ObjectiveThe widespread adoption of portable fundus cameras for primary care and community screening is hindered by limitations in current autofocus(AF) technologies. Image-based methods relying on sharpness evaluation require iterative searches, resulting in slow convergence, while projection-based techniques are susceptible to optical artifacts and calibration errors. To address these challenges, this study introduces a novel AF system based on direct wavefront sensing, designed to deliver simultaneous high speed, high precision, and operational robustness within the compact form factor essential for portable ophthalmic devices. MethodsOur approach fundamentally reimagines the AF process by directly measuring the ocular wavefront aberration. We developed a custom portable fundus camera integrating a miniaturized Shack-Hartmann wavefront sensor (SHWS) into the optical path. An 850 nm laser diode projects a point source onto the retina via oblique illumination to minimize corneal reflections. Light scattered from this spot carries the eye’s refractive error through the imaging optics and is directed to the SHWS, positioned at a plane optically conjugate to the primary color CMOS imaging sensor. A microlens array within the SHWS samples the incident wavefront, generating a pattern of focal spots on a CCD. Real-time centroid analysis of these spots provides a map of local wavefront slopes. These measurements are processed through a singular value decomposition (SVD) algorithm to fit a Zernike polynomial basis set, enabling real-time reconstruction of the wavefront phase. The defocus component (S) is extracted from the second-order Zernike coefficients, providing a direct, quantitative measure of the refractive error in diopters. This value serves as a precise error signal in a closed-loop control system, which commands a voice-coil actuated focusing lens to its null position in a single, deterministic step, eliminating the need for iterative search algorithms. ResultsComprehensive evaluation demonstrated the system’s high performance. Testing on a calibrated model eye (OEMI-7) established a highly linear relationship between the computed defocus S and the focusing lens position across a ±20 Diopter (D) compensation range, achievable within a 5 mm mechanical travel. The system achieved a focusing precision of 0.08 D, corresponding to an 18-fold improvement over a conventional projection spot-size method tested under identical conditions. The total focus acquisition time, encompassing wavefront measurement, computation, and lens actuation, averaged under 0.5 s. Clinical validation with 25 human volunteers (50 eyes, refractive range -15 D to +10 D) confirmed practical efficacy. The wavefront-sensing AF succeeded in 92% of attempts with a mean time of 0.5 s, substantially outperforming a projection-based benchmark which achieved only a 32% success rate with an average time of 4.25 s. The system provided instantaneous directional guidance and maintained stability during minor ocular movements. Objective assessment of image quality, via amplitude contrast of retinal vasculature, showed consistent and significant enhancement following AF correction across the entire tested diopter range. ConclusionThis work successfully implements and validates a direct wavefront-sensing autofocus paradigm for portable fundus cameras. By directly quantifying and compensating for the optical defocus aberration, this method bypasses the fundamental limitations of image-processing and projection-based techniques, enabling rapid, precise, and deterministic diopter compensation. The developed system delivers an exceptional combination of a wide operational range (±20 D), high accuracy (0.08 D), fast convergence (0.5 s), and a compact physical footprint. This technology provides a practical and high-performance focusing solution capable of enhancing the reliability, throughput, and diagnostic utility of portable retinal imaging in large-scale screening applications. Future efforts will be directed towards system cost optimization and performance adaptation for diverse ocular conditions.

Cholangiocarcinoma (CCA) is a malignancy characterized by tumor cells originating in the liver or bile ducts, exhibiting features of cholangiocyte differentiation. It poses a significant clinical challenge due to the limited diagnostic and therapeutic options available. Robust animal models are essential for advancing our understanding of CCA pathogenesis and developing effective treatments. This review provides a comprehensive overview of CCA mouse models, highlighting various approaches, including chemical induction, genetically engineered models, and tumor xenografts. Each model is discussed in terms of its establishment techniques, pathological characteristics, and research significance, with a focus on intrahepatic CCA. Chemical induction models, such as diethylnitrosamine- and azoxymethane-induced models, offer insights into tumorigenesis processes, whereas genetically modified models involving alterations in key genes such as Kirsten rat sarcoma viral oncogene homolog, tumor protein 53, and isocitrate dehydrogenase serve as important tools for studying the molecular mechanisms underlying CCA. Xenograft models, including patient-derived xenografts, bridge the gap between experimental research and clinical applications, allowing for precise therapeutic evaluations. By comparing these models, this review underscores their respective advantages and limitations, paving the way for future studies aiming to optimize and innovate CCA modeling strategies.

ObjectiveTo elucidate the critical role of rehabilitation medical records (including electronic records) in rehabilitation medicine's clinical practice and management, comprehensively analyzed the structure, core content and data standards of rehabilitation medical records, to develop a standardized medical record data architecture and core dataset suitable for rehabilitation medicine and to explore the application of rehabilitation data in performance evaluation and payment. MethodsBased on the regulatory documents Basic Specifications for Medical Record Writing and Basic Specifications for Electronic Medical Records (Trial) issued by National Health Commission of China, and referencing the World Health Organization (WHO) Family of International Classifications (WHO-FICs) classifications, International Classification of Diseases (ICD-10/ICD-11), International Classification of Functioning, Disability and Health (ICF), and International Classification of Health Interventions (ICHI Beta-3), this study constructed the data architecture, core content and data standards for rehabilitation medical records. Furthermore, it explored the application of rehabilitation record summary sheets (home page) data in rehabilitation medical statistics and payment methods, including Diagnosis-related Groups (DRG), Diagnosis-Intervention Packet (DIP) and Case Mix Index. ResultsThis study proposed a systematic standard framework for rehabilitation medical records, covering key components such as patient demographics, rehabilitation diagnosis, functional assessment, rehabilitation treatment prescriptions, progress evaluations and discharge summaries. The research analyzed the systematic application methods and data standards of ICD-10/ICD-11, ICF and ICHI Beta-3 in the fields of medical record terminology, coding and assessment. Constructing a standardized data structure and data standards for rehabilitation medical records can significantly improve the quality of data reporting based on the medical record summary sheet, thereby enhancing the quality control of rehabilitation services, effectively supporting the optimization of rehabilitation medical insurance payment mechanisms, and contributing to the establishment of rehabilitation medical performance evaluation and payment based on DRG and DIP. ConclusionStructured rehabilitation records and data standardization are crucial tools for quality control in rehabilitation. Systematically applying the three reference classifications of the WHO-FICs, and aligning with national medical record and electronic health record specifications, facilitate the development of a standardized rehabilitation record architecture and core dataset. Standardizing rehabilitation care pathways based on the ICF methodology, and developing ICF- and ICD-11-based rehabilitation assessment tools, auxiliary diagnostic and therapeutic systems, and supporting terminology and coding systems, can effectively enhance the quality of rehabilitation records and enable interoperability and sharing of rehabilitation data with other medical data, ultimately improving the quality and safety of rehabilitation services.

Objective:To investigate the application value of risk prediction model for acute kidney injury (AKI) after donation of cardiac death (DCD) liver transplantation based on machine learning algorithm.Methods:The retrospective cohort study was conducted. The clinicopathological data of 1 001 pairs of DCD liver transplant donors and recipients at five hospitals, including The First Affiliated Hospital of Zhejiang University School of Medicine et al, in the Chinese Liver Transplan-tation Registry from January 2015 to December 2023 were collected. Of the donors, there were 825 males and 176 females. Of the recipients, there were 806 males and 195 females, aged 52 (range, 18-75)years. There were 281 recipients included using oversampling technique, and all 1 282 recipients were divided to the training set of 897 recipients and the validation set of 385 recipients by a ratio of 7∶3 using computer-generated random numbers. Seven prediction models, including Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Logistic Regression (LR), Decision Tree (DT), K-Nearest Neighbors (KNN), and Categorical Boosting (CatBoost), were constructed for AKI after liver transplantation based on machine learning algorithm. Observation indicators: (1) comparison of clinicopathological characteristics between recipients with and without AKI and donors; (2) follow-up and survival of recipients with and without AKI; (3) construction and validation of nomogram prediction model of AKI after liver transplantation; (4) construction and validation of machine learning prediction model of AKI after liver transplantation. Comparison of measurement data with normal distribution between groups was conducted using the independent sample t test. Comparison of measurement data with skewed distribution between groups was conducted using the Mann-Whitney U test, and comparison among groups was conducted using the Kruskal-Wallis H test. Comparison of count data between groups was conducted using the chi-square test or corrected chi-square test. Kaplan-Meier method was used to calculate survival rates and plot survival curves. Logistic regression model was performed for univariate and multivariate analyses. The receiver operating characteristic (ROC) curve was plotted to calculate area under curve (AUC) and 95% confidence interval ( CI). The performance of prediction model was evaluated using DeLong test, accuracy, sensitivity, specificity. The calibration curve was plotted to evaluate the performance of predicted probability and actual probability. The interpretability analysis of machine learning algorithm and SHapley Additive exPlanations was used to explain the model decision separately. Results:(1) Comparison of clinicopathological characteristics between recipients with and without AKI and donors. Of 1 001 recipients, there were 360 cases with AKI and 641 cases without AKI after liver transplantation. There were significant differences in body mass index (BMI), hepatic encepha-lopathy, hepatitis B surfact antigen (HBsAg), hepatorenal syndrome (HRS) and donor diabetes, donor blood urea nitrogen, donor alanine aminotransferase, donor aspartate aminotransferase, mass of graft, volume of blood loss during liver transplantation, warm ischema time of donor liver, and operation time between recipients with and without AKI ( Z=-4.337, χ2=9.751, 9.088, H=11.142, χ2=5.286, Z=-3.360, -2.539, -3.084, -1.730, -3.497, -1.996, -2.644, P<0.05). (2) Follow-up and survival of recipients with and without AKI. All the 1 001 recipients received follow-up. The recipients with AKI after liver transplantation were followed up for 18.6(range, 0-102.3)months, and recipients without AKI after liver transplantation were followed up for 31.9(range, 0.1-105.5)months. The 1-, 3-, and 5-year overall survival rates were 72.1%, 63.5%, and 59.3% of recipients with AKI, versus 86.7%, 76.7%, and 72.5% of recipients without AKI, respectively, showing a significant difference in overall survival between them ( χ2=26.028, P<0.05). (3) Construction and validation of nomogram predic-tion model of AKI after liver transplantation. Results of multivariate analysis showed that recipient BMI, recipient creatinine, recipient HBsAg, recipient HRS, donor blood urea nitrogen, donor crea-tinine, anhepatic phase and volume of blood loss during liver transplantation were independent risk factors for AKI of recipients after liver transplantation ( odds ratio=1.113, 0.998, 0.605, 1.580, 1.047, 0.998, 1.006, 1.157, 95% CI as 1.070-1.157, 0.996-1.000, 0.450-0.812, 1.021-2.070, 1.021-1.074, 0.996-0.999, 1.000-1.012, 1.045-1.281, P<0.05). The nomogram prediction model of AKI after liver transplantation was constructed based on the results of multivariate analysis. Results of ROC curve showed that the AUC of 0.666 (95% CI as 0.637-0.696). (4) Construction and validation of machine learning prediction model of AKI after liver transplantation. Based on the Lasso regression analysis, seven machine learning algorithm prediction models, including RF, XGBoost, SVM, LR, DT, KNN, and CatBoost, were constructed, with ROC curves of the validation set plotted. The AUC of above models were 0.863, 0.841, 0.721, 0.637, 0.620, 0.708, 0.731, accuracies were 0.764, 0.782, 0.701, 0.592, 0.605, 0.605, 0.681, sensitivities were 0.764, 0.789, 0.719, 0.588, 0.694, 0.694, 0.704, specificities were 0.763, 0.774, 0.683, 0.597, 0.511, 0.511, 0.656, respectively. Delong test showed that the RF model with the highest AUC of 0.863(95% CI as 0.828-0.899). Calibration curve analysis showed the predicted probability closest to the actual probability of RF model, indicating the model with a good validation value. Further sorting of SHAP of different clinical factors based on RF model showed that recipient BMI, donor blood urea nitrogen, volume of blood loss during liver transplantation, donor age had large effects on the output outcomes. Conclusion:The nomogram prediction model and seven machine learning algorithm prediction models for AKI after DCD liver transplantation are constructed, and the RF model based on machine learning has a better predictive performance.

Blonanserin,a second-generation atypical antipsychotic agent,acts as an antagonist for dopamine D2,D3,and serotonin 5-HT2A receptors.Clinical studies have demonstrated that blonanserin is non-inferior to other antipsychotics,such as haloperidol and risperidone,in alleviating the symptoms of schizophrenia.Moreover,it exhib-its beneficial effects on cognitive symptoms and social functioning,with a favorable safety profile,making it one of the key treatment options for schizophrenia.With extensive clinical experience accumulated in China,this expert consensus aims to provide psychiatrists with updated and localized guidance on the optimal use of blonan-serin.Based on a systematic review of the latest evidence-particularly studies in Chinese population,this paper pres-ents the updated Chinese expert recommendations for the clinical use of blonanserin in 2024.

Objectives:To investigate the epidemiological characteristics and ethnic differences of cardiovascular-kidney-metabolic syndrome(CKM)among the Hani,Dai,Bai,and Lisu populations in Yunnan Province,and to provide evidence for developing effective prevention and control strategies for CKM.Methods:A cross-sectional survey was conducted among four ethnic minority groups.A total of 3 906 permanent residents aged 18 years and older were enrolled using a multistage cluster random sampling method.CKM stages(0-4)were defined based on the 2023 American Heart Association criteria,stages 3-4 were classified as advanced CKM.Descriptive statistics and chi-square tests were used to compare the prevalence of CKM stages across ethnic groups.Modified Poisson regression was applied to estimate relative risk(RR)and 95%confidence intervals(CI)for factors associated with advanced CKM.Results:The prevalence rates of CKM stage 1 and above among the Hani,Dai,Bai and Lisu ethnic groups were 80.1%,87.3%,84.8%and 67.8%,respectively.The prevalence of CKM was generally higher in males than in females,and the prevalence of CKM increased significantly with age.The Dai ethnic group had the highest prevalence of advanced CKM(24.7%,95%CI:22.1%-27.4%),while the Lisu ethnic group had the lowest prevalence of advanced CKM(13.7%,95%CI:11.5%-15.9%).Modified Poisson regression analysis showed that older age and higher body mass index were common risk factors for advanced CKM across all four ethnic groups.Additionally,except for the Lisu ethnic group,the other three ethnic groups had specific individual risk factors:among the Hani ethnic group,low educational attainment(RR=2.18,95%CI:1.12-4.25)and low income(RR=1.47,95%CI:1.00-2.18)were the primary risk factors of CKM.Among the Dai ethnic group,smoking(RR=1.60,95%CI:1.07-2.37)and a family history of cardiovascular disease(RR=1.61,95%CI:1.14-2.27)are the primary risk factors of CKM.Among the Bai ethnic group,male gender(RR=0.48,95%CI:0.29-0.79)was the primary risk factor of CKM.Conclusions:The prevalence of CKM stage 1 or higher is relatively high among the four minority ethnic groups in Yunnan province.There are significant differences in staging characteristics and primary risk factors across ethnic groups,necessitating the development of stratified,differentiated intervention strategies to achieve precise prevention and control and ethnic health equity in terms of CKM.

Objective To investigate the correlation between arterial stiffness(AS)and incident chronic kidney disease(CKD)among the elderly individuals taking health checkup.Methods A retrospective study was conducted on 857 elderly individuals without CKD at baseline who taking physical exams in our medical center from December 2009 to May 2021.Their clinical and labora-tory data were collected.Brachial-ankle pulse wave velocity(baPWV)was used to assess the se-verity of AS,and then the subjects were divided into normal elasticity group(201 cases),and moderate(490 cases)and severe AS group(166 cases).Kaplan-Meier curves were plotted to dis-play cumulative incidence rates of incident CKD across different AS groups.Restricted cubic splines(RCS)and Cox regression models were applied to analyze the correlation of baPWV and incident CKD risk.Results The severe AS group had significantly advanced age,greater ratio of hypertension,larger waist circumference,higher HR,SBP and DBP,increased urinary albumin/creatinine ratio(UACR),elevated levels of TG and fasting blood glucose,and baPWV than the normal elasticity group(P＜0.05).During the follow-up period,37 participants developed CKD.The incidence of CKD was obviously higher in the severe AS group than the normal arterial elas-ticity group(9.04％vs 3.48％).RCS analysis revealed a U-shaped relationship between baPWV and incident CKD risk.When baPWV ≥1 400 cm/s,each standard deviation increase in baPWV indicates the risk of incident CKD increasing by 71％(HR=1.71,95％CI:1.30-2.25,P＜0.01).Regardless of adjustment for covariates or not,baPWV remained positive correlation with inci-dent CKD risk(P＜0.05).Conclusion Among the elderly individuals undergoing health check-up,increased AS severity is significantly associated with higher risk of incident CKD when baP-WV ≥1400 cm/s.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective To explore the traditional Chinese medicine(TCM)syndrome characteristics of patients with Chikungunya hemorrhagic fever and to provide empirical data to support the application of TCM in diagnosing and treating Chikungunya hemorrhagic fever.Methods A cross-sectional survey was conducted to collect clinical data(sex,age,days since onset,and comorbidity underlying disease conditions)and TCM with four-examination information(symptoms,tongue manifestations,and pulse manifestations)from 255 patients with Chikungunya hemorrhagic fever who visited Lecong Hospital of Shunde,Foshan,the Third People's Hospital of Shunde District of Foshan,Shunde Hospital of Southern Medical University Affiliated Chencun Hospital between July 23 and July 29,2025.Factor and cluster analyses were used to summarize TCM syndrome characteristics and analyze core pathogenesis in conjunction with clinical features.Results Among the 255 patients with Chikungunya hemorrhagic fever,131 were male and 124 were female,with a age of(49.05±17.93)years and a disease duration of(3.26±1.78)days.Among the four types of examination information in TCM,35 items exhibited a frequency exceeding 10%.The most prevalent symptoms were arthralgia(180 patients,70.59%),exanthem(153 patients,60.00%),fatigue(99 patients,38.82%),anhidrosis(98 patients,38.43%),pruritus(96 patients,37.65%),and fever(92 patients,36.08%).Tongue and pulse manifestations were primarily white fur(155 patients,60.78%),pink tongue(111 patients,43.53%),slippery pulse(143 patients,56.08%),and greasy fur(134 patients,52.53%).Patients with disease onset≤3 d had a higher incidence of arthralgia,fatigue,fever,aversion to cold,generalized muscle pain,aversion to wind,insomnia,headache,sweating,low-grade fever,poor appetite,loose stool,hyperhidrosis,and red tongue than those with disease onset≥4 d(P<0.05).Patients with disease onset≥4 d had a higher incidence of pink tongue and thick fur than those with disease onset≤3 d(P<0.05).The syndrome elements in patients with Chikungunya hemorrhagic fever predominantly manifested on the defensive exterior,with involvement of the sinew-bone joints,skin-muscle,and spleen.Pathogenic factors were primarily characterized by external winds,dampness,and heat.Factor and cluster analysis result indicated three TCM pathogenesis progression patterns:imbalance of the defensive exterior with wind-dampness conflict and heat transformation;dampness-heat flowing into muscles and meridians causing joint obstruction and qi blood stasis;and dampness-heat congelation resulting in qi mechanism obstruction,consumption of body fluids,and infiltration of the skin.Conclusion Patients with Chikungunya hemorrhagic fever primarily present with fever,joint pain,and rashes.In TCM,this condition falls under the category of"dampness-warmth"syndrome.Its etiology is attributed to pathogens,with transmission occurring through mosquito bites.The core pathogenesis of TCM is the invasion of the defensive exterior and dampness-toxic heat accumulation.The therapeutic principles focus on clearing heat pathogens,resolving dampness pathogens,dispersing wind pathogens,and promoting the resolution of rashes.

Objective To explore the relationship of metabolic comorbidities and insulin resistance(IR)with chronic kidney disease(CKD)among elderly individuals undergoing health exam.Methods A cross-sectional observational study was conducted on 8358 older adults who took health exam in Chinese PLA General Hospital between December 2009 and May 2021.According to the guidelines for CKD diagnostic criteria,they were divided into CKD group(983 cases)and non-CKD(7375 cases).Clinical data was collected,and the eGDR was calculated.Quasi-Bayesian method was used for causal mediation analysis.Results The prevalence of metabolic comorbidi-ties including hypertension,CHD,DM,hyperlipidemia,and hyperuricemia was significantly higher in the CKD group than the non-CKD group(P＜0.01).The eGDR was obviously lower in the CKD group than the non-CKD group[6.88±2.09 mg/(kg·min)vs 8.41±2.12 mg/(kg·min),P＜0.01].Logistic regression analysis revealed that,without adjusting covariates,each 1-unit increase in eGDR was associated with a 29％reduction in the risk of developing CKD(OR=0.714,95％CI:0.691-0.738,P＜0.01),and after adjusting covariates,eGDR remained signifi-cantly negatively association with the risk of CKD(P＜0.01).Mediation analysis indicated that DM and brachial-ankle pulse wave velocity accounted for the highest proportions of the mediating effect in the relationship between eGDR and CKD(14.2％and 12.5％,respectively).Conclusion In the elderly population undergoing health exam,reduced insulin sensitivity is significantly asso-ciated with the development of CKD.Diabetes and arteriosclerosis exert mediating effect in this association.