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Record W7117324575 · doi:10.1002/alz70859_103999

A Novel Brain‐Penetrable Nanocarrier Delivers Brain‐derived Neurotrophic Factor for Treatment of Alzheimer’s Disease

2025· article· en· W7117324575 on OpenAlexaff
Xiao Yu Wu, Lily Yi Li, Elliya Park, Chunsheng He, Azhar Z. Abbasi, Taksim Ahmed, Paul E. Fraser, Andrew M. Rauth, Jeffrey T. Henderson

Bibliographic record

VenueAlzheimer s & Dementia · 2025
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDiseaseProgrammed cell deathApoptosisNanocarriersNeurotrophic factorsSynaptic plasticityBrain-derived neurotrophic factorCell

Abstract

fetched live from OpenAlex

BACKGROUND: Up to date, Alzheimer's disease (AD) has very limited disease-modifying treatment. With respect to neuroprotection, brain-derived neurotrophic factor (BDNF) has been shown to promote the survival and synaptic plasticity of glutamatergic and GABAergic neurons in brain regions associated with cognitive and emotive decline relevant to AD. However, the poor blood-brain barrier (BBB) permeability and pharmacokinetic properties of BDNF limit its utilization as a neuroprotective treatment. Herein we aim to design a new BDNF nanocarrier system using a novel BBB-permeable terpolymer (BDNF-TPN) and investigate its neuroprotective effect in neurones and AD mice. METHOD: Bioactivity of the BDNF-TPN was first evaluated in vitro using the SH-SY5Y cell differentiation assay. The protective effects of BDNF-TPN on primary murine hippocampal neurons were assessed following exposure to Aβ. The BDNF delivery and expression in the brain following IV injection were examined by ELISA and confocal microscopy. The biodistribution and safety were evaluated via hematologic, clinical biochemical, immunotoxicity and histology tests in APP transgenic TgCRND8 AD mice and CD-1 mice. The effects of the treatment were evaluated in AD mice via immunohistochemistry, ELISA and behavioral test after 4-week IV treatment (weekly, 1 mg BDNF/kg b.w.). RESULT: The BDNF-TPN maintained BDNF bioactivity and rescued Aβ42 toxified primary neurons in vitro. Biomarker studies demonstrated BDNF-mediated neuroprotective signaling in transgenic mice following IV treatment using BDNF-TPN. Compared to free BDNF, BDNF-TPN significantly reduced reactive microglia and astrocytes and apoptosis of neurons. The pAKT level increased more than 2-fold in BDNF-TPN-treated group compared to vehicle and free BDNF treated groups. Synaptophysin, a marker for synaptic plasticity and integrity, was profoundly increased. The improved hippocampal-dependent contextual learning in the AD mice was observed. There was not detectable toxicity following the BDNF-TPN treatment. CONCLUSION: Our findings suggest BDNF-TPN is a promising treatment for reducing neuroinflammation, apoptosis and programmed cell death in AD mouse brains, while improving synaptic plasticity and cognitive function. Reference 1. Zhang W, et al. Sig Transduct Target Ther 2023, 8, 267. 2. He C, et al. Nano Today. 2020;35:100965. 3. Park E, et al. Advanced Science. 2023, 10(12):2207238. 4. Park E, et al. Biomaterials. 2025 Jan 24:123142.

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 score0.002

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)0.0010.000

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 head0.062
GPT teacher head0.307
Teacher spread0.245 · 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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