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PreprintCC BY-NC-NDbioRxiv

Impact of noise on optical redox ratio estimation

  • E. K. Sharafuddin
  • X. Zhang
  • H. Hu
  • J. E. Sorrells1
  1. 1Washington University in St. Louis
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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.

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Cite

BibTeXRIS
BibTeX
@misc{sharafuddin2026impact,
  title = {{Impact of noise on optical redox ratio estimation}},
  author = {E. K. Sharafuddin and X. Zhang and H. Hu and J. E. Sorrells},
  howpublished = {bioRxiv},
  year = {2026},
  month = sep,
  doi = {10.64898/2026.09.18.751471},
  url = {https://www.biorxiv.org/content/10.64898/2026.09.18.751471v1},
  note = {CC BY-NC-ND},
}
RIS
TY  - UNPB
TI  - Impact of noise on optical redox ratio estimation
AU  - E. K. Sharafuddin
AU  - X. Zhang
AU  - H. Hu
AU  - J. E. Sorrells
PY  - 2026
DA  - 2026/09/18
PB  - bioRxiv
DO  - 10.64898/2026.09.18.751471
UR  - https://www.biorxiv.org/content/10.64898/2026.09.18.751471v1
AB  - 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.
ER  -