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.

BACKGROUND:The formation of postoperative abdominal adhesions is a complicated process,and the prevention of postoperative adhesions is an urgent problem in clinic. OBJECTIVE:To analyze the mechanism of adhesion at cellular and molecular levels,and to provide theoretical basis for the prevention and treatment of adhesion by mesenchymal stem cell exosomes. METHODS:"Abdominal adhesion,pelvic adhesion,postoperative adhesion,epithelial mesenchymal transformation,mesenchymal stem cells,stem cell exosomes,mesenchymal stem cell exosomes"were selected as Chinese and English search terms.We searched PubMed,CNKI,and Chinese biomedical literature and screened relevant articles on postoperative abdominal adhesion and mesenchymal stem cell exosomal intervention published from inception to August 2023.After systematic analysis,54 articles were finally included for the review. RESULTS AND CONCLUSION:(1)Any pathological factors such as peritoneal inflammation,mechanical injury,tissue ischemia,and foreign body implantation cause peritoneal surface injury,resulting in postoperative abdominal adhesion.The formation process of adhesion includes the interaction of peritoneal mesothelial cell repair,inflammatory response,fibrinolytic system,coagulation pathway and other processes,involving a variety of cytokines and signaling pathways.Wnt/β-catenin pathway can induce fibrosis and angiogenesis,and cooperate with transforming growth factor-β/Smads signaling pathway to stimulate fibroblast proliferation and cause peritoneal fibrosis.Meanwhile,nuclear factor-κB signaling pathway up-regulates the expression of cellular inflammatory factors,promotes fibroblast proliferation,and plays a key role in the process of tissue fibrosis.(2)The paracrine function of stem cells is an important direction of molecular intervention in abdominal adhesions based on regenerative medicine.It can participate in a variety of complex cytokines and signaling pathways involved in abdominal adhesions.(3)Compared with traditional methods for treating abdominal adhesions,mesenchymal stem cell exosome has biological activity and is safe to use.Mesenchymal stem cell exosomes without special culture and expansion have lower immunogenicity,longer stability and other advantages,can guide a normal repair and healing through a variety of ways.(4)Mesenchymal stem cell exosome has been proven to be involved in regulating the above processes of adhesion formation in previous studies,showing potential application prospects in clinical studies.However,further clinical studies are needed to explore appropriate treatment options for mesenchymal stem cell exosomes to address the problem of clinical translation.

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

Objective:To investigate the value of MULTI-parametric MR imaging with flexible design (MTP) combined with microview diffusion weighted imaging (DWI) in predicting pituitary tumor invasion of cavernous sinus.Methods:This was a cross-sectional study. The clinicopathological and imaging data of 59 patients with suspected pituitary tumor who were admitted to the First Affiliated Hospital of Dalian Medical University from December 2021 to August 2024 were prospectively analyzed. According to Knosp classification, patients with pituitary tumor were divided into non-invasive group (28 cases) and invasive group (31 cases). All patients underwent MTP and microview DWI sequence scanning, and the corresponding parameter values [T 1, R 2*, T 2* and apparent diffusion coefficient (ADC)] were measured on the MTP quantitative map and ADC map at the maximum diameter level of the pituitary tumor. Independent sample t test and Mann-Whitney U test were used to compare the clinical data, quantitative parameter values and proliferation index (Ki-67) between the non-invasive group and the invasive group. Quantitative parameter values with statistically significant differences were jointly included in logistic regression to construct the model. Receiver characteristic curve and area under the curve (AUC) were used to analyze single variables and logistic model in predicting the value invasion of pituitary tumor cavernous sinus invasion. Spearman correlation was used to analyze the correlation between the quantitative values and Ki-67 level. Results:There was no significant difference in age and gender between the non-invasive group and the invasive group ( P>0.05). T 1 and T 2* values in invasion group were higher than those in non-invasion group ( Z=4.42, P<0.001; Z=3.43, P<0.001), R 2* values and ADC values in the invasion group were lower than those in the non-invasion group, and the difference was statistically significant (t=4.07, P<0.001; Z=-3.07, P=0.002). The AUC values of T 1, R 2*, T 2*, ADC, logistic model 1(T 1+R 2*+ADC) and logistic model 2(T 1+T 2*+ADC) for predicting pituitary tumor cavernous sinus invasion were 0.835, 0.767, 0.760, 0.733, 0.926 and 0.925, respectively. Correlation analysis showed that the value of pituitary tumor T 1 was positively correlated with Ki-67 ( r=0.431, P=0.002). Conclusion:Quantitative parameters of MTP sequence and microview DWI sequence can quantitatively evaluate pituitary tumor invasion of cavernous sinus, and the combination of the two sequences can significantly improve the prediction efficiency.

Neuropathic pain(NP)is a type of chronic pain caused by damage or disease of the nervous system.It is mainly characterized by spontaneous pain,hyperalgesia,and allodynia,which seriously af-fect the quality of life of patients.The pathogenesis of NP is complex,involving abnormal regulation such as peripheral sensitization,central sensitization,ion channel changes,and glial cell activation.In recent years,the role of m6A in NP has attracted extensive attention.However,the research on the role of m6A modification in different diseases and pain models is still limited.Therefore,it is particularly important to clarify the role of m6A modification in different diseases and pain models.This article reviews the re-search progress on the role and mechanism of m6A methylation modification in the pathogenesis of NP in recent years,especially the role mechanism of the five classical m6A modification factors,METTL3,METTL14,FTO,ALKBH5 and YTHDF1,in mediating the formation of NP in different diseases and pain models,with the expectation of providing new insights and ideas for the drug development and pre-vention of NP from the perspective of m6A modification.

Objective:To evaluate the feasibility of a six-step suspension technique for endoscopic lateral neck dissection (LND) through the chest-breast approach in patients with papillary thyroid carcinoma (PTC).Methods:This is a retrospective case series study.Clinical data of 81 PTC patients who underwent endoscopic LND via the chest-breast approach using the six-step suspension method at the Department of Thyroid Surgery, Shenzhen People′s Hospital were collected from January 2022 to October 2024. The cohort consisted of 15 male and 66 female patients, with age of (35.2±10.2)years (range:8.5 to 65.0 years). Key variables, including LND duration, total operative time, postoperative hospital stay, details of lymph node metastasis, postoperative complications, and follow-up data were recorded and analyzed.Results:The duration of LND was (131.8±42.2)minutes (range: 65 to 275 minutes), and the total operative time was (195.5±49.6)minutes (range: 110 to 390 minutes). The postoperative hospital stay was (4.8±1.5)days(range:3 to 15 days). The number of dissected lateral cervical lymph nodes was 32.7±10.1 (range: 11 to 54). The maximum tumor diameter was (16.1±10.1)mm(range:2 to 30 mm), while the maximum size of metastatic lymph nodes was (16.7±6.2)mm(range:7 to 30 mm). The positivity rate was 24.7% (841/3 410) in the lateral cervical+central lymph node and 16.1% (427/2 646) in the lateral cervical lymph node. Postoperative lymphatic leakage occurred in 2 patients, both of whom were successfully treated conservatively. No other significant complications were reported. During the postoperative follow-up period, which lasted for (18.3±7.4) months (range: 1.1 to 34.4 months), the mean postoperative serum thyroglobulin (Tg) level ( M(IQR)) was 0.05 (0.50) μg/L (range: 0.01 to 7.90 μg/L), with 86.4% of patients showing a Tg ≤1.00 μg/L. Through imaging evaluations, no evidence of residual disease or recurrence was detected. Conclusion:Endoscopic LND via the chest-breast approach, utilizing the six-step suspension method, maybe a feasible and effective technique with promising clinical outcomes.

Objective:To analyze the prognostic value of systemic inflammatory score (SIS) in patients with unresectable stage Ⅲ non-small cell lung cancer (NSCLC) treated by definitive chemoradiotherapy (dCRT) combined with or without consolidation immunotherapy with immune checkpoint inhibitor (ICI).Methods:The medical record data of 229 patients who received dCRT from January 2014 to December 2017 and 183 patients who received dCRT combined with any form of ICI (induction, concurrent, consolidation or combination) from August 2018 to August 2022 in the Cancer Hospital, Chinese Academy of Medical Sciences were retrospectively analyzed. Upon admission, 1 and 3 months after treatment (efficacy evaluation) and upon tumor recurrence, peripheral blood count was collected, and neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and SIS were calculated, respectively. The SIS before, 1 and 3 months after treatment was defined as SIS 0, SIS 1 and SIS 3, respectively. Overall survival (OS) was considered as the primary endpoint. All patients were divided into dCRT group and dCRT+ICI group according to whether received immunotherapy, and then divided into different subgroups based on the cutoff value of SIS determined by X-Tile software. The prognostic value of SIS was evaluated by Kaplan-Meier survival analysis. The area under the receiver operating characteristic (ROC) curve (AUC) was used to evaluate the predictive efficiency. The predictive value of SIS was compared with inflammatory indexes (NLR, PLR) and independent prognostic factors. Results:In the dCRT group, the optimal cutoff value of SIS 0 was 590×10 9 and 530×10 9 in the dCRT+ICIs group. Univariate and multivariate analyses indicated that SIS 0 was an independent predictive factor of OS, progression - free survival (PFS), local - recurrence free survival (LRFS) and distant metastasis free survival (DMFS) in the dCRT group, but not associated with DMFS in the dCRT+ICI group. In the dCRT group, SIS 1>970×10 9 (optimal cutoff value) predicted poor OS ( HR=2.512, 95% CI=1.622-3.198, P<0.001), PFS ( HR=1.726, 95% CI=1.187-2.509, P=0.004), and DMFS ( HR=1.625, 95% CI=1.029-2.564, P=0.037). In the dCRT+ICI group, SIS 3>1570×10 9 (optimal cutoff value) indicated poor OS ( HR=5.107, 95% CI=1.731-15.069, P=0.003). In both groups, the AUC of SIS was higher than NLR, PLR and other traditional clinicopathological predictive indexes except T stage. Conclusions:SIS before treatment can be considered as an independent, dependable and easily acquired prognostic marker in patients with unresectable stage Ⅲ NSCLC treated by dCRT or dCRT+ICI. In the dCRT+ICI group, the optimal time point of post-radiotherapy SIS (3 months after treatment) is postponed than that (1 month after treatment) in the dCRT group.

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