Overexpression of Toll-Like Receptor 4 Amplifies the Host Response to Lipopolysaccharide and Provides a Survival Advantage in Transgenic Mice
Bibliographic record
Abstract
Toll-like receptors are transmembrane proteins that are involved in the innate immune recognition of microbial constituents. Among them, Toll-like receptor 4 (Tlr4) is a crucial signal transducer for LPS, the major component of Gram-negative bacteria outer cell membrane. The contribution of Tlr4 to the host response to LPS and to infection with virulent Salmonella typhimurium was studied in four transgenic (Tg) strains including three overexpressing Tlr4. There was a good correlation between the level of Tlr4 mRNA expression and the sensitivity to LPS both in vitro and in vivo: Tg mice possessing the highest number of Tlr4 copies respond the most to LPS. Overexpression of Tlr4 by itself appears to have a survival advantage in Tg mice early during infection: animals possessing more than two copies of the gene survived longer and in a greater percentage to Salmonella infection. The beneficial effect of Tlr4 overexpression is greatly enhanced when the mice present a wild-type allele at natural resistance-associated macrophage protein 1, another critical innate immune gene involved in resistance to infection with Salmonella. Tlr4 and natural resistance-associated macrophage protein 1 exhibit functional epistatic interaction to improve the capacity of the host to control bacterial replication. However, this early improvement in disease resistance is not conducted later during infection, because mice overexpressing Tlr4 developed an excessive inflammatory response detrimental to the host.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".