Bibliographic record
Abstract
The treatment of hemophilia, which has undergone many transformative changes over the past 60 years, is poised for yet another disruptive change: the use of gene therapy to produce functional cures in some persons with hemophilia A or B. The path toward achieving subnormal to normal levels of factor VIII and factor IX activity has not been straightforward and is littered with failures over these past 25 years. Through setbacks and iteration, adeno-associated virus (AAV) proved to be a useful vector to carry the factor VIII and IX transgenes; once cassettes were optimized and dose escalation proceeded, therapeutic levels of clotting factors were achieved by several groups. Because these transgenes produce fully active proteins, breakthrough bleeding and the use of exogenous clotting factors have nearly been eliminated for most clinical trial participants when they express a sufficient amount of protein. These first-generation gene therapies, which have initiated regulatory review, will decrease or eliminate the burden of hemophilia for many of the patients who are eligible to receive them. However, many are ineligible, including those who are seropositive or cross-reactive to multiple AAV serotypes, children, those with comorbid conditions, and those who live in countries where even the most basic plasma-derived clotting factors are not reliably available. Thus, although the first-generation gene therapies will have an important impact on the burden of hemophilia, many questions remain to be answered regarding safety, durability, and reliability as this technology advance progresses toward individuals worldwide with hemophilia.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| 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".