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Record W4405680125 · doi:10.1016/j.exer.2024.110219

How crosstalk between mitochondria, lysosomes, and other organelles can prevent or promote dry age-related macular degeneration

2024· review· en· W4405680125 on OpenAlexfundno aff
Aparna Lakkaraju, Patricia Boya, Marie Csete, Deborah A. Ferrington, James B. Hurley, Alfredo A. Sadun, Peng Shang, Ruchi Sharma, Debasish Sinha, Marius Ueffing, Susan E. Brockerhoff

Bibliographic record

VenueExperimental Eye Research · 2024
Typereview
Languageen
FieldMedicine
TopicRetinal Diseases and Treatments
Canadian institutionsnot available
FundersNational Eye InstituteBrightFocus FoundationResearch to Prevent BlindnessSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungFoundation Fighting Blindness
KeywordsCrosstalkMacular degenerationOrganelleMitochondrionAutophagyDegeneration (medical)Cell biologyLysosomeChemistryMedicineBiologyOphthalmologyApoptosisBiochemistryPhysicsOptics

Abstract

fetched live from OpenAlex

Organelles such as mitochondria, lysosomes, peroxisomes, and the endoplasmic reticulum form highly dynamic cellular networks and exchange information through sites of physical contact. While each organelle performs unique functions, this inter-organelle crosstalk helps maintain cell homeostasis. Age-related macular degeneration (AMD) is a devastating blinding disease strongly associated with mitochondrial dysfunction, oxidative stress, and decreased clearance of cellular debris in the retinal pigment epithelium (RPE). However, how these occur, and how they relate to organelle function both with the RPE and potentially the photoreceptors are fundamental, unresolved questions in AMD biology. Here, we report the discussions of the "Mitochondria, Lysosomes, and other Organelle Interactions" task group of the 2024 Ryan Initiative for Macular Research (RIMR). Our group focused on understanding the interplay between cellular organelles in maintaining homeostasis in the RPE and photoreceptors, how this could be derailed to promote AMD, and identifying where these pathways could potentially be targeted therapeutically.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.964
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.141
GPT teacher head0.477
Teacher spread0.336 · 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.

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

Citations10
Published2024
Admission routes1
Has abstractyes

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