A new approach to find biomarkers in (CFS/ME) by single-cell Raman micro-spectroscopy, 2018, Morten et al

[FMMM1]

Thanks to Andy I was able to access the paper. Here's the statement I was looking for [quote from paper]:
"A total accuracy of 98.1% was achieved based on 206 Raman spectra. Notably, with an increasing sample size and number of Raman spectra to construct the reference database, classification models with better robustness can be achieved. As one Raman spectrum can be obtained within seconds, one patient sample that consists of multiple spectra and multiple cells can be characterized and classified within a few minutes, which implies an enormous potential and feasibility in clinical practice."

@EspeMor @JaimeS

 

[Sly Saint]

A new approach to find biomarkers in chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) by single-cell Raman micro-spectroscopy

Abstract
Chronic fatigue syndrome (CFS), also called myalgic encephalomyelitis (ME), is a debilitating disorder characterized by physical and mental exhaustion. Mitochondrial and energetic dysfunction has been investigated in CFS patients due to a hallmark relationship with fatigue; however, no consistent conclusion has yet been achieved.

Single-cell Raman spectra (SCRS) are label-free biochemical profiles, indicating phenotypic fingerprints of single cells. In this study, we applied a new approach using single-cell Raman microspectroscopy (SCRM) to examine ρ0 cells that lack mitochondrial DNA (mtDNA), and peripheral blood mononuclear cells (PBMCs) from CFS patients and healthy controls.

The experimental results show that Raman bands associated with phenylalanine in ρ0 cells and CFS patient PBMCs were significantly higher than those of the wild-type model and healthy controls. As similar changes were observed in the ρ0 cell model with a known deficiency in the mitochondrial respiratory chain as well as in CFS patients, our results suggest that the increase in cellular phenylalanine may be related to mitochondrial/energetic dysfunction in both systems.

Interestingly, phenylalanine can be used as a potential biomarker for the diagnosis of CFS by SCRM. A machine learning classification model achieved an accuracy rate of 98% correctly assigning Raman spectra to either the CFS group or the control group. SCRM combined with a machine learning algorithm therefore has the potential to become a diagnostic tool for CFS.

"This article is part of the themed collection: Next wave advances in single cell analyses"

https://pubs.rsc.org/fa/content/articlelanding/2019/an/c8an01437j#!divAbstract

 

[Hutan]

This team has replicated the study in a larger group. Unfortunately, the finding of higher phenylalanine in Me/CFS doesn't seem to hold up.
Developing a blood cell-based diagnostic test for ME/CFS using peripheral blood mononuclear cells 2023 Xu, Morten et al