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Record W1735388412 · doi:10.3233/jad-2008-13402

Inflammatory Aspects of Alzheimer Disease and Other Neurodegenerative Disorders

2008· review· en· W1735388412 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Alzheimer s Disease · 2008
Typereview
Languageen
FieldNeuroscience
TopicNeuroinflammation and Neurodegeneration Mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMicrogliaInflammationPhagocytosisNeuroscienceProinflammatory cytokineNeuroinflammationMedicineInflammatory responseImmunologyAlzheimer's diseaseDiseaseBiologyPathology

Abstract

fetched live from OpenAlex

Alzheimer and a number of other neurodegenerative diseases are characterized by the presence of reactive microglia and reactive astrocytes in association with the lesions. The classic view that microglia exist primarily in either a resting or activated state needs to be broadened in view of recent results. Resting microglia are in constant activity sampling their surround. Activated microglia may be pro-inflammatory, releasing inflammatory cytokines and other inflammatory mediators, or anti-inflammatory, promoting the healing process. There is evidence that microglial phagocytosis is more powerful in the anti-inflammatory state. Activated astrocytes also have pro-inflammatory and anti-inflammatory properties. In the pro-inflammatory state they release inflammatory cytokines. In the anti-inflammatory state they release various growth factors. In AD and other neurodegenerative diseases, both microglia and astrocytes are in a pro-inflammatory state. From a therapeutic point of view it is desirable to find methods of tipping the balance towards an anti-inflammatory state for both types of glia.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.948
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.070
GPT teacher head0.317
Teacher spread0.247 · 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