ObjectiveTo investigate the current status of assistive device use and unmet needs among persons with disabilities in Sichuan-Chongqing region, and to identify the key factors associated with satisfaction with these devices. MethodsFrom October, 2024 to February, 2025, quota sampling was adopted to recruit 1 040 persons with disabilities in Sichuan and 260 persons with disabilities in Chongqing. Telephone and online questionnaires were used to collect data on demographic characteristics, status of assistive device utilization and unmet assistive device needs, as well as satisfaction with assistive device use. Correlation analysis, multiple linear regression analysis and structural equation modeling were performed to identify key factors associated with satisfaction. ResultsA total of 1 186 valid responses were collected, of which 942 were from Sichuan Province and 244 from Chongqing Municipality. The utilization rate of assistive devices among persons with disabilities in Sichuan-Chongqing region was 61.9%, and the rate of unmet assistive device needs was 30.6%. The assistive device utilization rate of participants with agricultural household registration (57.98%) was lower than that of participants with non-agricultural household registration (66.86%). The utilization rate showed a J-shaped upward trend with the increase of educational attainment. Educational attainment (P = 0.002), perceived usefulness of assistive devices (P < 0.001), home living environment (P < 0.001), public environment (P < 0.001) and disability type (significant differences were found in visual and hearing disabilities compared with physical disability, P < 0.05) were key predictors of satisfaction with assistive device use. The impact of public environment on satisfaction was exerted through two indirect mediating paths: mediating effect via perceived usefulness of assistive devices (ind₁ = 0.357, 95%CI 0.279 to 0.437, P < 0.001), contributing approximately 70% of the total indirect effect; mediating effect via home living environment (ind₂ = 0.129, 95%CI 0.006 to 0.242, P = 0.038), contributing approximately 25% of the total indirect effect. ConclusionThere is a structural imbalance between assistive device use and demand in Sichuan-Chongqing region. People with psycho-intellectual disabilities are most likely to be excluded from the service chain because they neither perceive need nor access information. Education exerts a robust positive effect on both adoption and satisfaction, so training content must be tailored to different educational levels. Satisfaction is shaped by disability type, device usefulness and environmental factors. Future product development should therefore integrate functional and psychosocial dimensions. Priority should be given to micro-scale home-and-community accessibility retrofits before extending upward to public transportation and employment settings, to maximize the cost-effectiveness of limited funds.

ObjectiveTo construct and evaluate various machine learning models for predicting the risk of chronic obstructive pulmonary disease （COPD） in individuals， thereby providing data support for early screening and intervention. MethodsA total of 823 subjects were selected for this study， comprising 142 individuals in the high-risk group for COPD and 681 individuals in the low-risk group. Data collected included demographic characteristics， smoking history， symptoms （such as cough and shortness of breath）， and scores from the Chronic obstructive pulmonary disease screening questionnaire. Four machine learning algorithms—Logistic regression， random forest， support vector machine， and XGBoost—were utilized to construct risk prediction models. The performance of these models was assessed using 5-fold cross-validation， with evaluation metrics including accuracy， precision， recall， F1-score， area under the receiver operating characteristic curve （AUC）， and average precision （AP）. Furthermore， a feature importance analysis was performed. ResultsThe Logistic Regression model exhibited superior performance， achieving an AUC of 0.982 and an AP of 0.939. This was closely followed by the Random Forest model， which recorded an AUC of 0.975 and an AP of 0.890. Feature importance analysis revealed that smoking history， symptoms of shortness of breath， and body weight were significant predictors. All models demonstrated robust performance in identifying low-risk populations； however， variations were observed in their efficacy in identifying high-risk populations. ConclusionMachine learning models have proven effective in identifying individuals at high risk for COPD. Among these， the Logistic regression model exhibits the best overall performance， efficiently identifying high-risk populations and serving as a valuable clinical auxiliary screening tool. Various models， each with distinct performance characteristics， are suited to different clinical screening scenarios， thereby offering targeted decision-making support for the establishment of a hierarchical and intelligent COPD screening pathway.

Objective To evaluate the characteristics, related therapeutic regimens, risk factors of cardiovascular adverse events (CVAEs) and prognosis in the current therapy of newly diagnosed multiple myeloma (NDMM) patients in China. Methods A retrospective observational study was performed on patients with NDMM treated at Zhongshan Hospital, Fudan University, from January 2013 to October 2021. The propensity score matching at a ratio of 1∶1 was employed to balance baseline confounders between the therapeutic group and the control group, and CVAEs incidences were compared between the corresponding groups. Independent risk factors for CVAEs were identified through Fine-Gray competing risk regression model. Kaplan-Meier survival curves and log-rank tests were used to assess overall survival and progression-free survival of patients. Results A total of 829 patients with NDMM were analyzed, with a median of 33.1 months of follow-up for survivors. CVAEs occurred in 65 patients (7.8%) during first-line treatment, and a total of 74 events were recorded, with 52.7% grade 3 or greater in severity. Arrhythmia (particularly atrial fibrillation), thrombotic event (TE), and heart failure were the most common types. The median time from treatment to the first occurrence of CVAEs was 26 days, while the medium occurrence time of TE was later than the other events (76 d vs 19 d, P＝0.003). The exposure to immunomodulatory drugs was related to a higher incidence of TEs, whereas other therapeutic regimens, including bortezomib, didn’t show the effect of cardiovascular toxicity. Results of multivariate analysis showed that Eastern Cooperative Oncology Group performance status ＞2, symptomatic heart diseases within three months before treatment, and estimated glomerular filtration rate≤50 mL·min⁻¹·(1.73 m²)⁻¹ were independent risk factors for CVAEs. Compared with patients without CVAE, patients who experienced CVAEs had significantly inferior progression-free survival and overall survival, and higher cardiovascular mortality (P＜0.001). Conclusions The incidence of CVAE is relatively high during first-line treatment in NDMM patients, and the prognosis of CVAE patients is poor. The risk of CVAE is significantly increased in patients with underlying cardiovascular diseases.

Objective: To explore the independent risk factors of allogeneic blood transfusion during perioperative period of cytoreductive surgery in patients with ovarian cancer, and to construct a predictive model to facilitate clinical risk assessment and optimize perioperative blood management. Methods: Clinical data of 156 patients who underwent cytoreductive surgery for ovarian cancer in our hospital from January 2020 to December 2025 were retrospectively collected. The patients were divided into transfusion group (n=51) and non-transfusion group (n=105) according to whether they received allogeneic blood transfusion during perioperative period. The 1∶1 propensity score matching (PSM) was used to correct the confounding factors. Independent sample t test or Mann-Whitney U test was used for measurement data, and chisquare test was used for enumeration data. Variables with P<0.05 in univariate analysis were included in binary logistic regression for multivariate analysis to determine independent risk factors. A nomogram model for perioperative allogeneic blood transfusion risk prediction was constructed based on independent risk factors. Bootstrap method (100 samples) was used for internal calibration verification. ROC curve was used to evaluate the discrimination efficiency, and decision curve analysis (DCA) was used to evaluate the clinical net benefit of the model. Results: After propensity matching, the baseline data of the two groups were balanced and comparable. Multivariate logistic regression analysis showed that preoperative prothrombin time (PT) (OR=2.666, 95%CI 1.249~5.693, P=0.011), preoperative hemoglobin (Hb) (OR=0.953, 95%CI 0.923~0.984, P=0.003), intraoperative blood loss (OR=1.004, 95%CI 1.001-1.006, P=0.004), preoperative anemia grade (OR=3.052, 95%CI 1.007-9.252, P=0.049) were independent influencing factors of perioperative allogeneic blood transfusion. The nomogram model based on the above four factors was significant (LR χ =58.617, P<0.001), and the internal calibration curve showed that the predicted probability of the model was in good agreement with the actual probability (mean absolute error=0.042). The area under the ROC curve (AUC) was 0.890, indicating good discrimination efficiency. DCA showed that the clinical net benefit of the model was better than that of the unified transfusion/non-transfusion strategy in the 0-0.45 risk threshold range. Conclusion: Intraoperative blood loss, preoperative PT, preoperative Hb and preoperative anemia grade are independent risk factors for perioperative allogeneic blood transfusion in patients undergoing cytoreductive surgery for ovarian cancer. The nomogram model based on the above factors has good predictive efficacy and clinical hierarchical decision-making value, which can provide reference for clinical implementation of individualized blood management for high-risk patients and reduction of unnecessary blood transfusion rate.

Objective To screen and analyze the differentially expressed genes (DEGs) related to oxidative stress in a silicosis mouse model using transcriptome sequencing technology. Methods i) A total of 30 workers without occupational dust-exposed history were selected as the control group and 17 patients with silicosis were selected as the silicosis group using a judgment sampling method. The levels of glutathione and malondialdehyde in the plasma of workers in the two groups were determined by enzyme-linked immunosorbent assay. ii) RAW264.7 cells in the logarithmic growth phase were randomly divided into the control group and the silica group, treated with 0 and 50 mg/L silica suspensions for 24 hours. Protein expression of superoxide dismutase 2 (SOD2), interleukin-6 (IL-6), and tumor necrosis factor-α (TNF-α) in the cells was determined by Western blotting. iii) The specific pathogen free male C57BL/6 mice were randomly divided into the control group and the silicosis model group, with 10 mice in each group. Mice were exposed to 50 μL of 0.9% sodium chloride solution and silica suspension at a mass concentration of 100 g/L, respectively, using a single tracheal exposure method. After 28 days of exposure, the pathological changes of mouse lung tissues were observed. Transcriptome sequencing was used to screen DEGs in the lung tissues of the silicosis mouse model, and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed. The expression of DEGs was verified using quantitative real-time polymerase chain reaction (qPCR). Results i) The level of malondialdehyde in the patients′ plasma was higher (P<0.01), while the level of glutathione was lower (P<0.01) in the silicosis group than that of the control group. ii) The relative expression of SOD2 protein decreased (P<0.05), while the relative expression of IL-6 and TNF-α proteins increased (all P<0.05) in the silica group of RAW264.7 cells compared with the control group. iii) The pathological results of lung tissues showed that the alveolar structure of mice was destroyed and silicotic nodules were formed in the silicosis model group. Transcriptome sequencing identified 3 703 DEGs, of which 3 199 were significantly down-regulated and 504 were significantly up-regulated. The GO enrichment analysis results showed that the DEGs were significantly enriched in biological processes such as oxidative stress, inflammation, immunity and hypoxia, with cellular components mainly located in membranes, cytoplasm, and nucleus. Molecular functions were enriched in oxidoreductase activity, protein binding, and adenosine triphosphate binding. The KEGG enrichment analysis results showed that the DEGs were mainly involved in the phosphatidylinositol 3-kinase-protein kinase B signaling pathway, cyclic adenosine monophosphate signaling pathway, chemokine signaling pathway, and apoptosis signaling pathway. A total of 28 DEGs involved in the "oxidative stress response" pathway were screened by GO enrichment analysis. The qPCR verification results showed that the relative expression of DEGs carbonic anhydrase 3 (Car3), matrix metalloproteinase 9 (Mmp9), and MutY DNA glycosylase (Mutyh) involved in the "oxidative stress response" of lung tissues in the silicosis model group were lower than those of the control group (all P<0.05). Conclusion Oxidative stress response exists in silicosis patients. The oxidative stress-related genes Car3, Mmp9, and Mutyh are altered in the mouse lung tissues of the silicosis model through the oxidative stress pathway, suggesting that they could be new targets for the treatment of silicosis.

PURPOSE: Early mortality in major trauma has decreased, but MODS remains a leading cause of poor outcomes, driven by trauma-induced cytokine storms that exacerbate injuries and organ damage. METHODS: This prospective cohort study included 79 major trauma patients (ISS >15) treated in the National Center for Trauma Medicine, Peking University People's Hospital, from September 1, 2021, to July 31, 2023. Patients (1) with ISS >15 (according to AIS 2015), (2) aged 15-80 years, (3) admitted within 6 h of injury, (4) having no prior treatment before admission, were included. Exclusion criteria were (1) GCS score <9 or AIS score ≥3 for TBI, (2) confirmed infection, infectious disease, or high infection risk, (3) pregnancy, (4) severe primary diseases affecting survival, (5) recent use of immunosuppressive or cytotoxic drugs within the past 6 months, (6) psychiatric patients, (7) participation in other clinical trials within the past 30 days, (8) patients with incomplete data or missing blood samples. Admission serum inflammatory cytokines and pathophysiological data were analyzed to develop machine learning models predicting MODS within 7 days. LR, DR, RF, SVM, NB, and XGBoost were evaluated based on the area under the AUROC. The SHAP method was used to interpret results. RESULTS: This study enrolled 79 patients with major trauma, and the median (Q₁, Q₃) age was 51 (35, 59) years (52 males, 65.8%). The inflammatory cytokine data were collected for all participants. Among these patients, 35 (44.3%) developed MODS, and 44 (55.7%) did not. Additionally, 2 patients (2.5%) from the MODS group succumbed. The logistic regression model showed strong performance in predicting MODS. Ten key cytokines, IL-18, Eotaxin, MCP-4, IP-10, CXCL12, MIP-3α, MCP-1, IL-1RA, Cystatin C, and MRP8/14 were identified as critical to the trauma-induced cytokine storm and MODS development. Early elevation of these cytokines achieved high predictive accuracy, with an AUROC of 0.887 (95% CI 0.813-0.976). CONCLUSION Trauma-induced cytokine storms are strongly associated with MODS. Early identification of inflammatory cytokine changes enables better prediction and timely interventions to improve outcomes.
Humans ; Prospective Studies ; Middle Aged ; Male ; Female ; Adult ; Aged ; Cytokine Release Syndrome/etiology* ; Adolescent ; Young Adult ; Aged, 80 and over ; Wounds and Injuries/complications* ; Cytokines/blood* ; Multiple Organ Failure/diagnosis* ; Machine Learning

Objective To investigate the effects of ulinastatin(UTI)combined with somatostatin(SOM)on intestinal damage in acute pancreatitis(AP)rats and the possible mechanisms of action.Methods The rats were randomly divided into sham-operated(sham)group,AP group,UTI group,UIT+SOM group and UIT+SOM+JAK2 activator(CA1)group,15 rats/group,respectively.Twelve hours after administration,the intestinal permeability,serum biochemical indicators,and inflammatory factor of rats were detected.HE staining was applied to observe the pathological changes in pancreatic and intestinal tissues.TUNEL method was applied to detect apoptosis in intestinal tissue.Western blot was applied to detect the expression of JAK2/STAT3 signaling pathway proteins.Results Compared with the sham group,the pancreatic tissue of rats in the AP group showed obvious inflammatory cell infiltration,edema and bleeding,while the intestinal mucosa showed inflammatory cell infiltration,irregular villi,shedding and necrosis of intestinal epithelial cells in the intestinal tissue.The intestinal permeability,serum amylase(AMY),lipase(LIPA)activities,diamine oxidase(DAO)activities,tumor necrosis factor α(TNF-α),interleukin-6(IL?6)level,pancreatic and intestinal histopathological scores,intestinal tissue cell apoptosis rate,and p?JAK2/JAK2,p?STAT3/STAT3 ratio all significantly increased(P<0.05).Compared with the AP group,the pancreatic and intestinal tissue injury of rats in the UTI group and UIT+SOM group was reduced,and inflammatory cell infil?tration was reduced.The intestinal permeability,serum AMY,LIPA activities,DAO activities,TNF?α,IL?6 level,pancreatic and intestinal histopathological scores,intestinal tissue cell apoptosis rate and p?JAK2/JAK2,p?STAT3/STAT3 ratio were all decreased(P<0.05).The pancreatic and intestinal tissue injury of rats in the UIT+SOM+CA1 group were more severe,and the trends of the above indicators were opposite to those found in UIT+SOM group(P<0.05).Conclusions The combination of UTI and SOM attenuated intestinal injury in AP rats,and potential mechanism may involve in the inhibition of the JAK2/STAT3 signaling pathway.

BACKGROUND: The American Heart Association recently released a new cardiovascular health (CVH) metric, Life's Essential 8 (LE8), for health promotion. However, the association between LE8 scores and the risk of chronic kidney disease (CKD) remains uncertain. We aimed to explore the association of LE8 scores with new-onset CKD and examine whether socioeconomic deprivation and genetic risk modify this association. METHODS: A total of 286,908 participants from UK Biobank and without prior CKD were included between 2006 and 2010. CVH was categorized using LE8 scores: low (LE8 scores <50), moderate (LE8 scores ≥50 but <80), and high (LE8 scores ≥80). The study outcome was new-onset CKD, ascertained by data linkage with primary care, hospital inpatient, and death data. Cox proportional hazard regression models were used to investigate the association between CVH categories and new-onset CKD. RESULTS: During a median follow-up of 12.5 years, 8857 (3.1%) participants developed new-onset CKD. Compared to the low CVH group, the moderate (adjusted hazards ratio [HR], 0.50; 95% confidence interval [CI]: 0.47-0.53) and high CVH (adjusted HR, 0.31; 95% CI: 0.27-0.34) groups had a significantly lower risk of developing new-onset CKD. The population-attributable risk associated with high vs. intermediate or low CVH scores was 40.3%. Participants who were least deprived ( vs.  most deprived; adjusted HR, 0.75; 95% CI: 0.71-0.79) and with low genetic risk of CKD ( vs.  high genetic risk; adjusted HR, 0.89; 95% CI: 0.85-0.94) had a significantly lower risk of developing new-onset CKD. However, socioeconomic deprivation and genetic risks of CKD did not significantly modify the relationship between LE8 scores and new-onset CKD (both P -interaction >0.05). CONCLUSION Achieving a higher LE8 score was associated with a lower risk of developing new-onset CKD, regardless of socioeconomic deprivation and genetic risks of CKD.
Humans ; Renal Insufficiency, Chronic/epidemiology* ; Male ; Female ; Middle Aged ; Genetic Predisposition to Disease/genetics* ; Aged ; Risk Factors ; Adult ; Proportional Hazards Models ; Socioeconomic Factors

Neuronal injury in glaucoma persists despite effective intraocular pressure (IOP) control, necessitating neuroprotective strategies for retinal ganglion cells (RGCs). In this study, we investigated the neuroprotective role of the γ-hydroxybutyrate analog HOCPCA in a glaucoma model, focusing on its effects on CaMKII signaling, oxidative stress, and neuroinflammatory responses. Retinal tissue from high IOP animal models was analyzed via proteomics. In vitro mouse retinal explants were subjected to elevated pressure and oxidative stress, followed by HOCPCA treatment. HOCPCA significantly mitigated the RGC loss induced by oxidative stress and elevated pressure, preserving neuronal function. It restored CaMKIIα and β levels, preserving RGC integrity, while also modulating oxidative stress and neuroinflammatory responses. These findings suggest that HOCPCA, through its interaction with CaMKII, holds promise as a neuroprotective therapy for glaucoma.
Animals ; Retinal Ganglion Cells/metabolism* ; Glaucoma/pathology* ; Oxidative Stress/drug effects* ; Neuroprotective Agents/pharmacology* ; Mice ; Calcium-Calmodulin-Dependent Protein Kinase Type 2/metabolism* ; Mice, Inbred C57BL ; Disease Models, Animal ; Neuroinflammatory Diseases/drug therapy* ; Neuroprotection/drug effects* ; Male ; Intraocular Pressure/drug effects*

The special natural environment of the plateau brings about great difficulties and challenges to the field medical support.The serious injury treatment group of the field medical team is responsible for the early treatment of the critically injured,which is highly demanding and is more likely to be adversely affected by the plateau environment.Based on the real experiences and current reality,this paper outlines the priorities of work done by the serious injury treatment group on the plateau in terms of personnel selection,professional training,material preparation,site construction,treatment regimens and combat readiness in the hope of providing references for the medical support for China's the military on the plateau.