Planet Neuroscience

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Comparison of the antimicrobial reduction effect of photodynamic inactivation with the addition of chlorophyll and curcumin photosensitizer in Aggregatibacter actinomycetemcomitans and Enterococcus faecalis [version 4; peer review: 3 approved with reserva

Background Aggregatibacter actinomycetemcomitans and Enterococcus faecalis are pathogenic bacteria of the oral cavity that cause various diseases such as periodontitis and endodontics. These bacteria are easily resistant to antibiotics. Photodynamic inactivation (PDI) is a method of inactivating microorganisms that utilizes light to activate a photosensitizer agent (PS) that produces reactive oxygen species causing cell lysis. Methods This study used the PDI method with a 405 nm diode laser at various energy density with the addition PS curcumin or chlorophyll Alfalfa, as much as 1.6 mg/ml on A. actinomycetemcomitans and E. faecalis bacteria. Results The study on E. faecalis bacteria showed that the energy density diode laser irradiation of 1.59 J/cm² gave the percentage of E. faecalis bacteria death 36.7% without PS, 69.30% with the addition of chlorophyll Medicago sativa L and 89.42% with the addition of curcumin. Meanwhile, the bacteria A. actinomycetemcomitans showed that the energy density diode laser irradiation of 1.59 J/cm² gave the percentage of bacterial death 35.81% without PS, 64.39% with the addition of chlorophyll Medicago sativa L and 89.82% with the addition of curcumin. PS was critical to the success of the PDI. Conclusions The addition of PS curcumin increased the effectiveness of reducing bacteria E. faecalis and A. actinomycetemcomitans compared to chlorophyll Medicago sativa L.

in F1000Research on 2025-04-04 08:09:26 UTC.

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Nonlinear sound-sheet microscopy: Imaging opaque organs at the capillary and cellular scale

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-04 07:00:00 UTC.

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Exogenous RNA surveillance by proton-sensing TRIM25

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-04 07:00:00 UTC.

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Homogeneous-heterogeneous bifunctionality in Pd-catalyzed vinyl acetate synthesis

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-04 07:00:00 UTC.

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Osteoarthritis treatment via the GLP-1–mediated gut-joint axis targets intestinal FXR signaling

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-04 07:00:00 UTC.

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A geological timescale for bacterial evolution and oxygen adaptation

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-04 07:00:00 UTC.

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Human high-order thalamic nuclei gate conscious perception through the thalamofrontal loop

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-04 07:00:00 UTC.

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Integrating multiple evidence streams to understand insect biodiversity change

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-04 07:00:00 UTC.

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On the threshold of excitable systems: An energy-based perspective

arXiv:2504.02171v1 Announce Type: cross Abstract: A fundamental characteristic of excitable systems is their ability to exhibit distinct subthreshold and suprathreshold behaviors. Precisely quantifying this distinction requires a proper definition of the threshold, which has remained elusive in neurodynamics. In this paper, we introduce a novel, energy-based threshold definition for excitable circuits grounded in dissipativity theory, specifically using the classical concept of required supply. According to our definition, the threshold corresponds to a local maximum of the required supply, clearly separating subthreshold passive responses from suprathreshold regenerative spikes. We illustrate and validate the proposed definition through analytical and numerical studies of three canonical systems: a simple RC circuit, the FitzHugh--Nagumo model, and the biophysically detailed Hodgkin--Huxley model.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-04 04:00:00 UTC.

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Orientation selectivity properties for integrated affine quasi quadrature models of complex cells

arXiv:2503.21611v4 Announce Type: replace Abstract: This paper presents an analysis of the orientation selectivity properties of idealized models of complex cells in terms of affine quasi quadrature measures, which combine the responses of idealized models of simple cells in terms of affine Gaussian derivatives by (i) pointwise squaring, (ii) summation of responses for different orders of spatial derivation and (iii) spatial integration. Specifically, this paper explores the consequences of assuming that the family of spatial receptive fields should be covariant under spatial affine transformations, thereby implying that the receptive fields ought to span a variability over the degree of elongation. We investigate the theoretical properties of three main ways of defining idealized models of complex cells and compare the predictions from these models to neurophysiologically obtained receptive field histograms over the resultant of biological orientation selectivity curves. It is shown that the extended modelling mechanism lead to more uniform behaviour and a wider span over the values of the resultat that are covered, compared to earlier presented idealized models of complex cells without spatial integration. More generally, we propose (i) to include a variability over the degree of elongation of the receptive fields in functional models of complex cells, and that (ii) the presented methodology with comparisons to biological orientation selectivity curves and orientation selectivity histograms could be used as a new tool to evaluate other computational models of complex cells in relation to biological measurements.

in arXiv: Quantitative Biology: Neurons and Cognition on 2025-04-04 04:00:00 UTC.

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LLM-Guided Evolution: An Autonomous Model Optimization for Object Detection

arXiv:2504.02280v1 Announce Type: new Abstract: In machine learning, Neural Architecture Search (NAS) requires domain knowledge of model design and a large amount of trial-and-error to achieve promising performance. Meanwhile, evolutionary algorithms have traditionally relied on fixed rules and pre-defined building blocks. The Large Language Model (LLM)-Guided Evolution (GE) framework transformed this approach by incorporating LLMs to directly modify model source code for image classification algorithms on CIFAR data and intelligently guide mutations and crossovers. A key element of LLM-GE is the "Evolution of Thought" (EoT) technique, which establishes feedback loops, allowing LLMs to refine their decisions iteratively based on how previous operations performed. In this study, we perform NAS for object detection by improving LLM-GE to modify the architecture of You Only Look Once (YOLO) models to enhance performance on the KITTI dataset. Our approach intelligently adjusts the design and settings of YOLO to find the optimal algorithms against objective such as detection accuracy and speed. We show that LLM-GE produced variants with significant performance improvements, such as an increase in Mean Average Precision from 92.5% to 94.5%. This result highlights the flexibility and effectiveness of LLM-GE on real-world challenges, offering a novel paradigm for automated machine learning that combines LLM-driven reasoning with evolutionary strategies.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-04 04:00:00 UTC.

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Learning and Improving Backgammon Strategy

arXiv:2504.02221v1 Announce Type: cross Abstract: A novel approach to learning is presented, combining features of on-line and off-line methods to achieve considerable performance in the task of learning a backgammon value function in a process that exploits the processing power of parallel supercomputers. The off-line methods comprise a set of techniques for parallelizing neural network training and $TD(\lambda)$ reinforcement learning; here Monte-Carlo ``Rollouts'' are introduced as a massively parallel on-line policy improvement technique which applies resources to the decision points encountered during the search of the game tree to further augment the learned value function estimate. A level of play roughly as good as, or possibly better than, the current champion human and computer backgammon players has been achieved in a short period of learning.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-04 04:00:00 UTC.

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SymDQN: Symbolic Knowledge and Reasoning in Neural Network-based Reinforcement Learning

arXiv:2504.02654v1 Announce Type: cross Abstract: We propose a learning architecture that allows symbolic control and guidance in reinforcement learning with deep neural networks. We introduce SymDQN, a novel modular approach that augments the existing Dueling Deep Q-Networks (DuelDQN) architecture with modules based on the neuro-symbolic framework of Logic Tensor Networks (LTNs). The modules guide action policy learning and allow reinforcement learning agents to display behaviour consistent with reasoning about the environment. Our experiment is an ablation study performed on the modules. It is conducted in a reinforcement learning environment of a 5x5 grid navigated by an agent that encounters various shapes, each associated with a given reward. The underlying DuelDQN attempts to learn the optimal behaviour of the agent in this environment, while the modules facilitate shape recognition and reward prediction. We show that our architecture significantly improves learning, both in terms of performance and the precision of the agent. The modularity of SymDQN allows reflecting on the intricacies and complexities of combining neural and symbolic approaches in reinforcement learning.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-04 04:00:00 UTC.

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Towards Green AI-Native Networks: Evaluation of Neural Circuit Policy for Estimating Energy Consumption of Base Stations

arXiv:2504.02781v1 Announce Type: cross Abstract: Optimization of radio hardware and AI-based network management software yield significant energy savings in radio access networks. The execution of underlying Machine Learning (ML) models, which enable energy savings through recommended actions, may require additional compute and energy, highlighting the opportunity to explore and adopt accurate and energy-efficient ML technologies. This work evaluates the novel use of sparsely structured Neural Circuit Policies (NCPs) in a use case to estimate the energy consumption of base stations. Sparsity in ML models yields reduced memory, computation and energy demand, hence facilitating a low-cost and scalable solution. We also evaluate the generalization capability of NCPs in comparison to traditional and widely used ML models such as Long Short Term Memory (LSTM), via quantifying their sensitivity to varying model hyper-parameters (HPs). NCPs demonstrated a clear reduction in computational overhead and energy consumption. Moreover, results indicated that the NCPs are robust to varying HPs such as number of epochs and neurons in each layer, making them a suitable option to ease model management and to reduce energy consumption in Machine Learning Operations (MLOps) in telecommunications.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-04 04:00:00 UTC.

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Evolving Generalizable Parallel Algorithm Portfolios via Domain-Agnostic Instance Generation

arXiv:2501.02906v3 Announce Type: replace Abstract: Generalization is the core objective when training optimizers from data. However, limited training instances often constrain the generalization capability of the trained optimizers. Co-evolutionary approaches address this challenge by simultaneously evolving a parallel algorithm portfolio (PAP) and an instance population to eventually obtain PAPs with good generalization. Yet, when applied to a specific problem class, these approaches have a major limitation. They require practitioners to provide instance generators specially tailored to the problem class, which is often non-trivial to design. This work proposes a general-purpose, off-the-shelf PAP construction approach, named domain-agnostic co-evolution of parameterized search (DACE), for binary optimization problems where decision variables take values of 0 or 1. The key novelty of DACE lies in its neural network-based domain-agnostic instance representation and generation mechanism that eliminates the need for domain-specific instance generators. The strong generality of DACE is validated across three real-world binary optimization problems: the complementary influence maximization problem (CIMP), the compiler arguments optimization problem (CAOP), and the contamination control problem (CCP). Given only a small set of training instances from these problem classes, DACE, without requiring domain knowledge, constructs PAPs with even better generalization performance than existing approaches on all three classes, despite their use of domain-specific instance generators.

in arXiv: Computer Science: Neural and Evolutionary Computing on 2025-04-04 04:00:00 UTC.

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Nanopore sensing of protein and peptide conformation for point-of-care applications

Nature Communications, Published online: 04 April 2025; doi:10.1038/s41467-025-58509-8

Nanopore electrical detection has shown potential in sensing subtle protein and peptide conformation changes, and its sensitivity makes it promising for point-of-care applications. In this Review, the authors discuss the capability of nanopore sensing for detecting and quantifying conformational modifications and enantiomers in biomarker proteins and peptides, as well as the practicalities and challenges for this approach to be used for clinical and point-of-care diagnosis.

in Nature Communications on 2025-04-04 00:00:00 UTC.

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Optimization and scaling-up of porous solid electrolyte electrochemical reactors for hydrogen peroxide electrosynthesis

Nature Communications, Published online: 04 April 2025; doi:10.1038/s41467-025-58385-2

The porous solid electrolyte (PSE) reactor for hydrogen peroxide (H2O2) electrosynthesis has gained global interest but is challenging to scale up. Here, the authors optimize the reactor design and develop a stacked PSE reactor with a total electrode area of 1200 cm2 for efficient H2O2 production.

in Nature Communications on 2025-04-04 00:00:00 UTC.

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A blood- and brain-based EWAS of smoking

Nature Communications, Published online: 04 April 2025; doi:10.1038/s41467-025-58357-6

Smoking remains a leading cause of preventable death and disease. Here, the authors explore the link between smoking and DNA methylation using arrays and next generation sequencing, and develop mCigarette, an epigenetic biomarker of smoking.

in Nature Communications on 2025-04-04 00:00:00 UTC.

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Continuous sensorimotor transformation enhances robustness of neural dynamics to perturbation in macaque motor cortex

Nature Communications, Published online: 04 April 2025; doi:10.1038/s41467-025-58421-1

How the motor cortex adapts to the changing environments remains unclear. Here, the authors show that continuous sensorimotor transformations enhance the motor cortex’s resilience to intracortical microstimulation perturbations during preparation for manual interception.

in Nature Communications on 2025-04-04 00:00:00 UTC.

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Purkinje cell branch morphology determines effect of inhibition and SK2 modulation on somatic pauses

Characterized by a highly complex branching of their dendrites, Purkinje cells (PCs) have a unique architecture that enables them to receive impressive amounts of sensorimotor information through their parallel fiber (PF) input. They are tasked to encode this information with high accuracy. In this work, we discuss the mechanisms through which PCs encode this information, and we show how they multiplex between linear-rate and burst-pause coding. Particularly, somatic pauses are of utmost importance due to their involvement in learning. Using a novel heterogeneous model, we show that all branches can achieve a burst-pause response in response to branch-specific PF clustered input. We quantify the somatic pauses obtained and propose various mechanisms to alter the pause duration. Firstly, our results show that increasing local SK2 channel conductance density systematically increases pause duration. In four branches somatic pauses occurred only when SK2 conductance was increased. Interestingly, when adding feed-forward inhibition via stellate cells, our results show either an increase or a decrease in somatic pauses, highlighting the important role of branch morphology and branch location within the PC.

in bioRxiv: Neuroscience on 2025-04-04 00:00:00 UTC.

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Novel multi-transmitter calyx-like giant synapse revealed in the extended amygdala

The calyx of Held, a giant excitatory cup-like axo-somatic synapse, has been historically described exclusively in the auditory brainstem. Here, using PACAP immunohistochemistry combined with confocal and tomographic electron microscopy, we report the discovery of a morphologically similar calyx-like synapse in the extended amygdala of rodents, exhibiting unique neurochemical features. This previously unrecognized structure forms massive axo-somatic terminals with mixed glutamatergic and cholinergic identities, co-expressing VGluT1, VGluT2, VAChT, and the neuropeptides PACAP, CGRP, and neurotensin, along with calretinin in the presynaptic compartment. The postsynaptic targets are a distinct subset of PKC{delta}-expressing neurons that co-express the synaptic adhesion molecule GluD1. Strikingly, GluD1 immunolabeling is concentrated specifically at axo-somatic contact sites apposed to VAChT+ calyceal terminals, but absent at PSD of conventional type I synapse, suggesting a specialized molecular architecture for calyceal synapse. Our findings reveal a previously unknown calyx-like synapse in the forebrain, exhibiting a unique convergence of fast and modulatory transmission with implications for transmission fidelity within emotional-viscerosensory circuits.

in bioRxiv: Neuroscience on 2025-04-04 00:00:00 UTC.

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Accuracy of Systemic Inflammatory Indices in identifying Neonatal Sepsis in preterms in a tertiary care hospital in Mangalore [version 1; peer review: awaiting peer review]

Background Both term and preterm neonates can develop sepsis, a potentially lethal and life-threatening condition, during the first 28 days of life. Neonatal sepsis accounts for 8% of all neonatal fatalities. This study aimed to evaluate the predictive power of lab-based diagnostic indices for neonatal sepsis in preterm infants. Methods The Systemic Inflammatory Indices of the two groups of preterms – one control group without sepsis and one case group with sepsis–were compared to assess their value in predicting Neonatal Sepsis. Data from 138 preterm neonates were used in the present study. Systemic Inflammatory Indices were calculated and compared from the collected data in both the case and control groups. Results Platelet count, Pan Immune Inflammation Value (PIV), Platelet to Lymphocyte Ratio (PLR) and Systemic Immune Inflammatory Index (SII) were found to be significant predictors of neonatal sepsis. Platelet count had the highest predictive value, with an AUC value of 0.715 and optimal cut-off value of 219500. It had a sensitivity of 75.4 and specificity of 65.2. Conclusion According to this study, sepsis in preterm infants can be predicted by using systemic inflammatory indices. This will aid in early sepsis diagnosis and management and, in turn, reduce neonatal morbidity and mortality associated with sepsis.

in F1000Research on 2025-04-03 17:07:28 UTC.

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Assesing Conversion Rate, Treatment Success and Mortality of Drug Induce Liver Injury from First Line Antituberculosis Regiment: A Systematic Review and Meta -Analysis [version 1; peer review: awaiting peer review]

The prevalence of Drug Induce Liver Injury (DILI) in Tuberculosis (TB) patients is a critical concern, as it complicates the treatment regimen. The hepatotoxicity of first-line anti-TB drugs such as isoniazid and rifampicin can lead to significant liver damage, which in turn affects the metabolism of these medications, potentially resulting in treatment failure or increased mortality. Given the limited certainty surrounding the clinical outcomes of tuberculosis-associated drug-induced liver injury (TB-DILI), an in-depth evaluation of existing evidence is essential. This systematic review and meta-analysis aimed to assess the clinical outcomes in patients with TB-DILI. Comprehensive searches were conducted across the Scopus, Embase, and PubMed databases, adhering to inclusion criteria derived from the PICOS framework. Keywords related to "drug-induced liver injury" and "tuberculosis," as well as their synonyms, were employed in the search. The Newcastle-Ottawa Scale (NOS) was utilized to assess the risk of bias in observational studies. Data were independently extracted, and the quality of the included studies was evaluated. Relative risk (RR) and tests for heterogeneity were conducted, and results were visualized through RR estimates and forest plots. A total of five studies, encompassing 5,798 patients, were ultimately included in the analysis. This study indicates that TB DILI has no significant risk on 2 months conversion compared to TB Non – DILI patients with RR: 1.03; 95%CI: 0.97–1.03, p<0.31. However, treatment success (RR: 1.11; 95%CI: 1.05–1.18, p<0.0004) and mortality risk (RR: 2.62; 95%CI: 1.14–6.03, p<0.02) were significant in TB Non – DILI patients.

in F1000Research on 2025-04-03 17:06:10 UTC.

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Using text-mining to measure the scientific impact and legacy of ELIXIR, a distributed research infrastructure for life science data [version 2; peer review: 1 approved, 1 approved with reservations]

Background ELIXIR is a pan-European public-funded research infrastructure dedicated to life science data. As such, it must demonstrate public value to its funders and stakeholders. We present methods to inventory research publications linked to ELIXIR that have received funding and support, as well as related citation metrics, used as performance metrics for these audiences. Methods To overcome challenges inherent in ELIXIR’s distributed structure, and the fact that those publishing ELIXIR-supported work are typically working part-time on ELIXIR matters, a semi-automated approach, consisting of text-mining followed by manual curation, is presented. A country-level case study (ELIXIR Italy) refines and expands the methods, notably by introducing more granularity in the curation process (e.g. considering all national-level grants, examining affiliations to report publication per institute) and by additionally looking at the scientific impact of the resources developed and operated by the Italian Node of ELIXIR. Results Overall, the methods described in this article have shown to: (1) be repeatable with acceptable levels of accuracy and consistency (notably across curators); (2) require reasonable effort in terms of curation of monthly ‘harvests’ of publications (obtained by text-mining); and (3) to be well-adapted to ELIXIR’s distributed nature. Conclusions Concrete examples are provided of downstream uses of the inventoried publications and their citations, both for ELIXIR as a whole and for the Italian case study. Limitations of the methods are discussed, particularly the challenges associated with using an ‘Open literature’ database (Europe PMC) for the text-mining, and the constraints related to curation capacity. The methods, along with the valuable lessons learned during their development, are sufficiently generic and pragmatic enough to be readily adapted by other similar research infrastructures.

in F1000Research on 2025-04-03 17:04:18 UTC.

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Methodology used to develop the minimum common data elements for surveillance and Reporting of Musculoskeletal Injuries in the MILitary (ROMMIL) statement [version 2; peer review: 1 approved, 2 approved with reservations]

Background The objective was to summarize the methodology used to develop the international minimum data elements for surveillance and Reporting of Musculoskeletal Injuries in the MILitary (ROMMIL) statement. This is a recommended list of elements to be collected and reported when conducting injury surveillance research in military settings. Methods A Delphi methodology was employed to reach consensus. Preliminary steps included conducting a literature review and surveying a convenience sample of military stakeholders to 1) identify barriers and facilitators of military musculoskeletal injury (MSKI) prevention programs, 2) identify relevant knowledge gaps, and 3) establish future research priorities. A sequential three-round Delphi consensus survey followed, including relevant stakeholders from militaries around the world, using results to conduct an asynchronous knowledge user meeting (mixture of in-person and live video conference and recording) to explore the level of agreement among subject matter experts. Knowledge users, including former and current military service members, civilian practitioners working in military health networks, and international subject matter experts having experience with policy, execution, or clinical investigation of MSKI mitigation programs, MSKI diagnoses, and MSKI risk factors in military settings. For each round, participants scored questions on a Likert scale of 1-5. Scores ranged from No Importance (1) to Strong Importance (5). Results Literature review and surveys helped inform the scope of potential variables. Three rounds were necessary to reach minimum consensus. Ninety-five, 65, and 42 respondents participated in the first, second and third rounds, respectively. Conclusions Achieving consensus across relevant knowledge users representing military organizations globally can be challenging. This paper details the methodology employed to reach consensus for a core minimum data elements checklist for conducting MSKI research in military settings and improve data harmonization and scalability efforts. These methods can be used as a resource to assist in future consensus endeavors of similar nature.

in F1000Research on 2025-04-03 17:02:14 UTC.

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Prevalence of common mental health problems and associated factors among university students visiting Supara mental health service: A cross-sectional study [version 5; peer review: 2 approved]

Background: Early studies found that the mental health problems rate was relatively high in university students. We aimed to investigate the prevalence of mental problems and associated factors in university students. Methods: We conducted a cross-sectional descriptive study at Supara mental health service in the Faculty of Medicine Vajira Hospital between February 2020 to June 2021. The primary outcome was the prevalence of psychiatric diagnosis according to the 10th revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10). The secondary assessments included the Patient Health Questionnaire-9 (PHQ-9), 8 items from the Mini International Neuropsychiatric Interview (MINI) to assess suicidal risk (8Q), , and the Thai Mental Health Indicator (TMHI-15). The prevalence of mental health problems was presented by frequency and percentage. In addition, multivariable regression analysis was used to identify potential predictors of mental health problems. Results: A total of 184 participants (62% female; mean age = 22.49 years (SD 3.93) were recruited. The depressive disorders, adjustment disorders, and anxiety disorders rates were 57.1%, 15.2% and 13.6%, respectively. Grade point averages (GPAs) below 3.0 (OR=3.09, 95%CI: 1.17-8.14) and a family history of mental disorder (OR=3.40, 95%CI: 1.10-10.48) were significant associated factors of moderate to severe mental health problems. Detecting and screening these factors may help the university to provide early detection and treatment for students. Conclusions: Depressive disorders were the most common mental health disorders. Females, low GPAs and a family history of mental disorder were predictors of moderate to severe mental health problems.

in F1000Research on 2025-04-03 16:59:39 UTC.

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A complementary approach to measure construct validity of WHO QOL BREF in Indian multidrug-resistant tuberculosis (MDR-TB) patients through psychometric property and factor analysis [version 2; peer review: 1 approved with reservations]

Background Multidrug-resistant tuberculosis (MDR TB) affects the physical, psychosocial and inter-relationship structure and thus quality of life (QoL) of an individual. WHO QOL BREF is presumed to capture the QoL construct. This study investigates the diagnostic accuracy and construct of WHO QOL BREF from a psychometric perspective and complements and converges findings through classical test theory. Methods The instrument validity study was conducted in a district of Central India amongst the microbiologically confirmed MDR TB cohort of year 2017 (n=98). We calculated global and domain-specific Cronbach alpha and Inter-domain Pearson correlations. The dichotomized items were fitted through Rasch model for item endorsement, response pattern and for variation inconsistencies. Item Characteristic Curves and person item maps were also plotted. We performed DIF (Differential Item Functioning) to check the effect of subgroups on underlying traits. This was complimented with an Exploratory Factor Analysis (EFA) using oblique ProMax rotation. The optimum number of factors were identified by Scree plot and parallel analysis approach and the emerging factor structure was compared with the result obtained through the Rasch model. Results The global Cronbach’s alpha was 0.94 (95% CI 0.92-0.96). Social relationship domain had poor correlations with all three domains (r=0.42, r=0.41 r=0.58), higher beta values and less discrimination. DIF showed a differential response by gender. There was a visual clustering and a non-uniform distribution of items across the perceived QoL. A 3-factor model emerged through EFA and was reframed on the notion of self-concept. Items related to pain, medical aid had significant misfit and weak factor loading while items of sexual activity and social support had relatively poor performance in Infit, Wald, DIF on factor loading parameters. Conclusions The study indicates the possible deviation of scale from theorized dimensional construct in Indian MDR TB context more with the items of the social relationship domain.

in F1000Research on 2025-04-03 16:58:30 UTC.

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Searching for non-English literature may be unnecessary for German HTA Reports [version 2; peer review: 2 approved with reservations, 1 not approved]

Background Health technology assessment (HTA) reports are based on comprehensive information retrieval. Current standards discourage the use of search restrictions, such as publication date and language. Given limited resources, it was unclear whether the effort invested in screening and translating studies published in languages other than English provided relevant additional information compared with the inclusion of English-language publications alone. We therefore analysed the impact of non-English publications on the conclusions of HTA reports produced by the German HTA agency, the Institute for Quality and Efficiency in Health Care (IQWiG). Methods We determined whether non-English publications were included in all German HTA reports on non-drug interventions (published by IQWiG between 06/2007 to 08/2018) and on selected drug interventions. If at least one non-English publication was included, we assessed for each endpoint whether or not the exclusion of non-English publications changed the conclusion. If a non-English publication did not contain information relevant to the HTA report, we classified the publication as “not relevant”. Results Of 70 HTA reports, 38 (54%) included 126 non-English publications. In 4 reports (6%) with 50 endpoints investigated in 39 PICO questions, the exclusion of a total of 10 non-English publications led to a change in the conclusions for 13 endpoints (8 PICO questions). This was largely due to the fact that in many cases, non-English publications were the predominant or only literature available, resulting in a lack of analysable data after their exclusion. Conclusions In general, studies only published in non-English languages have little influence on the conclusions of German HTA reports. For the vast majority of topics, a language restriction to English seems justified. Studies published in non-English languages may be useful in exceptional cases, for example when an intervention is only available in certain countries.

in F1000Research on 2025-04-03 16:55:15 UTC.

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Is relief the most common reaction to abortion? Self-assessed intensity of emotions attributed to abortion in a national sample of women aged 41 to 45 [version 2; peer review: 2 approved]

Background It is widely reported that the most prominent emotion following abortions is relief. This claim primarily rests on two studies of abortion clinic patients which had methodological and self-censure bias. Other studies have indicated that negative emotions are more common than positive emotions. The objective of this study is to obtain self-assessed data on the intensity of emotional responses to abortion and pregnancy loss in a random national sample. Methods Using visual analog scales, a random sample of 1,925 women aged 41 to 45 completed a survey in which respondents rated the degree to which they experienced emotional responses to their first abortion or natural pregnancy loss. The emotions assessed included relief, grief, depression, anxiety, guilt, emptiness, anger, regret, shame, unforgiveness of self, uncontrollable weeping, frequent thoughts of the child they could have had, and difficulty completing the grief process. Women were categorized into five groups based on pregnancy outcomes, and four abortion decision types: Wanted, Inconsistent, Unwanted, or Coerced. Results Among women with a history of abortion (n=409), negative emotions were reported more intensely than relief. Relief was the predominant emotion only among the 29.8% of women whose abortions were freely wanted and consistent with their own values and preferences. For all other groups, relief was low and negative emotions were more prominent. Emotions following natural pregnancy losses were similar to those following abortion, but less severe following wanted abortions and more severe following coerced abortions. Conclusions Relief is only common after freely wanted abortions. Most abortions are inconsistent or contrary to women’s own values. In these cases, strong negative emotions are far more dominant than relief. These results should inform pre-abortion screening, counseling supportive of women’s own values and preferences, and mental health support post-abortion.

in F1000Research on 2025-04-03 16:52:54 UTC.

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A Quasi-Experimental Study Protocol on the Impact of a Mobile Health Program for HIV Counseling and Testing in the Deaf Community [version 2; peer review: 1 approved with reservations]

Background Deaf individuals are considered a high-risk population for health disparities. During the covid-19 epidemic, deaf and hearing loss persons also suffer from psychological issues, post-traumatic stress disorder, and seropositive HIV. Objective This study aims to examine the effectiveness of an mobile health educational program to increase mental health and HIV prevention among deaf community Methods This study employs a quasi-experimental design with a non-randomized controlled trial, involving single-blinded participants and a parallel group assignment, purpose for health service research, study phase 2-3. pronounced to escalate the sample size to 40 deaf per group, which is 80 total participants. Results The analysis of the data will be conducted utilizing the generalized estimation equation, with a confidence interval set at 95%. Significant differences, both between and within groups, will be identified at a threshold of P<.05. The findings of this study highlight the efficacy of a mobile educational program in enhancing mental health and preventing HIV within the deaf community. Furthermore, the outcomes of this research will augment existing knowledge regarding psychological distress, HIV prevention practices, and coping self-efficacy among individuals who are deaf. Conclusion The intervention group is expected to demonstrate significantly lower scores in psychological distress during both the immediate evaluation and the assessment conducted three months post-intervention, compared to the wait-list group. Additionally, the intervention group is anticipated to exhibit enhanced levels of HIV prevention practices and coping self-efficacy, resulting in a greater degree of adjustment. Clinical trial SLCTR/2024/039, 25 November 2024, https://slctr.lk/trials/slctr-2024-039

in F1000Research on 2025-04-03 16:51:27 UTC.

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The effect of surface treatments on the bond strength of polyetheretherketone posts: a systematic review protocol [version 3; peer review: 2 approved with reservations, 1 not approved]

Background Polyetheretherketone (PEEK) is widely used in the biomedical field due to its outstanding biological and mechanical properties. Originally employed as a temporary abutment in implantology, recent research has expanded its indications for more definitive applications, such as frameworks and dental post and core. However, PEEK’s inert nature and low surface energy pose challenges for adhesion, necessitating surface modifications. Various physical and chemical modification techniques, including acid etching (e.g., 98% sulfuric acid), sandblasting with alumina oxide (Al₂O₃), plasma treatment, laser irradiation, silanization, and air abrasion with silica-coated particles, have been proposed to enhance PEEK’s bonding performance. Despite numerous clinical investigations, standardized protocols for surface treatment remain lacking. This systematic review aims to assess the impact of surface treatments on the bonding performance of PEEK posts. Methods A detailed search of the literature will be conducted across several databases including PubMed, Scopus and clinical trial registries. Additional databases such as Cochrane Central, EMBASE, Web of Science and EBSCO will also be included. The search strategy will target controlled randomized studies and non-randomized clinical trials evaluating the impact of surface treatments on PEEK post adhesion strength. The Newcastle-Ottawa Scale (NOS) will be used to assess bias in non-randomized studies, while the Cochrane Risk of Bias (ROB II) tool will be employed for evaluating randomized controlled trials. Data extraction will focus on study design, treatment methods, outcomes and results. This systematic review protocol will adhere to the guidelines for systematic reviews outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Discussion The discussion will explore the implications of findings on clinical practice, highlighting the importance of enhancing PEEK’s bioactivity and surface energy to improve bonding efficacy in dental procedures. Moreover, it will suggest areas for future research to advance dental materials science, aiming to optimize the utilization of PEEK in dental applications Systematic review registration PROSPERO: CRD42024529783 (Registered on 08/04/2024).

in F1000Research on 2025-04-03 16:49:48 UTC.

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Identifying and Assessing Physiological Biomarkers for Food and Energy Intake: A Systematic Review with Meta-Analysis Protocol [version 2; peer review: 1 approved with reservations]

Background Traditional dietary assessments are often inaccurate and prone to self-reporting biases. Tracking the physiological responses associated with eating and digestion events via wearable technologies may provide an effective approach for continuously monitoring food intake and estimating energy consumption. Eating and digestion are accompanied by a series of changes in the heart rate, skin temperature, blood oxygen saturation, and blood pressure. These changes can be tracked by wearable devices, such as smartwatches, which have been widely accepted in the market. This systematic review is the first to evaluate the effectiveness of tracking such physiological biomarkers in differentiating between high- and low-calorie meals, potentially paving the way for more accurate dietary monitoring. Methods Following the PRISMA-P guidelines, we will conduct a systematic literature search through MEDLINE, EMBASE, and PubMed for clinical trials that investigated physiological responses following meal intake in healthy subjects. Two independent reviewers will screen and select articles based on pre-defined eligibility criteria, with a third review to resolve any discrepancies. This will be followed by data extraction and quality assessment of the included studies. Statistical analyses, including meta-analyses, will be performed using R Studio software. Our primary outcome will be the comparison of physiological biomarkers before and after meal intake, while secondary outcomes will include comparisons of physiological biomarkers between high- and low-calorie meal consumption and the correlation between the caloric content of consumed meals and postprandial physiological changes. Discussion This systematic review and meta-analysis will identify physiological indicators for eating events and inform the design of wearable sensors that estimate food intake in healthy subjects. Systematic Review Registration PROSPERO Registration ID: CRD42024544353

in F1000Research on 2025-04-03 16:47:32 UTC.

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Mortality involving and not involving COVID-19 among vaccinated vs. unvaccinated in England between Apr 21 and May 23 [version 2; peer review: 2 not approved]

Background Comparing non-randomized groups, such as COVID-19 vaccinated and unvaccinated, even in the presence of seemingly relevant control variables, is challenging, but in this study, using English data, I show an achievable approach. Methods First, I estimated age-standardized all-cause mortality among vaccinated and unvaccinated ten years and older, covering 26 months from Apr 21 to May 23. Then, I estimated mortality not involving COVID-19, and finally, I differentiated the calculations. Results First, I found that all-cause mortality among unvaccinated was higher than among vaccinated. But, as the pattern was similar concerning mortality not involving COVID-19, the discrepancy is attributed mainly to unvaccinated having inferior health at the outset. There was nonetheless significant protection for vaccinated between July 21 and Jan 22. Absent of control variables as a means to compare non-randomized groups, I reached that finding by differentiating all-cause mortality from mortality not involving COVID-19. However, while mortality not involving COVID-19 decreased among unvaccinated compared to the first observation month, it was high among vaccinated, i.e., a relative increase in mortality among vaccinated. Conclusions An interpretation is that vaccination, despite temporary protection, increased mortality. Strengthening the interpretation was relatively high mortality among vaccinated not involving COVID-19 counterintuitively following periods of excess mortality. Further strengthening the interpretation was relatively high mortality not involving COVID-19 among vaccinated, corresponding with excess mortality during much of the same period. An implication of the study, which particularly has relevance for future pandemics, is that vaccinated may have a limited time window of protection and can even be exposed to detrimental health consequences. The pattern should be followed up over an extended period in future research. Also, future research should examine different age groups, vaccination types, and the number of doses given.

in F1000Research on 2025-04-03 15:12:51 UTC.

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Campus air quality dataset [version 1; peer review: awaiting peer review]

Background Elevated levels of carbon dioxide (CO2) within academic settings can adversely affect the health and academic efficacy of both students and faculty. High concentrations of CO2 are correlated with reduced cognitive functioning, compromised decision-making abilities, diminished academic performance, and various health-related issues. The escalating apprehensions regarding the detrimental health consequences of air pollution have precipitated an increase in research focused on air quality assessment and amelioration. Method The investigation utilized Internet of Things (IoT) devices that were outfitted with sensors to gather data on various environmental parameters, such as temperature, humidity, CO2 concentrations, and light intensity. This data underwent analysis through the application of summary statistics to delineate the dataset and to visualize the distribution of variables via scatter matrix plots. Result The dataset obtained, which encompasses essential air quality and environmental parameters, is now accessible to the public through the Mendeley repository. The analytical findings illuminated significant characteristics of the data concerning CO2 levels and their prospective ramifications on the academic milieu. Conclusion The amalgamation of IoT technology with summary statistical analysis presents a promising methodology for the real-time surveillance of air quality. This approach yields critical insights into the health and academic ramifications of heightened CO2 levels within educational environments, underscoring the necessity for ongoing air quality monitoring to enhance campus conditions.

in F1000Research on 2025-04-03 14:38:30 UTC.

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The Effects of Information-Motivation-Behavioral Skills Model in Predicting Safer Sexual Dual Protection Behaviors Among Female University Students: A Cross-sectional Study [version 1; peer review: awaiting peer review]

Background The burden of sexually transmitted infections (STIs) and unintended pregnancy remains a significant public health concern, with young women being disproportionately affected. While both risks can be prevented simultaneously by the same safe sexual practice, such as abstinence or dual protection use, little is known about the patterns and predictors of a range of safer sexual dual protection behaviors among youth based on theoretical models in Ethiopia. This study aimed to examine the effects of information-motivation-behavioral skills (IMB) model in predicting various safer sexual dual protection behaviors, including primary sexual abstinence and dual-protection use among female university students in Ethiopia. Methods A cross-sectional study was conducted among female university students at MattuUniversity. Data were collected using a self-administered questionnaire and analyzed using SPSS version 23. Bivariate and multivariate analyses were conducted using structural equation modeling (SEM) with AMOS 23. Results Of the 1,020 participants, 624 (61.2%) practiced primary sexual abstinence, whereas 396 (38.8%) have ever had sexual intercourse, of whom only 76 (20.5%) used dual protection at their last sexual encounter. Results of the structural equation model analysis indicated that primary sexual abstinence was strongly correlated with motivation (β = 0.34, P < 0.001) and behavioralskills (β = 0.24, P < 0.001) and information (β = 0.11, P < 0.001). Among sexually active participants, dual protection use was strongly correlated with motivation (β = 0.23, P < 0.05) and behavioral skills (β = 0.24, P < 0.001), while it was moderately correlated with information (β = 0.04, P < 0.05). Approximately 28% of the variance in primary sexual abstinence and 27.4% of the variance in dual protection use was explained by the model constructs. Conclusions The findings indicate that the IMB model is useful for identifying powerful predictors of sexual abstinence and dual protection use among female university students, which has potential implications for designing interventions to improve knowledge, motivation, behavioral skills and practice of abstinence and/or dual protection use among youth at risk of both STI/HIV and unwanted pregnancy in settings with high HIV burdens.

in F1000Research on 2025-04-03 14:30:35 UTC.

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Integrating multiple spatial transcriptomics data using community-enhanced graph contrastive learning

by Wenqian Tu, Lihua Zhang

Due to the rapid development of spatial sequencing technologies, large amounts of spatial transcriptomic datasets have been generated across various technological platforms or different biological conditions (e.g., control vs. treatment). Spatial transcriptomics data coming from different platforms usually has different resolutions. Moreover, current methods do not consider the heterogeneity of spatial structures within and across slices when modeling spatial transcriptomics data with graph-based methods. In this study, we propose a community-enhanced graph contrastive learning-based method named Tacos to integrate multiple spatial transcriptomics data. We applied Tacos to several real datasets coming from different platforms under different scenarios. Systematic benchmark analyses demonstrate Tacos’s superior performance in integrating different slices. Furthermore, Tacos can accurately denoise the spatially resolved transcriptomics data.

in PLoS Computational Biology on 2025-04-03 14:00:00 UTC.

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CINner: Modeling and simulation of chromosomal instability in cancer at single-cell resolution

by Khanh N. Dinh, Ignacio Vázquez-García, Andrew Chan, Rhea Malhotra, Adam Weiner, Andrew W. McPherson, Simon Tavaré

Cancer development is characterized by chromosomal instability, manifesting in frequent occurrences of different genomic alteration mechanisms ranging in extent and impact. Mathematical modeling can help evaluate the role of each mutational process during tumor progression, however existing frameworks can only capture certain aspects of chromosomal instability (CIN). We present CINner, a mathematical framework for modeling genomic diversity and selection during tumor evolution. The main advantage of CINner is its flexibility to incorporate many genomic events that directly impact cellular fitness, from driver gene mutations to copy number alterations (CNAs), including focal amplifications and deletions, missegregations and whole-genome duplication (WGD). We apply CINner to find chromosome-arm selection parameters that drive tumorigenesis in the absence of WGD in chromosomally stable cancer types from the Pan-Cancer Analysis of Whole Genomes (PCAWG, n=718 ). We found that the selection parameters predict WGD prevalence among different chromosomally unstable tumors, hinting that the selective advantage of WGD cells hinges on their tolerance for aneuploidy and escape from nullisomy. Analysis of inference results using CINner across cancer types in The Cancer Genome Atlas (n=8207) further reveals that the inferred selection parameters reflect the bias between tumor suppressor genes and oncogenes on specific genomic regions. Direct application of CINner to model the WGD proportion and fraction of genome altered (FGA) in PCAWG uncovers the increase in CNA probabilities associated with WGD in each cancer type. CINner can also be utilized to study chromosomally stable cancer types, by applying a selection model based on driver gene mutations and focal amplifications or deletions (chronic lymphocytic leukemia in PCAWG, n=95). Finally, we used CINner to analyze the impact of CNA probabilities, chromosome selection parameters, tumor growth dynamics and population size on cancer fitness and heterogeneity. We expect that CINner will provide a powerful modeling tool for the oncology community to quantify the impact of newly uncovered genomic alteration mechanisms on shaping tumor progression and adaptation.

in PLoS Computational Biology on 2025-04-03 14:00:00 UTC.

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Playbook workflow builder: Interactive construction of bioinformatics workflows

by Daniel J.B. Clarke, John Erol Evangelista, Zhuorui Xie, Giacomo B. Marino, Anna I. Byrd, Mano R. Maurya, Sumana Srinivasan, Keyang Yu, Varduhi Petrosyan, Matthew E. Roth, Miroslav Milinkov, Charles Hadley King, Jeet Kiran Vora, Jonathon Keeney, Christopher Nemarich, William Khan, Alexander Lachmann, Nasheath Ahmed, Alexandra Agris, Juncheng Pan, Srinivasan Ramachandran, Eoin Fahy, Emmanuel Esquivel, Aleksandar Mihajlovic, Bosko Jevtic, Vuk Milinovic, Sean Kim, Patrick McNeely, Tianyi Wang, Eric Wenger, Miguel A. Brown, Alexander Sickler, Yuankun Zhu, Sherry L. Jenkins, Philip D. Blood, Deanne M. Taylor, Adam C. Resnick, Raja Mazumder, Aleksandar Milosavljevic, Shankar Subramaniam, Avi Ma’ayan

The Playbook Workflow Builder (PWB) is a web-based platform to dynamically construct and execute bioinformatics workflows by utilizing a growing network of input datasets, semantically annotated API endpoints, and data visualization tools contributed by an ecosystem of collaborators. Via a user-friendly user interface, workflows can be constructed from contributed building-blocks without technical expertise. The output of each step of the workflow is added into reports containing textual descriptions, figures, tables, and references. To construct workflows, users can click on cards that represent each step in a workflow, or construct workflows via a chat interface that is assisted by a large language model (LLM). Completed workflows are compatible with Common Workflow Language (CWL) and can be published as research publications, slideshows, and posters. To demonstrate how the PWB generates meaningful hypotheses that draw knowledge from across multiple resources, we present several use cases. For example, one of these use cases prioritizes drug targets for individual cancer patients using data from the NIH Common Fund programs GTEx, LINCS, Metabolomics, GlyGen, and ExRNA. The workflows created with PWB can be repurposed to tackle similar use cases using different inputs. The PWB platform is available from: https://playbook-workflow-builder.cloud/.

in PLoS Computational Biology on 2025-04-03 14:00:00 UTC.

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SpaMask: Dual masking graph autoencoder with contrastive learning for spatial transcriptomics

by Wenwen Min, Donghai Fang, Jinyu Chen, Shihua Zhang

Understanding the spatial locations of cell within tissues is crucial for unraveling the organization of cellular diversity. Recent advancements in spatial resolved transcriptomics (SRT) have enabled the analysis of gene expression while preserving the spatial context within tissues. Spatial domain characterization is a critical first step in SRT data analysis, providing the foundation for subsequent analyses and insights into biological implications. Graph neural networks (GNNs) have emerged as a common tool for addressing this challenge due to the structural nature of SRT data. However, current graph-based deep learning approaches often overlook the instability caused by the high sparsity of SRT data. Masking mechanisms, as an effective self-supervised learning strategy, can enhance the robustness of these models. To this end, we propose SpaMask, dual masking graph autoencoder with contrastive learning for SRT analysis. Unlike previous GNNs, SpaMask masks a portion of spot nodes and spot-to-spot edges to enhance its performance and robustness. SpaMask combines Masked Graph Autoencoders (MGAE) and Masked Graph Contrastive Learning (MGCL) modules, with MGAE using node masking to leverage spatial neighbors for improved clustering accuracy, while MGCL applies edge masking to create a contrastive loss framework that tightens embeddings of adjacent nodes based on spatial proximity and feature similarity. We conducted a comprehensive evaluation of SpaMask on eight datasets from five different platforms. Compared to existing methods, SpaMask achieves superior clustering accuracy and effective batch correction.

in PLoS Computational Biology on 2025-04-03 14:00:00 UTC.

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Predicting and comparing transcription start sites in single cell populations

by Shiwei Fu, Wei Vivian Li

The advent of 5’ single-cell RNA sequencing (scRNA-seq) technologies offers unique opportunities to identify and analyze transcription start sites (TSSs) at a single-cell resolution. These technologies have the potential to uncover the complexities of transcription initiation and alternative TSS usage across different cell types and conditions. Despite the emergence of computational methods designed to analyze 5’ RNA sequencing data, current methods often lack comparative evaluations in single-cell contexts and are predominantly tailored for paired-end data, neglecting the potential of single-end data. This study introduces scTSS, a computational pipeline developed to bridge this gap by accommodating both paired-end and single-end 5’ scRNA-seq data. scTSS enables joint analysis of multiple single-cell samples, starting with TSS cluster prediction and quantification, followed by differential TSS usage analysis. It employs a Binomial generalized linear mixed model to accurately and efficiently detect differential TSS usage. We demonstrate the utility of scTSS through its application in analyzing transcriptional initiation from single-cell data of two distinct diseases. The results illustrate scTSS’s ability to discern alternative TSS usage between different cell types or biological conditions and to identify cell subpopulations characterized by unique TSS-level expression profiles.

in PLoS Computational Biology on 2025-04-03 14:00:00 UTC.

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Spatial structure facilitates evolutionary rescue by drug resistance

by Cecilia Fruet, Ella Linxia Müller, Claude Loverdo, Anne-Florence Bitbol

Bacterial populations often have complex spatial structures, which can impact their evolution. Here, we study how spatial structure affects the evolution of antibiotic resistance in a bacterial population. We consider a minimal model of spatially structured populations where all demes (i.e., subpopulations) are identical and connected to each other by identical migration rates. We show that spatial structure can facilitate the survival of a bacterial population to antibiotic treatment, starting from a sensitive inoculum. Specifically, the bacterial population can be rescued if antibiotic resistant mutants appear and are present when drug is added, and spatial structure can impact the fate of these mutants and the probability that they are present. Indeed, the probability of fixation of neutral or deleterious mutations providing drug resistance is increased in smaller populations. This promotes local fixation of resistant mutants in the structured population, which facilitates evolutionary rescue by drug resistance in the rare mutation regime. Once the population is rescued by resistance, migrations allow resistant mutants to spread in all demes. Our main result that spatial structure facilitates evolutionary rescue by antibiotic resistance extends to more complex spatial structures, and to the case where there are resistant mutants in the inoculum.

in PLoS Computational Biology on 2025-04-03 14:00:00 UTC.

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The end of long-term ecological data?

by Daniel T. Blumstein

Can we ever have too much ecological field data? Are data-sharing norms and the environmental costs of travel disincentivizing its collection? Allocating proper funding and resources to the collection of long-term ecological data is essential for studies of behavior and adaptation, which are particularly important in the face of anthropogenic change.

in PLoS Biology on 2025-04-03 14:00:00 UTC.

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Gas1-high quiescent neural stem cells are multipotent and produce oligodendrocytes during aging and after demyelinating injury

by Chaoqiong Ding, Zhenzhong Pan, Xiang Yan, Ran Zhou, Huifang Li, Lu Chen, Yuan Wang, Yan Zhang

Quiescent neural stem cells (qNSCs) in the adult mouse subventricular zone (SVZ) normally have limited capacity to generate glia. Gliogenic domains are present in both dorsal and ventral SVZ, with the ventral region featuring a subpopulation of Gli1⁺ qNSCs. In dorsal SVZ, however, the molecular identity and developmental origin of oligodendrogenic qNSCs remains elusive. Here, through single-cell analysis and lineage tracing, we identify an undefined subpopulation of Gas1^high qNSCs in dorsal SVZ, distinct from Gli1⁺ qNSCs. These cells originate from embryonic Gas1^high dorsal radial glia, and persist into the aged SVZ. Remarkably, they are multipotent and more gliogenic than Gas1^low/− qNSCs, continuously generating oligodendrocytes in the adult and aged brain, and can be mobilized for myelin repair upon demyelination. Together, our study uncovers a subpopulation of dorsally derived, multipotent long-term qNSCs in the adult and aged SVZ with enhanced gliogenic potential, shedding light on the heterogeneity and plasticity of NSCs in normal, aging, and disease conditions.

in PLoS Biology on 2025-04-03 14:00:00 UTC.

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MRI‐T2 Relaxometry is Increased in Mild Traumatic Brain Injury: Indications of Acute Brain Abnormalities After Injury

Central nervous system disorders impair information transmission by causing synapse loss and dysfunction. Synaptic plasticity, involving the dynamic strengthening or weakening of synapses, enables brain adaptation. Regulating this process can alleviate disease progression and support synaptic recovery, introducing innovative treatment strategies that restore neural connectivity and improve overall brain function.

ABSTRACT

Mild traumatic brain injury (mTBI) is a common condition, particularly pervasive in contact sports environments. A range of symptoms can accompany this type of injury and negatively impact people's lives. As mTBI diagnosis and recovery largely rely on subjective reports, more objective injury markers are needed. The current study compared structural brain MRI-T2 relaxometry between a group of 40 male athletes with mTBI within 14 days of injury and 40 age-matched male controls. Voxel-averaged T2 relaxometry within the gray matter was increased for the mTBI group compared to controls (p < 0.001), with statistically significant increased T2 relaxometry particularly in superior cortical regions. Our findings indicate subtle brain abnormalities can be identified in acute mTBI using MRI-T2 relaxometry. These brain abnormalities may reflect inflammation present in the brain and could constitute an objective injury marker to supplement current subjective methods that dominate clinical decisions regarding diagnosis and prognosis. Future research should validate this potential marker with other data types, such as blood biomarkers or histological samples.

in Journal of Neuroscience Research on 2025-04-03 13:05:56 UTC.

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The influence of postural threat-induced anxiety on locomotor learning and updating: a mini-review

Journal of Neurophysiology, Volume 133, Issue 4, Page 1205-1207, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:26 UTC.

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Visual properties of action consequences and not environments affect context-specific motor learning

Journal of Neurophysiology, Volume 133, Issue 4, Page 1176-1190, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:25 UTC.

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Reply to Castro and Carvalho

Journal of Neurophysiology, Volume 133, Issue 4, Page 1148-1149, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:22 UTC.

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Postural strategy for two potential targets considering motor costs for postural stabilization and probabilistic information

Journal of Neurophysiology, Volume 133, Issue 4, Page 1191-1204, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:21 UTC.

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String-pulling by the common marmoset

Journal of Neurophysiology, Volume 133, Issue 4, Page 1222-1233, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:20 UTC.

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Choice anticipation as gated accumulation of sensory predictions

Journal of Neurophysiology, Volume 133, Issue 4, Page 1159-1175, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:19 UTC.

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Changes in gait asymmetry may be caused by adaptation of spinal reflexes

Journal of Neurophysiology, Volume 133, Issue 4, Page 1208-1215, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:18 UTC.

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Subcortical responses to continuous speech under bimodal divided attention

Journal of Neurophysiology, Volume 133, Issue 4, Page 1216-1221, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:18 UTC.

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Microbiome’s effect on white matter in autism

Journal of Neurophysiology, Volume 133, Issue 4, Page 1150-1158, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:17 UTC.

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Synaptic dynamics linked to widespread elevation of H-reflex before peripheral denervation in amyotrophic lateral sclerosis

Journal of Neurophysiology, Volume 133, Issue 4, Page 1146-1147, April 2025.

in Journal of Neurophysiology on 2025-04-03 11:45:15 UTC.

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Erratum for the Research Article “Whale song shows language-like statistical structure” by I. Arnon et al.

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-03 07:00:00 UTC.

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Beyond the Binary: Navigating AI’s Uncertain Future in Africa

Science, Volume 388, Issue 6742, April 2025.

in Science on 2025-04-03 07:00:00 UTC.

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