bluuebunny/crossref_metadata_2025_split huggingface dataset:
Extracellular vesicles-based point-of-care testing for the diagnosis and monitoring of Alzheimer’s disease
Authors: Li Xiang , Chen Jie , Yang Yang , Cai Hongwei , Ao Zheng , Xing Yantao , Li Kangle , Yang Kaiyuan , Wallace Abigail , Friend James , Lee Luke P. , Wang Nian , Guo Feng 
Published: April 2024

AbstractAlzheimer’s disease (AD) is a debilitating condition that affects millions of people worldwide. One promising strategy for detecting and monitoring AD early on is using extracellular vesicles (EVs)-based point-of-care testing; however, diagnosing AD using EVs poses a challenge due to the low abundance of EV-biomarkers. Here, we present a fully integrated organic electrochemical transistor (OECT) that enables high accuracy, speed, and convenience in the detection of EVs from AD patients. We incorporated self-aligned acoustoelectric enhancement of EVs on a chip that rapidly propels, enriches, and specifically binds EVs to the OECT detection area. With our enhancement of pre-concentration, we increased the sensitivity to a limit of detection of 500 EV particles/μL and reduced the required detection time to just two minutes. We also tested the sensor on an AD mouse model to monitor AD progression, examined mouse Aβ EVs at different time courses, and compared them with intraneuronal Aβ cumulation using MRI. This innovative technology has the potential to diagnose Alzheimer’s and other neurodegenerative diseases accurately and quickly, enabling monitoring of disease progression and treatment response.
Comparison of three sequencing methods for identifying and quantifying antibiotic resistance genes (ARGs) in sewage
Authors: Mondhe Divya , Ishtiaq Farah 
Published: April 2024

AbstractBackgroundGlobally, antimicrobial resistance (AMR) poses a critical threat, requiring robust surveillance methodologies to tackle the growing challenge of drug-resistant microbes. AMR is a huge challenge in India due to high disease burden, lack of etiology-based diagnostic tests and over the counter availability of antibiotics and inadequate treatment of wastewaters are important drivers of AMR in India. There is lack of effective surveillance platforms that monitor health-associated infections. This include developing an understanding on background levels of AMR in the environment and comparison of AMR monitoring methods.ObjectivesThis study evaluated the performance of three AMR sequencing methods, Illumina AmpliSeq AMR panel, QIAseq xHYB AMR panel and shotgun sequencing method for the detection of antimicrobial resistance genes (ARGs) in urban sewage. Our goal is to provide insights into the application and robustness of each sequencing method.MethodsWe compare the prevalence, diversity, and composition of ARGs across sequencing method and by sample type (inlet vs outlet) in four sewage treatment plants (STP).ResultsRegardless of the sequencing method used the dominant ARGs remained consistent, and their differential analysis showed consistent trends in detection of epidemiologically relevant ARGs. The cost-effectiveness analysis revealed comparable per-sample costs, with amplicon-based sequencing offering specificity for targeted genes, and shotgun sequencing uses a whole-genome sequencing approach that provides high-resolution taxonomic information for the characterisation of pathogens. This methodology can only detect ARGs that have been annotated in the reference database (e.g., CARD). Therefore, some novel types of ARGs present in the samples may be missed since the analysis is based on a similarity search. Differential abundance analysis to understand change in abundance in dominant ARGs from inlet to outlet of STP showed consistent trends across methods. However, with caution raised regarding potential artifacts introduced by enrichment steps in QIAseq xHYB AMR panel.ConclusionThe choice of panel used would be governed by the context of the study. Nonetheless, our exploratory study shows that the data gathered using different sequencing pipelines helps in quantifying the ARG burden in the environment. This information is crucial in understanding the spatio-temporal distribution of ARGs in different environment and could help in developing PCR-based approaches for targeted surveillance.
Inferring gene regulatory networks by hypergraph variational autoencoder
Authors: Su Guangxin , Wang Hanchen , Zhang Ying , Coster Adelle CF , Wilkins Marc R. , Canete Pablo F. , Yu Di , Yang Yang , Zhang Wenjie 
Published: April 2024

AbstractIn constructing Gene Regulatory Networks (GRNs), it is crucial to consider cellular heterogeneity and differential gene regulatory modules. However, traditional methods have predominantly focused on cellular heterogeneity, approaching the subject from a relatively narrow scope. We present HyperG-VAE, a Bayesian deep generative model that utilizes a hypergraph to model single-cell RNA sequencing (scRNA-seq) data. HyperG-VAE employs a cell encoder with a Structural Equation Model to address cellular heterogeneity and build GRNs, alongside a gene encoder using hypergraph self-attention to identify gene modules. Encoders are synergistically optimized by a decoder, enabling HyperG-VAE to excel in GRN inference, single-cell clustering, and data visualization, evidenced by benchmarks. Additionally, HyperG-VAE effectively reveals gene regulation patterns and shows robustness in varied downstream analyses, demonstrated using B cell development data in bone marrow. The interplay of encoders by the overlapping genes between predicted GRNs and gene modules is further validated by gene set enrichment analysis, underscoring that the gene encoder boosts the GRN inference. HyperG-VAE proves efficient in scRNA-seq data analysis and GRN inference.
Biotic challenges in the city: Dietary restrictions and body fat content of female sexuals in urban ant populations
Authors: Trigos-Peral Gema , Witek Magdalena , Csata Enikő , Chudzik Paulina , Heinze Jürgen 
Published: April 2024

AbstractUrban habitats represent an important challenge for many organisms. Besides the abiotic changes, urban habitats are also characterized by changes in the biotic conditions, such as a more uniform species composition and declining population sizes. For urban ants this can result in dietary shortages. In our study, we tested whether urban ant colonies might suffer from dietary restrictions by carrying out a common garden experiment in which ant colonies from urban and rural habitats were exposed to high carbohydrate, protein, and fat / protein diets. We also investigated the body fat content of individuals from both habitat types. Our findings suggest a lower availability of high-quality carbohydrates in urban areas. Additionally, while not statistically significant, rural colonies exhibited a tendency to consume greater quantities of proteins and fat compared to urban colonies. This trend was in line with a higher body fat content observed in female sexuals (gynes) from rural colonies. These results might indicate the outcome of an evolutionary feedback process in which ant colonies adapt to nutritional constraints in urban environments. They achieve this by minimizing the investment in gynes, which might require fewer reserves for survival during colony foundation due to reduced competition for nesting sites within urban green spaces.
Dynamic population coding of social novelty in the insular cortex
Authors: Sato Masaaki , Overton Eric T. N. , Fujima Shuhei , Takumi Toru 
Published: April 2024

AbstractThe familiarity of socially interacting peers has a profound impact on behavior1–3, but little is known about the neuronal representations distinguishing familiar from novel conspecifics. The insular cortex (IC) regulates social behavior4–9, and our previous study revealed that neurons in the agranular IC (aIC) encode ongoing social interactions10. To elucidate how these neurons discriminate between interactions with familiar and novel conspecifics, we monitored neuronal activity in mice by microendoscopic calcium imaging during social recognition memory (SRM) and linear chamber social discrimination (LCSD) tasks. In the SRM task, repeated interactions with the same target activated largely nonoverlapping cells during each session. The fraction of cells associated with social investigation (social cells) decreased as the subject repeatedly interacted with the same target, whereas substitution of a second novel target and subsequent exchange with the first familiar target recruited more new social cells. In the LCSD task, the addition of a novel target to an area containing a familiar target transiently increased the number of cells responding to both targets, followed by an eventual increase in the number of cells responding to the novel target. These results support the view that the aIC dynamically encodes social novelty, rather than consistently encode social identity, by rapidly reorganizing the neural representations of conspecific information.
Computational Mechanisms of Neuroimaging Biomarkers Uncovered by Multicenter Resting-State fMRI Connectivity Variation Profile
Authors: Yamashita Okito , Yamashita Ayumu , Takahara Yuji , Sakai Yuki , Okamoto Yasumasa , Okada Go , Takamura Masahiro , Nakamura Motoaki , Itahashi Takashi , Hanakawa Takashi , Togo Hiroki , Yoshihara Yujiro , Murai Toshiya , Okada Tomohisa , Narumoto Jin , Takahashi Hidehiko , Takagishi Haruto , Hosomi Koichi , Kasai Kiyoto , Okada Naohiro , Abe Osamu , Imamizu Hiroshi , Hayashi Takuya , Koike Shinsuke , Tanaka Saori C. , Kawato Mitsuo ,   Brain/MINDS Beyond Human Brain MRI Group
Published: April 2024

AbstractResting-state functional connectivity (rsFC) is increasingly used to develop biomarkers for psychiatric disorders. Despite progress, development of the reliable and practical FC biomarker remains an unmet goal, particularly one that is clinically predictive at the individual level with generalizability, robustness, and accuracy. In this study, we propose a new approach to profile each connectivity from diverse perspective, encompassing not only disorder-related differences but also disorder-unrelated variations attributed to individual difference, within-subject across-runs, imaging protocol, and scanner factors. By leveraging over 1500 runs of 10-minute resting-state data from 84 traveling-subjects across 29 sites and 900 participants of the case-control study with three psychiatric disorders, the disorder-related and disorder-unrelated FC variations were estimated for each individual FC. Using the FC profile information, we evaluated the effects of the disorder-related and disorder-unrelated variations on the output of the multi-connectivity biomarker trained with ensemble sparse classifiers and generalizable to the multicenter data. Our analysis revealed hierarchical variations in individual functional connectivity, ranging from within-subject across-run variations, individual differences, disease effects, inter-scanner discrepancies, and protocol differences, which were drastically inverted by the sparse machine-learning algorithm. We found this inversion mainly attributed to suppression of both individual difference and within-subject across-runs variations relative to the disorder-related difference by weighted-averaging of the selected FCs and ensemble computing. This comprehensive approach will provide an analytical tool to delineate future directions for developing reliable individual-level biomarkers.
Fur microbiome as a putative source of symbiotic bacteria in sucking lice
Authors: Říhová Jana Martin , Gupta Shruti , Nováková Eva , Hypša Václav 
Published: April 2024

AbstractSymbiosis between insects and bacteria has been established countless times. While it is well known that the symbionts originated from a variety of different bacterial taxa, it is usually difficult to determine their environmental source and a route of their acquisition by the host. In this study, we address this question using a model of Neisseriaceae symbionts in rodent lice. These bacteria established their symbiosis independently with different louse taxa (Polyplax, Hoplopleura, Neohaematopinus), most likely from the same environmental source. We first applied amplicon analysis to screen for candidate source bacterium in the louse environment, that is, three species of rodents (Microtus arvalis, Clethrionomys glareolus, andApodemus flavicollis). The screened samples included rodent fur, skin, spleen, and ectoparasites sampled from the rodents. The amplicon analysis revealed a Neisseriaceae bacterium, closely related to the known louse symbionts. We assembled genome drafts of this environmental bacterium from all three rodent hosts. The sizes of the three drafts converged to a remarkably small size of approximately 1.4 Mbp, which is even smaller than the genomes of the related symbionts. Based on these findings, we propose a hypothetical scenario of the genome evolution during the transition of a free-living bacterium to the member of the rodent fur-associated microbiome and subsequently to the facultative and obligate louse symbionts.
The Tradeoffs Between Persistence and Mutation Rates at Sub-Inhibitory Antibiotic Concentrations inStaphylococcus aureus
Authors: Ismail Alysha S. , Berryhill Brandon A. , Gil-Gil Teresa , Manuel Joshua A. , Smith Andrew P. , Baquero Fernando , Levin Bruce R. 
Published: April 2024

AbstractThe rational design of the antibiotic treatment of bacterial infections employs these drugs to reach concentrations that exceed the minimum needed to prevent the replication of the target bacteria. However, within a treated patient, spatial and physiological heterogeneity promotes antibiotic gradients such that the concentration of antibiotics at specific sites is below the minimum needed to inhibit bacterial growth. Here, we investigate the effects of sub-inhibitory antibiotic concentrations on three parameters central to bacterial infection and the success of antibiotic treatment, usingin vitroexperiments withStaphylococcus aureusand mathematical-computer simulation models. Our results, using drugs of six different classes, demonstrate that exposure to sub-inhibitory antibiotic concentrations not only alters the dynamics of bacterial growth but also increases the mutation rate to antibiotic resistance and decreases the rate of production of persister cells thereby reducing the persistence level. Understanding this trade-off between mutation rates and persistence levels resulting from sub-inhibitory antibiotic exposure is crucial for optimizing, and mitigating the failure of, antibiotic therapy.
Dissecting Reactive Astrocyte Responses: Lineage Tracing and Morphology-based Clustering
Authors: Delgado-García Lina M. , Ojalvo-Sanz Ana C. , Nakamura Thabatta K. E. , Martín-López Eduardo , Porcionatto Marimelia , Lopez-Mascaraque Laura 
Published: April 2024

AbstractAbstract FigureGraphical AbstractBrain damage triggers diverse cellular and molecular events, with astrocytes playing a crucial role in activating local neuroprotective and reparative signaling within damaged neuronal circuits. Here, we investigated reactive astrocytes using a multidimensional approach to categorize their responses into different subtypes based on morphology using the StarTrack lineage tracer, single-cell imaging reconstruction and multivariate data analysis. Our findings revealed three profiles of reactive astrocyte responses affecting cell size- and shape-related morphological parameters: “moderate,” “strong,” and “very strong”. We also explored the heterogeneity in astrocyte reactivity, with a particular emphasis in the spatial and clonal distribution. Our research highlights the importance of the relationships between the different astrocyte subpopulations with their reactive responses, showing an enrichment of protoplasmic and fibrous astrocytes within the “strong” and “very strong” subtypes. Overall, our study contributes to a better understanding of astrocyte heterogeneity in response to an injury. By elucidating the diverse reactive responses among astrocyte subpopulations, we pave the way for future research aimed at uncovering novel therapeutic targets for mitigating the effects of brain damage and promoting neural repair.
Dispersal syndromes allow understanding but not predicting dispersal ability across the tree of life
Authors: Fandos Guillermo , Robinson Robert A. , Zurell Damaris 
Published: April 2024

AbstractDispersal is fundamental to many ecological and evolutionary processes, yet understanding the determinants and predictability of dispersal remains a crucial challenge. Dispersal syndromes, which describe patterns in the covariation of traits associated with dispersal, can help to gain a deeper understanding of the evolutionary dynamics of dispersal and its implications for range dynamics and ecosystem functioning in the face of global change. However, the extent to which such dispersal syndromes are generalizable across a large taxonomic scale has been hampered by low availability of standardized dispersal data across species. In this study, we used the most comprehensive and up-to-date empirical dispersal dataset for European birds to investigate the formation of dispersal syndromes and their effectiveness in predicting dispersal across species. We found body mass, feeding guild, and life-history traits shape dispersal syndromes in birds. Yet, only body mass and life history accurately predicted dispersal for unassessed species, while even multi-trait dispersal syndromes poorly predicted dispersal for phylogenetically distant species. These results shed light on the complex nature of bird dispersal and emphasize the need for refined approaches in elucidating the mechanisms and constraints underlying dispersal evolution. Our study highlights the importance of considering multiple factors and expanding empirical datasets to enhance our understanding of dispersal in avian populations.
GENOME-WIDE IDENTIFICATION, CHARACTERIZATION AND EXPRESSION ANALYSIS OF NA+/H+EXCHANGER GENE FAMILY IN TWO CORCHORUS SPECIES
Authors: Ahmed Borhan , Tabassum Anika , Bashar Kazi Khayrul , Aktar Nasima , Hossain Sabbir , Mamun Abdullah-Al , Roni Shyduzzaman , Hasan Fakhrul , Alam Mobashwer 
Published: April 2024

AbstractNa+/H+exchangers (NHXs) are secondary ion transporter to exchange H+ and transfer Na+or K+across membrane plays crucial role in cellular pH and Na+and K+homeostasis in plant. In the present study, we have performed genomewide identification, characterization and comparative analysis of NHXs genes in two cultivated jute species and found seven Co and Cc NHXs in each genome. Subsequently phylogenetic analysis demonstrated that Co and Cc NHXs have three sub-group that correlate with other plant species containing 10-12 transmembrane helices (TMH) and a hydrophilic C-terminal domain in the cytoplasmic region, the TMH compose a hollow cylinder to provide the channel for Na+and H+transport. Promoter profiling of both species NHXs genes revealed in enrichment of cis element involved in stress responsiveness reflecting their potential involvement against abiotic stress. Transcriptome data and real time PCR of Co and Cc NHXs gene expression analysis under saline and drought condition showed significant differences, which suggest their potential role in abiotic stress conditions. This is the first comprehensive analysis providing baseline information of Co and Cc NHXs genes in abiotic stress condition which can be used for the development of abiotic stress tolerant jute variety.
Differential Roles of Kinetic On- and Off-Rates in T-Cell Receptor Signal Integration Revealed with a Modified Fab’-DNA Ligand
Authors: Wilhelm Kiera B. , Vissa Anand , Groves Jay T. 
Published: April 2024

ABSTRACTAntibody-derived T-cell receptor (TCR) agonists are commonly used to activate T cells. While antibodies can trigger TCRs regardless of clonotype, they bypass native T cell signal integration mechanisms that rely on monovalent, membrane-associated, and relatively weakly-binding ligand in the context of cellular adhesion. Commonly used antibodies and their derivatives bind much more strongly than native peptide-MHC (pMHC) ligands bind their cognate TCRs. Because ligand dwell time is a critical parameter that tightly correlates with physiological function of the TCR signaling system, there is a general need, both in research and therapeutics, for universal TCR ligands with controlled kinetic binding parameters. To this end, we have introduced point mutations into recombinantly expressed α-TCRβ H57 Fab to modulate the dwell time of monovalent Fab binding to TCR. When tethered to a supported lipid bilayer via DNA complementation, these monovalent Fab’-DNA ligands activate T cells with potencies well-correlated with their TCR binding dwell time. Single-molecule tracking studies in live T cells reveal that individual binding events between Fab’-DNA ligands and TCRs elicit local signaling responses closely resembling native pMHC. The unique combination of high on- and off-rate of the H57 R97L mutant enables direct observations of cooperative interplay between ligand binding and TCR-proximal condensation of the linker for activation of T cells (LAT), which is not readily visualized with pMHC. This work provides insights into how T cells integrate kinetic information from synthetic ligands and introduces a method to develop affinity panels for polyclonal T cells, such as cells from a human patient.STATEMENT OF SIGNIFICANCET cells read kinetic information from ligands binding to T-cell receptors (TCRs) to make cell fate decisions. Unique kinetic features of a modified Fab’-DNA ligand enable direct visualization multiple TCR signal coordination through a nascent LAT condensation event. We further observed positive feedback through a kinetic on-rate enhancement in the growing LAT condensate. These observations help unify several seemingly disparate aspects of TCR signaling that have been debated in the literature. Furthermore, calibration of the Fab’-DNA ligand against native agonist pMHC establishes a basis for quantitative analysis of TCR signaling in polyclonal T cell populations.