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

BACKGROUND:The phosphatidylinositol 3-kinase/protein kinase(PI3K/AKT)signaling pathway plays a pivotal role in regulating osteoclast activation,which is essential for maintaining bone homeostasis.Bone destruction in osteoarticular tuberculosis is caused by aberrant osteoclastogenesis induced by Mycobacterium tuberculosis infection.However,the role of the PI3K signaling pathway in Mycobacterium tuberculosis-induced aberrant osteoclastogenesis remains unclear. OBJECTIVE:To investigate the effects and mechanisms of the PI3K/AKT signaling pathway inhibitor BYL-719 on aberrant osteoclastogenesis induced by Mycobacterium tuberculosis. METHODS:RAW264.7 cells were infected with bovine Mycobacterium tuberculosis bacillus calmette-cuerin vaccine,and Ag85B was used for cellular immunofluorescence staining.The cell counting kit-8 assay was employed to determine the safe concentration of BYL-719.There were four groups in the experiment:blank control group,BYL-719 group,BCG group,and BCG+BYL-719 group.Under the induction of receptor activator of nuclear factor kappa-B ligand,the effects of BYL-719 on post-infection osteoclast differentiation and fusion were explored through tartrate-resistant acid phosphatase staining and phalloidin staining.RT-PCR and western blot were used to detect the expression of osteoclast-related genes and proteins,and further investigate the mechanism of action. RESULTS AND CONCLUSION:Immunofluorescence staining showed that RAW264.7 cells phagocytosed Mycobacterium tuberculosis.Cell counting kit-8 data indicated that 40 nmol/L BYL-719 was non-toxic to cells.Tartrate-resistant acid phosphatase staining and phalloidin staining showed that BYL-719 inhibited the generation and fusion ability of osteoclasts following infection.RT-PCR and western blot results also indicated that BYL-719 suppressed the upregulation of osteoclast-specific genes(including c-Fos,NFATc1,matrix metalloproteinase 9,and CtsK)induced by Mycobacterium tuberculosis infection(P<0.05).Western blot and immunofluorescence staining revealed that BYL-719 inhibited excessive osteoclast differentiation induced by Mycobacterium tuberculosis by downregulating the expression of IκBα-p65.To conclude,BYL-719 inhibits aberrant osteoclastogenesis induced by Mycobacterium tuberculosis through the downregulation of IκBα/p65.Therefore,the IκBα/p65 signaling pathway is a potential therapeutic target for osteoarticular tuberculosis,and BYL-719 holds potential value for the preventing and amelioration of bone destruction in osteoarticular tuberculosis.BYL-719 has the potential to prevent and ameliorate bone destruction in osteoarticular tuberculosis.

Objective:To explore the application value of diaphragmatic thickening fraction (DTF) and lung ultrasound score (LUS) in predicting the weaning outcome of elderly patients with acute respiratory distress syndrome (ARDS) under mechanical ventilation, and to analyze their correlation, thereby providing evidence for clinical decision-making.Methods:A retrospective analysis was conducted on elderly ARDS patients admitted to the ICU of the First Affiliated Hospital of Jinzhou Medical University from January 2020 to December 2023. The inclusion criteria included age > 60 years, endotracheal intubation, mechanical ventilation time >24 h, and a diagnosis of ARDS based on the Berlin definition. Exclusion criteria included neuromuscular diseases, spinal cord injury, post-thoracoabdominal surgery, thoracic or tracheal deformity, and mid-course tracheostomy conversion. Patients were divided into a success group and a failure group based on weaning outcomes. Demographic data, Acute Physiology and Chronic Health EvaluationⅡ (APACHEⅡ) scores, Sequential Organ Failure Assessment (SOFA) scores, oxygenation index at ICU admission, and pre-extubation DTF, LUS, and oxygenation index were recorded. Binary logistic regression analysis was used to identify independent risk factors affecting weaning outcomes. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of DTF and LUS for weaning outcomes. Pearson correlation analysis was conducted to examine the relationship between DTF and LUS.Results:A total of 317 patients were included, including 212 in the success group and 105 in the failure group. There were no statistically significant differences in gender, age, APACHEⅡ score, SOFA score, etc., between the two groups (all P>0.05). Pre-weaning LUS was higher in the failure group than in the success group [(17.26±3.04) vs. (13.69±4.06), P<0.001], and the DTF was significantly lower than that of the successful group [(27.83%±6.37%) vs. (40.15%±6.49%), P<0.001]. Binary logistic regression identified LUS and DTF as independent influencing factors for weaning outcomes (both P<0.05). ROC analysis revealed that LUS predicted weaning failure with an AUC of 0.748 (95% CI: 0.695-0.801, P<0.001), sensitivity of 83.81% and specificity of 56.60%. DTF predicted weaning success with an AUC of 0.935 (95% CI: 0.909-0.961, P<0.001), sensitivity of 83.02% and specificity of 89.52%. A negative correlation was observed between LUS and DTF before weaning ( r=-0.385, P<0.001). Conclusions:Both DTF and LUS are effective indicators for assessing weaning outcomes in elderly ARDS patients, offering complementary clinical insights. Higher LUS reflects more severe pulmonary pathology and increased weaning risk, while lower DTF indicates impaired diaphragmatic function and reduced likelihood of successful extubation. Integration of these parameters provides a comprehensive foundation for clinical decision-making.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

This study was aimed at establishing a sensitive and specific sandwich ELISA detection method for Brucella.We screened monoclonal capture antibodies and detection antibodies for Brucella detection,and optimized and determined the opti-mal antibody coating time and concentration,as well as the optimal blocking solution,blocking time,and yin-yang critical val-ue.The specificity of this method was verified by examination of other bacteria prone to cross-reacting with Brucella.The sen-sitivity of the method was verified by detection of a gradient dilution of inactivated Brucella.Moreover,the sandwich ELISA detection results were compared with test tube agglutination and qPCR results.The selected capture antibody was 4A12,and the selected detection antibody was 6C12.Experimental analysis indicated that the optimal coating concentration for the 4A12 capture antibody was 5 μg/mL,and the optimal dilution ratio for the 6C12 detection antibody was 1∶2000.The optimal coating conditions were overnight at 4℃,and blocking with 5％skim milk powder for 2 hours.The established double antibody sand-wich ELISA method reacted with only Brucella but not other bacteria,thus demonstrating the method's good specificity.Inac-tivated Brucella solution was still detectable after dilution to 1 × 105 CFU/mL,thus demonstrating the method's good sensitiv-ity.The intra-and inter batch coefficients of variation were both below 10％,thus indicating the method's good repeatability.Thus,this study successfully established a dual antibody sandwich ELISA method for Brucella detection,which has good spe-cificity and sensitivity,and might provide an effective approach for the precise diagnosis and effective prevention and control of brucellosis.

This study was aimed at establishing a sensitive and specific sandwich ELISA detection method for Brucella.We screened monoclonal capture antibodies and detection antibodies for Brucella detection,and optimized and determined the opti-mal antibody coating time and concentration,as well as the optimal blocking solution,blocking time,and yin-yang critical val-ue.The specificity of this method was verified by examination of other bacteria prone to cross-reacting with Brucella.The sen-sitivity of the method was verified by detection of a gradient dilution of inactivated Brucella.Moreover,the sandwich ELISA detection results were compared with test tube agglutination and qPCR results.The selected capture antibody was 4A12,and the selected detection antibody was 6C12.Experimental analysis indicated that the optimal coating concentration for the 4A12 capture antibody was 5 μg/mL,and the optimal dilution ratio for the 6C12 detection antibody was 1∶2000.The optimal coating conditions were overnight at 4℃,and blocking with 5％skim milk powder for 2 hours.The established double antibody sand-wich ELISA method reacted with only Brucella but not other bacteria,thus demonstrating the method's good specificity.Inac-tivated Brucella solution was still detectable after dilution to 1 × 105 CFU/mL,thus demonstrating the method's good sensitiv-ity.The intra-and inter batch coefficients of variation were both below 10％,thus indicating the method's good repeatability.Thus,this study successfully established a dual antibody sandwich ELISA method for Brucella detection,which has good spe-cificity and sensitivity,and might provide an effective approach for the precise diagnosis and effective prevention and control of brucellosis.

Objective:To investigate the value of biparametric-MRI (bpMRI) based peritumoral radiomics for preoperative prediction of extraprostatic extension (EPE) in prostate cancer (PCa).Methods:In this cross-sectional study, consecutive bpMRI of patients undergoing prostatectomy for PCa were retrospectively collected from the First Medical Center (center 1) and the Third Medical Center (center 2) of Chinese PLA General Hospital. A total of 274 patients were finally enrolled. Patients at center 1 from January 2020 to December 2022 were randomly divided into a training set (149 cases) and an internal validation set (63 cases) by stratified random sampling. Patients at center 2 from January 2023 to March 2024 were assigned to the external test set (62 cases). Patients were categorized into EPE-positive group and EPE-negative group according to pathological assessment postoperatively. In the training set, there were 49 cases in EPE-positive group and 100 cases in EPE-negative group. In the internal validation set, there were 26 cases in EPE-positive group and 37 cases in EPE-negative group. In the external test set, there were 22 cases in EPE-positive group and 40 cases in EPE-negative group. Axial T 2WI and apparent diffusion coefficient (ADC) images were manually annotated to obtain index lesion regions of interest (ROIs), with the peritumoral ROIs subsequently delineated by semi-automatic segmentation technique. Radiomics features were extracted from intra-tumoral, peri-tumoral, and intra-tumoral plus peri-tumoral ROIs. The training set data was employed to select and optimize features to build the radiomics models. The logistic regression analysis was used to develop radiomics, clinical, and integrated models. The predictive performance was assessed by the area under the receiver operating characteristic curve (AUC) in the external test set, and compared by the DeLong test. The sensitivity and specificity were compared by the exact McNemar test. Results:In the external test set, the peri-tumoral radiomics model based on bpMRI showed the highest performance in evaluating EPE, with an AUC of 0.739 (95% CI 0.611-0.842), which was identified as the optimal radiomics model. EPE grade ( OR=6.151, 95% CI 3.371-11.226, P<0.001) was incorporated into the clinical model, with an AUC of 0.780 (95% CI 0.657-0.875) in the external test set. The integrated model had an AUC of 0.817 (95% CI 0.698-0.904) in the external test set. There was no statistically significant difference in comparisons of AUCs among the three models (all P>0.05). The sensitivity of the integrated model (68.2%) showed no significant difference from those of the clinical model and the optimal radiomics model (77.3% and 86.4%, respectively; P=0.500 and P=0.289). However, the specificity of the integrated model (85.0%) was significantly higher than those of the clinical model (67.5%, P=0.016) and the optimal radiomics model (50.0%, P<0.001). Conclusion:A bpMRI-based peritumoral radiomics integrating clinical model demonstrates high performance for preoperative prediction of EPE in PCa.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

Acute Stanford type A aortic dissection has the characteristics of acute onset, severe condition and high mortality. Once making a definite diagnosis, surgical treatment is needed as soon as possible. It is difficult for cardiac surgeons to treat the acute aortic dissection involving the aortic sinus, which is an important risk factor for death. Improving the surgical treatment for the aortic sinus can be a key to improving the prognosis. In this review, we will introduce the modified sandwich technique for acute Stanford type A aortic dissection and the prognosis, and summarize the experiences of different modified sandwich techniques. However, there is still no unified standardized technique in aortic root repair, and there is a lack of large studies with long-term follow-up, so it is necessary to further improve the aortic root repair techniques.

Objective:To investigate the correlation between diaphragmatic-rapid shallow breathing index (D-RSBI) and lung ultrasound score (LUS) in elderly patients with mechanical ventilation and its predictive value for weaning results.Methods:A retrospective study was conducted. The clinical data of elderly patients (age > 60 years old) with invasive positive pressure ventilation (IPPV) admitted to the department of intensive care unit (ICU) of the First Affiliated Hospital of Jinzhou Medical University from January 2021 to June 2022 were enrolled. According to the outcome of withdrawal, the patients were divided into successful and failed groups. The differences in gender, age, acute physiology and chronic health evaluation Ⅱ (APACHEⅡ), D-RSBI and LUS before weaning and extubation were compared between the two groups. Pearson correlation was used to analyze the correlation between D-RSBI and LUS. The predictive value of D-RSBI and LUS on weaning results of elderly patients with IPPV was analyzed by receiver operator characteristic curve (ROC curve).Results:A total of 398 elderly patients with IPPV were enrolled, including 300 successful weaning patients and 98 failed weaning patients. There were no significant differences in gender and age between the failed group and successful group [male: 55.1% (54/98) vs. 59.0% (177/300), age (years old): 67.02±5.03 vs. 66.96±4.99, both P > 0.05]. APACHEⅡ score in the failed group was significantly higher than that in the successful group (17.09±3.30 vs. 16.06±3.81, P < 0.05), and the D-RSBI and LUS score before extubation were significantly higher than those in the successful group [D-RSBI (time·min -1·mm -1): 2.19±0.33 vs. 1.60±0.22, LUS: 17.30±3.04 vs. 11.97±3.20, both P < 0.01]. All patients showed a significant positive correlation between D-RSBI and LUS score ( r = 0.406, P = 0.000). ROC curve analysis showed that the area under the curve (AUC) of D-RSBI for predicting weaning outcomes in elderly IPPV patients was 0.920, with a 95% confidence interval (95% CI) of 0.881-0.958 and P = 0.000. When the cut-off value was 1.85 times·min -1·mm -1, the sensitivity was 88.7% and the specificity was 86.7%. The AUC of LUS score for predicting weaning outcome in elderly IPPV patients was 0.875, with a 95% CI of 0.839-0.912 and P = 0.000. When the cut-off value was 14.50, the sensitivity was 75.7% and the specificity was 84.7%. Conclusion:There is a significant correlation between D-RSBI and LUS score in elderly mechanically ventilated patients, both of them can predict weaning outcome in elderly patients with mechanical ventilation.