CD14 Impairs Host Defense against Gram‐Negative Sepsis Caused by<i>Burkholderia pseudomallei</i>in Mice
Bibliographic record
Abstract
BACKGROUND: CD14 is a pattern-recognition receptor that can facilitate the presentation of bacterial components to either Toll-like receptor 2 (TLR2) or TLR4. We have recently shown that during melioidosis, a severe infection caused by the gram-negative bacterium Burkholderia pseudomallei, TLR2 but not TLR4 impacts the immune response of the intact host in vivo. METHODS: The function of CD14 in melioidosis was analyzed by means of in vitro and in vivo approaches, using wild-type (WT) and CD14 knockout (KO) mice. RESULTS: CD14-deficient macrophages and whole blood leukocytes released less tumor necrosis factor (TNF)-alpha on stimulation with B. pseudomallei or B. pseudomallei lipopolysaccharide in vitro, compared with WT cells. Strikingly, CD14 KO mice intranasally inoculated with B. pseudomallei demonstrated reduced lethality and significantly decreased bacterial outgrowth, compared with WT mice. Administration of recombinant soluble CD14 to CD14 KO mice partially reversed their phenotype to that of WT mice. Lastly, CD14 deficiency did not alter the capacity of macrophages or neutrophils to phagocytose or kill B. pseudomallei. CONCLUSION: CD14 is crucially involved in the recognition of B. pseudomallei by innate immune cells but plays a remarkable detrimental role in the host response against B. pseudomallei. Inhibition of CD14 may be a novel treatment strategy in melioidosis.
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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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".