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Record W2518401648 · doi:10.2217/nmt-2016-0028

Elucidating the Link Between the Modifiable Risk Factors of Alzheimer’s Disease and Neuroinflammation

2016· article· en· W2518401648 on OpenAlexaff
Stephanie M. Schindler, Andis Klegeris

Bibliographic record

VenueNeurodegenerative Disease Management · 2016
Typearticle
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsNeuroinflammationMicrogliaDiseaseMedicineAlzheimer's diseaseDiabetes mellitusNeuroscienceImmune systemRisk factorImmunologyPsychologyInflammationInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Increased worldwide longevity through medical interventions, although beneficial, has allowed the age-related Alzheimer's disease (AD) to become an epidemic of the 21st century. AD pathology involves adverse activation of microglia, the immune cells of the brain and resulting chronic neuroinflammation. Certain diets, physical inactivity and Type 2 diabetes mellitus have been identified as the risk factors for developing AD, which may increase the risk of AD by neuroimmune mechanisms primarily through the overactivation of microglia. Thus, modifying these risk factors may represent an alternative therapeutic strategy for lowering the incidence of AD. We highlight the link between select modifiable risk factors and neuroimmune mechanisms, and demonstrate that by controlling microglial activation and neuroinflammation the prevalence of AD may be decreased.

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)0.001
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 score0.206
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.046
GPT teacher head0.264
Teacher spread0.218 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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