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Record W2160159279 · doi:10.1155/2010/830307

Methods for Monitoring Endoplasmic Reticulum Stress and the Unfolded Protein Response

2010· article· en· W2160159279 on OpenAlexfundno aff
Afshin Samali, Una FitzGerald, Shane Deegan, Sanjeev Gupta

Bibliographic record

VenueInternational Journal of Cell Biology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsnot available
FundersQueen's UniversityUniversity of GalwayScience Foundation IrelandEnterprise IrelandQueen's University BelfastMultiple Sclerosis SocietyNational University of Ireland
KeywordsEndoplasmic reticulumUnfolded protein responseProtein foldingDownregulation and upregulationCell biologyComputer scienceMedicineBioinformaticsBiologyBiochemistry

Abstract

fetched live from OpenAlex

The endoplasmic reticulum (ER) is the site of folding of membrane and secreted proteins in the cell. Physiological or pathological processes that disturb protein folding in the endoplasmic reticulum cause ER stress and activate a set of signaling pathways termed the Unfolded Protein Response (UPR). The UPR can promote cellular repair and sustained survival by reducing the load of unfolded proteins through upregulation of chaperones and global attenuation of protein synthesis. Research into ER stress and the UPR continues to grow at a rapid rate as many new investigators are entering the field. There are also many researchers not working directly on ER stress, but who wish to determine whether this response is activated in the system they are studying: thus, it is important to list a standard set of criteria for monitoring UPR in different model systems. Here, we discuss approaches that can be used by researchers to plan and interpret experiments aimed at evaluating whether the UPR and related processes are activated. We would like to emphasize that no individual assay is guaranteed to be the most appropriate one in every situation and strongly recommend the use of multiple assays to verify UPR activation.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.013
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.007
GPT teacher head0.325
Teacher spread0.318 · 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

Citations260
Published2010
Admission routes1
Has abstractyes

Explore more

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