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Record W2995989799 · doi:10.1126/sciadv.aax7331

Sleep fragmentation, microglial aging, and cognitive impairment in adults with and without Alzheimer’s dementia

2019· article· en· W2995989799 on OpenAlexafffund
Kirusanthy Kaneshwaran, Marta Olah, Shinya Tasaki, Lei Yu, Elizabeth M. Bradshaw, Julie A. Schneider, Aron S. Buchman, David A. Bennett, Philip L. De Jager, Andrew Lim

Bibliographic record

VenueScience Advances · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsSunnybrook Health Science Centre
FundersNational Institute of Neurological Disorders and StrokeCanadian Institutes of Health ResearchNational Institute on AgingNational Institutes of Health
KeywordsDementiaSleep (system call)Cognitive impairmentCognitionNeuroscienceMedicineCognitive declineMicrogliaMemory impairmentBrain agingPsychologyGerontologyDiseaseInflammationImmunologyPathology

Abstract

fetched live from OpenAlex

Sleep disruption is associated with cognitive decline and dementia in older adults; however, the underlying mechanisms are unclear. In rodents, sleep disruption causes microglial activation, inhibition of which improves cognition. However, data from humans are lacking. We studied participants in two cohort studies of older persons-the Rush Memory and Aging Project and the Religious Orders Study. We assessed sleep fragmentation by actigraphy and related this to cognitive function, to neocortical microglial marker gene expression measured by RNA sequencing, and to the neocortical density of microglia assessed by immunohistochemistry. Greater sleep fragmentation was associated with higher neocortical expression of genes characteristic of aged microglia, and a higher proportion of morphologically activated microglia, independent of chronological age- and dementia-related neuropathologies. Furthermore, these were, in turn, associated with worse cognition. This suggests that sleep fragmentation is accompanied by accelerated microglial aging and activation, which may partially underlie its association with cognitive impairment.

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 score0.044
Threshold uncertainty score0.399

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.276
Teacher spread0.264 · 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

Citations96
Published2019
Admission routes2
Has abstractyes

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