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 analyze the distribution characteristics of mirtazapine steady-state trough concentration and concentration-to-dose ratio （ C / D ）， and to investigate the influence of clinical and genetic factors on C / D . METHODS A retrospective study was conducted on hospitalized patients with depression who received mirtazapine treatment and underwent therapeutic drug monitoring at the First Hospital of Hebei Medical University from May 2022 to May 2025. The collected data included patients’ gender， age， body mass index， daily dose， steady-state trough concentration， smoking status， history of liver disease， drug type， concomitant medications， and CYP2D6 metabolic phenotype. The C / D was calculated. Spearman rank correlation was used to analyze the relationship between mirtazapine steady-state trough concentration and daily dose. Univariate analysis and multiple linear regression model were employed to screen the factors potentially influencing the C / D of mirtazapine. RESULTS A total of 226 patients were included. The daily dose of mirtazapine was 25.00 （24.82， 30.00） mg/d， the steady-state trough concentration was 44.46 （20.00， 70.00） ng/mL， and the C / D was 1.83 （1.00， 2.00） （ng·d）/（mL·mg）. Steady-state trough concentrations were within the reference range （30-80 ng/mL） in 121 patients （53.54%）， below the lower limit in 80 patients （35.40%）， and above the upper limit in 25 patients （11.06%）. A positive correlation was observed between mirtazapine steady-state trough concentration and daily dose （coefficient of determination was 0.320 8， P ＜0.001）. Gender， smoking status， and CYP2D6 metabolic phenotype were significantly associated with the mirtazapine C / D （ P ＜0.05）. CONCLUSIONS Significant interindividual variability exists in mirtazapine steady-state trough concentrations. Gender， smoking status， and CYP2D6 metabolic phenotype are identified as independent influencing factors for the mirtazapine C / D ， with higher C / D ratios observed in females， non-smokers， and intermediate metabolizers.

Rheumatoid arthritis （RA） is a common autoimmune disease characterised clinically by symmetrical joint pain， swelling， and stiffness. Long-term chronic synovial inflammation can lead to severe joint damage and even disability， thereby affecting quality of life for patients. Current clinical treatment of RA emphasises an integrated approach combining traditional Chinese and Western medicine， with traditional Chinese medicine offering certain advantages in reducing disease activity of RA， preventing relapses， and other aspects. Modern clinical evidence confirms that Guizhi Shaoyao Zhimutang （GSZT） is effective in improving symptoms such as immune metabolism， joint stiffness， and joint pain in RA patients. Pharmacological studies have revealed that GSZT primarily contains components such as cinnamaldehyde， total glucosides of paeony， total alkaloids of Aconiti Lateralis Radix Praeparata， glycyrrhetinic acid， zingiberone， isoimperatorin， ephedra polysaccharides， and cedrol. It improves RA symptoms via multiple mechanisms and targets， including enhancing immune responses， exerting anti-inflammatory and analgesic effects， regulating relevant signalling pathways， inhibiting cell apoptosis， and suppressing bone destruction. This paper reviewed the syndrome patterns and pharmacological basis of GSZT in the treatment of RA， as well as its clinical applications and related mechanisms， thereby providing a theoretical basis and reference for the further development and utilisation of GSZT in the treatment of RA.

Rheumatoid arthritis （RA） is a common autoimmune disease characterised clinically by symmetrical joint pain， swelling， and stiffness. Long-term chronic synovial inflammation can lead to severe joint damage and even disability， thereby affecting quality of life for patients. Current clinical treatment of RA emphasises an integrated approach combining traditional Chinese and Western medicine， with traditional Chinese medicine offering certain advantages in reducing disease activity of RA， preventing relapses， and other aspects. Modern clinical evidence confirms that Guizhi Shaoyao Zhimutang （GSZT） is effective in improving symptoms such as immune metabolism， joint stiffness， and joint pain in RA patients. Pharmacological studies have revealed that GSZT primarily contains components such as cinnamaldehyde， total glucosides of paeony， total alkaloids of Aconiti Lateralis Radix Praeparata， glycyrrhetinic acid， zingiberone， isoimperatorin， ephedra polysaccharides， and cedrol. It improves RA symptoms via multiple mechanisms and targets， including enhancing immune responses， exerting anti-inflammatory and analgesic effects， regulating relevant signalling pathways， inhibiting cell apoptosis， and suppressing bone destruction. This paper reviewed the syndrome patterns and pharmacological basis of GSZT in the treatment of RA， as well as its clinical applications and related mechanisms， thereby providing a theoretical basis and reference for the further development and utilisation of GSZT in the treatment of RA.

Objective: To investigate the factors influencing the co-prevalence of allergic rhinitis and obesity among primary and secondary school students in Inner Mongolia, so as to provide a data foundation and theoretical basis for developing targeted intervention measures. Methods: In September and October 2024, a stratified cluster random sampling method was employed to select 139 102 students from 539 schools across 12 leagues/cities and 103 banners/counties in Inner Mongolia Autonomous Region. Participants who were diagnosed with allergic rhinitis by a doctor at least once within one year and had a body mass index ≥ 28 kg/m 2 were considered to have comorbid conditions. Results: The coprevalence rate of allergic rhinitis and obesity among primary and secondary school students in Inner Mongolia was 6.4% (8 931 cases). Lasso-Logistic regression revealed that nonboarding status, higher maternal education, consuming high protein foods ≥1 time daily, occasionally or never eating breakfast, engaging in moderate to vigorous physical activity for ≥60 minutes on fewer than half of holidays, and having been exposed to second hand smoke in person within the past seven days were associated with higher odds ratios for co-prevalence of allergic rhinitis and obesity( OR = 1.23 , 1.22-1.63, 1.20, 1.19, 1.38, 1.35); being female, higher grade level, residence in flag/county/district areas, non only child status, never having consumed a full glass of alcohol, non hypertensive status, and households without pets were associated with lower co-prevalence risks ( OR =0.65, 0.67-0.77, 0.81, 0.87, 0.73, 0.41, 0.68) (all P <0.05). The ROC curve indicated an area under the curve of 0.64 for the predictive model, demonstrating satisfactory discriminatory ability. The calibration curve showed consistency between predicted and actual occurrence probabilities. Conclusions The co-prevalence of allergic rhinitis and obesity among primary and secondary school students in Inner Mongolia is closely associated with demographic characteristics, dietary behaviours, and lifestyle habits. Future prevention and control strategies should prioritize these factors to implement targeted interventions.

ObjectiveTo explore the dose-effect relationship and safety of high， medium， and low doses of raw Astragali Radix in the modified Huangqi Chifengtang （MHCD） for treating proteinuria in immunoglobulin A （IgA） nephropathy， and to provide scientific evidence for the clinical use of high-dose Astragali Radix in the treatment of proteinuria in IgA nephropathy. MethodsA total of 120 patients with IgA nephropathy， diagnosed with Qi deficiency and blood stasis combined with wind pathogen and heat toxicity， were randomly divided into a control group and three treatment groups. The control group received telmisartan combined with a Chinese medicine placebo， while the treatment groups were given telmisartan combined with MHCD containing different doses of raw Astragali Radix （60， 30， 15 g）. Each group contained 30 patients， and the treatment period was 12 weeks. Changes in 24-hour urinary protein （24 hUTP）， traditional Chinese medicine （TCM） syndrome scores， effective rate， and renal function were observed before and after treatment. Safety was assessed by monitoring liver function and blood routine. ResultsAfter 12 weeks of treatment， 24 hUTP significantly decreased in the high， medium， and low-dose groups， as well as the control group （P<0.05， P<0.01）. The TCM syndrome scores in the high， medium， and low-dose groups also significantly decreased （P<0.01）. Comparisons between groups showed that the 24 hUTP in the high-dose group was significantly lower than in the medium， low-dose， and control groups （P<0.05， P<0.01）， and the 24 hUTP in the medium-dose group was significantly lower than in the control group （P<0.05）. The TCM syndrome scores in the high and medium-dose groups were significantly lower than in the low-dose and control groups （P<0.05， P<0.01）. The total effective rates for proteinuria in the high， medium， low-dose， and control groups were 92.59% （25/27）， 85.19% （23/27）， 60.71% （17/28）， and 57.14% （16/28）， respectively. The effective rates in the high and medium-dose groups were significantly higher than in the low-dose and control groups （χ²=13.185， P<0.05， P<0.01）. The effective rates for TCM syndrome scores in the high， medium， low-dose， and control groups were 88.89% （24/27）， 81.48% （22/27）， 71.43% （20/28）， and 46.43% （13/28）， respectively. The efficacy of TCM syndrome scores in the high and medium-dose groups was significantly higher than in the control group （χ²=14.053， P<0.01）. Compared with pre-treatment values， there was no statistically significant difference in eGFR and serum creatinine in the high and medium-dose groups. However， eGFR significantly decreased in the low-dose and control groups after treatment （P<0.05）， and serum creatinine levels increased significantly in the control group （P<0.05）. No statistically significant differences were observed in urea nitrogen， uric acid， albumin， total cholesterol， triglycerides， liver function， and blood routine before and after treatment in any group. ConclusionThere is a dose-effect relationship in the treatment of IgA nephropathy with high， medium， and low doses of raw Astragali Radix in MHCD. The high-dose group exhibited the best therapeutic effect and good safety profile.

OBJECTIVES: To explore the mediating role of sleep duration in the relationship between depression symptoms and myopia among middle school students. METHODS: This study was a cross-sectional research conducted using a stratified cluster random sampling method. A total of 1 728 middle school students were selected from two junior high schools and two senior high schools in certain urban areas and farms of the Xinjiang Production and Construction Corps. Questionnaire surveys and vision tests were conducted among the students. Spearman analysis was used to analyze the correlation between depression symptoms, sleep duration, and myopia. The Bootstrap method was employed to investigate the mediating effect of sleep duration between depression symptoms and myopia. RESULTS: The prevalence of myopia in the overall population was 74.02% (1 279/1 728), with an average sleep duration of (7.6±1.0) hours. The rate of insufficient sleep was 83.62% (1 445/1 728), and the proportion of students exhibiting depression symptoms was 25.29% (437/1 728). Correlation analysis showed significant negative correlations between visual acuity in both eyes and sleep duration with depressive emotions as measured by the Center for Epidemiologic Studies Depression Scale (with correlation coefficients of -0.064, -0.084, and -0.199 respectively; P<0.01), as well as with somatic symptoms and activities (with correlation coefficients of -0.104, -0.124, and -0.233 respectively; P<0.01) and interpersonal relationships (with correlation coefficients of -0.052, -0.059, and -0.071 respectively; P<0.05). The correlation coefficients for left and right eye visual acuity and sleep duration were 0.206 and 0.211 respectively (P<0.001). Sleep duration exhibited a mediating effect between depression symptoms and myopia (indirect effect=0.056, 95%CI: 0.029-0.088), with the mediating effect value for females (indirect effect=0.066, 95%CI: 0.024-0.119) being higher than that for males (indirect effect=0.042, 95%CI: 0.011-0.081). CONCLUSIONS Sleep duration serves as a partial mediator between depression symptoms and myopia in middle school students.
Humans ; Myopia/etiology* ; Male ; Female ; Depression/physiopathology* ; Cross-Sectional Studies ; Sleep ; Adolescent ; Students ; Child ; Time Factors ; Sleep Duration

OBJECTIVES: To investigate the relationship between the polygenic risks for various psychiatric disorders and clinical and neuropsychological characteristics in children with attention-deficit/hyperactivity disorder (ADHD). METHODS: Using a cross-sectional design, 285 children with ADHD and 107 healthy controls were assessed using the Child Behavior Checklist, the Behavior Rating Inventory of Executive Function for parents, the Wechsler Intelligence Scale for Children, Fourth Edition, and the Cambridge Neuropsychological Test Automated Battery. Blood samples were collected for genetic data. Polygenic risk scores (PRSs) for various psychiatric disorders were calculated using the PRSice-2 software. RESULTS: Compared with the healthy controls, the children with ADHD displayed significantly higher PRSs for ADHD, major depressive disorder, anxiety disorder, and obsessive-compulsive disorder (P<0.05). In terms of daily-life executive function, ADHD-related PRS was significantly correlated with the working memory factor; panic disorder-related PRS was significantly correlated with the initiation factor; bipolar disorder-related PRS was significantly correlated with the shift factor; schizophrenia-related PRS was significantly correlated with the inhibition, emotional control, initiation, working memory, planning, organization, and monitoring factors (P<0.05). The PRS related to anxiety disorders was negatively correlated with total IQ and processing speed index (P<0.05). The PRS related to obsessive-compulsive disorder was negatively correlated with the processing speed index and positively correlated with the stop-signal reaction time index of the stop-signal task (P<0.05). CONCLUSIONS PRSs for various psychiatric disorders are closely correlated with the behavioral and cognitive characteristics in children with ADHD, which provides more insights into the heterogeneity of ADHD.
Humans ; Attention Deficit Disorder with Hyperactivity/genetics* ; Child ; Male ; Female ; Cross-Sectional Studies ; Neuropsychological Tests ; Multifactorial Inheritance ; Adolescent ; Mental Disorders/etiology* ; Executive Function ; Genetic Risk Score

Specific learning disorder (SLD) is a common neurodevelopmental disorder in children that significantly affects academic performance and quality of life. At present, diagnosis mainly relies on standardized tests and professional evaluations, a process that is complex and time-consuming. Multiple studies have shown that machine learning can analyze diverse data, including test scores, handwriting samples, eye movement data, neuroimaging data, and genetic data, to automatically learn the relationships between input features and output labels and achieve efficient prediction. It shows great potential for early screening, auxiliary diagnosis, and research on underlying mechanisms in SLD. This article reviews the applications of machine learning in the auxiliary diagnosis of SLD and discusses its performance when handling different data types.
Humans ; Machine Learning ; Specific Learning Disorder/diagnosis* ; Child