The global burden of disease attributable to preterm birth and low birth weight in 204 countries and territories from 1990 to 2019: An analysis of the Global Burden of Disease Study.

Background: Preterm birth and low birth weight (PBLBW), recognised globally as primary contributors to infant mortality in children under five, have not been sufficiently investigated in terms of their worldwide impact. In this study we aimed to thoroughly evaluate the contemporary trends in disease burden attributable to PBLBW. Methods: We analysed data from 204 countries and territories between 1990-2019, as sourced from the 2019 Global Burden of Disease Study. We analysed the global incidence of mortality and disability-adjusted life years (DALYs) associated with PBLBW, stratified by age, gender, year, and geographic location, alongside the socio-demographic index (SDI). We calculated the annual percentage changes to evaluate the dynamic trends over time. We employed a generalised linear model and scrutinised the relationship between the SDI and the disease burden attributed to PBLBW. Results: In 2019, the global age-standardised rate of deaths and DALYs related to PBLBW showed significant declines. Over the period 1990-2019, both death and DALY rates displayed substantial downward trends, with similar change trends observed for both females and males. Age-specific ratios revealed a decrease in PBLBW-related deaths and DALYs with increasing age, primarily during the neonatal stages (zero to 27 days). The leading three causes of PBLBW-related DALYs in 2019 were neonatal disorders, lower respiratory infections, and sudden infant death syndrome. Furthermore, the association between SDI and PBLBW-related DALYs indicated that the age-standardised DALY rates in 204 countries and territories worldwide were negatively correlated with SDI in 2019. From 1990 to 2019, the age-standardised DALY rates decreased linearly in most regions, except sub-Saharan Africa. Conclusions: The persistent global burden of disease associated with PBLBW is particularly pronounced in neonates aged less than 28 days and in regions with low SDI. In this study, we highlighted the critical need for tailored interventions aimed at mitigating the detrimental effects of PBLBW to attain specific sustainable development goals, particularly those centred on enhancing child survival and overall well-being.

Feasibility of ultrasound radiomics based models for classification of liver fibrosis due to Schistosoma japonicum infection.

BACKGROUND: Schistosomiasis japonica represents a significant public health concern in South Asia. There is an urgent need to optimize existing schistosomiasis diagnostic techniques. This study aims to develop models for the different stages of liver fibrosis caused by Schistosoma infection utilizing ultrasound radiomics and machine learning techniques. METHODS: From 2018 to 2022, we retrospectively collected data on 1,531 patients and 5,671 B-mode ultrasound images from the Second People's Hospital of Duchang City, Jiangxi Province, China. The datasets were screened based on inclusion and exclusion criteria suitable for radiomics models. Liver fibrosis due to Schistosoma infection (LFSI) was categorized into four stages: grade 0, grade 1, grade 2, and grade 3. The data were divided into six binary classification problems, such as group 1 (grade 0 vs. grade 1) and group 2 (grade 0 vs. grade 2). Key radiomic features were extracted using Pyradiomics, the Mann-Whitney U test, and the Least Absolute Shrinkage and Selection Operator (LASSO). Machine learning models were constructed using Support Vector Machine (SVM), and the contribution of different features in the model was described by applying Shapley Additive Explanations (SHAP). RESULTS: This study ultimately included 1,388 patients and their corresponding images. A total of 851 radiomics features were extracted for each binary classification problems. Following feature selection, 18 to 76 features were retained from each groups. The area under the receiver operating characteristic curve (AUC) for the validation cohorts was 0.834 (95% CI: 0.779-0.885) for the LFSI grade 0 vs. LFSI grade 1, 0.771 (95% CI: 0.713-0.835) for LFSI grade 1 vs. LFSI grade 2, and 0.830 (95% CI: 0.762-0.885) for LFSI grade 2 vs. LFSI grade 3. CONCLUSION: Machine learning models based on ultrasound radiomics are feasible for classifying different stages of liver fibrosis caused by Schistosoma infection.

Pressure-controlled inverse ratio ventilation improves gas exchange in obese children undergoing laparoscopic surgery: a randomized controlled study.

BACKGROUND: Obese children undergoing laparoscopic surgery frequently experience high end-tidal carbon dioxide partial pressure (PETCO2) and respiratory acidosis. This study aimed to investigate the effects of pressure-controlled inverse ratio ventilation (IRV) with an inspiratory to expiratory ratio (I:E) of 1.5:1 on obese children undergoing laparoscopic surgery. METHODS: Eighty children undergoing laparoscopic surgery were randomly assigned to either the IRV group (I:E=1.5:1) or the control group (I:E=1:1.5). The lungs were mechanically ventilated following tracheal intubation. The children underwent pressure-controlled ventilation with an I:E ratio of 1.5:1 or 1:1.5. Respiratory mechanics, hemodynamic values, and ventilation-related side effects were recorded. RESULTS: Thirty minutes after establishing CO2 pneumoperitoneum, the IRV group exhibited significantly higher tidal volume (Vt) and arterial partial pressure of oxygen (PaO2) compared to the control group (97.6 ± 6.6 vs. 93.2 ± 8.0 ml, 283 ± 54 vs. 247 ± 40 mmHg, respectively) (P < 0.01). Furthermore, PaCO2 was significantly lower in the IRV group than in the control group (41.4 ± 5.8 vs. 45.5 ± 5.7 mmHg, P=0.002). The incidence of intra-operative hypercapnia was significantly decreased in the IRV group (25% vs. 42.5%, P=0.03). CONCLUSION: Pressure-controlled IRV can reduce the incidence of hypercapnia, increasing Vt, and thereby improving CO2 elimination in obese children undergoing laparoscopy. This ventilation technique significantly improves gas exchange in this patient population. (Registration number: ChiCTR2000035589).

Prediction of Oncomelania hupensis distribution in association with climate change using machine learning models.

BACKGROUND: Oncomelania hupensis is the sole intermediate host of Schistosoma japonicum. Its emergence and recurrence pose a constant challenge to the elimination of schistosomiasis in China. It is important to accurately predict the snail distribution for schistosomiasis prevention and control. METHODS: Data describing the distribution of O. hupensis in 2016 was obtained from the Yunnan Institute of Endemic Disease Control and Prevention. Eight machine learning algorithms, including eXtreme Gradient Boosting (XGB), support vector machine (SVM), random forest (RF), generalized boosting model (GBM), neural network (NN), classification and regression trees (CART), k-nearest neighbors (KNN), and generalized additive model (GAM), were employed to explore the impacts of climatic, geographical, and socioeconomic variables on the distribution of suitable areas for O. hupensis. Predictions of the distribution of suitable areas for O. hupensis were made for various periods (2030s, 2050s, and 2070s) under different climate scenarios (SSP126, SSP245, SSP370, and SSP585). RESULTS: The RF model exhibited the best performance (AUC: 0.991, sensitivity: 0.982, specificity: 0.995, kappa: 0.942) and the CART model performed the worst (AUC: 0.884, sensitivity: 0.922, specificity: 0.943, kappa: 0.829). Based on the RF model, the top six important variables were as follows: Bio15 (precipitation seasonality) (33.6%), average annual precipitation (25.2%), Bio2 (mean diurnal temperature range) (21.7%), Bio19 (precipitation of the coldest quarter) (14.5%), population density (13.5%), and night light index (11.1%). The results demonstrated that the overall suitable habitats for O. hupensis were predominantly distributed in the schistosomiasis-endemic areas located in northwestern Yunnan Province under the current climate situation and were predicted to expand north- and westward due to climate change. CONCLUSIONS: This study showed that the prediction of the current distribution of O. hupensis corresponded well with the actual records. Furthermore, our study provided compelling evidence that the geographical distribution of snails was projected to expand toward the north and west of Yunnan Province in the coming decades, indicating that the distribution of snails is driven by climate factors. Our findings will be of great significance for formulating effective strategies for snail control.

Three Gorges Dam: Potential differential drivers and trend in the spatio-temporal evolution of the change in snail density based on a Bayesian spatial-temporal model and 5-year longitudinal study.

BACKGROUND: Snail abundance varies spatially and temporally. Few studies have elucidated the different effects of the determinants affecting snail density between upstream and downstream areas of the Three Gorges Dam (TGD). We therefore investigated the differential drivers of changes in snail density in these areas, as well as the spatial-temporal effects of these changes. METHODS: A snail survey was conducted at 200 sites over a 5-year period to monitor dynamic changes in snail abundance within the Yangtze River basin. Data on corresponding variables that might affect snail abundance, such as meteorology, vegetation, terrain and economy, were collected from multiple data sources. A Bayesian spatial-temporal modeling framework was constructed to explore the differential determinants driving the change in snail density and the spatial-temporal effects of the change. RESULTS: Volatility in snail density was unambiguously detected in the downstream area of the TGD, while a small increment in volatility was detected in the upstream area. Regarding the downstream area of the TGD, snail density was positively associated with the average minimum temperature in January of the same year, the annual Normalized Difference Vegetation Index (NDVI) of the previous year and the second, third and fourth quartile, respectively, of average annual relative humidity of the previous year. Snail density was negatively associated with the average maximum temperature in July of the previous year and annual nighttime light of the previous year. An approximately inverted "U" curve of relative risk was detected among sites with a greater average annual ground surface temperature in the previous year. Regarding the upstream area, snail density was positively associated with NDVI and with the second, third and fourth quartile, respectively, of total precipitation of the previous year. Snail density was negatively associated with slope. CONCLUSIONS: This study demonstrated a rebound in snail density between 2015 and 2019. In particular, temperature, humidity, vegetation and human activity were the main drivers affecting snail abundance in the downstream area of the TGD, while precipitation, slope and vegetation were the main drivers affecting snail abundance in the upstream area. These findings can assist authorities to develop and perform more precise strategies for surveys and control of snail populations.

Spatiotemporal distribution of schistosomiasis transmission risk in Jiangling County, Hubei Province, P.R. China.

OBJECTIVE: This study aims to explore the spatiotemporal distribution of schistosomiasis in Jiangling County, and provide insights into the precise schistosomiasis control. METHODS: The descriptive epidemiological method and Joinpoint regression model were used to analyze the changes in infection rates of humans, livestock, snails, average density of living snails and occurrence rate of frames with snails in Jiangling County from 2005 to 2021. Spatial epidemiology methods were used to detect the spatiotemporal clustering of schistosomiasis transmission risk in Jiangling county. RESULTS: The infection rates in humans, livestock, snails, average density of living snails and occurrence rate of frames with snails in Jiangling County decreased from 2005 to 2021 with statistically significant. The average density of living snails in Jiangling County was spatially clustered in each year, and the Moran's I varied from 0.10 to 0.26. The hot spots were mainly concentrated in some villages of Xionghe Town, Baimasi Town and Shagang Town. The mean center of the distribution of average density of living snails in Jiangling County first moved from northwest to southeast, and then returned from southeast to northwest after 2014. SDE azimuth fluctuated in the range of 111.68°-124.42°. Kernal density analysis showed that the high and medium-high risk areas of Jiangling County from 2005 to 2021 were mainly concentrated in the central and eastern of Jiangling County, and the medium-low and low risk areas were mainly distributed in the periphery of Jiangling County. CONCLUSIONS: The epidemic situation of schistosomiasis decreased significantly in Jiangling County from 2005 to 2021, but the schistosomiasis transmission risk still had spatial clustering in some areas. After transmission interruption, targeted transmission risk intervention strategies can be adopted according to different types of schistosomiasis risk areas.

Three Gorges Dam: the changing trend of snail density in the Yangtze River basin between 1990 and 2019.

BACKGROUND: The area of Oncomelania hupensis snail remains around 3.6 billion m2, with newly emerging and reemergent habitats continuing to appear in recent years. This study aimed to explore the long-term dynamics of snail density before and after the operation of Three Gorges Dam (TGD). METHODS: Data of snail survey between 1990 and 2019 were collected from electronic databases and national schistosomiasis surveillance. Meta-analysis was conducted to estimate the snail density. Joinpoint model was used to identify the changing trend and inflection point. Inverse distance weighted interpolation (IDW) was used to determine the spatial distribution of recent snail density. RESULTS: A total of 3777 snail survey sites with a precise location of village or beach were identified. For the downstream area, snail density peaked in 1998 (1.635/0.11 m2, 95% CI: 1.220, 2.189) and fluctuated at a relatively high level before 2003, then declined steadily from 2003 to 2012. Snail density maintained lower than 0.150/0.11 m2 between 2012 and 2019. Joinpoint model identified the inflection of 2003, and a significant decreasing trend from 2003 to 2012 with an annual percentage change (APC) being - 20.56% (95% CI: - 24.15, - 16.80). For the upstream area, snail density peaked in 2005 (0.760/0.11 m2, 95% CI: 0.479, 1.207) and was generally greater than 0.300/0.11 m2 before 2005. Snail density was generally lower than 0.150/0.11 m2 after 2011. Snail density showed a significant decreasing trend from 1990 to 2019 with an APC being - 6.05% (95% CI: - 7.97, - 7.09), and no inflection was identified. IDW showed the areas with a high snail density existed in Poyang Lake, Dongting Lake, Jianghan Plain, and the Anhui branch of the Yangtze River between 2015 and 2019. CONCLUSIONS: Snail density exhibited a fluctuating downward trend in the Yangtze River basin. In the downstream area, the operation of TGD accelerated the decline of snail density during the first decade period, then snail density fluctuated at a relatively low level. There still exists local areas with a high snail density. Long-term control and monitoring of snails need to be insisted on and strengthened.

Establishment of an indicator framework for the transmission risk of the mountain-type zoonotic visceral leishmaniasis based on the Delphi-entropy weight method.

BACKGROUND: Visceral leishmaniasis (VL) is one of the most important neglected tropical diseases. Although VL was controlled in several regions of China during the last century, the mountain-type zoonotic visceral leishmaniasis (MT-ZVL) has reemerged in the hilly areas of China in recent decades. The purpose of this study was to construct an indicator framework for assessing the risk of the MT-ZVL in China, and to provide guidance for preventing disease. METHODS: Based on a literature review and expert interview, a 3-level indicator framework was initially established in November 2021, and 28 experts were selected to perform two rounds of consultation using the Delphi method. The comprehensive weight of the tertiary indicators was determined by the Delphi and the entropy weight methods. RESULTS: Two rounds of Delphi consultation were conducted. Four primary indicators, 11 secondary indicators, and 35 tertiary indicators were identified. The Delphi-entropy weight method was performed to calculate the comprehensive weight of the tertiary indicators. The normalized weights of the primary indicators were 0.268, 0.261, 0.242, and 0.229, respectively, for biological factors, interventions, environmental factors, and social factors. The normalized weights of the top four secondary indicators were 0.122, 0.120, 0.098, and 0.096, respectively, for climatic features, geographical features, sandflies, and dogs. Among the tertiary indicators, the top four normalized comprehensive weights were the population density of sandflies (0.076), topography (0.057), the population density of dogs, including tethering (0.056), and use of bed nets or other protective measures (0.056). CONCLUSIONS: An indicator framework of transmission risk assessment for MT-ZVL was established using the Delphi-entropy weight method. The framework provides a practical tool to evaluate transmission risk in endemic areas.

Transmission Risk Predicting for Schistosomiasis in Mainland China by Exploring Ensemble Ecological Niche Modeling.

Schistosomiasis caused by Schistosoma japonicum is one of the major neglected tropical diseases worldwide. The snail Oncomelania hupensis is the only intermediate host of S. japonicum, which is recognized as an indicator of the schistosomias occurrence. In order to evaluate the risk of schistosomiasis in China, this work investigate the potential geographical distribution of host snail habitus by developing an ensemble ecological niche model with reference to the suitable environmental factors. The historical records of snail habitus were collected form the national schistosomiasis surveillance program from the year of 2005 to 2014. A total of 25 environmental factors in terms of the climate, geographic, and socioeconomic determinants of snail habitats were collected and geographically coded with reference to the snail data. Based on the correlations among snail habitats and the geographically associated environmental factors, an ensemble ecological niche model was developed by integrating ten standard models, aiming for improving the predictive accuracy. Three indexes are used for model performance evaluation, including receiver operating characteristic curves, kappa statistics, and true skill statistics. The model was used for mapping the risk of schistosomiasis in the middle and lower reaches of the Yangtze River. The results have shown that the predicted risk areas were classified into low risk (4.55%), medium risk (2.01%), and high risk areas (4.40%), accounting for 10.96% of the land area of China. This study demonstrated that the developed ensemble ecological niche models was an effective tool for evaluating the risk of schistosomiasis, particularly for the endemic regions, which were not covered by the national schistosomiasis control program.

Ergonomic Consideration in Pillow Height Determinants and Evaluation.

(1) Background: Sleep problems have become one of the current serious public health issues. Pillow height affects the alignment of the cervical spine and is closely related to the mechanical environment of the cervical spine. An appropriate pillow height can provide adequate support for the head and neck to reduce the stress in the cervical spine and relax the muscles of the neck and shoulder, thereby relieving pain and improving sleep quality. (2) Methods: We reviewed the current trends, research methodologies, and determinants of pillow height evaluation, summarizing the evidences published since 1997. In particular, we scrutinized articles dealing with the physiological and mechanical characteristics of the head-neck-shoulder complex. (3) Results: Through the investigation and analysis of these articles, we presented several quantitative and objective determinants for pillow height evaluation, including cervical spine alignment, body dimension, contact pressure, and muscle activity. The measurement methods and selection criteria for these parameters are described in detail. However, the suggested range for achieving optimal cervical spine alignment, appropriate pressure distribution, and minimal muscle activity during sleep cannot yet be identified considering the lack of sufficient evidence. Moreover, there remain no firm conclusions about the optimal pillow height for the supine and lateral positions. (4) Conclusions: A comprehensive evaluation combining the above determinants provides a unique solution for ergonomic pillow design and proper pillow height selection, which can effectively promote the public sleep health. Therefore, it is necessary to develop a reasonable algorithm to weigh multiple determinants.

The Potential Distribution Prediction of Oncomelania hupensis Based on Newly Emerging and Reemergent Habitats - China, 2015-2019.

What is already known about this topic? Oncomelania hupensis (O. hupensis) is the only intermediate host of Schistosoma japonica. The distribution of O. hupensis is affected by a series of climate, geographical, sand ocioeconomic factors, which reflect the risk areas of schistosomiasis. What is added by this report? There were certain geographical aggregations in the potential high distribution areas of O. hupensis, which were mainly distributed in Poyang Lake area, Dongting Lake area, and the middle and the lower reaches of the Yangtze River. What are the implications for public health practice? Monitoring and forecasting the distribution of O. hupensis is conducive to improving the early warning capabilities of the potential risk of schistosomiasis transmission and progressively promoting the elimination of schistosomiasis nationwide.

Identification of the high-risk area for schistosomiasis transmission in China based on information value and machine learning: a newly data-driven modeling attempt.

BACKGROUND: Schistosomiasis control is striving forward to transmission interruption and even elimination, evidence-lead control is of vital importance to eliminate the hidden dangers of schistosomiasis. This study attempts to identify high risk areas of schistosomiasis in China by using information value and machine learning. METHODS: The local case distribution from schistosomiasis surveillance data in China between 2005 and 2019 was assessed based on 19 variables including climate, geography, and social economy. Seven models were built in three categories including information value (IV), three machine learning models [logistic regression (LR), random forest (RF), generalized boosted model (GBM)], and three coupled models (IV + LR, IV + RF, IV + GBM). Accuracy, area under the curve (AUC), and F1-score were used to evaluate the prediction performance of the models. The optimal model was selected to predict the risk distribution for schistosomiasis. RESULTS: There is a more prone to schistosomiasis epidemic provided that paddy fields, grasslands, less than 2.5 km from the waterway, annual average temperature of 11.5-19.0 °C, annual average rainfall of 1000-1550 mm. IV + GBM had the highest prediction effect (accuracy = 0.878, AUC = 0.902, F1 = 0.920) compared with the other six models. The results of IV + GBM showed that the risk areas are mainly distributed in the coastal regions of the middle and lower reaches of the Yangtze River, the Poyang Lake region, and the Dongting Lake region. High-risk areas are primarily distributed in eastern Changde, western Yueyang, northeastern Yiyang, middle Changsha of Hunan province; southern Jiujiang, northern Nanchang, northeastern Shangrao, eastern Yichun in Jiangxi province; southern Jingzhou, southern Xiantao, middle Wuhan in Hubei province; southern Anqing, northwestern Guichi, eastern Wuhu in Anhui province; middle Meishan, northern Leshan, and the middle of Liangshan in Sichuan province. CONCLUSIONS: The risk of schistosomiasis transmission in China still exists, with high-risk areas relatively concentrated in the coastal regions of the middle and lower reaches of the Yangtze River. Coupled models of IV and machine learning provide for effective analysis and prediction, forming a scientific basis for evidence-lead surveillance and control.

IL-1ß promotes cervical cancer through activating NF-κB/CCL-2.

Cervical cancer is a malignancy with high morbidity and mortality among women. Interleukin (IL)-1ß, chemokine (C-C motif) ligand 2 (CCL-2), and activation of NF-κB have been proven to be closely related to the progression of various tumors. However, their role in cervical cancer remains unclear. Cell proliferation, migration, and invasion were detected using MTT, wound healing, and transwell assays. Western blotting and qRT-PCR were used to measure expression of target genes. IL-1ß greatly promoted the release of CCL-2 from HeLa cells. Activation of NF-κB and phosphorylated NF-κB (p65) nuclear translocation were accelerated by IL-1ß. TPCA-1, a blocker of NF-κB, significantly inhibited the release of CCL-2 from HeLa cells. TPCA-1 markedly reversed the promotional effect of IL-1ß on viability of HeLa cells. IL-1ß increased the cell migration, proliferation, and invasion of HeLa cells through targeting the NF-κB/CCL-2 pathway. IL-1ß/NF-κB/CCL-2 might be a promising treatment target for cervical cancer treatment and prevention.

Spatio-temporal clustering of Mountain-type Zoonotic Visceral Leishmaniasis in China between 2015 and 2019.

With several decades of concerted control efforts, visceral leishmaniasis(VL) eradication had almost been achieved in China. However, VL cases continue to be detected in parts of western China recent years. Using data of reported cases, this study aimed to investigate the epidemiology and spatio⁃temporal distribution, of mountain-type zoonotic visceral leishmaniasis (MT-ZVL) in China between the years 2015 and 2019. Epidemiological data pertaining to patients with visceral leishmaniasis (VL) were collected in Gansu, Shaanxi, Sichuan, Shanxi, Henan and Hebei provinces between the years 2015 and 2019. Joinpoint regression analysis was performed to determine changes in the epidemic trend of MT-ZVL within the time period during which data was collected. Spatial autocorrelation of infection was examined using the Global Moran's I statistic wand hotspot analysis was carried out using the Getis-Ord Gi* statistic. Spatio-temporal clustering analysis was conducted using the retrospective space-time permutation flexible spatial scanning statistics. A total of 529 cases of MT-ZVL were detected in the six provinces from which data were collected during the study time period, predominantly in Gansu (55.0%), Shanxi (21.7%), Shaanxi (12.5%) and Sichuan (8.9%) provinces. A decline in VL incidence in China was observed during the study period, whereas an increase in MT-ZVL incidence was observed in the six provinces from which data was obtained (t = 4.87, P < 0.05), with highest incidence in Shanxi province (t = 16.91, P < 0.05). Significant differences in the Moran's I statistic were observed during study time period (P < 0.05), indicating spatial autocorrelation in the spatial distribution of MT-ZVL. Hotspot and spatial autocorrelation analysis revealed clustering of infection cases in the Shaanxi-Shanxi border areas and in east of Shanxi province, where transmission increased rapidly over the study duration, as well as in well know high transmission areas in the south of Gansu province and the north of the Sichuan province. It indicates resurgence of MT-ZVL transmission over the latter three years of the study. Spatial clustering of infection was observed in localized areas, as well as sporadic outbreaks of infection.

Cajanonic acid A regulates the ratio of Th17/Treg via inhibition of expression of IL-6 and TGF-ß in insulin-resistant HepG2 cells.

BACKGROUND: The objectives of the present study are to investigate whether cajanonic acid A (CAA) can reduce insulin resistance (IR) in HepG2 cells and to gain a preliminary understanding of the mechanisms underlying this effect. METHODS: Following induction of IR in HepG2 cells, we tested the regulatory effect of CAA on glucose consumption and evaluated hepatocyte production of IL-6, TGF-ß, and key molecules in the insulin transduction pathway. A transwell co-culturing system was used to assess the effect of CAA on IR in HepG2 cells during the differentiation of CD4+ T cells by calculating the ratio of (Th17)/regulatory T cell (Treg). We evaluated the effect of CAA on the expression of IL-17RC cells and HepG2 cell apoptosis by immunofluorescence and flow cytometry assay. RESULTS: CAA improved dexamethasone-induced reduction in glucose consumption in HepG2 cells, inhibited hepatocyte production of IL-6 and TGF-ß, increased the expression of IL-17RC cell, and increased cellular apoptosis in insulin-resistant HepG2 cells. When co-cultured with CD4+ T cells, insulin-resistant HepG2 cells induced a decrease in the ratio of Th17/Treg, but CAA dampened the effect. Application of IL-6 and TGF-ß, together with CAA, reversed the effect of CAA on insulin-resistant HepG2 cells. Overexpression of IL17R, however, counteracted the effect of IL-6 neutralizing antibody within the culture system. CONCLUSION: CAA can regulate the ratio of Th17/Treg by mediating the expression of IL-6 and TGF-ß in insulin-resistant HepG2 cells.

Role and mechanism of the Th17/Treg cell balance in the development and progression of insulin resistance.

The pathogenic mechanism of insulin resistance and associated diseases such as metabolic syndrome and diabetes remains unclear. Since inflammatory cytokines secreted by T cells play an important role in immune system homeostasis, we evaluated the role of interleukin-6 (IL-6) and the Th17/Treg balance in insulin sensitivity and the underlying mechanism in a rat model. After establishing an insulin-resistant rat model, the rats were injected with anti-mouse IL-6R receptor antibody (MR16-1) to block IL-6. Adipose tissue and blood samples were obtained for the analysis of cytokines, Th17 and Treg markers, and insulin sensitivity blood parameters, for comparisons with those of the normal control group, IL-6-blocked control group, and insulin resistance control group. In the insulin resistance control group, the expression levels of IL-6, RORγt, and IL-17 increased, whereas those of IL-10, FoxP3, and CD4+CD25+Treg decreased. Insulin sensitivity decreased, whereas glucose, total serum cholesterol, triglycerides, and free fatty acid levels significantly increased. However, the completely opposite effects for all parameters were detected in the insulin resistance IL-6-blocked group. Insulin resistance can cause inflammation and an imbalance in Th17 cells/Treg cells. IL-6 can restore this imbalance and play an important role in the development and progression of insulin resistance.

A framework for assessing local transmission risk of imported malaria cases.

BACKGROUND: A key issue in achieving and sustaining malaria elimination is the need to prevent local transmission arising from imported cases of malaria. The likelihood of this occurring depends on a range of local factors, and these can be used to allocate resources to contain transmission. Therefore, a risk assessment and management strategy is required to identify risk indexes for malaria transmission when imported cases occur. These risks also need to be quantified and combined to give a weighted risk index score. This can then be used to allocate the resources to each administrative region to prevent transmission according to the degree of risk. METHODS: A list of potential risk indexes were generated from a literature review, expert consultation and panel discussion. These were initially classified into 4 first-level indexes including infection source, transmitting conditions, population vulnerability and control capacity. Each of these was then expanded into more detailed second-level indexes. The Delphi method was then used to obtain expert opinion to review and revise these risk indexes over two consecutive rounds to quantify agreement among experts as to their level of importance. Risk indexes were included in the final Transmission Risk Framework if they achieved a weighted importance score ≥ 4. The Analytic Hierarchy Process was then used to calculate the weight allocated to each of the final risk indexes. This was then used to create an assessment framework that can be used to evaluate local transmission risk in different areas. RESULTS: Two rounds of Delphi consultation were conducted. Twenty-three experts were used at each round with 100% recovery rate of participant questionnaires. The coordination coefficients (W) for the two rounds of Delphi consultation were 0.341 and 0.423, respectively (P < 0.05). Three first-level indexes and 13 second-level indexes were identified. The Analytic Hierarchy Process was performed to calculate the weight of the indexes. For the first-level indexes, infection source, transmitting conditions, and control capacity, the index weight was 0.5396, 0.2970 and 0.1634 respectively. For the three top second-level indexes, number of imported malaria cases, Anopheles species, and awareness of timely medical visit of patient, the index weight was 0.3382, 0.2475, and 0.1509 respectively. CONCLUSIONS: An indexed system of transmission risk assessment for imported malaria was established using the Delphi method and the Analytic Hierarchy Process. This was assessed to be an objective and practical tool for assessing transmission risk from imported cases of malaria into China.

[A retrospective analysis on the diagnosis and reporting of imported malaria in Jiangxi Province during 2012-2015].

Objective: To provide scientific basis for malaria surveillance in the elimination phase by retrospectively analyzing the diagnosis and reporting of imported malaria in Jiangxi Province. Methods: Data on malaria endemic situation and individual cases during 2012-2015 were collected through the National Information Management System for Infectious Diseases and the Report and Information Management System for Parasitic Diseases Control and Prevention. Detailed information on primary medical units, laboratory testing units, reporting units, diagnostic methods, time from onset to first medical visit, time from first medical visit to reporting, and time from onset to reporting was analyzed with the descriptive analysis method. Results: A total of 207 malaria cases were reported during 2012-2015 in Jiangxi, all were imported cases and 96.62%(200/207) were diagnosed with laboratory tests. The main primary medical units were found to be county-level (29.95%, 62/207) and prefecture-level (25.60%, 53/207) medical institutions, while the main laboratory testing units were prefecture-level medical institutions(35.27%,73/207) and county-level CDCs (20.29%, 42/207). There was a significant difference in the proportion of different laboratory testing units among the years(P < 0.05). The median time from onset to first medical visit was 1 d (0-149 d), from first medical visit to reporting was 3 d (0-144 d), and from onset to reporting was 5 d (0-149 d). Conclusions: The first visit and the laboratory testing of malaria cases mainly occur in the prefecture-level and county-level medical institutions.

Association of TLR4 and Treg in Helicobacter pylori Colonization and Inflammation in Mice.

The host immune response plays an important role in the pathogenesis of Helicobacter pylori infection. The aim of this study was to clarify the immune pathogenic mechanism of Helicobacter pylori infection via TLR signaling and gastric mucosal Treg cells in mice. To discover the underlying mechanism, we selectively blocked the TLR signaling pathway and subpopulations of regulatory T cells in the gastric mucosa of mice, and examined the consequences on H. pylori infection and inflammatory response as measured by MyD88, NF-κB p65, and Foxp3 protein expression levels and the levels of Th1, Th17 and Th2 cytokines in the gastric mucosa. We determined that blocking TLR4 signaling in H. pylori infected mice decreased the numbers of Th1 and Th17 Treg cells compared to controls (P < 0.001-0.05), depressed the immune response as measured by inflammatory grade (P < 0.05), and enhanced H. pylori colonization (P < 0.05). In contrast, blocking CD25 had the opposite effects, wherein the Th1 and Th17 cell numbers were increased (P < 0.001-0.05), immune response was enhanced (P < 0.05), and H. pylori colonization was inhibited (P < 0.05) compared to the non-blocked group. In both blocked groups, the Th2 cytokine IL-4 remained unchanged, although IL-10 in the CD25 blocked group was significantly decreased (P < 0.05). Furthermore, MyD88, NF-κB p65, and Foxp3 in the non-blocked group were significantly lower than those in the TLR4 blocked group (P < 0.05), but significantly higher than those of the CD25 blocked group (P < 0.05). Together, these results suggest that there might be an interaction between TLR signaling and Treg cells that is important for limiting H. pylori colonization and suppressing the inflammatory response of infected mice.

[Research Progress on Risk Assessment of Secondary Transmission of Imported Malaria].

In 2015, WHO issued the Global Technical Strategy for Malaria 2016-2030, which sets the target of reducing global malaria incidence and mortality rates by at least 90% by 2030. Although many countries have successfully achieved malaria elimination, they are facing the risk of imported malaria. In China, despite the acceleration of malaria elimination, imported malaria has become a potential threat to achieving complete malaria elimination. This paper reviews the worldwide research progress on risk assessment of secondary transmission of imported malaria, in the aim of providing reference for risk assessment of imported malaria and preventing secondary transmission in China.