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.

ObjectiveThis study aims to explore the mechanism of action of Huangqi Guizhi Wuwutang in treating rheumatoid arthritis （RA）-associated sarcopenia by regulating autophagy and improving skeletal muscle homeostasis based on network pharmacology，bioinformatics，machine learning，and animal experiments. MethodsActive ingredients and targets of Huangqi Guizhi Wuwutang were screened using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform （TCMSP），PubChem，and SwissTargetPrediction databases. RA-related datasets were retrieved from the GEO database，and differential genes were screened. Sarcopenia-related targets were searched through GeneCards and the Comparative Toxicology Database （CTD），and autophagy-related gene sets were downloaded from the Human Autophagy Database （HADb）. Their intersection was analyzed to identify autophagy-related therapeutic targets，followed by enrichment analysis. A protein-protein interaction （PPI） network was constructed using the STRING database，and key targets were selected using multiple methods. Machine learning was applied to predict models based on the expression profiles of intersecting targets，and nomogram models were constructed based on key targets. Molecular docking of the top four active ingredients with key targets was performed using AutoDockVina. A collagen-induced arthritis （CIA） rat model was established using bovine type Ⅱ collagen，with SD rats divided into groups including a blank group，a model group，and low-，medium-，and high-dose groups of Huangqi Guizhi Wuwutang （2.44，4.88，and 9.76 g·kg^-1） and administered for five consecutive weeks. Joint scores and gastrocnemius muscle mass were recorded and analyzed after modeling. Hematoxylin and eosin （HE） staining and Masson's staining were used to observe pathological changes in muscle tissue. Immunofluorescence staining was applied to observe the protein expression levels of myosin heavy chain （MYHC） and insulin-like growth factor-1 （IGF-1） in skeletal muscle. Western blot was used to detect the protein expression levels of autophagy-related proteins ATG5，Beclin1，LC3B，muscle-specific proteins （MuRF1），MaFbx，and MYHC. Real-time quantitative reverse transcription PCR （Real-time PCR） was performed to measure the mRNA expression levels of ATG5，Beclin1，LC3B，MuRF1，MaFbx，and MYHC in muscle tissue. ResultsNetwork pharmacology revealed that Huangqi Guizhi Wuwutang shared 25 common targets with autophagy genes related to RA-associated sarcopenia. The PPI network and machine learning identified six key targets，which were primarily involved in autophagy and inflammatory pathways. Animal experiments showed that compared to the blank group，the model group had significantly higher joint scores （P<0.01） and lower gastrocnemius muscle index （P<0.01）. HE staining indicated a significant reduction in the cross-sectional area of gastrocnemius muscle fibers，with notable inflammatory cell infiltration and muscle atrophy in the model group. Masson's staining revealed obvious collagen fiber proliferation and deposition，with significant muscle fibrosis in the model group. The protein and mRNA expression levels of ATG5，Beclin1，LC3B，MuRF1，and MaFbx were significantly increased （P<0.01），while the protein expression of MYHC and IGF1 was significantly downregulated （P<0.01）. Compared with the model group，the high-dose group of Huangqi Guizhi Wuwutang showed significantly reduced protein and mRNA expression levels of ATG5，Beclin1，LC3B，MuRF1，and MaFbx （P<0.01） and increased protein expression levels of MYHC and IGF1 （P<0.01）. The cross-sectional area of muscle fibers increased，and the muscle cell morphology approached normal. Moreover，pathological abnormalities in the gastrocnemius muscle were significantly improved，with reduced collagen fiber proliferation （P<0.01）. ConclusionHuangqi Guizhi Wuwutang can mediate autophagy by regulating the expression of ATG5，Beclin1，LC3B，and IGF1，thereby reducing skeletal muscle catabolism and improving skeletal muscle homeostasis，which contributes to the treatment of RA-associated sarcopenia. The findings provide insight into the mechanisms underlying the effects of Huangqi Guizhi Wuwutang in the treatment of RA-related sarcopenia and offer a reference for its enhanced clinical application.

The use of wastewater analysis, or wastewater-based epidemiology, to assess and monitor the situation of drug abuse is now widely used at home and abroad. However, there is currently a lack of effective evaluation methods and effective ways of comparison, supervision and standardization, which is not conducive to the analysis and comparisons of data in different countries and regions. Quality control techniques can control the laboratory's analytical errors, safeguard the consistency and comparability of identification conclusions, and promote the further improvement of the level and capacity of urban drug governance, thus playing significant roles. This paper provides an overview of sample collection, sample preservation and transportation, laboratory analysis, back-calculation of drug use and external laboratory quality control in the process of wastewater analysis, with a view to exploring more comprehensive scientific and objective methods and approaches suitable for examining and evaluating qualitative and quantitative analysis of drugs in wastewater among laboratories.

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.

BACKGROUND: Osteoarthritis (OA) is a prevalent joint disorder that significantly impairs quality of life among elderly individuals because of chronic pain and physical disability. As the global burden of OA continues to rise, novel therapeutic strategies are urgently needed. Kaempferide (KA), a flavonoid derived from traditional Chinese herbal medicine, is known for its anti-inflammatory properties. However, the effect of KA on the progression of OA has not been well investigated. This study aimed to explore the therapeutic potential of KA in an OA model and investigate the underlying mechanisms via transcriptomic sequencing. METHODS: An in vitro OA model was established using SW1353 cells treated with interleukin-1 beta (IL-1β) and different concentrations of KA (30, 60, or 90 μmol/L) for 24 h. The anti-inflammatory effects of KA were assessed using quantitative real-time polymerase chain reaction (qRT-PCR), enzyme-linked immunosorbent assay (ELISA), and Western blotting. In vivo , a papain-induced OA rat model was used to evaluate the therapeutic effects of KA through histological and behavioral analyses. Transcriptomic sequencing was performed to explore the differentially expressed genes (DEGs) and related signaling pathways. Statistical analysis was conducted using one-way analysis of variance. RESULTS: KA significantly increased cell viability in the OA chondrocyte model and downregulated the expression of inflammatory cytokines and cartilage degradation markers, with the greatest reduction observed at 90 μmol/L. In vivo , KA treatment mitigated cartilage degradation and improved gait behavior in OA rats. Transcriptomic analysis revealed substantial modulation of DEGs, implicating the hypoxia-inducible factor-1 (HIF-1) signaling pathway as a key mechanism. Further blocking and rescue experiments revealed that KA regulated key molecules within the HIF-1 pathway, specifically interferon-gamma (IFN-γ) and hypoxia-inducible factor 1-alpha (HIF-1α), confirming their critical roles in mediating the therapeutic effects of KA. CONCLUSION KA inhibited the progression of OA by targeting the HIF-1 signaling pathway, reducing inflammation, and cartilage degradation.
Animals ; Osteoarthritis/metabolism* ; Signal Transduction/drug effects* ; Rats ; Rats, Sprague-Dawley ; Humans ; Male ; Hypoxia-Inducible Factor 1/metabolism* ; Interleukin-1beta

Steroid-induced osteonecrosis of femoral head (SONFH) is a disease characterized by femoral head collapse and local pain caused by excessive use of glucocorticoids. Peroxisome proliferator-activated receptor-γ (PPARγ) is mainly expressed in adipose tissue. Wnt/β-catenin, AMPK and other related signaling pathways play an important role in regulating adipocyte differentiation, fatty acid uptake and storage. Bone marrow mesenchymal cells (BMSCs) have the ability to differentiate into adipocytes or osteoblasts, and the use of hormones upregulates PPARγ expression, resulting in BMSCs biased towards adipogenic differentiation. The increase of adipocytes affects the blood supply and metabolism of the femoral head, and the decrease of osteoblasts leads to the loss of trabecular bone, which eventually leads to partial or total ischemic necrosis and collapse of the femoral head. MicroRNAs (miRNAs) are a class of short non-coding RNAs that regulate gene expression by inhibiting the transcription or translation of target genes, thereby affecting cell function and disease progression. Studies have shown that miRNAs affect the progression of SONFH by regulating PPARγ lipid metabolism-related signaling pathways. Therefore, it may be an accurate and feasible SONFH treatment strategy to regulate adipogenic-osteoblast differentiation in BMSCs by targeted intervention of miRNA differential expression to improve lipid metabolism. In this paper, the miRNA-mediated PPARγ-related signaling pathways were classified and summarized to clarify their effects on lipid metabolism in SONFH, providing a theoretical reference for miRNA targeted therapy of SONFH, and then providing scientific evidence for SONFH precision medicine.
MicroRNAs/physiology* ; PPAR gamma/metabolism* ; Femur Head Necrosis/metabolism* ; Humans ; Signal Transduction/physiology* ; Lipid Metabolism/physiology* ; Animals ; Cell Differentiation ; Mesenchymal Stem Cells/cytology* ; Glucocorticoids/adverse effects*

The thought of medicine and food homology and substances with both edible and medicinal values are an important part of China's excellent traditional culture and medicine treasure, playing an important role in human diet and health maintenance for thousands of years. Substances with both edible and medicinal values are a standardized name governed by existing regulations, and many substances with both edible and medicinal values in the list lack important information such as original plants and edible and medicinal parts. Some substances change as the relevant regulations change, which confuses the use and regulation. According to the definition and inclusion conditions of substances with both edible and medicinal values in the Regulation of Substances with Both Edible and Medicinal Values Catalogue, this paper comprehensively reviewed the first batch of 87 substances with both edible and medicinal values published in 2002 by collecting information and investigating the practical application. Some substances supplemented, deleted, and revised were analyzed and discussed, and a complete revised list was compiled, encompassing a total of 90 substances, which were when combined with the 19 substances of the last three batches(published in 2019, 2023, and 2024), amounted to a total of 109 substances. In addition, the substances not currently in the published list but have both edible and medicinal values according to the latest definition were summarized, which revealed at least 27 other substances. Therefore, there were at least 136 substances with both edible and medicinal values. Additionally, the potential substances that could be included in the list of substances with edible and medicinal values were prospected, providing a focus for future expansion of the list. This paper systematically reviewed and revised the list of substances with both edible and medicinal values to lay a foundation for the regulatory authorities to revise the catalog of these substances and provide basic information for promoting the new quality productive forces in the health field and boosting the orderly and rapid development of the big health industry.
China ; Humans ; Drugs, Chinese Herbal/standards* ; Plants, Medicinal/chemistry* ; Medicine, Chinese Traditional