The magnitude of infectious diseases in the twenty-first century created an urgent need for point-of-care diagnostics. Critical shortages in reagents and testing kits have had a large impact on the ability to test patients with a suspected parasitic, bacteria, fungal, and viral infections. New point-of-care tests need to be highly sensitive, specific, and easy to use and provide results in rapid time. Infrared spectroscopy, coupled to multivariate and machine learning algorithms, has the potential to meet this unmet demand requiring minimal sample preparation to detect both pathogenic infectious agents and chronic disease markers in blood. This focal point article will highlight the application of Fourier transform infrared spectroscopy to detect disease markers in blood focusing principally on parasites, bacteria, viruses, cancer markers, and important analytes indicative of disease. Methodologies and state-of-the-art approaches will be reported and potential confounding variables in blood analysis identified. The article provides an up to date review of the literature on blood diagnosis using infrared spectroscopy highlighting the recent advances in this burgeoning field.

Malaria is a life-threatening disease caused by a parasite, which can be transmitted to humans through bites of infected female Anopheles mosquitoes. This disease plagues a significant population of the...

Malaria is considered to be one of the most catastrophic health issues in the whole world. Vibrational spectroscopy is a rapid, robust, label-free, inexpensive, highly sensitive, non-perturbative and non-destructive technique with high diagnostic potential for the early detection of disease agents. In particular, the fingerprinting capability of Attenuated Total Reflection (ATR) spectroscopy is promising as a point-of-care (POC) diagnostic tool in resource limited areas. However, improvements are required to expedite the measurements of biofluids, including the drying procedure and subsequent cleaning of the internal reflection element (IRE) to enable high throughput successive measurements. As an alternative, we propose using an inexpensive coverslip to reduce the sample preparation time by enabling multiple samples to be collectively dried together under the same temperature and conditions. In conjunction with Partial Least-Squares Regression (PLS-R), ATR spectroscopy was able to detect and quantify the parasitemia with Root Mean Square Error of Cross Validation (RMSECV) and R² values of 0.177 and 0.985, respectively. Here we characterise an inexpensive, disposable coverslip for the high throughput screening of malaria parasitic infections and thus demonstrate an alternative approach to direct deposition of the sample onto the IRE.

The identification of biomarkers from blood plasma is at the heart of many diagnostic tests. These tests often need to be conducted frequently and quickly, but the logistics of sample collection and processing not only delays the test result, but also puts a strain on the healthcare system due to the sheer volume of tests that need to be performed. The advent of microfluidics has made the processing of samples quick and reliable, with little or no skill required on the user’s part. However, while several microfluidic devices have been demonstrated for plasma separation, none of them have validated the chemical integrity of the sample post-process. Here, we present Haemoprocessor: a portable, robust, open-fluidic system that utilizes Travelling Surface Acoustic Waves (TSAW) with the expression of overtones to separate plasma from 20× diluted human blood within a span of 2 min to achieve 98% RBC removal. The plasma and red blood cell separation quality/integrity was validated through Attenuated Total Reflection Fourier Transform Infrared (ATR-FTIR) spectroscopy and multivariate analyses to ascertain device performance and reproducibility when compared to centrifugation (the prevailing gold-standard for plasma separation). Principal Component Analysis (PCA) showed a remarkable separation of 92.21% between RBCs and plasma components obtained through both centrifugation and Haemoprocessor methods. Moreover, a close association between plasma isolates acquired by both approaches in PCA validated the potential of the proposed system as an eminent cell enrichment and plasma separation platform. Thus, compared to contemporary acoustic devices, this system combines the ease of operation, low sample requirement of an open system, the versatility of a SAW device using harmonics, and portability.

Serum is an important candidate in proteomics analysis as it potentially carries key markers on health status and disease progression. However, several important diagnostic markers found in the circulatory proteome and the low-molecular-weight (LMW) peptidome have become analytically challenging due to the high dynamic concentration range of the constituent protein/peptide species in serum. Herein, we propose a novel approach to improve the limit of detection (LoD) of LMW amino acids by combining mid-IR (MIR) and near-IR spectroscopic data using glycine as a model LMW analyte. This is the first example of near-IR spectroscopy applied to elucidate the detection limit of LMW components in serum; moreover, it is the first study of its kind to combine mid-infrared (25–2.5 μm) and near-infrared (2500–800 nm) to detect an analyte in serum. First, we evaluated the prediction model performance individually with MIR (ATR-FTIR) and NIR spectroscopic methods using partial least squares regression (PLS-R) analysis. The LoD was found to be 0.26 mg/mL with ATR spectroscopy and 0.22 mg/mL with NIR spectroscopy. Secondly, we examined the ability of combined spectral regions to enhance the detection limit of serum-based LMW amino acids. Supervised extended wavelength PLS-R resulted in a root mean square error of prediction (RMSEP) value of 0.303 mg/mL and R2 value of 0.999 over a concentration range of 0–50 mg/mL for glycine spiked in whole serum. The LoD improved to 0.17 mg/mL from 0.26 mg/mL. Thus, the combination of NIR and mid-IR spectroscopy can improve the limit of detection for an LMW compound in a complex serum matrix.