MiR-103a targeting Piezo1 is involved in acute myocardial infarction through regulating endothelium function

Background: Acute myocardial infarction (AMI) is commonly known as the heart attack. The molecular events involved in the development of AMI remain unclear. This study was to investigate the expression of miR-103a in patients with high blood pressure (HBP) and AMI patients with and without HBP, as well as its effect on endothelial cell functions. Methods: MiR-103a expression in plasma and peripheral blood mononuclear cells (PBMCs) was measured by real-time polymerase chain reaction (PCR). The regulatory effect of miR-103a on Piezo1 gene was identified by a luciferase reporter system. The role of miR-103a in endothelial cells was evaluated by the capillary tube formation ability and cell viability of human umbilical vein endothelial cells (HUVECs). Results: The plasma miR-103a concentration was significantly elevated in patients with HBP alone, AMI alone, and comorbidity of AMI and HBP. The miR-103a expression in PBMCs in patients with AMI and HBP was significantly higher than the one in healthy controls (p < 0.05), however miR-103a expression in PBMCs was not significantly different among patients with HBP alone, patients with AMI alone, and healthy controls. MiR-103a targeted Piezo1 and inhibited Piezo1 protein expression, which subsequently reduced capillary tube formation ability and cell viability of HUVECs. Conclusions: MiR-103a might be a potential biomarker of myocardium infarction and could be used as an index for the diagnosis of AMI. It may be involved in the development of HBP and onset of AMI through regulating the Piezo1 expression.

Work engagement and associated factors among healthcare professionals in the post-pandemic era: a cross-sectional study

BackgroundWith the shift of strategy in fighting COVID-19, the post-pandemic era is approaching. However, the “hard times” for healthcare systems worldwide are not yet ending. Healthcare professionals suffer negative impacts caused by the epidemic, which may seriously threaten their work motivation, concentration, and patient safety.ObjectiveInvestigating the status and factors associated with Chinese healthcare professionals’ work engagement in the post-pandemic era.MethodsA cross-sectional study was conducted to investigate healthcare professionals from 10 hospitals in Hunan Province. Data were collected using demographic characteristics, Generalized Anxiety Disorder-2, Patient Heath Qstionaire-2, Utrecht Work Engagement Scale, Work-Related Basic Need Satisfaction Scale, National Aeronautics and Space Administration-Task Load Index, and self-compassion scale. Descriptive and multiple linear regression analyses explored the factors associated with work engagement.ResultsA total of 1,037 eligible healthcare professionals participated in this study, including 46.4% of physicians, 47.8% of nurses, and 5.8% of others. The total mean score of work engagement was 3.36 ± 1.14. The main predictor variables of work engagement were gender (p = 0.007), years of work experience (p < 0.001), whether currently suffering challenges in the care of patients with COVID-19 (p = 0.003), depression (p < 0.001), work-related basic need satisfaction (p < 0.001), and mindfulness (p < 0.001).ConclusionHealthcare professionals have a medium level of work engagement. Managers need to pay attention to the physical and psychological health of healthcare professionals, provide adequate support, help them overcome challenges, and acknowledge their contribution and value to improve their work engagement, enhance the quality of care and ensure patient safety

The prediction model for intraoperatively acquired pressure injuries in orthopedics based on the new risk factors: a real-world prospective observational, cross-sectional study

Introduction: Orthopedic patients are at high risk for intraoperatively acquired pressure injuries (IAPI), which cause a serious issue and lead to high-expense burden in patient care. However, there are currently no clinically available scales or models to assess IAPI associated with orthopedic surgery.Methods: In this real-world, prospective observational, cross-sectional study, we identified pressure injuries (PI)-related risk factors using a systematic review approach and clinical practice experience. We then prepared a real-world cohort to identify and confirm risk factors using multiple modalities. We successfully identified new risk factors while constructing a predictive model for PI in orthopedic surgery.Results: We included 28 orthopedic intraoperative PI risk factors from previous studies and clinical practice. A total of 422 real-world cases were also included, and three independent risk factors—preoperative limb activity, intraoperative wetting of the compressed tissue, and duration of surgery—were successfully identified using chi-squared tests and logistic regression. Finally, the three independent risk factors were successfully used to construct a nomogram clinical prediction model with good predictive validity (area under the ROC curve = 0.77), which is expected to benefit clinical patients.Conclusion: In conclusion, we successfully identified new independent risk factors for IAPI-related injury in orthopedic patients and developed a clinical prediction model to serve as an important complement to existing scales and provide additional benefits to patients. Our study also suggests that a single measure is not sufficient for the prevention of IAPI in orthopedic surgery patients and that a combination of measures may be required for the effective prevention of IAPI

DFSeer: A visual analytics approach to facilitate model selection for demand forecasting

Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users' demanding requirements for the model, it is challenging for demand analysts to select a proper model. Although existing model selection methods can reduce the manual burden to some extent, they often fail to present model performance details on individual products and reveal the potential risk of the selected model. This paper presents DFSeer, an interactive visualization system to conduct reliable model selection for demand forecasting based on the products with similar historical demand. It supports model comparison and selection with different levels of details. Besides, it shows the difference in model performance on similar products to reveal the risk of model selection and increase users' confidence in choosing a forecasting model. Two case studies and interviews with domain experts demonstrate the effectiveness and usability of DFSeer.Comment: 10 pages, 5 figures, ACM CHI 202

Research of the Fundamental Wave of Wound-Rotor Brushless Doubly-Fed Machine

The brushless doubly-fed machine (BDFM) is a special type of machine with two sets of stator windings and one set of rotor winding. The magnetic field of the BDFM is considered to be complex with no regularity. To study the principles of magnetic fields for the BDFM, a general expression of the fundamental wave is deduced, which shows that the fundamental wave can be regarded as a standing wave when it is observed from rotor reference; also, some discussions about the characteristics of the fundamental wave are presented in the paper. Next, a model of wound-rotor BDFM prototype is established, and the enveloping line and the relations between rotor position and its electrical angle of the magnetic field are figured out in the paper. Finally, after detecting the induced electromotive force (EMF) of measurement coils embedded in the corresponding prototype machine, the validity of the proposed conclusions is verified

Correlation coefficients of relation between left ventricular mass index and some parameters.

<p>*Spearman correlation coefficient</p><p>Correlation coefficients of relation between left ventricular mass index and some parameters.</p

Prevalence of Hypertension in Rural Areas of China: A Meta-Analysis of Published Studies

<div><p>Background</p><p>Hypertension is one of the leading causes of disease burden across the world. In China, the latest nationwide survey of prevalence of hypertension was ten year ago, and data in rural areas is little known. More information about hypertension prevalence could help to improve overall antihypertensive health care. We aimed to estimate the pooled prevalence of hypertension in rural areas of China.</p><p>Methods</p><p>Comprehensive electronic searches of PubMed, Web of Knowledge, Chinese Web of Knowledge, Wangfang, Weipu and SinoMed databases were conducted to identify any study in each database published from January 1, 2004 to December 31, 2013, reporting the prevalence of hypertension in Chinese rural areas. Prevalence estimates were stratified by age, area, sex, publication year, and sample size. All statistical calculations were made using the Stata Version 11.0 (College Station, Texas) and Statsdirect Version 2.7.9.</p><p>Results</p><p>We identified 124 studies with a total population of 3,735,534 in the present meta-analysis. Among people aged 18 years old in Chinese rural areas, the summarized prevalence is 22.81% (19.41%–26.41%). Subgroup analysis shows the following results: for male 24.46% (21.19%–27.89%, for female 22.17% (18.25%–26.35%). For 2004–2006: 18.94% (14.41%–23.94%), for 2007–2009, 21.24% (15.98%–27.01%) for 2010–2013: 26.68%, (20.79%–33.02%). For Northern region 25.76% (22.36%–29.32%), for Southern region 19.30%, (15.48%–24.08%).</p><p>Conclusions</p><p>The last decade witnessed the growth in prevalence of hypertension in rural areas of China compared with the fourth national investigation, which has climbed the same level as the urban area. Guidelines for screening and treatment of hypertension in rural areas need to be given enough attention.</p></div