Flow Cytometric Quantification of T Cell Proliferation and Division Kinetics in Woodchuck Model of Hepatitis B
Bibliographic record
Abstract
Woodchucks infected with woodchuck hepatitis virus (WHV) represent the closest natural animal model to study the immunopathogenesis of liver injury caused by essentially noncytopathic, highly human specific hepatitis B virus (HBV). The importance of antiviral T cell response in induction of hepatitis and in control of HBV replication has been demonstrated. However, the understanding of how these responses contribute to the development of different immunomorphological forms of liver disease and their outcomes remain elusive. In this study, we established and standardized a flow cytometry assay using peripheral blood mononuclear cells labeled with carboxyfluorescein diacetate succinimidyl ester (CFSE) to assess WHV-specific and mitogen-driven T lymphocyte proliferative responses in woodchucks. The assay is of significantly greater sensitivity than the adenine incorporation assay currently used when applied to measure either WHV-specific T cell responses in acute (P < 0.001) and chronic (P < 0.03) viral hepatitis or those induced by mitogens in both healthy and WHV-infected animals. It also provides a new type of information, not previously available, characterizing the strength of woodchuck T cell proliferative reactivity by measuring cell division rates. The study shows that woodchuck PBMC labeled with CFSE exhibit light scatter and fluorescence profiles compatible to those of human PBMC, allowing quantitation and deconvolution of the flow cytometric data by applying the existing analytical softwares. The availability of this novel assay should facilitate a more precise and comprehensive evaluation of hepadnavirus-specific and generalized T cell responses in experimental WHV hepatitis.
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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 | 0.000 |
| 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 | 0.001 |
| 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".