Role of integrin β3 in neutrophil recruitment in <i>Streptococcus pneumoniae</i> induced lung inflammation.
Bibliographic record
Abstract
Streptococcus pneumoniae (SP) is one of the most common causes of bacterial pneumonias in humans. Neutrophil migration into SP‐infected lungs is central to host defense. But the mechanisms of SP‐mediated neutrophil recruitment into lungs are not completely understood. Therefore, we studied the role of an adhesion molecule, integrin β3, in a mouse model of SP‐induced lung inflammation. Integrin β3 knockout (KO) mice and the wild type (WT) mice were intratracheally instilled with either 50μl of SP (ATCC ® 6303; 3.5X10 7 /ml; n=7/group) or saline (n= 4–7/group). Another group of WT mice were treated intraperitoneally with 50μg of monoclonal antibody against integrin β3 (n=5) or with an isotype matched antibody (n=5) 2h before instillation of SP. All the mice were euthanized 24h after SP or saline instillation. Flow cytometry confirmed absence and presence of integrin β3 on peripheral blood neutrophils in the KO and WT mice, respectively. Broncheoalveoalr lavage fluid (BALF) from KO mice showed lower total leukocytes (P=0.042) but not neutrophils compared to WT. However, both the number of leukocytes (P=0.012) and neutrophils (P=0.027) in BALF were less in antibody+SP treated mice compared SP treated WT mice. There was no difference between the isotype antibody+SP treated mice compared to SP treated WT mice. The peripheral blood neutrophil numbers were not different among the groups. We conclude that blockade of integrin β3 reduces neutrophil migration into the SP‐infected and inflamed lungs. Therefore, integrin β3 could be one of the adhesion molecules mediating neutrophil recruitment in SP‐induced pneumonias. Funding: NSERC, Canada.
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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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".