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.

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.

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.

BACKGROUND: Hypertension is associated with an increased risk of calcific aortic valve stenosis (CAVS). However, the directionality of causation between blood pressure traits and aortic stenosis is unclear, as is the benefit of antihypertensive drugs for CAVS. METHODS: Using genome-wide association studies (GWAS) summary statistics, we performed bidirectional two-sample univariable mendelian randomization (UVMR) to assess the causal associations of systolic blood pressure (SBP), diastolic blood pressure (DBP), and pulse pressure (PP) with CAVS. Multivariable mendelian randomization (MVMR) was conducted to evaluate the direct effect of hypertension on CAVS, adjusting for confounders. Drug target mendelian randomization (MR) and summary-level MR (SMR) were used to estimate the effects of 12 classes of antihypertensive drugs and their target genes on CAVS risk. Inverse variance weighting was the primary MR method, with sensitivity analyses to validate results. RESULTS: UVMR showed SBP, DBP, and PP have causal effects on CAVS, with no significant reverse causality. MVMR confirmed the causality between hypertension and CAVS after adjusting for confounders. Drug-target MR analyses indicated that calcium channel blockers (CCBs), loop diuretics, and thiazide diuretics via SBP lowering exerted protective effects on CAVS risk. SMR analysis showed that the CCBs target gene CACNA2D2 and ARBs target gene AGTR1 were positively associated with CAVS risk, while diuretics target genes SLC12A5 and SLC12A1 were negatively associated with aortic stenosis risk. CONCLUSIONS Hypertension has a causal relationship with CAVS. Managing SBP in hypertensive patients with CCBs may prevent CAVS. ARBs might exert protective effects on CAVS independent of blood pressure reduction. The relationship between diuretics and CAVS is complex, with opposite effects through different mechanisms.

BACKGROUND: Quantitative flow ratio (QFR) holds significant value in guiding drug-coated balloon (DCB) treatment and enhancing outcomes. However, the predictive capability of post-angioplasty QFR for long-term clinical events in patients with de novo lesions who receive DCB treatment remains uncertain. The aim of this study was to explore the potential significance of post-angioplasty QFR measurements in predicting clinical outcomes in patients underwent DCB treatment for de novo lesions. METHODS: Patients who underwent DCB-only intervention for de novo lesions were enrolled. QFR was conducted after DCB treatment. The patients were then categorized based on post-angioplasty QFR. The primary endpoint was major adverse cardiac events (MACE), encompassing all-cause death, cardiovascular death, nonfatal myocardial infarction, stroke, and target vessel revascularization. RESULTS: A total of 553 patients with 561 lesions were included. The median follow-up period was 505 days, during which 66 (11.8%) MACEs occurred. Based on post-procedural QFR grouping, there were 259 cases in the high QFR group (QFR > 0.93) and 302 cases in the low QFR group (QFR ≤ 0.93). Kaplan-Meier analysis revealed a significantly higher cumulative incidence of MACE in the low QFR group (log-rank P = 0.004). The multivariate Cox proportional hazards model demonstrated a significant inverse correlation between QFR and the occurrence of MACEs (HR = 0.522, 95%CI: 0.289-0.942, P = 0.031). Landmark analysis indicated that high QFR had a significant reducing effect on the cumulative incidence of MACEs within 1 year (log-rank P = 0.016) and 1-5 years (log-rank P = 0.026). CONCLUSIONS In patients who underwent DCB-only treatment for de novo lesions, higher post-procedural QFR values (> 0.93) were identified as an independent protective factor against adverse prognosis.

OBJECTIVE: To evaluate the effect and safety of Chinese medicine (CM) Fuzheng Huazhuo Decoction (FHD) in treating patients with coronavirus disease 2019 (COVID-19) who persistently tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS: This retrospective cohort study was conducted at Shanghai New International Expo Center shelter hospital in China between April 1 and May 30, 2022. Patients diagnosed as COVID-19 with persistently positive SARS-CoV-2 reverse transcription-polymerase chain reaction (RT-PCR) test results for ⩾8 days after diagnosis were enrolled. Patients in the control group received conventional Western medicine (WM) treatment, while those in the FHD group received conventional WM plus FHD for at least 3 days. The primary outcome was viral clearance time. Secondary outcomes included negative conversion rate within 14 days, length of hospital stay, cycle threshold (Ct) values of the open reading frame 1ab (ORF1ab) and nucleocapsid protein (N) genes, and incidence of new-onset symptoms during hospitalization. Adverse events (AEs) that occurred during the study period were recorded. RESULTS: A total of 1,765 eligible patients were enrolled in this study (546 in the FHD group and 1,219 in the control group). Compared with the control group, patients receiving FHD treatment showed shorter viral clearance time for nucleic acids [hazard ratio (HR): 1.500, 95% confidence interval (CI): 1.353-1.664, P<0.001] and hospital stays (HR: 1.371, 95% CI: 1.238-1.519, P<0.001), and a higher negative conversion rate within 14 days (96.2% vs. 82.6%, P<0.001). The incidence of new-onset symptoms was 59.5% in the FHD group, similar to 57.8% in the control group (P>0.05). The Ct values of ORF1ab and N genes increased more rapidly over time in the FHD group than those in the control group post-randomization (ORF1ab gene: β =0.436±0.053, P<0.001; N gene: β =0.415 ±0.053, P<0.001). The incidence of AEs in the FHD group was lower than that in the control group (24.2% vs. 35.4%, P<0.001). No serious AEs were observed. CONCLUSION FHD was effective and safe for patients with persistently positive SARS-CoV-2 PCR tests. (Registration No. ChiCTR2200063956).
Humans ; Drugs, Chinese Herbal/adverse effects* ; Retrospective Studies ; Male ; Female ; Middle Aged ; COVID-19 Drug Treatment ; SARS-CoV-2/drug effects* ; COVID-19/virology* ; Adult ; Aged ; Treatment Outcome