Defective antibody production in double-strand DNA breakage syndromes: insights and implications
Bibliographic record
Abstract
DNA double-strand breakage (DSB) syndrome are rare monogenic inborn errors of immunity with a vast spectrum of manifestations. In addition to a high predisposition to malignancies, these patients are also at risk of recurrent, severe, or opportunistic infections. Therefore, monitoring of immunoglobulin levels and responses to vaccination, as well as interventions such as immunoglobulin replacement therapy should be considered to improve the patients’ outcomes. As DNA double-strand breakage repair pathways have a great impact on lymphocyte development through involvement in the generation of B and T cell receptors, disruption in one of their components may lead to genomic instability, aberrant B-cell receptor (BCR)/T-cell receptor (TCR) development, impaired B cell lymphocyte development and antibody production. The aim of this review is to describe the most common of DBSs, such as ataxia telangiectasia (AT), AT-like disorder (ATLD), Nijmegen breakage syndrome (NBS), Nijmegen breakage syndrome-like disorder (NBSLD), Bloom syndrome (BS), Fanconi anemia (FA) and some others with a focus on the role of DNA repair proteins in the development of humoral immunity. We also describe the immunoglobulin profile, recommendations for diagnosis, screening, and interventions for the ideal management of affected patients.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".