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Record W2039668915 · doi:10.1016/j.jalz.2010.05.1932

P3‐390: The synthetic retinoid, AHPN, attenuates lipopolysaccharide and β‐amyloid–induced microglial activation: A possible therapeutic agent for inflammatory‐mediated neurodegenerative diseases

2010· article· en· W2039668915 on OpenAlexaff
Mark Farso, Slavica Krantic, Rémi Quirion

Bibliographic record

VenueAlzheimer s & Dementia · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsDouglas Mental Health University InstituteMcGill University
Fundersnot available
KeywordsMicrogliaNeuroinflammationLipopolysaccharideInflammationLactate dehydrogenaseRetinoic acidChemistryPharmacologyImmunologyCell cultureCancer researchBiologyBiochemistryEnzyme

Abstract

fetched live from OpenAlex

Chronic neuroinflammation, mediated by sustained microglial activation, is now recognised to play a vital role in the pathogenesis of various neurodegenerative diseases, particularly Alzheimer's disease (AD). Endogenous retinoid ligands, all-trans-retinoic acid (RA) and 9-cis-RA, have been previously shown to exhibit anti-inflammatory actions against β-amyloid (Aβ)/lipopolysaccharide (LPS) -mediated activation of microglia in vitro. Synthetic retinoids have received much attention as therapeutic agents for cancer, leukaemia and proliferative skin disorders but their effects in brain-mediated inflammation remain unknown. One such analog, 6-[3-adamantyl-4-hydroxyphenyl]-2-napthalene carboxylic acid (AHPN or CD437), is a highly potent apoptotic agent in cancer and leukemia cell lines. The current study aimed to determine the effects of AHPN on the activation profile of dissociated microglia in culture. Microglia cells were exposed to either 1 μg/ml LPS or 10 μM Aβ1-42 plus 10 ng/ml IFN-γ in the presence of AHPN (0.5-100 μM) for 24 h. Cell-free culture supernatant was investigated for the accumulation of nitrite (NO2), cytokines (via ELISA analysis), and lactate dehydrogenase (LDH) for cell death. Labelling the cells with anti-CD-11b (OX-42) enabled microglia morphology to be visualised under microscopy for qualitative assessment of activation. Findings from these experiments showed that AHPN (5-100 μM) decreased LPS-mediated production of NO2 but not cytokines. Western immunoblotting demonstrated a significant attenuation of phosphorylated nuclear factor kappa B (NF-κB) and iNOS by 5 μM AHPN. Microscopy analysis of CD-11b-positive cells indicated that 5 μM AHPN reverted LPS-induced activated morphologies whilst reducing cell number through Cyclin D1 inhibition. However, higher concentrations of AHPN (50-100 μM) induced cell death through increased LDH accumulation and condensation of nuclei (through Hoechst dye staining). Preliminary results also indicated that production of NO2 by Aβ1-42 (+ IFN-γ) was reduced by AHPN. Taken together, the results show that microglial activation can be attenuated by AHPN, as evidenced by the inhibition of both proliferation and NO2 production - through reduced NF-κB activation and iNOS production. In conclusion, these new findings provide a possible anti-inflammatory role for synthetic retinoids, which could be a useful therapeutic strategy for neurodegenerative diseases that involve an inflammatory component, such as 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.248
Teacher spread0.234 · 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".

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Citations0
Published2010
Admission routes1
Has abstractyes

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