Globally, over 300 million surgeries are performed each year, and more than 50% of surgeries involve patients aged 65 and older. Aging poses significant challenges to perioperative brain health, as the deterioration of brain structure and function increases susceptibility to postoperative neurological complications. Protecting perioperative brain health remains a worldwide clinical challenge. With senescence, the brain undergoes a progressive decline in homeostasis across various molecular, cellular, and regional functions. Anesthetics and surgical stimuli may accelerate the disruption of brain homeostasis and exacerbate age-related neurodegeneration. This review provides a framework for understanding how anesthesia and surgery can affect brain health in the aging population and contribute to postoperative neurological complications, with a particular focus on perioperative neurocognitive disorder.

Objective Based on the assumption of spatial heterogeneity,the distribution pattern and risk characteristics of health poverty in middle-aged and elderly people with chronic diseases are described from the perspective of spatial differentiation.In order to providing a theoretical basis for the optimization of subsequent poverty reduction policies and a model policy for other countries.Methods It used factor detector and interaction detector to capture the role of single-factor and multi-factor interactions on the spatial differentiation of health poverty,and risk detectors were utilized to explore the high-risk factors in risky areas Results The single factor explanation of medical assistance and health education activities is prominent,and the factors such as PM2.5,old-age dependency ratio and urban unemployment rate have strong interaction.Furthermore,it identified high-risk factor characteristics in areas at high risk of health poverty.Conclusion The spatial differentiation pattern of health poverty among the middle-aged and elderly chronic disease population in China is the result of the synergistic driving effect of multidimensional factors,and there is variability in the risk characteristics among regions.The government should establish a contextual optimization strategy and pay attention to the joint effect of multiple factors to establish a synergistic management system.

Objective To compare the safety of laparoscopic pancreatoduodenectomy(LPD)and open pancreatoduodenectomy(OPD)and analyze the learning curve and safety at different stages of LPD.Methods A retrospective analysis was conducted on the clinical data of 50 LPD patients and 54 OPD patients in the Department of Hepatopancreatobiliary Surgery of Suzhou Hospital Affiliated to Nanjing Medical University from January 2020 to June 2024,and intraoperative and postoperative conditions were compared.The Cumulative Sum(CUSUM)analysis method was used to analyze the technical nodes of the LPD learning curve.Results There were no significant differences in operation time and intraoperative blood loss between the LPD group and the OPD group(P＞0.05).There was also no significant difference in the incidence rates of pancreatic fistula(grade B and C),delayed gastric emptying,postoperative bleeding,biliary fistula and intra-abdominal infection between the LPD group and the OPD group(P＞0.05).A time series plot of operation time was drawn based on the patient's operation time and surgical sequence,yielding a fitted curve.Curve analysis showed initial stage and stable stage were finished at the 17th and 24th cases.The LPD learning curve could be divided into three stages:stage Ⅰ characterized as the initial stage(cases 1 to 17),stage Ⅱ characterized as the stable stage(cases 18 to 24),and stage Ⅲ characterized as the proficient stage(cases 25 to 50).The operation time in stages Ⅱ and Ⅲ was significantly shorter than that in stage Ⅰ,and the intraoperative blood loss in stage Ⅰ was significantly higher than that in stage Ⅲ(P＜0.05).There was no significant difference in the incidence of complications among the three stages(P＞0.05).Conclusion LPD and OPD show no significant differences in indications and safety.The LPD learning curve can be divided into three stages.As the number of surgeries completed increa-ses,the operation time of physicians gradually shortens,and the incidence of complications of patients gradually decreases.

Dental caries is the most common oral disease in children,not only impairing chewing,speech,and other functions while also impacting maxillofacial development and overall health.Recent researches have established the"ecological plaque theory",which posits that an imbalance in the oral plaque microecology leads to the demineralization of teeth hard tissues,as the widely ac-cepted etiology of dental caries.However,the significant variability in the composition and function of children's plaque microorgan-isms,influenced by primary tooth eruption and replacement,changes in diet,and increase in social interactions,makes traditional culture methods inadequate for studying this complex micro-ecosystem.Advances in multi-omics technologies have recently created new opportunities for studiing complex microecology.High-throughput sequencing technologies,such as 16S rRNA gene sequencing and metagenomics,allow for the exploration of microbial diversity and the analysis of genomic functions and their associations with dental caries.Mass spectrometry-based technologies,including metabolomics and proteomics,might elucidate the molecular mecha-nisms of dental caries by analyzing differential metabolites and pathways.This review focuses on the application of multi-omics tech-nologies to explore the relationships between the structure,function,and metabolic state of oral microbial communities and pediatric dental caries.It further discusses the future of oral microorganisms as diagnosis and therapeutic targets for caries,and is expected to provide novel strategies for the prevention and treatment of pediatric dental caries.

Coronary CT angiography(CCTA)plays an important role in study of coronary atherosclerotic plaques,which can be used to assess plaque composition and vulnerability,hence predicting major adverse cardiovascular events.Furthermore,CCTA combined with radiomics analysis is helpful for optimizing cardiovascular risk stratification.The research progresses in CCTA of coronary atherosclerotic plaques were reviewed in this article.

Dental caries is the most common oral disease in children,not only impairing chewing,speech,and other functions while also impacting maxillofacial development and overall health.Recent researches have established the"ecological plaque theory",which posits that an imbalance in the oral plaque microecology leads to the demineralization of teeth hard tissues,as the widely ac-cepted etiology of dental caries.However,the significant variability in the composition and function of children's plaque microorgan-isms,influenced by primary tooth eruption and replacement,changes in diet,and increase in social interactions,makes traditional culture methods inadequate for studying this complex micro-ecosystem.Advances in multi-omics technologies have recently created new opportunities for studiing complex microecology.High-throughput sequencing technologies,such as 16S rRNA gene sequencing and metagenomics,allow for the exploration of microbial diversity and the analysis of genomic functions and their associations with dental caries.Mass spectrometry-based technologies,including metabolomics and proteomics,might elucidate the molecular mecha-nisms of dental caries by analyzing differential metabolites and pathways.This review focuses on the application of multi-omics tech-nologies to explore the relationships between the structure,function,and metabolic state of oral microbial communities and pediatric dental caries.It further discusses the future of oral microorganisms as diagnosis and therapeutic targets for caries,and is expected to provide novel strategies for the prevention and treatment of pediatric dental caries.

Coronary CT angiography(CCTA)plays an important role in study of coronary atherosclerotic plaques,which can be used to assess plaque composition and vulnerability,hence predicting major adverse cardiovascular events.Furthermore,CCTA combined with radiomics analysis is helpful for optimizing cardiovascular risk stratification.The research progresses in CCTA of coronary atherosclerotic plaques were reviewed in this article.

Objective Based on the assumption of spatial heterogeneity,the distribution pattern and risk characteristics of health poverty in middle-aged and elderly people with chronic diseases are described from the perspective of spatial differentiation.In order to providing a theoretical basis for the optimization of subsequent poverty reduction policies and a model policy for other countries.Methods It used factor detector and interaction detector to capture the role of single-factor and multi-factor interactions on the spatial differentiation of health poverty,and risk detectors were utilized to explore the high-risk factors in risky areas Results The single factor explanation of medical assistance and health education activities is prominent,and the factors such as PM2.5,old-age dependency ratio and urban unemployment rate have strong interaction.Furthermore,it identified high-risk factor characteristics in areas at high risk of health poverty.Conclusion The spatial differentiation pattern of health poverty among the middle-aged and elderly chronic disease population in China is the result of the synergistic driving effect of multidimensional factors,and there is variability in the risk characteristics among regions.The government should establish a contextual optimization strategy and pay attention to the joint effect of multiple factors to establish a synergistic management system.

Objective To investigate the prognostic value of atherogenic index of plasma(AIP)for the occurrence of major adverse cardiovascular events(MACE)in elderly patients with acute ST-segment elevation myocardial infarction(STEMI).Methods A total of 355 elderly patients with acute STEMI who received coronary interventional therapy in Department of Cardiology,Affilia-ted Hospital of Hebei University from January to May 2023 were recruited retrospectively,and fi-nally 343 of them with complete telephone follow-up data were included in this study.According to their AIP quartile level,they were divided into A1 group(＜0.212,84 cases),A2 group(0.212-0.339,87 cases),A3 group(0.339-0.434,86 cases)and A4 group(≥0.434,86 cases).The incidences of cardiac death,nonfatal myocardial infarction,ischemia-driven target vessel re-modeling and heart failure re-hospitalization were observed during 1-year follow-up.Kaplan-Meier survival curve was plotted to compare the incidence of MACE in the 4 groups.ROC curve analysis was employed to determine the predictive value of AIP.Results During 1-year follow-up,signifi-cant differences were observed in the proportions of ischemia-driven target vessel revasculariza-tion,heart failure re-hospitalization and non-fatal acute myocardial infarction among the 4 groups(P＜0.05,P＜0.01),and such difference was also seen in the cumulative survival rate among them(log rankx2=8.528,P=0.036).Multivariate Cox proportional hazards regression analysis showed that gender,hypertension,atrial fibrillation,multi-vessel disease,left main artery disease,number of stents,SYNTAX score,Killip grade,BNP,HbA1c,TC,LDL-C and HDL-C levels,and AIP were independent predictors of MACE.The AUC value of AIP in predicting MACE in elderly patients with acute STEMI was 0.855(95％CI:0.776-0.933),with a sensitivity of 66.7％and a specificity of 93.0％.When the above indicators combined together,the AUC value was 0.907(95％CI:0.954-0.987),and the sensitivity and specificity was 100.0％and 90.7％,respectively.The AUC value of combined prediction was significantly better than that of single indicator(P＜0.05).Conclusion AIP is a powerful biomarker,and can be used to predict the prognosis of elderly acute STEMI after coronary interventional therapy,and it combined with Killip grade,SYNTAX score,HbA1c,and number of stents shows better predictive efficacy.

Objective:To explored the correlation between anxiety and depression and cerebral small vessel disease(CSVD)in the elderly patients with type 2 diabetes mellitus(T2DM), and analyzed the influencing factors of anxiety and depression.Methods:Clinical data of 101 elderly T2DM inpatients admitted to the Department of Endocrinology, the Second Affiliated Hospital of Fujian Medical University from July 2020 to December 2021 were retrospectively analyzed, and clinical features, laboratory tests and examination data were collected.The Hamilton Depression Scale and the Hamilton Anxiety Scale were used for assessment, with a cut-off value of 14 points for anxiety and 8 points for depression.Brain scans were performed using 3.0T magnetic resonance scanner, including T1WI sequence, T2WI sequence, 3D-FLAIR sequence, SWI sequence.According to the total MRI load scoring standard of CSVD proposed by Staals, MRI imaging changes of CSVD, namely lacunar foci(LIs), cerebral microhemorrhage(CMBs), perivascular space(PVSs), and white matter high signal(WMHs), were analyzed and scored respectively.Load score ≥1 was defined as CSVD group.According to the above criteria, the enrolled patients were divided into depression group and anxiety group, and the clinical characteristics, biochemical test data and MRI imaging characteristics of CSVD between the two groups were analyzed by single factor analysis, and then Spearman correlation analysis was used to analyze the related factors of the elderly T2DM with anxiety and depression.Binary logistic analysis was used to analyze the risk factors of depression and anxiety in the elderly patients with T2DM.Results:Compared with the non-depressed group, the elderly T2DM patients with depression were older, more female, and the incidence of WMHs and DWMHs was higher( P<0.05).Compared with the non-anxious group, the incidence of WMHs and DWMHs in the elderly T2DM patients with anxiety group was higher( P<0.05).Spearman correlation analysis showed that age( r=0.224, P=0.024), WMHs( r=0.231, P=0.020), PWMHs( r=0.201, P=0.044), DWMHs( r=0.274, P=0.006)was positively correlated with depression in the elderly T2DM, while gender( r=-0.225, P=0.024)、ALT( r=-0.208, P=0.037)、AST( r=-0.204, P=0.041)was negatively correlated with depression in the elderly T2DM.WMHs( r=0.213, P=0.033)and DWMHs( r=0.270, P=0.006)were positively correlated with anxiety in the elderly T2DM.Binary logistic regression analysis showed that gender( OR=0.359, 95% CI: 0.130-0.990, P=0.048), DWMHs(OR=4.373, 95% CI: 1.290-14.828, P=0.018)were the influencing factors for the elderly T2DM patients with depression, and DWMHs( OR=5.000, 95% CI: 1.444-17.317, P=0.011)was the influencing factors for the elderly T2DM patients with anxiety. Conclusions:DWMHs is closely related to the onset of depression and anxiety in the elderly T2DM patients, suggesting that CSVD may be involved in the development of depression and anxiety in the elderly T2DM patients.