bluuebunny/crossref_metadata_2025_split huggingface dataset:
FusionDTA: attention-based feature polymerizer and knowledge distillation for drug-target binding affinity prediction
Authors: Yuan Weining , Chen Guanxing , Chen Calvin Yu-Chian 
Published: November 2021

Abstract
The prediction of drug-target affinity (DTA) plays an increasingly important role in drug discovery. Nowadays, lots of prediction methods focus on feature encoding of drugs and proteins, but ignore the importance of feature aggregation. However, the increasingly complex encoder networks lead to the loss of implicit information and excessive model size. To this end, we propose a deep-learning-based approach namely FusionDTA. For the loss of implicit information, a novel muti-head linear attention mechanism was utilized to replace the rough pooling method. This allows FusionDTA aggregates global information based on attention weights, instead of selecting the largest one as max-pooling does. To solve the redundancy issue of parameters, we applied knowledge distillation in FusionDTA by transfering learnable information from teacher model to student. Results show that FusionDTA performs better than existing models for the test domain on all evaluation metrics. We obtained concordance index (CI) index of 0.913 and 0.906 in Davis and KIBA dataset respectively, compared with 0.893 and 0.891 of previous state-of-art model. Under the cold-start constrain, our model proved to be more robust and more effective with unseen inputs than baseline methods. In addition, the knowledge distillation did save half of the parameters of the model, with only 0.006 reduction in CI index. Even FusionDTA with half the parameters could easily exceed the baseline on all metrics. In general, our model has superior performance and improves the effect of drug–target interaction (DTI) prediction. The visualization of DTI can effectively help predict the binding region of proteins during structure-based drug design.
scIAE: an integrative autoencoder-based ensemble classification framework for single-cell RNA-seq data
Authors: Yin Qingyang , Wang Yang , Guan Jinting , Ji Guoli 
Published: November 2021

Abstract
Single-cell RNA sequencing (scRNA-seq) allows quantitative analysis of gene expression at the level of single cells, beneficial to study cell heterogeneity. The recognition of cell types facilitates the construction of cell atlas in complex tissues or organisms, which is the basis of almost all downstream scRNA-seq data analyses. Using disease-related scRNA-seq data to perform the prediction of disease status can facilitate the specific diagnosis and personalized treatment of disease. Since single-cell gene expression data are high-dimensional and sparse with dropouts, we propose scIAE, an integrative autoencoder-based ensemble classification framework, to firstly perform multiple random projections and apply integrative and devisable autoencoders (integrating stacked, denoising and sparse autoencoders) to obtain compressed representations. Then base classifiers are built on the lower-dimensional representations and the predictions from all base models are integrated. The comparison of scIAE and common feature extraction methods shows that scIAE is effective and robust, independent of the choice of dimension, which is beneficial to subsequent cell classification. By testing scIAE on different types of data and comparing it with existing general and single-cell–specific classification methods, it is proven that scIAE has a great classification power in cell type annotation intradataset, across batches, across platforms and across species, and also disease status prediction. The architecture of scIAE is flexible and devisable, and it is available at https://github.com/JGuan-lab/scIAE.
MatrixQCvis: shiny-based interactive data quality exploration for omics data
Authors: Naake Thomas , Huber Wolfgang 
Published: November 2021

AbstractMotivationFirst-line data quality assessment and exploratory data analysis are integral parts of any data analysis workflow. In high-throughput quantitative omics experiments (e.g. transcriptomics, proteomics and metabolomics), after initial processing, the data are typically presented as a matrix of numbers (feature IDs × samples). Efficient and standardized data quality metrics calculation and visualization are key to track the within-experiment quality of these rectangular data types and to guarantee for high-quality datasets and subsequent biological question-driven inference.ResultsWe present MatrixQCvis, which provides interactive visualization of data quality metrics at the per-sample and per-feature level using R’s shiny framework. It provides efficient and standardized ways to analyze data quality of quantitative omics data types that come in a matrix-like format (features IDs × samples). MatrixQCvis builds upon the Bioconductor SummarizedExperiment S4 class and thus facilitates the integration into existing workflows.Availability and implementationMatrixQCVis is implemented in R. It is available via Bioconductor and released under the GPL v3.0 license.Supplementary informationSupplementary data are available at Bioinformatics online.
GADGETS: a genetic algorithm for detecting epistasis using nuclear families
Authors: Nodzenski Michael , Shi Min , Krahn Juno M , Wise Alison S , Li Yuanyuan , Li Leping , Umbach David M , Weinberg Clarice R 
Published: November 2021

Abstract

Motivation
Epistasis may play an etiologic role in complex diseases, but research has been hindered because identification of interactions among sets of single nucleotide polymorphisms (SNPs) requires exploration of immense search spaces. Current approaches using nuclear families accommodate at most several hundred candidate SNPs.

Results
GADGETS detects epistatic SNP-sets by applying a genetic algorithm to case-parent or case-sibling data. To allow for multiple epistatic sets, island subpopulations of SNP-sets evolve separately under selection for evident joint relevance to disease risk. The software evaluates the identified SNP-sets via permutation testing and provides graphical visualization. GADGETS correctly identified epistatic SNP-sets in realistically simulated case-parent triads with 10 000 candidate SNPs, far more SNPs than competitors can handle, and it outperformed competitors in simulations with many fewer SNPs. Applying GADGETS to family-based oral-clefting data from dbGaP identified SNP-sets with possible epistatic effects on risk.

Availability and implementation
GADGETS is part of the epistasisGA package at https://github.com/mnodzenski/epistasisGA.

Supplementary information
Supplementary data are available at Bioinformatics online.
T2-DAG: a powerful test for differentially expressed gene pathways via graph-informed structural equation modeling
Authors: Jin Jin , Wang Yue 
Published: November 2021

AbstractMotivationA major task in genetic studies is to identify genes related to human diseases and traits to understand functional characteristics of genetic mutations and enhance patient diagnosis. Compared with marginal analyses of individual genes, identification of gene pathways, i.e. a set of genes with known interactions that collectively contribute to specific biological functions, can provide more biologically meaningful results. Such gene pathway analysis can be formulated into a high-dimensional two-sample testing problem. Given the typically limited sample size of gene expression datasets, most existing two-sample tests tend to have compromised powers because they ignore or only inefficiently incorporate the auxiliary pathway information on gene interactions.ResultsWe propose T2-DAG, a Hotelling’s T2-type test for detecting differentially expressed gene pathways, which efficiently leverages the auxiliary pathway information on gene interactions from existing pathway databases through a linear structural equation model. We further establish its asymptotic distribution under pertinent assumptions. Simulation studies under various scenarios show that T2-DAG outperforms several representative existing methods with well-controlled type-I error rates and substantially improved powers, even with incomplete or inaccurate pathway information or unadjusted confounding effects. We also illustrate the performance of T2-DAG in an application to detect differentially expressed KEGG pathways between different stages of lung cancer.Availability and implementationThe R (R Development Core Team, 2021) package T2DAG which implements the proposed T2-DAG test is available on Github at https://github.com/Jin93/T2DAG.Supplementary informationSupplementary data are available at Bioinformatics online.
Genetic variation in the symbiont partners in the endangered macrolichenSeirophora villosa(Teloschistaceae: Ascomycota)
Authors: Garrido-Benavent Isaac , Molins Arántzazu , Barreno Eva 
Published: November 2021

AbstractThe decline observed in many populations of highly sensitive lichens has led to the inclusion of some species on regional Red Lists, but this has seldom been accompanied by an examination of the genetic variation of the fungal and algal symbiotic partners. Here, the red-listed epiphytic lichen Seirophora villosa was surveyed in 14 Mediterranean coastal populations to examine the genetic diversity of both partners. The geographical distribution of four-locus haplotypes followed the same trend in mycobiont and photobiont data sets, some being widespread and others restricted to single localities. The fungus showed a moderate selectivity in its photobiont choice, associating with two undescribed Trebouxia microalgae with a biased distribution across the western Mediterranean. One alga species occurred exclusively in the Italian Peninsula. This region also hosted the highest number of haplotypes for both symbionts. The use of 454-pyrosequencing revealed no clear signs of algal coexistence within selected thalli. The phylogenetic reconstruction for the mycobiont showed uncertain limits among Seirophora spp., stressing the need for further taxonomic evaluation. Additionally, we found that Ramalina lacera, a co-occurring epiphytic lichen in the studied area, shared photobiont genotypes with S. villosa. Our results thus suggest that the protection not only of the red-listed species S. villosa, but also of the whole epiphytic lichen community investigated here might be advisable.
The evolution of a bitter taste receptor gene in primates
Authors: Liang Qiufang , Shu Fanglan , Dong Xiaoyan , Feng Ping 
Published: November 2021

AbstractBitter taste perception is critical to prevent animals from ingesting potentially harmful substances. The aim of this study was to characterize the evolution of T2R4 and test the hypothesis that different regions of the T2R gene are subject to disparate selective pressures, with extracellular regions (ECs) being erratic while transmembrane (TMs) and intracellular regions (ICs) being constrained. Thus, we examined the selective pressures acting on T2R4 and its different regions in 37 primates, and discovered that T2R4 and ECs were subject to neutral evolution and purifying selection, respectively, whereas both TMs and ICs showed purifying selection, as suggested by the hypothesis. We attribute this result to the relatively conservative property of T2R4 gene and the limited number of bitter tastants that T2R4 can respond to. Furthermore, we found that positive selection had acted on the first loop of extracellular regions (EL1). In contrast, the second loop (EL2) and transmembrane region-3, -6, -7 (TM367) were subject to purifying selection, and the third loop (EL3) was subject to neutral evolution. This discovery is probably because EL2, EL3, and TMs play a crucial role in the ligand-binding process, and EL1 is involved in the tastant recognition process. We further tested whether the ω of T2R4 differs among species with different diets and found that a specialized diet affected the evolution of T2R4. Feeding habits, fewer T2Rs, and a dietary shift may account for the results. This study can help to uncover the evolution of T2Rs during the primate evolutionary course.
Association of cardiometabolic microRNAs with COVID-19 severity and mortality
Authors: Gutmann Clemens , Khamina Kseniya , Theofilatos Konstantinos , Diendorfer Andreas B , Burnap Sean A , Nabeebaccus Adam , Fish Matthew , McPhail Mark J W , O'Gallagher Kevin , Schmidt Lukas E , Cassel Christian , Auzinger Georg , Napoli Salvatore , Mujib Salma F , Trovato Francesca , Sanderson Barnaby , Merrick Blair , Roy Roman , Edgeworth Jonathan D , Shah Ajay M , Hayday Adrian C , Traby Ludwig , Hackl Matthias , Eichinger Sabine , Shankar-Hari Manu , Mayr Manuel 
Published: November 2021

Abstract

Aims
Coronavirus disease 2019 (COVID-19) can lead to multiorgan damage. MicroRNAs (miRNAs) in blood reflect cell activation and tissue injury. We aimed to determine the association of circulating miRNAs with COVID-19 severity and 28 day intensive care unit (ICU) mortality.

Methods and results
We performed RNA-Seq in plasma of healthy controls (n = 11), non-severe (n = 18), and severe (n = 18) COVID-19 patients and selected 14 miRNAs according to cell- and tissue origin for measurement by reverse transcription quantitative polymerase chain reaction (RT–qPCR) in a separate cohort of mild (n = 6), moderate (n = 39), and severe (n = 16) patients. Candidates were then measured by RT–qPCR in longitudinal samples of ICU COVID-19 patients (n = 240 samples from n = 65 patients). A total of 60 miRNAs, including platelet-, endothelial-, hepatocyte-, and cardiomyocyte-derived miRNAs, were differentially expressed depending on severity, with increased miR-133a and reduced miR-122 also being associated with 28 day mortality. We leveraged mass spectrometry-based proteomics data for corresponding protein trajectories. Myocyte-derived (myomiR) miR-133a was inversely associated with neutrophil counts and positively with proteins related to neutrophil degranulation, such as myeloperoxidase. In contrast, levels of hepatocyte-derived miR-122 correlated to liver parameters and to liver-derived positive (inverse association) and negative acute phase proteins (positive association). Finally, we compared miRNAs to established markers of COVID-19 severity and outcome, i.e. SARS-CoV-2 RNAemia, age, BMI, D-dimer, and troponin. Whilst RNAemia, age and troponin were better predictors of mortality, miR-133a and miR-122 showed superior classification performance for severity. In binary and triplet combinations, miRNAs improved classification performance of established markers for severity and mortality.

Conclusion
Circulating miRNAs of different tissue origin, including several known cardiometabolic biomarkers, rise with COVID-19 severity. MyomiR miR-133a and liver-derived miR-122 also relate to 28 day mortality. MiR-133a reflects inflammation-induced myocyte damage, whilst miR-122 reflects the hepatic acute phase response.
Into the Wild: Evidence for the Enemy Release Hypothesis in the Invasive Callery Pear (Pyrus calleryana) (Rosales: Rosaceae)
Authors: Hartshorn Jessica A , Palmer J Forest , Coyle David R 
Published: November 2021

Abstract
Wild Callery pear (Pyrus calleryana Decne.) results from a cross between various cultivars of P. calleryana and any other Pyrus individual. While many cultivars of this species are still commercially produced and sold for horticultural purposes in the United States, Callery pear is a detrimental invasive species that encroaches on many managed and natural areas, damages equipment and injures people, pets, and livestock with its thorny branches, and likely causes detrimental ecological impacts. Despite its importance as an invasive species, the mechanisms behind Callery pear’s invasion and spread are unclear. To identify potential drivers of invasion, we quantified feeding of generalist and specialist herbivores on Callery pear and four native tree species, based on insect host ranges, with choice and no-choice experiments followed by field surveys of herbivory on these same tree species. Feeding by all herbivores was lower on Callery pear than on native tree species in no-choice assays. Specifically, feeding on Callery pear was moderate by generalists and very low by specialists. Specialist feeding on Callery pear was comparable to native species in choice assays but was significantly reduced in no-choice assays. Reduced specialist feeding along with moderate generalist feeding on Callery pear in the field provides evidence for the Enemy Release Hypothesis as a potential driving mechanism behind its invasion success.
Incidence, clinical presentation, management, and outcome of acute pericarditis and myopericarditis
Authors: Prepoudis Alexandra , Koechlin Luca , Nestelberger Thomas , Boeddinghaus Jasper , Lopez-Ayala Pedro , Wussler Desiree , Zimmermann Tobias , Rubini Giménez Maria , Strebel Ivo , Puelacher Christian , Shrestha Samyut , Keller Dagmar I , Christ Michael , Gualandro Danielle M , Twerenbold Raphael , Martinez-Nadal Gemma , Lopez-Barbeito Beatriz , Miro Oscar , Mueller Christian ,   for the APACE investigators
Published: November 2021

Abstract

Aims
Little is known about the epidemiology, clinical presentation, management, and outcome of acute pericarditis and myopericarditis.

Methods and results
The final diagnoses of acute pericarditis, myopericarditis, and non-ST-segment elevation myocardial infarction (NSTEMI) of patients presenting to seven emergency departments in Switzerland with acute chest pain were centrally adjudicated by two independent cardiologists using all information including serial measurements of high-sensitivity cardiac troponin T. The overall incidence of pericarditis and myopericarditis was estimated relative to the established incidence of NSTEMI. Current management and long-term outcome of both conditions were also assessed. Among 2533 chest pain patients, the incidence of pericarditis, myopericarditis, and NSTEMI were 1.9% (n = 48), 1.1% (n = 29), and 21.6% (n = 548), respectively. Accordingly, the estimated incidence of pericarditis and myopericarditis in Switzerland was 10.1 [95% confidence interval (95% CI) 9.3–10.9] and 6.1 (95% CI 5.6–6.7) cases per 100 000 population per year, respectively, vs. 115.0 (95% CI 112.3–117.6) cases per 100 000 population per year for NSTEMI. Pericarditis (85% male, median age 46 years) and myopericarditis (62% male, median age 56 years) had male predominance, and commonly (50% and 97%, respectively) resulted in hospitalization. No patient with pericarditis or myopericarditis died or had life-threatening arrhythmias within 30 days [incidence 0% (95% CI 0.0–4.8%)]. Compared with NSTEMI, the 2-year all-cause mortality adjusted hazard ratio of pericarditis and myopericarditis was 0.40 (95% CI 0.05–2.96), being 0.59 (95% CI 0.40–0.88) for non-cardiac causes of chest pain.

Conclusion
Pericarditis and myopericarditis are substantially less common than NSTEMI and have an excellent short- and long-term outcome.

Clinical trial registration
ClinicalTrial.gov, number NCT00470587, https://clinicaltrials.gov/ct2/show/NCT00470587.
Referral decisions based on a pre-hospital HEART score in suspected non-ST-elevation acute coronary syndrome: final results of the FamouS Triage study
Authors: Tolsma Rudolf T , Fokkert Marion J , van Dongen Dominique N , Badings Erik A , van der Sluis Aize , Slingerland Robbert J , van ’t Riet Esther , Ottervanger Jan Paul , van ’t Hof Arnoud W J 
Published: November 2021

Abstract

Aims
Although pre-hospital risk stratification of patients with suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) by ambulance paramedics is feasible, it has not been investigated in daily practice whether referral decisions based on this risk stratification is safe and does not increase major adverse cardiac events (MACE). In Phase III of the FamouS Triage study, it was investigated whether referral decisions by ambulance paramedics based on a pre-hospital HEART score, is non-inferior to routine management.

Methods and results
FamouS Triage Phase III is a non-inferiority study, comparing the occurrence of MACE before (Phase II) and after (Phase III) implementation of referral decisions based on a pre-hospital HEART score. In Phase II, all patients were risk-stratified and referred to the hospital; in Phase III, low-risk patients (HEART score ≤ 3) were not referred. Primary endpoint was MACE (acute coronary syndrome, revascularization, or death) within 45 days. A total of 1236 patients were included. Mean age was 63 years, 43% were female, 700 patients were included in the second phase and 536 in the third phase in which 149 low-risk patients (28%) were not transferred to the hospital. Occurrence of 45 days MACE was 16.6% in Phase II and 15.7% in Phase III (P = 0.67). Percentage MACE in low-risk patients was 2.9% in Phase II and 1.3% in Phase III. After adjustments for differences in baseline variables, the hazard ratio of 45 days MACE in Phase III was 0.88 (95% confidence interval 0.63–1.25) as compared to Phase II.

Conclusion
Pre-hospital risk stratification of patients with suspected NSTE-ACS, avoiding hospitalization of a substantial number of low-risk patients, seems feasible and non-inferior to transferring all patients to the hospital.
Are polygenic risk scores for systolic blood pressure and LDL-cholesterol associated with treatment effectiveness, and clinical outcomes among those on treatment?
Authors: Tapela Neo M , Collister Jennifer , Liu Xiaonan , Clifton Lei , Stiby Alexander , Murgia Federico , Hopewell Jemma C , Hunter David J 
Published: November 2021

Abstract

Aims
Many studies have investigated associations between polygenic risk scores (PRS) and the incidence of cardiovascular disease (CVD); few have examined whether risk factor-related PRS predict CVD outcomes among adults treated with risk-modifying therapies. We assessed whether PRS for systolic blood pressure (PRSSBP) and for low-density lipoprotein cholesterol (PRSLDL-C) were associated with achieving SBP and LDL-C-related targets, and with major adverse cardiovascular events (MACE: non-fatal stroke or myocardial infarction, CVD death, and revascularization procedures).

Methods and results
Using observational data from the UK Biobank (UKB), we calculated PRSSBP and PRSLDL-C and constructed two sub-cohorts of unrelated adults of White British ancestry aged 40–69 years and with no history of CVD, who reported taking medications used in the treatment of hypertension or hypercholesterolaemia. Treatment effectiveness in achieving adequate risk factor control was ascertained using on-treatment blood pressure (BP) or LDL-C levels measured at enrolment (uncontrolled hypertension: BP ≥ 140/90 mmHg; uncontrolled hypercholesterolaemia: LDL-C ≥ 3 mmol/L). We conducted multivariable logistic and Cox regression modelling for incident events, adjusting for socioeconomic characteristics, and CVD risk factors. There were 55 439 participants using BP lowering therapies (51.0% male, mean age 61.0 years, median follow-up 11.5 years) and 33 787 using LDL-C lowering therapies (58.5% male, mean age 61.7 years, median follow-up 11.4 years). PRSSBP was associated with uncontrolled hypertension (odds ratio 1.70; 95% confidence interval: 1.60–1.80) top vs. bottom quintile, equivalent to a 5.4 mmHg difference in SBP, and with MACE [hazard ratio (HR) 1.13; 1.04–1.23]. PRSLDL-C was associated with uncontrolled hypercholesterolaemia (HR 2.78; 2.58–3.00) but was not associated with subsequent MACE.

Conclusion
We extend previous findings in the UKB cohort to examine PRSSBP and PRSLDL-C with treatment effectiveness. Our results indicate that both PRSSBP and PRSLDL-C can help identify individuals who, despite being on treatment, have inadequately controlled SBP and LDL-C, and for SBP are at higher risk for CVD events. This extends the potential role of PRS in clinical practice from identifying patients who may need these interventions to identifying patients who may need more intensive intervention.