The use of vibrational spectroscopy techniques, such as Fourier-transform infrared (FTIR) and Raman spectroscopy, has been a successful method to study the interaction of light with biological materials and facilitate novel cell biology analysis. Disease screening and diagnosis, microbiological studies, forensic and environmental investigations make use of spectrochemical analysis very attractive due to its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for multivariate classification protocols allowing one to analyse biological-derived spectrochemical data in order to obtain accurate and reliable results. This is stimulated by the fact that applications of deep-learning algorithms of complex datasets are being increasingly recognized as critical towards extracting important information and visualizing it in a readily interpretable form. Hereby, we have constructed a protocol for multivariate classification analysis of vibrational spectroscopy data [FTIR, Raman and near-infrared (NIR)] highlighting a series of critical steps, such as pre-processing, data selection, feature extraction, classification and model validation. This is an essential aspect towards the construction of a practical spectrochemical analysis model for biological analysis in real-world applications, where fast, accurate and reliable classification models are fundamental.

Spectroscopic techniques, such as Fourier-transform infrared (FTIR) spectroscopy, are used to study the interaction of light with biological materials. This interaction forms the basis of many analytical assays used in disease screening and diagnosis, microbiological studies, forensic and environmental investigations. Advantages of spectrochemical analysis are its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for repetition and validation of these methods in large-scale studies and across different research groups, which would bring the method closer to clinical and/or industrial implementation. In order for this to succeed, it is important to understand and reduce the effect of random spectral alterations caused by inter-individual, inter-instrument and/or inter-laboratory variations, such as variations in air humidity and CO2 levels, and the aging of instrumental parts.Thus, it is evident that spectral standardization is crucial for the widespread adoption of these spectrochemical technologies. By using calibration transfer procedures, where the spectral response of a secondary instrument is standardized to resemble the spectral response of a primary instrument, different sources of variations can be normalized into a single model using computational-based methods, such as direct standardization (DS) and piecewise direct standardization (PDS); therefore, measurements performed under different conditions can generate the same result, eliminating the need for a full recalibration. In this paper, we have constructed a protocol for model standardization using different transfer technologies described for FTIR spectrochemical applications. This is a critical step towards the construction of a practical spectrochemical analysis model for daily routine analysis, where uncertain and random variations are present. 4 worldwide are developing spectrochemical approaches for diagnosis, discrimination and monitoring of diseases, as well as for other uses. Combination of multiple datasets would facilitate the conduction of large-scale studies which are still lacking in the field of bio-spectroscopy. Sensor-based technologiesSensor-based technologies are an integral part of daily life ranging from locating sensorbased technology, such as global positioning system (GPS) 6 , to image biosensors, such as X-rays 7-10 and γ-rays [11][12][13] , which are used extensively for medical applications. Other powerful approaches that make use of sensor-based technologies toward medical disease examination and diagnostics include circular dichroism (CD) spectroscopy 14-17 , ultraviolet (UV) or visible spectroscopy 18,19 , fluorescence 20-24 , nuclear magnetic resonance (NMR) spectroscopy 25-29 and ultrasound (US) 7,30- .Over the last two decades, optical biosensors employing vibrational spectroscopy, particularly IR spectroscopy, have seen tremendous progress in biomedical and biological research. A number of studies using the above-mentioned methods ha...

The progressive aging of the world's population makes a higher prevalence of neurodegenerative diseases inevitable. The necessity for an accurate, but at the same time, inexpensive and minimally invasive, diagnostic test is urgently required, not only to confirm the presence of the disease but also to discriminate between different types of dementia to provide the appropriate management and treatment. In this study, attenuated total reflection FTIR (ATR-FTIR) spectroscopy combined with chemometric techniques were used to analyze blood plasma samples from our cohort. Blood samples are easily collected by conventional venepuncture, permitting repeated measurements from the same individuals to monitor their progression throughout the years or evaluate any tested drugs. We included 549 individuals: 347 with various neurodegenerative diseases and 202 age-matched healthy individuals. Alzheimer's disease (AD; n = 164) was identified with 70% sensitivity and specificity, which after the incorporation of apolipoprotein e4 genotype (APOE e4) information, increased to 86% when individuals carried one or two alleles of e4, and to 72% sensitivity and 77% specificity when individuals did not carry e4 alleles. Early AD cases (n = 14) were identified with 80% sensitivity and 74% specificity. Segregation of AD from dementia with Lewy bodies (DLB; n = 34) was achieved with 90% sensitivity and specificity. Other neurodegenerative diseases, such as frontotemporal dementia (FTD; n = 30), Parkinson's disease (PD; n = 32), and progressive supranuclear palsy (PSP; n = 31), were included in our cohort for diagnostic purposes. Our method allows for both rapid and robust diagnosis of neurodegeneration and segregation between different dementias.Alzheimer's disease | dementia with Lewy bodies | apolipoprotein E | differential diagnosis | spectroscopy

a b s t r a c tThis review presents a retrospective of the studies carried out in the last 10 years (2006e2016) using spectroscopic methods as a research tool in the field of virology. Spectroscopic analyses are sensitive to variations in the biochemical composition of the sample, are non-destructive, fast and require the least sample preparation, making spectroscopic techniques tools of great interest in biological studies. Herein important chemometric algorithms that have been used in virological studies are also evidenced as a good alternative for analyzing the spectra, discrimination and classification of samples. Techniques that have not yet been used in the field of virology are also suggested. This methodology emerges as a new and promising field of research, and may be used in the near future as diagnosis tools for detecting diseases caused by viruses.