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Record W2789955431 · doi:10.21037/aes.2018.ab003

AB003. Deregulated autophagy and energy-deficient photoreceptors drive angiogenesis in a model of age-related macular degeneration

2018· article· en· W2789955431 on OpenAlexaff
Jean‐Sébastien Joyal

Bibliographic record

VenueAnnals of Eye Science · 2018
Typearticle
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsUniversité de MontréalMcGill UniversityCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsAutophagyMacular degenerationDegeneration (medical)AngiogenesisMedicineNeuroscienceOphthalmologyChemistryBiologyCancer researchBiochemistryApoptosis

Abstract

fetched live from OpenAlex

Abstract: Autophagy recycles intracellular substrate in part to fuel mitochondria during starvation. Deregulated autophagy caused by dyslipidemia, oxidative stress, and aging is associated with early signs of age-related macular degeneration (AMD), such as lipofuscin and perhaps drusen accumulation. Intracellular nutrient sensors for glucose and amino acids regulate autophagy. The role of lipid sensors in controlling autophagy, however, remains ill-defined. Here we will show that abundant circulating lipids trigger a satiety signal through FA receptors that restrain autophagy and oxidative mitochondrial metabolism. In the presence of excess dietary lipids, fatty acid sensors might protect tissues with high metabolic rates against lipotoxicity, favoring their storage, instead, in adipose tissues. However, sustained exposure to lipid reduces retinal metabolic efficiency. In photoreceptors with high metabolic needs, it predisposes to an energy failure and triggers compensatory albeit pathological angiogenesis, leading to blinding neovascular AMD.

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 score0.225
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.034
GPT teacher head0.323
Teacher spread0.289 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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