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Record W7117294827 · doi:10.1002/alz70859_104682

Heterocyclic Quinoline Derivatives as Innovative Neuroprotective Agents for Alzheimer's Disease

2025· article· en· W7117294827 on OpenAlexaff
Maria Paula Faccin Huth, Angélica Rocha Joaquim, Marcela Silva Lopes, Karine Rigon Zimmer, Saulo Fernandes de Andrade, Aline Rigon Zimmer

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicCholinesterase and Neurodegenerative Diseases
Canadian institutionsMcGill University
Fundersnot available
KeywordsNeuroprotectionQuinolineDrugAntioxidantDerivative (finance)

Abstract

fetched live from OpenAlex

Heterocyclic Quinoline Derivatives as Novel Neuroprotective Agents for Alzheimer's Disease BACKGROUND: Alzheimer's disease (AD) is a complex multifactorial neurodegenerative disease and the leading cause of dementia. Different pathological processes contribute to the disease's progress, and a multitarget approach is considered an attractive strategy for drug design and discovery in AD. Quinolines are a class of heterocyclic compounds with diverse biological activities, especially chelating properties, antioxidants, and reducing brain Aβ levels. Quinolinic scaffolds have been explored as potential applications in the treatment of AD. In this study, quinolinic-based analogous has been designed targeting anti-inflammatory and antioxidant activity to be used at the early stages of Alzheimer's disease and reduce the disease's onset and progression. METHOD: We designed a series of quinolinic-based compounds and evaluated the drug-like properties and the blood-brain barrier (BBB) permeability using in silico virtual platforms. The cytotoxicity and neuroprotective effects of the most promising derivatives were tested in in vitro assays using three different brain cell lines (BV-2 microglial, C6 astroglial, and HT-22 neuronal cells) against inflammatory (LPS) and oxidative (H2O2) insults. The effects on the production of nitrite and reactive oxygen species were determined. We also tested the toxicity and effects of the compounds on the in vivo Caenorhabditis elegans transgenic model (CL2355, neurons expressing Aβ1-42, and VPR839 strains). RESULT: All molecules have shown high potential for oral absorption, and 80% are promising to cross BBB. The heterocyclic derivatives that exhibited IC50 values higher than 50 µM in all tested brain cells were classified as low toxicity and chosen for neuroprotection assays. Two quinolinic derivatives successfully protected the glial and neuronal cells of oxidative insults and showed a tendency towards neuroinflammatory protection in neuronal cells, in concentrations lower than 5 µM. These compounds reduced nitric oxide levels by 30%. The studies with the C. elgans fluorescent strains are in progress. CONCLUSION: The designed heterocyclic-based derivative showed physicochemical characteristics compatible with oral use and passage through BBB and relevant antioxidant and anti-inflammatory effects. These findings suggest these compounds are promising multitarget agents for preventing AD, offering opportunities for future drug design in this field.

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 score0.008

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.048
GPT teacher head0.347
Teacher spread0.299 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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