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.

ObjectiveTo investigate the epidemiological and clinical characteristics of human bocavirus (HBoV) in hospitalized children with acute lower respiratory tract infection (ALRTI) at a single-center children’s hospital in Shanghai, thereby providing evidence for the diagnosis, treatment, and prevention of HBoV infection. MethodsA retrospective study was conducted on 19 537 hospitalized children with ALRTI at Shanghai Children’s Hospital from January 2021 to December 2023. Multiplex polymerase chain reaction (PCR) combined with capillary electrophoresis was used to detect HBoV and 12 other common respiratory viruses /atypical pathogens. The positive detection rate, demographic characteristics (sex, age), temporal distribution (year, season) of HBoV, as well as the clinical characteristics of severe and non-severe pneumonia were analyzed. ResultsThe overall HBoV-positive rate was 2.57% (503/19 537), with 59.44% (299/503) being single infections and 40.56% (204/503) being co-infections. The positive detection rate was significantly higher in boys than that in girls (2.78% vs 2.33%, χ²=3.88, P=0.049). The highest infection rate was observed in toddlers, followed by infants (χ²=379.57, P<0.001). The positive rate peaked in 2021 and reached its lowest point in 2023 (χ²=45.49, P<0.001), with epidemics mainly prevalent in summer and autumn. The main clinical symptoms were cough (90.06%, 453/503), fever (75.94%, 382/503), and wheezing (39.96%, 201/503). Children with severe pneumonia showed a higher incidence of wheezing compared with the non-severe group (P<0.001), while underlying diseases and co-infections had no significant association with disease severity (P>0.05). ConclusionHBoV was an important pathogen of ALRTI in children, predominantly affecting infants and toddlers, with higher susceptibility in boys and seasonal peaks in autumn and summer. The main clinical manifestations included cough, fever, and wheezing, with wheezing being more prevalent in children with severe pneumonia.

Objective To investigate the epidemiological characteristics, influencing factors, and community dietary network drivers of clonorchiasis in Longjiang Village, Congjiang County, Guizhou Province using social network analysis from a One Health perspective, so as to provide insights into implementation of precision control measures. Methods Longjiang Village, Congjiang County, Guizhou Province was selected as a survey point. A total of 128 permanent residents at ages of over 6 years were sampled using a random sampling method, and subjects’ stool samples were collected. In addition, at least 10 fecal samples were collected from domestic cats and dogs, reservoir hosts of Clonorchis sinensis, and at least 80 freshwater snails and at least 200 freshwater fish, intermediate hosts of C. sinensis, were sampled in Longjiang Village. C. sinensis eggs were detected in human, domestic cat and domestic dog fecal samples using a modified Kato-Katz thick smear method (two slides for one stool sample) . The C. sinensis metacercariae were detected in freshwater fish with a compression method and the C. sinensis cercariae were detected in freshwater snails with a cercarial shedding method, respectively. Participants’ demographic characteristics, dietary and drinking hygiene behaviors and food-sharing relationships were collected with structured questionnaires and semi-structured in-depth interviews, and factors affecting C. sinensis infection were identified using regression analysis. Based on the north-south orientation delineated by the village river, participants were divided into groups a and b. Subjects’ food-sharing network was analyzed using social network analysis, and the Louvain algorithm was employed to investigate the community structure and key nodes of the network. Results The overall prevalence of C. sinensis infection was 33.59% (43/128) among participants in Longjiang Village, Congjiang County, Guizhou Province. The detection of C. sinensis metacercariae was 7.63% (22/288) in freshwater fish, and no C. sinensis cercariae were detected in freshwater snails. The prevalence of C. sinensis infection was 7.69% (1/13) in domestic cats, and no infection was detected in domestic dogs. Regression analysis identified age groups of 25 to 45 years [adjusted odds ratio (AOR) = 23.17, 95% confidence interval (CI): (1.85, 490.29)], Dong ethnicity [AOR = 26.80, 95% CI: (1.54, 1 105.09)], frequent consumption of raw water [AOR = 9.39, 95% CI: (1.58, 99.79)], and consumption of raw fish [AOR = 3.49, 95% CI: (1.52, 34.69)] as independent risk factors for C. sinensis infection among villagers in Longjiang Village (all P values < 0.05). Social network analysis showed a significantly higher global clustering coefficient (0.52 vs. 0.16; t = 2.41, P = 0.02) and average local clustering coefficient (0.52 vs. 0.16; t = 2.41, P = 0.02) in Group b than in Group a, and a significantly higher degree centrality was found among C. sinensis-infected individuals than among uninfected individuals in Group b (17.54 vs. 4.26; t = 2.33, P = 0.02). There was a high-risk community S11 with a 45.83% prevalence rate of C. sinensis infection in Group b, and C. sinensis-infected individuals with high betweenness centrality in Group b might serve as critical “bridges” in the food-sharing network, which facilitated the aggregation and diffusion of the risk of C. sinensis infection in the community. Conclusions Individual dietary behaviors, such as drinking raw water and consuming raw or undercooked fish, and sociocultural factors of household-neighborhood food-sharing networks, may contribute to the clustering transmission of clonorchiasis in Longjiang Village. The clonorchiasis control strategy is recommended to shift from individual-centered health education towards integrated interventions under a One Health framework in this region, which focus on key individuals within social networks, strengthen coordinated water and environmental management, and enhance community participation to improve the acceptability and sustainability of interventions.

ObjectiveTo explore the long-term dynamic trajectories of fasting blood glucose （FBG） and insulin resistance （IR） in patients with type 2 diabetes mellitus （T2DM） and their influencing factors. MethodsThis retrospective cohort study included 1 896 T2DM patients registered at Tongren Hospital from May 2020 to May 2025. Based on longitudinal follow-up data of FBG and fasting insulin， joint latent class mixed models （JLMM） were applied to identify FBG-IR trajectories. Univariate and multinomial logistic regression was used to examine demographic characteristics， lifestyle， and clinical determinants of trajectory type. ResultsFour distinct FBG-IR trajectories were identified： stable FBG-IR （9.76%）， rising FBG-stable IR （5.01%）， stable FBG-elevated IR （75.90%）， and elevated FBG-IR （9.34%）. Compared with the stable FBG-IR group， age ≥60 years was protective against the elevated FBG-stable IR trajectory （OR=0.55， 95%CI：0.33-0.92， P=0.023）. Highereducation increased the risk of stable FBG-elevated IR （OR=1.40， 95%CI：1.01-1.94， P=0.046）. Abnormal blood pressure was associated with lower risks of stable FBG-elevated IR （OR=0.66， 95%CI：0.48-0.92， P=0.013） and elevated FBG-IR （OR=0.48， 95%CI：0.31-0.74， P=0.001）. Non-drinkers were less likely to belong to the stable FBG-elevated IR trajectory （OR=0.39， 95%CI：0.16-0.95， P=0.038）. ConclusionsThe evolution trajectory of FBG and IR in T2DM patients shows significant heterogeneity. The majority of patients have a deterioration of IR first. Age， education level， blood pressure， and alcohol consumption are the main influencing factors. Joint assessment of FBG and IR is helpful for early identification of high-risk individuals and guiding individualized intervention.

To promote the standardization and normalization of perioperative care for follicular unit extraction(FUE) hair transplantation, ensure treatment efficacy, and align with advancements in the specialty, the Nursing Branch of the Chinese Association of Plastic and Aesthetics organized a panel of domestic experts. By integrating evidence-based medicine with clinical practice experience, and following thorough discussions, these experts developed the Clinical Practice Expert Consensus on Perioperative Nursing Care for Follicular Unit Extraction (2025). This consensus provides a comprehensive overview of hair transplantation, covering preoperative preparation, surgical procedures, intraoperative coordination, postoperative management, and complication prevention and treatment. It serves as a key reference and guide for implementing standardized perioperative nursing care in FUE hair transplantation.

Liposomes serve as critical carriers for drugs and vaccines,with their biological effects influenced by their size.The microfluidic method,renowned for its precise control,reproducibility,and scalability,has been widely employed for liposome preparation.Although some studies have explored factors affecting liposomal size in microfluidic processes,most focus on small-sized liposomes,predominantly through experimental data analysis.However,the production of larger liposomes,which are equally significant,remains underexplored.In this work,we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning(ML)model capable of accurately predicting liposomal size.Experimental validation was conducted using a staggered herringbone micromixer(SHM)chip.Our findings reveal that most investigated variables significantly influence liposomal size,often interrelating in complex ways.We evaluated the predictive performance of several widely-used ML algorithms,including ensemble methods,through cross-validation(CV)for both lipo-some size and polydispersity index(PDI).A standalone dataset was experimentally validated to assess the accuracy of the ML predictions,with results indicating that ensemble algorithms provided the most reliable predictions.Specifically,gradient boosting was selected for size prediction,while random forest was employed for PDI prediction.We successfully produced uniform large(600 nm)and small(100 nm)liposomes using the optimised experimental conditions derived from the ML models.In conclusion,this study presents a robust methodology that enables precise control over liposome size distribution,of-fering valuable insights for medicinal research applications.

Objective To investigate the spatial distribution of Aedes albopictus in China at different time periods from 2000 to 2019, so as to provide insights into precise management of Ae. albopictus in China. Methods Data pertaining to the distribution of Ae. albopictus in China from 2000 to 2019 were collected through literature retrieval with terms of “Aedes albopictus”, “monitoring”, “survey”, “density”, “distribution”, and “outbreak” in national and international databases. The title and time of the publication, sampling sites, sampling time, mosquito capture methods, and mosquito species and density were extracted, and the longitude and latitude of sampling sites were obtained through Baidu Map. Meteorological element data at meteorological observation stations within China were obtained from the National Climatic Data Center of the United States, and the annual maximum temperature, annual minimum temperature, average temperature in January, average temperature in July, annual temperature range, daily temperature range and relative humidity were calculated and subjected to Kriging interpolation. Monthly cumulative precipitation grid data and monthly average temperature grid data with a resolution of 1 km for China from 2000 to 2019 were obtained from the National Tibetan Plateau Scientific Data Center, and the annual precipitation and annual average temperature were calculated cumulatively. Population density data in China from 2000 to 2019 were obtained from the WorldPop Hub, and the gross domestic product (GDP) in China was obtained from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences. The above data were divided into 5-year intervals to calculate data during the periods from 2000 to 2004, from 2005 to 2009, from 2010 to 2014, and from 2015 to 2019. Ae. albopictus distribution data were modeled in China from 2000 to 2019 and during each period with the classification random forest (RF) model, to predict the distribution of Ae. albopictus across the country and analyze the distribution of Ae. albopictus based on the seven major climate zones in China. The performance of RF models was evaluated by accuracy, precision, recall, and area under the receiver operating characteristic curve (AUC), and the importance of each feature in the RF model was evaluated with mean decrease accuracy (MDA). Results A total of 1 191 Chinese publictions and 391 English publications were retrieved, among which 580 articles provided detailed data on the sampling sites of Ae. albopictus and specific sampling years, meeting the inclusion criteria. A total of 2 234 Ae. albopictus sampling sites were included in China from 2000 to 2019, and RF modeling results showed that the overall Ae. Albopictus distribution area was mainly found in southeastern and southwestern provinces of China from 2000 to 2019, with scattered distribution in coastal areas of northeastern provinces, such as Liaoning Province. The accuracy, precision, recall and AUC of the RF model were 0.915 to 0.947, 0.933 to 0.975, 0.898 to 0.978, and 0.902 to 0.932 for the distribution of Ae. albopictus at different time periods from 2000 to 2019. Among all features in the RF models, population density was the most contributing factor to the distribution of Ae. albopictus in China, followed by GDP, and all meteorological variables contributed relatively less to the predictive power of the RF model. In China’s seven major climate zones, Ae. albopictus was almost entirely distributed in the marginal tropical humid region, the north subtropical humid region, and the warm temperate semi-humid region. The combined distribution area of these three zones accounted for 100.0% of the national distribution area from 2000 to 2004, from 2005 to 2009, and from 2010 to 2014, and 99.9% from 2015 to 2019, and the proportion of Ae. albopictus distribution area in the warm temperate semihumid region increased gradually from 20.2% to 30.2%. Conclusions Ae. albopictus is mainly distributed in the southeastern and southwestern provinces of China and is greatly influenced by population and economic factors. The warm temperate semi-humid region in China is gradually becoming a hot spot for the distribution of Ae. albopictus.

OBJECTIVE To construct a predictive tool for surgical site infections(SSIs)in spinal surgery for Chi-nese population to provide evidence support for reducing SSIs.METHODS A systematic review of Chinese and English database literature was conducted for Meta-analysis to obtain pooled risk values for influencing factors,and a risk prediction scoring tool was constructed based on the logistic regression model.Patients who underwent spinal surgery and completed postoperative follow-up in a tertiary hospital in Beijing from Jan.to Dec.2021 were selected to validate the predictive effect of the tool.RESULTS The predictive model for SSIs in Chinese spinal sur-gery patients was Logit(P)=—3.47+0.63(age 60 years)+0.31 ×(patient with cardiovascular disease)+0.69 ×(rheumatoid arthritis)+1.07 ×(diabetes)+1.06 ×(operation duration＞3 h)+1.17 ×(preopera-tive albumin＜35 g/L)+0.71 ×(history of spinal surgery)+0.67 ×(carrying internal implants)+0.73 ×(blood transfusion).The total score of the predictive tool was 92,with a cutoff score of≥24.50 indicating high-risk individuals.The area under the curve was 0.733,with the sensitivity 58.30％and the specificity 79.60％.CONCLUSION The established predictive model for SSIs in Chinese spine surgery demonstrates good predictive performance and can be used as a reference assessment tool in clinical practice.

Spine fracture and dislocation are common traumatic spinal conditions that often require surgical intervention due to compromised spinal stability. Surgical approaches include anterior, posterior, and combined anterior-posterior spinal procedures. According to the specific surgical requirements, patients may be placed in the prone position or repositioned between prone and supine positions during surgery. Intraoperative repositioning has become an essential step in patient positioning. However, during repositioning, patients with spinal fracture and dislocation are at increased risk for complications such as hemodynamic instability, nerve injury, and pressure injuries to the skin and soft tissue. Notably, due to the instability of the spinal cord, even minor manipulations can further exacerbate the damage, potentially leading to severe outcomes like paraplegia. Although the current clinical guidelines provide instructive recommendations for standard position, there remains no specific protocols for intraoperative repositioning in patients with spine fracture and dislocation. With a concern for the lack of clinical studies on positioning techniques, risk prevention, and operational norms for special patients, no applicable guidelines or standards are available. A consensus was required to provide clinical reference, meet the requirements of surgical treatment, and minimize the safety risks of patients caused by improper placement of positions. Professional Committee of Operating Room Nursing of Shaanxi Nursing Association organized experts in nursing management and operating room nursing from major hospitals across China to formulate Expert consensus on intraoperative repositioning for patients with spinal fracture and dislocation ( version 2025). The consensus provides 11 recommendations covering pre-repositioning preparation, intraoperative maneuvers, and post-repositioning observation, aiming to provide references for clinical standardization of the intraoperative repositioning process and protection of patients′ safety.