Objective To evaluate the performance of the artificial intelligence (AI)-enabled snail identification system for recognition of Oncomelania hupensis robertsoni and Tricula in schistosomiasis-endemic areas of Yunnan Province. Methods Fifty O. hupensis robertsoni and 50 Tricula samples were collected from Yongbei Township, Yongsheng County, Lijiang City, a schistosomiasis-endemic area in Yunnan Province in May 2024. A total of 100 snail sample images were captured with smartphones, including front-view images of 25 O. hupensis robertsoni and 25 Tricula samples (upward shell opening) and back-view images of 25 O. hupensis robertsoni and 25 Tricula samples (downward shell opening). Snail samples were identified as O. hupensis robertsoni or Tricula by schistosomiasis control experts with a deputy senior professional title and above according to image quality and morphological characteristics. A standard dataset for snail image classification was created, and served as a gold standard for recognition of snail samples. A total of 100 snail sample images were recognized with the AI-enabled intelligent snail identification system based on a WeChat mini program in smartphones. Schistosomiasis control professionals were randomly sampled from stations of schistosomisis prevention and control and centers for disease control and prevention in 18 schistosomiasis-endemic counties (districts, cities) of Yunnan Province, for artificial identification of 100 snail sample images. All professionals are assigned to two groups according the median years of snail survey experiences, and the effect of years of snail survey experiences on O. hupensis robertsoni sample image recognition was evaluated. A receiver operating characteristic (ROC) curve was plotted, and the sensitivity, specificity, accuracy, Youden’s index and the area under the curve (AUC) of the AI-enabled intelligent snail identification system and artificial identification were calculated for recognition of snail sample images. The snail sample image recognition results of AI-enabled intelligent snail identification system and artificial identification were compared with the gold standard, and the internal consistency of artificial identification results was evaluated with the Cronbach’s coefficient alpha. Results A total of 54 schistosomiasis control professionals were sampled for artificial identification of snail sample image recognition, with a response rate of 100% (54/54), and the accuracy, sensitivity, specificity, Youden’s index, and AUC of artificial identification were 90%, 86%, 94%, 0.80 and 0.90 for recognition of snail sample images, respectively. The overall Cronbach’s coefficient alpha of artificial identification was 0.768 for recognition of snail sample images, and the Cronbach’s coefficient alpha was 0.916 for recognition of O. hupensis robertsoni snail sample images and 0.925 for recognition of Tricula snail sample images. The overall accuracy of artificial identification was 90% for recognition of snail sample images, and there was no significant difference in the accuracy of artificial identification for recognition of O. hupensis robertsoni (86%) and Tricula snail sample images (94%) (χ² = 1.778, P > 0.05). There was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (88%) and downward shell openings (92%) (χ² = 0.444, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less (75%) and more than 6 years (90%) (χ² = 7.792, P < 0.05). The accuracy, sensitivity, specificity and AUC of the AI-enabled intelligent snail identification system were 88%, 100%, 76% and 0.88 for recognition of O. hupensis robertsoni snail sample images, and there was no significant difference in the accuracy of recognition of O. hupensis robertsoni snail sample images between the AI-enabled intelligent snail identification system and artificial identification (χ² = 0.204, P > 0.05). In addition, there was no significant difference in the accuracy of artificial identification for recognition of snail sample images with upward (90%) and downward shell openings (86%) (χ² = 0.379, P > 0.05), and there was a significant difference in the accuracy of artificial identification for recognition of snail sample images between schistosomiasis control professionals with snail survey experiences of 6 years and less and more than 6 years (χ² = 5.604, P_adjusted < 0.025). Conclusions The accuracy of recognition of snail sample images is comparable between the AI-enabled intelligent snail identification system and artificial identification by schistosomiasis control professionals, and the AI-enabled intelligent snail identification system is feasible for recognition of O. hupensis robertsoni and Tricula in Yunnan Province.

OBJECTIVE: In Pakistan, traditional medicines are an important component of the medical system, with numerous varieties and great demands. However, due to the scattered resources and the lack of systematic collection and collation, adulteration of traditional Pakistani medicine (TPM) is common, which severely affects the safety of their medicinal use and the import and export trades. Therefore, it is urgent to systematically organize and unify the management of TPM and establish a set of standards and operable methods for the identification of TPM. METHODS: We collected and organized the information on 128 TPMs with regard to their medicinal parts, efficacy, usage, and genetic material, based on Pakistan Hamdard Pharmacopoeia of Eastern Medicine: Pharmaceutical Codex. The genetic information of TPM is summarized from national center for biotechnology information (NCBI) and global pharmacopoeia genome database (GPGD). Furthermore, we utilized bioinformatics technology to supplement the chloroplast genome (cp-genome) data of 12 TPMs. To build the web server, we used the Linux + Apache + MySQL + PHP (LAMP) system and constructed the webpage on a PHP: Hypertext Preprocessor (PHP) model view controller (MVC) framework. RESULTS: We constructed a new genomic database, the traditional Pakistani medicine genomic database (TPMGD). This database comprises five entries, namely homepage, medicinal species, species identification, basic local alignment search tool (BLAST), and download. Currently, TPMGD contains basic profiles of 128 TPMs and genetic information of 102 TPMs, including 140 cytochrome c oxidase subunit I (COI) sequences and 119 mitochondrial genome sequences from Bombyx mori, 1 396 internal transcribed spacer 2 (ITS2) sequences and 1 074 intergenic region (psbA-trnH) sequences specific to 92 and 83 plant species, respectively. Additionally, TPMGD includes 199 cp-genome sequences of 82 TPMs. CONCLUSION TPMGD is a multifunctional database that integrates species description, functional information inquiry, genetic information storage, molecular identification of TPM, etc. The database not only provides convenience for TPM information queries but also establishes the scientific basis for the medication safety, species identification, and resource protection of TPM.

Objective To analyze chemical constituents of compound Maxing Shigan decoction by ultra-high perfor-mance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS). Methods The separation was performed on a UPLC BEH C₁₈ column (2.1 mm×100 mm, 2.5 µm)，with a gradient elution applying 0.1% aqueous formic acid solution and 0.1% formic acid acetonitrile as a mobile phase. The column temperature was 40 °C. The flow rate was 0.4 ml/min and the analysis time was 15 min. Mass spectrometry (MS) data were collected in both positive and negative ESI ion modes. Results Through UPLC-QTOF/MS analysis and reference validation, a total of 59 chemical components in Maxing Shigan decoction were identified. Conclusion An ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) method was established to identify the chemical components of Maxing Shigan decoction. This method is simple, efficient, sensitive and accurate, and provides a basis for the elucidation of the pharmacodynamic material basis and mechanism of Maxing Shigan decoction. It can provide data reference for the optimization of the compatibility of traditional Chinese medicine in the treatment of COVID-19.

OBJECTIVE To compare the efficacy and safety of chemotherapy combined with tislelizumab or sintilimab in patients with advanced non-small cell lung cancer （NSCLC）， and to analyze the influential factors of prognostic. METHODS A retrospective study was conducted on 163 patients with advanced NSCLC who received chemotherapy combined with tislelizumab or sintilimab at the First People’s Hospital of Yunnan Province from September 1， 2021 to November 30， 2024. Among them， there were 90 patients in the tislelizumab group and 73 patients in the sintilimab group. The objective response rate （ORR）， disease control rate （DCR）， progression free survival （PFS）， and overall survival （OS） of two groups were observed， and the occurrence of adverse drug reactions in patients was evaluated. Kaplan-Meier method was used to plot PFS and OS survival curves， Log-rank test was applied for univariate analysis， and Cox regression model was used to evaluate the independent prognostic factors of PFS and OS. RESULTS The median PFS of patients in the tislelizumab group and the sintilimab group were 14.14 months （95%CI of 10.95-17.33） and 10.95 months （95%CI of 8.75-13.15）， respectively. The median OS was 25.89 months （95%CI of 22.67-29.11） and 24.25 months （95%CI of 19.34-29.16）， with ORR of 45.56% and 49.32%， DCR of 94.44% and 90.41%， and the incidence of adverse drug reactions of 84.44% and 79.45%， respectively， the differences were not statistically significant （P＞0.05）. Age ≥60 years （HR＝1.542， 95%CI of 1.044-2.278， P＝0.029） and systemic immune inflammatory nutritional index （SIINI）＞ 116.58 （HR＝1.541， 95%CI of 1.058-2.245， P＝0.024） were risk factors for PFS in NSCLC patients receiving immune checkpoint inhibitor therapy； the use of antibiotics may affect the overall survival of patients （P＝0.001）. CONCLUSIONS The efficacy and safety of chemotherapy combined with tislelizumab or sintilimab for advanced NSCLC are comparable； age≥60 years and SIINI ＞116.58 are risk factors for PFS in NSCLC patients， and the use of antibiotics may affect the patients’ OS.

Schistosomiasis was once hyper-endemic in Yunnan Province. Following concerted efforts for over 70 years, remarkable achievements have been made for schistosomiasis control in the province. In 2004, the Mid- and Long-term Plan for Schistosomiasis Prevention and Control in Yunnan Province was initiated in Yunnan Province, and the target for transmission control of schistosomiasis was achieved in the province in 2009. Following the subsequent implementation of the Outline for Key Projects in Integrated Schistosomiasis Control Program (2009—2015) and the 13th Five - year Plan for Schistosomiasis Control in Yunnan Province, no acute schistosomiasis had been identified in Yunnan Province for successive 12 years, and no local Schistosoma japonicum infections had been detected in humans, animals or Oncomelania hupensis snails for successive 6 years in the province by the end of 2020. The transmission of schistosomiasis was interrupted in Yunnan Province in 2020. This review summarizes the history of schistosomiasis, changes in schistosomiasis prevalence and progress of schistosomiasis control in Yunnan Province, and proposes the future priorities for schistosomiasis control in the province.

Objective To investigate the knowledge, attitudes and practices (KAP) towards scrub typhus control and analyse the influencing factors among residents in Longling County, Yunnan Province in 2023, so as to provide insights into management of scrub typhus in the county. Methods Two townships were randomly sampled from Longling County, Baoshan City, Yunnan Province in July 2023, and 2 to 3 administrative villages were randomly selected from each township. Then, 20 to 40 households were randomly selected from each village, and 1 to 2 villagers were surveyed in each household. Residents’ KAP towards scrub typhus control was investigated, and factor affecting residents’ KAP towards scrub typhus control were identified with independent samples t test or analysis of variance (ANOVA) and multiple linear regression analysis. Results A total of 417 questionnaires were allocated, and 410 valid questionnaires were recovered, with an effective recovery rate of 98.32%. Of all respondents, 65.85% (270/410) heard of scrub typhus but were not familiar with it, and 12.68% (52/410) and 1.95% (8/410) were familiar and very familiar with it, respectively. Residents mainly acquired scrub typhus control knowledge via their relatives and friends. The knowledge, attitude, and behavior scores of the respondents with regard to scrub typhus were (34.14 ± 13.07), (55.04 ± 6.69), and (21.40 ± 5.61), respectively, and the total score for knowledge, belief, and behavior in relation to scrub typhus prevention and control was (110.57 ± 18.80). Univariate analysis revealed that age (F = 3.12, P < 0.05), education (F = 10.77, P < 0.05), occupation (F = 4.89, P < 0.05), frequency of outdoor activities (F = 3.61, P < 0.05), and type of place of residence (t = 1.33, P < 0.05) were the factors that influenced the participants’ scores for knowledge of the prevention and control of scrub typhus. Multiple linear regression analysis revealed that literacy level (β = 10.20 to 16.71, P < 0.05) and category of residence (β = −7.23, P < 0.05) were the factors that influenced residents’ current knowledge and trust behavior in relation to scrub typhus. Conclusions Place of residence and educational level are critical factors affecting scrub typhus control among residents in Longling County, Yunnan Province. Intensified health education pertaining to scrub typhus control and appropriate behavioral interventions are required among residents living in urban areas, with a low educational level and frequent outdoor activities.

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 textureclay 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 > 0.950 and TSS values of > 0.850 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 > 0.900 and all mean TSS values and Kappa values of > 0.800, 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 > 0.950 and TSS values of > 0.850 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.

To screen novel anti-dengue virus (DENV) NS5 RdRp enzyme inhibitors, a series of 5-cyano-2-thiacetoaryl pyrimidinone compounds were designed and synthesized by molecular hybridization method with HCV NS5B RdRp inhibitor 3jc and ZIKV NS5 RdRp inhibitor 4w as lead compounds. The anti-DENV activity of these compounds was evaluated by MTT assay and plaque assay and five compounds showed anti-DENV activity. The most active compound 7a'k showed better anti-DENV activity than that of the positive control ribavirin (EC₅₀ = 7.86 μmol·L^-1 vs EC₅₀ = 18.07 μmol·L^-1), and the other four compounds showed almost the same anti-DENV activity as ribavirin. Finally, the prediction and simulation of the binding mode through molecular provided new ideas for the further development of this new DENV NS5 RdRp inhibitor.

OBJECTIVES: To explore the cytotoxicity of four wild mushrooms involved in a case of Yunnan sudden unexplained death (YNSUD), to provide the experimental basis for prevention and treatment of YNSUD. METHODS: Four kinds of wild mushrooms that were eaten by family members in this YNSUD incident were collected and identified by expert identification and gene sequencing. Raw extracts from four wild mushrooms were extracted by ultrasonic extraction to intervene HEK293 cells, and the mushrooms with obvious cytotoxicity were screened by Cell Counting Kit-8 (CCK-8). The selected wild mushrooms were prepared into three kinds of extracts, which were raw, boiled, and boiled followed by enzymolysis. HEK293 cells were intervened with these three extracts at different concentrations. The cytotoxicity was detected by CCK-8 combined with lactate dehydrogenase (LDH) Assay Kit, and the morphological changes of HEK293 cells were observed under an inverted phase contrast microscope. RESULTS: Species identification indicated that the four wild mushrooms were Butyriboletus roseoflavus, Boletus edulis, Russula virescens and Amanita manginiana. Cytotoxicity was found only in Amanita manginiana. The raw extracts showed cytotoxicity at the mass concentration of 0.1 mg/mL, while the boiled extracts and the boiled followed by enzymolysis extracts showed obvious cytotoxicity at the mass concentration of 0.4 mg/mL and 0.7 mg/mL, respectively. In addition to the obvious decrease in the number of HEK293 cells, the number of synapses increased and the refraction of HEK293 cells was poor after the intervention of Amanita manginiana extracts. CONCLUSIONS The extracts of Amanita manginiana involved in this YNSUD case has obvious cytotoxicity, and some of its toxicity can be reduced by boiled and enzymolysis, but cannot be completely detoxicated. Therefore, the consumption of Amanita manginiana is potentially dangerous, and it may be one of the causes of the YNSUD.
Humans ; HEK293 Cells ; Sincalide ; China ; Amanita ; Death, Sudden

Objective: To establish a dynamic syndromic surveillance system in the border areas of Yunnan Province based on information technology, evaluate its effectiveness and timeliness in the response to common communicable disease epidemics and improve the communicable disease prevention and control in border areas. Methods: Three border counties were selected for full coverage as study areas, and dynamic surveillance for 14 symptoms and 6 syndromes were conducted in medical institutions, the daily collection of information about students' school absence in primary schools and febrile illness in inbound people at border ports were conducted in these counties from January 2016 to February 2018 to establish an early warning system based on mobile phone and computer platform for a field experimental study. Results: With syndromes of rash, influenza-like illness and the numbers of primary school absence, the most common communicable disease events, such as hand foot and mouth disease, influenza and chickenpox, can be identified 1-5 days in advance by using EARS-3C and Kulldorff time-space scanning models with high sensitivity and specificity. The system is easy to use with strong security and feasibility. All the information and the warning alerts are released in the form of interactive charts and visual maps, which can facilitate the timely response. Conclusions: This system is highly effective and easy to operate in the detection of possible outbreaks of common communicable diseases in border areas in real time, so the timely and effective intervention can be conducted to reduce the risk of local and cross-border communicable disease outbreaks. It has practical application value.
Humans ; Influenza, Human ; Sentinel Surveillance ; Syndrome ; China ; Cell Phone