A novel method for isolation and flow cytometry analysis of intraepithelial lymphocytes from colon biopsies
Bibliographic record
Abstract
Investigating the immune responses of the intestine in response to different insults is predominantly limited to indirect methods such as circulating markers of intestinal health or gene expression from dissections. We describe here a validated protocol for the isolation and subsequent flow cytometry analysis of intestinal intraepithelial lymphocytes (IEL) from colonic biopsy samples. Colon biopsy samples were collected with endoscopy forceps from Holstein dairy bull calves at d 2, 28, and 42 of life. The biopsies were put into an isolation solution of Hanks' balanced salt solution, and fetal bovine serum followed by digestion solution. The solution was filtered and the flow-through, containing IEL, was stained with fluorescent antibodies for flow cytometry analysis. Density gradient separation of the isolate yielded higher viability and cleaner samples for flow cytometry analysis. Anti-bovine γ chain of the T cell receptor was used to identify populations of gamma delta (γδ) T cells via flow cytometry. In addition, γδ T cell subsets were identified using an anti-bovine antibody against the coreceptor workshop cluster 1. This method allowed for the precise identification of lymphocyte populations and evaluation of the proportion of different subsets of γδ T cells from intestinal IEL over time. The technique described here will allow the research community to characterize intestinal immune function over time and improve our understanding of how different management and nutritional strategies affect intestinal health.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".