Analysis of the fatigue status of medical security personnel during the closed-loop period using multiple machine learning methods: a case study of the Beijing 2022 Olympic Winter Games.

Using machine learning methods to analyze the fatigue status of medical security personnel and the factors influencing fatigue (such as BMI, gender, and wearing protective clothing working hours), with the goal of identifying the key factors contributing to fatigue. By validating the predicted outcomes, actionable and practical recommendations can be offered to enhance fatigue status, such as reducing wearing protective clothing working hours. A questionnaire was designed to assess the fatigue status of medical security personnel during the closed-loop period, aiming to capture information on fatigue experienced during work and disease recovery. The collected data was then preprocessed and used to determine the structural parameters for each machine learning algorithm. To evaluate the prediction performance of different models, the mean relative error (MRE) and goodness of fit (R2) between the true and predicted values were calculated. Furthermore, the importance rankings of various parameters in relation to fatigue status were determined using the RF feature importance analysis method. The fatigue status of medical security personnel during the closed-loop period was analyzed using multiple machine learning methods. The prediction performance of these methods was ranked from highest to lowest as follows: Gradient Boosting Regression (GBM) > Random Forest (RF) > Adaptive Boosting (AdaBoost) > K-Nearest Neighbors (KNN) > Support Vector Regression (SVR). Among these algorithms, four out of the five achieved good prediction results, with the GBM method performing the best. The five most critical parameters influencing fatigue status were identified as working hours in protective clothing, a customized symptom and disease score (CSDS), physical exercise, body mass index (BMI), and age, all of which had importance scores exceeding 0.06. Notably, working hours in protective clothing obtained the highest importance score of 0.54, making it the most critical factor impacting fatigue status. Fatigue is a prevalent and pressing issue among medical security personnel operating in closed-loop environments. In our investigation, we observed that the GBM method exhibited superior predictive performance in determining the fatigue status of medical security personnel during the closed-loop period, surpassing other machine learning techniques. Notably, our analysis identified several critical factors influencing the fatigue status of medical security personnel, including the duration of working hours in protective clothing, CSDS, and engagement in physical exercise. These findings shed light on the multifaceted nature of fatigue among healthcare workers and emphasize the importance of considering various contributing factors. To effectively alleviate fatigue, prudent management of working hours for security personnel, along with minimizing the duration of wearing protective clothing, proves to be promising strategies. Furthermore, promoting regular physical exercise among medical security personnel can significantly impact fatigue reduction. Additionally, the exploration of medication interventions and the adoption of innovative protective clothing options present potential avenues for mitigating fatigue. The insights derived from this study offer valuable guidance to management personnel involved in organizing large-scale events, enabling them to make informed decisions and implement targeted interventions to address fatigue among medical security personnel. In our upcoming research, we will further expand the fatigue dataset while considering higher precisionprediction algorithms, such as XGBoost model, ensemble model, etc., and explore their potential contributions to our research.

Improving the Use of Blockchain Technology in Stroke Care Information Management Systems.

Blockchain is a new and popular technology in the digital age. Blockchain technology is referred to as decentralised and distributed digital ledgers, which are called blocks. These blocks are linked together with the cryptographic hashes and are used to record transactions between many computers. No single block can be altered without altering the related blocks. Modification of individual block data is impossible because each block contains information from the previous block. This is the unique strength of blockchain. Timestamps and hashes are some of the important terms when blockchains are considered. Data security is guaranteed with this advanced technology. Blockchain technology finds its application in the healthcare industry with many advantages in a queue. Medical data can be transferred safely and securely for fool-proof management of the medicine supply chain, which helps in healthcare research. Blockchains are used to securely encrypt a patient's information in the event of an outbreak of a pandemic disease. A stroke is referred to as a brain attack, also called cerebral infarction. A cerebral infarction is a sudden stoppage of blood flow in the blood vessels connected to the brain. This study focused on evaluating the application of blockchain technology in Stroke Nursing Information Management Systems. This emerging technology is already in use in the healthcare industry. The patient's data is kept decentralized, transparent, and mainly incorruptible, thus keeping it secured and sharing of data is quick.

Efficacy of Bevacizumab Combined with Pemetrexed in the Treatment of Recurrent and Metastatic Cervical Cancer.

Background: To investigate the efficacy and safety of bevacizumab combined with pemetrexed in the treatment of recurrent and metastatic cervical cancer. Methods: Clinical data of 65 patients with recurrent and metastatic cervical cancer who were admitted to our hospital were collected for retrospective analysis. All patients were administered with bevacizumab combined with pemetrexed for 4-6 cycles (21 days as 1 cycle). The short-term clinical efficacy and adverse reactions were compared between the two groups. In addition, the survival status of patients was followed up and recorded. Results: At least 4 cycles of chemotherapy were given to the 65 patients. There were 0 cases of complete response (CR), 14 cases of partial response (PR), 36 cases of stable disease (SD) and 15 cases of progressive disease (PD). The objective response rate (ORR) and the disease control rate (DCR) were 21.5% (14/65) and 76.9% (50/65), respectively. DCR was superior in patients with squamous cell carcinoma to that in those with adenocarcinoma (p = 0.039), but no statistically significant difference was found in ORR. Patients with extra-pelvic metastatic lesions had a better efficacy than those with intra-pelvic metastatic lesions, but the difference was not statistically significant (p > 0.05). The post-treatment adverse reactions mainly involved fatigue, nausea and vomiting, bleeding, leukopenia, anemia, thrombocytopenia, transaminase elevation, hypertension, proteinuria and neurotoxicity, most of which were grade I-II that ameliorated after symptomatic therapy. Grade III adverse reactions mainly included pain in 5 cases (7.7%), leukopenia in 17 cases (26.2%), anemia in 22 cases (33.8%), thrombocytopenia in 6 cases (9.2%), hypertension in 5 cases (7.7%) and neurotoxicity in 7 cases (10.8%). The follow-up results manifested that median overall survival (OS) and median progression-free survival (PFS) were 10.6 months and 6.6 months, respectively. Conclusion: Bevacizumab combined with pemetrexed exhibits certain efficacy in the treatment of recurrent and metastatic cervical cancer, with tolerable adverse reactions. Therefore, this therapeutic option deserves clinical popularization and application.

lncRNA ROR and miR-125b Predict the Prognosis in Heart Failure Combined Acute Renal Failure.

OBJECTIVE: To elucidate the correlation between expression levels of long noncoding RNA (lncRNA) ROR and microRNA-125b (miR-125b) with the prognosis in heart failure (HF) patients combined acute renal failure (ARF). METHODS: HF patients combined ARF (n = 90) and healthy controls (n = 90) in the same period were included in our hospital from April 2016 to December 2018. Every subject was followed up for 24 months. Serum levels of lncRNA ROR and miR-125b were detected, and their expression correlation was analyzed by Pearson correlation test. Receiver operating characteristic (ROC) curves were depicted for assessing the sensitivity and specificity of lncRNA ROR and miR-125b in diagnosing HF combined ARF. RESULTS: lncRNA ROR was upregulated in serum of HF patients combined ARF, and its level was positively correlated to NYHA classification. miR-125b displayed an opposite trend. In serum samples of HF combined ARF, expression level of lncRNA ROR was negatively related to that of miR-125b. Diagnostic potentials of lncRNA ROR and miR-125b in HF combined ARF were confirmed by ROC curve analyses (lncRNA ROR: AUC = 0.9199, cutoff value = 5.595, sensitivity = 92.22%, and specificity = 73.33%; miR-125b: AUC = 0.8509, cutoff value = 2.290, sensitivity = 81.11%, and specificity = 74.44%). After 2-year follow-up, 16 cases were dead. Higher incidences of death and rehospitalization were observed in HF combined ARF cases expressing higher serum level of lncRNA ROR or lower level of miR-125b. CONCLUSIONS: Serum level of lncRNA ROR is upregulated, and miR-125b is downregulated in HF patients combined ARF. Their levels are linked to NYHA classification, which can be utilized as prognostic biomarkers in HF combined ARF.

miR-20a-5p inhibits endometrial cancer progression by targeting janus kinase 1.

Endometrial cancer (EC) is a multi-factorial disease of which pathogenesis has not been fully elucidated. The function and underlying mechanism of microRNA-20a-5p (miR-20a-5p) in EC remain poorly understood. The present study aimed to analyze the association between miR-20a-5p expression and the clinicopathological characteristics of patients with EC. Whether miR-20a-5p could inhibit EC progression by targeting janus kinase 1 (Jak1) was subsequently investigated. To do so, human EC tissues and paracancerous tissues were collected from 47 patients with EC. miR-20a-5p and Jak1 mRNA and protein expression was determined by reverse transcription quantitative PCR and western blotting, respectively. Cell proliferation, invasive ability and adhesion were investigated by MTT, Matrigel invasion and cell adhesion assays, respectively. Dual luciferase reporter assay was used to verify whether miR-20a-5p could directly target Jak1. The results demonstrated that miR-20a-5p was downregulated and that Jak1 was upregulated in EC tissues compared with paracancerous tissues. In addition, miR-20a-5p expression and Jak1 expression level were negatively correlated in EC tissues. miR-20a-5p expression was also significantly associated with the depth of myometrial invasion, FIGO stage, histologic grade and lymph node metastasis in patients with EC. Furthermore, Jak1 was identified as a new direct target of miR-20a-5p, and Jak1 overexpression was demonstrated to reverse the effects of miR-20a-5p-mimic on EC cell proliferation, invasive ability and adhesion. Taken together, the results from this study revealed for the first time that miR-20a-5p expression was significantly associated with the clinicopathological characteristics of patients with EC. These findings suggested that miR-20a-5p may act as a tumor suppressor in EC, in part through decreasing Jak1 expression. miR-20a-5p and Jak1 may therefore serve as potential therapeutic targets in EC.

Silence of Long Noncoding RNA SNHG14 Alleviates Ischemia/Reperfusion-Induced Acute Kidney Injury by Regulating miR-124-3p/MMP2 Axis.

PURPOSE: Ample evidence has proved that lncRNAs are pivotal regulators in acute kidney injury (AKI). Here, we focus on the role and mechanism of lncRNA SNHG14 in ischemia/reperfusion- (I/R-) caused AKI. METHODS: I/R and hypoxia/reoxygenation (H/R) were applied to induce rats and HK-2 cells to establish AKI models in vivo and in vitro. Relative expression of SNHG14, miR-124-3p, and MMP2 was determined by qRT-PCR. HE staining was used to evaluate pathological changes in renal tissues, and acute tubular necrosis (ATN) score was calculated. Renal function was evaluated by measuring serum creatinine content and blood urea nitrogen content. Levels of IL-1ß, IL-6, and TNF-α were measured by ELISA. Cell viability was examined by MTT assay. Oxidative stress was assessed by measuring SOD, MDA, and ROS levels. The target of SNHG14 or miR-124-3p was verified by DLR assay. Protein expression of MMP2 was examined by western blot. RESULTS: SNHG14 was boosted in renal tissues of I/R-stimulated rats and H/R-induced HK-2 cells, while miR-124-3p was diminished in H/R-stimulated HK-2 cells. Si-SNHG14 or miR-124-3p mimics repressed inflammation and oxidative stress and enhanced cell viability in H/R-stimulated HK-2 cells. Sh-SNHG14 mitigated I/R-induced AKI in rats. MiR-124-3p was targeted by SNHG14, and MMP2 was targeted by miR-124-3p. Inhibition of miR-124-3p or upregulation of MMP2 reversed inhibitory effects of SNHG14 silence on inflammation and oxidative stress as well as the promoting effect of SNHG14 silence on cell viability in H/R-induced HK-2 cells. CONCLUSION: Knockdown of SNHG14 alleviated I/R-induced AKI by miR-124-3p-mediated downregulation of MMP2.