Objective:To analyze the clinical characteristics of children with head and neck rhabdomyosarcoma (RMS) and to summarize the mid-long term efficacy of Beijing Children′s Hospital Rhabdomyosarcoma 2006 (BCH-RMS-2006) regimen and China Children′s Cancer Group Rhabdomyosarcoma 2016 (CCCG-RMS-2016) regimen.Methods:A retrospective cohort study. Clinical data of 137 children with newly diagnosed head and neck RMS at Beijing Children′s Hospital, Capital Medical University from March 2013 to December 2021 were collected. Clinical characteristic of patients at disease onset and the therapeutic effects of patients treated with the BCH-RMS-2006 and CCCG-RMS-2016 regimens were compared. The treatments and outcomes of patients with recurrence were also summarized. Survival analysis was performed by Kaplan-Meier method, and Log-Rank test was used for comparison of survival rates between groups.Results:Among 137 patients, there were 80 males (58.4%) and 57 females (41.6%), the age of disease onset was 59 (34, 97) months. The primary site in the orbital, non-orbital non-parameningeal, and parameningeal area were 10 (7.3%), 47 (34.3%), and 80 (58.4%), respectively. Of all patients, 32 cases (23.4%) were treated with the BCH-RMS-2006 regimen and 105 (76.6%) cases were treated with the CCCG-RMS-2016 regimen. The follow-up time for the whole patients was 46 (20, 72) months, and the 5-year progression free survival (PFS) and overall survival (OS) rates for the whole children were (60.4±4.4)% and (69.3±4.0)%, respectively. The 5-year OS rate was higher in the CCCG-RMS-2016 group than in BCH-RMS-2006 group ((73.0±4.5)% vs. (56.6±4.4)%, χ2=4.57, P=0.029). For the parameningeal group, the 5-year OS rate was higher in the CCCG-RMS-2016 group (61 cases) than in BCH-RMS-2006 group (19 cases) ((57.3±7.6)% vs. (32.7±11.8)%, χ2=4.64, P=0.031). For the group with meningeal invasion risk factors, the 5-year OS rate was higher in the CCCG-RMS-2016 group (54 cases) than in BCH-RMS-2006 group (15 cases) ((57.7±7.7)% vs. (30.0±12.3)%, χ2=4.76, P=0.029). Among the 10 cases of orbital RMS, there was no recurrence. In the non-orbital non-parameningeal RMS group (47 cases), there were 13 (27.6%) recurrences, after re-treatment, 7 cases survived. In the parameningeal RMS group (80 cases), there were 40 (50.0%) recurrences, with only 7 cases surviving after re-treatment. Conclusions:The overall prognosis for patients with orbital and non-orbital non-parameningeal RMS is good. However, children with parameningeal RMS have a high recurrence rate, and the effectiveness of re-treatment after recurrence is poor. Compared with the BCH-RMS-2006 regimen, the CCCG-RMS-2016 regimen can improve the treatment efficacy of RMS in the meningeal region.

OBJECTIVE: To elucidate the rules of temporal and spatial variations in distal skin potential at Hegu (LI4) under different stimulation modes by extracting nonlinear characteristic parameters from array multichannel data and adopting multivariate statistical analysis. METHODS: Seven healthy subjects were selected and the surface potential at the left Quchi (LI11) was collected using 14×9 array multichannel electrodes. Using Hegu (LI4) on the left as the stimulation point, four stimulation modes were applied, i.e. being quiescent, point pressing, moxibustion, and manual needling manipulation. Electrical signals were collected for 30 s in each mode, with a 5-min interval between operations, and a sampling frequency of 16 384 Hz. The data was denoised using ensemble empirical mode decomposition (EEMD), and sample entropy (SaEn) features were extracted. Statistical analysis was conducted on these data using factor analysis and multivariate analysis of variance. RESULTS: The SaEn values of most electrode channels were higher under point pressing, moxibustion and manual needling manipulation compared with those under quiescent condition. Under manual needling manipulation, the SaEn value of the electrode channel reached the peak in the first time interval (1-5 s) and it was declining thereafter. Factor analysis showed that the specificity of activation channels was concentrated at the left Quchi (LI11) (loading capacity ≥0.90). Analysis of variance indicated that the significant differences were presented in average sample entropy (SaEn()) values of activation channels among different stimulation modes at Hegu (LI4) (P<0.001), but there was no statistically significant interaction effect between groups and time intervals (P>0.05). CONCLUSION Through nonlinear characteristic parameter extraction and multivariate statistical analysis, we have uncovered the complex temporal and spatial dynamical rules of distal skin potential at Hegu (LI4) under various stimulation modes and successfully identified the specific activation characteristics at Quchi (LI11).
Humans ; Moxibustion ; Acupuncture Points ; Male ; Adult ; Female ; Young Adult ; Acupuncture Therapy/instrumentation*

OBJECTIVE: To explore the pain-location interaction between pressure-sensitive points on the body surface and traditional acupoints in patients with chronic non-specific low back pain (CNLBP) under different disease courses, using Euclidean distance and multivariate statistical analysis. METHODS: A pressure-sensitive point detection was performed on 30 CNLBP patients with varying disease courses. A constant pressure was applied using an FDK20 algometer within a designated lumbar area, a total of 50 points were tested, and the tested points were numbered; the visual analogue scale (VAS) pain score was recorded simultaneously. MatlabR2022a9.12. software was used to extract the positions of pressure-sensitive points, and preprocessing and normalization of point location and VAS scores data were conducted. Under constraint conditions (VAS≥8.0 ∩ Euclidean distance to acupoint≤0.5), the proportion of pressure-sensitive points within the Euclidean distance threshold to each acupoint (PVD_acupoint) was calculated, followed by multivariate statistical analysis. RESULTS: ①Constrained analysis of PVD_acupoint showed that PVD_{Qihaishu (BL24)} and PVD_{Dachangshu (BL25)} were positively correlated with disease course (r=0.55, P<0.01). ②Factor analysis and silhouette analysis revealed that PVD_{Shenshu (BL23)} and PVD_{Dachangshu (BL25)} exhibited trends consistent with disease course progression (P>0.05), with different degree (P<0.01). CONCLUSION The PVD_acupoint value based on Euclidean distance can characterize the pressure sensitivity features of traditional acupoints associated with disease. Multivariate statistical analysis of PVD_acupoint confirms that selecting the acupoint combination of Shenshu (BL23) and Dachangshu (BL25) for CNLBP is associated with the distribution of surrounding pressure-sensitive points and the pathological characteristics of the condition.
Humans ; Acupuncture Points ; Low Back Pain/physiopathology* ; Male ; Female ; Middle Aged ; Adult ; Aged ; Acupuncture Therapy ; Young Adult ; Pressure

Metabolic-associated fatty liver disease (MAFLD) and osteoporosis (OP) are two very common metabolic diseases. A growing body of experimental evidence supports a pathophysiological link between MAFLD and OP. MAFLD is often associated with the development of OP. Rutaecarpine (RUT) is one of the main active components of Chinese medicine Euodiae Fructus. Our previous studies have demonstrated that RUT has lipid-lowering, anti-inflammatory and anti-atherosclerotic effects, and can improve the OP of rats. However, whether RUT can improve both fatty liver and OP symptoms of MAFLD mice at the same time remains to be investigated. In this study, we used C57BL/6 mice fed a high-fat diet (HFD) for 4 months to construct a MAFLD model, and gave the mice a low dose (5 mg·kg^-1) and a high dose (15 mg·kg^-1) of RUT by gavage for 4 weeks. The effects of RUT on liver steatosis and bone metabolism were then evaluated at the end of the experiment [this experiment was approved by the Experimental Animal Ethics Committee of Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences (approval number: IMB-20190124D₃03)]. The results showed that RUT treatment significantly reduced hepatic steatosis and lipid accumulation, and significantly reduced bone loss and promoted bone formation. In summary, this study shows that RUT has an effect of improving fatty liver and OP in MAFLD mice.

Objective: To conduct a scoping review on the types, construction methods and predictive performance of health literacy prediction models based on machine learning methods, so as to provide the reference for the improvement and application of such models. Methods: Publications on health literacy prediction models conducted using machine learning methods were retrieved from CNKI, Wanfang Data, VIP, PubMed and Web of Science from inception to May 1, 2024. The quality of literature was assessed using the Prediction Model Risk of Bias ASsessment Tool. Basic characteristics, modeling methods, data sources, missing value handling, predictors and predictive performance were reviewed. Results: A total of 524 publications were retrieved, and 22 publications between 2007 and 2024 were finally enrolled. Totally 48 health literacy prediction models were involved, and 25 had a high risk of bias (52.08%), with major issues focusing on missing value handling, predictor selection and model evaluation methods. Modeling methods included regression models, tree-based machine learning methods, support vector machines and neural network models. Predictors primarily encompassed factors at four aspects: individual, interpersonal, organizational and society/policy aspects, with age, educational level, economic status, health status and internet use appearing frequently. Internal validation was conducted in 14 publications, and external validation was conducted in 4 publications. Forty-two models reported the areas under the receiver operating characteristic curve, which ranged from 0.52 to 0.983, indicating good discrimination. Conclusion Health literacy prediction models based on machine learning methods perform well, but have deficiencies in risk of bias, data processing and validation.

OBJECTIVE: To explore and quantify the association of hot night exposure during the sperm development period (0-90 lag days) with semen quality. METHODS: A total of 6,640 male sperm donors from 6 human sperm banks in China during 2014-2020 were recruited in this multicenter study. Two indices (i.e., hot night excess [HNE] and hot night duration [HND]) were used to estimate the heat intensity and duration during nighttime. Linear mixed models were used to examine the association between hot nights and semen quality parameters. RESULTS: The exposure-response relationship revealed that HNE and HND during 0-90 days before semen collection had a significantly inverse association with sperm motility. Specifically, a 1 °C increase in HNE was associated with decreased sperm progressive motility of 0.0090 (95% confidence interval [ CI]: -0.0147, -0.0033) and decreased total motility of 0.0094 (95% CI: -0.0160, -0.0029). HND was significantly associated with reduced sperm progressive motility and total motility of 0.0021 (95% CI: -0.0040, -0.0003) and 0.0023 (95% CI: -0.0043, -0.0002), respectively. Consistent results were observed at different temperature thresholds on hot nights. CONCLUSION Our findings highlight the need to mitigate nocturnal heat exposure during spermatogenesis to maintain optimal semen quality.
Humans ; Male ; Semen Analysis ; Adult ; Sperm Motility ; Hot Temperature/adverse effects* ; China ; Middle Aged ; Spermatozoa/physiology* ; Young Adult

OBJECTIVE: To identify prognostic genes associated with lysosome-dependent cell death (LDCD) in patients with gastric cancer (GC). METHODS: Differentially expressed genes (DEGs) were identified using The Cancer Genome Atlas - Stomach Adenocarcinoma. Weighted gene co-expression network analysis was performed to identify the key module genes associated with LDCD score. Candidate genes were identified by DEGs and key module genes. Univariate Cox regression analysis, and least absolute shrinkage and selection operator regression and multivariate Cox regression analyses were performed for the selection of prognostic genes, and risk module was established. Subsequently, key cells were identified in the single-cell dataset (GSE183904), and prognostic gene expression was analyzed. Cell proliferation and migration were assessed using the Cell Counting Kit-8 assay and the wound healing assay. RESULTS: A total of 4,465 DEGs, 95 candidate genes, and 4 prognostic genes, including C19orf59, BATF2, TNFAIP2, and TNFSF18, were identified in the analysis. Receiver operating characteristic curves indicated the excellent predictive power of the risk model. Three key cell types (B cells, chief cells, and endothelial/pericyte cells) were identified in the GSE183904 dataset. C19orf59 and TNFAIP2 exhibited predominant expression in macrophage species, whereas TNFAIP2 evolved over time in endothelial/pericyte cells and chief cells. Functional experiments confirmed that interfering with C19orf59 inhibited proliferation and migration in GC cells. CONCLUSION C19orf59, BATF2, TNFAIP2, and TNFSF18 are prognostic genes associated with LDCD in GC. Furthermore, the risk model established in this study showed robust predictive power.
Stomach Neoplasms/pathology* ; Humans ; Prognosis ; Lysosomes/physiology* ; RNA-Seq ; Cell Death ; Single-Cell Analysis ; Gene Expression Regulation, Neoplastic ; Cell Proliferation ; Single-Cell Gene Expression Analysis

OBJECTIVE: Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health. Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment, including high dimensionality, correlated exposure, and subtle individual effects. METHODS: We proposed a novel statistical approach, the generalized functional linear model (GFLM), to analyze the health effects of exposure mixtures. GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation. The robustness and efficiency was evaluated under various scenarios through extensive simulation studies. RESULTS: We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey (NHANES). In the first application, we examined the effects of 37 nutrients on BMI (2011-2016 cycles). The GFLM identified a significant mixture effect, with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI, respectively. For the second application, we investigated the association between four pre- and perfluoroalkyl substances (PFAS) and gout risk (2007-2018 cycles). Unlike traditional methods, the GFLM indicated no significant association, demonstrating its robustness to multicollinearity. CONCLUSION GFLM framework is a powerful tool for mixture exposure analysis, offering improved handling of correlated exposures and interpretable results. It demonstrates robust performance across various scenarios and real-world applications, advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
Humans ; Environmental Exposure/analysis* ; Linear Models ; Nutrition Surveys ; Environmental Pollutants ; Body Mass Index

The inappropriate utilisation of the agricultural insecticide lambda-cyhalothrin (LCT) has the potential to result in residues that compromise food safety and human health. Respiratory exposure represents a major route of LCT contact in humans. Nevertheless, its deleterious effects on the respiratory system remain inadequately characterized. It is imperative to elucidate the potential relationship and mechanisms by which lung cancer, a significant malignant neoplasm of the respiratory system, is associated with exposure to LCT. The objective of this study is to utilise bioinformatics methodologies to screen and analyse the key target molecules affected by LCT in the occurrence of lung cancer, and their mechanisms of action. Specifically, network toxicology methods were employed to identify core targets of LCT-induced lung cancer. Subsequently, functional annotation to delineate associated cellular pathways, and finally, molecular docking to simulate binding modes between LCT and shared core targets. Core target screening identified 50 targets for large cell lung cancer, 54 for small cell lung cancer, 29 for lung squamous cell carcinoma, and 28 for lung adenocarcinoma, with EGFR, HSP90AA1, JUN, CCL2, MYC, CXCL8, and HSPA4 shared in all subtypes. Functional annotation revealed that LCT-triggered oncogenic pathways predominantly involved ubiquitination, chemotaxis, and tumor immune signaling. Molecular docking demonstrated spontaneous binding of LCT to core targets mediated by hydrogen bonds and π-cation interactions. These results establish a theoretical framework for evaluating LCT-associated risks of lung cancer and respiratory system damage.
Lung Neoplasms/metabolism* ; Pyrethrins/toxicity* ; Humans ; Insecticides/toxicity* ; Nitriles/toxicity* ; Molecular Docking Simulation

Objective To investigate the diagnostic value of our regression model based on quantitative parameters of dual-energy CT and clinical features for stages T2 and T3 colorectal cancer.Methods A cross-section study was performed on 91 patients with colorectal cancer confirmed by postoperative pathology in our hospital from January 2022 to November 2023.All of them underwent dual-energy CT examination.According to the pathological T staging criteria of Chinese Colorectal Cancer Diagnosis and Treatment Standard(2020 Edition),they were divided into T2 group(n=43)and T3 group(n=48).Univariate analysis was used to compare the differences in quantitative CT parameters and clinical features between the 2 groups,and the obtained significant variables were employed to construct diagnosis models by univariate or multivariate logistic regression analysis.The area under receiver operating characteristic curve(AUC)of the CT parametric model and the model combined with clinical features was compared to evaluate the efficacy of diagnosing T2 and T3 stages.Results Univariate analysis showed that carcinoembryonic antigen(CEA),N stage,tumor location,tumor longest diameter(LD),CT value of virtual noncontrast(CT-VNC),fat fraction,electron density(Rho)and dual energy index(DEI)were significantly different between the T2 and T3 groups(P＜0.05).Multivariate logistic regression analysis found that N stage,tumor location,LD,fat fraction and DEI were independent risk factors for the diagnosis of stage T3.The AUC value of the model of above CT parameters in diagnosing stage T3 colorectal cancer was 0.671(95％CI:0.558～0.783),and the AUC value of the combined model of above CT parameters and clinical features was 0.886(95％CI:0.815～0.957),and statistical difference was observed in the AUC value between the combined model and the CT parametric model(P＜0.01).Conclusion The regression model constructed with dual-energy CT quantitative parameters combined with clinical features has high value in the preoperative diagnosis of stages T2 and T3 colorectal cancer before surgery.