Should we Try to Alleviate Immunosenescence and Inflammaging - Why, How and to What Extent?
Bibliographic record
Abstract
With advancing age, immune responses of human beings to external pathogens, i.e., bacteria, viruses, fungi and parasites, and to internal pathogens - malignant neoplasm cells - become less effective. Two major features in the process of aging of the human immune system are immunosenescence and inflammaging. The immune systems of our predecessors co-evolved with pathogens, which led to the occurrence of effective immunity. However, the otherwise beneficial activity may pose problems to the organism of the host and so it has builtin brakes (regulatory immune cells) and - with age - it undergoes adaptations and modifications, examples of which are the mentioned inflammaging and immunosenescence. Here we describe the mechanisms that first created our immune systems, then the consequences of their changes associated with aging, and the mechanisms of inflammaging and immunosenescence. Finally, we discuss to what extent both processes are detrimental and to what extent they might be beneficial and propose some therapeutic approaches for their wise control.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".