Bibliographic record
Abstract
INTRODUCTION: Haemophilia therapy has evolved from rudimentary transfusion-based approaches to an unprecedented level of innovation with glimmers of functional cure brought by gene therapy. After decades of misfires, gene therapy has normalized factor (F)VIII and factor (F)IX levels in some individuals in the long term. Several clinical programmes testing adeno-associated viral (AAV) vector gene therapy are approaching completion with imminent regulatory approvals. DISCUSSION: Phase 3 studies along with multiyear follow-up in earlier phase investigations raised questions about efficacy as well as short- and long-term safety, prompting a reappraisal of AAV vector gene therapy. Liver toxicities, albeit mostly low-grade, occur in the first year in at least some individuals in all haemophilia A and B trials and are poorly understood. Extreme variability and unpredictability of outcome, as well as a slow decline in factor expression (seemingly unique to FVIII gene therapy), are vexing because immune responses to AAV vectors preclude repeat dosing, which could increase suboptimal or restore declining expression, while overexpression may result in phenotoxicity. The long-term safety will need lifelong monitoring because AAV vectors, contrary to conventional wisdom, integrate into chromosomes at the rate that calls for vigilance. CONCLUSIONS: AAV transduction and transgene expression engage the host immune system, cellular DNA processing, transcription and translation machineries in ways that have been only cursorily studied in the clinic. Delineating those mechanisms will be key to finding mitigants and solutions to the remaining problems, and including individuals who cannot avail of gene therapy at this time.
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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.041 | 0.021 |
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".