OBJECTIVE This study investigated the clinical implications of endothelial cell-specific molecule 1(ESM-1)in obstructive sleep apnea(OSA)patients,with particular focus on its dynamic correlation with adhesion molecules,aiming to elucidate the regulatory role of ESM-1 in OSA-associated vascular endothelial impairment.METHODS This cross-sectional study enrolled participants undergoing polysomnography(PSG)at the Sleep Medicine Center of Beijing Anzhen Hospital,Capital Medical University between March 2017 and January 2018.Based on the inclusion criteria,161 participants were ultimately included and divided into OSA group(n=118)and control group(n=43).Demographic data and polysomnography parameters were collected.We used a powerful high-throughput Multiplex Immunobead Assay technology to simultaneously test plasm cytokines levels of ESM-1,inter-cellular adhesion molecule 1(ICAM-1),vascular cell adhesion molecule 1(VCAM-1).Circulating C-reactive protein(CRP)and homocysteine(Hcy)were detected by routine blood chemistry panel.RESULTS Circulating ESM-1 levels were significantly elevated in patients with OSA compared with healthy controls[819.73(612.36-1393.47)pg/ml]vs.[286.17(114.48-513.81)pg/ml,P<0.001].After adjusting for confounding factors,we found that circulating ESM-1 levels were an independent risk factor for OSA(odds ratio=2.162,95%CI=1.522-3.072,P<0.001)and circulating ESM-1 levels were positively associated with ICAM-1 and VCAM-1 levels(β=1.977,95%CI=1.429-2.734,P<0.001).CONCLUSION Circulating ESM-1 levels were significantly increased in patients with OSA,which is closely related with adhesion molecules levels.ESM-1 may be a surrogate endothelial dysfunction marker and an independent risk factor for OSA.

Objective : To explore the factors influencing the efficacy of first-generation EGFR tyrosine kinase inhibitors(EGFR-TKIs) in patients with EGFR-mutated advanced lung adenocarcinoma and to construct and validate a corresponding nomogram prediction model. Methods : A total of 220 patients with EGFR-mutated advanced lung adenocarcinoma treated with icotinib were enrolled and randomly divided into a training group(154 cases) and a validation group(66 cases) in a 7 ∶3 ratio. Cox regression analysis was performed to identify factors affecting the efficacy of first-generation EGFR-TKIs in the training group. A prediction model was constructed, and calibration curves and receiver operating characteristic(ROC) curves were plotted to validate the model′s performance. Results: In the training group, the objective response rate was 35.71%, the disease control rate was 77.27%, the median progression-free survival(PFS) was 12.5 months, the median overall survival was 18 months, the 2-year OS rate was 66.23%, and the PFS rate was 42.21%. Univariate analysis showed that brain metastasis, bone metastasis, TNM stage, differentiation degree, neutrophil-to-lymphocyte ratio(NLR), post-treatment p53 levels, p53 difference(Δp53), post-treatment cancer antigen gene(CAGE) levels, and CAGE difference(ΔCAGE) were associated with PFS(P2=4.429, P=0.351). ROC curve analysis in the training group showed that the nomogram model had a sensitivity of 80.00%, specificity of 77.53%, and AUC of 0.864 for predicting therapeutic efficacy, while the validation group showed a sensitivity of 74.08%, specificity of 71.43%, and AUC of 0.835. Conclusion Changes in lung cancer autoantibodies(Δp53 and ΔCAGE), TNM stage, and NLR are key factors influencing the efficacy of first-generation EGFR-TKIs in EGFR-mutated advanced lung adenocarcinoma. The nomogram prediction model based on p53 and CAGE demonstrates good predictive performance.

Hearing loss is one of the most prevalent sensory disorders affecting the human nervous system. Liquid-liquid phase separation (LLPS) is a physiological process that facilitates the reversible and dynamic assembly of biomolecular condensates. Increasing evidence suggests that LLPS plays a significant role in the pathogenesis of hereditary hearing loss. Nevertheless, there is a conspicuous lack of systematic investigations exploring the impact of LLPS abnormalities on the etiology of hereditary hearing loss. In this review, we examine the mechanisms by which dysfunctions in LLPS contribute to hereditary hearing loss, specifically focusing on its effects on mechanoelectrical transduction in hair bundles, transcriptional regulation, post-transcriptional modifications, the actin cytoskeleton, ion homeostasis within the inner ear, and energy and redox homeostasis. Furthermore, we evaluate the considerable potential of targeting LLPS as a therapeutic approach for hearing loss and propose innovative perspectives on LLPS that may guide future research initiatives in the field of auditory disorders.
Humans ; Animals ; Hearing Loss/physiopathology* ; Phase Separation

This consensus will introduce the characteristics of fillers used in the surgical cavities of domestic nasal surgery patients based on relevant literature and expert opinions. It will also provide recommendations for the selection of cavity fillers for different nasal diseases, with chronic sinusitis as a representative example.
Humans ; Nasal Cavity/surgery* ; Nasal Surgical Procedures ; China ; Consensus ; Sinusitis/surgery* ; Dermal Fillers

Objective To provide experimental evidence for selecting acupuncture timing in clinical practice,the optimal time for enhancing the brain effects of electroacupuncture at the Hegu acupoint(LI4)by observing brain imaging data,hemodynamic changes and differences in brain functional connectivity across the twelve traditional Chinese time periods were determined.Methods Thirty-six C57BL/6 mice were randomly divided into 12 groups corresponding to each of the twelve time periods(Zi,Chou,Yin,Mao,Chen,Si,Wu,Wei,Shen,You,Xu,Hai),with 3 mice per group.Each mouse received electroacupuncture stimulation using the same protocol.Brain imaging data and dynamic hemodynamic changes were collected using functional ultrasound imaging(FUS)ultrasound imaging technology every 0.4 s over a total duration of 420 s,covering pre-acupuncture(resting state),during acupuncture(task state),and post-acupuncture(post-task state)phases.The hippocampal region(HIP)was used as the observation point to analyze changes in functional connectivity between HIP and other brain regions before and after acupuncture.Results Compared to other time periods,the Mao group exhibited the largest whole-brain activation area and the highest average activation signal intensity.The hemodynamic signal increase in the hippocampal region was more pronounced,and the post-acupuncture blood flow signal intensity remained significantly higher than the pre-acupuncture resting state.Functional connectivity data revealed that,using 0.2 as the standard value,the Mao group showed the greatest number of altered brain regions before and after acupuncture.Notably,only in the Mao group was there a significant enhancement in connectivity between the bilateral hippocampal regions.Conclusion The immediate effects of electroacupuncture at the Hegu acupoint(LI4)and brain functional connectivity vary significantly across different time periods,aligning with the traditional Chinese medicine theory of meridian qi and blood flow.Mao time is identified as the optimal period.

Objective:To explore the effects of smoking on peripheral regulatory T cells (Tregs), transforming growth factor beta1 (TGF-β 1) and interleukin-10 (IL-10) in elderly patients with non-small cell lung cancer (NSCLC). Methods:This was a cross-sectional study. A total of 43 elderly patients (≥60 years old) who were hospitalized in the Department of Geriatrics Medicine, Guangzhou First People′s Hospital from January 2018 to December 2024 and were newly diagnosed with NSCLC were recruited. According to smoking history, patients were divided into non-smoking group (15 cases), low smoking group (13 cases, smoking index<400) and high smoking group (15 cases, smoking index≥400). Venous blood samples were collected from participants, plasma and cells were separated. Flow cytometry was used to measure the proportions of Tregs and the expression of forkhead box P3 (Foxp3) in peripheral blood. Plasma levels of TGF-β 1 and IL-10 were measured by enzyme-linked immunosorbent assay. The effects of smoking on peripheral Tregs, TGF-β 1, and IL-10 in elderly patients with NSCLC were analyzed. Data were analyzed by one-way ANOVA, rank-sum test, and Fisher′s exact test. Results:The proportions of Tregs in non-smoking group, low smoking group and high smoking group were 2.50% (2.32%, 2.81%), 2.83% (2.48%, 3.72%), and 3.01% (2.37%, 3.73%), respectively, and there were no statistically significant differences among the three groups ( H=3.845, P>0.05). The proportions of Foxp3 +Tregs were (3.72±0.84)%, (4.64±1.10)%, and (4.68±1.27%), respectively. The mean fluorescence intensities (MFI) of Foxp3 were 123.0 (108.0, 128.0), 131.0 (123.5, 350.0), and 222.0 (141.0, 311.0), respectively. Both the proportions of Foxp3 +Tregs and the MFI of Foxp3 were higher in low smoking group and high smoking group than those in non-smoking group (all P<0.05). However, there were no significant differences between low smoking group and high smoking group (all P>0.05). The concentrations of IL-10 were 2.27 (1.42, 3.95), 3.42 (2.30, 5.08), and 3.26 (2.35, 6.28) ng/L, respectively. There were no statistically significant differences among the three groups ( H=2.930, P>0.05). The concentrations of TGF-β 1 were (10.72±9.37), (13.46±10.39), and (25.28±16.67) ng/ml, respectively. The concentration of TGF-β 1 in high smoking group was higher than that in non-smoking group and low smoking group (all P<0.05). However, there was no statistically significant difference between low smoking group and non-smoking group ( P>0.05). Conclusions:Smoking intensity may be correlated with the immunosuppressive function of Tregs in elderly patients with NSCLC. Higher smoking levels are associated with increased Foxp3 expression in Tregs and elevated plasma levels of TGF-β 1, potentially enhancing the immunosuppressive function of Tregs.

Objective:To detect adverse reaction risk signals of triazole antifungal agents and provide evidences for their safe use in clinic.Methods:Adverse reaction/event reports with fluconazole, itraconazole, voriconazole, posaconazole, or isavuconazonium as the primary suspect drug were collected from the data in National Adverse Drug Reaction Monitoring System of China reported by Shandong Province from January 2004 to June 2024 and the US Food and Drug Administration Adverse Event Reporting System (FAERS) database from the first quarter of 2004 to the second quarter of 2023. Adverse reaction/event terms were standardized using the preferred term (PT) and system organ class in Medical Dictionary for Regulatory Activities 24.0. Risk signals were detected using the reporting odds ratio (ROR) method and the Bayesian confidence propagation neural network (BCPNN) algorithm. A PT was defined as an adverse reaction risk signal if the number of reports was ≥3, the lower limit of the 95% confidence interval ( CI) for ROR was >2, and the lower limit of the 95% CI for the information component ( IC) was >0. Descriptive statistical analysis was performed. Results:A total of 3 988 reports with the above 5 antifungal drugs as the primary suspect drug were collected from data in National Adverse Drug Reaction Monitoring System of China reported by Shandong Province, 822 (20.6%) of which were serious cases. Voriconazole, fluconazole, itraconazole, posaconazole, and isavuconazonium was the primary suspect drug in 1 852, 1 395, 703, 27, and 11 cases among the 3 988 reports, and in 591 (31.9%), 149 (10.7%), 59 (8.4%), 18 (66.7%), and 5 (5/11) serious cases among the 822 serious case reports, respectively. A total of 20 066 reports with the above 5 drugs as the primary suspect drug were collected in FAERS database, 9 635 (48.0%) of which were serious cases. Voriconazole, fluconazole, itraconazole, posaconazole, and isavuconazonium was the primary suspect drug in 7 758, 6 180, 2 869, 1 796, and 1 463 cases among the 20 066 reports, and in 4 295 (55.4%), 2 806 (45.4%), 1 191 (41.5%), 828 (46.1%), and 515 (35.2%) serious cases among the 9 635 serious case reports, respectively. Based on the data reported by Shandong Province and in FAERS database, 18 and 207 risk signals of adverse reaction not mentioned in the labels were identified, respectively, and 5 of them were identified in both databases, including fluconazole-induced renal impairment and voriconazole-induced oliguria, delirium, psychiatric disorders, and rhabdomyolysis. In the data reported by Shandong Province and in FAERS database, 13 and 189 reports of muscle-related disorders (rhabdomyolysis, myopathy, and myositis) were identified respectively, involving voriconazole (in 8 and 62 cases), itraconazole (in 4 and 74 cases), and fluconazole (in 1 and 53 cases).Conclusions:Renal impairment induced by fluconazole and oliguria, delirium, psychiatric disorders, and rhabdomyolysis induced by voriconazole are risk signals of adverse reaction not mentioned in the labels for triazole antifungal agents. Voriconazole, itraconazole, and fluconazole may also cause muscle-related disorders, warranting vigilance in clinical practice.

Objective To develop a combined model integrating radiomics and 3D deep learning features for improving the predictive efficacy of overall survival in non-small cell lung cancer(NSCLC)patients undergoing radiotherapy,thereby providing a foundation for optimizing individualized radiotherapy strategies.Methods A retrospective analysis was conducted on 522 NSCLC patients from 3 centers.Radiomics features were extracted from the tumor region of interest on radiotherapy planning CT scans,and a 3D-SE-ResNet was constructed to extract deep learning features.Following feature extraction,features were selected via univariate Cox analysis and Lasso-Cox regression,and a combined model was established by fusing the two feature types through principal component analysis.The discriminative ability of the model was evaluated using the concordance index(C-index)and the area under the receiver operating characteristic curve(AUC),while the risk stratification efficacy was verified by Kaplan-Meier survival analysis.Results The predictive performance of deep learning features was significantly superior to that of radiomics features(C-index:0.73 vs 0.65).The combined model achieved the highest predictive performance in the training set,internal test set,and external test set(C-index:0.74,0.69,0.72 respectively),with higher AUC values for predicting 1-year,2-year,and 3-year OS than either single model.Kaplan-Meier analysis showed significant differences in survival between the high-and low-risk groups(Log-rank test,P<0.001),and calibration curves indicated good consistency between predicted and actual survival outcomes.Conclusion The combined model integrating radiomics and 3D deep learning features can accurately predict survival outcomes in NSCLC patients undergoing radiotherapy.The multi-center validation results support its potential application in prognosis stratification for individualized radiotherapy.