Nuclear segmentation facilitates neutrophil migration
Bibliographic record
Abstract
Neutrophils are among the fastest-moving immune cells. Their speed is critical to their function as 'first responder' cells at sites of damage or infection, and it has been postulated that the unique segmented nucleus of neutrophils functions to assist their rapid migration. Here, we tested this hypothesis by imaging primary human neutrophils traversing narrow channels in custom-designed microfluidic devices. Individuals were given an intravenous low dose of endotoxin to elicit recruitment of neutrophils into the blood with a high diversity of nuclear phenotypes, ranging from hypo- to hyper-segmented. Both by cell sorting of neutrophils from the blood using markers that correlate with lobularity and by directly quantifying the migration of neutrophils with distinct lobe numbers, we found that neutrophils with one or two nuclear lobes were significantly slower to traverse narrower channels, compared to neutrophils with more than two nuclear lobes. Thus, our data show that nuclear segmentation in primary human neutrophils provides a speed advantage during migration through confined spaces.
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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) | 0.002 | 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".