Resistance to age-dependent thymic atrophy in long-lived mice that are deficient in pregnancy-associated plasma protein A
Bibliographic record
Abstract
Pregnancy-associated plasma protein A (PAPPA) is a metalloproteinase that controls the tissue availability of insulin-like growth factor (IGF). Homozygous deletion of PAPPA in mice leads to lifespan extension. Since immune function is an important determinant of individual fitness, we examined the natural immune ecology of PAPPA(-/-) mice and their wild-type littermates reared under specific pathogen-free condition with aging. Whereas wild-type mice exhibit classic age-dependent thymic atrophy, 18-month-old PAPPA(-/-) mice maintain discrete thymic cortex and medulla densely populated by CD4(+)CD8(+) thymocytes that are capable of differentiating into single-positive CD4 and CD8 T cells. Old PAPPA(-/-) mice have high levels of T cell receptor excision circles, and have bone marrows enriched for subsets of thymus-seeding progenitors. PAPPA(-/-) mice have an overall larger pool of naive T cells, and also exhibit an age-dependent accumulation of CD44(+)CD43(+) memory T cells similar to wild-type mice. However, CD43(+) T cell subsets of old PAPPA(-/-) mice have significantly lower prevalence of 1B11 and S7, glycosylation isoforms known to inhibit T cell activation with normal aging. In bioassays of cell activation, splenic T cells of old PAPPA(-/-) mice have high levels of activation antigens and cytokine production, and also elicit Ig production by autologous B cells at levels equivalent to young wild-type mice. These data suggest an IGF-immune axis of healthy longevity. Controlling the availability of IGF in the thymus by targeted manipulation of PAPPA could be a way to maintain immune homeostasis during postnatal development and aging.
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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) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".