Randomized trial of autologous bone marrow mesenchymal stem cells transplantation for hepatitis <scp>B</scp> virus cirrhosis: Regulation of <scp>T</scp>reg/<scp>T</scp>h17 cells
Bibliographic record
Abstract
BACKGROUND AND AIM: Liver cirrhosis is one of the major consequences of hepatitis B virus (HBV) infection, and transplantation of autologous bone marrow mesenchymal stem cells (ABMSCs) is one of promising therapies for patients with HBV-related liver cirrhosis (HBV-LC). However, the mechanism is unclear. The aim of the current study was to explore the role of Treg/Th17 cells in ABMSCs transplantation in patients with HBV-LC. METHODS: In this prospective study, 56 patients were enrolled and randomly assigned to transplantation group and control group. After 24-week follow-up, 39 patients completed the study (20 cases in transplantation group and 19 cases in control group). The Model for End-Stage Liver Disease scores, liver function, changes of Treg/Th17 cells, as well as related transcription factors and serum cytokines, were determined. RESULTS: Although patients in both groups showed significant improvement after Entecavir treatment, ABMSC transplantation further improved patients' liver function. Moreover, there was a significant increase in Treg cells and a marked decrease in Th17 cells in the transplantation group compared with control, leading to an increased Treg/Th17 ratio. Furthermore, mRNA levels of Treg-related transcription factor (Foxp3) and Th17-related transcription factor (RORγt) were increased and decreased, respectively. In addition, serum transforming growth factor-β levels were significantly higher at early weeks of transplantation, while serum levels of interleukin-17, tumor necrosis factor-α, and interleukin-6 were significantly lower in patients in the transplantation group compared with control. CONCLUSION: ABMSCs transplantation was effective in improving liver function in patients with HBV-LC, which was mediated, at least in part, through the regulation of Treg/Th17 cell balance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".