Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

AIM: To explore the dynamic expression of high mobility group box 1(HMGB1)in scar tissues after glaucoma drainage valve implantation, and to further reveal the role and possible mechanism of HMGB1 in scarring after glaucoma surgery.METHODS: A total of 60 New Zealand white rabbits were randomly divided into control group(n=20), model group(n=20, silicone implantation under conjunctival sac)and model with drug administration group(n=20, silicone implantation under conjunctival sac combined with 5-fluorouracil injection). The conjunctival tissues were collected at 4 and 8 wk after surgery. HE staining and Masson staining were used to detect the proliferation and distribution of fibroblasts and collagen fibers in conjunctival tissues. Immunohistochemistry was utilized to detect the distribution and changes of HMGB1, transforming growth factor(TGF)-β1, Smad3 and α-smooth muscle actin(SMA)in conjunctival tissues. RT-PCR and Western blot were adopted to detect the mRNA and protein expression of HMGB1, TGF-β1, Smad3 and α-SMA in conjunctival tissues.RESULTS: HE staining and Masson staining showed that the proliferation of inflammatory cells, fibroblasts and collagen fibers in the model group was significantly higher than that in the control group at both 4 and 8 wk. Meanwhile, the proliferation of fibroblasts and collagen fibers in the model with drug administration group was significantly lower than that in the model group. Immunohistochemical staining showed that the expression of HMGB1, TGF-β1, Smad3 and α-SMA protein was observed in the conjunctival tissues of the model group both 4 and 8 wk, with brown and significantly deeper staining of the model group at 8 wk. Meanwhile, the positive staining in the model with drug administration group at both 4 and 8 wk was significantly lower than that in the model group. There was positive correlations between the number of fibroblasts stained with HE and the expression of HMGB1 in the conjunctival tissue of the model group at both 4 and 8 wk(r=0.602, 0.703, all P<0.05). RT-PCR and Western blot revealed that the mRNA and protein expression levels of HMGB1, TGF-β1, Smad3 and α-SMA in the model group were significantly higher than those in the control group at both 4 and 8 wk(all P<0.05). Meanwhile, the mRNA and protein expression levels of HMGB1, TGF-β1, Smad3 and α-SMA in the model with drug administration group were significantly lower than those in the model group(all P<0.05). There was positive correlations between mRNA expressions of HMGB1 and TGF-β1, Smad3 in the model group and the model with drug administration group(all P<0.05).CONCLUSION: The expression of HMGB1 increased at a time-dependent manner after glaucoma valve implantation. HMGB1 acts an indispensable role in the initiation and progression of scar formation after glaucoma surgery, which may be involved in the regulation of TGF-β/Smad signaling pathway.

Objective:To analyze the correlation between peripheral blood lymphocyte subsets, especially B cells, and the relapse of autoimmune encephalitis (AE).Methods:A retrospective analysis was conducted on patients with AE who were diagnosed and treated in Peking Union Medical College Hospital from January 2012 to January 2023. The clinical data including gender, age and changes in related indicators of CD19 +B cells, CD16/56 +NK cells, CD3 +T cells, CD4 +T cells, CD8 +T cells, IgG, IgA, and IgM before and after recurrence were analyzed.Binary Logistic regression analysis was applied to the study of correlation between AE recurrence and gender, age, CD19 +B cells, CD16/56 +NK cells, CD3 +T cells, CD4 +T cells, CD8 +T cells, IgG, IgA and IgM. The receiver operating characteristic (ROC) curves of the cells that affect AE recurrence (CD19 +B cells, CD16/56 +NK cells, CD3 +T cells, CD4 +T cells and CD8 +T cells) were plotted separately. Results:A total of 198 eligible AE patients were included, including 98 males and 100 females, aged (39.52±17.91) years. Among these patients, 78 cases had relapses, with a recurrence rate of 39.4%. The results of Logistic regression analysis showed that CD19 +B cells ( B=0.006, P<0.001), CD16/56 +NK cells ( B=0.004, P<0.05), CD3 +T cells ( B=-0.011, P<0.05), CD4 +T cells ( B=0.014, P<0.05) and CD8 +T cells ( B=0.010, P<0.05) were highly correlated with the relapse of AE. ROC curve analysis showed that CD19 +B cells (area under the curve: 0.833, P<0.001, critical value: 73.5/μl; sensitivity: 69.2%, specificity: 86.7%), CD3 +T cells (area under the curve: 0.784, P<0.001), CD4 +T cells (area under the curve: 0.808, P<0.001), and CD8 +T cells (area under the curve: 0.742, P<0.001) all had a certain predictive value for AE relapse. Among all the indicators, the area under the curve of CD19 +B cells was the largest, which had a higher value in predicting AE recurrence. Conclusion:The increase in peripheral blood CD19 +B cells has high predictive value for the relapse of AE.

A 65-year-old male patient was admitted for recurrent lymph node enlargement for 5 years and elevated creatinine for 6 months. This patient was diagnosed with angioimmunoblastic T-cell lymphoma 5 years ago and underwent multiple lines of anti-tumor therapy, including cytotoxic chemotherapy; epigenetic modifying drugs such as chidamide and azacitidine; the immunomodulator lenalidomide; and targeted therapy such as rituximab, a CD20-targeting antibody, and brentuximab vedotin, which targets CD30. Although the tumor was considered stable, multiple virus activation (including BK virus, JC virus, and cytomegalovirus) accompanied by the corresponding organ damage (polyomavirus nephropathy, cytomegalovirus retinitis, and progressive multifocal leukoencephalopathy) occurred during anti-tumor treatment. Anti-tumor therapy was suspended and ganciclovir was used. The serum viral load decreased and organ functions were stabilized. The purpose of this report was to raise clinicians′ awareness of opportunistic virus reactivation during anti-tumor treatment.

Objective to explore the use of performance management as a lever in public hospitals to achieve quality improvement,efficiency enhancement,and high-quality development under the dual influences of na-tional civil service examination and Diagnosis-Related Groups(DRGs)payment policy reform.Methods A questionnaire survey was conducted to summarize the current situation and problems of performance assessment in public hospitals in China.Based on the identified problems,an upgraded performance management system was proposed,and key indicators were selected through a case study in a specific hospital.Results An empirical study in a specific hospital demonstrated the positive effects of the upgraded performance management system on hospital management improvement.Conclusion Public hospitals should establish a long-term mechanism for performance management,focusing on organizational positioning,indicator design,management levers,and talent development,to continuously support high-quality development.