Faculty Opinions recommendation of Immune quiescence: a model of protection against HIV infection.
Bibliographic record
Abstract
Aberrant immune activation is a strong correlate of HIV disease progression, but little is known about how immune activation alters susceptibility to HIV infection. Susceptibility to HIV infection varies between individuals, but the immunological determinants of HIV transmission are not well understood. Here, we present evidence from studies of HIV transmission in the context of clinical trials and HIV-exposed seronegative (HESN) cohorts that implicates elevated immune activation as a risk factor for acquiring HIV. We propose a model of protection from infection based on a phenotype of low baseline immune activation referred to as immune quiescence. Immune quiescence is evidenced by reduced expression of T cell activation markers, low levels of generalized gene transcription and low levels of proinflammatory cytokine and chemokine production in the periphery and genital mucosa of HESN. Since HIV preferentially replicates in activated CD4+ T cells, immune quiescence may protect against infection by limiting HIV target cell availability. Although the determinants of immune quiescence are unclear, several potential factors have been identified that may be involved in driving this phenotype. HESN were shown to have elevated proportions of regulatory T cells (Tregs), which are known to suppress T cell activation. Likewise, proteins involved in controlling inflammation in the genital tract have been found to be elevated in HESN. Furthermore, expression of interferon regulatory factor 1 (IRF-1) is reduced in HESN as a consequence of genetic polymorphisms and differential epigenetic regulation. Since IRF-1 is an important regulator of immune responses, it may play a role in maintaining immune quiescence. Based on this model, we propose a novel avenue for HIV prevention targeted based on reducing host mucosal immune activation. PMID: 24257114 Funding information This work was supported by: Canadian Institutes of Health Research, Canada Grant ID: MOP 86721
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.186 | 0.059 |
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".