bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nanoscale Optical Imaging, Reconstruction, and Spatial Analysis of Whole Mouse Glomeruli
Authors: Ali Adilijiang , Liu Zixuan , Ye Kenan , Guan Yun , Chen Siying , Liu Tingxuan , Guo Ziyu , Wong Madeline K. , Vasquez Pedro , Poudel Chetan , Mustonen Benjamin C. , Eng Diana G. , Pippin Jeffrey W. , Shankland Stuart J. , Wang Sheng , Vaughan Joshua C. 
Published: November 2024

AbstractRenal glomeruli have traditionally been studied by micrometer-scale optical microscopy to interrogate overall physiology or molecular distributions and by nanoscale electron microscopy to interrogate the ultrastructure of thin sections. While these approaches are powerful, they have been limited in their ability to obtain detailed views of the glomeruli as holistic 3D functional units. To fill this knowledge gap, we have developed a novel pipeline for imaging, reconstructing, and analyzing whole mouse glomeruli at 100 nm resolution using super-resolution fluorescence microscopy. This pipeline integrates both manual and machine learning approaches to annotate and analyze glomerular structures. Using this method, we created 18 detailed glomerulus models, from a range of healthy, aged, and model diseased mice, that outline all major structures and cell types. These models have been made publicly accessible in an online repository, providing a valuable resource for further studies. Our results also uncovered a diverse set of novel phenotypes including nuclear enlargement in all glomerular cell types in aging and disease, as well as an aging-related pattern of regional thickening of the Bowman’s capsule basement membrane near the tubular-glomerular junction.
Drivers of antibiotic resistance in two monsoon-impacted Indian urban rivers receiving untreated wastewater
Authors: Bagra Kenyum , Singh Harshita , Klümper Uli , Singh Gargi 
Published: November 2024

AbstractRivers in India receive 78.7% of untreated sewage from cities and towns making it a potential global “hotspot” for AMR. During monsoon, flooding is common in most Indian cities bringing in fecal contamination in storm runoff. Identifying the major driving factors contributing to the elevated levels of AMR in these rivers is essential to combat AMR proliferation. Determining whether the introduction of ARBs and ARGs through fecal pollution or subsequent (co-) selection for ARGs through chemical pollutants is responsible for the rise and spread of AMR is important in mitigation efforts. To achieve this, we targeted two rivers in northern India which received untreated wastewater and assessed the level of two fecal indicators (E. coliandintI1) and wastewater-associated ARGs (ermF,sul1,sul2, andtetW) along with heavy metals (Ag, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, and Zn). Water and sediment samples were collected in triplicates at 5-6 locations for each river. Consequently, to evaluate how seasonality affects the ARG levels as well as their drivers in these heavily polluted rivers, sampling campaigns were carried out during three seasons: in summer (pre-monsoon), during monsoon, and post-monsoon in winter. We here demonstrate that the main source for the river resistome in the Bindal and Rispana is the constant inflow of untreated wastewater throughout the year and not the co-selection of ARGs due to the presence of heavy metals. This may be true for many Indian rivers that receive untreated or partially treated wastewater. The rainfall adds to the ARG abundance of the river instead of diluting it. MGEintI1 is more reliable thanE. colias an indicator for fecal pollution and horizontal gene transfer. Heavy metals, despite being present in the river in higher concentrations than the MCSC, no evidence for co-selection was observed.
Streamlining Asymmetry Quantification in Fetal Mouse Imaging: A Semi-Automated Pipeline Supported by Expert Guidance
Authors: Rolfe S.M. , Mao D. , Maga A. M. 
Published: November 2024

AbstractAsymmetry is a key feature of numerous developmental disorders and in phenotypic screens is often used as a readout for environmental or genetic perturbations to normal development. A better understanding of the genetic basis of asymmetry and its relationship to disease susceptibility will help unravel the complex genetic and environmental factors and their interactions that increase risk in a range of developmental disorders. Large-scale imaging datasets offer opportunities to work with sample sizes needed to detect and quantify differences in morphology beyond severe deformities while also posing challenges to manual phenotyping protocols. In this work, we introduce a semi-automated open-source workflow to quantify abnormal asymmetry of craniofacial structures that integrates expert anatomical knowledge. We apply this workflow to explore the role of genes contributing to abnormal asymmetry by deep phenotyping 3D fetal microCT images from knockout strains acquired as part of the Knockout Mouse Phenotyping Program (KOMP2). Four knockout strains:Ccdc186,Acvr2a,Nhlh1, andFam20cwere identified with highly significant asymmetry in craniofacial regions, making them good candidates for further analysis into their potential roles in asymmetry and developmental disorders.Summary StatementWe introduce an open-source, semi-automated pipeline to detect abnormally asymmetric phenotypes in 3D scans of fetal mice to explore the relationship between facial asymmetry, perturbed development, and developmental instability.
StreptococcusPhage Genomes Reveal Extensive Diversity, New Taxonomic Insights, and Novel Endolysin-Derived Antimicrobial Peptides
Authors: Karim Daniyal , Mondal Shakhinur Islam , Rolin Mohimenul Haque , Jewel Nurnabi Azad , Hoque Hammadul , Buttimer Colin , Rahman Md Mahfuzur , Azad Abul Kalam , Akter Arzuba 
Published: November 2024

AbstractThe global rise of antibiotic-resistant bacteria, particularly amongStreptococcusspecies, poses an escalating public health threat. Traditional antibiotic development has proven inadequate, making innovative approaches such as bacteriophage-based therapies promising alternatives. A deep understanding of phage biology at the genomic level is essential for advancing therapeutic applications. Here, we analyzed 709Streptococcusphage genomes to bridge gaps in genomic diversity and propose revisions toStreptococcusphage taxonomy. The phage genomes were clustered based on shared proteins, resulting in 66 clusters and 35 singletons with significant variation in genome characteristics. Through proteome phylogeny, average nucleotide identity, and inter-cluster core genes, we propose 21 new family-level classifications and 296 genus-level subclusters, providing an updated framework forStreptococcusphage taxonomy. Further analysis revealed diverse domain architectures inStreptococcusphage endolysins, including previously unreported structures. Specific domains were associated with distinct streptococcal hosts, suggesting adaptive evolution. We also observed variation in endolysin gene organization, with purifying selection acting on most sites, though some were subject to diversifying selection. Additionally, 182 novel endolysin-derived antimicrobial peptides (AMPs) were identified, some exhibiting antifungal, antiviral, cell-penetrating and non-toxic properties. Molecular dynamics and docking simulations demonstrated high stability and strong binding affinity of peptides EP-39 and EP-121 to theStreptococcus pneumoniaevirulence factor autolysin. This is the first comprehensive comparative study ofStreptococcusphage genomes, providing critical insights into phage diversity and taxonomy. It also highlights the therapeutic potential of endolysin-derived AMPs against multidrug-resistantStreptococcusstrains. Further experimental validation is required to assess their clinical potential.
TFAP2C is a key regulator of intrauterine trophoblast cell invasion and deep hemochorial placentation
Authors: Dominguez Esteban M. , Moreno-Irusta Ayelen , Scott Regan L. , Iqbal Khursheed , Soares Michael J. 
Published: November 2024

AbstractTranscription factor AP-2 gamma (TFAP2C) has been identified as a key regulator of the trophoblast cell lineage and hemochorial placentation. The rat possesses deep placentation characterized by extensive intrauterine trophoblast cell invasion, which resembles human placentation.Tfap2c isexpressed in multiple trophoblast cell lineages, including invasive trophoblast cells situated within the uterine-placental interface of the rat placentation site. Global genome-editing was used to explore the biology ofTfap2cin rat placenta development. Homozygous global disruption ofTfap2cresulted in prenatal lethality. Heterozygous global disruption ofTfap2cwas associated with diminished invasive trophoblast cell infiltration into the uterus. The role of TFAP2C in the invasive trophoblast cell lineage was explored using Cre-lox conditional mutagenesis. Invasive trophoblast cell-specific disruption ofTfap2cresulted in inhibition of intrauterine trophoblast cell invasion and intrauterine and postnatal growth restriction. The invasive trophoblast cell lineage was not impaired following conditional monoallelic disruption ofTfap2c. In summary, TFAP2C contributes to the progression of distinct stages of placental development. TFAP2C is a driver of early events in trophoblast cell development and reappears later in gestation as an essential regulator of the invasive trophoblast cell lineage. A subset of TFAP2C actions on trophoblast cells are dependent on gene dosage.
Elongation of the nascent avian foregut requires coordination of intrinsic and extrinsic cell behaviors
Authors: Powell Olivia , Garcia Emily , Sriram Vanshika , Qu Yi , Nerurkar Nandan L. 
Published: November 2024

AbstractThe foregut tube gives rise to the lungs and upper gastrointestinal tract, enabling vital functions of respiration and digestion. How the foregut tube forms during embryonic development has historically received considerable attention, but over the past few decades this question has primarily been addressed indirectly through studies on morphogenesis of the primitive heart tube, a closely related process. As a result, many aspects of foregut development remain unresolved. Here, we exploit the accessibility of the chick embryo to study the initial formation of the foregut tube, combining embryology with fate mapping, live imaging, and biomechanical analyses. The present study reveals that the foregut forms and elongates over a narrower time window than previously thought, and displays marked dorso-ventral and left-right asymmetries early in its development. Through tissue-specific ablation of endoderm along the anterior intestinal portal, we confirm its central biomechanical role in driving foregut morphogenesis, despite not directly contributing cells to the elongating tube. We further confirm the important role of this cell population in formation of the heart tube, with evidence that this role extends to later stages of cardiac looping as well. Together, these data reveal the need for an intricate balance between intrinsic cell behaviors and extrinsic forces for normal foregut elongation, and set the stage for future studies aimed at understanding the underlying molecular cues that coordinate this balance.GRAPHICAL ABSTRACT
Viral vector-mediatedSLC9A6gene replacement reduces cerebellar dysfunction in theshakerrat model of Christianson syndrome
Authors: Anderson Collin J , Figueroa Karla P , Paul Sharan , Gandelman Mandi , Dansithong Warunee , Katakowski Joseph A , Scoles Daniel R. , Pulst Stefan M 
Published: November 2024

AbstractBackgroundChristianson syndrome (CS) is an x-linked recessive neurodevelopmental and neurodegenerative condition characterized by severe intellectual disability, cerebellar degeneration, ataxia, and epilepsy. Mutations to theSLC9A6gene encoding NHE6 are responsible for CS, and we recently demonstrated that a mutation to the ratSlc9a6gene causes a similar phenotype in the spontaneousshakerrat model, which exhibits cerebellar degeneration with motor dysfunction. In previous work, we used the PhP.eB-L7-Slc9a6-GFP adeno-associated viral (AAV) vector to demonstrate that gene replacement in Purkinje cells reduced theshakermotor and molecular phenotype.MethodsWe carried out a 20-week longitudinal study evaluating the impact of Purkinje cell-specific gene replacement on ataxia and tremor. Taking advantage of the high homology between humanSLC9A6and ratSlc9a6, we tested a more clinically relevant construct, AAV9-CAG-hSLC9A6 AAV vector in theshakerrat. In both experimental cohorts, we performed molecular studies to evaluate expression of NHE6 and key cerebellar markers. We then characterized the relationship between molecular markers and motor function, as well between tremor and ataxia.ResultsAdministration of either of PhP.eB-L7-Slc9a6-GFP or AAV9-CAG-hSLC9A6 AAV vectors led to significant improvement in the molecular and motor phenotypes. The abundance of each disease-relevant cerebellar proteins was significantly correlated to motor ataxia. Further, we found that the relationship between cerebellar ataxia and tremor devolved over time, with disease modifying therapy disrupting their temporal relationship.ConclusionsThese findings impact futureSLC9A6-targeted gene therapy efforts for CS and strongly support gene replacement as a viable therapeutic strategy. Furthermore, tremor and ataxia phenotypes may arise from dissociable cerebellar mechanisms.Graphical Abstract
Analysis of sparse animal social networks
Authors: Mylne Helen K , Abell Jackie , Beale Colin M , Brent Lauren JN , Bro-Jørgensen Jakob , Evans Kate E , DA Hart Jordan , Sakala Dabwiso , Simpamba Twakundine , Youldon David , Franks Daniel W 
Published: November 2024

AbstractLow-density social networks can be common in animal societies, even among species generally considered to be highly social. Social network analysis is commonly used to analyse animal societal structure, but edge weight (strength of association between two individuals) estimation methods designed for dense networks can produce biased measures when applied to low-density networks. Frequentist methods suffer when data availability is low, because they contain an inherent flat prior that will accept any possible edge weight value, and contain no uncertainty in their output. Bayesian methods can accept alternative priors, so can provide more reliable edge weights that include a measure of uncertainty, but they can only reduce bias when sensible prior values are selected. Currently, neither accounts for zero-inflation, so they produce edge weight estimates biased towards stronger associations than the true social network, which can be seen through diagnostic plots of data quality against output estimate. We address this by adding zero-inflation to the model, and demonstrate the process using group-based data from a population of male African savannah elephants. We show that the Bayesian approach performs better than the frequentist to reduce the bias caused by these problems, though the Bayesian requires careful consideration of the priors. We recommend the use of a Bayesian framework, but with a conditional prior that allows the modelling of zero-inflation. This reflects the fact that edge weight derivation is a two-step process: i) probability of ever interacting, and ii) frequency of interaction for those who do. Additional conditional priors could be added where the biology requires it, for example in a society with strong community structure, such as female elephants in which kin structure would create additional levels of social clustering. Although this approach was inspired by reducing bias observed in sparse networks, it could have value for networks of all densities.
A chaotrope-based approach for rapidin vitroassembly and loading of bacterial microcompartment shells
Authors: Range Kyleigh L. , Chiang Timothy K. , Pramanik Arinita , Landa Joel F. , Snyder Samuel N. , Zuo Xiaobing , Tiede David M. , Utschig Lisa M. , Hegg Eric L. , Sutter Markus , Kerfeld Cheryl A. , Ralston Corie Y. 
Published: November 2024

AbstractBacterial microcompartments (BMCs) are proteinaceous organelles that self-assemble into selectively permeable shells that encapsulate enzymatic cargo. BMCs enhance catalytic pathways by reducing crosstalk among metabolites, preventing harmful intermediates from leaking into the cytosol, and increasing reaction efficiency via enzyme colocalization. The intrinsic properties of BMCs make them attractive for biotechnological engineering. However,in vivoexpression methods for shell synthesis have significant drawbacks that limit the potential design space for these nanocompartments. Here we describe the development of a new, efficient, and rapid method forin vitroassembly of BMC shells from their protein building blocks. Our method enables large-scale construction of BMC shells by utilizing urea as a chaotropic agent to control self-assembly, and provides an approach for encapsulation of both biotic and abiotic cargo under a broad range of reaction conditions. We demonstrate an enhanced level of control over the assembly of BMC shellsin vitroand expand the design parameter space for engineering BMC systems with specialized and enhanced catalytic properties.
Genetic risk of inflammatory bowel disease is associated with disease course severity
Authors: Vestergaard Marie Vibeke , Allin Kristine Højgaard , Nøhr Anne Krogh , Lominchar Jesus Vicente Torresano , Christensen Heidi Søgaard , Krarup Henrik , Nielsen Kaspar René , Jacobsen Henrik Albæk , Bybjerg-Grauholm Jonas , Bækvad-Hansen Marie , Brøndum Rasmus Froberg , Bøgsted Martin , Larsen Lone , Sazonovs Aleksejs , Jess Tine 
Published: November 2024

AbstractBackgroundGenetic susceptibility to inflammatory bowel disease (IBD) has been widely studied, whereas the genetic contribution to disease progression over time remains largely unknown. In a unique population-based cohort, we explored if genetic susceptibility to IBD associated with disease course severity.MethodsIn a Danish nationwide cohort of 3688 patients with Crohn’s disease (CD), 4491 patients with ulcerative colitis (UC), and 9469 controls, we estimated polygenic scores (PGS) for IBD susceptibility. We then investigated the association between susceptibility PGS and severe versus less severe disease courses. Patients were categorized as having a severe disease course if needing I) at least two IBD-related hospitalizations exceeding two days, II) at least two IBD-related major surgeries, III) one hospitalization and one major surgery not overlapping in time, or IV) total use of minimum 5000 mg systemic corticosteroids within the first three years of diagnosis. Secondary analyses explored the association with other severity measures including inflammatory markers, exposure to biologics and immunomodulators, and time to hospitalization and major IBD-related surgery. Statistical analyses included logistic, linear, and Cox proportional hazards regression, and predictive modeling using random forest.FindingsPatients with severe disease courses had higher susceptibility PGS than patients with less severe disease courses (CD: OR=1·27,P=7·73×10−10, UC: OR=1·35,P=7·29×10−17per SD increase in susceptibility PGS). When comparing the highest versus lowest PGS quintile, we observed a hazard ratio (HR) for major surgery of 2·74 (P=7·19×10−18) in patients with CD and 2·04 (P=4·36×10−7) in patients with UC. A higher susceptibility PGS was also associated with longer and more frequent hospitalizations, higher levels of C-reactive protein, decreased hemoglobin, and a higher need for corticosteroids, immunomodulators, and biologic therapies.InterpretationPatients with a higher genetic burden for developing IBD also experience a more severe disease course, suggesting a shared genetic architecture between disease susceptibility and severity.FundingDanish National Research Foundation, DNRF148, Lundbeck Foundation, R313-2019-857, Novo Nordisk Foundation, NNF23OC0087616, Danish Colitis Crohn Association.
Nowcasting epidemic trends using hospital- and community-based virologic test data
Authors: Lim Tse Yang , Kanjilal Sanjat , Doron Shira , Penney Jessica , Haddix Meredith , Koo Tae Hee , Danza Phoebe , Fisher Rebecca , Grad Yonatan H. , Hay James A. 
Published: November 2024

AbstractEpidemiological surveillance typically relies on reported incidence of cases or hospitalizations, which can suffer significant reporting lags, biases and under-ascertainment. Here, we evaluated the potential of viral loads measured by RT-qPCR cycle threshold (Ct) values to track epidemic trends. We used SARS-CoV-2 RT-qPCR results from hospital testing in Massachusetts, USA, municipal testing in California, USA, and simulations to identify predictive models and covariates that maximize short-term epidemic trend prediction accuracy. We found SARS-CoV-2 Ct value distributions correlated with epidemic growth rates under real-world conditions. We fitted generalized additive models to predict log growth rate or direction of reported SARS-CoV-2 case incidence using features of the time-varying population Ct distribution and assessed the models’ ability to track epidemic dynamics in rolling two-week windows. Observed Ct value distributions accurately predicted epidemic growth rates (growth rate RMSE ∼ 0.039-0.052) and direction (AUC ∼ 0.72-0.78). Performance degraded during periods of rapidly changing growth rate. Predictive models were robust to testing regimes and sample sizes; accounting for population immunity or symptom status yielded no substantial improvement. Trimming Ct value outliers improved performance. These results indicate that analysis of Ct values from routine PCR tests can help monitor epidemic trends, complementing traditional incidence metrics.
Phenotype Scoring of Population Scale Single-Cell Data Dissects Alzheimer’s Disease Complexity
Authors: He Chenfeng , Li Athan Z. , Arachchilage Kalpana Hanthanan , Gupta Chirag , Huang Xiang , Zhao Xinyu ,   PsychAD Consortium, Girdhar Kiran , Voloudakis Georgios , Hoffman Gabriel E. , Bendl Jaroslav , Fullard John F. , Lee Donghoon , Roussos Panos , Wang Daifeng 
Published: November 2024

AbstractThe complexity of Alzheimer’s disease (AD) manifests in diverse clinical phenotypes, including cognitive impairment and neuropsychiatric symptoms (NPSs). However, the etiology of these phenotypes remains elusive. To address this, the PsychAD project generated a population-level single-nucleus RNA-seq dataset comprising over 6 million nuclei from the prefrontal cortex of 1,494 individual brains, covering a variety of AD-related phenotypes that capture cognitive impairment, severity of pathological lesions, and the presence of NPSs. Leveraging this dataset, we developed a deep learning framework, called Phenotype Associated Single Cell encoder (PASCode), to score single-cell phenotype associations, and identified ∼1.5 million phenotype associate cells (PACs). We compared PACs within 27 distinct brain cell subclasses and prioritized cell subpopulations and their expressed genes across various AD phenotypes, including the upregulation of a reactive astrocyte subtype with neuroprotective function in AD resilient donors. Additionally, we identified PACs that link multiple phenotypes, including a subpopulation of protoplasmic astrocytes that alter their gene expression and regulation in AD donors with depression. Uncovering the cellular and molecular mechanisms underlying diverse AD phenotypes has the potential to provide valuable insights towards the identification of novel diagnostic markers and therapeutic targets. All identified PACs, along with cell type and gene expression information, are summarized into an AD-phenotypic single-cell atlas for the research community.