BackgroundMalaria remains a public health concern in Hubei Province despite the significant decrease in malaria incidence over the past decades. Furthermore, history reveals that malaria transmission is unstable and prone to local outbreaks in Hubei Province. Thus, understanding spatial, temporal, and spatiotemporal distribution of malaria is needed for the effective control and elimination of this disease in Hubei Province.MethodsAnnual malaria incidence at the county level was calculated using the malaria cases reported from 2004 to 2011 in Hubei Province. Geographical information system (GIS) and spatial scan statistic method were used to identify spatial clusters of malaria cases at the county level. Pure retrospective temporal analysis scanning was performed to detect the temporal clusters of malaria cases with high rates using the discrete Poisson model. The space-time cluster was detected with high rates through the retrospective space-time analysis scanning using the discrete Poisson model.ResultsThe overall malaria incidence decreased to a low level from 2004 to 2011. The purely spatial cluster of malaria cases from 2004 to 2011 showed that the disease was not randomly distributed in the study area. A total of 11 high-risk counties were determined through Local Moran’s I analysis from 2004 to 2011. The method of spatial scan statistics identified different 11 significant spatial clusters between 2004 and 2011. The space-time clustering analysis determined that the most likely cluster included 13 counties, and the time frame was from April 2004 to November 2007.ConclusionsThe GIS application and scan statistical technique can provide means to detect spatial, temporal, and spatiotemporal distribution of malaria, as well as to identify malaria high-risk areas. This study could be helpful in prioritizing resource assignment in high-risk areas for future malaria control and elimination.

The study aimed to reveal the risk factors and predict the prevalence of human cystic echinococcosis (CE) in Western China. To do this, we analyzed county-wide data relating to the prevalence of human CE in seven provinces of Western China, along with associated human, natural geographical environmental data. We then used spatial analysis and multiple regression analysis to investigate the correlation between the prevalence of human CE and associated environmental factors and to create a risk map of the disease in the seven provinces. Our analysis showed that grassland area ratio and Tibetan population ratio were independent variables positively correlated with the prevalence of human CE and that gross domestic product (GDP) and land surface temperature (LST; Spring) were negative independent variables. We also created a predictive risk map of human CE that revealed that the high-risk areas were mainly located in the south of Qinghai, the Northwest of Sichuan and most of the Tibet Autonomous Region. Knowledge of the spatial distribution and risk factors associated with human CE could help to prevent and control echinococcosis in China.

With the development of cloud computing technology, the microservice architecture (MSA) has become a prevailing application architecture in cloud-native applications. Many user-oriented services are supported by many microservices, and the dependencies between services are more complicated than those of a traditional monolithic architecture application. In such a situation, if an anomalous change happens in the performance metric of a microservice, it will cause other related services to be downgraded or even to fail, which would probably cause large losses to dependent businesses. Therefore, in the operation and maintenance job of cloud applications, it is critical to mine the causality of the problem and find its root cause as soon as possible. In this paper, we propose an approach for mining causality and diagnosing the root cause that uses knowledge graph technology and a causal search algorithm. We verified the proposed method on a classic cloud-native application and found that the method is effective. After applying our method on most of the services of a cloud-native application, both precision and recall were over 80%.

This study aims to identify the landscape ecological determinants related to Oncomelania hupensis distribution, map the potential high risk of O. hupensis habitats at the microscale, and assess the effects of two environmental control strategies. Sampling was performed on 242 snail sites and 726 non-snail sites throughout Qianjiang City, Hubei Province, China. An integrated approach of landscape pattern analysis coupled with multiple logistic regression modeling was applied to investigate the effects of environmental factors on snail habitats. The risk probability of snail habitats positively correlated with patch fractal dimension (FD), paddy farm land proportion, and wetness index but inversely correlated with categorized normalized difference vegetation index (NDVI) and elevation. These findings indicate that FD can identify irregular features (e.g., irrigation ditches) in plain regions and that a moderate NDVI increases the microscale risk probability. Basing on the observed determinants, we predicted a map showing high-risk areas of snail habitats and simulated the effects of conduit hardening and paddy farming land rotation to dry farming land. The two approaches were confirmed effective for snail control. These findings provide an empirical basis for health professionals in local schistosomiasis control stations to identify priority areas and promising environmental control strategies for snail control and prevention.

Background. Fluoxetine (FLU) is the first-line and widely used medication for depression; however, FLU treatment is almost ineffective in 30%-40% of patients with depression. In addition, there are some problems in FLU treatment, such as delayed efficacy, large side effects, and poor tolerance. Chaihu Shugan San (CSS) is a classic and effective antidepressant Chinese herbal medicine that has been used in China for thousands of years. CSS or coadministration of CSS and FLU has become one of the most recommended methods in the treatment of depression in China. However, the specific pathways of CSS and coadministration of CSS and FLU for antidepressant are still unclear. Objective. This study was designed to evaluate the antidepressant effects of CSS and coadministration of CSS and FLU. Methods. The chronic unpredictable mild stress (CUMS) rat model was used to simulate depression. 120 healthy adult male Sprague-Dawley (SD) rats were randomly divided into seven groups: the control group, CUMS group, low-dose CSS group, high-dose CSS group, FLU group, coadministration of low-dose CSS and FLU group, and coadministration of high-dose CSS and FLU group. The rats in different groups were given different interventions. Then, the depression-like behavior and cognitive function were evaluated by the sucrose preference test (SPT), forced swimming test (FST), open field test (OFT), and Y-maze test. What is more, the antidepressant mechanism of CSS and coadministration of CSS and FLU were studied through BDNF mRNA, ERK mRNA, CREB mRNA, BDNF, p-ERK/ERK, and p-CREB/CREB levels in the hippocampus and frontal cortex by Western blot and RT-PCR. Results. Compared with the CUMS group, CSS and coadministration of CSS and FLU could alleviate the depressive symptoms and improve cognitive function in CUMS rats (p<0.05); CSS and coadministration of CSS and FLU could increase the expression of BDNF, p-CREB/CREB, p-ERK/ERK, and BDNF mRNA, CREB mRNA, and ERK mRNA in the hippocampus and frontal cortex (p<0.05). Besides, the high-dose CSS combined with the fluoxetine group was significantly better than the fluoxetine group and CSS group (p<0.05). Discussion and Conclusion. Finally, we found that both CSS and coadministration of CSS and FLU play an antidepressant role, which may be due to the regulation of the BDNF/ERK/CREB signaling pathway in the hippocampus and frontal cortex. Among them, the coadministration of CSS and FLU can enhance the antidepressant effect of CSS or FLU alone, and the underlying mechanism needs further investigation.

IntroductionMore than 80% of schistosomiasis patients in China live in the lake and marshland regions. The purpose of our study is to assess the effect of a comprehensive strategy to control transmission of Schistosoma japonicum in marshland regions.Methodology/Principal FindingsIn a cluster randomized controlled trial, we implemented an integrated control strategy in twelve villages from 2009 through 2011 in Gong'an County, Hubei Province. The routine interventions included praziquantel chemotherapy and controlling snails, and were implemented in all villages. New interventions, mainly consisting of building fences to limit the grazing area for bovines, building safe pastures for grazing, improving the residents' health conditions and facilities, were only implemented in six intervention villages. Results showed that the rate of S. japonicum infection in humans, bovines, snails, cow dung and mice in the intervention group decreased from 3.41% in 2008 to 0.81% in 2011, 3.3% to none, 11 of 6,219 to none, 3.9% to none and 31.7% to 1.7%, respectively (P<0.001 for all comparisons). In contrast, there were no statistically significant reductions of S. japonicum infection in humans, bovines and snails from 2008 to 2011 in the control group (P>0.05 for all comparisons). Moreover, a generalized linear model showed that there was a higher infection risk in humans in the control group than in the intervention group (OR = 1.250, P = 0.001) and an overall significant downward trend in infection risk during the study period.Conclusions/SignificanceThe integrated control strategy, designed to reduce the role of bovines and humans as sources of S. japonicum infection, was highly effective in controlling the transmission of S. japonicum in marshland regions in China.Trial RegistrationChinese Clinical Trial Registry ChiCTR-PRC-12002405.

No abstract

No abstract