ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

ObjectiveHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） and GC-triple quadrupole MS（GC-QqQ-MS） in combination with non-targeted and targeted metabolomics were employed to systematically analyze the chemical composition differences of Xihuangwan prepared with natural musk and artificial musk， and establish an identification system for them. MethodsThe volatile components of 9 batches of Xihuangwan samples from 8 manufacturers were analyzed by HS-SPME-GC-MS non-targeted metabolomics， and identified by comparing their MS data with the National Institute of Standards and Technology（NIST） spectral library. Orthogonal partial least squares-discriminant analysis（OPLS-DA） was used to identify differential volatile components of Xihuangwan prepared with natural musk and artificial musk. Additionally， GC-QqQ-MS targeted metabolomics was applied to quantify the levels of α-pinene， β-elemene， muscone， dehydroepiandrosterone， bornyl acetate， and octyl acetate in 27 batches of samples from 9 manufacturers. Cluster analysis， principal component analysis（PCA）， and partial least squares-discriminant analysis（PLS-DA） were conducted to further explore the differences in volatile components between Xihuangwan samples prepared with natural musk and artificial musk. ResultsNon-targeted metabolomics identified 291 volatile compounds in Xihuangwan， including alkanes， esters， alkanes， alcohols， ketones， naphthalenes and others. OPLS-DA analysis revealed distinct separation between Xihuangwan samples containing artificial musk（A1， C1， D1， E1， F1， G1， I1） and those containing natural musk（H1， H3）. A total of 30 differential metabolites were identified. The relative contents of these 30 differential metabolites were visualized using a radar chart， revealing significant differences in the levels of octanol， borneol acetate and muscone. Cluster analysis and PCA results from targeted metabolomics indicated that Xihuangwan could be classified into two distinct groups：one composed of natural musk（H1， H3） and the other of artificial musk， sample H2. PLS-DA identified muscone， octyl acetate， and dehydroepiandrosterone as key differential volatile components. Although no significant difference was observed in the content of octyl acetate between the two groups， statistically significant differences were found for muscone and dehydroepiandrosterone（P<0.05）. ConclusionMuscone and dehydroepiandrosterone can be used for the differentiation of Xihuangwan samples containing natural musk from those containing artificial musk. This study systematically and comprehensively analyzed the differences in the types and contents of major volatile components in Xihuangwan prepared with natural musk and artificial musk， providing a scientific basis for quality evaluation and control of Xihuangwan.

Objective: To characterize longitudinal trajectories of testicular development in boys and breast development in girls, so as to provide reference data for understanding patterns of pubertal sexual maturation. Methods: Based on the Shanghai Pudong New Area Cohort Study on Growth, Development and Health in Children and Adolescents, a baseline survey was conducted in 2020 using a mult stage cluster random sampling method. A total of 2 184 children who completed all follow ups during the primary school period from 13 elementary schools in Pudong New Area,Shanghai,with annual follow ups during 2021-2025. Testicular volume and Tanner stage of breast development were assessed by professional physicians using standardized visual inspection and palpation. The age distribution of testicular volume and breast development was fitted by using cumulative link mixed models and Turnbull s nonparametric maximum likelihood estimation method. Results: Median ages for testicular volumes of 2, 3, 4 and 5 mL in boys were 7.07, 9.24, 10.29, and 11.57 years old, respectively. Median ages for Tanner breast stages Ⅱ, Ⅲ, Ⅳ, and Ⅴ in girls were 8.55 , 10.17, 11.18, and 13.78 years old, respectively. Based on overweight and obesity, stratified analysis showed that earlier pubertal onset among overweight/obesity children, and the key milestones for pubertal initiation were testicular volume reaching 4 mL in boys and breast Tanner II in girls for 10.29, 10.83; 8.18, 9.00 years. Conclusion Overweight and obesity are associated with earlier pubertal initiation,but there are certain gender and developmental stage specific patterns.

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.

Objective To analyze the incidence rate and risk factors of atrial fibrillation (AF) in elderly patients with chronic obstructive pulmonary disease (COPD). Methods A total of 392 patients with COPD in the hospital were selected from December 2020 to December 2024. Patients' data (medical history, echocardiographic data, etc.) were recorded. The incidence rate of AF in patients was recorded and the patients were grouped according to whether or not they developed AF. The differences were compared between the two groups, and the risk factors of AF occurrence in elderly patients with COPD were analyzed. Results Among the 392 patients with COPD, 127 cases (32.40%) met the diagnostic criteria of AF. There were statistically significant differences in age, pulmonary infection, heart failure, diabetes, smoking history, disease duration, LAD, severe renal insufficiency and coronary heart disease between the AF group and the non-AF group (P<0.05). Multivariate logistic regression analysis suggested that age, pulmonary infection, heart failure, diabetes mellitus, smoking history, disease course, LAD, severe renal insufficiency and coronary heart disease were all risk factors for elderly patients with COPD (OR=1.129, 4.246, 3.955, 4.125, 2.038, 1.112, 1.102, 4.397, and 3.865, P<0.05). Conclusion The incidence rate of AF is high in elderly patients with COPD. Age, pulmonary infection, heart failure, diabetes mellitus, smoking history, course of disease, LAD, severe renal insufficiency, and coronary heart disease are all risk factors for AF.

Objective: To determine the potential genetic causal relationship between sleep related phenotypes and female pubertal onset using the two sample Mendelian randomization approach. Methods: Genetic instrumental variables for sleep and age at menarche were sourced from FinnGen, IEU Open GWAS and GWAS Catalog three publicly available Genome Wide Association Study databases. Causal effects were estimated using the inverse variance weighted method, supplemented by sensitivity analyses and tests for heterogeneity, pleiotropy, and direction. Results: Genetically predicted sleep duration was positively associated with age at menarche ( β =0.61, 95% CI =0.30-0.91, P <0.01). Conversely, overall sleep problems ( β =-0.13, 95% CI =-0.20 to -0.07 ), two specific types of sleep disorders (sleep apnea: β =-0.10, 95% CI =-0.16 to -0.03; insomnia: β =-0.40, 95% CI = -0.69 to -0.11) were causally associated with earlier age at menarche (all P <0.01). Sensitivity analyses confirmed the robustness of these findings with consistent effect directions and no evidence of significant directional pleiotropy. Conclusions The study reveales a genetic causal relationship between sleep and pubertal onset. Adequate sleep duration appears to have a protective effect. These findings suggest that sleep may have a critical regulatory role in the initiation of pubertal development.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

Objective To compare the efficacy of five Blastocystis staining method for staining cells with different morphologies and in different developmental stages to select appropriate staining techniques for specific scenarios and experimental purposes. Methods Blastocystis was stained using Wright-Giemsa, periodic acid-Schiff (PAS), Oil Red O, Nile Red, and Lugol's iodine solution respectively. The staining effects of the five method on Blastocystis were compared. Results Wright-Giemsa staining colored the cytoplasm and nucleus of Blastocystis bluish-purple, with other parts lightly stained; PAS staining rendered Blastocystis cells red; Oil Red O staining showed different structures within Blastocystis in varying intensities of orange-red; Nile Red enabled Blastocystis to fluoresce orange-yellow under a fluorescence microscope; Lugol's iodine solution stained the cytoplasm and nucleus a dark brownish-yellow. Conclusions Wright-Giemsa staining is recommended for clinical diagnosis. For metabolic studies, a combination of periodic acid-Schiff (PAS) staining and Oil Red O staining is suggested; PAS + Oil Red O staining can provide comprehensive morphological evidence for cell metabolism research. Nile Red staining is recommended for dynamic observation of live Blastocystis. Lugol's iodine staining is suitable for preliminary screening of large-scale samples.

Objective:To explore the influence of artificial intelligence(AI)-assisted compressive sensing(ACS)technique with different acceleration factors on the image quality and scan time of three dimensional time-of-flight magnetic resonance angiography(3D-TOF-MRA)for brain.Methods:Thirty participants who underwent brain magnetic resonance imaging(MRI)at Tongzhou Branch of Beijing Friendship Hospital were recruited.All subjects underwent imaging scans about four different parameters:a non-accelerated technique(control group),ACS technique integrated with acceleration factor of 4.03(ACS4 group),ACS technique integrated with acceleration factor of 5.02(ACS5 group),and ACS technique integrated with acceleration factor of 6.06(ACS6 group).The image clarity,ranking of imaging capabilities of distal branch blood vessels and the ratio of pseudo-stenosis were qualitatively analyzed.The signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR),edge sharpness,and scan time were quantitatively analyzed.Results:There was not difference in vessel clarity among three ACS groups at the proximal and middle intracranial segments.For distal segments of blood vessel,the ACS4 group[3.0(3.0,3.0)]and ACS5 group[3.0(3.0,3.0)]were better than ACS6[2.5(2.0,3.0)](q=29.800,27.500,P<0.05).The imaging capabilities of distal-branch vessel of ACS4 group and ACS5 group were better than ACS6 group.There was no stenosis in the proximal and middle segments of the images of the three ACS group,and there were no stenosis in the images of distal vessels of ACS4 group and ACS5 group.A total of 5 cases were pseudo-stenosis in the distal vessels of ACS6 group.Compared with the control group,the incidence of pseudo-stenosis in the distal vessels of ACS6 group was 16.7%.The SNR and CNR values of quantitative analysis for proximal vessels in ACS6 group were higher than them in ACS4 group(q=27.800,26.200,P<0.05),and there was not significant difference in them among ACS4 group,ACS6 group and ACS5 group(P>0.05).The differences of SNR and CNR values in the middle and distal segments of blood vessels among different groups were not significant(P>0.05).There was not significant difference in the edge sharpness of blood vessels among ACS4 group,ACS5 group,and ACS6 group(P>0.05),while all of them were higher than those of control group,and the differences were significant(q=48.150,53.367,44.883,P<0.001).Compared with control group,the scan-time of ACS4 group was reduced by 55.19%,and that of ACS5 group was reduced by 64.07%,and that of ACS6 group was reduced by 70%.Conclusion:ACS technique can accelerate the imaging speed of brain 3D-TOF-MRA and ensure image quality.It is clinically recommended to set the ACS acceleration factor as 5.02 to undergo brain 3D-TOF-MRA scans.

Objective:To understand the prevalence of frailty and the importance of its influencing factors in adult population in Shaanxi Province.Methods:The data were from Shaanxi baseline survey of natural population cohort study in northwest China during 2018-2019. The frailty index (FI) was constructed to evaluate the frailty status of the population, and XGboost model combined with Shapley method was used to analyze the importance of the sociodemographic and life behavior factors affecting the prevalence of frailty by gender and age.Results:A total of 25 079 subjects were included, in whom 964 (3.8%) had frailty, and there was no significant difference in the overall prevalence of frailty between women (3.9%) and men (3.8%) ( P=0.629), but there was a gender specific difference in the distribution of FI ( P<0.001), and the proportion of the pre-frailty in men was higher than that in women. The prevalence of frailty increased with age ( P<0.001), the prevalence of frailty were 1.3%, 2.5% and 7.8% in young, middle-aged and elderly women, respectively, and 1.9%, 2.7% and 5.5% in young, middle-aged and elderly men, respectively. Sociodemographic characteristics and lifestyle patterns were both influencing factors for the prevalence of frailty, but their importance varied with gender and age. The top five contributing factors were education level, staying up late, annual family income level, sedentary time and marital status in young women, and staying up late, smoking, annual family income level, sedentary time and drinking in young men. The top five contributing factors were education level, annual family income level, passive exposure to smoking, staying up late, and sedentary time in middle-aged women, and annual family income level, education level, sedentary time, staying up late and drinking in middle-aged men. The top five contributing factors were annual family income level, passive exposure to smoking, sedentary time, marital status, and smartphone use in elderly women, and education level, annual family income level, smoking, smartphone use and sedentary time in elderly men. Conclusions:There are gender specific differences in the distribution of FI in Shaanxi. The prevalence of frailty increased with age, but young and middle-aged people also have frailty risk. The prevalence of frailty in young men was mainly related to unhealthy life behaviors, such as staying up late, smoking, sedentary behavior and drinking, while the prevalence of frailty in middle-aged and elderly men and women were more affected by sociodemographic factors, such as education level, economic status and marital status.