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Record W2162727760 · doi:10.1038/emboj.2013.124

OPA1 promotes pH flashes that spread between contiguous mitochondria without matrix protein exchange

2013· article· en· W2162727760 on OpenAlexaff
Jaime Santo‐Domingo, Marta Giacomello, Damon Poburko, Luca Scorrano, Nicolas Demaurex

Bibliographic record

VenueThe EMBO Journal · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsSimon Fraser University
FundersServier
KeywordsMitochondrionBiophysicsDepolarizationBiologyMitochondrial matrixMembrane potentialHyperpolarization (physics)Cell biologymitochondrial fusionBiochemistryCytosolNuclear magnetic resonanceMitochondrial DNAPhysics

Abstract

fetched live from OpenAlex

The chemical nature and functional significance of mitochondrial flashes associated with fluctuations in mitochondrial membrane potential is unclear. Using a ratiometric pH probe insensitive to superoxide, we show that flashes reflect matrix alkalinization transients of ∼0.4 pH units that persist in cells permeabilized in ion-free solutions and can be evoked by imposed mitochondrial depolarization. Ablation of the pro-fusion protein Optic atrophy 1 specifically abrogated pH flashes and reduced the propagation of matrix photoactivated GFP (paGFP). Ablation or invalidation of the pro-fission Dynamin-related protein 1 greatly enhanced flash propagation between contiguous mitochondria but marginally increased paGFP matrix diffusion, indicating that flashes propagate without matrix content exchange. The pH flashes were associated with synchronous depolarization and hyperpolarization events that promoted the membrane potential equilibration of juxtaposed mitochondria. We propose that flashes are energy conservation events triggered by the opening of a fusion pore between two contiguous mitochondria of different membrane potentials, propagating without matrix fusion to equilibrate the energetic state of connected mitochondria.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.172
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.021
GPT teacher head0.262
Teacher spread0.242 · 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

Citations107
Published2013
Admission routes1
Has abstractyes

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