Work-related musculoskeletal disorders (WMSDs) represent a significant occupational health challenge among healthcare professionals globally, posing substantial threats to physical and mental well-being as well as work sustainability. Adopting preventive behaviors—including ergonomic postural adjustments, optimized work-rest scheduling, proper use of protective and assistive equipment, and regular physical activity—is essential for mitigating the risk of WMSDs. Guided by the social ecological model, the review synthesized current evidence on the determinants of WMSDs preventive behaviors across four levels: intrapersonal characteristics, work environment conditions, interpersonal support, and policy/institutional factors. The findings suggest that higher educational attainment, favorable health-related behavioral patterns, optimized ergonomic work environments, adoption of supportive collaborative systems, strong organizational support, as well as policy safeguards facilitate preventive behavior adoption. Conversely, limited prevention-related knowledge, low risk perception, insufficient physical activity, excessive workload, lack of appropriate protective equipment, inadequate ergonomic training, a prevailing culture of presenteeism, and inadequate policy implementation constitute significant barriers. Multi-dimensional intervention strategies targeting these determinants are warranted to enhance preventive behaviors, reduce the risk of WMSDs, and strengthen occupational health protection for healthcare professionals.

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.

ObjectiveFlavonoids are clinically significant natural products, yet their oxygen-glycosylation in aqueous environments relies heavily on expensive nucleotide-activated sugar donors such as UDP-glucose. Liquid-liquid phase separation (LLPS) creates specialized, membraneless physicochemical microenvironments capable of modulating enzymatic functions and overcoming mass transfer limitations. This study aims to investigate whether the gut microbiota-derived DgpB/C complex—a multienzyme system traditionally recognized for cleaving stable C-glycosidic bonds and facilitating isomerization—can undergo functional remodeling within phase-separated condensates. Our core objective is to elucidate the role of phase separation in expanding enzymatic catalytic plasticity and to provide a non-canonical, highly cost-effective biocatalytic mechanism for the direct utilization of free sugars in the synthesis of O-glycosylated natural products. MethodsAn artificial phase-separation platform was constructed utilizing the multivalent arginine-glycine-glycine motif (RGG)-repeat domain derived from the Caenorhabditis elegans LAF-1 protein. To ensure precise spatial compartmentalization, the DgpB/C complex was specifically recruited into the RGG condensates via a high-affinity SZ1/SZ2 heterodimerization tag system. Condensate formation and substrate partitioning were visualized using light and confocal fluorescence microscopy. The chemical structures and regioselectivity of the reaction products were rigorously characterized using high-performance liquid chromatography (HPLC) and liquid chromatography-mass spectrometry (LC-MS)/MS systems. Furthermore, molecular docking and 20-ns molecular dynamics (MD) simulations were performed via the Hermite platform and Uni-GBSA pipeline to elucidate the structural and thermodynamic basis underlying the phase-transition-induced functional shift. ResultsWe observed that the condensates formed by RGG proteins selectively recruited and significantly enriched hydrophobic flavonoid substrates. Strikingly, within the LLPS microenvironment, the DgpB/C complex—which typically exhibits only degradative or isomerase activities—underwent a profound functional remodeling, transforming into an efficientO-glycosyltransferase. Diverging from canonical pathways that require high-energy donors, the sequestered DgpB/C complex directly utilized unactivated free glucose to catalyze the formation of new O-glycosidic bonds. This remodeled activity was found to be evolutionarily conserved across DgpB/C homologs from diverse gut microbiota strains, such as P581a and W974-1. LC-MS/MS analysis further revealed that the phase-separated environment reduced the regioselectivity constraints of the enzyme, enabling catalytic action on multiple hydroxyl positions of the flavonoid scaffold. MD simulations further indicated that the low-water-activity microenvironment of the condensates reconfigured the conformational dynamics of the catalytic pocket, favoring a spatial orientation highly conducive to dehydration condensation. ConclusionThis study demonstrates that LLPS drives the functional remodeling of the gut microbiota enzyme DgpB/C through the reconfiguration of the physicochemical microenvironment. These findings challenge traditional perceptions regarding the functional boundaries of metabolic enzymes and reveal a novel biocatalytic pathway that bypasses the requirement for nucleotide-activated sugars. Consequently, this provides a highly promising artificial compartmentalization strategy for the green manufacturing of complex, high-value-added natural products.

Objective To investigate the prognostic value of albumin-corrected anion gap (ACAG) in patients with advanced lung cancer receiving immune checkpoint inhibitors (ICIs). Methods A total of 637 patients with advanced lung cancer who received ICI treatment were enrolled. Baseline clinical data and laboratory parameters were collected, and ACAG was calculated. The optimal prognostic Cut-off value for ACAG (11.58 mmol/L) was determined using X-Tile software, and patients were divided into low (≤11.58 mmol/L) and high (>11.58 mmol/L) ACAG groups. Propensity score matching was performed to control for confounding factors. Survival curves were plotted using the Kaplan-Meier method. A Cox proportional hazards regression model was employed to analyze prognostic factors, and subgroup analyses were conducted. Results Among 637 patients, 440 patients remained in the matched cohort. Multivariate Cox analysis showed that after adjusting for clinical and laboratory parameters, ACAG >11.58 mmol/L was an independent risk factor for OS (HR=1.74, 95%CI: 1.02–2.98, P=0.044) but was not an independent predictor for PFS. After adjusting for different sets of covariates, stratified analysis further confirmed that ACAG >11.58 mmol/L was consistently associated with a significantly shortened OS. Survival curves demonstrated that the median OS in the high ACAG group (47.0 months) was significantly lower than that in the low ACAG group. Subgroup analysis indicated that the predictive value of ACAG for OS was more pronounced in males, patients aged <65 years, and patients with squamous cell carcinoma than in other patients. Conclusion In patients with advanced lung cancer treated with ICIs, a high baseline ACAG level (>11.58 mmol/L) is an independent risk factor for shortened OS but is not significantly associated with PFS. ACAG may serve as a simple and effective biological marker for assessing overall survival prognosis in patients with advanced lung cancer undergoing immunotherapy.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective To evaluate the reliability and validity and perform cost-consequence analysis of the brief version of the Montreal cognitive assessment(MoCA)for identifying cognitive impairment in a community-based population ≥50 years of age.Methods The internal consistency and retest reliability of the brief version of the MoCA were analyzed,and the area under the curve(AUC),sensitivity,and specificity were determined to discriminate mild cognitive impairment(MCI)and dementia with the clinical dementia rating(CDR)as the diagnostic criterion.The consistency between the brief version and the full version was analyzed by the Kappa test and the Bland-Altman method,and the number of individuals entering the diagnostic assessment and the overall assessment time were estimated and compared between the two versions.Results A total of 303 individuals were included in this study,of whom 192,94,and 17 had normal cognitive function,MCI,and dementia,respectively.The Cronbach's α and re-test coefficients of the brief version of MoCA were 0.754 and 0.711(P<0.001),respectively.The brief version showed the AUC,sensitivity,and specificity of 0.889,74.5%,and 93.8% for identifying MCI,and 0.994,100%,and 93.8% for identifying dementia,respectively.When the brief version of MoCA was used to identify 94 patients with MCI in 303 individuals,107 individuals required additional diagnostic assessment,with an overall assessment time of 142.4 h,which represented decreases of 21.3% and 32.7%,respectively,compared with those of the full version.When the brief version of MoCA was used to identify 17 patients with dementia in 303 individuals,35 individuals required additional diagnostic assessment,with an overall assessment time of 70.4 h,a decrease of 29.5% in the time cost compared with the full version.Conclusions The brief version of MoCA can identify cognitively impaired individuals in a community-based middle-aged and elderly population,with diagnostic validity comparable to that of the full version but less time cost and fewer individuals needing additional diagnostic assessment to detect true-positive cases.It could be expanded for use in the community-based primary screening setting.
Humans ; Aged ; Middle Aged ; Cognitive Dysfunction/diagnosis* ; Male ; Female ; Mental Status and Dementia Tests ; Reproducibility of Results ; Dementia/diagnosis* ; Sensitivity and Specificity ; Aged, 80 and over ; Cost-Benefit Analysis

The subcortical visual pathway is generally thought to be involved in dangerous information processing, such as fear processing and defensive behavior. A recent study, published in Human Brain Mapping, shows a new function of the subcortical pathway involved in the fast processing of non-emotional object perception. Rapid object processing is a critical function of visual system. Topological perception theory proposes that the initial perception of objects begins with the extraction of topological property (TP). However, the mechanism of rapid TP processing remains unclear. The researchers investigated the subcortical mechanism of TP processing with transcranial magnetic stimulation (TMS). They find that a subcortical magnocellular pathway is responsible for the early processing of TP, and this subcortical processing of TP accelerates object recognition. Based on their findings, we propose a novel training approach called subcortical magnocellular pathway training (SMPT), aimed at improving the efficiency of the subcortical M pathway to restore visual and attentional functions in disorders associated with subcortical pathway dysfunction.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.