Bibliographic record
Abstract
Potential conflict of interest: Nothing to report. B cells are a diverse and multifaceted cell population comprising both regulatory and effector cells. This diversity could allow B cells to be both friend and foe in autoimmune hepatitis (AIH). Similar to CD4+ T cells, which can be either T‐helper or regulatory T cells, B‐cell subpopulations can be either pathologic (e.g., presenting autoantigens) or protective (e.g., interleukin‐10 secreting B cells). In our recent article, we showed that B‐cell depletion in a mouse model leads to remission of AIH,1 a result also observed in patients.2 These results may seem to conflict with the data of Liu et al.,4 in which a subset of regulatory B cells (interleukin‐10‐dependent CD11b+ B cells) inhibited pathogenic CD4 T cells in a different model of AIH. In their model, the absence of B cells exacerbates the disease and regulatory B cells improve it. This apparent discrepancy may stem, as discussed in their article,4 from the S100 experimental AIH model that is based on complete Freund adjuvant administration, a model in which the pathogenesis is considerably different from that of AIH patients or from the type 2 AIH model. While a role of regulatory B cells in our murine model and AIH patients cannot be excluded, clinical and laboratory evidence suggests a predominant role for a pathological subset(s) of B cells. As pointed out, sustained B‐cell depletion raises concerns as to increased risk of infections and deleterious side effects. Our study provided preclinical data on the efficacy and mechanism of B‐cell depletion in AIH and did not aim to address safety issues. However, the data suggest that rituximab is well tolerated in AIH patients,2 and the rate of severe infection during multiple courses of rituximab is between four and six cases per 100 patients, comparable to that of anti‐tumor necrosis factor‐α therapy.5 Rituximab is used to treat various conditions and has an established safety profile and a treatment regimen that minimizes serious side effects. Because B‐cell depletion seems to effectively induce remission of AIH, it would be interesting to develop new therapies able to target pathological, while sparing regulatory, B‐cell subsets to see if treatment efficacy could be improved and side effects minimized.
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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 | 0.002 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.163 | 0.083 |
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".