Hysteresis effects of different levels of storm flooding on susceptible enteric infectious diseases in a central city of China.

BACKGROUND: Recently, attention has focused on the impact of global climate change on infectious diseases. Storm flooding is an extreme weather phenomenon that not only impacts the health of the environment but also worsens the spread of pathogens. This poses a significant challenge to public health security. However, there is still a lack of research on how different levels of storm flooding affect susceptible enteric infectious diseases over time. METHODS: Data on enteric infectious diseases, storm flooding events, and meteorology were collected for Changsha, Hunan Province, between 2016 and 2020. The Wilcoxon Rank Sum Test was used to identify the enteric infectious diseases that are susceptible to storm flooding. Then, the lagged effects of different levels of storm flooding on susceptible enteric infectious diseases were analyzed using a distributed lag nonlinear model. RESULTS: There were eleven storm flooding events in Changsha from 2016 to 2020, concentrated in June and July. 37,882 cases of enteric infectious diseases were reported. During non-flooding days, the daily incidence rates of typhoid/paratyphoid and bacillary dysentery were 0.3/100,000 and 0.1/100,000, respectively. During flooding days, the corresponding rates increased to 2.0/100,000 and 0.8/100,000, respectively. The incidence rates of both diseases showed statistically significant differences between non-flooding and flooding days. Correlation analysis shows that the best lags for typhoid/paratyphoid and bacillary dysentery relative to storm flooding events may be 1 and 3 days. The results of the distributed lag nonlinear model showed that typhoid/paratyphoid had the highest cumulative RR values of 2.86 (95% CI: 1.71-4.76) and 8.16 (95% CI: 2.93-22.67) after 4 days of general flooding and heavy flooding, respectively; and bacillary dysentery had the highest cumulative RR values of 1.82 (95% CI: 1.40-2.35) and 3.31 (95% CI: 1.97-5.55) after 5 days of general flooding and heavy flooding, respectively. CONCLUSIONS: Typhoid/paratyphoid and bacillary dysentery are sensitive enteric infectious diseases related to storm flooding in Changsha. There is a lagging effect of storm flooding on the onset of typhoid/paratyphoid and bacillary dysentery, with the best lagging periods being days 1 and 3, respectively. The cumulative risk of typhoid/paratyphoid and bacillary dysentery was highest at 4/5 days lag, respectively. The higher of storm flooding, the higher the risk of disease, which suggests that the authorities should take appropriate preventive and control measures before and after storm flooding.

m6A regulator-mediated RNA methylation modification patterns are involved in the regulation of the immune microenvironment in ischaemic cardiomyopathy.

The role of RNA N6-methyladenosine (m6A) modification in the regulation of the immune microenvironment in ischaemic cardiomyopathy (ICM) remains largely unclear. This study first identified differential m6A regulators between ICM and healthy samples, and then systematically evaluated the effects of m6A modification on the characteristics of the immune microenvironment in ICM, including the infiltration of immune cells, the human leukocyte antigen (HLA) gene, and HALLMARKS pathways. A total of seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15 and YTHDF3, were identified using a random forest classifier. A diagnostic nomogram based on these seven key m6A regulators could effectively distinguish patients with ICM from healthy subjects. We further identified two distinct m6A modification patterns (m6A cluster-A and m6A cluster-B) that are mediated by these seven regulators. Meanwhile, we also noted that one m6A regulator, WTAP, was gradually upregulated, while the others were gradually downregulated in the m6A cluster-A vs. m6A cluster-B vs. healthy subjects. In addition, we observed that the degree of infiltration of the activated dendritic cells, macrophages, natural killer (NK) T cells, and type-17 T helper (Th17) cells gradually increased in m6A cluster-A vs. m6A cluster-B vs. healthy subjects. Furthermore, m6A regulators, including FTO, YTHDC1, YTHDF3, FMR1, ZC3H13, and RBM15 were significantly negatively correlated with the above-mentioned immune cells. Additionally, several differential HLA genes and HALLMARKS signalling pathways between the m6A cluster-A and m6A cluster-B groups were also identified. These results suggest that m6A modification plays a key role in the complexity and diversity of the immune microenvironment in ICM, and seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15, and YTHDF3, may be novel biomarkers for the accurate diagnosis of ICM. Immunotyping of patients with ICM will help to develop immunotherapy strategies with a higher level of accuracy for patients with a significant immune response.

ACSL1, CH25H, GPCPD1, and PLA2G12A as the potential lipid-related diagnostic biomarkers of acute myocardial infarction.

Lipid metabolism plays an essential role in the genesis and progress of acute myocardial infarction (AMI). Herein, we identified and verified latent lipid-related genes involved in AMI by bioinformatic analysis. Lipid-related differentially expressed genes (DEGs) involved in AMI were identified using the GSE66360 dataset from the Gene Expression Omnibus (GEO) database and R software packages. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to analyze lipid-related DEGs. Lipid-related genes were identified by two machine learning techniques: least absolute shrinkage and selection operator (LASSO) regression and support vector machine recursive feature elimination (SVM-RFE). The receiver operating characteristic (ROC) curves were used to descript diagnostic accuracy. Furthermore, blood samples were collected from AMI patients and healthy individuals, and real-time quantitative polymerase chain reaction (RT-qPCR) was used to determine the RNA levels of four lipid-related DEGs. Fifty lipid-related DEGs were identified, 28 upregulated and 22 downregulated. Several enrichment terms related to lipid metabolism were found by GO and KEGG enrichment analyses. After LASSO and SVM-RFE screening, four genes (ACSL1, CH25H, GPCPD1, and PLA2G12A) were identified as potential diagnostic biomarkers for AMI. Moreover, the RT-qPCR analysis indicated that the expression levels of four DEGs in AMI patients and healthy individuals were consistent with bioinformatics analysis results. The validation of clinical samples suggested that 4 lipid-related DEGs are expected to be diagnostic markers for AMI and provide new targets for lipid therapy of AMI.

Estradiol and Hyperhomocysteinemia Are Linked Predominantly Through Part Renal Function Indicators.

Background: Previous studies have shown that estrogen, kidney function, and homocysteine (Hcy) or hyperhomocysteinemia (HHcy) are related to each other. However, the underlying biological mechanisms still remain unclear. We aimed to explore the association between estradiol (E2) and HHcy in the female population, and to further evaluate the mediating role of renal function indicators. Methods: This unmatched case-control study consisted of 1,044 female participants who were 60.60 ± 12.46 years old. Data on general demographic characteristics, such as age, smoking and drinking status, menopause and so on were collected in a personal interview, and laboratory examinations were performed by well-trained personnel. The mediating effect model was applied to analyze the direct and indirect effects of E2 on Hcy. Results: The average levels of Hcy and E2 of the participants were 12.6 µmol/L and 14.95 pg/ml. There were statistical differences in renal indexes blood urea nitrogen (BUN), serum creatinine (Scr), uric acid (UA), glomerular filtration rate (GFR) and E2 between HHcy group and non-HHcy group. The logistic regression models showed that UA was risk factor for HHcy (P <0.001), GFR and E2 were protective factors for HHcy after adjusting for confounding factors (P <0.001). The indirect effects of E2 on Hcy through UA and GFR accounted for 14.63 and 18.29% of the total impacts of E2 on Hcy. Conclusions: These data indicated that E2 was a protective factor of HHcy, and the effects of E2 on HHcy may be mediated by renal function indicators UA and GFR.

Effects of meteorological factors on the incidence of mumps and models for prediction, China.

BACKGROUND: Mumps is an acute respiratory infectious disease with obvious regional and seasonal differences. Exploring the impact of climate factors on the incidence of mumps and predicting its incidence trend on this basis could effectively control the outbreak and epidemic of mumps. METHODS: Considering the great differences of climate in the vast territory of China, this study divided the Chinese mainland into seven regions according to the administrative planning criteria, data of Mumps were collected from the China Disease Prevention and Control Information System, ARIMA model and ARIMAX model with meteorological factors were established to predict the incidence of mumps. RESULTS: In this study, we found that precipitation, air pressure, temperature, and wind speed had an impact on the incidence of mumps in most regions of China and the incidence of mumps in the north and southwest China was more susceptible to climate factors. Considering meteorological factors, the average relative error of ARIMAX model was 10.87%, which was lower than ARIMA model (15.57%). CONCLUSIONS: Meteorology factors were the important factors which can affect the incidence of mumps, ARIMAX model with meteorological factors could better simulate and predict the incidence of mumps in China, which has certain reference value for the prevention and control of mumps.

Spatial-temporal analysis and visualization of scarlet fever in mainland China from 2004 to 2017.

This study retrospectively analyzed the spatio-temporal distribution and spatial clustering of scarlet fever in mainland China from 2004 to 2017. In recent years, the incidence of scarlet fever is increasing. Previous studies on the spatial distribution of scarlet fever in China are mainly focused at the provincial and municipal levels, and there is few systematic report on the spatial and temporal distribution characteristics of scarlet fever on the national level. Based on the incidence information of scarlet fever in mainland China between 2004 and 2017 collected from the China Center for Disease Control, this paper systematically explored the Spatio-temporal distribution of scarlet fever by three methods, contains spatial autocorrelation analysis, Spatio-temporal scanning analysis, and trend surface analysis. The results demonstrate that the incidence of scarlet fever varies by seasons, which is in line with double-peak distribution.The first peak generally occurs from May to June and the second one from November to December, while February and August is the lowest period of incidence. Trend surface analysis indicates that the incidence of scarlet fever in northern China is higher than the south, slightly higher in western compared to the east, and lower in the central part. Additionally, the results show that the clustering regions of scarlet fever centrally distributed in the northeast, northwest, north china and some provinces in the east, such as Zhejiang, Shanghai, Shandong, and Jiangsu.

Research about the optimal strategies for prevention and control of varicella outbreak in a school in a central city of China: based on an SEIR dynamic model.

Varicella is an acute respiratory infectious diseases, with high transmissibility and quick dissemination. In this study, an SEIR (susceptible-exposed-infected-recovered) dynamic model was established to explore the optimal prevention and control measures according to the epidemiological characteristics about varicella outbreak in a school in a central city of China. Berkeley Madonna 8.3.18 and Microsoft Office Excel 2010 software were employed for the model simulation and data management, respectively. The result showed that the simulated result of SEIR model agreed well with the reported data when ß (infected rate) equal to 0.067. Models showed that the cumulative number of cases was only 13 when isolation adopted when the infected individuals were identified (assuming isolation rate was up to 100%); the cumulative number of cases was only two and the TAR (total attack rate) was 0.56% when the vaccination coefficient reached 50%. The cumulative number of cases did not change significantly with the change of efficiency of ventilation and disinfection, but the peak time was delayed; when δ (vaccination coefficient) = 0.1, m (ventilation efficiency) = 0.7 or δ = 0.2, m = 0.5 or δ = 0.3, m = 0.1 or δ = 0.4 and above, the cumulative number of cases would reduce to one case and TAR would reduce to 0.28% with combined interventions. Varicella outbreak in school could be controlled through strict isolation or vaccination singly; combined interventions have been adopted when the vaccination coefficient was low.

The HO-1 Signal Prevents HMGB1-Mediated Activation of NLRP3 Inflammasomes in Lipopolysaccharide-Induced Acute Lung Injury In Vitro.

BACKGROUND: Current treatments of lipopolysaccharide (LPS)-induced acute lung injury (ALI) are unsatisfactory due to the insufficient understanding of the pathogenesis of LPS-induced ALI. The NLRP3 inflammasome is an essential part of the innate protection system and is involved in LPS-induced ALI; however, comprehensive understanding of molecular pathogenesis of the disease is lacking. Our study explored the effect of heme oxygenase-1 (HO-1) on NLRP3 inflammasomes in vitro. METHODS: Alveolar macrophages (NR8383) were preincubated with high-mobility group box-1 (HMGB1) or HO-1 CRISPR plasmids before LPS stimulation. Then, we detected the effect of HO-1 on NLRP3 inflammasomes. RESULTS: Our study demonstrates that the activation of HO-1 represses the level of NLRP3 inflammasomes and the subsequent increases of the level of IL-1ß. Moreover, NLRP3 inflammasome activation was sensitive to the HMGB1 activity, and HO-1 was able to reduce the amount of HMGB1 released. Furthermore, downregulation of NLRP3 inflammasomes was related to NADPH quinone oxidoreductase 1 (an HO-1-related gene). CONCLUSIONS: Our study clarifies the constrained coordination of the HO-1 signal in the HMGB1-mediated activation of NLRP3 inflammasomes in NR8383 alveolar macrophages after LPS stimulation.

The study on the early warning period of varicella outbreaks based on logistic differential equation model.

Chickenpox is a common acute and highly contagious disease in childhood; moreover, there is currently no targeted treatment. Carrying out an early warning on chickenpox plays an important role in taking targeted measures in advance as well as preventing the outbreak of the disease. In recent years, the infectious disease dynamic model has been widely used in the research of various infectious diseases. The logistic differential equation model can well demonstrate the epidemic characteristics of epidemic outbreaks, gives the point at which the early epidemic rate changes from slow to fast. Therefore, our study aims to use the logistic differential equation model to explore the epidemic characteristics and early-warning time of varicella. Meanwhile, the data of varicella cases were collected from first week of 2008 to 52nd week of 2017 in Changsha. Finally, our study found that the logistic model can be well fitted with varicella data, besides the model illustrated that there are two peaks of varicella at each year in Changsha City. One is the peak in summer-autumn corresponding to the 8th-38th week; the other is in winter-spring corresponding to the time from the 38th to the seventh week next year. The 'epidemic acceleration week' average value of summer-autumn and winter-spring are about the 16th week (ranging from the 15th to 17th week) and 45th week (ranging from the 44th to 47th week), respectively. What is more, taking warning measures during the acceleration week, the preventive effect will be delayed; thus, we recommend intervene during recommended warning weeks which are the 15th and 44th weeks instead.

Health care and risk of adverse pregnancy outcomes among diabetic women: an updated meta-analysis.

PURPOSE: Diabetic women appear to have adverse pregnancy outcomes. Although there were two meta-analyzes that examined the association between health care and adverse pregnancy outcomes, their results were limited because they only included congenital anomaly and perinatal mortality, and they did not clarify the detailed situations of diabetes and health care. This meta-analysis aims to completely evaluate the effects of health care in improving adverse pregnancy outcomes among diabetic mothers. METHODS: CNKI, EMBASE, Web of Science, and PubMed databases were searched for eligible studies up to December 2017, without any restrictions. Relevant cohort studies characterizing the relationship between health care and adverse pregnancy outcomes were selected for inclusion in the meta-analysis. We also screened the reference list of relevant studies. The fixed-effect models or random-effect models were used to calculate the risk estimates. The potential sources of heterogeneity were explored by stratified and sensitivity analyzes. RESULTS: Twenty-one studies with 6685 cases were included in our analysis. Health care was associated with significantly decreased risk of congenital anomaly (RR 0.237; 95% CI 0.166-0.338), perinatal death (RR 0.457; 95% CI 0.294-0.712), large for gestational age (LGA) (RR 0.794; 95% CI 0.640-0.986), and neonatal hypoglycemia (RR 0.672; 95% CI 0.486-0.929). Publication bias was not found in most results, with the exception of congenital anomaly and small for gestational age (SGA). CONCLUSION: Health care is associated with decreased risk of congenital anomaly, perinatal death, LGA, neonatal hypoglycemia.