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.

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 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.

Hepatocellular carcinoma(HCC)is categorized into two major classes based on the heterogeneity of histological phenotypes:proliferative HCC and non-proliferative HCC.These classes exhibit distinct clinical,molecular and imaging characteristics.Within these two major categories,there exist multiple pathological subtypes,each demonstrating unique molecular and histological features that manifest differently in imaging findings.Additionally,the prognosis of these HCC pathological subtypes diverges from that of not-otherwise-specified HCC,and current clinical guidelines for their treatment remain unclear.This article aims to summarize the imaging manifestations and prognosis of the histopathological subtypes of HCC,so as to enhance identification and judgement of HCC subtypes,and to provide a theoretical basis for selecting appropriate therapeutic strategies.

Objective:To investigate the related factors of cognitive impairment in middle-aged and old-aged patients with type 2 diabetes mellitus(T2DM).Methods:A total of 970 patients with T2DM(585 middle-aged group and 385 old-aged group)were selected from residents of a large community in Beijing from September to December 2018.The Mini-Mental State Examination(MMSE)was used to assess the cognitive func-tion.Multivariate logistic regression was used to analyze the related factors.Results:The detection rates of cognitive impairment were 12.0％and 13.5％in middle-aged and old-aged patients with T2DM,respectively.Among mid-dle-aged patients with T2DM,work(OR=0.22,95％CI:0.03-0.77)and education at the junior college or un-dergraduate level and above(OR=0.18,95％CI:0.04-0.55)were protective factors for cognitive impair-ment.Myocardial infarction(OR=4.13,95％CI:1.26-13.63)was a risk factor for cognitive impairment.Among old-aged patients with T2DM,drinking tea 1-2 times a week(OR=0.11,95％CI:0.01-0.58)and education at the junior college or undergraduate level and above(OR=0.19,95％CI:0.05-0.54)were protective factors for cognitive impairment.Stroke(OR=3.64,95％CI:1.55-8.39)and good sleep self-assessment(OR=2.75,95％CI:1.13-7.35)were risk factors for cognitive impairment.Conclusion:Cognitive impairment in middle-aged pa-tients with T2DM is related to work,education level and myocardial infarction,and cognitive impairment in old-aged patients with T2DM is related to lifestyle,education level and stroke.

This study was aimed at investigating the effects of demethylase fat mass and obesity-associated protein(FTO)and methyltransferase methyltransferase like protein 3(METTL3),key molecules in N6-methyladenosine(m6A)modification,on the replication and proliferation of Japanese encephalitis virus(JEV).Recombinant lentiviruses were generated by packaging the FTO and green fluorescent protein into lentiviral vectors.Neuro2a cells,a mouse neuroblastoma cell line,were infected with the lentivirus,and stable FTO-expressing cell lines were obtained through puromycin selection.Successful overexpression of FTO was confirmed through fluorescence microscopy,real-time quantitative PCR,and western blot analysis.When Neuro2a cells overexpressing FTO were infected with JEV,the overexpression of FTO decreased JEV replication in the cells,and increased the expression of interferon(IFN)and related molecules.Additionally,treatment of JEV-infected Neuro2a cells with the METTL3-specific inhibitor STM2457 resulted in a dose-dependent decrease in JEV replication and viral protein expression.These findings suggested that lowering m6A methylation levels inhibits JEV replication,thus shedding light on the regulatory role of methylation modification in JEV replication.

Objective To investigate the association between cystatin C level and 6-month mortali-ty as well as re-hospitalization in elderly patients with heart failure(HF).Methods The clinical data in this study were from a retrospective cohort study,Zigong Heart Failure Study.A total of 1786 elderly HF patients admitted in Zigong Fourth People's Hospital from December 2016 to June 2019 were selected.According to the tertiles of cystatin C level,the subjected patients were divided into three groups,with the cystatin C level of 1.10±0.17(587 cases),1.60±0.17(599 ca-ses),and 2.91±0.90 mg/L(600 cases),respectively.The primary endpoint was a composite end-point of death at 6 months after discharge and readmission due to HF.Multivariate Cox propor-tional hazards regression analysis was employed to analyze the relationship of the cystatin C level with the composite endpoint of 6-month mortality and readmission due to HF.Restricted cubic spline was used to model the relationship between the cystatin C level and the composite end-point,Kaplan-Meier survival curve was plotted to analyze the differences in 6-month event free survival rates among the three groups,and ROC curve was drawn to analyze the predictive value of cystatin C level for the composite endpoint.Results Multivariate Cox proportional hazards re-gression analysis showed that the middle and upper tertiles of cystatin C level were risk factors for the composite endpoint of 6-month mortality and readmission due to HF(HR=1.170,95％CI:0.970-1.390,P=0.111;HR=1.452,95％CI:1.190-1.756,P=0.000).When taking cystatin C level as a continuous variable,the results remained consistent:for every one standard deviation increase in cystatin C level,HR=1.141,95％CI:1.060-1.226 in Model 3;For every 1 mg/L in-crease,HR=1.152,95％CI:1.057-1.250 in Model 3.Restricted cubic spline displayed a non-linear inverse J-shaped relationship between cystatin C level and the composite endpoint of 6-month mortality and readmission due to HF,with a risk inflection point of cystatin C level at 2.13 mg/L.ROC curve analysis showed that the AUC value of cystatin C level in predicting the composite endpoint,6-month death and re-admission due to HF was 0.572,0.667 and 0.554,respectively.Conclusion Elevated cystatin C level is independently associated with an increased risk of the composite endpoint of 6-month death and re-admission in elderly HF patients.

Objective:To investigate the computed tomography (CT) imaging features of patients with chronic hydrocephalus after intracerebral hemorrhage surgery and the difference between endoscopic third ventriculostomy (ETV) and ventricular peritoneal shunt (VPS).Methods:A total of 158 patients with intracerebral hemorrhage who received surgical treatment in the Department of Neurosurgery of the People′s Hospital of Jinan from January 2021 to June 2023 were retrospectively selected as the study objects, including 78 patients with chronic hydrocephalus after surgery as the hydrocephalus group, and 80 patients with no hydrocephalus after surgery as the non-hydrocephalus group, and the CT imaging data of the patients were statistically analyzed. Hydrocephalus group was divided into ETV group (42 cases) and VPS group (36 cases) according to different treatment methods. The efficacy and quality of life of the two groups were compared, and the incidence of complications in the two groups were counted.Results:There was no significant difference between hydrocephalus group and non-hydrocephalus group in the site of cerebral hemorrhage, hematoma morphology and the proportion of patients with mixed signs, lobular signs and black hole signs (all P>0.05). The proportion of patients with ventricular dilation and hematoma enlargement in hydrocephalus group was significantly higher than that in non-hydrocephalus group (all P<0.05). The National Institute of Health Stroke Scale (NIHSS) scores of hydrocephalus patients in the two groups were measured continuously at different time points, and there was no significant difference in NIHSS scores between the ETV group and the VPS group before treatment, at 2 weeks and 4 weeks of treatment (all P>0.05). There was no significant difference between the ETV group and the VPS group ( P>0.05). The recurrence rate of the ETV group was lower than that of the VPS group ( P<0.05). The quality of life scores of patients in ETV group were higher than those in the VPS group at 3 months and 6 months after surgery ( P<0.05). Conclusions:CT examination of patients with chronic hydrocephalus after intracerebral hemorrhage will show obvious characteristics of hematoma enlargement and ventricle enlargement. The efficacy of ETV and VPS in the treatment of chronic hydrocephalus after intracerebral hemorrhage surgery is similar, but the former has a lower recurrence rate and a higher postoperative quality of life.

In view of the characteristics of H5N6 subtype avian influenza virus(AIV)that it has both high pathogenicity and the risk of cross-species transmission,posing a serious threat to the poultry farming industry and public health security,in order to effectively prevent and control the spread of H5N6 avian influenza,a rapid,sensitive and specific detection technolo-gy was established in this study.The specific monoclonal antibodies against the neuraminidase N6 protein of avian influenza A virus subtype H5N6 were obtained through hybridoma and monoclonal antibody technology.These antibodies were coupled and labeled with carboxyl-functionalized fluorescent quantum dots,along with previously prepared specific antibodies against the hemagglutinin H5 protein.A rapid fluorescence immunochromatographic detection method for the H5N6 subtype of avian influ-enza virus was established according to the principle of double-antibody sandwich immunochromatography.This method a-chieved a detection sensitivity of 1 ng/mL for recombinant hemagglutinin H5 subtype protein and 0.1 ng/mL for recombinant neuraminidase N6 subtype protein.Moreover,the method exhibited no cross-reactivity with other influenza subtypes or patho-gens,such as Newcastle disease(ND),infectious bronchitis(IB),and infectious laryngotracheitis(ILT),thus demonstrating good specificity.The method effectively identified the highly pathogenic avian influenza virus H5 subtype and directly distin-guished the H5N6 subtype with good accuracy.The fluorescent quantum dot immunochromatographic typing detection method established herein met the sensitivity,specificity,and accuracy requirements for H5N6 subtype detection,and can be further used for rapid detection of the H5 and H5N6 subtypes of avian influenza virus.