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.

Objective: To investigate the hemolytic phenotypes of Staphylococcus aureus clinical isolates． Methods: The hemolytic phenotypes of 105 Staphylococcus aureus isolates were analyzed and summarized using the three-point inoculation method．Real-time fluorescence quantitative PCR was used to measure the mRNA expression levels of four hemolysin genes (hla，hlb，hlc，and hld) ; The VITEK 2 GP639 antimicrobial susceptibility card was used to detect resistance to commonly used antibiotics ; DNA gel electrophoresis was performed to determine the prevalence of the mecA，sea，tst，and pvl genes ; The microtiter plate crystal violet staining method was used to assess biofilm formation ability ; The CCK-8 assay was used to evaluate cytotoxicity against macrophages． Results: Seven hemo- lytic phenotypes were identified among the Staphylococcus aureus clinical isolates． Differences were found among Staphylococcus aureus clinical isolates with different hemolytic phenotypes in terms of mRNA expression levels of he- molysin genes，antibiotic resistance，virulence gene prevalence，biofilm formation ability，and cytotoxicity to mouse macrophages (P ＜0. 05 ) ． Conclusion Staphylococcus aureus clinical isolates exhibit diverse hemolytic pheno- types，which should be a focus across multiple dimensions，including microbiological testing，clinical treatment， and nosocomial infection prevention and control．

Objective:To explore the clinical characteristics of biliary system diseases complicated by severe acute pancreatitis(SAP) and the risk factors.Methods:This is a retrospective cohort study. A retrospective analysis was conducted on the clinical data of 159 SAP patients admitted to the Department of Pancreatic and Biliary Surgery,the First Affiliated Hospital of Harbin Medical University from January 2019 to October 2024. There were 105 male cases, 54 female cases;aged (42.3±10.8)years (range:20 to 71 years). Grouping was performed according to the presence or absence of concurrent acute acalculous cholecystitis (AAC) and biliary stricture. There were 58 cases in the AAC group,including 40 males and 18 females;aged (43.8±10.6) years (range:28 to 71 years);101 cases in the non-AAC group,including 64 males and 37 females;aged (41.5±10.8) years (range:20 to 64 years);there were statistically significant differences between the two groups in terms of admission total bilirubin,Balthazar-CTSI score,fasting time,and the proportions of concurrent shock and sepsis (all P<0.05);the time from onset of SAP to diagnosis of AAC( M (IQR)) was 10.5 (13.3) days (range: 3 to 34 days). There were 15 cases in the biliary stricture group,including 13 males and 2 females;age (46.5±10.0) years (range:33 to 63 years);141 cases in the non-biliary stricture group,including 89 males and 52 females;age (41.9±10.8) years (range: 20 to 71 years); there were statistically significant differences between the two groups in the proportions of infected pancreatic necrosis,pancreatic head necrosis,and lower extremity venous thrombosis (all P<0.05);the time from the onset of SAP to the diagnosis of biliary stenosis in patients with biliary stenosis was 2.0 (3.0) months (range: 1 to 19 months). Univariate analysis was performed using independent sample t-test, Mann-Whitney U test, χ 2 test,or Fisher′s exact probability method,and variables with P<0.05 in univariate analysis were included in multivariate logistic regression analysis. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic and predictive value of the multivariate logistic regression model for AAC and biliary stricture. Results:There were statistically significant differences in fasting time,Balthazar-CTSI score,admission total bilirubin,and the proportions of concurrent shock and sepsis between the AAC group and non-AAC group ( P<0.05). Multivariate logistic analysis showed that admission total bilirubin ( OR=1.033,95% CI: 1.010 to 1.058, P=0.004),Balthazar-CTSI score ( OR=1.276,95% CI: 1.036 to 1.572, P=0.022),fasting time ( OR=1.127,95% CI: 1.044 to 1.216, P=0.002), and sepsis ( OR=4.033, 95% CI: 1.419 to 11.462, P=0.009) were independent risk factors for AAC complicated by SAP. The area under the curve (AUC) of the ROC curve was 0.820 (95% CI: 0.752 to 0.888). There were statistically significant differences in the proportions of infected pancreatic necrosis,pancreatic head necrosis,and lower extremity venous thrombosis between the biliary stricture group and non-biliary stricture group ( P<0.05). Multivariate logistic analysis showed that infected pancreatic necrosis ( OR=7.376,95% CI:1.566 to 37.750, P=0.012) and pancreatic head necrosis ( OR=3.898,95% CI:1.180 to 12.877, P=0.026) were independent risk factors for biliary stricture complicated by SAP. The AUC of the ROC curve was 0.806 (95% CI:0.715 to 0.898). Conclusions:AAC typically occurs in the early stage of SAP,and biliary stricture usually occurs in the late stage of SAP. Admission total bilirubin,Balthazar-CTSI score,fasting duration,and concurrent sepsis are independent risk factors for AAC complicating SAP. Infected pancreatic necrosis and pancreatic head necrosis are independent risk factors for biliary stricture complicating SAP.

This study analyzed the burden and trends in enteric infections in China from 1990 to 2021 from a One Health perspec-tive.Data on mortality associated with enteric infections were extracted from the 2021 Global Burden of Disease(GBD)database.The analysis focused on assessing the mortality rates of enteric infectious diseases attributed to various etiologies and risk factors,along with the age and sex distribution,from 1990 to 2021.Average annual percentage change(AAPC)was used to assess the total changes in disease burden.The age-standardized mortality rate of intestinal infections in China decreased from 9.642/100 000 in 1990 to 0.439/100 000 in 2021,with an AAPC of-57.103%(95%CI:-57.118%to-57.088%).In 2021,Rotavirus,Norovirus,and Crypto-sporidium were the top three etiologies contributing to disease burden,with mortality rates of 1.020/100 000,0.040/100 000 and 0.079/100 000,respectively.A significant variation in etiology distribution was observed across age groups:Rotavirus,Shigella,and Crypto-sporidium dominated among children under 5 years of age,whereas Cryptosporidium,Norovirus,and Clostridioides difficile were more prevalent in older populations.Risk factor analysis indicated that unsafe water sources and poor sanitation accounted for 73.394%of all enteric disease-related deaths.In conclusion,the burden of enteric infections in China markedly declined from 1990 to 2021,and sig-nificant variations in the etiological spectrum and disease burden were observed across age groups.The persistent effects of unsafe wa-ter sources and poor sanitation underscore the need for targeted interventions to further decrease the burden of these diseases.Our find-ings highlight the success of public health interventions in decreasing the burden of enteric infections in China,while emphasizing the need for targeted measures to address disparities in high-risk populations and improve environmental sanitation.

Severe open tibiofibular fractures account for approximately 28.1% of all open fractures. Among them, Gustilo-Anderson type IIIB/C fractures present significant clinical challenges due to associated bone and soft tissue defects, high infection rates, and risk of amputation. Inadequate preoperative assessment may lead to suboptimal emergency surgical planning or intraoperative complications. Historically, external fixation was often preferred, but this approach has been associated with limitations such as restricted joint mobility, delayed bone union, joint stiffness, and disuse osteoporosis, resulting in poor functional recovery. With advancements of debridement techniques, standardization of antibiotic use, and popularization of early soft tissue coverage, early internal fixation has gained broader acceptance. Nevertheless, controversies persist regarding the choice of fixation method, timing of definitive fixation, use of reamed versus unreamed intramedullary nailing, and necessity of fibular fixation. To standardize the diagnosis and early management of severe open tibiofibular fractures, reduce complication rates, and improve functional recovery, the Society of Microsurgery of the Chinese Medical Association organized a panel of domestic experts to develop the Evidence-based guideline for the diagnosis and early fixation of severe open tibiofibular fractures ( version 2025), using evidence-based methodology. The guidelines provided 12 recommendations covering diagnostic and early fixation strategies of severe open tibiofibular fractures, aiming to provide clinicians with scientifically grounded and standardized guidance.

Objective To explore the predictive value of automated breast ultrasound(ABUS)features combined with Ki-67 in predicting pathological complete response(pCR)after neoadjuvant chemotherapy(NAC)in triple-negative breast cancer(TNBC).Methods A retrospective analysis was conducted on 127 female TNBC patients treated at Xijing Hospital,Air Force Medical University from March 2019 to December 2023.All patients underwent NAC and surgical treatment after ABUS examination.Based on postoperative pathological results,patients were divided into pCR group(n=60)and non-pathological complete response(npCR)group(n=67).Differences in various parameters before NAC were compared between the two groups.LASSO regression was used to identify independent factors influencing pCR after NAC in TNBC patients,and a predictive model was constructed using multivariate logistic regression.The prediction model was internally validated using the Bootstrap method(1000 resamples).The discriminative ability of the model was evaluated using receiver operating characteristic(ROC)curves,and the area under the curves(AUCs)of different prediction models were compared using De-long's test.The accuracy of the model was assessed using calibration curves,and the clinical benefit of the model was evaluated using clinical decision curve analysis(DCA).Results Significant differences were observed between two groups in terms of age,Ki-67,menopausal status,tumor type,posterior echo,coronal plane convergence sign,coronal plane skip sign,and coronal plane white wall sign before NAC(P<0.05).LASSO regression analysis showed that Ki-67,coronal plane convergence sign,and coronal plane white wall sign were independent influencing factors of pCR after NAC in TNBC patients(P<0.05).The AUC of the multivariate logistic regression model based on Ki-67 was 0.733(95%CI 0.646-0.819),the AUC of ABUS model was 0.777(95%CI 0.695-0.858),and the AUC of ABUS combined with Ki-67 model was 0.816(95%CI 0.741-0.890).De-long's test showed that the AUC of the combined model was higher than those of ABUS feature model and Ki-67 model,with statistically significant differences(P<0.05).There was no significant difference in the AUC between ABUS feature model and Ki-67 model(P=0.40).Hosmer-Lemeshow test indicated that the combined model had a good fit(P=0.304).Internal validation results showed that the combined model had a good stability with a consistency index(C-index)of 0.820(95%CI 0.726-0.879).The calibration curve demonstrated good consistency between the predicted and actual probabilities of the combined prediction model,and the DCA curve indicated that the model had favorable clinical benefit.Conclusion The combined ABUS feature and Ki-67 model can be used to predict the probability of pCR after NAC in TNBC patients,providing a reference for the formulation of clinical treatment plans in TNBC patients.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent cause of chronic liver disease worldwide, and its intricate pathogenesis presents challenges in the development of new drugs. As a common way of post-translational modification, acetylation regulates protein stability, enzyme activity, and subcellular localization, occurring extensively in MASLD-associated processes such as lipid metabolism, inflammatory response, and oxidative stress. In this paper, we comprehensively review the mechanism of acetylation in MASLD, analyze the expression levels of acetylases in liver tissues of MASLD patients from the gene expression omnibus (GEO), discuss the changes in relevant enzyme expression and mechanisms in animal models, and further explore the feasibility of targeting acetylation for MASLD treatment, in the hope of offering a new perspective for advancing drug discovery in the field of MASLD.

OBJECTIVE: To analyze the laboratory detection results of hemolytic disease of the fetus and newborn(HDFN). METHODS: Related test results of 283 newborns and their mothers' blood samples from Kunming Maternal and Child Health Hospital from August 2023 to May 2024 were collected, including mother and child ABO blood group, RhD blood group, as well as 3 tests of HDFN, total bilirubin (TBil) and indirect bilirubin (IBil). RESULTS: 283 were ABO incompatibility, among which 187 were HDFN positive, with a positive rate of 66.08%; the positive rate of HDFN in neonates with antigen-A incompatibility was 74.12%(126/170), the positive rate of HDFN in neonates with antigen-B incompatibility was 53.57%(60/112), which was the highest in neonates with O/A incompatibility ［75.45%(126/167)］, followed by O/B incompatibility［54.55%(60/110)］. Group by age, the positive rates of HDFN in the ≤1 d group, 2 d group, 3 d group, 4 d group, 5 d group and ≥6 d group were 76.03%(111/146), 67.86%(38/56), 57.14%(24/42), 38.46%(5/13), 46.15%(6/13) and 23.08%(3/13), respectively. With the increase of age, the positive rates of HDFN gradually decreased, there was a statistically significant difference between the ≤3 day age group and >3 day age group ( P <0.05). There was no statistically significant difference in TBil and IBil levels between the "direct antibody+indirect antibody+release+" group and the HDFN negative group in newborns. HDFN infants exhibited a rapid increase in bilirubin levels within the first day after birth, with significantly higher TBil and IBil values compared to Non ABO-HDFN infants in the ≤1 day group ( P <0.01). However, the difference of bilirubin levels between the two groups gradually narrowed from 2-6 days after birth, and the difference was not statistically significant (P >0.05). The peak value of TBil and IBil occurred on the 4th day after birth in HDFN infants. CONCLUSION ABO-HDFN is most commonly seen in newborns whose mothers are type-O, and the positive rate was the highest in newborns with O/A incompatibility. The detection rate of HDFN is affected by the age of the newborns, and the two were correlated inversely. ABO-HDFN group developed more rapidly with a higher peak. Therefore, HDFN tests should be carried out as soon as possible for mothers and newborns with incompatible blood types, and appropriate treatment should be provided to prevent complications.
Humans ; Infant, Newborn ; ABO Blood-Group System ; Erythroblastosis, Fetal/epidemiology* ; Female ; China/epidemiology* ; Blood Group Incompatibility ; Male ; Bilirubin/blood*

Objective To explore the effects of the disinfection port position and diameter and disinfectant concentration on the in-situ decontamination of the flow field-based biosafety high efficiency particulate air filter device with the computational fluid dynamics(CFD)method.Methods ANSYS DesignModeler was used to construct five models for the high efficiency particulate air filter device with the disinfection port at the side end in four ones and upper end in the remained one model,with the diameter being 70,100,150,260 and 260 mm respectively;secondly,a standard k-ε turbulence model was applied to simulating the velocity field and concentration field inside the high efficiency particulate air filter device,so as to analyze the influence of the vortex position inside the device and the structure of the device on the disinfection effect and to determine the optimal structure of the device;finally,H2O2 with the concentration of 0.45,0.35 or 0.30 mol/L was selected as the disinectant to investigate the effect of the disinfectant concentration on the disinfection under the optimal device structure.Results Simulation showed that there were vortexes existed the cavity between the filter compression structure and the filter of the high efficiency particulate air filter device.The disinfection effect in case of the disinfection port at the side end was higher than that in case of the disinfection port at the upper end;the diameter of the disinfection port had influences on the disinfection effect,and high-concentration disinfectant was found in the device when the diameter was 100 mm.The optimal structure with the disinfection port at the side end and the diameter of 100 mm was determined for the high efficiency particulate air filter device.An increase in H2O2 concentration was beneficial to improve disinfection without corroding and damaging the device when the in-situ decontamination of the flow field-based biosafety high efficiency particulate air filter device was carried out.Conclusion The characteristics of the internal flow field of the flow field-based biosafety high efficiency particulate air filter device and the influencing factors of the in-situ disinfection effect are revealed,and theoretical references are provided for the optimal design of the device.[Chinese Medical Equipment Journal,2025,46(9):22-27]

Background and purpose:Diffuse large B-cell lymphoma(DLBCL)is subclassified into germinal center B-cell-like(GCB)and non-GCB subtypes,which differ in prognosis and treatment response.However,current distinction still relies on invasive pathological assays.This study developed radiomics and deep-learning models based on multiparametric magnetic resonance imaging(MRI)to non-invasively differentiate the two subtypes preoperatively,thereby reducing dependence on histopathological examination.Methods:This study retrospectively included patients with pathologically confirmed DLBCL diagnosed at Huashan Hospital,Fudan University,and other institutions between March 2013 and December 2024.Using multiparametric MRI data,we developed DLBCL-subtype classification models that combined 4 radiomics-based machine-learning algorithms:support vector machine(SVM),logistic regression(LR),Gaussian process(GP)and Naive Bayes(NB),with 3 deep-learning architectures[densely-connected convolutional networks 121(DenseNet121),residual network 101(ResNet101)and EfficientNet-b5].Additionally,two radiologists with different experience levels independently classified DLBCL on MRI in a blinded fashion.Model and radiologist performance were quantified using the area under the receiver operating characteristic curve(AUC),accuracy(ACC),and F1-score to evaluate their ability to distinguish GCB from non-GCB subtypes.This study was approved by the Ethics Committee of Huashan Hospital of Fudan University(No.KY2024-663),and all patients signed informed consents.Results:A total of 173 patients were enrolled(55 with GCB subtype and 118 with non-GCB subtype).Radiomics and deep learning methods effectively distinguished DLBCL subtypes.Among these,the GP radiomics model(based on T1-CE+T2-FLAIR+ADC sequences)and DenseNet121 deep learning model(based on T1-CE+T2-FLAIR+ADC sequences)demonstrated optimal performance.Both achieved excellent results on the internal validation set(GP:AUC=0.900,ACC=0.896,F1=0.840;DenseNet121:AUC=0.846,ACC=0.854,F1=0.774)and maintained robustness on the external validation set.Furthermore,the classification efficacy of the optimal AI model surpassed that of experienced radiologists(highest physician AUC=0.678).Conclusion:Radiomics and deep-learning models based on multiparametric MRI features can effectively differentiate GCB from non-GCB subtypes of DLBCL.Among them,GP and DenseNet121 exhibit outstanding performance,especially when integrating multi-sequence feature sets for classifying DLBCL subtypes on complex imaging data.