ObjectiveThe exacerbating trend of global population aging poses profound socioeconomic and public health challenges, making the comprehensive elucidation of biological aging mechanisms and the discovery of effective anti-aging interventions an urgent priority in the life sciences. Based on our previous serum metabolomics findings that dimethylglycine, an intermediate metabolite of amino acid metabolism naturally present in the human body, was significantly enriched in the serum of longevity families, this study aimed to systematically investigate the anti-aging effects of dimethylglycine both in living organisms and in controlled laboratory environments, and to preliminarily elucidate its underlying molecular mechanisms. While existing literature indicates that dimethylglycine possesses antioxidant and immunomodulatory properties, its direct anti-aging efficacy and the specific molecular pathways through which it operates remain largely unexplored. MethodsTo comprehensively evaluate the anti-aging properties of dimethylglycine, we utilized replicative senescent human embryonic lung fibroblasts, specifically the WI-38 cell line, as an experimental model in a controlled laboratory environment. Cell viability and safety were thoroughly assessed using Cell Counting Kit-8 and lactate dehydrogenase release assays across various concentrations of dimethylglycine. The impact of dimethylglycine on cellular senescence phenotypes, oxidative stress, and proliferative capacity was evaluated via senescence-associated beta-galactosidase staining, reactive oxygen species fluorescence detection, and 5-ethynyl-2'-deoxyuridine incorporation assays. Furthermore, the molecular alterations of senescence-associated secretory phenotype factors and core senescence signaling pathways were quantified using quantitative reverse transcription polymerase chain reaction for the messenger RNA levels of interleukin-6, interleukin-8, p21, and matrix metalloproteinase-1, and enzyme-linked immunosorbent assay for the measurement of p16 and p21 protein expression levels. For the living organism model, the wild-type nematode Caenorhabditis elegans was used to evaluate systemic physiological effects. We conducted a comprehensive lifespan analysis at 20°C, heat stress resistance survival assays at 35℃, senescence-associated beta-galactosidase staining, lipofuscin accumulation tracking, intracellular reactive oxygen species measurement, and Oil Red O staining to ascertain systemic lipid accumulation. Additionally, network pharmacology bioinformatics tools, including PharmMapper and STRING databases, and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were utilized to predict target pathways, alongside highly detailed molecular docking simulations utilizing SwissDock and Protein-Ligand Interaction Profiler to examine interactions with the cytochrome P450 family 2 subfamily C member 9 protein. ResultsThe experimental outcomes robustly demonstrate the potent anti-aging capabilities of dimethylglycine. At the cellular level, toxicity analyses firmly confirmed that dimethylglycine is highly safe; continuous treatment with 50 mol/L and 70 mol/L of dimethylglycine for 5 d did not induce any cellular membrane damage or cytotoxicity, but rather actively promoted cellular proliferation. Utilizing the optimal standardized concentration of 50 mol/L, dimethylglycine treatment significantly ameliorated senescent phenotypic markers in human embryonic lung fibroblasts, which was evidenced by a drastic and highly significant reduction in the senescence-associated beta-galactosidase positive cell percentage (P<0.000 1) and intracellular reactive oxygen species levels (P<0.000 1), alongside a marked increase in the 5-ethynyl-2'-deoxyuridine-positive proliferation rate (P=0.003 5). On a molecular expression scale, dimethylglycine significantly downregulated the messenger RNA expression of multiple core senescence-associated secretory phenotype inflammatory factors, including interleukin-6, interleukin-8, p21, and matrix metalloproteinase-1. Concurrently, it effectively suppressed the protein expression of critical cell cycle arrest markers, diminishing p16 protein levels by 57.3% (P=0.000 4) and p21 protein levels by 27.2% (P=0.000 7). In the nematode Caenorhabditis elegans animal model, dimethylglycine significantly extended the mean lifespan from 20.402 d to an impressive 23.066 d (P<0.000 1) and notably enhanced overall survival rates under severe heat stress environmental conditions (P=0.017). Furthermore, systemic dimethylglycine intervention significantly mitigated age-related physiological decline by decreasing bodily lipofuscin accumulation (P<0.000 1), significantly reducing senescence-associated beta-galactosidase activity, lowering systemic reactive oxygen species fluorescence (P=0.008), and effectively alleviating overall fat accumulation (P<0.000 1). Mechanistically, extensive network pharmacology and Kyoto Encyclopedia of Genes and Genomes analyses strongly revealed that the potential targets of dimethylglycine are significantly enriched in fundamental drug metabolism and oxidative stress response pathways. Precision molecular docking simulations conclusively demonstrated that dimethylglycine forms highly stable structural interactions with the cytochrome P450 family 2 subfamily C member 9 protein, specifically highlighting the definitive formation of 5 stable hydrogen bonds involving serine 365, leucine 366, and serine 429 residues, as well as two critical salt bridge formations with arginine 97 and histidine 368 residues. It is additionally predicted to interact favorably with glutathione S-transferase family proteins. ConclusionDimethylglycine exhibits a profoundly significant and multifaceted anti-aging activity at both the cellular and entire living animal levels. By powerfully alleviating oxidative stress, heavily suppressing the core p16 and p21-dependent cellular senescence signaling pathways, and substantially mitigating the detrimental senescence-associated secretory phenotype, dimethylglycine effectively delays fundamental cellular senescence processes and drastically extends whole-organism lifespan. The biological mechanisms driving these robust protective effects are highly likely closely associated with its direct stable interactions with crucial metabolic and detoxifying enzyme systems, such as cytochrome P450 family 2 subfamily C member 9 and glutathione S-transferase family proteins, thereby systemically improving metabolic dysregulation and restoring critical redox homeostasis. This comprehensive study provides highly solid experimental evidence supporting dimethylglycine as a highly potent and safe potential anti-aging intervention agent, while simultaneously offering a clear molecular mechanistic explanation for the previously documented high abundance of dimethylglycine observed within exceptionally long-lived human populations.

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 develop and validate interpretable machine learning models for predicting the risk of medication-related osteonecrosis of the jaw （MRONJ） and surgical outcomes， thereby providing quantitative support for MRONJ risk assessment and treatment decision-making.METHODS Two study cohorts were established. Cohort A adopted a nested case-control study design to develop a predictive model for the risk of MRONJ onset. Cohort B comprised patients with MRONJ from Cohort A who underwent surgical treatment and met the follow-up eligibility criteria， and employed a prospective follow-up cohort study design to develop a predictive model for the efficacy of MRONJ surgery. After missing-data processing， variable standardization， and encoding， predictive features were selected using the least absolute shrinkage and selection operator （LASSO） regression， and collinearity was assessed using the variance inflation factor （VIF）. Random Forest （RF）， eXtreme Gradient Boosting （XGB）， Multi-layer Perceptron （MLP）， Support Vector Machine （SVM）， and Gaussian Naive Bayes （NB） models were subsequently developed using the selected features. Hyperparameter optimization and internal performance evaluation were performed using two-level nested cross-validation repeated 20 times. In Cohort B， the synthetic minority over-sampling technique （SMOTE） was applied within the inner training folds to address class imbalance. Model performance was comprehensively evaluated using the receiver operating characteristic （ROC） curve， the precision-recall （PR） curve， calibration curve， and decision curve analysis （DCA）. Shapley additive explanations （SHAP） were used to quantify the relative contributions of individual clinical features to model predictions.RESULTS Seven clinical features， including alkaline phosphatase and tooth extraction， were retained for Cohort A； whereas eight clinical features， including age and duration of medication use， were retained for Cohort B. In Cohort A， the area under the ROC curve， the area under the PR curve， Brier score， sensitivity， and specificity of the RF model were 0.94， 0.92， 0.09， 0.92， and 0.85， respectively； the corresponding values in Cohort B were 0.93， 0.93， 0.12， 0.83， and 0.93， respectively. The results of calibration curves and DCA indicated that the RF models achieved favorable calibration and clinical net benefit， with VIF values for all variables below 5. SHAP visualization results showed that alkaline phosphatase， tooth extraction， and cumulative drug dose made substantial contributions to MRONJ risk prediction in Cohort A， whereas age， duration of medication use， and MRONJ stage contributed substantially to surgical outcome prediction in Cohort B.CONCLUSIONS The RF-based models for predicting MRONJ risk and surgical outcomes demonstrated good discrimination， accuracy of probabilistic predictions， and potential clinical utility during internal validation. These models may provide decision support for comprehensive MRONJ risk management and individualized clinical decision-making. However， external validation in independent， multicenter， and geographically diverse cohorts is still required.

Objective To observe the origin and course of the obturator artery(OA),so as to provide anatomical reference for reducing hemorrhage during pelvic surgery and pubic fracture fixation.Methods A total of 65 human hemi-pelvises specimens with intact structure were dissected to observe the origin,course and other variations of OA.Measure the length of the inner section of OA basin and the outer diameter at the origin,etc.Results OA originated from the internal iliac artery in 57 cases(87.7%),including 3 cases(4.6%)of the superior gluteal artery,5 cases(7.7%)of the inferior gluteal artery,3 cases(4.6%)of the external iliac artery and 5 cases(7.7%)of the inferior epigastric artery.OA participated in the formation of the arterial trunk in 3 cases(4.6%).The length of the pelvic segment of the OA in male and female was(50.87±15.41)mm and(51.71±14.19)mm,respectively,with no statistically significant difference between them(P>0.05).The outer diameters at the origin of the OA in male and female were(2.79±1.05)mm and(2.35±0.86)mm,and there was no statistically significant difference between them(P>0.05).Conclusion OA mainly originated from the anterior trunk of the internal iliac artery,with a few OA originated from the branches of the posterior trunk or the inferior epigastric artery,or participated in the formation of the arterial trunk.In pelvic surgery involving OA area,attention should be paid to the length of its pelvic segment and the outer diameter at the origin of OA,so as to better locate and protect blood vessels during surgery.

Objective To explore the effect of evening primrose oil(EPO)on aortic endothelial damage in rats with polycystic ovary syndrome(PCOS),using network pharmacology and in vivo experiments.Methods The potential targets of EPO for improving aortic endothelial injury in PCOS rats were predicted by network pharmacology,and the selected core targets and renin-angiotensin signaling(RAS)pathway were verified by experiments.Fifty-eight female SD rats were divided randomly into a blank group(n=10)and a modeling group(n=48).Rats in the blank group were fed a normal diet and rats in the modeling group received a high-fat diet for 8 weeks.The PCOS model was prepared at week 6 by administration of letrozole(1 mg/(kg·d))for 21 days.Blood was taken from the tail vein after modeling and serum was collected to detect hormone levels.The model rats were then divided randomly into four groups and treated with the corresponding drugs for 6 weeks.Blood,blood vessels,and ovaries were then collected.Tissue morphology was examined by hematoxylin and eosin staining and serum levels of luteinizing hormone(LH),testosterone(T),follicle-stimulating hormone(FSH),endothelin(ET-1),and tumor necrosis factor(TNF-α)were detected by enzyme-linked immunosorbent assay(ELISA).Serum levels of nitric oxide(NO)were determined by spectrophotometry.Protein expression levels of core targets and RAS pathway-related factors were assessed by western blotting and immunohistochemistry.Results Twenty-five intersection targets of EPO and PCOS were identified by network pharmacological analysis.Kyoto encyclopedia of genes and genomes analysis showed that EPO improved vascular injury in PCOS rats via multiple pathways,including RAS.Serum levels of ET-1,FSH,LH,and T measured by ELISA were significantly decreased after EPO treatment,compared with the model group(P＜0.01).EPO significantly decreased the expression levels of Ang Ⅰ,VEGF-B,AT2R,ET-1,and TNF-α proteins in the aorta(P＜0.01)and significantly increased expression levels of Ang Ⅱ,CD31,and endothelial NO synthase proteins(P＜0.01).Conclusions EPO may ameliorate vascular endothelial injury in PCOS model rats by inhibiting the RAS signaling pathway and by overactivation of the ACE/Ang Ⅱ/AT1 axis.

To investigate the protective effect of Lycium barbarum glycopeptide(LbGp)on testicu-lar injury induced by D-galactose(D-gal)in aging rats,male SD rats were randomly divided into 6 groups:the blank control group(Control),aging model group(Model),positive control group(β-nicotinamide mononucleotide,NMN),low dose LbGp group(LLbGp),medium dose LbGp group(MLbGp)and high dose LbGp group(HLbGp).The testicular mass of rats was counted,the morphological changes of testicular tissue were observed by hematoxylin-eosin(HE)staining,the testicular senescence was detected by β-galactosidase(SA-β-gal)staining,and the levels of testos-terone(T),luteinizing hormone(LH)and follicle stimulating hormone(FSH)in serum were de-tected.The levels of oxidative factors such as glutathione peroxidase(GSH-Px),superoxide dis-mutase(SOD),malondialdehyde(MDA),catalase(CAT)and inflammatory factors such as tumor necrosis factor-α(TNF-α),interleukin-1β(IL-1β)and interleukin-6(IL-6)in rat tissues were measured.TUNEL staining was used to detect the apoptosis of testicular cells,epididymal sperm quality,and the expression of Keap1,Nrf2 and Nqo1 mRNA were analyzed.The results showed that compared with the Model group,the testicular coefficient of Lycium barbarum glycopeptide rats in MLbGp and HLbGp groups increased(P＜0.01),the level of T in serum and sperm quality increased(P＜0.05),the structural degeneration and aging of testicular tissue decreased(P＜0.01),the level of antioxidant factors increased,and the levels of inflammatory factors and apopto-sis decreased(P＜0.05).The expression of Keap1 decreased significantly(P＜0.01),while the ex-pression of Nrf2 and Nqo1 mRNA increased(P＜0.05).The above results indicate that Lycium barbarum glycopeptide can improve D-gal-induced testicular senescence,attenuate oxidative stress,reduce inflammatory response,decrease apoptosis,and exert a protective effect on testicular injury in rats due to senescence through the Keap1-Nrf2 signaling pathway.

Objective:To investigate lipid metabolism gene mutations and pathogenicity of hypertriglyceridemia acute pancreatitis (HTG-AP) patients.Methods:Clinical data of 495 HTG-AP patients admitted from June 2018 to June 2020 in the center for severe acute pancreatitis of Eastern Theater General Hospital were retrospectively analyzed. Whole-exome sequencing and mutation verification were performed by next-generation sequencing technology and Sanger sequencing. The pathogenicity of gene mutation was analyzed by population mutation ratio, pathogenicity prediction software, conservation scoring software, protein structure prediction, and in vitro experiments. Results:The mutation ratio of lipid metabolism-related genes, namely LPL, APOA5, LMF1, GPIHBP1, and APOC2, were 14.81%, 55.78%, 43.61%, 1.62%, and 0.61%, respectively. Among them, 44 heterozygous mutations in LPL gene were detected including 36 missense mutations, 5 nonsense mutations and 3 frameshift mutations, which were all rarely carried in single patient. Six HTG-AP patients carried the LPL gene heterozygous mutation c.835C>G (p.Leu279Val). The mean level of serum triglyceride at the onset of HTG-AP was 27.4 mmol/L. All of them had a history of recurrent HTG-AP, and most of them had severe acute pancreatitis. The serum LPL concentration and activity were lower than the normal level. The pathogenicity analysis results suggested that the LPL p.Leu279Val was a rare, highly possible pathogenic and highly conserved gene mutation. The in vitro results showed that the LPL p.Leu279Val could significantly reduce the synthesis and secretion ability of LPL as well as its enzymatic activity. Conclusions:The mutation ratio of lipid metabolism-related genes, including LPL, APOA5, LMF1, GPIHBP1, and APOC2, are relatively high in the HTG-AP patients. The LPL p.Leu279Val is a rare and highly possible pathogenic gene mutation, which may lead to recurrent episodes of HTG-AP.

Objective:To investigate the longitudinal association between the Chinese Visceral Adiposity Index(CVAI) and cardiovascular disease(CVD) risk in middle-aged and elderly individuals with abnormal glucose metabolism.Methods:A total of 3 662 individuals with abnormal glucose metabolism from the China Health and Retirement Longitudinal Study(CHARLS) database were included. The cumulative incidence of CVD events was estimated using Kaplan-Meier curves. Cox proportional hazards models were used to assess the association between CVAI and CVD events, and a multivariate-adjusted restricted cubic spline(RCS) curve was fitted to test the dose-response relationship between CVAI and incident CVD events. Subgroup analyses were also conducted to explore potential effect modifiers. Results:During the follow-up, 844 participants experienced CVD events. In the fully adjusted model, every interquartile range( IQR) increment in CVAI was significantly associated with an increased risk of CVD events, with a hazard ratio( HR)[95% confidence interval( CI)] of 1.22(1.11-1.35). Compared to the first quartile( Q1) of CVAI, the HRs(95% CI) for CVD event incidence in Q2- Q4 were 1.22(0.98-1.52), 1.29(1.05-1.61), and 1.51(1.22-1.88), respectively. Subgroup analysis indicated a significant interaction effect between CVAI and age on the risk of CVD events in individuals with abnormal glucose metabolism( P for interaction <0.05). No significant interactions were found for gender, body mass index(BMI), waist circumference(WC), smoking, alcohol consumption, and hypertension(all P for interaction >0.05). Furthermore, the multivariate-adjusted RCS regression revealed a significant dose-response relationship between CVAI and CVD events( P<0.001, P for nonlinearity=0.568). Conclusions:In middle-aged and elderly individuals with abnormal glucose metabolism, CVAI is independently associated with an increased risk of incident CVD events and may serve as a reliable surrogate marker for assessing visceral adiposity in this population. Regular monitoring of CVAI should be considered for integration into routine clinical practice to improve CVD prevention in individuals with abnormal glucose metabolism.

Objective:To establish a practical patient-based internal quality control method for valproic acid drug concentration monitoring.Methods:Observational Study. A PBRTQC model based on the exponentially weighted moving average (EWMA) method was established using Python. All results of a total of 28, 757 valproic acid concentration data from February 1, 2023 to January 31, 2024 were collected and split into training set and validation set at a ratio of 80% and 20% respectively. The truncation limit (TL) was optimized by using the winsorized mean method and the trimmed mean method. Different weighting coefficients λ were set. Different TL and different λ were combined with the EWMA algorithm into different patient-based real-time quality control (PBRTQC) models. The optimized models were verified by introducing simulated constant errors (CE) and proportional errors (PE) respectively. The false positive alarm rate (FAR) was used to evaluate specificity, and the average number of patients before error detection (ANPed) was used to evaluate sensitivity. According to the daily test volume and quality target requirements, we comprehensively judged whether the performance evaluation indicators of FAR and ANPed meet the laboratory requirements. Bias detection curve was used for determination of the best model.Results:The parameters of the best PBRTQC model for valproic acid drug concentration monitoring are: trimmed mean method with 1.5 standard deviations (i.e., truncating data outside 1.5 standard deviations of the data mean), λ=0.01. The performance verification result shows that ANPed of CE and PE of this model are both less than 100. The comparison between the EQA results and the EWMA results show that the EWMA method results are comparable to the EQA results.Conclusion:A PBRTQC model for the valproic acid drug concentration monitoring project based on the EWMA method has been successfully established. It is comparable with both IQC and EQA results, which means PBRTQC may be used as a supplement to the quality control of daily quality control products.

Objective To construct a nursing follow-up checklist for patients undergoing autologous hematopoietic stem cell transplantation,providing a basis for postoperative follow-up care.Methods Using evidence-based methods,the literature from major guide websites and databases using Chinese and English search terms was retrieved,and their quality was evaluated.The relevant items were extracted,and a first draft was formed.15 experts were selected in relevant fields from 14 tertiary hospitals in 13 provinces,cities,and autonomous regions across the country for Delphi inquiry.The nursing follow-up checklist was revised again based on expert opinions and clinical practice.The nursing follow-up checklist was initially applied and then revised again to form the final draft.Results 15 experts include 12 undergraduate and 3 master's degree holders.The positivity coefficients of the 2 rounds of inquiry were 100％;the authority coefficients of the experts were 0.815;the Kendall coefficients were 0.119 and 0.144,respectively;the differences were statistically significant(P＜0.001).The final nursing follow-up checklist was formed,which includes 6 primary indicators,including physiological status,psychological status,social and family support,living conditions,disease knowledge,and laboratory tests.19 patients(95％)found the follow-up content to be comprehensive.The follow-up nurses's satisfaction rate exceeded 85％.There were 27 secondary indicators and 61 tertiary indicators,with coefficients of variation of all indicators less than 0.25.Conclusion The nursing follow-up checklist is scientific,reliable,and practical,which can provide a basis for clinical nursing staff to follow up and comprehensively manage patients after autologous hematopoietic stem cell transplantation.