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Record W2102941331 · doi:10.1084/jem.191.6.1017

Regulation of FAS Ligand Expression during Activation-Induced Cell Death in T Cells by p38 Mitogen-Activated Protein Kinase and C-Jun Nh2-Terminal Kinase

2000· article· en· W2102941331 on OpenAlexaff
Jian Zhang, Jianxin Gao, Kostantin Salojin, Qing Shao, Marsha Grattan, Craig Meagher, Dale W. Laird, Terry L. Delovitch

Bibliographic record

VenueThe Journal of Experimental Medicine · 2000
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsWestern UniversityRobarts Clinical Trials
Fundersnot available
KeywordsFas ligandCell biologyp38 mitogen-activated protein kinasesProtein kinase AMAPK/ERK pathwayMitogen-activated protein kinaseKinaseBiologyProgrammed cell deathMolecular biologyApoptosisChemistryBiochemistry

Abstract

fetched live from OpenAlex

Activation-induced cell death (AICD) is a mechanism of peripheral T cell tolerance that depends upon an interaction between Fas and Fas ligand (FasL). Although c-Jun NH2-terminal kinase (JNK) and p38 mitogen-activated protein kinase (MAPK) may be involved in apoptosis in various cell types, the mode of regulation of FasL expression during AICD in T cells by these two MAPKs is incompletely understood. To investigate the regulatory roles of these two MAPKs, we analyzed the kinetics of TCR-induced p38 MAPK and JNK activity and their regulation of FasL expression and AICD. We report that both JNK and p38 MAPK regulate AICD in T cells. Our data suggest a novel model of T cell AICD in which p38 MAPK acts early to initiate FasL expression and the Fas-mediated activation of caspases. Subsequently, caspases stimulate JNK to further upregulate FasL expression. Thus, p38 MAPK and downstream JNK converge to regulate FasL expression at different times after T cell receptor stimulation to elicit maximum AICD.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.356

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.009
GPT teacher head0.247
Teacher spread0.238 · 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

Citations89
Published2000
Admission routes1
Has abstractyes

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