Evidence mapPaperPMID 40919264Full record

ReviewNeurophotonics2025

Genetically encoded biosensors of metabolic function for the study of neurodegeneration, a review and perspective.

Minglei Zhao, Saman Behboudi Tanourlouee, Sean McCracken, Philip R Williams

Abstract readReview
In one paragraph

Review in Neurophotonics, 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

4 authors.

Minglei ZhaoWashington University School of Medicine, John F. Hardesty, MD Department of Ophthalmology and Visual Sciences, St. Louis, Missouri, United States.
Saman Behboudi TanourloueeWashington University School of Medicine, John F. Hardesty, MD Department of Ophthalmology and Visual Sciences, St. Louis, Missouri, United States.ORCID https://orcid.org/0000-0002-2777-1169
Sean McCrackenWashington University School of Medicine, John F. Hardesty, MD Department of Ophthalmology and Visual Sciences, St. Louis, Missouri, United States.ORCID https://orcid.org/0000-0002-3652-3458
Philip R WilliamsWashington University School of Medicine, John F. Hardesty, MD Department of Ophthalmology and Visual Sciences, St. Louis, Missouri, United States.

Funding

Kinase regulators of retinal ganglion cell survival and axon regenerationR01EY035684 · BOSTON CHILDREN'S HOSPITAL · 2025 to 2025
$629k
Identifying and leveraging strategies of inherently resilient retinal neurons to treat degenerationR01EY032908 · WASHINGTON UNIVERSITY · 2025 to 2025
$385k
NEI NIH HHS R01 EY032908NEI NIH HHS R01 EY035684
6 · The paper itself

Abstract

Nervous system tissue is the most metabolically active in the body and neurons are the primary consumers of oxygen and metabolites in nervous tissue. Many processes support neuronal metabolism, and dysregulation of these processes or intrinsic neuronal metabolism is often tied to neurodegenerative diseases. While many techniques are available to query metabolic function and disease (e.g. Seahorse XF, histology, immunostaining), almost all of these approaches are destructive and few offer cellular resolution. However, genetically encoded biosensors can optically measure metabolic features in any tissue with optical access. Biosensors represent an approach to non-destructively monitor metabolic components and regulatory signaling repeatedly over time in intact tissues. In this review, we discuss the application of genetically encoded biosensors that measure metabolites and metabolic processes as applied to studies of neurodegeneration.

Indexed as

genetically encoded biosensorsmetabolismneurodegeneration

Identifiers

PMID40919264
PMCPMC12408211

What Socratic holds

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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 Socratic graph.