Over the past several years, researchers have postulated that Magnet® organizations improve collegiality and potentially could mitigate workplace bullying and lateral violence (BLV). In order to synthesize and evaluate the existing literature on BLV in the Magnet® setting, an integrative review was conducted. The final analysis consisted of 11 articles (8 quantitative and 3 qualitative studies) and revealed that researchers still use a variety of terms to define and measure BLV. Several of the studies used blended samples of both Magnet® and non-Magnet nurses, making it difficult to evaluate for response differences. The existing studies suggest that BLV continues to exist and remain a large issue even in the Magnet® setting (Hickson, 2013; Latham, Ringl, & Hogan, 2013). Future studies should examine the prevalence of BLV in both Magnet® and non-Magnet organizations and also explore the organizational factors that reduce its occurrence.
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http://dx.doi.org/10.1177/1527154418755802 | DOI Listing |
Biomark Res
January 2025
BK21 FOUR KNU Convergence Educational Program of Biomedical Sciences for Creative Future Talents, Department of Biomedical Sciences, School of Medicine, Kyungpook National University, Daegu, 41944, Korea.
Macrophages are pivotal in the body's defense and response to inflammation. They are present in significant numbers and are widely implicated in various diseases, including cancer. While molecular and histological techniques have advanced our understanding of macrophage biology, their precise function within the cancerous microenvironments remains underexplored.
View Article and Find Full Text PDFPrenat Diagn
January 2025
Key Laboratory of Reproductive Genetics (Ministry of Education) and Department of Reproductive Endocrinology, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
Prenatal cell-free DNA (cfDNA) screening has advanced significantly, extending beyond detecting aneuploidies to sub-chromosomal copy number variations. However, its application for screening dominant single-gene conditions, often caused by de novo variants, remains underutilized in the general obstetric population. This study reviews recent data and experience on prenatal cfDNA screening for dominant monogenic conditions using multiple-gene panels, highlighting its potential to enhance early detection and management of genetic disorders.
View Article and Find Full Text PDFStem Cell Res Ther
January 2025
Organoid Innovation Center, Suzhou Institute of Nanotech and Nano-bionics, Chinese Academy of Sciences, 398 Ruoshui Rd, Suzhou, Jiangsu, 215123, China.
The lack of in vivo accurate human liver models hinders the investigation of liver-related diseases, injuries, and drug-related toxicity, posing challenges for both basic research and clinical applications. Traditional cellular and animal models, while widely used, have significant limitations in replicating the liver's complex responses to various stressors. Liver organoids derived from human pluripotent stem cells, adult stem cells primary cells, or tissues can mimic diverse liver cell types, major physiological functions, and architectural features.
View Article and Find Full Text PDFBMC Anesthesiol
January 2025
Kaiser Permanente Division of Research, 2000 Broadway, Oakland, CA, 94612, USA.
Background: Clinical determination of patients at high risk of poor surgical outcomes is complex and may be supported by clinical tools to summarize the patient's own personalized electronic health record (EHR) history and vitals data through predictive risk models. Since prior models were not readily available for EHR-integration, our objective was to develop and validate a risk stratification tool, named the Assessment of Geriatric Emergency Surgery (AGES) score, predicting risk of 30-day major postoperative complications in geriatric patients under consideration for urgent and emergency surgery using pre-surgical existing electronic health record (EHR) data.
Methods: Patients 65-years and older undergoing urgent or emergency non-cardiac surgery within 21 hospitals 2017-2021 were used to develop the model (randomly split: 80% training, 20% test).
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