# Autofluorescence of Red Blood Cells Infected with P. falciparum as a Preliminary Analysis of Spectral Sweeps to Predict Infection

## TL;DR

This study explores using red blood cell autofluorescence to detect malaria infection, finding specific wavelengths that can distinguish infected from uninfected cells with high accuracy.

## Contribution

The study identifies two previously undocumented excitation wavelengths (315 and 320 nm) for detecting Plasmodium falciparum infection via autofluorescence.

## Key findings

- Two excitation wavelengths (315 and 320 nm) accurately differentiate infected from uninfected red blood cells.
- Autofluorescence increases in the ultraviolet and blue regions due to natural fluorophores like tryptophan and FAD.
- Linear Discriminant Analysis correctly classified over 91% of samples, showing strong potential for field diagnostics.

## Abstract

Malaria, an infectious disease caused by parasites of the genus Plasmodium—including the most lethal species, Plasmodium falciparum—alters the physicochemical properties of host red blood cells, including their intrinsic autofluorescence after infecting them. This exploratory study aims to investigate the possibility of using autofluorescence as a method for detecting infection in red blood cells. The autofluorescence spectra of uninfected and in vitro infected red blood cells with Plasmodium falciparum were monitored and compared across an excitation wavelength range of 255 to 630 nm. Principal Component Analysis revealed that only two wavelengths (315 and 320 nm), previously undocumented, were able to accurately differentiate infected from uninfected red blood cells, showing an increase in autofluorescence in the ultraviolet and blue regions. This phenomenon is hypothetically associated with the presence of natural fluorophores such as tryptophan, FAD, NADH, porphyrins, and lipopigments. To classify the samples, Linear Discriminant Analysis (LDA) was employed, and Wilks’ Lambda test confirmed that the discriminant function was significant, enabling correct classification of samples in more than 91% of cases. Overall, our results support the potential use of autofluorescence as an effective approach for detecting malaria parasite infection in red blood cells, with the possibility of implementation in portable devices for rapid field diagnostics.