Objective To construct a prediction model for the population with hypertension and diabetes to assess the risk of chronic kidney disease (CKD), and to provide a scientific basis for formulating targeted CKD prevention and control measures. Methods Based on physical examination data from community residents aged 60 years and above in Nanjing in 2022, 10 221 patients with hypertension and diabetes were selected as the study subjects. Variables associated with CKD prevalence were screened using univariate analysis, and further variable selection was performed using LASSO regression. Finally, a CKD risk prediction model was constructed based on logistic regression. The model's performance was evaluated using the ROC curve and calibration curve. Results The prevalence rate of CKD in the study population was 22.71%, with a mean age of 71.66 years. LASSO regression identified seven variables associated with CKD: age, blood urea nitrogen (BUN), hemoglobin, uric acid, triglyceride-glucose (TyG) index, urine protein-to-creatinine ratio (UPCR), and medical insurance type. The final logistic regression model incorporated six variables: age [OR=1.067 (95% CI: 1.058-1.076)], BUN [OR=1.377 (95% CI: 1.338-1.418)], hemoglobin [OR=0.992 (95% CI: 0.989-0.995)], uric acid [OR=1.004 (95% CI: 1.003-1.004)], TyG index [OR=1.445 (95% CI: 1.324-1.577)], and self-payment medical insurance [OR=1.732 (95% CI: 1.542-1.945)]. The model had an AUC of 0.759 (95% CI: 0.747-0.770) and a Brier score of 0.140 (95% CI: 0.136-0.145), indicating good predictive performance. The calibration curve showed good agreement between the predicted risk and the observed value. Conclusion The constructed LASSO-logistic regression risk prediction model in this study can effectively assess the risk of CKD in elderly individuals aged 60 years and above with hypertension and diabetes, providing a basis for early identification of high-risk individuals and the formulation of targeted CKD prevention and control measures.

OBJECTIVE To confirm trigger items for adverse drug reaction （ADR） induced by bevacizumab， to identify and analyze the occurrence of related ADR， and to establish a predictive model for severe adverse reaction （SAR） caused by this drug. METHODS Based on the global trigger tool （GTT） theory， and referencing the GTT White Paper， drug package inserts and relevant literature， trigger items for bevacizumab-related ADR were confirmed using a single-round Delphi method. Utilizing these established items， electronic medical records of relevant patients at Guilin People’s Hospital from January 2020 to September 2024 were actively screened via the China Hospital Pharmacovigilance System. Pharmacists then identified and tallied the occurrence of bevacizumab-induced ADR. Data from patients with any positive trigger item served as the study subjects （divided into training and test sets at a ratio of 7∶3）， candidate feature variables were selected from 39 related variables using the Boruta algorithm， and the multivariable Logistic regression analysis was performed with the occurrence of SAR as the dependent variable. Based on these candidate features， Logistic Regression， Extreme Gradient Boosting， Light Gradient Boosting Machine， Random Forest， and Categorical Boosting models were constructed. Model performance was evaluated using metrics including the area under the curve （AUC） of receiver operating characteristic curve and recall rate. The Shapley Additive exPlanations （SHAP） method was applied to analyze and interpret the contribution of each variable. A nomogram was constructed based on the optimal model. RESULTS A total of 38 trigger items for active monitoring of bevacizumab-related ADR were determined， comprising 17 laboratory indicators， 13 clinical manifestations， and 8 intervention measures. In total， 483 patients with positive trigger items were included， and 318 patients with bevacizumab-induced ADR were identified， including 83 SARs. The positive predictive values for the trigger items and cases were 43.57% （708/1 625） and 63.84% （318/483）， respectively. Bevacizumab-induced ADR involved 7 systems/organs， with the hematological system being the most frequently involved （64.15%）. The Boruta algorithm selected 7 vari ables： serum potassium， hematocrit， albumin-to-globulin ratio， prealbumin， hypertension history， age and red blood cell count. Multivariable Logistic regression showed that elevated serum potassium levels were associated with a decreased risk of bevacizumab-induced SAR （OR＝0.234， P ＝0.002）， while a history of hypertension （OR＝2.642， P ＝0.006） and increased age （OR＝1.040， P ＝0.025） were associated with an increased risk. The Logistic Regression model demonstrated superior performance with higher AUC， F1 score and recall rate （0.761， 0.447， 0.607）， compared to other models. SHAP evaluation results indicated that variables such as serum potassium， hematocrit， and age ranked highest in importance. CONCLUSIONS Totally 38 trigger entries have been successfully identified for active screening of bevacizumab-related ADR. Elevated serum potassium levels are a protective factor against bevacizumab-induced SAR， whereas the hypertension history and increased age are risk factors. The Logistic Regression model is the optimal predictive model.

Depression is a common mental disorder that falls under the category of "stagnation syndrome" in traditional Chinese medicine （TCM）. Its complex pathogenesis poses challenges for the development of novel therapeutic agents. Currently， clinically used antidepressants are often accompanied by significant side effects， and statistics show that about one-third of patients do not respond to these medications. TCM demonstrates advantages in the treatment of depression through multi-target， multi-pathway and multi-mechanistic approaches. Pinelliae Rhizoma， a phlegm-resolving herb， exhibits effects such as drying dampness and resolving phlegm， as well as eliminating stuffiness and reducing masses. The characteristics of harmonizing Yin and Yang and resolving stagnation in the middle energizer align precisely with the pathogenesis of depression syndrome， demonstrating therapeutic efficacy in affected patients. Literature studies have found that the active ingredients of Pinelliae Rhizoma， such as cavidine， baicalein， β-sitosterol， as well as Pinelliae Rhizoma herb pairs， such as Pinelliae Rhizoma-Magnoliae Officinalis Cortex， Pinelliae Rhizoma-husked sorghum， Pinelliae Rhizoma-Prunellae Spica， exhibit significant antidepressant effects. Furthermore， TCM formulas containing Pinelliae Rhizoma as the principal therapeutic agent， such as Banxia Xiexin Tang， Banxia Houpo Tang， and Wendan Tang， as well as formulas incorporating Pinelliae Rhizoma like compound Xiaochaihu Tang， Chaihu Jia Longgu Muli Tang， and Erchen Tang， have also demonstrated favorable antidepressant efficacy. The antidepressant mechanism of these agents may involve modulation of 5-hydroxytryptamine （5-HT） and dopamine （DA） levels， up-regulation of brain-derived neurotrophic factor （BDNF） expression， regulation of the hypothalamus-pituitary-adrenal （HPA） axis， reduction of oxidative stress， modulation of nuclear transcription factor-κB （NF-κB） signaling pathway， and inhibition of microglia-mediated inflammatory responses. This review summarized the antidepressant mechanisms and clinical applications of the active components， herb pairs， and TCM formulas containing Pinelliae Rhizoma， aiming to provide a reference for modern research on the use of Pinelliae Rhizoma in antidepressant therapy.

Objective To investigate the correlation between the inflammatory burden index(IBI)and major adverse cardiovascular events(MACEs)in patients with ST-segment elevation myocardial infarction(STEMI)after percutaneous coronary intervention(PCI),and to assess the efficacy of IBI in predicting in-hospital and long-term MACEs.Methods This retrospective study included 465 STEMI patients who received PCI treatment in No.904 Hospital of Joint Logistics Support Force of PLA from Dec.2017 to Dec.2021.The IBI was calculated for each patient.The predictive value for in-hospital and long-term MACEs was evaluated using receiver operating characteristic(ROC)curves,and the area under curve(AUC)was calculated.The population was grouped based on the optimal IBI cut-off value for clinical characteristic analysis.Multivariate logistic regression and Cox regression analyses were used to identify factors independently associated with MACEs.The Kaplan-Meier estimator and log-rank test were used to assess the MACE risk of different IBI groups.Results The AUC value for predicting MACEs during hospitalization in STEMI patients using IBI was 0.687,and the AUC value for predicting long-term MACEs was 0.634.Multivariate logistic regression analysis revealed that a high IBI 102.33 mg/L)independently increased the risk of MACEs during hospitalization in STEMI patients(odds ratio=10.900,95％confidence interval[95％CI]4.273-29.180,P＜0.001).Multivariate Cox regression analysis further indicated that during long-term follow-up of STEMI patients,a high IBI(≥55.88 mg/L)independently predicted MACEs(hazard ratio=1.989,95％CI 1.128-3.506,P=0.018).Conclusion IBI is a valuable predictor for the occurrence of MACEs during hospitalization and long-term follow-up after PCI in STEMI patients.

Pancreatic cancer is a highly aggressive malignancy with a poor prognosis,and surgical resection remains the only potentially curative treatment.However,since most patients are diagnosed at a locally advanced or metastatic stage,the feasibility of upfront surgery is limited.In recent years,neoadjuvant and conversion therapy have emerged as crucial strategies for borderline resectable and locally advanced pancreatic cancer,aiming to increase the R0 resection rate and improve survival outcomes.Studies have shown that FOLFIRINOX and gemcitabine plus nab-paclitaxel are commonly used neoadjuvant chemotherapy regimens,with the former being more suitable for patients with good performance status,while the latter is better tolerated across a broader patient population due to its lower toxicity.Additionally,radiotherapy,such as stereotactic body radiotherapy(SBRT),can enhance local tumor control,increase tumor cell eradication,and minimize damage to normal tissues,thereby optimizing overall treatment efficacy.Despite the significant advantages of this approach,challenges remain,including the management of toxic side effects and the optimization of treatment protocols.Future research will focus on personalized precision medicine,integrating genomic sequencing and radiomics to refine neoadjuvant/conversion therapy strategies and exploring the combination of chemotherapy,radiotherapy,immunotherapy,and targeted therapy to improve long-term survival in pancreatic cancer patients.This paper summarizes recent advancements in neoadjuvant/conversion therapy combined with radiotherapy for pancreatic cancer and discusses its potential role in modulating tumor biology and optimizing treatment strategies.

Pancreatic cancer is a highly aggressive malignancy with a poor prognosis,and surgical resection remains the only potentially curative treatment.However,since most patients are diagnosed at a locally advanced or metastatic stage,the feasibility of upfront surgery is limited.In recent years,neoadjuvant and conversion therapy have emerged as crucial strategies for borderline resectable and locally advanced pancreatic cancer,aiming to increase the R0 resection rate and improve survival outcomes.Studies have shown that FOLFIRINOX and gemcitabine plus nab-paclitaxel are commonly used neoadjuvant chemotherapy regimens,with the former being more suitable for patients with good performance status,while the latter is better tolerated across a broader patient population due to its lower toxicity.Additionally,radiotherapy,such as stereotactic body radiotherapy(SBRT),can enhance local tumor control,increase tumor cell eradication,and minimize damage to normal tissues,thereby optimizing overall treatment efficacy.Despite the significant advantages of this approach,challenges remain,including the management of toxic side effects and the optimization of treatment protocols.Future research will focus on personalized precision medicine,integrating genomic sequencing and radiomics to refine neoadjuvant/conversion therapy strategies and exploring the combination of chemotherapy,radiotherapy,immunotherapy,and targeted therapy to improve long-term survival in pancreatic cancer patients.This paper summarizes recent advancements in neoadjuvant/conversion therapy combined with radiotherapy for pancreatic cancer and discusses its potential role in modulating tumor biology and optimizing treatment strategies.

Dental implantology has developed rapidly for over half a century,since pure titanium(99.7％)dental cylindrical threaded implants were exploited and osseointegration was introduced in 1960s by Prof.Br?nemark.The long term retention rates of 10 years or more are over 95％.However,the biological complications jeopardize the long term effects of dental implant treatment seriously.The prevalence of dental implant biological complications varies greatly among different reports resulting from the disparities on the defini-tions of dental implant biological complications.After analyzing and summarizing the major opinions proposed internationally in recent years,the consensus for the definition of dental implant biological complications has been reached.Generally the dental implant biologi-cal implications can be classified into early stage(before restoration)biological complications and late stage(after restoration)biological complications.The early stage biological complications include acute and chronic infections,pain,soft tissue deficiency,and osseointegration failure,etc.The late stage complications include peri-implant diseases(peri-implant mucositis and peri-implantitis),soft tissue deficiency around implant,implant loosening and dropping off,etc.The various risk factors related to different dental implant biological complications,the strategies of the prevention and treatment for the dental implant biological complications have been discussed comprehensively,and the consensus has been reached.It is aimed to advocate the dentist to pay more attention to the early prevention of the biological implant complications,to promote more researches on the implant biological complications,and to help elevate the level of dental implantology in our country.

Objective To investigate the correlation between c-MYC expression and mitochondrial metabolism in malignant duct epithelial cells of pancreatic cancer patients.Methods GEPIA database was used to analyze the correlation between c-MYC expression and overall survival.The expression of c-MYC in tumor tissues was detected by immunohistochemical staining.The difference of DLAT and DLST gene expression between tumor and normal tis-sues was compared in GEPIA database.HP A database was used to analyze the correlation between c-MYC and DLAT,DLST expression in tumor tissues.The expression level of DLAT and DLST in tumor tissues was evaluated by immunofluorescence staining.Results The high expression of c-MYC gene was negatively correlated with overall survival(P＜0.01).The level of c-MYC protein was positively correlated with the pathological grade of PanIN.Compared with normal tissues,the expression of DLAT and DLST genes in pancreatic cancer cells was increased(P＜0.01).The protein level of c-MYC was positively correlated with those of DLAT and DLST(P＜0.01,P＜0.001).Conclusions The high expression of mitochondrial metabolic enzymes DLAT and DLST in pancreatic ductal adenocarcinoma cells is significantly correlated with the expression level of c-MYC,which increases with the progression of pancreatic cancer.

Dental implantology has developed rapidly for over half a century,since pure titanium(99.7％)dental cylindrical threaded implants were exploited and osseointegration was introduced in 1960s by Prof.Br?nemark.The long term retention rates of 10 years or more are over 95％.However,the biological complications jeopardize the long term effects of dental implant treatment seriously.The prevalence of dental implant biological complications varies greatly among different reports resulting from the disparities on the defini-tions of dental implant biological complications.After analyzing and summarizing the major opinions proposed internationally in recent years,the consensus for the definition of dental implant biological complications has been reached.Generally the dental implant biologi-cal implications can be classified into early stage(before restoration)biological complications and late stage(after restoration)biological complications.The early stage biological complications include acute and chronic infections,pain,soft tissue deficiency,and osseointegration failure,etc.The late stage complications include peri-implant diseases(peri-implant mucositis and peri-implantitis),soft tissue deficiency around implant,implant loosening and dropping off,etc.The various risk factors related to different dental implant biological complications,the strategies of the prevention and treatment for the dental implant biological complications have been discussed comprehensively,and the consensus has been reached.It is aimed to advocate the dentist to pay more attention to the early prevention of the biological implant complications,to promote more researches on the implant biological complications,and to help elevate the level of dental implantology in our country.