Regulatory vs. helper CD4 <sup>+</sup> T-cell ratios and the progression of HIV/AIDS disease
Bibliographic record
Abstract
Abstract The causes of individual variability in the length of time between human immunodeficiency virus (HIV) infection and the development of AIDS are incompletely understood. Here, we present a novel hypothesis: that the relative magnitude of responses to HIV mediated by CD4 + T regulatory (Treg) cells vs. CD4 + T effector (Teff) cells is a critical determinant of variability in AIDS progression rates. We use a simple mathematical model to show that this hypothesis can plausibly explain three qualitatively different outcomes of HIV infection – fast or slow progression to AIDS, and long-term non-progression to AIDS – based on individual variation in underlying T-cell response. This hypothesis also provides a unifying explanation for various other empirical observations, suggesting in particular that both aging and certain dual infections increase the rate of AIDS progression because they increase the strength of the Treg cell response. We discuss potential therapeutic implications of our results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".