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Record W2031293088 · doi:10.1073/pnas.0604983103

Phosphorylation and cleavage of presenilin-associated rhomboid-like protein (PARL) promotes changes in mitochondrial morphology

2006· article· en· W2031293088 on OpenAlexaff
Danny V. Jeyaraju, Liqun Xu, Marie-Claude Letellier, Sirisha Bandaru, Rodolfo Zunino, Eric A. Berg, Heidi M. McBride, Luca Pellegrini

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of OttawaUniversité Laval
Fundersnot available
KeywordsMitochondrial fissionCell biologymitochondrial fusionBiologyRhomboidPhosphorylationMitochondrionInner mitochondrial membranePresenilinMitochondrial apoptosis-induced channelMitochondrial carrierCleavage (geology)Mitochondrial DNABiochemistryBacterial outer membraneProteases

Abstract

fetched live from OpenAlex

Remodeling of mitochondria is a dynamic process coordinated by fusion and fission of the inner and outer membranes of the organelle, mediated by a set of conserved proteins. In metazoans, the molecular mechanism behind mitochondrial morphology has been recruited to govern novel functions, such as development, calcium signaling, and apoptosis, which suggests that novel mechanisms should exist to regulate the conserved membrane fusion/fission machinery. Here we show that phosphorylation and cleavage of the vertebrate-specific Pbeta domain of the mammalian presenilin-associated rhomboid-like (PARL) protease can influence mitochondrial morphology. Phosphorylation of three residues embedded in this domain, Ser-65, Thr-69, and Ser-70, impair a cleavage at position Ser(77)-Ala(78) that is required to initiate PARL-induced mitochondrial fragmentation. Our findings reveal that PARL phosphorylation and cleavage impact mitochondrial dynamics, providing a blueprint to study the molecular evolution of mitochondrial morphology.

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)0.000
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 score0.047
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.261
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

Citations95
Published2006
Admission routes1
Has abstractyes

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