Correlation between Th17 and nTreg cell frequencies and the stages of progression in chronic hepatitis B
Bibliographic record
Abstract
Several studies have suggested that the balance of T helper 17 (Th17) and natural regulatory T (nTreg) cells in the Th17‑mediated immune response are critical in the pathogenesis of viral hepatitis. The aim of the present study was to examine the role of circulating Th17 and nTreg cells in the disease progression of hepatitis B virus (HBV) infection. A total of 40 patients with chronic HBV (CHB), 27 patients with HBV‑associated cirrhosis, 20 patients with HBV‑associated liver failure and 20 healthy controls were enrolled in the present study. The frequencies of Th17 and nTreg cells in the peripheral blood were examined using flow cytometry. Th17‑associated serum cytokine levels were measured using an enzyme‑linked immunosorbent assay. The results revealed a significantly higher frequency of circulating Th17 cells in the patients with CHB, cirrhosis and liver failure compared, with the normal controls, particularly in the patients with liver failure. The same trend was observed in the serum levels of interleukin (IL)‑17. The frequency of Th17 cells and the serum levels of IL‑17 were positively correlated with the levels of alanine aminotransferase and the prothrombin times. There was a significantly higher frequency of circulating nTreg cells in the patients with CHB, compared with the normal controls. The nTreg cell frequencies were significantly and positively correlated with plasma HBV DNA load, and were negatively correlated with Th17 frequencies in the cohort of patients with HBV. Taken together, the results suggested that Th17 cell‑mediated inflammation is associated with progression from CHB to cirrhosis, and to liver failure. Peripheral Th17 cell frequency and serum levels of IL‑17 may assisting in predicting the severity of liver damage and fibrosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".