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.

Aim To investigate the protective effect of Vaccarin(Va)on epithelial-mesenchymal transition(EMT)in renal fibrosis model mice through regulating STAT3,and the underlying mechanism.Methods Left ureter ligation was used to establish a mouse model of unilateral ureteral obstruction(UUO);human kid-ney tubular epithelial(HK2)cells were induced to differentiate by transforming growth factor-β(TGF-β)in vitro.HE and Masson staining were used to observe the morphological changes of renal tissue;kits were used to detect the levels of BUN,Cr,IL-1β and IL-7 in mouse serum;CCK-8 was used to detect the effect of Va on the viability of HK2 cells;RT-PCR was used to detect the levels of inflammatory factors in HK2 cells;Western blot was used to detect the expression of STAT3,p-STAT3,E-cadherin,and α-SMA proteins in renal tissue and HK2 cells;to further investigate the regulation of Va on STAT3,JAK/STAT3 pathway acti-vator RO8191 was used to treat TGF-β-induced HK2 cells,and functional loss was detected.Results Va improved the pathological damage in UUO mice,inhibi-ted the levels of BUN,Cr and inflammatory factors;Va inhibited the phosphorylation of STAT3,upregulated E-cadherin,and downregulated α-SMA protein expres-sion;RO8191 counteracted the inhibitory effect of Va on the phosphorylation of STAT3.Conclusions Va inhibits the phosphorylation of STAT3 and the release of inflammatory factors,improves EMT,thus exerting an anti-renal fibrosis effect.

Objective:To quantitatively evaluate the policy texts on mutual recognition of examination and inspection results at the national and local levels in China from 2006 to 2025 based on the PMC index model,and provide reference for policy formulation and improvement.Methods:The ROSTCM6 software was used to sort out and conduct text mining on 27 policy documents issued at the national and local levels,establishing the PMC index model for the mutual recognition of examination and inspection results in China.Quantitative analysis was conducted through a PMC evaluation system consisting of 9 first-level variables and 39 second-level variables.Results:The average PMC index was 6.06(excellent level).Among the 27 policies,4 were rated as perfect,18 as excellent,and 5 as acceptable.Conclusions:Current policies need to strengthen the formulation of scientific and feasible goals,improve legal guarantees and medical insurance coordination mechanisms,and build a complete data security maintenance system to provide policy support and guarantees for the continuous advancement of the mutual recognition of examination and inspection results.

Aim To investigate the protective effect of Vaccarin(Va)on epithelial-mesenchymal transition(EMT)in renal fibrosis model mice through regulating STAT3,and the underlying mechanism.Methods Left ureter ligation was used to establish a mouse model of unilateral ureteral obstruction(UUO);human kid-ney tubular epithelial(HK2)cells were induced to differentiate by transforming growth factor-β(TGF-β)in vitro.HE and Masson staining were used to observe the morphological changes of renal tissue;kits were used to detect the levels of BUN,Cr,IL-1β and IL-7 in mouse serum;CCK-8 was used to detect the effect of Va on the viability of HK2 cells;RT-PCR was used to detect the levels of inflammatory factors in HK2 cells;Western blot was used to detect the expression of STAT3,p-STAT3,E-cadherin,and α-SMA proteins in renal tissue and HK2 cells;to further investigate the regulation of Va on STAT3,JAK/STAT3 pathway acti-vator RO8191 was used to treat TGF-β-induced HK2 cells,and functional loss was detected.Results Va improved the pathological damage in UUO mice,inhibi-ted the levels of BUN,Cr and inflammatory factors;Va inhibited the phosphorylation of STAT3,upregulated E-cadherin,and downregulated α-SMA protein expres-sion;RO8191 counteracted the inhibitory effect of Va on the phosphorylation of STAT3.Conclusions Va inhibits the phosphorylation of STAT3 and the release of inflammatory factors,improves EMT,thus exerting an anti-renal fibrosis effect.

Objectives:To investigate the association between the triglyceride-glucose(TyG)index and risk of non-alcoholic fatty liver disease(NAFLD)in young and middle-aged(<60 years)adults.Methods:From June 2006 to October 2007,47 675 employees of Kailuan Group with no liver disease were selected as the study objects.Based on the TyG index quartile,participants were divided into Q1 group(TyG index≤8.08,n=11 924),Q2 group(8.0836.46,n=11 919),the association between TyG index,cum-TyG and cumulative exposure time and the risk of NAFLD was analyzed.Results:The average age of the study population was(44.3±8.7)years,36 345 participants were males(76.23%).During a median follow-up period of 11.55(7.28,13.89)years,4 635(9.72%)participants developed new-onset NAFLD.After adjusting for confounders,cox regression analysis showed that compared with the Q1 group,the HR(95%CI)for NAFLD in the Q2 to Q4 groups were 1.328(1.191-1.480),1.591(1.430-1.770),and 2.106(1.861-2.384),respectively,Ptrend<0.001.Compared with the cum-Q1 group,the HR(95%CI)for NAFLD in the cum-Q2 to cum-Q4 groups were 1.571(1.426-1.730),2.123(1.935-2.330)and 2.593(2.367-2.840),respectively,Ptrend<0.001.Compared with the TyG index for 0 year,the HR(95%CI)of NAFLD for 2,4 and 6 years was 1.333(1.196-1.486),1.879(1.690-2.088)and 3.184(2.860-3.545),respectively,Ptrend<0.001.Conclusions:Increased TyG index is an independent risk factor for the new-onset NAFLD in young and middle-aged population.

Microbial detection and control of traditional Chinese medicine(TCM) decoction pieces are crucial for the quality control of TCM preparations. It is also a key area of research in the measurement technology and equipment development for TCM manufacturing. Guided by TCM manufacturing measurement methodologies, this study presented a design of a novel portable microbial detection device, using Atractylodis Macrocephalae Rhizoma decoction pieces as a demonstration. Immunomagnetic separation technology was employed for specific isolation and labeling of target microorganisms. Enzymatic signal amplification was utilized to convert weak biological signals into colorimetric signals, constructing an optical biosensor. A self-developed smartphone APP was further applied to analyze the colorimetric signals and quantify target concentrations. A portable and automated detection system based on Arduino microcontroller was developed to automatically perform target microbial separation/extraction, as well as mimetic enzyme labeling and catalytic reactions. The developed equipment specifically focuses on the rapid and quantitative microbial analysis of TCM active pharmaceutical ingredients, intermediates in TCM manufacturing, and final TCM products. Experimental results demonstrate that the equipment could detect Salmonella in samples within 2 h, with a detection limit as low as 5.1 × 10~3 CFU·mL~(-1). The equipment enables the rapid detection of microorganisms in TCM decoction pieces, providing a potential technical solution for on-site rapid screening of microbial contamination indicators in TCM. It has broad application prospects in measurement technology for TCM manufacturing and offers strong technical support for the modernization, industrialization, and intelligent development of TCM.
Drugs, Chinese Herbal/analysis* ; Atractylodes/microbiology* ; Rhizome/microbiology* ; Biosensing Techniques/methods* ; Medicine, Chinese Traditional ; Colorimetry/instrumentation* ; Quality Control

Objectives:To investigate the association between the triglyceride-glucose(TyG)index and risk of non-alcoholic fatty liver disease(NAFLD)in young and middle-aged(<60 years)adults.Methods:From June 2006 to October 2007,47 675 employees of Kailuan Group with no liver disease were selected as the study objects.Based on the TyG index quartile,participants were divided into Q1 group(TyG index≤8.08,n=11 924),Q2 group(8.0836.46,n=11 919),the association between TyG index,cum-TyG and cumulative exposure time and the risk of NAFLD was analyzed.Results:The average age of the study population was(44.3±8.7)years,36 345 participants were males(76.23%).During a median follow-up period of 11.55(7.28,13.89)years,4 635(9.72%)participants developed new-onset NAFLD.After adjusting for confounders,cox regression analysis showed that compared with the Q1 group,the HR(95%CI)for NAFLD in the Q2 to Q4 groups were 1.328(1.191-1.480),1.591(1.430-1.770),and 2.106(1.861-2.384),respectively,Ptrend<0.001.Compared with the cum-Q1 group,the HR(95%CI)for NAFLD in the cum-Q2 to cum-Q4 groups were 1.571(1.426-1.730),2.123(1.935-2.330)and 2.593(2.367-2.840),respectively,Ptrend<0.001.Compared with the TyG index for 0 year,the HR(95%CI)of NAFLD for 2,4 and 6 years was 1.333(1.196-1.486),1.879(1.690-2.088)and 3.184(2.860-3.545),respectively,Ptrend<0.001.Conclusions:Increased TyG index is an independent risk factor for the new-onset NAFLD in young and middle-aged population.

OBJECTIVE: To assess the independent and combined effects of air pollutants, meteorological factors, and greenspace exposure on new tuberculosis (TB) cases. METHODS: TB case data from Shanghai (2013-2018) were obtained from the Shanghai Center for Disease Control and Prevention. Environmental data on air pollutants, meteorological variables, and greenspace exposure were obtained from the National Tibetan Plateau Data Center. We employed a distributed-lag nonlinear model to assess the effects of these environmental factors on TB cases. RESULTS: Increased TB risk was linked to PM _2.5, PM ₁₀, and rainfall, whereas NO ₂, SO ₂, and air pressure were associated with a reduced risk. Specifically, the strongest cumulative effects occurred at various lags: PM _2.5 ( RR = 1.166, 95% CI: 1.026-1.325) at 0-19 weeks; PM ₁₀ ( RR = 1.167, 95% CI: 1.028-1.324) at 0-18 weeks; NO ₂ ( RR = 0.968, 95% CI: 0.938-0.999) at 0-1 weeks; SO ₂ ( RR = 0.945, 95% CI: 0.894-0.999) at 0-2 weeks; air pressure ( RR = 0.604, 95% CI: 0.447-0.816) at 0-8 weeks; and rainfall ( RR = 1.404, 95% CI: 1.076-1.833) at 0-22 weeks. Green space exposure did not significantly impact TB cases. Additionally, low temperatures amplified the effect of PM _2.5 on TB. CONCLUSION Exposure to PM _2.5, PM ₁₀, and rainfall increased the risk of TB, highlighting the need to address air pollutants for the prevention of TB in Shanghai.
China/epidemiology* ; Humans ; Air Pollutants/analysis* ; Tuberculosis/epidemiology* ; Incidence ; Meteorological Concepts ; Particulate Matter/adverse effects* ; Environmental Exposure ; Male ; Female ; Adult ; Air Pollution ; Middle Aged