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.

Olfactory receptors (ORs) form the largest superfamily of G protein-coupled receptors (GPCRs). Traditionally recognized for their role in the nasal olfactory epithelium, where they mediate the sense of smell, accumulating evidence has firmly established their ectopic expression in non-olfactory tissues, including the intestine, lungs, and kidneys. The intestine, as the primary site for nutrient digestion and absorption, harbors a highly complex chemical environment. To adapt to this environment, the gut employs a sophisticated network of “chemosensors” to monitor luminal contents and maintain homeostasis. Among these sensors, intestinal ORs have emerged as crucial functional components, serving as a molecular bridge that connects environmental chemical signals—such as food-derived odorants—to specific physiological responses. This discovery has significantly deepened our understanding of how dietary flavors and compounds influence intestinal physiology at the molecular level. This review systematically summarizes the expression profiles, ligand classification, and biological functions of ORs within the gastrointestinal tract. Studies indicate that intestinal ORs exhibit distinct spatial distribution patterns across different gut segments and display cell-type specificity, particularly within enterocytes and enteroendocrine cells. These receptors function as versatile sensors capable of recognizing a wide variety of ligands, including exogenous dietary components, gut microbiota metabolites such as short-chain fatty acids, and endogenous small molecules like azelaic acid. Upon activation by specific ligands, intestinal ORs trigger intracellular signaling cascades, primarily involving the AC-cAMP-PKA pathway or calcium influx channels. A major focus of this review is to elucidate the molecular mechanisms by which these receptors regulate the secretion of gut hormones. Activation of specific ORs in enteroendocrine cells has been shown to stimulate the release of hormones such as glucagon-like peptide-1 (GLP-1), peptide YY (PYY), and serotonin (5-HT), thereby modulating systemic energy metabolism, glucose homeostasis, and gastrointestinal motility. Furthermore, the review addresses the critical roles of ORs in immune regulation and pathology. Evidence suggests that specific ORs contribute to the maintenance of intestinal immune homeostasis and may offer protection against inflammation. Beyond their involvement in inflammatory responses, ORs such as Olfr78 have been shown to regulate the differentiation and function of intestinal endocrine cells. Similarly, Olfr544 has been demonstrated to alleviate intestinal inflammation by remodeling the gut microbiome and metabolome. These findings collectively suggest that specific ORs hold promise as therapeutic targets for mitigating intestinal inflammation and maintaining gut homeostasis. Additionally, the review explores the emerging role of ORs in cancer. Although OR expression is often downregulated in tumor tissues compared to normal mucosa, activation of specific ORs by certain ligands can inhibit tumor cell proliferation and migration and induce apoptosis via pathways such as MEK/ERK and p38 MAPK. Conversely, other receptors, such as OR7C1, may serve as biomarkers for cancer-initiating cells. In conclusion, intestinal ORs represent a vital component of the gut’s sensory network. The review also discusses the translational potential of these findings. By elucidating the precise pairing relationships between dietary components and specific ORs, novel therapeutic strategies could be developed. Intestinal ORs may thus emerge as promising targets for nutritional and pharmacological interventions in metabolic diseases, inflammatory bowel diseases, and malignancies.

Objective To analyze the infection status and epidemic trends of soil-borne nematode infections in Yubei, Chongqing City, in 2010,2021, and 2022. Methods The local populations from four survey sites of four towns in 2010 and five sites of five towns in 2021 and 2022 were surveyed regarding their basic information using a unified form. Fecal samples of the participants were collected and tested for soil-borne nematode infections using the modified Kato-Katz thick smear method. Results In 2010, 2 049 participants were surveyed, followed by 1 000 participants in 2021 and 2022. The overall prevalence of parasitic infections declined significantly from 3.86% to 0.20%. In 2010, soil-transmitted nematode included hookworms(3.81%) and roundworms(0.29%). In 2021, the infection rates of roundworms and hookworms were 1.70% and 0.10% respectively. Notably, only Ascaris was identified in 2022(0.20%). The≥60 age group consistently exhibited the highest infection rates across all surveys, followed by the 40-59 age group. The infection rates of males in the three surveys were 3.31%,1.92%, and 0.20% respectively, and those of females were 4.37%, 1.46%, and 0.20% respectively. There was no statistically significant difference in the infection rates between males and females. Educational attainment was inversely associated with infection; in 2010, the highest prevalence was observed among those with primary education or below, whereas in 2021, illiterate or semi-literate individuals showed the highest susceptibility. The occupational distribution of infections in 2010 indicated that retirees (8.33%), farmers(4.86%), and homemakers or unemployed individuals(3.45%)were the most affected. However, in 2021 and 2022, farmers emerged as the predominant occupational group with soil-transmitted nematode infections. Conclusions The infection rate of soil-borne nematodes showed a decreasing trend in Yubei, and the infection species changed from hookworms in 2010 to Ascaris in 2022. Farmers, the elderly, and people with low education levels should continue to be the focus of preventive and control efforts.

Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Given the current ethical issues such as unknown high risks in the clinical application of new biomedical technology， thus， medical institutions need to establish new technology management systems， including clarifying the concept， the assessment and admission mechanism， and ethical management systems of new technology. According to the direction of the development of new technology in the medical institution， the ethics review committee should also perfect the management system of ethics committees and the professional composition of ethics review committee members， improve the ability of ethics committee members to evaluate new biomedical technology， increase the assessment of ethical risks of new technology in the preliminary review stage， strengthen the requirements for emergency plan formulation， as well as set the frequency of the follow-up review based on the risk level of new technology. The ethics review committee should work together with the medical management department to formulate an ethical standardization training system for the clinical application of medical technology in the institution， and regularly conduct training for all staff， to promote medical workers’ understanding of the management requirements of biomedical technologies. Different types of new biomedical technology have different ethical risks. Therefore， the medical management departments and ethics review committees of medical institutions should formulate specific management rules based on the characteristics of new technology types. However， it should be noted that when new biomedical technology generally is first introduced into clinical practice， there are often issues regarding fairness and justice in the use of the technology.

Objective:To explore the efficacy of different second-line treatment strategies in the real world after progression of first-line immunotherapy and its combination therapies in patients with driver gene-negative advanced non-small cell lung cancer (NSCLC) .Methods:A retrospective analysis was conducted on the clinical data of 93 driver gene-negative advanced NSCLC patients who received first-line immunotherapy and its combination therapies from January 1, 2018 to December 31, 2023 at the First Affiliated Hospital of Xinxiang Medical University and Xinxiang Central Hospital. Patients were categorized into immune checkpoint inhibitors (ICIs) -resistant ( n=43) and ICIs-responsive ( n=50) groups according to whether progression free survival (PFS) exceeded 6 months after first-line treatment. Patients were categorized into ICIs-treated ( n=55) and non-ICIs-treated ( n=38), anti-angiogenic-treated ( n=51) and non-anti-angiogenic-treated ( n=42) groups according to the different second-line treatment strategies after progression of first-line immunotherapy and its combination therapies. The median PFS2 (mPFS2) and median overall survival (mOS) 2 after second-line treatment of each group were compared. The Kaplan-Meier method was used for survival analysis. Results:The mPFS2 and mOS2 of 93 advanced NSCLC patients who progressed after first-line ICIs treatment were 4.9 months (95% CI: 4.1-5.7 months) and 14.7 months (95% CI: 11.2-18.2 months). The mPFS2 of patients in the first-line ICIs-responsive and ICIs-resistant groups were 6.0 and 3.8 months, respectively, with no statistically significant difference ( χ2=2.00, P=0.157), and the mOS2 were 25.3 and 11.3 months, respectively, with a statistically significant difference ( χ2=12.13, P<0.001). The mPFS2 of patients in the second-line ICIs-treated group and the non-ICIs-treated group were 5.2 and 4.6 months, respectively, with no statistically significant difference ( χ2=0.16, P=0.687). The mOS2 were 15.1 and 12.7 months, respectively, with no statistically significant difference ( χ2=0.01, P=0.930). The mPFS2 of patients in the second-line anti-angiogenic-treated and non-anti-angiogenic-treated groups were 4.5 and 6.0 months, respectively, with no statistically significant difference ( χ2=0.41, P=0.525), the mOS2 were 14.7 and 16.8 months, respectively, with no statistically significant difference ( χ2=0.01, P=0.943) . Conclusions:After progression of first-line ICIs therapy in patients with driver gene-negative advanced NSCLC, first-line ICIs-responsive patients have significantly longer OS after second-line treatment compared with ICIs-resistant patients. The efficacy of second-line therapy in patients after progression of first-line ICIs therapy does not show significant differences due to the type of treatment strategies.

Objective To explore the effect of repetitive transcranial magnetic stimulation(rTMS)on the sleep disorder and examination results of recruits.Methods At a training base,the Pittsburgh Sleep Quality Index(PSQI)was used to screen the recruits with sleep disorders(total score of PSQI>7).The recruits were randomly assigned to rTMS group or sham rTMS group.Both groups received cognitive and behavioral intervention therapy,including sleep health education and relaxation training.Moreover,the rTMS group was treated with rTMS at the right posterior parietal lobe by continuous theta burst stimulation(cTBS)twice a day at an interval of at least 50 min for 5 consecutive days as a course of treatment with an interval of 2 days for a total of 2 courses of treatment.The coil position and stimulus intensity of sham rTMS group were consistent with the rTMS group,but the head of subjects was perpendicular to the coil plane and there was no effective stimulation.Before and after treatment,PSQI,self-rating depression scale,generalized anxiety disorder-7 and health questionnaire-15 were used to evaluate the sleep,mood and physical state of the recruits.The training result was assessed one month after treatment.The total effective rate of PSQI improvement and examination results were compared between the two groups.The independent influencing factors of excellent examination result were analyzed.Results Among 351 recruits,83 with sleep disorders completed treatment and follow-up.There were 40 patients in the rTMS group and 43 patients in the sham rTMS group.There was no significant difference between the two groups at baseline.After treatment,the total effective rate of PSQI improvement in the rTMS group was higher than that in the sham rTMS group(77.50%vs 53.49%,P=0.022).The average examination score and excellent rate of the rTMS group were higher than those of the sham rTMS group(91.58±3.19 vs 89.47±4.67,P=0.020;85%vs 65.12%,P=0.037).Logistic regression analysis showed that the treatment mode(rTMS group)was the independent influencing factor of excellent examination results(P=0.032).Conclusion rTMS can effectively and safely improve the sleep disorders and examination results of recruits.rTMS may play a positive role in improving the learning and training effect of recruits,which needs to be further proved.

Objective To explore the relationships of job engagement with mental elasticity and resilience in the nurses of burn unit,so as to provide references for the construction of stable nursing team.Methods A total of 159 nurses who were selected from 16 burn centers in 9 provinces and cities such as Shanghai and Jiangsu by convenience sampling from January to April 2024 were enrolled in this study.General data questionnaire,work engagement scale,psychological resilience scales,and medical staff resilience scales were used.Results The total scores of job engagement,mental elasticity and resilience were 34.25±8.59,67.77±12.70,and 74.62±10.51,respectively.The total score and the scores of all dimensions of job engagement were positively correlated with mental elasticity and resilience(P<0.01).Univariate analysis showed that the working years,the number of late night shifts,and children affected the job engagement of the nurses(P<0.05).The optimal scale analysis showed that the number of late night shifts,mental elasticity and stress scores were the main factors affecting the job engagement(P<0.01).The structural equation model showed that both mental elasticity and resilience could directly predict the job engagement,and the path coefficient was 0.372 and 0.387(P<0.01).Mental elasticity indirectly acted on the job engagement through stress resistance,the indirect effect was 0.248,and the mediation effect accounted for 30.8%of the total effect.Conclusion The mental elasticity and resilience of nurses can be improved by optimizing the allocation of human resources and the scheduling structure,so as to increase the job engagement and further stabilize the burn care team.

As early mobilization of patients in the intensive care unit(ICU)is increasingly recognized as a key measure for improving patient prognosis and reducing complications,related research is increasing.However,conventional early mobilization methods are often limited by factors such as patient condition,nursing resources,and environmental factors,making it difficult to achieve optimal results.In recent years,virtual reality(VR)technology,owing to its unique immersion and interactive features,has emerged as a focus of research in the field of ICU patient rehabilitation.This review summarizes the advances in the application of VR technology in the early mobilization of ICU patients,focusing on its advantages over traditional methods,specific implementation approaches,clinical outcomes,and challenges encountered during application.By synthesizing existing evidence,this review aims to provide valuable references for clinical practice and to explore future directions for VR technology in ICU rehabilitation,with the goal of promoting its widespread application in the early mobilization of critically ill patients.