bluuebunny/crossref_metadata_2025_split huggingface dataset:
Evolution of median fin patterning and modularity in living and fossil osteichthyans
Authors: Charest France , Fernández Jorge Mondéjar , Grünbaum Thomas , Cloutier Richard 
Published: July 2022

AbstractMorphological and developmental similarities, and interactions among developing structures are interpreted as evidences of modularity. Such similarities exist between the dorsal and anal fins of living actinopterygians: (1) both fins differentiate in the same direction [dorsal and anal fin patterning module (DAFPM)], and (2) radials and lepidotrichia differentiate in the same direction [endoskeleton and exoskeleton module (EEM)]. To infer the evolution of these common developmental patternings among osteichthyans, we address (1) the complete description and quantification of the DAFPM and EEM in a living actinopterygian (the rainbow troutOncorhynchus mykiss) and (2) the presence of these modules in fossil osteichthyans (coelacanths, lungfishes, porolepiforms and ‘osteolepiforms’). InOncorhynchus, sequences of skeletal elements are determined based on (1) apparition (radials and lepidotrichia), (2) chondrification (radials), (3) ossification (radials and lepidotrichia), and (4) segmentation plus bifurcation (lepidotrichia). Correlations are then explored between sequences. In fossil osteichthyans, sequences are determined based on (1) ossification (radials and lepidotrichia), (2) segmentation, and (3) bifurcation of lepidotrichia. Segmentation and bifurcation patterns were found crucial for comparisons between living and extinct taxa. Our data suggest that the EEM is plesiomorphic at least for actinopterygians, and the DAFPM is plesiomorphic for osteichthyans, with homoplastic dissociation. Finally, recurrent patterns suggest the presence of a Lepidotrichia Patterning Module (LPM).
GroovDB: A database of ligand-inducible transcription factors
Authors: d’Oelsnitz Simon , Ellington Andrew D. 
Published: July 2022

AbstractGenetic biosensors are integral to synthetic biology. In particular, ligand-inducible prokaryotic transcription factors are frequently used in high-throughput screening, for dynamic feedback regulation, as multi-layer logic gates, and in diagnostic applications. In order to provide a curated source that users can rely on for engineering applications, we have developed GroovDB (available at https://groov.bio), a Web-accessible database of ligand-inducible transcription factors that contains all information necessary to build chemically-responsive genetic circuits, including biosensor sequence, ligand, and operator data. Ligand and DNA interaction data has been verified against the literature, while an automated data curation pipeline is used to programmatically fetch metadata, structural information, and references for every entry. A custom tool to visualize the natural genetic context of biosensor entries provides additional information that provides potential insights into alternative ligands and systems biology.
Fixing reference errors efficiently improves sequencing results
Authors: Behera S. , LeFaive J. , Orchard P. , Mahmoud M. , Paulin L. F. , Farek J. , Soto D. C. , Parker Stephen C.J. , Smith A. V. , Dennis M. Y. , Zook J. M. , Sedlazeck F.J. 
Published: July 2022

AbstractThe GRCh38 reference is the current standard in human genomics research and clinical applications, but includes errors across 33 protein-coding genes, including 12 with medical relevance. Current studies rely on the correctness of this reference genome and require an accurate and cost-effective way to improve variant calling and expression analysis across these erroneous loci. We identified likely artifacts in GTEx, gnomAD, 1000 Genomes Project, and other important genomic resources leading to wrong interpretations for these genes. Here, we present FixItFelix together with a modified GRCh38 version that improves the subsequent analysis across these genes within minutes for an existing BAM/CRAM file. We showcase these improvements over multi-ethnic control samples across short and long-read DNA-, and RNA-sequencing. Furthermore, applying our approach across thousands of genomes demonstrates improvements for population variant calling as well as eQTL studies. Still, some genes e.g., DUSP22 indicate mixed results due to their complexity.
COVID-19-associated pulmonary aspergillosis in immunocompetent patients: A virtual patient cohort study
Authors: Ribeiro Henrique AL , Scindia Yogesh , Mehrad Borna , Laubenbacher Reinhard 
Published: July 2022

AbstractPurposeThe opportunistic fungusAspergillus fumigatusinfects the lungs of immunocompromised hosts, including patients undergoing chemotherapy or organ transplantation. More recently however, immunocompetent patients with severe SARS-CoV2 have been reported to be affected by COVID-19 Associated Pulmonary Aspergillosis (CAPA), in the absence of the conventional risk factors for invasive aspergillosis. This paper explores the hypothesis that contributing causes are the destruction of the lung epithelium permitting colonization by opportunistic pathogens. At the same time, the exhaustion of the immune system, characterized by cytokine storms, apoptosis, and depletion of leukocytes may hinder the response toA. fumigatusinfection. The combination of these factors may explain the onset of invasive aspergillosis in immunocompetent patients.MethodsWe used a previously published computational model of the innate immune response to infection withAspergillus fumigatus. Variation of model parameters was used to create a virtual patient population. A simulation study of this virtual patient population to test potential causes for co-infection in immunocompetent patients.ResultsThe two most important factors determining the likelihood of CAPA were the inherent virulence of the fungus and the effectiveness of the neutrophil population, as measured by granule half-life and ability to kill fungal cells. Varying these parameters across the virtual patient population generated a realistic distribution of CAPA phenotypes observed in the literature.ConclusionsComputational models are an effective tool for hypothesis generation. Varying model parameters can be used to create a virtual patient population for identifying candidate mechanisms for phenomena observed in actual patient populations.
No evidence of theory of mind reasoning in the human language network
Authors: Shain Cory , Paunov Alexander , Chen Xuanyi , Lipkin Benjamin , Fedorenko Evelina 
Published: July 2022

AbstractLanguage comprehension and the ability to infer others’ thoughts (theory of mind, ToM) are interrelated during development and language use. However, neural evidence that bears on the relationship between language and ToM mechanisms is mixed. Although robust dissociations have been reported in brain disorders, brain activations for contrasts that target language and ToM bear similarities, and some have reported overlap (Deen et al., 2015). We take another look at the language-ToM relationship by evaluating the response of the language network (Fedorenko et al., 2010), as measured with fMRI, to verbal and non-verbal ToM across 151 participants. Individual-subject analyses reveal that all core language regions respond more strongly when participants read vignettes about false beliefs compared to the control vignettes. However, we show that these differences are largely due to linguistic confounds, and no such effects appear in a non-verbal ToM task. These results argue against cognitive and neural overlap between language processing and ToM. In exploratory analyses, we find responses to social processing in the “periphery” of the language network—right hemisphere homotopes of core language areas and areas in bilateral angular gyri—but these responses are not selectively ToM-related and may reflect general visual semantic processing.
NeuVue: A Framework and Workflows for High-Throughput Electron Microscopy Connectomics Proofreading
Authors: Xenes Daniel , Kitchell Lindsey M. , Rivlin Patricia K. , Brodsky Rachel , Gooden Hannah , Joyce Justin , Luna Diego , Norman-Tenazas Raphael , Ramsden Devin , Romero Kevin , Rose Victoria , Villafane-Delgado Marisel , Gray-Roncal William , Wester Brock 
Published: July 2022

1.AbstractNeuVue is a software platform created for large-scale proofreading of machine segmentation and neural circuit reconstruction in high-resolution electron microscopy connectomics datasets. The NeuVue platform provides a robust web-based interface for proofreaders to collaboratively view, annotate, and edit segmentation and connectivity data. A backend queuing service organizes proofreader tasks into purpose-driven task types and increases proofreader throughput by limiting proofreader actions to simple, atomic operations. A collection of analytical dashboards, data visualization tools, and Application Program Interface (API) capabilities provide stakeholders real-time access to proofreading progress at an individual proofreader level as well as insights on task generation priorities. NeuVue is agnostic to the underlying data being proofread and improves upon the traditional proofreader experience through quality-of-life features that streamline complex editing operations such as splitting and merging objects in dense nanoscale segmentation.NeuVue heavily leverages cloud resources to enable proofreaders to simultaneously access and edit data on the platform. Production-quality features such as load-balancing, auto-scaling, and pre-deployment testing are all integrated into the platform’s cloud architecture. Additionally, NeuVue is powered by well-supported open-source connectomics tools from the community such as Neuroglancer, PyChunkedGraph, and Connectomics Annotation Versioning Engine (CAVE). The modular design of NeuVue facilitates easy integration and adoption of useful community tools to allow proofreaders to take advantage of the latest improvements in data visualization, processing, and analysis.We demonstrate our framework through proofreading of the mouse visual cortex data generated on the IARPA MICrONS Project. This effort has yielded over 40,000 proofreader edits across the 2 petavoxels of “Minnie” neuroimaging data. 44 unique proofreaders of various skill levels have logged a cumulative 3,740 proofreading hours, and we have been able to validate the improved connectivity of thousands of neurons in the volume. With sustained development on the platform, new integrated error detection and error correction capabilities, and continuous improvements to the proofreader model, we believe that the NeuVue framework can enable high-throughput proofreading for large-scale connectomics datasets of the future.
Interpreting single-step genomic evaluations as mixed effects neural networks of three layers: pedigree, genotypes, and phenotypes
Authors: Zhao Tianjing , Cheng Hao 
Published: July 2022

ABSTRACTThe single-step approach has become the most widely-used methodology for genomic evaluations when only a subset of phenotyped individuals in the pedigree are genotyped, where the genotypes for non-genotyped individuals are imputed based on gene contents of genotyped individuals through their pedigree relationships. We proposed a new method named single-step NN-MM to represent the single-step genomic evaluations as mixed effects neural networks of three sequential layers: pedigree, genotypes, and phenotypes, where the gene contents of non-genotyped individuals are sampled based on pedigree, genotypes, and phenotypes. In simulation analysis, the single-step NN-MM had similar or better prediction performance than the conventional single-step approach. In addition to imputation of genotypes using three sources of information including phenotypes, genotypes, and pedigree, single-step NN-MM provides a more flexible framework to allow nonlinear relationships between genotypes and phenotypes, and individuals being genotyped with different SNP panels. The single-step NN-MM has been implemented in a package called “JWAS”.
Phase Heterogeneity in Cholesterol-containing Ternary Phospholipid Lamellar Phases
Authors: Gater Deborah L. , Hughes Keontré I. , Stojanoff Vivian , Isakovic A. F. 
Published: July 2022

AbstractPseudo-ternary mixtures of lamellar phase phospholipids (DPPC and brain sphingomyelin with cholesterol) were studied below Tm, while comparing the influence of cholesterol content, temperature and the presence of small quantities of Vitamin D binding protein (DBP) or Vitamin D receptor (VDR). The measurements, conducted by X-ray diffraction (XRD) and nuclear magnetic resonance (NMR), cover a range of cholesterol concentrations (20% mol. wt to 40% mol. wt.) and physiologically relevant temperature range (294 K – 314 K). In addition to rich intra-phase behaviour, data and modelling are used to approximate the lipids’ headgroup location variations under the above-mentioned experimental conditions.
Metabolic network models ofGardnerellapangenome identify interactions in the vaginal environment
Authors: Dillard Lillian R , Glass Emma M , Lewis Amanda L , Thomas-White Krystal , Papin Jason A 
Published: July 2022

AbstractGardnerellais the primary pathogenic bacterial genus present in the polymicrobial infection known as bacterial vaginosis (BV). Despite BV’s high prevalence and associated chronic and acute women’s health impacts, theGardnerellapangenome is largely uncharacterized at both the genetic and functional metabolic level. Here, we used genome scale metabolic models to characterizein silicotheGardnerellapangenome metabolic content and assessed metabolic functional capacity within a BV positive cervicovaginal fluid context. Metabolic capacity varied widely across the pangenome, with 38.15% of all reactions as core to the genus, compared to 49.6% of reactions identified as unique to a smaller subset of species. Four genes –gpsA, fas, suhB, psd– were identified as core essential genes, critical forin silicometabolic function of all analyzed bacterial species in theGardnerellagenus. Further understanding of these core essential metabolic functions could inform novel therapeutic strategies to treat BV. These data represent the first metabolic modelling of theGardnerellapangenome and illustrate strain-specific interactions with the vaginal metabolic environment across the pangenome.
Prediction models of bronchopulmonary dysplasia: a systematic review and meta-analysis with validation
Authors: Kwok T’ng Chang , Batey Natalie , Luu Ka Ling , Prayle Andrew , Sharkey Don 
Published: July 2022

AbstractIntroductionNeonatal bronchopulmonary dysplasia (BPD) is associated with lifelong respiratory and neurological sequalae. Prediction models could identify infants at greatest risk of BPD and allow targeted preventative strategies. We performed a systematic review and meta-analysis with external validation of identified models.MethodsStudies using predictors available before day 14 of life to predict BPD in very preterm infants were included. Two reviewers assessed 7,628 studies for eligibility. Meta-analysis of externally validated models was followed by validation using 62,864 very preterm infants in England and Wales.Results64 studies using 53 prediction models were included totalling 274,407 infants (range 32–156,587/study). 35 (55%) studies predated 2010; 39 (61%) were single-centre studies. 46 (87%) models were developed for the first week of life. Overall, 97% of studies had a high risk of bias, especially in the analysis domain. Internal (25%) and external (30%) validation were performed infrequently in the 44 model derivation studies. Following meta-analysis of 22 BPD and 11 BPD/death composite models, Laughon’s day one model was the most promising in predicting BPD and death with a fair C-statistic of 0.76 (95% CI 0.70–0.81) and good calibration. Six models were externally validated in our cohort with a C-statistic between 0.70 to 0.90 but with poor calibration.ConclusionFew BPD prediction models were developed with contemporary populations, underwent external validation, or had calibration and impact analyses. To reduce the adverse impact of BPD, we need contemporary, validated, and dynamic prediction models to allow targeted preventative strategies.What is the key question?This review aims to provide a comprehensive assessment of all BPD prediction models developed to address the clinical uncertainty of which predictive model is sufficiently valid and generalisable for use in clinical practice and research.What is the bottom line?Published BPD prediction models are mostly outdated, single centre and lack external validation.Why read on?Laughon’s 2011 model is the most promising but more robust models, using contemporary data with external validation are needed to support better treatments.
Streptomycin and Pyridomycin drug molecules provide the most potential inhibitors against Rv3871 to cure Tuberculosis
Authors: Bhushan Shikha , Raja Yashpal Singh , Mishra Surya 
Published: July 2022

AbstractThe ESX-1 secretion system of Mycobacterium tuberculosis delivers bacterial virulence factors to host cells during infection. The most abundant factor, the ESAT-6/CFP-10 dimer, is targeted for secretion via a C-terminal signal sequence on CFP-10 that is recognized by the cytosolic ATPase, Rv3871. ATPase that is a component of the ESAT-6/CFP-10 secretion system. ESX locus contains genes encoding conserved secretion machinery components termed EccCb1. these core components are required for ESAT-6/CFP-10 secretion [70, 71]. Rv3871 is a cytoplasmic protein connected with the Rv3870 and encoded by the EccCb1 gene. These proteins supply energy for the secretion process. Each of these ATPases is involved in targeting protein for ESX-1 secretion. EccCb1 binds a seven amino acid C-terminal signal peptide of CFT-10, which is required for secretion of the ESAT-6/CFP-10 complex. In this we target the Rv3871 seven amino acid c-terminal region and block it through multiple drugs so, it cannot be activated by the ATPases and not to supply energy for the secretion protein during infection (Tuberculosis). In the present study we have comparatively studied different Rv3871 inhibitory antagonist drug molecule which could be a potential drug molecule to inhibit ATPases on the Rv3871 molecule that is responsible for the energy supply. We have 16 antagonistic drug molecules as shortlisted based on previous studies, that block the target site on the Rv3871 molecule.
Compositional profiling of EV-lipoprotein mixtures by AFM nanomechanical imaging
Authors: Ridolfi Andrea , Conti Laura , Brucale Marco , Frigerio Roberto , Cardellini Jacopo , Musicò Angelo , Romano Miriam , Zendrini Andrea , Polito Laura , Bergamaschi Greta , Gori Alessandro , Montis Costanza , Barile Lucio , Berti Debora , Radeghieri Annalisa , Bergese Paolo , Cretich Marina , Valle Francesco 
Published: July 2022

AbstractThe widely overlapping physicochemical properties of lipoproteins (LPs) and extracellular vesicles (EVs) represents one of the main obstacles for the isolation and characterization of these pervasive biogenic lipid nanoparticles. We herein present the application of an atomic force microscopy (AFM)-based quantitative morphometry assay to the rapid nanomechanical screening of mixed LPs and EVs samples.The method can determine the diameter and the mechanical stiffness of hundreds of individual nanometric objects within few hours. The obtained diameters are in quantitative accord with those measured via cryo-electron microscopy (cryo-EM); the assignment of a specific nanomechanical readout to each object enables the simultaneous discrimination of co-isolated EVs and LPs even if they have overlapping size distributions. EVs and all classes of LPs are shown to be characterized by specific combinations of diameter and stiffness, thus making it possible to estimate their relative abundance in EV/LP mixed samples in terms of stoichiometric ratio, surface area and volume. As a side finding, we show how the mechanical behaviour of specific LP classes is correlated to distinctive structural features revealed by cryo-EM. To the best of our knowledge, these results represent the first systematic single-particle mechanical investigation of lipoproteins.The described approach is label-free, single-step and relatively quick to perform. Importantly, it can be used to analyze samples which prove very challenging to assess with several established techniques due to ensemble-averaging, low sensibility to small particles, or both, thus providing a very useful tool for quickly assessing the purity of EV/LP isolates including plasma- and serum-derived preparations.
Age-related Macular Degeneration is associated with faster rates of structural brain changes and widespread differences in connectivity
Authors: Stout Jacques A , Dai Rui , Anderson Robert J , Cousins Scott , Zhuang Jie , Lad Eleonora M , Whitaker Diane , Madden David , Potter Guy , Whitson Heather E , Badea Alexandra 
Published: July 2022

AbstractAge-related macular degeneration (AMD) is a prevalent disease impeding vision. More recently, AMD has also been linked to cognitive impairment, such as deficits in language and memory skills. In order to better understand the extent of AMD-related changes in the whole brain structure and connectivity, we have conducted an MRI diffusion acquisition study on 40 participants (20 diagnosed with AMD and 20 controls). These acquisitions were then performed again in a follow up two years later. We developed novel analysis methods for diffusion based tractography and connectomes to better determine which, if any, brain region connections saw the greatest changes between the AMD and the age-matched control groups. Using voxel-based analysis, we identified atrophy in AMD participants in the cuneate gyrus, which has been associated with vision, and the left superior temporal gyrus, which has been associated with language, while later acquisitions compounded this with a deficiency in the bilateral cingulate gyrus, itself linked to higher cognition and memory. These regional atrophy findings support that people with AMD experience widespread neuronal degradation that is not limited to retinal neurons. Regions that saw drastically lowered fractional anisotropy among AMD vs. control included the visual cortex, such as the bilateral occipital lobe and the frontoparietal cortex. Tensor Network Principal Component Analysis (TN-PCA) isolated lingual and temporal connections as important differentiators of AMD connectomes compared to controls, thus supporting our morphometric and texture findings in regions related to vision, but also connectopathies of language and memory brain regions. Bundle based analyses in baseline data revealed that the lingual gyrus had greater spread of tracts overall in the AMD participants, which may be explained by prior reorganization in this area, demonstrating a connection between retinal health and lingual structure. Moreover, we noted group differences in the interhemispheric temporal connections, and lingual cerebellar connections, supporting extensive downstream effects of vision loss. Our bundle-based analyses expand the toolset available for neuroimaging-based phenotyping, and reveal widespread changes in AMD participants beyond brain regions and tractography networks directly involved in vision processing, including those involved in language and memory.