Limited Role of the Receptor for Advanced Glycation End Products during <b><i>Streptococcus pneumoniae</i></b> Bacteremia
Bibliographic record
Abstract
Streptococcus pneumoniae is one of the most common causes of sepsis. Sepsis is associated with the release of 'damage-associated molecular patterns' (DAMPs). The receptor for advanced glycation end products (RAGE) is a multiligand receptor, abundantly expressed in the lungs, that recognizes several of these DAMPs. Triggering of RAGE leads to activation of the NF-κB pathway and perpetuation of inflammation. Earlier investigations have shown that the absence of RAGE reduces inflammation and bacterial dissemination and increases survival in sepsis caused by S. pneumoniae pneumonia. We hypothesized that the detrimental role of RAGE depends on the level of RAGE expression in the primary organ of infection. By directly injecting S. pneumoniae intravenously, thereby circumventing the extensive RAGE-expressing lung, we here determined whether RAGE contributes to an adverse outcome of bacteremia or whether its role is restricted to primary lung infection. During late-stage infection (48 h), rage(-/-) mice had an attenuated systemic inflammatory response, as reflected by lower plasma levels of proinflammatory cytokines, reduced endothelial cell activation (as measured by E-selectin levels) and less neutrophil accumulation in lung tissue. However, RAGE deficiency did not influence bacterial loads or survival in this model. In accordance, plasma markers for cell injury were similar in both mouse strains. These results demonstrate that while RAGE plays a harmful part in S. pneumoniae sepsis originating from the respiratory tract, this receptor has a limited role in the outcome of primary bloodstream infection by this pathogen.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".