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Endoplasmic reticulum stress in wake‐active neurons progresses with aging

2011· article· en· W1537691457 on OpenAlexaff
Nirinjini Naidoo, Jingxu Zhu, Yan Zhu, Polina Fenik, Jie Lian, Ray Galante, Sigrid C. Veasey

Bibliographic record

VenueAging Cell · 2011
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsCanadian Sleep & Circadian Network
FundersNational Heart, Lung, and Blood InstituteNational Institute on Aging
KeywordsWakefulnessEndoplasmic reticulumUnfolded protein responseBiologyNeuroscienceSenescenceFragmentation (computing)EndocrinologyInternal medicineCell biologyMedicine

Abstract

fetched live from OpenAlex

Fragmentation of wakefulness and sleep are expected outcomes of advanced aging. We hypothesize that wake neurons develop endoplasmic reticulum dyshomeostasis with aging, in parallel with impaired wakefulness. In this series of experiments, we sought to more fully characterize age-related changes in wakefulness and then, in relevant wake neuronal populations, explore functionality and endoplasmic reticulum homeostasis. We report that old mice show greater sleep/wake transitions in the active period with markedly shortened wake periods, shortened latencies to sleep, and less wake time in the subjective day in response to a novel social encounter. Consistent with sleep/wake instability and reduced social encounter wakefulness, orexinergic and noradrenergic wake neurons in aged mice show reduced c-fos response to wakefulness and endoplasmic reticulum dyshomeostasis with increased nuclear translocation of CHOP and GADD34. We have identified an age-related unfolded protein response injury to and dysfunction of wake neurons. It is anticipated that these changes contribute to sleep/wake fragmentation and cognitive impairment in aging.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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 head0.042
GPT teacher head0.263
Teacher spread0.221 · 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 designObservational
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

Citations63
Published2011
Admission routes1
Has abstractyes

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