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.

Lung cancer is a leading cause of cancer-related morbidity and mortality worldwide. Coupled with the substantial workload, the clinical management of lung cancer is challenged by the critical need to efficiently and accurately process increasingly complex medical information. In recent years, large language models (LLMs) technology has undergone explosive development, demonstrating unique advantages in handling complex medical data by leveraging its powerful natural language processing capabilities, and its application value in the field of lung cancer diagnosis and treatment is continuously increasing. The paper systematically analyzes that the exceptional potential of LLMs in lung cancer auxiliary diagnosis, tumor feature extraction, automatic staging, progression/outcome analysis, treatment recommendations, medical documentation generation, and patient education. However, they face critical technical and ethical challenges including inconsistent performance in complex integrated decision-making (e.g., TNM staging, personalized treatment suggestions) and "black box" opacity issues, along with dilemmas such as training data biases, model hallucinations, data privacy concerns, and cross-lingual adaptation challenges ("data colonization"). Future directions should prioritize constructing high-quality multimodal corpora specific to lung cancer, developing interpretable and compliant specialized models, and achieving seamless integration with existing clinical workflows. Through dual drivers of technological innovation and ethical standardization, LLMs should be prudently advanced for holistic lung cancer management processes, ultimately promoting efficient, standardized, and personalized diagnosis and treatment practices.

INTRODUCTION: Comparison of patient health-related quality of life (HRQOL) scores to a reference group is needed to quantify the HRQOL impact of disease or treatment. This study aimed to establish population norms for 2 HRQOL questionnaires-EuroQol 5-dimension 5-level questionnaire (EQ-5D-5L) and European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core Question-naire 30 (EORTC QLQ-C30) according to age, sex and ethnicity-and to explore relationships between the EQ-5D-5L, EORTC QLQ-C30 and sociodemographic characteristics. We used a representative sample of adult Singapore residents aged 21 years and above. METHOD: This study used data collected from a cross-sectional household survey in which 600 adult Singaporeans completed questions on sociodemo-graphic characteristics-the EQ-5D-5L and the EORTC QLQ-C30. Multiple linear regression analyses were conducted to explore associations between sociodemographic characteristics, the EQ-5D-5L scores and the EORTC QLQ-C30 scores. Regression-based population norms were computed for each subgroup using a post-stratification method. RESULTS: In multiple linear regression analysis, age was significantly associated with EQ-5D-5L index and visual analogue scale (VAS) scores, while no sociodemographic characteristics were significantly associated with EORTC QLQ-C30 summary scores. The normative EQ-5D-5L index and VAS scores decreased in adults aged 65 years and above, and EQ-5D-5L index scores were slightly lower in females than males and in non-Chinese than Chinese. The normative EORTC QLQ-C30 summary scores were slightly higher in Chinese than in the non-Chinese group and in the 45-64 age group than other age groups. CONCLUSION This study provides population norms for the EQ-5D-5L and EORTC QLQ-C30 for the general adult population in Singapore. Future studies of patient populations in Singapore using EQ-5D-5L or QLQ-C30 can use these normative data to interpret the HRQOL data collected.
Humans ; Quality of Life ; Singapore ; Male ; Female ; Middle Aged ; Adult ; Cross-Sectional Studies ; Aged ; Surveys and Questionnaires ; Young Adult ; Health Status ; Age Factors ; Linear Models ; Aged, 80 and over

AIM To investigate the protective effects and mechanisms of aqueous extract of Cimicifugae Rhizoma on intestinal mucosa in a mouse model of ulcerative colitis(UC).METHODS The UC mouse models established by sodium dextran sulfate were allocated into different groups and administered with sulfasalazine(200 mg/kg)or aqueous extract of Cimicifugae Rhizoma(3.9,7.8 g/kg)by gavage,respectively.The mice had their changes of body weight,defecation patterns,disease activity index(DAI)and colon length recorded;their colon tissue pathological alterations and goblet cell quantification analyzed through HE and AB-PAS staining;their ROS levels in colon tissue measured via ELISA;their mRNA expressions of inflammatory cytokines,Nrf2/HO-1 signaling pathway components and NLRP3/Caspase-1/GSDMD pathway regulators in colon tissue assessed by RT-qPCR;their protein expressions of Nrf2/HO-1 and NLRP3/Caspase-1/GSDMD pathway verified by immunohistochemistry;and their ZO1 and Occludin tight junction proteins in colon tissues quantified by Western blot analysis.RESULTS Compared to the model group,the high-dose Cimicifugae Rhizoma aqueous extract group demonstrated significantly increased body weight,colon length and DAI scores(P＜0.01);mitigated intestinal mucosal barrier damage;reduced ROS levels in colon tissue(P＜0.01);suppressed mRNA levels of pro-inflammatory factors IL-1β,IL-6 and TNF-α in colon(P＜0.01);elevated expressions of tight junction protein ZO1 and Occludin in colon tissue(P＜0.05);upregulated mRNA and protein expressions of Nrf2,NQO1 and HO-1 in colon tissue(P＜0.05,P＜0.01);downregulated mRNA and protein expressions of Keap1(P＜0.05);and reduced expressions of NLRP3 inflammasome components(ASC,Caspase-1,GSDMD)in mRNA and protein(P＜0.05,P＜0.01).CONCLUSION The aqueous extract of Cimicifugae Rhizoma exerts protective effects against UC through dual mechanisms involving redox regulation and pyroptosis inhibition by reducing ROS level via Nrf2/HO-1 pathway activation and attenuating NLRP3-mediated pyroptosis via Caspase-1/GSDMD pathway inhibition,and thereby synergistically preserves the structural and functional integrity of intestinal mucosal barrier and mitigates UC progression.

Objective To observe the value of Node-RADS based on dynamic contrast-enhanced MRI(DCE-MRI)for assessing axillary lymph node metastasis of breast cancer.Methods A total of 308 patients with breast cancer were retrospectively enrolled and divided into metastasis group(n=153)and non-metastasis group(n=155)based on the presence of axillary lymph node metastasis or not.Two radiologists independently scored the axillary lymph nodes shown on DCE-MRI according to Node-RADS criteria.Inter-observer scores was assessed using Kappa test.Taken pathological result as the gold standard,receiver operating characteristic curves were plotted,and the area under the curve(AUC)was calculated to evaluate the efficacy of Node-RADS scores for diagnosing axillary lymph node metastasis.Results Good inter-observer consistency of Node-RADS scores was observed.When Node-RADS score＞2,the highest AUC of 2 radiologists was 0.928 and 0.921,respectively,being not significantly different(P＞0.05).Conclusion Node-RADS based on DCE-MRI had good efficacy for evaluating axillary lymph node metastasis of breast cancer.Node-RADS score higher than 2 strongly indicated possibility of lymph node metastasis.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Objective:To compare the efficacy and safety of continuous venetoclax combined azacitidine (VA) chemotherapy and intermedium/high-dose cytarabine (I/HDAC) consolidation in patients with acute myeloid leukemia (AML) fit for standard chemotherapy (transform from UNFIT) .Methods:Clinical data of patients who were fit for standard chemotherapy were collected among those with AML who underwent VA induction in the Department of Hematology, the Second Hospital of Hebei Medical University. The overall survival (OS), relapse-free survival (RFS), event-free survival (EFS), and incidence of adverse events were analyzed retrospectively.Results:This study enrolled 69 patients, consisting of 46 cases in the VA group and 23 cases in the I/HDAC group. We revealed the following. ① The median OS, RFS, EFS were 26.18, 24.69, 20.34 months in the VA group, and 34.14, 30.99, 28.42 months in the I/HDAC group, respectively, with no statistically significant difference (all P>0.05). Median OS of patients who underwent I/HDAC consolidation with European Leukemia Net (ELN) favorable-risk, positive measurable residual disease (MRD), wild type FLT3, or IDH1/2 mutation was significantly longer than those who received VA ( P<0.05). ②Adverse events rate of grade 3 - 4 neutropenia, grade 3 - 4 thrombocytopenia, and bacteremia were significantly lower in the VA group than in the I/HDAC group ( P<0.05) . Conclusions:I/HDAC consolidation was more likely to help get survival benefits for patients with ELN favorable-risk, positive MRD, wild type FLT3, or IDH1/2 mutation. Continuous VA chemotherapy exhibited superior safety than I/HDAC consolidation.

Periodontal bone defects, primarily caused by periodontitis, are highly prevalent in clinical settings and manifest as bone fenestration, dehiscence, or attachment loss, presenting a significant challenge to oral health. In regenerative medicine, harnessing developmental principles for tissue repair offers promising therapeutic potential. Of particular interest is the condensation of progenitor cells, an essential event in organogenesis that has inspired clinically effective cell aggregation approaches in dental regeneration. However, the precise cellular coordination mechanisms during condensation and regeneration remain elusive. Here, taking the tooth as a model organ, we employed single-cell RNA sequencing to dissect the cellular composition and heterogeneity of human dental follicle and dental papilla, revealing a distinct Platelet-derived growth factor receptor alpha (PDGFRA) mesenchymal stem/stromal cell (MSC) population with remarkable odontogenic potential. Interestingly, a reciprocal paracrine interaction between PDGFRA⁺ dental follicle stem cells (DFSCs) and CD31⁺ Endomucin⁺ endothelial cells (ECs) was mediated by Vascular endothelial growth factor A (VEGFA) and Platelet-derived growth factor subunit BB (PDGFBB). This crosstalk not only maintains the functionality of PDGFRA⁺ DFSCs but also drives specialized angiogenesis. In vivo periodontal bone regeneration experiments further reveal that communication between PDGFRA⁺ DFSC aggregates and recipient ECs is essential for effective angiogenic-osteogenic coupling and rapid tissue repair. Collectively, our results unravel the importance of MSC-EC crosstalk mediated by the VEGFA and PDGFBB-PDGFRA reciprocal signaling in orchestrating angiogenesis and osteogenesis. These findings not only establish a framework for deciphering and promoting periodontal bone regeneration in potential clinical applications but also offer insights for future therapeutic strategies in dental or broader regenerative medicine.
Receptor, Platelet-Derived Growth Factor alpha/metabolism* ; Humans ; Neovascularization, Physiologic/physiology* ; Dental Sac/cytology* ; Single-Cell Analysis ; Transcriptome ; Mesenchymal Stem Cells/metabolism* ; Bone Regeneration ; Animals ; Dental Papilla/cytology* ; Periodontium/physiology* ; Stem Cells/metabolism* ; Regeneration ; Angiogenesis

General anesthesia is widely used in clinical practice,whereas the exact mechanism behind the general anesthetic-induced reversible loss of consciousness remains unclear.Recent studies have revealed a close relationship between the dopaminergic system and general anesthetic-induced loss of consciousness.This system,encompassing dopamine neurons,dopamine receptors,and related neural pathways,regulates functions such as movement,memory,arousal,and cognition.The dopaminergic neurons in the ventral periaqueductal gray and ventral tegmental area,along with D1 receptors,have been shown to facilitate emergence from anesthesia.However,the role of D2 receptors remains controversial.This review summarizes recent advancements in the role of the dopaminergic system in general anesthesia and the underlying mechanism,with the aim of clarifying the mechanism of general anesthesia and providing a theoretical basis for preventing delayed emergence from anesthesia.
Humans ; Anesthesia, General ; Brain/metabolism* ; Dopaminergic Neurons/physiology* ; Dopamine/physiology* ; Animals