Humoral immunity in hepatitis B virus infection: Rehabilitating the B in HBV
Bibliographic record
Abstract
Insights into the immunopathogenesis of chronic HBV infections are fundamental in the quest for novel treatment approaches aimed at a functional cure. While much is known about the ineffective HBV-specific T-cell responses that characterise persistent HBV replication, B cells have been left largely understudied. However, an important role for humoral immunity during the natural history of HBV infections, as well as after functional cure, has been inadvertently revealed by the occurrence of HBV flares following B cell-depleting treatments. Herein, we review our current understanding of the role of the humoral immune response in chronic HBV, both at the level of HBV-specific antibody production and at the phenotypic and broader functional level of B cells. The recent development of fluorescently labelled HBV proteins has given us unprecedented insights into the phenotype and function of HBsAg- and HBcAg-specific B cells. This should fuel novel research into the mechanisms behind dysfunctional HBsAg-specific and fluctuating, possibly pathogenic, HBcAg-specific B-cell responses in chronic HBV. Finally, novel immunomodulatory treatments that partly target B cells are currently in clinical development, but a detailed assessment of their impact on HBV-specific B-cell responses is lacking. We plead for a rehabilitation of B-cell studies related to both the natural history of HBV and treatment development programmes.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".