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.

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and the second leading cause of cancer-related mortality worldwide. Despite therapeutic advancements over recent decades, the prognosis for patients with metastatic CRC (mCRC) remains poor. Approximately 2%-4% of mCRC cases exhibit human epidermal growth factor receptor 2 (HER2) amplification or overexpression, defining a distinct molecular subtype. This HER2-positive status is strongly associated with primary resistance to anti-epidermal growth factor receptor (EGFR) therapies, which are the standard of care for patients with RAS wild-type tumors. Beyond its well-established role in breast and gastric cancers, HER2 has emerged as a pivotal biomarker and actionable therapeutic target in mCRC. However, selecting appropriate treatment strategies remains challenging due to patient heterogeneity and diverse molecular subtypes. This review systematically summarizes the molecular biology, diagnostic strategies, and advances in targeted therapies for HER2-positive mCRC. On the diagnostic front, we discuss the applications of immunohistochemistry (IHC), fluorescence in situ hybridization (FISH), next-generation sequencing (NGS), and circulating tumor DNA (ctDNA) detection technologies. We highlight discrepancies in diagnostic criteria across key clinical trials—such as HERACLES, DESTINY, and MOUNTAINEER—underscoring the urgent need for standardized, CRC-specific definitions to ensure consistent patient selection and comparability of efficacy data across studies. Although NGS enables comprehensive genomic profiling, its cost-effectiveness relative to traditional methods must be carefully considered. Therapeutically, we summarize clinical trial data for HER2-directed agents, including tyrosine kinase inhibitors (TKIs) such as tucatinib and lapatinib, monoclonal antibodies like trastuzumab, bispecific antibodies, and antibody-drug conjugates (ADCs) such as trastuzumab deruxtecan. We review dual-targeting strategies and note recent FDA approvals that represent significant milestones in second-line treatment. Additionally, we explore the potential of combining immune checkpoint inhibitors with HER2-targeted therapies to enhance antitumor immunity through mechanisms including antibody-dependent cellular cytotoxicity (ADCC) and modulation of the tumor microenvironment. ADCs enable precise delivery of cytotoxic payloads, reducing off-target toxicity while effectively inhibiting oncogenic pathways. A substantial portion of this review is dedicated to dissecting the molecular mechanisms underlying primary and acquired resistance to HER2-targeted therapies—persistent challenges that limit clinical benefit. These mechanisms include reactivation of downstream signaling pathways such as PI3K/AKT/mTOR and MAPK, concurrent mutations in genes like KRAS or BRAF, and alterations in HER2 expression that compromise treatment efficacy. For instance, specific HER2 mutations (e.g., L755S) can reduce drug binding affinity, while ctDNA monitoring facilitates early detection of emerging resistance clones during disease progression, thereby enabling timely therapeutic adjustments. Tumor heterogeneity and dynamic interactions with the microenvironment further complicate resistance patterns observed in clinical practice. HER2-targeted therapy represents a new frontier in precision oncology for mCRC, offering renewed hope for improving patient outcomes. Realizing this potential will require continued optimization of diagnostic algorithms and treatment workflows. Future efforts must focus on overcoming resistance, validating liquid biopsy approaches for dynamic monitoring, and establishing unified clinical guidelines. HER2 has become an essential biomarker for stratifying mCRC patients beyond traditional RAS and BRAF status, underscoring the shift from empiric treatment to biomarker-driven precision medicine. International, multidisciplinary collaboration will be critical to validate emerging biomarkers and refine treatment algorithms globally.

ObjectiveChronic atrophic gastritis (CAG) is usually diagnosed by gastroscopy and histopathological biopsy. These procedures remain the reference standard, but their invasive nature and resource requirements may limit their use in large-scale population screening and repeated follow-up. A convenient and reproducible method for noninvasive auxiliary screening may help identify individuals who require further endoscopic assessment. Fingertip photoplethysmography (PPG) provides a noninvasive recording of peripheral pulse waves and allows harmonic features to be extracted from the signal. In this study, the so-called meridian-related variables were defined as PPG-derived harmonic parameters labelled according to meridian nomenclature, rather than as direct measurements of meridian physiology. This study aimed to compare these harmonic parameters between patients with CAG and non-CAG controls, identify parameters that remained different after age adjustment, and develop a multivariable model for noninvasive auxiliary screening and pre-endoscopic risk stratification of CAG. MethodsA total of 343 participants were included, comprising 171 patients with CAG and 172 non-CAG controls. CAG diagnosis was established using gastroscopy and histopathology as the reference standard. Fingertip PPG signals were collected using a PPG-based pulse acquisition device. Eight PPG-derived harmonic parameters labelled according to meridian nomenclature were extracted for analysis. Between-group differences were first assessed using nonparametric tests. Age-adjusted analyses were then performed to reduce potential confounding by age. The false discovery rate (FDR) method was applied for multiple-comparison correction. A multivariable logistic regression model integrating age and multiple harmonic parameters was constructed. Model performance was evaluated using receiver operating characteristic (ROC) analysis and the area under the curve (AUC). Internal validation performance was assessed using stratified five-fold cross-validation and bootstrap optimism correction. Threshold performance was examined using both a high-specificity strategy and a Youden index-based cutoff. Decision curve analysis was used to evaluate the model’s net clinical benefit across a range of threshold probabilities. ResultsAll eight harmonic parameters were non-normally distributed. In the univariate analysis, the stomach-labelled harmonic parameter (ST), bladder-labelled harmonic parameter (BL), and liver-labelled harmonic parameter (LR) differed between the CAG and non-CAG groups. After age adjustment and FDR correction, only ST and BL remained statistically significant. Compared with non-CAG controls, patients with CAG showed higher ST values and lower BL values. This finding indicates an associated differential harmonic pattern that was not fully explained by age distribution. However, the discriminative ability of a single harmonic parameter was limited. The best-performing single indicator was ST, with an AUC of 0.652 (95% CI: 0.595-0.707). The multivariable model integrating age and multiple harmonic parameters achieved an AUC of 0.791 (95% CI: 0.743-0.835), representing an improvement of 0.139 over ST alone. In internal validation, stratified five-fold cross-validation yielded a mean AUC of 0.753 (95% CI: 0.715-0.781), and the bootstrap optimism-corrected AUC was 0.748. These results suggest that the model retained moderate discriminative performance after internal validation.At a specificity of at least 95%, the model achieved a sensitivity of only 40.4% (95% CI: 25.7%-49.7%). This high-specificity cutoff may be suboptimal as the preferred threshold for an initial screening setting because of the potential risk of missed CAG cases. The Youden index-based optimal cutoff was 0.419, corresponding to a sensitivity of 80.7% and a specificity of 62.8%. This threshold may better match the practical aim of noninvasive auxiliary screening, where sensitivity is usually prioritized to reduce missed cases. Decision curve analysis showed that, within a threshold probability range of 10%-55%, the model provided higher net clinical benefit than the reference strategies of recommending gastroscopy for all participants or for none. ConclusionPatients with CAG showed associated harmonic differences in fingertip PPG-derived features, mainly characterized by higher ST and lower BL values after age adjustment and FDR correction. Compared with a single harmonic parameter, the multivariable model showed better overall discrimination and retained moderate internal validation performance. These findings suggest that PPG-derived harmonic parameters labelled according to meridian nomenclature may provide auxiliary information for noninvasive auxiliary screening and front-line triage before gastroscopic confirmation in CAG. The present results support further validation rather than immediate clinical implementation. External validation in independent, multicenter, and preferably prospective screening cohorts is needed to assess the model’s generalizability, screening performance, and potential clinical utility.

ObjectiveChronic atrophic gastritis (CAG) is usually diagnosed by gastroscopy and histopathological biopsy. These procedures remain the reference standard, but their invasive nature and resource requirements may limit their use in large-scale population screening and repeated follow-up. A convenient and reproducible method for noninvasive auxiliary screening may help identify individuals who require further endoscopic assessment. Fingertip photoplethysmography (PPG) provides a noninvasive recording of peripheral pulse waves and allows harmonic features to be extracted from the signal. In this study, the so-called meridian-related variables were defined as PPG-derived harmonic parameters labelled according to meridian nomenclature, rather than as direct measurements of meridian physiology. This study aimed to compare these harmonic parameters between patients with CAG and non-CAG controls, identify parameters that remained different after age adjustment, and develop a multivariable model for noninvasive auxiliary screening and pre-endoscopic risk stratification of CAG. MethodsA total of 343 participants were included, comprising 171 patients with CAG and 172 non-CAG controls. CAG diagnosis was established using gastroscopy and histopathology as the reference standard. Fingertip PPG signals were collected using a PPG-based pulse acquisition device. Eight PPG-derived harmonic parameters labelled according to meridian nomenclature were extracted for analysis. Between-group differences were first assessed using nonparametric tests. Age-adjusted analyses were then performed to reduce potential confounding by age. The false discovery rate (FDR) method was applied for multiple-comparison correction. A multivariable logistic regression model integrating age and multiple harmonic parameters was constructed. Model performance was evaluated using receiver operating characteristic (ROC) analysis and the area under the curve (AUC). Internal validation performance was assessed using stratified five-fold cross-validation and bootstrap optimism correction. Threshold performance was examined using both a high-specificity strategy and a Youden index-based cutoff. Decision curve analysis was used to evaluate the model’s net clinical benefit across a range of threshold probabilities. ResultsAll eight harmonic parameters were non-normally distributed. In the univariate analysis, the stomach-labelled harmonic parameter (ST), bladder-labelled harmonic parameter (BL), and liver-labelled harmonic parameter (LR) differed between the CAG and non-CAG groups. After age adjustment and FDR correction, only ST and BL remained statistically significant. Compared with non-CAG controls, patients with CAG showed higher ST values and lower BL values. This finding indicates an associated differential harmonic pattern that was not fully explained by age distribution. However, the discriminative ability of a single harmonic parameter was limited. The best-performing single indicator was ST, with an AUC of 0.652 (95% CI: 0.595-0.707). The multivariable model integrating age and multiple harmonic parameters achieved an AUC of 0.791 (95% CI: 0.743-0.835), representing an improvement of 0.139 over ST alone. In internal validation, stratified five-fold cross-validation yielded a mean AUC of 0.753 (95% CI: 0.715-0.781), and the bootstrap optimism-corrected AUC was 0.748. These results suggest that the model retained moderate discriminative performance after internal validation.At a specificity of at least 95%, the model achieved a sensitivity of only 40.4% (95% CI: 25.7%-49.7%). This high-specificity cutoff may be suboptimal as the preferred threshold for an initial screening setting because of the potential risk of missed CAG cases. The Youden index-based optimal cutoff was 0.419, corresponding to a sensitivity of 80.7% and a specificity of 62.8%. This threshold may better match the practical aim of noninvasive auxiliary screening, where sensitivity is usually prioritized to reduce missed cases. Decision curve analysis showed that, within a threshold probability range of 10%-55%, the model provided higher net clinical benefit than the reference strategies of recommending gastroscopy for all participants or for none. ConclusionPatients with CAG showed associated harmonic differences in fingertip PPG-derived features, mainly characterized by higher ST and lower BL values after age adjustment and FDR correction. Compared with a single harmonic parameter, the multivariable model showed better overall discrimination and retained moderate internal validation performance. These findings suggest that PPG-derived harmonic parameters labelled according to meridian nomenclature may provide auxiliary information for noninvasive auxiliary screening and front-line triage before gastroscopic confirmation in CAG. The present results support further validation rather than immediate clinical implementation. External validation in independent, multicenter, and preferably prospective screening cohorts is needed to assess the model’s generalizability, screening performance, and potential clinical utility.

ObjectiveTo investigate the effect and underlying mechanism of the Wulao Qisun prescription on pathological new bone formation in ankylosing spondylitis （AS）. MethodsSynovial fibroblasts were isolated from the hip joints of AS patients and observed under a microscope to assess cell morphology. The cells were identified using immunofluorescence staining. The isolated AS fibroblasts were divided into blank group， low drug-containing serum group， medium drug-containing serum group， high drug-containing serum group， and positive drug group. After drug intervention， cell proliferation was measured using the cell counting kit-8 （CCK-8） assay to observe fibroblast growth and determine the optimal intervention time. Alkaline phosphatase （ALP） activity was measured using the alkaline phosphatase assay. Protein expression of osteocalcin （OCN）， osteopontin （OPN）， and runt-related transcription factor 2 （Runx2） was detected by Western blot. The mRNA expression levels of Wnt5a， β-catenin， and Dickkopf-1 （DKK-1） were measured by real-time quantitative polymerase chain reaction （Real-time PCR）. ResultsCompared with the blank group， each drug-containing serum group of Wulao Qisun prescription and the positive drug group inhibited the proliferation of AS fibroblasts and reduced ALP expression （P<0.01）. Compared with the blank group， the low drug-containing serum group of Wulao Qisun prescription downregulated β-catenin mRNA expression （P<0.05）. The medium and high drug-containing serum groups and the positive drug group significantly downregulated Wnt5a and β-catenin mRNA expression （P<0.05， P<0.01）， with the positive drug group showing the most pronounced effect （P<0.01）. The high drug-containing serum group and the positive drug group significantly upregulated DKK-1 mRNA expression （P<0.01）. Compared with the blank group， the low drug-containing serum group of Wulao Qisun prescription inhibited the expression of OPN and Runx2 proteins （P<0.05， P<0.01）， while the medium and high drug-containing serum groups and the positive drug group inhibited the expression of OCN， OPN， and Runx2 proteins （P<0.05， P<0.01）. ConclusionThe Wulao Qisun prescription can inhibit the proliferation and osteogenic differentiation of AS fibroblasts， thereby delaying the formation of pathological new bone in AS. The possible mechanism involves the regulation of Wnt/β-catenin-related gene expression， further inhibiting the transcription of downstream target genes.

Objective To develop models for predicting response to chemotherapy combined with immunotherapy in patients with esophageal squamous carcinoma with various machine learning algorithms,and then select the optimal model.Methods A retrospective study was performed for 174 patients with esophageal squamous cell carcinoma undergoing chemotherapy combined with immunotherapy admitted in Department of Thoracic Surgery of the First Affiliated Hospital of Army Medical University from January 2022 to December 2023.The CT scans and clinical information were collected before treatment.They were randomly divided into a training set(n=122)and a testing set(n=52)in a ratio of 7∶3.CT radiomic features were extracted and selected,and then 5 machine-learning algorithms were employed to establish the prediction models,including radiomics model and clinical-radiomics model.Five-fold cross-validation was conducted on the training set,and the performance of the prediction models was evaluated on the testing set using receiver operating characteristic(ROC)curve and the F1 score.The best-performing model was further explained using local interpretable model-agnostic explanations(LIME)algorithm.Results Among the 174 patients,115(66.1%)achieved clinical remission.From the clinical information and CT images,1 clinical features and 10 radiomic features were identified.The area under of ROC curve(AUC)for the radiomics and clinical-radiomics models was 0.750(95%CI:0.616～0.883),and 0.766(95%CI:0.637～0.895),respectively.The F1 score of the optimal clinical-radiomics model was 0.829.LIME algorithm indicated that this best model demonstrated reliability in predicting individual samples.Conclusion The clinical-radiomics prediction model based on machine learning algorithm performs well,and can provide a reference for doctors'clinical decision-making by predicting the response to chemotherapy combined with immunotherapy in patients with esophageal squamous cell carcinoma.

Objective To investigate the role of poly(rC)-binding protein 1(PCBP1)in cadmium(Cd)-induced ferroptosis in mouse neuroblastoma Neuro-2a(N2A)cells.Methods N2A cells were exposed to a concentration gradient of CdCl?(0,1,2,4 μmol/L)for 72 h.Cell viability was assessed by trypan blue staining.Western blotting was employed to detect the expression of ferroptosis-related proteins(GPX4,HMOX1,ACSL4)and PCBP1.Intracellular Fe2? level and lipid peroxidation were detected using FerroOrange and BODIPY581/591 C11 probes,respectively.Ferrostatin-1(Fer-1),a ferroptosis inhibitor,was applied to confirm the critical role of ferroptosis in Cd-induced cytotoxicity.Molecular docking was performed to elucidate the interaction between PCBP1 and ferritin,as well as the binding sites of Cd2?.PCBP1 overexpression plasmid was further constructed for functional validation.Results Cd exposure suppressed cell viability in N2A cells in a dose-dependent manner(P<0.01),significantly down-regulated GPX4 expression(P<0.05),up-regulated HMOX1 expression(P<0.01),and induced Fe2? overload and lipid peroxidation(P<0.01).Molecular docking revealed that Cd2? directly bound to the KH2 domain of PCBP1 and then co-localized on the outer surface of ferritin heavy chain.Overexpression of PCBP1 markedly reversed Cd-induced Fe2? accumulation,GPX4 down-regulation,lipid peroxidation,and cell death.Conclusion Cd exposure disrupts PCBP1-mediated iron homeostasis via transcriptional suppression and competitive displacement of metal ions,and then synergistically drives Fe2? overload-triggered ferroptosis cascades,ultimately leading to neurotoxicity.Targeting PCBP1-mediated iron homeostasis can effectively mitigate Cd-induced neurotoxicity,and may serve as a novel therapeutic strategy.

The single photon counting imaging detector based on microchannel plate(MCP)has the characteristics of high sensitivity and low dark count rate,and has been applied to the optical remote sensing detection of weak ultraviolet spectral signals in space.In this work,by using planar array single photon counting imaging detector as the detector,flat-field concave grating as the splitter,and electrodeless discharge lamp(EDL)as the excitation light source,a dispersion detection system suitable for hydride generation-atomic fluorescence spectrometry(HG-AFS)was developed.The wavelength calibration of the system was carried out,and the negative high pressure and EDL stability time of the planar array single photon counting imaging detector were analyzed and optimized.The characteristic emission spectral lines of As and Bi elements excited in the wavelength range of 180-320 nm were analyzed,and the scattering interference in the wavelength range of 257.3-306.7 nm was discussed.The results showed that the AFS dispersion detection system based on the planar array single photon counting imaging detector could detect and analyze the HG-AFS fluorescence signal initially,and the influence of scattering interference on the detection results was effectively avoided.The system had the advantages including simple structure,no refrigeration and temperature control,no moving parts and simultaneous measurement of multi-band.

Bismuth iodide(BiOI)with different crystal plane ratios of(110)to(001)was synthesized,and typeⅡheterojunction formed between(001)and(110)crystal planes of BiOI was used to improve the separation efficiency of photogenerated electrons and holes.Then the BiOI(001)/(110)was composited with nitrogen-doped graphene quantum dots(N-GQDs)to prepare a ternary composites,which could enhance the range and intensity of light absorption,and prolonged the lifetime of photogenerated electrons due to the formation of Z-scheme heterojunctions between BiOI and N-GQDs,thereby leading to the excellent photoelectric performance of the BiOI/N-GQDs for generating sensitive photoelectric response signals.A photoelectrochemical sensor for sensitive detection of chlorpyrifos(CPF)was designed with BiOI/N-GQDs-modified FTO electrode as a photocathode.The S and N atoms contained in CPF were coordinated with Bi(Ⅲ)on the surface of BiOI,which reduced the photocurrent of BiOI/N-GQDs.The photocurrent change was linear with logarithm of concentration of CPF in the range of 1.5×10-12-5.0×10-9 mol/L,and the detection limit was 1.5×10-12 mol/L.The sensor was highly sensitive,selective and stable,and could be used for determination of trace CPF in environmental and food samples.