variants that cause disruption of the LAR:NGL-3 interaction, which results in loss of transcellular adhesion and synaptogenic effects. Furthermore, we show that overexpression of two of these variants elicit altered morphological phenotypes in an imaging-based morphological profiling assay compared to wild type LAR, suggesting that destabilization of the LAR ECD has broad effects on LAR function. In conclusion, our study identifies three rare, missense variants in LAR that could provide insights into LAR involvement with psychiatric pathobiology.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Reactive Pericytes Lead to Microvascular Dysfunction and Cortical Neurodegeneration During Experimental Autoimmune Encephalomyelitis

The mechanisms underlying neurodegeneration in multiple sclerosis remain incompletely understood. In this study, we aimed to investigate the role of vascular dysfunction in cortical neurodegeneration using a chronic cranial window model of experimental autoimmune encephalomyelitis in mice. After the induction of experimental autoimmune encephalomyelitis with myelin oligodendrocyte glycoprotein peptides in C57BL/6J mice, we assessed cerebrovascular reactivity though a chronic cranial window using laser speckle contrast imaging and intrinsic optical signal imaging in awake animals. We observed a significant reduction in cortical cerebrovascular reactivity during peak inflammation in the EAE group, as detected by laser speckle contrast imaging after 5% hypercapnia (p=0.04) and optical signal imaging after whisker stimulation (p=0.008). Histological analysis revealed a diffuse increase in CD13+ pericyte coverage (p=0.001), accompanied by focal IgG deposition within the microvascular lumen (p=0.04) and increased amount of CD45+ leukocytes stalled in microvessels (p=0.03) in the cortex of experimental autoimmune encephalomyelitis mice. Microglial activation was also present in the cortex of experimental autoimmune encephalomyelitis mice (p=0.04) and was particularly evident around microvessels with IgG deposition. Subpial and intracortical foci exhibiting loss of NeuN reactivity (p=0.03) and axonal loss (p=0.007) were detected in experimental autoimmune encephalomyelitis, but not in control mice. Altogether, these results demonstrate that microvascular function and neurovascular unit elements are globally affected in the cortex during autoimmune neuroinflammation and is related to neurodegeneration.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Leveraging a Vision-Language Model with Natural Text Supervision for MRI Retrieval, Captioning, Classification, and Visual Question Answering

Large multimodal models are now extensively used worldwide, with the most powerful ones trained on massive, general-purpose datasets. Despite their rapid deployment, concerns persist regarding the quality and domain relevance of the training data, especially in radiology, medical research, and neuroscience. Additionally, healthcare data privacy is paramount when querying models trained on medical data, as is transparency regarding service hosting and data storage. So far, most deep learning algorithms in radiologic research are designed to perform a specific task (e.g., diagnostic classification) and cannot be prompted to perform multiple tasks using natural language. In this work, we introduce a framework based on vector retrieval and contrastive learning to efficiently learn visual brain MRI concepts via natural language supervision. We show how the method learns to identify factors that affect the brain in Alzheimer's disease (AD) via joint embedding and natural language supervision. First, we pre-train separate text and image encoders using self-supervised learning, and jointly fine-tune these encoders to develop a shared embedding space. We train our model to perform multiple tasks, including MRI retrieval, MRI captioning, and MRI classification. We show its versatility by developing a retrieval and re-ranking mechanism along with a transformer decoder for visual question answering. By learning a cross-modal embedding of radiologic features and text, our approach can learn to perform diagnostic and prognostic assessments in AD research as well as to assist practicing clinicians. Integrating medical imaging with clinical descriptions and text prompts, we aim to provide a general, versatile tool for detecting radiologic features described by text, offering a new approach to radiologic research.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Parameter Efficient Fine-tuning of Transformer-based Masked Autoencoder Enhances Resource Constrained Neuroimage Analysis

Recent innovations in artificial intelligence (AI) have increasingly focused on large-scale foundational models that are more general purpose in contrast to conventional models trained to perform specialized tasks. Transformer-based architectures have become the standard backbone in foundation models across data modalities (image, text, audio, video). There has been a keen interest in applying parameter-efficient fine-tuning (PEFT) methods to adapt these models to specialized downstream tasks in language and vision. These methods are particularly essential for medical image analysis where the limited availability of training data could lead to overfitting. In this work, we evaluated different types of PEFT methods on pre-trained vision transformers relative to typical training approaches, such as full fine-tuning and training from scratch. We used a transformer-based masked autoencoder (MAE) framework, to pretrain a vision encoder on T1-weighted (T1-w) brain MRIs. The pretrained vision transformers were then fine-tuned using different PEFT methods that reduced the trainable model parameters to as few as 0.04% of the original model size. Our study shows that: 1. PEFT methods were competitive with or outperformed the reference full fine-tuning approach and outperformed training from scratch, with only a fraction of the trainable parameters; 2. PEFT methods with a 32% reduction in model size boosted Alzheimer's disease (AD) classification by 3% relative to full fine-tuning and 11% relative to a 3D CNN, with only 258 training scans; and 3. PEFT methods performed well on diverse neuroimaging tasks including AD and Parkinson's disease (PD) classification, and "brain-age" prediction based on T1-w MRI datasets - a standard benchmark for deep learning models in neuroimaging; 4. smaller model sizes were competitive with larger models in test performance. Our results show the value of adapting foundation models to neuroimaging tasks efficiently and effectively in contrast to training stand-alone special purpose models.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Modulations of thalamo-cortical coupling during voluntary movement in patients with essential tremor

The ventral intermediate nucleus of the thalamus (VIM) is the main thalamic hub for processing cerebellar inputs and the main deep brain stimulation target for the treatment of essential tremor (ET). As such, it presumably plays a critical role in motor control. So far, however, this structure has been rarely investigated in humans, and almost all of the existing studies focus on tremor. Here, we set out to study neural oscillations in the VIM and their coupling to cortical oscillations during voluntary movement. We investigated thalamo-cortical coupling by means of simultaneous recordings of thalamic local field potentials and magnetoencephalography in 10 ET patients with externalized deep brain stimulation electrodes. Brain activity was measured while patients were pressing a button repeatedly in response to a visual cue. In a whole-brain analysis of coherence between VIM and cortex, we contrasted activity around a pre-movement baseline and button pressing. Button pressing was associated with a bilateral decrease of thalamic power in the alpha (8-12 Hz) and beta (13-21 Hz) band and a contralateral power increase in the gamma (35-90 Hz) band. Moreover, changes in VIM-cortex coherence were observed. Alpha/low beta (8-20 Hz) coherence decreased before and during movement, and the effect localized to the supplementary motor area and premotor cortex. A rebound of high beta (21-35 Hz) coherence occurred in the same region, but was more focal than the suppression. Pre-movement levels of thalamo-cortex low-beta coherence correlated with reaction time. Our results demonstrate that voluntary movement is associated with modulations of behaviourally relevant thalamic coupling, primarily to premotor areas. We observed a clear distinction between low- and high-beta frequencies and our results suggest that the concept of antikinetic beta oscillations, originating from research on Parkinson's disease, is transferable to ET.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Influence of sustained cognitive loading on finger circulatory and thermoperceptual responsiveness to localized cooling

Our aim was to examine whether finger vasomotor and thermoperceptual responses to local cooling would be modulated by sustained cognitive loading. To this end, finger temperature, circulatory (i.e., cutaneous vascular conductance, CVC) and perceptual responses were monitored, in twelve healthy men, during and after a 30-min hand immersion in 8{degrees}C water, performed either immediately after a 60-min continual execution of a cognitive task battery (cognitive[->]cold trial), or during the simultaneous performance of the cognitive task (cognitive+cold trial). Subjects responses were compared with those obtained in a control cold-provocation trial, wherein they watched an emotionally-neutral documentary. The cognitive task temporary enhanced the perceived levels of mental effort and fatigue in both intervention trials. In the cognitive[->]cold trial, the cold-induced reduction in finger CVC and increase in mean arterial pressure were blunted (P < 0.01), and the thermal discomfort was alleviated (P = 0.05). In the cognitive+cold trial, no intertrial differences were noted during the cold-water immersion phase (P [≥] 0.28), but the finger CVC was enhanced during the last part of the rewarming phase (P = 0.05). Present findings, therefore, demonstrate that (i) in moderately mentally-fatigued individuals, finger cold-induced vasoconstriction is transiently attenuated, and thermal discomfort is mitigated, and (ii) superimposition of cognitive loading on cold stress does not alter finger vasoreactivity or thermosensitivity during cooling, but facilitates finger reperfusion following cooling.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Gender imbalance in citations most pronounced in high-impact neuroscience journals

In the past several years, neuroscience, like many other fields, has worked to address pervasive gender imbalances. Although tangible improvements have been made in academic publishing and conference participation, gender imbalances in citations among leading neuroscience journals persist and are increasing with time. Here, we expand upon prior work by providing a more comprehensive analysis of citation practices across fifty journals to improve our understanding of the dynamics of the field as a whole, particularly across different kinds of journals. We first confirm that reference lists tend to include more papers with men as first and last author than expected if gender were unrelated to citation practices. Further, we demonstrate that this effect is strongest in the most influential journals. We also find that the apparent closure of the gender gap is due to the interaction of three unique, nuanced patterns of citation: one that is characterized by relative overcitation of papers with men as both first and last author; one that is characterized by relative overcitation of women as the last author, and one that is characterized by relative undercitation of women as the first author. In addition, we find that these patterns of citation are not distributed evenly across the field: more prestigious journals tend to have articles with citation gaps favoring men, while less prestigious journals tend to overcite papers with women as last authors. We discuss potential drivers for these patterns and suggest some implications for the field moving forward.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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CellFIE: Integrating Pathway Discovery With Pooled Profiling of Perturbations Uncovers Pathways of Huntington's Disease, Including Genetic Modifiers of Neuronal Development and Morphology

Genomic screens and GWAS are powerful tools for identifying disease-modifying genes, but it is often challenging to understand the pathways by which these genes function. Here, we take an integrated approach that combines network analysis and an imaging-based pooled genetic perturbation study to examine modifiers of Huntington's disease (HD). The computational analysis highlighted several genes in a subnetwork enriched for modifiers of neuronal development and morphology. To test the functional roles of these genes, we developed an experimental pipeline that allows pooled CRISPRi KD of 21 genes in human iPSC-derived neurons followed by optical analysis of genotypes, neuronal arborization, multiplexed pathway activity and morphological fingerprint readout. This approach recovered known genes involved in morphology and confirmed unexpected links from the network between several genetic modifiers of HD and morphology. Our approach overcomes challenges in pooled measurement of neuronal function and health and could be adapted for other phenotypes in HD and other neurological diseases.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Boosting Brainpower in Ageing: Task-Specific and Transfer Effects of tDCS-Enhanced Working Memory Training

Ageing is associated with neural alterations that impair cognitive abilities, particularly working memory (WM)--the capacity to temporarily store and manipulate information essential for daily functioning. Transcranial Direct Current Stimulation (tDCS) has shown promise in enhancing WM in older adults by modulating cortical excitability and promoting neuroplasticity. However, findings on the combined effects of tDCS and WM training remain inconsistent, particularly regarding transfer effects to non-trained WM tasks (near transfer) or other cognitive domains (far transfer). This study examined the behavioural and neural effects of tDCS on distinct WM phases (encoding, retention/manipulation, recall) in older adults. Over three weeks, participants underwent six sessions of adaptive WM training paired with tDCS targeting the left dorsolateral prefrontal cortex (DLPFC). Neural activity was assessed via EEG, focusing on theta and alpha bands. Participants were divided into tDCS and placebo groups and completed two WM tests, the Letter Span and Corsi Test, with retention and manipulation conditions. Results showed no additional behavioural or neural benefits of tDCS. However, both groups exhibited near-transfer effects that persisted one-month post-training. Neural changes varied by task: the Letter Span showed increased alpha power during manipulation, indicating enhanced maintenance of information during that phase, while the Corsi Test showed reduced left-hemisphere theta power during recall, reflecting reduced hemispheric asymmetry. Inter-individual variability likely contributed to inconsistencies and a lack of correlations between outcomes. These findings highlight the importance of personalised tDCS protocols and suggest adaptive WM training can yield enduring cognitive and neural benefits in older adults.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Effective connectivity between the medial temporal lobes and early visual cortex modulated by unrestricted viewing predicts memory retrieval and gaze reinstatement

Memory and gaze behavior are intricately linked, guiding one another to extract information and create mental representations of our environment for subsequent retrieval. Recent findings from functional neuroimaging and computational modeling suggest that reciprocal interactions between the extended hippocampal system and visuo-oculomotor regions are functionally relevant for building these mental representations during visual exploration. Yet, evidence for the directionality of information flow during encoding within this reciprocal architecture in humans is limited. In the current study, we used dynamic causal modeling (DCM) to give a non-invasive account for the directional influences between these systems when new memories are created. Here, we provide novel evidence demonstrating how unrestricted, naturalistic visual exploration induces changes in this connectivity. Subsequent memory retrieval performance was also predicted by the pattern of connectivity modulated by unrestricted visual exploration, identifying the mechanism underlying a rich history of previous work linking increased gaze behavior during encoding to later memory. Together, these findings suggest that gaze behavior shapes the ways in which brain dynamics within and between the hippocampal system and early visual cortex unfold during encoding in humans. Importantly, these directional interactions support the building of coherent, lasting mental representations.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Effects of Pesticide Exposure on Neuroinflammation and Microglial Gene Expression: Relevance to Mechanisms of Alzheimer's Disease Risk

Background: Alzheimer's disease (AD) is characterized by the presence of amyloid-{beta} plaques, neurofibrillary tangles, and neuroinflammation. Previously, we reported serum levels of dichlorodiphenyldichloroethylene (DDE), the primary metabolite of the pesticide dichlorodiphenyltrichloroethane (DDT), were significantly higher in AD patients compared to age-matched controls and that DDT exposure worsened AD pathology in animal models. Objective: Here, we investigated the effect of DDT on neuroinflammation in primary mouse microglia (PMG) and C57BL/6J mice. Methods: Effects of DDT on inflammation and disease-associated microglia were determined in primary mouse microglia and C57BL/6J mice. Results: PMG exposed to DDT (0.5-5.0 M) elicited a ~2-3-fold increase in Il-1b mRNA levels, with similar concentration-dependent upregulation in Il-6, Nos2, and Tnfa. These effects were blocked by the sodium channel antagonist tetrodotoxin, demonstrating the role of DDT-microglial sodium channel interactions in mediating this response. Additionally, NOS2 protein levels increased by ~1.5-2-fold, while TNFa was elevated by 2-4-fold. C57BL/6J male and female mice exposed to DDT (30 mg/kg) demonstrated significantly increased mRNA levels of Nos2, Il-1b, and Il-6 in the frontal cortex (1.5-2.3-fold), and Nos2, Il-1b, and Tnfa (1.5-1.8-fold) in the hippocampus. Furthermore, microglial homeostatic genes, Cx3cr1, P2ry12, and Tmem119, were downregulated, while stage 1 disease-associated microglia genes were upregulated both in vitro and in vivo. Notably, Apoe and Trem2 were only upregulated in the frontal cortex and hippocampus of females. Conclusion: These data indicate that DDT increases neuroinflammation, which may result from direct actions of DDT on microglia, providing a novel pathway by which DDT may contribute to AD risk.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Intracellular Trafficking SNARE Protein, Syntaxin-6, is a Modifier of Prion and Tau Pathogenesis in vivo and in Cellular Models

Syntaxin-6, a SNARE protein involved in intracellular protein trafficking, is a proposed risk factor for sporadic prion disease, progressive supranuclear palsy and Alzheimer's disease. However, no study has validated its functional role in these diseases, explored the disease stage at which it is acting nor its mechanism of action. Here, we show that syntaxin-6 acts at early stages of prion disease in experimental mice by increasing disease transmission risk following inoculation with low prion doses. Conversely, syntaxin-6 does not affect prion propagation kinetics or toxicity during established disease. Syntaxin-6 manipulation in cellular models profoundly alters the subcellular distribution and morphologies of disease-related PrP and modifies prion export. Furthermore, syntaxin-6 knockout in a transgenic tauopathy mouse model exerts protective effects on numerous physiological, behavioural and neuropathological outcome measures. Therefore, our studies firmly establish syntaxin-6 as a modifier of prion and tau pathogenesis, providing key insights into a fundamental mechanism of neurodegeneration.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Syngap+/- CA1 pyramidal neurons exhibit upregulated translation of long mRNAs associated with LTP

In the Syngap+/- model of SYNGAP1-related intellectual disability (SRID), excessive neuronal protein synthesis is linked to deficits in synaptic plasticity. Here, we use Translating Ribosome Affinity Purification and RNA-seq (TRAP-seq) to identify mistranslating mRNAs in Syngap+/- CA1 pyramidal neurons that exhibit enhanced synaptic stability and impaired long-term potentiation (LTP). We find the translation environment is significantly altered in a manner that is distinct from the Fmr1-/y model of Fragile X Syndrome (FXS), another monogenic model of autism and intellectual disability (ID). The Syngap+/- translatome is enriched for regulators of DNA repair, and mimics changes induced with chemical LTP (cLTP) in WT. This includes a striking upregulation in the translation of mRNAs with a longer length (>2kb) coding sequence (CDS). In contrast, long CDS transcripts are downregulated with induction of Gp1 metabotropic glutamate receptor induced long-term depression (mGluR-LTD) in WT, and this profile is mimicked in the Fmr1-/y model. Together, our results show the Syngap+/- and Fmr1-/y models mimic the translation environments of LTP and LTD, respectively, consistent with the dysregulation of these plasticity states in each model. Moreover, we show that translation of >2kb mRNAs is a defining feature of LTP that is oppositely regulated during LTD, revealing a novel mRNA signature of plasticity.

in bioRxiv: Neuroscience on 2025-02-20 00:00:00 UTC.

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Distinct insula subdivisions of resting-state functional connectivity in individuals with opioid and methamphetamine use disorders

Abstract

Different addictive drugs can impact the function and morphology of the brain in diverse ways. The insula cortex, an important brain node involved in craving and reward neural circuits in individuals with substance use disorders (including damage to the insula cortex), has been reported to reduce addictive behaviors. However, less is known about whether there is a functional difference between individuals with opioid and methamphetamine use disorders, especially regarding the function of the insula cortex. Fifty-eight individuals with opioid use disorder and sixty individuals with methamphetamine use disorder underwent resting-state and 3D-T1-weighted magnetic resonance imaging and completed craving questionnaires. Differences in insula subdivision resting-state functional connectivity between the groups were assessed, and their correlations with craving were analyzed. Compared with the methamphetamine group, the opioid group demonstrated increased connectivity of the right dorsal anterior insula but decreased connectivity of the right posterior insula and the left dorsal anterior insula/posterior insula/ventral anterior insula. Additionally, a negative correlation between functional connectivity and craving was observed in individuals with opioid and methamphetamine use disorders. This study provides insights into the various brain function connection patterns that are associated with different types of drug use with respect to opioid and methamphetamine use disorders.

Highlights

The methamphetamine, opioid, and healthy groups demonstrated different patterns of connectivity of the insula subdivisions.
A negative correlation between functional connectivity and craving was observed in individuals with opioid and methamphetamine use disorders.
This study provides insights into the various brain function connection patterns that are associated with different types of drug use with respect to opioid and methamphetamine use disorders.

in Cerebral Cortex on 2025-02-20 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 221: Effects of Packet Loss on Neural Decoding Effectiveness in Wireless Transmission

Brain Sciences, Vol. 15, Pages 221: Effects of Packet Loss on Neural Decoding Effectiveness in Wireless Transmission

Brain Sciences doi: 10.3390/brainsci15030221

Authors: Jiaqi Zheng Yuan Li Liangliang Chen Fei Wang Boxuan Gu Qixiang Sun Xiang Gao Fan Zhou

Background: In brain&ndash;computer interfaces, neural decoding plays a central role in translating neural signals into meaningful physical actions. These signals are transmitted to processors for decoding via wired or wireless channels; however, they are often subject to data loss, commonly referred to as &ldquo;packet loss&rdquo;. Despite their importance, the effects of different types and degrees of packet loss on neural decoding have not yet been comprehensively studied. Understanding these effects is critical for advancing neural signal processing. Methods: This study addresses this gap by constructing four distinct packet loss models that simulate the congestion, distribution, and burst loss scenarios. Using macaque superior arm movement decoding experiments, we analyzed the effects of the aforementioned packet loss types on decoding performance across six parameters (position, velocity, and acceleration in the x and y dimensions). The performance was assessed using the R2 metric and statistical comparisons across different loss scenarios. Results: Our results indicate that sudden, consecutive packet loss significantly degraded decoding performance. For the same packet loss probability, burst loss led to the largest decrease in the R2 value. Notably, when the packet loss rate reached 10%, the decoding performance for acceleration dropped to 73% of the original R2 value. On the other hand, when the packet loss rate was within 2%, the neural signal decoding results across all packet loss models remained largely unaffected. However, as the packet loss rate increased, the impact became more pronounced. These findings highlight the varying degrees to which different packet loss models affect decoding outcomes. Conclusions: This study quantitatively evaluated the relationship between packet loss and neural decoding outcomes, highlighting the differential effects of loss patterns on decoding parameters, and it proposed some methods and devices to solve the problem of packet loss. These findings offer valuable insights for the development of resilient neural signal acquisition and processing systems capable of mitigating the impact of packet loss.

in Brain Sciences on 2025-02-20 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 220: From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications

Brain Sciences, Vol. 15, Pages 220: From Neural Networks to Emotional Networks: A Systematic Review of EEG-Based Emotion Recognition in Cognitive Neuroscience and Real-World Applications

Brain Sciences doi: 10.3390/brainsci15030220

Authors: Evgenia Gkintoni Anthimos Aroutzidis Hera Antonopoulou Constantinos Halkiopoulos

Background/Objectives: This systematic review presents how neural and emotional networks are integrated into EEG-based emotion recognition, bridging the gap between cognitive neuroscience and practical applications. Methods: Following PRISMA, 64 studies were reviewed that outlined the latest feature extraction and classification developments using deep learning models such as CNNs and RNNs. Results: Indeed, the findings showed that the multimodal approaches were practical, especially the combinations involving EEG with physiological signals, thus improving the accuracy of classification, even surpassing 90% in some studies. Key signal processing techniques used during this process include spectral features, connectivity analysis, and frontal asymmetry detection, which helped enhance the performance of recognition. Despite these advances, challenges remain more significant in real-time EEG processing, where a trade-off between accuracy and computational efficiency limits practical implementation. High computational cost is prohibitive to the use of deep learning models in real-world applications, therefore indicating a need for the development and application of optimization techniques. Aside from this, the significant obstacles are inconsistency in labeling emotions, variation in experimental protocols, and the use of non-standardized datasets regarding the generalizability of EEG-based emotion recognition systems. Discussion: These challenges include developing adaptive, real-time processing algorithms, integrating EEG with other inputs like facial expressions and physiological sensors, and a need for standardized protocols for emotion elicitation and classification. Further, related ethical issues with respect to privacy, data security, and machine learning model biases need to be much more proclaimed to responsibly apply research on emotions to areas such as healthcare, human&ndash;computer interaction, and marketing. Conclusions: This review provides critical insight into and suggestions for further development in the field of EEG-based emotion recognition toward more robust, scalable, and ethical applications by consolidating current methodologies and identifying their key limitations.

in Brain Sciences on 2025-02-20 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 219: Resting-State Electroencephalogram and Speech Perception in Young Children with Developmental Language Disorder

Brain Sciences, Vol. 15, Pages 219: Resting-State Electroencephalogram and Speech Perception in Young Children with Developmental Language Disorder

Brain Sciences doi: 10.3390/brainsci15030219

Authors: Ana Campos Rocio Loyola-Navarro Claudia González Paul Iverson

Background/Objectives: Endogenous oscillations reflect the spontaneous activity of brain networks involved in cognitive processes. In adults, endogenous activity across different bands correlates with, and can even predict, language and speech perception processing. However, it remains unclear how this activity develops in children with typical and atypical development. Methods: We investigated differences in resting-state EEG between preschoolers with developmental language disorder (DLD), their age-matched controls with typical language development (TLD), and a group of adults. Results: We observed significantly lower oscillatory power in adults than in children (p &lt; 0.001 for all frequency bands), but no differences between the groups of children in power or hemispheric lateralisation, suggesting that oscillatory activity reflects differences in age, but not in language development. The only measure that differed between the children&rsquo;s groups was theta/alpha band ratio (p = 0.004), which was significantly smaller in TLD than in DLD children, although this was an incidental finding. Behavioural results also did not fully align with previous research, as TLD children performed better in the filtered speech test (p = 0.01), but not in the speech-in-babble one, and behavioural test scores did not correlate with high-frequency oscillations, lateralisation indices, or band ratio measures. Conclusions: We discuss the suitability of these resting-state EEG measures to capture group-level differences between TLD/DLD preschoolers and the relevance of our findings for future studies investigating neural markers of typical and atypical language development.

in Brain Sciences on 2025-02-20 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 218: Losing Your Sense of Smell: How Bad Is It?—A Comparative Study on the Personal Importance of Smell

Brain Sciences, Vol. 15, Pages 218: Losing Your Sense of Smell: How Bad Is It?—A Comparative Study on the Personal Importance of Smell

Brain Sciences doi: 10.3390/brainsci15030218

Authors: Maximiliaan K. P. Becht Garmt B. Dijksterhuis Digna M. A. Kamalski

The hierarchical perspective on senses has relegated smell to the lowest rank in Western culture while granting vision superiority. Studies show that olfactory impairments, like vision and hearing impairments, reduce quality of life. Our study examines the perceived value of smell in a student population in comparison to hearing and vision, hypothesizing differences based on previous loss of smell (&ge;2 weeks) and gender. University students were enlisted in a survey comparing smell to vision, hearing, and forfeiting the senses for various commodities (phone, EUR 10,000, hair, and social media). A total of 200 participants completed the survey, with 52 reporting previous loss of smell and 148 reporting no history of smell loss. Overall, smell was the most frequently forfeited sense. While the sacrifice of hearing and vision remained consistent across various commodities, smell was notably forfeited more for certain items. When comparing groups with and without previous loss of smell, no significant differences were observed in forfeiting the senses across various commodities, except for hair. However, it is noteworthy that smell was forfeited more often for all commodities when considering percentages. Furthermore, females exhibited a greater willingness to sacrifice their sense of smell for USD 10,000 and hair. Smell is valued the lowest among the three senses when asked directly and compared to various commodities. There were no significant differences in its perceived value between those with and without previous loss of smell. Furthermore, females tend to value their sense of smell less than males, according to the surveyed commodities.

in Brain Sciences on 2025-02-20 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 217: Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage

Brain Sciences, Vol. 15, Pages 217: Research on Anti-Interference Performance of Spiking Neural Network Under Network Connection Damage

Brain Sciences doi: 10.3390/brainsci15030217

Authors: Yongqiang Zhang Haijie Pang Jinlong Ma Guilei Ma Xiaoming Zhang Menghua Man

Background: With the development of artificial intelligence, memristors have become an ideal choice to optimize new neural network architectures and improve computing efficiency and energy efficiency due to their combination of storage and computing power. In this context, spiking neural networks show the ability to resist Gaussian noise, spike interference, and AC electric field interference by adjusting synaptic plasticity. The anti-interference ability to spike neural networks has become an important direction of electromagnetic protection bionics research. Methods: Therefore, this research constructs two types of spiking neural network models with LIF model as nodes: VGG-SNN and FCNN-SNN, and combines pruning algorithm to simulate network connection damage during the training process. By comparing and analyzing the millimeter wave radar human motion dataset and MNIST dataset with traditional artificial neural networks, the anti-interference performance of spiking neural networks and traditional artificial neural networks under the same probability of edge loss was deeply explored. Results: The experimental results show that on the millimeter wave radar human motion dataset, the accuracy of the spiking neural network decreased by 5.83% at a sparsity of 30%, while the accuracy of the artificial neural network decreased by 18.71%. On the MNIST dataset, the accuracy of the spiking neural network decreased by 3.91% at a sparsity of 30%, while the artificial neural network decreased by 10.13%. Conclusions: Therefore, under the same network connection damage conditions, spiking neural networks exhibit unique anti-interference performance advantages. The performance of spiking neural networks in information processing and pattern recognition is relatively more stable and outstanding. Further analysis reveals that factors such as network structure, encoding method, and learning algorithm have a significant impact on the anti-interference performance of both.

in Brain Sciences on 2025-02-20 00:00:00 UTC.

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Brain Sciences, Vol. 15, Pages 216: Downregulation of Parahippocampal Copper Chaperone for Superoxide Dismutase in Alzheimer’s Disease

Brain Sciences, Vol. 15, Pages 216: Downregulation of Parahippocampal Copper Chaperone for Superoxide Dismutase in Alzheimer’s Disease

Brain Sciences doi: 10.3390/brainsci15030216

Authors: Nicholas Sanchez Danilo S. Boskovic Charles W. Diamond Timothy W. Lyons Salvador Soriano Wolff M. Kirsch

Background/Objectives: Proper regulation of copper is essential for maintaining neuronal stability and is facilitated by several chaperone proteins, protecting cells from oxidative damage that would otherwise be caused by improperly regulated copper ions. Oxidative stress, resulting from such dysregulation, is hypothesized to play a significant role in the pathogenesis of Alzheimer&rsquo;s disease (AD). Methods: In this study, we evaluated the concentrations of the copper chaperones CCS, DCTN4, and ATOX1 in control and AD cases via Western blotting and ELISA, and quantified the copper concentrations in fractionated neurons using ICP-MS. Results: Our findings reveal a significant reduction in CCS levels in AD cases (p = 0.0085), with a progressive decline observed with advancing age. This decline was more pronounced in women, although the difference did not reach statistical significance (p = 0.0768). No significant differences were observed in copper concentrations within synaptosomal (p = 0.3869) or cytosolic fractions (p = 0.4461) between the AD and control cases. Additionally, comprehensive analyses of the effects of sex and age showed no significant impact on the levels of copper chaperones or copper distribution across cellular compartments. Conclusions: These results suggest a strong association between reduced CCS levels and AD pathology, highlighting a potential role for CCS in the redistribution of copper ions within neurons. This redistribution may contribute to oxidative stress and neuronal dysfunction, offering new insights into the mechanisms underlying AD pathogenesis.

in Brain Sciences on 2025-02-20 00:00:00 UTC.

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This Week in The Journal

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Microvascular Dysfunction, Mitochondrial Reprogramming, and Inflammasome Activation as Critical Regulators of Ischemic Stroke Severity Induced by Chronic Exposure to Prescription Opioids

The opioid epidemic endangers not only public health but also social and economic welfare. Growing clinical evidence indicates that chronic use of prescription opioids may contribute to an elevated risk of ischemic stroke and negatively impact poststroke recovery. In addition, NLRP3 inflammasome activation has been related to several cerebrovascular diseases, including ischemic stroke. Interestingly, an increase in NLRP3 inflammasome activation has also been reported in chronic opioid exposure. Given the pivotal roles of the blood–brain barrier (BBB) and oxidative stress in ischemic stroke pathophysiology, this study focuses on the impact of chronic exposure to prescription opioids on the integrity of cerebrovascular microvasculature, endothelial mitochondrial homeostasis, and the outcomes of ischemic stroke in male wild-type and NLRP3-deficient mice. Our results demonstrate that chronic opioid exposure can compromise the integrity of the BBB and elevate the generation of reactive oxygen species (ROS), resulting in endothelial mitochondrial dysfunction and apoptosis activation. We also provide evidence that opioid exposure enhances inflammasome activation and inflammatory responses and increases the severity of an ischemic stroke. The antioxidant N-acetylcysteine ameliorated these opioid-induced alterations and accelerated the poststroke tissue restoration and functional recovery processes in opioid-exposed mice. Importantly, there was also a significant decrease in ischemic stroke damage in the NLRP3-deficient mice with chronic opioid exposure as compared with wild-type controls. These findings indicate that chronic exposure to prescription opioids impacts the outcome of ischemic stroke by damaging microvascular cerebral integrity through inflammasome activation and mitochondrial dysfunction.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Development of Differential Sublaminar Feedforward Inhibitory Circuits in CA1 Hippocampus Requires Satb2

Pyramidal cells (PCs) in CA1 hippocampus can be classified by their radial position as deep or superficial and organize into subtype-specific circuits necessary for differential information processing. Specifically, superficial PCs receive fewer inhibitory synapses from parvalbumin (PV)-expressing interneurons than deep PCs, resulting in weaker feedforward inhibition of input from CA3 Schaffer collaterals. Using mice, we investigated mechanisms underlying CA1 PC differentiation and the development of this inhibitory circuit motif. We found that the transcriptional regulator SATB2, which is necessary for pyramidal cell differentiation in the neocortex, is selectively expressed in superficial PCs during early postnatal development. To investigate its role in CA1, we conditionally knocked out Satb2 from pyramidal cells during embryonic development using both male and female Emx1^IRES-Cre; Satb2^flox/flox mice. Loss of Satb2 resulted in increased feedforward inhibition of CA3 Schaffer collateral input to superficial PCs, which matched that observed to deep PCs in control mice. Using paired whole-cell recordings between PCs and PV+ interneurons, we found this was due to an increase in the strength of unitary inhibitory synaptic connections from PV+ interneurons to mutant superficial PCs. Regulation of synapse strength was restricted to inhibitory synapses; excitatory synaptic connections from CA3 to CA1 PCs and CA1 PCs to PV+ interneurons were not affected by loss of Satb2. Finally, we show that SATB2 expression in superficial PCs is necessary to suppress the formation of synapses from PV+ interneurons during synaptogenesis. Thus, early postnatal expression of SATB2 in superficial PCs is necessary for the development of biased feedforward inhibition in CA1.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Distinct Roles of Astrocytes and GABAergic Neurons in the Paraventricular Thalamic Nucleus in Modulating Diabetic Neuropathic Pain

Diabetic neuropathic pain (DNP) is a common chronic complication of diabetes mellitus and a clinically common form of neuropathic pain. The thalamus is an important center for the conduction and modulation of nociceptive signals. The paraventricular thalamic nucleus (PVT) is an important midline nucleus of the thalamus involved in sensory processing, but the specific role of PVT astrocytes and GABAergic neurons in DNP remains unclear. Here, we examined the activity of PVT astrocytes and neurons at various time points during the development of DNP by fluorescence immunohistochemistry and found that the activity of PVT astrocytes was significantly increased while that of PVT neurons was significantly decreased 14 d after streptozotocin injection in male rats. The inhibition of PVT astrocytes by chemogenetic manipulation relieved mechanical allodynia in male DNP model rats, whereas the activation of PVT astrocytes induced mechanical allodynia in normal male rats. Interestingly, chemogenetic activation of GABAergic neurons in the PVT alleviated mechanical allodynia in male DNP model rats, whereas chemogenetic inhibition of GABAergic neurons in the PVT induced mechanical allodynia in normal male rats. These data demonstrate the distinct roles of PVT astrocytes and GABAergic neurons in modulating DNP, revealing the mechanism of DNP pathogenesis and the role of the PVT in pain modulation.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Synaptic Vesicle Glycoprotein 2A Knockout in Parvalbumin and Somatostatin Interneurons Drives Seizures in the Postnatal Mouse Brain

Synaptic vesicle glycoprotein 2A (SV2A) is a presynaptic protein targeted by the antiseizure drug levetiracetam. One or more of the three SV2 genes is expressed in all neurons and is essential to normal neurotransmission. Loss of SV2A results in a seizure phenotype in mice and mutations in humans are also linked to congenital seizures. How SV2A action impacts the epileptic phenotype remains unclear, especially among the diverse neuronal populations that regulate network excitability. This study explored how brain structure and function are affected by SV2A conditional knock-out (SV2A-cKO) in specific neural cell subtypes. We show that SV2A-cKO in all neurons of the postnatal brain triggers lethal seizures, suggesting that the seizures observed in earlier knock-out models were not due to aberrant brain development. Similar lethal seizures are detected in mice in which the loss of SV2A is limited to GABAergic neurons, whereas loss in excitatory neurons produces no noticeable phenotype. No apparent gender difference was ever observed. Further investigation revealed that SV2A-cKO in different GABAergic interneuron populations induces seizure, with variable timescales and severity. Most notably SV2A-cKO in parvalbumin interneurons (PV⁺) leads to lethal seizures in young animals, while SV2A-cKO in somatostatin (SST) inhibitory neurons results in seizures that were scarcely observed only in adult mice. These results support the crucial role SV2A plays in PV and SST interneurons and suggest that the action of levetiracetam may be due largely to effects on a subset of GABAergic interneurons.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Regulation of Mutant Huntingtin Mitochondrial Toxicity by Phosphomimetic Mutations within Its N-Terminal Region

Huntington's disease (HD), a neurodegenerative disease, affects approximately 30,000 people in the United States, with 200,000 more at risk. Mitochondrial dysfunction caused by mutant huntingtin (mHTT) drives early HD pathophysiology. mHTT binds the translocase of the mitochondrial inner membrane (TIM23) complex, inhibiting mitochondrial protein import and altering the mitochondrial proteome. The 17 aa HTT N-terminal sequence (N17) acts as a regulatory domain in HD pathogenesis; phosphomimetic modification of serines 13 and 16 of the N17 domain impacts subcellular localization and degradation and ameliorates toxicity in mouse and cell models of HD. Using cellular and mouse (either sex) HD models, we investigated the mechanisms by which HTT phosphorylation affects intracellular localization. We demonstrate that introducing phosphomimetic mutations within the mHTT fragment N17 domain decreased TIM23 binding affinity and reduced inhibition of mHTT-mediated mitochondrial protein import. BACHD-SD mice expressing full-length mHTT harboring the same two N17 phosphomimetic mutations have an ameliorated HD-like phenotype as compared with mice expressing mHTT. Consistent with reduced toxicity in vivo, we found that the amount of full-length mHTT in the brain mitochondria of BACHD-SD transgenic mice is less when the mHTT has two phosphomimetic mutations. To complement the relevance of the phosphomimetic HTT findings, endogenous N17 phospho-mHTT is less likely to translocate to the mitochondria compared with nonphosphorylated mHTT. We demonstrate that phosphorylation of mHTT at serines 13 and 16 is critical for negatively regulating mHTT mitochondrial targeting and that reducing mHTT mitochondrial localization and binding to TIM23 results in amelioration of mHTT-induced mitochondrial and neuronal toxicity.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Estrogen-Regulated Lateral Septal Kisspeptin Neurons Abundantly Project to GnRH Neurons and the Hypothalamic Supramammillary Nucleus

While hypothalamic kisspeptin (KP) neurons play well-established roles in the estrogen-dependent regulation of reproduction, little is known about extrahypothalamic KP-producing (KP_LS) neurons of the lateral septum. As established previously, Kiss1 expression in this region is low and regulated by estrogen receptor- and GABA_B receptor-dependent mechanisms. Our present experiments on Kiss1-Cre/ZsGreen knock-in mice revealed that transgene expression in the LS begins at Postnatal Day (P)33–36 in females and P40–45 in males and is stimulated by estrogen receptor signaling. Fluorescent cell numbers continue to increase in adulthood and are higher in females. Viral tracing uncovered that the bulk of KP_LS fibers joins the medial forebrain bundle and terminates in the hypothalamic supramammillary nucleus. Smaller subsets innervate the medial amygdala or project to other limbic structures. One-quarter of gonadotropin-releasing hormone (GnRH)-immunoreactive perikarya in the preoptic area and their dendrites receive appositions from KP_LS axons. OVX adult Kiss1-Cre/ZsGreen mice treated for 4 d with 17β-estradiol or vehicle were used for RNA sequencing studies of laser-microdissected KP_LS neurons. The transcriptome included markers of GABAergic and neuropeptidergic (Penk, Cartpt, Vgf) cotransmission and 571 estrogen-regulated transcripts. Estrogen treatment upregulated the acetylcholine receptor transcript Chrm2 and, in slice electrophysiology experiments, caused enhanced muscarinic inhibition of KP_LS neurons. Finally, we provided immunohistochemical evidence for homologous neurons in the postmortem human brain, suggesting that KP_LS neurons may contribute to evolutionarily conserved regulatory mechanisms. Future studies will need to investigate the putative roles of KP_LS neurons in the estrogen-dependent control of GnRH neurons and/or various hypothalamic/limbic functions.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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A Singular Theory of Sensorimotor Coordination: On Targeted Motions in Space

Gravity has long been purported to serve a unique role in sensorimotor coordination, but the specific mechanisms underlying gravity-based visuomotor realignment remain elusive. In this study, astronauts (nine males, two females) performed targeted hand movements with eyes open or closed, both on the ground and in weightlessness. Measurements revealed systematic drift in hand-path orientation seen only when eyes were closed and only in very specific conditions with respect to gravity. In weightlessness, drift in path orientation was observed in two postures (seated, supine) for two different movement axes (longitudinal, sagittal); on Earth, such drift was only observed during longitudinal (horizontal) movements performed in the supine posture. In addition to providing clear evidence that gravitational cues play a fundamental role in sensorimotor coordination, these unique observations lead us to propose an "inverted pendulum" hypothesis to explain the saliency of the gravity vector for eye–hand coordination—and why eye–hand coordination is altered during body tilt or in weightlessness.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Characterizing Brain-Cardiovascular Aging Using Multiorgan Imaging and Machine Learning

The structure and function of the brain and cardiovascular system change over the lifespan. In this study, we aim to establish the extent to which age-related changes in these two vital organs are linked. Utilizing normative models and data from the UK Biobank, we estimate biological ages for the brain and heart for 2,904 middle-aged and older healthy adults, including both males and females. Biological ages were based on multiple structural, morphological, and functional features derived from brain and cardiovascular imaging modalities. We find that cardiovascular aging, particularly aging of its functional capacity and physiology, is selectively associated with the aging of specific brain networks, including the salience, default mode, and somatomotor networks as well as the subcortex. Our work provides unique insight into brain–heart relationships and may facilitate an improved understanding of the increased co-occurrence of brain and heart diseases in aging.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Enhanced Somatosensory Inhibition Sharpens Hand Representation and Sensorimotor Skills in Pianists

Dexterous motor skills, like those needed for playing musical instruments and sports, require the somatosensory system to accurately and rapidly process somatosensory information from multiple body parts. This is challenging due to the convergence of afferent inputs from different body parts into a single neuron and the overlapping representation of neighboring body parts in the somatosensory cortices. How do trained individuals, such as pianists and athletes, manage this? Here, a series of five experiments with pianists and nonmusicians (female and male) shows that pianists have enhanced inhibitory function in the somatosensory system, which isolates the processing of somatosensory afferent inputs from each finger. This inhibitory function was assessed using a paired-pulse paradigm of somatosensory evoked potentials in electroencephalography, which measures the suppressive effect of a first stimulus [i.e., conditioning stimulus (CS)] on the response to a subsequent second stimulus. We found that pianists and nonmusicians showed an inhibitory response to the sequential stimuli to the peripheral somatosensory nerve at the wrist when the CS was intense. However, only pianists exhibited an inhibitory response to a weak CS, indicating enhanced inhibitory function in pianists. Additionally, the CS increased the information content segregating individual fingers represented in the cortical activity evoked by passive finger movements and improved the perception of fast multifinger sequential movements, specifically for pianists. Our findings provide the first evidence for experience-dependent plasticity in somatosensory inhibitory function and highlight its role in the expert motor performance of pianists.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Single-Nuclei Sequencing Reveals a Robust Corticospinal Response to Nearby Axotomy But Overall Insensitivity to Spinal Injury

The ability of neurons to sense and respond to damage is crucial for maintaining homeostasis and facilitating nervous system repair. For some cell types, notably dorsal root ganglia and retinal ganglion cells, extensive profiling has uncovered a significant transcriptional response to axon injury, which influences survival and regenerative outcomes. In contrast, the injury responses of most supraspinal cell types, which display limited regeneration after spinal damage, remain mostly unknown. In this study, we used single-nuclei sequencing in adult male and female mice to profile the transcriptional responses of diverse supraspinal cell types to spinal injury. Surprisingly, thoracic spinal injury induced only modest changes in gene expression across all populations, including corticospinal tract (CST) neurons. Additionally, CST neurons exhibited minimal response to cervical injury but showed a much stronger reaction to intracortical axotomy, with upregulation of numerous regeneration and apoptosis-related transcripts shared with injured DRG and RGC neurons. Thus, the muted response of CST neurons to spinal injury is linked to the injury's distal location, rather than intrinsic cellular characteristics. More broadly, these findings indicate that a central challenge for enhancing regeneration after a spinal injury is the limited detection of distant injuries and the subsequent modest baseline neuronal response.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Temporally Dissociable Neural Representations of Pitch Height and Chroma

The extraction and analysis of pitch underpin speech and music recognition, sound segregation, and other auditory tasks. Perceptually, pitch can be represented as a helix composed of two factors: height monotonically aligns with frequency, while chroma cyclically repeats at doubled frequencies. Although the early perceptual and neurophysiological mechanisms for extracting pitch from acoustic signals have been extensively investigated, the equally essential subsequent stages that bridge to high-level auditory cognition remain less well understood. How does the brain represent perceptual attributes of pitch at higher-order processing stages, and how are the neural representations formed over time? We used a machine learning approach to decode time-resolved neural responses of human listeners (10 females and 7 males) measured by magnetoencephalography across different pitches, hypothesizing that different pitches sharing similar neural representations would result in reduced decoding performance. We show that pitch can be decoded from lower-frequency neural responses within auditory-frontal cortical regions. Specifically, linear mixed-effects modeling reveals that height and chroma explain the decoding performance of delta band (0.5–4 Hz) neural activity at distinct latencies: a long-lasting height effect precedes a transient chroma effect, followed by a recurrence of height after chroma, indicating sequential processing stages associated with unique perceptual and neural characteristics. Furthermore, the localization analyses of the decoder demonstrate that height and chroma are associated with overlapping cortical regions, with differences observed in the right orbital and polar frontal cortex. The data provide a perspective motivating new hypotheses on the mechanisms of pitch representation.

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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ss-arrestins Form a Protein Complex with Smo and Src Family Kinases to Drive Shh-Mediated Axon Guidance in Spinal Cord Commissural Neurons

in Journal of Neuroscience on 2025-02-19 17:30:23 UTC.

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Are You Safe or Should I Go? How Perceived Trustworthiness and Probability of a Sexual Transmittable Infection Impact Activation of the Salience Network

Functional imaging studies indicate that both the assessment of a person as untrustworthy and the assumption that a person has a sexually transmitted infection are associated with activation in regions of the salience network. However, studies are missing that combine these aspects and investigate the perceived trustworthiness of individuals previously assessed with high or low probability of a sexually transmitted infection. During fMRI measurements, 25 participants viewed photographs of people preclassified as having high or low HIV probability and judged their trustworthiness. In a postrating, stimuli were rated for trustworthiness, attractiveness, and HIV probability. Persons preclassified as HIV– in contrast to those preclassified as HIV+ were rated more trustworthy and with lower HIV probability. Activation in medial orbitofrontal cortex was higher for those rated and preclassified as HIV– than HIV+. Based on the individual ratings, but not the preclassification, there was significantly higher activation in the insula, amygdala, anterior cingulate cortex, and nucleus accumbens in response to untrustworthy than to trustworthy faces. Activation of the salience network occurred when a person was judged as untrustworthy, but not according to a preclassification. Activation in the medial orbitofrontal cortex, a structure associated with reward, was enhanced when a person was perceived as trustworthy and also when a person was preclassified with low HIV probability. Our findings suggest that trustworthiness and HIV– perception have consistency across samples, while the perception of risk and associated activation of the salience network has restricted cross-sample consistency.

in eNeuro on 2025-02-19 17:30:23 UTC.

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Improving Tracking of Selective Attention in Hearing Aid Users: The Role of Noise Reduction and Nonlinearity Compensation

Hearing impairment (HI) disrupts social interaction by hindering the ability to follow conversations in noisy environments. While hearing aids (HAs) with noise reduction (NR) partially address this, the "cocktail-party problem" persists, where individuals struggle to attend to specific voices amidst background noise. This study investigated how NR and an advanced signal processing method for compensating for nonlinearities in Electroencephalography (EEG) signals can improve neural speech processing in HI listeners. Participants wore HAs with NR, either activated or deactivated, while focusing on target speech amidst competing masker speech and background noise. Analysis focused on temporal response functions to assess neural tracking of relevant target and masker speech. Results revealed enhanced neural responses (N1 and P2) to target speech, particularly in frontal and central scalp regions, when NR was activated. Additionally, a novel method compensated for nonlinearities in EEG data, leading to improved signal-to-noise ratio (SNR) and potentially revealing more precise neural tracking of relevant speech. This effect was most prominent in the left-frontal scalp region. Importantly, NR activation significantly improved the effectiveness of this method, leading to stronger responses and reduced variance in EEG data and potentially revealing more precise neural tracking of relevant speech. This study provides valuable insights into the neural mechanisms underlying NR benefits and introduces a promising EEG analysis approach sensitive to NR effects, paving the way for potential improvements in HAs.

in eNeuro on 2025-02-19 17:30:23 UTC.

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A Simple, Low-Cost Implant for Reliable Diaphragm EMG Recordings in Awake, Behaving Rats

Breathing is a complex neuromuscular process vital to sustain life. In preclinical animal models, the study of respiratory motor control is primarily accomplished through neurophysiologic recordings and functional measurements of respiratory output. Neurophysiologic recordings that target neural or muscular output via direct nerve recordings or respiratory muscle electromyography (EMG) are commonly collected during anesthetized conditions. While offering tight control of experimental preparations, the use of anesthesia results in respiratory depression, may impact cardiovascular control, eliminates the potential to record volitional nonventilatory behaviors, and can limit translation. Since the diaphragm is a unique muscle which is rhythmically active and difficult to access, placing diaphragm EMGs to collect chronic recordings in awake animals is technically challenging. Here, we describe methods for fabricating and implanting indwelling diaphragm EMG electrodes to enable recordings from awake rodents for longitudinal studies. These electrodes are relatively easy and quick to produce (~1 h), are affordable, and provide high-quality and reproducible diaphragm signals using a tethered system that allows animals to ad libitum behave. This system is also designed to work in conjunction with whole-body plethysmography to facilitate simultaneous recordings of diaphragm EMG and ventilation. We include detailed instructions and considerations for electrode fabrication and surgical implantation. We also provide a brief discussion on data acquisition, material considerations for implant fabrication, and the physiological implications of the diaphragm EMG signal.

in eNeuro on 2025-02-19 17:30:23 UTC.

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Author-Centered Approach to Scientific Publishing

in Journal of Neuroscience on 2025-02-19 17:30:22 UTC.

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Disinhibition across Secondary Motor Cortical Regions during Motor Sequence Learning: A TMS-EEG Study

Secondary motor cortical regions, such as the supplementary motor area (SMA), are involved in planning and learning motor sequences; however, the neurophysiological mechanisms across these secondary cortical networks remain poorly understood. In the primary motor cortex, changes in excitatory and inhibitory neurotransmission (E:I balance) accompany motor sequence learning. In particular, there is an early reduction in inhibition (i.e., disinhibition). Here, we investigated whether disinhibition occurs across secondary motor cortical regions during motor sequence learning using combined transcranial magnetic stimulation (TMS) and electroencephalography (EEG). Twenty-nine healthy adults (14 female) practiced a sequential motor task with TMS applied to the SMA during sequence planning. TMS-evoked potentials (TEPs) were measured with EEG before, during, and after practice. The N45 TEP peak was our primary measure of disinhibition, while we analyzed the slope of aperiodic EEG activity as an additional E:I balance measure. We observed a reduction in N45 amplitudes across an electrode cluster encompassing the SMA and nearby cortical regions as participants began learning new motor sequences, compared with a baseline rest phase (p < 0.01). Smaller N45 amplitudes during early learning were associated with improvements in reaction times across learning (p < 0.05). Intriguingly, aperiodic exponents increased as learning progressed and were associated with greater improvements in skill (p < 0.05). Overall, our results show that inhibition is modulated across SMA and secondary motor cortex during the planning phase of motor sequence learning and thus provide novel insight on the neurophysiological mechanisms within higher-order motor cortex that accompany new sequence learning.

in Journal of Neuroscience on 2025-02-19 17:30:22 UTC.

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Optimal Estimation of Local Motion-in-Depth with Naturalistic Stimuli

Estimating the motion of objects in depth is important for behavior and is strongly supported by binocular visual cues. To understand both how the brain should estimate motion in depth and how natural constraints shape and limit performance in two local 3D motion tasks, we develop image-computable ideal observers from a large number of binocular video clips created from a dataset of natural images. The observers spatiotemporally filter the videos and nonlinearly decode 3D motion from the filter responses. The optimal filters and decoder are dictated by the task-relevant image statistics and are specific to each task. Multiple findings emerge. First, two distinct filter subpopulations are spontaneously learned for each task. For 3D speed estimation, filters emerge for processing either changing disparities over time or interocular velocity differences, cues that are used by humans. For 3D direction estimation, filters emerge for discriminating either left–right or toward–away motion. Second, the filter responses, conditioned on the latent variable, are well-described as jointly Gaussian, and the covariance of the filter responses carries the information about the task-relevant latent variable. Quadratic combination is thus necessary for optimal decoding, which can be implemented by biologically plausible neural computations. Finally, the ideal observer yields nonobvious—and in some cases counterintuitive—patterns of performance like those exhibited by humans. Important characteristics of human 3D motion processing and estimation may therefore result from optimal information processing in the early visual system.

in Journal of Neuroscience on 2025-02-19 17:30:22 UTC.

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Disruption of Extracellular Matrix and Perineuronal Nets Modulates Extracellular Space Volume and Geometry

Extracellular matrix (ECM) is a network of macromolecules which has two forms—perineuronal nets (PNNs) and a diffuse ECM (dECM)—both influence brain development, synapse formation, neuroplasticity, CNS injury and progression of neurodegenerative diseases. ECM remodeling can influence extrasynaptic transmission, mediated by diffusion of neuroactive substances in the extracellular space (ECS). In this study we analyzed how disrupted PNNs and dECM influence brain diffusibility. Two months after oral treatment of rats with 4-methylumbelliferone (4-MU), an inhibitor of hyaluronan (HA) synthesis, we found downregulated staining for PNNs, HA, chondroitin sulfate proteoglycans, and glial fibrillary acidic protein. These changes were enhanced after 4 and 6 months and were reversible after a normal diet. Morphometric analysis further indicated atrophy of astrocytes. Using real-time iontophoretic method dysregulation of ECM resulted in increased ECS volume fraction α in the somatosensory cortex by 35%, from α = 0.20 in control rats to α = 0.27 after the 4-MU diet. Diffusion-weighted magnetic resonance imaging revealed a decrease of mean diffusivity and fractional anisotropy (FA) in the cortex, hippocampus, thalamus, pallidum, and spinal cord. This study shows the increase in ECS volume, a loss of FA, and changes in astrocytes due to modulation of PNNs and dECM that could affect extrasynaptic transmission, cell-to-cell communication, and neural plasticity.

in Journal of Neuroscience on 2025-02-19 17:30:22 UTC.

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The Value of Applying Big Data Analytics in Health Supply Chain Management [version 4; peer review: 2 approved]

This study aims to evaluate the impact of big data analytics (BDA) on the performance of healthcare supply chain management (HCSCMP) by examining both overall efficiency improvements and identifying critical success factors for effective implementation. Through a systematic literature review, the research investigates how BDA enhances real-time decision-making within healthcare supply chains (HCSCs) and identifies the key enablers required for successful BDA adoption. A comprehensive search strategy was employed to analyze 65 papers, resulting in the inclusion of 39 studies published between 2016 and 2023. The review revealed a preference for literature reviews and questionnaires as the primary research methods. The findings indicate that BDA significantly improves HCSCs’ efficiency, particularly in real-time decision-making and operational management. However, successful BDA implementation depends on addressing critical enablers and overcoming associated challenges.

in F1000Research on 2025-02-19 14:43:28 UTC.

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Delirium management and current practice among Intensive Care Units Doctors, Khartoum [version 4; peer review: 2 approved, 1 approved with reservations]

Delirium is a brain dysfunction characterized by attention and cognitive disturbances in a fluctuating manner. The international guidelines recommend daily screening for delirium. The Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) and Intensive Care Delirium Screening Checklist (ICDSC) are the most commonly used methods for assessing delirium. This study aimed to identify barriers and gaps in knowledge and practice. This was a hospital-based Cross-Sectional study. Stratified random sampling was used in this study. 72 ICU doctors were randomly selected. Statistical analyses were performed using IBM SPSS version 23. Descriptive data were presented, and the chi-squared test was used to determine the associations among variables. Statistical significance was set at p < 0.05. More than 70% of the doctors were ≤ 30 years of age and female. A total of 69.4% of the participants had < 1year of experience. In total, 94.4% of the participants worked in medical ICUs. Less than 20% of the doctors used delirium assessment tools, with a statistically significant difference based on experience (p=0.012). Delirium was not regularly assessed in 13.9% of the patients. Non-pharmacological management was applied by 76.4% of doctors, and communication with patients was the most frequent (75%). Haloperidol was the most commonly used drug (83.3%). A total of 40.3% of doctors did not stop delirium medication on ICU discharge. A regular delirium assessment was performed. However, the use of validated assessment tools is uncommon. Nonpharmacological management of delirium is important and is mostly performed. Our doctors prescribed antipsychotics for the treatment of both forms of delirium, and almost half of them did not stop the medications on ICU discharge. Medication reconciliation and contact with the next in-charge of the patients are important.

in F1000Research on 2025-02-19 14:24:52 UTC.

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Compression-enabled interpretability of voxelwise encoding models

by Fatemeh Kamali, Amir Abolfazl Suratgar, Mohammadbagher Menhaj, Reza Abbasi-Asl

Voxelwise encoding models based on convolutional neural networks (CNNs) have emerged as state-of-the-art predictive models of brain activity evoked by natural movies. Despite their superior predictive performance, the huge number of parameters in CNN-based models have made them difficult to interpret. Here, we investigate whether model compression can build more interpretable and more stable CNN-based voxelwise models while maintaining accuracy. We used multiple compression techniques to prune less important CNN filters and connections, a receptive field compression method to select receptive fields with optimal center and size, and principal component analysis to reduce dimensionality. We demonstrate that the model compression improves the accuracy of identifying visual stimuli in a hold-out test set. Additionally, compressed models offer a more stable interpretation of voxelwise pattern selectivity than uncompressed models. Finally, the receptive field-compressed models reveal that the optimal model-based population receptive fields become larger and more centralized along the ventral visual pathway. Overall, our findings support using model compression to build more interpretable voxelwise models.

in PLoS Computational Biology on 2025-02-19 14:00:00 UTC.

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Bayesian classification of OXPHOS deficient skeletal myofibres

by Jordan Childs, Tiago Bernardino Gomes, Amy E Vincent, Andrew Golightly, Conor Lawless

Mitochondria are organelles in most human cells which release the energy required for cells to function. Oxidative phosphorylation (OXPHOS) is a key biochemical process within mitochondria required for energy production and requires a range of proteins and protein complexes. Mitochondria contain multiple copies of their own genome (mtDNA), which codes for some of the proteins and ribonucleic acids required for mitochondrial function and assembly. Pathology arises from genetic defects in mtDNA and can reduce cellular abundance of OXPHOS proteins, affecting mitochondrial function. Due to the continuous turn-over of mtDNA, pathology is random and neighbouring cells can possess different OXPHOS protein abundance. Estimating the proportion of cells where OXPHOS protein abundance is too low to maintain normal function is critical to understanding disease severity and predicting disease progression. Currently, one method to classify single cells as being OXPHOS deficient is prevalent in the literature. The method compares a patient’s OXPHOS protein abundance to that of a small number of healthy control subjects. If the patient’s cell displays an abundance which differs from the abundance of the controls then it is deemed deficient. However, due to the natural variation between subjects and the low number of control subjects typically available, this method is inflexible and often results in a large proportion of patient cells being misclassified. These misclassifications have significant consequences for the clinical interpretation of these data. We propose a single-cell classification method using a Bayesian hierarchical mixture model, which allows for inter-subject OXPHOS protein abundance variation. The model accurately classifies an example dataset of OXPHOS protein abundances in skeletal muscle fibres (myofibres). When comparing the proposed and existing model classifications to manual classifications performed by experts, the proposed model results in estimates of the proportion of deficient myofibres that are consistent with expert manual classifications.

in PLoS Computational Biology on 2025-02-19 14:00:00 UTC.

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Quantifying infectious disease epidemic risks: A practical approach for seasonal pathogens

by Alexander R Kaye, Giorgio Guzzetta, Michael J Tildesley, Robin N Thompson

For many infectious diseases, the risk of outbreaks varies seasonally. If a pathogen is usually absent from a host population, a key public health policy question is whether the pathogen’s arrival will initiate local transmission, which depends on the season in which arrival occurs. This question can be addressed by estimating the “probability of a major outbreak” (the probability that introduced cases will initiate sustained local transmission). A standard approach for inferring this probability exists for seasonal pathogens (involving calculating the Case Epidemic Risk; CER) based on the mathematical theory of branching processes. Under that theory, the probability of pathogen extinction is estimated, neglecting depletion of susceptible individuals. The CER is then one minus the extinction probability. However, as we show, if transmission cannot occur for long periods of the year (e.g., over winter or over summer), the pathogen will most likely go extinct, leading to a CER that is equal (or very close) to zero even if seasonal outbreaks can occur. This renders the CER uninformative in those scenarios. We therefore devise an alternative approach for inferring outbreak risks for seasonal pathogens (involving calculating the Threshold Epidemic Risk; TER). Estimation of the TER involves calculating the probability that introduced cases will initiate a local outbreak in which a threshold number of cumulative infections is exceeded before outbreak extinction. For simple seasonal epidemic models, such as the stochastic Susceptible-Infectious-Removed model, the TER can be calculated numerically (without model simulations). For more complex models, such as stochastic host-vector models, the TER can be estimated using model simulations. We demonstrate the application of our approach by considering chikungunya virus in northern Italy as a case study. In that context, transmission is most likely in summer, when environmental conditions promote vector abundance. We show that the TER provides more useful assessments of outbreak risks than the CER, enabling practically relevant risk quantification for seasonal pathogens.

in PLoS Computational Biology on 2025-02-19 14:00:00 UTC.

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Neural development goes retro: Gags as essential modulators of synapse formation

by Yung-Heng Chang, Josh Dubnau

Neurodevelopment requires dynamic control of synapse number. A new study in PLOS Biology reveals that the gag protein of Copia, an active retrotransposon, forms virus-like capsids that transfer its own RNA across the Drosophila neuromuscular junction. Here, Copia acts antagonistically with Arc, another retrotransposon gag protein, to regulate synapse formation. Neurodevelopment requires dynamic control of synapse number. This Primer highlights a new study in PLOS Biology which reveals that the gag protein of Copia, an active retrotransposon, forms virus-like capsids that transfer its own RNA across the Drosophila neuromuscular junction, to regulate synapse formation.

in PLoS Biology on 2025-02-19 14:00:00 UTC.

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The mind–machine connection: adaptive information processing and new technologies promoting mental health in older adults

The Neuroscientist, Ahead of Print.
The human brain demonstrates an exceptional adaptability, which encompasses the ability to regulate emotions, exhibit cognitive flexibility, and generate behavioral responses, all supported by neuroplasticity. Brain–computer interfaces (BCIs) employ adaptive algorithms and machine learning techniques to adapt to variations in the user’s brain activity, allowing for customized interactions with external devices. Older adults may experience cognitive decline, which could affect the ability to learn and adapt to new technologies such as BCIs, but both (human brain and BCI) demonstrate adaptability in their responses. The human brain is skilled at quickly switching between tasks and regulating emotions, while BCIs can modify signal-processing algorithms to accommodate changes in brain activity. Furthermore, the human brain and BCI participate in knowledge acquisition; the first one strengthens cognitive abilities through exposure to new experiences, and the second one improves performance through ongoing adjustment and improvement. Current research seeks to incorporate emotional states into BCI systems to improve the user experience, despite the exceptional emotional regulation abilities of the human brain. The implementation of BCIs for older adults could be more effective, inclusive, and beneficial in improving their quality of life. This review aims to improve the understanding of brain–machine interfaces and their implications for mental health in older adults.

in The Neuroscientist on 2025-02-19 12:57:56 UTC.

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Blockchain-enhanced electoral integrity: a robust model for secure digital voting systems in Oman [version 1; peer review: awaiting peer review]

Background Ensuring the security and trustworthiness of a digitized and automated electoral process remains a significant challenge in democratic systems. As digital voting systems are increasingly being investigated around the world, ensuring the integrity of the process using robust security measures is of great importance. This paper presents a simplified model to enhance electoral integrity by leveraging Blockchain technology in the context of Oman’s digital voting system. The model uses Blockchain technology to create a secure and trustworthy voting environment, addressing key vulnerabilities in digital electoral systems. Methods The research utilized a quantitative approach, employing an experimental design methodology using open-source software to simulate voting systems. Synthetic population data is utilized for operating these systems, while advanced biometric authentication technologies are used to verify voter identities. Blockchain technology is leveraged to ensure secure vote recording, with smart contracts used to authenticate voters and securely record votes. Additionally, synchronous transactions are executed for both voter registration and voting processes, enhancing the overall security and efficiency of the system. Results The experimental results shows that Blockchain enhances electoral integrity and security in Oman voting system, improves transparency and reliability in elections. The performance evaluation of the model focuses on efficiency, reliability, and scalability metrics. Asynchronous transactions are utilized to improve processing time for voter registration and voting. Election administrators can manage, monitor, and certify election results, while Ethereum nodes ensure decentralized verification and transparency in the voting process. Conclusion This research offers insights for policymakers to consider Blockchain for electoral reforms, addressing issues like data integrity, fraud prevention, and transparency to boost voter trust. A strong regulatory framework and public awareness are crucial for successful implementation. Pilot projects are needed to assess Blockchain’s practical impact. Oman could lead global innovation in electoral technology, though infrastructure and public resistance challenges must be managed.

in F1000Research on 2025-02-19 12:13:28 UTC.

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Case Report: Emergency endovascular management of a ruptured giant abdominal aortic aneurysm with severely angulated and conical shaped neck using novel multiple stiff wire technique [version 2; peer review: 1 approved]

Background Ruptured abdominal aortic aneurysm (rAAA) is commonly fatal, with an overall mortality rate of nearly 90%, and the risk of subsequent rupture remains high, especially in large aneurysm diameters or progressive disease. Unfavorable neck anatomy in EVAR is linked to early graft failure and long-term complications. Recently, a novel multiple stiff wire (MSW) technique has been developed to overcome the challenges of hostile neck anatomy without introducing additional devices and procedural complexity. It has also been feasible in a series of elective cases. In this case, we report the first-ever utilization of the MSW technique in an emergency case of an acute contained rAAA with a conical-shaped, severely angulated neck who underwent Endovascular Aortic Repair (EVAR). Case presentation A 61-year-old man came with intermittent sharp stomach pain radiating to his back since three weeks ago. Physical examination showed elevated blood pressure and anemic conjunctiva. Laboratory examinations showed anemia, leukocytosis, elevated D-dimer level, high creatinine level, and low eGFR. CT-Scan Angiography (CTA) revealed severely hostile anatomy, a conical-shaped abdominal aorta aneurysm with a length of 13.2 cm and a maximum diameter of 9.3 cm with angulation of 90.1°. The patient was diagnosed with Ruptured AAA with a conical-shaped, severely angulated neck. Endovascular Aortic Repair (EVAR) management with MSW technique was planned for him. After four days, The patient was discharged in a clinically stable condition with optimal medical treatment and education. Conclusion The endovascular approach could be performed in emergency settings and has been proven to reduce length of stay, mortality, and morbidity rates. In this case, the endovascular approach with the MSW technique showed promising results for the patient.

in F1000Research on 2025-02-19 11:52:55 UTC.

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Choice anticipation as gated accumulation of sensory predictions

Journal of Neurophysiology, Ahead of Print.

in Journal of Neurophysiology on 2025-02-19 11:30:20 UTC.

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The Relationship between Average Savings Deposit Rates and Average Commercial Bank Lending Rates in Ghana [version 1; peer review: awaiting peer review]

Background This study explores the relationship between average savings deposit rates and average commercial banks’ lending rates in Ghana from 2000 to 2020. Appreciating the connection is essential for developing successful policies that promote financial intermediation and economic growth. Methods A quantitative research approach was adopted by utilising the ARIMA model to forecast trends in average savings deposit rates and analyse their future behaviour. The study controlled for macroeconomic factors such as inflation (INF) and inter-bank weighted average (IWA) to assess their impact on both savings and lending rates. Results The findings reveal a significant positive correlation between average savings deposit rates and average lending rates with a correlation coefficient of 0.75 (p < 0.01). Inflation negatively impacts lending rates as evidenced by a coefficient of -0.40 (p < 0.05). Additionally, IWA exerts a minimal but favourable influence on average savings deposit rates. Conclusions The results underscore the need for effective policies aimed at stabilising savings deposit rates and fostering competition within the banking sector. Such measures are essential to enhance financial intermediation and promote sustainable economic growth in Ghana.

in F1000Research on 2025-02-19 11:20:57 UTC.

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