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Record W4313555640 · doi:10.1126/science.abj8894

Past history of obesity triggers persistent epigenetic changes in innate immunity and exacerbates neuroinflammation

2023· article· en· W4313555640 on OpenAlexaff
Masayuki Hata, Elisabeth M. M. A. Andriessen, Maki Hata, Roberto Diaz-Marin, Frédérik Fournier, Sergio Crespo‐Garcia, Guillaume Blot, Rachel Juneau, Frédérique Pilon, Agnieszka Dejda, Vera Guber, Émilie Heckel, Caroline Daneault, Virginie Calderon, Christine Des Rosiers, Heather J. Melichar, Thomas Langmann, Jean‐Sébastien Joyal, Ariel M. Wilson, Przemysław Sapieha

Bibliographic record

VenueScience · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsMontreal Heart InstituteCentre Hospitalier Universitaire Sainte-JustineMontreal Clinical Research InstituteUniversité de MontréalHôpital Maisonneuve-Rosemont
Fundersnot available
KeywordsNeuroinflammationBiologyTLR4Innate immune systemImmunologyEpigeneticsProinflammatory cytokineMicrogliaInflammationNeuroscienceImmune systemGenetics

Abstract

fetched live from OpenAlex

Age-related macular degeneration is a prevalent neuroinflammatory condition and a major cause of blindness driven by genetic and environmental factors such as obesity. In diseases of aging, modifiable factors can be compounded over the life span. We report that diet-induced obesity earlier in life triggers persistent reprogramming of the innate immune system, lasting long after normalization of metabolic abnormalities. Stearic acid, acting through Toll-like receptor 4 (TLR4), is sufficient to remodel chromatin landscapes and selectively enhance accessibility at binding sites for activator protein-1 (AP-1). Myeloid cells show less oxidative phosphorylation and shift to glycolysis, ultimately leading to proinflammatory cytokine transcription, aggravation of pathological retinal angiogenesis, and neuronal degeneration associated with loss of visual function. Thus, a past history of obesity reprograms mononuclear phagocytes and predisposes to neuroinflammation.

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)0.001
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 score0.040
Threshold uncertainty score0.452

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.047
GPT teacher head0.250
Teacher spread0.203 · 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

Citations175
Published2023
Admission routes1
Has abstractyes

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