Evidence map›Paper›PMID 35614075›Full record

ArticleScientific reports2022

Multiscale entropy analysis of retinal signals reveals reduced complexity in a mouse model of Alzheimer's disease.

Joaquín Araya-Arriagada, Sebastián Garay, Cristóbal Rojas, Claudia Duran-Aniotz, Adrián G Palacios, Max Chacón, Leonel E Medina

Abstract read
In one paragraph

Article in Scientific reports, 2022. 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

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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.

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4 · The record

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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

7 authors.

Joaquín Araya-ArriagadaEscuela de Tecnología Médica, Facultad de Salud, Universidad Santo Tomás, Santiago, Chile.
Sebastián GarayDepartamento de Ingeniería Informática, Universidad de Santiago de Chile, Santiago, Chile.
Cristóbal RojasInstituto de Ingeniería Matemática y Computacional, Pontificia Universidad Católica de Chile, Santiago, Chile.
Claudia Duran-AniotzLatin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile.
Adrián G PalaciosCentro Interdisciplinario de Neurociencia de Valparaíso, Universidad de Valparaíso, Valparaíso, Chile.
Max ChacónDepartamento de Ingeniería Informática, Universidad de Santiago de Chile, Santiago, Chile.
Leonel E MedinaDepartamento de Ingeniería Informática, Universidad de Santiago de Chile, Santiago, Chile. leonel.medina@usach.cl.

Funding

Alzheimer's Association 2018-AARG-591107
6 · The paper itself

Abstract

Alzheimer's disease (AD) is one of the most significant health challenges of our time, affecting a growing number of the elderly population. In recent years, the retina has received increased attention as a candidate for AD biomarkers since it appears to manifest the pathological signatures of the disease. Therefore, its electrical activity may hint at AD-related physiological changes. However, it is unclear how AD affects retinal electrophysiology and what tools are more appropriate to detect these possible changes. In this study, we used entropy tools to estimate the complexity of the dynamics of healthy and diseased retinas at different ages. We recorded microelectroretinogram responses to visual stimuli of different nature from retinas of young and adult, wild-type and 5xFAD-an animal model of AD-mice. To estimate the complexity of signals, we used the multiscale entropy approach, which calculates the entropy at several time scales using a coarse graining procedure. We found that young retinas had more complex responses to different visual stimuli. Further, the responses of young, wild-type retinas to natural-like stimuli exhibited significantly higher complexity than young, 5xFAD retinas. Our findings support a theory of complexity-loss with aging and disease and can have significant implications for early AD diagnosis.

Indexed as

Alzheimer DiseaseAgedAgingAnimalsDisease Models, AnimalEntropyHumansMiceRetina

Identifiers

PMID35614075
PMCPMC9132967

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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 Socratic graph.