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This protocol describes how in-solution protein FTIR can be used to obtain information about the relative contributions of α-helices, β-sheets, β-turn, and random coil structures to a protein's secondary structure. Fourier transform IR (FTIR) spectroscopy is a nondestructive technique for structural characterization of proteins and polypeptides. The IR spectral data of polymers are usually interpreted in terms of the vibrations of a structural repeat. The repeat units in proteins give rise to nine characteristic IR absorption bands (amides A, B and I–VII). Amide I bands (1,700–1,600 cm −1 ) are the most prominent and sensitive vibrational bands of the protein backbone, and they relate to protein secondary structural components. In this protocol, we have detailed the principles that underlie the determination of protein secondary structure by FTIR spectroscopy, as well as the basic steps involved in protein sample preparation, instrument operation, FTIR spectra collection and spectra analysis in order to estimate protein secondary-structural components in aqueous (both H 2 O and deuterium oxide (D 2 O)) solution using algorithms, such as second-derivative, deconvolution and curve fitting. Small amounts of high-purity (>95%) proteins at high concentrations (>3 mg ml −1 ) are needed in this protocol; typically, the procedure can be completed in 1–2 d.

Advances in sample preparation and computation analysis make FTIR of biological materials a rapidly expanding research area. Researchers from a number of universities have collaborated to provide procedures for FTIR analysis of biological samples. IR spectroscopy is an excellent method for biological analyses. It enables the nonperturbative, label-free extraction of biochemical information and images toward diagnosis and the assessment of cell functionality. Although not strictly microscopy in the conventional sense, it allows the construction of images of tissue or cell architecture by the passing of spectral data through a variety of computational algorithms. Because such images are constructed from fingerprint spectra, the notion is that they can be an objective reflection of the underlying health status of the analyzed sample. One of the major difficulties in the field has been determining a consensus on spectral pre-processing and data analysis. This manuscript brings together as coauthors some of the leaders in this field to allow the standardization of methods and procedures for adapting a multistage approach to a methodology that can be applied to a variety of cell biological questions or used within a clinical setting for disease screening or diagnosis. We describe a protocol for collecting IR spectra and images from biological samples (e.g., fixed cytology and tissue sections, live cells or biofluids) that assesses the instrumental options available, appropriate sample preparation, different sampling modes as well as important advances in spectral data acquisition. After acquisition, data processing consists of a sequence of steps including quality control, spectral pre-processing, feature extraction and classification of the supervised or unsupervised type. A typical experiment can be completed and analyzed within hours. Example results are presented on the use of IR spectra combined with multivariate data processing.

Background Unsupervised segmentation of multi-spectral images plays an important role in annotating infrared microscopic images and is an essential step in label-free spectral histopathology. In this context, diverse clustering approaches have been utilized and evaluated in order to achieve segmentations of Fourier Transform Infrared (FT-IR) microscopic images that agree with histopathological characterization. Results We introduce so-called interactive similarity maps as an alternative annotation strategy for annotating infrared microscopic images. We demonstrate that segmentations obtained from interactive similarity maps lead to similarly accurate segmentations as segmentations obtained from conventionally used hierarchical clustering approaches. In order to perform this comparison on quantitative grounds, we provide a scheme that allows to identify non-horizontal cuts in dendrograms. This yields a validation scheme for hierarchical clustering approaches commonly used in infrared microscopy. Conclusions We demonstrate that interactive similarity maps may identify more accurate segmentations than hierarchical clustering based approaches, and thus are a viable and due to their interactive nature attractive alternative to hierarchical clustering. Our validation scheme furthermore shows that performance of hierarchical two-means is comparable to the traditionally used Ward’s clustering. As the former is much more efficient in time and memory, our results suggest another less resource demanding alternative for annotating large spectral images.

Three data fusion strategies (low-llevel, mid-llevel, and high-llevel) combined with a multivariate classification algorithm (random forest, RF) were applied to authenticate the geographical origins of Panax notoginseng collected from five regions of Yunnan province in China. In low-level fusion, the original data from two spectra (Fourier transform mid-IR spectrum and near-IR spectrum) were directly concatenated into a new matrix, which then was applied for the classification. Mid-level fusion was the strategy that inputted variables extracted from the spectral data into an RF classification model. The extracted variables were processed by iterate variable selection of the RF model and principal component analysis. The use of high-level fusion combined the decision making of each spectroscopic technique and resulted in an ensemble decision. The results showed that the mid-level and high-level data fusion take advantage of the information synergy from two spectroscopic techniques and had better classification performance than that of independent decision making. High-level data fusion is the most effective strategy since the classification results are better than those of the other fusion strategies: accuracy rates ranged between 93% and 96% for the low-level data fusion, between 95% and 98% for the mid-level data fusion, and between 98% and 100% for the high-level data fusion. In conclusion, the high-level data fusion strategy for Fourier transform mid-IR and near-IR spectra can be used as a reliable tool for correct geographical identification of P. notoginseng.

Mid-infrared spectroscopy is a widely used tool for material identification and secondary structure analysis in chemistry, biology and biochemistry. However, the diffraction limit prevents nanoscale protein studies. Here we introduce mapping of protein structure with 30 nm lateral resolution and sensitivity to individual protein complexes by Fourier transform infrared nanospectroscopy (nano-FTIR). We present local broadband spectra of one virus, ferritin complexes, purple membranes and insulin aggregates, which can be interpreted in terms of their α-helical and/or β-sheet structure. Applying nano-FTIR for studying insulin fibrils—a model system widely used in neurodegenerative disease research—we find clear evidence that 3-nm-thin amyloid-like fibrils contain a large amount of α-helical structure. This reveals the surprisingly high level of protein organization in the fibril’s periphery, which might explain why fibrils associate. We envision a wide application potential of nano-FTIR, including cellular receptor in vitro mapping and analysis of proteins within quaternary structures. Mid-infrared spectroscopy offers important chemical and structural information about biological samples but diffraction prevents nanoscale studies. Amenabar et al. demonstrate Fourier transform infrared nanospectroscopy for analysing the secondary structure of protein complexes with 30 nm spatial resolution.

Plant cells, tissues and organs are composed of various biomolecules arranged as structurally diverse units, which represent heterogeneity at microscopic levels. Molecular knowledge about those constituents with their localization in such complexity is very crucial for both basic and applied plant sciences. In this context, infrared imaging techniques have advantages over conventional methods to investigate heterogeneous plant structures in providing quantitative and qualitative analyses with spatial distribution of the components. Thus, particularly, with the use of proper analytical approaches and sampling methods, these technologies offer significant information for the studies on plant classification, physiology, ecology, genetics, pathology and other related disciplines. This review aims to present a general perspective about near-infrared and mid-infrared imaging/microspectroscopy in plant research. It is addressed to compare potentialities of these methodologies with their advantages and limitations. With regard to the organization of the document, the first section will introduce the respective underlying principles followed by instrumentation, sampling techniques, sample preparations, measurement, and an overview of spectral pre-processing and multivariate analysis. The last section will review selected applications in the literature.

In the present study, polycaprolactone (PCL) composite films incorporated with various concentrations of grapefruit seed extract (GSE) as an antimicrobial agent were prepared using a twin-screw extruder. Physical characteristics as well as antimicrobial properties of the PCL/GSE composite films were analyzed. The results showed that the surface color of the films gradually changed with increasing GSE concentration. Fourier transform infrared spectra indicated no significant structural changes such as chemical bond formation between PCL and GSE. Thermal properties were slightly affected due to GSE incorporation. Crystallinity of the composite films decreased as the amount of GSE increased. In vitro analysis indicated that the antimicrobial activity of the PCL/GSE composite films increased as the GSE concentration increased, with a 5% concentration showing the strongest inhibitory activity against Listeria monocytogenes , with 5.8-log reduction in bacterial count. Application testing of the films was carried out for cheese packaging, and biodegradation of the samples was assessed via soil burial testing. Our findings confirmed the potential use of PCL/GSE composite films as biodegradable food packaging material with antimicrobial activity.

Rapid, high-resolution, label-free Fourier-transform infrared imaging of biological samples is made possible by combining multiple synchrotron beams with wide-field detection. Conventional Fourier-transform infrared (FTIR) microspectroscopic systems are limited by an inevitable trade-off between spatial resolution, acquisition time, signal-to-noise ratio (SNR) and sample coverage. We present an FTIR imaging approach that substantially extends current capabilities by combining multiple synchrotron beams with wide-field detection. This advance allows truly diffraction-limited high-resolution imaging over the entire mid-infrared spectrum with high chemical sensitivity and fast acquisition speed while maintaining high-quality SNR.

Background Fourier Transform Infrared (FTIR) spectroscopy has emerged as a powerful analytical tool in medical research, offering non‐invasive and precise examination of the molecular composition of biological samples. The primary objective of this review is to underscore the benefits of FTIR spectroscopy in medicinal research, emphasizing its ability to delineate molecular fingerprints and assist in the identification of biochemical structures and key peaks in biological samples. Methods This review comprehensively explores the diverse applications of FTIR spectroscopy in medical investigations, with a specific focus on its utility in analyzing tissue, cells, and hair samples. Various sources, including Google Scholar, PubMed, WorledCat and Scopus, were utilized to conduct this comprehensive literature review. Results Recent advancements showcase the versatility of FTIR spectroscopy in elucidating cellular and molecular processes, facilitating disease diagnostics, and enabling treatment monitoring. Notably, FTIR spectroscopy has found significant utility in clinical assessment, particularly in screening counterfeit medicines, owing to its user‐friendly operation and minimal sample preparation requirements. Furthermore, customs officials can leverage this technique for preliminary analysis of suspicious samples. Conclusion This review aims to bridge a gap in the literature and serve as a valuable resource for future research endeavors in FTIR spectroscopy within the medical domain. Additionally, it presents fundamental concepts of FTIR spectroscopy and spectral data interpretation, highlighting its utility as a tool for molecular analysis using Mid‐Infrared (MIR) radiation.

This study aims to collect information about soil investigation by FTIR. As we know, the FTIR technique is most often used in organic and bioorganic chemistry, while in geochemistry FTIR spectroscopy is not used very often. Therefore, there is a problem with the identification and interpretation of the IR spectra of minerals contained in sediments and soils. The reason for this is a deficiency of data about characteristic wavenumbers for minerals. Therefore, this study reviews and sums up, in one place, published articles that are connected to an investigation of minerals from 2002 to 2021 (based on the Scopus database). Additionally, the present review highlights various analytical techniques (ATR-FTIR, DRIFT, 2D-IR, and SR-FTIR) and discusses some of them for geochemical study. Additionally, the study describes helpful tools in the data pre-processing of IR spectra (normalization, baseline correction, and spectral derivatives).