AIM: To screen and analyze the influencing factors of myopia among primary and secondary school students and establish a predictive model to provide ideas for the prevention and control measures of myopia among children and adolescents.METHODS:A total of 1 759 primary and secondary school students from 2 primary schools, 2 junior high schools, 2 senior high schools and 1 vocational high school in the urban area of Qingdao were sampled by means of stratified cluster sampling in September 2023. Vision screening and a questionnaire survey on influencing factors were carried out based on machine learning algorithms. The screening and determination were mainly conducted in accordance with the Standard Logarithmic Visual Acuity Chart(GB/T11533-2011)and the Specifications for Screening Myopia in Children and Adolescents. The influencing factors of myopia were analyzed and a prediction model was developed based on the machine learning algorithms LASSO in combination with XGBoost, and visualization was achieved through an interactive Nomogram. Statistical analysis was performed using R statistical software version 4.3.3.RESULTS:The screening prevalence of myopia among primary and secondary school students in the urban area of Qingdao was 70.61%(1 242 cases). The optimal predictive variables for screening were grade, gender, whether parents were myopic, daily indoor sedentary time, appropriate distance between eyes and books during reading and writing, daily sleep time, distance between eyes and TV screen when watching TV/playing video games exceeding 3 meters, the playground during breaks, total duration of tutorial classes, how often eyes are rested during near work, daily computer usage time, and average daily homework time after school, totaling 12 influencing factors. The AUCs of the training set and test set were 0.770(95%CI:0.751-0.789)and 0.732(95%CI:0.714-0.750), respectively.CONCLUSION: A machine learning-based prediction model was developed and validated to predict the risk of myopia onset in primary and secondary school students, accompanied by effective visualization techniques.

ObjectiveThis study proposes a novel single-cell protein localization method based on a class perception graph convolutional network (CP-GCN) to overcome several critical challenges in protein microscopic image analysis, including the scarcity of cell-level annotations, inadequate feature extraction, and the difficulty in achieving precise protein localization within individual cells. The methodology involves multiple innovative components designed to enhance both feature extraction and localization accuracy. MethodsFirst, a class perception module (CPM) is developed to effectively capture and distinguish semantic features across different subcellular categories, enabling more discriminative feature representation. Building upon this, the CP-GCN network is designed to explore global features of subcellular proteins in multicellular environments. This network incorporates a category feature-aware module to extract protein semantic features aligned with label dimensions and establishes a subcellular relationship mining module to model correlations between different subcellular structures. By doing so, it generates co-occurrence embedding features that encode spatial and contextual relationships among subcellular locations, thereby improving feature representation. To further refine localization, a multi-scale feature analysis approach is employed using the K-means clustering algorithm, which classifies multi-scale features within each subcellular category and generates multi-cell class activation maps (CAMs). These CAMs highlight discriminative regions associated with specific subcellular locations, facilitating more accurate protein localization. Additionally, a pseudo-label generation strategy is introduced to address the lack of annotated single-cell data. This strategy segments multicellular images into single-cell images and assigns reliable pseudo-labels based on the CAM-predicted regions, ensuring high-quality training data for single-cell analysis. Under a transfer learning framework, the model is trained to achieve precise single-cell-level protein localization, leveraging both the extracted features and pseudo-labels for robust performance. ResultsExperimental validation on multiple single-cell test datasets demonstrates that the proposed method significantly outperforms existing approaches in terms of robustness and localization accuracy. Specifically, on the Kaggle 2021 dataset, the method achieves superior mean average precision (mAP) metrics across 18 subcellular categories, highlighting its effectiveness in diverse protein localization tasks. Visualization of the generated CAM results further confirms the model’s capability to accurately localize subcellular proteins within individual cells, even in complex multicellular environments. ConclusionThe integration of the CP-GCN network with a pseudo-labeling strategy enables the proposed method to effectively capture heterogeneous cellular features in protein images and achieve precise single-cell protein localization. This advancement not only addresses key limitations in current protein image analysis but also provides a scalable and accurate solution for subcellular protein studies, with potential applications in biomedical research and diagnostic imaging. The success of this method underscores the importance of combining advanced deep learning architectures with innovative training strategies to overcome data scarcity and improve localization performance in biological image analysis. Future work could explore the extension of this framework to other types of microscopic imaging and its application in large-scale protein interaction studies.

Objective To investigate the prevalence of primary drug resistance among HIV-1 patients in Hubei Province from 2020 to 2022, and to provide corresponding basis and data support for HIV antiviral therapy (ART) in Hubei Province. Methods During 2020-2022, plasma samples of HIV-1 infected patients before ART were collected., Patients’ demographic data and baseline laboratory test data were also collected. HIV-1 pol region was amplified by in-house method for sub-type typing and drug-resistant mutation site analysis. Results The pol gene sequence was successfully amplified in 242 of 285 cases, with a success rate of 84.9%. CRF07_BC was the predominant HIV-1 sub-type, accounting for 47.11% (114/242), followed by CRF01_AE, accounting for 25.21% (61/242), sub-type B, accounting for 14.16% (35/242), and CRF55_01B, accounting for 4.13% (10/242). The primary resistance rate was 6.20% (15/242). The mutation site of nucleoside reverse transcriptase inhibitors (NRTIs) was mainly M184V, and the mutation sites of non-nucleoside reverse transcriptase inhibitors (NNRTIs) were mainly E138A/G/EG and V179E. These different mutation sites led to different degrees of drug resistance to 12 drugs. The incidence of drug resistance mutation of CRF55_01B sub-type was significantly higher than that of other sub-types. Conclusion The primary drug resistance rate of HIV-1 infected patients is at a slightly high level in Hubei Province, and close monitoring of primary drug resistance and mutation sites should be strengthened before ART, especially for CRF55_01B sub-type.

The "pre-disease" theory of traditional Chinese medicine focuses on the dynamic and continuous evolution from health to disease, and emphasizes early identification and intervention in the complex and gradual process of evolution from health to disease. The "pre-disease" theory and complexity science share the same perspective on health and disease from the standpoint of features of the dynamic evolution and holism, i. e., life is considered as a complex system with ongoing dynamic changes, which exhibit the nonlinear features of " homeostasis-destabilization-phase transition-another homeostasis". In this paper, from the perspective of nonlinear dynamics in complexity science, we explain the scientific connotation of the evolution law of "pre-disease"-disease based on the theory of critical slowing down in traditional Chinese medicine. Based on the theory of critical slowing down and the dynamic network biomarker method generated by its development, combined with the macro signs of comprehensive analysis of data gained by four diagnostic method and the micro features including transcriptomics and the microbiomics, this paper proposes to integrate macro and micro multi-hierarchy information to construct a "pre-disease" critical slowing down identification model with the characteristics of traditional Chinese medicine diagnosis and treatment, which provides a new perspective and method for the early warning of complex diseases.

BACKGROUND:Previous studies have reported inconsistent results with positive,negative,and J-shaped associations between alcohol consumption and the hazard of aortic aneurysm and dissection(AAD).This study aimed to examine the connections between weekly alcohol consumption and the subsequent risk of AAD. METHODS:The UK Biobank study is a population-based cohort study.Weekly alcohol consumption was assessed using self-reported questionnaires and the congenital risk of alcohol consumption was also evaluated using genetic risk score(GRS).Cox proportional hazards models were used to estimate hazard ratios(HRs)with 95%confidence intervals(CIs)for the associations between alcohol consumption and AAD.Several sensitivity analyses were performed to assess the robustness of the results. RESULTS:Among the 388,955 participants(mean age:57.1 years,47.4%male),2,895 incident AAD cases were documented during a median follow-up of 12.5 years.Compared with never-drinkers,moderate drinkers(adjusted HR:0.797,95%CI:0.646-0.984,P<0.05)and moderate-heavy drinkers(adjusted HR:0.794,95%CI:0.635-0.992,P<0.05)were significantly associated with a decreased risk of incident AAD.Interaction-based subgroup analysis revealed that the protective effect of moderate drinking was reflected mainly in participants younger than 65 years and women. CONCLUSION:Our findings support a protective effect of moderate alcohol consumption on AAD,but are limited to participants younger than 65 years and women.

Objective:To investigate the clinical value of endometrial receptivity test(ERT)combined with per-sonalized embryo transfer in improving pregnancy outcomes in patients with repeated implantation failures.Meth-ods:The clinical data of patients diagnosed with repeated implantation failure at the Reproductive Medicine Cen-ter,The Sixth Affiliated Hospital of Sun Yat-Sen University from March 2019 to August 2022 were retrospectively analyzed,among which 428 patients who underwent endometrial receptivity test were included in the ERT group.396 patients who did not undergo ERT were selected by propensity score matching of SPSS 26.0 software as the control group.We compared the clinical characteristic and pregnancy outcomes of two groups and ana-lyzed the pregnancy outcomes of individualized embryo transfer in patients with normal,delayed by 1 day and de-layed by 2 days of endometrial window of implantation(WOI)after personalized embryo implantation of shifting WOI patients.Results:The clinical pregnancy rate(47.73％vs.12.79％)and the live birth rate(38.97％vs.9.76％)of ERT group were significantly higher than those in the control group(P＜0.05).Moreover,endome-triosis and polycystic ovary syndrome(PCOS)accounted for a higher proportion of infertility factors in the ERT group compared to the control group(P＜0.05).Among 428 patients who underwent ERT,there were 316 pa-tients with normal WOI(73.83％),112 patients with WOI displaced(26.17％).There was no statistical difference in the pregnancy outcome among the three groups of normal WOI delayed by 1 day and WOI delayed by 2 days(P＞0.05).Conclusions:ERT technology combined with personalized embryo transfer protocol can improve the fertility outcomes of RIF patients,especially for those with WOI displacement.ERT technology has application prospect and clinical application value.

Objective:To assess the effectiveness of a 6-month Ba Duan Jin exercise program in improving the balance of community-dwelling older adults.Methods:A two arms, parallel-group, cluster randomized controlled trial was conducted in 1 028 community residents aged 60-80 years in 40 communities in 5 provinces of China. Participants in the intervention group (20 communities, 523 people) received Ba Duan Jin exercise 5 days/week, 1 hour/day for 6 months, and three times of falls prevention health education, and the control group (20 communities, 505 people) received falls prevention health education same as the intervention group. The Berg balance scale (BBS) score was the leading outcome indicator, and the secondary outcome indicators included the length of time of standing on one foot (with eyes open and closed), standing in a tandem stance (with eyes open and closed), the closed circle test, and the timed up to test.Results:A total of 1 028 participants were included in the final analysis, including 731 women (71.11%) and 297 men (28.89%), and the age was (69.87±5.67) years. After the 3-month intervention, compared with the baseline data, the BBS score of the intervention group was significantly higher than the control group by 3.05 (95% CI: 2.23-3.88) points ( P<0.001). After the 6-month intervention, compared with the baseline data, the BBS score of the intervention group was significantly higher than the control group by 4.70 (95% CI: 4.03-5.37) points ( P<0.001). Ba Duan Jin showed significant improvement ( P<0.05) in all secondary outcomes after 6 months of exercise in the intervention group compared with the control group. Conclusions:This study showed that Ba Duan Jin exercise can improve balance in community-dwelling older adults aged 60-80. The longer the exercise time, the better the improvement.

Objective To explore the efficacy and safety of recombinant human anti-severe acute respiratory syn-drome coronavirus 2(anti-SARS-CoV-2)monoclonal antibody injection(F61 injection)in the treatment of patients with coronavirus disease 2019(COVID-19)combined with renal damage.Methods Patients with COVID-19 and renal damage who visited the PLA General Hospital from January to February 2023 were selected.Subjects were randomly divided into two groups.Control group was treated with conventional anti-COVID-19 therapy,while trial group was treated with conventional anti-COVID-19 therapy combined with F61 injection.A 15-day follow-up was conducted after drug administration.Clinical symptoms,laboratory tests,electrocardiogram,and chest CT of pa-tients were performed to analyze the efficacy and safety of F61 injection.Results Twelve subjects(7 in trial group and 5 in control group)were included in study.Neither group had any clinical progression or death cases.The ave-rage time for negative conversion of nucleic acid of SARS-CoV-2 in control group and trial group were 3.2 days and 1.57 days(P=0.046),respectively.The scores of COVID-19 related target symptom in the trial group on the 3rd and 5th day after medication were both lower than those of the control group(both P＜0.05).According to the clinical staging and World Health Organization 10-point graded disease progression scale,both groups of subjects improved but didn't show statistical differences(P＞0.05).For safety,trial group didn't present any infusion-re-lated adverse event.Subjects in both groups demonstrated varying degrees of elevated blood glucose,elevated urine glucose,elevated urobilinogen,positive urine casts,and cardiac arrhythmia,but the differences were not statistica-lly significant(all P＞0.05).Conclusion F61 injection has initially demonstrated safety and clinical benefit in trea-ting patients with COVID-19 combined with renal damage.As the domestically produced drug,it has good clinical accessibility and may provide more options for clinical practice.

Objective To explore the application of nucleic acid test in the diagnosis of HIV western blotting (WB) indeterminate and negative samples. Methods A total of 2 518 HIV samples to be confirmed were collected from the Hubei HIV Confirmation Center Laboratory from 2014 to 2022. The results of follow-up antibody test and nucleic acid test of WB indeterminate and negative samples were analyzed, and the diagnostic rate, sensitivity, specificity and coincidence rate of the two detection strategies were compared. Results There were totally 133 indeterminate or negative samples by WB test. Of the 99 indeterminate samples , 76 (76.77%) had nucleic acid test results >5000 copies/mL. 40 cases were followed up, of which 33 cases (82.50%) turned positive and 7 (17.50%) were still uncertain. Of the 7 samples with 20~5000 copies /mL (7.07%), 2 cases were followed up and both turned positive during the follow-up. 1 case (1.01%) with nucleic acid <20 copies/mL turned positive during follow-up. Among the 34 WB negative samples, 15 cases (45.45%) were > 5 000 copies/mL, 9 of which were seroconversion. The diagnostic rates of ^“antibody confirmation^” and ^“nucleic acid test^” were 96.78% (2 437/2 518) and 99.60% (2 508/2 518), respectively. The sensitivities were 98.02% (2 430/2 479) and 99.88% (2476/2 479), and the specificities were 78.13% (25/32) and 100.00 % (32/32), respectively. The coincidence rates were 97.77% (2 455/2 511) and 99.88% (2 508/2 511), respectively. Conclusion Nucleic acid supplemental test strategy has high diagnostic rate, sensitivity, specificity and coincidence rate. WB indeterminate and negative samples can be diagnosed as early as possible through nucleic acid supplemental testing.

Chronic heart failure （CHF） and diabetes mellitus （DM） comorbidity presents a myriad of symptoms and a complex pathogenesis， making the traditional diagnostic and treatment model of "using disease to treat syndrome" often inadequate in clinical practice. The concept of "syndrome-based treatment of disease" is rooted in the core thinking of traditional Chinese medicine （TCM） syndrome differentiation and treatment， emphasizing the importance of syndrome as the guiding principle. This approach categorizes various diseases according to their corresponding syndrome categories for exploration， adhering to the principle of starting from the syndrome and addressing the disease thereafter， which highlights the advantages of TCM holistic view and syndrome differentiation and treatment. The pathogenesis of CHF is characterized by deficiency of both Qi and Yin， along with blood stasis， affecting organs such as the lung， spleen， and kidney， which in turn impacts the distribution and metabolism of body fluids. Dysfunction in body fluid regulation leads to stagnation， resulting in pathological products like phlegm and turbidity， which exacerbates syndromes of Yin deficiency and excessive heat. As the conditions of Yin deficiency and dryness-heat intensify， and as body fluid depletion continues， the patient's DM symptoms worsen， contributing to or aggravating the comorbidity. Following the diagnostic approach of "syndrome-based treatment of disease"， TCM diagnosis and treatment of CHF and DM comorbidity should focus on the core pathogenesis of "deficient Qi retention". This study categorized CHF and DM comorbidity into four stages： A （comorbid risk period）， B （precomorbid period）， C （intermediate stage of comorbidity）， and D （advanced comorbidity）， proposing corresponding TCM syndrome types for each stage. In terms of treatment， adhering to the principle of "tonifying deficiency and relieving stagnation"， the specific methods included invigorating Qi and strengthening the body， nourishing Yin and generating body fluids， activating blood circulation and Qi， and promoting diuresis and removing toxins. This study reviewed recent research progress on Chinese medicine compound prescriptions for CHF combined with DM， aiming to achieve precise treatment for both diseases and provide a scientific basis for the application of TCM in the prevention and treatment of CHF and DM comorbidity.