Thin Film Formation of HSA in the Presence of CTAB-Capped Gold Nanorods through Phase Separation

Phase behavior in protein-nanoparticle systems in light of protein corona formation has been investigated. We report the formation of HSA thin films following the addition of a solid protein to a solution of CTAB-capped gold nanorods (AuNRs) via phase separation. The phase separation behavior was observed through UV-vis spectroscopy, turbidity assays, and DLS studies. UV-vis spectra for the protein-AuNR solution indicated a possible self-assembly formation by CTAB-HSA complexes and AuNR-HSA conjugates. The turbidity was found to increase linearly up to 30-50% v/v for each component. The growth phase slope is proportional to the concentration of the components, AuNRs, and HSA, with no lag phase. Dynamic light scattering (DLS) shows the formation of larger aggregates with time, implying a segregated phase of AuNR-HSA and a CTAB-HSA-AuNR network. ζ-potential values confirm surface modification, implying protein corona formation on nanorods. The thin films were also characterized using SEM, AFM, SAXS, XPS, FTIR, and TGA studies. SEM images show a smooth surface with a reduced number of pores, indicating the compactness of the deposited structure. AFM shows two different structural pattern formations with the deposition, indicating possible self-assembly of the protein-conjugated nanoparticles. FTIR studies indicate a change in the hydrogen bonding network and confirm the CTAB-HSA-AuNR complex network formation. The XPS studies indicate Au-S bond formation, along with Au-S-S-Au interactions. SAXS studies indicate the formation of aggregates (oligomers), as well as the presence of dominant attractive intermolecular interactions in the thin films.

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.

Investigating centrifugal filtration of serum-based FTIR spectroscopy for the stratification of brain tumours

Discrimination of brain cancer versus non-cancer patients using serum-based attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy diagnostics was first developed by Hands et al with a reported sensitivity of 92.8% and specificity of 91.5%. Cameron et al. then went on to stratifying between specific brain tumour types: glioblastoma multiforme (GBM) vs. primary cerebral lymphoma with a sensitivity of 90.1% and specificity of 86.3%. Expanding on these studies, 30 GBM, 30 lymphoma and 30 non-cancer patients were selected to investigate the influence on test performance by focusing on specific molecular weight regions of the patient serum. Membrane filters with molecular weight cut offs of 100 kDa, 50 kDa, 30 kDa, 10 kDa and 3 kDa were purchased in order to remove the most abundant high molecular weight components. Three groups were classified using both partial least squares-discriminate analysis (PLS-DA) and random forest (RF) machine learning algorithms; GBM versus non-cancer, lymphoma versus non-cancer and GBM versus lymphoma. For all groups, once the serum was filtered the sensitivity, specificity and overall balanced accuracies decreased. This illustrates that the high molecular weight components are required for discrimination between cancer and non-cancer as well as between tumour types. From a clinical application point of view, this is preferable as less sample preparation is required.

Fast and Deep Diagnosis Using Blood-Based ATR-FTIR Spectroscopy for Digestive Tract Cancers

Attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) of liquid biofluids enables the probing of biomolecular markers for disease diagnosis, characterized as a time and cost-effective approach. It remains poorly understood for fast and deep diagnosis of digestive tract cancers (DTC) to detect abundant changes and select specific markers in a broad spectrum of molecular species. Here, we present a diagnostic protocol of DTC in which the in-situ blood-based ATR-FTIR spectroscopic data mining pathway was designed for the identification of DTC triages in 252 blood serum samples, divided into the following groups: liver cancer (LC), gastric cancer (GC), colorectal cancer (CC), and their different three stages respectively. The infrared molecular fingerprints (IMFs) of DTC were measured and used to build a 2-dimensional second derivative spectrum (2D-SD-IR) feature dataset for classification, including absorbance and wavenumber shifts of FTIR vibration peaks. By comparison, the Partial Least-Squares Discriminant Analysis (PLS-DA) and backpropagation (BP) neural networks are suitable to differentiate DTCs and pathological stages with a high sensitivity and specificity of 100% and averaged more than 95%. Furthermore, the measured IMF data was mutually validated via clinical blood biochemistry testing, which indicated that the proposed 2D-SD-IR-based machine learning protocol greatly improved DTC classification performance.

Improving Vibrational Spectroscopy Prospects in Frontline Clinical Diagnosis: Fourier Transform Infrared on Buccal Mucosa Cancer

We report a novel method with higher than 90% accuracy in diagnosing buccal mucosa cancer. We use Fourier transform infrared spectroscopic analysis of human serum by suppressing confounding high molecular weight signals, thus relatively enhancing the biomarkers’ signals. A narrower range molecular weight window of the serum was also investigated that yielded even higher accuracy on diagnosis. The most accurate results were produced in the serum’s 10–30 kDa molecular weight region to distinguish between the two hardest to discern classes, i.e., premalignant and cancer patients. This work promises an avenue for earlier diagnosis with high accuracy as well as greater insight into the molecular origins of these signals by identifying a key molecular weight region to focus on.

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.

Surface-enhanced Raman spectroscopic analysis of the centrifugally filtered blood serum samples of the hepatitis C patients

BACKGROUND

Previously Raman spectroscopy technique is a use to analyze non-invasive disease related to body fluids.

OBJECTIVES

For the qualitative and quantitative analysis of HCV serum samples surface-enhanced Raman spectroscopy (SERS) based method is developed.

METHOD

Surface-enhanced Raman spectroscopy (SERS) technique is employed for analysis of filtrate portions of blood serum samples of hepatitis C virus (HCV) infected patients and healthy ones by using 50 kDa centrifugal filter device. The filtrate portions of the serum obtained in this way contain proteins smaller than 50 kDa and removal of bigger size protein which allows to acquire SERS spectral features of smaller proteins more effectively which are probably associated with Hepatitis C infection. Moreover, SERS spectral features of the filtrates of different level of viral load including low, medium and high viral loads are compared with SERS spectral features of the filtrate portions of healthy/control serum samples. SERS spectral data sets of different samples are further analyzed by using multivariate data analysis techniques such as principal component analysis (PCA) and partial least square regression (PLSR). Some SERS spectral features are solely observed in the filtrate portions of the serum samples of hepatitis C and their intensities are increased as the level of viral load increases and might be used for HCV diagnosis.

RESULTS

PCA was found helpful for differentiation of SERS spectral data sets of filtrate portions of the serum samples of hepatitis C and healthy persons. The PLSR model helped for the quantification of viral loads in the unknown serum samples with 99 % accuracy.

Mechanochemical Preparation, Characterization and Biological Activity of Stable CuS Nanosuspension Capped by Bovine Serum Albumin

The biocompatible nanosuspension of CuS nanoparticles (NPs) using bovine serum albumin (BSA) as a capping agent was prepared using a two-stage mechanochemical approach. CuS NPs were firstly synthetized by a high-energy planetary ball milling in 15 min by milling elemental precursors. The stability of nanoparticles in the simulated body fluids was studied, revealing zero copper concentration in the leachates, except simulated lung fluid (SLF, 0.015%) and simulated gastric fluid (SGF, 0.078%). Albumin sorption on CuS NPs was studied in static and dynamic modes showing a higher kinetic rate for the dynamic mode. The equilibrium state of adsorption was reached after 90 min with an adsorption capacity of 86 mg/g compared to the static mode when the capacity 59 mg/g was reached after 2 h. Then, a wet stirred media milling in a solution of BSA was introduced to yield the CuS-BSA nanosuspension, being stable for more than 10 months, as confirmed by photon cross-correlation spectroscopy. The fluorescent properties of the nanosuspension were confirmed by photoluminescence spectroscopy, which also showed that tryptophan present in the BSA could be closer to the binding site of CuS than the tyrosine residue. The biological activity was determined by in vitro tests on selected cancer and non-tumor cell lines. The results have shown that the CuS-BSA nanosuspension inhibits the metabolic activity of the cells as well as decreases their viability upon photothermal ablation.

Rapid Discrimination of Neuromyelitis Optica Spectrum Disorder and Multiple Sclerosis Using Machine Learning on Infrared Spectra of Sera

Neuromyelitis optica spectrum disorder (NMOSD) and multiple sclerosis (MS) are both autoimmune inflammatory and demyelinating diseases of the central nervous system. NMOSD is a highly disabling disease and rapid introduction of the appropriate treatment at the acute phase is crucial to prevent sequelae. Specific criteria were established in 2015 and provide keys to distinguish NMOSD and MS. One of the most reliable criteria for NMOSD diagnosis is detection in patient’s serum of an antibody that attacks the water channel aquaporin-4 (AQP-4). Another target in NMOSD is myelin oligodendrocyte glycoprotein (MOG), delineating a new spectrum of diseases called MOG-associated diseases. Lastly, patients with NMOSD can be negative for both AQP-4 and MOG antibodies. At disease onset, NMOSD symptoms are very similar to MS symptoms from a clinical and radiological perspective. Thus, at first episode, given the urgency of starting the anti-inflammatory treatment, there is an unmet need to differentiate NMOSD subtypes from MS. Here, we used Fourier transform infrared spectroscopy in combination with a machine learning algorithm with the aim of distinguishing the infrared signatures of sera of a first episode of NMOSD from those of a first episode of relapsing-remitting MS, as well as from those of healthy subjects and patients with chronic inflammatory demyelinating polyneuropathy. Our results showed that NMOSD patients were distinguished from MS patients and healthy subjects with a sensitivity of 100% and a specificity of 100%. We also discuss the distinction between the different NMOSD serostatuses. The coupling of infrared spectroscopy of sera to machine learning is a promising cost-effective, rapid and reliable differential diagnosis tool capable of helping to gain valuable time in patients’ treatment.

ATR-Spin: an open-source 3D printed device for direct cytocentrifugation onto attenuated total reflectance crystals

Infrared spectroscopy (IR) enables the direct and rapid characterization of cells at the molecular level. Achieving a rapid and consistent cell preparation is critical for the development of point-of-care diagnostics for cell analysis. Here we introduce an open-source, 3D printed device for integrating the isolation, preconcentration, and measurement of attenuated total reflectance IR spectra of cells from biofluids. The tool comprises a disposable card for cytocentrifugation, equipped with magnets, which allows reproducible integration into the pathlength of the IR spectrophotometer. Preliminary results using cell culture media containing A549 cells indicate that this system enables a qualitative and quantitative characterization of cells down to 10 cells μL^-1 by using a single and cost-effective device and within a few minutes.

Molecular Origin of Blood-Based Infrared Spectroscopic Fingerprints*

Infrared spectroscopy of liquid biopsies is a time- and cost-effective approach that may advance biomedical diagnostics. However, the molecular nature of disease-related changes of infrared molecular fingerprints (IMFs) remains poorly understood, impeding the method's applicability. Here we probe 148 human blood sera and reveal the origin of the variations in their IMFs. To that end, we supplemented infrared spectroscopy with biochemical fractionation and proteomic profiling, providing molecular information about serum composition. Using lung cancer as an example of a medical condition, we demonstrate that the disease-related differences in IMFs are dominated by contributions from twelve highly abundant proteins-that, if used as a pattern, may be instrumental for detecting malignancy. Tying proteomic to spectral information and machine learning advances our understanding of the infrared spectra of liquid biopsies, a framework that could be applied to probing of any disease.

Impacts of Space Restriction on the Microstructure of Calcium Silicate Hydrate

The effect of hydration space on cement hydration is essential. After a few days, space restriction affects the hydration kinetics which dominate the expansion, shrinkage and creep of cement materials. The influence of space restriction on the hydration products of tricalcium silicate was studied in this paper. The microstructure, morphology and composition of calcium silicate hydrate (C-S-H) were explored from the perspective of a specific single micropore. A combination of Raman spectra, Fourier transform infrared spectra, scanning electron microscopy and energy dispersive X-ray spectroscopy were employed. The results show that space restriction affects the structure of the hydration products. The C-S-H formed in the micropores was mainly composed of Q³ silicate tetrahedra with a high degree of polymerization. The C-S-H formed under standard conditions with a water to cement ratio of 0.5 mostly existed as Q² units. Space restriction during hydration is conducive to the formation of C-S-H with silica tetrahedra of a high polymerization degree, while the amount of water filling the micropore plays no obvious role on the polymeric structure of C-S-H during hydration.

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.

How to draw the line - Raman spectroscopy as a tool for the assessment of biomedicines

Biomedicines are complex biochemical formulations with multiple components that require extensive quality control during manufacturing and in subsequent batch testing. A proof-of-concept study has shown that an application of Raman spectroscopy can be beneficial for a classification of vaccines. However, the complexity of biomedicines introduces new challenges to spectroscopic methodology that require advanced experimental protocols. We further show the impact of analytical protocols on vaccine classification using R as an Open Source data analysis platform. In conclusion, we advocate for standardized and transparent experimental and analytical procedures and discuss current findings and open challenges.

Detection of Glycine as a Model Protein in Blood Serum Using 2D-IR Spectroscopy

Glycine (Gly) is used as a model system to evaluate the ability of ultrafast two-dimensional infrared (2D-IR) spectroscopy to detect and quantify the low-molecular-weight proteinaceous components of blood serum. Combining data acquisition schemes to suppress absorption bands of H₂O that overlap with the protein amide I band with analysis of peak patterns appearing in the off-diagonal region of the 2D-IR spectrum allows separation of the Gly spectral signature from that of the dominant protein fraction of serum in a transmission-mode 2D-IR measurement without any sample manipulation, e.g., filtration or drying. 2D-IR spectra of blood serum samples supplemented with varying concentrations of Gly were obtained, and a range of data analysis methods compared, leading to a detection limit of ∼3 mg/mL for Gly. The reported methodology provides a platform for a critical assessment of the sensitivity of 2D-IR for measuring the concentrations of amino acids, peptides, and low-molecular-weight proteins present in serum samples. We conclude that, in the case of several clinically relevant diagnostic molecules and their combinations, the potential exists for 2D-IR to complement IR absorption methods as the benefits of the second frequency dimension offered by 2D-IR spectroscopy outweigh the added technical complexity of the measurement.

Quantitative analysis of human blood serum using vibrational spectroscopy

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State of the art of quantitative Vibrational Spectroscopic analysis of human blood serum is reviewed.

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Technical considerations for infrared absorption and Raman analysis are discussed.

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Quantitative analyses of Endogenous and Exogenous constituents are presented.

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The potential for clinical translation of spectroscopic serology is argued.

Analysis of bodily fluids using vibrational spectroscopy has attracted increasing attention in recent years. In particular, infrared spectroscopic screening of blood products, particularly blood serum, for disease diagnostics has been advanced considerably, attracting commercial interests. However, analyses requiring quantification of endogenous constituents or exogenous agents in blood are less well advanced. Recent advances towards this end are reviewed, focussing on infrared and Raman spectroscopic analyses of human blood serum. The importance of spectroscopic analysis in the native aqueous environment is highlighted, and the relative merits of infrared absorption versus Raman spectroscopy are considered, in this context. It is argued that Raman spectroscopic analysis is more suitable to quantitative analysis in liquid samples, and superior performance for quantification of high and low molecular weight components, is demonstrated. Applications for quantitation of viral loads, and therapeutic drug monitoring are also discussed.

Understanding the discrimination and quantification of monoclonal antibodies preparations using Raman spectroscopy

The use of Raman spectroscopy for analytical quality control of anticancer drug preparations in clinical pharmaceutical dispensing units is increasing in popularity, notably supported by commercially available, purpose designed instruments. Although not legislatively compulsory, analytical methods are frequently used post-preparation to verify the accuracy of a preparation in terms of identity and quantity of the drug in solution. However, while the rapid, cost effective and label free analysis achieved with Raman spectroscopy is appealing, it is important to understand the molecular origin of the spectral contributions collected from the solution of actives and excipients, to evaluate the strength and limitation for the technique, which can be used to identify and quantify either the prescribed commercial formulation, and/or the active drug itself, in personalised solutions. In the current study, four commercial formulations, Erbitux®, Truxima®, Ontruzant® and Avastin® of monoclonal antibodies (mAbs), corresponding respectively to cetuximab, rituximab, trastuzumab and bevacizumab have been used to highlight the key role of excipients in discrimination and quantification of the formulations. It is demonstrated that protein based anticancer drugs such as mAbs have a relatively weak Raman response, while excipients such as glycine, trehalose or histidine contribute significantly to the spectra. Multivariate analysis (partial least square regression and partial least square discriminant analysis) further demonstrates that the signatures of the mAbs themselves are not prominent in mathematical models and that those of the excipients are solely responsible for the differentiation of formulation and accurate determination of concentrations. While Raman spectroscopy can successfully validate the conformity of mAbs intravenous infusion solutions, the basis for the analysis should be considered, and special caution should be given to excipient compositions in commercial formulations to ensure reliability and reproducibility of the analysis.

Biomolecular and bioanalytical applications of infrared spectroscopy - A review

Infrared (IR; or mid-infrared, MIR; 4000-400 cm^-1; 2500-25,000 nm) spectroscopy has become one of the most powerful and versatile tools at the disposal of modern bioscience. Because of its high molecular specificity, applicability to wide variety of samples, rapid measurement and non-invasivity, IR spectroscopy forms a potent approach to elucidate qualitative and quantitative information from various kinds of biological material. For these reasons, it became an established bioanalytical technique with diverse applications. This work aims to be a comprehensive and critical review of the recent accomplishments in the field of biomolecular and bioanalytical IR spectroscopy. That progress is presented on a wider background, with fundamental characteristics, the basic principles of the technique outlined, and its scientific capability directly compared with other methods being used in similar fields (e.g. near-infrared, Raman, fluorescence). The article aims to present a complete examination of the topic, as it touches the background phenomena, instrumentation, spectra processing and data analytical methods, spectra interpretation and related information. To suit this goal, the article includes a tutorial information essential to obtain a thorough perspective of bio-related applications of the reviewed methodologies. The importance of the fundamental factors to the final performance and applicability of IR spectroscopy in various areas of bioscience is explained. This information is interpreted in critical way, with aim to gain deep understanding why IR spectroscopy finds extraordinarily intensive use in this remarkably diverse and dynamic field of research and utility. The major focus is placed on the diversity of the applications in which IR biospectroscopy has been established so far and those onto which it is expanding nowadays. This includes qualitative and quantitative analytical spectroscopy, spectral imaging, medical diagnosis, monitoring of biophysical processes, and studies of physicochemical properties and dynamics of biomolecules. The application potential of IR spectroscopy in light of the current accomplishments and the future prospects is critically evaluated and its significance in the progress of bioscience is comprehensively presented.

Detection and quantification of warfarin in pharmaceutical dosage form and in spiked human plasma using surface enhanced Raman scattering

Analytical approaches for the quantitation of warfarin in plasma are high in demand. In this study, a novel surface enhanced Raman scattering (SERS) technique for the quantification of the widely used anticoagulant warfarin sodium in pharmaceutical dosage form and in spiked human plasma was developed. The colloidal-based SERS measurements were carefully optimized considering the laser wavelength, the type of metal nanoparticles, their surface functionalization and concentration as well as the time required for warfarin to associate with the metal surface. Poly(diallyldimethylammonium chloride) coated silver nanoparticles (PDDA-AgNPs) were established as a substrate which greatly enhanced the weak warfarin Raman signal with high reproducibility. The limit of detection was calculated in both water and human plasma to be 0.56 nM (0.17 ngmL^-1) and 0.25 nM (0.08 ngmL^-1) respectively, with a high degree of accuracy and reproducibility. The proposed method is simple, economical, and easily applied for routine application requiring only small plasma samples and also could be potentially useful for pharmacokinetic research on warfarin.

Field-resolved infrared spectroscopy of biological systems

The proper functioning of living systems and physiological phenotypes depends on molecular composition. Yet simultaneous quantitative detection of a wide variety of molecules remains a challenge^1-8. Here we show how broadband optical coherence opens up opportunities for fingerprinting complex molecular ensembles in their natural environment. Vibrationally excited molecules emit a coherent electric field following few-cycle infrared laser excitation^9-12, and this field is specific to the sample's molecular composition. Employing electro-optic sampling^10,12-15, we directly measure this global molecular fingerprint down to field strengths 10⁷ times weaker than that of the excitation. This enables transillumination of intact living systems with thicknesses of the order of 0.1 millimetres, permitting broadband infrared spectroscopic probing of human cells and plant leaves. In a proof-of-concept analysis of human blood serum, temporal isolation of the infrared electric-field fingerprint from its excitation along with its sampling with attosecond timing precision results in detection sensitivity of submicrograms per millilitre of blood serum and a detectable dynamic range of molecular concentration exceeding 10⁵. This technique promises improved molecular sensitivity and molecular coverage for probing complex, real-world biological and medical settings.

Quantification of low-content encapsulated active cosmetic ingredients in complex semi-solid formulations by means of attenuated total reflectance-infrared spectroscopy

Attenuated total reflectance-infrared (ATR-IR) spectroscopy is a robust tool for molecular characterisation of matter. Applied to semi-solid formulations, it enables rapid and reliable data collection without pre-analytical requirements. Based on nano-encapsulated Omegalight®, a skin-lightening active cosmetic ingredient (ACI), incorporated in a hydrogel, it is first demonstrated that, despite the high water content and the chemical complexity of the samples (i.e. number of ingredients), the spectral features of the ACI can be detected and monitored. Secondly, with a total of 105 samples divided into a training set (n = 60) and an unknown set (n = 45) covering a 0.5% w/w-5% w/w concentration range, the study further investigates the quantitative performance of ATR-IR coupled with partial least squares regression (PLSR). Through a step-by-step approach in testing different cross-validation protocols, accuracy (root mean square error of cross-validation (RMSECV)) and linearity between the experimental and predicted concentrations (R²) of ATR-IR are consistently evaluated to be respectively 0.097% (w/w) and 0.995 with a lower LOD = 0.067% (w/w). Subsequently, further evaluation of the accuracy (relative error of the predicted concentration compared with the true value, expressed as %) of the analysis was undertaken with the 45 unknown samples that were defined as unknown and analysed by PLSR. The outcome of the analysis demonstrates the ruggedness and the consistency of the determination performed using the ATR-IR data. With an average relative error of 2.5% w/w and only 5 samples out of 45 blind samples exhibiting a relative error above the 5% threshold, high accuracy quantification of the nano-encapsulated ACI can be unambiguously achieved by means of the label-free and non-destructive technique of ATR-IR spectroscopy. Ultimately, the study demonstrates that the analytical capabilities of ATR-IR hold significant potential for applications in the cosmetics industry, and although the path remains long, the present study is one step further to support validation of the technique, albeit for the specific case of Omegalight®.

Development of high-throughput ATR-FTIR technology for rapid triage of brain cancer

Non-specific symptoms, as well as the lack of a cost-effective test to triage patients in primary care, has resulted in increased time-to-diagnosis and a poor prognosis for brain cancer patients. A rapid, cost-effective, triage test could significantly improve this patient pathway. A blood test using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy for the detection of brain cancer, alongside machine learning technology, is advancing towards clinical translation. However, whilst the methodology is simple and does not require extensive sample preparation, the throughput of such an approach is limited. Here we describe the development of instrumentation for the analysis of serum that is able to differentiate cancer and control patients at a sensitivity and specificity of 93.2% and 92.8%. Furthermore, preliminary data from the first prospective clinical validation study of its kind are presented, demonstrating how this innovative technology can triage patients and allow rapid access to imaging.

Is Infrared Spectroscopy Ready for the Clinic?

Fourier transform-infrared spectroscopy (FT-IR) represents an attractive molecular diagnostic modality for translation to the clinic, where comprehensive chemical profiling of biological samples may revolutionize a myriad of pathways in clinical settings. Principally, FT-IR provides a rapid, cost-effective platform to obtain a molecular fingerprint of clinical samples based on vibrational transitions of chemical bonds upon interaction with infrared light. To date, considerable research activities have demonstrated competitive to superior performance of FT-IR strategies in comparison to conventional techniques, with particular promise for earlier, accessible disease diagnostics, thereby improving patient outcomes. However, amidst the changing healthcare landscape in times of aging populations and increased prevalence of cancer and chronic disease, routine adoption of FT-IR within clinical laboratories has remained elusive. Hence, this perspective shall outline the significant clinical potential of FT-IR diagnostics and subsequently address current barriers to translation from the perspective of all stakeholders, in the context of biofluid, histopathology, cytology, microbiology, and biomarker discovery frameworks. Thereafter, future perspectives of FT-IR for healthcare will be discussed, with consideration of recent technological advances that may facilitate future clinical translation.

Qualitative and quantitative analysis of therapeutic solutions using Raman and infrared spectroscopy

Anticancer drugs are prescribed and administrated to an increasing number of patients on a daily basis. As a consequence, a number of concerns have been raised about the patient health and safety in the case that the drugs administered are not at the required concentration or even worse not the correct ones. Quality control of therapeutic solutions has therefore been extensively implemented in hospital environments, in order to avoid any failure in the intense workflow faced by administering pharmacists. In the present study, infrared (IR) and Raman spectroscopy have been employed for the analysis of 3 commercially available therapeutic solutions TEVA®, MYLAN®, CERUBIDINE®, respectively containing doxorubicin, epirubicin and daunorubicin. They perfectly illustrate the analytical difficulties encountered, as these 3 chemotherapeutic drugs are isomers, hardly distinguishable with conventional approaches such as UV/VIS spectrometry. Any analytical failure to identify these molecules can lead to delays in patient treatment. While Partial Least Squares Regression analysis demonstrates that both Raman and IR can deliver satisfactory quantitative analysis in the clinical range, with respective Root Mean Square Error of Cross Validation (RMSECV) between 0.0127 - 0.0220 g·L^-1 and 0.0573 - 0.0759 g·L^-1, the identification rate between the 2 techniques differs substantially. Indeed, Principal Component Analysis - Factorial Discriminant Analysis (PCA-FDA) highlights that, depending on the data preprocessing applied to Raman spectra, the discrimination between the 3 drugs is decreased, with in some cases specificity and sensitivity below 50%. However, IR analysis displays encouraging results with an overall specificity and sensitivity between 99 and 100%, suggesting that reliable validation of the therapeutic solution for administration to patients can be achieved. IR and Raman spectroscopy could assist and support quality control of chemotherapeutic solutions prepared in personalised concentrations for each patient. The effective and reliable characterisation of therapeutic solutions could have a lot to offer to improve current practices in a near future.

Optimised spectral pre-processing for discrimination of biofluids via ATR-FTIR spectroscopy

Pre-processing is an essential step in the analysis of spectral data. Mid-IR spectroscopy of biological samples is often subject to instrumental and sample specific variances which may often conceal valuable biological information. Whilst pre-processing can effectively reduce this unwanted variance, the plethora of possible processing steps has resulted in a lack of consensus in the field, often meaning that analysis outputs are not comparable. As pre-processing is specific to the sample under investigation, here we present a systematic approach for defining the optimum pre-processing protocol for biofluid ATR-FTIR spectroscopy. Using a trial-and-error based approach and a clinically relevant dataset describing control and brain cancer patients, the effects of pre-processing permutations on subsequent classification algorithms were observed, by assessing key diagnostic performance parameters, including sensitivity and specificity. It was found that optimum diagnostic performance correlated with the use of minimal binning and baseline correction, with derivative functions improving diagnostic performance most significantly. If smoothing is required, a Sovitzky-Golay approach was the preferred option in this investigation. Heavy binning appeared to reduce classification most significantly, alongside wavelet noise reduction (filter length ≥6), resulting in the lowest diagnostic performances of all pre-processing permutations tested.

Raman spectroscopy as a potential tool for label free therapeutic drug monitoring in human serum: the case of busulfan and methotrexate

A methodology is proposed, based on Raman spectroscopy coupled with multivariate analysis, to determine the Limit of Detection (LOD) and Limit of Quantification (LOQ) for therapeutic drug monitoring in human serum, using the examples of Busulfan and Methotrexate.

Analysis of bodily fluids using vibrational spectroscopy: a direct comparison of Raman scattering and infrared absorption techniques for the case of glucose in blood serum

Analysis of biomarkers present in the blood stream can potentially deliver crucial information on patient health and indicate the presence of numerous pathologies.

Raman spectroscopic screening of high and low molecular weight fractions of human serum

This study explores the suitability of Raman spectroscopy as a bioanalytical tool, when coupled with ultra-filtration and multivariate analysis, to detect imbalances in both high molecular weight and low molecular weight fractions of the same samples of human patient serum, in the native liquid form.

ATR-IR coupled to partial least squares regression (PLSR) for monitoring an encapsulated active molecule in complex semi-solid formulations

Attenuated Total Reflectance-Infrared (ATR-IR) spectroscopy holds great promise for industrial applications as a quality control tool for complex galenic formulations. Although the technique is often promoted for the molecular information it delivers in a label free and cost effective fashion, other advantages can emerge compared to the gold standard analytical tools such as liquid chromatography coupled to mass spectrometry. The present study demonstrates how ATR-IR measurements enable accurate quantitative analysis of an active cosmetic ingredient such as Omegalight® encapsulated in a complex alginate based nano-capsule. The study demonstrates how precise concentrations can be obtained without the requirement for fastidious extraction and separation protocols prior to ATR-IR analysis. However, data mining remains a crucial aspect with particular emphasis on the preprocessing of the data that will be subjected to Partial Least Squares Regression (PLSR) analysis. Therefore, different pre-processing methods have been evaluated to investigate the relationship between corrections applied and PLSR outcomes (i.e. precision, ratio of performance to deviation (RPD) and accuracy of the analysis). Ultimately, it has been found that, against all expectations, some of the preprocessing methods do not necessarily lead to improvements in the end result, while Extended Multiplicative Scattering Correction (EMSC) is the only one which delivers satisfying results, as defined by a Root Mean Square Error (RMSEV) of 0.07% (w/w) and a RPD greater than 30 when performing analysis over the range 0.4-8.2% (w/w). Despite the presence of large amounts of additives such as glycerol and preservatives in the formulation, implementing Leave One Out Cross Validation (LOOCV) further validates the method with a RPD of 18 and relative errors for the predicted concentrations below the 5% (w/w) threshold, hence demonstrating that ATR-IR has analytical capabilities for applications in the cosmetic industry.

Biofluid spectroscopic disease diagnostics: A review on the processes and spectral impact of drying

The complex patterns observed from evaporated liquid drops have been examined extensively over the last 20 years. Complete understanding of drop deposition is vital in many medical processes, and one which is essential to the translation of biofluid spectroscopic disease diagnostics. The promising use of spectroscopy in disease diagnosis has been hindered by the complicated patterns left by dried biological fluids which may inhibit the clinical translation of this technology. Coffee-ring formation, cracking and gelation patterns have all been observed in biofluid drops, and with surface homogeneity being a key element to many spectroscopic techniques, experimental issues have been found to arise. A better understanding of the fundamental processes involved in a drying droplet could allow efficient progression in this research field, and ultimately benefit the population with the development of a reliable cancer diagnostic.

Raman spectroscopic analysis of high molecular weight proteins in solution – considerations for sample analysis and data pre-processing

This study explores the potential of Raman spectroscopy, coupled with multivariate regression techniques and ion exchange chromatography, to quantitatively monitor diagnostically relevant changes in high molecular weight proteins in liquid plasma.

Clinical applications of infrared and Raman spectroscopy: state of play and future challenges

This review examines the state-of-the-art of clinical applications of infrared absorption and Raman spectroscopy, outstanding challenges, and progress towards translation.

Centrifugal ultrafiltration of human serum for improving immunoglobulin A quantification using attenuated total reflectance infrared spectroscopy

Attenuated total reflectance infrared (ATR-IR) spectroscopy is a simple, rapid and cost-effective method for the analysis of serum. However, the complex nature of serum remains a limiting factor to the reliability of this method. We investigated the benefits of coupling the centrifugal ultrafiltration with ATR-IR spectroscopy for quantification of human serum IgA concentration. Human serum samples (n = 196) were analyzed for IgA using an immunoturbidimetric assay. ATR-IR spectra were acquired for whole serum samples and for the retentate (residue) reconstituted with saline following 300 kDa centrifugal ultrafiltration. IR-based analytical methods were developed for each of the two spectroscopic datasets, and the accuracy of each of the two methods compared. Analytical methods were based upon partial least squares regression (PLSR) calibration models - one with 5-PLS factors (for whole serum) and the second with 9-PLS factors (for the reconstituted retentate). Comparison of the two sets of IR-based analytical results to reference IgA values revealed improvements in the Pearson correlation coefficient (from 0.66 to 0.76), and the root mean squared error of prediction in IR-based IgA concentrations (from 102 to 79 mg/dL) for the ultrafiltration retentate-based method as compared to the method built upon whole serum spectra. Depleting human serum low molecular weight proteins using a 300 kDa centrifugal filter thus enhances the accuracy IgA quantification by ATR-IR spectroscopy. Further evaluation and optimization of this general approach may ultimately lead to routine analysis of a range of high molecular-weight analytical targets that are otherwise unsuitable for IR-based analysis.

Quantitative analysis of curcumin-loaded alginate nanocarriers in hydrogels using Raman and attenuated total reflection infrared spectroscopy

Core-shell nanocarriers are increasingly being adapted in cosmetic and dermatological fields, aiming to provide an increased penetration of the active pharmaceutical or cosmetic ingredients (API and ACI) through the skin. In the final form, the nanocarriers (NC) are usually prepared in hydrogels, conferring desired viscous properties for topical application. Combined with the high chemical complexity of the encapsulating system itself, involving numerous ingredients to form a stable core and quantifying the NC and/or the encapsulated active without labor-intensive and destructive methods remains challenging. In this respect, the specific molecular fingerprint obtained from vibrational spectroscopy analysis could unambiguously overcome current obstacles in the development of fast and cost-effective quality control tools for NC-based products. The present study demonstrates the feasibility to deliver accurate quantification of the concentrations of curcumin (ACI)-loaded alginate nanocarriers in hydrogel matrices, coupling partial least square regression (PLSR) to infrared (IR) absorption and Raman spectroscopic analyses. With respective root mean square errors of 0.1469 ± 0.0175% w/w and 0.4462 ± 0.0631% w/w, both approaches offer acceptable precision. Further investigation of the PLSR results allowed to highlight the different selectivity of each approach, indicating only IR analysis delivers direct monitoring of the NC through the quantification of the Labrafac®, the main NC ingredient. Raman analyses are rather dominated by the contribution of the ACI which opens numerous perspectives to quantify the active molecules without interferences from the complex core-shell encapsulating systems thus positioning the technique as a powerful analytical tool for industrial screening of cosmetic and pharmaceutical products. Graphical abstract Quantitative analysis of encapuslated active molecules in hydrogel-based samples by means of infrared and Raman spectroscopy.