The effect of workplace bullying on knowledge sharing of the employees in scientific and technological enterprises: a moderated mediation model.

Purpose: This study aims to understand how workplace bullying affects knowledge sharing among employees in Chinese scientific and technological enterprises.

Methodology: A convenience sampling method was employed to survey 275 employees from scientific and technological enterprises of Yangtze River Delta, China. The survey utilized a general information questionnaire, a workplace bullying scale, an organizational belonging scale, a knowledge sharing scale, and a forbearance scale.

Simultaneously Regulating Electrochemical Corrosion Behavior and Wettability of Magnesium-Neodymium Alloy by Self-Layered Chemical Conversion Coating.

Rapid corrosion in aqueous solutions of magnesium alloys is one of the major obstacles to their wide application, and coating plays a crucial role in their corrosion protection. Recently, protection- and function-integrated coatings have attracted much attention in the research field of magnesium alloys. In this work, a simple chemical conversion process is proposed to fabricate a composite coating on a magnesium-neodymium alloy through immersion in an aqueous solution made of Ca(OH) and NaHCO.

Achieving high inter-rater reliability in establishing data labels: a retrospective chart review study.

Background: In medical research, the effectiveness of machine learning algorithms depends heavily on the accuracy of labeled data. This study aimed to assess inter-rater reliability (IRR) in a retrospective electronic medical chart review to create high quality labeled data on comorbidities and adverse events (AEs).

Methods: Six registered nurses with diverse clinical backgrounds reviewed patient charts, extracted data on 20 predefined comorbidities and 18 AEs.

Effect of health rights accessibility on the urban integration of minority rural migrants in China: a cross-sectional study.

Background: Accessing health rights is an integral component of people's aspirations for a better life. Existing discussions and evaluations regarding the accessibility of health rights for minority rural migrants are insufficient. In comparison to objective health conditions, inequalities in health rights lead to chronic and long-term depletion of human capital among minority rural migrants.

How does choice of residential community affect the social integration of rural migrants: insights from China.

The construction of public space is a new and important way to integrate rural migrants into urban society. Existing studies mainly discussed the factors affecting the social integration of rural migrants from the micro-individual and macro-system levels. Still, they seldom analyzed the differences between rural migrants' residential communities and the roles these differences play in their social integration, especially from the perspective of residential space.

BERT-Based Neural Network for Inpatient Fall Detection From Electronic Medical Records: Retrospective Cohort Study.

Background: Inpatient falls are a substantial concern for health care providers and are associated with negative outcomes for patients. Automated detection of falls using machine learning (ML) algorithms may aid in improving patient safety and reducing the occurrence of falls.

Objective: This study aims to develop and evaluate an ML algorithm for inpatient fall detection using multidisciplinary progress record notes and a pretrained Bidirectional Encoder Representation from Transformers (BERT) language model.

High-throughput virtual screening to identify potential small molecule inhibitors of the Zα domain of the adenosine deaminases acting on RNA 1(ADAR1).

Changes in RNA editing are closely associated with diseases such as cancer, viral infections, and autoimmune disorders. Adenosine deaminase (ADAR1), which acts on RNA 1, plays a key role in adenosine to inosine editing and is a potential therapeutic target for these various diseases. The p150 subtype of ADAR1 is the only one that contains a Zα domain that binds to both Z-DNA and Z-RNA.

Development of machine learning models for the detection of surgical site infections following total hip and knee arthroplasty: a multicenter cohort study.

Background: Population based surveillance of surgical site infections (SSIs) requires precise case-finding strategies. We sought to develop and validate machine learning models to automate the process of complex (deep incisional/organ space) SSIs case detection.

Methods: This retrospective cohort study included adult patients (age ≥ 18 years) admitted to Calgary, Canada acute care hospitals who underwent primary total elective hip (THA) or knee (TKA) arthroplasty between Jan 1st, 2013 and Aug 31st, 2020.

A longitudinal seroepidemiology study to evaluate antibody response to SARS-CoV-2 virus infection and vaccination in children in Calgary, Canada from July 2020 to April 2022: Alberta COVID-19 Childhood Cohort (AB3C) Study.

Background: Measurement of SARS-CoV-2 antibody seropositivity is important to accurately understand exposure to infection and/or vaccination in specific populations. This study aimed to estimate the serologic response to SARS-CoV-2 virus infection and vaccination in children in Calgary, Alberta over a two-year period.

Methods: Children with or without prior SARS-CoV-2 infections, were enrolled in Calgary, Canada in 2020.

Developing an Inpatient Electronic Medical Record Phenotype for Hospital-Acquired Pressure Injuries: Case Study Using Natural Language Processing Models.

Background: Surveillance of hospital-acquired pressure injuries (HAPI) is often suboptimal when relying on administrative health data, as International Classification of Diseases (ICD) codes are known to have long delays and are undercoded. We leveraged natural language processing (NLP) applications on free-text notes, particularly the inpatient nursing notes, from electronic medical records (EMRs), to more accurately and timely identify HAPIs.

Objective: This study aimed to show that EMR-based phenotyping algorithms are more fitted to detect HAPIs than ICD-10-CA algorithms alone, while the clinical logs are recorded with higher accuracy via NLP using nursing notes.

10-Gingerol Enhances the Effect of Taxol in Triple-Negative Breast Cancer via Targeting ADRB2 Signaling.

Purpose: Although paclitaxel is widely used in cancer treatment, severe side effects and drug resistance limit its clinical use. 10-gingerol (10-G) is a natural compound isolated from ginger, which displays anti-inflammatory, antioxidant, and antiproliferative properties. However, the chemotherapy-sensitization effect of 10-G on triple-negative breast cancer (TNBC) has not been fully clarified.

Performance of machine learning algorithms for surgical site infection case detection and prediction: A systematic review and meta-analysis.

Background: Medical researchers and clinicians have shown much interest in developing machine learning (ML) algorithms to detect/predict surgical site infections (SSIs). However, little is known about the overall performance of ML algorithms in predicting SSIs and how to improve the algorithm's robustness. We conducted a systematic review and meta-analysis to summarize the performance of ML algorithms in SSIs case detection and prediction and to describe the impact of using unstructured and textual data in the development of ML algorithms.

A New Method of Identifying Pathologic Complete Response After Neoadjuvant Chemotherapy for Breast Cancer Patients Using a Population-Based Electronic Medical Record System.

Background: Accurate identification of pathologic complete response (pCR) from population-based electronic narrative data in a timely and cost-efficient manner is critical. This study aimed to derive and validate a set of natural language processing (NLP)-based machine-learning algorithms to capture pCR from surgical pathology reports of breast cancer patients who underwent neoadjuvant chemotherapy (NAC).

Methods: This retrospective cohort study included all invasive breast cancer patients who underwent NAC and subsequent curative-intent surgery during their admission at all four tertiary acute care hospitals in Calgary, Alberta, Canada, between 1 January 2010 and 31 December 2017.

Disrupted gut microbiota aggravates working memory dysfunction induced by high-altitude exposure in mice.

Background: The widely accepted microbiome-gut-brain axis (MGBA) hypothesis may be essential for explaining the impact of high-altitude exposure on the human body, especially brain function. However, studies on this topic are limited, and the underlying mechanism remains unclear. Therefore, this study aimed to determine whether high-altitude-induced working memory dysfunction could be exacerbated with gut microbiota disruption.

Preparing Thick Gradient Surface Layer in Cu-Zn Alloy via Ultrasonic Severe Surface Rolling for Strength-Ductility Balance.

A gradient structure (GS) design is a prominent strategy for strength-ductility balance in metallic materials, including Cu alloys. However, producing a thick GS surface layer without surface damage is still a challenging task limited by the available processing technology. In this work, a gradient structure (GS) surface layer with a thickness at the millimeter scale is produced in the Cu-38 wt.

Research on the Efficiency of Green Agricultural Science and Technology Innovation Resource Allocation Based on a Three-Stage DEA Model-A Case Study of Anhui Province, China.

In order to achieve sustainable development of agriculture, people have gradually begun to attach importance to the development of low-carbon agriculture and to regard green agricultural technology innovation and promotion as increasingly more important. Taking the Anhui Province of China as an example, this study analyzed the impact of green agricultural science and technology innovation resource allocation on rural revitalization by constructing an econometric model. We found that the overall efficiency of the overall allocation of agricultural science and technology innovation resources in Anhui Province increased in the sample period, but the scale efficiency level was relatively low.

Validated algorithms for identifying timing of second event of oropharyngeal squamous cell carcinoma using real-world data.

Background: Understanding occurrence and timing of second events (recurrence and second primary cancer) is essential for cancer specific survival analysis. However, this information is not readily available in administrative data.

Methods: Alberta Cancer Registry, physician claims, and other administrative data were used.

Exploration of the Mechanism of Lianhua Qingwen in Treating Influenza Virus Pneumonia and New Coronavirus Pneumonia with the Concept of "Different Diseases with the Same Treatment" Based on Network Pharmacology.

The 31 main components of Lianhua Qingwen (LHQW) were obtained through a literature and database search; the components included glycyrrhizic acid, emodin, chlorogenic acid, isophoroside A, forsythia, menthol, luteolin, quercetin, and rutin. Sixty-eight common targets for the treatment of novel coronavirus pneumonia (NCP) and influenza virus pneumonia (IVP) were also obtained. A "component-target-disease" network was constructed with Cytoscape 3.

Exploring the molecular targets and mechanisms of [10]-Gingerol for treating triple-negative breast cancer using bioinformatics approaches, molecular docking, and experiments.

Background: Triple-negative breast cancer (TNBC) is the most aggressive among breast cancer subtypes with the worst prognosis. Ginger is widely used in pharmaceuticals and as food. Its anticancer properties are known, but the mechanism is still unclear.

Validity of ICD-10 codes for COVID-19 patients with hospital admissions or ED visits in Canada: a retrospective cohort study.

Objective: To evaluate the validity of COVID-19 International Classification of Diseases, 10th Revision (ICD-10) codes and their combinations.

Design: Retrospective cohort study.

Setting: Acute care hospitals and emergency departments (EDs) in Alberta, Canada.

A Multicenter Cohort Study of Falls Among Patients Admitted to the ICU.

Objectives: To determine the incidence of falls, risk factors, and adverse outcomes, among patients admitted to the ICU.

Design: Retrospective cohort study.

Setting: Seventeen ICUs in Alberta, Canada.

The Economic Effects of Direct and Indirect Employee Involvement: Evidence From Corporate Social Responsibility Reports of Chinese Listed Companies.

Employee direct involvement and indirect involvement have been identified as essential forms of an enterprise's democratic management in the digital economy. Research on the complementary effects of direct and indirect involvement is still in a blank state in China, which limits the external validity and accumulation of employee participation theory. The present study aimed to investigate the complementary effects of employee direct involvement and indirect involvement on the firm's financial performance.