ObjectiveTo evaluate the anti-inflammatory activity of the novel magnolol ester derivative YW and to investigate its effects on chondrocyte senescence and preliminary mechanisms. MethodsMagnolol and p-methylbenzoic acid were used as raw materials to synthesize the magnolol ester derivative YW （Molecular Formula： C₂₆H₂₄O₃， Molecular Weight： 384.17， HPLC Purity >96%） via DCC/DMAP-catalyzed esterification. Cytotoxicity was assessed using the CCK-8 assay. A lipopolysaccharide （LPS）-induced RAW264.7 macrophage activation model and an interleukin-1β （IL-1β）-induced rat primary chondrocyte model were established. The release and mRNA expression of inflammatory factors including nitric oxide （NO）， IL-1β， tumor necrosis factor-alpha （TNF-α）， and IL-6 were detected by enzyme-linked immunosorbent assay （ELISA）， Griess reagent method， and quantitative real-time PCR （RT-qPCR）. The expression of senescence markers such as inducible nitric oxide synthase （iNOS）， pro-interleukin-1β （pro-IL-1β）， lysine acetyltransferase 7 （KAT7）， cyclin-dependent kinase inhibitor 1A （p21）， and cyclin-dependent kinase inhibitor 2A （p16）， as well as proteins related to chondrocyte extracellular matrix synthesis and catabolism， were analyzed by Western blot （WB）. Molecular docking was performed using Discovery Studio 2019 to validate target binding. ResultsYW exhibited no significant cytotoxicity at concentrations ≤20 μmol/L. YW concentration-dependently inhibited LPS-induced macrophage inflammatory cytokine release， significantly downregulated iNOS， Pro-IL-1β protein， and inflammatory cytokine mRNA expression （P<0.01）. YW stably bound to KAT7 protein （binding energy： -94.2 kcal/mol）； YW downregulated KAT7 and aging marker protein expression in naturally aged and IL-1β-induced chondrocyte models （P<0.01）； YW regulated chondrocyte matrix synthesis and catabolic protein expression in IL-1β-induced chondrocytes （P<0.01）. ConclusionYW inhibits macrophage activation and inflammatory cytokine release while downregulating KAT7 and senescence marker protein expression in chondrocytes， thereby blocking chondrocyte senescence.

ObjectiveTo explore the effects of vascular endothelial growth factor A （VEGFA） rs2010963 and rs3025039 polymorphisms on chemotherapy toxicities and clinical prognosis in children with brain tumors. MethodsA total of 104 pediatric patients with brain tumors receiving standardized chemotherapy were enrolled. Matrix-assisted laser desorption/ionization time of flight mass spectrometry was used for VEGFA rs2010963 and rs3025039 genotyping. The χ² test was applied to analyze the association between genotypes and chemotherapy‑related toxicities. Cox regression was used to evaluate the correlations of clinicopathological characteristics and genotypes with the progression‑free survival （PFS）. In addition， bioinformatic analyses were conducted to investigate the regulatory factors potentially affected by the two SNP loci. ResultsThe VEGFA expression in brain tumors （5.17±1.81） was significantly higher than that in normal tissues （4.33±1.56， P<0.001）. Patients with high VEGFA expression had significantly worse overall survival than patients with low VEGFA expression （P<0.001）. Among the 104 children with brain tumors included， the rs2010963 CC， CG， and GG genotypes accounted for 14.42%， 55.77%， and 29.81%， respectively. The frequencies of C and G alleles were 42.31% and 57.69%， respectively. The rs3025039 CC， CT， and TT genotypes accounted for 70.19%， 25.96%， and 3.85%， respectively. The frequencies of C and T alleles were 83.17% and 16.83%， respectively. The children with the rs3025039 CC genotype had significantly higher incidences of thrombocytopenia （46.58%） and gastrointestinal toxicity （56.16%） than CT genotype carriers （22.22% and 33.33%， respectively， P<0.05）， and significantly lower incidences of coagulation disorders （4.11%） than TT genotype carriers （50.00%， P<0.05）.The incidence of hyperlipidemia （2.74%） was significantly lower than that in the CT genotype carriers （14.82%， P<0.05）. The tumor type and the rs2010963 genotype were significantly associated with PFS （P<0.05） in univariable and multivariable Cox regression analysis. Bioinformatic analysis indicated that the rs2010963 and rs3025039 polymorphisms regulated VEGFA expression by affecting the binding of transcription factors and miRNAs to their target gene sequences， respectively. ConclusionThe VEGFA rs3025039 CC genotype is a risk factor for thrombocytopenia and gastrointestinal toxicity， and a protective factor for coagulation disorders and hyperlipidemia. The rs2010963 CG genotype is a protective factor for brain tumor progression.

ObjectiveTo analyze the effects of the progestin-primed ovarian stimulation （PPOS） protocol on embryo euploidy rate and clinical pregnancy outcomes in infertile patients. MethodsWomen who underwent Preimplantation genetic testing for aneuploidy （PGT-A） cycles were selected as study participants （a total of 656 cycles and 3 081 blastocysts）. Participants were divided into two age groups （≤35 years and >35 years） and further stratified by ovarian stimulation protocol： the Progestin-Primed Ovarian Stimulation （PPOS） group （n=48 and 60， respectively）， the Luteal Phase Long Protocol （LP） group （n=160 and 57， respectively）， and the Gonadotropin-Releasing Hormone Antagonist Protocol （AP） group （n=220 and 111， respectively）. Baseline characteristics， ovarian stimulation outcomes， and embryo development parameters were compared among the three protocols within each age group. Additionally， clinical pregnancy outcomes of the first frozen embryo transfer （FET） cycle were compared. The primary outcome measure was the embryo euploidy rate. Results① In the ≤35 years age group， baseline follicle-stimulating hormone （bFSH） levels were significantly higher in the PPOS group compared to the LP and AP groups， and the bFSH/bLH ratio was significantly higher in the PPOS group than in the AP group （P < 0.05）. In the >35 years age group， bFSH levels in both the PPOS and AP groups were significantly higher than in the LP group （P < 0.05）.② In the ≤35 years group， there were no significant differences in the rates of metaphase II （MII） oocytes， 2-pronuclei （2 PN） zygotes， cleavage， 2 PN cleavage， blastocyst formation， high-quality embryos， or embryo euploidy between the PPOS group and either the LP or AP groups. However， the PPOS group showed significantly lower values for the following parameters compared to the other two groups： total oocytes retrieved， number of MII oocytes， number of 2 PN zygotes， number of cleaved embryos， number of 2 PN cleaved embryos， number of blastocysts formed， number of high-quality embryos， number of high-grade blastocysts， number of transferable embryos， number of cryopreserved embryos， number of biopsied blastocysts， number of euploid embryos， and the rate of obtaining at least one euploid embryo. In the >35 years group， no significant differences were observed among the PPOS， LP， and AP groups in the rates of MII oocytes， 2 PN cleavage， blastocyst formation， or in the number of euploid embryos， euploidy rate， and the rate of obtaining at least one euploid embryo. However， the PPOS group had significantly lower numbers of total oocytes retrieved， MII oocytes， 2 PN zygotes， cleaved embryos， 2 PN cleaved embryos， blastocysts formed， transferable embryos， and cryopreserved embryos compared to the LP group （P<0.05）. The high-quality embryo rate was significantly lower in the PPOS group than in the AP group （P<0.05）. The numbers of high-quality embryos， high-grade blastocysts， and biopsied blastocysts were significantly lower in the PPOS group than in both the LP and AP groups （P<0.05）. Notably， the 2 PN fertilization rate was significantly higher in the PPOS group than in the AP group， and the cleavage rate was significantly higher in the PPOS group than in both the LP and AP groups （P<0.05）.③ No significant differences were found among the three groups in the biochemical pregnancy rate， clinical pregnancy rate， live birth rate， early miscarriage rate， and late miscarriage rate following the first FET cycle. ConclusionCompared to the other two protocols， the PPOS protocol does not significantly affect embryo euploidy or clinical pregnancy rates. However， in freeze-all cycles with PGT-A， the PPOS protocol does not reduce the rate of chromosomally normal embryos but may decrease the total number of available embryos. It may not be the optimal choice for younger women， but it can be considered as a viable option for women of advanced maternal age.

With the continuous deepening of the concept of precision diagnosis and treatment for lung cancer, how to achieve higher efficiency and accuracy in the screening, diagnosis, and treatment pathways in clinical practice has become an important issue that urgently needs to be overcome. The current clinical difficulty lies in the fact that despite continuous advancements in imaging and molecular diagnostic technologies, there are still limitations in manual efficiency and subjective experience when it comes to massive data analysis and multi-scale feature extraction. Artificial intelligence (AI), especially algorithm systems based on deep learning, is an innovative technology capable of deeply empowering medical big data. This method utilizes algorithms such as convolutional neural networks, combined with radiomics, pathomics, and multi-modal data fusion analysis, demonstrating immense potential in early precise detection and benign-malignant differentiation of pulmonary nodules, digital pathological subtype recognition and non-invasive prediction of driver genes, precise 3D surgical planning and automatic delineation of radiotherapy target volumes, as well as dynamic risk warning during follow-up. This innovative technology provides a brand-new solution for realizing intelligent and individualized lung cancer diagnosis and treatment models. This consensus, based on the latest evidence from evidence-based medicine and combined with the development trends in the AI field and real-world clinical needs, was ultimately formed by gathering the consensus opinions of multidisciplinary experts in radiology, pathology, thoracic surgery, and other fields. The main content covers the application specifications of AI in the three core scenarios of lung cancer screening, diagnosis, and treatment, the technical standards for data collection and algorithm validation, as well as the ethical and regulatory challenges faced at the current stage. It aims to clarify the applicable boundaries of AI as a clinical auxiliary decision support tool, providing scientific guidance and standardized exploration directions for peers currently engaged in or planning to carry out AI-assisted clinical diagnosis, treatment, and translation of lung cancer.

Objective: To examine the characteristics of physical activity among secondary vocational school students and its associations with depressive symptoms, anxiety symptoms, and their co-existence, so as to provide evidence for promoting their mental health. Methods: From September to December 2024, a questionnaire survey was conducted on 5 141 secondary vocational school students using convenience sampling method across 16 secondary vocational schools in 8 provinces/municipalities, including Fujian, Chongqing, Guangdong, Guangxi, Hubei, Jiangxi, Shanghai and Zhejiang. A self designed questionnaire, International Physical Activity Questionnaire Short Form, Patient Health Questionnaire-9 and Generalized Anxiety Disorder Scale-7 were used to assess basic information, physical activity characteristics, and depressive and anxiety symptoms. Chi-square test and Logistic regression model were used to analyze the associations of physical activity characteristics with depressive symptoms, anxiety symptoms, and their co-existence. Results: Among secondary vocational school students, 22.2% had depressive symptoms, 12.2% had anxiety symptoms, and 10.5% had both conditions. After adjustment for confounding factors such as sex, grade, and family structure, Logistic regression analyses showed that a high physical activity level, meeting the recommendation for daily moderate to vigorous physical activity (MVPA), and a concentrated physical activity pattern were associated with lower odds of depressive symptoms, anxiety symptoms, and their co-existence ( OR =0.70-0.81, all P <0.05). Regular weekly MVPA and a regular physical activity pattern were associated only with lower odds of depressive symptoms ( OR =0.79, 0.70, both P <0.05). Sex stratified analyses showed that meeting the recommendation for daily MVPA and a concentrated physical activity pattern were associated with lower odds of depressive symptoms, anxiety symptoms, and their co-existence among boys ( OR =0.60-0.71); a high physical activity level, regular weekly MVPA, and a regular physical activity pattern were associated with lower odds of depressive symptoms among boys ( OR =0.65-0.78)(all P <0.05). Meanwhile, a high physical activity level, meeting the recommendation for daily MVPA, regular weekly MVPA, and regular and concentrated physical activity patterns were associated with lower odds of depressive symptoms in female students ( OR =0.72-0.79) (all P <0.05). Conclusions Physical activity characteristics are associated with depressive symptoms, anxiety symptoms, and their co-existence among secondary vocational school students. Schools should optimize physical activity promotion strategies according to sex specific characteristics to reduce the occurrence of depressive and anxiety symptoms among secondary vocational school students.

Objective: To explore the association role of anxiety and depressive symptoms with Internet gaming disorder (IGD) and emotional-behavioral problems among junior high school students, so as to provide references for preventing the occurrence and progression of emotional-behavioral problems in middle school students. Methods: From September to October 2024, a random cluster sampling method was adopted to select 38 069 students from 28 junior high schools in 14 counties (cities and districts) and functional areas of Jining City, Shandong Province. Surveys were conducted by Nine item Internet Gaming Disorder Scale-Short Form, Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, and Strengths and Difficulties Questionnaire. The correlation of emotional and behavioral issues, online game addiction, anxiety and depressive symptoms among junior high school students was analyzed by Speaman correlation analysis. Mediation analysis was used to explore the role of anxiety and depressive symptoms between IGD and emotional-behavioral problems among junior high school students. Results: The detection rates of emotional-behavioral problems, anxiety symptoms, depressive symptoms, and IGD among junior high school students were 19.24 %, 9.48%, 16.69%, and 19.68%, respectively. The scores of emotional-behavioral problems, anxiety symptoms, depressive symptoms and IGD were 10.00 (6.00, 15.00), 3.00 (0.00, 7.00), and 4.00 (1.00, 8.00), 13.00 (10.00, 19.00), respectively. There were positive correlations between each pair of emotional-behavioral problem, IGD, anxiety symptoms, and depressive symptoms scores ( r =0.51-0.81, all P <0.01). Anxiety and depressive symptoms played mediating roles between IGD and emotional-behavioral problems among junior high school students, with mediating effect values of 0.16 (95% CI =0.15-0.17) and 0.12 (95% CI =0.11-0.14), respectively (both P <0.01). Conclusions Anxiety and depressive symptoms mediate the relationship between IGD and emotional-behavioral problems among junior high school students. It is necessary to identify early signs of IGD among junior high school students, strengthen intervention for anxiety and depressive symptoms, to prevent the occurrence and development of emotional and behavioral issues.

Objective: To explore the related factors of college students social network addiction based on problem behavior theory, so as to provide a basis for improving social networking addiction in this population. Methods: From May to June 2023, a method combining convenient sampling and cluster random sampling was used to select 1 768 college students from five universities in Shanghai for a questionnaire survey on social networking addiction, self esteem, loneliness, depressive symptoms, social support, interpersonal needs, sense of distress and frustration; at the same time, the physical exercise, smoking and drinking of college students were investigated. Multivariate Logistic regression analysis was applied to explore the association between the three systems of the problem behavior theory (personality, behavior, and social environment) and social networking addiction among college students. Results: The score on the Social Network Addiction Tendency Scale was (21.08±6.29) among college students, and the detection rate of social networking addiction was 66.29%. After adjusting for gender, family economic status, parental divorce status, and whether being an only child, multivariate Logistic regression analysis showed that in the personality system, higher loneliness ( OR =1.66) and higher depressive symptoms ( OR =2.18) were associated with increased risk of social networking addiction among college students; in the behavior system, alcohol consumption ( OR =1.42) was associated with higher risk of soical networking addiction compared to non drinkers; and in the social environment system, low social support ( OR =1.43) was associated with increased risk of social networking addiction (all P <0.05). Conclusions The rate of social networking addiction among college students is relatively high, and the systems of personality, behavior, and social environment are all related to social network addiction. Providing social support, cultivating healthy lifestyle habits, and increasing interpersonal interactions may help reduce excessive dependence on social networking among college students.

This study aimed to design and synthesize a series of novel photocaged compounds based on the precise binding mode of cyclin-dependent kinase 2 (CDK2) inhibitor AT7519 with its target, to achieve precise optical control over molecular activity. Using AT7519 as the structural foundation, different types of photoremovable protecting groups were introduced at its key interaction sites (the NH of the pyrazole ring and the NH of the piperidine ring), resulting in the synthesis of eight dual-photocaged compounds. Their structures were confirmed by NMR and mass spectrometry, and their photochemical properties—including photolysis wavelength, photolysis time, and photolysis efficiency—were systematically evaluated. The optically controlled inhibitory effects of the compounds on HCT116 cell proliferation were assessed using MTT assay. The photoresponsive characteristics of the photocaged compounds were significantly influenced by the type of photoremovable protecting group and its introduction site. Among them, compounds 1a, 1b, and 2d exhibited excellent photolysis efficiency, each achieving a rate exceeding 90%. Particularly, compounds 1b and 2d demonstrated excellent optically controlled activity: under dark conditions, their half maximal inhibitory concentration (IC50) values were both greater than 150 µmol/L, indicating negligible cell proliferation inhibitory activity; however, upon irradiation, their cell proliferation inhibitory activity significantly increased, with IC50 values comparable to those of the positive control AT7519. The obtained compounds 1b and 2d possess excellent optically controlled properties, and can be further investigated as potential candidates for optically controlled CDK2 inhibitors.

Objective To systematically evaluate the risk prediction models for acute kidney injury in patients with acute coronary syndrome (ACS) based on machine learning, providing a reference for clinical selection of appropriate risk assessment tools. Methods Clinical studies using machine learning methods for predicting the risk of acute kidney injury in ACS patients were retrieved from PubMed, Cochrane Library, Embase, Web of Science core database, CNKI, Wanfang Database, CBM, and VIP. The retrieval time was from the establishment of the database to May 24, 2025. The quality of the models were evaluated using the prediction model risk of bias assessment tool. Results Nine articles were included, and a total of 58 prediction models were constructed using 20 machine learning methods. The area under the receiver operating characteristic curve ranged from 0.733 to 0.894. The most commonly used predictors were age and creatinine. The overall bias risk of the included studies was relatively high, but the applicability was good.Conclusion Machine learning models can identify the risk of acute kidney injury in ACS patients. All models have good predictive potential, but they are still in the development stage. It is recommended that future studies adopt prospective design with external validation to improve the stability and predictive accuracy of the models.

Digital transformation is reshaping disease monitoring. We assessed the real-world utility of linking hospital information systems with the foodborne disease surveillance network in Shenzhen. Analysing data from 53 sentinel hospitals (2024–2025) and surveying 263 staff members, we found that integration triggered a 125% surge in case reports. However, regional performance varied sharply (Nanshan +161% vs Pingshan -44%), and personnel training frequency remained low (3.08/5). While automation solves the volume problem, it exposes a technology capacity gap that requires urgent human-centric intervention.