Cellular Senescence, Immunosenescence and HIV
Bibliographic record
Abstract
Aging is a complex biological process that leads to several physiological changes. Among these changes, the most striking are those involving the innate and adaptive parts of the immune system. Furthermore, these changes are associated with a low-grade inflammation called inflamm-aging, which is the result of several lifelong antigenic stimulations, including chronic viral infections such as cytomegalovirus. Immunosenescence, concomitantly with inflamm-aging, is considered as the leading cause of age-related diseases including cardiovascular, neurodegenerative and metabolic diseases, and cancer. HIV infection, once considered a unique deadly infectious disease, has now become a chronic disease with efficacious highly active antiretroviral therapy. This signifies that the treatment transforms HIV infection from a chronic infection to a chronic inflammatory disease. Most people with HIV infection become aged, and older adults have been contracting HIV infection. Thus, there is a great interest to study HIV infection in relation to immunosenescence and inflamm-aging to determine whether immunosenescence contributes to HIV infection, or if HIV is causing immunosenescence and, as such, represents a premature immunosenescence and accelerated aging. Although there are many similarities in the immune and inflammatory changes and the occurrence of age-related chronic diseases between normal aging and HIV infection, the interaction between these processes is not well understood, and consequently the concept that HIV infection is an accelerated aging model is questioned. Future studies are needed to effectively answer this question for the better care of HIV-infected elderly patients.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".