bluuebunny/crossref_metadata_2025_split huggingface dataset:
Boosting single-cell gene regulatory network reconstruction via bulk-cell transcriptomic data
Authors: Shu Hantao , Ding Fan , Zhou Jingtian , Xue Yexiang , Zhao Dan , Zeng Jianyang , Ma Jianzhu 
Published: September 2022

Abstract
Computational recovery of gene regulatory network (GRN) has recently undergone a great shift from bulk-cell towards designing algorithms targeting single-cell data. In this work, we investigate whether the widely available bulk-cell data could be leveraged to assist the GRN predictions for single cells. We infer cell-type-specific GRNs from both the single-cell RNA sequencing data and the generic GRN derived from the bulk cells by constructing a weakly supervised learning framework based on the axial transformer. We verify our assumption that the bulk-cell transcriptomic data are a valuable resource, which could improve the prediction of single-cell GRN by conducting extensive experiments. Our GRN-transformer achieves the state-of-the-art prediction accuracy in comparison to existing supervised and unsupervised approaches. In addition, we show that our method can identify important transcription factors and potential regulations for Alzheimer’s disease risk genes by using the predicted GRN. Availability: The implementation of GRN-transformer is available at https://github.com/HantaoShu/GRN-Transformer.
Icolos: a workflow manager for structure-based post-processing of de novo generated small molecules
Authors: Moore J Harry , Bauer Matthias R , Guo Jeff , Patronov Atanas , Engkvist Ola , Margreitter Christian 
Published: September 2022

Abstract

Summary
We present Icolos, a workflow manager written in Python as a tool for automating complex structure-based workflows for drug design. Icolos can be used as a standalone tool, for example in virtual screening campaigns, or can be used in conjunction with deep learning-based molecular generation facilitated for example by REINVENT, a previously published molecular de novo design package. In this publication, we focus on the internal structure and general capabilities of Icolos, using molecular docking experiments as an illustrative example.

Availability and implementation
The source code is freely available at https://github.com/MolecularAI/Icolos under the Apache 2.0 license. Tutorial notebooks containing minimal working examples can be found at https://github.com/MolecularAI/IcolosCommunity.

Supplementary information
Supplementary data are available at Bioinformatics online.
dsMTL: a computational framework for privacy-preserving, distributed multi-task machine learning
Authors: Cao Han , Zhang Youcheng , Baumbach Jan , Burton Paul R , Dwyer Dominic , Koutsouleris Nikolaos , Matschinske Julian , Marcon Yannick , Rajan Sivanesan , Rieg Thilo , Ryser-Welch Patricia , Späth Julian ,   The COMMITMENT Consortium, Herrmann Carl , Schwarz Emanuel 
Published: September 2022

AbstractMotivationIn multi-cohort machine learning studies, it is critical to differentiate between effects that are reproducible across cohorts and those that are cohort-specific. Multi-task learning (MTL) is a machine learning approach that facilitates this differentiation through the simultaneous learning of prediction tasks across cohorts. Since multi-cohort data can often not be combined into a single storage solution, there would be the substantial utility of an MTL application for geographically distributed data sources.ResultsHere, we describe the development of ‘dsMTL’, a computational framework for privacy-preserving, distributed multi-task machine learning that includes three supervised and one unsupervised algorithms. First, we derive the theoretical properties of these methods and the relevant machine learning workflows to ensure the validity of the software implementation. Second, we implement dsMTL as a library for the R programming language, building on the DataSHIELD platform that supports the federated analysis of sensitive individual-level data. Third, we demonstrate the applicability of dsMTL for comorbidity modeling in distributed data. We show that comorbidity modeling using dsMTL outperformed conventional, federated machine learning, as well as the aggregation of multiple models built on the distributed datasets individually. The application of dsMTL was computationally efficient and highly scalable when applied to moderate-size (n &lt; 500), real expression data given the actual network latency.Availability and implementationdsMTL is freely available at https://github.com/transbioZI/dsMTLBase (server-side package) and https://github.com/transbioZI/dsMTLClient (client-side package).Supplementary informationSupplementary data are available at Bioinformatics online.
Is Active Learning Enough? The Contributions of Misconception-Focused Instruction and Active-Learning Dosage on Student Learning of Evolution
Authors: Nehm Ross H , Finch Stephen J , Sbeglia Gena C 
Published: September 2022

abstract
Prior studies of active learning (AL) efficacy have typically lacked dosage designs (e.g., varying intensities rather than simple presence or absence) or specification of whether misconceptions were part of the instructional treatments. In this study, we examine the extent to which different doses of AL (approximately 10%, 15%, 20%, 36% of unit time), doses of misconception-focused instruction (MFI; approximately 0%, 8%, 11%, 13%), and their intersections affect evolution learning. A quantitative, quasiexperimental study (N &gt; 1500 undergraduates) was conducted using a pretest, posttest, delayed posttest design with multiple validated measures of evolution understanding. The student background variables (e.g., binary sex, race or ethnicity), evolution acceptance, and prior coursework were controlled. The results of hierarchical linear and logistic models indicated that higher doses of AL and MFI were associated with significantly larger knowledge and abstract reasoning gains and misconception declines. MFI produced significant learning above and beyond AL. Explicit misconception treatments, coupled with AL, should be explored in more areas of life science education.
Visit-to-visit variability in blood pressure and kidney disease progression in IgA nephropathy
Authors: Tang Chen , Zhang Xiao-Yan , Lv Ji-Cheng , Shi Su-Fang , Zhou Xu-Jie , Liu Li-Jun , Zhang Hong 
Published: September 2022

ABSTRACT

Background
The visit-to-visit variability (VVV) in blood pressure (BP) is an important risk factor for stroke and coronary heart disease and may also be associated with kidney damage and the development of chronic kidney disease (CKD). Data on the association between VVV in BP and the risk of CKD progression among patients with immunoglobulin A nephropathy (IgAN) are limited. We aimed to evaluate the relationships of VVV in BP with the progression of IgAN.

Methods
We assessed 1376 patients with IgAN at Peking University First Hospital. The main VVV in BP was expressed as the standard deviation (SD), coefficient of variation (CV) and average real variability (ARV). The associations of variability in BP with composite kidney disease progression events, defined as a 50% decline in estimated glomerular filtration rate (eGFR) and kidney failure, were examined using Cox models.

Results
During a median follow-up of 44.1 months (interquartile range 23.0–76.7), 247 (18.0%) patients experienced composite kidney disease progression events. With a higher SD in systolic BP (SBP) values, the risk of kidney disease progression events increased {hazard ratio [HR] 1.07 [95% confidence interval (CI) 1.03–1.11]; P &lt; .001} after maximal adjustment, including baseline SBP and mean SBP during the first 12-month period. Using the first quartile of SD SBP values as the reference, the risk of composite kidney disease progression events was higher among patients with higher SD SBP values; the HR was 2.12 (95% CI 1.31–3.44) in the highest quartile (P for trend &lt; .001). A similar trend could be observed when analysing the SD of diastolic BP, but the risk was not significantly increased. The associations were similar when analysed with the CV and ARV.

Conclusion
SBP variability was significantly associated with kidney disease progression in IgAN.
CarrotOmics: a genetics and comparative genomics database for carrot (Daucus carota)
Authors: Rolling William R , Senalik Douglas , Iorizzo Massimo , Ellison Shelby , Van Deynze Allen , Simon Philipp W 
Published: September 2022

AbstractCarrotOmics (https://carrotomics.org/) is a comprehensive database for carrot (Daucus carota L.) breeding and research. CarrotOmics was developed using resources available at the MainLab Bioinformatics core (https://www.bioinfo.wsu.edu/) and is implemented using Tripal with Drupal modules. The database delivers access to download or visualize the carrot reference genome with gene predictions, gene annotations and sequence assembly. Other genomic resources include information for 11 224 genetic markers from 73 linkage maps or genotyping-by-sequencing and descriptions of 371 mapped loci. There are records for 1601 Apiales species (or subspecies) and descriptions of 9408 accessions from 11 germplasm collections representing more than 600 of these species. Additionally, 204 Apiales species have phenotypic information, totaling 28 517 observations from 10 041 biological samples. Resources on CarrotOmics are freely available, search functions are provided to find data of interest and video tutorials are available to describe the search functions and genomic tools. CarrotOmics is a timely resource for the Apiaceae research community and for carrot geneticists developing improved cultivars with novel traits addressing challenges including an expanding acreage in tropical climates, an evolving consumer interested in sustainably grown vegetables and a dynamic environment due to climate change. Data from CarrotOmics can be applied in genomic-assisted selection and genetic research to improve basic research and carrot breeding efficiency.Database URLhttps://carrotomics.org/
Opportunistic Infections in Patients with Inflammatory Bowel Disease Treated with Advanced Therapies: A Systematic Review and Meta-Analysis of Randomized Controlled Trials
Authors: Olivera Pablo A , Lasa Juan S , Zubiaurre Ignacio , Jairath Vipul , Abreu Maria T , Rubin David T , Reinisch Walter , Magro Fernando , Rahier Jean-François , Danese Silvio , Rabaud Christian , Peyrin-Biroulet Laurent 
Published: September 2022

AbstractBackground and AimsAdvanced therapies for inflammatory bowel disease [IBD] could potentially lead to a state of immunosuppression with an increased risk of opportunistic infections [OIs]. We aimed to provide an update on the incidence of OIs among adult IBD patients in randomized controlled trials [RCTs] of approved biologics and small-molecule drugs [SMDs]. Also, we aimed to describe OI definitions utilized in RCTs, to ultimately propose a standardized definition.MethodsElectronic databases were searched from January 1, 1990, until April 16, 2022. Our primary outcome was incidence rate of overall OIs among IBD patients exposed and unexposed to biologics or SMDs. We also describe specific OIs reported in included trials, as well as definitions of OIs within studies when provided.ResultsNinety studies were included. The incidence rates of reported OIs were 0.42 and 0.21 per 100 person-years in patients exposed to advanced therapies and placebo, respectively. This was highest for anti-tumour necrosis factors [0.83 per 100 person-years] and Janus kinase inhibitors [0.55 per 100 person-years] and lowest for anti-integrins and ozanimod. On meta-analysis, no increased risk of OIs was observed. None of the studies provided a detailed definition of OIs, or a comprehensive list of infections considered as OIs.ConclusionDifferent mechanisms of action may have specific OI profiles. In the absence of a uniform definition of OIs, these estimates are less reliable. We propose a definition to be used in future studies to help provide standardized reporting. When using this definition, we saw significant differences in incidence rates of OIs across mechanisms of action.
European Society of Cardiology quality indicators for the cardiovascular pre-operative assessment and management of patients considered for non-cardiac surgery. Developed in collaboration with the European Society of Anaesthesiology and Intensive Care
Authors: Gencer Baris , Gale Chris P , Aktaa Suleman , Halvorsen Sigrun , Beska Ben , Abdelhamid Magdy , Mueller Christian , Tutarel Oktay , McGreavy Paul , Schirmer Henrik , Geissler Tobias , Sillesen Henrik , Niessner Alexander , Zacharowski Kai , Mehilli Julinda , Potpara Tatjana 
Published: September 2022

Abstract

Aims
To establish a set of quality indicators (QIs) for the cardiovascular (CV) assessment and management of patients undergoing non-cardiac surgery (NCS).

Methods and results
The Quality Indicator Committee of the European Society of Cardiology (ESC) and European Society of Anaesthesiology and Intensive Care (ESAIC) in collaboration with Task Force members of the 2022 ESC Guidelines on CV assessment and management of patients undergoing NCS followed the ESC methodology for QI development. This included (1) identification, by constructing a conceptual framework of care, of domains of the CV assessment, and management of patients with risk factors or established cardiovascular disease (CVD) who are considered for or undergoing NCS, (2) development of candidate QIs following a systematic literature review, (3) selection of the final set of QIs using a modified Delphi method, and (4) evaluation of the feasibility of the developed QIs. In total, eight main and nine secondary QIs were selected across six domains: (1) structural framework (written policy), (2) patient education and quality of life (CV risk discussion), (3) peri-operative risk assessment (indication for diagnostic tests), (4) peri-operative risk mitigation (use of hospital therapies), (5) follow-up (post-discharge assessment), and (6) outcomes (major CV events).

Conclusion
We present the 2022 ESC/ESAIC QIs for the CV assessment and management of patients with risk factors or established CVD who are considered for or are undergoing NCS y. These indicators are supported by evidence from the literature, underpinned by expert consensus, and align with the 2022 ESC Guidelines on CV assessment and management of patients undergoing NCS.
An Adaptable Physiological Model of Endocytic Megalin Trafficking in Opossum Kidney Cells and Mouse Kidney Proximal Tubule
Authors: Shipman Katherine E , Long Kimberly R , Cowan Isabella A , Rbaibi Youssef , Baty Catherine J , Weisz Ora A 
Published: September 2022

Abstract
The cells that comprise the proximal tubule (PT) are specialized for high-capacity apical endocytosis necessary to maintain a protein-free urine. Filtered proteins are reclaimed via receptor-mediated endocytosis facilitated by the multiligand receptors megalin and cubilin. Despite the importance of this pathway, we lack a detailed understanding of megalin trafficking kinetics and how they are regulated. Here, we utilized biochemical and quantitative imaging methods in a highly differentiated model of opossum kidney (OK) cells and in mouse kidney in vivo to develop mathematical models of megalin traffic. A preliminary model based on biochemically quantified kinetic parameters was refined by colocalization of megalin with individual apical endocytic compartment markers. Our model predicts that megalin is rapidly internalized, resulting in primarily intracellular distribution of the receptor at steady state. Moreover, our data show that early endosomes mature rapidly in PT cells and suggest that Rab11 is the primary mediator of apical recycling of megalin from maturing endocytic compartments. Apical recycling represents the rate-limiting component of endocytic traffic, suggesting that this step has the largest impact in determining the endocytic capacity of PT cells. Adaptation of our model to the S1 segment of mouse PT using colocalization data obtained in kidney sections confirms basic aspects of our model and suggests that our OK cell model largely recapitulates in vivo membrane trafficking kinetics. We provide a downloadable application that can be used to adapt our working parameters to further study how endocytic capacity of PT cells may be altered under normal and disease conditions.
Motivational Drivers of Temporal Dynamics in Postretirement Work
Authors: Hansson Isabelle , Henkens Kène , van Solinge Hanna 
Published: September 2022

Abstract

Objectives
Many retirees continue to work in retirement, but the temporal dynamics of this process are not well understood. This article examined the extent to which retirees increase, decrease, and exit their work engagement over time. We hypothesized that different motives for postretirement work—financial, social, personal, and organizational—have differential affects on changes in work extent.

Methods
We analyzed 7 waves of the HEalth, Aging and Retirement Transitions in Sweden study (n = 3,123). Postretirement work was defined as working for pay while receiving pension benefits. Changes in work extent were estimated with multistate models and examined in relation to the 4 motives.

Results
Results showed a gradual decrease in work extent following retirement. Financial motives increased the likelihood to take up more work and decreased the likelihood to reduce work hours. Social motives increased the likelihood to reduce and exit work, while personal motives decreased the likelihood for those same pathways. Organizational (demand-driven) motives increased the likelihood to stop working.

Discussion
Our findings suggest that financial motives constitute an important driver for taking up more work in retirement, while motives related to the personal meaning of work explain why retirees maintain their level of engagement over time. The social function of work, on the other hand, may be gradually replaced by social activities outside of work, resulting in a gradual disengagement from work. Finally, demand-driven motives appear insufficient to remain in the labor force, highlighting the need to acknowledge the diversity of motives for continuing to work.
Racial Capitalism in Voltaire’s Enlightenment
Authors: Giovannetti-Singh Gianamar 
Published: September 2022

Abstract
This essay argues that the concept of ‘racial capitalism’ can help us understand the connections between seemingly disparate parts of Voltaire’s extensive corpus of work. It contends that even though the Enlightenment’s racial politics abounded with contradictions and ambivalences, Voltaire stood out from his contemporaries. While the connections between his polygenism – the theory that humans of different races were created separately – and material investments in colonial commerce have long been debated by radical historians, this essay suggests that Voltaire’s views about race’s relationship to labour were transformed by France’s colonial losses during the Seven Years’ War.
Decreasing the Interval Wait Times for Screening Mammogram Results Using the “Reflex Testing” Algorithm
Authors: Alvarenga Julio , Moran Jay , Bulgaru Anca , Moran Meena S 
Published: September 2022

Abstract

Objective
The purpose of this analysis was to determine whether our “reflex testing” (RefT) intervention, implemented to address barriers in scheduling, communication, and diagnostic order placement for resolving BI-RADS 0 screening mammograms, resulted in decreased interval wait times (IWT) for patients with abnormal screening mammograms (abSM).

Methods
All BI-RADS 0 cases over two six-month periods (pre-RefT and post-RefT) were analyzed. Timelines were generated for each BI-RADS 0 case. Elapsed days were computed from date of BI-RADS 0 report to the date of biopsy, additional diagnostic testing, and final resolution. The means of each endpoint within the pre-RefT and post-RefT cohorts were statistically analyzed using Pearson chi-square analysis to assess whether IWT differed significantly after RefT implementation.

Results
The analytic cohort consisted of 1523 BI-RADS 0 cases (n(pre-RefT) = 647, n(post-RefT) = 876). Reflex testing decreased the overall mean IWT from 23.5 to 8.2 days (P &lt; 0.001). For patients not requiring biopsy (1190/1523, 78.1%), the mean IWT from the BI-RADS 0 designation to first diagnostic test or resolution decreased from 29.7 to 10.8 days (P &lt; 0.010). For patients who had biopsy (333/1523, 21.9%), RefT significantly decreased the IWT from BI-RADS 0 to first diagnostic test from 31.4 to 7.7 days (P &lt; 0.001) and also significantly decreased the IWT from first diagnostic test to biopsy (20.9 to 17.7 days; P &lt; 0.013).

Conclusion
Reflex testing intervention streamlines the workflow and significantly decreases IWT for resolving BI-RADS 0 abSM. The RefT intervention could be considered to improve efficiency at other breast centers.
Using the Medical Audit to Improve Practice Performance
Authors: Friedewald Sarah M , Schacht David V , Houshmand Golbahar , Nishikawa Robert M , Linver Michael N 
Published: September 2022

Abstract
Feedback to physicians on their clinical performance is critical to continuous learning and maintenance of skills as well as maintaining patient safety. However, it is fraught with challenges around both implementation and acceptance. Additionally, rewarding of performance improvement is not often done, putting into question the efficacy of the process. Physician audit and feedback have been studied extensively and shown to be beneficial in many fields of medicine. Documenting physician performance and sharing individual and group data have been positively linked to changing physician behavior, ultimately leading to improved patient outcomes. Although casual review of one’s own performance is often the easiest approach, it is frequently over- or underestimated by self-evaluation. Objective measures are therefore important to provide concrete data on which physicians can act. A fundamental question remains in mammography: Is reporting the information to the physician and accreditation bodies enough, or should there be consequences for the radiologist and/or facility if there is outlier behavior?