Role of Galectin-3 in Leukocyte Recruitment in a Murine Model of Lung Infection by <i>Streptococcus pneumoniae</i>
Bibliographic record
Abstract
Pneumonia can be caused by a variety of pathogens, among which Streptococcus pneumoniae causes one of the most common forms of community-acquired pneumonia. Depending on the invading pathogen, the elements of the immune response triggered will vary. For most pathogens, such as Escherichia coli, neutrophil recruitment involves a well-described family of adhesion molecules, beta(2)-integrins. In the case of streptococcal pneumonia, however, neutrophil recruitment occurs mainly through a beta(2)-integrin-independent pathway. Despite decades of research on this issue, the adhesion molecules involved in neutrophil recruitment during lung infection by S. pneumoniae have not been identified. We have previously shown that galectin-3, a soluble mammalian lectin, can be found in lungs infected by S. pneumoniae, but not by E. coli, and can mediate the adhesion of neutrophils on the endothelial cell layer, implying its role in the recruitment of neutrophils to lungs infected with S. pneumoniae. In this study, using galectin-3 null mice, we report further evidence of the involvement of this soluble lectin in the recruitment of neutrophils to S. pneumonia-infected lungs. Indeed, in the absence of galectin-3, lower numbers of leukocytes, mainly neutrophils, were recruited to the infected lungs during infection by S. pneumoniae. In the case of beta(2)-integrin-dependent recruitment induced by lung infection with E. coli, the number of recruited neutrophils was not reduced. Thus, taken together, our data suggest that galectin-3 plays a role as a soluble adhesion molecule in the recruitment of neutrophils to lungs infected by S. pneumoniae, which induces beta(2)-integrin-independent migration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".