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.

Background Prenatal exposure to fine particulate matter (PM_2.5) is closely associated with cortical damage and neuroinflammation in offspring. The cyclic guanosine monophosphate–adenosine monophosphate synthase (cGAS)–stimulator of interferon genes (STING) signaling pathway is a key regulator of inflammation and may be subject to epigenetic regulation. Objective To investigate the role of cGAS-STING pathway activation in PM_2.5-induced cortical damage in offspring mice during pregnancy and the underlying epigenetic regulatory mechanisms. Methods Open field tests were used to assess depressive-like behavior in offspring mice. Morphological analysis was conducted to evaluate cortical damage and microglial activation in offspring brains. Real-time fluorescent quantitative PCR (RT-qPCR) and Western blot (WB) were performed to detect changes in the expression of key molecules in the cGAS-STING pathway in cortical tissue. A PM_2.5-induced microglial cell injury model was established in BV2 cells. Microglial activation was observed, cell viability was measured using the Cell Counting Kit-8 (CCK-8), and the expression levels of inducible nitric oxide synthase (iNOS) and key molecules in the cGAS-STING pathway were detected by RT-qPCR and WB. Bioinformatics analysis was performed to explore the epigenetic regulatory association between the STING signaling pathway and lysine-specific demethylase 5A (KDM5A). Changes in KDM5A mRNA and protein expression, as well as the protein level of histone H3 lysine 4 trimethylation (H3K4me3), were detected in an in vitro PM_2.5 injury model. Using small interfering RNA (siRNA) technology, the KDM5A gene was silenced in BV2 cells exposed to PM_2.5. The protein expression of H3K4me3 was detected to evaluate improvements in microglial activation, changes in inflammatory markers such as iNOS and mannose receptor (CD206), and alterations in the cGAS-STING pathway. Results Compared with the control group, the total distance of offspring mice in the PM_2.5 group was significantly reduced, and both the distance traveled and the time spent in the central area of the open field were significantly decreased (P<0.01, P<0.001), indicating depressive-like behavior in the offspring mice. Compared with the control group, the offspring mice in the PM_2.5 group exhibited disorganized cortical structure and significantly activated microglia (P<0.01), with significantly increased mRNA and protein levels of cGAS and STING (P<0.05, P<0.01, or P<0.001). The in vitro experiments demonstrated that the PM_2.5 treatment induced BV2 cells to polarize toward the M1 phenotype, exhibiting a distinct amoeboid morphology, with upregulated expression of the pro-inflammatory factor iNOS (P<0.05, P<0.01, or P<0.001) and activation of the cGAS-STING pathway (P<0.05, P<0.01). The analysis of RNA-seq data from KDM5A knockout cells revealed significantly downregulated STING expression, suggesting that KDM5A may activate the STING signaling pathway. The in vitro experiments further confirmed that the PM_2.5-treated BV2 cells exhibited significantly elevated mRNA and protein levels of KDM5A (P<0.01), while the H3K4me3 protein levels were markedly reduced (P<0.05). After silencing KDM5A in BV2 cells exposed to PM_2.5, compared with the PM_2.5+siNC group, the PM_2.5+siKDM5A group showed no obvious microglial activation and polarized toward the M2 phenotype, with significantly decreased expression levels of iNOS, cluster of differentiation 16 (CD16), and interleukin-1β (P<0.05, P<0.01), and significantly increased expression levels of anti-inflammatory factors CD206, YM1, and interleukin-10 (P<0.01, P<0.001). Meanwhile, the expression levels of cGAS and STING were also reduced (P<0.05, P<0.01). Conclusion KDM5A activates microglia through the cGAS-STING pathway, thereby contributing to PM_2.5-induced cortical damage in offspring mice during pregnancy.

Background Existing studies have confirmed that fine particulate matter (PM_2.5)is one of the important factors inducing pulmonary fibrosis. Pulmonary fibrosis is the terminal stage of a major category of lung diseases characterized by the destruction of tissue structure, and eventually leading lung ventilation and ventilation dysfunction. No effective pulmonary fibrosis treatment is available yet. Objective To investigate the protective effect of salidroside on pulmonary fibrosis induced by the exposure of PM_2.5 and its molecular mechanism. Methods Seventy 7-week-old male C57BL/6 mice were randomly divided into four groups: control group (intratracheal instillation of normal saline + saline by gavage, n=25), Sal group (intratracheal instillation of normal saline + Sal 60 mg·kg⁻¹ by gavage, n=10), PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ + saline by gavage, n=10), and Sal + PM_2.5 group (intratracheal instillation of PM_2.5 5 mg·kg⁻¹ +Sal 60 mg·kg⁻¹ by gavage, n=10). The mice were administered by gavage once daily, intratracheal instillation once every 3 d, and every 3 d constituted an experimental cycle. At the end of the 26-30th cycles, 3 mice in the control group and 3 mice in the PM_2.5 group were randomly sacrificed, and the lung tissues were collected for Masson staining to verify whether the pulmonary fibrosis model was successfully established. After 30 cycles, the model was successfully constructed. After 1 week of continuous observation, the mice were sacrificed, and the blood and lung tissues of the mice were collected to make lung tissue sections. Assay kits were correspondingly employed to detect oxidative stress indicators such as serum malondialdehyde (MDA) and superoxide dismutase (SOD). Western blotting was used to detect the expression of fibrosis-related proteins (Collagen-III, α-SMA), mitochondrial dynamics-related proteins (MFN1, Drp1), and mitophagy-related proteins (PINK1, Parkin, and LC3). Results Compared with the control group, the weight gain rate of the PM_2.5 group was slowed down (P<0.05), which was alleviated by the Sal intervention (P<0.05). The lung coefficient increased after the PM_2.5 exposure (P<0.05), which was alleviated by Sal intervention. Compared with the control group, the PM_2.5 group showed severe alveolar structure damage, inflammatory cell infiltration, and blue collagen deposition, and significantly increased the lung injury score, collagen volume fraction (CVF), Szapiel score, and Ashcroft score (P<0.05), as well as serum oxidative stress levels (P<0.05). The protein expression levels of Collagen-III, α-SMA, Drp1, PINK1, Parkin, and LC3 II/I were increased (P<0.05), and the expression of MFN1 was decreased (P<0.05). Compared with the PM_2.5 group, the Sal intervention alleviated lung injury, reduced inflammatory cell infiltration and collagen deposition, showing decreased lung injury score, CVF, Szapiel score, and Ashcroft score (P<0.05), and decreased serum oxidative stress levels (P<0.05); the protein expression levels of Collagen-III, α-SMA, PINK1, Parkin, and LC3 II/I were decreased (P<0.05), the expression level of Drp1 was decreased, and the expression level of MFN1 was increased. Conclusion In the process of pulmonary fibrosis induced by PM_2.5 exposure in mice, Sal may affect mitochondrial autophagy through PINK1/Parkin pathway and play a protective role. The specific mechanism needs to be further verified.

Sophora Flavescens is the dried root of the leguminous plant Sophora Flavescens Ait. It was first published in Shen Nong's Herbal Classic. Sophora Flavescens contains a variety of active ingredients, mainly including matrine and oxymatrine, with anti-inflammatory, anti-tumor, anti-arrhythmia, disease-resistant pathogenic microorganisms and other pharmacological effects. Clinically, the compound preparations of Sophora Flavescens include Compound KuShen injection and KuShen gel and so on, which can be used to treat many types of cancers and improve skin, mucous pruritus, pain and other symptoms. Due to the poor bioavailability, the structure of matrine needs to be reformed. MASM, matrine derivative, only needs a low concentration to have a good therapeutic effect on sepsis and liver fibrosis. In this article, the chemical composition, pharmacological effects, compound preparations and structural modification of matrine were mainly discussed, aiming to provide a theoretical basis for the clinical application of Sophora Flavescens and the development of new drugs.

Matrine is an alkaloid compound isolated and extracted from the traditional Chinese medicinal plant Sophora flavescens, which has anti-tumor, anti-inflammatory, and anti-viral effects. However, its clinical application has been limited due to its low in vivo activity, short duration of efficacy, and significant toxic side effects. In response to this challenge，pharmaceutical experts modified the structure of Matrine to obtain derivatives that addressed its limitations. Currently, research on the anti-tumor effects of Matrine and its derivatives is more prevalent, while research in inflammatory-related diseases still needs further strengthening.The progress on the role and mechanism of Matrine and its derivatives in inflammatory diseases were summarized in this paper, which offered valuable insights for the development of therapeutic agents based on Matrine.

Objective:To investigate the distribution characteristics of CTLA-4 on the surface of CD4+T cells in patients with breast cancer at different stages,and to evaluate its predictive value for the efficacy of radical mastectomy.Methods:A retrospective study was conducted on 200 breast cancer patients admitted between January 2020 and December 2022.Patients were divided into four groups based on clinical staging:stage Ⅰ(64 cases),stage Ⅱ(57 cases),stage Ⅲ(43 cases),and stage Ⅳ(36 cases).The clinical pathological characteristics of the four groups were compared,and the expression level of CTLA-4 on the surface of CD4+T cells in peripheral venous blood(CTLA-4+CD4+)was detected.Patients were divided into a poor prognosis group(52 cases)and a good prognosis group(148 cases)based on their prognosis,and the clinical pathological characteristics of the two groups were compared.A stratified regression model was used to analyze the relationship between CTLA-4+CD4+expression levels and different clinical characteristics.Logistic regression analysis was employed to evaluate the independent correlation between CTLA-4+CD4+expression levels and the risk of poor prognosis.An unconditional logistic regression model was used to analyze the multiplicative interaction effect of CTLA-4+CD4+expression levels and clinical staging on prognosis prediction.Restricted cubic spline analysis was used to investigate the relationship between CTLA-4+CD4+expression levels and poor patient prognosis.Results:Significant differences were observed in tumor diameter,ECOG score,lesion multiplicity,lymph node metastasis,tumor differentiation degree,ER,PR,HER2,Ki-67,CA125,CA153,and CEA among patients with different clinical stages(P<0.05).Significant differences were also observed in CD3+,CD4+,CD8+,and CTLA-4+CD4+(P<0.05).As the clinical stage increased,the proportions of CD3+,CD4+,and CD8+decreased,while the proportion of CTLA-4 on the surface of CD4+T cells increased(P<0.05).Significant differences were observed in clinical stage,tumor diameter,lymph node metastasis,tumor differentiation degree,ECOG score,ER,PR,HER2,and CTLA-4+CD4+among patients with different prognosis groups(P<0.05).Hierarchical regression analysis indicated that clinical stage,tumor diameter,lymph node metastasis,tumor differentiation degree,ECOG score,and HER2 had a significant positive impact on CTLA-4+CD4+(P<0.05),while ER and PR had a significant negative impact on CTLA-4+CD4+(P<0.05).Logistic regression analysis showed that CTLA-4+CD4+was positively correlated with poor prognosis(P<0.05).CTLA-4+CD4+and clinical stage had multiplicative and additive interactions on prognosis.Regardless of the clinical stage,CTLA-4+CD4+on the surface of CD4+T cells was significantly positively correlated with poor prognosis.Conclusion:The expression level of CTLA-4+CD4+in patients with advanced breast cancer is significantly elevated,playing a crucial role in the clinical pathological characteristics of breast cancer.An elevated level may indicate a poor prognosis.

Objective To investigate the feasibility of simultaneous multi-slice(SMS)acquisition combined with single-shot echo-planar imaging(SSEPI)multi-model diffusion weighted imaging(DWI)for breast lesions.Methods Totally 108 cases of breast lesions were retrospectively enrolled and divided into malignant group(n=66)and benign group(n=42)based on pathology.3.0T MR scanner was used to acquire SSEPI and SMS-SSEPI multi-b values DWI,7 derived parameters were obtained through post-processing with mono-exponential,fractional-order calculus(FROC)and continuous-time random walk(CTRW)models.Then the imaging quality and derived parameters of SMS-SSEPI and SSEPI DWI were compared between groups.Spearman correlation analysis was performed to explore the relationships of corresponding parameters between SMS-SSEPI DWI and SSEPI DWI.Diagnostic performance of each parameter for distinguishing malignant and benign lesions was evaluated according to the area under the receiver operating characteristic curve(AUC).Results Background noise score of SMS-SSEPI DWI was lower than that of SSEPI DWI(P＜0.05),whereas no significant difference of overall imaging quality,normal anatomical structure depiction,lesion conspicuity,geometric distortion,signal-to-noise ratio(SNR)nor contrast-to-noise ratio(CNR)was found between SMS-SSEPI DWI and SSEPI DWI(all P＞0.05).Parameters derived from SMS-SSEPI DWI were all moderately to highly positively correlated with those from SSEPI DWI(rs=0.66-0.98).Malignant lesions exhibited significantly lower apparent diffusion coefficient(ADC),diffusion coefficient based on FROC(DFROC),fractional order derivative in space(βFROC),diffusion coefficient based on CTRW(DCTRW),temporal diffusion heterogeneity index(αCTRW)and spatial diffusion heterogeneity index(βCTRW)values,but higher spatial parameter(μFROC)value than benign lesions(all P＜0.05).AUC of SMS-SSEPI DWI derived parameters for differentiating malignant from benign lesions were 0.699-0.900,of those from SSEPI DWI were 0.654-0.887,while in both SMS-SSEPI DWI and SSEPI DWI,DFROC had the highest diagnostic efficacy(AUC=0.900,0.887).Conclusion SMS-SSEPI DWI could be used to effectively differentiate malignant and benign breast lesions.

Practice shows that the Outline of the"Healthy China 2030"Plan is an effective means and way to cope with the growing medical needs of the people and realize the health of all people in China,and the benign interaction and synergistic development of the reform of the health insurance payment method reform and the development of public hospitals is precisely one of the policy focuses for the high-quality promotion of the construction of Healthy China.Based on the synergy theory and SFIC model,it explains the basic logic of the synergistic development of public hospital development and health insurance payment method reform,and sort out the optimization path of the synergistic development of the two:clarify the construction goal,and reach the starting conditions of effective synergistic development;give full play to the catalytic leadership led by the Party building,and build the foundation of synergistic reform;improve the system design,and build a policy system that fits the actual situation;create a good cooperative and interactive relationship to optimize the process of policy synergy.

Objective:To evaluate the application of metagenomic next-generation sequencing（mNGS）in the identification of non-tuberculous mycobacteria（NTM）.Methods:A retrospective analysis was conducted on mNGS results of 358 bronchoalveolar lavage fluid（BALF）samples positive for NTM collected at the First Affiliated Hospital of Zhejiang University School of Medicine from February 2021 to January 2024. The analysis included the distribution of NTM species，the detection of mixed pathogens，and the performance of conventional mycobacterial detection methods.Results:The results showed that 362 strains of 15 NTM species were identified from 350 specimens，8 specimens were not precise to the species level. The most frequently detected species were Mycobacterium intracellulare（37.3%，135/362）， Mycobacterium abscessus（26.8%，97/362），followed by Mycobacterium avium（11.0%，40/362）， Mycobacterium kansasii（8.0%，29/362）and Mycobacterium chelonae（7.7%，28/362）. Single NTM species were detected in 339 specimens，while two or three NTM species were simultaneously detected in 11 specimens（3.1%，11/358）. Non-NTM microorganisms co-infected were detected in 53.4%（191/358）of NTM-positive BALF samples，including common pathogens such as Pseudomonas aeruginosa， Staphylococcus aureus，and Aspergillus fumigatus；and difficult-to-identify pathogens such as Legionella pneumophila and Talaromyces marneffei. In NTM-positive patients detected by mNGS，the results supported the diagnosis of NTM infection in 298 cases（298/358，83.2%）and 105 cases（105/358，29.3%）initiated anti-NTM treatment accordingly；while in 60 cases（60/358，16.8%）the positive results were considered as colonization or unrelated to clinical infection. For samples tested with acid-fast staining，mycobacterial liquid culture，and DNA microarray，the positivity rates for NTM were 31.5%（73/232），48.7%（57/117），and 43.0%（46/107），respectively. Conclusions:mNGS demonstrates advantages in identification of NTM. However，the test may detect multiple microorganisms，in that case，the interpretation with clinical and radiological results is requried to determine the main pathogens.