Evidence map›Paper›PMID 40978680›Full record

ArticleNano research2025

Incidental vs. Engineered Nanoparticles in Alzheimer's and Parkinson's Disease: Pathological Pathways and Therapeutic Interventions.

Hanyu Li, Ning Wang, Xiaobo Mao

Abstract read
In one paragraph

Article in Nano research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Hanyu LiNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Ning WangNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
Xiaobo MaoNeuroregeneration and Stem Cell Programs, Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.

Funding

Determine the role of atmospheric particulate matter pollutants in contributing to Lewy Body DementiaRF1AG079487 · NIA · JOHNS HOPKINS UNIVERSITY · PI LIU, PENGFEI, MAO, XIAOBO · 2023 to 2023
$2.3M
Determine the role of atmospheric particulate matter pollutants in contributing to Lewy Body DementiaR01AG079487 · NIA · JOHNS HOPKINS UNIVERSITY · PI Pengfei Liu, Xiaobo Mao · 2026 to 2026
$746k
NIA NIH HHS R01 AG079487NIA NIH HHS RF1 AG079487
6 · The paper itself

Abstract

Nanoparticles (NPs) play dual roles in neurodegeneration. Incidental NPs, generated unintentionally from environmental and industrial sources, are linked to oxidative stress, neuroinflammation, and disruption of the blood-brain barrier in Alzheimer's disease (AD) and Parkinson's disease (PD). Engineered NPs are designed for diagnosis and therapy using nanobodies, nanozymes, and other engineered nanoparticle (ENP) platforms that enable targeted delivery, modulation of neuroimmune pathways, and interference with pathological protein aggregation. This review aligns source-based classes (incidental versus engineered) with composition-based families (metal-based, carbon-based, and polymeric or inorganic), and summarizes routes of exposure, mechanistic toxicology, and engineered interventions relevant to AD and PD. We also evaluate current limitations, including biocompatibility, relevance to chronic exposure, and clinical benchmarking, and we outline priorities for translating nanotechnology into practical diagnostics and therapeutics for neurodegenerative disease.

Indexed as

Alzheimer’s diseaseEngineered NanoparticlesNanobodyNanozymeParkinson’s disease

Identifiers

PMID40978680
PMCPMC12448076

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.