Non-invasive analysis of stored red blood cells using diffuse resonance Raman spectroscopy

Assessment of spatially offset Raman spectroscopy to detect differences in bone matrix quality

Since spatially offset Raman spectroscopy (SORS) can acquire biochemical measurements of tissue quality through light scattering materials, we investigated the feasibility of this technique to acquire Raman bands related to the fracture resistance of bone. Designed to maximize signals at different offsets, a SORS probe was used to acquire spectra from cadaveric bone with and without skin-like tissue phantoms attenuating the light. Autoclaving the lateral side of femur mid-shafts from 5 female and 5 male donors at 100 °C and again at 120 °C reduced the yield stress of cortical beams subjected to three-point bending. It did not affect the volumetric bone mineral density or porosity. Without tissue phantoms, autoclaving affected more Raman characteristics of the organic matrix when determined by peak intensity ratios, but fewer matrix properties depended on the three offsets (5 mm, 6 mm, and 7 mm) when determined by band area ratios. The cut-off in the thickness of the tissue phantom layers was ∼4 mm for most properties, irrespective of offset. Matching trends when spectra were acquired without phantom layers between bone and the probe, ν1PO43-/Amide III and ν1PO43-/(proline + OH-proline) were higher and lower in the non-treated bone than in the autoclaved bone, respectively, when the thickness of tissue phantom layers was 4 mm. The layers, however, caused a loss of sensitivity to autoclaving-related changes in ν3CO3/ν1PO43- and crystallinity. Without advanced post-processing of Raman spectra, SORS acquisition through turbid layers can detect changes in Raman properties of bone that accompany a loss in bone strength.

Detection of primary myelofibrosis in blood serum via Raman spectroscopy assisted by machine learning approaches; correlation with clinical diagnosis

Primary myelofibrosis (PM) is one of the myeloproliferative neoplasm, where stem cell-derived clonal neoplasms was noticed. Diagnosis of this disease is based on: physical examination, peripheral blood findings, bone marrow morphology, cytogenetics, and molecular markers. However, the molecular marker of PM, which is a mutation in the JAK2V617F gene, was observed also in other myeloproliferative neoplasms such as polycythemia vera and essential thrombocythemia. Therefore, there is a need to find methods that provide a marker unique to PM and allow for higher accuracy of PM diagnosis and consequently the treatment of the disease. Continuing, in this study, we used Raman spectroscopy, Principal Components Analysis (PCA), and Partial Least Squares (PLS) analysis as helpful diagnostic tools for PM. Consequently, we used serum collected from PM patients, which were classified using clinical parameters of PM such as the dynamic international prognostic scoring system (DIPSS) for primary myelofibrosis plus score, the JAK2V617F mutation, spleen size, bone marrow reticulin fibrosis degree and use of hydroxyurea drug features. Raman spectra showed higher amounts of C-H, C-C and C-C/C-N and amide II and lower amounts of amide I and vibrations of CH3 groups in PM patients than in healthy ones. Furthermore, shifts of amides II and I vibrations in PM patients were noticed. Machine learning methods were used to analyze Raman regions: (i) 800 cm-1 and 1800 cm-1, (ii) 1600 cm-1-1700 cm-1, and (iii) 2700 cm-1-3000 cm-1 showed 100 % accuracy, sensitivity, and specificity. Differences in the spectral dynamic showed that differences in the amide II and amide I regions were the most significant in distinguishing between PM and healthy subjects. Importantly, until now, the efficacy of Raman spectroscopy has not been established in clinical diagnostics of PM disease using the correlation between Raman spectra and PM clinical prognostic scoring. Continuing, our results showed the correlation between Raman signals and bone marrow fibrosis, as well as JAKV617F. Consequently, the results revealed that Raman spectroscopy has a high potential for use in medical laboratory diagnostics to quantify multiple biomarkers simultaneously, especially in the selected Raman regions.

A novel Raman spectroscopic method for detecting traces of blood on an interfering substrate

Traces of body fluids discovered at a crime scene are a primary source of DNA evidence. Raman spectroscopy is a promising universal technique for identifying biological stains for forensic purposes. The advantages of this method include the ability to work with trace amounts, high chemical specificity, no need for sample preparation and the nondestructive nature. However, common substrate interference limits the practical application of this novel technology. To overcome this limitation, two approaches called "Reducing a spectrum complexity" (RSC) and "Multivariate curve resolution combined with the additions method" (MCRAD) were investigated for detecting bloodstains on several common substrates. In the latter approach, the experimental spectra were "titrated" numerically with a known spectrum of a targeted component. The advantages and disadvantages of both methods for practical forensics were evaluated. In addition, a hierarchical approach to reduce the possibility of false positives was suggested.

Label-free testing strategy to evaluate packed red blood cell quality before transfusion to leukemia patients

Patients worldwide require therapeutic transfusions of packed red blood cells (pRBCs), which is applied to the high-risk patients who need periodic transfusions due to leukemia, lymphoma, myeloma and other blood diseases or disorders. Contrary to the general hospital population where the transfusions are carried out mainly for healthy trauma patients, in case of high-risk patients the proper quality of pRBCs is crucial. This leads to an increased demand for efficient technology providing information on the pRBCs alterations deteriorating their quality. Here we present the design of an innovative, label-free, noninvasive, rapid Raman spectroscopy-based method for pRBCs quality evaluation, starting with the description of sample measurement and data analysis, through correlation of spectroscopic results with reference techniques' outcomes, and finishing with methodology verification and its application in clinical conditions. We have shown that Raman spectra collected from the pRBCs supernatant mixture with a proper chemometric analysis conducted for a minimum one ratio of integral intensities of the chosen Raman marker bands within the spectrum allow evaluation of the pRBC quality in a rapid, noninvasive, and free-label manner, without unsealing the pRBCs bag. Subsequently, spectroscopic data were compared with predefined reference values, either from pRBCs expiration or those defining the pRBCs quality, allowing to assess their utility for transfusion to patients with acute myeloid leukemia (AML) and lymphoblastic leukemia (ALL).

Assessing the quality of stored red blood cells using handheld Spatially Offset Raman spectroscopy with multisource correlation analysis

In this work we employ Spatially Offset Raman Spectroscopy (SORS) to non-invasively identify storage-related changes in red blood cell concentrate (RCC) in-situ within standard plastic transfusion bags. To validate the measurements, we set up a parallel study comparing both bioanalytical data (obtained by blood-gas analysis, hematology analysis and spectrophotometric assays), and Raman spectrometry data from the same blood samples. We then employ Multisource Correlation Analysis (MuSCA) to correlate the different types of data in RCC. Our analysis confirmed a strong correlation of glucose, methemoglobin and oxyhemoglobin with their respective bioassay values in RCC units. Finally, by combining MuSCA with k-means clustering, we assessed changes in all Raman wavenumbers during cold storage in both RCC Raman data from the current study and parallel RCC supernatant Raman data previously acquired from the same units. Direct RCC quality monitoring during storage, would help to establish a basis for improved inventory management of blood products in blood banks and hospitals based on analytical data.

Assessment of skin inflammation using near-infrared Raman spectroscopy combined with artificial intelligence analysis in an animal model

Near-infrared (NIR) Raman spectroscopy was applied to detect skin inflammation in an animal model. Artificial intelligence (AI) analysis improved prediction accuracy for skin inflammation.

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.

Raman spectroscopy on blood serum samples of patients with end-stage liver disease

Raman spectroscopy has shown to be a promising method for the examination of biomedical samples. However, until now, its efficacy has not been established in clinical diagnostics. In this study, Raman spectroscopy’s potential application in medical laboratories is evaluated for a large variety (38) of biomarkers. Given 234 serum samples from a cohort of patients with different stages of liver disease, we performed Raman spectroscopy at 780nm excitation wavelength. The Raman spectra were analyzed in combination with the results of routine diagnostics using specifically developed complex mathematical algorithms, including fluorescence filtering, frequency subset selection and several overfitting circumventing strategies, such as independent validation. With the results of this cohort, which were validated in 328 independent samples, a significant proof-of-concept study was completed. This study highlights the need to prevent overfitting and to use independent data for validation. The results reveal that Raman spectroscopy has high potential for use in medical laboratory diagnostics to simultaneously quantify multiple biomarkers.

Multivariate analysis of mean Raman spectra of erythrocytes for a fast analysis of the biochemical signature of ageing

Ageing of red blood cells (RBC) is a physiological process, fundamental to ensure a proper blood homeostasis that, in vivo, balances the production of new cells and the removal of senescent erythrocytes. A detailed characterization at the cellular level of the progression of the ageing phenomenon can reveal biological, biophysical and biochemical fingerprints for diseases related to misbalances of the cell turnover and for blood pathologies. We applied Principal Components Analysis (PCA) to mean Raman spectra of single cells at different ageing times to rapidly highlight subtle spectral differences associated with conformational and biochemical modifications. Our results demonstrate a two-step ageing process characterized by a first phase in which proteins plays a relevant role, followed by a further cellular evolution driven by alterations in the membrane lipid contribution. Moreover, we used the same approach to directly analyse relevant spectral effects associated to reduction in Haemoglobin oxygenation level and membrane fluidity induced by the ageing. The method is robust and effective, allowing to classify easily the studied cells based on their age and morphology, and consequently to evaluate the biological quality of a blood sample.

Feature Selection and Rapid Characterization of Bloodstains on Different Substrates

Establishing the precise timeline of a crime can be challenging as current analytical techniques used suffer from many limitations and are destructive to the body fluids encountered at crime scenes. Raman spectroscopy has demonstrated excellent potential in forensic science as it provides direct information about the structural and molecular changes without the need for processing or extracting samples. However, its current applicability is limited to pure body fluids, as signals from the substrate underlying these fluids greatly influence the current models used for age estimation. In this study, we utilized Raman spectroscopy to identify selective spectral markers that delineate the bloodstain age in the presence of interfering signals from the substrate. The pure bloodstains and the bloodstains on the substrate were aged for two weeks at 21 ± 2 ℃ in the dark. Least absolute shrinkage and selection operator (LASSO) regression was employed to guide the feature selection in the presence of interference from substrates to accurately predict the bloodstain age. Substrate-specific regression models guided by an automated feature selection algorithm yielded low values of predictive root mean square error (0.207, 0.204, 0.222 h in logarithmic scale) and high R² (0.924, 0.926, 0.913) on test data consisting of blood spectra on floor tile, facial tissue, and linoleum-polymer substrates, respectively. This framework for an automated feature selection algorithm relies entirely on pure bloodstain spectra to train substrate-specific models for estimating the age of composite (blood on substrate) spectra. The model can thus be easily applied to any new composite spectra and is highly scalable to new environments. This study demonstrates that Raman spectroscopy coupled with LASSO could serve as a reliable and nondestructive technique to determine the age of bloodstains on any surface while aiding forensic investigations in real-world scenarios.

Defocused Spatially Offset Raman Spectroscopy in Media of Different Optical Properties for Biomedical Applications Using a Commercial Spatially Offset Raman Spectroscopy Device

In this study, we show how defocused spatially offset Raman spectroscopy (SORS) can be employed to recover chemical information from media of biomedical significance within sealed plastic transfusion and culture bags using a commercial SORS instrument. We demonstrate a simple approach to recover subsurface spectral information through a transparent barrier by optimizing the spatial offset of the defocused beam. The efficiency of the measurements is assessed in terms of the SORS ratio and signal-to-noise ratio (S/N) through a simple manual approach and an ordinary least squares model. By comparing the results for three different biological samples (red blood cell concentrate, pooled red cell supernatant and a suspension of Jurkat cells), we show that there is an optimum value of the offset parameter which yields the maximum S/N depending on the barrier material and optical properties of the ensemble contents. The approach was developed in the context of biomedical applications but is generally applicable to any three-layer system consisting of turbid content between transparent thin plastic barriers (i.e., front and back bag surfaces), particularly where the analyte of interest is dilute or not a strong scatterer.