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Record W2089773406 · doi:10.1111/tra.12183

In Sickness and in Health: The Role of <scp>TRAPP</scp> and Associated Proteins in Disease

2014· review· en· W2089773406 on OpenAlexafffund
Stephanie Brunet, Michael Sacher

Bibliographic record

VenueTraffic · 2014
Typereview
Languageen
FieldMedicine
TopicParkinson's Disease Mechanisms and Treatments
Canadian institutionsMcGill UniversityConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyGuanine nucleotide exchange factorGTPaseProtein subunitCell biologyPhenotypeFunction (biology)OrganelleGeneticsGene

Abstract

fetched live from OpenAlex

Transport protein particle (TRAPP) represents a series of related protein complexes that function in specific stages of inter-organelle traffic. They share a core of subunits that can activate the GTPase Rab1 through a guanine nucleotide exchange factor (GEF) activity and are distinguished by 'accessory' subunits giving each complex its distinct function. The subunits are ubiquitously expressed and, thus, mutations in TRAPP subunits would be expected to be embryonic lethal. However, since its discovery, a number of subunits have been found to be mutated in several diverse human disorders suggesting that some of these subunits may have cell- or tissue-specific functions. Here we review the current state of knowledge with respect to TRAPP subunit mutations in human disease. We suggest ideas to explain their tissue-specific phenotypes and present avenues for future investigation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.023
GPT teacher head0.303
Teacher spread0.280 · 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 source (direct Gemma or distilled Codex), 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

Citations51
Published2014
Admission routes2
Has abstractyes

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