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Record W2304287990 · doi:10.1074/jbc.m115.695825

Loss of Mitochondrial Function Impairs Lysosomes

2016· article· en· W2304287990 on OpenAlexafffund
Julie Demers-Lamarche, Gérald Guillebaud, Mouna Tlili, Kiran Todkar, Noémie Bélanger, Martine Grondin, Angela Nguyen, Jennifer J. Carlisle Michel, Marc Germain

Bibliographic record

VenueJournal of Biological Chemistry · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsUniversity of OttawaUniversité du Québec à Trois-Rivières
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFunction (biology)Cell biologyMitochondrionChemistryLoss functionBiologyBiochemistryPhenotypeGene

Abstract

fetched live from OpenAlex

Alterations in mitochondrial function, as observed in neurodegenerative diseases, lead to disrupted energy metabolism and production of damaging reactive oxygen species. Here, we demonstrate that mitochondrial dysfunction also disrupts the structure and function of lysosomes, the main degradation and recycling organelle. Specifically, inhibition of mitochondrial function, following deletion of the mitochondrial protein AIF, OPA1, or PINK1, as well as chemical inhibition of the electron transport chain, impaired lysosomal activity and caused the appearance of large lysosomal vacuoles. Importantly, our results show that lysosomal impairment is dependent on reactive oxygen species. Given that alterations in both mitochondrial function and lysosomal activity are key features of neurodegenerative diseases, this work provides important insights into the etiology of 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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

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 head0.015
GPT teacher head0.243
Teacher spread0.228 · 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 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

Citations251
Published2016
Admission routes2
Has abstractyes

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