High level of plasma TILRR protein is associated with faster HIV seroconversion
Bibliographic record
Abstract
BACKGROUND: TILRR (Toll-like Interleukin-1 Receptor Regulator) is a modulator of many genes in NF-κB (nuclear factor kappa-light-chain-enhancer of activated B cells) signaling. It promotes the production of inflammatory mediators and the migration of immune cells. Recently, we showed that TILRR protein circulates in human blood. Thus, it could influence systemic inflammation. Systemic and mucosal inflammations increase the susceptibility to HIV infection. In this study, we analyzed the TILRR protein levels of the archived plasma samples of women enrolled in the Pumwani cohort to determine whether the plasma TILRR protein levels before seroconversion are correlated with differential risk of HIV seroconversion. METHODS: TILRR protein of 941 archived HIV negative plasma samples from 390 women who were HIV negative at the cohort enrollment was quantified with an in-house developed multiplex bead array method. Proinflammatory cytokines/chemokines were measured using a 14-plex bead array method. Spearman rank correlation analysis was used to determine the correlation between plasma TILRR protein and proinflammatory cytokines/chemokines. Kaplan-Meier survival analysis was conducted to evaluate whether the median plasma TILRR protein levels correlate with increased risk of HIV seroconversion. FINDINGS: The level of plasma TILRR protein was positively correlated with plasma IL-1β (rho: 0.2593, p<0.0001), MCP-1 (rho: 0.2377, p<0.0001), and IL-17A (rho: 0.1225, p=0.0216). Women with median plasma TILRR protein levels ≥100 ng/ml seroconverted significantly faster than women with plasma TILRR protein levels <100 ng/ml (log-rank= 100.124, p<0.0001; relative risk= 3.72 and odds ratio= 15.29). Furthermore, the factors causing genital inflammation, such as STIs (sexually transmitted infections), vaginal discharge, and genital ulcers were not statistically significantly different among women with different median plasma TILRR protein levels. INTERPRETATION: The high plasma TILRR protein levels are highly correlated with several plasma proinflammatory cytokines/chemokines. High median plasma TILRR protein (≥100 ng/ml) strongly predicted an increased risk of HIV seroconversion. Reducing plasma TILRR protein levels may reduce the risk of HIV acquisition. FUNDING: The study was funded by an operating grant from the Canadian Institutes of Health Research (CIHR), operating grant-PA: CHVI Vaccine Discovery and Social Research (http://www.cihr-irsc.gc.ca/e/193.html), and National Microbiology Laboratory of Canada.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".