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: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Geraniin, a polyphenol derived from the fruit peel of Nephelium lappaceum L., has been shown to possess anti-inflammatory and antioxidant properties in the cardiovascular system. The present study explored whether geraniin could protect against an isoproterenol (ISO)-induced cardiac hypertrophy model. Mice in the ISO group received an intraperitoneal injection of ISO (5 mg/kg) once daily for 9 days, and the administration group were injected with ISO after 5 days of treatment with geraniin or spironolactone. Potential therapeutic effects and related mechanisms analysed by anatomical coefficients, histopathology, blood biochemical indices, reverse transcription-PCR and immunoblotting. Geraniin decreased the cardiac pathologic remodeling and myocardial fibrosis induced by ISO, as evidenced by the modifications to anatomical coefficients, as well as the reduction in collagen I/III á1mRNA and protein expression and cross-sectional area in hypertrophic cardiac tissue. In addition, geraniin treatment reduced ISO-induced increase in the mRNA and protein expression levels of interleukin (IL)-6, IL-1β and tumor necrosis factor-α, whereas ISO-induced IL-10 showed the opposite behaviour in hypertrophic cardiac tissue.Further analysis showed that geraniin partially reversed the ISO-induced increase in malondialdehyde and nitric oxide, and the ISO-induced decrease in glutathione, superoxide dismutase and glutathione. Furthermore, it suppressed the ISO-induced cellular apoptosis of hypertrophic cardiac tissue, as evidenced by the decrease in Bcell lymphoma-2 (Bcl-2)-associated X/caspase-3/caspase-9 expression, increase in Bcl-2 expression, and decrease in TdT-mediated dUTP nick-end labeling-positive cells.These findings suggest that geraniin can attenuate ISO-induced cardiac hypertrophy by inhibiting inflammation, oxidative stress and cellular apoptosis.

Membrane proteins are integral components of cellular membranes, accounting for approximately 30% of the mammalian proteome and serving as targets for 60% of FDA-approved drugs. They are critical to both physiological functions and disease mechanisms. Their functional protein-protein interactions form the basis for many physiological processes, such as signal transduction, material transport, and cell communication. Membrane protein interactions are characterized by membrane environment dependence, spatial asymmetry, weak interaction strength, high dynamics, and a variety of interaction sites. Therefore, in situ analysis is essential for revealing the structural basis and kinetics of these proteins. This paper introduces currently available in situ analytical techniques for studying membrane protein interactions and evaluates the characteristics of each. These techniques are divided into two categories: label-based techniques (e.g., co-immunoprecipitation, proximity ligation assay, bimolecular fluorescence complementation, resonance energy transfer, and proximity labeling) and label-free techniques (e.g., cryo-electron tomography, in situ cross-linking mass spectrometry, Raman spectroscopy, electron paramagnetic resonance, nuclear magnetic resonance, and structure prediction tools). Each technique is critically assessed in terms of its historical development, strengths, and limitations. Based on the authors’ relevant research, the paper further discusses the key issues and trends in the application of these techniques, providing valuable references for the field of membrane protein research. Label-based techniques rely on molecular tags or antibodies to detect proximity or interactions, offering high specificity and adaptability for dynamic studies. For instance, proximity ligation assay combines the specificity of antibodies with the sensitivity of PCR amplification, while proximity labeling enables spatial mapping of interactomes. Conversely, label-free techniques, such as cryo-electron tomography, provide near-native structural insights, and Raman spectroscopy directly probes molecular interactions without perturbing the membrane environment. Despite advancements, these methods face several universal challenges: (1) indirect detection, relying on proximity or tagged proxies rather than direct interaction measurement; (2) limited capacity for continuous dynamic monitoring in live cells; and (3) potential artificial influences introduced by labeling or sample preparation, which may alter native conformations. Emerging trends emphasize the multimodal integration of complementary techniques to overcome individual limitations. For example, combining in situ cross-linking mass spectrometry with proximity labeling enhances both spatial resolution and interaction coverage, enabling high-throughput subcellular interactome mapping. Similarly, coupling fluorescence resonance energy transfer with nuclear magnetic resonance and artificial intelligence (AI) simulations integrates dynamic structural data, atomic-level details, and predictive modeling for holistic insights. Advances in AI, exemplified by AlphaFold’s ability to predict interaction interfaces, further augment experimental data, accelerating structure-function analyses. Future developments in cryo-electron microscopy, super-resolution imaging, and machine learning are poised to refine spatiotemporal resolution and scalability. In conclusion, in situ analysis of membrane protein interactions remains indispensable for deciphering their roles in health and disease. While current technologies have significantly advanced our understanding, persistent gaps highlight the need for innovative, integrative approaches. By synergizing experimental and computational tools, researchers can achieve multiscale, real-time, and perturbation-free analyses, ultimately unraveling the dynamic complexity of membrane protein networks and driving therapeutic discovery.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Objective: To investigate the association between monocyte to high-density lipoprotein cholesterol ratio (MHR) and periodontitis and to provide new epidemiologic evidence on the factors affecting periodontitis. Methods: Data on MHR, periodontitis, and other covariates were selected from the NHANES(National Health and Nutrition Examination) database for 3 cycles of subjects in 2009-2010, 2011-2012, and 2013-2014, and a total of 8 456 study subjects were included. The study participants were grouped according to the prevalence of periodontitis (presence or absence), and three regression models (unadjusted covariates, partially adjusted covariates, and fully adjusted covariates) were constructed to analyze the relationship between MHR and periodontitis by using a weighted logistic regression method with stepwise adjustment for confounders. MHR was divided into four groups from Q1 to Q4 according to quartiles from small to large for weighted trend analysis, and the nonlinear relationship between MHR (continuous) and periodontitis was analyzed using a restricted cubic spline with subgroup analysis and sensitivity analysis. Results: All three logistic regression models showed a positive association between MHR and periodontitis (OR = 2.92, 95%CI: 2.14-3.99, P<0.001 (not adjusted); OR = 1.97, 95%CI: 1.39-2.78, P<0.001 (partially adjusted); OR = 1.62, 95%CI: 1.10-2.39, P = 0.017 (fully adjusted)). Trend analysis showed a significantly higher risk of developing periodontitis in the Q4 group compared with the Q1 group in both single (OR = 1.92, 95% CI: 1.58-2.33, P<0.001) and multifactorial analyses (OR = 1.30, 95% CI: 1.03-1.64, P = 0.029). Restricted cubic spline results did not support a nonlinear relationship between MHR and periodontitis (P for nonlinear>0.05), subgroup analysis showed no significant interaction between the covariates and MHR (P>0.05), and sensitivity analysis also showed a positive correlation between MHR and periodontitis (OR = 1.67, 95%CI: 1.31-2.14, P<0.001). Conclusion MHR is positively associated with the risk of developing periodontitis.

Geraniin, a polyphenol derived from the fruit peel of Nephelium lappaceum L., has been shown to possess anti-inflammatory and antioxidant properties in the cardiovascular system. The present study explored whether geraniin could protect against an isoproterenol (ISO)-induced cardiac hypertrophy model. Mice in the ISO group received an intraperitoneal injection of ISO (5 mg/kg) once daily for 9 days, and the administration group were injected with ISO after 5 days of treatment with geraniin or spironolactone. Potential therapeutic effects and related mechanisms analysed by anatomical coefficients, histopathology, blood biochemical indices, reverse transcription-PCR and immunoblotting. Geraniin decreased the cardiac pathologic remodeling and myocardial fibrosis induced by ISO, as evidenced by the modifications to anatomical coefficients, as well as the reduction in collagen I/III á1mRNA and protein expression and cross-sectional area in hypertrophic cardiac tissue. In addition, geraniin treatment reduced ISO-induced increase in the mRNA and protein expression levels of interleukin (IL)-6, IL-1β and tumor necrosis factor-α, whereas ISO-induced IL-10 showed the opposite behaviour in hypertrophic cardiac tissue.Further analysis showed that geraniin partially reversed the ISO-induced increase in malondialdehyde and nitric oxide, and the ISO-induced decrease in glutathione, superoxide dismutase and glutathione. Furthermore, it suppressed the ISO-induced cellular apoptosis of hypertrophic cardiac tissue, as evidenced by the decrease in Bcell lymphoma-2 (Bcl-2)-associated X/caspase-3/caspase-9 expression, increase in Bcl-2 expression, and decrease in TdT-mediated dUTP nick-end labeling-positive cells.These findings suggest that geraniin can attenuate ISO-induced cardiac hypertrophy by inhibiting inflammation, oxidative stress and cellular apoptosis.

Geraniin, a polyphenol derived from the fruit peel of Nephelium lappaceum L., has been shown to possess anti-inflammatory and antioxidant properties in the cardiovascular system. The present study explored whether geraniin could protect against an isoproterenol (ISO)-induced cardiac hypertrophy model. Mice in the ISO group received an intraperitoneal injection of ISO (5 mg/kg) once daily for 9 days, and the administration group were injected with ISO after 5 days of treatment with geraniin or spironolactone. Potential therapeutic effects and related mechanisms analysed by anatomical coefficients, histopathology, blood biochemical indices, reverse transcription-PCR and immunoblotting. Geraniin decreased the cardiac pathologic remodeling and myocardial fibrosis induced by ISO, as evidenced by the modifications to anatomical coefficients, as well as the reduction in collagen I/III á1mRNA and protein expression and cross-sectional area in hypertrophic cardiac tissue. In addition, geraniin treatment reduced ISO-induced increase in the mRNA and protein expression levels of interleukin (IL)-6, IL-1β and tumor necrosis factor-α, whereas ISO-induced IL-10 showed the opposite behaviour in hypertrophic cardiac tissue.Further analysis showed that geraniin partially reversed the ISO-induced increase in malondialdehyde and nitric oxide, and the ISO-induced decrease in glutathione, superoxide dismutase and glutathione. Furthermore, it suppressed the ISO-induced cellular apoptosis of hypertrophic cardiac tissue, as evidenced by the decrease in Bcell lymphoma-2 (Bcl-2)-associated X/caspase-3/caspase-9 expression, increase in Bcl-2 expression, and decrease in TdT-mediated dUTP nick-end labeling-positive cells.These findings suggest that geraniin can attenuate ISO-induced cardiac hypertrophy by inhibiting inflammation, oxidative stress and cellular apoptosis.

Geraniin, a polyphenol derived from the fruit peel of Nephelium lappaceum L., has been shown to possess anti-inflammatory and antioxidant properties in the cardiovascular system. The present study explored whether geraniin could protect against an isoproterenol (ISO)-induced cardiac hypertrophy model. Mice in the ISO group received an intraperitoneal injection of ISO (5 mg/kg) once daily for 9 days, and the administration group were injected with ISO after 5 days of treatment with geraniin or spironolactone. Potential therapeutic effects and related mechanisms analysed by anatomical coefficients, histopathology, blood biochemical indices, reverse transcription-PCR and immunoblotting. Geraniin decreased the cardiac pathologic remodeling and myocardial fibrosis induced by ISO, as evidenced by the modifications to anatomical coefficients, as well as the reduction in collagen I/III á1mRNA and protein expression and cross-sectional area in hypertrophic cardiac tissue. In addition, geraniin treatment reduced ISO-induced increase in the mRNA and protein expression levels of interleukin (IL)-6, IL-1β and tumor necrosis factor-α, whereas ISO-induced IL-10 showed the opposite behaviour in hypertrophic cardiac tissue.Further analysis showed that geraniin partially reversed the ISO-induced increase in malondialdehyde and nitric oxide, and the ISO-induced decrease in glutathione, superoxide dismutase and glutathione. Furthermore, it suppressed the ISO-induced cellular apoptosis of hypertrophic cardiac tissue, as evidenced by the decrease in Bcell lymphoma-2 (Bcl-2)-associated X/caspase-3/caspase-9 expression, increase in Bcl-2 expression, and decrease in TdT-mediated dUTP nick-end labeling-positive cells.These findings suggest that geraniin can attenuate ISO-induced cardiac hypertrophy by inhibiting inflammation, oxidative stress and cellular apoptosis.