Comparison of different infrared measurement techniques in the clinical analysis of biofluids

Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) detection limits for blood on fabric: Orientation and coating uniformity effects

Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) was used to analyze four types of forensically relevant fabrics coated with varying dilutions of blood. The blood was applied in two manners, dip coating with a smooth and uniform layer and drip coating with droplets from pipettes. Spectra of neat and dip coated fabrics were acquired using controlled orientations, and these were compared to spectra collected on samples with random orientations. The improved reproducibility seen in visual inspection of the spectra is confirmed by principal component and linear discriminant projections of the spectra, as well as by statistical hypothesis testing. Principal component regression (PCR), using the regions of the IR spectra associated with the amide A/B, I, II, and III vibrational bands (3500-2800, 1650, 1540, and 1350 cm^-1), was employed on the more uniform dip coated spectra to estimate limits of detection for blood on two of the four fabrics - acrylic and nylon. These results demonstrate that detection limits for blood on fabrics can be decreased significantly by controlling for the orientation and face of the fabric samples while collecting spectra. Limits of detection for acrylic and nylon were found to be 196 × and 227 × diluted blood, respectively.

Biomedical Vibrational Spectroscopy in the Era of Artificial Intelligence

Biomedical vibrational spectroscopy has come of age. The past twenty years have brought many advancements and new developments and now its practitioners face a new challenge: artificial intelligence. Artificial intelligence has the capability to detect meaningful relationships in data sets such as those found in an infrared or Raman spectrum. The present narrative assesses the degree to which biomedical vibrational spectroscopy has already embraced artificial intelligence and what can be expected going forward. This article belongs to the Special Issue Biomedical Applications of Infrared and Raman Spectroscopy.

Feasibility of a handheld near infrared device for the qualitative analysis of bloodstains

One of the most common tasks in criminal investigation is to determine from which tissue source a biological fluid stain originates. As a result, there are many tests that are frequently used to determine if a stain is blood, semen or saliva by exploiting the properties of certain molecules present within the fluids themselves. These include chemical reagents such as the Kastle-Meyer or Acid Phosphatase tests, as well as other techniques like the use of alternative light sources. However, most of the tests currently available have some major drawbacks. In this study, a handheld near-infrared spectrometer is investigated for the specific identification of deposited bloodstains. First, a calibration was carried out by scanning over 500 positive (blood present) and negative (blood absent) samples to train several predictive models based on machine learning principles. These models were then tested on over 100 new positive and negative samples to evaluate their performance. All models tested were able to correctly classify deposited stains as blood in at least 81% of tested samples, with some models allowing for even higher classification accuracy at over 94%. This suggests that handheld near infrared devices could offer great opportunity for the rapid, low cost and non-destructive screening of body fluids at scenes of crime.

Assessing the challenges of Fourier transform infrared spectroscopic analysis of blood serum

There are many approaches to measuring the infrared spectrum of a blood serum sample. Naturally, each approach will have both advantages and disadvantages. We report on the progress of the application of infrared spectroscopy in the field of blood serum analysis towards clinical application, with a focus on prostate cancer. In order to perform a high-powered study with clinical relevance, choosing the most suitable approach must undergo careful consideration. We review the possibilities of using different sample preparation methods and speculate upon the potential pitfalls of both transmission and attenuated total reflectance (ATR) techniques.

Application of multivariate data-analysis techniques to biomedical diagnostics based on mid-infrared spectroscopy

The objective of this contribution is to review the application of advanced multivariate data-analysis techniques in the field of mid-infrared (MIR) spectroscopic biomedical diagnosis. MIR spectroscopy is a powerful chemical analysis tool for detecting biomedically relevant constituents such as DNA/RNA, proteins, carbohydrates, lipids, etc., and even diseases or disease progression that may induce changes in the chemical composition or structure of biological systems including cells, tissues, and bio-fluids. However, MIR spectra of multiple constituents are usually characterized by strongly overlapping spectral features reflecting the complexity of biological samples. Consequently, MIR spectra of biological samples are frequently difficult to interpret by simple data-analysis techniques. Hence, with increasing complexity of the sample matrix more sophisticated mathematical and statistical data analysis routines are required for deconvoluting spectroscopic data and for providing useful results from information-rich spectroscopic signals. A large body of work relates to the combination of multivariate data-analysis techniques with MIR spectroscopy, and has been applied by a variety of research groups to biomedically relevant areas such as cancer detection and analysis, artery diseases, biomarkers, and other pathologies. The reported results indeed reveal a promising perspective for more widespread application of multivariate data analysis in assisting MIR spectroscopy as a screening or diagnostic tool in biomedical research and clinical studies. While the authors do not mean to ignore any relevant contributions to biomedical analysis across the entire electromagnetic spectrum, they confine the discussion in this contribution to the mid-infrared spectral range as a potentially very useful, yet underutilized frequency region. Selected representative examples without claiming completeness will demonstrate a range of biomedical diagnostic applications with particular emphasis on the advantageous interaction between multivariate data analysis and MIR spectroscopy.

Detection of calcium phosphate crystals in the joint fluid of patients with osteoarthritis - analytical approaches and challenges

Clinically, osteoarthritis (OA) is characterised by joint pain, stiffness after immobility, limitation of movement and, in many cases, the presence of basic calcium phosphate (BCP) crystals in the joint fluid. The detection of BCP crystals in the synovial fluid of patients with OA is fraught with challenges due to the submicroscopic size of BCP, the complex nature of the matrix in which they are found and the fact that other crystals can co-exist with them in cases of mixed pathology. Routine analysis of joint crystals still relies almost exclusively on the use of optical microscopy, which has limited applicability for BCP crystal identification due to limited resolution and the inherent subjectivity of the technique. The purpose of this Critical Review is to present an overview of some of the main analytical tools employed in the detection of BCP to date and the potential of emerging technologies such as atomic force microscopy (AFM) and Raman microspectroscopy for this purpose.

Analysis of biofluids in aqueous environment based on mid-infrared spectroscopy

In this study we describe a semiautomatic Fourier transform infrared spectroscopic methodology for the analysis of liquid serum samples, which combines simple sample introduction with high sample throughput. The applicability of this new infrared technology to the analysis of liquid serum samples from a cohort of cattle naturally infected with bovine spongiform encephalopathy and from controls was explored in comparison to the conventional approach based on transmission infrared spectroscopy of dried serum films. Artifical neural network analysis of the infrared data was performed to differentiate between bovine spongiform encephalopathy-negative controls and animals in the late stage of the disease. After training of artifical neural network classifiers, infrared spectra of sera from an independent external validation data set were analyzed. In this way, sensitivities between 90 and 96% and specificities between 84 and 92% were achieved, respectively, depending upon the strategy of data collection and data analysis. Based on these results, the advantages and limitations of the liquid sample technique and the dried film approach for routine analysis of biofluids are discussed.

Nanoliter serum sample analysis by mid-infrared spectroscopy for minimally invasive blood-glucose monitoring

The aim of this study was to demonstrate that mid-infrared spectroscopy is able to quantify glucose in a serum matrix with sample volumes well below 1 muL. For this, we applied mid-infrared attenuated total reflectance (ATR) or transmission-based spectroscopic methods to glucose quantification in microsamples of dry-film sera, either undiluted or diluted 10 times in distilled water. The sample series spanned physiological glucose concentrations between 50 and 600 mg/dL and volumes of 80, 8, and 1 nL. Calibration was carried out using multivariate partial least-squares (PLS) modeling with spectral data between 1180 and 940 cm(-1). Best performance was achieved in the ATR experiments. For raw ATR spectra, the optimum standard error of prediction (SEP) of 13.3 mg/dL was obtained for the 8 nL sample series with subsequent 10-fold dilution. With respect to the coefficient of variation of the glucose assay, CV(pred), we obtained a value of 3% for the 80 nL volume samples with spectral preprocessing using matrix protein absorption bands as an internal standard, 4% for the 8 nL samples, and 6% for the 1 nL samples with raw data. Spectral standardization resulted in significant improvement, especially for the 80 nL volume sample series. By contrast, the accuracy of the glucose assay for the 1 nL sample volume series could not be improved either by internal standardization or by considering the dry film areas for normalization, which we attribute to varying topographies of the dry films.

Glucose quantification in dried-down nanoliter samples using mid-infrared attenuated total reflection spectroscopy

The aim of this study was to determine the feasibility of minimally invasive glucose concentration measurement of a body fluid within the physiologically important range below 100 nL with a number of samples such as interstitial fluid, plasma, or whole blood using mid-infrared spectroscopy, but starting with preliminary measurements on samples of simple aqueous glucose solutions. The Fourier transform infrared spectrometer was equipped with a Golden Gate single reflection diamond attenuated total reflection (ATR) accessory and a room-temperature pyroelectric detector. As the necessary detection limits can be achieved only for dried samples within the spectrometric conditions realized by a commercial instrument, the work focused on the optimization of such ATR measurements. We achieved quantification of samples with volumes as low as 7 nL between 10 and 600 mg/dL. The standard error of prediction (SEP) for the concentration range 10-100 mg/dL is 3.2 mg/dL with full interval data between 1180 and 940 cm(-1). The performance of the prediction is given by a coefficient of variation of prediction (CV(pred) ) of 6.2%. When all samples within the whole concentration range are included, the SEP increases to 20.2 mg/dL, and hence the CV(pred) to 10.6% due to a nonlinear signal dependence on glucose concentration. A detection limit for glucose of 0.7 ng with a signal-to-noise ratio of 10 was obtained.

Application of infrared spectroscopy (attenuated total reflection) for monitoring enzymatic activity on substrate films

Infrared film analysis, a method based on infrared spectroscopy in the mode of attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR), is demonstrated as a novel analytical method for monitoring enzymatic activity on surface-attached substrate films in the mid infrared range (400-4000 cm(-1)). The ATR-FTIR technique is sensitive to molecules within a distance of approximately 1 microm from the ATR sampling unit surface (a 7 cm(2) hydrophobic ZnSe crystal). Applying a 0.2-0.3 microm thick film on the ATR unit surface, any chemical changes within this film as well as at the interface can be continuously monitored, even having an aqueous phase on top of the film. Infrared film analysis is considered especially useful for studying detergent enzymes, which act on surface bound films consisting of food component like vegetable oils (triacylglycerols) and carbohydrates (e.g. starch). Experimental data are presented for hydrolysis of a triacylglycerol film (triolein) by use of a triacylglycerol lipase (cutinase), and starch film degradation by use of an alpha-amylase.

Detection of pathological molecular alterations in scrapie-infected hamster brain by Fourier transform infrared (FT-IR) spectroscopy

In this report a new approach for the identification of pathological changes in scrapie-infected Syrian hamster brains using Fourier transform infrared microspectroscopy is discussed. Using computer-based pattern recognition techniques and imaging, infrared maps with high structural contrast were obtained. This strategy permitted comparison of spectroscopic data from identical anatomical structures in scrapie-infected and control brains. Consistent alterations in membrane state-of-order, protein composition, carbohydrate and nucleic acid constituents were detected in scrapie-infected tissues. Cluster analysis performed on spectra of homogenized medulla oblongata and pons samples also reliably separated uninfected from infected specimens. This method provides a useful tool not only for the exploration of the disease process but also for the development of rapid diagnostic and screening techniques of transmissible spongiform encephalopathies.