Investigating M. Tuberculosis Infection in DTLR2 and DTLR4 Macrophages
Bibliographic record
Abstract
Mycobacterium tuberculosis (M. tb), the causative agent of tuberculosis, poses a significant global health problem. Toll-like receptors (TLRs) on the surface of phagocytic cells facilitate pathogen recognition and mount an inflammatory innate immune response upon activation. The role of TLR2 and TLR4 in the innate immune response to M. tb is intricate and complex, with evidence supporting both host and pathogen beneficial outcomes. Using CRISPR-Cas9 editing to generate TLR2 and TLR4 knockout macrophages, I assessed the role of these receptors in mycobacterial infection. I demonstrated that the absence of either of these receptors negatively impacts the replication and survival of M. tb within the macrophage during late-stage infection. Secondly, I found that TLR2 and TLR4 have differential, gene-specific roles in the induction of pro-inflammatory cytokines. Ultimately these findings support the notion that TLR2 and TLR4 serve pathogen beneficial roles in infection.
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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) | 0.004 | 0.002 |
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".