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.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Pulmonary fibrosis（PF） is a progressive and life-threatening disease with limited therapeutic options， highlighting the urgent need for innovative drug discovery strategies. To address this challenge， the authors propose the formula-originated rational intelligent screening&translation（FIRST）， a systematic framework for developing anti-fibrotic monomers derived from classical traditional Chinese medicine（TCM）. The strategy integrates three key dimensions， including tissue-oriented intelligent screening of active compounds， structural optimization based on drug-target spatial interactions and plant biosynthetic pathways， and cross-scale validation of drug. We further highlight its applications in discovering tissue-oriented novel drugs from clinically validated TCM， the development and mechanistic elucidation of anti-fibrotic therapeutics， as well as the clinical translation and secondary development of candidate drugs. This strategy paves the way for first-in-class， formula-derived monomeric drugs with defined structures， clarified mechanisms， and proven safety， offering a transformative avenue to meet the urgent therapeutic needs of PF and setting a new paradigm for TCM-based drug innovation.

Cyclic GMP-AMP synthase (cGAS), a pivotal molecule in innate immunity, has emerged as a keypoint in interdisciplinary research at the intersection of basic immunology and tumor biology. As a cytosolic nucleic acid sensor, cGAS is primarily characterized by its capacity to recognize double-stranded DNA (dsDNA) in the cytosol. Upon binding to dsDNA, cGAS undergoes a conformational change that promotes its dimerization and subsequent enzymatic activation. Once activated, it catalyzes the synthesis of the second messenger 2',3'-cGAMP from ATP and GTP. cGAMP then binds to the adaptor protein STING, which resides on the endoplasmic reticulum (ER) membrane. The binding process triggers STING to traffic from the ER to the Golgi apparatus, where it is phosphorylated by the kinase TBK1. Phosphorylated STING serves as a docking site for the transcription factor IRF3, facilitating its phosphorylation by TBK1. Once phosphorylated, IRF3 forms dimers and translocates to the nucleus, where it drives the expression of type I interferons and pro-inflammatory cytokines, initiating a potent antimicrobial state. The DNA-sensing mechanism of cGAS is inherently non-selective regarding the origin of its ligand. It readily detects exogenous DNA from invading pathogens, thereby playing an indispensable role in host defense against microbial infections. However, this same mechanism also enables cGAS to recognize self-DNA that leaks from the nucleus or mitochondria into the cytosol under various cellular stress conditions. While critical for immunity, the recognition of self-dsDNA by cGAS can disrupt cellular homeostasis and trigger aberrant inflammatory responses. The loss of self-tolerance can precipitate or exacerbate the pathogenesis of autoimmune disorders such as systemic lupus erythematosus (SLE) and Aicardi-Goutières syndrome (AGS), highlighting the dual role of cGAS as both a sentinel for infection and a potential driver of autoimmune pathology. Notably, the subcellular localization of cGAS is not still. Increasing recent researches have revealed that cGAS is also abundant within the nucleus, challenging the traditional view of it solely as a cytosolic nucleic acid sensor. Within the nucleus, cGAS exhibits non-canonical functions that are distinct from its canonical immunological role. First, cGAS exists in a state of stringent immunological silence in the nucleus, with mechanisms involving its competitive binding to histones and its post-translational modifications which block the activation of cGAS enzymatic activity, thus, effectively preventing it from mounting an autoimmune attack on genomic DNA. Second, cGAS plays a critical role in maintaining genomic stability. Upon DNA damage, cGAS is rapidly recruited to the lesion site and participates in the DNA damage repair process. Moreover, under conditions of DNA replication stress, cGAS contributes to the stabilization of replication forks, preventing the cell from entering a state of uncontrolled hyper-replication. Consequently, in light of the dual role of cGAS in both immune regulation and tumor development, the development of small-molecule drugs targeting cGAS holds significant therapeutic promise. This review summarizes the structural characteristics of cGAS and its canonical function as a pattern recognition receptor in the cytosol, including the types of pathogens it recognizes and the autoimmune responses resulting from erroneous recognition of self-DNA. It then focuses on its emerging non-canonical functions within the nucleus, detailing its nucleocytoplasmic shuttling, the mechanisms underlying its nuclear immune quiescence, and its role in mediating DNA damage repair and replication fork stabilization. Finally, the review discusses the progress and application prospects of small-molecule drugs targeting cGAS for the treatment of autoimmune diseases and cancer.

Cyclic GMP-AMP synthase (cGAS), a pivotal molecule in innate immunity, has emerged as a keypoint in interdisciplinary research at the intersection of basic immunology and tumor biology. As a cytosolic nucleic acid sensor, cGAS is primarily characterized by its capacity to recognize double-stranded DNA (dsDNA) in the cytosol. Upon binding to dsDNA, cGAS undergoes a conformational change that promotes its dimerization and subsequent enzymatic activation. Once activated, it catalyzes the synthesis of the second messenger 2',3'-cGAMP from ATP and GTP. cGAMP then binds to the adaptor protein STING, which resides on the endoplasmic reticulum (ER) membrane. The binding process triggers STING to traffic from the ER to the Golgi apparatus, where it is phosphorylated by the kinase TBK1. Phosphorylated STING serves as a docking site for the transcription factor IRF3, facilitating its phosphorylation by TBK1. Once phosphorylated, IRF3 forms dimers and translocates to the nucleus, where it drives the expression of type I interferons and pro-inflammatory cytokines, initiating a potent antimicrobial state. The DNA-sensing mechanism of cGAS is inherently non-selective regarding the origin of its ligand. It readily detects exogenous DNA from invading pathogens, thereby playing an indispensable role in host defense against microbial infections. However, this same mechanism also enables cGAS to recognize self-DNA that leaks from the nucleus or mitochondria into the cytosol under various cellular stress conditions. While critical for immunity, the recognition of self-dsDNA by cGAS can disrupt cellular homeostasis and trigger aberrant inflammatory responses. The loss of self-tolerance can precipitate or exacerbate the pathogenesis of autoimmune disorders such as systemic lupus erythematosus (SLE) and Aicardi-Goutières syndrome (AGS), highlighting the dual role of cGAS as both a sentinel for infection and a potential driver of autoimmune pathology. Notably, the subcellular localization of cGAS is not still. Increasing recent researches have revealed that cGAS is also abundant within the nucleus, challenging the traditional view of it solely as a cytosolic nucleic acid sensor. Within the nucleus, cGAS exhibits non-canonical functions that are distinct from its canonical immunological role. First, cGAS exists in a state of stringent immunological silence in the nucleus, with mechanisms involving its competitive binding to histones and its post-translational modifications which block the activation of cGAS enzymatic activity, thus, effectively preventing it from mounting an autoimmune attack on genomic DNA. Second, cGAS plays a critical role in maintaining genomic stability. Upon DNA damage, cGAS is rapidly recruited to the lesion site and participates in the DNA damage repair process. Moreover, under conditions of DNA replication stress, cGAS contributes to the stabilization of replication forks, preventing the cell from entering a state of uncontrolled hyper-replication. Consequently, in light of the dual role of cGAS in both immune regulation and tumor development, the development of small-molecule drugs targeting cGAS holds significant therapeutic promise. This review summarizes the structural characteristics of cGAS and its canonical function as a pattern recognition receptor in the cytosol, including the types of pathogens it recognizes and the autoimmune responses resulting from erroneous recognition of self-DNA. It then focuses on its emerging non-canonical functions within the nucleus, detailing its nucleocytoplasmic shuttling, the mechanisms underlying its nuclear immune quiescence, and its role in mediating DNA damage repair and replication fork stabilization. Finally, the review discusses the progress and application prospects of small-molecule drugs targeting cGAS for the treatment of autoimmune diseases and cancer.

ObjectiveTo explore the association between metabolic score for visceral fat（METS-VF） and cardiometabolic multimorbidity（CMM） as well as cognitive function in the elderly population， revealing the role of METS-VF as an assessment tool in this population， and providing evidence and new perspectives for the early screening and intervention strategies of CMM and cognitive function. MethodsThis study is based on cross-sectional data from the Hubei memory and aging cohort study（HMACS）， which includes elderly individuals aged 60 and above. The METS-VF index was calculated and divided into quartiles（Q1-Q4）. CMM was assessed through a questionnaire， defining CMM as the coexistence of at least two of the following conditions： diabetes， heart disease， and stroke. Standardized cognitive tests were used to evaluate overall cognition， memory， language， executive function， and attention. Logistic and Linear regression analysis was performed to explore the association between METS-VF and the risk of CMM as well as cognitive function. A restricted cubic spline was used to test the dose-response relationship， and subgroup analysis was conducted to assess the variation of METS-VF in different populations. Additionally， multinomial unordered logistic regression was used to evaluate the performance of METS-VF in predicting CMM morbidity patterns. ResultsA total of 3 790 elderly participants aged 60 and above were included. After adjusting for confounding factors， compared with the lowest quartile（Q1）， the Q4 group of METS-VF was associated with a higher risk of CMM ［OR=3.00，95%CI （2.18， 4.16）］， and with lower scores in overall cognition ［b=-0.12， 95%CI （-0.21，-0.04）］， attention ［b=-0.14， 95%CI （-0.24，-0.05）］， and executive function ［b=-0.10， 95%CI （-0.20，-0.00）］. Dose-response analysis did not show a nonlinear relationship between METS-VF and either CMM or cognitive function （P for nonlinear > 0.05）. Subgroup analysis revealed that the male group with higher METS-VF had lower overall cognitive scores， while the female group showed lower executive function scores （P for interaction ＜ 0.05 for both）. Multinomial unordered logistic regression analysis indicated that the METS-VF index was associated with an increased risk of diabetes with coronary heart disease ［OR=2.62，95%CI （1.66， 4.15）］ or concomitant stroke ［OR=2.66，95%CI （1.73， 4.09）］， especially in the group with both diabetes and stroke and coronary heart disease， where the association between METS-VF and the risk was strongest. ConclusionsAn increased METS-VF is associated with a higher risk of CMM and lower scores in overall cognition， attention， and executive function in the elderly population. Diabetes may be a key driving factor in the multimorbidity model. The METS-VF index can serve as a dual-purpose tool for screening cardiovascular metabolic risks and assessing cognitive function.

This article reports a 14-year-old boy who presented with "a nearly 7-year history of a right upper arm mass and a more than 1-year history of cervical lymphadenopathy". His main clinical manifestations included a subcutaneous mass in the right upper arm, bilateral eyelid and submandibular masses, and multiple enlarged cervical lymph nodes, accompanied by persistent peripheral blood eosinophilia. Biopsies of the right upper arm lesion and a left submandibular lymph node showed lymphoid hyperplasia with prominent eosinophilic infiltration, vascular and fibrous tissue proliferation, and eosinophilic microabscess formation in the left submandibular lymph node, confirming the diagnosis of Kimura′s disease. The lesions regressed markedly after glucocorticoid therapy but recurred after treatment discontinuation. Because the patient and his family were concerned about long-term glucocorticoid therapy, mepolizumab was subsequently administered. Peripheral eosinophil counts normalized, whereas the local tissue lesions showed limited improvement. A multidisciplinary team comprehensively evaluated the diagnosis, the need for repeat biopsy of atypical lymph nodes on imaging, the possible association between the cardiac valve abnormalities and the underlying disease, and subsequent treatment options. The patient is currently receiving methotrexate with folic acid supplementation and remains under regular follow-up. This case indicates that the diagnosis of Kimura′s disease relies on clinical manifestations and histopathological findings. Once diagnosed, comprehensive evaluation, individualized treatment, and long-term management should be implemented.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.

Objective: The CT/MRI Liver Imaging Reporting and Data System (LI-RADS) demonstrates high specificity with relatively limited sensitivity for diagnosing hepatocellular carcinoma (HCC) in high-risk patients. This study aimed to explore the possibility of improving sensitivity by combining CT/MRI LI-RADS v2018 with second-line contrast-enhanced ultrasound (CEUS) LI-RADS v2017 using sulfur hexafluoride (SHF) or perfluorobutane (PFB). Materials and Methods: This retrospective analysis of prospectively collected multicenter data included high-risk patients with treatment-naive hepatic observations. The reference standard was pathological confirmation or a composite reference standard (only for benign lesions). Each participant underwent concurrent CT/MRI, SHF-enhanced US, and PFB-enhanced US examinations. The diagnostic performances for HCC of CT/MRI LI-RADS alone and three combination strategies (combining CT/ MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or a modified algorithm incorporating the Kupffer-phase findings for PFB [modified PFB]) were evaluated. For the three combination strategies, apart from the CT/MRI LR-5 criteria, HCC was diagnosed if CT/MRI LR-3 or LR-4 observations met the LR-5 criteria using LI-RADS SHF, LI-RADS PFB, or modified PFB. Results: In total, 281 participants (237 males; mean age, 55 ± 11 years) with 306 observations (227 HCCs, 40 non-HCC malignancies, and 39 benign lesions) were included. Using LI-RADS SHF, LI-RADS PFB, and modified PFB, 20, 23, and 31 CT/MRI LR-3/4 observations, respectively, were reclassified as LR-5, and all were pathologically confirmed as HCCs. Compared to CT/MRI LI-RADS alone (74%, 95% confidence interval [CI]: 68%–79%), the three combination strategies combining CT/MRI LI-RADS with either LI-RADS SHF, LI-RADS PFB, or modified PFB increased sensitivity (83% [95% CI: 77%–87%], 84% [95% CI: 79%–89%], 88% [95% CI: 83%–92%], respectively; all P < 0.001), while maintaining the specificity at 92% (95% CI: 84%–97%). Conclusion The combination of CT/MRI LI-RADS with second-line CEUS using SHF or PFB improved the sensitivity of HCC diagnosis without compromising specificity.