Associations between congenital heart disease and air pollutants at different gestational weeks: a time-series analysis.

Exposure to air pollution during pregnancy has been linked to birth defects. But the directions of studies on the associations between air pollutants exposure and effect on the incidence of congenital heart disease (CHDs) were inconsistent. To date, few studies were concentrated on the effects of both particulate matter and gaseous air pollutant exposure on CHDs across the full gestational week simultaneously. Our study aimed to investigate the critical exposure windows for each air pollutant throughout 40 gestational weeks. Data on CHDs, air pollution, and meteorological factors from 2013 to 2019 were collected in Lanzhou, China. A distributed lag nonlinear model combined with a quasi-Poisson regression model was applied to evaluate the weekly exposure-lag-response association between air pollutants levels and CHDs, and the subgroup analyses were conducted by gender (baby boy and baby girl). The study included 1607 mother-infant pairs. The results demonstrated that exposure of pregnant women to particulate matter ≤ 5 µm (PM2.5) at lag 1-4 weeks was significantly associated with the risk of CHDs, and the strongest effects were observed in the lag 1 week (1.150, 95%CI 1.059-1.248). For exposure to particulate matter ≤ 10 µm (PM10) at lag 1-3 weeks, the strongest effects were observed in the lag 1 week (1.075, 95% CI 1.026-1.128). For exposure to sulfur dioxide (SO2) at lag 1-4 weeks, the strongest effects were observed in the lag 1 week (1.154, 95% CI 1.025-1.299). For exposure to carbon monoxide (CO) at lag 1-3 weeks, the strongest effects were observed in the lag 1 week (1.089, 95% CI 1.002-1.183). For exposure to ozone (O3) concentration at lag 9-15 weeks, the strongest effects were observed in the lag 15 weeks (1.628, 95% CI 1.001-2.649). The cumulative effects of PM2.5, PM10, SO2, and CO along weeks with a maximum of 1.609 (95%CI 1.000-2.589), 1.286 (95%CI 1.007-1.641), 1.648 (95%CI 1.018-2.668), and 1.368 (95%CI 1.003, 1.865), respectively. The effects were obvious in the initial gestational weeks too. Through the gender stratification analysis, the air pollutants with significant effects were PM2.5 for baby boys and PM2.5, PM10, SO2, CO, NO2, and O3 for baby girl. For the relationship between CHDs and air pollution in Lanzhou, PM2.5, PM10, SO2, CO, and O3 played an important role in the initial gestational weeks, especially for baby girl.

Association between air pollutants and neural tube defects during pregnancy in Lanzhou, China: a time series analysis.

Few studies have evaluated the association between air pollutants and neural tube defects (NTDs). Moreover, the existing research ignores the lag effect of air pollution on health and provides inconsistent epidemiological evidence. We aim to estimate the association between air pollution and NTDs during the first trimester of pregnancy and identify specific susceptible windows. Birth data was collected from the Birth Defects Surveillance Network in Lanzhou from September 1, 2014, to December 31, 2019. Air quality and meteorological data were collected from ambient air monitoring stations and China Meteorological Data Network. The log connection function of the Poisson distribution function is used to establish a DLNM model to estimate the exposure-effect relationship and exposure-lag relationship association between air pollutants levels and NTDs. There were 320,787 perinatal infants in Lanzhou from September 1, 2014, to December 31, 2019, and 486 cases of NTDs (1.5‰). The result indicates that exposure to inhalable particles (PM10) at lag 2-4 weeks was significantly associated with the risk of NTDs, with the most significant impact at the lag 2 week (RR=1.048, 95%CI, 1.015-1.084). Exposure to fine particulate matter (PM2.5) at the lag 2 week was significantly associated with the risk of NTDs, with the most significant impact at the lag 2 week (RR=1.077, 95%CI, 1.004-1.155). Exposure to sulfur dioxide (SO2) and nitrogen dioxide (NO2) at lag 3-6weeks was significantly associated with the risk of NTDs, with the most significant impact at the lag 4 week (RR=1.220, 95%CI, 1.105-1.348; RR=1.143, 95%CI, 1.048-1.245). This study provides further evidence that exposure to air pollutants in the first trimester of pregnancy significantly increases the risk of neural tube defects.

The screening value of RT-LAMP and RT-PCR in the diagnosis of COVID-19: systematic review and meta-analysis.

The purpose of this systematic review is to evaluate the test accuracy of reverse-transcription loop-mediated isothermal amplification (RT-LAMP) and reverse transcription-PCR (RT-PCR) for the diagnosis of coronavirus disease 2019 (COVID-19). We comprehensively searched PUBMED, Web of Science, the Cochrane Library, the Chinese National Knowledge Infrastructure, and the Chinese Biomedical Literature Service System until September 1, 2021. We included clinical studies assessing the sensitivity and specificity of RT-PCR and RT-LAMP using respiratory samples. Thirty-three studies were included with 9360 suspected cases of SARS-CoV-2 infection. The RT-PCR or other comprehensive diagnostic method was defined as the reference method. The results showed that the overall pooled sensitivity of RT-PCR and RT-LAMP was 0.96 (95 % CI, 0.93-0.98) and 0.92 (95 % CI, 0.85-0.96), respectively. RT-PCR and RT-LAMP had a 0.06 (95 % CI, 0.04-0.08) and 0.12 (95 % CI, 0.06-0.16) false-negative rates (FNR), respectively. Moreover, subgroup analysis showed mixed sampling and multiple target gene diagnosis methods had better diagnostic value than single-site sampling and a single target gene. The sensitivity and FNR were also significantly affected by the reference method. Comparing RT-LAMP with established suboptimal RT-PCR may exaggerate the performance of RT-LAMP. RT-PCR and RT-LAMP showed high values in the diagnosis of COVID-19, but there was still a FNR of about 6%-12%.

Time series analysis on association between ambient air pollutants and orofacial clefts during pregnancy in Lanzhou, China.

Current studies on air pollutant exposure during pregnancy and orofacial clefts (OFCs) have inconsistent results, and few studies have investigated refined susceptible windows for OFCs. We aim to estimate association between air pollution and OFCs during the first trimester of pregnancy and identify specific susceptible windows. Birth data was obtained from Birth Defects Surveillance Network in Lanzhou from 2014 to 2019. Air pollution data and temperature data were obtained from ambient air monitoring stations and China Meteorological Data Network, respectively. A distribution lag nonlinear model (DLNM) was applied to estimate weekly-exposure-lag-response association between air pollutant levels and OFCs. The study included 320,787 perinatal infants from 2014 to 2019, of which 685 (2.14‰) were OFCs. The results demonstrated that exposure of pregnant women to aerodynamic diameter ≤ 10 µm (PM10) at lag 4-5 weeks was significantly associated with the risk of OFCs, with the greatest impact at the lag 4 week (RR = 1.029, 95% CI = 1.001-1.057). Exposure to sulfur dioxide (SO2) at lag 2-4 weeks was significantly associated with the risk of OFCs, with the greatest impact at the lag 3 week (RR = 1.096, 95% CI = 1.041-1.177). This study provides further evidence that exposure to air pollution increases the risk of OFCs in the first trimester of pregnancy.

A new mouse model of type 2 diabetes mellitus established through combination of high-fat diet, streptozotocin and glucocorticoid.

AIM: A stable induced type 2 diabetes model (T2DM) still needs to be explored for basic and clinical research, due to nonuniform model methods and unstable consequences. Our aims were to explore and establish an optimized induced T2DM model in mice that exhibits insulin resistance and ß-cell damage. MATERIALS AND METHODS: C57BL/6 mice were treated with a high-fat diet (HFD), streptozotocin (STZ) and dexamethasone (DEX) at different doses and in combination. The general growth status, blood glucose and fasting insulin were detected, and the success rate and insulin sensitivity indices were calculated. KEY FINDING: Low-dose STZ injection multiple times was more secure in the process of T2DM model production. Combined intervention was more efficient in reducing insulin sensitivity and improving the success rate of T2DM model construction. SIGNIFICANCE: Combined with a high-fat diet, glucocorticoids and streptozotocin, a new mouse model of T2DM with insulin resistance and ß-cell damage could be established. The optimized experimental method can serve as a stable model for further studies on the mechanisms and therapy of T2DM.

Effects of metformin in obesity treatment in different populations: a meta-analysis.

OBJECTIVE: Some studies have shown that metformin can reduce body weight. However, metformin has not been officially approved as a medicine for weight loss because its effect on different populations remains inconsistent. This meta-analysis aimed to summarize the weight loss effect of metformin quantitatively. METHOD: The randomized controlled and high-quality case-control trials of metformin monotherapy in obesity treatment were eligible. Baseline body mass index (BMI) was chosen as a self-control to compare the changes in BMI of different populations before and after treatment. All changes were calculated as differences between the final and initial BMI values (with negative values indicating a decrease). Results were presented as weighted mean difference (WMD) with a 95% confidence interval (CI 95%). Subgroup analysis was performed based on baseline BMI, age, daily dose, and duration of medication. RESULTS: A total of 21 trials (n = 1004) were included, and the meta-analysis of metformin treatment in different populations showed that metformin has a modest reduction in the BMI of included participants (WMD -0.98; 95% CI, -1.25 to -0.72), and the reduction of BMI was most significant in the simple obesity population (WMD -1.31; 95% CI, -2.07 to -0.54). The subgroup analysis showed that metformin treatment significantly reduced BMI in obesity patients with a BMI >35kg/m2 (WMD -1.12; 95% CI, -1.84 to -0.39) compared with before treatment. BMI in the high dose group decreased by 1.01 units (WMD-1.01; 95% CI, -1.29 to -0.73) and BMI did not continue to decrease significantly after treatment of more than 6 months. CONCLUSION: Patients treated with metformin experienced about a one-unit reduction in BMI at the end of treatment. But whether this decreased value produced enough weight loss (5% of baseline body weight) to qualify as a "weight loss drug" as current guidelines require, requires larger specific randomized control trials.