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Record W2058488647 · doi:10.1016/j.jalz.2012.05.823

P2‐118: Liver X receptors ligand and minocycline: Effectiveness of combined drug therapy in an Alzheimer's transgenic mouse model

2012· article· en· W2058488647 on OpenAlexaffabout
Valeria Flaque, A. Claudio Cuello, Martín A. Bruno

Bibliographic record

VenueAlzheimer s & Dementia · 2012
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsMinocyclineNeuroinflammationApolipoprotein ENeuroprotectionLiver X receptorGenetically modified mouseMedicineNeuropathologyPharmacologyTransgeneInternal medicineDiseaseBiologyNuclear receptorGene

Abstract

fetched live from OpenAlex

Alzheimer's disease (AD) is a multifactorial disorder (combination of genes and environmental factors) and apparently involves several different etiopathogenic mechanisms. Currently, there is no effective treatment to halt the progression or prevent the onset of AD. A number of theories involving various risk factors such as diet, lifestyle, socioeconomic status, genetic predisposition and head injury have been proposed, but the degree of contribution of each factor is still controversial. Along with age, several factors appear to be widely acknowledged as early risk factors for development of AD including chronic neuroinflammation, brain oxidative damage, hypercholesterolemia and Apolipoprotein E. On the other hand, there is a solid body of scientific evidence that the progressive brain accumulation of the peptide Abeta is key to the AD neuropathology. In recent studies, the initiation and progression of AD has been linked to neuroinflammation, cholesterol metabolism (including APOE activity) and Abeta accumulation, processes that can be modulated by minocycline and liver x receptors (LXRs). This study is aimed to test the effectiveness of the combined daily administration of minocycline with LXRs agonist (during four weeks) to establish the extent of the benefits of the combined therapy (synergism), as opposed to monotherapy with the two above-mentioned agents in our AD-like transgenic mouse model coded McGill-Thy1-APP. We have been able to demonstrate and replicate the known beneficial CNS effects of minocycline treatment as an antioxidant and anti-inflammatory agent in our transgenic AD mouse model. Moreover, we have confirmed that Liver X receptor (LXRs) agonists' treatment in our AD transgenic mouse model reverse cognitive deficits and facilitated the proteolytic degradation of Abeta, without inducing hepatic steatosis and hypertriglyceridemia. When combined, animals receiving both agents simultaneously, displayed a marked reduction of cortical peroxynitrite-mediated oxidative damage, lowered burden of Aβ and decreased pro-inflammatory markers (IL-1β). This preliminary study provides evidence of the benefits of the combined therapy (synergism), as opposed to monotherapy with minocycline and LXRs agonist in our AD-like transgenic mouse model. These observations suggest that the combined administration may represent a promising therapeutic opportunity.

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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.281
Teacher spread0.237 · 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
Published2012
Admission routes2
Has abstractyes

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