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Record W1993118551 · doi:10.4161/cc.5.8.2635

CARD Tricks: Controlling the Interactions of CARD6 with RICK and Microtubules

2006· review· en· W1993118551 on OpenAlexfundno aff
Almut Dufner, Tak W. Mak

Bibliographic record

VenueCell Cycle · 2006
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsnot available
FundersNational Cancer InstituteTerry Fox Foundation
KeywordsBiologyMicrotubuleCell biologyComputational biology

Abstract

fetched live from OpenAlex

In recent years, a number of proteins have been identified that contain a homotypic interaction motif called the caspase recruitment domain (CARD). Most proteins containing a CARD are involved in pathways regulating apoptosis or adaptive or innate immunity. Examples of prominent CARD proteins are caspase-9 and Apaf1, which are involved in the intrinsic death pathway; BCL10 and CARD11, which mediate antigen receptor-induced NF-kappaB activation; and receptor-interacting protein (RIP)-like interacting caspase-like apoptosis regulatory protein kinase (RICK) and the nucleotide-binding oligomerization domain (NOD) proteins, which induce NF-kappaB activation in response to intracellular bacterial peptidoglycan. The most recently discovered pathway involving CARD proteins senses virally-derived double-stranded (ds) RNA and initiates a host defense signaling program. CARD6 is a CARD-containing protein with a domain structure not shared by any other CARD protein. Although the CARD6 cDNA was deposited in GenBank five years ago, the physiological function of full-length CARD6 has yet to be reported. Here we review our initial characterization of CARD6 and discuss the functional implications of various conserved modules found in the CARD6 protein sequence. We conclude that CARD6 is structurally and potentially functionally related to the superfamily of interferon (IFN)-inducible GTPases, a growing family of host defense proteins that confer cell-autonomous immunity.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.252
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 designNot applicable
Domainnot available
GenreReview

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

Citations23
Published2006
Admission routes1
Has abstractyes

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