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:In recent years,deep learning technologies have been increasingly applied in the field of oral medicine,enhancing the efficiency and accuracy of oral imaging analysis and promoting the rapid development of intelligent oral medicine. OBJECTIVE:To elaborate the current research status,advantages,and limitations of deep learning based on oral imaging in the diagnosis and treatment decision-making of oral diseases,as well as future prospects,exploring new directions for the transformation of oral medicine under the backdrop of deep learning technology. METHODS:PubMed was searched for literature related to deep learning in oral medical imaging published from January 2017 to January 2024 with the search terms"deep learning,artificial intelligence,stomatology,oral medical imaging."According to the inclusion criteria,80 papers were finally included for review. RESULTS AND CONCLUSION:(1)Classic deep learning models include artificial neural networks,convolutional neural networks,recurrent neural networks,and generative adversarial networks.Scholars have used these models in competitive or cooperative forms to achieve more efficient interpretation of oral medical images.(2)In the field of oral medicine,the diagnosis of diseases and the formulation of treatment plans largely depend on the interpretation of medical imaging data.Deep learning technology,with its strong image processing capabilities,aids in the diagnosis of diseases such as dental caries,periapical periodontitis,vertical root fractures,periodontal disease,and jaw cysts,as well as preoperative assessments for procedures such as third molar extraction and cervical lymph node dissection,helping clinicians improve the accuracy and efficiency of decision-making.(3)Although deep learning is promising as an important auxiliary tool for the diagnosis and treatment of oral diseases,it still has certain limitations in model technology,safety ethics,and legal regulation.Future research should focus on demonstrating the scalability,robustness,and clinical practicality of deep learning,and finding the best way to integrate automated deep learning decision support systems into routine clinical workflows.

OBJECTIVE To study the efficacy of Tianjiang xueshuantong pills in the treatment of coronary heart disease. METHODS In accordance with the common pathogenesis of coronary heart disease， acute myocardial ischemia model， hyperlipidemia model， blood stasis model， and carotid artery thrombosis model were established using Wistar rats or SD rats as the experimental subjects. The effects of Tianjiang xueshuantong pills administered at high， medium， and low doses （0.6， 1.2 and 2.4 g/kg） on hemodynamic parameters and myocardial enzyme markers [lactate dehydrogenase （LDH）， creatine kinase-MB （CK- MB）]， oxidative stress factors [superoxide dismutase （SOD）， malondialdehyde （MDA）， glutathione （GSH）]， inflammatory cytokines [tumor necrosis factor-α （TNF-α）， interleukin-6 （IL-6）， IL-1β， monocyte chemotactic protein-1 （MCP-1）， intercellular adhesion molecule-1 （ICAM-1）]， myocardial infarction percentage， serum lipid indexes [total cholesterol （TC）， triglycerides （TG）， low-density lipoprotein （LDL）， high-density lipoprotein （HDL）]， platelet aggregation function 话：022-84845240。E-mail：jiangx@tjipr.com [maximum aggregation rate （MAR）]， and thrombus formation indexes [thrombosis time， thrombus mass， thrombus protein content， plasminogen activator inhibitor-1 （PAI-1）， and tissue-type plasminogen activator （t-PA）] were evaluated in the rat models. RESULTS In myocardial ischemia tests， Tianjiang xueshuantong pills significantly reduced the percentage of myocardial infarction and the levels of CK-MB， LDH， MDA， GSH， IL-6， TNF-α， IL- 1β， and MCP-1 in serum （P＜0.05 or P＜0.01）. In hyperlipidemia tests， high dose of Tianjiang xueshuantong pills significantly reduced the serum levels of TC， LDL and significantly increased the level of HDL in rats after 2 weeks and 4 weeks of administration. In blood stasis tests， different doses of Tianjiang xueshuantong pills significantly reduced MAR of rats （P＜0.01）. In artery thrombosis tests， high dose of Tianjiang xueshuantong pills significantly prolonged the time of thrombosis formation （P＜ 0.01）， significantly reduced the weight and protein content of thrombus and the level of PAI-1 in serum （P＜0.01）. CONCLUSIONS Tianjiang xueshuantong pills exert therapeutic effects on coronary heart disease through multi-dimensional synergistic actions， including anti-myocardial ischemia， lipid-lowering， and anti-thrombotic effects.

Systemic lupus erythematosus (SLE) is an autoimmune disease of unknown etiology, primarily characterized by systemic inflammation and hyperactivation of both B and T lymphocytes. Key immunological features include increased consumption of complement components, sustained overproduction of type I interferons (IFN-I), and persistent production of a broad spectrum of autoantibodies, such as anti-dsDNA antibodies. However, the use of autoantibodies as biomarkers for the early detection of SLE is associated with a high false-positive rate, suggesting that antibody characteristics evolve during disease progression.N-glycosylation is a critical post-translational modification of antibodies that significantly influences their structure and receptor-binding properties, thereby modulating biological activities and functions. In particular, glycosylation patterns affect the antibody’s affinity for Fc gamma receptors (FcγRs), subsequently regulating various antibody-mediated immune responses. Numerous studies have investigated the impact of individual monosaccharides—such as sialic acid, fucose, and N-acetylglucosamine, which constitute N-glycans—on the immunological functions of antibodies. This review systematically summarizes the aberrant immunoglobulin G (IgG) N-glycosylation patterns observed in SLE patients, with a focus on correlations between disease progression or complications and quantitative alterations in individual glycan components. We first review how different types of N-glycosylation modifications affect the biological activity and functional properties of IgG, particularly regarding the effects of specific monosaccharides—such as sialic acid, fucose, and galactose—on FcγR binding affinity and the resulting downstream immune functions. We then summarize the differential expression of IgGN-glycans and glycosyltransferase genes between SLE patients and healthy controls, and outline the associations between glycosylation changes and SLE-related pathological responses. In response to the inconsistencies and limitations in current research, we propose potential explanations from the perspectives of study methodologies, participant characteristics, and variations in N-glycan structures, aiming to provide a constructive reference for future studies. Given the close relationship between antibody glycosylation and SLE, this review highlights the potential of IgG N-glycosylation patterns as promising biomarkers for early diagnosis and disease monitoring. In terms of therapy, we discuss how IgG glycosylation can enhance the efficacy of intravenous immunoglobulin (IVIg) treatment and introduce emerging therapeutic strategies that aim to modulate endogenous IgG N-glycans as a novel glycan-based approach for SLE management. In summary, N-glycans are essential structural components of antibodies that regulate immune responses by modulating antibody-receptor interactions. Aberrant glycosylation is closely associated with the pathogenesis of autoimmune diseases, including SLE. However, due to the structural diversity of N-glycans and the complexity of glycosylation processes, the precise roles of IgGN-glycosylation in SLE pathophysiology remain incompletely understood. Moreover, therapeutic strategies targeting IgG glycosylation are still in early development and have not yet reached clinical application. Continued progress in glycan analysis technologies and other biological tools, along with interdisciplinary collaboration, will be essential for advancing this field.

Objective: To investigate the status of drug resistance before anti-retroviral therapy among newly dignosed HIV/AIDS patients aged ≥50 years in Yangzhou City, Jiangsu Province, so as to provide the evidence for improving the anti-retroviral therapy effect of AIDS. Methods: HIV/AIDS patients aged ≥50 years who were newly dignosed in Yangzhou City from 2021 to 2024 and did not receive anti-retroviral therapy were selected. Basic information were collected through the Chinese Disease Prevention and Control Information System. Blood samples were collected to determine CD4+T lymphocyte (CD4 cell) counts and HIV-1 viral load. Following nucleic acid extraction, the pol gene region was amplified using reverse transcription and nested PCR, and subsequently subjected to Sanger sequencing. The resulting sequences were uploaded to the Stanford University HIV Drug Resistance Database to analyze drug resistance to non-nucleoside reverse transcriptase inhibitors (NNRTIs), protease inhibitors (PIs), and nucleoside reverse transcriptase inhibitors (NRTIs). Results: Totally 404 blood samples from HIV/AIDS patients were collected, with successful sequencing of the pol gene region in 341 cases. Among them, 253 (74.19%) were males and 88 (25.81%) were females, with a mean age of (62.48±7.60) years. A total of 152 cases (44.57%) had CD4 cell counts below 200 cells/μL, and 296 cases (86.80%) had HIV-1 viral loads exceeding 5 000 copies/mL. A total of 87 cases exhibited drug resistance-associated mutations, corresponding to a mutation rate of 25.51%. The predominant mutation site was V179, with a mutation rate of 17.01%. A total of 29 cases exhibited resistance to at least one drug, resulting in a resistance rate of 8.50%. The resistance rates to NNRTIs, PIs, and NRTIs were 5.57%, 2.93%, and 1.17%, respectively. The HIV/AIDS patients exhibited varying degrees of resistance to 13 anti-retroviral drugs, with low- or intermediate-level drug resistance being predominant. High-level drug resistance cases were observed against NNRTIs such as nevirapine and efavirenz. Conclusions The drug resistance rate before anti-retroviral therapy among newly dignosed HIV/AIDS patients aged ≥50 years in Yangzhou City was at a moderate level. The predominant resistance mutation was observed at V179 site, with NNRTIs resistance being most prevalent, primarily demonstrating low- or intermediate-level drug resistance.

Objective: To investigate the Alzheimer's disease (AD) influencing factors among the elderly, so as to provide a basis for early prevention and intervention. Methods: From March to June 2024, participants aged 60 years and above from a sub-district in Haishu District, Ningbo City, Zhejiang Province were selected using a convenience sampling method. Data on demographics, lifestyle, and health status were collected through questionnaire surveys. Depressive symptoms were evaluated using the short-form Geriatric Depression Scale. The Chinese Mini-Mental State Examination (MMSE) was used for the initial screening of AD, and individuals who screened positive were further diagnosed by psychiatrists. Factors affecting AD among the elderly were analyzed using a multivariable logistic regression model. Results: A total of 3 644 individuals were surveyed, comprising 1 526 males (41.88%) and 2 118 females (58.12%). The mean age was (71.85±7.44) years. AD was detected in 200 cases, with a detection rate of 5.49%. Multivariable logistic regression analysis showed that individuals aged ≥65 years (65-<70 years, OR=3.012, 95%CI: 1.007-9.012; 70-<75 years, OR=3.131, 95%CI: 1.059-9.260; 75-<80 years, OR=5.779, 95%CI: 1.989-16.784; ≥80 years, OR=16.810, 95%CI: 5.926-47.685), those who were unmarried, divorced, or widowed (OR=1.973, 95%CI: 1.383-2.815), those with hearing loss (OR=1.573, 95%CI: 1.128-2.193), those with diabetes mellitus (OR=1.958, 95%CI: 1.362-2.814), and those with depressive symptoms (OR=4.143, 95%CI: 2.997-5.728) had a higher risk of AD. Conversely, individuals with an educational level of primary school or above (primary school, OR=0.579, 95%CI: 0.401-0.835; junior high school or above, OR=0.438, 95%CI: 0.259-0.741), and those who engaged in regular physical exercise (OR=0.414, 95%CI: 0.264-0.649) had a lower risk of AD. Conclusions The detection rate of AD was relatively high among the elderly in Haishu District. AD among the elderly was related to age, educational level, marital status, physical exercise, hearing loss, diabetes mellitus, and depressive symptoms.

This study aims to comprehensively analyze the material basis of toad visceral oil(hereafter referred to as toad oil), and explore the pharmacological effect of toad oil on atopic dermatitis(AD). Ultra-high performance liquid chromatography-linear ion trap/orbitrap high-resolution mass spectrometry(UHPLC-LTQ-Orbitrap-MS) and gas chromatography-mass spectrometry(GC-MS) were employed to comprehensively identify the chemical components in toad oil. The animal model of AD was prepared by the hapten stimulation method. The modeled animals were respectively administrated with positive drug(0.1% hydrocortisone butyrate cream) and low-and high-doses(1%, 10%) of toad oil by gavage. The effect of toad oil on AD was evaluated with the AD score, ear swelling rate, spleen index, and pathological section results as indicators. A total of 99 components were identified by UHPLC-LTQ-Orbitrap-MS, including 14 bufadienolides, 7 fatty acids, 6 alkaloids, 10 ketones, 18 amides, and other compounds. After methylation of toad oil samples, a total of 20 compounds were identified by GC-MS. Compared with the model group, the low-and high-dose toad oil groups showed declined AD score, ear swelling rate, and spleen index, alleviated skin lesions, and reduced infiltrating mast cells. This study comprehensively analyzes the chemical composition and clarifies the material basis of toad oil. Meanwhile, this study proves that toad oil has a good therapeutic effect on AD and is a reserve resource of traditional Chinese medicine for external use in the treatment of AD.
Animals ; Dermatitis, Atopic/immunology* ; Disease Models, Animal ; Mice ; Male ; Gas Chromatography-Mass Spectrometry ; Humans ; Bufonidae ; Oils/administration & dosage* ; Chromatography, High Pressure Liquid ; Female ; Mice, Inbred BALB C

Colorectal cancer(CRC) is one of the most common malignant tumors worldwide, primarily originating from recurrent inflammatory bowel disease(IBD). Therefore, blocking the inflammation-cancer transformation in the colon has become a focus in the early prevention and treatment of CRC. The inflammation-cancer transformation in the colon involves multiple types of cells and complex pathological processes, including inflammatory responses and tumorigenesis. In this complex pathological process, immune cells(including non-specific and specific immune cells) and non-immune cells(such as tumor cells and fibroblasts) interact with each other, collectively promoting the progression of the disease. In traditional Chinese medicine(TCM), inflammation-cancer transformation in the colon belongs to the categories of dysentery and diarrhea, with the main pathogenesis being cold and heat in complexity. This paper first elaborates on the complex molecular mechanisms involved in the inflammation-cancer transformation process in the colon from the perspectives of inflammation, cancer, and their mutual influences. Subsequently, by comparing the pathogenic characteristics and clinical manifestations between inflammation-cancer transformation and the TCM pathogenesis of cold and heat in complexity, this paper explores the intrinsic connections between the two. Furthermore, based on the correlation between inflammation-cancer transformation in the colon and the TCM pathogenesis, this paper delves into the importance of the interaction between inflammation and cancer. Finally, it summarizes and discusses the clinical and basic research progress in the TCM intervention in the inflammation-cancer transformation process, providing a theoretical basis and treatment strategy for the treatment of CRC with integrated traditional Chinese and Western medicine.
Humans ; Colon/pathology* ; Integrative Medicine ; Animals ; Cold Temperature ; Cell Transformation, Neoplastic/drug effects* ; Medicine, Chinese Traditional ; Hot Temperature ; Inflammation ; Drugs, Chinese Herbal/therapeutic use* ; Colonic Neoplasms/drug therapy*

Objective To evaluate the clinical efficacy of a novel sleep-aid decoction in treating elderly insomnia patients with different traditional Chinese medicine (TCM) constitutional types, and its effects on neurotransmitter and inflammatory factor levels. Methods A total of 200 patients with four different TCM constitutions-peaceful, Qi-deficient, Yin-deficient, and Yang-deficient-were recruited. Peripheral blood neurotransmitter and inflammatory factor levels were measured for variations among insomnia patients across different constitutions. These patients were treated using the novel sleep-aid decoction, the effects of which were evaluated based on changes in neurotransmitters and inflammatory factors. Results Compared to the peaceful constitution group, insomnia patients with Qi-deficient, Yin-deficient, and Yang-deficient constitutions exhibited significantly elevated baseline levels of neurotransmitters (5-HT, GABA) and inflammatory factors (IL-6, TNF-α, IL-1β, CRP). Following the treatment, the Qi-deficient and Yin-deficient groups showed a marked increase in 5-HT levels, restored balance of Glu, GABA, and melatonin, and significant reductions in IL-6 and TNF-α levels. The overall effective rate was 83.5%, with optimal efficacy observed in the Qi-deficient (97.72%) and Yin-deficient (95.34%) groups. Conclusion The novel sleep-aid decoction is effective in treating insomnia in elderly patients, with the best results observed in the Qi-deficient and Yin-deficient constitution groups.
Humans ; Sleep Initiation and Maintenance Disorders/blood* ; Aged ; Male ; Female ; Drugs, Chinese Herbal/therapeutic use* ; Medicine, Chinese Traditional ; Middle Aged ; Tumor Necrosis Factor-alpha/blood* ; Sleep Aids, Pharmaceutical/therapeutic use* ; Anti-Inflammatory Agents/therapeutic use* ; Interleukin-6/blood* ; Interleukin-1beta/blood* ; Neurotransmitter Agents/blood* ; Aged, 80 and over ; C-Reactive Protein/metabolism*