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Record W4367303399 · doi:10.3168/jdsc.2022-0352

A novel method for isolation and flow cytometry analysis of intraepithelial lymphocytes from colon biopsies

2023· article· en· W4367303399 on OpenAlexafffund
K. Lamers, M.A. Steele, L.R. Cangiano

Bibliographic record

VenueJDS Communications · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFlow cytometryIntraepithelial lymphocyteBiologyAntibodyImmune systemMolecular biologyCytometryImmunology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.810
Threshold uncertainty score0.338

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.038
GPT teacher head0.327
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes2
Has abstractyes

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