Aim To establish and evaluate an alternative meth-od for detecting skin sensitization of cosmetics based on local lymph node assay using bromodeoxyuridine(BrdU)with flow cytometry(FCM).Methods(1)25％hexyl cinnamic alde-hyde(HCA)was chosen as a positive control with an acetone:olive oil(4∶1,V/V,AOO)mixture as a vehicle control for the experiment.The dorsal sides of both ears of mice were treated with test solutions on day 1,day 2,and day 3.Brdu solution was injected inter-peritoneally on day 5.On day 6,the bilateral ears and mandibular lymph nodes were excised,and the number of Brdu positive cells was measured by flow cytometry.The stim-ulation index(SI)was calculated to identify whether it was ≥3,in order to establish the method of LLNA:Brdu-FCM.(2)BrdU-FCM test was conducted using a blind method with the fif-teen reference substances listed in OECD TG429 whose skin sensitization potentials were known.The test substances were dissolved in AOO,N,N-dimethylformamide(DMF)or dimeth-yl sulfoxide(DMSO)at three different concentrations.Tests were performed the same as above.SI and EC2.7 were calculat-ed to evaluate whether the test substance was categorized as a skin sensitizer.The reliability and accuracy of the method were validated by comparing the classification of test substances with that in OECD TG429.Results The SI for 25％HCA was 3.9,showing positive in the skin sensitization test.It demonstrated that the LLNA:Brdu-FCM test method was properly implemen-ted.Nine test substances(2,4-dinitrochlorobenzene,4-pheny-lenediamine,cobalt chloride,2-mercaptobenzothiazole,hexyl-cinnamaldehyde,eugenol,phenyl benzoate,cinnamic alcohol,imidazolidinyl urea)were positive,and six test substances(methyl methacrylate,chlorobenzene,isopropanol,lactic acid,methyl salicylate,salicylic acid)were negative.The method was evaluated with sensitivity of 90％,specificity of 100％,positive prediction rate of 100％,negative prediction rate of 83％,false positive rate of 0％,false negative rate of 17％and accuracy of 93％.The LLNA:BrdU-FCM assay could correctly categorize the test substances that were skin sensitizers or non-sensitizers.Conclusion The LLNA:BrdU-FCM assay appears to be a relia-ble predictor of skin sensitization protential of chemicals,and it is expected to an alternative method for identifying skin sensitization as a supplementary in safety evaluation of cosmetic ingredient.

Objective To construct a clinical-radiological nomo-gram model for severe mycoplasma pneumoniae pneumonia coinfec-tion with other pathogens(Co-SMPP)in children.Methods The clinical and radiological data of children with severe mycoplasma pneumoniae pneumonia(SMPP)who underwent nucleic acid testing or bronchoalveolar lavage(BAL)were analyzed retrospectively.The data analysis were performed by using SPSS 27.0 software.The group comparison between simple SMPP and Co-SMPP children was conducted by using t-tests,Mann-Whitney U tests,or chi-square tests.Nomogram analysis was performed by using R software and rms packages.The predictive performance of the model was evaluated by using the receiver operating characteristic(ROC)curve.Results A total of 194 SMPP children were included in the study,including 136 cases(70.1％)with simple SMPP,58 cases(29.9％)with Co-SMPP.The fibrinogen and albumin levels were lower in Co-SMPP children[(3.53±0.85)g/L,41.00(39.03,43.68)g/L]than in simple SMPP children[(3.79±0.80)g/L,42.80(41.00,44.40)g/L],with P values of 0.047 and 0.036,respec-tively.The probability of bronchial stenosis and grid shadow were higher in Co-SMPP children than in simple SMPP children,and there were significant differences between the two groups(P＜0.001,P=0.010).The odds ratio of bronchial stenosis in predicting Co-SMPP children was 14.085.The clinical-radiological nomogram model had an area under the curve(AUC)of 0.840,with sensi-tivity and specificity of 0.756 and 0.848,respectively.Conclusion The nomogram model based on clinical-radiological features can effectively predict Co-SMPP.

BACKGROUND:Endoplasmic reticulum stress is closely associated with the occurrence and progression of osteoarthritis,but the key genes and regulatory mechanisms remain unclear.OBJECTIVE:Utilizing bioinformatics to identify crucial endoplasmic reticulum stress-related genes in osteoarthritis,followed by experimental validation in cell models,aiming to offer new strategies for the prevention and treatment of osteoarthritis from the perspective of endoplasmic reticulum stress.METHODS:Osteoarthritis-related dataset GSE55235 was downloaded from the GEO database.Differential genes in synovial tissue of osteoarthritis were obtained through WGCNA machine learning algorithm and intersected with endoplasmic reticulum stress-related genes from the GeneCard database to acquire differential endoplasmic reticulum stress-related genes in osteoarthritis(ERSDEGs).These genes underwent GO and KEGG enrichment analysis,construction of a protein-protein interaction network,and validation of diagnostic efficiency in external datasets.Human primary synovioblast model of osteoarthritis was constructed.The control group was not treated,and the experimental group received 20 ng/mL lipopolysaccharide to simulate osteoarthritic synoviocyte modeling.Real-time fluorescence quantitative PCR was then performed to validate the expression level of each differential gene followed by immune infiltration analysis.RESULTS AND CONCLUSION:A total of 27 key endoplasmic reticulum stress-related genes in osteoarthritis were identified.GO enrichment analysis revealed that these genes were mainly enriched in collagen metabolism,chemokine,antigen binding,and immunoglobulin receptor binding processes.KEGG analysis indicated that they were mainly enriched in pathways such as rheumatoid arthritis and relaxin signaling pathways.The protein-protein interaction network was constructed,and the top five genes with the highest scores were identified using the Degree algorithm in Cytoscape software,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,collagen type 1 alpha 1,and chemokine C-X-C motif ligand 12.Immune infiltration analysis showed that immune cells were mainly distributed in M2 macrophages,chemokine C-X-C motif ligand 12 showed a significant positive correlation with resting mast cells(r=0.70,P＜0.001)and a significant negative correlation with resting memory CD4+T cells(r=-0.72,P＜0.001).Matrix metallopeptidase 9 showed a significant positive correlation with MO macrophages(r=0.94,P＜0.001).Collagen type 1 alpha 1 was significantly positively correlated with resting NK cells(r=0.77,P＜0.001)and MO macrophages(r=0.76,P＜0.001).Receiver operator characteristic curve analysis in external datasets GSE77298 and GSE1919 showed that the five key genes had good disease prediction value.In vitro cell experiments demonstrated significant differences in the expression levels of matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12 in the osteoarthritic cell model compared to the control group.These results showed that the key genes related to endoplasmic reticulum stress in osteoarthritis,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12,influence the occurrence and development of osteoarthritis through the links of collagen degradation and immune regulation,which are expected to provide new insights into the targeted treatment of osteoarthritis.

In recent decades,the incidence of human papillomavirus(HPV)-associated oropharyngeal squamous cell carcinoma(OPSCC)has shown a marked increase.Significant changes have also occurred in the OPSCC diagnosis and treatment paradigm.Deter-mining HPV status prior to treatment is now essential,and radiotherapy/chemotherapy,immunotherapy,and minimally invasive surgical techniques have progressively emerged as key modalities for managing OPSCC.However,alongside these paradigm shifts,a comprehen-sive technical consensus guiding the entire diagnostic and therapeutic process for OPSCC patients is currently lacking.Given China's large population base and the rising incidence of OPSCC,an expert panel convened to develop a clinical technical consensus on OPSCC diagno-sis and management tailored to China's specific context.This consensus aims to further enhance and standardize understanding of OPSCC management techniques among relevant healthcare professionals.

BACKGROUND:Endoplasmic reticulum stress is closely associated with the occurrence and progression of osteoarthritis,but the key genes and regulatory mechanisms remain unclear.OBJECTIVE:Utilizing bioinformatics to identify crucial endoplasmic reticulum stress-related genes in osteoarthritis,followed by experimental validation in cell models,aiming to offer new strategies for the prevention and treatment of osteoarthritis from the perspective of endoplasmic reticulum stress.METHODS:Osteoarthritis-related dataset GSE55235 was downloaded from the GEO database.Differential genes in synovial tissue of osteoarthritis were obtained through WGCNA machine learning algorithm and intersected with endoplasmic reticulum stress-related genes from the GeneCard database to acquire differential endoplasmic reticulum stress-related genes in osteoarthritis(ERSDEGs).These genes underwent GO and KEGG enrichment analysis,construction of a protein-protein interaction network,and validation of diagnostic efficiency in external datasets.Human primary synovioblast model of osteoarthritis was constructed.The control group was not treated,and the experimental group received 20 ng/mL lipopolysaccharide to simulate osteoarthritic synoviocyte modeling.Real-time fluorescence quantitative PCR was then performed to validate the expression level of each differential gene followed by immune infiltration analysis.RESULTS AND CONCLUSION:A total of 27 key endoplasmic reticulum stress-related genes in osteoarthritis were identified.GO enrichment analysis revealed that these genes were mainly enriched in collagen metabolism,chemokine,antigen binding,and immunoglobulin receptor binding processes.KEGG analysis indicated that they were mainly enriched in pathways such as rheumatoid arthritis and relaxin signaling pathways.The protein-protein interaction network was constructed,and the top five genes with the highest scores were identified using the Degree algorithm in Cytoscape software,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,collagen type 1 alpha 1,and chemokine C-X-C motif ligand 12.Immune infiltration analysis showed that immune cells were mainly distributed in M2 macrophages,chemokine C-X-C motif ligand 12 showed a significant positive correlation with resting mast cells(r=0.70,P＜0.001)and a significant negative correlation with resting memory CD4+T cells(r=-0.72,P＜0.001).Matrix metallopeptidase 9 showed a significant positive correlation with MO macrophages(r=0.94,P＜0.001).Collagen type 1 alpha 1 was significantly positively correlated with resting NK cells(r=0.77,P＜0.001)and MO macrophages(r=0.76,P＜0.001).Receiver operator characteristic curve analysis in external datasets GSE77298 and GSE1919 showed that the five key genes had good disease prediction value.In vitro cell experiments demonstrated significant differences in the expression levels of matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12 in the osteoarthritic cell model compared to the control group.These results showed that the key genes related to endoplasmic reticulum stress in osteoarthritis,including matrix metallopeptidase 1,tumor necrosis factor ligand superfamily member 11,matrix metallopeptidase 9,and chemokine C-X-C motif ligand 12,influence the occurrence and development of osteoarthritis through the links of collagen degradation and immune regulation,which are expected to provide new insights into the targeted treatment of osteoarthritis.

Aim To establish and evaluate an alternative meth-od for detecting skin sensitization of cosmetics based on local lymph node assay using bromodeoxyuridine(BrdU)with flow cytometry(FCM).Methods(1)25％hexyl cinnamic alde-hyde(HCA)was chosen as a positive control with an acetone:olive oil(4∶1,V/V,AOO)mixture as a vehicle control for the experiment.The dorsal sides of both ears of mice were treated with test solutions on day 1,day 2,and day 3.Brdu solution was injected inter-peritoneally on day 5.On day 6,the bilateral ears and mandibular lymph nodes were excised,and the number of Brdu positive cells was measured by flow cytometry.The stim-ulation index(SI)was calculated to identify whether it was ≥3,in order to establish the method of LLNA:Brdu-FCM.(2)BrdU-FCM test was conducted using a blind method with the fif-teen reference substances listed in OECD TG429 whose skin sensitization potentials were known.The test substances were dissolved in AOO,N,N-dimethylformamide(DMF)or dimeth-yl sulfoxide(DMSO)at three different concentrations.Tests were performed the same as above.SI and EC2.7 were calculat-ed to evaluate whether the test substance was categorized as a skin sensitizer.The reliability and accuracy of the method were validated by comparing the classification of test substances with that in OECD TG429.Results The SI for 25％HCA was 3.9,showing positive in the skin sensitization test.It demonstrated that the LLNA:Brdu-FCM test method was properly implemen-ted.Nine test substances(2,4-dinitrochlorobenzene,4-pheny-lenediamine,cobalt chloride,2-mercaptobenzothiazole,hexyl-cinnamaldehyde,eugenol,phenyl benzoate,cinnamic alcohol,imidazolidinyl urea)were positive,and six test substances(methyl methacrylate,chlorobenzene,isopropanol,lactic acid,methyl salicylate,salicylic acid)were negative.The method was evaluated with sensitivity of 90％,specificity of 100％,positive prediction rate of 100％,negative prediction rate of 83％,false positive rate of 0％,false negative rate of 17％and accuracy of 93％.The LLNA:BrdU-FCM assay could correctly categorize the test substances that were skin sensitizers or non-sensitizers.Conclusion The LLNA:BrdU-FCM assay appears to be a relia-ble predictor of skin sensitization protential of chemicals,and it is expected to an alternative method for identifying skin sensitization as a supplementary in safety evaluation of cosmetic ingredient.

Circadian rhythm is an endogenous biological clock mechanism that enables organisms to adapt to the earth’s alternation of day and night. It plays a fundamental role in regulating physiological functions and behavioral patterns, such as sleep, feeding, hormone levels and body temperature. By aligning these processes with environmental changes, circadian rhythm plays a pivotal role in maintaining homeostasis and promoting optimal health. However, modern lifestyles, characterized by irregular work schedules and pervasive exposure to artificial light, have disrupted these rhythms for many individuals. Such disruptions have been linked to a variety of health problems, including sleep disorders, metabolic syndromes, cardiovascular diseases, and immune dysfunction, underscoring the critical role of circadian rhythm in human health. Among the numerous systems influenced by circadian rhythm, the skin—a multifunctional organ and the largest by surface area—is particularly noteworthy. As the body’s first line of defense against environmental insults such as UV radiation, pollutants, and pathogens, the skin is highly affected by changes in circadian rhythm. Circadian rhythm regulates multiple skin-related processes, including cyclic changes in cell proliferation, differentiation, and apoptosis, as well as DNA repair mechanisms and antioxidant defenses. For instance, studies have shown that keratinocyte proliferation peaks during the night, coinciding with reduced environmental stress, while DNA repair mechanisms are most active during the day to counteract UV-induced damage. This temporal coordination highlights the critical role of circadian rhythms in preserving skin integrity and function. Beyond maintaining homeostasis, circadian rhythm is also pivotal in the skin’s repair and regeneration processes following injury. Skin regeneration is a complex, multi-stage process involving hemostasis, inflammation, proliferation, and remodeling, all of which are influenced by circadian regulation. Key cellular activities, such as fibroblast migration, keratinocyte activation, and extracellular matrix remodeling, are modulated by the circadian clock, ensuring that repair processes occur with optimal efficiency. Additionally, circadian rhythm regulates the secretion of cytokines and growth factors, which are critical for coordinating cellular communication and orchestrating tissue regeneration. Disruptions to these rhythms can impair the repair process, leading to delayed wound healing, increased scarring, or chronic inflammatory conditions. The aim of this review is to synthesize recent information on the interactions between circadian rhythms and skin physiology, with a particular focus on skin tissue repair and regeneration. Molecular mechanisms of circadian regulation in skin cells, including the role of core clock genes such as Clock, Bmal1, Per and Cry. These genes control the expression of downstream effectors involved in cell cycle regulation, DNA repair, oxidative stress response and inflammatory pathways. By understanding how these mechanisms operate in healthy and diseased states, we can discover new insights into the temporal dynamics of skin regeneration. In addition, by exploring the therapeutic potential of circadian biology in enhancing skin repair and regeneration, strategies such as topical medications that can be applied in a time-limited manner, phototherapy that is synchronized with circadian rhythms, and pharmacological modulation of clock genes are expected to optimize clinical outcomes. Interventions based on the skin’s natural rhythms can provide a personalized and efficient approach to promote skin regeneration and recovery. This review not only introduces the important role of circadian rhythms in skin biology, but also provides a new idea for future innovative therapies and regenerative medicine based on circadian rhythms.

BACKGROUND:Glucose metabolism plays a crucial role in maintaining the normal physiological function of the body.Glucose metabolism disorder can lead to a range of health problems.At present,the molecular mechanism of glucose metabolism and potential gene targets in osteoarthritis need to be further studied.OBJECTIVE:To analyze the genes related to glucose metabolism in osteoarthritis by bioinformatics methods,and to verify them by cell experiments in vitro,so as to provide new ideas for prevention and treatment of osteoarthritis from the perspective of glucose metabolism.METHODS:Differentially expressed genes and glucose metabolism related genes were screened out from GEO database and GeneCards database.The genes related to both osteoarthritis and glucose metabolism were obtained.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analysis were used to screen the functions and pathways of these genes.To further investigate the interactions between these genes,a protein-protein interaction network was constructed and computational methods using Cytoscape software were utilized to identify key genes(Hub genes)for osteoarthritis glucose metabolism.In addition,CIBERSORT algorithm was used to analyze immune cell infiltration in GSE98918 data set.Finally,the expression of Hub gene was verified by cell experiment in vitro.RESULTS AND CONCLUSION:A total of 134 osteoarthritis glucose metabolism-related genes were obtained.GO enrichment analysis showed that GO was mainly involved in the reaction of toxic substances,the positive regulation of inflammatory reaction,the reaction of lipopolysaccharide and so on.KEGG enrichment analysis showed that it was closely related to PI3K-Akt signaling pathway,interleukin-17 signaling pathway,and AGE-RAGE signaling pathway in diabetic complications.Macrophages,monocytes,resting natural killer cells,regulatory T cells,and CD8+T cells were the main infiltrating cells obtained by immune infiltration analysis.In vitro cell experiments showed that the expression of Hub genes SERPINF1,TAC1,GLUL,APOE,and TMEM176A in the experimental group was significantly different from that in the control group.The mRNA expression of HLA-DRA was not statistically significant.The results show that SERPINF1,TAC1,Glul,APOE,and TMEM176A may be the key genes of glucose metabolism in osteoarthritis,and may be potential new targets for the prevention and treatment of osteoarthritis.

Objective To analyze the willingness and influencing factors of doctors in Beijing public hospitals to set up clinics in the community,and to provide scientific basis for promoting quality health technicians to go down to the grassroots and realize hierarchical diagnosis and treatment.Methods Doctors from 6 specialized hospita ls and 3 general hospitals in Beijing were selected as subjects for questionnaire survey.By stratified sampling,a questionnaire survey was conducted on 518 doctors from 9 public hospitals in Beijing through stratified sampling method.Descriptive analysis,rank sum test and ordered logistic regression were used to explore doctors'willingness to open clinics and its influencing factors.Results In all survey respondents,212(40.93%)physicians were very or somewhat willing to open a clinic in the community,physicians with higher benefit perception,and greater willingness to publicize relevant policies were more willing to set up clinics.Conclusion Opening of clinics by doctors in public hospitals is affected by perceived benefits and willingness to advocate policies.It is suggested to further improve relevant systems and policies,reduce the risk of doctors opening clinics,and promote doctors in public hospitals to open clinics in communities,so as to realize the sinking of high-quality health human resources to the grassroots.

Objective:To evaluate the effect of the radiation dose of thoracic cage bone structure on clinical prognosis in patients with locally advanced non‐small cell lung cancer (LA‐NSCLC) receiving chemoradiotherapy, and to develop and verify a combined model combining the radiation dose of bone structure, the estimated radiation dose of immune cells (EDRIC) and other related factors to predict the prognosis of LA‐NSCLC.Methods:Clinical data of 197 patients with LA‐NSCLC who underwent chemoradiotherapy were retrospectively analyzed. All patients were randomly divided into the training set and testing set at a ratio of 7:3 using computer random partitioning. The EDRIC value was calculated using the model developed by Jin et al. and modified by Ladbury et al. The scope of the thoracic cage structure includes the ribs, sternal manubrium, sternal body, thoracic vertebral body, thoracic vertebral appendages, and thoracic vertebrae. The tumor volume, ERDIC, and average bone structure dose (D mean) were categorized into two groups using the P25, P50, P75 value from the quartile method. Univariate and multivariate Cox proportional hazards regression were used to analyze the influencing factors of overall survival (OS), local progression‐free survival (LPFS), and distant metastasis‐free survival (DMFS) for predicting the outcome, and significant correlated variables were retained to construct a combined prediction model with EDRIC. The receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration curves were plotted for subjects at the 2‐year time point of the combined model to evaluate the predictive performance. The model was visualized through a nomograph. Results:In the thoracic cage bone structure, D mean > 47.3 Gy of the sternal manubrium was an independent risk factor of OS, LPFS, and DMFS of LA-NSCLC patients. D mean > 23.1 Gy of thoracic vertebral body was an independent risk factor of OS, and D mean > 14.4 Gy of thoracic vertebral body was an independent risk factor of DMFS. Among other variables, gross tumor volume (GTV) >50.2 cm 3 was a risk factor for OS, and GTV >87.0 cm 3 was a risk factor for LPFS. Planning target volume >571.9 cm 3 was a risk factor for DMFS. A combined prediction model for OS, LPFS, and DMFS was established with EDRIC using features significantly associated with these three predicted outcomes. The area under the ROC curve (AUC) of OS combined model in the training set and test set were 0.708 and 0.696, respectively, and the AUC of DMFS combined model were 0.675 and 0.639, respectively. The calibration curve and DCA curve of the two prediction endpoints showed that the combined model had good prediction accuracy and clinical benefit. However, the LPFS model was not good in accuracy and clinical applicability. Conclusions:The radiation dose of sternal manubrium and thoracic vertebral body in the thoracic cage bone structure is an independent influencing factor for the prognosis of LA‐NSCLC patients after chemoradiotherapy. The combined model has good predictive performance for OS and DMFS.