Case report: Experience and insights on the treatment of two cases of cryptococcal meningitis during the later stages of the COVID-19 pandemic.

In the late stages of the COVID-19 pandemic, there's an increasing trend in opportunistic infections, including bacterial and fungal infections. This study discusses the treatment process of two cases of cryptococcal meningitis during the COVID-19 pandemic. It highlights the importance of laboratory testing for these co-infections and stresses the need for vigilance, early diagnosis, and proactive treatment to improve patient outcomes in the post-pandemic era.

Case study of colorectal endometriosis treated with endoscopic submucosal excavation.

Colorectal endometriosis (CEM) is a rare and complicated form of deep invasive endometriosis. Its treatment methods include drug therapy and surgery. However, it is often difficult to alleviate symptoms and address problems, such as infertility, using drug treatment alone. Surgical intervention provides a histologic diagnosis, allows assessment of pelvic cysts or masses with features concerning for malignancy, and reduces pain by destroying the endometriotic implants. We consider surgery in women with the following: Persistent pain despite medical therapy; Contraindications to or refusal of medical therapy; Need for a tissue diagnosis of endometriosis; Exclusion of malignancy in an adnexal mass; Obstruction of the bowel or urinary tract. But there is no consensus about the surgical methods. With the rapid development of gastroenteroscopy technology in recent years, many local gastrointestinal tumors that previously required surgical resection can now be removed by endoscopic surgery. Herein, we report one case of CEM treated by endoscopic submucosal excavation (ESE) to provide a new treatment option for the radical resection of single CEM.

Artificial intelligence in endoscopic ultrasonography: risk stratification of gastric gastrointestinal stromal tumors.

Background: Previous studies have identified useful endoscopic ultrasonography (EUS) features to predict the malignant potential of gastrointestinal stromal tumors (GISTs). However, the results of the studies were not consistent. Artificial intelligence (AI) has shown promising results in medicine. Objectives: We aimed to build a risk stratification EUS-AI model to predict the malignancy potential of GISTs. Design: This was a retrospective study with external validation. Methods: We developed two models using EUS images from two hospitals to predict the GIST risk category. Model 1 was the four-category risk EUS-AI model, and Model 2 was the two-category risk EUS-AI model. The diagnostic performance of the models was validated with external cohorts. Results: A total of 1320 images (880 were very low-risk, 269 were low-risk, 68 were intermediate-risk, and 103 were high-risk) were finally chosen for building the models and test sets, and a total of 656 images (211 were very low-risk, 266 were low-risk, 88 were intermediate-risk, and 91 were high-risk) were chosen for external validation. The overall accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for the four-category risk EUS-AI model in the external validation sets by tumor were 74.50%, 55.00%, 79.05%, 53.49%, and 81.63%, respectively. The accuracy, sensitivity, specificity, PPV, and NPV for the two-category risk EUS-AI model for the prediction of very low-risk GISTs in the external validation sets by tumor were 86.25%, 94.44%, 79.55%, 79.07%, and 94.59%, respectively. Conclusion: We developed a EUS-AI model for the risk stratification of GISTs with promising results, which may complement current clinical practice in the management of GISTs. Registration: The study has been registered in the Chinese Clinical Trial Registry (No. ChiCTR2100051191).

Artificial Intelligence in the Prediction of Gastrointestinal Stromal Tumors on Endoscopic Ultrasonography Images: Development, Validation and Comparison with Endosonographers.

Background/Aims: The accuracy of endosonographers in diagnosing gastric subepithelial lesions (SELs) using endoscopic ultrasonography (EUS) is influenced by experience and subjectivity. Artificial intelligence (AI) has achieved remarkable development in this field. This study aimed to develop an AI-based EUS diagnostic model for the diagnosis of SELs, and evaluated its efficacy with external validation. Methods: We developed the EUS-AI model with ResNeSt50 using EUS images from two hospitals to predict the histopathology of the gastric SELs originating from muscularis propria. The diagnostic performance of the model was also validated using EUS images obtained from four other hospitals. Results: A total of 2,057 images from 367 patients (375 SELs) were chosen to build the models, and 914 images from 106 patients (108 SELs) were chosen for external validation. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the model for differentiating gastrointestinal stromal tumors (GISTs) and non-GISTs in the external validation sets by images were 82.01%, 68.22%, 86.77%, 59.86%, and 78.12%, respectively. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy in the external validation set by tumors were 83.75%, 71.43%, 89.33%, 60.61%, and 80.56%, respectively. The EUS-AI model showed better performance (especially specificity) than some endosonographers. The model helped improve the sensitivity, specificity, and accuracy of certain endosonographers. Conclusions: We developed an EUS-AI model to classify gastric SELs originating from muscularis propria into GISTs and non-GISTs with good accuracy. The model may help improve the diagnostic performance of endosonographers. Further work is required to develop a multi-modal EUS-AI system.

Effect of the transdifferentiation of BECs into myofibroblasts on the pathogenesis of secondary cholestatic hepatic fibrosis.

The present study investigated the effect of the transdifferentiation of bile duct epithelial cells (BECs) into myofibroblasts on the pathogenesis of secondary cholestatic hepatic fibrosis and examined the underlying mechanisms. A total of 60 male rats with hepatic fibrosis were randomly divided into two groups: A secondary cholestatic hepatic fibrosis model group induced by ligation of the bile duct (BDL) and a sham group, which only underwent segregation of the choledochus. Rats in the BDL group were dynamically observed after week 1, 2, 3 and 4 post-BDL, and the remaining rats were sacrificed after week 5 to determine histological changes and hydroxyproline content. The cellular co-localization of cytokeratin (CK)7/α-smooth muscle actin (SMA) or α-SMA/desmin was detected by immunofluorescence staining and laser confocal microscopy, while the protein expression levels of CK7, α-SMA and desmin were determined by western blot analysis. Sirius red staining was also performed and quantified. The results revealed a significant correlation between the protein expression of CK7 and α-SMA (r=0.9692, P<0.01). Furthermore, a predominant correlation between the number of cells stained for CK7/α-SMA and collagen deposition in liver tissues was identified, while the correlation of cells with co-localized α-SMA and desmin was less pronounced. The transdifferentiation of BECs into myofibroblasts may be a key pathological factor in secondary cholestatic hepatic fibrosis formation.

[Mechanism of hepatocytes transdifferentiation to bile duct epithelial cells and intervention of huangqi decoction].

OBJECTIVE: To investigate the mechanism of hepatocytes transdifferentiation to bile duct epithelial cells (BECs) and intervention of Huangqi decoction (HQD) on hepatic fibrosis formation in rats with secondary cholestasis. METHODS: Seventy-five SD male rats were made into cholestatic hepatic fibrosis model animals by bile duct ligation, and randomized into the control group (n = 50) and the HQD group (n = 15). Starting from one week after modeling, they were administered orally with saline and HQD respectively for four weeks. Besides, a sham-operated group was set up with 10 rats operated by choledochus segregating only and administered after then with saline. Rats were killed in batches at different time points, i.e. each five from the control group and sham-operated group at the end of the 1st week, five from the control group for each time at the end of the 2nd, 3rd and 4th week, and all the remaining rats at the end of the 5th week. Their liver tissues were taken for histological change examination, content of hydroxyproline (Hyp) determination; protein expression of BECs marker cytokeratin 7 (CK7) and the hepatocyte specific antigen HepPar detection by Western blot, and CK7-Hep Par co-localization by laser confocal microscopy. Then IPP software was used to analyze Sirius red stained positive areas of CK7 and Hep Par, as well as the average IOD of CK7/Hep Par co-localization. RESULTS: Hepatocytes in hepatic tissues (Hep Par positive cell) in the model rats decreased gradually along was time went by after modeling (Sham > M1w > M2w > M3w > M4w > M5w), which was in parallel with the increase of BECs (CK7 positive cells), degree of fibrosis, Hyp content and CK7 protein expression. Increasing of co-localized positive cells of CK7/Hep Par began at 1 week and reached the peak 3 weeks after modeling, then it decreased gradually. The Hep Par protein expression was negatively correlated with that of CK7; the Hep Par positive cell expression was negatively correlated with CK7 positive cell expression and collagen deposition; while the CK7 positive cell expression was positively correlated with the collagen deposition in the liver tissue. Compared with the model control group, the mortality, CK7/Hep Par co-localized positive cells, fibrosis degree, Hyp content and CK7 protein expression were lesser obviously (P < 0.01), while Hep Par positive cell and protein expressions were higher significantly in the HQD group. CONCLUSIONS: Hepatocytes transdifferentiation to BECs might be a key pathological element for secondary cholestatic hepatic fibrosis formation; the restraining action of HQD is possibly a major action mechanism of HQD for effectively intervening and treating secondary cholestasis hepatic fibrosis.

[Huangqi decoction inhibits cholangiocyte proliferation and transdifferentiation in cholestatic liver fibrosis induced by BDL in rats].

OBJECTIVE: To elucidate the antifibrotic mechanism of Huangqi decoction in rats with BDL-induced cholestatic liver fibrosis. METHODS: Liver fibrosis model was induced by ligating the common bile duct (BDL) in rats. Sham-operation was performed in control rats. The BDL rats were randomly divided into two groups: the BDL group and the Huangqi decoction group. Huanqi decoction was given intragastrically for 4 weeks. At the end of the fifth week after BDL, animals were sacrificed. RESULTS: Compared with the sham control group, mortality rate in BDL group was 33.3% and incidence rate of ascites was 90%, and hepatic function was abnormal in most of the rats in BDL group. The number of Hepatocytes was decreased and the number of cholangiocytes significantly increased in BDL group. In addition, Hyp content of liver tissue and protein expression of CK 7 and a-SMA were significantly increased. Immunostaining indicated that CK 7 and a-SMA were co-localized in BDL group. These changes were markedly suppressed by the Huangqi decoction. CONCLUSIONS: These observations suggest that Huangqi decoction can inhibit cholangiocyte proliferation and cholangiocyte transdifferentiation.