bluuebunny/crossref_metadata_2025_split huggingface dataset:
Individuals with recent prior SARS-CoV-2 infection are at reduced risk of Omicron infection and associated hospitalization
Authors: Nadig Mihika , Niesen Michiel JM , Lenehan Patrick , Agarwal Vineet , Ross Jason , Ardhanari Sankar , Venkatakrishnan AJ , Soundararajan Venky 
Published: August 2022

AbstractOmicron sub-lineages such as BA2.12.1 and BA5 have breached prior infection-induced immunity and vaccine-induced immunity. This capacity of Omicron to reinfect patients calls for a characterization of vaccination, infection, and reinfection patterns. We analyzed de-identified longitudinal electronic health records for 389,746 individuals (88,679 fully-vaccinated, 184,205 boosted, 73,184 with prior infection) across multiple US states. Compared to individuals with only full vaccination, the rates of SARS-CoV-2 infections in the Omicron era were reduced for individuals with additional prior infection (1.4 to 1.8-fold reduced, depending on vaccine status) or booster vaccination (1.3 to 2.0-fold reduced). Although prior infection was associated with lower incidence of SARS-CoV-2 infection, we found that the relative risk (RR) of infections for individuals with prior infection has increased during Omicron. During October, 2021, RR was 0.11 [0.10-0.13, 95% CI] while during May, 2022, it increased to 0.57 [0.46-0.68, 95% CI], suggesting an increase in reinfections with Omicron. Furthermore, we found that time since prior infection is associated with risk of reinfection, providing evidence of waning immunity. Prior infections before June, 2021, were associated with marginal reduction in risk of infection (eg., RR = 0.80 [0.68-0.90] for prior infection during January, 2021), while recent prior infections were associated with significant reduction in risk (eg., RR = 0.24 [0.20-0.29, 95% CI] for prior infection during November, 2021). Despite an observed increase in reinfections and vaccine breakthrough infections, our findings emphasize the protective effect of natural and vaccine immunity, with prior infection providing ∼6 months of protection from reinfection.
Transformer Enables Reference Free And Unsupervised Analysis of Spatial Transcriptomics
Authors: Zhao Chongyue , Xu Zhongli , Wang Xinjun , Chen Kong , Huang Heng , Chen Wei 
Published: August 2022

AbstractThe development of spatial transcriptomics technologies makes it possible to study tissue heterogeneity at the scale of spatial expressed microenvironment. However, most of the previous methods collapse the spatial patterns in the low spatial resolution. Existing reference based deconvolution methods integrate single-cell reference and spatial transcriptomics data to predict the proportion of cell-types, but the availability of suitable single-cell reference is often limited. In this paper, we propose a novel Transformer based model (TransfromerST) to integrate the spatial gene expression measurements and their spatial patterns in the histology image (if available) without single cell reference. TransfromerST enables the learning of the locally realistic and globally consistent constituents at nearly single cell resolution. TransfromerST firstly uses a transformer based variational autoencoder to explore the latent representation of gene expression, which is further embedded with the spatial relationship learned from adaptive graph Transformer model. The super-resolved cross-scale graph network improves the model-fit to enhanced structure-functional interactions. The public and in-house experimental results with multimodal spatial transcriptomics data demonstrate TransfromerST could highlight the tissue structures at nearly single cell resolution and detect the spatial variable genes and meta gene for each spatial domain. In summary, TransfromerST provides an effective and efficient alternative for spatial transcriptomics tissue clustering, super-resolution and gene expression prediction from histology image.
Extracellular matrix educates a tumor macrophage phenotype found in ovarian cancer metastasis
Authors: Puttock E. H. , Tyler E. J. , Manni M. , Maniati E. , Butterworth C. , Peerani E. , Hirani P. , Gauthier V. , Liu Y. , Maniscalco G. , Rajeeve V. , Cutillas P. , Trevisan C. , Pozzobon M. , Lockley M. , Rastrick J. , Läubli H. , White A. , Pearce O. M. T. 
Published: August 2022

AbstractRecent studies have shown the tumor extracellular matrix (ECM) associates with immunosuppression, and that targeting the ECM can improve immune infiltration and immunotherapy response. A question that remains is whether the ECM is directly educating the immune phenotypes seen in cancer. We identified a tumor-associated macrophage (TAM) population correlated with poor prognosis, interruption of the cancer immunity cycle, and tumor ECM composition. To investigate whether ECM was capable of generating the TAM phenotype seen, we developed a decellularized tissue model that retains the native ECM architecture and composition. Macrophages cultured on decellularized ovarian metastasis shared transcriptional profiles with the TAMs found in human tissues. ECM educated macrophages have a tissue remodeling and immunoregulatory phenotype, inducing altered T cell function. We conclude that the tumor ECM is directly educating this macrophage population found in cancer tissues. Therefore, current and emerging cancer therapies that target the tumor ECM may be tailored to improve macrophage phenotype and their downstream regulation of immunity.
Modular response analysis reformulated as a multilinear regression problem
Authors: Borg Jean-Pierre , Colinge Jacques , Ravel Patrice 
Published: August 2022

AbstractMotivationModular response analysis (MRA) is a well-established method to infer biological networks from perturbation data. Classically, MRA requires the solution of a linear system and results are sensitive to noise in the data and perturbation intensities. Applications to networks of 10 nodes or more are difficult due to noise propagation.ResultsWe propose a new formulation of MRA as a multilinear regression problem. This enables to integrate all the replicates and potential, additional perturbations in a larger, over determined and more stable system of equations. More relevant confidence intervals on network parameters can be obtained and we show competitive performance for networks of size up to 100. Prior knowledge integration in the form of known null edges further improves these results.Availability and implementationThe R code used to obtain the presented results is available from GitHub: https://github.com/J-P-Borg/BioInformaticsContactPatrice.ravel@umontpellier.fr
Tensor Image Registration Library: Automated Deformable Registration of Stand-Alone Histology Images to Whole-Brain Post-Mortem MRI Data
Authors: Huszar Istvan N. , Pallebage-Gamarallage Menuka , Bangerter-Christensen Sarah , Brooks Hannah , Fitzgibbon Sean , Foxley Sean , Hiemstra Marlies , Howard Amy F.D. , Jbabdi Saad , Kor Daniel Z. L. , Leonte Anna , Mollink Jeroen , Smart Adele , Tendler Benjamin C. , Turner Martin R. , Ansorge Olaf , Miller Karla L. , Jenkinson Mark 
Published: August 2022

AbstractBackgroundAccurate registration between microscopy and MRI data is necessary for validating imaging biomarkers against neuropathology, and to disentangle complex signal dependencies in microstructural MRI. Existing registration methods often rely on serial histological sampling or significant manual input, providing limited scope to work with a large number of stand-alone histology sections. Here we present a customisable pipeline to automate the registration of stand-alone histology sections to whole-brain MRI data.MethodsOur pipeline registers stained histology sections to whole-brain post-mortem MRI in 4 stages, with the help of two photographic intermediaries: a block face image (to undistort histology sections) and coronal brain slice photographs (to insert them into MRI space). Each registration stage is implemented as a configurable stand-alone Python script using our novel platform, Tensor Image Registration Library (TIRL), which provides flexibility for wider adaptation. We report our experience of registering 87 PLP-stained histology sections from 14 subjects and perform various experiments to assess the accuracy and robustness of each stage of the pipeline.ResultsAll 87 histology sections were successfully registered to MRI. Histology-to-block registration (Stage 1) achieved 0.2-0.4 mm accuracy, better than commonly used existing methods. Block-to-slice matching (Stage 2) showed great robustness in automatically identifying and inserting small tissue blocks into whole brain slices with 0.2 mm accuracy. Simulations demonstrated sub-voxel level accuracy (0.13 mm) of the slice-to-volume registration (Stage 3) algorithm, which was observed in over 200 actual brain slice registrations, compensating 3D slice deformations up to 6.5 mm. Stage 4 combined the previous stages and generated refined pixelwise aligned multi-modal histology-MRI stacks.ConclusionsOur open-source pipeline provides robust automation tools for registering stand-alone histology sections to MRI data with sub-voxel level precision, and the underlying framework makes it readily adaptable to a diverse range of microscopy-MRI studies.HighlightsNew software framework for prototyping bespoke image registration pipelinesAutomated pipeline to register stand-alone histology sections to whole-brain MRINovel deformable slice-to-volume registration algorithmNo strict necessity for serial histological sectioning for MRI-histology registration
Effects of Connectivity on Narrative Temporal Processing in Structured Reservoir Computing
Authors: Dominey Peter Ford , Ellmore Timothy M. , Ventre-Dominey Jocelyne 
Published: August 2022

AbstractComputational models of language are having an increasing impact in understanding the neural bases of language processing in humans. A recent model of cortical dynamics based on reservoir computing was able to account for temporal aspects of human narrative processing as revealed by fMRI. In this context the current research introduces a form of structured reservoir computing, where network dynamics are further constrained by the connectivity architecture in order to begin to explain large scale hierarchical network properties of human cortical activity during narrative comprehension. Cortical processing takes place at different time scales depending on the position in a “hierarchy” from posterior sensory input areas to higher level associative frontal cortical areas. This phenomena is likely related to the cortical connectivity architecture. Recent studies have identified heterogeneity in this posterior-anterior hierarchy, with certain frontal associative areas displaying a faster narrative integration response than much more posterior areas. We hypothesize that these discontinuities can be due to white matter connectivity that would create shortcuts from fast sensory areas to distant frontal areas. To test this hypothesis, we analysed the white matter connectivity of these areas and discovered clear connectivity patterns in accord with our hypotheses. Based on these observations we performed simulations using reservoir networks with connectivity patterns structured with an exponential distance rule, yielding the sensory-associative hierarchy. We then introduce connectivity short-cuts corresponding to those observed in human anatomy, resulting in frontal areas with unusually fast narrative processing. Using structured reservoir computing we confirmed the hypothesis that topographic position in a cortical hierarchy can be dominated by long distance connections that can bring frontal areas closer to the sensory periphery.
Merging Bioactivity Predictions from Cell Morphology and Chemical Fingerprint Models Using Similarity to Training Data
Authors: Seal Srijit , Yang Hongbin , Trapotsi Maria-Anna , Singh Satvik , Carreras-Puigvert Jordi , Spjuth Ola , Bender Andreas 
Published: August 2022

ABSTRACTThe applicability domain of machine learning models trained on structural fingerprints for the prediction of biological endpoints is often limited by the lack of diversity of chemical space of the training data. In this work, we developed similarity-based merger models which combined the outputs of individual models trained on cell morphology (based on Cell Painting) and chemical structure (based on chemical fingerprints) and the structural and morphological similarities of the compounds in the test dataset to compounds in the training dataset. We applied these similarity-based merger models using logistic regression models on the predictions and similarities as features and predicted assay hit calls of 177 assays from ChEMBL, PubChem and the Broad Institute (where the required Cell Painting annotations were available). We found that the similarity-based merger models outperformed other models with an additional 20% assays (79 out of 177 assays) with an AUC>0.70 compared with 65 out of 177 assays using structural models and 50 out of 177 assays using Cell Painting models. Our results demonstrated that similarity-based merger models combining structure and cell morphology models can more accurately predict a wide range of biological assay outcomes and further expanded the applicability domain by better extrapolating to new structural and morphology spaces.Abstract FigureFigure:For TOC Only
Human Satellite 1 (HSAT1) analysis provides novel evidence of pericentromeric transcription
Authors: Lopes Mariana , Louzada Sandra , Ferreira Daniela , Veríssimo Gabriela , Eleutério Daniel , Gama-Carvalho Margarida , Chaves Raquel 
Published: August 2022

AbstractPericentromeric regions of human chromosomes are composed of tandem-repeated and highly organized sequences named satellite DNAs. Although being known for a long time as the most AT-rich fraction of the human genome, classical satellite HSAT1 has been disregarded in genomic and transcriptional studies, falling behind other human satellites in terms of knowledge. The path followed herein trails with HSAT1 isolation and cloning, followed byin silicoanalysis. Monomer copy number and expression data was obtained in a wide variety of human cell lines, with greatly varying profiles in tumoral/non-tumoral samples. HSAT1 was mapped in human chromosomes and applied inin situtranscriptional assays. Additionally, it was possible to observe the nuclear organization of HSAT1 transcripts and further characterize them by 3’ RACE-Seq. Size-varying polyadenylated HSAT1 transcripts were detected, which possibly accounts for the intricate regulation of alternative polyadenylation. As far as we know, this work pioneers HSAT1 transcription studies. With the emergence of new human genome assemblies, acrocentric pericentromeres are becoming relevant characters in disease and other biological contexts. HSAT1 sequences and associated noncoding RNAs will most certainly prove significant in the future of HSAT research.
Sex-specificity of the C. elegans metabolome
Authors: Burkhardt Russell N. , Artyukhin Alexander B. , Aprison Erin Z. , Curtis Brian J. , Fox Bennett W. , Ludewig Andreas H. , Chaturbedi Amaresh , Panda Oishika , Wrobel Chester J. J. , Lee Siu S. , Ruvinsky Ilya , Schroeder Frank C. 
Published: August 2022

AbstractRecent studies of animal metabolism have revealed large numbers of novel metabolites that are involved in all aspects of organismal biology, but it is unclear to what extent metabolomes differ between sexes. Here, using untargeted comparative metabolomics for the analysis of wildtype animals and a series of germline mutants, we show that C. elegans hermaphrodites and males exhibit pervasive metabolomic differences. Several hundred small molecules are produced exclusively or in much larger amounts in one sex, including a host of previously unreported metabolites that incorporate building blocks from nucleoside, carbohydrate, lipid, and amino acid metabolism. A subset of male-enriched metabolites is specifically associated with the presence of a male germline, whereas enrichment of other compounds requires a male soma. Further, we show that one of the male germline-dependent metabolites, an unusual dipeptide incorporating N,N-dimethyltryptophan, accelerates the last stage of larval development in hermaphrodites. Our results serve as a foundation for mechanistic studies of how the genetic sex of soma and germline shape the C. elegans metabolome and provides a blueprint for the discovery of sex-dependent metabolites in other animals.
Heat stress induces unreduced male gamete formation by targeting the meiotic cyclin TAM/CYCA1;2
Authors: Schindfessel Cédric , Jin Chunlian , Geelen Danny 
Published: August 2022

ABSTRACTHeat stress promotes the formation of unreduced (2n) male gametes, a driving force of evolutionary polyploidization in the plant kingdom. Here we report that the molecular mechanism underlying heat tolerance of the reproductive system in Arabidopsis thaliana relies on sustained synthesis of the cell cycle protein TAM/CYCA1;2. Under heat stress TAM protein accumulates in stress granules when expressed from a gene that is derived from a heat tolerant Arabidopsis accession such as Col-0. Heat sensitive TAM alleles do not support TAM protein synthesis at elevated temperatures resulting in over 80% of the pollen being diploid. However, sustained expression of TAM is not sufficient as heat stress also promotes formation of unreduced male gametes in Col-0 mutants of the meiosis exit regulators THREE DIVISION MUTANT1 (TDM1) and SUPPRESSOR WITH MORPHOGENETIC EFFECTS ON GENITALIA7 (SMG7). These findings reveal a TDM1 and SMG7 dependent licencing mechanism securing protein synthesis and male meiosis progression under heat stress conditions. Arabidopsis accessions that do not possess this heat tolerant translation mechanism are poised to produce high frequencies of unreduced male gametes and generate polyploid offspring at elevated temperature.
Antagonistic, synergistic, and social pleiotropy in microbial cheaters
Authors: Manhes Pauline , Schaal Kaitlin A. , Velicer Gregory J. 
Published: August 2022

AbstractCooperation is widespread among microbes. One mechanism proposed to constrain cheating is antagonistic pleiotropy, wherein mutations that cause defection from cooperation, while potentially under positive selection for this effect, reduce fitness at other traits. The bacterium Myxococcus xanthus engages in pleiotropically connected complex multicellular behaviors, including motility, predation, and starvation-induced fruiting-body development. Sporulation during development is susceptible to cheating. Here we investigate pleiotropic impacts on how cheater spores respond to stressful environmental changes after development, relative to cooperator spores. A cheater with a mutation in the developmental-signaling gene asgB shows antagonistic pleiotropy under both heat and basic-pH stress, while a cheater mutated at csgA shows synergistic pleiotropy under basic-pH stress. Further, in a social form of pleiotropy, cooperator spores formed in mixture with the asgB cheater are less resilient under basic pH than those from pure groups; interaction of cooperators with cheaters reduces the cooperators’ physical robustness. Our results indicate that, depending on the mutation, pleiotropy can promote as well as limit cheating alleles. They additionally demonstrate that alleles can pleiotropically alter traits in organisms not carrying those alleles. Synergistic and social pleiotropy may contribute to shaping the evolutionary dynamics of cooperation and cheating in many social systems.
Unraveling the Myotis Morass: Ultraconserved-Element Analysis Reveals Introgression, Cryptic Diversity, and Taxonomic Trouble in the Most Species-rich Bat Genus
Authors: Korstian Jennifer M. , Stevens Richard D. , Lee Thomas E. , Baker Robert J. , Ray David A. 
Published: August 2022

AbstractUsing sequences from 2615 UCE loci and multiple methodologies we inferred phylogenies for the largest genetic dataset of New World Myotis to date. The resulting phylogenetic trees were populated with short branch lengths and widespread conflict, hallmarks consistent with rapid adaptive radiations. The degree of conflict observed in Myotis has likely contributed to difficulties disentangling deeper evolutionary relationships. Unlike earlier phylogenies based on 1-2 gene sequences, this UCE dataset places M. brandtii outside the New World clades. Introgression testing of a small subset of our samples revealed evidence of historical but not contemporary gene flow, suggesting that hybridization occurs less frequently in the Neotropics than the Nearctic. We identified several instances of cryptic lineages within described species as well as several instances of potential taxonomic over-splitting. Evidence from Central and South American localities suggests that diversity in those regions is not fully characterized. In light of the accumulated evidence of the evolutionary complexity in Myotis and our survey of the taxonomic implications from our phylogenies it is apparent that the definition of species and regime of species delimitation need to be re-evaluated for Myotis. This will require substantial collaboration and sample sharing between geneticists and taxonomists to build a system that is both robust and applicable in a genus as diverse as Myotis.
Directed differentiation of mouse pluripotent stem cells into functional lung-specific mesenchyme
Authors: Alber Andrea B. , Marquez Hector A. , Ma Liang , Kwong George , Thapa Bibek R. , Villacorta-Martin Carlos , Lindstrom-Vautrin Jonathan , Bawa Pushpinder , Luo Yongfeng , Ikonomou Laertis , Shi Wei , Kotton Darrell N. 
Published: August 2022

AbstractThe successful generation of endodermal, ectodermal, and most mesodermal lineages from pluripotent stem cells has resulted in basic discoveries and regenerative medicine clinical trials of cell-based therapies. In contrast, the derivation of tissue-specific mesenchyme via directed differentiation in vitro has markedly lagged, due in part to a limited understanding of the signaling pathways regulating in vivo mesenchymal development and a lack of specific markers or reporters able to purify such lineages. The derivation of lung-specific mesenchyme is a particularly important goal since this tissue plays important roles in lung development and respiratory disease pathogenesis. Here we generate a mouse induced pluripotent stem cell (iPSC) line carrying a lung-specific mesenchymal reporter/lineage tracer facilitating the tracking and purification of engineered lung-specific mesenchyme. We identify the key signaling pathways (RA and Shh) necessary to specify lung mesenchyme from lateral plate mesodermal precursors and find that mouse iPSC-derived lung mesenchyme (iLM) expresses the molecular and functional phenotypes of primary developing lung mesenchyme. Purified iLM can be recombined with separately engineered lung epithelial progenitors, self-organizing into 3-dimensional organoids featuring significantly augmented structural complexity and lineage purity, including interacting juxtaposed layers of epithelium and mesenchyme. Co-culture with iLM increases the yield of lung epithelial progenitors and impacts epithelial and mesenchymal differentiation programs, suggesting functional epithelial-mesenchymal crosstalk. Our iPSC-derived population thus expresses key features of developing lung mesenchyme, providing an inexhaustible source of cells for studying lung development, modeling diseases, and developing therapeutics.