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 correlation between parent-child separation experience and non suicidal self injury (NSSI) behavior among junior and senior high school students, so as to provide a reference for the prevention and improvement of NSSI behavior among junior and senior high school students. Methods: Using a stratified cluster random sampling method, 3 114 junior and senior high school students aged 11-19 years were recruited from Chenzhou and Jishou cities in Hunan Province between November 2024 and September 2025. A self designed questionnaire and the Functional Self injury Behavior Assessment Scale were used to collect information on parental labor migration and adolescents NSSI behavior status. Binary Logistic regression model was used to analyse the association between parent-child separation experiences and NSSI behavior among junior and senior high school students, with further stratified analysis by gender. Results: The prevalence rate of NSSI behavior among junior and senior high school students was 9.9%, and the overall incidence of parent-child separation was 48.9%, comprising 17.1% separated from their father only, 5.5% separated from their mother only, and 26.3% separated from both parents. After adjusting for variables such as age, gender, and ethnicity, the results of binary Logistic regression analyses indicated that adolescents with parent-child separation experiences had a higher risk of NSSI behavior ( OR =1.31, 95% CI =1.01-1.69, P <0.05). Compared with those without parent-child separation experiences, adolescents who were separated from their mother only ( OR =1.68, 95% CI =1.03-2.74) or from both parents ( OR =1.41, 95% CI =1.04-1.92) showed significantly increased risks of NSSI behavior (both P <0.05). Conclusions Parent-child separation experiences are associated with an increased risk of NSSI behavior among junior and senior high school students. Strengthened attention should be paid to left behind senior high school students to reduce the occurrence of NSSI in adolescents.

Chemical constituents of n-butanol fraction of ethanol extract from the leaves of Cyclocarya paliurus (Batalin) Iljinskaja were studied. Ten compounds were purified by silica gel, MCI, ODS, Sephadex LH-20 column chromatography and semi-preparative high-performance liquid chromatography. Based on the physicochemical properties and spectroscopic data, these compounds were identified as (4S)-4,8-dihydroxy-α-tetralone-5-[6′-(3′′,5′′-dimethoxy-(E)-p-coumaroyl)]-β-D-glucopyranoside (1), (4S)-4,8-dihydroxy-α-tetralone-5-[6′-(E)-feruloyl]-β-D-glucopyranoside (2), (1S,3R,4S,5R)-4,5-di-O-caffeoyl quinic acid methyl ester (3), (1R,3R,4S,5R)-3,4-di-O-caffeoyl quinic acid methyl ester (4), (3R,5R)-3,4,5-tri-O-caffeoylquinic acid methyl ester (5), (1R,3R,4S,5R)-3-O-caffeoyl-5-O-p-coumaroyl quinic acid methyl ester (6), (1R,3R,4S,5R)-3-O-p-coumaroy-4-O-caffeoyl quinic acid methyl ester (7), (1R,3R,4S,5R)-3-O-caffeoyl-4-O-p-coumaroy quinic acid methyl ester (8), (3R,5R)-3,5-di-O-caffeoyl quinic acid methyl ester (9) and (1S,3R,4R,5R)-4-O-caffeoyl-5-O-feruloyl quinic acid methyl ester (10). Among them, compound 1 was a new compound, and compounds 3–10 were isolated from the genus Cyclocarya for the first time.

Background/Aims: Lenvatinib resistance remains a critical barrier in advanced hepatocellular carcinoma (HCC) therapy. However, the underlying mechanisms and strategies for reversing resistance remain incompletely understood. Methods: Integrated transcriptomics of lenvatinib-resistant patient tumors and an acquired-resistance murine model identified a novel macrophage subpopulation. Functional validation employed CRISPR-SAM screening, conditioned medium (CM) assays, subcutaneous/orthotopic xenografts, patient-derived organoids (PDOs), and patient-derived xenografts (PDXs). Mechanistic studies included ChIP-qPCR, co-immunoprecipitation, and pharmacologic targeting. Clinical relevance was assessed in a retrospective cohort. Results: Resistant HCC exhibited significant enrichment of a COLEC12high TAM subset , which correlated with poor survival and treatment response. These TAMs secreted neuregulin-1 (NRG1) , activating HER2/HER3-AKT signaling in tumor cells to drive cancer stemness and lenvatinib resistance. Mechanistically, in TAMs COLEC12 sequestered STAT1 in the cytoplasm, preventing its phosphorylation, and thereby derepressing STAT3-mediated NRG1 transcription. Depletion of NRG1 reversed the stemness phenotypes and resensitized tumors to lenvatinib both in vitro and in vivo. Clinically, high NRG1 expression predicted an inferior lenvatinib response and shorter survival. Crucially, the bispecific anti-HER2/HER3 antibody zenocutuzumab restored lenvatinib efficacy in PDOs, PDXs, and murine models. Conclusions Our work establishes the COLEC12high TAM/NRG1 axis as a master regulator of therapeutic resistance and identifies NRG1 as a predictive biomarker, providing a clinically actionable strategy to overcome lenvatinib resistance in HCC.

Laboratory animal science is an emerging interdisciplinary field supporting life science and medical research, and a key component of talent cultivation and technological innovation in medical colleges. Currently, this field faces challenges such as a significant imbalance between talent supply and demand and a weak systematic training system. To respond to national strategies and societal needs, Shandong First Medical University established the School of Laboratory Animal through industry-education integration during the 14th Five-Year Plan period. The school is based on The Medical Laboratory Technology major, cultivates application-oriented, interdisciplinary professionals in laboratory animal science, and has constructed a three-in-one training system integrating "course learning–scientific research–industry practice". Specific measures for talent cultivation include: optimizing the general education, professional courses, and intensive practical modules in the talent training program, and establishing the "Yellow River Class" integrating industry and education; implementing an undergraduate mentor system, and conducting scientific research training based on The Model Animal Research and Development Engineering Laboratory; collaborating with bases across the entire industrial chain of laboratory animal production, research, application, and quality control, appointing industry mentors, and strengthening practical teaching. Practice has shown that this system has been remarkably effective: a total of 320 undergraduate students have been enrolled since 2020; the employment rate of undergraduate graduates for two consecutive cohorts has reached 100%, and the postgraduate enrollment rate has exceeded 50%; undergraduate students have won numerous national and provincial awards in academic competitions, and have obtained multiple patents and published papers. In the future, the school will further integrate the advantages of medicine, agriculture, and science, optimize the depth and breadth of courses, strengthen the construction of faculty and teaching materials, and improve the undergraduate-master's integrated training mechanism. This article can provide a reference for the training of professionals in laboratory animal science and related biomedical fields in medical colleges.

Objective To explore the molecular mechanism of Jianfu mixture in the treatment of erectile dysfunction （ED） by network pharmacology and molecular docking techniques, and validate its core targets and mechanisms through in vitro experiments. Methods The active components and corresponding molecular targets of Jianfu mixture were searched by searching TCMSP and Batman-TCM databases, and the disease targets of ED were searched by using GeneCards database. Find the intersection of drug ingredient target and disease target. The interaction between intersected targets was described and analyzed by String database, and the analysis results were visualized by Cytoscape software to determine the core target and the corresponding active components. GO functional enrichment analysis and KEGG pathway enrichment analysis were performed for intersection targets; the core target within the intersection were found through MCODE plug-in on Cytoscape software and molecular docking was performed with the corresponding active ingredients. An endothelial dysfunction model was established by transfecting HUVECs with si-eNOS. Intervene with different concentrations of the Jianfu mixture for the model cells for 24 h. QPCR was used to detect mRNA expression of core targets （MAPK1, MAPK3, JUN, ESR1, MAPK8）; Western blot was used to analyze protein expression （eNOS, JUN, p-JUN, MAPK, p-MAPK） and phosphorylation levels. Results 144 effective active components and 168 active components target-disease targe intersection of Jianfu mixture were obtained. GO analysis revealed 200 5 biological processes, 151 molecular functions, and 63 cellular components. KEGG analysis yielded 181 pathways. 5 core targets including MAPK1, MAPK3, JUN, ESR1 and MAPK8 were screened out. The active components such as β-sitosterol, kaempferol, astapterocarpan had good binding affinity with the core target. In vitro experiments confirmed successful construction of the endothelial dysfunction model （eNOS expression significantly decreased after si-eNOS transfection）. Jianfu mixture dose-dependently inhibited mRNA expression of MAPK1, MAPK3, JUN, ESR1, and MAPK8. Additionally, it reduced phosphorylation levels of JUN and MAPK, indicating inhibition of the JNK/c-Jun and ERK/MAPK signaling pathways to improve endothelial function. Conclusion Jianfu mixture treats ED by suppressing abnormal activation of multi-target signaling pathways （MAPK/JUN/ESR1）, reducing endothelial apoptosis, and promoting NO synthesis. This mechanism aligns with the traditional Chinese medicine principle of “activating blood circulation, resolving stasis, tonifying Qi, and strengthening cardiovascular function.” The study provided molecular-level evidence for the therapeutic efficacy of Jianfu mixture in ED management.

Objective To explore the molecular mechanism of Jianfu mixture in the treatment of erectile dysfunction （ED） by network pharmacology and molecular docking techniques, and validate its core targets and mechanisms through in vitro experiments. Methods The active components and corresponding molecular targets of Jianfu mixture were searched by searching TCMSP and Batman-TCM databases, and the disease targets of ED were searched by using GeneCards database. Find the intersection of drug ingredient target and disease target. The interaction between intersected targets was described and analyzed by String database, and the analysis results were visualized by Cytoscape software to determine the core target and the corresponding active components. GO functional enrichment analysis and KEGG pathway enrichment analysis were performed for intersection targets; the core target within the intersection were found through MCODE plug-in on Cytoscape software and molecular docking was performed with the corresponding active ingredients. An endothelial dysfunction model was established by transfecting HUVECs with si-eNOS. Intervene with different concentrations of the Jianfu mixture for the model cells for 24 h. QPCR was used to detect mRNA expression of core targets （MAPK1, MAPK3, JUN, ESR1, MAPK8）; Western blot was used to analyze protein expression （eNOS, JUN, p-JUN, MAPK, p-MAPK） and phosphorylation levels. Results 144 effective active components and 168 active components target-disease targe intersection of Jianfu mixture were obtained. GO analysis revealed 200 5 biological processes, 151 molecular functions, and 63 cellular components. KEGG analysis yielded 181 pathways. 5 core targets including MAPK1, MAPK3, JUN, ESR1 and MAPK8 were screened out. The active components such as β-sitosterol, kaempferol, astapterocarpan had good binding affinity with the core target. In vitro experiments confirmed successful construction of the endothelial dysfunction model （eNOS expression significantly decreased after si-eNOS transfection）. Jianfu mixture dose-dependently inhibited mRNA expression of MAPK1, MAPK3, JUN, ESR1, and MAPK8. Additionally, it reduced phosphorylation levels of JUN and MAPK, indicating inhibition of the JNK/c-Jun and ERK/MAPK signaling pathways to improve endothelial function. Conclusion Jianfu mixture treats ED by suppressing abnormal activation of multi-target signaling pathways （MAPK/JUN/ESR1）, reducing endothelial apoptosis, and promoting NO synthesis. This mechanism aligns with the traditional Chinese medicine principle of “activating blood circulation, resolving stasis, tonifying Qi, and strengthening cardiovascular function.” The study provided molecular-level evidence for the therapeutic efficacy of Jianfu mixture in ED management.

ObjectiveTo investigate the value of liver stiffness measurement （LSM） and spleen stiffness measurement （SSM） measured by two-dimensional shear wave elastography （2D-SWE） in the diagnosis of severe portal hypertension （SPH） and high-risk varices （HRV）， and to provide a basis for noninvasive assessment of portal hypertension. MethodsA prospective study was conducted among 78 patients with cirrhotic portal hypertension who were treated in Liver Research Center of Beijing Friendship Hospital， Capital Medical University， from December 2019 to April 2023. According to hepatic venous pressure gradient （HVPG）， the patients were divided into 6 mmHg≤HVPG<12 mmHg group， 12 mmHg≤HVPG<20 mmHg group， and HVPG ≥20 mmHg group. All patients underwent gastroscopy and 2D-SWE within 1 week after HVPG measurement， and SWE-LSM and SWE-SSM measured by 2D-SWE were recorded. A one-way analysis of variance or the Kruskal-Wallis H test was used for comparison of continuous data between multiple groups， and the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. With HVPG and gastroscopy findings as the gold standard， the receiver operating characteristic （ROC） curve was plotted and the area under the ROC curve （AUC） was calculated to evaluate diagnostic performance， while the DeLong test was used for comparison of AUC. The Pearson or Spearman correlation analysis was used to investigate the correlation between variables， and the linear regression analysis and the Logistic regression analysis were used to investigate the influencing factors for HVPG and HRV. ResultsThe mean HVPG was 18.1±6.4 mmHg for the patients enrolled in this study， and HRV was observed in 62 patients （79.5%）. Both SWE-LSM and SWE-SSM were significantly positively correlated with HVPG （r=0.413 and 0.633， both P<0.001）， with an AUC of 0.812 and 0.902， respectively， in the diagnosis of HVPG≥12 mmHg and an AUC of 0.804 and 0.789， respectively， in the diagnosis of HVPG≥20 mmHg （all P>0.05）. The multivariate linear regression analysis showed that SWE-SSM was an independent influencing factor for HVPG （β=0.17， P<0.001）. In the diagnosis of HRV， only SWE-SSM showed a significant positive correlation with HRV （r=0.432， P<0.001）， with a better diagnostic performance than SWE-LSM in terms of AUC （0.808 vs 0.642， Z=2.775， P=0.006）. The multivariate Logistic regression analysis showed that platelet count was an independent influencing factor for HRV （odds ratio=0.97， P=0.014）. ConclusionSWE-SSM is closely correlated with both HVPG and HRV， showing a good performance in the diagnosis of SPH and HRV， and therefore， it is expected to become an effective noninvasive tool for assessing portal hypertension.

To analyze the clinical and genetic features of oculopharyngodistal myopathy (OPDM) patients and compare the phenotypic differences among various causative genes.

ObjectiveHepatocellular carcinoma (HCC) represents 90% of all primary liver cancers. The main risk factors associated with HCC include viral hepatitis (B and/or C), alcohol abuse, and metabolic dysfunction-associated steatotic liver disease (MASLD), which progressively advance to liver fibrosis, cirrhosis, and ultimately evolve into HCC. Surgical resection represents the most effective treatment for HCC, while recent advances in immunotherapy, including immune checkpoint inhibitors and adoptive cell therapies, have provided improved treatment prospects for patients with unresectable HCC. However, the complex metabolic heterogeneity of HCC limits the therapeutic efficacy. Metabolic intermediates acyl-CoA not only provide energy and substrates for numerous biochemical reactions but also serve as donors for protein lysine acylation, a major class of post-translational modification (PTM). Therefore, a deeper understanding of the molecular mechanisms underlying protein lysine acylation and hepatocarcinogenesis is urgently needed. MethodsThe levels of protein lysine acylation and silence information regulator 5 (SIRT5) expression levels in clinical HCC samples were analyzed by Western blot. Quantitative malonylome and succinylome of HCC samples were analyzed by antibody-based affinity enrichment coupled with tandem mass spectrometry. The proliferation of HCC cells was analyzed with Cell Counting Kit-8 (CCK-8) assays, the apoptosis was quantified by Annexin V-FITC/propidium iodide (PI) staining coupled with flow cytometry, and the ability of cells to migrate was assayed by Transwell assays. The enzymatic activity of glutathione S-transferase Mu 1 (GSTM1) was quantified. Transgenic mice with hepatic overexpression of SIRT5 were constructed using CRISPR-Cas9, and primary hepatocarcinogenesis was induced by administration of diethylnitrosamine. ResultsWestern blot analysis indicated that the expression level of SIRT5 was elevated in clinical samples from HCC patients, and the levels of lysine malonylation, glutarylation, and succinylation were significantly reduced in HCC tissues. Knockout of SIRT5 in MHCC-97H and MHCC-97L hepatoma cells suppressed cell proliferation, and increased the percentage of apoptotic cells significantly. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the differentially malonylome and succinylome of HCC samples revealed significant enrichment in two major classes of biological processes: core energy metabolism (e.g., glycolysis/gluconeogenesis, tricarboxylic acid metabolic process, fatty acid beta oxidation) and detoxification and oxidative stress response (e.g., response to toxic substance, chemical carcinogenesis, reactive oxygen species (ROS)). SIRT5 removes malonylation from lysine residues in GSTM1 and restores its detoxification activity, which is crucial for the survival of hepatocytes under stressed conditions. More importantly, in vivo experiment indicated that hepatic-specific overexpression of SIRT5 in mice accelerated diethylnitrosamine-induced liver fibrosis and hepatocarcinogenesis, indicating the critical role of SIRT5 in HCC progression. ConclusionThis study highlights the previously unrecognized SIRT5-GSTM1 axis as a key regulator in hepatocarcinogenesis, and suggests a potential target for the treatment of patients with HCC.