bluuebunny/crossref_metadata_2025_split huggingface dataset:
Predicting a Positive Antibody Response After 2 SARS-CoV-2 mRNA Vaccines in Transplant Recipients: A Machine Learning Approach With External Validation
Authors: Alejo Jennifer L. , Mitchell Jonathan , Chiang Teresa P.-Y. , Chang Amy , Abedon Aura T. , Werbel William A. , Boyarsky Brian J. , Zeiser Laura B. , Avery Robin K. , Tobian Aaron A.R. , Levan Macey L. , Warren Daniel S. , Massie Allan B. , Moore Linda W. , Guha Ashrith , Huang Howard J. , Knight Richard J. , Gaber Ahmed Osama , Ghobrial Rafik Mark , Garonzik-Wang Jacqueline M. , Segev Dorry L. , Bae Sunjae 
Published: July 2022

Background.
Solid organ transplant recipients (SOTRs) are less likely to mount an antibody response to SARS-CoV-2 mRNA vaccines. Understanding risk factors for impaired vaccine response can guide strategies for antibody testing and additional vaccine dose recommendations.

Methods.
Using a nationwide observational cohort of 1031 SOTRs, we created a machine learning model to explore, identify, rank, and quantify the association of 19 clinical factors with antibody responses to 2 doses of SARS-CoV-2 mRNA vaccines. External validation of the model was performed using a cohort of 512 SOTRs at Houston Methodist Hospital.

Results.
Mycophenolate mofetil use, a shorter time since transplant, and older age were the strongest predictors of a negative antibody response, collectively contributing to 76% of the model’s prediction performance. Other clinical factors, including transplanted organ, vaccine type (mRNA-1273 versus BNT162b2), sex, race, and other immunosuppressants, showed comparatively weaker associations with an antibody response. This model showed moderate prediction performance, with an area under the receiver operating characteristic curve of 0.79 in our cohort and 0.67 in the external validation cohort. An online calculator based on our prediction model is available at http://transplantmodels.com/covidvaccine/.

Conclusions.
Our machine learning model helps understand which transplant patients need closer follow-up and additional doses of vaccine to achieve protective immunity. The online calculator based on this model can be incorporated into transplant providers’ practice to facilitate patient-centric, precision risk stratification and inform vaccination strategies among SOTRs.
Class imbalance should not throw you off balance: Choosing the right classifiers and performance metrics for brain decoding with imbalanced data
Authors: Thölke Philipp , Mantilla-Ramos Yorguin-Jose , Abdelhedi Hamza , Maschke Charlotte , Dehgan Arthur , Harel Yann , Kemtur Anirudha , Berrada Loubna Mekki , Sahraoui Myriam , Young Tammy , Bellemare Pépin Antoine , El Khantour Clara , Landry Mathieu , Pascarella Annalisa , Hadid Vanessa , Combrisson Etienne , O’Byrne Jordan , Jerbi Karim 
Published: July 2022

AbstractMachine learning (ML) is increasingly used in cognitive, computational and clinical neuroscience. The reliable and efficient application of ML requires a sound understanding of its subtleties and limitations. Training ML models on datasets with imbalanced classes is a particularly common problem, and it can have severe consequences if not adequately addressed. With the neuroscience ML user in mind, this paper provides a didactic assessment of the class imbalance problem and illustrates its impact through systematic manipulation of data imbalance ratios in (i) simulated data and (ii) brain data recorded with electroencephalography (EEG) and magnetoencephalography (MEG). Our results illustrate how the widely-used Accuracy (Acc) metric, which measures the overall proportion of successful predictions, yields misleadingly high performances, as class imbalance increases. Because Acc weights the per-class ratios of correct predictions proportionally to class size, it largely disregards the performance on the minority class. A binary classification model that learns to systematically vote for the majority class will yield an artificially high decoding accuracy that directly reflects the imbalance between the two classes, rather than any genuine generalizable ability to discriminate between them. We show that other evaluation metrics such as the Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC), and the less common Balanced Accuracy (BAcc) metric – defined as the arithmetic mean between sensitivity and specificity, provide more reliable performance evaluations for imbalanced data. Our findings also highlight the robustness of Random Forest (RF), and the benefits of using stratified cross-validation and hyperprameter optimization to tackle data imbalance. Critically, for neuroscience ML applications that seek to minimize overall classification error, we recommend the routine use of BAcc, which in the specific case of balanced data is equivalent to using standard Acc, and readily extends to multi-class settings. Importantly, we present a list of recommendations for dealing with imbalanced data, as well as open-source code to allow the neuroscience community to replicate and extend our observations and explore alternative approaches to coping with imbalanced data.
Regulation of mRNA transcripts, protein isoforms, glycosylation and spatial localization of ACE2 and other SARS-CoV-2-associated molecules in human airway epithelium upon viral infection and type 2 inflammation
Authors: Stocker N , Radzikowska U , Wawrzyniak P , Tan G , Huang M , Ding M , Akdis CA , Sokolowska M 
Published: July 2022

AbstractSARS-CoV-2 infection continues to pose a significant life threat, especially in patients with comorbidities. It remains unknown, if asthma or allergen- and virus-induced airway inflammation are risk factors or can constitute some forms of protection against COVID-19. ACE2 and other SARS-CoV-2-related host proteins are limiting factors of an infection, expression of which is regulated in a more complex way than previously anticipated. Hence, we studied the expression of ACE2 mRNA and protein isoforms, together with its glycosylation and spatial localization in house dust mite (HDM)-, interleukin-13 (IL-13)- and human rhinovirus (RV)-induced inflammation in the primary human bronchial airway epithelium of healthy subjects and patients with asthma. IL-13 decreased the expression of long ACE2 mRNA and glycosylation of full-length ACE2 protein via alteration of the N-linked glycosylation process, limiting its availability on the apical side of ciliated cells. RV infection increased short ACE2 mRNA, but it did not influence its protein expression. HDM exposure did not affect ACE2 mRNA or protein. IL-13 and RV significantly regulated mRNA, but not protein expression of TMPRSS2 and NRP1. Regulation of ACE2 and other host proteins was similar in healthy and asthmatic epithelium, underlining the lack of intrinsic differences, but rather the dependence on the inflammatory milieu in the airways.
Signatures for Viral Infection and Inflammation in the Proximal Olfactory System in Familial Alzheimer’s Disease
Authors: Bubak Andrew N. , Merle Laetitia , Niemeyer Christy S. , Baxter B. Dnate’ , Polese Arianna Gentile , Ramakrishnan Vijay , Gomez Johana , Madrigal Lucia , Villegas-Lanau Andres , Lopera Francisco , Macklin Wendy , Frietze Seth , Nagel Maria A. , Restrepo Diego 
Published: July 2022

AbstractObjectiveAlzheimer’s disease (AD) is characterized by loss of smell and olfactory system pathology that precedes the diagnosis of dementia. Understanding these early processes can potentially identify diagnostic and therapeutic targets to slow AD progression. Here we analyzed differential gene and protein expression in the olfactory bulb (OB) and olfactory tract (OT) of familial AD (FAD) individuals carrying the autosomal dominant presenilin 1 E280A paisa mutation and age-matched controls.MethodsFormalin-fixed, paraffin-embedded sections containing both the OB and OT from 6 FAD individuals and 6 age-matched controls were obtained. Tissue morphology and composition were characterized by immunohistochemistry using antibodies against the myelin marker proteolipid protein (PLP), amyloid-beta (Aβ), and microglia/macrophage markers Iba1 and CD68, respectively. OB and OT were analyzed separately by targeted RNA sequencing of the whole human transcriptome (BioSpyder TempO-Seq); ingenuity pathway analysis and R-computational program were used to identify differentially expressed genes and pathways between groups. The nanoString spatial proteomics assay for 88 proteins, including markers for AD and immune responses, was used to complement gene expression findings.ResultsCompared to control OT, FAD OT had significantly increased immunostaining for Aβ and CD68 in the high and low myelinated regions, as well as increased immunostaining for Iba1 in the high myelinated region only; both control and FAD OT samples had similar total area of high and low myelinated regions. In FAD samples, RNA sequencing showed a transcription profile consistent with: (1) viral infection in the OB; (2) inflammation in the OT that carries information via entorhinal cortex from the OB to hippocampus, a brain region essential for learning and memory; and (3) decreased oligodendrocyte deconvolved transcripts, indicating dysregulation of myelination. Interestingly, spatial proteomic analysis confirmed altered myelination in the OT of FAD individuals, implying dysfunction of communication between the OB and hippocampus.ConclusionsThese findings raise the possibility that viral infection and associated inflammation and dysregulation of myelination of the olfactory system may disrupt downstream hippocampal function, contributing to acceleration of FAD progression.
Probabilistic integration of transcriptome-wide association studies and colocalization analysis prioritizes molecular pathways of complex traits
Authors: Okamoto Jeffrey , Wang Lijia , Yin Xianyong , Luca Francesca , Pique-Regi Roger , Helms Adam , Im Hae Kyung , Morrison Jean , Wen Xiaoquan 
Published: July 2022

AbstractTranscriptome-wide association studies (TWAS) and colocalization analysis are complementary integrative genetic association approaches routinely used to identify functional units underlying complex traits in post-genome-wide association study (post-GWAS) analyses. Recent studies suggest that both approaches are individually imperfect, but joint usage can yield robust and powerful inference results. This paper introduces a new statistical framework, INTACT, to perform probabilistic integration of TWAS and colocalization evidence for implicating putative causal genes. This procedure is flexible and can work with a wide range of existing TWAS and colocalization approaches. It has the unique ability to quantify the uncertainty of implicated genes, enabling rigorous control of false-positive discoveries. Taking advantage of this highly-desirable feature, we describe an efficient algorithm, INTACT-GSE, for gene set enrichment analysis based on the integrated TWAS and colocalization analysis results. We examine the proposed computational methods and illustrate their improved performance over the existing approaches through simulation studies. Finally, we apply the proposed methods to the GTEx data and a variety of GWAS summary statistics derived from complex and molecular traits previously analyzed by Hukku et al. and Sinnott-Armstrong et al. We find empirical evidence that the proposed methods improve and complement existing putative gene implication methods and are advantageous in evaluating and identifying key gene sets and biological pathways.
Oral oxycodone self-administration leads to features of opioid addiction in male and female mice
Authors: Slivicki Richard A. , Earnest Tom , Chang Yu-Hsuan , Pareta Rajesh , Casey Eric , Li Jun-Nan , Tooley Jessica , Abiraman Kavitha , Vachez Yvan M. , Wolfe Drew K. , Sackey Jason T. , Gereau Robert W. , Copits Bryan A. , Kravitz Alexxai V. , Creed Meaghan C. 
Published: July 2022

AbstractUse of prescription opioids, particularly oxycodone is an initiating factor driving the current opioid epidemic. There are several challenges with modeling oxycodone abuse. First, prescription opioids including oxycodone are orally self-administered and have different pharmacokinetics and dynamics than morphine or fentanyl which have been more commonly used in rodent research. This oral route of administration determines the pharmacokinetic profile, which then influences the establishment of drug-reinforcement associations in animals. Moreover, the pattern of intake and the environment in which addictive drugs are self-administered are critical determinants of the levels of drug intake, of behavioral sensitization, and of propensity to relapse behavior. These are all important considerations when modeling prescription opioid use, which is characterized by continuous drug access in familiar environments. Thus, to model features of prescription opioid use and the transition to abuse, we designed an oral, homecage-based oxycodone self-administration paradigm. Mice voluntarily self-administer oxycodone in this paradigm without any taste modification such as sweeteners, and the majority exhibit preference for oxycodone, escalation of intake, physical signs of dependence, and reinstatement of seeking after withdrawal. In addition, a subset of animals demonstrate drug taking that is resistant to aversive consequences. This model is therefore translationally relevant and useful for studying the neurobiological substrates of prescription opioid abuse.
Sensory neurons safeguard from mutational inheritance by controlling the CEP-1/p53-mediated DNA damage response in primordial germ cells
Authors: Uszkoreit Simon , Meyer David H. , Rechavi Oded , Schumacher Björn 
Published: July 2022

AbstractThe genome integrity control in primordial germ cells (PGCs) is prerequisite for the inheritance of stable genomes. The PGCs inC. elegansare embedded in a somatic niche that regulates its DNA damage response (DDR). Here, we show that the AMPK-like kinases KIN-29 and AAK-2 are required for arresting PGCs carrying persistent DNA damage. We determined that the ASI neurons, which sense environmental conditions such as nutrient availability, secrete the TGF-beta-like ligand DAF-7 that is recognized by the DAF-1 receptor in PGCs. ASI-dependent DAF-7 signaling regulates the induction of CEP-1/p53 in the PGCs amid persistent DNA damage. Using single worm whole genome sequencing, we establish that defective ASI control of the CEP-1/p53-regulated DDR in PGCs ultimately results in the inheritance ofde novogermline mutations. Our results indicate that sensory neurons safeguard from the inheritance of germline mutations suggesting the possibility that perception of the environment could direct genetic inheritance.One sentence summaryThe ASI sensory neurons regulate the CEP-1/p53-dependent DNA damage response of primordial germ cells via TGF-beta signaling and influence inherited mutational burden.
Persistent homology analysis distinguishes pathological bone microstructure in non-linear microscopy images
Authors: Pritchard Ysanne , Sharma Aikta , Clarkin Claire , Ogden Helen , Mahajan Sumeet , Sánchez-García Rubén J. 
Published: July 2022

ABSTRACTWe present a topological method for the detection and quantification of bone microstructure from non-linear microscopy images. Specifically, we analyse second harmonic generation (SHG) and two photon excited autofluorescence (TPaF) images of bone tissue which capture the distribution of matrix (fibrillar collagen) structure and autofluorescent molecules, respectively. Using persistent homology statistics with a signed Euclidean distance transform filtration on binary patches of images, we are able to quantify the number, size, distribution, and crowding of holes within and across samples imaged at the microscale. We apply our methodology to a previously characterized murine model of skeletal pathology whereby vascular endothelial growth factor expression was deleted in osteocalcin-expressing cells (OcnVEGFKO) presenting increased cortical porosity, compared to wild type (WT) littermate controls. We show significant differences in topological statistics between the OcnVEGFKO and WT groups and, when classifying the males, or females respectively, into OcnVEGFKO or WT groups, we obtain high prediction accuracies of 98.7% (74.2%) and 77.8% (65.8%) respectively for SHG (TPaF) images. The persistence statistics that we use are fully interpretable, can highlight regions of abnormality within an image and identify features at different spatial scales.
Cas9+conditionally immortalized neutrophil progenitors as a tool for genome wide CRISPR screening for neutrophil differentiation and function
Authors: Jong Robyn M. , Ching Krystal L. , Garelis Nicholas E. , Zilinskas Alex , Nguyenla Xammy , Rawal Sagar , Hill Bianca C. , Luckie Bridget A. , Shallow Lillian , Cox Jeffery S. , Barton Gregory M. , Stanley Sarah A. 
Published: July 2022

AbstractNeutrophils are short-lived cells of the innate immune system that play numerous roles in defense against infection, regulation of immune responses, tissue damage and repair, autoimmunity, and other non-communicable diseases. Understanding neutrophil function at a mechanistic level has been hampered by the difficulty of working with primary neutrophils, which die rapidly upon isolation, and the relative paucity of neutrophil cell lines. Murine neutrophil progenitors that are immortalized with estrogen-regulated expression of Hoxb8 differentiate into neutrophils upon withdrawal of estrogen and facilitate the quantitative production of neutrophilsin vitro. Here we report the creation of a Cas9+ER-Hoxb8 neutrophil progenitor cell line that enables both forward and reverse genetic analysis of neutrophils for the first time. By editing progenitors via transduction with sgRNAs, and then withdrawing estrogen, Cas9 edited neutrophils are produced with high efficiency. Importantly, neutrophil differentiation of edited progenitors occurs bothin vitroin cell culture and when transferred into murine recipients. To demonstrate the utility of Cas9+ER-Hoxb8 progenitors for forward genetics, we performed a pooled CRISPR screen to identify factors required for survival during neutrophil differentiation. This screen identified hundreds of genes both negatively and positively selected under differentiation conditions. One of the top hits from this screen wasCebpe, a transcription factor known to be required for neutrophil differentiation from pre-neutrophils to immature neutrophils. Using the progenitor cell line, we also confirmed thatCepbeis required for neutrophil differentiationin vivo, validating the utility of this cell line both for screening and for studyingin vivophenotypes. The genome-wide screen also identified all components of the WASH complex as being required for neutrophil differentiation, a finding that extends the known role of WASH in hematopoietic stem cell differentiation to later stages of neutrophil development. Taken together, we demonstrate that Cas9+ER-Hoxb8 immortalized neutrophils can be used to study neutrophil function bothin vitroandin vivo. This new resource will enable the analysis of the role of neutrophils in numerous disease states using genetics for the first time.
GO Bench: Shared-hub for Universal Benchmarking of Machine Learning-Based Protein Functional Annotations
Authors: Dickson Andrew , Asgari Ehsaneddin , McHardy Alice C. , Mofrad Mohammad R.K. 
Published: July 2022

AbstractMotivationGene annotation is the problem of mapping proteins to their functions represented as Gene Ontology terms, typically inferred based on the primary sequences. Gene annotation is a multi-label multi-class classification problem, which has generated growing interest for its uses in the characterization of millions of proteins with unknown functions. However, there is no standard GO dataset used for benchmarking the newly developed new machine learning models within the bioinformatics community. Thus, the significance of improvements for these models remains unclear.SummaryThe Gene Benchmarking database is the first effort to provide an easy-to-use and configurable hub for the learning and evaluation of gene annotation models. It provides easy access to pre-specified datasets and takes the non-trivial steps of preprocessing and filtering all data according to custom presets using a web interface. The GO bench web application can also be used to evaluate and display any trained model on leaderboards for annotation tasks.Availability and ImplementationThe GO Benchmarking dataset is freely available at llp.berkeley.edu/GO_bench/dataset_form, and code is available at http://github.com/amdson/GO_pipeline.Contactamdickson@berkeley.eduSupplementary informationSupplementary data are available at Bioinformatics online.
Safety and biodistribution of Nanoligomers™ targeting SARS-CoV-2 genome for treatment of COVID-19
Authors: McCollum Colleen R. , Courtney Colleen M. , O’Connor Nolan J. , Aunins Thomas R. , Jordan Tristan X. , Rogers Keegan , Brindley Stephen , Brown Jared M. , Nagpal Prashant , Chatterjee Anushree 
Published: July 2022

AbstractAs the world braces to enter its third year in the coronavirus disease 2019 (COVID-19) pandemic, the need for accessible and effective antiviral therapeutics continues to be felt globally. The recent surge of Omicron variant cases has demonstrated that vaccination and prevention alone cannot quell the spread of highly transmissible variants. A safe and nontoxic therapeutic with an adaptable design to respond to the emergence of new variants is critical for transitioning to treatment of COVID-19 as an endemic disease. Here, we present a novel compound, called SBCoV202, that specifically and tightly binds the translation initiation site of RNA-dependent RNA polymerase within the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome, inhibiting viral replication. SBCoV202 is a Nanoligomer,™ a molecule that includes peptide nucleic acid sequences capable of binding viral RNA with single-base-pair specificity to accurately target the viral genome. The compound has been shown to be safe and nontoxic in mice, with favorable biodistribution, and has shown efficacy against SARS-CoV-2 in vitro. Safety and biodistribution were assessed after three separate administration methods, namely intranasal, intravenous, and intraperitoneal. Safety studies showed the Nanoligomer caused no outward distress, immunogenicity, or organ tissue damage, measured through observation of behavior and body weight, serum levels of cytokines, and histopathology of fixed tissue, respectively. SBCoV202 was evenly biodistributed throughout the body, with most tissues measuring Nanoligomer concentrations well above the compound KD of 3.37 nM. In addition to favorable availability to organs such as the lungs, lymph nodes, liver, and spleen, the compound circulated through the blood and was rapidly cleared through the renal and urinary systems. The favorable biodistribution and lack of immunogenicity and toxicity set Nanoligomers apart from other antisense therapies, while the adaptability of the nucleic acid sequence of Nanoligomers provides a defense against future emergence of drug resistance, making these molecules an attractive potential treatment for COVID-19.