Promotional etiology for common childhood acute lymphoblastic leukemia: The infective lymphoid recovery hypothesis
Bibliographic record
Abstract
This paper speculates on the role of infection in modifying a young child's risk of promoting precursor B-cell acute lymphoblastic leukemia (ALL). It is suggested that the heat shock instigated by infections, particularly in infancy, stimulates Th1 pro-inflammatory cytokines and an apoptosis-inhibitory environment. This infective stress also increases the number of cooperating oncogenic mutations in pre-leukemic cells, especially if the primary adaptive immune response is delayed. The glucocorticoid release that follows leads to acute thymic involution, a decline in antitumor immunity, and maturation arrest of B-lymphocytes. The infective lymphoid recovery hypothesis addresses an apparent contradiction-that a non-hygienic environment primes the adaptive immune response and is protective against childhood ALL, while multiple infections occurring later increase the risk of childhood ALL. In affluent (compared to less-affluent) societies, the characteristic ALL incidence peak in early childhood, and the shortened time to diagnosis, arise from surviving recurrent infections and the accumulated loss and recovery of lymphoid tissue. Evidence supporting the hypothesis, such as the role of lymphoid tissue reconstitution cytokines that stimulate proliferation stress on B-cell progenitors, comes from the study of children with congenital syndromes that are susceptible to leukemia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".