bluuebunny/crossref_metadata_2025_split huggingface dataset:
Characterization of isolated human astrocytes from aging brain
Authors: Serrano Geidy E. , Aslam Sidra , Walker Jessica E. , Piras Ignazio S. , Huentelman Matthew J. , Arce Richard A. , Glass Michael J. , Intorcia Anthony J. , Suszczewicz Katsuko E. , Borja Claryssa I. , Cline Madison P. , Qiji Sanaria H , Lorenzini Ileana , Beh Suet Theng , Mariner Monica , Krupp Addison , McHattie Rylee , Shull Anissa , Wermager Zekiel R , Beach Thomas G. 
Published: February 2025

ABSTRACTAstrocytes have multiple crucial roles, including maintaining brain homeostasis and synaptic function, performing phagocytic clearance and responding to injury and repair. It has been suggested that astrocyte performance is progressively impaired with aging, leading to imbalances in the brain’s internal milieu that eventually impact neuronal function and leads to neurodegeneration. Until now most of the evidence of astrocytic dysfunction in aging has come from experiments done with whole tissue homogenates, astrocytes collected by laser capture or cell cultures derived from animal models or cell lines. In this study we used postmortem-derived whole cells sorted with anti-GFAP antibodies to compare the unbiased, whole-transcriptomes of human astrocytes from control, older non-impaired individuals and subjects with different neurodegenerative diseases such as Parkinson’s disease (PD), Alzheimer’s disease (ADD) and progressive supranuclear palsy (PSP). We found hundreds of dysregulated genes between disease and control astrocytes. In addition, we identified numerous genes shared between these common neurodegenerative disorders that are similarly dysregulated; in particular, UBC a gene for ubiquitin, which is a protein integral to cellular homeostasis and critically important in regulating function and outcomes of proteins under cellular stress, was upregulated in PSP, PD, and ADD when compared to control.
BarQC: Quality Control and Preprocessing for SPLiT-Seq Data
Authors: Rossello Maria , Tandonnet Sophie , Almudi Isabel 
Published: February 2025

AbstractSummarySPLiT-seq is a cost-effective single-cell RNA-sequencing method, easy to implement in most laboratories. However, the data preprocessing is not straightforward, and no solution currently exists to perform a basic quality control of the data. Here, we present BarQC, a quality control tool, which identifies and corrects barcodes in SPLiT-seq data and provides a report on the distribution of each barcode and UMI as well as an estimation of the number of cells present in the data. Additionally, BarQC can be incorporated in the preprocessing pipeline by constructing a sorted BAM file tagged with each barcode sequence.Availability of ImplementationBarQC was implemented in Python3, and its source code is freely available on GitHub athttps://github.com/mayflylab/barQC/under the MIT Licence. BarQC has been tested on a Linux server.
A wireless, 60-channel, AI-enabled neurostimulation platform
Authors: Rizzuto Daniel S. , Hu Zhe , Utin Daniel , Kahn Joshua , Ho Chris , Smiles Andrew , Gross Robert E. , Lega Bradley C. , Das Sandhitsu R. , Kahana Michael J. 
Published: February 2025

AbstractElectrical stimulation of the human brain has emerged as a powerful therapeutic modality, enabling the alteration of neural circuits underlying cognition and behavior. Recent evidence indicates that stimulation’s effects on physiology and behavior depend on endogenous variation in brain state, as measured by field-potential recordings. Here, we describe a 60-channel brain-computer interface – the Smart Neurostimulation System (SNS) – that combines closed-loop analysis of spectral features of the field potential with multi-channel stimulation capabilities. We demonstrate system functionality via bench tests and from anin vivoovine study exercising a subset of the device’s functionality. Our ovine study shows that the SNS can reliably measure neural correlates of behavior (motion) and the physiological effects of stimulation. We demonstrate the safety of stimulation via histology following a 120-day stimulation study.
A single low-dimensional neural component of motor unit activity explains force generation across repetitive isometric tasks
Authors: Cabral Hélio V. , Inglis J. Greig , Pourreza Elmira , Dos Santos Milena A. , Cosentino Caterina , O’Reilly David , Delis Ioannis , Negro Francesco 
Published: February 2025

AbstractPrevious studies suggest that low-dimensional control underlies motor unit activity, with low-frequency oscillations in common synaptic inputs serving as the primary determinant of muscle force production. In this study, we used principal component analysis (PCA) and factor analysis (FA) to investigate the relationship between low-dimensional motor unit components and force oscillations during repetitive isometric tasks with similar force profiles. We assessed the consistency of these components across trials in both individual (tibialis anterior; first dorsal interosseous) and synergistic muscles (vastus medialis, VM; vastus lateralis, VL). Participants performed 15 trials of a force-matching learning task. Three post-skill acquisition trials were selected for analysis to ensure high similarity in force profiles. Motor units were decomposed from high-density surface electromyograms, tracked across trials, and their smoothed discharge rates were decomposed into low-dimensional components using PCA and FA. Parallel analysis indicated that a single component could explain the smoothed discharge rates for the individual muscles and two components for VM-VL. Importantly, the first component explained most of the variance (∼70%) in smoothed discharge rates across all muscles. The first motor unit component also showed significantly higher correlations with force oscillations than the second component and remained highly consistent across trials. These findings were further supported by a non-linear framework combining network- and information-theoretic tools, which revealed high motor unit network density in the first component of all muscles. Collectively, these results suggest that, during isometric contractions, motor unit activity is primarily controlled by a single dominant shared synaptic input that closely mirrors force oscillations.
Protocol of the study for Setting up of a system for “Medical Certification of Cause of Death” for non-institutional deaths in a selected area of a Taluk of Kolar district, Karnataka, India: feasibility and validity
Authors: Madhusudan M , Sukanya R , Vaitheeswaran K 
Published: February 2025

AbstractRationaleThe current coverage of “Medical Certification of Cause of Death” in India is only 22.5%. This is largely due to significant proportion of deaths occurring outside the hospitals (non-institutional deaths). The “cause of death” in such cases is unlikely to be certified by any doctor. The present study attempts to address this gap by developing a system of MCCD for “non-institutional deaths” in the country.NoveltyThis is a first of its kind study attempting to address the gap of coverage as well as reliability of MCCD for “non-institutional deaths”.ObjectivesTo assess the feasibility of “Physician derived Cause of death” approach for deducing “cause of death” in “non-institutional deaths” in a selected area of Kolar Taluk, Karnataka and to validate this approachMethodsDoctors of selected major hospitals in Kolar taluk and PHC medical officers and private practitioners of 2 selected PHC areas of the taluk would be trained in arriving at “Cause of Death” in “non-institutional deaths” using the “PhyCoD” tool. The “cause of death” deduced by this approach would be validated against the ‘gold standard’ autopsy wherever possible. The approach will also be tested for “inter-rater reliability”.Expected outcomeDevelopment of a tool for physicians for deducing “Cause of Death” in “non-institutional deaths”Increased coverage of MCCD for “non-institutional deaths”Improved accuracy in the reporting of “cause of death” for “non-institutional deaths”Reduced delay in the reporting of “cause of death” for “non-institutional deaths”
Assessment of trends and determinants of under-five mortality among children born to older women: Evidence from Ethiopian Demographic and Health Surveys
Authors: Temesegen Tamerat Denekew , Demissie Tariku Dejene , Damtew Solomon Abrha 
Published: February 2025

AbstractIntroductionMortality has long been used as an indicator of the level of socio-economic development of a country. Global attention has been drawn to under-five mortality through the Sustainable Development Goals (SDGs). The burden of under-five mortality of children is still not fairly divided. Two regions account for around 80% of under-five deaths among children: sub-Saharan Africa and South Asia. Ethiopia is one of six nations that account for half of the world’s under-five mortality.MethodsThe Ethiopia Demographic and Health Survey (EDHS) from the years 2000, 2005, 2011, and 2016 provided nationally representative cross-sectional data. Six thousand one hundred nighty nine (6,199) children born to older women within the five years prior to the study formed the data. Home interviews were used to gather demographic data, such as mother and child characteristics, socioeconomic factors, and environmental variables. Frequencies were computed to characterize the study participants Multiple-level binary regression analysis was utilized to get the Adjusted Odds Ratio (AOR) and its 95% confidence interval (CI).ResultThe absolute number of under five deaths is 128/1000 live births in the year 2000 which reduce to 56/1000 live births in 2016. This study identified factors contributing for under-five mortality among children of women aged 35 to 49 years old. Sex of the child (female_ 0.65 (0.53, 0.79)), late age at first birth, 31 to 4o years at first birth 0.34 (0.11, 0.98), family size, having a family size of 6 to 10 0.18 (0.14, 0.24), longer birth interval, greater than 3 years 0.35 (0.26, 0.47) and ANC visits 1 to 3 ANC vests 0.65 (0.5, 0.84) lowered the odds of under-five mortality among children of relatively elders. On the other hand, Women aged 35 to 49 years who gave a twin Birth 6.15 (3.94, 9.6)), those with number of births in the last five years having 4 children (2.64 (1.15, 6.06)), those with number of children ever born, having 9 or above children 3.79 (2.1, 6.84), those who gave birth at late age the index child, mother gave birth of the index child at late age (45 to 49) 2.13 (1.55, 2.93) had higher odds for their children experiencing child death before they celebrated their fifth birthday.ConclusionThe absolute number of under five deaths of older women is 128/1000 live births in the year 2000 which reduce to 56/1000 live births in 2016.Female children, children born from first from elder mothers, those children residing am family with large size, children born with longer birth interval and children for whom their mothers received ANC visits were found to Have lower odds of mortality.
ISME - Incoherent Sampling of Multi-Echo data to minimize cardiac-induced noise in brain maps of R2* and magnetic susceptibility
Authors: Raynaud Quentin , Oliveira Rita , Corbin Nadège , Balbastre Yaël , van Heeswijk Ruud B. , Lutti Antoine 
Published: February 2025

AbstractPurposeBrain maps of the MRI parameters R2* and magnetic susceptibility (χ) enable the investigation of microscopic tissue changes associated with brain disease in patient populations. However, maps of R2* andχare computed from gradient-echo data acquired at multiple echo times and are affected by cardiac-induced physiological noise. In this study, we introduce ISME – a sampling strategy that minimizes the level of cardiac-induced noise in brain maps of R2* andχ.MethodsCardiac-induced noise causes exponential-like effects on the decay of the signal magnitude that vary across the cardiac cycle, increasing the variability of R2* andχestimates. ISME uses phase-encoding gradients to shift the k-space frequency of the acquired data between consecutive readouts of a multi-echo train. As a result, the multi-echo data at a given k-space index is acquired at different phases of the cardiac cycle. We compare the variability of R2* andχmaps acquired with ISME and with standard multi-echo trajectories in N=10 healthy volunteers. We also investigate the effect of both sampling strategies on the spatial aliasing of pulsating MR signals in R2* andχmaps and propose a weighted-least square (NWLS) approach for the estimation of R2* that accounts for the increase in cardiac-induced noise with echo time.ResultsCompared to standard multi-echo trajectories, ISME reduces the variability of R2* andχacross repetitions by 25/26/21% and 24/32/23% in the cerebellum/brainstem/whole brain, respectively. With ISME, the spatial aliasing of pulsating MR signals is incoherent between raw echo images, leading to visually sharper R2* maps. The proposed NWLS approach for the estimation of R2* removes the dependence of the fitting residuals on echo time and brings an additional 3/2/1% reduction of the R2* variability in the cerebellum/brainstem/whole brain.ConclusionISME allows the mitigation of cardiac-induced noise in brain maps of R2* andχ, improving reproducibility.
Age-related differences in the association between REM sleep and the polygenic risk for Parkinson’s disease
Authors: Talwar Puneet , Mortazavi N. , Koshmanova Ekaterina , Muto Vincenzo , Degueldre Christian , Berthomier Christian , Collette Fabienne , Bastin Christine , Phillips Christophe , Maquet Pierre , Mikhail Zubkov , Vandewalle Gilles 
Published: February 2025

AbstractObjectiveParkinson’s disease (PD) is one of the rare diseases for which sleep alteration is a true marker of disease outcome. Yet, how the association between sleep and PD emerges over the healthy lifetime is not established. We examined association between polygenic risk score (PRS) for PD and the variability in the electrophysiology of Rapid Eye Movement (REM) sleep in 345 younger (18-31y) and 85 older (50-69y) healthy individuals.MethodsIn this prospective cross-sectional study, in-lab EEG recordings of sleep were recorded to extract REM sleep metrics. PRS was computed using SBayesR approach.ResultsGeneralized Additive Model for Location, Scale and Shape (GAMLSS) analysis showed significant association of REM duration (pcorr=0.002)and theta energy in REM (pcorr=0.0002) with PRS for PD in interaction with age group. In the younger sub-sample, REM duration and theta energy were positively associated with PD PRS. In contrast, in the older sub-sample, the same associations were negative (though only qualitatively for REM theta energy) and may differ between men and women.InterpretationREM sleep is associated with the PRS for PD in early adulthood, 2 to 5 decades prior to typical symptoms onset. The association switches from positive in younger individuals, presumably free of alpha-synuclein, to negative in older individuals, possibly because of the progressive presence of alpha-synuclein aggregates or of the repeated increased oxidative metabolism imposed by REM sleep. Our findings may unravel core associations between PD and sleep and may contribute to novel intervention targets to prevent or delay PD.
A Mean-Field Approach to Criticality in Spiking Neural Networks for Reservoir Computing
Authors: Freddi Ruggero , Cicala Francesco , Marzetti Laura , Basti Alessio 
Published: February 2025

AbstractReservoir computing is a neural network paradigm for processing temporal data by exploiting the dynamics of a fixed, high-dimensional system, enabling efficient computation with reduced complexity compared to fully trainable recurrent networks. This work presents an analytical framework for configuring in the critical regime a reservoir based on spiking neural networks with a highly general topology. Specifically, we derive and solve a mean-field equation that governs the evolution of the average membrane potential in leaky integrate-and-fire neurons, and provide an approximation for the critical point. This framework reduces the need for an extensive online fine-tuning, offering a streamlined path to near-optimal network performance from the outset. Through extensive simulations, we validate the theoretical predictions by analyzing the network’s spiking dynamics and quantifying its computational capacity using the information-based Lempel-Ziv-Welch complexity near criticality. Finally, we explore self-organized quasi-criticality by implementing a local learning rule for synaptic weights, demonstrating that the network’s dynamics remain close to the theoretical critical point. Beyond AI, our approach and findings also have significant implications for computational neuroscience, providing a principled framework for quantitatively understanding how biological networks leverage criticality for efficient information processing.
Neural responses in early, but not late, visual cortex are well predicted by random-weight CNNs with sufficient model complexity
Authors: Farahat Amr , Vinck Martin 
Published: February 2025

ABSTRACTConvolutional neural networks (CNNs) were inspired by the organization of the primate visual system, and in turn have become effective models of the visual cortex, allowing for accurate predictions of neural stimulus responses. While training CNNs on brain-relevant object-recognition tasks may be an important pre-requisite to predict brain activity, the CNN’s brain-like architecture alone may already allow for accurate prediction of neural activity. Here, we evaluated the performance of both task-optimized and brain-optimized convolutional neural networks (CNNs) in predicting neural responses across visual cortex, and performed systematic architectural manipulations and comparisons between trained and untrained feature extractors to reveal key structural components influencing model performance. For human and monkey area V1, random-weight CNNs employing the ReLU activation function, combined with either average or max pooling, significantly outperformed other activation functions. Random-weight CNNs matched their trained counterparts in predicting V1 responses. The extent to which V1 responses can be predicted correlated strongly with the neural network’s complexity, which reflects the non-linearity of neural activation functions and pooling operations. However, this correlation between encoding performance and complexity was significantly weaker for higher visual areas that are classically associated with object recognition, such as monkey IT. To test whether this difference between visual areas reflects functional differences, we trained neural network models on both texture discrimination and object recognition tasks. Consistent with our hypothesis, model complexity correlated more strongly with performance on texture discrimination than object recognition. Our findings indicate that random-weight CNNs with sufficient model complexity allow for comparable prediction of V1 activity as trained CNNs, while higher visual areas require precise weight configurations acquired through training via gradient descent.
Generation ofC9orf72h370mice, an intron 1 humanisedC9orf72repeat-expansion knock-in model
Authors: Nair Remya R , Carcolé Mireia , Thompson David , Tibbit Charlotte , McLeod Ross , Cammack Alexander , Jakubcova Tatiana , Biggs Daniel , Wyles Matthew , Parker Matthew , Caulder Adam , Teboul Lydia , Fisher-Ward Chloe L , Awan Ali R , Flower Michael , Davies Benjamin , Isaacs Adrian M , Fisher Elizabeth MC , Cunningham Thomas J 
Published: February 2025

AbstractAn autosomal dominant GGGGCC repeat expansion in intron 1 of theC9orf72gene is the most common genetic cause of both amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here, we set out to engineer a gene targeted mouse model harbouring a pathogenic length humanisedC9orf72repeat expansion allele, in order to model pathological mechanisms in a physiological context. In human disease, pathogenic repeats typically range from the hundreds to thousands of units in length, representing a considerable challenge for cellular and in vivo model generation given the instability of GC rich and repetitive DNA sequences during molecular cloning. To overcome this challenge, we developed new methodology to synthetically and iteratively build pure GGGGCC repeats within a linear vector system, which we then seamlessly and scarlessly embedded within the native human genomic sequence. This created a gene targeting DNA vector for homologous recombination of the human sequence in mouse embryonic stem cells. We used this novel targeting vector to generate a new gene targeted mouse allele,C9orf72h370, that for the first time has mouseC9orf72intron 1 scarlessly replaced with human intron 1 including a pure (GGGGCC)370hexanucleotide repeat expansion. We confirm that the mouse model expresses human intron 1-derived RNA and produces dipeptide repeat proteins derived from the GGGGCC repeat expansion. We now provide this model as a new freely available resource for the field. In addition, we demonstrate the utility of our cloning method for engineering diverse repeat expansion sequences for modelling other disorders, such as Fragile X Syndrome.
Verapamil and its metabolite norverapamil inhibit theMycobacterium tuberculosisMmpS5L5 efflux pump to potentiate the activity bedaquiline and other antitubercular drugs
Authors: Fountain Adam J , Waller Natalie JE , Cheung Chen-Yi , Jowsey William , Chrisp Michael T , Troll Mark , Edelstein Paul H , Cook Gregory M , McNeil Matthew B , Ramakrishnan Lalita 
Published: February 2025

AbstractBedaquiline is the cornerstone of a new regimen for the treatment of drug-resistant tuberculosis. However, its clinical use is threatened by the emergence of bedaquiline-resistant strains ofMycobacterium tuberculosis. Bedaquiline targets mycobacterial ATP synthase but the predominant route to clinical bedaquiline resistance is via upregulation of the MmpS5L5 efflux pump due to mutations that inactivate the transcriptional repressor Rv0678. Here, we show that the MmpS5L5 efflux pump reduces susceptibility to bedaquiline as well as its new, more potent derivative TBAJ-876 and other antimicrobial substrates, including clofazimine and the DprE1 inhibitors PBTZ-169 and OPC-167832. Furthermore, the increased resistance of Rv0678 mutants stems entirely from increased MmpS5L5 activity. These results highlight the potential of a pharmacological MmpS5L5 inhibitor to increase drug efficacy. Verapamil, primarily used as a calcium channel inhibitor, is known to inhibit diverse efflux pumps and to potentiate bedaquiline and clofazimine activity inM. tuberculosis. Here, we show that verapamil potentiates the activity of multiple diverse MmpS5L5 substrates. Using biochemical approaches, we demonstrate that verapamil does not exert this effect by acting as a disruptor of the protonmotive force used to power MmpS5L5, as previously proposed, suggesting that verapamil inhibits the function of the MmpS5L5 pump. Finally, norverapamil, the major verapamil metabolite, which has greatly reduced calcium channel activity, has equal potency in reducing resistance to MmpS5L5 substrates. Our findings highlight verapamil’s potential for enhancing bedaquiline TB treatment, for preventing acquired resistance to bedaquiline and other MmpS5L5 substrates, while also providing the impetus to identify additional MmpS5L5 inhibitors.Significance StatementBedaquiline, an antitubercular drug targeting ATP synthase, forms the backbone of highly efficacious treatment regimens for drug-resistant tuberculosis. Bedaquiline resistance is emerging as a significant problem and is most commonly caused by mutations in Rv0678 that result in upregulation of the MmpS5L5 efflux pump. Here we define the contribution of the MmpS5L5 efflux pump to drug resistance in wild-type and Rv0678 mutant strains and show that the commonly used drug verapamil can inhibit MmpS5L5 activity. This suggests that this safe and inexpensive drug may be useful in enhancing bedaquiline treatment of TB and to help prevent bedaquiline acquired resistance.