Protein determination in serum and whole blood by attenuated total reflectance infrared spectroscopy

MetaRF: attention-based random forest for reaction yield prediction with a few trails

Artificial intelligence has deeply revolutionized the field of medicinal chemistry with many impressive applications, but the success of these applications requires a massive amount of training samples with high-quality annotations, which seriously limits the wide usage of data-driven methods. In this paper, we focus on the reaction yield prediction problem, which assists chemists in selecting high-yield reactions in a new chemical space only with a few experimental trials. To attack this challenge, we first put forth MetaRF, an attention-based random forest model specially designed for the few-shot yield prediction, where the attention weight of a random forest is automatically optimized by the meta-learning framework and can be quickly adapted to predict the performance of new reagents while given a few additional samples. To improve the few-shot learning performance, we further introduce a dimension-reduction based sampling method to determine valuable samples to be experimentally tested and then learned. Our methodology is evaluated on three different datasets and acquires satisfactory performance on few-shot prediction. In high-throughput experimentation (HTE) datasets, the average yield of our methodology's top 10 high-yield reactions is relatively close to the results of ideal yield selection.

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.

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

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

From bench to worktop: Rapid evaluation of nutritional parameters in liquid foodstuffs by IR spectroscopy

We evaluated the use of attenuated total reflectance infrared spectroscopy for simultaneous in situ quantification of the nutritional composition of liquid food stuffs in the industrial kitchen context. Different methodologies were compared, including dry and wet acquisition along with instrument parameters and measurement times of 4 and 60 s. The most effective technique was 1-minute measurement, with prediction errors of 2.6, 0.7, 1.0, 2.2, 0.8, 2.4 g/100 mL and 150 Kcal, for carbohydrates, proteins, fat, sugars, saturated fat, water and energy values, respectively.The 4-second method resulted in larger errors but was more applicable for inline measurements. Dry measurements successfully predicted the fractions of proteins, fat, carbohydrates, and sugars, relative to total solids. An app was created to facilitate implementation in a kitchen environment. Compared with other techniques recommended by the FAO, the approach offered a simple alternative for simultaneous prediction of nutritional parameters in an industrial kitchen set-up.

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.

Multimodal vibrational studies of drug uptake in vitro: Is the whole greater than the sum of their parts?

Herein, we investigated the use of multimodal Raman and infrared (IR) spectroscopic microscopy for the elucidation of drug uptake and subsequent cellular responses. Firstly, we compared different methods for the analysis of the combined data. Secondly, we evaluated whether the combined analysis provided enough benefits to justify the fusion of the data. A459 cells inoculated with doxorubicin (DOX) at different times were fixed and analysed using each technique. Raman spectroscopy provided high sensitivity to DOX and enabled an accurate estimation of the drug uptake at each time point, whereas IR provided a better insight into the resultant changes in the biochemical composition of the cell. In terms of benefits of data fusion, 2D correlation analysis allowed the study of the relationship between IR and Raman variables, whereas the joint analysis of IR and Raman enabled the correlation of the different variables to be monitored over time. In summary, the complementary nature of IR and Raman makes the combination of these vibrational techniques an appealing tool to follow drug kinetics and cellular response.

Reagent-free total protein quantification of intact extracellular vesicles by attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy

Extracellular vesicles (EVs) are lipid bilayer–bounded particles that are actively synthesized and released by cells. The main components of EVs are lipids, proteins, and nucleic acids and their composition is characteristic to their type and origin, and it reveals the physiological and pathological conditions of the parent cells. The concentration and protein composition of EVs closely relate to their functions; therefore, total protein determination can assist in EV-based diagnostics and disease prognosis. Here, we present a simple, reagent-free method based on attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy to quantify the protein content of EV samples without any further sample preparation. After calibration with bovine serum albumin, the protein concentration of red blood cell–derived EVs (REVs) were investigated by ATR-FTIR spectroscopy. The integrated area of the amide I band was calculated from the IR spectra of REVs, which was proportional to the protein quantity in the sample‚ regardless of its secondary structure. A spike test and a dilution test were performed to determine the ability to use ATR-FTIR spectroscopy for protein quantification in EV samples, which resulted in linearity with R² values as high as 0.992 over the concentration range of 0.08 to 1 mg/mL. Additionally, multivariate calibration with the partial least squares (PLS) regression method was carried out on the bovine serum albumin and EV spectra. R² values were 0.94 for the calibration and 0.91 for the validation set. The results indicate that ATR-FTIR measurements provide a reliable method for reagent-free protein quantification of EVs.

A Comparative Study of Determination the Spectral Characteristics of Serum Total Protein Among Laser System and Spectrophotometric: Advantage and Limitation of Suggested Methods

Background and Objective:

Laser spectroscopy is becoming an increasingly paramount analytical tool. Scientists today have at their disposal many various types of laser-based analytical techniques. In this article, the possibility of using capabilities of a laser to analyze and find the concentration of Serum Total Protein (STP) was studied.

Materials and Methods:

The laser system includes a diode laser with 532 nm wavelength, with maximum output power being 5 mW. Laser bandwidth ranges around (524 nm – 546 nm) experimentally justified using a monochromator. A simple variable resistance with a range from zero to10Ω for obtaining a range of laser output power, detector, parallel variable resistance with the range from zero to 5 kΩ and meter for measuring the percentage of transmittance. The absorption spectroscopy of STP samples was measured by double beam spectrophotometer.

Results:

Maximum absorbance of STP is at the range (520-580 nm) and the peak at (500) nm. Laser system measurements included the study of absorbance of STP as a function of cuvet thickness, transmittance as a function of cuvet thickness and absorbance as a function of laser power. In order to ascertain our calculations, the results have been compared with the results of the spectrophotometer. The Relative Standard Deviation (RSD%) values are about (0.67-17.18).

Conclusion:

The diode laser system is a highly efficient and easy system and allows access to a range of powers. Since the divergence of the laser beam is very low. All results are in good agreement with conventional double beam spectrophotometer.

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.

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.

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.

Estimation of the age of human bloodstains under the simulated indoor and outdoor crime scene conditions by ATR-FTIR spectroscopy

Estimation of the age of human bloodstains is of great importance in forensic practices, but it is a challenging task because of the lack of a well-accepted, reliable, and established method. Here, the attenuated total reflection (ATR)-Fourier transform infrared (FTIR) technique combined with advanced chemometric methods was utilized to determine the age of indoor and outdoor bloodstains up to 107 days. The bloodstain storage conditions mimicked crime scene scenarios as closely as possible. Two partial least squares regression models—indoor and outdoor models with 7–85 days—exhibited good performance for external validation, with low values of predictive root mean squared error (5.83 and 4.77) and high R² values (0.94 and 0.96) and residual predictive deviation (4.08 and 5.14), respectively. Two partial least squares–discriminant analysis classification models were built and demonstrated excellent distinction between fresh (age ≤1 d) and older (age >1 d) bloodstains, which is highly valuable for forensic investigations. These findings demonstrate that ATR-FTIR spectroscopy coupled with advanced chemometric methods can be employed as a rapid and non-destructive tool for age estimation of bloodstains in real-world forensic investigation.

Complex refractive index spectra of whole blood and aqueous solutions of anticoagulants, analgesics and buffers in the mid-infrared

Mid-infrared (MIR) spectroscopy is a powerful tool for characterising the vibrations of molecular bonds and is therefore ideal for label-free detection of chemical species. Recent research into thin-film deposition and etching techniques for mid-infrared materials shows potential for realising miniaturised bedside biosensors for clinical diagnostics exploiting MIR spectroscopy, to replace laboratory based-techniques. However, lack of refractive index information for commonly encountered biological media and analytes hampers optimisation of biosensor performance for maximum sensitivity, especially for devices exploiting evanescent spectroscopy. Here we present refractive index data for human whole blood and several aqueous solutions of general interest to the clinical community: anticoagulants, analgesics and buffers. The refractive indices are generally dominated by the water content of each sample and the whole blood spectra exhibit additional strong features due to protein content. Furthermore, we present a generalised method for extracting complex refractive indices of aqueous solutions in the mid-infrared region using conventional attenuated total reflection Fourier transform spectroscopy (ATR-FTIR) without the need for collimated or polarised incident light, as is required for existing methods.

Characterization of postmortem biochemical changes in rabbit plasma using ATR-FTIR combined with chemometrics: A preliminary study

Postmortem interval (PMI) determination is one of the most challenging tasks in forensic medicine due to a lack of accurate and reliable methods. It is especially difficult for late PMI determination. Although many attempts with various types of body fluids based on chemical methods have been made to solve this problem, few investigations are focused on blood samples. In this study, we employed an attenuated total reflection (ATR)-Fourier transform infrared (FTIR) technique coupled with principle component analysis (PCA) to monitor biochemical changes in rabbit plasma with increasing PMI. Partial least square (PLS) model was used based on the spectral data for PMI prediction in an independent sample set. Our results revealed that postmortem chemical changes in compositions of the plasma were time-dependent, and various components including proteins, lipids and nucleic acids contributed to the discrimination of the samples at different time points. A satisfactory prediction within 48h postmortem was performed by the combined PLS model with a good fitting between actual and predicted PMI of 0.984 and with an error of ±1.92h. In consideration of the simplicity and portability of ATR-FTIR, our preliminary study provides an experimental and theoretical basis for application of this technique in forensic practice.

Plasma biomarkers of pulmonary hypertension identified by Fourier transform infrared spectroscopy and principal component analysis

The main goal of this study was to find specific plasma spectral markers associated with pulmonary arterial hypertension (PAH) induced by monocrotaline injection in rats. FTIR was used to monitor biochemical changes in plasma caused by PAH as compared with the systemic hypertension induced by partial ligation on the left artery and with the control group. Both pathologies, systemic and pulmonary hypertension, induced a unique response in the biochemical content of plasma, mainly related to the composition and secondary structure of plasma proteins. For PAH, β-pleated sheet components of plasma proteins were identified whereas the protein composition in systemic hypertension was dominated by unordered structures. In addition, a higher concentration of tyrosine-rich proteins was found in plasma in PAH than in systemic hypertension. The differences between both pathologies were identified also in terms of lipid composition/metabolism as well as in the content of RNA and glucose, suggesting that lipid peroxidation appears upon pulmonary hypertension development. In summary, this work demonstrates that FTIR spectroscopy supported by principal component analysis (PCA) has the potential to become a fast and non-destructive method for biochemical characterization of plasma that consequently could have a diagnostic significance in pulmonary hypertension.