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.

Objective To analyze the monitoring results of occupational hazard factors (OHF) in the workplace of key industries in Shaoguan City from 2021 to 2024. Methods A total of 486 enterprises of key industries in Shaoguan City, selected from the "Occupational Diseases Hazardous Items Reporting System" and the "Guangdong Provincial Occupational Health Quality Control Platform" from 2021 to 2024, were used as the research subjects. Data on the declaration of occupational hazard projects, the exposure to OHF and the occupational medical examinations for workers, the usage of protective equipment and the setup of protection facilities in enterprises, and the monitoring results of OHF were analyzed. Results From 2021 to 2024, a total of 486 enterprises of key industries in Shaoguan City were monitored, and the detection rate of OHF exceeding national standard was 57.0%. The exceedance rates in medium/large enterprises and small/micro enterprises were 67.1% and 55.0%, respectively. A total of 51 771 worker-exposures to OHF were recorded, with an exposure rate of 55.8%. Training coverage for enterprise managers, occupational health personnel, and workers were 96.7%, 97.1%, and 98.7%, respectively. Abnormal rates in occupational medical examinations were 3.3%, 0.2%, and 0.8% among workers exposed to noise, dust, and chemical factors, respectively. Provision rates of dust respirators, chemical respirators, hearing protection devices (earplugs and earmuffs) were 93.2%, 85.4% and 86.8%, respectively, with wearing compliance rates of 98.7%, 98.8% and 97.1%. Installation rates of dust control, chemical hazard control, and noise control facilities were 97.2%, 90.3%, and 69.9%, respectively, and all facilities were 100.0% effective. Exceedance rates for OHF and noise increased annually (all P<0.05), whereas those for dust and chemical factors decreased (all P<0.05). The exceedance rates of work position from high to low were dust (18.1%), noise (17.1%) and chemical factors (6.4%). Lead-related position had the highest exceedance rate (31.9%). Industries with higher exceedance rates included metal products manufacturing (27.3%), ferrous metal smelting and rolling (24.1%), and non-metallic mineral products manufacturing (23.7%). Conclusion Workplaces in key industries of Shaoguan City face relatively high risks of occupational hazards. It is essential to focus on noise management, with efforts to strengthen occupational health supervision and guidance for small/micro enterprises as well as industries with severe occupational hazards, promoting the standardization of occupational health management.

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 explore the key components and mechanism of Qufeng Ningfei Powder in treating asthma through qualitative analysis of its blood components, combined with network pharmacology and molecular docking techniques.Methods:The blood components of Qufeng Ningfei Powder were qualitatively analyzed using UPLC-QE-Orbitrap-MS technology. R language was employed to analyze chip data from the GEO database, obtaining a list of differentially expressed genes. SwissTargetPrediction was utilized to predict the targets of drug components. Asthma-related targets were searched through databases such as OMIM, GeneCards, and TTD. The intersection of drug and disease targets was identified using Venn online analysis tool, constructing a "drug-component-target-disease" network to screen potential core components. A protein-protein interaction network (PPI) of core targets was constructed using STRING platform and Cytoscape software. GO function enrichment and KEGG pathway analysis were conducted using DAVID database to validate potential mechanism. Molecular docking was performed to verify the interaction between key components and core targets.Results:A total of 64 components were identified, from which 53 active components were screened, corresponding to 609 targets. Further searching disease databases revealed 96 target genes related to asthma, with an intersection of 6 genes between drug and asthma differential genes. Core target gene IL6 and its corresponding core compound were determined through network topology analysis. Molecular docking confirmed the binding of the main active components of Qufeng Ningfei Powder with the core target protein IL6.Conclusion:The blood components of Qufeng Ningfei Powder may regulate IL-17 through IL6, counteract airway remodeling, oxidative stress, and airway hyperresponsiveness, and thus treat asthma.

Objective:To establish a mass spectrometry method for the determination of characteristic peptides of Galli Gigerii Endothelium Corneum that can identify the authenticity of Galli Gigerii Endothelium Corneum as well as its preparations; To evaluate their quality.Methods:Ultra performance chromatography-electrospray tandem mass spectrometry (UPLC-MS/MS) with the mode of multiple reaction monitoring quantification (MRM) was employed to monitor the ion pairs of m/z 379.21(charge: +2)→571.36, m/z 379.21(charge: +2)→385.26, m/z 785.41(charge: +2)→941.51 and m/z 785.41(charge: +2)→245.08, in order to detect the Galli Gigerii Endothelium Corneum crude drug and its preparations. Results:Chicken specific peptide I and chicken specific peptide Ⅱ could be detected in the 18 batches of Galli Gigerii Endothelium Corneum from different regions, their corresponding extractions and 4 batches of prescription preparations, while the chicken specific peptides were not detected in the 8 batches of endothelium corneums from ducks, geese and pigeons.Conclusions:The method established in this study can effectively supplement the deficiencies in standards of Galli Gigerii Endothelium Corneum and its decoction pieces, improve the quality control standard, and provide a reference for the safety and effectiveness of Galli Gigerii Endothelium Corneum in clinical medication.

Objective:To establish a method for the identification of Qianghuo (Notopterygii Rhizoma et Radix) dispensing granules with PCR for the identification of dispensing granules.Methods:The collected samples were identified by DNA bar code, and the methods of extracting genomic DNA from Notopterygii Rhizoma et Radix, Qianghuo standard decoction and dispensing granules were established. Specific differential primers were designed based on ITS2 sequence, and the PCR amplification system and reaction conditions were optimized.Results:The PCR amplification system and reaction conditions were determined. The target bands of about 216 bp were obtained by amplification of Notopterygii Rhizoma et Radix, Qianghuo standard decoction and dispensing granules, and there was no interference from counterfeit products and blank.Conclusions:The specific PCR identification method of Qianghuo (Notopterygii Rhizoma et Radix) dispensing granules is established, which has good specificity. The detection limit of Notopterygii Rhizoma et Radix is 0.91 ng, and the detection limit of dispensing granules is 7.36 ng, which also provides a reference for the identification of other kinds of TCM dispensing granules.

Objective: To investigate the clinical efficacy of transurethral 450 nm blue laser vaporization of prostate (BVP) and transurethral plasmakinetic resection of the prostate (PKRP) in the treatment of frail elderly patients with benign prostatic hyperplasia (BPH). Methods: A retrospective analysis was conducted on the clinical data of 62 frail elderly BPH patients undergoing BVP (n=32) or PKRP (n=30) in our hospital during Jan.2023 and Jun.2024.The two groups were compared in terms of postoperative hemoglobin drop, operation time, hospital stay, catheter indwelling time, bladder irrigation time, preoperative and postoperative 3-month postvoid residual (PVR), maximum urinary flow rate (Qmax), international prostate symptom score (IPSS), quality of life score (QoL), and postoperative complications. Results: The postoperative hemoglobin drop was lower in the BVP group than in the PKRP group [(1.62±1.04) g/L vs.(7.37±2.37) g/L, P＜0.001].The operation time [(24.53±7.52) min vs. (47.77±11.12) min], hospital stay [(2.78±1.62) d vs. (8.13±0.82) d], catheter indwelling time [(1.84±0.99) d vs. (5.40±0.81) d], and bladder irrigation time [(7.37±2.35) h vs. (51.60±19.72) h] were significantly shorter in the BVP group than in the PKRP group (all P＜0.001).At 3 months postoperatively, both groups showed significant improvements in IPSS, QoL, Qmax, and PVR compared to preoperative levels (P＜0.05), but there were no significant differences between the two groups (P>0.05).The overall incidence of early postoperative complications in the BVP group was lower than that in PKRP group (18.75% vs. 43.33%, P＜0.05).After 3 months of follow-up, there was no significant difference in the incidence of complications between the BVP group and PKRP group(3.13% vs. 13.33%, P=0.14). Conclusion: BVP for the treatment of frail elderly BPH patients is safe and reliable, associated with minimal bleeding, short operation time, catheterization time and hospital stay, and there is no need to discontinue anticoagulant drugs.

Objective To explore the mediating role of occupational well-being in the relationship between professional identity and safety behavior among nurses. Methods A total of 1 006 nurses from ten tertiary general hospitals in eight provincial administrative regions were selected as the research subjects using convenient sampling method. Their safety behavior, professional identity and occupational well-being were investigated using Nurse Safety Behavior Scale, Nurse Professional Identity Scale and Occupational Well-being Scale. Structural equation modeling was performed using AMOS 26.0 to examine the mediating effect of occupational well-being in the relationship between professional identity and safety behavior among nurses. Results The scores for safety behavior, professional identity, and occupational well-being were (53.0±6.1), (123.7±21.2) and (90.8±13.1), respectively. Safety behavior was positively correlated with both professional identity and occupational well-being (correlation coefficients were 0.50 and 0.50, respectively, both P<0.01). Professional identity was positively correlated with occupational well-being (correlation coefficient was 0.51, P<0.01). The multiple linear regression analysis results showed that the higher the professional identity and occupational well-being of nurses, the higher the level of safety behavior (both P<0.05). The result of mediating effect shows that the total effect of occupational identity on safety behavior was 0.498 [95% confidence interval (CI) was 0.405-0.576], and occupational well-being played a mediating role between professional identity and safety behavior among nurses with the mediation effect of 0.156 (95%CI was 0.112-0.205), accounting for 31.33% of the total effect. Conclusion The safety behavior of nurses is at a moderate level. Both professional identity and occupational well-being can affect the safety behavior of nurses. Professional identity can increase the safety behavior of nurses by affecting occupational well-being.

Objective To explore the potential categories of exercise perception in elderly hip arthroplasty(HA)patients,analyze the prediction factors of different categories,and provide references for clinical nursing.Methods A convenience sampling method was used to select elderly HA patients treated in 6 orthopedic wards of 2 tertiary A hospitals in Guilin from October 2024 to February 2025.The general data questionnaire,Exercise Benefits and Barriers Perception Scale for Hip/Knee Throplasty Patients,Tampa Scale of Kinesiophobia,the 5-Factor Modified Frailty Index,and Self-Efficacy for Rehabilitation Outcome Scale were used for investigation.Latent profile analysis was used to identify the potential categories of exercise perception of elderly HA patients,and decision tree model was used to explore the core predictive factors of different profile.Results 222 valid questionnaires were collected,with an effective response rate of 96.52％.A total of 222 elderly HA patients were divided into 3 profiles:high benefit-low barrier group(19.82％),low benefit-high barrier group(22.07％),and mild barrier group(58.11％).Frailty,kinesophobia,rehabilitation self-efficacy,residence,educational level and daily exercise were significant predictors of latent profiles(P＜0.05),and the frailty was located in the root node of the decision tree model.Conclusion The level of exercise perception in elderly HA patients needs to be improved,and shows population heterogeneity.Medical staff should prioritize interventions for low benefit-high barrier and mild-barrier groups,implementing targeted strategies based on profile characteristics and predictive factors to improve their exercise perception.

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.