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.

The inheritance, innovation, and development of traditional Chinese medicine(TCM) need to be based on Chinese medicinal materials. The TCM seed industry is the source of TCM production, which is related to the stable supply and quality safety of TCM. This paper summarizes the basic situation of the TCM seed industry and introduces relevant policies and regulations to TCM seeds in the seed industry and the TCM field. At present, the Management Measures of TCM Seeds and Seedlings has not yet promulgated, and TCM seeds are classified as non-major crops in the category of crops for management. This paper also describes the current situation of TCM seed and seedling system construction, which is in the development stage, from six aspects, including the construction of TCM seed industry technical support system; the establishment of TCM seed standard; the construction of germplasm resource preservation system; TCM seed testing, variety registration, and variety protection; production and management of TCM seeds; TCM seed supervision. According to the development status of the TCM seed industry, four problems are put forward, including imperfect systems and standards relevant to TCM seeds, insufficient supervision and law enforcement regarding TCM seeds, insufficient policy measures and capital investment to promote the development of the industry, and the industry's falling into a low-level cycle.Accordingly, four suggestions are provided, including improving laws, regulations, and policies, perfecting standards and norms,strengthening supervision and law enforcement, and promoting support system construction, in order to boost the high-quality development of the TCM seed industry.
Seeds/chemistry* ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal/standards* ; Plants, Medicinal/chemistry*

This study employed bioinformatics to screen the feature genes related to efferocytosis in diabetic kidney disease(DKD) and explores traditional Chinese medicine(TCM) regulating these feature genes. The GSE96804 and GSE30528 datasets were integrated as the training set, and the intersection of differentially expressed genes and efferocytosis-related genes(ERGs) was identified as DKD-ERGs. Subsequently, correlation analysis, protein-protein interaction(PPI) network construction, enrichment analysis, and immune infiltration analysis were performed. Consensus clustering was conducted on DKD patients based on the expression levels of DKD-ERGs, and the expression levels, immune infiltration characteristics, and gene set variations between different subtypes were explored. Eight machine learning models were constructed and their prediction performance was evaluated. The best-performing model was evaluated by nomograms, calibration curves, and external datasets, followed by the identification of efferocytosis-related feature genes associated with DKD. Finally, potential TCMs that can regulate these feature genes were predicted. The results showed that the training set contained 640 differentially expressed genes, and after intersecting with ERGs, 12 DKD-ERGs were obtained, which demonstrated mutual regulation and immune modulation effects. Consensus clustering divided DKD into two subtypes, C1 and C2. The support vector machine(SVM) model had the best performance, predicting that growth arrest-specific protein 6(GAS6), S100 calcium-binding protein A9(S100A9), C-X3-C motif chemokine ligand 1(CX3CL1), 5'-nucleotidase(NT5E), and interleukin 33(IL33) were the feature genes of DKD. Potential TCMs with therapeutic effects included Astragali Radix, Trionycis Carapax, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma, which mainly function to clear heat, replenish deficiency, activate blood, resolve stasis, and promote urination and drain dampness. Molecular docking revealed that the key components of these TCMs, including β-sitosterol, quercetin, and sitosterol, exhibited good binding activity with the five target genes. These results indicated that efferocytosis played a crucial role in the development and progression of DKD. The feature genes closely related to both DKD and efferocytosis, such as GAS6, S100A9, CX3CL1, NT5E, and IL33, were identified. TCMs such as Astragali Radix, Trionycis Carapa, Sargassum, Rhei Radix et Rhizoma, Curcumae Radix, and Alismatis Rhizoma may provide a new therapeutic strategy for DKD by regulating efferocytosis.
Humans ; Computational Biology ; Diabetic Nephropathies/physiopathology* ; Protein Interaction Maps ; Medicine, Chinese Traditional ; Drugs, Chinese Herbal ; Phagocytosis/genetics* ; Efferocytosis

OBJECTIVE: To analyze the prevalence and burden of headache disorders in China and its provinces from 1990 to 2021. METHODS: Using data from the Global Burden of Disease Study (GBD) 2021, the number of prevalent cases, prevalence rate, disability-adjusted life years (DALYs), and age-standardized DALY rates were analyzed by sex, age group, and province for headache disorders and their subtypes (migraine and tension-type headache [TTH]) between 1990 and 2021. Percentage changes during this period were also estimated. RESULTS: In 2021, approximately 426 million individuals in China were affected by headache disorders, with an age-standardized prevalence rate of 27,582.61/100,000. The age-standardized DALY rate for all headache disorders was 487.15/100,000. Between 1990 and 2021, the number of prevalent cases increased by 37.78%, while the prevalence of all headache disorders, migraine, and TTH increased by 6.92%, 7.57%, and 7.86%, respectively. The highest prevalence was observed in the 30-34 age group (39,520.60/100,000). Migraine accounted for a larger proportion of DALYs attributable to headache disorders, whereas TTH has a greater impact on its prevalence. In 2021, the highest age-standardized DALY rates for headache disorders were observed in Heilongjiang (617.85/100,000) and Shanghai (542.86/100,000). CONCLUSION The prevalence of headache disorders is increasing in China. Effective health education, improve diagnosis and treatment are essential, particularly for middle-aged working populations and women of childbearing age.
Humans ; China/epidemiology* ; Female ; Male ; Adult ; Middle Aged ; Prevalence ; Young Adult ; Adolescent ; Aged ; Child ; Headache Disorders/epidemiology* ; Disability-Adjusted Life Years ; Child, Preschool ; Cost of Illness ; Infant ; Aged, 80 and over

Objective To evaluate the value of imaging quantification parameters in artificial intelligence (AI) assisted diagnosis systems in clinical decision-making for lung nodules≤2 cm and the diagnostic efficacy of AI. Methods Lung nodule patients admitted to Affiliated Zhongshan Hospital of Dalian University from 2020 to 2023 were included. Imaging parameters of lung nodules were extracted using AI assisted diagnosis systems. Multifactor analysis was used to screen predictors for distinguishing benign and malignant nodules and high-risk predictors for recurrent invasive adenocarcinoma, and a diagnostic model was established and its performance evaluated. The diagnostic efficacy of the AI system was judged according to pathological results. Results A total of 594 patients with lung nodules were included, including 202 males and 392 females, with an average age of (58.75±11.55) years. Volume, average CT value, and 3D maximum diameter of non-solid nodules were independent predictors of malignant nodules, with thresholds of 287.4 mm3, −491 HU, and 12.0 mm, respectively. The area under the curve (AUC) for diagnostic efficacy was ranked from high to low as combined model (0.802), volume (0.783), average CT value (0.749), and 3D maximum diameter (0.714). The average CT value and 3D long diameter of solid nodules were independent predictors of malignant nodules, with thresholds of −81 HU and 17.5 mm, respectively, and AUC values of 0.874 and 0.686, respectively, with the combined prediction AUC of 0.957. The mass of cystic nodules was an independent predictor of malignancy when the mass>180.7 mg. Independent predictors of high recurrence risk of invasive adenocarcinoma in non-solid nodules were consolidation-tumor ratio (CTR), average CT value, 3D long diameter, and volume, with thresholds of 0.14, −386 HU, 15.6 mm, and 1018.9 mm3, respectively, and diagnostic efficacy was ranked from high to low as combined model (0.788), 3D long diameter (0.735), volume (0.725), average CT value (0.720), and CTR (0.697). The accuracy of AI in predicting benign and malignant target nodules was 87.4%, with positive predictive value of 96.6% and negative predictive value of 58.9%. Conclusion In clinical decision-making for lung nodules ≤2 cm, AI assisted diagnosis systems have high application value.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Objective To observe the origin and course of the obturator artery(OA),so as to provide anatomical reference for reducing hemorrhage during pelvic surgery and pubic fracture fixation.Methods A total of 65 human hemi-pelvises specimens with intact structure were dissected to observe the origin,course and other variations of OA.Measure the length of the inner section of OA basin and the outer diameter at the origin,etc.Results OA originated from the internal iliac artery in 57 cases(87.7%),including 3 cases(4.6%)of the superior gluteal artery,5 cases(7.7%)of the inferior gluteal artery,3 cases(4.6%)of the external iliac artery and 5 cases(7.7%)of the inferior epigastric artery.OA participated in the formation of the arterial trunk in 3 cases(4.6%).The length of the pelvic segment of the OA in male and female was(50.87±15.41)mm and(51.71±14.19)mm,respectively,with no statistically significant difference between them(P>0.05).The outer diameters at the origin of the OA in male and female were(2.79±1.05)mm and(2.35±0.86)mm,and there was no statistically significant difference between them(P>0.05).Conclusion OA mainly originated from the anterior trunk of the internal iliac artery,with a few OA originated from the branches of the posterior trunk or the inferior epigastric artery,or participated in the formation of the arterial trunk.In pelvic surgery involving OA area,attention should be paid to the length of its pelvic segment and the outer diameter at the origin of OA,so as to better locate and protect blood vessels during surgery.

Objective:Committee of Minimally Invasive Cardiovascular Surgery(CMICS) conducts an annual summary of minimally invasive cardiovascular surgery procedures performed throughout the country, which includes a comprehensive survey of the total number of minimally invasive procedures by region and the distribution of minimally invasive procedures by hospital. Since CMICS first published the 2018-2019 China Minimally Invasive Cardiovascular Surgery Data White Paper in 2020, the report has received great attention from peers within and outside the industry. In this statistical report, CMICS will focus on publishing the data related to minimally invasive cardiovascular surgery in China from 2021 to 2023 for reference and use by industry peers.

Objective:To explore the characteristics of T cells and natural killer (NK) cells in cerebrospinal fluid of patients with multiple sclerosis (MS).Methods:Cerebrospinal fluids from patients with relapsing-remitting multiple sclerosis (RRMS) and healthy controls attending the Second Hospital of Lanzhou University from January 2023 to October 2024 were collected and analyzed by single-cell RNA sequencing (scRNA-seq) and flow cytometry, and T and NK cell characteristics were summarized and compared in the two groups. The proposed time-series analysis was used to explore the differentiation trajectories of T cells and NK cells.Results:A total of 3 patients with RRMS and 3 healthy controls underwent scRNA-seq, and 6 patients with RRMS and 4 healthy controls underwent flow cytometry. The composition of cerebrospinal fluid T and NK cell subtypes was similar in the RRMS group and the healthy control group, but the proportion of the cell subtypes differed. The RRMS group exhibited significantly higher frequencies of CD4 +Naive T- IL7R [1 529/9 055(16.89%) vs 1 423/9 910(14.36%), χ2=22.980, P<0.001], CD4 +Naive T- CCR7 [1 573/9 055(17.37%) vs 948/9 910(9.57%), χ2=250.114, P<0.001], and CD4 +Naive T- LTB [1 369/9 055(15.12%) vs 1 079/9 910(10.89%), χ2=75.336, P<0.001] subsets compared to controls. Conversely, the control group demonstrated greater proportions of CD4 +Th1- GZMA [1 255/9 910(12.66%) vs 719/9 055(7.94%), χ2=113.213, P<0.001] and CD8 +Tem- GZMK cells [1 607/9 910(16.22%) vs 1 232/9 055(13.61%), χ2=25.326, P<0.001] than the RRMS group. The transcription factors and gene expression of each T cell subtype were also different between the 2 groups, and CD4 initial T cells and CD8 effector T cells were located at the beginning and the end of the differentiation trajectory, respectively. Conclusions:The cerebrospinal fluid of MS patients is characterized by increased expression of genes involved in T cell differentiation and over-activation of immune cells.