Immunosenescence in vertebrates and invertebrates
Bibliographic record
Abstract
There is an established consensus that it is primarily the adaptive arm of immunity, and the T cell subset in particular, that is most susceptible to the deleterious changes with age known as "immunosenescence". Can we garner any clues as to why this might be by considering comparative immunology and the evolutionary emergence of adaptive and innate immunity? The immune system is assumed to have evolved to protect the organism against pathogens, but the way in which this is accomplished is different in the innate-vs-adaptive arms, and it is unclear why the latter is necessary. Are there special characteristics of adaptive immunity which might make the system more susceptible to age-associated dysfunction? Given recent accumulating findings that actually there are age-associated changes to innate immunity and that these are broadly similar in vertebrates and invertebrates, we suggest here that it is the special property of memory in the adaptive immune system which results in the accumulation of cells with a restricted receptor repertoire, dependent on the immunological history of the individual's exposures to pathogens over the lifetime, and which is commonly taken as a hallmark of "immunosenescence". However, we further hypothesize that this immunological remodelling per se does not necessarily convey a disadvantage to the individual (ie. is not necessarily "senescence" if it is not deleterious). Indeed, under certain circumstances, or potentially even as a rule, this adaptation to the individual host environment may confer an actual survival advantage.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".