bluuebunny/crossref_metadata_2025_split huggingface dataset:
Aerosolization of viableMycobacterium tuberculosisbacilli by tuberculosis clinic attendees independent of sputum-GeneXpert status
Authors: Patterson Benjamin , Dinkele Ryan , Gessner Sophia , Koch Anastasia , Hoosen Zeenat , January Vanessa , Leonard Bryan , McKerry Andrea , Seldon Ronnett , Vazi Andiswa , Hermans Sabine , Cobelens Frank , Warner Digby F. , Wood Robin 
Published: November 2022

AbstractThe potential for bioaerosol release ofMycobacterium tuberculosis(Mtb) during different tuberculosis (TB) disease states is poorly understood. We quantified viable aerosolizedMtbfrom presumptive TB patients on diagnosis and, thereafter, through six months’ standard chemotherapy. At presentation, TB clinic attendees (n=102) were classified by laboratory, radiological, and clinical features into Group A: Sputum-GeneXpert-positive TB (n=52), Group B: Sputum-GeneXpert-negative TB (n=20), or Group C: TB not diagnosed (n=30). All were assessed forMtbbioaerosol release at baseline, and subsequently at two weeks, two months, and six months. In Groups A and B, comprising notified TB cases,Mtbwas isolated from 92% and 90% of participants at initial presentation; 87% and 74% at two weeks; 54% and 44% at two months; and 32% and 20% at six months, respectively. Surprisingly, similar numbers were detected in Group C: 93%, 70%, 48%, and 22% at the same timepoints. We also observed a temporal association betweenMtbbioaerosol release and TB symptoms in all three groups, with 30% of participants remainingMtbbioaerosol positive at six months irrespective of TB chemotherapy. CapturedMtbbacilli were predominantly acid-fast stain-negative and poorly culturable; however, followingin vitroincubation, one sputum-GeneXpert-positive and two sputum-GeneXpert-negative aerosol samples yielded sufficient biomass for whole-genome sequencing, revealing two differentMtblineages. The detection of viable aerosolizedMtbin most clinic attendees at presentation, independent of TB diagnosis, suggests that unidentifiedMtbtransmitters could account for a significant attributable proportion of community exposure. However, longitudinal studies are required to investigate this possibility.One Sentence Summary:M. tuberculosisbacilli are detected in bioaerosols of presumptive tuberculosis (TB) patients irrespective of final TB diagnosis and clear over time.
A Machine Learning Algorithm to Predict Hypoxic Respiratory Failure and risk of Acute Respiratory Distress Syndrome (ARDS) by Utilizing Features Derived from Electrocardiogram (ECG) and Routinely Clinical Data
Authors: Marshall Curtis Earl , Narendrula Saideep , Wang Jeffrey , De Souza Vale Joao Gabriel , Jeong Hayoung , Krishnan Preethi , Yang Phillip , Esper Annette , Kamaleswaran Rishi 
Published: November 2022

AbstractThe recognition of Acute Respiratory Distress Syndrome (ARDS) may be delayed or missed entirely among critically ill patients. This study focuses on the development of a predictive algorithm for Hypoxic Respiratory Failure and associated risk of ARDS by utilizing routinely collected bedside monitoring. Specifically, the algorithm aims to predict onset over time. Uniquely, and favorable to robustness, the algorithm utilizes routinely collected, non-invasive cardiorespiratory waveform signals. This is a retrospective, Institutional-Review-Board-approved study of 2,078 patients at a tertiary hospital system. A modified Berlin criteria was used to identify 128 of the patients to have the condition during their encounter. A prediction horizon of 6 to 36 hours was defined for model training and evaluation. Xtreme Gradient Boosting algorithm was evaluated against signal processing and statistical features derived from the waveform and clinical data. Waveform-derived cardiorespiratory features, namely measures relating to variability and multi-scale entropy were robust and reliable features that predicted onset up to 36 hours before the clinical definition is met. The inclusion of structured data from the medical record, namely oxygenation patterns, complete blood counts, and basic metabolics further improved model performance. The combined model with 6-hour prediction horizon achieved an area under the receiver operating characteristic of 0.79 as opposed to the first 24-hour Lung Injury Prediction Score of 0.72.
Dynamic modulation of genomic enhancer elements in the suprachiasmatic nucleus mediates daily timekeeping in mammals
Authors: Bafna Akanksha , Banks Gareth , Hastings Michael H. , Nolan Patrick M. 
Published: November 2022

AbstractThe mammalian suprachiasmatic nucleus (SCN), located in the ventral hypothalamus, is crucial for synchronising and resetting all cellular rhythms in accordance with critical environmental and visceral cues. Consequently, the systematic regulation of spatiotemporal gene transcription in the SCN is vital for daily timekeeping. Here, we sought to identify SCN enriched gene regulatory elements that enable temporal gene expression using histone-ChIP-seq. We found a vast majority of SCN enhancers not only exhibit robust 24-hour rhythmic modulation in H3K27ac occupancy, but also possess canonical E-box (CACGTG) motif, potentially influencing downstream cycling gene expression. In parallel, we conducted RNA-Seq at six distinct times to establish enhancer-gene relationships in the SCN. Surprisingly, around 35% of cycling H3K27ac abundance is seen adjacent to rhythmic gene transcripts, often preceding the rise in mRNA levels. We also noted that enhancers encompass non-coding actively transcribing enhancer RNAs (eRNAs), that in turn oscillate along with cyclic histone acetylation to direct gene transcription. Taken together, these findings shed light on genome-wide pre-transcriptional regulation operative in the central clock that enables its orchestration of daily timekeeping mechanisms in mammals.
Autism-specific PTEN p.I135L mutation and an autism genetic background combine to dysregulate cortical neurogenesis
Authors: Fu Shuai , Bury Luke , Eum Jaejin , Wynshaw-Boris Anthony 
Published: November 2022

SUMMARYAlterations in cortical neurogenesis are implicated in neurodevelopmental disorders including autism spectrum disorders (ASDs). The contribution of genetic backgrounds, in additional to ASD risk genes, on cortical neurogenesis remain understudied. Here, using isogenic induced pluripotent stem cell (iPSC)-derived neural progenitor cells (NPCs) and cortical organoid models, we report that a heterozygousPTENp.I135L mutation found in an ASD patient with macrocephaly activates PI3K/AKT and dysregulates cortical neurogenesis in an ASD genetic background-dependent fashion. Transcriptome analysis at both bulk and single cell level revealedPTENp.I135L mutation and ASD genetic background affected genes involved in neurogenesis, neural development and synapse signaling. We also found that thisPTENp.I135L mutation led to overproduction of NPC subtypes as well as neuronal subtypes including both deep and upper layer neurons in its ASD background, but not when introduced into a control genetic background. These findings provide experimental evidence that both aPTENp.I135L mutation and ASD genetic background contribute to cellular features consistent with ASD associated with macrocephaly.
Rapid, automated and experimenter-free assessment of cognitive flexibility reveals learning impairments following recovery from activity-based anorexia in female rats
Authors: Huang Kaixin , Milton Laura K , Dempsey Harry , Power Stephen J , Conn Kyna-Anne , Andrews Zane B , Foldi Claire J 
Published: November 2022

AbstractAnorexia nervosa (AN) has among the highest mortality rates of any psychiatric disorder and is characterised by cognitive inflexibility that persists after weight recovery and contributes to the low rates of recovery. What remains unknown is whether cognitive inflexibility predisposes individuals to AN, a question that is difficult to determine from human studies. Our previous work using the most well-established animal model of AN, known as activity-based anorexia (ABA) identified a neurobiological link between cognitive inflexibility and susceptibility to pathological weight loss in female rats. However, testing flexible learning prior to exposure to ABA in the same animals has been thus far impossible due to the length of training required and the necessity of daily handling, which can itself influence the development of ABA.Here we describe experiments that validate and optimise the first fully-automated and experimenter-free touchscreen cognitive testing system for rats (n=20) and use this novel system to examine the reciprocal links between reversal learning (an assay of cognitive flexibility) and weight loss in the ABA model (n=60). Firstly, we show substantially reduced testing time and increased throughput compared to conventional touchscreen testing methods because animals engage in test sessions at their own direction and can complete multiple sessions per day without experimenter involvement. We also show that, contrary to expectations, cognitive inflexibility does not predispose rats to pathological weight loss in ABA but instead that rats subsequently susceptible to weight loss performed better on the reversal learning task. Intriguingly, we show reciprocal links between ABA exposure and cognitive flexibility, with ABA exposed (but weight recovered) rats performing much worse that ABA naïve rats on the reversal learning task. On the other hand, animals that had been trained on reversal learning were better able to resist weight loss upon subsequent exposure to the ABA model. We also uncovered some stable behavioural differences between ABA susceptible versus resistant rats during touchscreen test sessions using machine learning tools that highlight possible predictors of anorectic phenotypes.These findings shed new light on the relationship between cognitive inflexibility and pathological weight loss and provide a robust target for future studies using the ABA model to investigate potential novel pharmacotherapies for AN.
Tumor proliferation and invasion are coupled through cell-extracellular matrix friction
Authors: Crawford Ashleigh J. , Gomez-Cruz Clara , Russo Gabriella C. , Huang Wilson , Bhorkar Isha , Muñoz-Barrutia Arrate , Wirtz Denis , Garcia-Gonzalez Daniel 
Published: November 2022

AbstractCell proliferation and invasion are two key drivers of tumor progression and are traditionally considered two independent cellular processes regulated by distinct pathways. Throughin vitroandin silicomethods, we provide evidence that these two processes are intrinsically coupled through matrix-adhesion friction. Using novel tumor spheroids, we show that both tumor cell proliferation and invasion are limited by a volumetric carrying capacity of the system, i.e. maximum spatial cell concentration supported by the system’s total cell count, nutrient consumption rate, and collagen gel mechanical properties. To manipulate these phenotypes in breast cancer cells, we modulate the expression of E-cadherin and its associated role in adhesion, invasion, and proliferation. We integrate these results into a mixed-constitutive formulation to computationally delineate the contributions of cellular and extracellular adhesion, stiffness, and mechanical properties of the extracellular matrix (ECM) to the proliferative and invasive fates of breast cancer tumor spheroids. Both approaches conclude that the dominant drivers of tumor fate are system properties modulating cell-ECM friction, such as E-cadherin dependent cell-ECM adhesion and matrix pore size.
Deep Representation Learning Determines Drug Mechanism of Action from Cell Painting Images
Authors: Wong Daniel R. , Logan David J. , Hariharan Santosh , Stanton Robert , Kiruluta Andrew 
Published: November 2022

AbstractFluorescent-based microscopy screens carry a broad range of phenotypic information about how compounds affect cellular biology. From changes in cellular morphology observed in these screens, one key area of medicinal interest is determining a compound’s mechanism of action. However, much of this phenotypic information is subtle and difficult to quantify. Hence, creating quantitative embeddings that can measure cellular response to compound perturbation has been a key area of research. Here we present a deep learning enabled encoder called MOAProfiler that captures phenotypic features for determining mechanism of action from Cell Painting images. We compared our method with both a traditional computer vision means of feature encoding via CellProfiler and a deep learning encoder called DeepProfiler. The results, on two independent and biologically different datasets, indicated that MOAProfiler encoded MOA-specific features that allowed for more accurate clustering and classification of compounds over hundreds of different MOAs.
Chromosomal inversions and the demography of speciation inDrosophila montanaandDrosophila flavomontana
Authors: Poikela N. , Laetsch D. R. , Hoikkala V. , Lohse K. , Kankare M 
Published: November 2022

AbstractChromosomal inversions may play a central role in speciation given their ability to locally reduce recombination and therefore genetic exchange between diverging populations. We analysed long- and short-read whole-genome data from sympatric and allopatric populations of twoDrosophila virilisgroup species,D. montanaandD. flavomontana, to understand if inversions have contributed to their divergence. We identified three large alternatively fixed inversions on the X chromosome and one on each of the autosomes 4 and 5. A comparison of demographic models estimated for inverted and non-inverted (colinear) chromosomal regions suggest that these inversions arose before the time of the species split. We detected a low rate of interspecific gene flow (introgression) fromD. montanatoD. flavomontana, which was further reduced inside inversions and was lower in allopatric than in sympatric populations. Together, these results suggest that the inversions were already present in the common ancestral population, and that gene exchange between the sister taxa was reduced within inversions both before and after the onset of species divergence. Such ancestrally polymorphic inversions may foster speciation by allowing the accumulation of genetic divergence in loci involved in adaptation and reproductive isolation inside inversions early in the speciation process, while gene exchange at colinear regions continues until the evolving reproductive barriers complete speciation. The overlapping X inversions are particularly good candidates for driving the speciation process ofD. montanaandD. flavomontana, since they harbour strong genetic incompatibilities that were detected in a recent study of experimental introgression.SignificanceChromosomal inversions, genomic rearrangements with reversed gene order, have been extensively studied, but it remains unclear whether and how inversions play a role in species divergence. Analysis of long- and short-read whole-genome data for twoDrosophilasister species,D. montanaandD. flavomontana, revealed five alternatively fixed inversions. Modelling the demographic history of these inversions shows that they were segregating already in the common ancestor of the species and that they have reduced gene exchange between these sister taxa both before and after the onset of species divergence. These results are compatible with a scenario in which ancestrally polymorphic inversions aid species divergence by protecting divergently selected loci from erosion via gene flow during the earliest stages of speciation.
PSMC2 and CXCL8-Modulated Four Critical Gene Biomarkers and Druggable and Vaccinable Targets for Colorectal Cancer
Authors: Liu Yongjun , Xu Yuqing , Li Xiaoxing , Chen Mengke , Wang Xueqin , Zhang Ning , Zhang Xiaofei , Zheng Wei , Zhang Heping , Zhang Zhengjun 
Published: November 2022

AbstractTranscriptomic studies have reported numerous differentially expressed genes in colorectal carcinoma (CRC) versus noncancerous tissues. Given the large number of genes identified, it is unclear which ones are the key genes that drive cancer development. To address the issue, we conducted a large-scale study of eight cohorts with thousands of tumor and nontumor samples, analyzed transcriptomic data, and identified the most miniature set of differentially expressed genes (DEGs) that can nearly perfectly describe the overall features of CRC at the genomic level. The analytical framework was built on a recently proven powerful max-linear competing risk factor model. We first analyzed six public transcriptomic datasets and identified four critical DEGs (i.e., CXCL8, PSMC2, APP, and SLC20A1) with nearly perfect (close to 100%) predictive power. The findings were further validated in a newly collected Chinese cohort and another public dataset. Among the four DEGs, PSMC2 and CXCL8 appeared to play a central role, and CXCL8 alone could serve as a biomarker for early-stage CRC. They rise as druggable and vaccinable targets for CRC. This work represents a pioneering effort to identify critical colorectal-specific genes and their interactions that have not been discovered in previous endeavors.Simple SummaryHuman knowledge of cancer is still limited. There don’t exist reliable genomic biomarkers for cancer diagnosis, and truly functional and druggable genomic (gene) targets haven’t been reported. One of the main reasons is due to lack of powerful discovery tools to discover the best possible and accurate miniature set of genes to fight against the cancer war. Our research was motivated by such an urgent need, and we hope our findings can fill up gaps in the literature and medical practice. We focus on colorectal cancers in this paper.
Temporal chromatin accessibility changes define transcriptional states essential for osteosarcoma metastasis
Authors: Pontius W. Dean , Hong Ellen S. , Faber Zachary J. , Gray Jeremy , Peacock Craig , Bayles Ian , Lovrenert Katreya , Bartels Cynthia F. , Scacheri Peter C. 
Published: November 2022

AbstractThe metastasis-invasion cascade describes the series of steps required for a cancer cell to successfully spread from its primary tumor and ultimately grow within a secondary organ. Despite metastasis being a dynamic, multistep process, most omics studies to date have focused on comparing primary tumors to the metastatic deposits that define end-stage disease. This static approach means we lack information about the genomic and epigenomic changes that occur during the majority of tumor progression. One particularly understudied phase of tumor progression is metastatic colonization, during which cells must adapt to the new microenvironment of the secondary organ. Through temporal profiling of chromatin accessibility and gene expressionin vivo, we identify dynamic changes in the epigenome that occur as osteosarcoma tumors form and grow within the lung microenvironment. Furthermore, we show through pairedin vivoandin vitroCRISPR drop-out screens and pharmacological validation that the upstream transcription factors represent a class of metastasis-specific dependency genes. While current models depict lung colonization as a discrete step within the metastatic cascade, our study shows it is a defined trajectory through multiple epigenetic states, revealing new therapeutic opportunities undetectable with standard approaches.
Conformational epistasis impairs AlphaFold structural predictions
Authors: Sawicki Luciana Rodriguez , Benitez Guillermo , Carletti Matias , Palopoli Nicolas , Fornasari Maria Silvina , Parisi Gustavo 
Published: November 2022

AbstractProtein structures have been massively predicted using homologous sequence information. AlphaFold2 (AF2) is a recent breakthrough to predict 3D models using machine learning approaches that reached an outstanding accuracy in recent quality evaluations. However, information derived from extant homologous sequences, as those used by AF2, might not contain enough information to accurately predict protein structure. This limitation could be related to the process known as epistasis, which describes the differential effect of a mutation on the evolutionary trajectory. Clear evidence of conformational epistasis, which has a specific impact on protein structure, was characterized in the evolutionary origin of the glucocorticoid receptor (GR) specificity during its functional divergence from the mineralocorticoid (MR) receptor. In this work we explore how AF2 can reproduce conformations derived from epistatic effects. Using structural clustering and principal component analysis to analyze the structural similarities in 16 and 13 extant GR and MR conformers, respectively, we found that AF2 models for human GR failed to reproduce extant GR conformations. Interestingly, AF2 models for human MR, for which no conformational epistasis was reported, were almost indistinguishable from extant MR. Our results showcase the importance of evolutionary trajectories to predict accurate 3D models.
A synthetic lethal screen for Snail-induced enzalutamide resistance identifies JAK/STAT signaling as a therapeutic vulnerability in prostate cancer
Authors: Ware Kathryn E. , Thomas Beatrice C. , Olawuni Pelumi , Sheth Maya U. , Hawkey Nathan , Yeshwanth M , Miller Brian C. , Vietor Katherine J. , Jolly Mohit Kumar , Kim So Young , Armstrong Andrew J. , Somarelli Jason A. 
Published: November 2022

AbstractDespite substantial improvements in the treatment landscape of prostate cancer, the evolution of hormone therapy-resistant and metastatic prostate cancer remains a major cause of cancer-related death globally. The mainstay of treatment for advanced prostate cancer is targeting of androgen receptor signaling, including androgen deprivation therapy plus second-generation androgen receptor blockade (e.g., enzalutamide, apalutamide, darolutamide), and/or androgen synthesis inhibition (abiraterone). While these agents have significantly prolonged the lives of patients with advanced prostate cancer, the evolution of resistance to these treatments in nearly universal. This therapy resistance is mediated by diverse mechanisms, including both androgen receptor-dependent mechanisms, such as androgen receptor mutations, amplifications, alternatively spliced isoforms, and structural rearrangements, as well as non-androgen receptor-mediated mechanisms, such as lineage plasticity toward neuroendocrine-like or epithelial-mesenchymal transition (EMT)-like lineages. Our prior work identified the EMT transcriptional regulator Snail as critical to hormonal therapy resistance and commonly detected in human metastatic prostate cancer. In the current study, we sought to interrogate the actionable landscape of EMT-mediated hormone therapy-resistant prostate cancer to identify synthetic lethality and collateral sensitivity approaches to treating this aggressive disease state. Using a combination of high-throughput drug screens and multi-parameter phenotyping by confluence imaging, ATP production, and phenotypic plasticity reporters of EMT, we identified candidate synthetic lethalities to Snail-mediated EMT in prostate cancer. These analyses identified multiple actionable targets, such as XPO1, PI3K/mTOR, aurora kinases, c-MET, polo-like kinases, and JAK/STAT as synthetic lethalities in Snail+ prostate cancer. We validated these targets in a subsequent validation screen in an LNCaP-derived model of resistance to sequential androgen deprivation and enzalutamide. This follow-up screen provided validation of inhibitors of JAK/STAT and PI3K/mTOR as therapeutic vulnerabilities for Snail+ and enzalutamide-resistant prostate cancer.