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.

ObjectiveType I interferon (IFN-I) signaling is essential for antiviral innate immunity, yet its sustained or excessive activation contributes to the pathogenesis of several autoimmune diseases and interferonopathies, such as systemic lupus erythematosus and Aicardi-Goutières syndrome. Current strategies targeting this pathway, exemplified by JAK inhibitors, act mainly on downstream signal transduction and provide limited direct control over upstream IFN-I production, while also carrying the risk of broad immunosuppression. Phyllanthus emblica L. has long been used in traditional medicine for inflammatory disorders, but the bioactive constituent responsible for its regulation of IFN-I signaling and the underlying molecular mechanism have not been clearly defined. This study aimed to identify the active anti-inflammatory component of P. emblica and to characterize its mechanism of action on the IFN-I pathway in macrophages. MethodsActive components ofP. emblica and their candidate targets were screened by network pharmacology using the TCMSP and DrugBank databases (oral bioavailability≥30%, drug-likeness≥0.18) and intersected with inflammation-related genes retrieved from public databases. The predicted interaction between EGCG and IFN-I pathway proteins (TBK1, IRF3, STAT1) was evaluated by molecular docking, with BX795 and GSK8612 used as reference TBK1 inhibitors. Mechanistic experiments were performed in THP-1-derived macrophages and primary bone marrow-derived macrophages (BMDM). Upstream signaling was activated by transfection of the nucleic acid analogs poly(I∶C) and poly(dA∶dT) or by lipopolysaccharide (LPS) stimulation, whereas downstream signaling was activated by exogenous IFN-β. An siRNA-mediated TREX1 knockdown model was used to mimic endogenous nucleic acid-driven interferonopathy. Expression of IFN-β1 and interferon-stimulated genes (ISGs) was measured by RT-qPCR, protein phosphorylation by Western blot, and IFN-β secretion by ELISA. Cellular thermal shift assay (CETSA) and drug affinity responsive target stability (DARTS) were used to probe the interactionbetween EGCG and IRF3. ResultsNetwork pharmacology identified (-)-epigallocatechin-3-gallate (EGCG) as a candidate IFN-I-suppressive constituent of P. emblica, with predicted binding to TBK1, IRF3, and STAT1. Molecular docking yielded binding energies of -9.2, -7.2, and -8.2 kcal/mol for TBK1, IRF3, and STAT1, respectively, indicating an affinity for TBK1 comparable to that of the reference inhibitors BX795 (-5.7 kcal/mol) and GSK8612 (-6.4 kcal/mol). EGCG suppressed IFN-β1 and ISG mRNA expression under poly (I∶C), poly (dA∶dT), and LPS stimulation in both THP-1 macrophages and BMDM. At the protein level, EGCG reduced the phosphorylation of TBK1 and IRF3 without affecting the levels of the upstream sensors cGAS and RIG-I, and lowered IFN-β secretion in a concentration-dependent manner. CETSA and DARTS showed that EGCG did not enhance the thermal stability or protease resistance of IRF3, indicating that its effect on IRF3 is indirect. Following IFN-β stimulation, prolonged EGCG treatment reduced STAT1 phosphorylation in a time-dependent manner without an apparent change in IRF9, and partially attenuated ISG transcription; this effect was not monotonicly concentration-dependent, and CXCL10 showed the most consistent suppression. In TREX1-knockdown cells, the elevated mRNA levels of ISG15, ISG56, and CXCL10 were reduced by EGCG. ConclusionEGCG suppresses IFN-I responses by concurrently inhibiting TBK1-IRF3-dependent IFN‑β production and JAK-STAT1-mediated downstream transcription. These in vitro findings provide a mechanistic basis for the anti-inflammatory use of P. emblica in traditional medicine and identify EGCG as a candidate for further evaluation in interferon-driven autoimmune disease models.

Objective:To construct and evaluate a training program for health management specialist nurses.Methods:Mainly qualitative analysis, The training system of health management specialist nurses was preliminarily drawn up based on literature review and semi-structured interview. The Delphi expert consultation method was used to conduct a two-round expert letter inquiry with 17 experts in the professions such as health management medicine, health management nursing, nursing management, and nursing education; and the analytic hierarchy process was applied to determine the weights of the indicators.Results:The effective recall rates of the questionnaires for the 2 rounds of expert consultation was 94.44%(17/18) and 100%(17/17), with expert authority coefficients of 0.90 and 0.92 and Kendall harmony coefficients of 0.207 and 0.249, respectively (all P<0.001). The training system of health management specialist nurses included 4 parts: training objective, training content, training management, training assessment and evaluation. There were 8 indicators in the training objective part. There were 5 first-level indicators, 15 second-level and 67 third-level indicators in the training content part. There were 5 first-level indicators, 12 second-level indicators in the training management part. There were 3 first-level indicators, 10 second-level indicators in the training assessment and evaluation part. Conclusion:The training program for specialized nurses in health management developed in this study demonstrates high levels of expert enthusiasm, authority, and consensus, indicating its feasibility.

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.

Cellular death in the body can occur through different processes,including apoptosis,pyroptosis and necrotic apoptosis,etc.PANoptosis is a newly discovered form of inflammatory cell death in recent years.It can be triggered by various stimulating factors and integrates multiple components that can induce cell death to assemble into various types of macromolecular complexes-PANoptosome,which then mediates cell death.Given the impact of PANoptosis on the entire disease spectrum,promoting or inhibiting its occurrence process may prevent the development of various diseases.The review summarizes the research progress on the occurrence mechanism of PANoptosis and its role in some diseases,and explores the crosstalk among multiple programmed cell death pathways,aiming to provide new ideas for the treatment of related diseases.

Objective To investigate the effects of estrogen signaling on T-cell recruitment and polarization in acutely injured skeletal muscle.Methods One hundred C57BL/6 male mice,one hundred and eighty C57BL/6 female mice were selected.Twenty-five female mice were ovariectomized(OVX)and 10 male mice were taken as the sham-operated(sham).Then,cardiotoxin(CTX)induced tibialis anterior(TA)injury for preparing mice myoinjury model.Subcutaneous injection of 17β-estradiol(E2)or estrogen receptor antagonist 4-hydroxytamoxifen(4-OHT)was performed.A total of 140 mice(70 males and 70 females)were divided into four group including:PBS-male,CTX-male,PBS-female,and CTX-female.Serum estradiol(E2)levels were measured by ELISA,and muscle injury models were validated via HE staining.Subsequently,20 male and 20 female mice were selected for immunofluorescence(IF)and Real-time PCR to assess estrogen receptors(ER)expression in injured muscle tissue.Further,10 male and 40 female mice were allocated into five experimental groups,including CTX,CTX+E2,CTX+4-OHT,CTX+OVX,CTX+sham.HE staining and IF were performed to evaluate inflammatory infiltration in the injured muscle.Additionally,50 female mice were divided into CTX and CTX+OVX groups,and IF combined with flow cytometry were used to analyze T-cell phenotypes and muscle fiber regeneration in the injured muscle.Results In vivo,serum E2 and myofiber ERβ increased post-injury in mice of both sexes,significantly higher in females.Compared to the control group,E2 alleviated inflammation,OVX exacerbated inflammation,increased CD4+T-cell infiltration,elevated T helper 1 cell(Th1)response,decreased regulatory T cells(Tregs),impaired regeneration.In vitro,IFN-γ/LPS significantly upregulated ERβ in myotubes.Conclusion Estrogen signaling critically regulates muscle inflammation.Estrogen deficiency(OVX)delays repair of skeletal muscle by promoting Th1 response and suppressing Tregs function.

Objective:Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions.Methods:Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from the Cancer Hospital of the Chinese Academy of Medical Sciences, Tianjin Central Hospital of Gynecology Obstetrics, Xinmi Maternal and Child Health Hospital of Henan Province, West China Second Affiliated Hospital of Sichuan University, and Heping Hospital Affiliated to Changzhi Medical College collected during April 2014 and March 2015. The hypermethylated gene fragments related to cervical cancer were selected by high-density, high-association, and hypermethylated gene fragment screening and the LASSO regression algorithm. Taking cervical intraepithelial neoplasia grade 2 (CIN2) or more severe lesions as the research outcome, machine learning predictive models based on the random forest (RF), naive Bayes (NB), and support vector machine (SVM) algorithm, respectively, were constructed. A total of 144 outpatient specimens were used as the training set and 80 cervical exfoliated cell specimens from women participating in the cervical cancer screening program were used as the test set to verify the predictive models. Using histological diagnosis results as the gold standard, the detection efficacy for CIN2 or more severe lesions of the three machine learning predictive models were compared with that of the human papilloma virus (HPV) detection and cytological diagnosis.Results:In the training set of 144 cases, there were 34 cases of HPV positivity, with a positive rate of 23.61%. Cytologically, there were 37 cases diagnosed as no intraepithelial lesion or malignancy (NILM), and 107 cases diagnosed as atypical squamous cells of undetermined significance (ASC-US) or above. Histologically, there were 28 cases without cervical intraepithelial neoplasia or benign cervical lesions, 31 cases of CIN1, 18 cases of CIN2, 31 cases of CIN3, and 36 cases of squamous cell carcinoma. Seven hypermethylated gene fragments were selected from 45 genes, and three machine learning prediction models based on the RF, NB, and SVM algorithm, respectively, were constructed. In the validation set of 80 cases, there were 28 cases of HPV positivity, with a positive rate of 35.00%. Cytologically, there were 65 cases diagnosed as NILM and 15 cases as ASC-US or above. Histologically, there were 39 cases without cervical intraepithelial neoplasia or benign cervical lesions, 10 cases of CIN1, 10 cases of CIN2, 11 cases of CIN3, and 10 cases of squamous cell carcinoma. In the validation set, the area under the curve (AUC) values of the RF model, NB model, SVM model, HPV detection, and cytological diagnosis of CIN2 or above were 0.90, 0.88, 0.82, 0.68, and 0.45, respectively. The DeLong test showed that there was no statistically significant difference in the AUC values between the RF, NB, and SVM models (all P＞0.05), and the AUC values of the RF and NB models were higher than that of HPV detection (both P＜0.01), and the AUC values of the RF, NB, and SVM models were higher than that of cytological diagnosis (all P＜0.01). Compared with the NB model, the sensitivity of the RF model was similar (80.65% vs. 77.42%), but the specificity of the NB model was much higher than that of the RF model (93.88% vs. 73.47%). Conclusion:Among the machine learning prediction models for cervical cancer and precancerous lesions constructed based on human DNA methylation, the NB model has good predictive performance for CIN2 and above lesions, and may be used for screening of cervical cancer and precancerous lesions.

This study analyzed the burden and trends in enteric infections in China from 1990 to 2021 from a One Health perspec-tive.Data on mortality associated with enteric infections were extracted from the 2021 Global Burden of Disease(GBD)database.The analysis focused on assessing the mortality rates of enteric infectious diseases attributed to various etiologies and risk factors,along with the age and sex distribution,from 1990 to 2021.Average annual percentage change(AAPC)was used to assess the total changes in disease burden.The age-standardized mortality rate of intestinal infections in China decreased from 9.642/100 000 in 1990 to 0.439/100 000 in 2021,with an AAPC of-57.103%(95%CI:-57.118%to-57.088%).In 2021,Rotavirus,Norovirus,and Crypto-sporidium were the top three etiologies contributing to disease burden,with mortality rates of 1.020/100 000,0.040/100 000 and 0.079/100 000,respectively.A significant variation in etiology distribution was observed across age groups:Rotavirus,Shigella,and Crypto-sporidium dominated among children under 5 years of age,whereas Cryptosporidium,Norovirus,and Clostridioides difficile were more prevalent in older populations.Risk factor analysis indicated that unsafe water sources and poor sanitation accounted for 73.394%of all enteric disease-related deaths.In conclusion,the burden of enteric infections in China markedly declined from 1990 to 2021,and sig-nificant variations in the etiological spectrum and disease burden were observed across age groups.The persistent effects of unsafe wa-ter sources and poor sanitation underscore the need for targeted interventions to further decrease the burden of these diseases.Our find-ings highlight the success of public health interventions in decreasing the burden of enteric infections in China,while emphasizing the need for targeted measures to address disparities in high-risk populations and improve environmental sanitation.

Natural products are an important source for innovative drugs,but unclear molecular targets and mechanisms limit their further development and application.The authors proposed a new method for the target identification of natural products based on proteolysis-targeting chimera(PROTAC)technology and quantitative proteomics,and established the targeted degradomics(TGDO) technology for the identification of weak-affinity tar-gets.This article summarizes the standardized workflow and the application of TGDO for target identification of natural products.

Objective To investigate the stability and reproducibility of the treatment fractions during the intensity-modulated radiotherapy(IMRT)for breast cancer and the effect of respiratory motion on the dose irradiation of breast cancer radiotherapy by comparing the results of breast cancer dosimetric verification based on fractionated images by an electronic portal imaging device(EPID).Methods A total of 28 IMRT patients admitted to some hospital from January to June 2023 were grouped according to the pathological results and effects of respiratory motion on the accuracy of radiotherapy during clinical treatment,including 14 cases in a breast group and 14 cases in a non-breast group with 8 ones of head and neck tumors,5 ones of esophageal cancer and 1 case of cervical cancer.All the patients underwent a scan with cone beam computed tomography(CBCT)before the first radiotherapy,and image registration was carried out with a positioning CT.An EPID was used to acquire transmission dose images of 10 fractions of radiotherapy,and γ analysis was performed using the RIT 113 QA software to compare the images of the subsequent 9 fractions with those of the first fraction,with the images of the first fraction of radiotherapy as the baseline values.Absolute maximum dose normalization was implemented under the condition of 10％dose assessment threshold,and the γ-pass rates under the 3 criteria of 2％/2 mm,3％/2 mm and 3％/3 mm were counted separately.The fraction dose verification results of the 28 patients were divided into 3 treatment phases of 2-4 times(T1),5-7 times(T2)and 8-10 times(T3)to analyze the stability of dose irradiation during the radiotherapy.SPSS 22.0 software was used for statistical analysis.Results Under the condition of 10％dose assessment threshold,the breast and non-breast groups had the γ-pass rates being(95.80±2.65)％and(94.60±6.59)％under the 2％/2 mm criterion and(98.46±1.31)％and(97.50±3.30)％under the 3％/2 mm criterion respectively,and the differences were statistically significant(all P<0.05).Under the assessment criteria of 2％/2 mm,3％/2 mm and 3％/3 mm,the breast group had the γ-pass rates of fractions of treatment significantly lower than those of the non-breast group(all P<0.05),while the γ-pass rates showed no significant differences at T1,T2 and T3 treatment phases(all P>0.05).Conclusion EPID fraction images contribute to evaluating IMRT accuracy effectively.IMRT has high stability and reproducibility during the treatment cycle,while respiration may result in dose deviation during the fraction radiotherapy for breast cancer,and optical surface tracking technology or active breathing control technology is suggested to be involved in to relieve dose deviation.[Chinese Medical Equipment Journal,2025,46(6):54-58]