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 study the mandibular characteristics of the modern population in Beijing region.Methods In this study,we examined 22 measurements and their sexual dimorphism index(SDI)of 193 adult mandibles(126 males,67 females)collected from the Beijing region.In addition,eight mandibular indexes were calculated.These mandibular dimensions of the Beijing population were compared with those of other modern and contemporary populations in Asia,as well as Neolithic-historical populations in Northern China.Results The predominant mandibular index in the contemporary Beijing population was dolichostenomandibular.The SDI of mandibular size exhibited a wide range of variation.It was noteworthy the minimum height of mandibular ramus,height of mandibular ramus,height of coronoid process and minimum breadth of mandibular ramus demonstrate significant sexual dimorphism(SDI≥10％).The mandibular size aligned with the variation range of modern and contemporary Asian populations,with the cluster analysis indicating an affiliation with Northern Mongoloids.But the Beijing population was far away from other Northern populations in China.The mandibular size was more gracile compared to ancient populations in Northern China,whereas the height of mandibular ramus was greater than those of the latter.Conclusion This study provides valuable insights into the physical characteristics of modern populations in Beijing region.

Objective To investigate the size variation in the first metatarsal of extant primates.Methods In this study,we analyzed 135 first metatarsal specimens across 12 primate genera,quantifying eight linear measurements,articular surface areas,mid-shaft cross-sectional area,total surface area,volume,and derived indices.Multivariate patterns were assessed through mean-based correspondence analysis and principal component analysis(PCA).Results Eulemur,Otolemur,Cebus,and Perodicticus exhibited a relatively high metatarsal surface-area-to-volume ratio.Perodicticus additionally showed a low articular facet index.Propithecus,Colobus,and Macaca displayed lower values for metatarsal shaft robusticity,the ratio of shaft cross-sectional area to base articular surface area,and the proximal articular facet index.Nasalis possessed a relatively high articular facet index.Pongo,Pan,Gorilla,and Homo sapiens were characterized by higher metatarsal shaft robusticity and a lower metatarsal surface-area-to-volume ratio.Principal component analysis revealed that the 12 extant primate genera could be broadly divided into two groups.Group 1 comprised Pongo,Pan,Gorilla and H.sapiens,although H.sapiens formed a distinct cluster relative to the extant great apes.Group 2 included Eulemur,Otolemur,Perodicticus,Propithecus,Cebus,Colobus,Macaca and Nasalis.Conclusion The relative sizedistribution of the first metatarsal provides some reference value for classifying extant primates.However,it demonstrates no clear correlations with specific locomotor patterns or foot grasping ability.

Background Occupational disease diagnosis appraisal is an appeal procedure initiated when a party disagrees with the occupational disease diagnosis conclusion. It is a legal procedure to safeguard the health rights of employees and the legitimate rights and interests of employers. Objective To analyze the data of occupational disease diagnosis appraisal in Shanghai, identify existing problems, and provide suggestions for improving. Methods Statistical analysis was conducted on basic situation, characteristics of workers and employers, disease classification, and consistency between diagnosis and appraisal conclusions of all occupational disease diagnosis appraisal cases from 2012 to 2024. All diagnosis conclusions were named in accordance with the Classified Catalogue of Occupational Diseases included employers were classified according to the Measures for the Statistical Classification of Large, Medium, Small and Micro Enterprises" and the Notice on Adjusting the Provisions for Classifying Enterprise Registration Types; industry classification followed the Industrial Classification for National Economic Activities (GB/T 4754-2017). Results From 2012 to 2024, a total of 260 cases of occupational diseases diagnosis appraisal were closed. The main diagnosis were 138 cases of ear, nose, throat, and oral diseases (53.1%), chemical poisoning (18.8%), and pneumoconiosis and other respiratory diseases (16.2%). The proportion of ear, nose, throat, and oral diseases gradually increased (2022 excluded). The incidence of annual municipal and provincial cases decreased by 76.3% and 85.0% respectively (2024 vs 2012). The consistency rate of conclusions between appraisal and diagnosis gradually increased. The total consistency rates between final appraisals and diagnostic conclusions were 81.5%, and 79.7%, 87.8%, 100.0%, 85.0% for ear, nose, throat, and oral diseases, chemical poisoning, and pneumoconiosis and other respiratory system diseases, respectively. Specifically, the consistency rates were 80.1% and 80.0% for noise-induced deafness and chronic benzene poisoning. In terms of inconsistency reasons, "inconsistent interpretation of standards and excessive discretion in standard application" accounted for 43.8%, followed by "failure to correctly apply standards" (31.3%) and and "discrepancies in occupational exposure history recognition" (15.6%). Conclusion The revisions and improvements of the legal system for occupational disease diagnosis appraisal have played a positive role in improving the consistency of conclusions between appraisal and diagnosis of occupational diseases in Shanghai. It is suggested to further strengthening the publicity and training of occupational disease diagnosis standards to improve the quality of occupational disease diagnosis.

Objective To analyze the risk factors associated with early recurrence after surgery for concomitant exo-tropia and establish a Nomogram prediction model.Methods A retrospective analysis was conducted on 243 cases(486 eyes)of concomitant exotropia treated in the Ophthalmology Department of our hospital from October 2015 to October 2021.The patients were divided into a training set(n=170)and a validation set(n=73)at a ratio of 7∶3.The Lasso re-gression,Boruta algorithm,and random forest algorithm were used to screen risk variables related to postoperative recur-rence of concomitant exotropia.The Spearman correlation analysis and variance inflation factor(VIF)were used to assess collinearity among variables,and a Nomogram prediction model was established using multivariate Cox regression.The re-ceiver operating characteristic curve,calibration curve,and clinical decision curve of the model at 6 months,18 months,and 24 months after surgery were used to assess the efficacy of the model.Results Three machine learning methods in-cluding Lasso regression,Boruta algorithm,and random forest algorithm identified six significant variables that might con-tribute to early recurrence after strabismus surgery from 22 risk variables in both training and validation sets.No collineari-ty was found among the six variables(r＜0.6,VIF＜5).Multivariate Cox regression revealed that strabismus type(inter-mittent exotropia),preoperative strabismus angle,best-corrected visual acuity(BCVA)in the right eye,BCVA in both eyes,and surgical procedures(unilateral lateral rectus recession)were risk factors for early recurrence after surgery for concomitant exotropia.Meanwhile,a Nomogram prediction model was constructed based on these 6 factors.The receiver operating characteristic,calibration,and clinical decision curves indicated that the prediction model had good accuracy,consistency,and clinical applicability.Conclusion Nomogram prediction model can effectively predict the risk of early recurrence after surgery for concomitant exotropia,and provides a reference for ophthalmologists to intervene early in pa-tients.

With the great improvement in the prognosis and survival of breast cancer patients, coupled with the widespread use of cardiotoxic drugs, the cardiotoxicity caused by radiation-induced heart disease (RIHD) partially offsets the overall survival benefits of breast cancer patients. Heart damage occurs in many structures, such as left and right coronary arteries, the cardiac conduction system, the pericardium, and heart valves. RIHD has a long incubation period, most of which occur more than 10 years after radiotherapy, and the clinical manifestations become prominent with the extension of time. Advanced modern radiotherapy concepts such as respiratory gating, image-guided radiotherapy, conformal intensity-modulated radiotherapy, and intensity-modulated proton therapy can effectively reduce the radiation dose of breast cancer radiotherapy-related heart and left anterior descending coronary artery. The study of precise radiotherapy protection technology for the heart and large vessels is expected to reduce non-tumor-related death and achieve long-term survival in patients with breast cancer. The important direction in the future is to study the mechanism of RIHD, to find the best cardiac dose reference point, and to define the ideal dose-response relations. Combined with hematological markers, auxiliary examination parameters and cardiovascular risk factors, a predictive model will be established to estimate the probability of radiation-related cardiotoxicity in patients with breast cancer. As the radiation-related cardiotoxicity of breast cancer has become increasingly prominent, the purpose of this article is to summarize the related studies of RIHD in order to improve the long-term survival rate and quality of life of these sufferers.

Objective To explore the predictive value of radiomics nomogram based on multiparameter MRI for the status of human epidermal growth factor receptor 2(HER-2)in endometrial cancer(EC).Methods A total of 154 patients with pathologically proved EC were retrospectively selected and randomly divided into training set(108 cases)and validation set(46 cases)according to the ratio of 7∶3.Radiomics features were extracted from the preoperative multiparameter MRI images of the patients.The predictive performance of different machine learning algorithms was evaluated by receiver operating characteristic(ROC)curves,and the nomogram was constructed in combination with clinical risk factors.Results The degree of differentiation and depth of myometrial invasion were clinical risk factors for predicting HER-2 positivity in EC patients.The support vector machine(SVM)was selected as the best radiomics model.The nomogram showed the highest predictive performance in the training and validation sets,with area under the curve(AUC)of 0.926 and 0.897,respectively.Conclusion The radiomics nomogram based on multiparameter MRI can accurately predict the HER-2 status of EC patients before surgery and can be used to guide clinical treatment decisions.

To analyze the distribution of serotypes and antimicrobial resistance of clinical Salmonella isolates from multiple centers across China.

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.