Liang Shi’s research while affiliated with Jiangsu Institute of Parasitic Diseases and other places

Schistosomiasis is commonly managed using the praziquantel, but it is only effective against adult worms and duration of action is short. Liver fibrosis will worsen if eggs are still present after stopping treatment. Therefore, this study aimed to develop a sustained drug release system for effectively preventing and treating schistosomiasis. A disulfide bond-induced three-dimensional (3D) recombinant collagen hydrogel was developed for sustained praziquantel release. Three collagen sequences were developed based on the sequence for Scl2 of S. pyogene, with different substitutions of residues for cysteine (S-VCL-S1, S-VCL-S2, and S-VCL-S3). Their properties were tested. Mice were infected with Schistosoma japonicum cercariae and treated either with praziquantel collagen hydrogel or niclosamide collagen hydrogel. The worm-killing effect was examined. The application of hydrogel-niclosamide on the skin for 24 h effectively prevented Schistosome cercariae from infecting mice and showed 70.95% and 81.73% reduction in the number of eggs and worms, respectively. The combined use of niclosamide and anti-cercariae cream showed 100% protection after 24 h. The hydrogel-praziquantel also showed a 100% reduction of worms and eggs after 24 h of subcutaneous injection. The subcutaneous injection of praziquantel after 28 days of infection showed 95.19% and 80.12% reduction of worm and egg counts, respectively, and the development of larvae was significantly slowed down. Liver analysis showed no infection after 7 days of treatment. These results suggest developing a novel type of sustained-release agent against schistosomiasis based on the recombinant collagen hydrogel that provides a potential new treatment for schistosomiasis. IMPORTANCE This study introduces an new way for treating schistosomiasis: a special collagen hydrogel that gradually releases medication to treat schistosomiasis effectively. This innovation provides a promising way to treat schistosomiasis. It represents a significant step forward in the fight against this disease and offers hope for more effective and safer treatments in the future.

Background Schistosoma japonicum, the causative agent of schistosomiasis, heavily relies on its single intermediate host, the Oncomelania hupensis snail, for its life cycle. Controlling these snails effectively plays a pivotal role in curbing the transmission and prevalence of this disease. While prior research has extensively investigated the impact of environmental factors such as temperature and vegetation on snail survival, growth, and reproduction, the contribution of water physicochemical properties has been notably underexplored. This study presents laboratory experiments designed to comprehensively explore the influence of water physicochemical properties on snail survival, offering valuable insights into environmental factors for more precise predictions of snail distribution. Methods We meticulously conducted laboratory snail survival experiments using water from different sources (river water/tap water), and employed a statistical approach amalgamating principal component analysis with Cox regression to preliminarily investigate the effects of different water physicochemical properties on the survival of snails. Results Our analysis indicates that after a 6-month laboratory snail survival experiment, the survival rate in the tap water group was significantly higher than that in the river water group for infected snails (χ² = 7.74, p = 0.005), while the difference in survival rates for non-infected snails was not statistically significant (χ² = 0.61, p = 0.434). The Principal Component-Cox regression analysis revealed that in the infected snail group, total phosphorus, pH value, five-day biochemical oxygen demand, conductivity, and nitrite were protective factors for snail survival, while phosphate and total nitrogen were risk factors. In the non-infected snail group, total phosphorus, pH value, five-day biochemical oxygen demand, conductivity, and nitrite were protective factors for snail survival, and total nitrogen, ammonia nitrogen, phosphate, and nitrate were risk factors. Conclusions This study underscores the substantial impact of water quality’s physicochemical properties on snail survival. The effects of water quality on snails are complex, and maintaining an appropriate level of organic matter content and controlling the pH value at a weak alkalescency level prove beneficial for snail survival. These findings hold significant promise for advancing our understanding of snail-borne diseases and optimizing control strategies.

Vector‐borne diseases (VBDs) represent a critical global public health concern, with approximately 80% of the world's population at risk of one or more VBD. Manual disease vector identification is time‐consuming and expert‐dependent, hindering disease control efforts. Deep learning (DL), widely used in image, text, and audio tasks, offers automation potential for disease vector identification. This paper explores the substantial potential of combining DL with disease vector identification. Our aim is to comprehensively summarize the current status of DL in disease vector identification, covering data collection, data preprocessing, model construction, evaluation methods, and applications in identification spanning from species classification to object detection and breeding site identification. We also discuss the challenges and possible prospects for DL in disease vector identification for further research. © 2024 Society of Chemical Industry.

Background: As the unique intermediate host of Schistosoma japonicum, the geographical distribution of Oncomelania hupensis (O. hupensis) is an important index in the schistosomiasis surveillance system. This study comprehensively analyzed the pattern of snail distribution along the Yangtze River in Jiangsu Province and identified the dynamic determinants of the distribution of O. hupensis. Methods: Snail data from 2017 to 2021 in three cities (Nanjing, Zhenjiang, and Yangzhou) along the Yangtze River were obtained from the annual cross-sectional survey produced by the Jiangsu Institute of Parasitic Diseases. Spatial autocorrelation and hot-spot analysis were implemented to detect the spatio–temporal dynamics of O. hupensis distribution. Furthermore, 12 factors were used as independent variables to construct an ordinary least squares (OLS) model, a geographically weighted regression (GWR) model, and a geographically and temporally weighted regression (GTWR) model to identify the determinants of the distribution of O. hupensis. The adjusted coefficients of determination (adjusted R², AICc, RSS) were used to evaluate the performance of the models. Results: In general, the distribution of O. hupensis had significant spatial aggregation in the past five years, and the density of O. hupensis increased eastwards in the Jiangsu section of the lower reaches of the Yangtze River. Relatively speaking, the distribution of O. hupensis wase spatially clustered from 2017 to 2021, that is, it was found that the border between Yangzhou and Zhenjiang was the high density agglomeration area of O. hupensis snails. According to the GTWR model, the density of O. hupensis was related to the normalized difference vegetation index, wetness, dryness, land surface temperature, elevation, slope, and distance to nearest river, which had a good explanatory power for the snail data in Yangzhou City (adjusted R² = 0.7039, AICc = 29.10, RSS = 6.81). Conclusions: The distribution of O. hupensis and the environmental factors in the Jiangsu section of the lower reaches of the Yangtze River had significant spatial aggregation. In different areas, the determinants affecting the distribution of O. hupensis were different, which could provide a scientific basis for precise prevention and control of O. hupensis. A GTWR model was prepared and used to identify the dynamic determinants for the distribution of O. hupensis and contribute to the national programs of control of schistosomiasis and other snail-borne diseases.

Schistosomiasis is serious parasitic disease with an estimated global prevalence of active infections of more than 190 million. Accurate methods for the assessment of schistosomiasis risk are crucial for schistosomiasis prevention and control in China. Traditional approaches to the identification of epidemiological risk factors include pathogen biology, immunology, imaging, and molecular biology techniques. Identification of schistosomiasis risk has been revolutionized by the advent of computer network communication technologies, including 3S, mathematical modeling, big data, and artificial intelligence (AI). In this review, we analyze the development of traditional and new technologies for risk identification of schistosomiasis transmission in China. New technologies allow for the integration of environmental and socio-economic factors for accurate prediction of the risk population and regions. The combination of traditional and new techniques provides a foundation for the development of more effective approaches to accelerate the process of schistosomiasis elimination.

The information system is an important part in schistosomiasis control work. The rapid development of information technology for epidemic data has promoted the establishment of China’s schistosomiasis elimination monitoring system, and has accelerated the process of schistosomiasis elimination. The schistosomiasis information system has not been established at the national level in Zanzibar’s and information management capabilities are very weak. There is a lack of data that can fully and dynamically reflect the population’s disease and risk factors epidemic trends and their influencing factors. This situation cannot meet the goal of eliminating schistosomiasis. The China expert team assisted Zanzibar to build an African schistosomiasis control information system suitable for local epidemics, which improve data management application level and service capabilities of schistosomiasis control work.

A cross-sectional survey of schistosomiasis was carried out in Pemba Island, Zanzibar from 2017 to 2019. The overall infection rate was 1.84% (353/19,194, 95% CI: 1.65%–2.03%). A total of 73.53% of shehia (50/68) were found to be infected with schistosomiasis, and the highest infection rate reached 18.77%. The infection rate of children aged 6–18 was 2.76%. The student infection rate was 2.2%, higher than other occupations. The infection rate of primary school students is 2.41%. There were statistically significant differences in the infection rate among regions, age groups, occupations, and education levels. Snail habitats were mainly found in stream (79.22%). Positive snail habitats were mainly found in stream (51.43%). Control measures must be strengthened in high infection areas and groups. Snail monitoring and control should be intensified in the future.

This study concerns an integrated strategy of schistosomiasis control, focusing on the management and elimination of the main transmission cycles and reservoirs along Yangtze river, Jiangsu Province (China), instituted in 2004. Our analysis, including mapping, spatial autocorrelation and spatio-temporal scanning, was implemented between 2001 and 2013 to explore the changes in the distribution of Oncomelania hupensis , the intermediate host of Schistosoma japonicum . Two high-density snail locations in the upper and middle reaches of the river were observed along with one high-risk area due to infected snails in the upper reaches at the beginning of the study period. The number of high-density snail habitats declined sharply after 2004 and infected snails disappeared completely by 2010. Global spatial autocorrelation showed spatial clustering of snails in general, as well as of infected ones when snail densities were relatively high, while local spatial autocorrelation showed the number of specific clusters declining and switching spatially from the upper to the middle reaches of the Yangtze river in Jiangsu Province during the study period. The integrated snail control strategy was found to be effective, but the middle reaches of the river will require continued strong control resources.