BackgroundSchistosomiasis is a snail-borne parasitic disease and is endemic in many tropical and subtropical countries. Biomphalaria straminea, an intermediate host for Schistosoma mansoni, is native to the southeastern part of South America and has established in other regions of South America, Central America and southern China during the last decades. S. mansoni is endemic in Africa, the Middle East, South America and the Caribbean. Knowledge of the potential global distribution of this snail is essential for risk assessment, monitoring, disease prevention and control.Methods and findingsA comprehensive database of cross-continental occurrence for B. straminea was compiled to construct ecological models. We used several approaches to investigate the distribution of B. straminea, including direct comparison of climatic conditions, principal component analysis and niche overlap analyses to detect niche shifts. We also investigated the impacts of bioclimatic and human factors, and then used the bioclimatic and footprint layers to predict the potential distribution of B. straminea at global scale. We detected niche shifts accompanying the invasions of B. straminea in the Americas and China. The introduced populations had enlarged its habitats to subtropical regions where annual mean temperature is relatively low. Annual mean temperature, isothermality and temperature seasonality were identified as most important climatic features for the occurrence of B. straminea. Additionally, human factors improved the model prediction (P<0.001). Our model showed that under current climate conditions the snail should mostly be confined to the tropic and subtropic regions, including South America, Central America, Sub-Saharan Africa and Southeast Asia.ConclusionsOur results confirmed that niche shifts took place in the invasions of B. straminea, in which bioclimatic and human factors played an important role. Our model predicted the global distribution of B. straminea based on habitat suitability, which would help for prioritizing monitoring and management efforts for B. straminea control in the context of ongoing climate change and human disturbances.

The rat lungworm Angiostrongylus cantonensis is a zoonotic nematode with a wide distribution. We report the first provincial survey of the prevalence of A. cantonensis infection among wild rodents and snails in Guangdong Province, China. A total of 2929 Pomacea canaliculata and 1354 Achatina fulica were collected from fields in 22 survey sites with a larval infection rates ranging from 0-26.6% to 0-45.4%. In addition, 114 Cipangopaludina sp and 252 Bellamya sp were bought from markets; larvae were found only in Bellamya snails from two survey sites with an infection rate of 1.4% (1 ⁄ 70) and 3.3% (3 ⁄ 91), respectively. Four hundred and ninety-one rodents were captured in nine sites (Rattus norvegicus, R. flavipectus, Suncus murinus, Mus musculus, Bandicota indica, R. losea and R. rattus). Adult worms were found in R. norvegicus, R. flavipectus and Bandicota indica. Our survey revealed a wide distribution of A. cantonensis and its intermediate hosts P. canaliculata and A. fulica in Guangdong. The prevalence of A. cantonensis in wild snails and rats poses a substantial risk for angiostrongyliasis in humans.

BackgroundBiomphalaria straminea is an invasive vector in China, posing a significant threat to public health. Understanding the factors affecting the establishment of this snail is crucial to improve our ability to manage its dispersal and potential risk of schistosomiasis transmission. This study sought to determine the spatial distribution of B. straminea in mainland China and whether environmental factors were divergent between places with and without B. straminea.MethodsA malacological survey of B. straminea was conducted in Guangdong Province, China. Snails were identified using anatomical keys. Water and sediment samples were taken, and their physicochemical properties were analyzed using national standard methods. Landscape and climatic variables were also collected for each site. We compared the environmental characteristics between sites with and without B. straminea using Mann-Whitney U test. We further used generalized linear mixed models to account for seasonal effects.ResultsB. straminea was found at six sites, including one in Dongguan and five in Shenzhen. Probability map found a hot spot of B. straminea distribution at Shenzhen and Hong Kong. Sites occupied by B. straminea were characterized by higher median altitude, mean annual precipitation and moderate temperature. Water with snails had higher median concentrations of total nitrogen, nitrate and nitrites, ammoniacal nitrogen, calcium, zinc and manganese but lower dissolved oxygen and magnesium. Sediments with snails had higher median copper, zinc and manganese. B. straminea was associated with maximum temperature of the warmest month (pMCMC < 0.001) and sediment zinc (pMCMC < 0.001).ConclusionsB. straminea is distributed in Shenzhen and its surrounding areas in Guangdong, China. Sites with and without B. straminea differed in the maximum temperature of the warmest month and sediment zinc. Surveillance should be continued to monitor the dispersal of this snail in China.Electronic supplementary materialThe online version of this article (10.1186/s40249-018-0492-6) contains supplementary material, which is available to authorized users.

ObjectiveTo assess the validity of pre- and posttreatment computed tomography (CT)-based radiomics signatures and delta radiomics signatures for predicting progression-free survival (PFS) in stage III-IV non-small-cell lung cancer (NSCLC) patients after immune checkpoint inhibitor (ICI) therapy.MethodsQuantitative image features of the largest primary lung tumours were extracted on CT-enhanced imaging at baseline (time point 0, TP0) and after the 2nd-3rd immunotherapy cycles (time point 1, TP1). The critical features were selected to construct TP0, TP1 and delta radiomics signatures for the risk stratification of patient survival after ICI treatment. In addition, a prediction model integrating the clinicopathologic risk characteristics and phenotypic signature was developed for the prediction of PFS.ResultsThe C-index of TP0, TP1 and delta radiomics models in the training and validation cohort were 0.64, 0.75, 0.80, and 0.61, 0.68, 0.78, respectively. The delta radiomics score exhibited good accuracy for distinguishing patients with slow and rapid progression to ICI treatment. The predictive accuracy of the combined prediction model was higher than that of the clinical prediction model in both training and validation sets (P&lt;0.05), with a C-index of 0.83 and 0.70, respectively. Additionally, the delta radiomics model (C-index of 0.86) had a higher predictive accuracy compared to PD-L1 expression (C-index of 0.50) (P&lt;0.0001).ConclusionsThe combined prediction model including clinicopathologic characteristics (tumour anatomical classification and brain metastasis) and the delta radiomics signature could achieve the individualized prediction of PFS in ICIs-treated NSCLC patients.