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Record W1823422771 · doi:10.1139/bcb-2014-0043

Protein transport into the human ER and related diseases, Sec61-channelopathies

2014· review· en· W1823422771 on OpenAlexvenueno aff
Sarah Haßdenteufel, Marie-Christine Klein, Armin Melnyk, Richard Zimmermann

Bibliographic record

VenueBiochemistry and Cell Biology · 2014
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsnot available
Fundersnot available
KeywordsTransport proteinMembrane proteinChemistryCell biologyComputational biologyBiophysicsBiologyBiochemistry

Abstract

fetched live from OpenAlex

Protein transport into the human endoplasmic reticulum (ER) is relevant to the biogenesis of most soluble and membrane proteins of organelles, which are involved in endo- or exo-cytsosis. It involves amino-terminal signal peptides in the precursor polypeptides and various transport components in the cytosol plus the ER, and can occur co- or post-translationally. The two mechanisms merge at the level of the ER membrane, specifically at the level of the heterotrimeric Sec61 complex, which forms a dynamic polypeptide-conducting channel in the ER membrane. Since the mammalian ER is also the main intracellular calcium storage organelle, and the Sec61 complex is calcium permeable, the Sec61 complex is tightly regulated in its equilibrium between the closed and open conformations, or "gated", by ligands, such as signal peptides of the transport substrates and the ER lumenal Hsp70-type molecular chaperone BiP. Furthermore, BiP binding to the incoming polypeptide contributes to the efficiency and unidirectionality of transport. Recent insights into the structure and dynamic equilibrium of the Sec61 complex have various mechanistic as well as medical implications.

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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.247
Teacher spread0.240 · 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

Citations23
Published2014
Admission routes1
Has abstractyes

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