Biological importance of the two Toll-like receptors, TLR2 and TLR4, in macrophage response to infection with<i>Candida albicans</i>
Bibliographic record
Abstract
The aim of this study was to assess the role of TLR2, TLR4 and MyD88 accessory molecule in the effector and secretory response of macrophages to viable microbial agents. Using TLR-deleted macrophage cell lines generated from the bone marrow of genetically engineered mice (TLR4 gene-deficient, MyD88- and TLR2-knockout mice) and wild-type control mice, we found that TLR2-deleted macrophages exhibit increased ability to contain Candida albicans infection compared to TLR2+/+ counterpart. In contrast, both MyD88-/- and TLR4-/- macrophages retain levels of functional activity comparable to that of the respective wild-type MyD88+/+ and TLR4+/+ controls. The difference in anticandidal effector functions observed between TLR2-/- and TLR2+/+ macrophages is abrogated upon opsonization of the fungal target and interestingly is not observed when using other microbial targets, such as Streptococcus pneumoniae and Helicobacter pylori. When tested for secretory response to C. albicans, TLR2-deleted macrophages show a pattern of cytokine production similar to that of TLR2+/+ controls. Finally, flow cytometry analysis reveals that TLR2-deleted macrophages express only TLR4, while, as expected, TLR2+/+ macrophages are both TLR2 and TLR4 positive; in no cases, modulation of such markers occurs in macrophages exposed to C. albicans infection. In conclusion, these data indicate that TLR2 and TLR4 have different biological relevance, in which TLR2 but not TLR4, is involved in the accomplishment of macrophage-mediated anticandidal activity, while the secretory response to C. albicans appears to be TLR4 but not TLR2-dependent.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".