bluuebunny/crossref_metadata_2025 huggingface dataset:
RNAcare: Integrating Clinical Data with Transcriptomic Evidence using Rheumatoid Arthritis as a Case Study
Authors: Tang Mingcan , Haese-Hill William , Morton Fraser , Goodyear Carl , Porter Duncan , Siebert Stefan , Otto Thomas D.
Published: February 2025

Background

Gene expression analysis is a crucial tool for uncovering the biological mechanisms that underlie differences between patient subgroups, offering insights that can inform clinical decisions. However, despite its potential, gene expression analysis remains challenging for clinicians due to the specialised skills required to access, integrate, and analyse large datasets. Existing tools primarily focus on RNA-Seq data analysis, providing user-friendly interfaces but often falling short in several critical areas: they typically do not integrate clinical data, lack support for patient-specific analyses, and offer limited flexibility in exploring relationships between gene expression and clinical outcomes in disease cohorts. Users, including clinicians with a general knowledge of transcriptomics, however, who may have limited programming experience, are increasingly seeking tools that go beyond traditional analysis. To overcome these issues, computational tools must incorporate advanced techniques, such as machine learning, to better understand how gene expression correlates with patient symptoms of interest.

Results

Our RNAcare platform, addresses these limitations by offering an interactive and reproducible solution specifically designed for analysing bulk RNA-Seq data from patient samples in a clinical context. This enables researchers to directly integrate gene expression data with clinical features, perform exploratory data analysis, and identify patterns among patients with similar diseases. By enabling users to integrate transcriptomic and clinical data, and customise the target label, the platform facilitates the analysis of the relationships between gene expression and clinical symptoms, like pain and fatigue. This allows users to generate hypotheses and illustrative visualisations/reports to support their research.

As proof of concept, we use RNAcare to link inflammation-related genes to pain and fatigue in rheumatoid arthritis (RA) and detect signatures in the drug response group, confirming previous findings and generating new hypotheses.

Conclusion

We present a novel computational platform allowing the interpretation of clinical and transcriptomics data in real-time. The platform can be used for data generated by the user, such as the patient data presented here or using published datasets.

The platform is available athttps://rna-care.mvls.gla.ac.uk/, with its source code athttps://github.com/sii-scRNA-Seq/RNAcare/.
Neural correlates of boundary extension during visual imagination
Authors: Vickery Timothy , Singh Banjit , Levy Alyssa , Sweetman Kallie , Cronin Zoe , Intraub Helene
Published: February 2025

People typically remember seeing a greater expanse of a scene than was visible in a studied close-up (boundary extension, BE). Multivoxel pattern analysis was used to test the neural correlates of BE. Classifiers were trained using a whole-brain searchlight method to discriminate between close-up and wider-angle versions of 16 scenes during repeated perceptual exposures. Earlier, each subject studied either the close or wide version of each scene and then visually imagined it from memory. If a brain region reflects BE, then unlike classification during perception, visual images of close views should sometimes be misclassified as wide (capturing false memory beyond the view), whereas visual images of wide views should be correctly classified. BE-consistent patterns during imagery were found in high-level visual regions, including posterior superior parietal cortex. This pattern did not reflect a brain-wide bias toward better classification of wider-angle views: the pattern reversed (better classification of close views) in the early visual cortex, presenting a novel distinction between early and late visual representations in imagery. We propose that this method reflects active maintenance of boundary-extended scene representations in memory and that it holds promise as a general purpose tool for decoding false memory in the brain.
Genome-wide identification and characterization of QTLs for transcriptional noise in human midbrain cells
Authors: Hirose Naoki , Mizuno Shota , Niwa Yuki , Hara Tomonori , Yamamoto Hirona , Koyama Emiko , Ueda Junko , Tsuboi Takashi , Takata Atsushi
Published: February 2025

Not only the abundance of gene expression but also its cell-to-cell variation, referred to as “transcriptional noise”, is known to have certain biological significance. However, the mechanistic basis of transcriptional noise, particularly how it is regulated by genetic variants, remains elusive. In this study, we analyzed single-cell RNA sequencing (scRNA- seq) data of human induced pluripotent stem cell (iPSC)-derived midbrain cells (795,661 cells in 17 conditions) from 155 individuals with their genotypes to perform genome-wide mapping of quantitative trait loci for transcriptional noise (tnQTLs). Our analyses controlling for confounding factors such as gene expression abundance identified a total of 101,024 significant tnQTL-gene pairs. A comparison with QTLs for expression levels (i.e. eQTLs) detected by an equivalent pipeline revealed that the majority (81%) of tnQTLs were also identified as eQTLs, while no significant eQTL effects were observed in the others, and a small portion (7%) of eQTLs were with significant tnQTL effects. The tnQTLs and eQTLs showed distinctive patterns of sharing across cellular conditions, where tnQTL effects were often more condition-specific than those of eQTLs. In particular, tnQTLs without significant eQTL effects (termed tn>eQTLs) were dramatically altered by rotenone-induced oxidative stress. The tn>eQTLs also exhibited unique patterns of enrichment in various functional genomic elements, such as being frequently observed in promoters of non-QTL target genes. In the analysis using summary statistics from genome-wide association studies (GWAS) for various human complex traits, we found nominally significant enrichment of heritability for schizophrenia in tn>eQTLs. Possible contributions of tn>eQTLs to schizophrenia risk were supported by the enrichment of association signals in their target genes. We also identified genes whose transcriptional noise was implicated to be causally associated with a trait by a Mendelian randomization analysis, includingHLAgenes andYWHAEassociated with multiple autoimmune/psychiatric disorders. To further explore the role of transcriptional noise dysregulation in disease, we analyzed scRNA-seq data from human schizophrenia and mouse model brains. Genes exhibiting differential transcriptional noise between cases and controls, i.e. differentially noisy genes (DNGs), were particularly abundant in the superficial and deep layer excitatory neurons, where association signals in schizophrenia GWAS were also enriched in their DNGs. Overall, our comprehensive mapping of tnQTLs provides a resource for a new class of regulatory genetic variants, deepens our understanding of the mechanistic basis of how genetic variants regulate transcriptional noise, and highlights the roles of tnQTLs and transcriptional noise dysregulation in human complex traits.
Multivalency controls the growth and dynamics of a biomolecular condensate
Authors: von Hofe Julian , Abacousnac Jatin , Chen Mechi , Sasazawa Moeka , Kristiansen Ida Javér , Westrey Soren , Grier David G. , Saurabh Saumya
Published: February 2025

Biomolecular condensates are essential for cellular organization and function, yet understanding how chemical and physical factors govern their formation and dynamics has been limited by a lack of non-invasive measurement techniques. Conventional microscopy methods often rely on fluorescent labeling and sub-strate immobilization, which can perturb the intrinsic properties of condensates. To overcome these challenges, we apply label-free, contact-free holographic video microscopy to study the behavior of a condensate-forming proteinin vitro. This technique enables rapid, high-throughput, and precise measurements of individual condensate diameters and refractive indexes, providing unprecedented insight into size distributions and dense-phase macromolecular concentrations over time. Using this method, we investigate the kinetics of droplet growth, aging, and equilibrium dynamics in the model condensate-forming protein PopZ. By systematically varying the concentration and valence of cations, we uncover how multivalent ions influence condensate organization and dynamics, a hypothesis we further test using super-resolution microscopy. Our findings reveal that PopZ droplet growth deviates from classical models such as Smoluchowski coalescence and Ostwald ripening. Instead, we show that condensate growth is consistent with gelation at the critical overlap concentration. Holographic microscopy offers significant advantages over traditional techniques, such as differential interference contrast (DIC) microscopy, delivering reproducible measurements and capturing condensate dynamics with unparalleled precision. This work highlights the power of holographic microscopy to probe the material properties and mechanistic underpinnings of biomolecular condensates, paving the way for deeper insights into their roles in synthetic systems.
Fine-Mapping of the TMEM106B Locus Reveals Four Haplotypes That are Differentially Associated With Risk for Neurodegeneration
Authors: Salazar Alex , Tesi Niccolò , Knoop Lydian , Pijnenburg Yolande , van der Lee Sven , Wijesekera Sanduni , Krizova Jana , Hiltunen Mikko , Damme Markus , Petrucelli Leonard , Reinders Marcel , Smit August B. , Hulsman Marc ,   ADGC, Bonn, CHARGE, EADB, EADI, FinnGen, GERAD, GR@ACE/DEGESCO, PGC-ALZ, Holstege Henne
Published: February 2025

Genome-wide association studies (GWAS) linkedTMEM106Bvariants to susceptibility for neurodegenerative diseases, but the causal genetic elements remain unclear.

Genotyping of 5,792 Alzheimer disease cases and controls revealed that theTMEM106Blocus consists of four major haplotypes: HA/Ha (covering the coding region), and HB/Hb (covering the upstream regulatory region). These combine into four combinations with varying population-frequencies:HAB(57%),HaB(34%),Hab(9%), andHAb(<1%).

Long-read sequencing of 513 individuals showed thatHAhaplotypes (marked by 185-Threonine) carry unique methylated CpG sites and an AluYb8-retrotransposon in the 3’ UTR, while theHahaplotypes are marked by the 185-Serine allele.Hbhaplotypes carry several structural variants (SVs) in nearby distal enhancers, including a 19 Kbp rearrangement, absent in all other haplotypes.

Joint association models revealed that theHABcombination (AluYb8+185-Threonine) is risk-increasing, whileHab(SVs+185-Serine) confers the protective effect.HaB(185-Serine only) is neutral, whileHAbwas too rare to assess. Indeed, relative to middle-aged non-demented controls, cognitively healthy centenarians were more enriched withHab(OR=1.49, padj=2.18×10-2) than withHaB(OR=1.23, padj=5.06×10-2). Finally, proteomic analysis of temporal cortex tissues (n=182) indicated that relative to the neutralHaBcombination, the protectiveHabis associated with 0.91-fold lower TMEM106B C-terminal peptide abundance (CI=[0.81-1.02]), while the risk-increasingHABis associated with 1.07-fold higher abundance (CI=[0.99-1.15]).

Together, this presents a complex genetic structure underlying the association of theTMEM106Blocus with neurodegenerative diseases.

ONE SENTENCE SUMMARY

GWAS and long-read sequencing suggests that the neurodegenerative genetic etiology associated withTMEM106Bis conferred by multiple independent haplotypes.
A Generalist Intracortical Motor Decoder
Authors: Ye Joel , Rizzoglio Fabio , Smoulder Adam , Mao Hongwei , Ma Xuan , Marino Patrick , Chowdhury Raeed H , Moore Dalton D , Blumenthal Gary , Hockeimer Will , Kunigk Nicolas G. , Mayo J Patrick , Batista Aaron P , Chase Steven M , Rouse Adam G , Boninger Michael L. , Greenspon Charles , Schwartz Andrew B. , Hatsopoulos Nicholas , Miller Lee E , Bouchard Kristofer , Collinger Jennifer , Wehbe Leila , Gaunt Robert
Published: February 2025

Mapping the relationship between neural activity and motor behavior is a central aim of sensorimotor neuroscience and neurotechnology. While most progress to this end has relied on restricting complexity, the advent of foundation models instead proposes integrating a breadth of data as an alternate avenue for broadly advancing downstream modeling. We quantify this premise for motor decoding from intracortical microelectrode data, pretraining an autoregressive Transformer on 2000 hours of neural population spiking activity paired with diverse motor covariates from over 30 monkeys and humans. The resulting model is broadly useful, benefiting decoding on 8 downstream decoding tasks and generalizing to a variety of neural distribution shifts. However, we also highlight that scaling autoregressive Transformers seems unlikely to resolve limitations stemming from sensor variability and output stereotypy in neural datasets. Code: https://github.com/joel99/ndt3
Reliable Monitoring of Respiratory Function with Home Spirometry in People Living with Amyotrophic Lateral Sclerosis
Authors: Peller Julián , Trevisan Marcos A , Bujia Gaston , Aguirre Felipe , Shalom Diego E. , Taitz Alan , Henze Stephanie , Bastola Silviya , Osik Jason , Shewcraft Ryan A. , Jiang Peng , Schwartz Joel , Heiman-Patterson Terry , Sherman Michael E. , Wipperman Matthew F. , Levy Oren , Shou Guofa , Sillay Karl A. , Ostrow Lyle W. , Fraenkel Ernest , Berry James D. , Bingham Indu Navar , Roitberg Esteban G.
Published: February 2025

Monitoring respiratory function is essential for assessing the progression of Amyotrophic Lateral Sclerosis (ALS) and planning interventions. Using spirometry data from the Radcliff Study —a fully remote, longitudinal, exploratory study with a cohort of 67 pALS—we demonstrate that flexible coaching, combined with a quality control analysis that excludes values of ‘0’ and timepoints with failed measurement trials, produces consistent remote spirometry results. Our findings indicate that home-measured Slow Vital Capacity (SVC) and Forced Vital Capacity (FVC) evolve similarly and progress linearly over the study period (7.7 ± 4.0 months). This remains true in both slow and fast progressor subpopulations. This observed linearity in respiratory trajectories supports the potential for early, accurate estimation of progression, reinforcing the feasibility of less frequent monitoring without compromising assessment precision, and reducing the burden on both pALS and the healthcare system. Furthermore, our results align with reported in-clinic pulmonary tests, validating remote monitoring as a means to promote more equitable and accessible clinical trial designs.
Peri-somatic modulation of diffracted light and its variation with consciousness
Authors: Helekar Santosh A.
Published: February 2025

Existing noninvasive neurophysiological recording methods can acquire neuronal correlates of consciousness, but they do not differentiate between conscious and unconscious states mechanistically. Here we describe a method that detects a new physical effect of apparent neural origin in the peri-somatic space that might allow such differentiation. This effect is a slow decrease in the intensity of diffracted low power laser light emitted within a photoelectronic device placed close to the body of an awake subject. It is markedly attenuated by general anesthesia in mice and unconsciousness in patients. Its direction is reversed when the device is exposed to live invertebrates or to the decapitated head of a euthanized mouse. These findings reveal a previously unrecognized biophysical phenomenon that appears to be related to consciousness.
How does the response of egocentric boundary cells depend upon the coordinate system of environmental features?
Authors: Hasselmo Michael E. , LaChance Patrick A. , Robinson Jennifer C. , Malmberg Samantha L. , Patel Mahir , Gross Elaina , Everett Danielle E. , Sankaranarayanan Shruthi , Fang Jiarui
Published: February 2025

Neurons in the retrosplenial (RSC) (Alexander et al., 2020a; LaChance and Hasselmo, 2024) and postrhinal cortex (POR) respond to environmental boundaries and configurations in egocentric coordinates relative to an animals current position. Neurons in these structures and adjacent structures also respond to spatial dimensions of self- motion such as running velocity (Carstensen et al., 2021; Robinson et al., 2024). Data and modeling suggest that these responses could be essential for guiding behaviors such as barrier avoidance and goal finding (Erdem and Hasselmo, 2012; 2014). However, these findings still leave the unanswered question: What are the features and what are the coordinate systems of these features that drive these egocentric neural responses? Here we present models of the potential circuit mechanisms generating egocentric responses in RSC. These can be generated based on coding of internal representations of barriers in head-centered coordinates of distance and angle that are transformed based on current running velocity for trajectory planning and obstacle avoidance. This hypothesis is compared with an alternate potentially complementary hypothesis that neurons in the same regions might respond to retinotopic position of features at the top, bottom or edges of walls as a precursor to head-centered coordinates. Alternate hypotheses include the forward scanning of trajectories (ray tracing) to test for collision with barriers, or the comparison of optic flow on different sides of the animal. These hypotheses generate complementary modeling predictions about how changes in environmental parameters could alter the neural responses of egocentric boundary cells that are presented here.
Exploring the relationship between cultural and structural workforce issues and retention of nurses in general practice (GenRet): A qualitative interview study
Authors: Anderson Helen , Brady Louise , Adamson Joy
Published: February 2025

Background

Increasing shortfalls in nursing workforces are detrimental to safety critical patient care. In general practice in England up to one-in-two nursing posts are predicted to be unfilled by 2030/31, with Wales similarly threatened. This is reflected internationally. Limited attention has been paid to how cultural and structural issues affect retention of nurses in general practice. The aim of our study is to understand factors that challenge retention and support nurses to stay in general practice.

Methods

We conducted an exploratory qualitative interview study with n=41 with members of nursing teams working in, or who have worked in, general practice as well as nurse leaders associated with general practice across England and Wales. Recruitment was through professional and social media networks and snowballing techniques. Data were collected between October 2023-June 2024 and analysed following framework analysis. University of York ethics approval (Ref: HSRGC/2023/586/A) was gained. The study was funded by the General Nursing Council Trust.

Results

Recognition of value of nurses working in general practice was central to the retention of nurses at all levels of practice and was affected by structural and cultural issues and reflected in several themes: The essence of nursing in general practice; The commodification and deprofessionalisation of nursing in general practice; Opportunities for development; Employment of nurses outside of the National Health Service; Lack of voice, precarity of position and lack of recourse; Tipping points.

Conclusion

Cultural and structural issues impacted on retention of nurses in general practice. While some supported retention, others revealed deep-seated, complex issues which require addressing at practice, local and national organisational levels. Nurses in general practice experience factors which leave them vulnerable and underserved. Policy makers, employers and professional organisations need to work to support retention and enable nurses in general practice, not only to survive, but thrive.

Protocol Registration

Open Science Framework (https://osf.io/) Identifier: DOI 10.17605/OSF.IO/2BYXChttps://osf.io/2byxc/
Fair machine learning models for disease prediction: In-depth interviews with key health experts
Authors: Nghiem Nhung , Tiatia Ramona
Published: February 2025

Artificial intelligence (AI) and machine learning (ML) pose enormous potential for improving quality of life. It can also generate significant social, cultural and other unintended risks. We aimed to explore fairness concepts that can be applied in ML models for disease prediction from key health experts’ perspectives in an ethnically diverse high-income country. In-depth interviews with key experts in the health sector in Aotearoa New Zealand (NZ) were implemented between July and December 2022. We invited participants who are key leaders in their ethnic communities, including Māori (Indigenous), Pasifika and Asian. The interview questionnaire comprised six sections: (1) Existing attitudes to healthcare allocation; (2) Existing attitudes to data held at the general practitioner (GP) level; (3) Acceptable data to have at the GP level for disease prediction models; (4) Trade-offs for obtaining benefits vs generating unnecessary concern in deploying these models; (5) Reducing bias in risk prediction models; and (6) Including community consensus into disease prediction models for fair outcomes. The study shows that participants were strongly united in the view that ML models should not create or exacerbate inequities in healthcare due to biased data and unfair algorithms. An exploration of fairness concepts showed that carefully selected data types must be considered for predictive modelling and that trade-offs for obtaining benefits versus generating unnecessary concern produced conflicting opinions. The participants expressed high acceptability for using ML models but expressed deep concerns about inequity issues and how these models might affect the most vulnerable communities (such as Māori in middle-ages and above and those living in deprived communities). Our results could help inform the development of ML models that consider social impacts in an ethnically diverse society.
Machine Learning Based Classification of Aggressive and Malignant Renal Tumors from Multimodal Data
Authors: Aminy Mehrnegar , Gala Tejal , Dasgupta Agnimitra , Cen Steven Y , Pawan S J , Gill Inderbir , Duddalwar Vinay , Oberai Assad A
Published: February 2025

1

Purpose

This study aimed to develop and evaluate a machine learning pipeline using multiphase contrast-enhanced CT images and clinical data to classify renal tumors as benign, malignant-indolent, or malignant-aggressive, while assessing the contribution of each data source to the classification.

Methods

In this retrospective study, 448 patients (mean age: 60.7±12.6 years, 306 male, 142 female) who underwent nephrectomy and preoperative CECT between June 2008 and July 2018 were included. Tumors were histologically categorized as benign-indolent, malignant-indolent, or malignant-aggressive. Self-supervised feature extraction converted 4-phase CECT images into 512 real-valued features, combined with clinical data and tumor size for classification. Two machine learning classifiers, random forest (RF) and multi-layer perceptron (MLP), were used to predict tumor type. Nested five-fold cross-validation was employed for hyperparameter tuning and model evaluation, and performance was assessed using area under the curve (AUC) analysis.

Results

The best-performing models achieved an AUC of 0.90 (95% CI: 0.88–0.93) for classifying indolent versus aggressive tumors and 0.76 (95% CI: 0.71–0.81) for benign versus malignant tumors. Models incorporating tumor size significantly improved classification accuracy. RF classifiers excelled in distinguishing indolent from aggressive tumors, while MLP classifiers performed better for benign versus malignant classification.

Conclusion

The machine learning pipeline demonstrated high accuracy in differentiating aggressive from indolent renal tumors, offering valuable prognostic insights for personalized treatment. Tumor size was a critical factor, complementing CECT images and clinical data. These findings highlight the potential of ML techniques in enhancing renal tumor risk stratification.
Iterative improvement of deep learning models using synthetic regulatory genomics
Authors: Ribeiro-dos-Santos André M. , Maurano Matthew T.
Published: February 2025

Generative deep learning models can accurately reconstruct genome-wide epigenetic tracks from the reference genome sequence alone. But it is unclear what predictive power they have on sequence diverging from the reference, such as disease- and trait-associated variants or engineered sequences. Recent work has applied synthetic regulatory genomics to characterized dozens of deletions, inversions, and rearrangements of DNase I hypersensitive sites (DHSs). Here, we use the state-of-the-art model Enformer to predict DNA accessibility across these engineered sequences when delivered at their endogenous loci. At high level, we observe a good correlation between accessibility predicted by Enformer and experimentally measured values. But model performance was best for sequences that more resembled the reference, such as single deletions or combinations of multiple DHSs. Predictive power was poorer for rearrangements affecting DHS order or orientation. We use these data to fine-tune Enformer, yielding significant reduction in prediction error. We show that this fine-tuning retains strong predictive performance for other tracks. Our results show that current deep learning models perform poorly when presented with novel sequence diverging in certain critical features from their training set. Thus an iterative approach incorporating profiling of synthetic constructs can improve model generalizability, and ultimately enable functional classification of regulatory variants identified by population studies.
Modular architecture confers robustness to damage and facilitates recovery in spiking neural networks modelingin vitroneurons
Authors: Sumi Takuma , Houben Akke Mats , Yamamoto Hideaki , Kato Hideyuki , Katori Yuichi , Soriano Jordi , Hirano-Iwata Ayumi
Published: February 2025

Impaired brain function is restored following injury through dynamic processes that involve synaptic plasticity. This restoration is supported by the brain’s inherent modular organization, which promotes functional separation and redundancy. However, it remains unclear how the modular structure interacts with synaptic plasticity, most notably in the form of spike-timing-dependent plasticity (STDP), to define the damage response and recovery efficiency. In this work, we numerically modeled the response and recovery to damage of a neuronal networkin vitrobearing a modular structure. Consistent with thein vitroobservations, thein siliconumerical model effectively captured the decline and subsequent recovery of spontaneous activity following the injury. We revealed that the modular structure confers robustness to injury, minimizes the decrease in neuronal activity, and promotes recovery via STDP. Finally, using the reservoir computing framework, we show that information representation in the neuronal network improves with the recovery of synchronous activity. Our work provides an experimental-numerical platform for predicting recovery in damaged neuronal networks and may help developing effective models for brain injury.
Cholecystokinin input from the anterior cingulate cortex to the lateral periaqueductal gray mediates nocebo pain behavior in mice
Authors: Poulson Sandra J. , Skvortsova Aleksandrina , Paz Lisiê V. , Cui Wanning , Mandatori Antonietta , Burek Jacob , Zahra Fatama T. , Dinh Anton , Boorman Damien C. , Liang Lianfang , Mogil Jeffrey S. , Martin Loren J.
Published: February 2025

The nocebo effect, the evil twin of the better-known placebo effect in which anticipation of harm causes that harm, is increasingly thought to be responsible for poor clinical outcomes. In humans, nocebo hyperalgesia (i.e., increased sensitivity to pain) is blocked by proglumide, a cholecystokinin (CCK) receptor antagonist. Yet the neural circuitry underlying nocebo hyperalgesia remains unidentified, largely due to lack of appropriate animal models. Independently, our two laboratories developed unique animal models of CCK-dependent nocebo hyperalgesia in which expectation of pain resulted from environmental or social cues. We find that both nocebo paradigms share a neural circuit involving CCK release from neurons projecting from the anterior cingulate cortex to the lateral periaqueductal gray. This pathway, which had not been previously recognized, could represent a promising target for therapeutic interventions in pain-related disorders.

One-Sentence Summary

Pain expectations, whether environmentally conditioned or transmitted socially, share a neural circuit, with cholecystokinin (CCK) projections from the anterior cingulate cortex (ACC) to the lateral periaqueductal gray (PAG) playing a pivotal role.
Health facility support and its influence on weight gain for neonates under Kangaroo Mother Care in Western Kenya
Authors: Mukabi Seline , Morema Everlyne Nyanchera , Kipmerewo Mary , Shisanya Morris Senghor
Published: February 2025

Introduction

Kangaroo Mother Care (KMC) is a recommended cost-effective intervention for low birthweight neonates that promotes neonatal growth, and survival. Its effectiveness is dependent on several factors. This study examines facility factors that influence outcome of KMC in Western Kenya.

Methods

This was a mixed methods study that examined facility support factors influencing KMC outcomes in Western Kenya. A multi-stage sampling approach was used attain the sample size (275). Data collection involved structured questionnaires for caregivers and key informant interviews (KIIs) for healthcare providers. Quantitative data was analyzed using SPSS v26. Binary logistic regression used to determine influence of facility support on KMC neonates weight gain with α = 0.05. Qualitative data from 12 KIIs was thematically analyzed to provide deeper insights into the factors affecting KMC implementation.

Results

The average facility KMC implementation score was 10.78±2.59 out of 19 (56.71%±13.65%). Only 38.18% of neonates achieved the recommended daily weight gain (≥15g/kg). Average daily weight gain was 12.96g±4.85g. The average length of stay on KMC was 36.25±10.09 days, less than the average recommended 41.21±16.02 days for optimal weight gain. Facility-related predictors of achieving ≥15g/kg daily weight gain included the availability of breast pumps (AOR:2.81, P=0.009), milk banks (AOR:3.22, P=0.004), adequate food for mothers (AOR:5.32, P<0.001), seating for mothers (AOR:3.72, P=0.001), dedicated rooms for breast milk expression (AOR:4.77, P<0.001), presence of easily understandable KMC information (AOR:2.86, P=0.007), family-centered KMC support (AOR:2.41, P=0.032), and adequate staffing for KMC (AOR:3.44, P=0.002). The qualitative data showed that nurses played key roles in clinical care, education, research, advocacy, and community engagement for KMC. While formal training improved competency, gaps remained, emphasizing the need for continuous learning..

Conclusions

Facility level support is crucial for maximizing benefits of KMC especially through provision of maternal nutrition, infrastructure support, guaranteeing maternal comfort, family-centered care and adequate staffing.
A genome-wide association study identified 10 novel genomic loci associated with intrinsic capacity
Authors: Beyene Melkamu Bedimo , Visvanathan Renuka , Alemu Robel , Benyamin Beben , Bhattacharjee Rudrarup , Beyene Habtamu B. , Theou Olga , Sumi Yuka , Thiyagarajan Jotheeswaran Amuthavalli , Cesari Matteo , Beard John R. , Amare Azmeraw T.
Published: February 2025

In 2015, the World Health Organization introduced the concept of intrinsic capacity (IC), a composite of all the individual-level attributes that contribute to healthy aging. To investigate the genetic basis of IC, we used data from the UK Biobank (UKB; N=44,631) and the Canadian longitudinal study on aging (CLSA; N=13,085). We estimated SNP-based heritability (h2SNP) at 25.2% in UKB and 19.5% in CLSA. A Genome-Wide Association Study (GWAS) identified 38 independent SNPs for IC across 10 genomic loci and 4,289 candidate SNPs mapped to 197 genes. Post-GWAS analysis revealed the role of these genes on cellular processes such as cell proliferation, immune function, metabolism, and neurodegeneration, with high expressions in muscle, heart, brain, adipose, and tibial nerve tissues. Of the 52 traits tested, 23 showed significant genetic correlations with IC, and a higher genetic loading for IC was associated with higher IC scores. This study is the first to identify genetic variants and pathways associated with IC, providing a foundation for future research on healthy aging.
Vascular amyloidβ load in the meningeal arterial network correlates with loss of cerebral blood flow and pial collateral vessel enlargement in the J20 murine model of Alzheimer’s disease
Authors: Kaloss Alexandra M. , Browning Jack L. , Li Jiangtao , Pan Yuhang , Watsen Sachi , Sontheimer Harald , Theus Michelle H. , Olsen Michelle L.
Published: February 2025

Structured Abstract

INTRODUCTION

Global reduction in cerebral blood flow (CBF) is an early pathology in Alzheimer’s disease, preceding significant plaque accumulation and neurological decline. Chronic reduced CBF and subsequent reduction in tissue oxygenation and glucose may drive neurodegeneration, yet the underlying cause of globally reduced CBF remains unclear.

METHODS

Using premortem delivery of Methoxy-XO4 to label Aβ, and arterial vascular labeling, we assessed Aβ burden on the pial artery/arteriole network and cerebral blood flow in aged male and female WT and J20 AD mice.

RESULTS

The pial artery/arteriole vascular network selectively displayed extensive vascular Aβ burden. Pial collateral arteriole vessels, the by-pass system that reroutes blood flow during occlusion, displayed significant enlargement in J20 mice. Despite this, CBF was decreased by approximately 15% in 12-month J20 mice when compared to WT littermates.

DISCUSSION

Significant Aβ burden on the meningeal arterial network may contribute to the restriction of CBF. Redistribution of CBF through enlarged pial collateral vessels may serve as a compensatory mechanism to alter CBF during disease progression in cases of CAA.
Group personality, rather than acoustic noise, causes variation in group decision-making in guppy shoals
Authors: Clark Molly A. , Waples Ella , Radford Andrew N. , Simpson Stephen D. , Ioannou Christos C.
Published: February 2025

Group living has essential fitness benefits for many species. While numerous studies have explored how environmental conditions impact collective movement, their impact on decisions made in a social context—a central component of group-living—is poorly documented. In this study, we assess how acoustic noise impacts group decision-making, cohesion and activity in fish shoals, using Trinidadian guppies (Poecilia reticulata) as a model species. Movements within a radially symmetric five-armed maze were measured using high-resolution trajectory data from video-tracking software. The behaviour of groups with and without continuous acoustic white noise were measured over a four-day testing period in a repeated-measures design. We found no significant change in swimming speed or group cohesion with additional acoustic noise. However, there was evidence for fewer following events (moves into already occupied arms) in the noise treatment compared to the control, but this additional noise had no effect on leadership attempts (moves into empty arms). We found strong evidence for consistent, repeatable differences between groups in all behavioural parameters indicating strong personality variation at the group level. Rather than environmental factors, these results provide evidence that consistent group-level differences dominate variation in collective behaviour, including group decision-making, in fish shoals.
Atypical plume-like events drive glutamate accumulation in metabolic stress conditions
Authors: Ziebarth Tim , Pape Nils , Nelson Joel S.E. , van Alphen Fleur I.M. , Kalia Manu , Meijer Hil G.E. , Rose Christine R. , Reiner Andreas
Published: February 2025

Neural glutamate homeostasis plays a key role in health and disease. In ischemic conditions, such as stroke, this homeostasis is severely disrupted since energy depletion and ion imbalances lead to more glutamate release and less uptake. We here used the fluorescent glutamate sensor SF-iGluSnFR(A184V) to probe the effects of chemical ischemia on extracellular glutamate dynamicsin situ, using organotypic slice cultures from mouse cortex. SF-iGluSnFR imaging reported spontaneous glutamate release events, which indicate synchronous network activity, similar to calcium signals detected with GCaMP6f. In addition, glutamate imaging revealed local, asynchronous release events, which were atypically large and long-lasting and showed plume-like characteristics. Under baseline conditions plumes occurred with low frequency, were independent of network activity, and persisted in the presence of TTX. Plume induction was strongly favored by blocking glutamate uptake with TFB-TBOA, whereas blocking ionotropic glutamate receptors (iGluRs) suppressed plumes. Upon inducing chemical ischemia plumes became more pronounced and overly abundant, which resulted in large-scale accumulation of extracellular glutamate. Similar plumes were recently also observed in models of cortical spreading depression and migraine. We therefore propose that plumes represent a more general phenomenon induced by glutamate uptake dysfunction, which may contribute to glutamate-related excitotoxicity in various neurodegenerative and neurological disorders.
Phenotypic and Functional Alterations in Peripheral Blood Mononuclear Cell-Derived Microglia in a Primate Model of Chronic Alcohol Consumption
Authors: Hemati Hami , Blanton Madison B. , True Heather E. , Koura Jude , Khadka Rupak , Grant Kathleen A. , Messaoudi Ilhem
Published: February 2025

Alcohol-induced dysregulation of microglial activity is associated with neuroinflammation, cognitive decline, heightened risk for neurodegenerative diseases, alcohol dependence, and escalation of alcohol drinking. Given the challenge of longitudinally sampling primary microglia, we optimized anin vitromethod to differentiate peripheral blood mononuclear cells (PBMC) from non-human primates (NHP) into microglia-like cells (induced-microglia; iMGL). The iMGLs displayed transcriptional profiles distinct from those of monocyte progenitors and closely resembling those of primary microglia. Notably, morphological features showed that differentiated iMGLs derived from NHPs with chronic alcohol consumption (CAC) possessed a more mature-like microglial morphology. Additionally, dysregulation in key inflammatory and regulatory markers alongside increased baseline phagocytic activity was observed in CAC-derived IMGLs in the resting state. Phenotypic and functional assessments following LPS stimulation indicated the presence of an immune-tolerant phenotype and enrichment of a CD86+hyper-inflammatory subpopulation in iMGLs derived from ethanol-exposed animals. Collectively, these findings demonstrate thatin vitrodifferentiation of PBMC offers a minimally invasive approach to studying the impact of CAC on microglial function revealing that CAC reshapes both functional and transcriptional profiles of microglia.
Antagonistic kinesin-14s within a single chromosomal drive haplotype
Authors: Brady Meghan J , Gupta Anjali , Gent Jonathan I , Swentowsky Kyle W , Unckless Robert L , Dawe R. Kelly
Published: February 2025

In maize, there are two meiotic drive systems that operate on large tandem repeat arrays called knobs that are found on chromosome arms. One meiotic drive haplotype, Abnormal chromosome 10 (Ab10), encodes two kinesin proteins that interact with two distinct tandem repeat arrays in a sequence-specific manner to confer meiotic drive. The kinesin KINDR associates with knob180 repeats while the kinesin TRKIN associates with TR-1 repeats. Prior data show that meiotic drive is conferred primarily by the KINDR/knob180 system, with the TRKIN/TR-1 system having little or no role. The second meiotic drive haplotype, K10L2, shows low levels of meiotic drive and only encodes the TRKIN/TR-1 system. Here we used long-read sequencing to assemble the K10L2 haplotype and showed that it has strong homology to an internal portion of the Ab10 haplotype. We also carried out CRISPR mutagenesis ofTrkinto test the role ofTrkinon Ab10 and K10L2. The data indicate that theTrkingene on Ab10 does not improve drive or fitness but instead has a weak deleterious effect when paired with a normal chromosome 10. The deleterious effect is more severe when Ab10 is paired with K10L2: in this context functionalTrkinon either chromosome nearly abolishes Ab10 drive. We modeled the effect ofTrkinon Ab10 and found it should not persist in the population. We conclude thatTrkineither confers an advantage to Ab10 in untested circumstances or that it is in the process of being purged from the Ab10 population.
Discovering Symbolic Cognitive Models from Human and Animal Behavior
Authors: Castro Pablo Samuel , Tomasev Nenad , Anand Ankit , Sharma Navodita , Mohanta Rishika , Dev Aparna , Perlin Kuba , Jain Siddhant , Levin Kyle , Éltető Noémi , Dabney Will , Novikov Alexander , Turner Glenn C , Eckstein Maria K , Daw Nathaniel D , Miller Kevin J , Stachenfeld Kimberly L
Published: February 2025

Symbolic models play a key role in cognitive science, expressing computationally precise hypotheses about how the brain implements a cognitive process. Identifying an appropriate model typically requires a great deal of effort and ingenuity on the part of a human scientist. Here, we adapt FunSearch Romera-Paredes et al. (2024), a recently developed tool that uses Large Language Models (LLMs) in an evolutionary algorithm, to automatically discover symbolic cognitive models that accurately capture human and animal behavior. We consider datasets from three species performing a classic reward-learning task that has been the focus of substantial modeling effort, and find that the discovered programs outperform state-of-the-art cognitive models for each. The discovered programs can readily be interpreted as hypotheses about human and animal cognition, instantiating interpretable symbolic learning and decision-making algorithms. Broadly, these results demonstrate the viability of using LLM-powered program synthesis to propose novel scientific hypotheses regarding mechanisms of human and animal cognition.
Neutron crystallography of the covalent intermediate of β-glucosidase reveals remodeling of the catalytic center
Authors: Yano Naomine , Arakawa Hiromu , Lin Chih-Chieh , Ishiwata Akihiro , Tanaka Katsunori , Kusaka Katsuhiro , Fushinobu Shinya
Published: February 2025

Anomer-retaining glycoside hydrolases (GHs) generally catalyze a double displacement reaction via a covalent intermediate; however, neutron crystallography of glycoside ligand-bound states has not been performed. In this study, we investigated β-glucosidase Td2F2 from GH family 1 as a model enzyme for anomer-retaining GHs. We determined joint X-ray/neutron structures of Td2F2 in ligand-free form, covalent intermediate with a 2-deoxy-2-fluoro glucoside (2F-Glc) inhibitor, and glucose product complex using hydrogen/deuterium-exchanged crystals at room temperature, with neutron diffraction resolutions of 1.80-1.70 Å. Extensive hydrogen bonds recognizing the hydroxy groups of 2F-Glc were identified, along with the positions of deuterium atoms. The acid/base catalyst residue Glu166 was anchored by a hydrogen bond network pivoted by Asn293. Tyr295 forms a hydrogen bond with the catalytic nucleophile residue Glu352 in the ligand-free and glucose complex forms, while the active center undergoes significant reorganization, including side chain displacements of Glu352 and Tyr295, as well as the incorporation of a water molecule. An alternative conformation of Tyr295 was observed in the 2F-Glc structure at room temperature, suggesting its role in positioning the nucleophilic water during the deglycosylation step. The tyrosine hydrogen bonded to the nucleophile is also conserved in many other anomer-retaining GH families, underscoring its importance in catalysis. Based on the deuterium/hydrogen positions determined from neutron structures, we proposed a detailed reaction mechanism for Td2F2.
Myelination across cortical hierarchies and depths in humans and macaques
Authors: Nishio Monami , Liu Xingyu , Mackey Allyson P. , Arcaro Michael J.
Published: February 2025

Myelination is fundamental to brain function, enabling rapid neural communication and supporting neuroplasticity throughout the lifespan. While hierarchical patterns of myelin maturation across the cortical surface are well-documented in humans, it remains unclear which features reflect evolutionarily conserved developmental processes versus human-characteristic adaptations. Moreover, the laminar development of myelin across the primate cortical surface, which shapes hierarchies and supports functions ranging from sensory integration to network communication, has been largely unexplored. Using neuroimaging to measure the T1-weighted/T2-weighted ratio in tissue contrast as a proxy for myelin content, we systematically compared depth-dependent trajectories of myelination across the cortical surface in humans and macaques. We identified a conserved “inside-out” pattern, with deeper layers exhibiting steeper increases in myelination and earlier plateaus than superficial layers. This depth-dependent organization followed a hierarchical gradient across the cortical surface, progressing from early maturation in sensorimotor regions to prolonged development in association areas. Humans exhibited a markedly extended timeline of myelination across both cortical regions and depths compared to macaques, allowing for prolonged postnatal plasticity across the entire cortical hierarchy — from sensory and motor processing to higher-order association networks. This extended potential for plasticity may facilitate the shaping of cortical circuits through postnatal experience in ways that support human-characteristic perceptual and cognitive capabilities.