Lymph flow directs rapid neutrophil positioning in the lymph node in infection
Bibliographic record
Abstract
Abstract Soon after Staphylococcus aureus ( S. aureus ) skin infection, neutrophils infiltrate the LN via the high endothelial venules (HEVs) to restrain and kill the invading microbes to prevent systemic spread of microbes. In this study, we found that rapid neutrophil migration depends on lymph flow, through which inflammatory chemokines/cytokines produced in the infected tissue are transported to the LN. Without lymph flow, bacteria accumulation in the LN was insufficient to stimulate chemokine production or neutrophil migration. Oxazolone (OX)-induced skin inflammation impaired lymphatic function, and reduced chemokines in the LN after a secondary infection with S. aureus . Due to LN reconstruction and impaired conduit-mediated lymph flow, neutrophil preferentially transmigrated in HEVs located in the medullary sinus, where the HEVs remained exposed to lymph-borne chemokines. Altered neutrophil migration resulted in persistent infection in the LN. Our studies showed that lymph flow directed chemokine dispersal in the LN and ensured rapid neutrophil migration for timely immune protection in infection. The impaired lymph flow and neutrophil migration may contribute to the frequent infection in skin inflammation, such as atopic dermatitis.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".