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Record W3111472490 · doi:10.1002/alz.046697

A novel P75‐neurotrophin receptor antagonist, EVT901, reduces neuroinflammation in the TGFAD344 rat model of Alzheimer’s disease

2020· article· en· W3111472490 on OpenAlexaff
Min Su Kang, Thomas A. Singleton, Arturo Aliaga, Gassan Massarweh, Serge Gauthier, Jean‐Paul Soucy, Alexey Kostikov, Pedro Rosa‐Neto

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicS100 Proteins and Annexins
Canadian institutionsMcGill Genome CentreMontreal Neurological Institute and HospitalMcGill University Health CentreMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsNeuroinflammationMedicineReceptor antagonistInternal medicineEndocrinologyPathologyPsychologyReceptorAntagonistInflammation

Abstract

fetched live from OpenAlex

Abstract Background p75‐neurotrophin receptor (p75NTR) plays an important role in cell death in adults and has been associated with age‐related basal forebrain degeneration and in Alzheimer’s disease (AD). A recent study demonstrated the reduced pro‐inflammatory response and improvement of the functional outcome by blocking p75NTR following traumatic brain injury. Here, we aimed to test whether a novel p75NTR antagonist, EVT901, reduces neuroinflammation caused by AD pathology in the TgFAD344 rat model (Tg). We hypothesized that chronic administration of EVT901 will reduce the neuroinflammation caused by amyloidosis and hyperphosphorylated tau in the AD rat model. Method Two parallel longitudinal studies were conducted to characterize the progression of amyloidosis and neuroinflammation in TgFAD344 rat models (WT = 15 & Tg = 22) and the effect of EVT901 on neuroinflammation (Tg = 6). In the first study, animals underwent 60‐minute dynamic PET scans using [18F]AZD4694 for amyloid‐beta and [11C]PBR28 for neuroinflammation at 15 and 22 months. During the intervention study, animals received 1 mg/kg of EVT901 for 7 days via tail vein injection at 22 months. These animals also underwent [11C]PBR28 PET one day before and after the intervention. The 1 mg/ml drug was prepared in a 10% PEG‐400/90% saline solution. All PET images were matched to the respective MRI and normalized to the average template. [18F]AZD4694 BPND and [11C]PBR28 BPND were quantified based on the SRTM method using pons and midbrain as a reference region, respectively. Result The first study demonstrated a significant increase in [18F]AZD4694 and [11C]PBR28 uptake in both the hippocampus and neocortex in Tg compared to WT at baseline and follow‐up. TgFAD344 rats showed a longitudinal increase in [18F]AZD4694 and [11C]PBR28 binding in similar regions. Our second study demonstrated a significant reduction in [11C]PBR28 binding following the intervention in the hippocampus and parietotemporal cortex. Conclusion This study demonstrated the amyloid pathology and neuroinflammation in the TgFAD344 rat model is captured by [18F]AZD4694 and [11C]PBR28 in vivo. Furthermore, a novel p75NTR antagonist, EVT901, reduces the neuroinflammation induced by AD pathophysiology. Blocking p75NTR can be considered a novel therapeutic target to reduce neuroinflammation in AD.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.264
Teacher spread0.221 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

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