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The objective of this study is to investigate the correlation between atmospheric pollen concentration and daily visits for allergic conjunctivitis. Daily counts of outpatient visits for allergic conjunctivitis, atmospheric pollen concentration, and meteorological data during pollen season of 2018 and 2019 were collected from Beijing Shijitan Hospital, China. A time-series analysis on generalized additive model with Poisson distribution was used to estimate the relationship between pollen concentration and visits for allergic conjunctivitis, after controlling for the time trend, weather variables, day of the week, and holiday effect. The RStudio was used to generate Spearman correlation coefficients and then to plot the lag-response curves for specific and incremental cumulative effects of relative risk (RR). There was a moderate positive correlation between pollen concentration and visits for allergic conjunctivitis, and Spearman's correlation coefficient was 0.521 in 2018 and 0.515 in 2019 (P0.01). The specific cumulative effect peak associated with per 10 grains/kmm

Purpose This study aimed to investigate the risk factors related to the termination of pregnancy via cesarean section and establish a prediction model for cesarean section based on the characteristics of pregnant women.Patients and methods: The clinical characteristics of 2552 singleton pregnant women who delivered a live baby between January 2020 and December 2021 were retrospectively reviewed. These women were divided into vaginal delivery group (n = 1850) and cesarean section group (n = 802). Lasso regression analysis was employed to screen the independent risk factors of cesarean section. Multivariate logistic regression analysis was used to establish the prediction model, followed by delineation of nomogram, receiver operating characteristic curve (ROC), calibration curve, Decision Curve Analysis (DCA) and confusion matrix.Results There were 1850 women in the vaginal delivery group and 702 women in the cesarean section group. There were significant differences in the age and height of women, maternal weight at birth, pregestational weight, weight gain during pregnancy, gravida, weeks of pregnancy, use of assisted reproductive technology, abnormal blood glucose, hypertension disorders of pregnancy(HDP), scarred uterus, premature rupture of membrane༈PROM༉, placenta previa, floating head, abnormal fetal presentation, cord entanglement and labor analgesia between two groups (P Conclusion The logistic regression prediction model of cesarean section has favorable discrimination, accuracy and consistency and can be employed as a reference for clinicians to improve the outcomes of pregnant women and neonates.

In clinic, perioperative neurocognitive disorder is becoming a common complication of surgery in old patients. Neuroinflammation and blood-brain barrier (BBB) disruption are important contributors for cognitive impairment. Atorvastatin, as a strong HMG-CoA reductase inhibitor, has been widely used in clinic. However, it remains unclear whether atorvastatin could prevent anesthesia and surgery-induced BBB disruption and cognitive injury by its anti-inflammatory property. In this study, aged C57BL/6J mice were used to address this question. Initially, the mice were subject to atorvastatin treatment for 7 days (10 mg/kg). After a simple laparotomy under 1.5% isoflurane anesthesia, Morris water maze was performed to assess spatial learning and memory. Western blot analysis, immunohistochemistry, and enzyme-linked immunosorbent assay were used to examine the inflammatory response, BBB integrity, and cell apoptosis. Terminal-deoxynucleotidyl transferase mediated nick end labeling assay was used to assess cell apoptosis. The fluorescein sodium and transmission electron microscopy were used to detect the permeability and structure of BBB. The results showed that anesthesia and surgery significantly injured hippocampal-dependent learning and memory, which was ameliorated by atorvastatin. Atorvastatin could also reverse the surgery-induced increase of systemic and hippocampal cytokines, including IL-1β, TNF-α, and IL-6, accompanied by inhibiting the nuclear factor kappa-B (NF-κB) pathway and Nucleotide-Binding Oligomerization Domain, or Leucine Rich Repeat and Pyrin Domain Containing 3 (NLRP3) inflammasome activation, as well as hippocampal neuronal apoptosis. In addition, surgery triggered an increase of BBB permeability, paralleled by a decrease of the ZO-1, occludin, and Claudin 5 proteins in the hippocampus. However, atorvastatin treatment could protect the BBB integrity from the impact of surgery, by up-regulating the expressions of ZO-1, occludin, and Claudin 5. These findings suggest that atorvastatin exhibits neuroprotective effects on cognition in aged mice undergoing surgery.

Objective To investigate correlations between environmental and meteorological factors and frequency of presentation for coronary heart disease (CHD) in Beijing.Methods Daily measurements of levels of six atmospheric pollutants were made, data relating to meteorological conditions collected and CHD-related outpatient visits recorded from January 2015 to December 2019 in Beijing. A time-series analysis was made, using a generalized additive model with Poisson distribution, and R 3.6.3 software was used to estimate relationships among levels of atmospheric pollutants, ambient temperature and visits occasioned by CHD. Results were controlled for time-dependent trend, other weather variables, day of the week and holiday effects. RStudio software was used to generate Spearman correlation coefficients in descriptive statistical analysis. Lag-response curves were plotted for specific and incremental cumulative effects of relative risk (RR). The aim was to correlate meteorological-environmental factors and the daily number of CHD-related hospital visits and to quantify the degree of correlation to identify any pathological associations.. Response diagrams and three-dimensional diagrams of predicted exposure lag effects were constructed in order to evaluate relationships among the parameters of air pollution，temperature and daily CHD visits. The fitted model was employed to predict the lag RR and 95% confidence interval (95% CI) for specific and incremental cumulative effects of random air pollutants at random concentrations. This model may then be used to predict effects on the outcome variable at any concentration of any defined pollutant, giving flexibility for public health purposes.Results The overall lag-response RR curves for the specific cumulative effects of the pollutants, particulate matter (PM)2.5, PM10, SO2, CO and NO2, were statistically significant and for PM2.5, PM10, CO and NO2, the overall lag-response RR curves for the incremental cumulative effect were statistically significant. When PM2.5, PM10, SO2, CO and NO2 concentrations were above threshold values and the temperature was below 45°F (reference value 70°F), the number of CHD-related hospital visits increased with a time lag effect.Conclusion Elevated PM2.5, PM10, SO2, CO and NO2 concentrations in the atmosphere combined and low ambient temperature increased the risk of CHD with a time lag effect.

To investigate correlations between environmental and meteorological factors and frequency of presentation for coronary heart disease (CHD) in Beijing. Daily measurements of levels of six atmospheric pollutants were made, data relating to meteorological conditions collected, and CHD-related outpatient visits recorded from January 2015 to December 2019 in Beijing. A time-series analysis was made, using a generalized additive model with Poisson distribution, and R 3.6.3 software was used to estimate relationships among levels of atmospheric pollutants, ambient temperature, and visits occasioned by CHD. Results were controlled for time-dependent trend, other weather variables, day of the week, and holiday effects. Lag-response curves were plotted for specific and incremental cumulative effects of relative risk (RR). The aim was to correlate meteorological-environmental factors and the daily number of CHD-related hospital visits and to quantify the degree of correlation to identify any pathological associations. Response diagrams and three-dimensional diagrams of predicted exposure lag effects were constructed in order to evaluate relationships among the parameters of air pollution, temperature, and daily CHD visits. The fitted model was employed to predict the lag RR and 95% confidence interval (95% CI) for specific and incremental cumulative effects of random air pollutants at random concentrations. This model may then be used to predict effects on the outcome variable at any concentration of any defined pollutant, giving flexibility for public health purposes. The overall lag-response RR curves for the specific cumulative effects of the pollutants, particulate matter (PM)2.5, PM10, SO