Air Pollutants and Mortality Risk in Patients with Aortic Dissection: Evidence from a Clinical Cohort, Single-Cell Sequencing, and Proteomics.

We aimed to evaluate the association between air pollutants and mortality risk in patients with acute aortic dissection (AAD) in a longitudinal cohort and to explore the potential mechanisms of adverse prognosis induced by fine particulate matter (PM2.5). Air pollutants data, including PM2.5, PM10.0, nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3), were collected from official monitoring stations, and multivariable Cox regression models were applied. Single-cell sequencing and proteomics of aortic tissue were conducted to explore the potential mechanisms. In total, 1,267 patients with AAD were included. Exposure to higher concentrations of air pollutants was independently associated with an increased mortality risk. The high-PM2.5 group carried approximately 2 times increased mortality risk. There were linear associations of PM10, NO2, CO, and SO2 exposures with long-term mortality risk. Single-cell sequencing revealed an increase in mast cells in aortic tissue in the high-PM2.5 exposure group. Enrichment analysis of the differentially expressed genes identified the inflammatory response as one of the main pathways, with IL-17 and TNF signaling pathways being among the top pathways. Analysis of proteomics also identified these pathways. This study suggests that exposure to higher PM2.5, PM10, NO2, CO, and SO2 are associated with increased mortality risk in patients with AAD. PM2.5-related activation and degranulation of mast cells may be involved in this process.

An ensemble forecast system for tracking dynamics of dengue outbreaks and its validation in China.

As a common vector-borne disease, dengue fever remains challenging to predict due to large variations in epidemic size across seasons driven by a number of factors including population susceptibility, mosquito density, meteorological conditions, geographical factors, and human mobility. An ensemble forecast system for dengue fever is first proposed that addresses the difficulty of predicting outbreaks with drastically different scales. The ensemble forecast system based on a susceptible-infected-recovered (SIR) type of compartmental model coupled with a data assimilation method called the ensemble adjusted Kalman filter (EAKF) is constructed to generate real-time forecasts of dengue fever spread dynamics. The model was informed by meteorological and mosquito density information to depict the transmission of dengue virus among human and mosquito populations, and generate predictions. To account for the dramatic variations of outbreak size in different seasons, the effective population size parameter that is sequentially updated to adjust the predicted outbreak scale is introduced into the model. Before optimizing the transmission model, we update the effective population size using the most recent observations and historical records so that the predicted outbreak size is dynamically adjusted. In the retrospective forecast of dengue outbreaks in Guangzhou, China during the 2011-2017 seasons, the proposed forecast model generates accurate projections of peak timing, peak intensity, and total incidence, outperforming a generalized additive model approach. The ensemble forecast system can be operated in real-time and inform control planning to reduce the burden of dengue fever.

Exposure to Fine Particulate Matter Constituents and Human Semen Quality Decline: A Multicenter Study.

Exposure to fine particulate matter (PM < 2.5 µm in diameter [PM2.5]) may accelerate human sperm quality decline, although research on this association is limited. Our objective was to investigate the relationship between exposure to the chemical constituents of PM2.5 air pollution and decreased sperm quality and to further explore the exposure-response relationship. We conducted a multicenter population-based cohort study including 78,952 semen samples from 33,234 donors at 6 provincial human sperm banks (covering central, northern, southern, eastern, and southwestern parts of China) between 2014 and 2020. Daily exposure to PM2.5 chemical composition was estimated using a deep learning model integrating a density ground-based measure network at a 1 km resolution. Linear mixed models with subject- and center-specific intercepts were used to quantify the harmful impacts of PM2.5 constituents on semen quality and explore their exposure-response relationships. Per interquartile range (IQR) increase in PM2.5 exposure levels during spermatogenesis was significantly associated with decreased sperm concentration, progressive motility, and total motility. For PM2.5 constituents, per IQR increment in Cl- (ß: -0.02, 95% CI: [-0.03, -0.00]) and NO3- (ß: -0.05, 95% CI: [-0.08, -0.02]) exposure was negatively associated with sperm count, while NH4+ (ß: -0.03, 95% CI: [-0.06, -0.00]) was significantly linked to decreased progressive motility. These results suggest that exposure to PM2.5 chemical constituents may adversely affect human sperm quality, highlighting the urgent need to reduce PM2.5 exposure.

Detection and Analysis of Microplastics in Human Sputum.

Microplastic pollution is an emerging environmental problem, and little research has focused on its impact on the human body. Based on retrospective case series, the study required participants to fill out a questionnaire and provide sputum samples in order to investigate the presence of microplastics in human sputum and determine whether humans involuntarily inhale them. A total of 22 patients suffering from different respiratory diseases were recruited. We used an Agilent 8700 laser infrared imaging spectrometer and Fourier-transform infrared microscope to analyze sputum samples and evaluate microplastics in the respiratory tract. Remarkably, the size range of the method for detecting microplastics in our study is 20-500 µm. The results showed that 21 types of microplastics were identified, and polyurethane was dominant, followed by polyester, chlorinated polyethylene, and alkyd varnish, accounting for 78.36% of the total microplastics. Most of the aspirated microplastics detected are smaller than 500 µm in size (median: 75.43 µm; interquartile range: 44.67-210.64 µm). Microplastics are ubiquitous in all sputum, indicating that inhalation is a potential way for plastics to enter the human body. Additionally, the quantities of microplastic types in the respiratory tract are related to smoking, invasive examination, etc. (P < 0.05). This study sheds new light on microplastic exposure, which provides basic data for the risk assessment of microplastics to human health.

The ASK-SEAT: a competency-based assessment scale for students majoring in clinical medicine.

BACKGROUND: To validate a competency-based assessment scale for students majoring in clinical medicine, ASK-SEAT. Students' competency growth across grade years was also examined for trends and gaps. METHODS: Questionnaires were distributed online from May through August in 2018 to Year-2 to Year-6 students who majored in clinical medicine at the Shantou University Medical College (China). Cronbach alpha values were calculated for reliability of the scale, and exploratory factor analysis employed for structural validity. Predictive validity was explored by correlating Year-4 students' self-assessed competency ratings with their licensing examination scores (based on Kendall's tau-b values). All students' competency development over time was examined using the Mann-Whitney U test. RESULTS: A total of 760 questionnaires meeting the inclusion criteria were analyzed. The overall Cronbach's alpha value was 0.964, and the item-total correlations were all greater than 0.520. The overall KMO measure was 0.966 and the KMO measure for each item was greater than 0.930 (P < 0.001). The eigenvalues of the top 3 components extracted were all greater than 1, explaining 55.351, 7.382, and 5.316% of data variance respectively, and 68.048% cumulatively. These components were aligned with the competency dimensions of skills (S), knowledge (K), and attitude (A). Significant and positive correlations (0.135 < Kendall's tau-b < 0.276, p < 0.05) were found between Year-4 students' self-rated competency levels and their scores for the licensing examination. Steady competency growth was associated with almost all indicators, with the most pronounced growth in the domain of skills. A lack of steady growth was seen in the indicators of "applying the English language" and "conducting scientific research & innovating". CONCLUSIONS: The ASK-SEAT, a competency-based assessment scale developed to measure medical students' competency development shows good reliability and structural validity. For predictive validity, weak-to-moderate correlations are found between Year-4 students' self-assessment and their performance at the national licensing examination (Year-4 students start their clinical clerkship during the 2nd semester of their 4th year of study). Year-2 to Year-6 students demonstrate steady improvement in the great majority of clinical competency indicators, except in the indicators of "applying the English language" and "conducting scientific research & innovating".

Sperm quality and ambient air pollution exposure: A retrospective, cohort study in a Southern province of China.

BACKGROUND: Abnormal semen quality is one of the common causes of infertility. The relationship between exposure to air pollutants and semen quality is unclear. OBJECTIVES: To evaluate the impact of ambient air pollutant exposures on semen quality. METHODS: We analyzed 3797 semen samples from Guangdong Human Sperm Bank between May 28, 2018 and March 31, 2019. The inverse distance weighted interpolation method was used to estimate the personal exposures to CO, SO2, NO2, O3, PM10 and PM2.5 during the entire period (0-90 lag days) and key periods (0-9, 10-14, 70-90 lag days) of sperm development. Linear mixed models were used to evaluate the exposure-response relationships between air pollutants and semen quality, including sperm concentration, sperm count and sperm motility, after adjusting for other covariates. The regression coefficients and 95% confidence intervals (CIs) associated with each interquartile range (IQR) increase in pollutant concentrations were estimated for each semen quality parameter. RESULTS: Overall, we observed a significant association of decreased sperm count with the exposure to PM10 (-0.2466; -0.4443, -0.0489) and PM2.5 (-0.2910; -0.5401, -0.0419). Among the sperm quality parameters assessed, sperm count was observed more frequently to be negatively associated with ambient air pollutants (CO, NO2, O3, PM10 and PM2.5), especially for the period during 10-14 lag days. In addition, motility decline was significantly associated with O3 in the late stage of sperm development. Sensitivity analyses for subgroup population yielded similar results. No significant association was found between all pollutants and sperm concentration (all P > 0.05). CONCLUSIONS: Our results indicate that ambient air pollutants exposures during sperm development may have an adverse effect on semen quality, especially for sperm count and motility. The findings emphasize the potential to improve semen quality by reducing ambient air pollutant exposures, and the importance of taking into account the critical period of sperm development when protective measures are implemented.

Years of life lost with premature death due to ambient temperatures in a southwest plateau region of China: a cause-specific and individual characteristics stratified mortality study.

We aimed to explore whether there were cold and heat temperature adverse effects on years of life lost (YLL) for non-accidental mortality in Yuxi, a southwest plateau region of China. From data for 89,467 non-accidental deaths over an 8-year study period, we used a general linear regression model combined with a distributed lag non-linear model to assess the burden of disease non-accidental mortality due to ambient temperature with the YLL indicator. We estimated the mean YLL change per 1 °C decrease from the 25th to 1st percentile mean temperature as the cold effect and per 1 °C increase from the 75th to 99th percentile as the heat effect. The 95% empirical confidence intervals (eCIs) were calculated by using a bootstrap simulation method. The exposure-response curve between average temperature and YLL was U-shaped. The cold effect peaked at the first day after exposure and disappeared at 2 weeks, and the heat effect only lasted for the first 3 days. A per 1 °C decrease from the 25th to 1st mean temperature percentile was associated with an increase of 15.6 (95% eCI: 2.4, 22.9) in YLL for non-accidental diseases, and the cumulative effects due to cold were stronger in contrast to that attributed by heat. Cold temperature had a significant impact on YLL among the subgroups, with higher YLL in cardiovascular disease, stroke, males, Han nationality, married, and those engaged in agriculture than their corresponding categories. An increasing death burden of non-accidental in Yuxi of China due to cold temperature was demonstrated, and the association was also modified by specific disease causes and individual features.

Global patterns and trends in ovarian cancer incidence: age, period and birth cohort analysis.

BACKGROUND: Ovarian cancer (OC) is the seventh most common malignancy worldwide and the most lethal gynaecological malignancy. We aimed to explore global geographical patterns and temporal trends from 1973 to 2015 for 41 countries in OC incidence and especially to analyse the birth cohort effect to gain further insight into the underlying causal factors of OC and identify countries with increasing risk of OC. METHODS: OC data were drawn from the Cancer Incidence in Five Continents databases and online databases published by governments. The joinpoint regression model was applied to detect changes in OC trends. The age-period-cohort model was applied to explore age and birth cohort effects. RESULTS: The age-standardized rate of OC incidence ranged from 3.0 to 11.4 per 100,000 women worldwide in 2012. The highest age-standardized rate was observed in Central and Eastern Europe, with 11.4 per 100,000 women in 2012. For the most recent 10-year period, the increasing trends were mainly observed in Central and South America, Asia and Central and Eastern Europe. The largest significant increase was observed in Brazil, with an average annual percentage change of 4.4%. For recent birth cohorts, cohort-specific increases in risk were pronounced in Estonia, Finland, Iceland, Lithuania, the United Kingdom, Germany, the Netherlands, Italy, Malta, Slovenia, Bulgaria, Russia, Australia, New Zealand, Brazil, Costa Rica, Ecuador, India, Japan, the Philippines and Thailand. CONCLUSIONS: Disparities in the incidence and risk of OC persist worldwide. The increased risk of birth cohort in OC incidence was observed for most countries in Asia, Central and Eastern Europe, and Central and South America. The reason for the increasing OC risk for recent birth cohorts in these countries should be investigated with further epidemiology studies.

Global patterns and trends in stomach cancer incidence: Age, period and birth cohort analysis.

The cases of stomach cancer (SC) incidence are increasing per year and the SC burden has remained very high in some countries. We aimed to evaluate the global geographical variation in SC incidence and temporal trends from 1978 to 2007, with an emphasis on the effect of birth cohort. Joinpoint regression and age-period-cohort model were applied. From 2003 to 2007, male rate were 1.5- to 3-fold higher than female in all countries. Rates were highest in Eastern Asian and South American countries. Except for Uganda, all countries showed favorable trends. Pronounced cohort-specific increases in risk for recent birth cohorts were seen in Brazil, Colombia, Iceland, New Zealand, Norway, Uganda and US white people for males and in Australia, Brazil, Colombia, Costa Rica, Czech Republic, Ecuador, Iceland, India, Malta, New Zealand, Norway, Switzerland, United Kingdom, Uganda, US black and white people for females. The cohort-specific ratio for male significantly decreased in Japan, Malta and Spain for cohorts born since 1950 and in Austria, China, Croatia, Ecuador, Russia, Switzerland and Thailand for cohorts born since 1960 and for female in Japan for cohorts born since 1950 and in Canada, China, Croatia, Latvia, Russia and Thailand for cohorts born since 1960. Disparities in incidence and carcinogenic risk persist worldwide. The favorable trends may be due to changes in environmental exposure and lifestyle, including decreased Helicobacter pylori prevalence, increased intake of fresh fruits and vegetables, the availability of refrigeration and decreased intake of salted and preserved food and smoking prevalence.

Association of cold temperature and mortality and effect modification in the subtropical plateau monsoon climate of Yuxi, China.

BACKGROUND: Consistent evidence has shown excess mortality associated with cold temperature, but some important details of the cold-mortality association (e.g. slope and threshold) have not been adequately investigated and few studies focused on the cold effect in high-altitude areas of developing countries. We attempted to quantify the cold effect on mortality, identify the details, and evaluate effect modification in the distinct subtropical plateau monsoon climate of Yuxi, a high plateau region in southwest China. METHODS: From daily mortality and meteorological data during 2009-2014, we used a quasi-Poisson model combined with a "natural cubic spline-natural cubic spline" distributed lag non-linear model to estimate the temperature-mortality relationship and then a simpler "hockey-stick" model to investigate the cold effect and details. RESULTS: Cold temperature was associated with increased mortality, and the relative risk of cold effect (1st relative to 10th temperature percentile) on non-accidental, cardiovascular, and respiratory mortality for lag 0-21 days was 1.40 (95% confidence interval: 1.19-1.66), 1.61 (1.28-2.02), and 1.13 (0.78-1.64), respectively. A 1°C decrease below a cold threshold of 9.1°C (8th percentile) for lags 0-21 was associated with a 7.35% (3.75-11.09%) increase in non-accidental mortality. The cold-mortality association was not significantly affected by cause-specific mortality, gender, age, marital status, ethnicity, occupation, or previous history of hypertension. CONCLUSIONS: There is an adverse impact of cold on mortality in Yuxi, China, and a temperature of 9.1°C is an important cut-off for cold-related mortality for residents.

Syphilis in the economic center of South China: results from a real-time, web-based surveillance program.

BACKGROUND: Guangzhou is the economic center of South China, which is currently suffering an insidious re-emergence of syphilis. Syphilis epidemic in this area is a matter of serious concern, because of the special economic position of Guangzhou and its large migrant population. Therefore, a comprehensive analysis of surveillance data is needed to provide further information for developing targeted control programs. METHOD: Case-based surveillance data obtained from a real-time, web-based system were analyzed. A hierarchical clustering method was applied to classify the 12 districts of Guangzhou into several epidemiological regions. The district-level annual incidence and clustering results were displayed on the same map to show the spatial patterns of syphilis in Guangzhou. RESULTS: A total of 60,178 syphilis cases were reported during the period from 2005 to 2013, among which primary/secondary syphilis accounted for 15,864 cases (26.36 %), latent syphilis for 41,078 cases (68.26 %) and congenital syphilis for 2,090 cases (3.47 %). Moreover, primary/secondary syphilis burden slightly decreased from 17.5-18.0 cases per 100,000 people in the first years to 10.6 cases per 100,000 in 2013, with latent syphilis largely increasing from 18.5 cases per 100,000 to 43.4 cases per 100,000. Districts of Guangzhou could be classified into 3 epidemiological regions according to the syphilis burden over the last 3 years of the study period. CONCLUSIONS: The burden of primary/secondary syphilis appears to be decreasing in recent years, whereas that of latent syphilis is increasing. Given the epidemiological features and the annual changes found in this study, it is suggested that future control programs should be more population-specific and spatially targeted.

Gene expression profile based classification models of psoriasis.

Psoriasis is an autoimmune disease, which symptoms can significantly impair the patient's life quality. It is mainly diagnosed through the visual inspection of the lesion skin by experienced dermatologists. Currently no cure for psoriasis is available due to limited knowledge about its pathogenesis and development mechanisms. Previous studies have profiled hundreds of differentially expressed genes related to psoriasis, however with no robust psoriasis prediction model available. This study integrated the knowledge of three feature selection algorithms that revealed 21 features belonging to 18 genes as candidate markers. The final psoriasis classification model was established using the novel Incremental Feature Selection algorithm that utilizes only 3 features from 2 unique genes, IGFL1 and C10orf99. This model has demonstrated highly stable prediction accuracy (averaged at 99.81%) over three independent validation strategies. The two marker genes, IGFL1 and C10orf99, were revealed as the upstream components of growth signal transduction pathway of psoriatic pathogenesis.

Preoperative aspartate aminotransferase to platelet ratio is an independent prognostic factor for hepatitis B-induced hepatocellular carcinoma after hepatic resection.

BACKGROUND: There is conflicting evidence concerning platelet status and hepatocellular carcinoma (HCC) prognosis. We evaluated the prognostic value of platelet-based indices, including platelet count, platelet/lymphocyte ratio (PLR), and aspartate aminotransferase to platelet ratio index (APRI) in HCC after hepatic resection. METHODS: We retrospectively reviewed 332 patients with HCC treated with hepatectomy between 2006 and 2009. Preoperative platelet count, as well as demographic, clinical, and pathologic data, were analyzed. RESULTS: Both disease-free survival (DFS) and overall survival (OS) were significantly improved for patients with low platelet count, PLR, and APRI compared to patients with elevated values. On multivariate analysis, APRI, tumor size ≥5 cm, noncapsulation, and multiple tumors were all associated with both poor DFS and OS. The 1-, 3-, and 5-year DFS rates were 52, 36, and 32 % for patients with APRI <0.62 and were 35, 22, and 19 % for patients with APRI ≥0.62. Correspondingly, the 1-, 3-, and 5-year OS rates were 77, 51, and 42, and 63, 35, and 29 % for both groups. Both DFS and OS of patients with APRI <0.62 were significantly better compared to patients with an elevated APRI (P = 0.009 and 0.002, respectively). Patients with elevated APRI tended to have cirrhosis, hepatitis B virus (HBV) infection, surgical margin <1 cm, and noncapsulated tumors. CONCLUSIONS: Elevated platelets based inflammatory indices, especially APRI, was associated with adverse characteristic features and poor prognosis in HCC, especially for patients with HBV infection or cirrhosis. Antiplatelet treatment may represent a potential therapy for HBV-induced HCC recurrence.

Persistence of severe global inequalities in the burden of blindness and vision loss from 1990 to 2019: findings from the Global Burden of Disease Study 2019.

AIMS: To assess the global burden and economic inequalities in the distribution of blindness and vision loss between 1990 and 2019. METHODS: A secondary analysis of the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019. Data for disability-adjusted life-years (DALYs) due to blindness and vision loss were extracted from the GBD 2019. Data for gross domestic product per capita were extracted from the World Bank database. Slope index of inequality (SII) and concentration index were computed to assess absolute and relative cross-national health inequality, respectively. RESULTS: Countries with high, high-middle, middle, low-middle and low Socio-demographic Index (SDI) had decline of age-standardised DALY rate of 4.3%, 5.2%, 16.0%, 21.4% and 11.30% from 1990 to 2019, respectively. The poorest 50% of world citizens bore 59.0% and 66.2% of the burden of blindness and vision loss in 1990 and 2019, respectively. The absolute cross-national inequality (SII) fell from -303.5 (95% CI -370.8 to -236.2) in 1990 to -256.0 (95% CI -288.1 to -223.8) in 2019. The relative inequality (concentration index) for global blindness and vision loss remained essentially constant between 1991 (-0.197, 95% CI -0.234 to -0.160) and 2019 (-0.193, 95% CI -0.216 to -0.169). CONCLUSION: Though countries with middle and low-middle SDI were the most successful in decreasing burden of blindness and vision loss, a high level of cross-national health inequality persisted over the past three decades. More attention must be paid to the elimination of avoidable blindness and vision loss in low-income and middle-income countries.

Effects of temperature anomaly on sperm quality: A multi-center study of 33,234 men.

Backgrounds: Global fertility rates continue to decline and sperm quality is a prime factor affecting male fertility. Both extreme cold and heat have been demonstrated to be associated with decreased sperm quality, but no epidemiological studies have considered human adaptation to long-term temperature. Our aim was to conduct a multi-center retrospective cohort study to investigate exposure-response relationship between temperature anomaly (TA) that deviate from long-term climate patterns and sperm quality. Methods: A total of 78,952 semen samples measured in 33,234 donors from 6 provincial human sperm banks in China were collected. This study considered heat and cold acclimatization to prolonged exposure in humans and explored the exposure-response relationship between TAs and sperm quality parameters (sperm concentrations, sperm count, progressive motility, progressive sperm count, total motility and total motile sperm count) during the hot and cold seasons, respectively. Linear mixed models and generalized linear models were built separately for specific centers to pool in a meta-analysis to obtain the pooled effect of TA on sperm quality, considering repeated measurements data structure and spatial heterogeneity. Results: We identified an inverted U-shaped exposure-response relationship between TA and sperm quality during the hot season. Significant negative effect of anomalous cold on sperm quality during the hot season was found after additional adjustment for Body mass index, marital status and childbearing history. The heat-related TA in hot season was significantly negatively associated with sperm concentration, progressive sperm count and total motile sperm count (all P-values<0.05). After adjusting the relative humidity, the cold-related TA in cold season was negatively associated with the sperm total motility (P-values<0.05). Conclusions: Our results suggest both heat-related and cold-related TAs are associated with decreased sperm quality. The findings highlight the importance of reducing exposure to anomalous temperatures to protect male fertility.

Beneficial effect of residential greenness on sperm quality and the role of air pollution: A multicenter population-based study.

BACKGROUND: Poor sperm quality is a major cause of male infertility. However, evidence remains scarce on how greenness affects male sperm quality. OBJECTIVES: To assess the associations of residential greenness with male sperm quality and the modification effect of air pollution exposure on the relationship. METHODS: A total of 78,742 samples from 33,184 sperm donors from 6 regions across China during 2014-2020 were included and analyzed. Individual residential greenness exposures of study subjects were estimated using the Normalized Difference Vegetation Index (NDVI) during the entire (0-90 lag days) and two key stages (0-37, and 34-77 lag days) of sperm development. Contemporaneous personal exposure levels to air pollutants were estimated using a spatio-temporal deep learning method. Linear mixed models were employed to assess the impact of greenspace in relation to sperm quality. The modification effect of air pollution on the greenspace-sperm quality relationship was also estimated. RESULTS: Per IQR increment in NDVI exposure throughout spermatogenesis were statistically associated with increasing sperm count by 0.0122 (95 % CI: 0.0007, 0.0237), progressive motility by 0.0162 (95 % CI: 0.0045, 0.0280), and total motility by 0.0147 (95 % CI: 0.0014, 0.0281), respectively. Similar results were observed when the model added air pollutants (PM1, PM2.5 or O3) for adjustment. Additionally, specific air pollutants, including PM1, PM2.5, and O3, were found to modify this association. Notably, the protective effects of greenness exposure were more pronounced at higher concentrations of PM1 and PM2.5 and lower concentrations of O3 (all Pinteraction < 0.05). Statistically significant positive effects of NDVI were observed on sperm motility in early spermatogenesis and sperm count in late spermatogenesis. CONCLUSIONS: Exposure to residential greenness may have beneficial effects on sperm quality and air pollution modifies their relationship. These findings highlight the importance of adopting adaptable urban greenspace planning and policies to safeguard male fertility against environmental factors.

Clinical effects of Xinmailong therapy in patients with chronic heart failure.

In the last 100 years, intensive studies have been done on the identification of the systematic approaches to find the cure for the chronic heart failure, however the mystery remains unresolved due to its complicated pathogenesis and ineffective early diagnosis. The present investigation was aimed to evaluate the potential effects of the traditional chinese medicine, Xinmailong, on the chronic heart failure (CHF) patients as compared to the standard western medical treatment available so far. In our study, we selected two groups of voluntary CHF patients at the Xiangya Hospital, which were allowed to administrate Xinmailong or standard treatments, respectively. Another group of voluntary healthy individuals were recruited as the control group. The treatment effectiveness was measured by five symptomatic factors, i.e. angiotensin II (Ang_II), high sensitivity C-reactive protein (hs_CRP), Left Ventricular End Systolic Volume Index (LVESVI), left ventricular ejection fraction (LVEF) and pro-B-type natriuretic peptide (NT_proBNP), between the control group and the CHF patients at different stages of drug administration and in different treatment groups. The timeline for the full dose administration was set to 15 days and five measurements as indicated above were taken on every 0, 7th and 15th day of the drug administration respectively. In the conducted study, similar symptomatic measurements were observed on day 0 in both treatment groups, and slight improvements were observed on 7th day. It was observed that after a full course of drug administration for 15 days, both of the treatment groups achieved statistically significant improvements in all the five measures, but Xinmailong was found to be more (almost double) statistically significant as compared with the available drug treatments for chronic heart failure.

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying high-risk women and adopting early intervention. In this study, we used four machine-learning models (LASSO logistic regression, random forest, backpropagation neural network, and support vector machines) to predict the occurrence of PIH in a prospective cohort. Candidate features for predicting the occurrence of middle and late PIH were acquired using a LASSO algorithm. The performance of predictive models was assessed using receiver operating characteristic analysis. Finally, a nomogram was established with the model scores, age, and nulliparity. Calibration, clinical usefulness, and internal validation were used to assess the performance of the nomogram. In the training set (2258 pregnant women), eleven candidate factors in the first trimester were significantly associated with the occurrence of PIH (P < 0.001 in the training set). Four models showed AUCs from 0.780 to 0.816 in the training set. For the validation set (939 pregnant women), AUCs varied from 0.516 to 0.795. The nomogram showed good discrimination, with an AUC of 0.847 (95% CI: 0.805-0.889) in the training set and 0.753 (95% CI: 0.653-0.853) in the validation set. Decision curve analysis suggested that the model was clinically useful. The model developed using LASSO logistic regression achieved the best performance in predicting the occurrence of PIH. The derived nomogram, which incorporates the model score and maternal risk factors, can be used to predict PIH in clinical practice. We develop a model with good performance for clinical prediction of PIH in the first trimester.

The size of the susceptible pool differentiates climate effects on seasonal epidemics of bacillary dysentery.

OBJECTIVES: At present, some studies have pointed out several possible climate drivers of bacillary dysentery. However, there is a complex nonlinear interaction between climate drivers and susceptible population in the spread of diseases, which makes it challenging to detect climate drivers at the size of susceptible population. METHODS: By using empirical dynamic modeling (EDM), the climate drivers of bacillary dysentery dynamic were explored in China's five temperature zones. RESULTS: We verified the availability of climate drivers and susceptible population size on bacillary dysentery, and used this information for bacillary dysentery dynamic prediction. Moreover, we found that their respective effects increased with the increase of temperature and relative humidity, and their states (temperature and relative humidity) were different when they reached their maximum effects, and the negative effect between the effect of temperature and disease incidence increased with the change of temperature zone (from temperate zone to warm temperate zone to subtropical zone) and the climate driving effect of the temperate zone (warm temperate zone) was greater than that of the colder (temperate zone) and warmer (subtropics) zones. When we viewed from single temperature zone, the climatic effect arose only when the size of the susceptible pool was large. CONCLUSIONS: These results provide empirical evidence that the climate factors on bacillary dysentery are nonlinear, complex but dependent on the size of susceptible populations and different climate scenarios.

Dengue transmission dynamics prediction by combining metapopulation networks and Kalman filter algorithm.

Predicting the specific magnitude and the temporal peak of the epidemic of individual local outbreaks is critical for infectious disease control. Previous studies have indicated that significant differences in spatial transmission and epidemic magnitude of dengue were influenced by multiple factors, such as mosquito population density, climatic conditions, and population movement patterns. However, there is a lack of studies that combine the above factors to explain their complex nonlinear relationships in dengue transmission and generate accurate predictions. Therefore, to study the complex spatial diffusion of dengue, this research combined the above factors and developed a network model for spatiotemporal transmission prediction of dengue fever using metapopulation networks based on human mobility. For improving the prediction accuracy of the epidemic model, the ensemble adjusted Kalman filter (EAKF), a data assimilation algorithm, was used to iteratively assimilate the observed case data and adjust the model and parameters. Our study demonstrated that the metapopulation network-EAKF system provided accurate predictions for city-level dengue transmission trajectories in retrospective forecasts of 12 cities in Guangdong province, China. Specifically, the system accurately predicts local dengue outbreak magnitude and the temporal peak of the epidemic up to 10 wk in advance. In addition, the system predicted the peak time, peak intensity, and total number of dengue cases more accurately than isolated city-specific forecasts. The general metapopulation assimilation framework presented in our study provides a methodological foundation for establishing an accurate system with finer temporal and spatial resolution for retrospectively forecasting the magnitude and temporal peak of dengue fever outbreaks. These forecasts based on the proposed method can be interoperated to better support intervention decisions and inform the public of potential risks of disease transmission.