BACKGROUND:Disruption of biological rhythms(circadian rhythms)is a typical problem associated with aging.Maintaining the normal function of biological rhythms may be a promising anti-aging strategy.Expression of nuclear factor erthroid 2-related factor 2(Nrf2)is biologically regulated.The glycogen synthase kinase 3(GSK3)system represents a"regulatory valve"that controls subtle oscillations in Nrf2 levels.Circadian changes in the transcript levels of antioxidant genes can influence the response of organisms to oxidative stress.However,the specific molecular mechanism of GSK3/Nrf2 in regulating organismal aging is still puzzling. OBJECTIVE:To search for the general pattern of GSK3/Nrf2-regulated biological rhythms in organismal aging by reviewing the literature in this field. METHODS:The bibliographic method was used to search,review and screen the relevant literature using the keywords of"glycogen synthase kinase 3,nuclear factor erthroid 2-related factor 2,biorhythms and aging"to lay a theoretical foundation for the analysis of the whole paper.Comparative analysis method,through reading and analyzing the obtained literature,was performed to compare the similarities and differences between the literature,thereby providing reasonable theoretical support for the argument.Further comparative analysis of the literature was conducted to clarify the relationship between the relevant indicators as well as the ideas for analysis throughout the text. RESULTS AND CONCLUSION:GSK3 can indirectly regulate Nrf2 expression through the regulation of rhythm genes.GSK3 and Nrf2 are components of anti-aging programs and are associated with biological rhythms.In addition,GSK3/Nrf2 is involved in several metabolic pathways,including those associated with age-related diseases(type 2 diabetes and cancer)and neurodegenerative diseases.

Objective To develop and validate a model to predict the risk of radiation-induced lung injury (RILI) and assess its clinical feasibility. Methods Clinical data from 125 patients with non-small cell lung cancer (NSCLC) were included in the study. The patients were divided into training group (88 cases) and validation group (38 cases). Key predictive factors were identified using univariate and multivariate logistic regression analyses combined with least absolute shrinkage and selection operator (LASSO) regression. A predictive model was constructed and evaluated using a nomogram, receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis. Results The key variables identified by the model were tumor volume (P = 0.017), Eastern Cooperative Oncology Group performance status score (P = 0.035), 95% of the minimum dose to the target volume (P = 0.028), percentage of bilateral lung volume receiving 20 Gy of radiation (P < 0.001), and neutrophil-to-lymphocyte ratio (P = 0.021). The ROC curve showed that the areas under the curve (AUC) for the model in the training and validation groups were 0.987 and 0.992, respectively, indicating good predictive ability. The calibration curve and decision curve further confirmed the accuracy and clinical practicability of the model. Conclusion The predictive model proposed in this study can accurately assess the risk of developing RILI in patients with NSCLC who have undergone radiotherapy, demonstrating its potential value in clinical practice.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Objective:To analyze the spatiotemporal correlation between the surveillance data of influenza in students reported by medical institutions and school absenteeism due to illness, and evaluate the application of Bayesian Structural Time Series model (BSTS) in the prediction of school influenza epidemic.Methods:A total of 13 schools in Dapeng new district of Shenzhen were selected. The incidence data of influenza in schools in Shenzhen from January 1, 2015 to December 31, 2019 were collected from China Disease Control and Prevention Information System and the illness related school absentence data during this period were collected from Shenzhen Student Health Surveillance System, and the spatiotemporal correlation between the data from two systems was analyzed and compared. BSTS was used to make long-term predictions of the monthly incidence of influenza in students in 2019 and short-term predictions of the weekly incidence of influenza in week 1-8 and week 45-52 of 2019 by using the data from two systems.Results:There was a temporal correlation between the data from China Disease Control and Prevention Information System and the data from Shenzhen Student Health Surveillance System ( r=0.93, P<0.001), and the lag of the former one was 1 day ( r=0.73, P<0.001). Influenza outbreaks were randomly distributed in different schools in Shenzhen, and there was no spatial correlation. The root mean square error ( RMSE) and mean absolute error ( MAE) were 0.35 and 0.28, respectively, in the long-term prediction, and the RMSE was 0.33 and 0.34, and the MAE was 0.26 and 0.28, respectively, in the short-term predictions of week 1-8 and week 45-52 of 2019, respectively, showing good prediction accuracy and fitting effect. Conclusion:By analyzing the data from China Disease Control and Prevention Information System and Shenzhen Student Health Surveillance System with BSTS, the dynamics of the school influenza epidemic can be accurately predicted, and effective technical support can be provided for the early warning and prevention and control of influenza epidemic.

Objective:To understand the changes in the prevelance smoking in people aged ≥15 years in Baoji, and provide evidence for the improvement of tobacco control strategies.Methods:Data were from the sampling survey of chronic diseases and their risk factors conducted in Baoji at an interval of five years from 2013 to 2023. The survey used multi-stage cluster random sampling method to select local people aged ≥15 years, and the information about their tobacco use were collected by face-to-face interview. Descriptive epidemiological methods were used to analyze the prevalence of smoking, and χ2 test was used to analyze the change trend. Results:The smoking rate in people aged ≥15 years in Baoji decreased from 2013 to 2023, and the standardized smoking rate decreased by 13.6% in 2023 compared with 2013. The standardized smoking cessation rate increased by 13.4% in 2018 compared with 2013, and the standardized smoking cessation rate decreased by 7.3% in 2023 compared with 2018. The standardized passive smoking rate decreased by 15.1% in 2018 compared with 2013, and the standardized passive smoking rate increased by 8.8% in 2023 compared with 2018. The average daily smoking amount increased by 3.7 cigarettes in 2018 compared with 2013, and the average daily smoking amount decreased by 3.9 cigarettes in 2023 compared with 2018.Conclusion:Progress has been made in tobacco control in Baoji, but problems still exist in tobacco control, to which close attention needs to be paid.

Objective To investigate the value of cranial CT cisternal grading combined with D-dimer(D-D)and Glasgow Coma Scale(GCS)score in predicting the short-term postoperative prog-nosis of patients with severe traumatic brain injury.Methods A total of 165 patients with severe trau-matic brain injury who were treated in the hospital from January 2019 to May 2024 were selected as study subjects,all underwent craniotomy surgery.Postoperative follow-up was conducted for 3 months to analyze the differences in clinical data and preoperative indicators such as cranial CT cisternal grad-ing,D-D levels,and GCS scores between patients with poor and good prognosis.The value of cranial CT cisternal grading,D-D levels,and GCS scores in predicting short-term postoperative poor prognosis in patients with severe traumatic brain injury was also analyzed.Results Compared with patients with good prognosis,patients with poor prognosis had higher proportion of age,cranial CT cisternal grading of Ⅰ to Ⅱ,D-D levels,and GCS scores＜6(P＜0.05).There were no statistically significant differences in C-reactive protein,prothrombin time,activated partial thromboplastin time,international normalized ratio,total cholesterol,triglycerides,high-density lipoprotein cholesterol,and low-density lipoprotein cholesterol levels between patients with poor and good prognosis(P＞0.05).Cranial CT cisternal grading,D-D levels,and GCS scores were influencing factors for short-term postoperative poor prognosis in patients with severe traumatic brain injury(P＜0.05).The area under the curve for poor prognosis by three indicators in combination was 0.941(95％CI,0.906 to 0.975),which was higher than the area under the curve for the individual predictions of cranial CT cisternal grad-ing,D-D levels,and GCS scores(P＜0.05).Conclusion The influencing factors for short-term postoperative prognosis in patients with severe traumatic brain injury include cranial CT cisternal grading,D-D levels,and GCS scores.The model based on these three indicators has certain appli-cation value in predicting patient prognosis.

BACKGROUND:Compensatory changes in sagittal parameters of the cervicothoracic spine after orthopedic surgery in patients with lumbar degenerative scoliosis and their intrinsic relationship,as well as the impact of these changes on quality of life,are still lacking.OBJECTIVE:To evaluate the compensatory alignment of cervical and thoracic vertebrae after correction of lumbar degenerative scoliosis.METHODS:103 patients who underwent surgical correction of lumbar degenerative scoliosis were included in this study.Patients'demographic characteristics and spinal sagittal parameters were assessed,and prediction equations between changes in cervical sagittal parameters and lumbar deformity correction were attempted.Simultaneously,the SRS-22 scale was used to assess the quality of life of patients and to explore the relationship between the compensatory changes of the cervical and thoracic spine after correction and the patients'health-related quality of life.RESULTS AND CONCLUSION:(1)At 3 months and 2 years after surgery,all indicators of the cervical spine and thoracic spine were significantly improved compared with those before surgery(P＜0.05),but there was no significant change at 3 months after surgery compared with 2 years after surgery(P＞0.05).At 3 months and 2 years after surgery,the lumbar spine parameters including lumbar lordosis,C7-S1 sagittal vertical axis,and pelvic incident-lumbar lordosis had significant changes compared with those before surgery(P＜0.05),but the change was not significant at 3 months after surgery compared with 2 years after surgery(P＞0.05).(2)Correlation analysis showed that the lumbar lordosis was highly correlated with the C3-C7 cervical lordosis,C1-C7 cervical lordosis,C2-7 sagittal vertical axis,thoracic inlet angle,and C7-S1 sagittal vertical axis(|r|≥ 0.5,P＜0.000 1).The lumbar lordosis was correlated with the thoracic kyphosis(r=-0.280).(3)Two prediction formulas were established for compensatory changes in cervical spine:cervical lordosis=0.524x,lumbar lordosis=-6.612,C2-7 sagittal vertical axis=-0.263x,and lumbar lordosis=-5.436(P＜0.05,R2＞0.6).(4)When postoperative C2-7 sagittal vertical axis was between 14.4 and 26.8 mm;cervical lordosis was between 9° and 41°,lumbar lordosis was between 42.7° and 68.7°,and sagittal vertical axis was between-40 and 40 mm,patients had better quality of life recovery.(5)It is indicated that significant compensatory changes in the sagittal plane of the cervical spine can be observed after correction of lumbar degenerative scoliosis.We found that each 1° increase in lumbar lordosis was associated with a corresponding increase of about 0.5° in cervical lordosis and a corresponding decrease of about 0.3 mm in the vertical axis of the C2-7 sagittal plane.Patient satisfaction was higher if compensatory changes were closer to normal sagittal plane.

The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobody-antigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.

Primary liver cancer is one of the most common causes of cancer-related deaths in China,with hepatocellular carcinoma(HCC)accounting for 75%-85%.Approximately 70%of HCC patients are in the advanced stage at the time of diagnosis and miss the opportunity for radical surgery,leading to a poor prognosis.Yttrium-90 microsphere selective internal radiation therapy(90Y-SIRT),an emerging therapeutic modality,delivers radioactive microspheres via the hepatic artery to target tumors and uses beta radiation for localized tumor ablation.Compared to conventional transarterial chemoembolization and pharmacotherapy,90Y-SIRT shows the advan-tages of significant clinical benefits,good safety profiles,and broad applicability across diverse patient populations.This article re-views the advances in the application of 90Y-SIRT in HCC treatment.