Milk Matters: Soluble Toll-Like Receptor 2 (sTLR2) in Breast Milk Significantly Inhibits HIV-1 Infection and Inflammation
Bibliographic record
Abstract
The majority of infants who breastfeed from their HIV-positive mothers remain uninfected despite constant and repeated exposure to virus over weeks to years. This phenomenon is not fully understood but has been closely linked to innate factors in breast milk (BM). Most recently we have focused on one such innate factor, soluble Toll-like receptor 2 (sTLR2) for its significant contribution as an inhibitor of inflammation triggered by bacterial and viral antigens. We hypothesized that sTLR2 in BM inhibits immune activation/inflammation and HIV-1 infection. sTLR2 protein profiles were analyzed in HIV-uninfected BM and showed dramatic variability in expression concentration and predominant sTLR2 forms between women. sTLR2 immunodepleted BM, versus mock-depleted BM, incubated with Pam(3)CSK(4) lead to significant increases in IL-8 production in a TLR2-dependant fashion in U937, HEK293-TLR2, and Caco-2. Importantly, TLR2-specific polyclonal and monoclonal antibody addition to BM prior to cell-free R5 HIV-1 addition led to significantly (P<0.01, P<0.001, respectively) increased HIV-1 infection in TZM-bl reporter cells. To confirm these findings, sTLR2-depletion in BM led to significantly (P<0.001) increased HIV-1 infection in TZM-bl cells. Notably, immunodepletion does not allow for the complete removal of sTLR2 from BM, thus functional testing shown here may underestimate the total effect elicited by sTLR2 against HIV-1 and synthetic bacterial ligand. This study provides evidence for the first time that sTLR2 in BM may provide a dual protective role for infants breastfeeding from their HIV-infected mothers by; (1) immunomodulating pro-inflammatory responses to bacterial ligands, and (2) directly inhibiting cell-free HIV-1 infection. Thus, sTLR2 in BM may be critical to infant health and prove beneficial in decreasing vertical HIV-1 transmission to infants.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".