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Record W7117295580 · doi:10.1002/alz70859_103609

Therapeutic Potential of INM‐901 in Mitigating Alzheimer’s Disease Pathology: Insights from a Long‐term 5xFAD Mouse Model Study

2025· article· en· W7117295580 on OpenAlexaff
R.K. Somvanshi, Shadi Madani, Singh SNEHA, S. Ng, Marjan Barazandeh, James T. Kealey, James Craig, Sapna Padania, Eric A Adams, Michael Woudenberg, Eric Hsu, Ujendra Kumar

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsInimex Pharmaceuticals (Canada)University of British ColumbiaNorth Island College
Fundersnot available
KeywordsTauopathyDiseaseTherapeutic approachInflammationImmune system

Abstract

fetched live from OpenAlex

BACKGROUND: Alzheimer's Disease (AD) is a neurodegenerative condition characterized by cognitive and sensorimotor deficits, affecting over 6.9 million people in the US, with an annual economic impact of over $700 billion in direct and indirect healthcare costs. While current treatments such as donepezil, and memantine manage symptoms, they do not halt disease progression. Moreover, amyloid beta (Aβ) antibody therapy faces challenges, including limited efficacy in advanced disease stages, infusion-related reactions, and high treatment costs. Cannabinoids have shown potential in alleviating Aβ toxicity, reducing tau phosphorylation, and suppressing inflammation via CB1 and CB2 receptors, supporting neuronal viability. Therefore, in this study, we investigated the effects of a novel synthetic cannabinoid analogue INM-901 on Aβ-induced toxicity and disease progression using the 5xFAD mice. METHOD: Male 5xFAD mice, which exhibit AD-like pathology, including accelerated Aβ-plaque accumulation, inflammation, neurodegeneration, and deficits in cognitive and motor functions, were treated (intra-peritoneally) with INM-901 at 15 or 30 mg/kg twice-weekly for 7 months. Control groups, including non-transgenic and 5xFAD mice, received vehicle-treatment. Behavioral tests, including the Open-field (OFT), Zero Maze, Barnes Maze, and Acoustic Startle Response, were conducted post-treatment. Brain tissue and plasma samples were collected and analyzed via RNAseq, immunohistochemistry, western blotting, and multiplex assay to assess the effects of INM-901 on AD-related genes and protein expression. RESULT: INM-901 treatment reversed changes in anxiety-like behavior in the Zero Maze and OFT, as well as improved spatial learning and memory in the Barnes Maze. INM-901 treated mice also exhibited improved acoustic startle response (%PPI), indicating enhanced auditory function. RNAseq showed decreased expression of several inflammatory genes that were upregulated in the 5xFAD mice, while multiplex assays revealed reduced levels of pro-inflammatory cytokines and neurodegeneration marker neurofilament light chain (NfL). Immunohistochemistry demonstrated a reduction in Aβ-aggregation, as well as changes in CB2R expression, highlighting the neuroprotective and anti-inflammatory effects of INM-901. CONCLUSION: INM-901 treatment reversed several behavioral changes, improved auditory deficits, decreased Aβ-aggregation, and modulated inflammatory and neuritogenesis markers in 5xFAD mice. These findings highlight the potential of INM-901 as a therapeutic candidate for AD and provide a basis for further evaluation in tauopathy and inflammatory neurodegenerative models.

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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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 head0.030
GPT teacher head0.320
Teacher spread0.290 · 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
Published2025
Admission routes1
Has abstractyes

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