Objective: To develop a prediction model for mild cognitive impairment (MCI) risk among the elderly, so as to provide a tool for MCI early screening. Methods : From July 2022 to September 2024, a multi-stage stratified random cluster sampling method was used to recruit permanent residents aged ≥65 years from the Xinjiang Uygur Autonomous Region as study participants. Data on sociodemographic characteristics, nutritional status, body composition indices, bone mineral density, and handgrip strength were collected through questionnaires and physical examinations. Sarcopenia was defined based on appendicular skeletal muscle index and handgrip strength. MCI was assessed using the Mini-Mental State Examination, with adjustments for educational level. Participants were randomly divided into a training set and a validation set in a 7∶3 ratio. LASSO regression and multivariable logistic regression models were employed to screen for predictors and construct an MCI risk prediction model. The predictive performance of the model was evaluated using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: A total of 1 641 participants were surveyed, including 755 males (46.01%) and 886 females (53.99%). The majority of participants were aged 65-<75 years, comprising 1 154 individuals (70.32%). MCI was detected in 517 participants, corresponding to a detection rate of 31.51%. Resultsfrom LASSO regression and multivariate logistic regression analysis showed that residence (rural, OR = 2.323, 95% CI: 1.682-3.210), age (75-<85 years, OR = 1.405, 95% CI: 1.019-1.937; ≥85 years, OR = 3.655, 95% CI: 1.696-7.875), educational level (primary school, OR = 0.341, 95% CI: 0.247-0.472; junior high school, OR = 0.255, 95% CI: 0.160-0.408; high school, OR = 0.286, 95% CI: 0.154-0.531; bachelor's degree or above, OR = 0.120, 95% CI: 0.041-0.351), history of alcohol consumption (yes, OR = 3.216, 95% CI: 2.164-4.779), risk of malnutrition (yes, OR = 1.464, 95% CI: 1.064-2.014), sarcopenia (yes, OR = 3.197, 95% CI: 2.332-4.385), and waist-to-hip ratio (abnormal, OR = 1.540, 95% CI: 1.159-2.048) were identified as predictive factors for MCI among the elderly. In the training set, the area under the ROC curve, sensitivity, and specificity were 0.788, 0.719, and 0.712, respectively. In the validation set, the corresponding values were 0.784, 0.913, and 0.542, respectively. DCA demonstrated that the model provided a higher clinical net benefit for predicting MCI risk when the risk threshold probability ranged from 0.124 to 0.764. Conclusion The prediction model developed in this study demonstrates good discriminative ability and clinical utility, indicating its substantial value for predicting the MCI risk among the elderly.

Patients with lung cancer experience a heavy symptom burden during the perioperative period, which seriously affects their recovery and quality of life. Traditional symptom management models rely mainly on scheduled ward rounds during hospitalization and outpatient follow-up after discharge. However, they have limitations such as delayed symptom recognition, lack of post-discharge monitoring, and non-quantitative symptom assessment, which often lead to delayed interventions and low patient satisfaction. In recent years, the symptom management model based on electronic patient-reported outcomes (ePRO) has been increasingly valued in clinical practice. Existing high-level evidence from both domestic and international studies indicates that, through proactive monitoring, real-time alerts, and remote interventions, this model enables dynamic and continuous symptom management and helps improve patient recovery and healthcare experience. As a supplement to routine medical care, the ePRO-based symptom management model aims to enhance the quality of care rather than replace existing medical processes. To promote the standardized application of this model in perioperative lung cancer care, this consensus integrates domestic and international evidence. After multiple rounds of voting by more than 50 experts, it formulates 12 consensus statements covering the three core components, symptom monitoring, alerting, and intervention, to provide scientific and practical recommendations for clinical practice.

Objective:To investigate and assess the situation of popularization and promotion of domestically innovative medical devices in Liaoning Province,so as to provide a basis for promoting the allocation policy of domestically innovation medical devices.Methods:Self-made questionnaire and on-site filling survey were conducted to implement investigation and analysis for the allocation situation of newly medical equipment of 188 medical institutions in 9 demonstration regions of the Project on Regional Application and Demonstration of Innovative Medical Equipment in Liaoning Province from 2015 to 2020.The allocation data of medical equipment between before(from 2015 to 2017)and after the demonstration projects were implemented(from 2018 to 2020)were compared.The occupancy rate of domestically medical devices(referred as"occupancy ratio of domestic device")was used as an evaluation indicator to assess the status of equipment allocation and application before and after the projects of application and demonstration were implemented in the region of innovative equipment for diagnosis and treatment.Results:In the 9 demonstrational regions of Liaoning province,the number of newly added domestic medical devices during the period from 2018 to 2020 increased from 1,608 units between 2015 and 2017 to 1,703 units.The occupancy ratio of newly added domestic devices increased from 72.7%to 84.9%.The occupancy ratio of domestic devices of newly added key equipment increased from 63.0%to 83.4%,and the growth rate reached 20.4%.In different districts and different grades of medical institution,the increase and application of domestically medical devices appeared difference.Conclusion:The occupancy rate of newly added domestically medical devices in 9 demonstration regions in Liaoning province has generally increased.However,there are still imbalances between different regions and different grades of medical institutions.The manufacturers of domestically medical devices still need strengthen brand building and marketing promotion,so as to further enhance market competitiveness of domestically medical devices.

Objective To optimize the processing technology of Curculigo orchioides Gaertn.Methods On the basis of single factor experiment,the ratio of material to liquid,frying temperature and frying time were taken as the influencing factors,and the comprehensive scores of appearance traits,curculigoside,orcinol glucoside and orcinol gentiobioside were taken as the evaluation indexes.The optimal processing technology was optimized by Box-Behnken response surface method combined with analytic hierarchy process,and the process verification was carried out.Results The optimal process was as follows:the raw C.orchioides pieces were mixed with the same amount of Evodia rutaecarpa juice,placed in a closed container,moistened until the juice was completely absorbed,stir-fried at 130 ℃ for 6 min,taken out and dried at 60 ℃.For each 100 kg of Curculigo,10 kg of Evodia rutaecarpa was used.Evodia rutaecarpa juice preparation method:10 kg of Evodia rutaecarpa was soaked in 12 times the amount of water for 60 min,decocted for 50 min,extracted for 3 times,combined with the filtrate,and concentrated to 100 kg to obtain Evodia rutaecarpa juice.Conclusion The optimal processing technology of Curculigo orchioides Gaertn.is stable and feasible.

Objective:To apply artificial intelligence（AI）in classifying ovarian tumors on ultrasound images，and compare the diagnostic results of several sonographers with varying seniority levels.Methods:A total of 645 patients diagnosed with adnexal masses via gynecological ultrasound examination at Qilu Hospital of Shandong University from January 2021 to December 2024 were enrolled. Three deep learning architectures，i.e.，Alexnet，Densenet121，and Resnet50 were developed and used to internally test the classification effectiveness of ovarian tumors，while the optimal model was selected for external testing. Two junior sonographers and two senior sonographers were recruited to independently diagnose ovarian tumors in the external test dataset. Subsequently，the benign and malignant results of the model's predictions were disclosed to each sonographer，and their revised diagnoses on the same external test data in combination with the best AI model were recorded.Results:The optimal model achieved an accuracy of 0.941，sensitivity of 0.936，and specificity of 0.944 on the internal test dataset，and maintained robust performance on the external test dataset with accuracy of 0.891，sensitivity of 0.880，and specificity of 0.907. Compared to junior sonographers，the optimal model demonstrated significantly higher sensitivity in discriminating benign from malignant ovarian tumors（0.880 vs. 0.723，0.602；all P<0.05）. No statistically significant difference was observed in diagnostic accuracy between the optimal model and senior sonographer 1（ P=0.05）. With assistance from the optimal model，junior sonographers achieved significant improvements in both sensitivity and specificity（sensitivity：0.723 vs. 0.843，0.602 vs. 0.819；specificity：0.778 vs. 0.833，0.685 vs. 0.741；all P<0.05）. Conclusions:The optimal model achieves comparable performance to that of senior sonographers in ovarian tumor classification. With model assistance，the diagnostic performance of junior sonographers is significantly improved.

Objective To investigate the effect of quercetin on paraptosis induced by low-concentration hydrogen peroxide(H2O2)in human lens epithelial cells(LECs).Methods The human lens epithelial cell line SRA01/04 was cul-tured in vitro and randomly divided into the following groups:control group,H2O2 group(50 μmol·L-1 H2O2),and H2O2+Quercetin group(50 μmol·L-1 H2O2 and 20 μmol·L-1 quercetin).The area and number of endoplasmic reticulum vacuoles in the cells were observed using transmission electron microscopy and super-resolution laser confocal microscopy.Intracellular reactive oxygen species(ROS)levels were detected using the DCFH-DA fluorescent probe.Western blot was performed to detect the expression levels of the following proteins:insulin-like growth factor 1 receptor(IGF1R),phos-phorylated IGF1R(p-IGF1R),ALG-2-interacting protein X(ALIX),glucose-regulated protein 78(GRP78),extracellular signal-regulated kinase(ERK),phosphorylated ERK(p-ERK),P38,and phosphorylated P38(p-P38).Additionally,len-ses from 8-week-old Sprague-Dawley rats were subjected to ex vivo culture and divided into the normal group,the H2O2 treatment group(50 μmol·L-1 H2O2),and the combination treatment group(50 μmol·L-1 H2O2 and 20 μmol·L-1 quer-cetin).The degree of lens opacity was observed under a stereomicroscope,and the area of lens opacity was quantified.The ultrastructure of the endoplasmic reticulum in the rat LECs was observed by transmission electron microscopy.Western blot was used to detect the expression levels of the aforementioned proteins in the rat LECs.Results Compared with the control group,the H2O2 group exhibited significant increases in the area and number of endoplasmic reticulum vacuoles,ROS levels,and the relative protein expression levels of p-IGF1R,p-ERK,p-P38,and GRP78,while the relative expression of ALIX protein was decreased(all P＜0.001).Compared with the H2 O2 group,the H2O2+quercetin group showed signifi-cant reductions in the area and number of endoplasmic reticulum vacuoles,ROS levels,and the relative expression levels of p-IGF1R,p-ERK,p-P38,and GRP78,while the relative expression of ALIX protein was increased(all P＜0.01).In the ex vivo cultured rat lens model,compared with the normal group,the H2O2 group displayed a significant increase in lens opac-ity area,expanded endoplasmic reticulum area in LECs,elevated relative expression levels of p-IGF1R,p-ERK,p-P38,and GRP78 proteins,and decreased ALIX expression(all P＜0.000 1).In contrast,the combination treatment group showed significantly reduced lens opacity area,decreased endoplasmic reticulum area in LECs,lower relative expression of p-IGF1R,p-ERK,p-P38,and GRP78,and increased ALIX expression compared to the H2O2 group(all P＜0.01).Conclu-sion Quercetin inhibits activation of the IGF1R/MAPK signaling pathway and alleviates endoplasmic reticulum stress,thereby effectively attenuating paraptosis in lens epithelial cells.These findings provide a novel strategy for the prevention and treatment of early age-related cataract.

Transmissible gastroenteritis(TGE)is a highly contagious gastrointestinal disease of pigs caused by the transmissible gastroenteritis virus(TGEV).It results in severe diarrhea and high mortality in suckling piglets.As no specific treatment available,vaccination is considered to be one of the most cost-effective measures for preventing and controlling TGE.However,the immune protection provided by vaccines based on traditional TGEV strains is becoming inadequate due to the continuous emergence of strong and new strains of the virus,which poses a serious threat to the pig industry's health and development.Therefore,the development of new vaccines with im-proved efficiency and broad-spectrum coverage is urgently needed.This paper aims to summarize the pathogenic structural characteristics of TGEV,discuss the latest advancements in TGEV vac-cine research and development,and propose future strategies for the development of highly effec-tive TGEV vaccines.The findings of this paper can serve as a valuable reference for effectively pre-venting and controlling TGE in clinical practice.

BACKGROUND: Ferroptosis-related genes play a crucial role in regulating intracellular iron homeostasis and lipid peroxidation, and they are involved in the regulation of tumor growth and drug resistance. The expression of ferroptosis-related genes in tumor tissues can be used to predict patients' future survival times, aiding doctors and patients in anticipating disease progression. Based on the sequencing data of lung adenocarcinoma (LUAD) patients from The Cancer Genome Atlas (TCGA) database, this study identified genes involved in the regulation of ferroptosis, constructed a prognostic model, and evaluated the predictive performance of the model. METHODS: A total of 1467 ferroptosis-related genes were obtained from the GeneCards database. Gene expression profiles and clinical data from 541 LUAD patients were collected from the TCGA database. The expression data of all ferroptosis-related genes were extracted, and differentially expressed genes were identified using R software. Survival analysis was performed on these genes to screen for those with prognostic value. Subsequently, a prognostic risk scoring model for ferroptosis-related genes was constructed using LASSO regression model. Each LUAD patient sample was scored, and the patients were divided into high-risk and low-risk groups based on the median score. Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated. Kaplan-Meier survival curves were generated to assess model performance, followed by validation in an external dataset. Finally, univariate and multivariate Cox regression analyses were conducted to evaluate the independent prognostic value and clinical relevance of the model. RESULTS: Through survival analysis, 121 ferroptosis-related genes associated with prognosis were initially identified. Based on this, a LUAD prognostic risk scoring model was constructed using 12 ferroptosis-related genes (ALG3, C1QTNF6, CCT6A, GLS2, KRT6A, LDHA, NUPR1, OGFRP1, PCSK9, TRIM6, IGF2BP1 and MIR31HG). The results indicated that patients in the high-risk group had significantly shorter survival time than those in the low-risk group (P<0.001), and the model demonstrated good predictive performance in both the training set (1-yr AUC=0.721) and the external validation set (1-yr AUC=0.768). Risk scores were significantly associated with the prognosis of LUAD patients in both univariate and multivariate Cox regression analyses (P<0.001), suggesting that this score is an important prognostic factor for LUAD patients. CONCLUSIONS This study successfully established a LUAD risk scoring model composed of 12 ferroptosis-related genes. In the future, this model is expected to be used in conjunction with the tumor-node-metastasis (TNM) staging system for prognostic predictions in LUAD patients.
Humans ; Ferroptosis/genetics* ; Prognosis ; Adenocarcinoma of Lung/pathology* ; Lung Neoplasms/pathology* ; Male ; Female ; Gene Expression Regulation, Neoplastic ; Middle Aged ; ROC Curve

Objective To investigate the effects of Jiuwei Jianbu Drink on oxidative stress and inflammatory injury in rats with knee osteoarthritis via the high mobility group box-1 protein(HMGB1)/receptor for advanced glycation endproducts(RAGE)/phosphatidyli-nositol 3-kinase(PI3K)/protein kinase B(Akt)signaling pathway.Methods A total of 60 rats were randomly divided into six groups according to the random number table method:blank control group,model group,positive drug group,and Jiuwei Jianbu Drink low-,medium-,and high-dose groups,with 10 rats in each group.Except for the blank control group,knee osteoarthritis models were estab-lished in the other groups,which were then subjected to corresponding treatments.Knee joint diameter and mechanical pain and thermal pain threshold changes were observed.Hematoxylin-eosin staining and safranin O/fast green staining were used to assess pathological changes in cartilage tissue.Oxidative stress markers and inflammatory factor levels in knee joint cartilage tissue of each group were meas-ured.Western blot was used to detect the expression of proteins related to the HMGB1/RAGE/PI3 K/Akt signaling pathway in knee joint tissues.Results Compared with the blank control group,the model group exhibited increased knee joint diameter and decreased mechan-ical pain and thermal pain threshold.Jiuwei Jianbu Drink at all doses groups and the positive control group significantly improved these in-dicators in a dose-dependent manner(P＜0.05).Additionally,the Mankin score and Osteoarthritis Research Society International(OARSI)score in the model group were significantly higher than those in the blank control group,while Jiuwei Jianbu Drink intervention significantly reduced the OARSI score,with the best effect observed in the high-dose group(P＜0.05).Compared with the blank con-trol group,the model group showed increased levels of nitric oxide(NO)and malondialdehyde(MDA),decreased levels of superoxide dismutase(SOD)and glutathione peroxidase(GSH-Px),and significantly elevated levels of tumor necrosis factor-alpha(TNF-α)and interleukin-1β(IL-1β).Compared with the model group,Jiuwei Jianbu Drink significantly inhibited oxidative stress and inflam-matory responses,especially at high doses(P＜0.05).Moreover,the expression of HMGB1,RAGE,p-PI3K/PI3K,and p-Akt/Akt in the model group was higher than that in the blank control group,while Jiuwei Jianbu Drink intervention dose-dependently downregulat-ed the expression of these proteins(P＜0.05).Conclusion Jiuwei Jianbu Drink alleviates oxidative stress and inflammatory injury in rats with knee osteoarthritis by inhibiting the HMGB1/RAGE/PI3K/Akt signaling pathway,thereby improving cartilage pathological chan-ges and demonstrating potential therapeutic value.

Objective To evaluate the diagnostic value of prostate health index(PHI)and prostate health index density(PHID)in identifying intermediate-to high-risk prostate cancer(PCa).Methods Clinical data of 160 treatment-na?ve patients with highly suspected PCa,who underwent initial prostate biopsy in our hospital during Jul.2022 and Feb.2024,were retrospectively analyzed.Data included age,body mass index(BMI),prostate volume(PV),total prostate-specific antigen(tPSA),free PSA(fPSA),[-2]proPSA(p2PSA),PHI and PHID.Biopsy-positive results were stratified according to the EAU D'Amico risk criteria.Receiver operating characteristic(ROC)curve and multivariate logistic regression analysis were employed to assess the diagnostic performance of PHI and PHID in predicting PCa and identifying intermediate-to high-risk PCa.Results There were statistically significant differences in tPSA,p2PSA,PHI and PHID between the negative and positive groups,as well as among the low-,medium-and high-risk groups(P＜0.01).Both PHI and PHID demonstrated good diagnostic performance in predicting PCa(AUC=0.820 8 and 0.875 7,respectively;all P＜0.001),and in identifying intermediate-to high-risk PCa(AUC=0.838 0 and 0.878 3,respectively;all P＜0.001).Compared to the baseline model,the incorporation of PHI and PHID individually into the multivariate model significantly improved the screening performance for PCa(AUC=0.910 and 0.898,respectively;all P＜0.001).Conclusion PHI and PHID exhibit high diagnostic efficacy in screening PCa,particularly in identifying intermediate-to high-risk disease.