MétaCan
Menu
Back to cohort

LF 15-0195 Generates Synergistic Tolerance by Promoting Formation of CD4+CD25+CTLA4+ T Cells

2005· article· en· W1995183264 on OpenAlexaff
Xiaoping Xia, Xiao Zhang, Xuyan Huang, Mu Li, Lina Zhao, Donghua Tian, Robert Zhong, Wei‐Ping Min

Bibliographic record

VenueJournal of Immunotherapy · 2005
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsLawson Health Research InstituteLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsChemistryCell biologyBiology

Abstract

fetched live from OpenAlex

The purpose of the present study was to investigate the influence of 15-deoxyspergualin (LF) on the phenotypes and functions of dendritic cells (DCs) and T cells and to further illustrate the mechanism of LF-inducing immunologic tolerance. DCs from mice were cultured and treated with varying doses of LF at specific time-points. Fluorescence-activated cell sorting (FACS) was used to verify the changes of phenotypes in the cultured DCs labeled with fluorescent antibody. DCs were also used as stimulators in mixed leukocyte reaction to detect their ability to stimulate T-cell proliferation. DCs and T cells, treated with or without LF, were cultured together; phenotypes and cytokine profile of the T cells were identified and assayed by FACS and enzyme-linked immunosorbent assay. LF induced a dose- and time-dependent suppression of maturation of DCs and a dose-dependent suppression of T-cell proliferation in mixed leukocyte reaction when LF-treated DCs were used as stimulators. LF-treated DCs, cultured with naive T cells, could promote the formation of CD4+CD25+CTLA4+ T-cell subtypes and the production of higher levels of interleukin-10. It was suggested that the mechanism of LF-induced tolerance was inhibiting maturation and function of DC and inducing the formation of regulatory T-cell subtype by "suppressor DCs" to achieve a new immune balance.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.118
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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.

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

Citations9
Published2005
Admission routes1
Has abstractyes

Explore more

Same venueJournal of ImmunotherapySame topicImmunotherapy and Immune ResponsesFrench-language works237,207