bluuebunny/crossref_metadata_2025_split huggingface dataset:
Improving the identification of miRNA–disease associations with multi-task learning on gene–disease networks
Authors: He Qiang , Qiao Wei , Fang Hui , Bao Yang 
Published: June 2023

Abstract
MicroRNAs (miRNAs) are a family of non-coding RNA molecules with vital roles in regulating gene expression. Although researchers have recognized the importance of miRNAs in the development of human diseases, it is very resource-consuming to use experimental methods for identifying which dysregulated miRNA is associated with a specific disease. To reduce the cost of human effort, a growing body of studies has leveraged computational methods for predicting the potential miRNA–disease associations. However, the extant computational methods usually ignore the crucial mediating role of genes and suffer from the data sparsity problem. To address this limitation, we introduce the multi-task learning technique and develop a new model called MTLMDA (Multi-Task Learning model for predicting potential MicroRNA-Disease Associations). Different from existing models that only learn from the miRNA–disease network, our MTLMDA model exploits both miRNA–disease and gene–disease networks for improving the identification of miRNA–disease associations. To evaluate model performance, we compare our model with competitive baselines on a real-world dataset of experimentally supported miRNA–disease associations. Empirical results show that our model performs best using various performance metrics. We also examine the effectiveness of model components via ablation study and further showcase the predictive power of our model for six types of common cancers. The data and source code are available from https://github.com/qwslle/MTLMDA.
A systematic review of computational methods for designing efficient guides for CRISPR DNA base editor systems
Authors: Giner Göknur , Ikram Saima , Herold Marco J , Papenfuss Anthony T 
Published: June 2023

Abstract
In only a few years, as a breakthrough technology, clustered regularly interspaced short palindromic repeats/CRISPR-associated protein (CRISPR/Cas) gene-editing systems have ushered in the era of genome engineering with a plethora of applications. One of the most promising CRISPR tools, so-called base editors, opened an exciting avenue for exploring new therapeutic approaches through controlled mutagenesis. However, the efficiency of a base editor guide varies depending on several biological determinants, such as chromatin accessibility, DNA repair proteins, transcriptional activity, factors related to local sequence context and so on. Thus, the success of genetic perturbation directed by CRISPR/Cas base-editing systems relies on an optimal single guide RNA (sgRNA) design, taking those determinants into account. Although there is 11 commonly used software to design guides specifically for base editors, only three of them investigated and implemented those biological determinants into their models. This review presents the key features, capabilities and limitations of all currently available software with a particular focus on predictive model-based algorithms. Here, we summarize existing software for sgRNA design and provide a base for improving the efficiency of existing available software suites for precise target base editing.
MASH Native: a unified solution for native top-down proteomics data processing
Authors: Larson Eli J , Pergande Melissa R , Moss Michelle E , Rossler Kalina J , Wenger R Kent , Krichel Boris , Josyer Harini , Melby Jake A , Roberts David S , Pike Kyndalanne , Shi Zhuoxin , Chan Hsin-Ju , Knight Bridget , Rogers Holden T , Brown Kyle A , Ong Irene M , Jeong Kyowon , Marty Michael T , McIlwain Sean J , Ge Ying 
Published: June 2023

Abstract

Motivation
Native top-down proteomics (nTDP) integrates native mass spectrometry (nMS) with top-down proteomics (TDP) to provide comprehensive analysis of protein complexes together with proteoform identification and characterization. Despite significant advances in nMS and TDP software developments, a unified and user-friendly software package for analysis of nTDP data remains lacking.

Results
We have developed MASH Native to provide a unified solution for nTDP to process complex datasets with database searching capabilities in a user-friendly interface. MASH Native supports various data formats and incorporates multiple options for deconvolution, database searching, and spectral summing to provide a “one-stop shop” for characterizing both native protein complexes and proteoforms.

Availability and implementation
The MASH Native app, video tutorials, written tutorials, and additional documentation are freely available for download at https://labs.wisc.edu/gelab/MASH_Explorer/MASHSoftware.php. All data files shown in user tutorials are included with the MASH Native software in the download .zip file.
S1000: a better taxonomic name corpus for biomedical information extraction
Authors: Luoma Jouni , Nastou Katerina , Ohta Tomoko , Toivonen Harttu , Pafilis Evangelos , Jensen Lars Juhl , Pyysalo Sampo 
Published: June 2023

Abstract

Motivation
The recognition of mentions of species names in text is a critically important task for biomedical text mining. While deep learning-based methods have made great advances in many named entity recognition tasks, results for species name recognition remain poor. We hypothesize that this is primarily due to the lack of appropriate corpora.

Results
We introduce the S1000 corpus, a comprehensive manual re-annotation and extension of the S800 corpus. We demonstrate that S1000 makes highly accurate recognition of species names possible (F-score =93.1%), both for deep learning and dictionary-based methods.

Availability and implementation
All resources introduced in this study are available under open licenses from https://jensenlab.org/resources/s1000/. The webpage contains links to a Zenodo project and three GitHub repositories associated with the study.
networkGWAS: a network-based approach to discover genetic associations
Authors: Muzio Giulia , O’Bray Leslie , Meng-Papaxanthos Laetitia , Klatt Juliane , Fischer Krista , Borgwardt Karsten 
Published: June 2023

AbstractMotivationWhile the search for associations between genetic markers and complex traits has led to the discovery of tens of thousands of trait-related genetic variants, the vast majority of these only explain a small fraction of the observed phenotypic variation. One possible strategy to overcome this while leveraging biological prior is to aggregate the effects of several genetic markers and to test entire genes, pathways or (sub)networks of genes for association to a phenotype. The latter, network-based genome-wide association studies, in particular suffer from a vast search space and an inherent multiple testing problem. As a consequence, current approaches are either based on greedy feature selection, thereby risking that they miss relevant associations, or neglect doing a multiple testing correction, which can lead to an abundance of false positive findings.ResultsTo address the shortcomings of current approaches of network-based genome-wide association studies, we propose networkGWAS, a computationally efficient and statistically sound approach to network-based genome-wide association studies using mixed models and neighborhood aggregation. It allows for population structure correction and for well-calibrated P-values, which are obtained through circular and degree-preserving network permutations. networkGWAS successfully detects known associations on diverse synthetic phenotypes, as well as known and novel genes in phenotypes from Saccharomycescerevisiae and Homo sapiens. It thereby enables the systematic combination of gene-based genome-wide association studies with biological network information.Availability and implementationhttps://github.com/BorgwardtLab/networkGWAS.git.
NoVaTeST: identifying genes with location-dependent noise variance in spatial transcriptomics data
Authors: Abrar Mohammed Abid , Kaykobad M , Rahman M Saifur , Samee Md Abul Hassan 
Published: June 2023

AbstractMotivationSpatial transcriptomics (ST) can reveal the existence and extent of spatial variation of gene expression in complex tissues. Such analyses could help identify spatially localized processes underlying a tissue’s function. Existing tools to detect spatially variable genes assume a constant noise variance across spatial locations. This assumption might miss important biological signals when the variance can change across locations.ResultsIn this article, we propose NoVaTeST, a framework to identify genes with location-dependent noise variance in ST data. NoVaTeST models gene expression as a function of spatial location and allows the noise to vary spatially. NoVaTeST then statistically compares this model to one with constant noise and detects genes showing significant spatial noise variation. We refer to these genes as “noisy genes.” In tumor samples, the noisy genes detected by NoVaTeST are largely independent of the spatially variable genes detected by existing tools that assume constant noise, and provide important biological insights into tumor microenvironments.Availability and implementationAn implementation of the NoVaTeST framework in Python along with instructions for running the pipeline is available at https://github.com/abidabrar-bracu/NoVaTeST.
Phylogeography of the grasshopper genusOedipoda(Acrididae: Oedipodinae) in the Mediterranean: classic refugia and cryptic lineages
Authors: Hochkirch Axel , Dey Lara-Sophie , Husemann Martin 
Published: June 2023

AbstractThe evolutionary history and biogeography of species is strongly influenced by climatic conditions and geomorphology. Most thermophilic organisms in Europe have survived colder periods in Mediterranean refugia, which can be inferred from their genetic structure. The band-winged grasshopper genus Oedipoda occurs with nine species in the Mediterranean. We inferred the phylogeny of the western Palaearctic Oedipoda species using gene sequences (two mitochondrial and one nuclear) of a comprehensive sample of most species. Our results show that genetic differentiation between most species is quite strong. Four subspecies (Oedipoda caerulescens amoricana Sellier, 1948 syn. nov., Oedipoda germanica kraussi Ramme, 1931 syn. nov.,Oedipoda fuscocincta moriniDefaut, 2006 syn. nov., and Oedipoda fuscocincta portugalensis Ramme, 1931 syn. nov.) are not supported by our study and are synonymized with the nominate subspecies. Two former subspecies (Oedipoda mauritanica Lucas, 1849 stat. nov. and Oedipoda meridionalis Ramme, 1931 stat. nov.) and one former synonym (Oedipoda pentagonalis Jannone, 1937 stat. nov.) are raised to species level. The status of Oedipoda fuscocincta Lucas, 1847 and Oedipoda coerulea Saussure, 1884 remains unresolved. The subspecies Oedipoda caerulescens sardetiDefaut, 2006 has a wider distribution, including the Iberian Peninsula, southern France, Corsica and Sardinia. The phylogeographic pattern is in line with classic Mediterranean refugia with two waves of differentiation.
Basic fibroblast growth factor induces proliferation and collagen production by fibroblasts derived from the bovine corpus luteum
Authors: Monaco Corrine F , Plewes Michele R , Przygrodzka Emilia , George Jitu W , Qiu Fang , Xiao Peng , Wood Jennifer R , Cupp Andrea S , Davis John S 
Published: June 2023

Abstract
Cyclic regression of the ovarian corpus luteum, the endocrine gland responsible for progesterone production, involves rapid matrix remodeling. Despite fibroblasts in other systems being known for producing and maintaining extracellular matrix, little is known about fibroblasts in the functional or regressing corpus luteum. Vast transcriptomic changes occur in the regressing corpus luteum, among which are reduced levels of vascular endothelial growth factor A (VEGFA) and increased expression of fibroblast growth factor 2 (FGF2) after 4 and 12 h of induced regression, when progesterone is declining and the microvasculature is destabilizing. We hypothesized that FGF2 activates luteal fibroblasts. Analysis of transcriptomic changes during induced luteal regression revealed elevations in markers of fibroblast activation and fibrosis, including fibroblast activation protein (FAP), serpin family E member 1 (SERPINE1), and secreted phosphoprotein 1 (SPP1). To test our hypothesis, we treated bovine luteal fibroblasts with FGF2 to measure downstream signaling, type 1 collagen production, and proliferation. We observed rapid and robust phosphorylation of various signaling pathways involved in proliferation, such as ERK, AKT, and STAT1. From our longer-term treatments, we determined that FGF2 has a concentration-dependent collagen-inducing effect, and that FGF2 acts as a mitogen for luteal fibroblasts. FGF2-induced proliferation was greatly blunted by inhibition of AKT or STAT1 signaling. Our results suggest that luteal fibroblasts are responsive to factors that are released by the regressing bovine corpus luteum, an insight into the contribution of fibroblasts to the microenvironment in the regressing corpus luteum.
No-harm calibration for generalized Oaxaca–Blinder estimators
Authors: Cohen P L , Fogarty C B 
Published: June 2023

Summary
In randomized experiments, adjusting for observed features when estimating treatment effects has been proposed as a way to improve asymptotic efficiency. However, among parametric methods, only linear regression has been proven to form an estimate of the average treatment effect that is asymptotically no less efficient than the treated-minus-control difference in means regardless of the true data generating process. Randomized treatment assignment provides this do-no-harm property, with neither truth of a linear model nor a generative model for the outcomes being required. We present a general calibration method that confers the same no-harm property onto estimators leveraging a broad class of nonlinear models. This recovers the usual regression-adjusted estimator when ordinary least squares is used, and further provides noninferior treatment effect estimators using methods such as logistic and Poisson regression. The resulting estimators are noninferior to both the difference-in-means estimator and to treatment effect estimators that have not undergone calibration. We show that our estimator is asymptotically equivalent to an inverse-probability-weighted estimator using a logit link with predicted potential outcomes as covariates. In a simulation study, we demonstrate that common nonlinear estimators without our calibration procedure may perform markedly worse than both the calibrated estimator and the unadjusted difference in means.
Increasing biodiversity knowledge through social media: A case study from tropical Bangladesh
Authors: Chowdhury Shawan , Aich Upama , Rokonuzzaman Md , Alam Shofiul , Das Priyanka , Siddika Asma , Ahmed Sultan , Labi Mahzabin Muzahid , Marco Moreno Di , Fuller Richard A , Callaghan Corey T 
Published: June 2023

Abstract
Citizen science programs are becoming increasingly popular among naturalists but remain heavily biased taxonomically and geographically. However, with the explosive popularity of social media and the near-ubiquitous availability of smartphones, many post wildlife photographs on social media. Here, we illustrate the potential of harvesting these data to enhance our biodiversity understanding using Bangladesh, a tropical biodiverse country, as a case study. We compared biodiversity records extracted from Facebook with those from the Global Biodiversity Information Facility (GBIF), collating geospatial records for 1013 unique species, including 970 species from Facebook and 712 species from GBIF. Although most observation records were biased toward major cities, the Facebook records were more evenly spatially distributed. About 86% of the Threatened species records were from Facebook, whereas the GBIF records were almost entirely Of Least Concern species. To reduce the global biodiversity data shortfall, a key research priority now is the development of mechanisms for extracting and interpreting social media biodiversity data.
T-SPOT.TB Reactivity in Southern African Children With and Without in Utero Human Immunodeficiency Virus Exposure
Authors: Iwase Saori C , Edlefsen Paul T , Bhebhe Lynnette , Motsumi Kesego , Moyo Sikhulile , Happel Anna-Ursula , Shao Danica , Mmasa Nicholas , Schenkel Sara , Gasper Melanie A , Dubois Melanie , Files Megan A , Seshadri Chetan , Duffy Fergal , Aitchison John , Netea Mihai G , Jao Jennifer , Cameron Donald W , Gray Clive M , Jaspan Heather B , Powis Kathleen M 
Published: June 2023

Abstract
Infants who are human immunodeficiency virus (HIV)-exposed uninfected (iHEU) experience higher risk of infectious morbidity than infants HIV-unexposed uninfected (iHUU). We compared tuberculosis (TB) infection prevalence in 418 Bacillus Calmette-Guérin vaccinated sub-Saharan African iHEU and iHUU aged 9–18 months using T-SPOT.TB. Prevalence of TB infection was low and did not differ by HIV exposure status.
The big squeeze: balancing the hemodynamics of cardiac tamponade and superior vena cava syndrome
Authors: Shah Keya , Ciancarelli James , DeLeon Joshua 
Published: June 2023

Abstract
In this clinical vignette, we describe an unusual aetiology of shock that was precipitated by the drainage of malignant pericardial effusion. Therapeutic intervention of the patient’s cardiac tamponade led to decreased venous pressures, increased external lung mass compression, worsening superior vena cava syndrome, and ultimately haemodynamic compromise leading to his expiration.
AMH as part of the diagnostic PCOS workup in large epidemiological studies
Authors: Piltonen Terhi T , Komsi Elina , Morin-Papunen Laure C , Korhonen Elisa , Franks Stephen , Järvelin Marjo-Riitta , Arffman Riikka K , Ollila Meri-Maija 
Published: June 2023

Abstract

Objectives
Previous studies have shown good correlation between polycystic ovarian morphology (PCOM) and serum anti-Müllerian hormone (AMH) levels. We evaluated the utility of AMH as a surrogate for PCOM as a part of the polycystic ovary syndrome (PCOS) diagnosis by describing how the use of different AMH cut-off values would change the prevalence of PCOS.

Methods
A general population-based birth cohort study. Anti-Müllerian hormone concentrations were measured from serum samples taken at age 31 years (n = 2917) using the electrochemiluminescence immunoassay (Elecsys). Anti-Müllerian hormone data were combined with data on oligo/amenorrhoea and hyperandrogenism to identify women with PCOS.

Results
The addition of AMH as a surrogate marker for PCOM increased the number of women fulfilling at least two PCOS features in accordance with the Rotterdam criteria. The prevalence of PCOS was 5.9% when using the AMH cut-off based on the 97.5% quartile (10.35 ng/mL) and 13.6% when using the recently proposed cut-off of 3.2 ng/mL. When using the latter cut-off value, the distribution of PCOS phenotypes A, B, C, and D was 23.9%, 4.7%, 36.6%, and 34.8%, respectively. Compared with the controls, all PCOS groups with different AMH concentration cut-offs showed significantly elevated testosterone (T), free androgen index (FAI), luteinizing hormone (LH), LH/follicle-stimulating hormone (FSH) ratio, body mass index (BMI), waist circumference, and homoeostatic model assessment of insulin resistance (HOMA-IR) values, as well as significantly decreased sex hormone-binding globulin (SHBG) values.

Conclusions
Anti-Müllerian hormone could be useful surrogate for PCOM in large data sets, where transvaginal ultrasound is not feasible, to aid the capturing of women with typical PCOS characteristics. Anti-Müllerian hormone measurement from archived samples enables retrospective PCOS diagnosis when combined with oligo/amenorrhoea or hyperandrogenism.
Risk of myocardial infarction and ischemic stroke in individuals with first-diagnosed paroxysmal vs. non-paroxysmal atrial fibrillation under anticoagulation
Authors: Ntaios George , Sagris Dimitrios , Buckley Benjamin J R , Harrison Stephanie L , Abdul-Rahim Azmil , Austin Philip , Lip Gregory Y H 
Published: June 2023

Abstract

Aims
There is conflicting evidence on whether the type of atrial fibrillation (AF) is associated with risk of cardiovascular events, including acute myocardial infarction (MI) and ischemic stroke. The aim of the present study was to investigate whether the risk of MI and ischemic stroke differs between individuals with first-diagnosed paroxysmal vs. non-paroxysmal AF treated with anticoagulants.

Methods and results
De-identified electronic medical records from the TriNetX federated research network were used. Individuals with a new diagnosis of paroxysmal AF who had no evidence of other types of AF in their records were 1:1 propensity score-matched with individuals with non-paroxysmal AF, defined as persistent or chronic AF, who had no evidence of other types of AF in their records. All patients were followed for three years for the outcomes of MI and ischemic stroke. Cox proportional hazard models were used to calculate hazard ratios (HRs) with 95% confidence intervals (CIs). In the propensity-matched cohort, among 24 848 well-matched AF individuals [mean age 74.4 ± 10.4; 10 101 (40.6%) female], 410 (1.7%) were diagnosed with acute MI and 875 (3.5%) with ischemic stroke during the three-year follow-up. Individuals with paroxysmal AF had significantly higher risk of acute MI (HR: 1.65, 95%CI: 1.35–2.01) compared to those with non-paroxysmal AF. First diagnosed paroxysmal AF was associated with higher risk of non-ST elevation MI (nSTEMI) (HR: 1.89, 95%CI: 1.44–2.46). No significant association was observed between the type of AF and risk of ischemic stroke (HR: 1.09, 95%CI: 0.95–1.25).

Conclusion
Patients with first-diagnosed paroxysmal AF had higher risk of acute MI compared to individuals with non-paroxysmal AF, attributed to the higher risk of nSTEMI among patients with first-diagnosed paroxysmal AF. There was no significant association between type of AF and risk of ischemic stroke.
The coevolutionary dynamics of cryptic female choice
Authors: Kustra Matthew C , Alonzo Suzanne H 
Published: June 2023

AbstractIn contrast to sexual selection on traits that affect interactions between the sexes before mating, little theoretical research has focused on the coevolution of postmating traits via cryptic female choice (when females bias fertilization toward specific males). We used simulation models to ask (a) whether and, if so, how nondirectional cryptic female choice (female-by-male interactions in fertilization success) causes deviations from models that focus exclusively on male-mediated postmating processes, and (b) how the risk of sperm competition, the strength of cryptic female choice, and tradeoffs between sperm number and sperm traits interact to influence the coevolutionary dynamics between cryptic female choice and sperm traits. We found that incorporating cryptic female choice can result in males investing much less in their ejaculates than predicted by models with sperm competition only. We also found that cryptic female choice resulted in the evolution of genetic correlations between cryptic female choice and sperm traits, even when the strength of cryptic female choice was weak, and the risk of sperm competition was low. This suggests that cryptic female choice may be important even in systems with low multiple mating. These genetic correlations increased with the risk of sperm competition and as the strength of cryptic female choice increased. When the strength of cryptic female choice and risk of sperm competition was high, extreme codivergence of sperm traits and cryptic female choice preference occurred even when the sperm trait traded off with sperm number. We also found that male traits lagged behind the evolution of female traits; this lag decreased with increasing strength of cryptic female choice and risk of sperm competition. Overall, our results suggest that cryptic female choice deserves more attention theoretically and may be driving trait evolution in ways just beginning to be explored.