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Record W3146199980 · doi:10.1177/25152564211001213

Post-Translational Modification of Cysteines: A Key Determinant of Endoplasmic Reticulum-Mitochondria Contacts (MERCs)

2021· review· en· W3146199980 on OpenAlexafffund
Arthur Bassot, Junsheng Chen, Thomas Simmen

Bibliographic record

VenueContact · 2021
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsEndoplasmic reticulumMitochondrionCell biologyOrganelleHomeostasisOxidative phosphorylationChemistryBiochemistryReactive oxygen speciesOxidative stressBiology

Abstract

fetched live from OpenAlex

Cells must adjust their redox state to an ever-changing environment that could otherwise result in compromised homeostasis. An obvious way to adapt to changing redox conditions depends on cysteine post-translational modifications (PTMs) to adapt conformation, localization, interactions and catalytic activation of proteins. Such PTMs should occur preferentially in the proximity of oxidative stress sources. A particular concentration of these sources is found near membranes where the endoplasmic reticulum (ER) and the mitochondria interact on domains called MERCs (Mitochondria-Endoplasmic Reticulum Contacts). Here, fine inter-organelle communication controls metabolic homeostasis. MERCs achieve this goal through fluxes of Ca 2+ ions and inter-organellar lipid exchange. Reactive oxygen species (ROS) that cause PTMs of mitochondria-associated membrane (MAM) proteins determine these intertwined MERC functions. Chronic changes of the pattern of these PTMs not only control physiological processes such as the circadian clock but could also lead to or worsen many human disorders such as cancer and neurodegenerative diseases.

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 score0.009

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 communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.031
GPT teacher head0.308
Teacher spread0.277 · 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

Citations12
Published2021
Admission routes2
Has abstractyes

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