The rapid development of artificial intelligence poses a huge impact on health and has become a core driving force for the new generation of the scientific and technological revolution in the field of healthcare. Recently, artificial intelligence has been gradually applied in the field of parasitic diseases and parasitology, including disease diagnosis, prognosis prediction, prediction of transmission risk, intelligent identification of vectors and intermediate hosts, and disease prevention and control, which facilitates the progress towards elimination of parasitic diseases. In addition, artificial intelligence provides highly efficient tools and approaches for healthcare workers and researchers. This comment mainly reviews the application of artificial intelligence in the fields of parasitic diseases and parasitology.

Objective　To construct a visual intelligent recognition model for Oncomelania hupensis robertsoni in Yunnan Province based on the EfficientNet⁃B4 model, and to evaluate the impact of data augmentation methods and model hyperparameters on the recognition of O. hupensis robertsoni. Methods　A total of 400 O. hupensis robertsoni and 400 Tricula snails were collected from Yongsheng County, Yunnan Province in June 2024, and snail images were captured following identification and classification of 300 O. hupensis robertsoni and 300 Tricula snails. A total of 925 O. hupensis robertsoni images and 1 062 Tricula snail images were collected as a dataset and divided into a training set and validation set in a ratio of 8∶2, while 352 images captured from the other 100 O. hupensis robertsoni and 354 images from 100 Tricula snails served as an external test set. All acquired images were subjected to preprocessing, including cropping and resizing. Three data augmentation approaches were employed, including baseline, Mixup and Gaussian blurring, and model hyperparameters included two optimization algorithms of adaptive moment estimation (Adam) and stochastic gradient descent (SGD), two loss functions of focal loss and cross entropy loss, and two learning rate decay strategies of cosine annealing and multi⁃step. The intelligent recognition models of O. hupensis robertsoni and Tricula snails were constructed based on the EfficientNet⁃B4 model, and 7 training strategy groups were generated by combinations of different data augmentation approaches and hyperparameters. The performance of intelligent recognition models was tested with external test sets, and evaluated with accuracy, precision, recall, F1 score, loss, Youden's index, and the area under the receiver operating characteristic curve (AUC) under different training strategies. Results　The variation of loss values was comparable among intelligent recognition models with different data augmentation approaches. The Group 4 model constructed with Mixup and Gaussian blurring data augmentation approaches showed the optimal performance, with an accuracy of 90.38%, precision of 90.07%, F1 score of 89.44%, Youden's index of 0.81 and AUC values of 0.961 in the external test set. The accuracy of models using the SGD optimizer reduced by 29.16% as compared to those using the Adam optimizer ([χ2] = 81.325, P < 0.001), and the accuracy of models using the cross entropy loss function reduced by 0.80% as compared to the Group 4 model ([χ2] = 3.147, P > 0.05), while the accuracy of models using the multi⁃step learning rate decay strategy increased by 0.65% as compared to the Group 4 model ([χ2] = 0.208, P > 0.05). In addition, the model with the baseline + Mixup + Gaussian blurring data augmentation approach and hyperparameters of Adam optimizer, focal loss function and multi⁃step learning rate decay strategy showed the highest performance, with an accuracy of 91.03%, precision of 91.97%, recall of 88.11%, F1 score of 90.00%, Youden's index of 0.82 and AUC values of 0.969 in external test set, respectively. Conclusions　The intelligent recognition model of O. hupensis robertsoni based on EfficientNet⁃B4 model is accurate for identification of O. hupensis robertsoni and Tricula snails in Yunnan Province.

Objective　To predict the potential geographic distribution of Oncomelania hupensis  in Yunnan Province using random forest (RF) and maximum entropy (MaxEnt) models, so as to provide insights into O. hupensis surveillance and control in Yunnan Province.  Methods　The O. hupensis snail survey data in Yunnan Province from 2015 to 2016 were collected and converted into O. hupensis snail distribution site data. Data of 22 environmental variables in Yunnan Province were collected, including twelve climate variables (annual potential evapotranspiration, annual mean ground surface temperature, annual precipitation, annual mean air pressure, annual mean relative humidity, annual sunshine duration, annual mean air temperature, annual mean wind speed, ≥ 0 ℃ annual accumulated temperature, ≥ 10 ℃ annual accumulated temperature, aridity and index of moisture), eight geographical variables (normalized difference vegetation index, landform type, land use type, altitude, soil type, soil texture⁃clay content, soil texture⁃sand content and soil texture⁃silt content) and two population and economic variables (gross domestic product and population).  Variables were screened with Pearson correlation test and variance inflation factor (VIF) test. The RF and MaxEnt models and the ensemble model were created using the biomod2 package of the software R 4.2.1, and the potential distribution of O. hupensis snails after 2016 was predicted in Yunnan Province. The predictive effects of models were evaluated through cross⁃validation and independent tests, and the area under the receiver operating characteristic curve (AUC), true skill statistics (TSS) and Kappa statistics were used for model evaluation. In addition, the importance of environmental variables was analyzed, the contribution of environmental variables output by the models with AUC values of > 0.95 and TSS values of > 0.85 were selected for normalization processing, and the importance percentage of environmental variables was obtained to analyze the importance of environmental variables. Results　Data of 148 O. hupensis snail distribution sites and 15 environmental variables were included in training sets of RF and MaxEnt models, and both RF and MaxEnt models had high predictive performance, with both mean AUC values of > 0.9 and all mean TSS values and Kappa values of > 0.8, and significant differences in the AUC (t = 19.862, P < 0.05), TSS (t = 10.140, P < 0.05) and Kappa values (t = 10.237, P < 0.05) between two models. The AUC, TSS and Kappa values of the ensemble model were 0.996, 0.954 and 0.920, respectively. Independent data verification showed that the AUC, TSS and Kappa values of the RF model and the ensemble model were all 1, which still showed high performance in unknown data modeling, and the MaxEnt model showed poor performance, with TSS and Kappa values of 0 for 24% (24/100) of the modeling results. The modeling results of 79 RF models, 38 MaxEnt models and their ensemble models with AUC values of > 0.95 and TSS values of > 0.85 were included in the evaluation of importance of environmental variables. The importance of annual sunshine duration (SSD) was 32.989%, 37.847% and 46.315% in the RF model, the MaxEnt model and their ensemble model, while the importance of annual mean relative humidity (RHU) was 30.947%, 15.921% and 28.121%, respectively. Important environment variables were concentrated in modeling results of the RF model, dispersed in modeling results of the MaxEnt model, and most concentrated in modeling results of the ensemble model. The potential distribution of O. hupensis snails after 2016 was predicted to be relatively concentrated in Yunnan Province by the RF model and relatively large by the MaxEnt model, and the distribution of O. hupensis snails predicted by the ensemble model was mostly the joint distribution of O. hupensis snails predicted by RF and MaxEnt models.  Conclusions 　Both RF and MaxEnt models are effective to predict the potential distribution of O. hupensis snails in Yunnan Province, which facilitates targeted O. hupensis snail control. 

Objective　To predict the areas of Oncomelania hupensis snail spread in Anhui Province from 1977 to 2023 using machine learning models, and to compare the effectiveness of different machine learning models for prediction of areas of O. hupensis snail spread, so as to provide insights into investigating the trends in areas of O. hupensis snail spread. Methods　Data pertaining to O. hupensis snail spread in Anhui Province from 1977 to 2023 were collected and a database was created. Five machine learning models were created using the software Matlab R2019b, including support vector regression (SVR), nonlinear autoregressive (NAR) neural network, back propagation (BP) neural network, gated recurrent unit (GRU) neural network and long short⁃term memory (LSTM) neural network models, and the model fitting effect was evaluated with mean absolute error (MAE), root mean squared error (RMSE) and coefficient of determination (R2). Following model training, the areas of O. hupensis snail spread were predicted in Anhui Province from 2024 to 2030. Results　The cumulative areas of O. hupensis snail spread were 40 241.32 hm2 in Anhui Province from 1977 to 2023, and the area of O. hupensis snail spread varied greatly among years, with a periodic peak every 4 to 6 years. The fitting curves of SVR, NAR neural network, BP neural network, GRU neural network and LSTM neural network models were increasingly closer to the real curves for areas of O. hupensis snail spread in Anhui Province. The trends in areas of O. hupensis snail spread in Anhui Province from 2024 to 2030 appeared approximately "M"⁃shaped curves by SVR and NAR neural network models, approximately "W"⁃shaped curves by BP and GRU neural network models, and a unimodal conical curve by the LSTM neural network model. The LSTM neural network model had the best effect for predicting areas of O. hupensis snail spread in Anhui Province, with the RMSE of 1 277 480, MAE of 797 422 and R2 of 0.978 9, respectively. Conclusions　Among the five models, The LSTM neural network model has a high efficiency for predicting areas of O. hupensis snail spread in Anhui Province, which may serve as a tool to investigate the trends in areas of O. hupensis snail spread. 

Objective　To investigate the Oncomelania hupensis snails spread and its spatio⁃temporal clustering characteristics in Suzhou City, Jiangsu Province, so as to provide insights into precision control of O. hupensis snails in the City. Methods O. hupensis snail surveillance data in Suzhou City from 2016 to 2023 were collected, and the areas of O. hupensis snail spread and areas of emerging and re⁃emerging snail habitats were retrieved. The spatial distribution characteristics and clustering types and locations of environments with O. hupensis snail spread were investigated using global and local spatial autocorrelation analyses with the software ArcGIS 10.7, and the clustering and cluster areas of O. hupensis snail spread were identified in Suzhou City using spatio⁃temporal scans with the software SaTScan 10.0.2.  Results　O. hupensis snail spread covered an area of 677 171 m2 in Suzhou City from 2016 to 2023, including 376 230 m2 emerging snail habitats and 300 941 m2 re⁃emerging snail habitats. Global spatial autocorrelation analysis showed overall clustering of O. hupensis snail spread in Suzhou City from 2016 to 2023 (Moran's I = 0.066, P = 0.007), and there were spatial clustering of areas with O. hupensis snail spread in 2019 (Moran's I = 0.086, P = 0.001) and 2021 (Moran's I = 0.045, P = 0.003). Local spatial autocorrelation analysis showed clusters of O. hupensis snail spread in Suzhou City from 2016 to 2023, with high⁃high clusters in Guangfu Township and Dongzhu Street, and the high⁃high clusters of O. hupensis snail spread were mainly distributed in southwestern Suzhou City. Spatio⁃temporal scans identified two clusters of areas with O. hupensis snail spread and areas of re⁃emerging snail habitats in Suzhou City from 2016 to 2023, with large clustering areas found in Guangfu Township, Dongzhu Street, Tong'an Township and Wangting Township [relative risk (RR) = 22.34, log likelihood ratio (LLR) = 163 295.32, P < 0.001] and small clustering areas in Xukou Township, Mudu Township and Xiangshan Street (RR = 2.73, LLR = 921.92, P < 0.001). Conclusions　There was spatial clustering of O. hupensis snail spread in Suzhou City from 2016 to 2023. Improved quality of O. hupensis snail control and intensified management of environments at a high risk of O. hupensis snail spread are recommended in Suzhou City. 

Objective　To investigate the epidemiological characteristics and spatial distribution characteristics of Clonorchis sinensis human infections in Guangdong Province from 2016 to 2022, so as to provide insights into formulation of the clonorchiasis control measures in the province.  Methods  Xinhui District of Jiangmen City, Longmen County of Huizhou City and Wengyuan County of Shaoguan City in Guangdong Province were selected as fixed surveillance sites for human clonorchiasis from 2016 to 2022, and additional 10% to 15% counties (districts) endemic for clonorchiasis were sampled from Guangdong Province as mobile surveillance sites each year from 2016 to 2022. A village (community) was randomly selected from each surveillance site according to the geographical orientations of east, west, south, north and middle, and subjects were randomly sampled from each village (community). C. sinensis eggs were detected in subjects' stool samples using the Kato⁃Katz technique, and the prevalence and intensity of C. sinensis infections were calculated. In addition, subjects' gender, age, ethnicity, educational level and occupation were collected. The Guangdong Provincial 1∶1 million electronic map in vector format was downloaded from the National Geomatics Center of China, and kernel density analysis and spatial autocorrelation analysis of C. sinensis human infections in Guangdong Province from 2016 to 2022 were performed using the software ArcGIS 10.7.  Results　A total of 153 188 residents were tested for C. sinensis infections in Guangdong Province from 2016 to 2022, including 75 596 men (49.35%) and 77 592 women (50.65%), and there were 5 369 residents infected with C. sinensis, with 3.50% overall prevalence of infections. The prevalence rates of severe, moderate and mild C. sinensis infections were 0.76%, 7.26% and 91.97% among C. sinensis⁃infected residents in Guangdong Province from 2016 to 2022, and there were age⁃, gender⁃, ethnicity⁃, occupation⁃ and educational level⁃specific prevalence of C. sinensis human infections ([χ2] = 2 578.31, 637.33, 52.22, 2 893.28 and 1 139.33, all P values < 0.05). Global spatial autocorrelation analysis showed a cluster in the prevalence of C. sinensis human infections in Guangdong Province (Moran's I = 0.63, Z = 27.31，P < 0.05). Kernel density analysis showed that the prevalence of C. sinensis human infections with a high kernel density in Guangdong Province was mainly distributed along the Zhujiang River basin in Pearl River Delta areas, followed by in eastern and northern Guangdong Province. In addition, local spatial autocorrelation analysis identified 73 high⁃high clusters of the prevalence of C. sinensis human infections in Guangdong Province. Conclusions　The prevalence of C. sinensis human infections was high in Guangdong Province from 2016 to 2022, and mild infection was predominant among all clonorchiasis cases, with spatial clusters identified in the prevalence of C. sinensis human infections. Targeted clonorchiasis control measures are required among high⁃risk populations and areas. 

Objective　To investigate the fluctuations in the population density of Aedes albopictus and changes in the population density of Ae. albopictus in different geographical areas and different breeding habitats in Guangdong Province from 2018 to 2023, so as to provide insights into prevention and control of mosquito⁃borne infectious diseases in the province. Methods　Ae. albopictus surveillance sites were assigned in 1 609 townships (streets) from 121 districts (counties) of 21 cities in Guangdong Province during the period between March and November from 2018 to 2023. The surveillance of the population density of Ae. albopictus was performed once a month in each surveillance site, and once a month in specific settings in cities where dengue were highly prevalent in Guangdong Province from December to February of the next year during the period from 2018 through 2023. Four streets (villages) were selected in each surveillance site according to the geographic orientation, and mosquito ovitraps were assigned in gardens, rooftops or public green belts at residential areas, parks, hospitals and construction sites. All mosquito ovitraps were collected, and the mosquito ovitrap index (MOI) was calculated. The population density of Ae. albopictus was classified into four grades in each surveillance site according to MOI, including no risk, low risk, medium risk and high risk. The risk classification of the Ae. albopictus density was analyzed in each surveillance site each year from 2018 to 2023, and the population density of Ae. albopictus was analyzed at different months and in different geographical areas and breeding habitats.  Results　A total of 118 241 Ae. albopictus surveillance sites were assigned in 21 cities of Guangdong Province from 2018 to 2023, and there were 68.26% of the surveillance sites with the population density of Ae. albopictus that met the requirements for dengue prevention and control, among which low, medium and high risk surveillance sites accounted for 23.61%, 6.67% and 1.47%. The risk classification of the Ae. albopictus density increased rapidly in Guangdong Province since April to May each year from 2018 to 2023, and then gradually reduced since September to October, with the peak during the period between May and July. The mean MOI was 4.21 at each surveillance site in Guangdong Province during the period from 2018 to 2023, with 4.69, 4.80, 4.38, 3.82, 3.38, and 4.33 from 2018 to 2023, respectively. The MOI was 4.35, 4.43, 3.53 and 3.58 in the Pearl River Delta region, and eastern, western, and northern Guangdong Province, respectively, and was 4.18, 5.44, 4.75, 3.24, 4.27 and 3.70 in residential areas, parks, construction sites, hospitals, waste collection stations, and other breeding habitats, respectively. Conclusions　The population density of adult Ae. albopictus peaked in Guangdong Province during the period between May and July from 2018 to 2023, with a high density of Ae. albopictus in the Pearl River Delta region and eastern Guangdong Province. Targeted Ae. albopictus control measures are recommended to be implemented prior to the peak of the Ae. albopictus population density to reduce the development of mosquito⁃borne infectious diseases.

Objective　To investigate the incidence of anemia and evaluate the immune status among newly reported HIV/AIDS patients in Jiangsu Province in 2021, and to identify the risk factors of anemia among patients living with HIV infections. Methods　Newly reported HIV/AIDS patients in Jiangsu Province from January 1 to December 31, 2021 that were registered in China's National AIDS Comprehensive Control Information Management System were enrolled. Subjects' fresh whole blood samples were collected, and hemoglobin levels, CD4 and CD8 cell counts and HIV viral loads were measured. Anemia was defined according to hemoglobin levels, and the immunological parameters and HIV viral loads were compared between HIV⁃infected patients with and without anemia. The risk factors of anemia were identified among individuals living with HIV infections using univariate analysis and multivariate logistic regression analysis. In addition, subjects' CD4 cell counts one year following antiretroviral therapy (ART) were retrieved from China's National AIDS Comprehensive Control Information Management System, and compared between subjects with and without anemia.  Results　A total of 635 newly diagnosed HIV/AIDS patients were reported in Jiangsu Province in 2021, including 544 males (85.67%) and 91 females (14.33%), and with ages of 15 to 83 years, and the overall incidence of anemia was 5.51% (35/635) among the study subjects. Men, individuals at ages of 45 years and lower and workers had relatively higher hemoglobin levels, with median hemoglobin levels of 156 (interquartile range, 22), 154 (interquartile range, 23) g/L and 162 (interquartile range, 19) g/L, respectively. The median baseline HIV viral load was 40 500.00 (interquartile range, 119 735.00) copies/mL among HIV⁃infected individuals with anemia and 29 754.00 (69 183.00) copies/mL among those without anemia (Z = -0.91, P = 0.31), and the median baseline CD4 and CD8 cell counts were significantly lower among HIV⁃infected individuals with anemia [166 (interquartile range, 143) cells/μL and 755 (653) cells/μL] than those without anemia [308 (253) cells/μL and 892 (638) cells/μL] (Z = -4.36 and -2.37, both P values < 0.05). The median CD4 cell counts remained lower among HIV⁃infected individuals with anemia than those without anemia [296 (interquartile range, 229) cells/μL vs. 457 (interquartile range, 313) cells/μL; Z = -3.71, P < 0.05] one year following ART, and the proportions of moderate and severe immunosuppression were significantly higher among HIV⁃infected individuals with anemia (40.00% and 17.14%) than those without anemia (21.00% and 9.33%) ([χ2]  = 10.37 and 8.79, both P values < 0.01). Univariate analysis showed a higher detection rate of anemia among female HIV⁃infected individuals than among males [odds ratio (OR) = 4.528, 95% confidence interval (CI): (3.811, 5.245), P < 0.001], a higher rate among HIV⁃infected individuals at ages of 45 to < 60 years [OR = 3.415, 95% CI: (1.191, 9.788), P = 0.022] and 60 years and older [OR = 5.820, 95% CI: (2.013, 16.826), P < 0.001] than among those at ages of 15 to < 30 years, a higher rate among HIV⁃infected individuals through heterosexual transmission than among those through homogeneous transmission [OR = 3.015, 95% CI: (1.423, 6.387), P = 0.004], a lower rate among HIV⁃infected individuals with an educational level of college and above than among those with an educational level of primary school [OR = 0.103, 95% CI: (0.028, 0.386), P < 0.001], a higher rate among HIV⁃infected individuals with baseline CD4 cell counts of < 200 cells/μL than among those with baseline CD4 cell counts of 200 cells/μL and higher [OR = 4.340, 95% CI: (2.165, 8.702), P < 0.001], and lower detection rates among HIV⁃infected individuals with CD4/CD8 cell ratios of 0.208 to < 0.326 [OR = 0.232, 95% CI: (0.076, 0.711), P = 0.011] and 0.516 and higher [OR = 0.292, 95% CI: (0.104, 0.818), P = 0.019] than among those with CD4/CD8 cell ratios of < 0.208. Multivariate logistic regression analysis identified woman [OR = 4.945, 95% CI: (3.944, 5.946), P = 0.002], and CD4 cell counts of < 200 cells/μL [OR = 3.597, 95% CI: (1.448, 8.937), P = 0.006] as risk factors of anemia among newly reported HIV/AIDS patients.  Conclusions　The incidence of anemia was low among newly reported HIV/AIDS patients in Jiangsu Province in 2021, and the immune status was poorer among HIV⁃infected individuals with anemia than those without anemia at baseline and one year following ART. Female and CD4 cell counts of < 200 cells/μL are risk factors of anemia among individuals living with HIV infections, and intensified surveillance, follow⁃up and precision interventions are recommended targeting female HIV⁃infected individuals and HIV⁃infected individuals with low CD4 cell counts.

Objective　To investigate the physiological characteristics of Bacillus thuringiensis subspecies israelensis (Bti) with double mutations of cwlE and sigK genes and to assess the activity of Bti against larvae of Culex pipiens pallens under different external factors, so as to provide the theoretical evidence for the use of engineered bacteria of Bti for effective mosquito control.  Methods　B. thuringiensis wild⁃type strain Bt⁃59 and Bt⁃59 strain with cwlE mutation [Bt⁃59 (ΔcwlE)] were cultured in nutrient broth media for 24 hours, and Bt⁃59 strains with sigK mutation [Bt⁃59 (ΔsigK)] and double mutations of cwlE and sigK [Bt⁃59 (ΔcwlE⁃sigK)] were cultured in nutrient broth media for 48 hours. Then, 5 μL of culture media were transferred to glass sides, and cell morphology and mother cell lysis were observed under an optical microscope. The optical densities of Bti strain culture media were measured at different time points of culture, and the growth curves of Bt⁃59, Bt⁃59 (ΔcwlE), Bt⁃59 (ΔsigK), and Bt⁃59 (ΔcwlE⁃sigK) strains were plotted. The differences in carbon source metabolism of four Bti strains were analyzed using the Biolog microplate culture method, and the metabolic activity of these strains was estimated with average well color development (AWCD). The fermentation media of these four Bti strains were diluted into final concentrations of 2.000, 1.000, 0.500, 0.250, and 0.125 μL/L, and the median lethal concentrations (LC50 values) of these four strains against the third instar larvae of Cx. pipiens pallens were determined. In addition, the fermentation media of Bti strains were processed as follows: pH adjusted to 5, 7 and 9; treated at 30, 40 ℃ and 50 ℃ for 12 hours; and exposed to irradiation with ultraviolet lights for 0 hour and 6 hours. Then, 20 third instar larvae of Cx. pipiens pallens were exposed to the above processed fermentation media at a final concentration of 1 μL/L in 200 mL of water at 26 ℃ for 24 hours, and the mosquito mortality was estimated to evaluate the effects of pH, temperature and ultraviolet irradiation on the larvicidal activity of four Bti strains.  Results　The growth curves of the Bt⁃59 strain and its mutants shared a similar changing trend, and both experienced a stable phase 6 hours post⁃culture. Both spores and crystal proteins were found in Bt⁃59 and Bt⁃59 (ΔcwlE) cells, and only crystal proteins were found in Bt⁃59 (ΔsigK) and Bt⁃59 (ΔcwlE⁃sigK) cells. No lysis was found in the cell wall of the Bt⁃59 (ΔcwlE⁃sigK) strain, and the crystal protein was embedded in the mother cell. Biolog microplate culture assay showed that the AWCD values of four Bti strains showed a similar changing trend over time, and 33 carbon sources were found to be metabolized by all of the four strains, including dextrin, D⁃maltose and D⁃trehalose. The LC50 values of the fermentation media of Bt⁃59, Bt⁃59 (ΔcwlE), Bt⁃59 (ΔsigK), and Bt⁃59 (ΔcwlE⁃sigK) strains were 0.60, 0.51, 0.70 μL/L and 0.72 μL/L against Cx. pipiens pallens, respectively. The adjusted mortality of larval Cx. pipiens pallens reduced by 76.60%, 76.00%, 66.67%, and 0 following exposure to the fermentation media of Bt⁃59, Bt⁃59 (ΔcwlE), Bt⁃59 (ΔsigK), and Bt⁃59 (ΔcwlE⁃sigK) strains at a pH of 5 relative to at a pH of 7, and the adjusted mortality reduced by 49.02%, 51.06%, 36.36%, and 4.44% following 6⁃hour exposure to ultraviolet irradiation relative to 0⁃hour exposure, while the adjusted mortality was 68.33% to 83.33% following treatment with the fermentation media of four Bti strains at different temperatures.  Conclusions　Bt⁃59 (ΔcwlE⁃sigK) strains  do not generate spores, and the absence of cwlE and sigK does not affect the growth, carbon source metabolism, and larvicidal activity of Bti strains against larval Cx. pipiens pallens. Cell wall embedding of Bt⁃59 (ΔcwlE⁃sigK) strains may protect larvicidal crystal proteins of Bti strains from external environmental factors, including ultraviolet irradiation, and pH alteration.

Objective　To investigate the distribution of Oncomelania hupensis snails in different water systems in Anqing City from 2016 to 2022, so as to provide insights into snail control in the city.  Methods　Snail survey data and distribution of water systems in snail⁃infested environments were collected from schistosomiasis⁃endemic areas of Anqing City from 2016 to 2022. The vector maps of towns and water systems in Anqing City were downloaded from National Geomatics Center of China. The GPS toolbox APP version 2.7.9 was downloaded from a smartphone to record the longitude and latitude of each snail⁃infested environment in Anqing City, which were loaded into the software LocaSpace Viewer version 4.4.6 to map the distribution of snail⁃infested environments. The area of snail habitats, area of emerging snail habitats, area of re⁃emerging snail habitats, type of snail habitats and density of living snails were descriptively analyzed. The spatial database of snail⁃infested environments in Anqing City was built with the software ArcGIS version 10.8, and the density of living snails was subjected to spatial autocorrelation analysis in snail⁃infested environments. The hotspot clusters of density of living snails were identified in snail⁃infested environments and the density of living snails was subjected to standard deviation ellipse analysis in snail⁃infested environments. Results　A total of 515 snail⁃infested environments were identified in water systems in Anqing City in 2022. The area of snail habitats reduced from 6 909.32 hm2 in 2016 to 6 087.48 hm2 in 2022, with a reduction of 11.89%, and the areas of snail habitats reduced by 2.39%, 21.71% and 1.67% in the main stream of the Yangtze River, the Wanhe River system and the Caizihu River system in Anhui City, respectively, while the area of snail habitats increased by 3.94% in the Huayang River system. Emerging or re⁃emerging snail habitats were identified in Anqing City each year during the period from 2016 to 2018 and from 2020 to 2020. The density of living snails appeared a tendency towards a decline in the Wanhe River system (b = -0.030, t = -3.019, P < 0.05) and Huayang River system (b = -0.029, t = -4.296, P < 0.05) in Anqing City from 2016 to 2022, and fluctuated in the main stream of the Yangtze River (b = 0.028, t = 1.019, P > 0.05) and the Caizihu River system (b = 0.020, t = 1.877, P > 0.05). A positive global spatial autocorrelation was identified in the density of living snails in Anqing City each year from 2016 to 2022 (all Moran's I values > 0, all P values < 0.05), and the hotspot clusters of density of living snails in snail⁃infested environments were mainly distributed in the Wanhe River system (Shankou Township, Hongpu Township, Yueshan Township and Wanghe Townshpi), the main stream system of the Yangtze River (Dalongshan Township, Wanhe Farm, Haikou Township and Huayang Township), the Huayang River system (Dashi Township and Xuqiao Township) and the Caizihu River system (Xiushan Township and Fangang Township). The ratio of the long to short axes of the standard deviation ellipse was 1.72 to 2.06 for the density of living snails in snail⁃infested environments in Anqing City from 2016 to 2022, and snails were mainly distributed in the southwest to northeast, and appeared the east⁃west and north⁃south spread. Conclusions　The areas of snail habitats and the density of living snails appeared a tendency towards a decline in different water systems in Anqing City from 2016 to 2022; however, there is still a risk of snail spread. Reinforced surveillance and precision control of snails are required in Anqing City.

Objective　To investigate the prevalence and molecular characteristics of Anaplasma infections in sheep and goats in Anhui Province, so as to provide insights into ovine anaplasmosis prevention and control. Methods　A total of 355 fresh blood samples were collected from 7 sheep and goat farms in Linquan County of Fuyang City, Lixin County of Bozhou City, Yu'an District of Lu'an City, Wangjiang County of Anqing City, Nanling County of Wuhu City, and Tianchang City and Fengyang County of Chuzhou City in Anhui Province from June to December 2020. A. bovis and A. phagocytophilum 16S ribosomal RNA (16S rRNA) gene, A. ovis major surface protein 4 (MSP4) gene and A. capra citric acid synthase (gltA) gene were amplified using PCR assay in all blood samples, and the prevalence of A. bovis, A. phagocytophilum, A. ovis and A. capra infections was calculated in sheep and goats. In addition, the positive amplification products were sequenced and subjected to genetic evolutionary analysis. Results　     The overall prevalence of Anaplasma infections was 17.5% (62/355) in sheep and goats in Anhui Province, and the prevalence of A. bovis, A. phagocytophilum, A. ovis and A. capra infections was 2.8% (10/355), 2.5% (9/355), 2.5% (9/355), and 7.0% (25/355), while the prevalence of A. bovis and A. phagocytophilum, A. phagocytophilum and A. ovis, A. phagocytophilum and A. capra and A. bovis, A. phagocytophilum and A. ovis co⁃infections was 0.8% (3/355), 1.1% (4/355), 0.3% (1/355) and 0.3% (1/355), respectively. No Anaplasma was detected in the sheep and goat farms in Fengyang County, while at least three Anaplasma species were detected in other sheep and goat farms, with co⁃infections of multiple Anaplasma species identified. The prevalence of Anaplasma infections was 14.7% (24/163) in goats and 19.8% (38/192) in sheep, and the prevalence of Anaplasma infections was 31.0% (31/100) in goats and sheep under 6 months of age, and 12.2% (31/255) in goats and sheep at ages of 6 months and older, respectively. A. bovis, A. phagocytophilum, A. ovis and A. capra were identified in sheep and goats of different breeds and ages. Conclusions　Multiple Anaplasma species infections are commonly prevalent in goats and sheep in Anhui Province, notably A. phagocytophilum, A. ovis and A. capra, which have zoonotic risks. Improved surveillance and prevention and control of Anaplasma infections are required in sheep and goats in Anhui Province.

Objective　To investigate the health education needs and available resources in schistosomiasis⁃endemic areas based on integration of community resources, and to explore the operation pathways for health education and promotion during the stage of schistosomiasis elimination. Methods　A community was selected from Nanji Township, Xinjian District, Nanchang City, Jiangxi Province around the Poyang Lake areas as the study site, and a questionnaire survey on health education needs for schistosomiasis control was conducted among permanent residents at ages of 20 years in the community during the period between June and July, 2022 using face⁃to⁃face interviews. In addition, the resources available for the community⁃based schistosomiasis control health education were investigated among workers in township⁃level specialized institutions, members of civil society organizations, villagers, teachers and high and primary school students through field observations, field surveys and thematic interviews. Results　A total of 304 individuals participated in the questionnaire survey on community⁃based health education needs for schistosomiasis control, and 94.41% (287/304) and 93.42% (284/304) of the respondents were most interested in knowing/understanding knowledge of the morphology of schistosomes and knowledge associated with the transmission route of schistosomiasis. The four most popular patterns for disseminating schistosomiasis control knowledge included live broadcasting of schistosomiasis control videos (94.41%, 287/304), printed brochures (89.80%, 273/304), special lectures by doctors (62.50%, 190/304) and physical health education materials for schistosomiasis control (61.51%, 187/304). There were 96.71% (294/304) and 77.63% (236/304) of respondents that accepted the participation of township healthcare center and township government/village committees in dissemination of schistosomiasis control knowledge, and there were 95.72% (291/304) and 80.59% (245/304) of respondents that mainly acquired schistosomiasis control knowledge through village allocation of leaflets and volunteer schistosomiasis control activities, respectively. There was 96.71% (294/304) of respondents participating in the dissemination activities of schistosomiasis control knowledge held by village committees, township healthcare centers, and high and primary schools/kindergartens, and 61.25% (177/289) of respondents were willing to participate in volunteer schistosomiasis control activities. A total of 115 individuals participated in the survey of available resources for community⁃based schistosomiasis control health education, and there were a large number of organizational, human and cultural resources in the community that were useful for health communication services. Conclusions　The abundant human and material resources from rural communities in schistosomiasis⁃endemic areas may be integrated into schistosomiasis control health education to generate a rural health education pathway with the joint participation of schistosomiasis control institutions, township governments, community departments and community residents, which may provide insights into the future development of schistosomiasis control health education.

Objective　To investigate the prevalence of parasitic infections in market⁃sold aquatic products in Shanghai Municipality, and to understand the knowledge and practice towards food⁃borne parasitic diseases among residents, so as to provide insights into the surveillance and control of food⁃borne parasitic diseases. Methods　Freshwater products, seawater products and pickled products were randomly obtained from agricultural trade markets, supermarkets, retail stores and restaurants in Huangpu, Putuo, Minhang and Qingpu districts of Shanghai Municipality from 2020 to 2023. Parasite metacercariae and larvae were detected in these aquatic products using pressing method, digestion method and the dissection method, and the detection of parasitic infection was compared in different types of aquatic products. In addition, the knowledge and practice towards food⁃borne parasitic diseases were investigated among residents aged 10⁃80 years old who randomly selected from agricultural trade markets, supermarkets, community streets and other population concentration areas in these four districts by questionnaire in 2023, and the awareness of food⁃borne parasitic diseases knowledge and percentage of healthy behaviors formation were analyzed. Results　A total of 2 109 aquatic products sampled from Huangpu, Putuo, Minhang and Qingpu districts of Shanghai Municipality from 2020 to 2023 were detected, and there were 317 products detected with parasitic infections, with an overall detection rate of 15.03%. There were 8 products detected with parasitic infections in 1 221 freshwater products, with a detection rate of 0.66%, and Clonorchis sinensis was the predominant parasite, which was detected in Pseudorasbora parva, Rhodeus amarus and Carassius auratus. There were 82 products detected with parasitic infections in 501 seawater products, with a detection rate of 16.37%, and Anisakis was the predominant parasite, which was detected in Trichiurus lepturus, Larimichthys polyactis, Pneumatophorus japonicus, Collchthys lucidus, Mugil cephalus, Larimichthys crocea, Scomberomorus niphonius, Stromateoides argenteus and Cololabis saira. There were 227 products detected with parasitic infections in 387 pickled products, with a detection rate of 58.66%, and the prevalence rates of Echinostoma metacercariae were 76.27% (225/295) in Bullacta exarata and 11.11% (2/18) in crab pastes, respectively ([χ2] = 159.511, P < 0.05). No Paragonimus infection was found in freshwater shrimps, crabs and pickled products, and no Diphyllobothrium latum larvae infection was detected in freshwater and seawater fish. Questionnaire surveys showed that the awareness of food⁃borne parasitic diseases knowledge was 79.00% (222/281), and the percentages of washing hands before and after meals, not drinking filtered water or tap water directly, not eating raw or semi⁃raw food, being willing to change special dietary preferences or bad living habits for health, and being willing to learn more about food⁃borne parasitic diseases knowledge were 99.64% (280/281), 72.24% (203/281), 56.23% (158/281), 96.80% (272/281) and 97.51%(274/281) among residents living in Huangpu, Putuo, Minhang and Qingpu districts, respectively. Conclusions　There are food⁃borne parasite contaminations in market⁃sold aquatic products in Shanghai Municipality. Although residents are aware of food⁃borne parasitic diseases knowledge, sustainable surveillance of food⁃borne parasitic diseases and improved health education are required to minimize the risk of human parasitic infections.

Objective　To investigate the prevalence of Cryptosporidium infection and the distribution of parasite species and genotypes among HIV⁃positive individuals in Jiangxi Province. Methods　HIV⁃positive individuals' sociodemographic and clinical data were collected from three AIDS designated hospitals in Jiangxi Province from January 2022 to March 2023. Subjects' stool samples were collected, and genomic DNA was extracted from stool samples. Nested PCR assay was performed based on the small subunit ribosomal RNA (SSU rRNA) gene of Cryptosporidium, and Cryptosporidium gp60 gene was amplified in stool samples positive for the SSU rRNA gene. The second⁃round PCR amplification product was checked with 1.5% agarose gel electrophoresis, and the products of suspected positive amplifications were sequenced, followed by sequence alignment. The phylogenetic tree was created using the Neighbor⁃Joining method with the software MEGA 11.0, to characterize the species, genotypes and sub⁃genotypes of Cryptosporidium.  Results　A total of 382 HIV⁃positive individuals were enrolled, with two cases identified with Cryptosporidium infection (0.52% prevalence), and both cases had no abdominal pain or diarrhea. Following sequencing and sequence alignment, the gene sequences of these two Cryptosporidium isolates shared 99.76% and 99.88% similarity with the gene sequence of C. meleagridis isolates. Phylogenetic analysis based on the Cryptosporidium SSU rRNA gene sequence identified the species of these two Cryptosporidium⁃positive stool samples as C. meleagridis. Following nested PCR amplification of the Cryptosporidium gp60 gene, sequencing and sequence alignment, the two C. meleagridis isolates were characterized as ⅢeA17G2R1 and ⅢbA25G1R1a sub⁃genotypes, and the sub⁃genotype ⅢbA25G1R1a was firstly described in humans. Conclusion　The prevalence of Cryptosporidium is low among HIV⁃positive individuals in Jiangxi Province. The likelihood of Cryptosporidium infection cannot be neglected among HIV⁃positive individuals without diarrhea. 

Objective　To establish an artificial intelligence (AI)⁃assisted platform for detection of parasite eggs, and to evaluate its detection efficiency and accuracy, so as to provide technical supports for elimination of parasitic diseases.  Methods　A total of 1 003 slides of Enterobius vermicularis, horkworm, Trichuris trichiura, Clonorchis sinensis, Taenia, Ascaris lumbricoides, Schistosoma japonicum, Paragonimus westermani and Fasciolopsis buski eggs were collected, and converted into digital images with an automatated scanning microscope to create a dataset. Based on the Object Detection platform on the Baidu Easy DL model, an AI⁃assisted platform for detection of parasite eggs was created through procedures of uploading, labeling, training, evaluation and optimization. Then, 70% of the datasets were randomly selected for model training, and the precision, recall and average accuracy were calculated to evaluate the effectiveness of platform for recognition of parasite eggs. In addition, the platform was deployed on the computer and smart phone terminals for use. Results　An AI⁃assisted platform for detection of parasite eggs was successfully created. If the platform was deployed using the public cloud application programming interface (API), the average accuracy, precision and recall of the platform were 93.42%, 92.55% and 89.32% for recognition of parasite eggs. If the platform was deployed using the offline software development kit (SDK), the average accuracy, precision and recall of the platform were 92.97%, 94.78% and 87.63% for recognition of parasite eggs. In addition, the precision of the platform was 97.00% and 96.23% for identification of Taenia and C. sinensis eggs, respectively. Conclusions　The AI⁃assisted platform for detection of parasite eggs has been successfully created, which is high in the accuracy for recognition of parasite eggs and convenient in use. This platform may provide a powerful technical support for parasitic disease diagnosis. 

Scorpion venom is a highly complicated cocktail of bioactive components including mucoproteins, enzymes, lipids, bioactive peptides, and other organic or inorganic molecules. Scorpion venom antimicrobial peptides are a class of small⁃molecule bioactive peptides extracted from scorpion venoms, which have shown a variety of biological activities, including antiviral, antibacterial, antifungal and antitumor actions. This review describes the progress of researches on the antiparasitic activities of scorpion venoms and their antimicrobial peptides, so as to provide insights into the research and development of novel antiparasitic agents.

There are multiple bioactive substances in the mosquito saliva, most of which are allergic to humans. Previous studies have demonstrated that mosquito bites may induce allergic reactions mediated by B and T lymphocytes, resulting in a reduction in the quality of life and even death among patients. To date, 11 salivary allergens and 8 non⁃salivary allergens have been characterized in mosquitoes. Nevertheless, there is still lack of highly sensitive, highly specific and safe tools for diagnosis of mosquito bites⁃induced allergy, and the difficulty in obtaining natural mosquito salivary allergens results in failure in widespread applications of immunotherapy for mosquito bites⁃induced allergy. This review provides an overview of the allergic symptoms of mosquito bites and underlying mechanisms, and mosquito salivary allergens that have been characterized and registered in the systematic allergen nomenclature website.

The article presents the diagnosis and treatment of an imported case with severe Plasmodium falciparum malaria, and the effect of plasma exchange combined with continuous renal replacement therapy.  Severe P. falciparum malaria is characterized by complex clinical symptoms and multiple complications, and plasma exchange combined with continuous renal replacement therapy has a satisfactory therapeutic efficacy for severe P. falciparum malaria.