Role of Triggering Receptor Expressed on Myeloid Cells-1/3 in <i>Klebsiella</i> -Derived Pneumosepsis
Bibliographic record
Abstract
Triggering receptor expressed on myeloid cells (TREM)-1 and -2 can affect Toll-like receptor-mediated activation of immune cells. Klebsiella pneumoniae is a common cause of pneumonia-derived sepsis. Here we studied the role of TREM-1/3 and TREM-2 in the host response during Klebsiella pneumonia. Macrophages lacking either TREM-1/3 or TREM-2 were tested for their responsiveness toward K. pneumoniae and for their capacity to internalize this pathogen in vitro. TREM-1/3- and TREM-2-deficient mice were infected with K. pneumoniae via the airways, and their responses were compared with those in wild-type mice. TREM-1/3-deficient macrophages produced lower cytokine levels upon exposure to K. pneumoniae, whereas TREM-2-deficient macrophages released higher cytokine concentrations. TREM-2-deficient, but not TREM-1/3-deficient, macrophages showed a reduced capacity to phagocytose K. pneumoniae. TREM-1/3-deficient mice showed an impaired host defense during Klebsiella pneumonia, as reflected by worsened survival and increased bacterial growth and dissemination. In contrast, TREM-2 deficiency did not affect disease outcome. Although TREM-1/3 and TREM-2 influence macrophage responsiveness to K. pneumoniae in vitro, only TREM-1/3 contribute to the host response during Klebsiella pneumonia in vivo, serving a protective role.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".