Studies on acute human infections using FTIR microspectroscopy and cluster analysis

Searching for serum biomarkers linking coronary heart disease and Helicobacter pylori infection using infrared spectroscopy and artificial neural networks

Helicobacter pylori (Hp) Gram-negative bacteria cause gastritis or gastric ulcers. They may be involved in the development of systemic diseases i.e. coronary heart disease (CHD). Both Hp infection and CHD are related to inflammation accompanied by C-reactive protein (CRP), tumor necrosis factor alfa (TNF-α) and homocysteine. Low density lipoprotein (LDL) and triglicerides are a classic risk factors of CHD. Infrared spectroscopy has been introduced for monitoring chronic infections or endogenous disorders using specific absorption bands for biocomponents typed as diagnostic markers. In this study we selected specific motives of infrared radiation (IR) spectra for the sera from CHD patients infected with Hp. In total 141 sera were used: 90 from patients with CHD, all Hp positive, and 51 from healthy donors, 32 Hp negative and 21 Hp positive. Hp status was evaluated by anti-Hp IgG antibodies and/or ¹³C urea breath testing. IR spectra were measured using FT-IR/FT-NIR Spectrum 400 spectrometer (PerkinElmer) chemometrically analyzed using artificial neural networks and they showed differences in absorption bands corresponding to triglicerides, CRP, homocysteine, LDL and TNF-α, and selected component groups between CHD patients infected with Hp vs healthy uninfected donors (96.15% accuracy). Triglicerides and CRP were the best biomarkers linking Hp infection with CHD.

Application of multi-wavelength dual-position absorption spectrum to improve the accuracy of leukocyte spectral quantitative analysis based on "M + N" theory

Leukocytes are the most important immune cells in human body, which are very important to maintain the immune function of human body. They can phagocytose foreign bodies and produce antibodies to resist the invasion of pathogens. Nowadays, the abuse of antibiotics is widespread, and the detection and analysis of leukocytes is very important for clinical diagnosis. It is of great medical significance to use chemical quantitative analysis method based on spectrum to realize the rapid and trace detection of leukocytes in clinic. It is the development direction of clinical detection in the future and provides a new way to improve the abuse of antibiotics. However, due to the influence of nonlinearity introduced by the measurement, the relationship between absorbance and concentration deviates from Lambert-Beer law, which leads to low measurement accuracy and restricts its development in clinical application. In order to improve the accuracy of spectral analysis, this paper with the guidance of "M + N" theory measured the transmission spectra of 392 whole blood samples under two different optical path lengths, and subtracts them to obtain the multi-band differential absorption spectra for modeling and prediction of leukocyte concentration. The following experiments were designed: using the transmission spectra measured at one position and the absorption spectra obtained by subtracting the transmission spectra measured at position 1 and position 2 as the input of modeling. Partial least squares (PLS) method was proposed in this paper for modeling and predicting the concentration of leukocyte. The experimental results show that the modeling results of dual-position absorption spectrum have been significantly improved and promoted compared with the modeling results of transmission spectrum in one position, and the calibration set correlation coefficient (R_C) values has increased by 57.92% to 0.864904, where the prediction set correlation coefficient (R_P) increased by 106.81% to 0.8502. The root mean square error of the calibration set (RMSEC) decreased by 40.01% from 3.1149 to 1.8686. The results suggest that modelling and analysing leukocytes with a multi-band dual-position absorption spectrum may reduce the influence of nonlinearity to a certain amount, significantly increase the model's prediction precision and accuracy, and obtain satisfactory results. This paper provides the possibility for rapid clinical micro-detection of leukocytes, as well as the ideas and directions for improving the accuracy of spectral quantitative analysis of components in complex solutions.

Fourier Transform Infrared (FTIR) Spectroscopy to Analyse Human Blood over the Last 20 Years: A Review towards Lab-on-a-Chip Devices

Since microorganisms are evolving rapidly, there is a growing need for a new, fast, and precise technique to analyse blood samples and distinguish healthy from pathological samples. Fourier Transform Infrared (FTIR) spectroscopy can provide information related to the biochemical composition and how it changes when a pathological state arises. FTIR spectroscopy has undergone rapid development over the last decades with a promise of easier, faster, and more impartial diagnoses within the biomedical field. However, thus far only a limited number of studies have addressed the use of FTIR spectroscopy in this field. This paper describes the main concepts related to FTIR and presents the latest research focusing on FTIR spectroscopy technology and its integration in lab-on-a-chip devices and their applications in the biological field. This review presents the potential use of FTIR to distinguish between healthy and pathological samples, with examples of early cancer detection, human immunodeficiency virus (HIV) detection, and routine blood analysis, among others. Finally, the study also reflects on the features of FTIR technology that can be applied in a lab-on-a-chip format and further developed for small healthcare devices that can be used for point-of-care monitoring purposes. To the best of the authors’ knowledge, no other published study has reviewed these topics. Therefore, this analysis and its results will fill this research gap.

Characteristics of electrically injured skin from human hand tissue samples using Fourier transform infrared microspectroscopy

This technical note describes a method for distinguishing normal skin tissue samples from those electrically injured by Fourier transform infrared microspectroscopy (FTIR MSP). Furthermore, the infrared spectral features of electrically injured cells and tissues were evaluated to identify molecular changes in epidermal cells. In the present study, 20 human hand tissue samples were evaluated macroscopically and histopathologically. The electrically injured skin samples were subdivided into 2 regions [normal cell regions (NCRs) and polarized cell regions (PCRs)] and 14 major spectral absorption bands were selected. The spectral results showed that the band absorbance at 1080, 1126, 1172, 1242, 1307, 1403, 1456, 1541, 2852, 2925, 2957, 3075, and 3300cm(-1) increased significantly both in the stratum and non-stratum corneum of the PCRs in electrically injured skin tissues samples. No significant difference was found between normal skin and the NCR of the electrically injured skin samples. The band absorbance ratios of A1172/A1126, A1456/A1403, and A2925/A2957 were significantly increased, whereas the A1652/A1541 ratio was decreased in the PCR of the stratum corneum and non-stratum corneum. Baseline changes from 4000 to near 1737cm(-1) were observed in the spectra of the electrically injured skin samples, which were interpreted in terms of the pathological process involved in electrical injury. FTIR-MSP presents a useful method to provide objective spectral markers for the assisted diagnosis of electrical marks.

Cluster analysis of infrared spectra of rabbit cortical bone samples during maturation and growth

Bone consists of an organic and an inorganic matrix. During development, bone undergoes changes in its composition and structure. In this study we apply three different cluster analysis algorithms [K-means (KM), fuzzy C-means (FCM) and hierarchical clustering (HCA)], and discriminant analysis (DA) on infrared spectroscopic data from developing cortical bone with the aim of comparing their ability to correctly classify the samples into different age groups. Cortical bone samples from the mid-diaphysis of the humerus of New Zealand white rabbits from three different maturation stages (newborn (NB), immature (11 days-1 month old), mature (3-6 months old)) were used. Three clusters were obtained by KM, FCM and HCA methods on different spectral regions (amide I, phosphate and carbonate). The newborn samples were well separated (71-100% correct classifications) from the other age groups by all bone components. The mature samples (3-6 months old) were well separated (100%) from those of other age groups by the carbonate spectral region, while by the phosphate and amide I regions some samples were assigned to another group (43-71% correct classifications). The greatest variance in the results for all algorithms was observed in the amide I region. In general, FCM clustering performed better than the other methods, and the overall error was lower. The discriminate analysis results showed that by combining the clustering results from all three spectral regions, the ability to predict the correct age group for all samples increased (from 29-86% to 77-91%). This study is the first to compare several clustering methods on infrared spectra of bone. Fuzzy C-means clustering performed best, and its ability to study the degree of memberships of samples to each cluster might be beneficial in future studies of medical diagnostics.

FTIR spectroscopic analysis of sputum: preliminary findings on a potential novel diagnostic marker for COPD

COPD is a common, progressively disabling disease and a major health burden worldwide. Fourier transform infrared (FTIR) spectroscopy provides for sensitive analysis of complex biological samples. COPD pathogenesis involves quantitative and qualitative changes in sputum biosynthesis. This first study explores whether FTIR can produce distinct spectral profiles of human sputum, and capture differences between COPD and health. Sputum obtained from 15 COPD patients and 15 healthy volunteers was analysed using FTIR spectroscopy; differences in peak positions, height and configuration were identified and measured. All samples gave reproducible characteristic IR absorption spectra. The most relevant regions identified were the amide and glycogen rich regions, showing crucial spectral differences between health and COPD relating to peak position shifts or intensity alteration. These novel preliminary findings support further exploration of FTIR sputum profiling in a clinical study to determine its potential as a practical method for monitoring COPD.

Biomolecular characterisation of leucocytes by infrared spectroscopy

Over the last 15 years, infrared (IR) spectroscopy has developed into a novel and powerful biomedical tool that has multiple applications in the field of haematology. By revealing subtle alterations in both the conformation and concentration of key macromolecules, such as DNA, protein and lipids, IR spectroscopy has been employed to investigate multiple aspects of leucocyte physiology. IR spectroscopy has been used, for example, to diagnose and prognose leukaemia; to characterise differentiation and apoptotic processes; to predict drug sensitivity and resistance in leukaemic patients undergoing chemotherapy; to monitor the response of leucocytes to chemotherapy and to perform human leucocyte antigen matching for bone marrow transplant patients. Such studies have provided insight into pathogenic mechanisms underlying specific leucocyte disorders, especially leukaemia. While it is likely to be some considerable time before IR spectroscopy is sufficiently developed to displace the established technologies, IR spectroscopy has the potential to become a valuable analytic tool in basic and clinical haematology.

Metabolic fingerprinting in disease diagnosis: biomedical applications of infrared and Raman spectroscopy

The ability to diagnose the early onset of disease, rapidly, non-invasively and unequivocally has multiple benefits. These include the early intervention of therapeutic strategies leading to a reduction in morbidity and mortality, and the releasing of economic resources within overburdened health care systems. Some of the routine clinical tests currently in use are known to be unsuitable or unreliable. In addition, these often rely on single disease markers which are inappropriate when multiple factors are involved. Many diseases are a result of metabolic disorders, therefore it is logical to measure metabolism directly. One of the strategies employed by the emergent science of metabolomics is metabolic fingerprinting; which involves rapid, high-throughput global analysis to discriminate between samples of different biological status or origin. This review focuses on a selective number of recent studies where metabolic fingerprinting has been forwarded as a potential tool for disease diagnosis using infrared and Raman spectroscopies.

The use of FTIR microscopy for evaluation of herpes viruses infection development kinetics

The kinetics of Herpes simplex infection development was studied using an FTIR microscopy (FTIR-M) method. The family of herpes viruses includes several members like H. simplex types I and II (HSV I, II), Varicella zoster (VZV) viruses which are involved in various human and animal infections of different parts of the body. In our previous study, we found significant spectral differences between normal uninfected cells in cultures and cells infected with herpes viruses at early stages of the infection. In the present study, cells in cultures were infected with either HSV-I or VZV and at various times post-infection they were examined either by optical microscopy or by advanced FTIR-M. Spectroscopic measurements show a consistent decrease in the intensity of the carbohydrate peak in correlation with the viral infection development, observed by optical microscopy. This decrease in cellular carbohydrate level was used as indicator for herpes viruses infection kinetics. This parameter could be used as a basis for applying a spectroscopic method for the evaluation of herpes virus infection development. Our results show also that the development kinetics of viral infection has an exponential character for these viruses.