ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

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.

Background: Maturity-onset diabetes of the young (MODY) due to variants of hepatocyte nuclear factor 1-beta (HNF1β) (MODY5) has not been well studied in the Chinese population. This study aimed to estimate its prevalence and evaluate the application of a clinical screening method (Faguer score) in Chinese early-onset diabetes (EOD) patients. Methods: Among 679 EOD patients clinically diagnosed with type 2 diabetes mellitus (age at diagnosis ≤40 years), the exons of HNF1β were sequenced. Functional impact of rare variants was evaluated using a dual-luciferase reporter system. Faguer scores ≥8 prompted multiplex ligation-dependent probe amplification (MLPA) for large deletions. Pathogenicity of HNF1β variants was assessed following the American College of Medical Genetics and Genomics (ACMG) guidelines. Results: Two rare HNF1β missense mutations (E105K and G454R) were identified by sequencing in five patients, showing functional impact in vitro. Another patient was found to have a whole-gene deletion by MLPA in 22 patients with the Faguer score above 8. Following ACMG guidelines, six patients carrying pathogenic or likely pathogenic variant were diagnosed with MODY5. The estimated prevalence of MODY5 in Chinese EOD patients was approximately 0.9% or higher. Conclusion MODY5 is not uncommon in China. The Faguer score is helpful in deciding whether to perform MLPA analysis on patients with negative sequencing results.

OBJECTIVE: This study aimed to investigate possible serum 25-hydroxyvitamin D [25(OH)D] cutoffs for the associations between 25(OH)D and Bone turnover markers (BTMs), and how GC gene variation influences such cutoffs in Chinese women of childbearing age. METHODS: In total, 1,505 non-pregnant or non-lactating women (18-45 years) were recruited from the 2015 Chinese Adult Chronic Disease and Nutrition Surveillance. Serum 25(OH)D, osteocalcin (OC), procollagen type 1 N-terminal propeptide (P1NP), β-CrossLaps of type 1 collagen containing cross-linked C-telopeptide (β-CTX), and single nucleotide polymorphisms were determined. Locally weighted regression and smoothing scatterplot and segmented regression were performed to estimate the 25(OH)D thresholds. RESULTS: The median serum 25(OH)D was 16.63 (11.96-22.55) ng/mL and the prevalence of low serum 25(OH)D (< 12 ng/mL) was 25.2%. Women with the lowest 25(OH)D had the highest β-CTX. After adjustment for the confounders, 25(OH)D cutoffs for OC [14.04 (12.84-15.23) ng/mL], β-CTX [13.94 (12.49-15.39) ng/mL], and P1NP [13.87 (12.37-15.37) ng/mL] in the whole population, cutoffs for OC [12.30 (10.68-13.91) ng/mL], β-CTX [12.23 (10.22-14.23) ng/mL], and P1NP [11.85 (10.40-13.31) ng/mL] in women with the GC rs2282679 G allele, and cutoffs for OC [12.75 (11.81-13.68) ng/mL], β-CTX [13.05 (11.78-14.32) ng/mL], and P1NP [12.81 (11.57-14.06) ng/mL] in women with the GC rs2282679 T allele, were observed. Below these cutoffs, BTMs were negatively associated with 25(OH)D, while above these cutoffs, BTMs plateaued. CONCLUSION In Chinese women of childbearing age, there were thresholds effect of serum 25(OH)D concentrations on BTMs. The results indicated that serum 25(OH)D concentrations < 13.87 ng/mL in this population had adverse influences on maintaining bone remodeling. BTMs were suppressed at a relatively lower serum 25(OH)D in women with the GC rs2282679 G allele compared with those with the T allele.
Humans ; Female ; Vitamin D/blood* ; Adult ; Middle Aged ; Polymorphism, Single Nucleotide ; Adolescent ; Young Adult ; China ; Biomarkers/blood* ; Bone Remodeling/genetics* ; Vitamin D-Binding Protein/genetics* ; Procollagen/blood* ; Osteocalcin/blood* ; Peptide Fragments/blood* ; East Asian People

OBJECTIVE: This study explored the job choice preferences of Center for Disease Prevention and Control (CDC) workers to provide CDC management information and recommendations for optimizing employee retention and motivation policies. METHODS: A discrete choice experiment was conducted in nine provinces across China. Seven key attributes were identified to analyze the job preferences of CDC workers. Mixed logit models, latent class models, and policy simulation tools were used. RESULTS: A valid sample of 5,944 cases was included in the analysis. All seven attributes significantly influenced the job choices of CDC workers. Heterogeneity analyses identified two main groups based on different levels of preference for attribute utility. Income-prioritizers were concerned with income and opportunities for career development, whereas bianzhi-prioritizers were concerned with bianzhi and welfare benefits. The policy simulation analysis revealed that income-prioritizers had a relatively higher sensitivity to multiple job preference incentives. CONCLUSION Income and bianzhi were the two key attributes influencing the job choices and retention preferences of CDC workers. Heterogeneity in job preferences was also identified. Based on the preference characteristics of different subgroups, policy content should be skewed to differentiate the importance of incentives.
China ; Humans ; Male ; Female ; Adult ; Centers for Disease Control and Prevention, U.S. ; Middle Aged ; Choice Behavior ; Career Choice ; Motivation

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

OBJECTIVES: This study aimed to explore the impact of cell spreading area on odontoblast polarization and differentiation using micropatterned surfaces ge-nerated by photolithography. METHODS: Micropatterned surfaces with differential adhesive properties were prepared using polyethylene glycol diacrylate (PEGDA)-ba-sed photolithography. Human dental pulp stem cells (hD-PSCs) were isolated into single cells and cultured on micropatterned surfaces with areas of 1 800, 2 700, and 3 600 μm². Immunofluorescence staining was used to observe cell morphology and analyze the relocating of the golgi apparatus and nucleus. Alkaline phosphatase staining was preformed to examine odontogenic differentiation. RESULTS: The hDPSCs were successfully isolated and cultured on micropatterned surfaces mimicking the morphology of polarized odontoblasts. Phalloidin staining confirmed that the isolated hDPSCs successfully recapitulated the morphology of predesigned micropatterns. Immunofluorescence staining showed that the polarization and differentiation levels of the hDPSCs with a 3600 μm² area were significantly higher than those with 1 800 and 2 700 μm² areas (P<0.05). CONCLUSIONS The polarization and differentiation of single hDPSCs increased with the cell areas on micropatterned surfaces.
Cell Differentiation ; Humans ; Dental Pulp/cytology* ; Odontoblasts/cytology* ; Stem Cells/cytology* ; Cells, Cultured ; Cell Polarity ; Surface Properties

OBJECTIVES: This study aimed to explore the expression of lysosomal-associated membrane protein 5 (LAMP5) and microRNA (miR)-302a-3p in oral squamous cell carcinoma (OSCC) and their functional mechanism on the invasion and metastasis of OSCC. METHODS: The expression of LAMP5 in OSCC and its sensitivity as a prognostic indicator were analyzed on the basis of The Cancer Genome Atlas database. Western blot, quantitative reverse transcription polymerase chain reaction, and cell immunocytochemistry were used to detect the expression of LAMP5 in OSCC tissues and cells. The effect of LAMP5 on the proliferation, migration, and invasion of OSCC cells was evaluated through cell counting kit-8, immunocytochemistry, migration, and invasion assays, respectively. The miRNA targeting prediction websites were used to predict the miR that regulates LAMP5 and verify the targeted regulatory effect of miR-302a-3p on LAMP5. The effect of LAMP5 knockdown on OSCC tumor growth was evaluated in a nude mouse tumorigenesis model. RESULTS: LAMP5 was highly expressed in OSCC tissues and cells. It showed high sensitivity in the early diagnosis of OSCC. LAMP5 knockdown significantly inhibited the proliferation, migration, and invasion of OSCC cells, whereas LAMP5 overexpression increased these cell activities. The expression of LAMP5 was regulated by miR-302a-3p. In vivo, LAMP5 knockdown significantly inhibited the growth of OSCC tumor. CONCLUSIONS LAMP5 promotes the malignant progression of OSCC by enhancing the proliferation, migration, and invasion of OSCC cells. The expression of LAMP5 is negatively regulated by miR-302a-3p.
MicroRNAs/metabolism* ; Mouth Neoplasms/metabolism* ; Humans ; Animals ; Carcinoma, Squamous Cell/genetics* ; Neoplasm Invasiveness ; Cell Proliferation ; Mice, Nude ; Cell Movement ; Lysosomal Membrane Proteins/genetics* ; Mice ; Cell Line, Tumor ; Neoplasm Metastasis