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Record W1964968817 · doi:10.1080/0929350310001619744

T helper cell polarisation as a measure of the maturation of the immune response

2003· article· en· W1964968817 on OpenAlexaff
Scott B. Cameron, Ellen H. Stolte, Anthony W. Chow, Huub F. J. Savelkoul

Bibliographic record

VenueMediators of Inflammation · 2003
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImmune systemMeasure (data warehouse)BiologyImmunologyComputer science

Abstract

fetched live from OpenAlex

BACKGROUND: T helper cell polarisation is important under chronic immune stimulatory conditions and drives the type of the evolving immune response. Mice treated with superantigens in vivo display strong effects on Th subset differentiation. The aim of the study was to detect the intrinsic capacity of T cells to polarise under various ex vivo conditions. METHODS: Purified CD4+ T cells obtained from super-antigen-treated mice were cultured under Th polarising conditions in vitro. By combining intracellular cytokine staining and subsequent flow cytometric analysis with quantitative cytokine measurements in culture supernatants by enzyme-linked immunosorbent assay (ELISA), the differential Th polarising capacity of the treatment can be detected in a qualitative and quantitative manner. RESULTS AND CONCLUSIONS: BALB/c mice were shown to be biased to develop strong Th2 polarised immune responses using Th0 stimulation of purified CD4+ T cells from phosphate-buffered saline-treated mice. Nevertheless, our analysis methodology convincingly showed that even in these mice, Toxic Shock Syndrome Toxin-1 treatment in vivo resulted in a significantly stronger Th1 polarising effect than control treatment. Our results indicate that populations of Th cells can be assessed individually for their differential Th1 or Th2 maturation capacity in vivo by analysing robust in vitro polarisation cultures combined with intracellular cytokine staining and ELISA.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.293

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.005
GPT teacher head0.192
Teacher spread0.187 · 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

Citations7
Published2003
Admission routes1
Has abstractyes

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