Characterization of freeze-dried oxidized human red blood cells for pre-transfusion testing by synchrotron FTIR microspectroscopy live-cell analysis.

Oxidative treatment of human red blood cells (RBCs) prior to freeze-drying appears to stabilize the RBCs to withstand dried storage at room temperature. To better understand the effects of oxidation and freeze-drying/rehydration on RBC lipids and proteins, single-cell measurements were performed by synchrotron-based Fourier transform infrared (FTIR) microspectroscopy 'live-cell' (unfixed) analysis. Lipid and protein spectral data of tert-butyl hydroperoxide (TBHP)-oxidized RBCs (oxRBCs), FDoxRBCs and control (untreated) RBCs were compared using principal component analysis (PCA) and band integration ratios. The oxRBCs and FDoxRBCs samples had similar spectral profiles that were clearly different to control RBCs. Spectral changes in the CH stretching region of oxRBCs and FDoxRBCs indicated the presence of increased saturated and shorter-chain lipids, consistent with lipid peroxidation and stiffening of the RBC membrane compared to control RBCs. The PCA loadings plot for the fingerprint region of control RBCs corresponding to the α-helical structure of hemoglobin, shows that oxRBCs and FDoxRBCs have conformational changes in the protein secondary structure to ß-pleated sheets and ß-turns. Finally, the freeze-drying process did not appear to compound or induce additional changes. In this context, FDoxRBCs could become a stable source of reagent RBCs for pre-transfusion blood serology testing. The synchrotron FTIR microspectroscopic live-cell protocol provides a powerful analytical tool to characterize and contrast the effects of different treatments on RBC chemical composition at the single cell level.

Synchrotron-Infrared Microspectroscopy of Live Leishmania major Infected Macrophages and Isolated Promastigotes and Amastigotes.

The prevalence of neglected tropical diseases (NTDs) is advancing at an alarming rate. The NTD leishmaniasis is now endemic in over 90 tropical and sub-tropical low socioeconomic countries. Current diagnosis for this disease involves serological assessment of infected tissue by either light microscopy, antibody tests, or culturing with in vitro or in vivo animal inoculation. Furthermore, co-infection by other pathogens can make it difficult to accurately determine Leishmania infection with light microscopy. Herein, for the first time, we demonstrate the potential of combining synchrotron Fourier-transform infrared (FTIR) microspectroscopy with powerful discrimination tools, such as partial least squares-discriminant analysis (PLS-DA), support vector machine-discriminant analysis (SVM-DA), and k-nearest neighbors (KNN), to characterize the parasitic forms of Leishmania major both isolated and within infected macrophages. For measurements performed on functional infected and uninfected macrophages in physiological solutions, the sensitivities from PLS-DA, SVM-DA, and KNN classification methods were found to be 0.923, 0.981, and 0.989, while the specificities were 0.897, 1.00, and 0.975, respectively. Cross-validated PLS-DA models on live amastigotes and promastigotes showed a sensitivity and specificity of 0.98 in the lipid region, while a specificity and sensitivity of 1.00 was achieved in the fingerprint region. The study demonstrates the potential of the FTIR technique to identify unique diagnostic bands and utilize them to generate machine learning models to predict Leishmania infection. For the first time, we examine the potential of infrared spectroscopy to study the molecular structure of parasitic forms in their native aqueous functional state, laying the groundwork for future clinical studies using more portable devices.

A star shaped acoustofluidic mixer enhances rapid malaria diagnostics via cell lysis and whole blood homogenisation in 2 seconds.

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 world, necessitating the need for better diagnostic platforms to enhance the detection sensitivity, whilst reducing processing times, sample volumes and cost. A critical step in achieving improved detection is the effective lysis of blood samples. Here, we propose the use of an acoustically actuated microfluidic mixer for enhanced blood cell lysis. Guided by numerical simulations, we experimentally demonstrate that the device is capable of lysing a 20× dilution of isolated red blood cells (RBCs) with an efficiency of ∼95% within 350 ms (0.1 mL). Further, experimental results show that the device can effectively lyse whole blood irrespective of its dilution factor. Compared to the conventional method of using water, this platform is capable of releasing a larger quantity of haemoglobin into plasma, increasing the efficiency without the need for lysis reagents. The lysis efficiency was validated with malaria infected whole blood samples, resulting in an improved sensitivity as compared to the unlysed infected samples. Partial least squares-regression (PLS-R) analysis exhibits cross-validated R2 values of 0.959 and 0.98 from unlysed and device lysed spectral datasets, respectively. Critically, as expected, the root mean square error of cross validation (RMSECV) value was significantly reduced in the acoustically lysed datasets (RMSECV of 0.97), indicating the improved quantification of parasitic infections compared to unlysed datasets (RMSECV of 1.48). High lysis efficiency and ultrafast processing of very small sample volumes makes the combined acoustofluidic/spectroscopic approach extremely attractive for point-of-care blood diagnosis, especially for detection of neonatal and congenital malaria in babies, for whom a heel prick is often the only option for blood collection.

Infrared Spectroscopy of Blood.

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.