Effects of Polarizer-Analyzer Configurations for FTIR Spectroscopy: Implications for Multiple Polarization Algorithms.

Polarized Fourier transform infrared (p-FTIR) spectroscopy is a widely used technique for determining orientational information in thin organic materials. Conventionally, a single polarizer is placed in the path of the incident light (termed the polarizer). Occasionally, a second polarizer is also placed after the sample (referred to as the analyzer). However, this polarizer-analyzer configuration has the potential to induce polarization-dependent variances in the final spectra beyond those that are expected, i.e., the squared-cosine relationship of absorptance with respect to polarization angle is no longer accurate. These variances are due to changes in the polarization state of the transmitted light induced by the sample and have yet to be explored in the context of p-FTIR. Consequently, this study employs both theoretical and experimental approaches to identify the effects of including a second polarizer in p-FTIR analyses of anisotropic organic samples. For thin samples, the most significant spectral variance arising from only birefringence is observed on the shoulders of the dichroic peaks. By adopting a crossed polarizer configuration, it is shown that there is potential to identify anisotropy of samples that are generally considered too thick for p-FTIR analysis by exploiting this feature. Furthermore, the squared-cosine relationship of absorptance with respect to the polarization angle is also shown to be inapplicable when a second parallel-oriented polarizer is included. Accordingly, a function that accounts for the second polarizer is proposed for multiple polarization techniques.

Point-of-care detection of fibrosis in liver transplant surgery using near-infrared spectroscopy and machine learning.

Introduction: Visual assessment and imaging of the donor liver are inaccurate in predicting fibrosis and remain surrogates for histopathology. We demonstrate that 3-s scans using a handheld near-infrared-spectroscopy (NIRS) instrument can identify and quantify fibrosis in fresh human liver samples. Methods: We undertook NIRS scans on 107 samples from 27 patients, 88 from 23 patients with liver disease, and 19 from four organ donors. Results: Liver disease patients had a median immature fibrosis of 40% (interquartile range [IQR] 20-60) and mature fibrosis of 30% (10%-50%) on histopathology. The organ donor livers had a median fibrosis (both mature and immature) of 10% (IQR 5%-15%). Using machine learning, this study detected presence of cirrhosis and METAVIR grade of fibrosis with a classification accuracy of 96.3% and 97.2%, precision of 96.3% and 97.0%, recall of 96.3% and 97.2%, specificity of 95.4% and 98.0% and area under receiver operator curve of 0.977 and 0.999, respectively. Using partial-least square regression machine learning, this study predicted the percentage of both immature (R 2 = 0.842) and mature (R 2 = 0.837) with a low margin of error (root mean square of error of 9.76% and 7.96%, respectively). Conclusion: This study demonstrates that a point-of-care NIRS instrument can accurately detect, quantify and classify liver fibrosis using machine learning.

Linearly Polarized Infrared Spectroscopy for the Analysis of Biological Materials.

The analysis of biological samples with polarized infrared spectroscopy (p-IR) has long been a widely practiced method for the determination of sample orientation and structural properties. In contrast to earlier works, which employed this method to investigate the fundamental chemistry of biological systems, recent interests are moving toward "real-world" applications for the evaluation and diagnosis of pathological states. This focal point review provides an up-to-date synopsis of the knowledge of biological materials garnered through linearly p-IR on biomolecules, cells, and tissues. An overview of the theory with special consideration to biological samples is provided. Different modalities which can be employed along with their capabilities and limitations are outlined. Furthermore, an in-depth discussion of factors regarding sample preparation, sample properties, and instrumentation, which can affect p-IR analysis is provided. Additionally, attention is drawn to the potential impacts of analysis of biological samples with inherently polarized light sources, such as synchrotron light and quantum cascade lasers. The vast applications of p-IR for the determination of the structure and orientation of biological samples are given. In conclusion, with considerations to emerging instrumentation, findings by other techniques, and the shift of focus toward clinical applications, we speculate on the future directions of this methodology.

Identification of Glucose-6 Phosphate Dehydrogenase Deficient Patients Using Attenuated Total Reflection Fourier Transform Infrared Spectroscopy Using Partial Least Squares Discriminant Analysis in Aqueous Blood Samples.

Glucose-6 phosphate dehydrogenase (G6PD) deficiency is an X-linked blood disease that affects 400 million people globally and is especially prevalent in malaria-endemic regions. A significant portion of carriers are asymptomatic and undiagnosed posing complications in the eradication of malaria as it restricts the types of drugs used for malaria treatment. A simple and accurate diagnosis of the deficiency is vital in the eradication of malaria. In this study, we investigate the potential of attenuated total reflection Fourier transform infrared spectroscopy (ATR FT-IR) as a diagnostic technique for G6PD deficiency. Venous blood samples were collected in lithium heparin anticoagulant tubes from G6PD partial and fully deficient volunteers, n = 17, and normal volunteers, n = 59, in Khon Kaen, Thailand. Spectra of aqueous and dry samples were acquired of whole blood, plasma, and red blood cells, and modeled using partial least squares discriminant analysis (PLS-DA). PLS-DA modeling resulted in a sensitivity of 0.800 and specificity of 0.800 correctly classifying fully deficient participants as well as a majority of partially deficient females who are often misdiagnosed as normal by current screening methods. The viability of utilizing aqueous samples has always been hindered by the variability of hydration in the sample, but by employing multicurve curve resolution-alternating least squares to subtract water from each sample we are able to produce high-quality spectra with minimized water contributions. The approach shows proof of principle that ATR FT-IR combined with multivariate data analysis could become a frontline screening tool for G6PD deficiency by improving tailored drug treatments and ultimately saving lives.

Near-infrared spectroscopy for structural bone assessment.

Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds. A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp). NIRS scans on both the inner (trabecular) surface or outer (cortical) surface accurately identified variations in bone collagen, water, mineral, and fat content, which then accurately predicted bone volume fraction (BV/TV, inner R2 = 0.91, outer R2 = 0.83), thickness (Tb.Th, inner R2 = 0.9, outer R2 = 0.79), and cortical thickness (Ct.Th, inner and outer both R2 = 0.90). NIRS scans also had 100% classification accuracy in grading the quartile of bone thickness and quality. We believe this is a fundamental step forward in creating an instrument capable of intraoperative real-time use.

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 Combined Near-Infrared and Mid-Infrared Spectroscopic Approach for the Detection and Quantification of Glycine in Human Serum.

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.

Visible microspectrophotometry coupled with machine learning to discriminate the erythrocytic life cycle stages of P. falciparum malaria parasites in functional single cells.

Malaria was regarded as the most devastating infectious disease of the 21st century until the COVID-19 pandemic. Asexual blood staged parasites (ABS) play a unique role in ensuring the parasite's survival and pathogenesis. Hitherto, there have been no spectroscopic reports discriminating the life cycle stages of the ABS parasite under physiological conditions. The identification and quantification of the stages in the erythrocytic life cycle is important in monitoring the progression and recovery from the disease. In this study, we explored visible microspectrophotometry coupled to machine learning to discriminate functional ABS parasites at the single cell level. Principal Component Analysis (PCA) showed an excellent discrimination between the different stages of the ABS parasites. Support Vector Machine Analysis provided a 100% prediction for both schizonts and trophozoites, while a 92% and 98% accuracy was achieved for predicting control and ring staged infected RBCs, respectively. This work shows proof of principle for discriminating the life cycle stages of parasites in functional erythrocytes using visible microscopy and thus eliminating the drying and fixative steps that are associated with other optical-based spectroscopic techniques.

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.

Haemoprocessor: A Portable Platform Using Rapid Acoustically Driven Plasma Separation Validated by Infrared Spectroscopy for Point-of-Care Diagnostics.

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.

Fatty acid distribution and polymorphism in solid lipid particles of milkfat and long chain omega-3 fatty acids.

Saturated fatty acid-containing lipids, such as milkfat, may protect long chain polyunsaturated fatty acids in fish oil when blended together into solid lipid particles (SLPs). One of the main challenges of SLPs is structural polymorphism, which can lead to expulsion of the protected component during prolonged storage. To investigate this phenomenon, the change in thermal and crystalline behaviours, and fatty acid distribution, were analysed in SLPs of fish oil and milkfat during storage at different temperatures for up to 28 days. X-ray diffraction analysis showed changes in molten and crystalline states occurred even at -22 °C. Room temperature (21 °C) storage led to more than 45% molten state but SLPs retained their initial shape. Confocal Raman Spectroscopy of the SLPs showed the distribution of fatty acids was not uniform, with 10 µm outermost layer of predominantly saturated fatty acids likely responsible for the intact SLP shape and stability of the core.

Disposable Coverslip for Rapid Throughput Screening of Malaria Using Attenuated Total Reflection Spectroscopy.

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, nonperturbative, and nondestructive technique with high diagnostic potential for the early detection of disease agents. In particular, the fingerprinting capability of attenuated total reflection spectroscopy is promising as a point-of-care 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 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, attenuated total reflection spectroscopy was able to detect and quantify the parasitemia with root mean square error of cross-validation and R2 values of 0.177 and 0.985, respectively. Here, we characterize 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 internal reflection element.

ATR-FTIR spectroscopy as a quality control system for monitoring the storage of blood products.

Blood screening is a fundamental part of disease diagnosis and monitoring health. Attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy offers an innovative solution to streamlining the process, especially for multianalyte detection in aqueous samples. However, samples always undergo a storage phase before they are processed for testing and blood transfusion. In this study, we investigated the effect of standard storage procedures on the macromolecular composition of whole blood, and plasma collected in blood tubes for diagnostic purposes and initial screening of blood products. Periphery blood samples were collected from 10 volunteers and then stored for 14 days at 4 °C. Samples were stored as isolated plasma and whole blood to provide three different datasets, namely: (1) plasma stored independently, (2) plasma stored with other blood components and (3) whole blood. ATR-FTIR spectra of aqueous blood were acquired every 24 h from the time of collection on a portable ATR-FTIR spectrophotometer to monitor the evolution of the macromolecular composition in each blood component. Principal component analysis (PCA), partial least squares regression (PLS-R) and multi-curve resolution alternate least squares (MCR-ALS) models were built to study changes in the spectra with the storage time and identify the key bands. Isolated plasma stored without red blood cells (RBCs) showed no changes over the 14 day period indicating limited degradation. By contrast, plasma stored with the other blood components showed visual and spectroscopic signs of degradation including increasing lipid bands and the amide I and II bands from haemoglobin (Hb). Ideally, for the application of IR spectroscopy in blood diagnostics and for initial screening of blood products, whole blood and isolated red blood cells can be stored for a maximum of 4 days at 4 °C in lithium-heparin anticoagulant tubes prior to spectral analysis before any signs of degradation. Isolated plasma, on the other hand, can be stored for much longer periods and shows no evidence of degradation in the spectra after 14 days.

Detection of Human Cholangiocarcinoma Markers in Serum Using Infrared Spectroscopy.

Cholangiocarcinoma (CCA) is a malignancy of the bile duct epithelium. Opisthorchis viverrini infection is a known high-risk factor for CCA and in found, predominantly, in Northeast Thailand. The silent disease development and ineffective diagnosis have led to late-stage detection and reduction in the survival rate. Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) is currently being explored as a diagnostic tool in medicine. In this study, we apply ATR-FTIR to discriminate CCA sera from hepatocellular carcinoma (HCC), biliary disease (BD) and healthy donors using a multivariate analysis. Spectral markers differing from healthy ones are observed in the collagen band at 1284, 1339 and 1035 cm-1, the phosphate band (vsPO2-) at 1073 cm-1, the polysaccharides band at 1152 cm-1 and 1747 cm-1 of lipid ester carbonyl. A Principal Component Analysis (PCA) shows discrimination between CCA and healthy sera using the 1400-1000 cm-1 region and the combined 1800-1700 + 1400-1000 cm-1 region. Partial Least Square-Discriminant Analysis (PLS-DA) scores plots in four of five regions investigated, namely, the 1400-1000 cm-1, 1800-1000 cm-1, 3000-2800 + 1800-1000 cm-1 and 1800-1700 + 1400-1000 cm-1 regions, show discrimination between sera from CCA and healthy volunteers. It was not possible to separate CCA from HCC and BD by PCA and PLS-DA. CCA spectral modelling is established using the PLS-DA, Support Vector Machine (SVM), Random Forest (RF) and Neural Network (NN). The best model is the NN, which achieved a sensitivity of 80-100% and a specificity between 83 and 100% for CCA, depending on the spectral window used to model the spectra. This study demonstrates the potential of ATR-FTIR spectroscopy and spectral modelling as an additional tool to discriminate CCA from other conditions.

Ultraviolet/Visible and Near-Infrared Dual Spectroscopic Method for Detection and Quantification of Low-Level Malaria Parasitemia in Whole Blood.

The scourge of malaria infection continues to strike hardest against pregnant women and children in Africa and South East Asia. For global elimination, testing methods that are ultrasensitive to low-level ring-staged parasitemia are urgently required. In this study, we used a novel approach for diagnosis of malaria infection by combining both electronic ultraviolet-visible (UV/vis) spectroscopy and near infrared (NIR) spectroscopy to detect and quantify low-level (1-0.000001%) ring-staged malaria-infected whole blood under physiological conditions uisng Multiclass classification using logistic regression, which showed that the best results were achieved using the extended wavelength range, providing an accuracy of 100% for most parasitemia classes. Likewise, partial least-squares regression (PLS-R) analysis showed a higher quantification sensitivity (R2 = 0.898) for the extended spectral region compared to UV/vis and NIR (R2 = 0.806 and 0.556, respectively). For quantifying different-stage blood parasites, the extended wavelength range was able to detect and quantify all thePlasmodium falciparum accurately compared to testing each spectral component separately. These results demonstrate the potential of a combined UV/vis-NIR spectroscopy to accurately diagnose malaria-infected patients without the need for elaborate sample preparation associated with the existing mid-IR approaches.

Addressing Delicate and Variable Cancer Morphology in Spectral Histopathology Using Canine Visceral Hemangiosarcoma.

Spectral histopathology has shown promise for the classification and diagnosis of tumors with defined morphology, but application in tumors with variable or diffuse morphologies is yet to be investigated. To address this gap, we evaluated the application of Fourier transform infrared (FTIR) imaging as an accessory diagnostic tool for canine hemangiosarcoma (HSA), a vascular endothelial cell cancer that is difficult to diagnose. To preserve the delicate vascular tumor tissue structure, and potential classification of single endothelial cells, paraffin removal was not performed, and a partial least square discrimination analysis (PLSDA) and Random Forest (RF) models to classify different tissue types at individual pixel level were established using a calibration set (24 FTIR images from 13 spleen specimens). Next, the prediction capability of the PLSDA model was tested with an independent test set (n = 11), resulting in 74% correct classification of different tissue types at an individual pixel level. Finally, the performance of the FTIR spectropathology and chemometric algorithm for diagnosis of HSA was established in a blinded set of tissue samples (n = 24), with sensitivity and specificity of 80 and 81%, respectively. Taken together, these results show that FTIR imaging without paraffin removal can be applied to tumors with diffuse morphology, and this technique is a promising tool to assist in canine splenic HSA differential diagnosis.

Multiplexed Fourier Transform Infrared and Raman Imaging.

Infrared (IR) and Raman spectroscopies are being increasingly employed for the label-free analysis of biochemical samples. Both are vibrational imaging techniques, but they provide complementary information about the chemical composition of the sample, and thus the integration of Raman and IR images leads to a comprehensive understanding of the samples. Here, we summarize the steps needed for performing multiplexed infrared and Raman imaging, identifying and overcoming the two main challenges: first, the technical difficulties caused by the incompatibilities of the techniques and, second, the necessity to extract the information from the large number of vibrational variables found in both IR and Raman spectra.

Correction: Synchrotron macro ATR-FTIR microspectroscopy for high-resolution chemical mapping of single cells.

Correction for 'Synchrotron macro ATR-FTIR microspectroscopy for high-resolution chemical mapping of single cells' by Jitraporn Vongsvivut et al., Analyst, 2019, 144, 3226-3238, DOI: 10.1039/C8AN01543K.