Objective To investigate the prevalence of work-related musculoskeletal disorders (WMSDs) in passenger drivers and its influencing factors. Methods A total of 951 passenger drivers in Guangdong Province were selected as the research subjects using the judgmental sampling method. A Musculoskeletal Injury Questionnaire was employed to assess the prevalence of WMSDs in the past year. Results The prevalence of WMSDs in passenger drivers was 41.11%. The result of multivariable logistic regression analysis showed that married drivers had a higher risk of WMSDs than single drivers (P<0.05). The lower the frequency of physical exercise, the longer the driving time per week, the longer the continuous driving time, the more restricted the driving working space, the poorer the foot comfort during driving, and the more affected the normal meal, the higher the risk of WMSDs (all P<0.05). The risk of WMSDs in drivers with sleep time ≤ 8.0 h/d was higher than that in drivers with sleep time > 8.0 h/d (P<0.01), and the risk of WMSDs in drivers with the same posture for a long time on the shoulder was higher than that in drivers without this poor working posture (P<0.01). Conclusion WMSDs were prevalent among passenger drivers, which was associated with demographic and adverse ergonomic factors. Intervention on lifestyle and adverse ergonomic factors could further reduce the risk of WMSDs of passenger drivers.

Objective To investigate the prevalence of common diseases among primary and secondary school students in Yichang City from 2019 to 2022, and to provide a scientific basis for formulating effective intervention measures in the future. Methods By random cluster sampling , 7 schools in urban areas and 5 schools in suburban counties were selected to screen common diseases such as myopia, dental caries, obesity and abnormal spinal curvature. Descriptive epidemiological methods were employed for statistical analysis. Results A total of 17 023 primary and secondary school students were screened from 2019 to 2022. The overall detection rate of common diseases from high to low was myopia (54.12%), caries (36.75%), overweight (15.17%), obesity (11.88%), malnutrition (5.80%), and abnormal spinal curvature (3.49%). The detection rates of myopia and abnormal curvature of the spine showed an increasing trend with years and school stages, while the detection rates of malnutrition and dental caries showed a decreasing trend with years and school stages. The detection rates of overweight and obesity showed no trend difference with years, and the detection rates of obesity showed a decreasing trend with school stages. The rates of myopia, overweight and obesity were higher in urban areas than those in suburban counties, and the rate of dental caries was higher in suburban counties than that in urban areas. The prevalence of overweight, obesity, and malnutrition in boys was higher than that in girls. The prevalence of myopia and dental caries in girls was higher than that in boys. The above differences were statistically significant (all P<0.05). Conclusion Myopia, dental caries, obesity, and abnormal curvature of the spine are the current focus of the prevention and treatment of common diseases in students. There are great differences between different regions, school stages, and genders. The ^“tripartite linkage^” of schools, families, and communities should be achieved with the joint efforts of the education and health departments to actively take targeted intervention measures to reduce the prevalence.

With the continuous development of society, a large number of new chemicals are continuously emerging, which presents a challenge to current risk assessment and safety management of chemicals. Traditional toxicology research methods have certain limitations in quickly, efficiently, and accurately assessing the toxicity of many chemicals, and cannot meet the actual needs. In response to this challenge, computational toxicology that use mathematical and computer models to achieve the prediction of chemical toxicity has emerged. In the meantime, as researchers increasingly pay attention to understanding the interaction mechanisms between exogenous chemical substances and the body from the system level, and multiomics technologies develop rapidly such as genomics, transcriptomics, proteomics, and metabolomics, huge amounts of data have been generated, providing rich information resources for studying the interactions between chemical substances and biological molecules. System toxicology and network toxicology have also developed accordingly. Of these, network toxicology can integrate these multiomics data to construct biomolecular networks, and then quickly predict the key toxicological targets and pathways of chemicals at the molecular level. This paper outlined the concept and development of network toxicology, summarized the main methods and supporting tools of network toxicology research, expounded the application status of network toxicology in studying potential toxicity of exogenous chemicals such as agricultural chemicals, environmental pollutants, industrial chemicals, and foodborne chemicals, and analyzed the development prospects and limitations of network toxicology research. This paper aimed to provide a reference for the application of network toxicology in other fields.

A 20-year-old male patient presented to the Department of Dermatology of Peking Union Medical College Hospital with complaints of an 8-year history of facial scarring, swelling of the lower limbs, and a 4-year history of scalp thickening. Physical examination showed thickening furrowing wrinkling of the skin on the face and behind the ears, ciliary body hirsutism, blepharoptosis, and cutis verticis gyrate. Both lower limbs were swollen, especially the knees and ankles. The skin of the palms and soles of the feet was keratinized and thickened. Laboratory examination using bone and joint X-ray showed periostosis of the proximal middle phalanges and metacarpals of both hands, distal ulna and radius, tibia and fibula, distal femurs, and metatarsals.Genetic testing revealed two variants in SLCO2A1, c.1658T > A and c.96+4A > C.Through multidisciplinary consultation, we confirmed the diagnosis of pachydermoperiostosis.

OBJECTIVE: To determine the role of Tripterygium wilfordii multiglycoside (TGW) in the treatment of psoriatic dermatitis from a cellular immunological perspective. METHODS: Mouse models of psoriatic dermatitis were established by imiquimod (IMQ). Twelve male BALB/c mice were assigned to IMQ or IMQ₊TGW groups according to a random number table. Histopathological changes in vivo were assessed by hematoxylin and eosin staining. Ratios of immune cells and cytokines in mice, as well as PAM212 cell proliferation in vitro were assessed by flow cytometry. Pro-inflammatory cytokine expression was determined using reverse transcription quantitative polymerase chain reaction. RESULTS: TGW significantly ameliorated the severity of IMQ-induced psoriasis-like mouse skin lesions and restrained the activation of CD45⁺ cells, neutrophils and T lymphocytes (all P<0.01). Moreover, TGW significantly attenuated keratinocytes (KCs) proliferation and downregulated the mRNA levels of inflammatory cytokines including interleukin (IL)-17A, IL-23, tumor necrosis factor α, and chemokine (C-X-C motif) ligand 1 (P<0.01 or P<0.05). Furthermore, it reduced the number of γ δ T17 cells in skin lesion of mice and draining lymph nodes (P<0.01). CONCLUSIONS TGW improved psoriasis-like inflammation by inhibiting KCs proliferation, as well as the associated immune cells and cytokine expression. It inhibited IL-17 secretion from γ δ T cells, which improved the immune-inflammatory microenvironment of psoriasis.
Male ; Animals ; Mice ; Tripterygium ; Psoriasis/drug therapy* ; Keratinocytes ; Skin Diseases/metabolism* ; Cytokines/metabolism* ; Imiquimod/metabolism* ; Dermatitis/pathology* ; Disease Models, Animal ; Mice, Inbred BALB C ; Skin/metabolism*

Chinese medicine (CM) diagnosis intellectualization is one of the hotspots in the research of CM modernization. The traditional CM intelligent diagnosis models transform the CM diagnosis issues into classification issues, however, it is difficult to solve the problems such as excessive or similar categories. With the development of natural language processing techniques, text generation technique has become increasingly mature. In this study, we aimed to establish the CM diagnosis generation model by transforming the CM diagnosis issues into text generation issues. The semantic context characteristic learning capacity was enhanced referring to Bidirectional Long Short-Term Memory (BILSTM) with Transformer as the backbone network. Meanwhile, the CM diagnosis generation model Knowledge Graph Enhanced Transformer (KGET) was established by introducing the knowledge in medical field to enhance the inferential capability. The KGET model was established based on 566 CM case texts, and was compared with the classic text generation models including Long Short-Term Memory sequence-to-sequence (LSTM-seq2seq), Bidirectional and Auto-Regression Transformer (BART), and Chinese Pre-trained Unbalanced Transformer (CPT), so as to analyze the model manifestations. Finally, the ablation experiments were performed to explore the influence of the optimized part on the KGET model. The results of Bilingual Evaluation Understudy (BLEU), Recall-Oriented Understudy for Gisting Evaluation 1 (ROUGE1), ROUGE2 and Edit distance of KGET model were 45.85, 73.93, 54.59 and 7.12, respectively in this study. Compared with LSTM-seq2seq, BART and CPT models, the KGET model was higher in BLEU, ROUGE1 and ROUGE2 by 6.00-17.09, 1.65-9.39 and 0.51-17.62, respectively, and lower in Edit distance by 0.47-3.21. The ablation experiment results revealed that introduction of BILSTM model and prior knowledge could significantly increase the model performance. Additionally, the manual assessment indicated that the CM diagnosis results of the KGET model used in this study were highly consistent with the practical diagnosis results. In conclusion, text generation technology can be effectively applied to CM diagnostic modeling. It can effectively avoid the problem of poor diagnostic performance caused by excessive and similar categories in traditional CM diagnostic classification models. CM diagnostic text generation technology has broad application prospects in the future.
Humans ; Medicine, Chinese Traditional ; Pattern Recognition, Automated ; Asian People ; Language ; Learning

Pathological vascular remodeling is a hallmark of various vascular diseases. Previous research has established the significance of andrographolide in maintaining gastric vascular homeostasis and its pivotal role in modulating endothelial barrier dysfunction, which leads to pathological vascular remodeling. Potassium dehydroandrographolide succinate (PDA), a derivative of andrographolide, has been clinically utilized in the treatment of inflammatory diseases precipitated by viral infections. This study investigates the potential of PDA in regulating pathological vascular remodeling. The effect of PDA on vascular remodeling was assessed through the complete ligation of the carotid artery in C57BL/6 mice. Experimental approaches, including rat aortic primary smooth muscle cell culture, flow cytometry, bromodeoxyuridine (BrdU) incorporation assay, Boyden chamber cell migration assay, spheroid sprouting assay, and Matrigel-based tube formation assay, were employed to evaluate the influence of PDA on the proliferation and motility of smooth muscle cells (SMCs). Molecular docking simulations and co-immunoprecipitation assays were conducted to examine protein interactions. The results revealed that PDA exacerbates vascular injury-induced pathological remodeling, as evidenced by enhanced neointima formation. PDA treatment significantly increased the proliferation and migration of SMCs. Further mechanistic studies disclosed that PDA upregulated myeloid differentiation factor 88 (MyD88) expression in SMCs and interacted with T-cadherin (CDH13). This interaction augmented proliferation, migration, and extracellular matrix deposition, culminating in pathological vascular remodeling. Our findings underscore the critical role of PDA in the regulation of pathological vascular remodeling, mediated through the MyD88/CDH13 signaling pathway.
Mice ; Rats ; Animals ; Myeloid Differentiation Factor 88/metabolism* ; Vascular Remodeling ; Cell Proliferation ; Vascular System Injuries/pathology* ; Carotid Artery Injuries/pathology* ; Molecular Docking Simulation ; Muscle, Smooth, Vascular ; Cell Movement ; Mice, Inbred C57BL ; Signal Transduction ; Succinates/pharmacology* ; Potassium/pharmacology* ; Cells, Cultured ; Diterpenes ; Cadherins

Macroautophagy (referred to as autophagy hereafter) is a major intracellular lysosomal degradation pathway that is responsible for the degradation of misfolded/damaged proteins and organelles. Previous studies showed that autophagy protects against acetaminophen (APAP)-induced injury (AILI) via selective removal of damaged mitochondria and APAP protein adducts. The lysosome is a critical organelle sitting at the end stage of autophagy for autophagic degradation via fusion with autophagosomes. In the present study, we showed that transcription factor EB (TFEB), a master transcription factor for lysosomal biogenesis, was impaired by APAP resulting in decreased lysosomal biogenesis in mouse livers. Genetic loss-of and gain-of function of hepatic TFEB exacerbated or protected against AILI, respectively. Mechanistically, overexpression of TFEB increased clearance of APAP protein adducts and mitochondria biogenesis as well as SQSTM1/p62-dependent non-canonical nuclear factor erythroid 2-related factor 2 (NRF2) activation to protect against AILI. We also performed an unbiased cell-based imaging high-throughput chemical screening on TFEB and identified a group of TFEB agonists. Among these agonists, salinomycin, an anticoccidial and antibacterial agent, activated TFEB and protected against AILI in mice. In conclusion, genetic and pharmacological activating TFEB may be a promising approach for protecting against AILI.

Aim To explore the mechanism of hydroxy-a-sanshool in the treatment of diabetic cardiomyopathy ( DCM) based on label-free quantitative proteomics detection technique. Methods DCM model was established by high fat diet and intraperitoneal injection of streptozotocin ( STZ) . They were divided into control group ( CON group ) , diabetic cardiomyopathy group (DCM group) and hydroxy-a-sanshool treatment group ( DCM + SAN group) . The cardiac function of mice was evaluated by echocardiography, the myocardial morphology was observed by pathology staining, the protective mechanism of hydroxy-a-sanshool on diabetic cardiomyopathy was speculated by proteomic technique , and the expression level of cAMP/PKA signaling pathway and key proteins were verified by Western blotting. Results Cardiac ultrasound and pathology staining showed that hydroxy-a-sanshool had protective effect on the heart of DCM mice. Label-free quantitative proteomic analysis was carried out between DCM + SAN group and DCM group, and 160 differential pro-teins were identified by proteomics, in which 127 proteins were up-regulated and 33 proteins were down regulated ; GO secondary functional annotations showed the biological process, molecular function and cellular component; KEGG enrichment analysis showed that cAMP signaling pathway was the most abundant; protein interaction network showed that PKA as the central node interacted with many proteins in the cAMP signaling pathway. Western blot showed that the relative expression of с AMP, PKA protein in DCM group was significantly lower than that in CON group ( P < 0. 05 ) , while the relative expression of cAMP, PKA protein in DCM + SAN group was significantly higher than that in DCM group ( P < 0. 05 ) . Conclusions Hydroxy-a-sanshool has protective effect on heart function of mice with diabetes, which plays a role through cAMP signaling pathway.

italic>Schisandra chinensis is a traditional Chinese medicine with the functions of reinforcing deficiency, strengthening, and inducing astringency, appliable to treat the chronic cough and deficiency in breath, palpitation, and insomnia, etc. A hybrid mass spectrometry scanning strategy (high-definition data-independent/data-dependent acquisition, HDDIDDA), enabling the ion mobility separation and alternating data-independent acquisition/data-dependent acquisition, was established, which, in combination with in-house library-driven automatic peak annotation workflows facilitated by the UNIFI software, was utilized to systematically characterize the multi-classes of chemical components from S. chinensis. The use of an HSS T3 column (100 mm × 2.1 mm, 1.8 μm), 0.1% formic acid in H₂O-acetonitrile as the mobile phase running at the flow rate of 0.3 mL·min^-1, and column temperature at 35 ℃, could enable good separation of the S. chinensis components within 42 min. HDDIDDA scan in both the positive and negative ion modes was employed for data acquisition. Based on the automatic peak annotation, reference standards comparison, MS² data interpretation, and literature analysis, we were able to identify or tentatively characterize 105 compounds in the S. chinensis decoction, involving 56 terpenoids, 42 lignans, five glycosides, one organic acid, and one flavonoid. HDDIDDA scanning can improve the coverage of data acquisition and improve the accuracy of identification, while CCS prediction analysis provides the possibility to distinguish isomers by the ion mobility technology. The results provide reference for the intelligent material basis research of TCM.