1.Current Status,Strategies and Prospects of Traditional Chinese Medicine Diagnosis and Treatment for Irritable Bowel Syndrome
Yandong WEN ; Zhi YANG ; Shaogang HUANG ; Zhongyu LI ; Xiangxue MA ; Qing XU ; Liqing DU ; Bochao YUAN ; Yibing TIAN ; Wentong GE ; Xiaofan ZHAO ; Chang LIU ; Xudong TANG
Journal of Traditional Chinese Medicine 2026;67(4):404-409
Irritable bowel syndrome (IBS) is a functional bowel disorder characterized primarily by abdominal pain and altered defecation habits. In recent years, traditional Chinese medicine (TCM) has made progress in multiple aspects of IBS research and treatment, including syndrome distribution, development of TCM formulas, clinical efficacy evaluation, external therapies, and psychosocial regulation. However, it still faces challenges such as over-reliance on symptomatic manifestations rather than biomarkers for diagnostic criteria, and the lack of high-quality evidence-based data supporting the efficacy of TCM formulas in treating IBS. This paper proposed that TCM diagnosis and treatment of IBS should adhere to the strategy of integrating the holistic concept with syndrome differentiation and treatment, combining TCM external therapies such as acupuncture, moxibustion and acupoint application), and emphasizing individualized diagnosis and treatment for psychosomatic abnormalities. Future research should integrate multi-omics technologies, artificial intelligence and other methods to deepen the understanding of the pathogenesis of IBS and the mechanisms of TCM formulas, so as to promote the standardization and internationalization of TCM in the diagnosis and treatment of IBS.
2.Two cases of acute radiation-induced skin injury caused by external exposure to 192Ir
Li LI ; Wei SHANG ; Yan LING ; Mi WANG ; Huisheng ZHANG ; Chiqiao LU ; Xiaohu ZHONG ; Shenglong XU ; Juan GUO ; Chang LIU ; Yulong LIU
Chinese Journal of Radiological Health 2026;35(1):56-61
Objective To introduce the causes of accidents and the diagnosis and treatment of two patients with radiation-induced skin injury admitted to our hospital in 2023, and to provide a reference for the clinical treatment of subsequent radiation-induced skin injury. Methods The clinical treatment process of two patients with acute skin injury caused by external radiation exposure were summarized and analyzed. Results The exposure history of the two patients was reconstructed, the flaw detection scenario was simulated, the biological dose and hand skin exposure dose were estimated, and the infrared thermal imaging device was used for dynamic monitoring. A comprehensive analysis was conducted based on clinical manifestations and other data. The diagnosis of “Xie” was excessive exposure combined with acute radiation-induced skin injury on both hands (Grade IV for the right hand palm, index finger, and middle finger and Grade II for the left hand little finger). The diagnosis of “Hao” was acute radiation-induced skin injury on both hands (Grade I). The two patients received different clinical treatment measures: “Xie” was treated with both local and systemic therapies, while “Hao” was mainly treated with systemic therapy. Conclusion After systematic and effective treatment, the radiation-induced skin injuries healed in both patients.
3.Impact of number of positive regional lymph nodes in N1 stage on the prognosis of patients with non-small cell lung cancer: A propensity score matching study
Dandan LIU ; Jiachen WANG ; Lidan CHANG ; Jia CHEN ; Ranran KONG ; Shiyuan LIU ; Minxia ZHU ; Jiantao JIANG ; Shaomin LI ; Zhengshui XU
Chinese Journal of Clinical Thoracic and Cardiovascular Surgery 2026;33(01):63-71
Objective To explore the impact of number of positive regional lymph nodes (nPRLN) in N1 stage on the prognosis of non-small cell lung cancer (NSCLC) patients. Methods Patients with TxN1M0 stage NSCLC who underwent lobectomy and mediastinal lymph node dissection from 2010 to 2015 were screened from SEER database (17 Regs, 2022nov sub). The optimal cutoff value of nPRLN was determined using X-tile software, and patients were divided into 2 groups according to the cutoff value: a nPRLN≤optimal cutoff group and a nPRLN>optimal cutoff group. The influence of confounding factors was minimized by propensity score matching (PSM) at a ratio of 1 : 1. Kaplan-Meier curves and Cox proportional hazards models were used to evaluate overall survival (OS) and lung cancer-specific survival (LCSS) of patients. Results A total of 1316 patients with TxN1M0 stage NSCLC were included, including 662 males and 654 females, with a median age of 67 (60, 73) years. The optimal cutoff value of nPRLN was 3, with 1165 patients in the nPRLN≤3 group and 151 patients in the nPRLN>3 group. After PSM, there were 138 patients in each group. Regardless of before or after PSM, OS and LCSS of patients in the nPRLN≤3 group were superior to those in the nPRLN>3 group (P<0.001). N1 stage nPRLN>3 was an independent prognostic risk factor for OS [HR=1.52, 95%CI (1.22, 1.89), P<0.001] and LCSS [HR=1.72, 95%CI (1.36, 2.18), P<0.001]. Conclusion N1 stage nPRLN>3 is an independent prognostic risk factor for NSCLC patients in TxN1M0 stage, which may provide new evidence for future revision of TNM staging N1 stage subclassification.
4.Risk factors for concurrent hepatic hydrothorax before intervention in primary liver cancer and construction of a nomogram prediction model
Yuanzhen WANG ; Renhai TIAN ; Yingyuan ZHANG ; Danqing XU ; Lixian CHANG ; Chunyun LIU ; Li LIU
Journal of Clinical Hepatology 2025;41(1):75-83
ObjectiveTo investigate the influencing factors for hepatic hydrothorax (HH) before intervention for primary hepatic carcinoma (PHC), and to construct and assess the nomogram risk prediction model. MethodsA retrospective analysis was performed for the clinical data of 353 hospitalized patients who attended the Third People’s Hospital of Kunming for the first time from October 2012 to October 2021 and there diagnosed with PHC, and according to the presence or absence of HH, they were divided into HH group with 153 patients and non-HH group with 200 patients. General data and the data of initial clinical testing after admission were collected from all PHC patients. The independent-samples t test was used for comparison of normally distributed continuous data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups; the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. After the multicollinearity test was performed for the variables with statistical significance determined by the univariate analysis, the multivariate Logistic regression analysis was used to identify independent influencing factors. The “rms” software package was used to construct a nomogram risk prediction model, and the Hosmer-Lemeshow test and the receiver operating characteristic (ROC) curve were used to assess the risk prediction model; the “Calibration Curves” software package was used to plot the calibration curve, and the “rmda” software package was used to plot the clinical decision curve and the clinical impact curve. ResultsAmong the 353 patients with PHC, there were 153 patients with HH, with a prevalence rate of 43.34%. Child-Pugh class B (odds ratio [OR]=2.652, 95% confidence interval [CI]: 1.050 — 6.698, P=0.039), Child-Pugh class C (OR=7.963, 95%CI: 1.046 — 60.632, P=0.045), total protein (OR=0.947, 95%CI: 0.914 — 0.981, P=0.003), high-sensitivity C-reactive protein (OR=1.007, 95%CI: 1.001 — 1.014, P=0.025), and interleukin-2 (OR=0.801, 95%CI: 0.653 — 0.981, P=0.032) were independent influencing factors for HH before PHC intervention, and a nomogram risk prediction model was established based on these factors. The Hosmer-Lemeshow test showed that the model had a good degree of fitting (χ2=5.006, P=0.757), with an area under the ROC curve of 0.752 (95%CI: 0.701 — 0.803), a sensitivity of 78.40%, and a specificity of 63.50%. The calibration curve showed that the model had good consistency in predicting HH before PHC intervention, and the clinical decision curve and the clinical impact curve showed that the model had good clinical practicability within a certain threshold range. ConclusionChild-Pugh class, total protein, interleukin-2, and high-sensitivity C-reactive protein are independent influencing factors for developing HH before PHC intervention, and the nomogram model established based on these factors can effectively predict the risk of developing HH.
5.Influencing factors for recompensation in patients with decompensated hepatitis C cirrhosis
Danqing XU ; Huan MU ; Yingyuan ZHANG ; Lixian CHANG ; Yuanzhen WANG ; Weikun LI ; Zhijian DONG ; Lihua ZHANG ; Yijing CHENG ; Li LIU
Journal of Clinical Hepatology 2025;41(2):269-276
ObjectiveTo investigate the influencing factors for recompensation in patients with decompensated hepatitis C cirrhosis, and to establish a predictive model. MethodsA total of 217 patients who were diagnosed with decompensated hepatitis C cirrhosis and were admitted to The Third People’s Hospital of Kunming l from January, 2019 to December, 2022 were enrolled, among whom 63 patients who were readmitted within at least 1 year and had no portal hypertension-related complications were enrolled as recompensation group, and 154 patients without recompensation were enrolled as control group. Related clinical data were collected, and univariate and multivariate analyses were performed for the factors that may affect the occurrence of recompensation. The independent-samples t test was used for comparison of normally distributed measurement data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed measurement data between two groups; the chi-square test or the Fisher’s exact test was used for comparison of categorical data between two groups. A binary Logistic regression analysis was used to investigate the influencing factors for recompensation in patients with decompensated hepatitis C cirrhosis, and the receiver operating characteristic (ROC) curve was used to assess the predictive performance of the model. ResultsAmong the 217 patients with decompensated hepatitis C cirrhosis, 63 (29.03%) had recompensation. There were significant differences between the recompensation group and the control group in HIV history (χ2=4.566, P=0.034), history of partial splenic embolism (χ2=6.687, P=0.014), Child-Pugh classification (χ2=11.978, P=0.003), grade of ascites (χ2=14.229, P<0.001), albumin (t=4.063, P<0.001), prealbumin (Z=-3.077, P=0.002), high-density lipoprotein (t=2.854, P=0.011), high-sensitivity C-reactive protein (Z=-2.447, P=0.014), prothrombin time (Z=-2.441, P=0.015), carcinoembryonic antigen (Z=-2.113, P=0.035), alpha-fetoprotein (AFP) (Z=-2.063, P=0.039), CA125 (Z=-2.270, P=0.023), TT3 (Z=-3.304, P<0.001), TT4 (Z=-2.221, P=0.026), CD45+ (Z=-2.278, P=0.023), interleukin-5 (Z=-2.845, P=0.004), tumor necrosis factor-α (Z=-2.176, P=0.030), and portal vein width (Z=-5.283, P=0.005). The multivariate analysis showed that history of partial splenic embolism (odds ratio [OR]=3.064, P=0.049), HIV history (OR=0.195, P=0.027), a small amount of ascites (OR=3.390, P=0.017), AFP (OR=1.003, P=0.004), and portal vein width (OR=0.600, P<0.001) were independent influencing factors for the occurrence of recompensation in patients with decompensated hepatitis C cirrhosis. The ROC curve analysis showed that HIV history, grade of ascites, history of partial splenic embolism, AFP, portal vein width, and the combined predictive model of these indices had an area under the ROC curve of 0.556, 0.641, 0.560, 0.589, 0.745, and 0.817, respectively. ConclusionFor patients with decompensated hepatitis C cirrhosis, those with a history of partial splenic embolism, a small amount of ascites, and an increase in AFP level are more likely to experience recompensation, while those with a history of HIV and an increase in portal vein width are less likely to experience recompensation.
6.Material Basis and Its Distribution in vivo of Qili Qiangxin Capsules Analyzed by UPLC-Q-Orbitrap-MS
Jianwei ZHANG ; Jiekai HUA ; Rongsheng LI ; Qin WANG ; Xinnan CHANG ; Wei LIU ; Jie SHEN
Chinese Journal of Experimental Traditional Medical Formulae 2025;31(5):185-193
ObjectiveBased on ultra-performance liquid chromatography-quadrupole-electrostatic field orbitrap high resolution mass spectrometry(UPLC-Q-Orbitrap-MS), the chemical constituents of Qili Qiangxin capsules was identified, and their distribution in vivo was analyzed. MethodsUPLC-Q-Orbitrap-MS was used to detect the sample solution of Qili Qiangxin capsules, as well as the serum, brain, heart, lung, spleen, liver and kidney tissues of mice after oral administration. Using the Thermo Xcalibur 2.2 software, the compound information database was constructed, and the molecular formulas of compounds corresponding to the quasi-molecular ions were fitted. Based on the information of retention time, accurate relative molecular mass and fragments, the compounds and their distribution in vivo were analyzed by comparing with the data of reference substances and literature. ResultsA total of 233 compounds, including 70 terpenoids, 60 flavonoids, 23 organic acids, 17 alkaloids, 20 steroids, 7 coumarins and 36 others, were identified or predicted from Qili Qiangxin capsules, 73 of which were identified matching with standard substances. Tissue distribution results showed that 71, 17, 38, 33, 32, 58 and 43 migrating components were detected in blood, brain, heart, lung, spleen, liver and kidney, respectively. Thirty-seven components were absorbed into the blood and heart, including quinic acid, benzoylaconitine benzoylmesaconine and so on. Fourteen components were absorbed into the blood and six tissues, including calycosin, methylnissolin, formononetin, alisol B, alisol A and so on. ConclusionThis study comprehensively analyzes the chemical components of Qili Qiangxin capsules and their distribution in vivo. Among them, astragaloside Ⅳ, salvianolic acid B, ginsenoside Rb1, ginsenoside Rb3, ginsenoside Rd, ginsenoside Rg3, calycosin-7-glucoside, and sinapine may be the important components for the treatment of heart failure, which can provide useful reference for its quality control and research on pharmacodynamic material basis.
7.Molecular biological research and molecular homologous modeling of Bw.03 subgroup
Li WANG ; Yongkui KONG ; Huifang JIN ; Xin LIU ; Ying XIE ; Xue LIU ; Yanli CHANG ; Yafang WANG ; Shumiao YANG ; Di ZHU ; Qiankun YANG
Chinese Journal of Blood Transfusion 2025;38(1):112-115
[Objective] To study the molecular biological mechanism for a case of ABO blood group B subtype, and perform three-dimensional modeling of the mutant enzyme. [Methods] The ABO phenotype was identified by the tube method and microcolumn gel method; the ABO gene of the proband was detected by sequence-specific primer polymerase chain reaction (PCR-SSP), and the exon 6 and 7 of the ABO gene were sequenced and analyzed. Homologous modeling of Bw.03 glycosyltransferase (GT) was carried out by Modeller and analyzed by PyMOL2.5.0 software. [Results] The weakening B antigen was detected in the proband sample by forward typing, and anti-B antibody was detected by reverse typing. PCR-SSP detection showed B, O gene, and the sequencing results showed c.721 C>T mutation in exon 7 of the B gene, resulting in p. Arg 241 Trp. Compared with the wild type, the structure of Bw.03GT was partially changed, and the intermolecular force analysis showed that the original three hydrogen bonds at 241 position disappeared. [Conclusion] Blood group molecular biology examination is helpful for the accurate identification of ambiguous blood group. Homologous modeling more intuitively shows the key site for the weakening of Bw.03 GT activity. The intermolecular force analysis can explain the root cause of enzyme activity weakening.
8.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
Background:
and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking.
Methods:
This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance.
Results:
Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal.
Conclusions
The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.
9.Predictive Modeling of Symptomatic Intracranial Hemorrhage Following Endovascular Thrombectomy: Insights From the Nationwide TREAT-AIS Registry
Jia-Hung CHEN ; I-Chang SU ; Yueh-Hsun LU ; Yi-Chen HSIEH ; Chih-Hao CHEN ; Chun-Jen LIN ; Yu-Wei CHEN ; Kuan-Hung LIN ; Pi-Shan SUNG ; Chih-Wei TANG ; Hai-Jui CHU ; Chuan-Hsiu FU ; Chao-Liang CHOU ; Cheng-Yu WEI ; Shang-Yih YAN ; Po-Lin CHEN ; Hsu-Ling YEH ; Sheng-Feng SUNG ; Hon-Man LIU ; Ching-Huang LIN ; Meng LEE ; Sung-Chun TANG ; I-Hui LEE ; Lung CHAN ; Li-Ming LIEN ; Hung-Yi CHIOU ; Jiunn-Tay LEE ; Jiann-Shing JENG ;
Journal of Stroke 2025;27(1):85-94
Background:
and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking.
Methods:
This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance.
Results:
Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal.
Conclusions
The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.
10.Value of FibroScan, gamma-glutamyl transpeptidase-to-platelet ratio, S index, interleukin-6, and tumor necrosis factor-α in the diagnosis of HBeAg-positive chronic hepatitis B liver fibrosis
Yingyuan ZHANG ; Danqing XU ; Huan MU ; Chunyan MOU ; Lixian CHANG ; Yuanzhen WANG ; Hongyan WEI ; Li LIU ; Weikun LI ; Chunyun LIU
Journal of Clinical Hepatology 2025;41(4):670-676
ObjectiveTo investigate the value of noninvasive imaging detection (FibroScan), two serological models of gamma-glutamyl transpeptidase-to-platelet ratio (GPR) score and S index, and two inflammatory factors of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α) in predicting liver fibrosis in patients with HBeAg-positive chronic hepatitis B (CHB), as well as the consistency of liver biopsy in pathological staging, and to provide early warning for early intervention of CHB. MethodsA retrospective analysis was performed for 131 HBeAg-positive CHB patients who underwent liver biopsy in The Third People’s Hospital of Kunming from January 2019 to December 2023. The results of liver biopsy were collected from all patients, and related examinations were performed before liver biopsy, including total bilirubin, alanine aminotransferase, platelet count, gamma-glutamyl transpeptidase, albumin, IL-6, TNF-α, liver stiffness measurement (LSM), and abdominal ultrasound. An analysis of variance was used for comparison of normally distributed continuous data between groups, and the Kruskal-Wallis H test was used for comparison of non-normally distributed continuous data between groups; the chi-square test was used for comparison of categorical data between groups. A Kappa analysis was used to investigate the consistency between LSM noninvasive histological staging and pathological staging based on liver biopsy, and the Spearman analysis was used to investigate the correlation between each variable and FibroScan in the diagnosis of liver fibrosis stage. The Logistic regression analysis was used to construct joint predictive factors. The receiver operating characteristic (ROC) curve was used to evaluate the value of each indicator alone and the joint predictive model in the diagnosis of liver fibrosis, and the Delong test was used for comparison of the area under the ROC curve (AUC). ResultsIn the consistency check, inflammation degree based on liver biopsy had a Kappa value of 0.807 (P<0.001), and liver fibrosis degree based on liver biopsy had a Kappa value of 0.827 (P<0.001), suggesting that FibroScan noninvasive histological staging and liver biopsy showed good consistency in assessing inflammation degree and liver fibrosis stage. Age was positively correlated with LSM, GPR score, S index, IL-6, and TNF-α (all P<0.05), and GPR score, S index, IL-6, and TNF-α were positively correlated with LSM (all P<0.05). GPR score, S index, IL-6, and TNF-α were all independent risk factors for diagnosing significant liver fibrosis (≥S2) and progressive liver fibrosis (≥S3) (all P<0.05). As for each indicator alone, GPR score had the highest value in the diagnosis of significant liver fibrosis (≥S2), followed by S index, IL-6, and TNF-α, while S index had the highest value in the diagnosis of progressive liver fibrosis (≥S3), followed by GPR score, TNF-α, and IL-6. The joint model had a higher predictive value than each indicator alone (all P<0.05). ConclusionThere is a good consistency between FibroScan noninvasive histological staging and pathological staging based on liver biopsy. GPR score, S index, IL-6, and TNF-α are independent risk factors for evaluating different degree of liver fibrosis in CHB, and the combined prediction model established by them can better diagnose liver fibrosis.

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