Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-associated death globally. Liver transplantation (LT) has emerged as a key treatment for patients with HCC, and the Milan criteria have been adopted as the cornerstone of the selection policy. To allow more patients to benefit from LT, a number of expanded criteria have been proposed, many of which use radiologic morphological characteristics with larger and more tumors as surrogates to predict outcomes. Other groups developed indices incorporating biological variables and dynamic markers of response to locoregional treatment. These expanded selection criteria achieved satisfactory results with limited liver supplies. In addition, a number of prognostic models have been developed using clinicopathological characteristics, imaging radiomics features, genetic data, and advanced techniques such as artificial intelligence. These models could improve prognostic estimation, establish surveillance strategies, and bolster long-term outcomes in patients with HCC. In this study, we reviewed the latest findings and achievements regarding the selection criteria and post-transplant prognostic models for LT in patients with HCC.

Fermented traditional Chinese medicine(TCM) has a long history of medicinal use, such as Sojae Semen Praeparatum, Arisaema Cum Bile, Pinelliae Rhizoma Fermentata, red yeast rice, and Jianqu. Fermentation technology was recorded in the earliest TCM work, Shen Nong's Classic of the Materia Medica. Microorganisms are essential components of the fermentation process. However, the contamination of fermented TCM by toxigenic fungi and mycotoxins due to unstandardized fermentation processes seriously affects the quality of TCM and poses a threat to the life and health of consumers. In this paper, the characteristics, microbial composition, and mycotoxin profile of fermented TCM are systematically summarized to provide a theoretical basis for its quality and safety control.
Fermentation ; Mycotoxins/analysis* ; Drugs, Chinese Herbal/analysis* ; Fungi/classification* ; Bacteria/genetics* ; Drug Contamination ; Medicine, Chinese Traditional

By employing the analytic hierarchy process(AHP), the CRITIC method(a weight determination method based on indicator correlations), and the AHP-CRITIC hybrid weighting method, the weight coefficients of evaluation indicators were determined, followed by a comprehensive score comparison. The grey correlation analysis was then performed to analyze the results calculated using the hybrid weighting method. Subsequently, a backpropagation-artificial neural network(BP-ANN) model was constructed to predict the extraction process parameters and optimize the extraction process for Shenxiong Huanglian Jiedu Granules(SHJG). In the extraction process, an L_9(3~4) orthogonal experiment was designed to optimize three factors at three levels, including extraction frequency, water addition amount, and extraction time. The evaluation indicators included geniposide, berberine, ginsenoside Rg_1 + Re, ginsenoside Rb_1, ferulic acid, and extract yield. Finally, the optimal extraction results obtained by the orthogonal experiment, grey correlation analysis, and BP-ANN method were compared, and validation experiments were conducted. The results showed that the optimal extraction process involved two rounds of aqueous extraction, each lasting one hour; the first extraction used ten times the amount of added water, while the second extraction used eight times the amount. In the validation experiments, the average content of each indicator component was higher than the average content obtained in the orthogonal experiment, with a higher comprehensive score. The optimized extraction process parameters were reliable and stable, making them suitable for subsequent preparation process research.
Drugs, Chinese Herbal/analysis* ; Neural Networks, Computer

OBJECTIVES: To investigate the predictive factors for plastic bronchitis (PB) in children with Mycoplasma pneumoniae pneumonia (MPP) and to establish a nomogram prediction model for PB occurrence. METHODS: A retrospective analysis was conducted on children with MPP hospitalized at The Affiliated Hospital of Xuzhou Medical University from January 2023 to June 2024. The patients were randomly divided into a training set (n=562) and a validation set (n=240) at a ratio of 7:3 using simple random sampling. In the training set, patients were categorized into a PB group (n=70) and a non-PB group (n=492) based on the occurrence of PB. Spearman correlation analysis was performed to exclude collinearity among variables, followed by univariate analysis and LASSO regression to identify predictive factors. A nomogram prediction model for PB in children with MPP was constructed. The discriminative ability of the model was assessed using receiver operating characteristic (ROC) curve analysis, model calibration was evaluated with calibration curves, and clinical utility was appraised through decision curve analysis. RESULTS: Compared with the non-PB group, the PB group exhibited significantly longer disease duration prior to bronchoscopy, prolonged fever duration, higher fever peaks, higher proportions of patients with a family history of allergy and personal allergy history, and a higher proportion of patients with pleural effusion, as well as significantly elevated levels of white blood cell count, neutrophil percentage, C-reactive protein, procalcitonin, fibrinogen, D-dimer, aspartate aminotransferase, alanine aminotransferase, creatine kinase, lactate dehydrogenase, immunoglobulin A, and interleukin-6, along with a significantly lower lymphocyte percentage (all P<0.05). LASSO regression analysis identified pleural effusion, procalcitonin, D-dimer, and lactate dehydrogenase as major predictive factors for PB occurrence in children with MPP. The nomogram model based on these factors demonstrated good discriminative ability (area under the ROC curve: 0.852 in the training set and 0.830 in the validation set), with satisfactory calibration and clinical benefit. CONCLUSIONS The nomogram prediction model based on pleural effusion, procalcitonin, D-dimer, and lactate dehydrogenase provides effective predictive performance for the occurrence of PB in children with MPP.
Humans ; Pneumonia, Mycoplasma/complications* ; Nomograms ; Male ; Female ; Child ; Child, Preschool ; Retrospective Studies ; Bronchitis/etiology* ; Infant ; ROC Curve ; Adolescent

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Background: Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indices of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. Methods: This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Results: Distribution of the TyAG and TyAG-BMI indices shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. Conclusion This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.

Background: Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indices of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. Methods: This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Results: Distribution of the TyAG and TyAG-BMI indices shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. Conclusion This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.

Objective:To retrospectively analyze the treatment status of tyrosine kinase inhibitors (TKI) in newly diagnosed patients with chronic myeloid leukemia (CML) in China.Methods:Data of chronic phase (CP) and accelerated phase (AP) CML patients diagnosed from January 2006 to December 2022 from 77 centers, ≥18 years old, and receiving initial imatinib, nilotinib, dasatinib or flumatinib-therapy within 6 months after diagnosis in China with complete data were retrospectively interrogated. The choice of initial TKI, current TKI medications, treatment switch and reasons, treatment responses and outcomes as well as the variables associated with them were analyzed.Results:6 893 patients in CP ( n=6 453, 93.6%) or AP ( n=440, 6.4%) receiving initial imatinib ( n=4 906, 71.2%), nilotinib ( n=1 157, 16.8%), dasatinib ( n=298, 4.3%) or flumatinib ( n=532, 7.2%) -therapy. With the median follow-up of 43 ( IQR 22-75) months, 1 581 (22.9%) patients switched TKI due to resistance ( n=1 055, 15.3%), intolerance ( n=248, 3.6%), pursuit of better efficacy ( n=168, 2.4%), economic or other reasons ( n=110, 1.6%). The frequency of switching TKI in AP patients was significantly-higher than that in CP patients (44.1% vs 21.5%, P<0.001), and more AP patients switched TKI due to resistance than CP patients (75.3% vs 66.1%, P=0.011). Multi-variable analyses showed that male, lower HGB concentration and ELTS intermediate/high-risk cohort were associated with lower cytogenetic and molecular responses rate and poor outcomes in CP patients; higher WBC count and initial the second-generation TKI treatment, the higher response rates; Ph + ACA at diagnosis, poor PFS. However, Sokal intermediate/high-risk cohort was only significantly-associated with lower CCyR and MMR rates and the poor PFS. Lower HGB concentration and larger spleen size were significantly-associated with the lower cytogenetic and molecular response rates in AP patients; initial the second-generation TKI treatment, the higher treatment response rates; lower PLT count, higher blasts and Ph + ACA, poorer TFS; Ph + ACA, poorer OS. Conclusion:At present, the vast majority of newly-diagnosed CML-CP or AP patients could benefit from TKI treatment in the long term with the good treatment responses and survival outcomes.