bluuebunny/crossref_metadata_2025_split huggingface dataset:
VisuaLife: library for interactive visualization in rich web applications
Authors: Kryś Justyna D , Gront Dominik 
Published: April 2021

Abstract

Motivation
Visualization is a powerful tool to analyze, understand and present big data. Computational biology, bioinformatics and molecular modeling require dedicated tools, tailored to very complex, highly multidimensional data. Over the recent years, numerous tools have been developed for online presentation, but new challenges like the COVID-19 pandemic require new libraries which will guarantee fast development of online tools for a better understanding of biomedical data/results.

Results
VisuaLife is a Python library that provides a new approach to visualization in a web browser. It offers 2D and 3D plotting capabilities as well as widgets designed to display the most common biological data types: nucleotide or protein sequences, 3D biomolecular structures and multiple sequence alignments. Components provided by the VisuaLife library can be assembled into a web application to create an analysis tool tailored to provide multidimensional analysis of a specific research problem. VisuaLife, to our best knowledge, is the most modern solution that allows one to implement such a client-side interactivity in Python.

Availability and implementation
The git repository of the library is hosted at BitBucket: https://bitbucket.org/dgront/visualife/. PyPI distribution is also provided for MacOS and Linux. While basic examples are provided in the supporting materials, the full documentation is available at ReadTheDocs website: https://visualife.readthedocs.io/.

Supplementary information
Supplementary data are available at Bioinformatics online.
A meta-inference framework to integrate multiple external models into a current study
Authors: Gu Tian , Taylor Jeremy M G , Mukherjee Bhramar 
Published: April 2021

SummaryIt is becoming increasingly common for researchers to consider incorporating external information from large studies to improve the accuracy of statistical inference instead of relying on a modestly sized data set collected internally. With some new predictors only available internally, we aim to build improved regression models based on individual-level data from an “internal” study while incorporating summary-level information from “external” models. We propose a meta-analysis framework along with two weighted estimators as the composite of empirical Bayes estimators, which combines the estimates from different external models. The proposed framework is flexible and robust in the ways that (i) it is capable of incorporating external models that use a slightly different set of covariates; (ii) it is able to identify the most relevant external information and diminish the influence of information that is less compatible with the internal data; and (iii) it nicely balances the bias-variance trade-off while preserving the most efficiency gain. The proposed estimators are more efficient than the naïve analysis of the internal data and other naïve combinations of external estimators.
Convergence of Modality Invariance and Attention Selectivity in the Cortical Semantic Circuit
Authors: Nakai Tomoya , Yamaguchi Hiroto Q , Nishimoto Shinji 
Published: April 2021

AbstractThe human linguistic system is characterized by modality invariance and attention selectivity. Previous studies have examined these properties independently and reported perisylvian region involvement for both; however, their relationship and the linguistic information they harbor remain unknown. Participants were assessed by functional magnetic resonance imaging, while spoken narratives (auditory) and written texts (visual) were presented, either separately or simultaneously. Participants were asked to attend to one stimulus when both were presented. We extracted phonemic and semantic features from these auditory and visual modalities, to train multiple, voxel-wise encoding models. Cross-modal examinations of the trained models revealed that perisylvian regions were associated with modality-invariant semantic representations. Attentional selectivity was quantified by examining the modeling performance for attended and unattended conditions. We have determined that perisylvian regions exhibited attention selectivity. Both modality invariance and attention selectivity are both prominent in models that use semantic but not phonemic features. Modality invariance was significantly correlated with attention selectivity in some brain regions; however, we also identified cortical regions associated with only modality invariance or only attention selectivity. Thus, paying selective attention to a specific sensory input modality may regulate the semantic information that is partly processed in brain networks that are shared across modalities.
Results of a Shortened Quarantine Protocol on a Midwestern College Campus
Authors: Fox Mark D , Leiszler Matthew S , Seamon Michael D , Garman Benjamin L 
Published: April 2021

AbstractA shortened quarantine protocol after severe acute respiratory syndrome coronavirus 2 exposure was implemented on a college campus. We assessed data on exposures, symptoms, and tests in 1152 unvaccinated individuals released from quarantine on day 7. A shortened quarantine period for asymptomatic individuals testing negative can be implemented with low risk.
Adverse Pregnancy Outcomes, Maternal Complications, and Severe Illness Among US Delivery Hospitalizations With and Without a Coronavirus Disease 2019 (COVID-19) Diagnosis
Authors: Ko Jean Y , DeSisto Carla L , Simeone Regina M , Ellington Sascha , Galang Romeo R , Oduyebo Titilope , Gilboa Suzanne M , Lavery Amy M , Gundlapalli Adi V , Shapiro-Mendoza Carrie K 
Published: April 2021

Abstract

Background
Evidence on risk for adverse outcomes from coronavirus disease 2019 (COVID-19) among pregnant women is still emerging. We examined the association between COVID-19 at delivery and adverse pregnancy outcomes, maternal complications, and severe illness, and whether these associations differ by race/ethnicity, and describe discharge status by COVID-19 diagnosis and maternal complications.

Methods
Data from 703 hospitals in the Premier Healthcare Database during March–September 2020 were included. Adjusted risk ratios (aRRs) overall and stratified by race/ethnicity were estimated using Poisson regression with robust standard errors. Proportion not discharged home was calculated by maternal complications, stratified by COVID-19 diagnosis.

Results
Among 489 471 delivery hospitalizations, 6550 (1.3%) had a COVID-19 diagnosis. In adjusted models, COVID-19 was associated with increased risk for acute respiratory distress syndrome (aRR, 34.4), death (aRR, 17.0), sepsis (aRR, 13.6), mechanical ventilation (aRR, 12.7), shock (aRR, 5.1), intensive care unit admission (aRR, 3.6), acute renal failure (aRR, 3.5), thromboembolic disease (aRR, 2.7), adverse cardiac event/outcome (aRR, 2.2), and preterm labor with preterm delivery (aRR, 1.2). Risk for any maternal complications or for any severe illness did not significantly differ by race/ethnicity. Discharge status did not differ by COVID-19; however, among women with concurrent maternal complications, a greater proportion of those with (vs without) COVID-19 were not discharged home.

Conclusions
These findings emphasize the importance of implementing recommended prevention strategies to reduce risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and further inform counseling and clinical care for pregnant women during the COVID-19 pandemic.
Transmission of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) in a Patient Transport Van
Authors: Jones Lucas D , Chan Ernest R , Zabarsky Trina F , Cadnum Jennifer L , Navas Maria E , Redmond Sarah N , Kovach Jeffrey D , Linger Marlin , Rutala William A , Zimmerman Peter A , Donskey Curtis J 
Published: April 2021

Abstract
We report 2 episodes of potential SARS-CoV-2 transmission from infected van drivers to passengers despite masking and physical distancing. Whole-genome sequencing confirmed relatedness of driver and passenger SARS-CoV-2. With the heater operating, fluorescent microspheres were transported by airflow &gt;3 meters from the front to the back of the van.
Suppressing Kv1.3 Ion Channel Activity with a Novel Small Molecule Inhibitor Ameliorates Inflammation in a Humanised Mouse Model of Ulcerative Colitis
Authors: Unterweger Anna-Lena , Jensen Morten Ø , Giordanetto Fabrizio , Jogini Vishwanath , Rüschher Alena , Seuß Marietta , Winkelmann Paula , Koletzko Leandra , Shaw David E , Siebeck Matthias , Gropp Roswitha , Beigel Florian , Aszodi Attila 
Published: April 2021

AbstractBackground and AimsThe potassium channel Kv1.3 is a potentially attractive therapeutic target in T cell-mediated inflammatory diseases, as the activity of antigen-activated T cells is selectively impeded by Kv1.3 inhibition. In this study, we examined Kv1.3 as a potential therapeutic intervention point for ulcerative colitis [UC], and studied the efficacy of DES1, a small-molecule inhibitor of Kv1.3, in vitro and in vivo.MethodsKv1.3 expression on T cells in peripheral blood mononuclear cells [PBMCs] isolated from donors with and without UC was examined by flow cytometry. In biopsies from UC patients, Kv1.3-expressing CD4+ T cells were detected by flow cytometry and immunohistochemistry. In vitro, we determined the ability of DES1 to inhibit anti-CD3-driven activation of T cells. In vivo, the efficacy of DES1 was determined in a humanised mouse model of UC and compared with infliximab and tofacitinib in head-to-head studies.ResultsKv1.3 expression was elevated in PBMCs from UC patients and correlated with the prevalence of TH1 and TH2 T cells. Kv1.3 expression was also detected on T cells from biopsies of UC patients. In vitro, DES1 suppressed anti-CD3-driven activation of T cells in a concentration-dependent manner. In vivo, DES1 significantly ameliorated inflammation in the UC model and most effectively so when PBMCs from donors with higher levels of activated T cells were selected for reconstitution. The efficacy of DES1 was comparable to that of either infliximab or tofacitinib.ConclusionInhibition of Kv1.3 [by DES1, for instance] appears to be a potential therapeutic intervention strategy for UC patients.
Advancing physician wellness, engagement and excellence in a mental health setting: a Canadian perspective
Authors: Wilkie Treena , Tajirian Tania , Stergiopoulos Vicky 
Published: April 2021

Summary
This article describes the development and implementation of wellness initiatives within a large Canadian academic mental health hospital, based on the Mental Health Commission of Canada’s workplace standards for mental health. To support the implementation of an organizational framework for physician wellness, a needs assessment of Centre for Addiction and Mental Health physicians (N = 181) was conducted between 21 November and 5 December 2017, including measuring physician burnout rates using two items on the Maslach Burnout Inventory tool. Based on findings, and the organizational wellness framework, a multi-pronged wellness approach was developed, improving physician supports at the individual, team and organizational levels. Eighty-four survey responses (46% response rate) were gathered across eight clinical divisions, with 59% of respondents stating that they were negatively impacted by emotionally stressful events at work within the past year. Themes emerging from open-ended questions included the importance of a culture of safety and wellbeing, leadership accountability and availability of formal supports and processes. In response to survey findings, and our organizational framework, the following six initiatives were implemented: (i) a peer support program, (ii) an office of professionalism, (iii) individual and group mentorship opportunities, (iv) communities of practice, (v) enhanced training and leadership development opportunities, and (vi) efforts to optimize use of electronic health records to enhance efficiency of practice. It is possible to implement a multifaceted organizational approach to physician wellness, engaging physicians and continuously adapting in response to physician input. Future robust evaluation of these strategies can inform organizational roadmaps to improve physician wellness.
Law and urban governance for health in times of rapid change
Authors: Burris Scott , Lin Vivian 
Published: April 2021

SummaryGovernance is an important factor in urban health, and law is an important element of healthy governance. Law can be an intervention local government wields to influence behavior and shape environments. Law can also be an important target of health promotion efforts: Law and the enforcement and implementation behaviors it fosters can promote unhealthy behaviors and environmental conditions, and can act as a barrier to healthy interventions or practices. Finally, law is a design and construction tool for the organization of governance. Law is the means through which cities are formally established. Their powers and duties, organizational structure, boundaries and decision-making procedures are all set by law. Regardless of the form of government, cities have legal levers they can manipulate for health promotion. Cities can use tax authority to influence the price of unhealthy products, or to encourage consumption of healthy foods. Cities can use their legal powers to address incidental legal effects of policies that they themselves cannot control. Cities may also have the authority to use law to address deeper determinants of health. The overall level of income or wealth inequality in a country reflects factors well-beyond a local government’s control, but city government nonetheless has levers to directly and indirectly reduce economic and social inequality and their effects. A renewed focus on law and urban governance is the key to assuring health and well-being and closing the health equity gap.
Educational note: causal decomposition of population health differences using Monte Carlo integration and the g-formula
Authors: Sudharsanan Nikkil , Bijlsma Maarten J 
Published: April 2021

Abstract
One key objective of the population health sciences is to understand why one social group has different levels of health and well-being compared with another. Whereas several methods have been developed in economics, sociology, demography, and epidemiology to answer these types of questions, a recent method introduced by Jackson and VanderWeele (2018) provided an update to decompositions by anchoring them within causal inference theory. In this paper, we demonstrate how to implement the causal decomposition using Monte Carlo integration and the parametric g-formula. Causal decomposition can help to identify the sources of differences across populations and provide researchers with a way to move beyond estimating inequalities to explaining them and determining what can be done to reduce health disparities. Our implementation approach can easily and flexibly be applied for different types of outcome and explanatory variables without having to derive decomposition equations. We describe the concepts of the approach and the practical steps and considerations needed to implement it. We then walk through a worked example in which we investigate the contribution of smoking to sex differences in mortality in South Korea. For this example, we provide both pseudocode and R code using our package, cfdecomp. Ultimately, we outline how to implement a very general decomposition algorithm that is grounded in counterfactual theory but still easy to apply to a wide range of situations.
The Limit Shape of the Leaky Abelian Sandpile Model
Authors: Alevy Ian , Mkrtchyan Sevak 
Published: April 2021

Abstract
The leaky Abelian sandpile model (Leaky-ASM) is a growth model in which $n$ grains of sand start at the origin in $\mathbb{Z}^2$ and diffuse along the vertices according to a toppling rule. A site can topple if its amount of sand is above a threshold. In each topple, a site sends some sand to each neighbor and leaks a portion $1-1/d$ of its sand. We compute the limit shape as a function of $d$ in the symmetric case where each topple sends an equal amount of sand to each neighbor. The limit shape converges to a circle as $d\to 1$ and a diamond as $d\to \infty $. We compute the limit shape by comparing the odometer function at a site to the probability that a killed random walk dies at that site. When $d\to 1$, the Leaky-ASM converges to the ASM with a modified initial configuration. We also prove that the limit shape is a circle when simultaneously with $n\to \infty $ we have that $d=d_n$ converges to $1$ slower than any power of $n$. To gain information about the ASM, faster convergence is necessary.
Vaccination With Detoxified Leukocidin AB Reduces Bacterial Load in a Staphylococcus aureus Minipig Deep Surgical Wound Infection Model
Authors: Fernandez Jeffrey , Sanders Holly , Henn Jessica , Wilson Jolaine M , Malone Danielle , Buoninfante Alessandra , Willms Matthew , Chan Rita , DuMont Ashley L , McLahan Craig , Grubb Kaitlyn , Romanello Anthony , van den Dobbelsteen Germie , Torres Victor J , Poolman Jan T 
Published: April 2021

Abstract
Vaccines against Staphylococcus aureus have eluded researchers for &gt;3 decades while the burden of staphylococcal diseases has increased. Early vaccine attempts mainly used rodents to characterize preclinical efficacy, and all subsequently failed in human clinical efficacy trials. More recently, leukocidin AB (LukAB) has gained interest as a vaccine antigen. We developed a minipig deep surgical wound infection model offering 3 independent efficacy readouts: bacterial load at the superficial and at the deep-seated surgical site, and dissemination of bacteria. Due to similarities with humans, minipigs are an attractive option to study novel vaccine candidates. With this model, we characterized the efficacy of a LukAB toxoid as vaccine candidate. Compared to control animals, a 3-log reduction of bacteria at the deep-seated surgical site was observed in LukAB-treated minipigs and dissemination of bacteria was dramatically reduced. Therefore, LukAB toxoids may be a useful addition to S. aureus vaccines and warrant further study.
COVID-19 trial graph: a linked graph for COVID-19 clinical trials
Authors: Du Jingcheng , Wang Qing , Wang Jingqi , Ramesh Prerana , Xiang Yang , Jiang Xiaoqian , Tao Cui 
Published: April 2021

Abstract

Objective
Clinical trials are an essential part of the effort to find safe and effective prevention and treatment for COVID-19. Given the rapid growth of COVID-19 clinical trials, there is an urgent need for a better clinical trial information retrieval tool that supports searching by specifying criteria, including both eligibility criteria and structured trial information.

Materials and Methods
We built a linked graph for registered COVID-19 clinical trials: the COVID-19 Trial Graph, to facilitate retrieval of clinical trials. Natural language processing tools were leveraged to extract and normalize the clinical trial information from both their eligibility criteria free texts and structured information from ClinicalTrials.gov. We linked the extracted data using the COVID-19 Trial Graph and imported it to a graph database, which supports both querying and visualization. We evaluated trial graph using case queries and graph embedding.

Results
The graph currently (as of October 5, 2020) contains 3392 registered COVID-19 clinical trials, with 17 480 nodes and 65 236 relationships. Manual evaluation of case queries found high precision and recall scores on retrieving relevant clinical trials searching from both eligibility criteria and trial-structured information. We observed clustering in clinical trials via graph embedding, which also showed superiority over the baseline (0.870 vs 0.820) in evaluating whether a trial can complete its recruitment successfully.

Conclusions
The COVID-19 Trial Graph is a novel representation of clinical trials that allows diverse search queries and provides a graph-based visualization of COVID-19 clinical trials. High-dimensional vectors mapped by graph embedding for clinical trials would be potentially beneficial for many downstream applications, such as trial end recruitment status prediction and trial similarity comparison. Our methodology also is generalizable to other clinical trials.
EHR “SWAT” teams: a physician engagement initiative to improve Electronic Health Record (EHR) experiences and mitigate possible causes of EHR-related burnout
Authors: Sequeira Lydia , Almilaji Khaled , Strudwick Gillian , Jankowicz Damian , Tajirian Tania 
Published: April 2021

Abstract
This case report describes an initiative implemented to improve physicians’ experience with Electronic Health Records (EHRs), and is one of several strategies within our organization developed to reduce physician burnout attributed to the EHR. The EHR SWAT Team—a 10-member team—with interdisciplinary representation from clinical informatics, pharmacy informatics, health information management, clinical applications, and project management, is a direct feedback channel for all physicians to express their EHR challenges and have their requests reviewed, prioritized, and fixed in a timely manner. Through in-person divisional meetings, we gathered 118 requests, 36.4% of which were related to re-education and 17% of which were quick fixes. Popular requests included keyword search functionality, minimizing freezing, auto-faxing and auto-save. Our brief evaluation of 46 physicians demonstrated that physicians were satisfied with the initiative, with 61.3% physicians reporting that it increased their proficiency in using EHR functionalities. Lessons learned from this initiative include the importance of buy-in from Information Technology (IT) and physician leadership, extensive physician engagement, and leveraging project management techniques for coordination. Next steps include measuring the impact of this SWAT initiative on EHR-related burnout through a post-intervention organizational wide survey and objective back-end usage logs.
Higher order electro-magneto-elastic free vibration analysis of piezomagnetic nano panel
Authors: Wang Guoping , Hao Huadong , Arefi Mohammad 
Published: April 2021

Abstract
This paper investigates electro-magneto-elastic free vibration responses of piezomagnetic cylindrical nano panel subjected to electro-magneto-mechanical loads based on third-order theory. Third-order shell theory is used for description of the displacement field. The zero transverse shear strains are obtained using the third-order displacement field. Hamilton’s principle is employed to obtain the governing equations of motion. The nano panel is subjected to a coupling of magnetic and electric loads, including a linear function along with the thickness direction and a 2D function along with the axial and circumferential directions. To account the effect of nanoscale in governing equations, the Eringen nonlocal elasticity theory is used. The numerical results are obtained to investigate the impact of significant parameters such as axial and circumferential mode numbers, the nanoscale parameter, applied electromagnetic potentials, and length-to-radius ratio. It is concluded that an increase in initial electric potential and a decrease in magnetic potential lead to an increase in natural frequencies of the nano panel.