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Record W4295780199 · doi:10.3389/frdem.2022.941879

The effect of Aβ seeding is dependent on the presence of knock-in genes in the AppNL−G−F mice

2022· article· en· W4295780199 on OpenAlexafffund
Sean G. Lacoursiere, Jiri Safar, David Westaway, Majid H. Mohajerani, Robert J. Sutherland

Bibliographic record

VenueFrontiers in Dementia · 2022
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of AlbertaUniversity of Lethbridge
FundersRIKEN Brain Science InstituteRIKENCanadian Institutes of Health Research
KeywordsSeedingEntorhinal cortexNeurosciencePathologicalAmyloid (mycology)BiologyPathologyPsychologyMedicineHippocampus

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) is characterized by the prion-like propagation of amyloid-β (Aβ). However, the role of Aβ in cognitive impairment is still unclear. To determine the causal role of Aβ in AD, we intracerebrally seeded the entorhinal cortex of a 2-month-old App NL − G − F mouse model with an Aβ peptide derived from patients who died from rapidly progressing AD. When the mice were 3 months of age or 1 month following seeding, spatial learning and memory were tested using the Morris water task. Immunohistochemical labeling showed seeding with the Aβ was found accelerate Aβ plaque deposition and microgliosis in the App NL − G − F mice, but this was dependent on the presence of the knocked-in genes. However, we found no correlation between pathology and spatial performance. The results of the present study show the seeding effects in the App NL − G − F knock-in model, and how these are dependent on the presence of a humanized App gene. But these pathological changes were not initially causal in memory 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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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 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

Citations3
Published2022
Admission routes2
Has abstractyes

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