bluuebunny/crossref_metadata_2025_split huggingface dataset:
Thymically imprinted differential responsivity of naïve CD4 T cells to IL2 results in a heterogeneity of both Treg induction and subsequent effector functioning
Authors: Pennock Nathan D. , Qian Yamin , Ishihara Kazumi , Nakamura Yamami , Cross Eric , Sakaguchi Shimon , White Jason T. 
Published: October 2023

ABSTRACTThymic selection predisposes naive T cells to particular outcomes when challenged later with cognate antigen, whether the antigen is self or foreign. This suggests that there is an inherent heterogeneity of functioning among T cells within the naive population (both CD4 and CD8s), and that each T cell, as part of its thymic development, is given a certain ‘programming’ which will affect its eventual fate decisions. In this project, we looked at the primary effects of this thymic imprinting on the conversion of naïve CD4 T cells into Tregs. Further, using an induced-Treg-reporter system, we exam the impact of thymic imprinted heterogeneity on effector functionality and identity stability. We report that naïve T cell differential responsivity to cytokines leads to the observed difference in Treg induction, and that the Tregs induced from T cells of different self-affinities maintain a heterogeneity of effector function and identity.
Lethal COVID-19 Associates With RAAS-Induced Inflammation For Multiple Organ Damage Including Mediastinal Lymph Nodes
Authors: Guarnieri Joseph W. , Topper Michael J. , Beigel Katherine , Haltom Jeffrey A. , Chadburn Amy , Frere Justin , An Julia , Cope Henry , Borczuk Alain , Sinha Saloni , Lim Christine , Kim JangKeun , Park Jiwoon , Meydan Cem , Foox Jonathan , Mozsary Christopher , Bram Yaron , Richard Stephanie , Epsi Nusrat J. , Agan Brian , Chenoweth Josh , Simons Mark , Tribble David , Burgess Timothy , Dalgard Clifton , Heise Mark T. , Moorman Nathaniel J. , Baxter Victoria K. , Madden Emily A. , Taft-Benz Sharon A. , Anderson Elizabeth J. , Sanders Wes A. , Dickmander Rebekah J. , Widjaja Gabrielle A , Janssen Kevin , Lie Timmy , Murdock Deborah , Angelin Alessia , Albrecht Yentli Soto , Olali Arnold , Cen Zimu , Dybas Joseph , Priebe Waldemar , Emmett Mark R. , Best Sonja M. , Johnson Maya Kelsey , Trovao Nidia S. , Clark Kevin B. , Zaksas Victoria , Meller Rob , Grabham Peter , Schisler Jonathan C. , Moraes-Vieira Pedro M. , Pollett Simon , Mason Christopher E. , Wurtele Eve Syrkin , Taylor Deanne , Schwartz Robert E. , Beheshti Afshin , Wallace Douglas C. , Baylin Stephen B. 
Published: October 2023

AbstractLethal COVID-19 outcomes are most often attributed to classic cytokine storm and attendant excessive immune signaling. We re-visit this question using RNA sequencing in nasopharyngeal and 40 autopsy samples from COVID-19-positive and negative individuals. In nasal swabs, the top 100 genes which significantly correlated with COVID-19 viral load, include many canonical innate immune genes. However, 22 much less studied "non-canonical" genes are found and despite the absence of viral transcripts, subsets of these are upregulated in heart, lung, kidney, and liver, but not mediastinal lymph nodes. An important regulatory potential emerges for the non-canonical genes for over-activating the renin-angiotensin-activation-system (RAAS) pathway, resembling this phenomenon in hereditary angioedema (HAE) and its overlapping multiple features with lethal COVID-19 infections. Specifically, RAAS overactivation links increased fibrin deposition, leaky vessels, thrombotic tendency, and initiating the PANoptosis death pathway, as suggested in heart, lung, and especially mediastinal lymph nodes, with a tightly associated mitochondrial dysfunction linked to immune responses. For mediastinal lymph nodes, immunohistochemistry studies validate the transcriptomic findings showing abnormal architecture, excess fibrin and collagen deposition, and pathogenic fibroblasts. Further, our findings overlap findings in SARS-CoV-2 infected hamsters, C57BL/6 and BALB/c mouse models, and importantly peripheral blood mononuclear cell (PBMC) and whole blood samples from COVID-19 patients infected with early variants and later SARS-CoV-2 strains. We thus present cytokine storm in lethal COVID-19 disease as an interplay between upstream immune gene signaling producing downstream RAAS overactivation with resultant severe organ damage, especially compromising mediastinal lymph node function.
Identification of CFAP52 as a novel diagnostic target of male infertility with defects of sperm head-tail connection and flagella development
Authors: Jin Hui-Juan , Ruan Tie-Chao , Dai Si-Yu , Geng Xin-Yan , Yang Yi-Hong , Shen Ying , Chen Su-Ren 
Published: October 2023

AbstractMale infertility is a worldwide population health concern. Asthenoteratozoospermia is a common cause of male infertility, but its etiology remains incompletely understood. No evidence indicates the relevance ofCFAP52mutations to human male infertility. Our whole-exome sequencing identified compound heterozygous mutations inCFAP52recessively cosegregating with male infertility status in a non-consanguineous Chinese family. Spermatozoa ofCFAP52-mutant patient mainly exhibited abnormal head-tail connection and deformed flagella.Cfap52-knockout mice resembled the human infertile phenotype, showing a mixed acephalic spermatozoa syndrome (ASS) and multiple morphological abnormalities of the sperm flagella (MMAF) phenotype. The ultrastructural analyses further revealed a failure of connecting piece formation and a serious disorder of ‘9+2’ axoneme structure. CFAP52 interacts with a head-tail coupling regulator SPATA6 and is essential for its stability. Expression of microtubule inner proteins and radial spoke proteins were reduced after the CFAP52 deficiency. Moreover, CFAP52-associated male infertility in humans and mice could be overcome by ICSI. The study reveals a prominent role for CFAP52 in sperm development, suggesting that CFAP52 might be a novel diagnostic target for male infertility with defects of sperm head-tail connection and flagella development
Unlocking DNA Damage Sensitivity of Cancer Cells: The Potential of Splicing Inhibitors
Authors: Anufrieva Ksenia S. , Lukina Maria M. , Ivanova Olga M. , Kazakova Anastasia N. , Shnaider Polina V. , Klimina Ksenia M. , Veselovsky Vladimir A. , Luzhin Artem V. , Velichko Artem K. , Kantidze Omar L. , Mochalova Elizaveta N. , Nikitin Maxim P. , Kashina Aleksandra V. , Vasilchikova Ekaterina A. , Deev Roman V. , Emelin Alexey M. , Turchin Anton N. , Liu Zhaojian , Wang Zixiang , Boichenko Veronika S. , Markina Nadezhda M. , Lagarkova Maria A. , Govorun Vadim M. , Arapidi Georgij P. , Shender Victoria O. 
Published: October 2023

ABSTRACTDespite the growing interest in pre-mRNA alternative splicing (AS) as a therapeutic anticancer target, the potential of splicing inhibitors in treating solid tumors remains largely unexplored. We conducted a meta-analysis of transcriptome data from six different tumor types and revealed that splicing inhibitors induced similar patterns of AS, resulting in widespread exon-skipping and intron retention events that often lead to nonsense-mediated decay of the transcripts. Interestingly, in many cases exon skipping is induced by a compensatory cellular response to splicing inhibitor treatment. It involves an upregulation of multiple splicing factors and incomplete recognition of branch points by U2 snRNP. These post transcriptional changes downregulate one-third of essential DNA repair genes, thereby creating a therapeutic vulnerability that can be exploited for cancer treatment. To harness this vulnerability, we proposed a new approach to cancer treatment consisting of sequential addition of a splicing inhibitors followed by a DNA-damaging agent. Ourin vitroandin vivoexperiments demonstrated that this strategy exhibits promising therapeutic potential for a wide range of tumors.
Model-driven characterization of functional diversity ofPseudomonas aeruginosaclinical isolates with broadly representative phenotypes
Authors: Islam Mohammad Mazharul , Kolling Glynis L. , Glass Emma M. , Goldberg Joanna B. , Papin Jason A. 
Published: October 2023

AbstractPseudomonas aeruginosais a leading cause of infections in immunocompromised individuals and in healthcare settings. This study aims to understand the relationships between phenotypic diversity and the functional metabolic landscape ofP. aeruginosaclinical isolates. To better understand the metabolic repertoire ofP. aeruginosain infection, we deeply profiled a representative set from a library of 971 clinicalP. aeruginosaisolates with corresponding patient metadata and bacterial phenotypes. The genotypic clustering based on whole-genome sequencing of the isolates, multi-locus sequence types, and the phenotypic clustering generated from a multi-parametric analysis were compared to each other to assess the genotype-phenotype correlation. Genome-scale metabolic network reconstructions were developed for each isolate through amendments to an existing PA14 network reconstruction. These network reconstructions show diverse metabolic functionalities and enhance the collectiveP. aeruginosapangenome metabolic repertoire. Characterizing this rich set of clinicalP. aeruginosaisolates allows for a deeper understanding of the genotypic and metabolic diversity of the pathogen in a clinical setting and lays a foundation for further investigation of the metabolic landscape of this pathogen and host-associated metabolic differences during infection.Impact statementPseudomonas aeruginosais a leading cause of infections in immunocompromised individuals and in healthcare settings. The treatment of these infections is complicated by the presence of a variety of virulence mechanisms and metabolic uniqueness among clinically relevant strains. This study is an attempt to understand the relationships between isolate phenotypic diversity and the functional metabolic landscape within a representative group ofP. aeruginosaclinical isolates. Characterizing this rich set of clinicalP. aeruginosaisolates allows for a deeper understanding of genotypic and metabolic diversity of the pathogen in a clinical setting and lays a foundation for further investigation of the metabolic landscape of this pathogen and host-associated metabolic differences in infection.
Pindel-TD: a tandem duplication detector based on a pattern growth approach
Authors: Yang Xiaofei , Zheng Gaoyang , Jia Peng , Wang Songbo , Ye Kai 
Published: October 2023

AbstractTandem duplication(TD) is a major type ofstructural variation(SV), and plays an important role in novel gene formation and human diseases. However, TDs are often missed or incorrectly classified as insertions by most of modern SV detection methods due to the lacking of specialized operation on TD related mutational signals. Herein, we developed a TD detection module of Pindel referred as Pindel-TD based on a TD specificpattern growthapproach. Pindel-TD detects TDs with a wide size range at single nucleotide resolution. Using simulation and real read data of HG002, we demonstrate that Pindel-TD outperformed other leading methods in terms of precision, recall, F1-score and robustness. Further applying Pindel-TD on data generated from K562 cancer cell line, we identified a TD located at the seventh exon ofSAGE1, explaining its high expression. Pindel-TD is available athttps://github.com/xjtu-omics/pindeland free for non-commercial use.
Instant Assembly of Collagen for Scaffolding, Tissue Engineering, and Bioprinting
Authors: Gong Xiangyu , Wen Zhang , Liang Zixie , Xiao Hugh , Lee Sein , Wright Thomas , Nguyen Ryan Y. , Rossello Alejandro , Mak Michael 
Published: October 2023

AbstractControllable assembly of cells and tissues offers potential for advancing disease and development modeling and regenerative medicine. The body’s natural scaffolding material is the extracellular matrix, composed largely of collagen I. However, challenges in precisely controlling collagen assembly limit collagen’s applicability as a primary bioink or glue for biofabrication. Here, we introduce a set of biopatterning methods, termed Tunable Rapid Assembly of Collagenous Elements (TRACE), that enables instant gelation and rapid patterning of collagen I solutions with wide range of concentrations. Our methods are based on accelerating the gelation of collagen solutions to instantaneous speeds via macromolecular crowding, allowing versatile patterning of both cell-free and cell-laden collagen-based bioinks. We demonstrate notable applications, including macroscopic organoid engineering, rapid free-form 3D bioprinting, contractile cardiac ventricle model, and patterning of high-resolution (below 5 (m) collagen filament. Our findings enable more controllable and versatile applications for multi-scale collagen-based biofabrication.
Elucidating Compound Mechanism of Action and Polypharmacology with a Large-scale Perturbational Profile Compendium
Authors: Hu Lucas ZhongMing , Douglass Eugene , Turunen Mikko , Pampou Sergey , Grunn Adina , Realubit Ron , Antolin Albert A. , Wang Alexander L.E. , Li Hai , Subramaniam Prem , Mundi Prabhjot S , Karan Charles , Alvarez Mariano , Califano Andrea 
Published: October 2023

AbstractThe Mechanism of Action (MoA) of a drug is generally represented as a small, non-tissue-specific repertoire of high-affinity binding targets. Yet, drug activity and polypharmacology are increasingly associated with a broad range of off-target and tissue-specific effector proteins. To address this challenge, we have leveraged a microfluidics-based Plate-Seq technology to survey drug perturbational profiles representing >700 FDA-approved and experimental oncology drugs, in cell lines selected as high-fidelity models of 23 aggressive tumor subtypes. Built on this dataset, we implemented an efficient computational framework to define a tissue-specific protein activity landscape of these drugs and reported almost 50 million differential protein activities derived from drug perturbationsvs.vehicle controls. These analyses revealed thousands of highly reproducible and novel, drug-mediated modulation of tissue-specific targets, leading to generation of a proteome-wide drug functional network, characterization of MoA-related drug clusters and off-target effects, dramatical expansion of druggable human proteome, and identification and experimental validation of novel, tissue-specific inhibitors of undruggable oncoproteins, most never reported before. The drug perturbation profile resource described here represents the first, large-scale, whole-genome-wide, RNA-Seq based dataset assembled to date, with the proposed framework, which is easily extended to elucidating the MoA of novel small-molecule libraries, facilitates mechanistic exploration of drug functions, supports systematic and quantitative approaches to precision oncology, and serves as a rich data foundation for drug discovery.
Feasibility of Inferring Spatial Transcriptomics from Single-Cell Histological Patterns for Studying Colon Cancer Tumor Heterogeneity
Authors: Fatemi Michael Y. , Lu Yunrui , Sharma Cyril , Feng Eric , Azher Zarif L. , Diallo Alos B. , Srinivasan Gokul , Rosner Grace M. , Pointer Kelli B. , Christensen Brock C. , Salas Lucas A. , Tsongalis Gregory J. , Palisoul Scott M. , Perreard Laurent , Kolling Fred W. , Vaickus Louis J. , Levy Joshua J. 
Published: October 2023

AbstractBackgroundSpatial transcriptomics involves studying the spatial organization of gene expression within tissues, offering insights into the molecular diversity of tumors. While spatial gene expression is commonly amalgamated from 1-10 cells across 50-micron spots, recent methods have demonstrated the capability to disaggregate this information at subspot resolution by leveraging both expression and histological patterns. However, elucidating such information from histology alone presents a significant challenge but if solved can better permit spatial molecular analysis at cellular resolution for instances where Visium data is not available, reducing study costs. This study explores integrating single-cell histological and transcriptomic data to infer spatial mRNA expression patterns in whole slide images collected from a cohort of stage pT3 colorectal cancer patients. A cell graph neural network algorithm was developed to align histological information extracted from detected cells with single cell RNA patterns through optimal transport methods, facilitating the analysis of cellular groupings and gene relationships. This approach leveraged spot-level expression as an intermediary to co-map histological and transcriptomic information at the single-cell level.ResultsOur study demonstrated that single-cell transcriptional heterogeneity within a spot could be predicted from histological markers extracted from cells detected within a spot. Furthermore, our model exhibited proficiency in delineating overarching gene expression patterns across whole-slide images. This approach compared favorably to traditional patch-based computer vision methods as well as other methods which did not incorporate single cell expression during the model fitting procedures. Topological nuances of single-cell expression within a Visium spot were preserved using the developed methodology.ConclusionThis innovative approach augments the resolution of spatial molecular assays utilizing histology as a sole input through synergistic co-mapping of histological and transcriptomic datasets at the single-cell level, anchored by spatial transcriptomics. While initial results are promising, they warrant rigorous validation. This includes collaborating with pathologists for precise spatial identification of distinct cell types and utilizing sophisticated assays, such as Xenium, to attain deeper subcellular insights.
What are the mechanisms of effect of group antenatal care? A systematic realist review and synthesis of the literature
Authors: Mehay Anita , Da Motta Giordana , Hunter Louise , Rayment Juliet , Wiggins Meg , Haora Penny , McCourt Christine , Harden Angela 
Published: October 2023

AbstractBackgroundThere is growing interest in the benefits of group models of antenatal care. Although clinical reviews exist, there have been few reviews that focus on the mechanisms of effect of this model.MethodsWe conducted a realist review using a systematic approach incorporating all data types (including non-research and audiovisual media), with synthesis along Context-Intervention-Mechanism-Outcome (CIMO) configurations.ResultsA wide range of sources were identified, yielding 100 relevant sources in total (89 written and 11 audiovisual). Overall, there was no clear pattern of ‘what works for whom, in what circumstances’. Findings revealed six interlinking mechanisms, including: social support, peer learning, active participation in health, health education and satisfaction or engagement with care. A further, relatively under-developed theory related to impact on professional practice (but was relatively under-developed). An overarching mechanism of empowerment featured across most studies but there was variation in how this was collectively or individually conceptualised and applied.ConclusionsMechanisms of effect are amplified in contexts where inequalities in access and delivery of care exist, but poor reporting of populations and contexts limited fuller exploration. We recommend future studies provide detailed descriptions of the population groups involved and that they give full consideration to theoretical underpinnings and contextual factors.RegistrationThe protocol for this realist review was registered in the International Prospective Register of Systematic Reviews (PROSPERO CRD42016036768)
TheEscherichia coliTolC efflux pump protein is immunogenic and elicits protective antibodies
Authors: Silva TO , Costa LVS , Chagas do Nascimento L , Barbosa LS , Fanticelli JGC , Rotilho C , Silva LS , dos Santos Abreu J , Rajsfus BF , Bulla ACS , Carneiro J , Allonso D , Salgado DR , da Silva ML , Echevarria-Lima J , Moreira LO , Olsen PC 
Published: October 2023

AbstractAntimicrobial resistance is an increasing worldwide public health burden that threatens to make the existent antimicrobials obsolete. Among the mechanisms of antimicrobial resistance is the overexpression of efflux pumps, such as the AcrA–AcrB–TolC which extrude diverse compounds, reducing the intracellular concentration of antimicrobials. TolC is the outer membrane protein of this pump and has recently gained attention as a therapeutic target. However, little is known about the immune response generated against the TolC protein. Here we evaluated the cellular and humoral immune response against the TolC fromEscherichia coli. Anin silicoepitope prediction of theE. coliTolC showed several residues could bind to human antibodies, and we showed that human plasma presented anti-TolC IgG and IgA antibodies. Gram-negative infected patients presented a slight increase in anti-TolC IgM amounts, compared to controls. RecombinantE. coliTolC protein stimulated macrophagesin vitroto produce nitric oxide, as well as IL-6 and TNF-α, assessed by Griess assay and ELISA, respectively. Immunization of mice with TolC intraperitoneally and anin vitrore-stimulation of lymph node cells led to increased percentage of T cell proliferation and IFNγ production, evaluated by flow cytometry and ELISA, respectively. We observed that TolC mouse immunization stimulated anti-TolC IgM and IgG production, with a higher level of IgG1 and IgG2, amongst the IgG subclasses. Finally, TolC IgG from mouse immune serum could bind to liveE. coli,increase bacterial uptake by macrophagesin vitro. TolC immunized mice had a survival rate increased in 60% post infection withE. coli. Our results showed that TolC is immunogenic, activating macrophages, T and B cells, leading to the production of protective antibodies againstE. coli.
Predicting prime editing efficiency across diverse edit types and chromatin contexts with machine learning
Authors: Mathis Nicolas , Allam Ahmed , Tálas András , Benvenuto Elena , Schep Ruben , Damodharan Tanav , Balázs Zsolt , Janjuha Sharan , Schmidheini Lukas , Böck Desirée , van Steensel Bas , Krauthammer Michael , Schwank Gerald 
Published: October 2023

AbstractPrime editing is a powerful genome editing technology, but its efficiency varies depending on the pegRNA design and target locus. Existing computational models for predicting prime editing rates are limited by their focus on specific edit types and by omitting the local chromatin environment. In our study, we developed machine learning models that predict prime editing efficiencies across a wide range of edit types up to 15 bp (’PRIDICT2.0’) and in different chromatin contexts (’ePRIDICT’). Both models can be accessed atwww.pridict.it.