Development of immunoglobulin variable heavy chain gene consensus probes with conjugated 3′ minor groove binder groups for monitoring minimal residual disease in childhood acute lymphoblastic leukaemia
Bibliographic record
Abstract
AIMS: To develop immunoglobulin heavy chain variable (VH) gene probes that are shorter and more flexible in position for monitoring minimal residual disease (MRD) in childhood leukaemia (ALL), using minor groove binder (MGB) technology. METHODS: All VH germline sequences registered in the database were aligned and the consensus regions were determined. The reliability of the MGB probes was compared with non-MGB probes in all 24 cases of ALL. RESULTS: Ten MGB probes (16 to 18 mers) were designed that enabled all the germline sequences on the database to be analysed, whereas the conventional non-MGB probes (21 to 27 mers) did not allow the analysis of four of the VH1 and five of the VH3 germline sequences. The sequencing results in five of the 24 cases of ALL were not matched to the non-MGB probes. CONCLUSIONS: MGB technology allows shorter probes to be designed, enabling MRD to be detected in childhood ALL. This would provide a considerable reduction in cost for a large MRD study.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".