Infrared Spectroscopy of Blood

Comparison of two metabolomics-platforms to discover biomarkers in critically ill patients from serum analysis

Serum metabolome analysis is essential for identifying disease biomarkers and predicting patient outcomes in precision medicine. Thus, this study aims to compare Ultra-High Performance Liquid Chromatography-High-Resolution Mass Spectrometry (UHPLC-HRMS) with Fourier Transform Infrared (FTIR) spectroscopy in acquiring the serum metabolome of critically ill patients, associated with invasive mechanical ventilation (IMV), and predicting death. Three groups of 8 patients were considered. Group A did not require IMV and survived hospitalization, while Groups B and C required IMV. Group C patients died a median of 5 days after sample harvest. Good prediction models were achieved when comparing groups A to B and B to C using both platforms' data, with UHPLC-HRMS showing 8-17 % higher accuracies (≥83 %). However, developing predictive models using metabolite sets was not feasible when comparing unbalanced populations, i.e., Groups A and B combined to Group C. Alternatively, FTIR-spectroscopy enabled the development of a model with 83 % accuracy. Overall, UHPLC-HRMS data yields more robust prediction models when comparing homogenous populations, potentially enhancing understanding of metabolic mechanisms and improving patient therapy adjustments. FTIR-spectroscopy is more suitable for unbalanced populations. Its simplicity, speed, cost-effectiveness, and high-throughput operation make it ideal for large-scale studies and clinical translation in complex populations.

High-fat/high-fructose diet and Opisthorchis viverrini infection promote metabolic dysfunction-associated steatotic liver disease via inflammation, fibrogenesis, and metabolic dysfunction

Metabolic dysfunction-associated steatotic liver disease (MASLD) and opisthorchiasis, caused by Opisthorchis viverrini (O. viverrini) infection, frequently co-exist in Northeast Thailand. However, the underlying pathophysiology remains unknown. We aimed to investigate the effect of a high-fat/high-fructose (HFF) diet combined with O. viverrini infection on MASLD. Four groups each of ten male golden hamsters were established: normal controls (NC), O. viverrini-infected (OV), HFF-fed, and HFF-fed plus O. viverrini infection (HFF+OV). After four months of treatment, histopathological study indicated substantial hepatic damage in groups given the HFF diet. In particular, the HFF+OV group demonstrated marked lipid-droplet accumulation, hepatocyte ballooning, inflammatory-cell clustering, and widespread fibrosis. Biochemical tests indicated that the HFF+OV group had the highest concentrations of alanine aminotransferase and triglycerides, but cholesterol and low-density lipoprotein levels had increased in both HFF groups. Increased expression of Tgf-β1 and α-SMA, indicative of greater fibrosis, was demonstrated by picrosirius-red staining in the HFF+OV group. There was a significant increase in levels of inflammatory markers (HMGB-1, p65, and F4/80) and expression of genes related to the synthesis of fatty acids and glucose. FTIR microspectroscopy revealed distinct changes in fatty acids and proteins, associated with the more pronounced histopathology and impaired liver function in the HFF+OV group. The findings indicate that the interplay of a HFF diet and O. viverrini infection aggravates the progression of MASLD by augmenting liver damage, inflammation, fibrogenesis, and metabolic dysfunction. This study highlights the significance of incorporating both nutritional and infection factors into the management of liver disorders, especially in areas where opisthorchiasis is common.

Research progress and application of bacterial traceability technology

Bacterial traceability refers to the use of a range of techniques to trace the origins and transmission pathways of bacteria. It is crucial in controlling the spread of diseases, analyzing bioterrorism incidents, and advancing microbial forensics. In recent years, the frequency and scope of bacterial outbreaks have continued to escalate, exerting significant impacts on global biosecurity, public health, and other areas. Consequently, it is required to process traceability of bacteria timely and accurately around the globe. The rapid development of biological and physicochemical traceability techniques provides convenience for tracing bacteria. These techniques not only surpass traditional methods in terms of sensitivity, traceability and throughput, but also find more extensive applications in elucidating bacterial growth mechanisms, transmission routes, and geographical origins. This paper systematically reviews the latest research progress and applications of technologies of bacterial traceability, highlighting key advancements and projecting future trends, with the intent of providing a valuable reference for researchers, facilitating further studies and innovations in this field.

A Multimodal Spectroscopic Approach Combining Mid-infrared and Near-infrared for Discriminating Gram-positive and Gram-negative Bacteria

The rapid and accurate identification of pathogenic bacteria is crucial for combating the growing threat of antibiotic resistance, nosocomial infections, and food safety concerns. This study presents a novel and comprehensive comparison of two vibrational spectroscopic techniques - attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy and a low-cost miniature near-infrared (NIR) spectrometer - for distinguishing Gram-positive and Gram-negative bacterial samples grown using the same stock media solution. This is the first report of NIR spectroscopy being applied to differentiate Gram-positive and Gram-negative bacteria, as well as the first direct comparison of ATR-FTIR and NIR for the combined multimodal analysis of clinical bacterial isolates. Using a data set of five Gram-positive and seven Gram-negative species and recording spectra in triplicate, the study employed advanced data fusion and multivariate analysis techniques to classify the spectra and facilitate NIR band assignment. 2D correlation analysis revealed strong positive correlations between key spectral markers identified in both modalities. Partial least-squares- and support vector machine discriminant analysis models were validated using a methodology based on 100 repeated random sampling of calibration and test sets. Models demonstrated that both the standalone ATR-FTIR and the combined ATR-FTIR/NIR approach achieved exceptional classification accuracy (>98%) in differentiating the two bacterial groups. Differences observed in the spectra were attributed to the distinct cell wall compositions of Gram-Positive and Gram-negative bacteria. Notably, the low-cost NIR technique also showed promising performance, with classification accuracy values above 90%. The findings highlight the potential of these rapid, noninvasive, and cost-effective vibrational spectroscopic techniques, particularly the NIR method, for point-of-care applications in clinical microbiology and food safety monitoring. The combination of ATR-FTIR and NIR data further enhances the robustness and reliability of bacterial identification, paving the way for broader adoption of these advanced analytical tools in various healthcare and food safety settings.

Advanced Vibrational Spectroscopy and Bacteriophages Team Up: Dynamic Synergy for Medical and Environmental Applications

Bacteriophages are emerging as a promising alternative in combating antibiotic-resistant bacteria amidst the escalating global antimicrobial resistance crisis. Recently, there has been a notable resurgence of interest in phages, prompting extensive research into their therapeutic potential. Beyond conventional microbiology and virology techniques, such as genomics and proteomics, novel phenotypic and chemical characterization methods are being explored. Among these, there is a growing interest in vibrational spectroscopy, especially in advanced modalities such as surface-enhanced Raman spectroscopy (SERS), tip-enhanced Raman spectroscopy (TERS), and atomic force microscopy-infrared spectroscopy (AFM-IR), which offer improved sensitivity and spatial resolution. This review explores the spectrum of uses of vibrational spectroscopy for bacteriophages, including its role in diagnostics, biosensing, phage detection, assistance in phage-based therapy, and advancing basic research.

Perspectives of FTIR as Promising Tool for Pathogen Diagnosis, Sanitary and Welfare Monitoring in Animal Experimentation Models: A Review Based on Pertinent Literature

Currently, there is a wide application in the literature of the use of the Fourier Transform Infrared Spectroscopy (FTIR) technique. This basic tool has also proven to be efficient for detecting molecules associated with hosts and pathogens in infections, as well as other molecules present in humans and animals' biological samples. However, there is a crisis in science data reproducibility. This crisis can also be observed in data from experimental animal models (EAMs). When it comes to rodents, a major challenge is to carry out sanitary monitoring, which is currently expensive and requires a large volume of biological samples, generating ethical, legal, and psychological conflicts for professionals and researchers. We carried out a survey of data from the relevant literature on the use of this technique in different diagnostic protocols and combined the data with the aim of presenting the technique as a promising tool for use in EAM. Since FTIR can detect molecules associated with different diseases and has advantages such as the low volume of samples required, low cost, sustainability, and provides diagnostic tests with high specificity and sensitivity, we believe that the technique is highly promising for the sanitary and stress and the detection of molecules of interest of infectious or non-infectious origin.

Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation

BACKGROUND

Glioma is a primary brain tumor and the assessment of its molecular profile in a minimally invasive manner is important in determining treatment strategies. Among the molecular abnormalities of gliomas, mutations in the isocitrate dehydrogenase (IDH) gene are strong predictors of treatment sensitivity and prognosis. In this study, we attempted to non-invasively diagnose glioma development and the presence of IDH mutations using multivariate analysis of the plasma mid-infrared absorption spectra for a comprehensive and sensitive view of changes in blood components associated with the disease and genetic mutations. These component changes are discussed in terms of absorption wavenumbers that contribute to differentiation.

METHODS

Plasma samples were collected at our institutes from 84 patients with glioma (13 oligodendrogliomas, 17 IDH-mutant astrocytoma, 7 IDH wild-type diffuse glioma, and 47 glioblastomas) before treatment initiation and 72 healthy participants. FTIR-ATR spectra were obtained for each plasma sample, and PLS discriminant analysis was performed using the absorbance of each wavenumber in the fingerprint region of biomolecules as the explanatory variable. This data was used to distinguish patients with glioma from healthy participants and diagnose the presence of IDH mutations.

RESULTS

The derived classification algorithm distinguished the patients with glioma from healthy participants with 83% accuracy (area under the curve (AUC) in receiver operating characteristic (ROC) = 0.908) and diagnosed the presence of IDH mutation with 75% accuracy (AUC = 0.752 in ROC) in cross-validation using 30% of the total test data. The characteristic changes in the absorption spectra suggest an increase in the ratio of β-sheet structures in the conformational composition of blood proteins of patients with glioma. Furthermore, these changes were more pronounced in patients with IDH-mutant gliomas.

CONCLUSIONS

The plasma infrared absorption spectra could be used to diagnose gliomas and the presence of IDH mutations in gliomas with a high degree of accuracy. The spectral shape of the protein absorption band showed that the ratio of β-sheet structures in blood proteins was significantly higher in patients with glioma than in healthy participants, and protein aggregation was a distinct feature in patients with glioma with IDH mutations.

Infrared Spectroscopy for Rapid Triage of Cancer Using Blood Derivatives: A Reality Check

Infrared (IR) spectroscopy of serum/plasma represents an alluring molecular diagnostic tool, especially for cancer, as it can provide a molecular fingerprint of clinical samples based on vibrational modes of chemical bonds. However, despite the superior performance, the routine adoption of this technique for clinical settings has remained elusive. This is due to the potential confounding factors that are often overlooked and pose a significant barrier to clinical translation. In this Perspective, we summarize the concerns associated with various confounding factors, such as fluid sampling, optical effects, hemolysis, abnormal cardiovascular and/or hepatic functions, infections, alcoholism, diet style, age, and gender of a patient or normal control cohort, and improper selection of numerical methods that ultimately would lead to improper spectral diagnosis. We also propose some precautionary measures to overcome the challenges associated with these confounding factors.

Reagentless Vis-NIR Spectroscopy Point-of-Care for Feline Total White Blood Cell Counts

Spectral point-of-care technology is reagentless with minimal sampling (<10 μL) and can be performed in real-time. White blood cells are non-dominant in blood and in spectral information, suffering significant interferences from dominant constituents such as red blood cells, hemoglobin and billirubin. White blood cells of a bigger size can account for 0.5% to 22.5% of blood spectra information. Knowledge expansion was performed using data augmentation through the hybridization of 94 real-world blood samples into 300 synthetic data samples. Synthetic data samples are representative of real-world data, expanding the detailed spectral information through sample hybridization, allowing us to unscramble the spectral white blood cell information from spectra, with correlations of 0.7975 to 0.8397 and a mean absolute error of 32.25% to 34.13%; furthermore, we achieved a diagnostic efficiency between 83% and 100% inside the reference interval (5.5 to 19.5 × 109 cell/L), and 85.11% for cases with extreme high white blood cell counts. At the covariance mode level, white blood cells are quantified using orthogonal information on red blood cells, maximizing sensitivity and specificity towards white blood cells, and avoiding the use of non-specific natural correlations present in the dataset; thus, the specifity of white blood cells spectral information is increased. The presented research is a step towards high-specificity, reagentless, miniaturized spectral point-of-care hematology technology for Veterinary Medicine.

A disposable optofluidic micro-transmission cell with tailorable length for Fourier-transform infrared spectroscopy of biological fluids

Mid-infrared Fourier-transform infrared (FT-IR) spectroscopy of liquid biological samples is limited by the high absorption of water in this spectral range, which makes conventional transmission cuvettes unsuitable as their centimeter-scale length is already too big. The most common alternative relies on the use of attenuated total reflection (ATR) accessories, which provide a small interaction path length for light along the interface between the analyte and the expensive ATR crystals. In this work, we address this issue by proposing a disposable and low-cost micro-transmission cell. Its construction relies on a simple technique, which consists of dispersing plastic spherical microparticles in a liquid sample before dispensing it between two pieces of silicon assembled one onto the other and acting as windows for the cell. Consequently, the microparticles act as a spacer of very precise height in-between the two silicon windows. This technique allows easy construction of infrared absorption cells with near-optimum optical interaction path length just by selecting the most appropriate particle size. The concept is demonstrated by measuring the concentration of glucose in aqueous solutions using microspheres of diameter 20 μm then 40 μm and analyzing the corresponding glucose absorption peaks in the wavenumber range 950-1200 cm-1. The performance is compared to that of standard ATR spectroscopy of the same samples. This resulted in a root-mean-square error of cross-validation (RMSECV) of 58.8 mg dl-1 as obtained for transmission measurements by partial least squares (PLS) regression, which is comparable to the RMSECV of 53 mg dl-1 for single-reflection diamond ATR measurements.

Providing potential solutions by using FT-IR spectroscopy for biofluid analysis: Clinical impact of optical screening and diagnostic tests

BACKGROUND

Currently, the potential of FT-IR spectroscopy for rapid diagnosis of many pathologies has been demonstrated by numerous research studies including those targeting COVID-19 detection. However, the number of clinicians aware of this potential and who are willing to use spectroscopy in their clinics and hospitals is still negligible. In addition, lack of awareness creates a huge gap between clinicians and researchers involved in clinical translation of current FT-IR technology hence hindering initiatives to bring basic and applied research together for the direct benefit of patients.

METHODS

Knowledge and medical training on FT-IR on the side of clinicians should be one of the first steps to be able to integrate it into the list of complementary exams which may be requested by health professionals. Countless FT-IR applications could have a life-changing impact on patients' lives, especially screening and diagnostic tests involving biofluids such as blood, saliva and urine which are routinely non-invasively or minimally-invasively.

RESULTS

Blood may be the most difficult to obtain by the invasive method of collection, but much can be evaluated in its components, and areas such as hematology, infectiology, oncology and endocrinology can be directly benefited. Urine with a relatively simple collection method can provide pertinent information from the entire urinary system, including the actual condition of the kidneys. Saliva collection can be simpler for the patient and can provide information on diseases affecting the mouth and digestive system and can be used to diagnose diseases such as oral cancer in its early-stages. An unavoidable second step is the active involvement of industries to design robust and portable instruments for specific purposes, as the medical community requires user-friendly instruments of advanced computational algorithms. A third step resides in the legal situation involving the global use of the technique as a new diagnostic modality.

CONCLUSIONS

It is important to note that decentralized funds for variety of technologies hinders the training of clinical and medical professionals for the use of newly arising technologies and affect the engagement of these professionals with technology developers. As a result of decentralized funding, research efforts are spread out over a range of technologies which take a long time to get validated and translated to the clinic. Partnership over similar groups of technologies and efforts to test the same technologies while overcoming barriers posed to technology validation in different areas around the globe may benefit the clinical/medical, research and industry community globally.

Infrared analysis in the aqueous humor of patients with uveitis: Preliminary results

Inflammatory processes affecting the uvea result in a temporary o permanent blurred vision and represent an important cause of visual impairment worldwide. It is often hard to make a precise diagnosis which is dependent on the clinical expertise, diagnostic tests, laboratory investigations in blood and sometimes in the aqueous humor (AH). With the aim of obtaining proof of principle Fourier Transformed Infrared (FT-IR) absorbance spectroscopy was applied to study the molecular composition of 72 AH samples collected in 26 patients with uveitis and in 44 controls. The unsupervised exploration of the internal structure of the dataset by principal component analysis reduced hundreds IR variables to those most representative allowing to obtain the predictive model that distinguished the AH spectra of patients with uveitis from controls. The same result was obtained by unsupervised agglomerative cluster analysis. After labeling the spectra with some clinical information it was observed that most severe uveitis with active processes were grouped separately from chronic and relapsing uveitis and controls. The consistence of prediction models is discussed in the light of supporting etiological diagnosis by machine learning processes. In conclusion, proof of principle has been obtained that the IR spectral pattern of AH may reflect particular uveal diseases.

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.

Rapid Biomarker-Based Diagnosis of Fibromyalgia Syndrome and Related Rheumatologic Disorders by Portable FT-IR Spectroscopic Techniques

Fibromyalgia syndrome (FM), one of the most common illnesses that cause chronic widespread pain, continues to present significant diagnostic challenges. The objective of this study was to develop a rapid vibrational biomarker-based method for diagnosing fibromyalgia syndrome and related rheumatologic disorders (systemic lupus erythematosus (SLE), osteoarthritis (OA) and rheumatoid arthritis (RA)) through portable FT-IR techniques. Bloodspot samples were collected from patients diagnosed with FM (n = 122) and related rheumatologic disorders (n = 70), including SLE (n = 17), RA (n = 43), and OA (n = 10), and stored in conventional protein saver bloodspot cards. The blood samples were prepared by four different methods (blood aliquots, protein-precipitated extraction, and non-washed and water-washed semi-permeable membrane filtration extractions), and spectral data were collected with a portable FT-IR spectrometer. Pattern recognition analysis, OPLS-DA, was able to identify the signature profile and classify the spectra into corresponding classes (Rcv > 0.93) with excellent sensitivity and specificity. Peptide backbones and aromatic amino acids were predominant for the differentiation and might serve as candidate biomarkers for syndromes such as FM. This research evaluated the feasibility of portable FT-IR combined with chemometrics as an accurate and high-throughput tool for distinct spectral signatures of biomarkers related to the human syndrome (FM), which could allow for real-time and in-clinic diagnostics of FM.

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.

Technique Evolutions for Microorganism Detection in Complex Samples: A Review

Rapid detection of microorganisms is a major challenge in the medical and industrial sectors. In a pharmaceutical laboratory, contamination of medical products may lead to severe health risks for patients, such as sepsis. In the specific case of advanced therapy medicinal products, contamination must be detected as early as possible to avoid late production stop and unnecessary costs. Unfortunately, the conventional methods used to detect microorganisms are based on time-consuming and labor-intensive approaches. Therefore, it is important to find new tools to detect microorganisms in a shorter time frame. This review sums up the current methods and represents the evolution in techniques for microorganism detection. First, there is a focus on promising ligands, such as aptamers and antimicrobial peptides, cheaper to produce and with a broader spectrum of detection. Then, we describe methods achieving low limits of detection, thanks to Raman spectroscopy or precise handling of samples through microfluids devices. The last part is dedicated to techniques in real-time, such as surface plasmon resonance, preventing the risk of contamination. Detection of pathogens in complex biological fluids remains a scientific challenge, and this review points toward important areas for future research.

ATR-IR Spectroscopy Application to Diagnostic Screening of Advanced Endometriosis

Endometriosis is one of the most common gynecological diseases among young women of reproductive age. Thus far, it has not been possible to define a parameter that is sensitive and specific enough to be a recognized biomarker for diagnosing this disease. Nonspecific symptoms of endometriosis and delayed diagnosis are impulses for researching noninvasive methods of differentiating endometriosis from other gynecological disorders. We compared three groups of individuals in our research: women with endometriosis (E), patients suffering from other gynecological disorders (nonendometriosis, NE), and healthy women from the control group (C). Partial least squares discriminant analysis (PLS-DA) models were developed based on selected serum biochemical parameters, specific regions of the serum’s infrared attenuated total reflectance (FTIR ATR) spectra, and combined data. Incorporating the spectral data into the models significantly improved differentiation among the three groups, with an overall accuracy of 87.5%, 97.3%, and 98.5%, respectively. This study shows that infrared spectroscopy and discriminant analysis can be used to differentiate serum samples among women with advanced endometriosis, women without this disease, i.e., healthy women, and, most importantly, also women with other benign gynecological disorders.

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.

Monitoring Neurochemistry in Traumatic Brain Injury Patients Using Microdialysis Integrated with Biosensors: A Review

In a traumatically injured brain, the cerebral microdialysis technique allows continuous sampling of fluid from the brain’s extracellular space. The retrieved brain fluid contains useful metabolites that indicate the brain’s energy state. Assessment of these metabolites along with other parameters, such as intracranial pressure, brain tissue oxygenation, and cerebral perfusion pressure, may help inform clinical decision making, guide medical treatments, and aid in the prognostication of patient outcomes. Currently, brain metabolites are assayed on bedside analysers and results can only be achieved hourly. This is a major drawback because critical information within each hour is lost. To address this, recent advances have focussed on developing biosensing techniques for integration with microdialysis to achieve continuous online monitoring. In this review, we discuss progress in this field, focusing on various types of sensing devices and their ability to quantify specific cerebral metabolites at clinically relevant concentrations. Important points that require further investigation are highlighted, and comments on future perspectives are provided.

Clinical Spectroscopy: Lost in Translation?

This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.

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.

Investigating the molecular structure of plasma in type 2 diabetes mellitus and diabetic nephropathy by synchrotron Fourier-transform infrared microspectroscopy

Diabetes mellitus (DM) is associated with a high incidence of morbidity and mortality which, in many cases, is derived from the progressive kidney dysfunction due to diabetic nephropathy (DN). In this study, synchrotron-Fourier-transform infrared (SR-FTIR) microspectroscopy was used to identify molecular changes in the lipid and protein regions in the plasma of patients with different stages of DN (mild, moderate, severe and end-stage), and patients with type 2 diabetes mellitus (T2DM) without DN. Our results revealed different conformational changes in the proteins secondary structure between DN stages, and between DN and T2DM groups illustrated by peak shifts and intensity alterations. End-stage DN showed the highest CH₂/CH₃ ratio and intensity of the carbonyl group in protein-carbonyl region compared to other DN stages indicating high level of unsaturation and lipid peroxidation and oxidation conditions. Moreover, end-stage DN group was characterized by a decrease in amide I and amide II absorption signals which reflected a sign of hypoalbuminemia. When compared to T2DM, DN group demonstrated a higher oxidation state as confirmed via the high intensity of the carbonyl group and the high level of malondialdehyde. The current study highlights the promising role of SR-FTIR microspectroscopy as a new sensitive analytical approach that can be used to provide better understanding of the pathophysiology of DN, and guide the development of new preventive therapies and treatments.

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

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.

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.

A Near-Infrared "Matchbox Size" Spectrometer to Detect and Quantify Malaria Parasitemia

New point-of-care diagnostic approaches for malaria that are sensitive to low parasitemia, easy to use in a field setting, and affordable are urgently required to meet the World Health Organization's objective of reducing malaria cases and related life losses by 90% globally on or before 2030. In this study, an inexpensive "matchbox size" near-infrared (NIR) spectrophotometer was used for the first time to detect and quantify malaria infection in vitro from isolated dried red blood cells using a fingerpick volume of blood. This the first study to apply a miniaturized NIR device to diagnose a parasitic infection and identify marker bands indicative of malaria infection in the NIR region. An NIR device has many advantages including wavelength accuracy and repeatability, speed, resolution, and a greatly improved signal-to-noise ratio compared to existing spectroscopic options. Using multivariate data analysis, we discriminated control red blood cells from infected cells and established the limit of detection of the technique. Principal component analysis displayed a good separation between the infected and uninfected RBCs, while partial least-squares regression analysis yielded a robust parasitemia prediction with root-mean-square error of prediction values of 0.446 and 0.001% for the higher and lower parasitemia models, respectively. The R² values of the higher and lower parasitemia models were 0.947 and 0.931, respectively. Finally, an estimated parasitemia detection limit of 0.00001% and a qunatification limit of 0.001% was achieved; to ascertain the true efficacy of the technique for point-of-care screening, clinical studies using large patient numbers are required, which is the subject of future studies.