BACKGROUND: Preclinical studies have indicated that Angong Niuhuang Pills (ANP) reduce cerebral infarct and edema volumes. This study aimed to investigate whether ANP safely reduces cerebral infarct and edema volumes in patients with moderate to severe acute ischemic stroke. METHODS: This randomized, double-blind, placebo-controlled pilot trial included patients with acute ischemic stroke with National Institutes of Health Stroke Scale (NIHSS) scores ranging from 10 to 20 in 17 centers in China between April 2021 and July 2022. Patients were allocated within 36 h after onset via block randomization to receive ANP or placebo (3 g/day for 5 days). The primary outcomes were changes in cerebral infarct and edema volumes after 14 days of treatment. The primary safety outcome was severe adverse events (SAEs) for 90 days. RESULTS: There were 57 and 60 patients finally included in the ANP and placebo groups, respectively for modified intention-to-treat analysis. The median age was 66.0 years, and the median NIHSS score at baseline was 12.0. The changes in cerebral infarct volume at day 14 were 0.3 mL and 0.4 mL in the ANP and placebo groups, respectively (median difference: -7.1 mL; interquartile range [IQR]: -18.3 to 2.3 mL, P = 0.30). The changes in cerebral edema volume of the ANP and placebo groups on day 14 were 11.4 mL and 4.0 mL, respectively ( median difference: 3.0 mL, IQR: -1.3 to 9.9 mL, P = 0.15). The rates of SAE within 90 days were similar in the ANP (3/57, 5%) and placebo (7/60, 12%) groups ( P = 0.36). Changes in serum mercury and arsenic concentrations were comparable. In patients with large artery atherosclerosis, ANP reduced the cerebral infarct volume at 14 days (median difference: -12.3 mL; IQR: -27.7 to -0.3 mL, P = 0.03). CONCLUSIONS: ANP showed a similar safety profile to placebo and non-significant tendency to reduce cerebral infarct volume in patients with moderate-to-severe stroke. Further studies are warranted to assess the efficacy of ANP in reducing cerebral infarcts and improving clinical prognosis. TRAIL REGISTRATION Clinicaltrials.gov , No. NCT04475328.
Aged ; Female ; Humans ; Male ; Middle Aged ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Ischemic Stroke/drug therapy* ; Pilot Projects ; Stroke/drug therapy* ; Treatment Outcome

OBJECTIVE: To investigate the effect of miR-483-5p on hepatocellular carcinoma (HCC) cells proliferation and stemness, as well as the attenuating effect of Pien Tze Huang (PZH). METHODS: Differentially expressed miRNA between HepG2 cells and hepatic cancer stem-like cells (HCSCs) were identified by a miRNA microarray assay. miR-483-5p mimics were transfected into HepG2 cells to explore the effects of miR-483-5p on cell proliferation and stemness. HepG2 cells and HCSCs were treated with PZH (0, 0.25, 0.50 and 0.75 mg/mL) to explore the effects of PZH on the proliferation and stemness, both in non-induced state and the state induced by miR-483-5p mimics. RESULTS: miR-483-5p was significantly up-regulated in HCSCs and its overexpression increased cell proliferation and stemness in HepG2 cells (P<0.05). PZH not only significantly inhibited proliferation in HepG2 cells, but also significantly suppressed the cell proliferation and self-renewal of HCSCs (P<0.05). The effects of miR-483-5p mimics on proliferation and stemness of HepG2 cells were partially abolished by PZH. CONCLUSIONS miR-483-5p promotes proliferation and enhances stemness of HepG2 cells, which were attenuated by PZH, demonstrating that miR-483-5p is a potential molecular target for the treatment of HCC and provide experimental evidence to support clinical use of PZH for patients with HCC.
Humans ; MicroRNAs/metabolism* ; Cell Proliferation/drug effects* ; Liver Neoplasms/drug therapy* ; Carcinoma, Hepatocellular/drug therapy* ; Hep G2 Cells ; Neoplastic Stem Cells/metabolism* ; Drugs, Chinese Herbal/therapeutic use* ; Gene Expression Regulation, Neoplastic/drug effects*

Objective:To assess the efficacy and safety of pain control nursing for burn patients.Methods:Databases including CNKI, Wanfang Data Knowledge Service Platform, Weipu Database, China Biomedical Literature Database, Web of Science and Cochrane Library were searched to collect the literature on pain control nursing of burn patients from their inception to December 31, 2024. Literature screening, data extraction and quality assessment were performed independently by 2 researchers based on inclusion and exclusion criteria. Meta-analysis of the included studies was performed by applying RevMan 5.4 software. The efficacy of pain control care was assessed in terms of improving care satisfaction, alleviating negative emotions, reducing pain, and decreasing infection rate. Publication bias was analyzed on the related studies.Results:A total of 9 papers were included, all of which were randomized controlled trial (RCT) studies, involving 791 burn patients, with 392 in the pain control nursing group and 399 in the conventional care group. Meta-analysis showed that compared with the conventional care, pain control nursing significantly increased satisfaction of care ( OR=0.28, 95% CI 0.22, 0.34), improved negative emotions ( SMD=-3.06, 95% CI -4.65, -1.47), reduced pain ( SMD=-2.49, 95% CI -3.41, -1.58), and effectively reduced the incidence of infection ( OR=0.13, 95% CI 0.05, 0.34). The studies related to negative emotions were at the risk of publication bias. Conclusion:Compared with conventional care, pain control nursing can significantly increase care satisfaction, alleviate negative emotions, reduce pain, and lower infection risk in burn patients.

Objective This study aims to evaluate the effectiveness of intelligent bed management model in integrating bed resources in a large comprehensive hospital.Methods Inpatient data from a tertiary hospital between January 2021 and De-cember 2024 were collected.An intelligent hospital-wide bed management platform was constructed to implement bed resource sharing mechanisms and establish a standardized bed reservation grading system.The implementation effect of the system was e-valuated from the perspective of bed occupancy rate,average length of stay,and patient satisfaction.Results After implementa-tion,bed occupancy rates in key monitored departments moved into a reasonable range:Rehabilitation Medicine Department fell from 113.18％to 101.48％(t=4.26,P＜0.01),while Neurology Department increased from 88.18％to 96.20％(t=3.85,P＜0.01).Annual inpatient admissions increased from 83,931 to 103,852(x2=156.82,P＜0.001),and average length of stay shortened from 7.15 days to 6.21 days(t=4.73,P＜0.01).The admission waiting time was cut by 72.7 hours(-43.1％),and satisfaction with bed allocation rationality improved by 11.2 points(t=5.94,P＜0.001).Staff time spent on bed-assignment fell by 42 minutes per shift(t=8.92,P＜0.001),and cross-department transfers increased by 378 episodes per month(x2=145.26,P＜0.001).Conclusion The intelligent bed management model can effectively improve hospital bed utili-zation efficiency,enhance healthcare service quality,reduce staff workload,and merits wider application in similar hospitals.

Objective This study aims to evaluate the effectiveness of intelligent bed management model in integrating bed resources in a large comprehensive hospital.Methods Inpatient data from a tertiary hospital between January 2021 and De-cember 2024 were collected.An intelligent hospital-wide bed management platform was constructed to implement bed resource sharing mechanisms and establish a standardized bed reservation grading system.The implementation effect of the system was e-valuated from the perspective of bed occupancy rate,average length of stay,and patient satisfaction.Results After implementa-tion,bed occupancy rates in key monitored departments moved into a reasonable range:Rehabilitation Medicine Department fell from 113.18％to 101.48％(t=4.26,P＜0.01),while Neurology Department increased from 88.18％to 96.20％(t=3.85,P＜0.01).Annual inpatient admissions increased from 83,931 to 103,852(x2=156.82,P＜0.001),and average length of stay shortened from 7.15 days to 6.21 days(t=4.73,P＜0.01).The admission waiting time was cut by 72.7 hours(-43.1％),and satisfaction with bed allocation rationality improved by 11.2 points(t=5.94,P＜0.001).Staff time spent on bed-assignment fell by 42 minutes per shift(t=8.92,P＜0.001),and cross-department transfers increased by 378 episodes per month(x2=145.26,P＜0.001).Conclusion The intelligent bed management model can effectively improve hospital bed utili-zation efficiency,enhance healthcare service quality,reduce staff workload,and merits wider application in similar hospitals.

Objective:To assess the efficacy and safety of pain control nursing for burn patients.Methods:Databases including CNKI, Wanfang Data Knowledge Service Platform, Weipu Database, China Biomedical Literature Database, Web of Science and Cochrane Library were searched to collect the literature on pain control nursing of burn patients from their inception to December 31, 2024. Literature screening, data extraction and quality assessment were performed independently by 2 researchers based on inclusion and exclusion criteria. Meta-analysis of the included studies was performed by applying RevMan 5.4 software. The efficacy of pain control care was assessed in terms of improving care satisfaction, alleviating negative emotions, reducing pain, and decreasing infection rate. Publication bias was analyzed on the related studies.Results:A total of 9 papers were included, all of which were randomized controlled trial (RCT) studies, involving 791 burn patients, with 392 in the pain control nursing group and 399 in the conventional care group. Meta-analysis showed that compared with the conventional care, pain control nursing significantly increased satisfaction of care ( OR=0.28, 95% CI 0.22, 0.34), improved negative emotions ( SMD=-3.06, 95% CI -4.65, -1.47), reduced pain ( SMD=-2.49, 95% CI -3.41, -1.58), and effectively reduced the incidence of infection ( OR=0.13, 95% CI 0.05, 0.34). The studies related to negative emotions were at the risk of publication bias. Conclusion:Compared with conventional care, pain control nursing can significantly increase care satisfaction, alleviate negative emotions, reduce pain, and lower infection risk in burn patients.

Schizophrenia is a serious mental disorder that is often associated with profound impairment in patients′ daily functioning, and its etiology and pathophysiology are still to be fully elucidated. There is a pathological correlation between inflammation, brain injuries, and the pathogenesis of schizophrenia, with microglia actively participating in these processes. This review provides a comprehensive overview of the impact of microglial cells on neurodevelopment and neuroplasticity, and microglia abnormalities mediating the onset of schizophrenia by contributing to damage in different brain regions.

This paper briefly introduced the varying coefficient model and used the varying coefficient Cox model as an example to demonstrate its application in the fields of medicine and public health through real data analysis,thereby provided methodological references for related research.The example was based on chronic disease management data from a Center for Disease Control and Prevention,fitting a varying coefficient Cox model to explore the time-varying association between body mass index(BMI)and mortality risk among a hypertensive population.The results showed that being underweight(BMI＜18.5 kg/m2)was associated with a higher risk of mortality,but this association weakened over time;being overweight(23 kg/m2≤BMI＜25 kg/m2)was associated with a lower risk of mortality,and this association also weakened over time.The varying coefficient model captured how the impact of exposure factors on outcomes changed with other variables,helping to comprehensively understand the complex relationships between variables,and had significant application and promotion value in medical and public health research.

Propensity score weighting methods are crucial tools for adjusting confounding and conducting causal inference in observational studies.This paper introduces various propensity score weighting methods,and details the key features of each to aid researchers in selecting the most suitable method for their analyses.Additionally,the application of these methods in the fields of medicine and public health is demonstrated through an example data analysis.The example is based on data from 996 patients who underwent percutaneous coronary intervention(PCI).Different propensity score weighting methods are used to explore the effect of PCI combined with abciximab on six-month post-operative survival rates.The results indicate that different propensity score weighting methods provide treatment effect estimates tailored to different inference goals,highlighting the importance of selecting the appropriate method based on the specific inference objective.Propensity score weighting methods enhance the balance of covariate distribution between treatment and control groups,making them powerful tools for adjusting confounding factors in observational studies.Their applicability and value in medical and public health research are significant.

This paper introduces a transfer learning approach based on regression models and demonstrates its application in the medical field through an example.Using data from the 2013-2014 U.S.National Health and Nutrition Examination Survey,the study investigates the association of sleep duration with depression levels and depressive disorder.It employs demographic characteristics and lifestyle factors as predictor variables to predict depression levels and depressive disorder across different racial groups.Compared to models built solely on target racial groups,transfer learning enhances the accuracy of estimating the effect of sleep duration in the target group and improves the prediction accuracy for depression levels and depressive disorder.The results illustrate that transfer learning effectively integrates source data to significantly improve estimation and prediction capabilities of target models,especially in situations with limited target data and heterogeneous data sources.