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.

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.

Traditional Chinese medicine(TCM)exerts integrative effects on complex diseases owing to the char-acteristics of multiple components with multiple targets.However,the syndrome-based system of diagnosis and treatment in TCM can easily lead to bias because of varying medication preferences among physicians,which has been a major challenge in the global acceptance and application of TCM.Therefore,a standardized TCM prescription system needs to be explored to promote its clinical application.In this study,we first developed a gradient weighted disease-target-herbal ingredient-herb network to aid TCM formulation.We tested its efficacy against intracerebral hemorrhage(ICH).First,the top 100 ICH targets in the GeneCards database were screened according to their relevance scores.Then,SymMap and Traditional Chinese Medicine Systems Pharmacology(TCMSP)databases were applied to find out the target-related ingredients and ingredient-containing herbs,respectively.The relevance of the resulting ingredients and herbs to ICH was determined by adding the relevance scores of the corresponding targets.The top five ICH therapeutic herbs were combined to form a tailored TCM prescriptions.The absorbed components in the serum were detected.In a mouse model of ICH,the new prescription exerted multifaceted effects,including improved neurological function,as well as attenuated neuronal damage,cell apoptosis,vascular leakage,and neuroinflammation.These effects matched well with the core pathological changes in ICH.The multi-targets-directed gradient-weighting strategy presents a promising avenue for tailoring precise,multipronged,unbiased,and standardized TCM prescriptions for complex diseases.This study provides a paradigm for advanced achievements-driven modern innovation in TCM concepts.

Protozoan infections(e.g.,malaria,trypanosomiasis,and toxoplasmosis)pose a considerable global burden on public health and socioeconomic problems,leading to high rates of morbidity and mortality.Due to the limited arsenal of effective drugs for these diseases,which are associated with devastating side effects and escalating drug resistance,there is an urgent need for innovative antiprotozoal drugs.The emergence of drug repurposing offers a low-cost approach to discovering new therapies for pro-tozoan diseases.In this review,we summarize recent advances in drug repurposing for various human protozoan diseases and explore cost-effective strategies to identify viable new treatments.We highlight the cross-applicability of repurposed drugs across diverse diseases and harness common chemical motifs to provide new insights into drug design,facilitating the discovery of new antiprotozoal drugs.Chal-lenges and opportunities in the field are discussed,delineating novel directions for ongoing and future research.

Objective To design an intelligent airborne soldier physical training system based on human body composition analysis to solve the problems in diversity of training mode,targeted training plan and high incidence of military training-related injuries.Methods The intelligent airborne military physical training system was designed with B/S architecture and developed with Python language,which was composed of four functional modules for airborne soldier information acquisition,trainee physical fitness state assessment,physical fitness training program recommendation and airborne soldier physical fitness training program evaluation.The airborne soldier information acquisition module collected and analyzed the trainee physiological parameter information with a human body composition analyzer,clarified the parameter characteristics related to physical training with considerations on military physical training requirements and constructed a trainee physical fitness assessment parameter model;the trainee physical fitness state assessment module established an evaluation model based on machine learning to realize stage-by-stage physical fitness evaluation for airborne soldiers;the physical fitness training program recommendation module was constructed based on the physical training feature similarity algorithm and graph embedding theory to provide decision making assistance for program development of airborne military physical training;the airborne soldier physical fitness training program evaluation module compared the physical fitness and evaluation results before and after training by means of list and chart,and updated the training program based on the evaluation results by calling the physical training program recommendation module.Results The intelligent airborne soldier physical training system contributed to forming an individualized physical fitness training recommendation mechanism after trainee body evaluation,modifying training program based on comparison and feedback for stage-by-stage training evaluation,so as to decrease the incidence of military training-related injuries while increasing the training efficiency.Conclusion The system developed improves airborne soldier physical training in rationality and reliability,and provides references for intelligent military training of the PLA.[Chinese Medical Equipment Journal,2025,46(2):16-23]

Objective To compare the success rate and stability of rat models of comorbid chronic pain and depression induced by different doses of complete Freund's adjuvant(CFA).Methods Sixty SD rats were divided randomly into a control group,low-dose CFA group(CFA-L),and high-dose CFA group(CFA-H)(n=20 rats per group).Rats in the CFA-L and CFA-H groups were injected with 50 and 100 μL CFA,respectively,and rats in the control group were injected with 0.9％sodium chloride solution.The general state,body weight,mechanical withdrawal threshold(MWT),and thermal withdrawal latency(TWL)were observed at 0,7,14,21,and 28 days after modeling.Depressive behavior was evaluated using the open field test(OFT),forced swim test(FST),and tail suspension test(TST).Glutamate(Glu)and γ-aminobutyric acid(GABA)levels in the anterior cingulate cortex were detected by enzyme-linked immunosorbent assay.Brain-derived neurotrophic factor(BDNF)expression in the anterior cingulate cortex was detected by immunohistochemistry,and pathological changes in the anterior cingulate cortex were observed by HE staining.Results(1)Regarding the general condition of the rats,the left ankle joint and toes were obviously red and swollen in the CFA-L and CFA-H groups on the 7th day after modeling,and the swelling was more severe in the CFA-H group.The redness and swelling of the left hind foot and ankle joint and toes gradually recovered in the CFA-L group on days 14,21,and 28 after modeling,but were still obvious in the CFA-H group,and the water and food intake decreased.(2)The body mass was significantly lower in rats in the CFA-H group compared with those in the blank and CFA-L groups on days 14,21,and 28 after modeling(P＜0.05,P＜0.05).(3)Regarding pain-related behavior,the MWT and TWL were significantly decreased in the CFA-L and CFA-H groups on the 7th and 14th days after modeling,compared with the control group(P＜0.05,P＜0.05).On day 21 after modeling,MWT was significantly lower in the CFA-H group than in the blank and CFA-L groups(P＜0.05,P＜0.05),and TWL was significantly lower in the CFA-L and CFA-H groups than in the blank group(P＜0.05,P＜0.05).On day 28 after modeling,MWT and TWL were significantly lower in the CFA-H group than in the blank and CFA-L groups(P＜0.05,P＜0.05).(4)In terms of depression-related behaviors,the total OFT movement distance was significantly lower in the CFA-H group than in the blank and CFA-L groups on day 7 after modeling(P＜0.05,P＜0.05).The total OFT distance and central dwell time were significantly lower in the CFA-H group than in the blank and CFA-L groups on days 14,21,and 28 after modeling(P＜0.05,P＜0.05),and the result in the FST and TST were significantly higher than in the blank and CFA-L groups(P＜0.05,P＜0.05).(5)Glu,GABA,and BDNF expression levels were significantly higher in the CFA-H group than in the blank and CFA-L groups(P＜0.05,P＜0.05),while GABA,Glu/GABA,and BDNF levels were significantly lower in the CFA-H group than in the blank and CFA-L groups(P＜0.05,P＜0.05,P＜0.05).(6)The CFA-L group showed less damage in the anterior cingulate cortex,more pyramidal cells,more arranged cells,clear nucleoli,and a small number of cells with karyokynesis and deep staining.Compared with the CFA-L group,rats in the CFA-H group showed a disordered cell arrangement in the injured area of the anterior cingulate cortex,a large number of pyknotic and hyperchromatic neurons,significantly fewer or absent pyramidal cells,and vacuoles,red blood cells,and neurofibrillary tangles in the interstitial space.Conclusions Injection of CFA 100 μL can be used to establish a rat model of chronic inflammatory pain and depression,showing hyperalgesia,depression-like behavioral changes,changes in levels of Glu,GABA,and BDNF in the anterior cingulate cortex,and pathological changes in the anterior cingulate cortex,consistent with the pathophysiological characteristics of chronic pain and depression.

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:The clinicopathological features of pulmonary epithelioid hemangioendothelioma (PEHE) were analyzed to provide guidance for clinical practice.Methods:The clinical manifestations, imaging examination, pathological morphology and molecular characteristics, treatment and prognosis of patients with pulmonary epithelioid hemangioendothelioma were retrospectively collected. All cases were admitted to Fujian Medical University Union Hospital from January 2012 to May 2023.Results:Of 7 PEHE cases, 2 underwent tumor biopsy and 5 underwent tumor resection. There were 4 males and 3 females, with a median age of 58 years old. Six cases showed multiple bilateral nodules, and only one case showed a single lesion in the lower left lung lobe. Five patients presented with respiratory symptoms, like cough, sputum, hemoptysis, shortness of breath. There were round-like solid lesions with clear border and homogeneous density on lung CT. Histologically, it showed nodular growth with a distinctive myxohyaline stroma. Necrosis was seen in the center of some cases. Epithelioid tumor cells were arranged in cords, solid pattern or single cells, with abundant eosinophilic cytoplasm and occasional intracytoplasmic vacuoles. The plasmacytoid nucleus were round to oval in shape with obvious nucleoli, minimal pleomorphism and few mitoses. The tumor cells were positive for vascular endothelial markers: CD31 (7/7), CD34 (5/7), ERG (6/6), and Fli-1 (5/6); CKpan was focally positive in 3 cases (3/7), and TFE3 in 2 cases. Ki-67 index ranged from 5% to 10%. Additionally, the tumor cells partially express PD-L1 in two cases. Moreover, lung carcinoma-related gene detection was negative in one case. The TFE3 break-apart probe in two cases did not display a split signal. In terms of treatment, 4 cases were treated with surgery, 1 case was treated with chemotherapy and surgery, and 2 cases were follow-up observation. After the median 34.4 months follow-up time, one was lost to follow-up, six were survived. Their CT scans showed slight enlargement of pulmonary nodules without other organ metastases.Conclusions:PEHE is a rare vascular-derived tumor, which is usually characterized by multiple solid bilateral nodules with slow growth. It tends to lack specific clinical symptoms, and is prone to be misdiagnosed as a metastatic carcinoma. Diagnosis primarily rely on pathology, with the use of an immunohistochemical package being crucial for definitive and differential diagnosis.

This study was aimed at investigating the immunoregulatory function of Mycobacterium tuberculosis Rv3641c gene in modulating host type Ⅰ interferon responses.The shuttle plasmid pMV261 was used to construct Rv3641c overexpression recombinant Mycobacterium smegmatis,and the biological characteristics of the recombinant bacteria were analyzed to explore the effect of Rv3641c on the growth curve,colony morphology and stress resistance of Mycobacterium.Subsequently,RAW264.7 cells were infected with Rv3641c overexpressing Mycobacterium smegmatis,and the transcriptional expression of genes related to the inhibition of type I inter-feron pathway was determined by RT-PCR.The expression level of IFN-βprotein was determined by ELISA,and the intracellular sur-vival level was determined.As a result,the recombinant rMS::pMV261-Rv3641c was successfully constructed.The results of biologi-cal characteristics analysis showed that Rv3641c did not affect the growth of mycobacteria,but significantly changed the colony mor-phology of mycobacteria and improved its resistance to H2O2.The results of recombinant bacteria infection experiments showed that Rv3641c significantly down-regulated the transcription levels of IFN-α,IFN-βand downstream ISGs genes CXCL10,IFIT2 and IL-1β in host cells,and Rv3641c significantly down-regulated the transcription levels of IFN-α,IFN-βand downstream ISGs genes CXCL10,IFIT2 and IL-1βin host cells.The results of intracellular colonization experiments showed that the intracellular mycobacte-ria in the overexpression recombinant bacteria infection group were significantly higher than those in the empty vector group,indicat-ing that Rv3641c could promote the intracellular surviv al of mycobacteria.In summary,the Rv3641c gene of M.tuberculosis can inhibit the host type I interferon response and promote the intracellular survival of M.tuberculosis,which provides a new idea for further explor-ing the immune escape function of M.tuberculosis and the discovery of new targets for anti-tuberculosis drugs.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.