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Record W2535150517 · doi:10.1016/j.jalz.2016.06.1775

P3‐117: Progressive Inflammatory Pathology in the Retina of Aluminum‐Fed 5XFAD Transgenic Mice

2016· article· en· W2535150517 on OpenAlexaff
Aileen I. Pogue, Walter J. Lukiw, Maire E. Percy, Prerna Dua, James M. Hill, Yuhai Zhao, Surjyadipta Bhattacharjee

Bibliographic record

VenueAlzheimer s & Dementia · 2016
Typearticle
Languageen
FieldMedicine
TopicAlzheimer's disease research and treatments
Canadian institutionsUniversity of TorontoAlchemy (Canada)
Fundersnot available
KeywordsNeuropathologyGenetically modified mouseRetinaBiologyTransgeneBACE1-ASAmyloid (mycology)PeptideNeuroinflammationPathologyCentral nervous systemAmyloid precursor proteinP3 peptideMolecular biologyAlzheimer's diseaseInflammationEndocrinologyNeuroscienceImmunologyMedicineBiochemistryGeneDisease

Abstract

fetched live from OpenAlex

Approximately 60 murine transgenic models for Alzheimer's disease (Tg-AD) have been developed that overexpress the 42 amino acid amyloid-beta (Aβ42) peptide in the central nervous system (CNS). These 'humanized murine Tg-AD models' have significantly expanded our understanding of the contribution of Aβ42 peptide-mediated pro-inflammatory and amyloidogenic neuropathology to the AD process. Several laboratories using different amyloid-overexpressing Tg-AD models have independently reported that the supplementation of murine Tg-AD diets and/or drinking water with aluminum (sulfate) significantly enhances Aβ42 peptide-mediated inflammatory pathology, amyloidogenesis and AD-type cognitive change compared to age-matched controls. In humans AD-type neuropathology appears to originate in the limbic system and progressively spreads into primary processing and sensory regions such as the primary visual cortex and the retina. For the first time, here we assess the propagation of Aβ42 peptide-mediated amyloidogenesis and pro-inflammatory gene expression (at the level of miRNA, mRNA and protein) in the neocortical-thalamic-retinal visual pathway of 5xFAD Tg-AD amyloid-overexpressing mice whose diets were supplemented with aluminum (sulfate). 5xFAD Tg-AD murine models, RNA sequencing, GeneChip (microRNA and mRNA), RT-PCR, LED-Northern, Western, ELISA and bioinformatics analysis. The three most significant findings were (i) in aluminum-supplemented animals, markers for inflammatory neuropathology appeared in both the brain and the retina as evidenced by an evolving presence of Aβ42 peptides; (ii) increases in Aβ42 peptide abundance in these animals were accompanied by the up-regulation of several pro-inflammatory markers including cyclooxygenase-2 (COX-2) and C-reactive protein (CRP); and (iii) that as similarly reported in other Tg-AD murine models, there was a significantly accelerated development of Aβ42-mediated inflammatory neuropathology in 5xFAD Tg-AD mice fed aluminum. Taken together the results indicate that in the 5xFAD Tg-AD model aluminum not only enhances an Aβ42-mediated inflammatory neurodegeneration in the brain but also significantly induces AD-type neuropathology in anatomically-linked primary sensory areas that involve the acquisition and processing of visual signals.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.025
GPT teacher head0.302
Teacher spread0.277 · 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 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

Citations0
Published2016
Admission routes1
Has abstractyes

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