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Record W2766260841 · doi:10.1101/204396

ILF and vReD pathways cooperate to control lysosomal transporter protein lifetimes

2017· preprint· en· W2766260841 on OpenAlexaff
Erin Kate McNally, Christopher L. Brett

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2017
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular transport and secretion
Canadian institutionsConcordia University
Fundersnot available
KeywordsCell biologyTransporterCycloheximideCytoplasmCatabolismChemistryVacuoleLysosomeBiochemistryBiologyEnzymeProtein biosynthesisGene

Abstract

fetched live from OpenAlex

Lysosomal nutrient transporter proteins move lumenal products of biomaterial catabolism to the cytoplasm for reuse by the cell. Two mechanisms control their lifetimes: the ILF (IntraLumenal Fragment) and vReD (Vacuole REcycling and Degradation) pathways. But it is not clear if they function independently. Using S. cerevisiae as a model, here we show that the ILF pathway mediates constitutive turnover of the lysine transporter Ypq1 and zinc transporter Cot1-known vReD client proteins-in vivo and in vitro. In contrast, the vReD pathway mediates constitutive degradation of the amino acid transporter Vba4. Activation of TOR with cycloheximide enhances their degradation by these pathways. However, misfolding by heat stress shunts all three into the ILF pathway. Thus, both pathways control individual transporter lifetimes, although only the ILF pathway mediates protein quality control. The pathway chosen depends on protein fate: degradation is imminent by the ILF pathway, whereas the vReD pathway permits reuse.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.009
GPT teacher head0.196
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 source (direct Gemma or distilled Codex), 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

Citations0
Published2017
Admission routes1
Has abstractyes

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Same venuebioRxiv (Cold Spring Harbor Laboratory)→Same topicCellular transport and secretion→French-language works237,207→