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.

ObjectiveTo investigate the expression of prefrontal cortical neurons， methyltransferase-like 3 （METTL3）， fat mass and obesity-associated gene （FTO）， and AlkB homolog 5 （ALKBH5） proteins in a mouse model of post-traumatic stress disorder （PTSD）. MethodsA PTSD mouse model was established using a single prolonged stress and foot shock stimulation （SPSS） method. The despair， anxiety， and learning and memory functions of PTSD mice were assessed through the open field test， Y-maze test， and forced swimming test. Neuronal damage was detected via HE and Nissl staining. The expression levels of METTL3， FTO， ALKBH5， and neuronal nuclear protein （NEUN） were assessed by Western blot and immunofluorescence staining. ResultsCompared to control group， PTSD mice subjected to SPSS exhibited signs of despair， anxiety， and impaired learning and memory. HE and Nissl staining results showed neuronal damage in the prefrontal cortex of PTSD mice. Western blot and immunofluorescence staining results showed that the expression of the m6A-related proteins METTL3 and FTO decreased， while the expression of ALKBH5 increased in the prefrontal cortex. Additionally， NEUN protein levels showed a declining trend. ConclusionThe pathogenesis of PTSD may be associated with neuronal damage in the prefrontal cortex and alterations in m6A methylation proteins.

The classic formula Fangji Fulingtang is from ZHANG Zhongjing's Synopsis of the Golden Chamber in the Eastern Han dynasty. It is composed of Stephaniae Tetrandrae Radix， Astragali Radix， Cinnamomi Ramulus， Poria， and Glycyrrhizae Radix et Rhizoma， with the effects of reinforcing Qi and invigorating spleen， warming Yang and promoting urination. By a review of ancient medical books， this paper summarizes the composition， original plants， processing， dosage， decocting methods， indications and other key information of Fangji Fulingtang， aiming to provide a literature basis for the research， development， and clinical application of preparations based on this formula. Synonyms of Fangji Fulingtang exist in ancient medical books， while the formula composition in the Synopsis of the Golden Chamber is more widespread and far-reaching. In this formula， Stephaniae Tetrandrae Radix， Astragali Radix， Cinnamomi Ramulus， Poria， and Glycyrrhizae Radix et Rhizoma are the dried root of Stephania tetrandra， the dried root of Astragalus embranaceus var. mongholicus， the dried shoot of Cinnamomum cassia， the dried sclerotium of Poria cocos， and the dried root and rhizome of Glycyrrhiza uralensis， respectively. Fangji Fulingtang is mainly produced into powder， with the dosage and decocting method used in the past dynasties basically following the original formula. Each bag is composed of Stephaniae Tetrandrae Radix 13.80 g， Astragali Radix 13.80 g， Cinnamomi Ramulus 13.80 g， Poria 27.60 g， and Glycyrrhizae Radix et Rhizoma 9.20 g. The raw materials are purified， decocted in water from 1 200 mL to 400 mL， and the decoction should be taken warm， 3 times a day. Fangji Fulingtang was originally designed for treating skin edema， and then it was used to treat impediment in the Qing dynasty. In modern times， it is mostly used to treat musculoskeletal and connective tissue diseases and circulatory system diseases， demonstrating definite effects on various types of edema and heart failure. This paper clarifies the inheritance of Fangji Fulingtang and reveals its key information （attached to the end of this paper）， aiming to provide a theoretical basis for the development of preparations based on this formula.

The classic formula Fangji Fulingtang is from ZHANG Zhongjing's Synopsis of the Golden Chamber in the Eastern Han dynasty. It is composed of Stephaniae Tetrandrae Radix， Astragali Radix， Cinnamomi Ramulus， Poria， and Glycyrrhizae Radix et Rhizoma， with the effects of reinforcing Qi and invigorating spleen， warming Yang and promoting urination. By a review of ancient medical books， this paper summarizes the composition， original plants， processing， dosage， decocting methods， indications and other key information of Fangji Fulingtang， aiming to provide a literature basis for the research， development， and clinical application of preparations based on this formula. Synonyms of Fangji Fulingtang exist in ancient medical books， while the formula composition in the Synopsis of the Golden Chamber is more widespread and far-reaching. In this formula， Stephaniae Tetrandrae Radix， Astragali Radix， Cinnamomi Ramulus， Poria， and Glycyrrhizae Radix et Rhizoma are the dried root of Stephania tetrandra， the dried root of Astragalus embranaceus var. mongholicus， the dried shoot of Cinnamomum cassia， the dried sclerotium of Poria cocos， and the dried root and rhizome of Glycyrrhiza uralensis， respectively. Fangji Fulingtang is mainly produced into powder， with the dosage and decocting method used in the past dynasties basically following the original formula. Each bag is composed of Stephaniae Tetrandrae Radix 13.80 g， Astragali Radix 13.80 g， Cinnamomi Ramulus 13.80 g， Poria 27.60 g， and Glycyrrhizae Radix et Rhizoma 9.20 g. The raw materials are purified， decocted in water from 1 200 mL to 400 mL， and the decoction should be taken warm， 3 times a day. Fangji Fulingtang was originally designed for treating skin edema， and then it was used to treat impediment in the Qing dynasty. In modern times， it is mostly used to treat musculoskeletal and connective tissue diseases and circulatory system diseases， demonstrating definite effects on various types of edema and heart failure. This paper clarifies the inheritance of Fangji Fulingtang and reveals its key information （attached to the end of this paper）， aiming to provide a theoretical basis for the development of preparations based on this formula.

OBJECTIVE To evaluate the efficacy， safety and cost-effectiveness of apixaban in the prevention and treatment of cancer-associated venous thromboembolism （CA-VTE）， and provide evidence-based reference for clinical treatment. METHODS Retrieved from PubMed， the Cochrane Library， CNKI， Wanfang， VIP database and other websites of health technology assessment （HTA）， systematic review/meta-analysis， pharmacoeconomic studies and HTA reports of apixaban in the prevention and treatment of CA-VTE were collected. After data extraction and quality evaluation， the results of the included study were analyzed descriptively. RESULTS A total of 23 literatures were included， involving 16 systematic review/meta-analysis and 7 pharmacoeconomic studies. In terms of efficacy， compared with placebo， prophylactic use of apixaban could significantly reduce the incidence of venous thromboembolism （VTE） in outpatient adult cancer patients receiving chemotherapy （P＜0.05）. Compared with low-molecular weight heparin （LMWH）， rivaroxaban and warfarin， there were no statistically significant differences in the incidence of VTE for apixaban （P＞0.05）； nevertheless， apixaban was ranked as the most preferable choice. For the treatment of patients with CA-VTE， compared with warfarin， apixaban could significantly reduce the recurrence rate of VTE （P＜0.05）. While compared with patients treated with LMWH， rivaroxaban， edoxaban and dabigatran， there were no statistically significant differences in the recurrence rates of VTE， deep venous thrombosis and pulmonary embolism among patients using apixaban （P＞0.05）. In terms of safety， compared with placebo， prophylactic use of apixaban showed a higher occurrence of major bleeding in outpatient adult cancer patients receiving chemotherapy （P＜0.05）， while compared withpatients treated with LMWH， rivaroxaban， and warfarin， there were no statistically significant differences in the incidence of major bleeding among patients using apixaban （P＞0.05）； despite this， apixaban was ranked as the most favorable option. For the treatment of patients with CA-VTE， compared with dalteparin， the incidence of major bleeding and all-cause mortality of apixaban were similar （P＞0.05）， while the incidence of clinically relevant non-major bleeding （CRNMB） was higher （P＜0.05）. Compared with edoxaban， the incidence of major bleeding of apixaban was reduced significantly （P＜0.05）， while there was no significant difference in the incidence of CRNMB， the incidence of clinically relevant bleeding and all-cause mortality （P＞0.05）. Compared with rivaroxaban， warfarin and dabigatran， there were no significant differences in the incidence of major bleeding， the incidence of CRNMB， the incidence of clinically relevant bleeding and all-cause mortality （P＞0.05）. In terms of cost-effectiveness， the researches in China showed that apixaban was cost-effective in preventing CA-VTE； foreign studies showed that apixaban was cost-effective in preventing and treating CA-VTE. CONCLUSIONS Apixaban is effective， safe and cost- effective in the prevention and treatment of CA-VTE.

Objective:To analyze the efficacy of different doses of esketamine in maintaining general anesthesia in elderly patients undergoing radical resection of esophageal cancer.Methods:A total of 98 elderly patients who underwent radical resection of esophageal cancer and admitted from Jun. 2023 to May. 2025 in Shangqiu First People’s Hospital were selected and divided into Group A ( n=50, 0.25 mg·kg -1·h -1) and Group B ( n=48,0.5 mg·kg -1·h -1) according to the dose of esketamine. The following situations between the two groups were compared: (1) hemodynamics [mean arterial pressure (MAP), heart rate (HR) ] before anesthesia induction (T0), 30 minutes after the start of the operation (T1), and at extubation (T2) ; (2) Stress inflammatory indicators [norepinephrine (NE), C-reactive protein (CRP) ] before the operation and 1 day after the operation; (3) Analgesia status [Dosage of propofol and remifentanil, remedial analgesia rate, and the degree of analgesia was evaluated by visual analogue scale (VAS) 2 hours after the operation]; (4) Postoperative recovery [postoperative eye-opening time, extubation time, anesthesia recovery time, and postoperative recovery quality was evaluated using the Chinese version of the 15-item Quality of Recovery (QoR-15) Scale 1 day after the operation]; (5) Safety. Results:(1) At time T1, MAP of both groups was lower than that at time T0,and at time T2, MAP of group B was higher than that at time T1 ( P<0.05). At times T1 and T2, HR of both groups was lower than that at time T0, and HR of both groups at time T2 was higher than that at time T1 ( P<0.05). At time T1, MAP and HR in group B were lower than those in group A ( P<0.05). (2) The dosages of propofol and remifentanil in group B were lower ( P<0.05) ,while the comparison of remedial analgesia rate and VAS score between the two groups showed P>0.05. (3) One day after the operation,the levels of serum NE and CRP in both groups were higher than those before the operation,while those in group B were even lower ( P<0.05). (4) The incidence of adverse reactions in group B (20.83%) was slightly higher than that in group A (10.00%). (5) The eye-opening time,extubation time and anesthesia recovery time after surgery in group B were all longer than those in group A ( P<0.05), while the comparison of QoR-15 scores between the two groups showed P>0.05. Conclusions:In the maintenance of general anesthesia for elderly patients undergoing radical resection of esophageal cancer, the intraoperative hemodynamic fluctuations of low-dose esketamine are smaller. Although the dosages of propofol and remifentanil are higher and the postoperative recovery time is longer, there are no significant differences in analgesic effect, adverse reactions or recovery quality, while the stress and inflammatory responses of high-dose esketamine are smaller.

Acute large vessel occlusion stroke(ALVOS)of anterior circulation is associated with severe clinical manifestations and high rates of disability and mortality.Mechanical thrombectomy has emerged as the primary therapeutic intervention.However,post-procedural outcomes remain highly variable,and patients continue to face elevated risks of poor prognosis.Machine learning,a transformative tool in medical research,enables comprehensive analysis of multimodal data to identify specific biomarkers and improve the accuracy of predictions for clinical outcomes and adverse events.This review summarized the latest developments in machine learning applications aim at predicting post-thrombectomy prognosis and risk of adverse event,including futile recanalization,hemorrhagic transformation,and malignant cerebral edema in patients with anterior circulation ALVOS in order to provide a basis for developing personalized treatment plan and improve their clinical prognosis.

Objective:To fine-tune the mT5 (massively multilingual pre-trained text-to-text transformer) large language model, automatically generate report conclusions for teaching purposes from chest CT image descriptions, and assess the quality of automatically generated conclusions.Methods:The training set included 3 000 high-quality physical examination chest CT reports from one hospital, and the external validation set consisted of 600 physical examination chest CT reports from two other hospitals. Experienced radiology teaching physicians assessed the consistency between the generated conclusions and the original physician-written conclusions in the external validation set using a 5-point Likert scale across five linguistic indicators (correctness of examination information, correctness of lesion detection, standardization of terminology, applicability of the conclusions, and simplicity of conclusions). Using the original report conclusions as the reference, the accuracy of the conclusions generated based on the external validation set in describing four major thoracic conditions (pulmonary nodules, pneumonia, emphysema, pleural effusion) was evaluated. Perform chi square test using SPSS 25.0.Results:In the external validation set, the mean consistency score between the generated conclusions and the original conclusions given by the radiology teaching physicians was >4 points, indicating agreement with the original conclusions. In the generated conclusions, the description of the four major thoracic conditions demonstrated 0.95-1.00 (95% CI=0.91-1.00) accuracy, 0.76-1.00 (95% CI=0.59-1.00) sensitivity, and 0.97-1.00 (95% CI=0.91-1.00) specificity. Conclusions:The chest CT report conclusion generation system based on the mT5 large language model demonstrated high accuracy and is expected to provide immediate and efficient automated guidance for standardized residency training.

Objective To evaluate the role of dynamic contrast-enhanced magnetic resonance imaging(DCE-MRI)in the diagnosis of axillary lymph node metastasis(ALNM)in breast cancer patients with low HER-2 expression.Methods A total of 297 breast cancer patients with low HER-2 expression treated at the Affiliated Hospital of Xuzhou Medical University were enrolled and divided into ALNM group(n=71)and non-ALNM group(n=226)according to whether there was ALNM.All patients underwent DCE-MRI,and DCE-MRI derived parameters were collected and analyzed.Logistic regression analysis was used to identify the risk factors for ALNM,and the efficacy of DCE-MRI in diagnosing ALNM was assessed using receiver operating characteristic curve.Results Significant differences were observed between two groups in lesion distribution,TNM staging,vascular invasion,and most DCE-MRI derived parameters including short-to-long axis ratio,Ve,Ktrans,Kep,ADC and SER(all P<0.05).Multivariate regression analysis revealed that the short-to-long axis ratio,Ve,Ktrans,Kep,ADC and SER were significant risk factors for ALNM in breast cancer patients.Comparative analysis demonstrated that the combination of DCE-MRI derived parameters yielded a maximum area under the curve of 0.976,with a sensitivity of 91.5%and a specificity of 92.9%.Conclusion DCE-MRI is an effective tool for determining the presence of ALNM in breast cancer patients with low HER-2 expression,providing significant diagnostic evidence for clinical practice.