Intracellular signalling pathways: targets to reverse immunosenescence
Bibliographic record
Abstract
Ageing is a very complex process, the result of the dysregulation of multiple systems interacting in many ways. A prominent change occurring with ageing is related to the architecture and functioning of the immune system, viewed commonly as detrimental and termed 'immunosenescence'. However, age-associated changes may also lead to increased function in certain respects, which can be viewed as adaptive. None the less, on balance it is well-recognized that immunosenescence is accompanied by the low-grade inflammation observed commonly in elderly people, which has been dubbed 'inflamm-ageing'. The exact cause and significance of all these changes is not clear, but there is a consensus that they are related to the occurrence of chronic non-infectious age-associated disease, as well as increased susceptibility to infections. Alterations to immune cell signalling may be a prominent cause of malfunctioning immunity. Emerging attempts to reverse immunosenescence have recently targeted the signalling pathways in various different cell types of the immune system. Here, we review and discuss alterations in the signalling pathways of immune cells with ageing and consider current targets and means to modulate altered functions. We discuss the potential dangers as well as the benefits of these interventions, and consider future approaches to this problem.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".