Simplified Human Neutrophil Extracellular Traps (NETs) Isolation and Handling
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neutrophil Extracellular Traps (NETs) have been recently identified as part of the neutrophil's antimicrobial armamentarium. Apart from their role in fighting infections, recent research has demonstrated that they may be involved in many other disease processes, including cancer progression. Isolating purified NETs is a crucial element to allow the study of these functions. In this video, we demonstrate a simplified method of cell free NET isolation from human whole blood using readily available reagents. Isolated NETs can then be used for immunofluorescence staining, blotting or various functional assays. This enables an assessment of their biologic properties in the absence of the potential confounding effects of neutrophils themselves. A density gradient separation technique is employed to isolate neutrophils from healthy donor whole blood. Isolated neutrophils are then stimulated by phorbol 12-myristate 13-acetate (PMA) to induce NETosis. Activated neutrophils are then discarded, and a cell-free NET stock is obtained. We then demonstrate how isolated NETs can be used in an adhesion assay with A549 human lung cancer cells. The NET stock is used to coat the wells of a 96 well cell culture plate O/N, and after ensuring an adequate NET monolayer formation on the bottom of the wells, CFSE labeled A549 cells are added. Adherent cells are quantified using a Nikon TE300 fluorescent microscope. In some wells, 1000U DNAse1 is added 10 min before counting to degrade NETs.
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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 | 0.000 |
| 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) | 0.000 | 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 it