Abstract The prevention and control of myopia in Chinese children and adolescents has become a major public health issue. While maintaining increased outdoor activity as a cornerstone intervention, there is an urgent need to explore new complementary approaches that can be effectively implemented in both indoor and outdoor settings. In recent years, environmental spatial frequency has gained increasing attention as one of the key environmental factors influencing the development and progression of myopia. Both animal studies and human research have confirmed that indoor environments lacking mid to high spatial frequency components, often characterized as "visually impoverished", can promote axial elongation and myopia through mechanisms such as disruption of retinal neural signaling, impaired accommodative function, and altered expression of related molecules. Based on the scientific consensus, it is recommended that "enriching of environmental spatial frequency" should be integrated into the myopia prevention and control framework. Following the principles of schoolled organization, family cooperation, community involvement, and student participation, specific measures are put forward in three areas：optimizing school visual settings, improving home spatial environments, and promoting healthy visual behavior. The aim is to create "visually friendly" indoor environments as an important supplement to outdoor activity, thereby providing a novel perspective and strategy for comprehensively advancing myopia prevention and control among children and adolescents.

ObjectiveTo investigate the preventive and therapeutic effects of Qingfei Paidu decoction (QFPDD) on acute lung injury (ALI) in mice and its underlying molecular mechanisms based on miRNA sequencing technology. MethodsTwenty-four 4-week-old male KM mice were randomly divided into a control group, a model group, and a QFPDD group (n = 8 per group). After one week of acclimatization, mice in the control and model groups were intragastrically administered ultrapure water (0.2 mL per dose), whereas mice in the QFPDD group were intragastrically administered QFPDD (1.6 g crude drug/mL, 0.2 mL per dose), twice daily for 8 consecutive days. On days 2–8, mice in the model and QFPDD groups were exposed to aerosolized lipopolysaccharide (LPS) solution (2.5 g/L, 4 mL per exposure) for 7 consecutive days. On day 9, blood was collected via the retro-orbital venous plexus under deep anesthesia, and lung tissues were harvested. Body weight and lung weight were measured, and the lung coefficient was calculated. Serum levels of inflammatory cytokines tumor necrosis factor-α (TNF-α), interleukin (IL)-1β, and IL-6 were detected by ELISA. Lung histopathological changes were observed by HE staining of paraffin-embedded sections. miRNA expression profiles in lung tissues were analyzed using the Illumina HiSeq 2500 sequencing platform. Target genes of differentially expressed miRNAs were predicted using bioinformatics databases, and functional enrichment analysis of these target genes was performed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases. Differentially expressed miRNAs were validated by reverse transcription quantitative real-time PCR (RT-qPCR). ResultsCompared with the control group, the model group showed a consistent body weight growth trend but a significantly increased lung coefficient (P < 0.01). ELISA results showed that serum levels of TNF-α and IL-6 were significantly elevated in the model group compared with the control group (P < 0.01), whereas QFPDD treatment significantly reduced serum TNF-α and IL-6 levels compared with the model group (P < 0.05). HE staining showed that, compared with the control group, the model group exhibited widened alveolar septa, massive inflammatory cell infiltration, partial alveolar expansion, and mild capillary dilation with congestion. In contrast, the QFPDD group showed only slightly widened alveolar septa and mild inflammatory cell infiltration compared with the model group. Intersection analysis of miRNA sequencing data identified 13 differentially expressed miRNAs common to both the model vs. control and QFPDD vs. model comparisons. Among them, 6 miRNAs (mmu-miR-203-3p, mmu-miR-181b-5p_R-1, hsa-miR-4286_R+1, mmu-miR-1843b-5p_L+1R-1_2, mmu-miR-22-3p, and mmu-miR-1964-3p) were significantly up-regulated in the model group (P < 0.05) and significantly down-regulated after QFPDD treatment (P < 0.05), showing a therapeutic reversal trend. GO analysis revealed that the target genes of the differentially expressed miRNAs were mainly enriched in biological processes such as RNA polymerase Ⅱ transcriptional regulation. KEGG analysis indicated that target genes were mainly enriched in signaling pathways including the mitogen-activated protein kinase (MAPK) pathway. RT-qPCR validation result for mmu-miR-203-3p was consistent with the sequencing analysis results. ConclusionQFPDD may exert preventive and therapeutic effects against ALI by regulating the expression of mmu-miR-203-3p and other miRNAs, thereby modulating inflammatory responses and the MAPK signaling pathway and participating in the pathological process of lung injury.

Objective: To explore the consistency between self perceived body size and body mass index (BMI) evaluation among medical students, and analyze their association with depressive symptoms, so as to provide scientific evidence for psychological intervention targeting medical students. Methods: From September to November 2022, a convenient cluster sampling method was employed to select 1 850 college students from two universities in Hefei, Anhui Province, and Nanjing, Jiangsu Province. The Patient Health Questionnaire-9 (PHQ-9) was used to assess their depressive symptoms. Chi-square test was applied to compare the rates of depressive symptoms among medical students with different demographic characteristics. Kappa consistency test was performed to evaluate the consistency between self-perceived body size and BMI evaluation. Generalized linear models with binomial distribution and Logit link were constructed to analyze the associations of self-perceived body size and consistency between self-rated and BMI evaluation with depressive symptoms, as well as gender differences in these associations. Results: A total of 40.7 % of medical students overestimated or underestimated their body size. Specifically, the underestimation rate was 20.5% in males and 4.9 % in females, while the overestimation rate was 12.7% in males and 40.5% in females, the distribution of consistency in the misclassification rate of body self-perception between males and females was statistically significant ( χ 2=221.54, P ＜0.01). The overall consistency between self perceived body size and BMI evaluation was low for both males and females, with Kappa values of 0.518 and 0.281 respectively (both P <0.01). After adjusting for confounding variables, generalized linear model analyses showed that medical students with self perceived obesity and body size overestimation had higher risks of depressive symptoms ( OR =1.62, 1.26, both P ＜0.05). Stratified analyses by gender revealed that girls with self perceived overweight and obesity had higher risks of depressive symptoms in female students ( OR =1.43, 1.66, both P <0.05), whereas no statistically significant associations among boys ( OR =0.84, 1.86, both P >0.05). Girls with body size overestimation had a higher risk of depressive symptoms ( OR=1.20, P ＜ 0.05), with no significant association in boys ( OR=1.00, P >0.05). Conclusions Differences exist related between self perceived body size and BMI evaluation among medical students. Self perceived obesity and body size overestimation are related factors to depressive symptoms.

Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

This article discusses the revision background and core content of 9621 General Requirements for Phar-maceutical Packaging Materials and Containers in the Chinese Pharmacopoeia 2025 Edition.In combination with the requirements of bundling review of pharmaceutical packaging and drug products,as well as harmonization of inter-national standards,it analyzed the revision philosophy of the new guideline and the impact to industry.The new edition of the guideline 9621 introduces the concept of "pharmaceutical packaging system" for the first time,constructing four suitability evaluation dimensions covering protection,compatibility,safety,and functionality,it also introduces the requirements for the self-stability evaluation of plastic and rubber pharmaceutical packaging materials,and strengthening the concept of full lifecycle management and risk management.Through the"1+4+58" standard system,the basis for determining the key quality attributes of packaging materials for phar-maceutical use and the optimization path of dynamic inspection rules have been clarified.This revision has resolved the contradiction between the old version of standards and current regulatory requirements through a systematic upgrade,promoting the transformation of pharmaceutical packaging materials and containers quality control towards a scientific,international,and full lifecycle management model,proving technical supports in ensuring the safety,effectiveness of drug products from standard perspective,including advancing the industry high-quality development.

Ovarian cancer poses a significant threat to women's health, necessitating effective therapeutic strategies. Emd-D, an emodin derivative, demonstrates enhanced pharmaceutical properties and bioavailability. In this study, Cell Counting Kit 8 (CCK8) assays and Ki-67 staining revealed dose-dependent inhibition of cell proliferation by Emd-D. Migration and invasion experiments confirmed its inhibitory effects on OVHM cells, while flow cytometry analysis demonstrated Emd-D-induced apoptosis. Mechanistic investigations elucidated that Emd-D functions as an inhibitor by directly binding to the glycolysis-related enzyme PFKFB4. This was corroborated by alterations in intracellular lactate and pyruvate levels, as well as glucose transporter 1 (GLUT1) and hexokinase 2 (HK2) expression. PFKFB4 overexpression experiments further supported the dependence of Emd-D on PFKFB4-mediated glycolysis and SRC3/mTORC1 pathway-associated apoptosis. In vivo experiments exhibited reduced xenograft tumor sizes upon Emd-D treatment, accompanied by suppressed glycolysis and increased expression of Bax/Bcl-2 apoptotic proteins within the tumors. In conclusion, our findings demonstrate Emd-D's potential as an anti-ovarian cancer agent through inhibition of the PFKFB4-dependent glycolysis pathway and induction of apoptosis. These results provide a foundation for further exploration of Emd-D as a promising drug candidate for ovarian cancer treatment.
Female ; Humans ; Ovarian Neoplasms/physiopathology* ; Phosphofructokinase-2/genetics* ; Apoptosis/drug effects* ; Glycolysis/drug effects* ; Animals ; Cell Line, Tumor ; Mice ; Cell Proliferation/drug effects* ; Emodin/administration & dosage* ; Mice, Nude ; Mice, Inbred BALB C ; Hexokinase/metabolism* ; Xenograft Model Antitumor Assays

Objective:To develop and validate a prediction model for medication adherence among patients receiving allergen sublingual immunotherapy (SLIT).Methods:A prospective cross-sectional study was conducted, and a total of 288 patients who received SLIT treatment at an allergy center in the First Affiliated Hospital with Nanjing Medical University (Jiangsu Province Hospital) from December 2023 to July 2024 were assigned to the modeling group. Additionally, 122 patients from August to October 2024 were assigned to the validation group. Data of patients′ general information, medication beliefs, anxiety levels, social support, disease perception, and medication adherence were collected. Single-factor analysis and LASSO regression were utilized to identify potential predictors, and a prediction model for medication adherence was constructed using multifactorial logistic regression. A nomogram was then developed based on the model. The model′s discriminatory ability was evaluated using receiver operating characteristic curve (ROC), the area under curve (AUC), sensitivity, and specificity. The model was then validated in the validation cohort.Results:Single-factor analysis and LASSO regression identified a total of nine predictive factors. Logistic regression revealed that medical belief tendency [ OR (95% CI) =2.420 (1.116-5.248), P=0.025], the somatic control dimension in self-rating anxiety scales [ OR (95% CI)=1.404 (1.241-1.589), P<0.001], the subjective support dimension in social support assessment [ OR (95% CI)=0.784 (0.725-0.847), P<0.001], and the cognitive dimension in illness perception [ OR (95% CI)=0.725 (0.647-0.813), P<0.001] were independent predictors of medication adherence in patients undergoing SLIT. The AUC value of the model was 0.899 (95% CI=0.863-0.934) in the modeling group and 0.882 (95% CI=0.820-0.944) in the validation group, indicating good discriminatory ability. The optimal cutoff value of the model was 0.493, with a sensitivity of 81.1% and specificity of 85.7% in the modeling group, and a sensitivity of 87.3% and specificity of 82.5% in the validation group. Conclusion:The medication adherence prediction model developed in this study for patients undergoing SLIT exhibits good predictive performance and provides valuable guidance for early intervention by clinical healthcare professionals.

Objective:To develop an ultrasound multi-view fusion recognition model and evaluate its clinical value in diagnosing fetal conotruncal defects (CTD).Methods:This prospective study collected cardiac ultrasound images from fetuses at 20-32 weeks of gestation undergoing prenatal ultrasound at Dongguan Maternal and Child Health Hospital between September 2022 and May 2024. The case group comprised fetuses diagnosed with CTD, while controls with normal cardiac structures were collected at a 1∶2 ratio. Both groups were divided into modeling training and validation sets at a 3∶1 ratio. One optimal standard image each from the four-chamber view, left ventricular outflow tract view, right ventricular outflow tract view, and three vessels and trachea view was included per fetus. A deep learning-based multi-view fusion recognition model was developed to differentiate normal conotruncal anatomy from CTD. Model performance was validated against post-abortion pathology or postnatal echocardiography results. SAS software was used for statistical analysis to calculate the sensitivity and specificity of three fusion models (based on positivity in any two, three, or four views, and were designated as Fusion Model 1, Fusion Model 2, and Fusion Model 3, respectively), with the optimal model determined by the maximum Youden index. Senior, intermediate, and junior prenatal sonologists independently diagnosed cases in the validation set under blinding conditions. Their diagnostic results were compared with those of the optimal model. Paired Chi-square test (Cochran's Q test) was employed to compare the differences between the diagnostic accuracy rates of sonologists at different experience levels and the sensitivity of the optimal model, thereby analyzing the auxiliary diagnostic value of the multi-view fusion recognition model. Results:The study included 88 CTD cases, excluding six cases (non-CTD diagnosed by post-abortion pathology or postnatal echocardiography or poor image quality), divided into 60 training and 22 validation cases (12 tetralogy of Fallot, four double outlet right ventricle, three transposition of great arteries, three persistent truncus arteriosus). The control group included 176 cases, excluding 15 cases (other cardiac abnormalities confirmed postnatally or poor image quality after re-evaluation), divided into 120 training and 41 validation cases. The sensitivities of Fusion Model 1, Fusion Model 2, and Fusion Mudel 3 were 0.86, 0.64, and 0.27, while their specificities were 0.76, 0.95, and 1.00, respectively. Fusion Model 1 demonstrated the highest Youden index (0.62) and was selected as optimal. Its diagnostic sensitivity showed no significant difference from senior sonologists [86% vs. 91% (20/22), Bonferroni-corrected P>0.999], but was significantly higher than intermediate [55% (12/22), Bonferroni-corrected P=0.049] and junior sonologists [32% (7/22), Bonferroni-corrected P=0.003]. Conclusion:The deep learning multi-view fusion model achieved diagnostic performance comparable to senior sonologists, demonstrating potential value in assisting CTD diagnosis, training less experienced sonologists, and supporting research and education.

Objective:To explore the value of a model based on 18F-FDG PET/CT radiomics features in assessing the prognosis of patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer undergoing neoadjuvant targeted chemotherapy. Methods:This retrospective analysis included 132 female patients (age (50±11) years) diagnosed with HER2-positive breast cancer who underwent 18F-FDG PET/CT prior to treatment between January 2016 and August 2022 in Tianjin Medical University Cancer Institute and Hospital. Data were split into training (105 cases) and validation (27 cases) cohorts using stratified sampling (8∶2). Clinical pathological data and progression-free survival (PFS) were recorded. PET and CT images were annotated for lesion delineation and radiomics features extraction. The least absolute shrinkage and selection operator (LASSO) algorithm was used to select features in the training cohort, and the radiomics score (Rad-score) was calculated. Cox proportional hazards regression analysis was performed to identify risk factors for PFS. A nomogram model was constructed, and the concordance index (C-index) was calculated to assess predictive performance. Results:Univariate Cox regression showed that N stage (hazard ratio ( HR)=2.36, 95% CI: 1.04-5.37, P=0.040) and Rad-score ( HR=14.50, 95% CI: 3.39-62.13, P<0.001) were related to PFS in patients with HER2-positive breast cancer after neoadjuvant therapy. Multivariate analysis indicated the Rad-score as an independent risk factor for PFS ( HR=13.32, 95% CI: 3.10-57.20, P<0.001). The nomogram model combining N stage and Rad-score predicted PFS more accurately than the Rad-score model alone, with C-indexes of 0.80 vs 0.74 in the training cohort, and 0.77 vs 0.71 in the validation cohort. Conclusions:Radiomics based on pre-treatment 18F-FDG PET/CT can predict PFS in patients with HER2-positive breast cancer undergoing neoadjuvant targeted chemotherapy. The nomogram model combining radiomics features and clinical risk factor improves prognostic prediction.

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.