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.

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 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.

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.

Background/Aims: Liver transplantation (LT) following total hepatectomy is a life-saving treatment for hepatocellular carcinoma (HCC). The HCC recurrence after LT hinders the effectiveness of the procedure. The objective of this study is to develop a pre-operative risk stratification model based on a liquid biopsy. Methods: We conducted a comprehensive multi-omics study of 260 HCC patients from three centers, including clinical data, low-coverage whole-genome sequencing of cell-free DNA (cfDNA) from plasma, as well as whole-exome, single-nucleus RNA, and spatial transcriptomics from matched tumor and non-tumor tissues. Results: We identified cfDNA-derived copy number alteration (CNA) signatures associated with post-transplant recurrence. By integrating cfDNA-derived CNA profiles with single-cell transcriptomic data, we traced recurrence-associated cfDNA to a distinct subpopulation of malignant cells within the primary tumor. These cells were embedded in a pro-metastatic microenvironment of specialized endothelial subtypes and cancer-associated fibroblasts. Notably, most recurrence-associated lesions were detectable in cfDNA prior to liver transplantation (LT). Building on these insights, we developed the ZJU Criteria based on CNA fragments and tumor markers, a pre-LT risk prediction tool that integrates conventional clinical factors with cfDNA-derived CNA signatures, and validated it using internal and independent external cohorts. Conclusion Our findings suggest that post-transplant recurrence commonly originates from advanced subclones that emerge late during tumor evolution. The ZJU Criteria provides an accurate, non-invasive strategy that significantly improves pre-LT risk stratification and clinical decision-making for patients with HCC.

Postoperative cognitive dysfunction (POCD) is a clinically significant complication in elderly patients, largely driven by surgery-induced neuroinflammation. The cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) pathway, a crucial regulator of innate immunity, has been implicated in neuroinflammatory activation. This study investigated whether electroacupuncture (EA) improves POCD by modulating this pathway in aged rats. Aged male Sprague-Dawley rats were subjected to sevoflurane anesthesia and splenectomy to establish a POCD model. Animals were divided into sham, POCD, POCD+EA, and POCD+EA+cGAS inhibitor groups. The EA groups received stimulation at Baihui (Governor Vessel 20 (GV20)), Neiguan (Pericardium 6 (PC6)), and Zusanli (Stomach 36 (ST36)) acupoints. Cognitive function was evaluated using the Morris water maze, while hippocampal expression of cGAS-STING pathway components and downstream effectors—interferon regulatory factor 3 (IRF3), nuclear factor kappa B (NF-κB), and interleukin-1 beta (IL-1β)—was assessed by Western blot. Cellular localization was determined by immunofluorescence staining. Compared with the Sham group, rats in the POCD group showed significant impairments in spatial memory, accompanied by upregulated protein expression of cGAS, STING, NF-κB, IRF3, and IL-1β in the hippocampus. Upon pathway activation, cGAS and STING proteins were predominantly co-localized with neurons, and their fluorescence intensity in the hippocampus was markedly increased. These behavioral deficits and molecular alterations were partially reversed in both the POCD+EA and POCD+EA+inhibitor groups. Electroacupuncture alleviates POCD in aged rats by inhibiting hippocampal cGAS-STING pathway activation and reducing neuroinflammation, suggesting a promising non-pharmacological strategy for POCD management.

[摘 要] 目的：探讨m6A调控因子在宫颈癌预后评估、免疫微环境特征及治疗反应中的作用，构建基于m6A调控因子的预后风险模型，并分析其与免疫浸润、药物敏感性及细胞间通信的关系。方法：基于TCGA和GEO数据库中宫颈鳞癌及腺癌（CESC）转录组数据，分析22个m6A调控因子的表达与突变情况；采用LASSO‑Cox回归构建m6A相关预后风险模型，并依据风险评分将患者分为高、低风险组。利用CIBERSORT和ESTIMATE算法评估两组免疫细胞浸润及微环境特征；通过oncoPredict预测抗肿瘤药物敏感性。整合单细胞转录组数据（E-MTAB-12305），采用CellChat分析细胞间通信网络。结果：共鉴定出12个在宫颈癌中差异表达的m6A调控因子。高风险组患者总生存期缩短（P < 0.05），免疫评分降低，且对紫杉醇、氟尿嘧啶、多柔比星等抗肿瘤药物敏感性较差（IC50较高）。单细胞分析显示宫颈癌组织中细胞间通信网络发生改变，其中T细胞与内皮/上皮细胞间的相互作用可能主要由CCL5‑ACKR1和MIF‑（CD74 + CXCR4）配体‑受体介导。在临床样本中，对关键的m6A调控因子进行mRNA和蛋白水平的验证，结果显示部分调控因子在宫颈癌组织中的表达水平高于正常宫颈组织（P < 0.05）。结论：m6A调控因子特征可有效预测宫颈癌患者预后，其风险评分与肿瘤免疫浸润、药物敏感性及细胞通信密切相关，为宫颈癌的预后分层及个体化治疗提供了新的分子依据。

ObjectiveTo elucidate the effects of autonomic neuromodulators [calcium chloride (CaCl₂)-acetylcholine (ACh)] on atrial electrical remodeling and histopathological changes in rats, thereby providing evidence for further investigation into the pathological mechanisms by which autonomic imbalance induces atrial fibrillation (AF). MethodsTen 8-week-old male Sprague-Dawley (SD) rats were randomly divided into experimental and control groups, with 5 rats in each group. The experimental group received daily tail vein injections of a CaCl₂-ACh mixed solution for 28 days, while the control group received an equal volume of saline. Surface electrocardiograms were recorded before and after daily administration. On day 28 of administration, under isoflurane inhalation anesthesia, echocardiography was performed, and then the rats were euthanized by exsanguination under isoflurane anesthesia for tissue collection. Body weight and heart weight of rats were measured, and electrophysiological parameters including AF inducibility, conduction velocity, and conduction dispersion in isolated rat hearts were monitored using the MappingLab multichannel electrophysiological mapping system. HE staining was performed to evaluate atrial tissue architecture and inflammatory cell infiltration. The expression levels of matrix metalloproteinase 9 (MMP-9) and interleukin-1 beta (IL-1β) were analyzed by Western blotting. Masson staining was used to quantitatively analyze the proportional distribution of collagen fibers and myocardial fibers, and to calculate the area of collagen deposition, thereby evaluating the degree of myocardial fibrosis. Wheat germ agglutinin (WGA) staining was used to evaluate morphological changes of cardiomyocytes. Dihydroethidium (DHE) staining was used to detect the level of oxidative stress in atrial myocytes. Terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) staining was used to detect atrial cell apoptosis. ResultsCompared with the control group, the experimental group showed obvious arrhythmias on electrocardiograms. Echocardiography after 28 days of administration revealed significant structural remodeling in the experimental group, with a marked increase in left atrial anteroposterior diameter (P < 0.05), and also showed cardiac dysfunction, with significant decreases in left ventricular ejection fraction and left ventricular fractional shortening (P < 0.01). Compared with the control group, the experimental group showed a significantly increased heart weight-to-body weight ratio (P < 0.05), a markedly higher AF inducibility (P < 0.001), a significantly slowed atrial conduction velocity (P < 0.05), an uneven isochronal map with irregular directions, and a significantly increased conduction dispersion (P < 0.01). HE staining showed that atrial myocytes in the experimental group were disorganized, with slight inflammatory cell infiltration. Western blotting showed that the expression levels of MMP-9 and IL-1β in the atrial tissue of the experimental group were significantly upregulated (P < 0.05). Masson staining showed a significant increase in collagen deposition and a significant increase in fibrosis area in the atrial tissue of the experimental group (P < 0.001). WGA staining showed that cardiomyocytes in the experimental group were significantly hypertrophied compared with the control group (P < 0.05). DHE staining and TUNEL staining revealed that the level of oxidative stress in atrial myocytes (P < 0.001) and the apoptotic rate (P < 0.01) were both significantly increased. Conclusion Daily tail vein injections of the autonomic neuromodulator CaCl₂-ACh mixed solution for 28 days can successfully induce AF in rats, accompanied by significant atrial structural remodeling, electrical remodeling, and oxidative stress.

Short-chain fatty acids （SCFA） are the main metabolic products generated by the fermentation of dietary fiber by gut microbiota. Studies have shown that SCFA not only play a role in energy metabolism， but also act as important signaling molecules， exhibiting a significant potential in alleviating liver and pancreatic fibrosis. The core mechanism of SCFA mainly involves the regulation of various key signaling pathways by activating G protein-coupled receptors and inhibiting the activity of histone deacetylase， thereby suppressing the activation and proliferation of hepatic stellate cell （HSC） and pancreatic stellate cell （PSC）， which is a key link in fibrosis formation. In addition， SCFA can effectively alleviate tissue inflammation response， improve intestinal barrier function， and regulate gut microbiota balance， thus indirectly preventing the process of fibrosis mediated by the “gut-liver/pancreas axis”. Compared with the research on SCFA in liver fibrosis， studies on their role in pancreatic fibrosis are limited. Given that HSC and PSC are highly homologous， the transcription factors and proteins that have been confirmed in liver fibrosis-related studies are also similarly expressed in PSC， suggesting that they may also influence the activation of PSC. This article systematically summarizes the recent advances in the research on SCFA in alleviating liver and pancreatic fibrosis， in order to provide new perspectives for exploring the mechanism of pancreatic fibrosis and developing related interventional strategies.

ObjectiveTo evaluate the effect of neuromuscular electrical stimulation (NMES) on pain, quadriceps strength and motor function of patients after total knee arthroplasty (TKA). MethodsThe databases of CNKI, Wanfang data, VIP, PubMed, Embase, Cochrane, Web of Science and Scopus were retrieved from inception to April, 2025. Randomized controlled trials (RCT) related to the intervention of NMES after TKA were collected. The quality of the included literature was evaluated using the Cochrane Risk of Bias Assessment Tool and the Physical Therapy Evidence Database (PEDro) scale. Meta-analysis was performed with RevMan 5.4. ResultsA total of twelve RCT were included, involving 772 subjects. The PEDro scale score ranged from four to seven. NMES improved postoperative quadriceps muscle strength (SMD = 0.61, 95%CI 0.34 to 0.88, P < 0.001) and knee flexion range of motion (SMD = 1.35, 95%CI 0.30 to 2.41, P = 0.010), and reduced the Timed Up and Go Test (TUGT) time (SMD = -0.86, 95%CI -1.45 to -0.26, P = 0.005). Compared with the control group, the intervention group achieved better outcomes in the 2-Minute Walk Test (2MWT) (SMD = 19.44, 95%CI 10.44 to 30.43, P < 0.001), 3-Minute Walk Test (SMD = 23.57, 95%CI 14.77 to 32.36, P < 0.001), 6-Minute Walk Test (SMD = 42.29, 95%CI 9.71 to 74.86, P = 0.010), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) (SMD = -0.52, 95%CI -1.00 to -0.04, P = 0.040), as well as the Physical Component Summary (PCS) (SMD = 2.90, 95%CI 0.73 to 5.06, P = 0.009) and Mental Component Summary (MCS) (SMD = 2.84, 95%CI 1.40 to 4.28, P = 0.040) of the 36-Item Short Form Health Survey (SF-36). Subgroup analysis demonstrated that two to four weeks after surgery, NMES enhanced patients' quadriceps muscle strength (SMD = 0.90, 95%CI 0.58 to 1.21, P < 0.001), shortened TUGT time (SMD = -1.28, 95%CI -2.57 to -0.02, P < 0.05) and increased walking distance in 2MWT (SMD = 20.43, 95%CI 10.44 to 30.43, P < 0.001). For patients followed up for two to three months, NMES yielded improvements in WOMAC scores (SMD = -0.44, 95%CI -0.79 to -0.09, P = 0.010) and SF-36 MCS scores (SMD = 4.17, 95%CI 2.43 to 5.91, P < 0.001). ConclusionNMES can significantly improve the quadriceps strength and walking ability of the TKA patients two to four weeks after surgery, and enhance the quality of life of patients two to three months after surgery.