Evidence map›Paper›PMID 42817954›Full record

ArticlebioRxiv : the preprint server for biology2026

Impact of noise on optical redox ratio estimation.

Evan K Sharafuddin, Xinyuan Zhang, Hong Hu, Janet E Sorrells

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Evan K SharafuddinDepartment of Electrical And Systems Engineering, McKelvey School of Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, MO 63130, USA.ORCID 0000-0002-1733-8601
Xinyuan ZhangDepartment of Electrical And Systems Engineering, McKelvey School of Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, MO 63130, USA.
Hong HuDepartment of Electrical And Systems Engineering, McKelvey School of Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, MO 63130, USA.
Janet E SorrellsDepartment of Electrical And Systems Engineering, McKelvey School of Engineering, Washington University in St. Louis, 1 Brookings Drive, St. Louis, MO 63130, USA.ORCID 0000-0003-0071-8509

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical redox ratio (ORR) is a commonly used metric to quantify the metabolic state of biological samples based on autofluorescence of NAD(P)H and FAD. Despite its relevance and popularity, little work has been done to quantify the estimation error of ORR, especially in low-photon count data. Here, we provide an analytical solution to determine ORR variability in the presence of shot noise and dark counts. We then validate this analytical model with simulated and experimental data. This work will enable researchers to quantify the uncertainty in their ORR measurements, aiding in more accurate and efficient experimental design and data analysis.

Identifiers

PMID42817954
PMCPMC13622034

What Socratic holds

Textmetadata
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.