John Adeola Adegoke

Spectroscopic techniques have emerged as crucial tools in the field of malaria research, offering immense potential for improved diagnosis and enhanced understanding of the disease. This review article pays tribute to the pioneering contributions of Professor Henry Mantsch in the realm of clinical biospectroscopy, by comprehensively exploring the diverse applications of spectroscopic methods in malaria research. From the identification of reliable biomarkers to the development of innovative diagnostic approaches, spectroscopic techniques spanning the ultraviolet to far-infrared regions have played a pivotal role in advancing our knowledge of malaria. This review will highlight the multifaceted ways in which spectroscopy has contributed to the field, with a particular emphasis on its impact on diagnostic advancements and drug research. By leveraging the minimally invasive and highly accurate nature of spectroscopic techniques, researchers have made significant strides in improving the detection and monitoring of malaria parasites. These advancements hold the promise of enhancing patient outcomes and aiding in the global efforts towards the eradication of this devastating disease.

Spectroscopic techniques have emerged as crucial tools in the field of malaria research, offering immense potential for improved diagnosis and enhanced understanding of the disease. This re-view article pays tribute to the pioneering contributions of Professor Henry Mantsch in the realm of clinical biospectroscopy, by comprehensively exploring the diverse applications of spectro-scopic methods in malaria research. From the identification of reliable biomarkers to the devel-opment of innovative diagnostic approaches, spectroscopic techniques spanning the ultraviolet to far-infrared regions have played a pivotal role in advancing our knowledge of malaria. This re-view will highlight the multifaceted ways in which spectroscopy has contributed to the field, with a particular emphasis on its impact on diagnostic advancements and drug research. By leverag-ing the minimally invasive and highly accurate nature of spectroscopic techniques, researchers have made significant strides in improving the detection and monitoring of malaria parasites. These advancements hold the promise of enhancing patient outcomes and aiding in the global ef-forts towards the eradication of this devastating disease.

Invited for this month‘s cover are the collaborating group(s) of Center for Biospectroscopy at Monash University and Austin Health at the University of Melbourne, University of Eastern Finland and the University of Queensland. The cover‐art shows a handheld near‐infrared spectroscopic probe to detect fibrosis in real time using a murine model. More information can be found in the Research Article by John A. Adegoke, Jaishankar Raman, Bayden R. Wood, and co‐workers.

Clinical diagnosis of fibrosis is currently reliant on conventional methods. The current “gold standard” for fibrosis diagnosis is histological examination of a biopsy, which is labour intensive and requires extensive sample preparation. Here we show that a portable handheld near‐infrared spectrometer coupled with machine learning algorithms can discriminate between kidney and cardiac fibrosis in a rat model of kidney failure compared to healthy rats without kidney failure. The most significant changes in the spectra of fibrotic tissue included shifts in absorption bands at 1509, 1581, 1689 and 1725 nm attributed to collagen components. The best discrimination of fibrosis was achieved in kidney tissue (AUC=0.962), which showed a higher level of fibrosis compared to cardiac tissue (AUC=0.882). The results show the potential of the NIR spectroscopy to detect and to quantify fibrosis in the heart and kidney that in the future could be applied as an intraoperative surgical tool to guide surgical procedures.

Visible microspectroscopy combined with machine learning is able to detect and quantify functional malaria infected erythrocytes at different stages of the P. falciparum erythrocytic life cycle.