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.

This study employed the "disease-medicine-dose" pattern to mine the medication rules of traditional Chinese medicine(TCM) prescriptions containing Astragali Radix in ancient Chinese medical books, aiming to provide a scientific basis for the clinical application of Astragali Radix and the development of new medicines. The TCM prescriptions containing Astragali Radix were retrieved from databases such as Chinese Medical Dictionary and imported into Excel 2020 to construct the prescription library. Statical analysis were performed for the prescriptions regarding the indications, syndromes, medicine use frequency, herb effects, nature and taste, meridian tropism, dosage forms, and dose. SPSS statistics 26.0 and IBM SPSS Modeler 18.0 were used for association rules analysis and cluster analysis. A total of 2 297 prescriptions containing Astragali Radix were collected, involving 233 indications, among which sore and ulcer, consumptive disease, sweating disorder, and apoplexy had high frequency(>25), and their syndromes were mainly Qi and blood deficiency, Qi and blood deficiency, Yin and Yang deficiency, and Qi deficiency and collateral obstruction, respectively. In the prescriptions, 98 medicines were used with the frequency >25 and they mainly included Qi-tonifying medicines and blood-tonifying medicines. Glycyrrhizae Radix et Rhizoma, Angelicae Sinensis Radix, Ginseng Radix et Rhizoma, Atractylodis Macrocephalae Rhizoma, and Citri Reticulatae Pericarpium were frequently used. The medicines with high frequency mainly have warm or cold nature, and sweet, pungent, or bitter taste, with tropism to spleen, lung, heart, liver, and kidney meridians. In the treatment of sore and ulcer, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to promote granulation and heal up sores. In the treatment of consumptive disease, Astragali Radix was mainly used with the dose of 37.30 g and combined with Ginseng Radix et Rhizoma to tonify deficiency and replenish Qi. In the treatment of sweating disorder, Astragali Radix was mainly used with the dose of 3.73 g and combined with Glycyrrhizae Radix et Rhizoma to consolidate exterior and stop sweating. In the treatment of apoplexy, Astragali Radix was mainly used with the dose of 7.46 g and combined with Glycyrrhizae Radix et Rhizoma to dispell wind and stop convulsions. Astragali Radix can be used in the treatment of multiple system diseases, with the effects of tonifying Qi and ascending Yang, consolidating exterior and stopping sweating, and expressing toxin and promoting granulation. According to the manifestations of different diseases, when combined with other medicines, Astragali Radix was endowed with the effects of promoting granulation and healing up sores, tonifying deficiency and Qi, consolidating exterior and stopping sweating, and dispelling wind and replenishing Qi. The findings provide a theoretical reference and a scientific basis for the clinical application of Astragali Radix and the development of new medicines.
Drugs, Chinese Herbal/history* ; Humans ; Medicine, Chinese Traditional/history* ; History, Ancient ; Astragalus Plant/chemistry* ; China ; Astragalus propinquus

Obesity is a significant risk factor for cancer and is associated with breast cancer metastasis. Nevertheless, the mechanism by which alterations in systemic metabolism affect tumor microenvironment (TME) and consequently influence tumor metastasis remains inadequately understood. Herein, we found that perturbations in circulating metabolites induced by obesity promote metastasis-like phenotypes in breast cancer. Oleoylcarnitine (OLCarn) concentrations were elevated in the serum of obese mice and humans. Administration of exogenous OLCarn induces metastasis-like characteristics in breast cancer cells. Mechanistically, OLCarn directly interacts with the Arg176 site of adenylate cyclase 10 (ADCY10), leading to the activation of ADCY10 and enhancement of cAMP production. Mutations at Arg176 prevent OLCarn from binding to ADCY10, disrupting the ADCY10-mediated activation of cyclic adenosine monophosphate (cAMP) signaling pathway. This activation promotes transcription factor 4 (TCF4)-dependent kinesin family member C1 (KIFC1) transcription, thereby driving breast cancer metastasis. Conversely, the neutralization of both ADCY10 and KIFC1 through knockdown or pharmacological inhibition abrogates the oncogenic effects mediated by OLCarn. Hence, obesity-induced systemic environmental changes lead to the aberrant accumulation of OLCarn within the TME, making it a potential therapeutic target and biomarker for breast cancer.

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.

Objective To describe and analyze the epidemiological characteristics of scrub typhus in Huai'an, Jiangsu Province from 2006 to 2024 and explore the long-term incidence trend and distribution of high-risk areas, and to formulate targeted prevention and control strategies. Methods The scrub typhus case report data of Huai'an from 2006 to 2024 in the Chinese Disease Prevention and Control Information System were extracted for descriptive analysis. Results A total of 898 cases of scrub typhus were reported in Huai'an, with an average annual incidence rate of 0.96 per 100 000 from 2006 to 2024. There was a turning point in the incidence trend of scrub typhus in 2011. From 2006 to 2011, the annual percentage change (APC) was 47.09% (95% CI: 7.53 - 859.39), and the upward trend was statistically significant (P < 0.05). From 2012 to 2024, the APC was -2.12% (95% CI: -29.09 - 3.75), and the downward trend was not statistically significant. October and November were the high-incidence months, and the total concentration from 2006 to 2024 was 0.93, indicating that scrub typhus had strict seasonality. The circular distribution method estimated that the peak period of the epidemic was from October 11th to November 25th, and the peak day of incidence was November 3rd. Jinhu County was a high-incidence area. The ratio of male to female cases was 1.03. The age group with the highest reported incidence was 40 to < 80 years old. The occupation with the highest proportion was farmers, accounting for 78.03%. Conclusion From 2006 to 2024, scrub typhus in Huai'an shows a peak every 3 - 4 years. Middle-aged and elderly farmers are the key population at risk, and Jinhu County is a key area. In the future, targeted health education should be carried out to effectively control the prevalence of scrub typhus.

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 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 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.