MétaCan
Menu
Back to cohort
Record W3128142168 · doi:10.1007/s11064-021-03256-7

Physiological and Pathological Ageing of Astrocytes in the Human Brain

2021· review· en· W3128142168 on OpenAlexfundno aff
Marloes Verkerke, Elly M. Hol, Jinte Middeldorp

Bibliographic record

VenueNeurochemical Research · 2021
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsnot available
FundersAlzheimer NederlandUniversitair Medisch Centrum UtrechtNederlandse Organisatie voor Wetenschappelijk OnderzoekNewfoundland and LabradorZonMw
KeywordsAgeingNeuroscienceHuman brainDementiaPathologicalAstrocyteCognitive declineAlzheimer's diseaseApolipoprotein EAging brainDiseaseBiologyCognitionPsychologyCentral nervous systemMedicinePathology

Abstract

fetched live from OpenAlex

Ageing is the greatest risk factor for dementia, although physiological ageing by itself does not lead to cognitive decline. In addition to ageing, APOE ε4 is genetically the strongest risk factor for Alzheimer's disease and is highly expressed in astrocytes. There are indications that human astrocytes change with age and upon expression of APOE4. As these glial cells maintain water and ion homeostasis in the brain and regulate neuronal transmission, it is likely that age- and APOE4-related changes in astrocytes have a major impact on brain functioning and play a role in age-related diseases. In this review, we will discuss the molecular and morphological changes of human astrocytes in ageing and the contribution of APOE4. We conclude this review with a discussion on technical issues, innovations, and future perspectives on how to gain more knowledge on astrocytes in the human ageing brain.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.424
GPT teacher head0.490
Teacher spread0.066 · 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 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

Citations48
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueNeurochemical ResearchSame topicNeuroinflammation and Neurodegeneration MechanismsFrench-language works237,207