Neutrophil Crawling in Capillaries; A Novel Immune Response to Staphylococcus aureus
Bibliographic record
Abstract
Methicillin-resistant Staphylococcus aureus (MRSA), particularly the USA300 strain, is a highly virulent pathogen responsible for an increasing number of skin and soft tissue infections globally. Furthermore, MRSA-induced soft tissue infections can rapidly progress into life-threatening conditions, such as sepsis and necrotizing fasciitis. The importance of neutrophils in these devastating soft tissue infections remains ambiguous, partly because of our incomplete understanding of their behaviour. Spinning disk confocal microscopy was used to visualize the behaviour of GR1-labelled neutrophils in subcutaneous tissue in response to GFP-expressing MRSA attached to a foreign particle (agarose bead). We observed significant directional neutrophil recruitment towards the S. aureus agarose bead but not a control agarose bead. A significant increase in neutrophil crawling within the capillaries surrounding the infectious nidus was noted, with impaired capillary perfusion in these vessels and increased parenchymal cell death. No neutrophils were able to emigrate from capillaries. The crawling within these capillaries was mediated by the β(2) and α(4) integrins and blocking these integrins 2 hours post infection eliminated neutrophil crawling, improved capillary perfusion, reduced cell death and reduced lesion size. Blocking prior to infection increased pathology. Neutrophil crawling within capillaries during MRSA soft tissue infections, while potentially contributing to walling off or preventing early dissemination of the pathogen, resulted in impaired perfusion and increased tissue injury with time.
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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 | 0.000 |
| 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".