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:Recent research indicates that disc degeneration is closely related to abnormal stress load,and mechanotransduction proteins play a key role in it. OBJECTIVE:To investigate the role and mechanism of mechanotransduction proteins in the mechanotransduction process induced by abnormal mechanical stimulation in disc degeneration,and to summarize the current treatment strategies targeting mechanotransduction to delay intervertebral disc degeneration. METHODS:Using"intervertebral disc,nucleus pulposus,annulus fibrosus,cartilaginous endplate,cell,mechanics,signal transduction,protein,biomechanics"as Chinese search terms,and"intervertebral disc,nucleus pulposus,annulus fibrosus,cartilaginous endplate,cell,mechanical stimulation,signal transduction,protein,biomechanics"as English search terms,relevant literature in the PubMed and CNKI databases was searched.A total of 88 articles were ultimately included for review. RESULTS AND CONCLUSION:Disc cells can sense external mechanical stimulation through various mechanotransduction proteins and convert it into biological responses within the cells.These transduction proteins mainly include collagen proteins in the extracellular matrix,cell membrane surface receptors(such as integrins and ion channels),and cytoskeleton structural proteins.Their regulation of mechanotransduction processes primarily involves the activation of multiple pathways,such as the PI3K/AKT signaling pathway,nuclear factor-kB signaling pathway,and Ca2+/Calpain2/Caspase3 pathway.Mechanotransduction proteins play a key role in the mechanotransduction of disc cells.Abnormal expression of these proteins or resulting changes in the extracellular matrix environment can disrupt the mechanical balance of disc cells,leading to disc degeneration.In-depth study of the expression and regulatory mechanisms of mechanotransduction proteins in disc cells,and identification of key pathological links and therapeutic targets,is of significant importance for developing treatment strategies for disc degeneration.Current strategies to delay intervertebral disc degeneration by targeting mechanotransduction mainly include regulation of transduction proteins and improvement of the extracellular matrix.However,research in this area is still in its early stages.As research continues,new breakthroughs are expected in the regulation of disc degeneration by mechanotransduction proteins.

Objective: This study aimed to explore the correlation between balance function and core muscle activation in patients with adolescent idiopathic scoliosis (AIS), compared to healthy individuals. Methods: A total of 24 AIS patients and 25 healthy controls were recruited. The limits of stability (LOS) test were conducted to assess balance function, while surface electromyography was used to measure the activity of core muscles, including the internal oblique, external oblique, and multifidus. Diaphragm thickness was measured using ultrasound during different postural tasks. Center of pressure (COP) displacement and trunk inclination distance were also recorded during the LOS test. Results: AIS patients showed significantly greater activation of superficial core muscles, such as the internal and external oblique muscles, compared to the control group (p < 0.05). Diaphragm activation was lower in AIS patients during balance tasks (p < 0.01). Although no significant difference was observed in COP displacement between the groups, trunk inclination was significantly greater in the AIS group during certain tasks (p < 0.05). Conclusion These findings suggest distinct postural control patterns in AIS patients, highlighting the importance of targeted interventions to improve balance and core muscle function in this population.

This paper systematically summarizes the practical experience of the 2025 Dingri earthquake emergency medical rescue in Tibet. It analyzes the requirements for earthquake medical rescue under conditions of high-altitude hypoxia, low temperature, and low air pressure. The paper provides a detailed discussion on the strategic layout of earthquake medical rescue at the national level, local government level, and through social participation. It covers the construction of rescue organizational systems, technical systems, material support systems, and information systems. The importance of building rescue teams is emphasized. In high-altitude and cold conditions, rapid response, scientific decision-making, and multi-party collaboration are identified as key elements to enhance rescue efficiency. By optimizing rescue organizational structures, strengthening the development of new equipment, and promoting telemedicine technologies, the precision and effectiveness of medical rescue can be significantly improved, providing important references for future similar disaster rescues.

OBJECTIVE To analyze the potential adverse drug interactions based on pharmacokinetics （PK-pADIs） of gefitinib， and establish its corresponding prescription review rules. METHODS Outpatient prescriptions of gefitinib combination therapy in our hospital from January 1， 2022 to November 30， 2024 were collected through rational drug software system. PK- pADIs present in the prescriptions were identified based on the Drugs.com® drug interactions database. The specific combination drugs and cases of PK-pADIs were statistically analyzed， and prescription review rules were established according to the severity classification of PK-pADIs. RESULTS & CONCLUSIONS A total of 217 prescriptions of gefitinib combination therapy were enrolled. Among them， 28 prescriptions （12.90%）， involving a total of 28 patients， had 29 cases of PK-pADIs， with respiratory medicine prescriptions （22 prescriptions） being the main type. The combination drugs included proton pump inhibitors （13 cases）， strong cytochrome P450 3A4 （CYP3A4） inhibitors （7 cases）， H2 receptor antagonists （4 cases）， CYP3A4 inducers （3 cases）， and CYP2D6 substrates （2 cases）. The severity classifications for these interactions were severe， moderate， severe， moderate and moderate， respectively. Based on the above severity classification of PK-pADIs， four prescription review rules had been established as follows： when gefitinib was combined with acid-suppressing drugs， it should be subject to “manual review”； when gefitinib was combined with dexamethasone， metoprolol， or strong CYP3A4 inhibitors， an “alert” should be triggered， and the physician should be informed via an alert box to strengthen the monitoring of relevant indicators. Clinical pharmacists need to conduct in-depth training on knowledge related to gefitinib drug interactions in key clinical departments such as respiratory medicine. They should strengthen the monitoring and guidance of rational drug use for patients who are on long-term gefitinib therapy， and promptly identify and intervene in PK-pADIs， thereby enhancing the rationality， safety， and effectiveness of clinical drug use.

Objective: To explore the changes of mechanosensitive channels Piezos (Piezo 1 and Piezo 2) in neurogenic bladder (NB) of young rats and their effects，so as to provide reference for clinical search of new therapeutic targets. Methods: A total of 30 female young SD rats were divided into 5 groups based on random number table method：sham operation group (sham)，2-week nerve transection group (NB-2W)，6-week nerve transection group (NB-6W)，2-week nerve transection + Piezos inhibitor group (NB-P-2W) and 6-week nerve transection + Piezos inhibitor group (NB-P-6W)，with 6 rats in each group.The NB models were constructed by transecting the L6 and S1 spinal nerves of young rats.The NB-2W and NB-6W groups were not intervened after modeling，while the NB-P-2W and NB-P-6W groups were intraperitoneally injected with Piezos inhibitor GsMTx4 (10 mg/kg) every 2 days after modeling.Bladder cystometry and ultrasound were performed after 2 and 6 weeks of transection.The expressions of Piezos and fibrosis-related indexes (Collagen Ⅰ and α-smooth muscle actin) were detected in bladder tissues. Results: The results of bladder cystometry showed that the basal bladder pressure in NB-2W group was significantly increased，while it was slightly decreased but was still higher in NB-6W group than in the sham group (P<0.05).Basal bladder pressure was lower in NB-P-2W group than in NB-2W group，but was higher than that in the sham group; basal bladder pressure was lower in NB-P-6W group than in NB-6W group，but higher than that in the sham group (P<0.05).Compared with the sham group，the NB-2W and NB-6W groups had firstly increased and then decreased maximum cystometric capacity (MCC) (P<0.05).Compared with NB-2W group，NB-P-2W group had lower bladder leakage point pressure (BLPP)，but higher MCC and bladder compliance (BC) (P<0.05).Compared with NB-6W group，NB-P-6W group had significantly lower BLPP but higher MCC and BC (P<0.05).HE and MASSON staining and ultrasound results showed that，with the extension of nerve transection time，bladder fibrosis gradually worsened，the bladder wall became rough and thickened，calculi were visible inside，and hydronephrosis gradually appeared; the degree of fibrosis in NB-P-2W and NB-P-6W groups was less than that in NB-2W and NB-6W groups，and no hydronephrosis was observed in the upper urinary tract.In addition，Western blotting and immunohistochemical results showed that NB-2W and NB-6W groups had significantly higher relative expression levels of Piezos，Collagen Ⅰ and α-SMA than the sham group (P<0.01)，while NB-P-2W and NB-P-6W groups had lower relative expression levels of Piezos,Collagen Ⅰ and α-SMA than NB-2W and NB-6W groups (P<0.01). Conclusion: The increased expressions of mechanosensitive channels Piezos in NB young rats may be involved in the progression of bladder fibrosis，but its mechanism needs further study.

Objective: To investigate the influencing factors of overactive bladder (OAB) in college freshmen and the impacts of OAB on their mental health, quality of life and social interaction. Methods: An epidemiological questionnaire survey was conducted in an anonymous manner on the prevalence of OAB among 5300 freshmen aged 17 to 22 years enrolled in the 2023—2024 academic year in Xinxiang Medical University and Sanquan College of Xinxiang Medical University.The questionnaire included questions on basic information, history of urinary tract infection, constipation, smoking, history of alcohol consumption, history of coffee/strong tea drinking, history of carbonated beverage drinking, redundant prepuce, phimosis, holding urine, chronic insomnia, self-rating anxiety scale (SAS), quality of life score (QoL), and social avoidance and distress scale (SADS).The influencing factors of OAB were analyzed with multivariate logistic regression analysis.The subjects were grouped according to whether they had OAB, and the differences in SAS, QoL and SADS between the OAB group and non-OAB group were compared.The impacts of OAB on the anxiety level, quality of life, and social interaction were analyzed with multiple linear regression analysis. Results: The overall prevalence rate of OAB was 4.9% (244/5018).Multivariate logistic regression analysis showed that the history of urinary tract infection (OR=0.177), constipation (OR=0.636), smoking (OR=0.582), alcohol consumption (OR=0.685), coffee/strong tea drinking (OR=0.387), carbonated beverage drinking (OR=0.631), redundant prepuce (OR=0.673), phimosis (OR=0.311), urine holding (OR=0.593), and chronic insomnia (OR=0.256) were influencing factors for the occurrence of OAB (P＜0.05).The OAB group had higher SAS score [(41.18±6.54) vs. (38.61±6.36)], QoL score [(3.65±1.20) vs. (2.79±0.95)], social avoidance score [(6.25±1.86) vs. (5.86±1.51)], social distress score [(6.27±1.59) vs. (5.97±1.32)], and total SADS score [(12.51±2.35) vs. (11.84±2.01)] than the non-OAB group (P＜0.05).The results of multiple linear regression analysis showed that OAB could independently affect the scores of QoL, SAS, and SADS.The OAB group had higher scores of QoL, SAS, and SADS compared with the non-OAB group (P＜0.001). Conclusion: History of urinary tract infection, constipation, smoking, alcohol consumption, coffee/strong tea drinking, carbonated beverage drinking, redundant prepuce, phimosis, urine holding, and chronic insomnia are influencing factors for the occurrence of OAB in male college students.Moreover, OAB has negative impacts on their mental health, quality of life, and social interaction.

Objective To evaluate the predictive ability and clinical application value of artificial intelligence (AI) systems in the benign and malignant differentiation and pathological type of pulmonary nodules, and to summarize clinical application experience. Methods A retrospective analysis was conducted on the clinical data of patients with pulmonary nodules admitted to the Department of Thoracic Surgery, Second Hospital of Lanzhou University, from February 2016 to February 2025. Firstly, pulmonary nodules were divided into benign and non-benign groups, and the discriminative abilities of AI systems and clinicians were compared. Subsequently, lung nodules reported as precursor glandular lesions (PGL), microinvasive adenocarcinoma (MIA), and invasive adenocarcinoma (IAC) in postoperative pathological results were analyzed, comparing the efficacy of AI systems and clinicians in predicting the pathological type of pulmonary nodules. Results In the analysis of benign/non-benign pulmonary nodules, clinical data from a total of 638 patients with pulmonary nodules were included, of which there were 257 males (10 patients and 1 patient of double and triple primary lesions, respectively) and 381 females (18 patients and 1 patient of double and triple primary lesions, respectively), with a median age of 55.0 (47.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis of the two groups of variables showed that, except for nodule location, the differences in the remaining variables were statistically significant (P<0.05). Multivariate logistic regression analysis showed that age, nodule type (subsolid pulmonary nodule), average density, spicule sign, and vascular convergence sign were independent influencing factors for non-benign pulmonary nodules, among which age, nodule type (subsolid pulmonary nodule), spicule sign, and vascular convergence sign were positively correlated with non-benign pulmonary nodules, while average density was negatively correlated with the occurrence of non-benign pulmonary nodules. The area under the receiver operating characteristic curve (AUC) of the malignancy risk value given by the AI system in predicting non-benign pulmonary nodules was 0.811, slightly lower than the 0.898 predicted by clinicians. In the PGL/MIA/IAC analysis, clinical data from a total of 411 patients with pulmonary nodules were included, of which there were 149 males (8 patients of double primary lesions) and 262 females (17 patients of double primary lesions), with a median age of 56.0 (50.0, 61.0) years. Different lesions in the same patient were analyzed as independent samples. Univariate analysis results showed that, except for gender, nodule location, and vascular convergence sign, the differences in the remaining variables among the three groups of PGL, MIA, and IAC patients were statistically significant (P<0.05). Multinomial multivariate logistic regression analysis showed that the differences between the parameters in the PGL group and the MIA group were not statistically significant (P>0.05), and the maximum diameter and average density of the nodules were statistically different between the PGL and IAC groups (P<0.05), and were positively correlated with the occurrence of IAC as independent risk factors. The average AUC value, accuracy, recall rate, and F1 score of the AI system in predicting lung nodule pathological type were 0.807, 74.3%, 73.2%, and 68.5%, respectively, all better than the clinical physicians’ prediction of lung nodule pathological type indicators (0.782, 70.9%, 66.2%, and 63.7% respectively). The AUC value of the AI system in predicting IAC was 0.853, and the sensitivity, specificity, and optimal cutoff value were 0.643, 0.943, and 50.0%, respectively. Conclusion This AI system has demonstrated high clinical value in predicting the benign and malignant nature and pathological type of lung nodules, especially in predicting lung nodule pathological type, its ability has surpassed that of clinical physicians. With the optimization of algorithms and the adequate integration of multimodal data, it can better assist clinical physicians in formulating individualized diagnostic and treatment plans for patients with lung nodules.

Lung cancer has the highest morbidity and mortality rate among all cancers. Because of the complex pathogenesis， there are limitations in the common Western medicine treatment methods. Clinical and experimental studies have proved that traditional Chinese medicine （TCM） can not only effectively treat lung cancer and alleviate the clinical symptoms of cancer patients but also reduce the adverse reactions and complications caused by surgery， chemotherapy， and radiotherapy to improve the quality of life of the patients. The biological behaviors of lung cancer cells， such as proliferation， invasion， and metastasis， are closely related to their metabolic reprogramming. Metabolic reprogramming in lung cancer involves a series of metabolic changes such as increased glucose uptake and consumption， enhanced glycolysis， increased amino acid uptake and catabolism， and enhanced lipid and protein synthesis. Studies have reported that TCM active components， extracts， and compound prescriptions can effectively inhibit the biological behaviors of lung cancer by regulating metabolic reprogramming. Therefore， this paper reviews the pharmacological mechanisms of TCM active components， extracts， and compound prescriptions in regulating metabolic reprogramming of lung cancer， with the aim of providing a new way of thinking for the treatment of lung cancer by TCM regulation of metabolic reprogramming of lung cancer cells. The available studies suggest that TCM mainly inhibits the extracellular signal-regulated protein kinase （ERK）/c-Myc， phosphatidylinositol 3-kinase （PI3K）/protein kinase B （Akt）/mammalian target of rapamycin （mTOR）， and hypoxia-inducible factor-α （HIF-1α） pathways. Furthermore， the expression of monocarboxylate transporter 4 （MCT4）， glucose transporter 1 （GLUT1）， pyruvate dehydrogenase （PDH）， phosphofructokinase 1 （PFK1）， pyruvate dehydrogenase kinase 1 （PDK1）， pyruvate kinase M2 （PKM2）， hexokinase （HK）， lactate dehydrogenase （LDH）， and lactate dehydrogenase A （LDHA） are inhibited. In this way， TCM inhibits the glucose uptake by lung cancer cells and glycolysis in lung cancer cells to reduce the energy metabolism of tumor cells， ultimately achieving the therapeutic effect on lung cancer.