Evidence map›Paper›PMID 33317213›Full record

ArticleBiomedicines2020

Metabolic Profiling of Female Tg2576 Mouse Brains Provides Novel Evidence Supporting Intranasal Low-Dose Pioglitazone for Long-Term Treatment at an Early Stage of Alzheimer's Disease.

Ling Rong Wong, Peiyan Wong, Paul Chi-Lui Ho

Open access · goldAbstract read
In one paragraph

Article in Biomedicines, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.9field-weighted citation impact, top 13% of its field
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

13 citing papers in PubMed, 19 citations in OpenAlex.

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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 at 1 institution in 1 country.

Ling Rong WongDepartment of Pharmacy, Faculty of Science, National University of Singapore, Singapore 117543, Singapore.
Peiyan WongNeuroscience Phenotyping Core, Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456, Singapore.
Paul Chi-Lui HoDepartment of Pharmacy, Faculty of Science, National University of Singapore, Singapore 117543, Singapore.
National University of Singapore · SG

Funding

National University Health System (NUHS) Centre Grant Seed Funding (Singapore) R-148-000-180-112.
6 · The paper itself

Abstract

Accumulating evidence suggests that disruptions in brain energy metabolism may be a key player in the pathogenesis of Alzheimer's disease (AD). Pioglitazone (PIO) has been found to exert beneficial effects on metabolic dysfunction in many AD preclinical studies. However, limited success in clinical trials remains an obstacle to its development for the treatment of AD. PIO's poor brain penetration was often cited as a contributing factor to the lack of clinical benefit. In this study, we prepared PIO-loaded poly(lactic-co-glycolic acid) (PLGA) nanoparticles and administered them as suspended nanoparticles via nebulization. Preliminary investigation of drug distribution to the brain revealed comparatively reduced systemic exposure after administering PIO nanoparticles via the intranasal route. In vitro, extracellular flux analysis showed significantly raised spare respiratory capacity when cells were treated with low-dose PIO nanoparticles. Tg2576 transgenic mice treated with low-dose PIO nanoparticles over four months exhibited an overall trend of reduced hyperactivity in open field tests but did not show any visible effect on alternation rates in the Y-maze task. Subsequent

Indexed as

Alzheimer’s diseaseintranasal deliverymetabolic profilingpioglitazonePLGA nanoparticles

Identifiers

PMID33317213
PMCPMC7764407
OpenAlexW3111668057

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.