Neutrophil recruitment to the lymph node in response to <i>S. aureus</i> infection
Bibliographic record
Abstract
Abstract Bacterial skin infections can be cleared and pose no immediate threat to the host. However, if a bacterial infection is not contained and disseminates into the bloodstream, this can lead to system-wide bacteremia and death. Lymph nodes along lymphatic vessels may act as barriers by filtering the lymphatic fluid. This barrier is not merely passive, but is actively modulated in response to inflammation. In tissues, neutrophils are extremely important in controlling bacterial infections and are robustly recruited to the lymph node upon infection with pathogens at a distant site. Intriguingly, how the neutrophils reach the lymph node and their role upon arrival is only beginning to be understood. Neutrophil recruitment to the popliteal lymph node occurs within 2 hours of Staphylococcus aureus infection in the footpad, plateauing at 6 hours. Using intravital multiphoton imaging and the Lysm eGFP reporter mouse we have visualized the behaviour of neutrophils in lymph node blood vessels and in the lymph node tissue. Neutrophils accumulate within wide blood vessels in the lymph node, exhibiting rolling, adhesion, crawling and transmigration from vessel lumen into lymph node tissue. No neutrophils can be seen in afferent lymphatics. Imaging of the subcapsular sinus shows neutrophil accumulation and swarming as well as neutrophils actively phagocytosing S. aureus. This suggests neutrophils are being quickly recruited to the lymph node to prevent dissemination from an initial site of infection via lymphatics. This project aims to define the role of neutrophils as cellular barriers in preventing dissemination of bacteria via lymphatics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".