Tropical diseases, the transmission of which is affected by multiple natural and social factors, pose a great challenge to global public health, notably in African countries. During the past several decades, China and African countries have continuously collaborated for the control of neglected tropical diseases and malaria, which has become an important part of global South-to-South cooperation and global health governance. This article reviews the history of China-Africa cooperation for tropical diseases control, summarizes the experiences and achievements over the past decade, analyzes the current challenges in the coopera tion, and proposes future recommendations. The China-Africa cooperation has achieved significant progress in the control of tropical diseases, such as malaria, schistosomiasis, and filariasis, and established a China-Africa cooperation network for tropical diseases control. Through the "Three-Step" strategy of China-Africa cooperation, the effectiveness of China's integrated control strategies has been validated in Africa, and the application of China's tropical disease control technologies has been promoted in African disease-epidemic countries. Currently, China-Africa collaboration, however, still experiences multiple realistic challenges, such as insufficient resources, difficulty in technology transfer, and weak primary healthcare systems. In the future, both sides are recommended to further strengthen policy coordination, deepen technological cooperation, innovate cooperation models, aiming to continuously promote the high-quality development of China-Africa cooperation for tropical diseases control.

As a neglected tropical disease, schistosomiasis remains a major public health challenge in underdeveloped areas, notably Africa. Currently, the national schistosomiasis control programmes in Africa mainly depend on foreign aids; however, conventional international aid models have multiple limitations. To enhance the effectiveness and sustainability of global schistosomiasis control programmes, this article proposes a trinity collaboration model based on international rules, China’s experiences and local needs, which is explained with China aid project of schistosomiasis control in Zanzibar as an example. Based on the successful experiences from the national schistosomiasis control programme in China, this model emphasizes the compliance with World Health Organization guidelines and fully considers local actual needs to promote the effectiveness and sustainability of the schistosomiasis control programme through integrating international resources and promoting China’s experience to meet local needs. The successful practice of the China aid project of schistosomiasis control in Zanzibar provides strong evidence that the model is of great theoretical significance and practical value to improve the efficiency of multilateral collaboration and promote global health governance.

Recently, there has been an increasing risk of importation of tropical diseases into China and the resultant re-transmission in the country with the in-depth implementation of the “Belt and Road” Initiative, which poses a serious threat to the national public health security. To effectively respond to the cross-border transmission risk of tropical diseases and facilitate the process towards tropical disease control and elimination in China and the countries along the “Belt and Road” Initiative, this article analyzes the current status and governance risks of major imported tropical diseases, cross-border joint prevention and control polices implemented for tropical diseases and challenges in the establishment of the joint prevention and control system for tropical diseases in China, and discusses the establishment and implementation path of the joint prevention and control system for tropical diseases in countries along the “Belt and Road” Initiative. This path covers the establishment of cross-border cooperation mechanisms, research and development and pilot production of Chinese public health products, and implementation of key cross-border tropical disease prevention and control projects. The establishment of this system will further improve Chinese prevention and control capabilities for key cross-border tropical diseases, build a demonstrative prevention and control model for tropical diseases, and promote international technical exchanges and cooperation of tropical diseases.

Objective To investigate the global burden of visceral leishmaniasis (VL) from 1990 to 2021 and predict the trends in the burden of VL from 2022 to 2035, so as to provide insights into global VL prevention and control. Methods The global age-standardized incidence, prevalence, mortality and disability-adjusted life years (DALYs) rates of VL and their 95% uncertainty intervals (UI) were captured from the Global Burden of Disease Study 2021 (GBD 2021) data resources. The trends in the global burden of VL were evaluated with average annual percent change (AAPC) and 95% confidence interval (CI) from 1990 to 2021, and gender-, age-, country-, geographical area- and socio-demographic index (SDI)-stratified burdens of VL were analyzed. The trends in the global burden of VL were projected with a Bayesian age-period-cohort (BAPC) model from 2022 to 2035, and the associations of age-standardized incidence, prevalence, mortality, and DALYs rates of VL with SDI levels were examined with a smoothing spline model. Results The global age-standardized incidence [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)], prevalence [AAPC = -0.06%, 95% CI: (-0.06%, -0.06%)], mortality [AAPC = -0.25%, 95% CI: (-0.25%, -0.24%)] and DALYs rates of VL [AAPC = -2.38%, 95% CI: (-2.44%, -2.33%)] all appeared a tendency towards a decline from 1990 to 2021, and the highest age-standardized incidence [2.55/10⁵, 95% UI: (1.49/10⁵, 4.07/10⁵)], prevalence [0.64/10⁵, 95% UI: (0.37/10⁵, 1.02/10⁵)], mortality [0.51/10⁵, 95% UI: (0, 1.80/10⁵)] and DALYs rates of VL [33.81/10⁵, 95% UI: (0.06/10⁵, 124.09/10⁵)] were seen in tropical Latin America in 2021. The global age-standardized incidence and prevalence of VL were both higher among men [0.57/10⁵, 95% UI: (0.45/10⁵, 0.72/10⁵); 0.14/10⁵, 95% UI: (0.11/10⁵, 0.18/10⁵)] than among women [0.27/10⁵, 95% UI: (0.21/10⁵, 0.33/10⁵); 0.06/10⁵, 95% UI: (0.05/10⁵, 0.08/10⁵)], and the highest mortality of VL was found among children under 5 years of age [0.24/10⁵, 95% UI: (0.08/10⁵, 0.66/10⁵)]. The age-standardized incidence (r = -0.483, P < 0.001), prevalence (r = -0.483, P < 0.001), mortality (r = -0.511, P < 0.001) and DALYs rates of VL (r = -0.514, P < 0.001) correlated negatively with SDI levels from 1990 to 2021. In addition, the global burden of VL was projected with the BAPC model to appear a tendency towards a decline from 2022 to 2035, and the age-standardized incidence, prevalence, mortality and DALYs rates were projected to be reduced to 0.11/10⁵, 0.03/10⁵, 0.02/10⁵ and 1.44/10⁵ in 2035, respectively. Conclusions Although the global burden of VL appeared an overall tendency towards a decline from 1990 to 2021, the burden of VL showed a tendency towards a rise in Central Asia and western sub-Saharan African areas. The age-standardized incidence and prevalence rates of VL were relatively higher among men, and the age-standardized mortality of VL was relatively higher among children under 5 years of age. The global burden of VL was projected to continue to decline from 2022 to 2035.

Objective To analyze the structural and phylogenetic characteristics of the mitochondrial genome from Bulinus globosus, so as to provide a theoretical basis for classification and identification of species within the Bulinus genus, and to provide insights into understanding of Bulinus-schistosomes interactions and the mechanisms of parasite transmission. Methods B. globosus samples were collected from the Ruya River basin in Zimbabwe. Mitochondrial DNA was extracted from B. globosus samples and the corresponding libraries were constructed for high-throughput sequencing on the Illumina NovaSeq 6000 platform. After raw sequencing data were subjected to quality control using the fastp software, genome assembly was performed using the A5-miseq and SPAdes tools, and genome annotation was conducted using the MITOS online server. Circular maps and sequence plots of the mitochondrial genome were generated using the CGView and OGDRAW software, and the protein conservation motifs and structures were analyzed using the TBtools software. Base composition and codon usage bias were analyzed and visualized using the software MEGA X and the ggplot2 package in the R software. In addition, a phylogenetic tree was created in the software MEGA X after sequence alignment with the software MAFFT 7, and visualized using the software iTOL. Results The mitochondrial genome of B. globosus was a 13 730 bp double-stranded circular molecule, containing 2 ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and 13 protein-coding genes, with a marked AT preference. The mitochondrial genome composition of B. globosus was similar to that of other species within the Bulinus genus. Phylogenetic analysis revealed that the complete mitochondrial genome sequence of B. globosus was clustered with B. truncatus, B. nasutus, and B. ugandae into the same evolutionary clade, and gene superfamily analysis showed that the metabolism-related proteins of B. globosus were highly conserved, notably the cytochrome c oxidase family, which showed a significant consistency. Conclusions This is the first whole mitochondrial genome sequencing to decode the compositional features of the mitochondrial genome of B. globosus from Zimbabwe and its evolutionary relationship within the Bulinus genus, which provides important insights for further understanding of the phylogeny and mitochondrial genome characteristics of the Bulinus genus.

OBJECTIVE: To propose a machine learning-based method for predicting the trajectories during manual acupuncture manipulation (MAM), aiming to improve the precision and consistency of acupuncture practitioner' operation and provide the real-time suggestions on MAM error correction. METHODS: Computer vision technology was used to analyze the hand micromotion when holding needle during acupuncture, and provide a three-dimensional coordinate description method of the index finger joints of the holding hand. Focusing on the 4 typical motions of MAM, a machine learning-based MAM trajectory predictive model was designed. By integrating the changes of phalangeal joint angle and hand skeletal information of acupuncture practitioner, the motion trajectory of the index finger joint was predicted accurately. Besides, the roles of machine learning-based MAM trajectory predictive model in the skill transmission of acupuncture manipulation were verified by stratified randomized controlled trial. RESULTS: The performance of MAM trajectory predictive model, based on the long short-term memory network (LSTM), obtained the highest stability and precision, up to 98%. The learning effect was improved when the model applied to the skill transmission of acupuncture manipulation. CONCLUSION The machine learning-based MAM predictive model provides acupuncture practitioner with precise action prediction and feedback. It is valuable and significant for the inheritance and error correction of manual operation of acupuncture.
Humans ; Acupuncture Therapy/instrumentation* ; Machine Learning ; Adult ; Male ; Female

Objective:To analyze the clinical application of different diagnostic methods for heart failure with preserved ejection fraction (HFpEF) in maintenance hemodialysis (MHD) patients.Methods:It was a single-center retrospective cohort study. Uremia patients who underwent hemodialysis at Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine from July 2020 to June 2021 were enrolled. The demographic characteristics, laboratory indicators, and echocardiography parameters were collected. The 2016 European Society of Cardiology (ESC) criteria, H 2FPEF score [composite score based on weighted scores of heavy (H), hypertensive (H), atrial fibrillation (F), pulmonary hypertension (P), elder (E), and filling pressure (F)], and Heart Failure Association (HFA) -PEFF score [including pre-test assessment (P), echocardiography and natriuretic peptide score (E), functional testing (F) and final aetiology (F)] were used to diagnose HFpEF, respectively, and the difference of three diagnostic methods was compared. The association between HFpEF diagnosed by the three methods and poor outcomes (all-cause death, cardiovascular death) was analyzed. Results:A total of 160 MHD patients were included, whose age was (58.5±13.4) years, median dialysis age was 5.0 (2.3, 9.6) years, median H 2FPEF score was 2 (1, 3), median HFA-PEFF score was 4 (3, 5), and 92 (57.5%) were males. Of these patients, 118 patients (73.8%) met the 2016 ESC criteria for diagnosis of HFpEF, 4 (2.5%) met H 2FPEF score for diagnosis of HFpEF, and 56 (35.0%) met HFA-PEFF score for diagnosis of HFpEF. The consistency of three methods in diagnosing HFpEF was poor with κ values of 0.018 between ESC criteria and H 2FPEF score, 0.322 between ESC criteria and HFA-PEFF score, and 0.056 between H 2FPEF score and HFA-PEFF score. After a median follow-up of 2.6 years, 20 (12.5%) of the 160 MHD patients died. The Kaplan-Meier survival analysis showed a significant difference in mortality between patients diagnosed with HFpEF and those without using the H 2FPEF score (Log-rank test, χ2=6.95, P=0.008). After adjusting for demographic and clinical parameters, multivariate Cox regression analysis showed that HFpEF diagnosed by HFA-PEFF score was associated with all-cause mortality ( HR=2.73, 95% CI 1.07-6.98, P=0.036) and cardiovascular mortality ( HR=4.77, 95% CI 1.31-17.30, P=0.018). Conclusions:The 2016 ESC criteria, H 2FPEF score, and HFA-PEFF score have high heterogeneity and poor consistency in diagnosing HFpEF in MHD patients. Among the three diagnostic methods, only the diagnosis based on HFA-PEFF score is associated with the prognosis of MHD patients. The HFA-PEFF score can be used to assess the risk of HFpEF in MHD patients, and more clinical studies are needed to further verify it in the future.

Objective To evaluate the molluscicidal effect of spraying different formulations of niclosamide ethanolamine salt with drones against Oncomelania hupensis in ditches. Methods A semi-dry and semi-wet ditch with O. hupensis snails was selected in the second branch field of Jiangbei Farm, Jiangling County, Hubei Province in May 2023, and divided into 4 experimental areas, named groups A1, A2, B1 and B2. Environmental cleaning was performed in groups A1 and B2, and was not conducted in groups A2 or B2. Then, 50% wettable powder of niclosamide ethanolamine salt was sprayed with drones at an effective dose of 2 g/m² in groups A1 and A2, and 5% niclosamide ethanolamine salt granule was sprayed with drones at an effective dose of 2 g/m² in groups B1 and B2. O. hupensis snails were surveyed using the systematic sampling method 1, 3, 5, 7, 14 days after spraying, and the natural mortality and corrected mortality of O. hupensis snails were calculated. Results The occurrence of frames with living snails, mean density of living snails and natural mortality of snails were 97.50% (117/120), 6.30 snails/0.1 m² and 1.18% (9/765) in the test ditch before spraying, respectively. There were significant differences in the mortality of snails among four groups 1, 3, 5, 7 and 14 days after spraying niclosamide formulations with drones (χ² = 17.230, 51.707, 65.184, 204.050 and 34.435, all P values < 0.01). The overall mortality rates of snails were 94.51% (1 051/1 112), 79.44% (908/1 143), 96.54% (977/1 012) and 88.55% (1 021/1 153) in groups A1, A2, B1 and B2 (χ² = 207.773, P < 0.05), respectively. In addition, there was no significant difference in the overall snail mortality between groups A1 and B1 (P > 0.05), and the snail mortality in groups A1 and B1 were both statistically different from that in groups A2 and B2 (all P values < 0.05). Conclusion Both 50% wettlable powder of niclosamide ethanolamine salt and 5% niclosamide ethanolamine salt granule sprayed with drones are active against O. hupensis snails in ditches, and environmental cleaning may improve the molluscicidal effect.

With the growth of the global economy , changes in climate and ecological environments, and increased mobility of humans and animals, the transmission risk of vector-borne tropical diseases continues to rise. To address this challenge, strengthening surveillance of vector-borne tropical diseases is urgent. This consensus brought together 29 renowned experts in related professional fields from 26 institutions in China, who, through analyzing the epidemic trend and hazard situation of vector-borne tropical diseases and summarizing the working experiences of experts, have firstly reached following consensus: the burden of vector-borne tropical diseases is heavy with great threats to human health; China has achieved remarkable results in prevention and control of vector-borne tropical diseases , but still needs to strengthen the surveillance and response actively. Secondly, a unanimous consensus has been reached on the aspects of surveillance definition, objectives, contents, and methods of vector-borne tropical diseases. Thirdly, detail requirements have been agreed including: strengthening the concept of early surveillance and forecast, standarding the function, evaluation steps, and construction requirements of surveillance system for vector-borne tropical diseases. Fourthly, key tasks were put forward that need to be investigated and strengthened in the future. This expert consensus provides a standardized reference for the construction of the surveillance pathway and surveillance system for vector-borne tropical diseases in China.

Objective To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. Methods Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People’s Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients’radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients’radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. Results The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = −5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. Conclusions The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.