Machine Learning Approaches for the Fusion of Near-Infrared, Mid-Infrared, and Raman Data to Identify Cartilage Degradation in Human Osteochondral Plugs.

Vibrational spectroscopy methods such as mid-infrared (MIR), near-infrared (NIR), and Raman spectroscopies have been shown to have great potential for in vivo biomedical applications, such as arthroscopic evaluation of joint injuries and degeneration. Considering that these techniques provide complementary chemical information, in this study, we hypothesized that combining the MIR, NIR, and Raman data from human osteochondral samples can improve the detection of cartilage degradation. This study evaluated 272 osteochondral samples from 18 human knee joins, comprising both healthy and damaged tissue according to the reference Osteoarthritis Research Society International grading system.

Signatures of top versus bottom illuminations and their predicted implications for infrared transmission microspectroscopy.

Since both top and bottom illuminations are widely used in infrared transmission measurements, in this paper, we study the effects of different illuminations on the signatures in infrared microspectroscopy. By simulating a series of dielectric samples, we show that their extinction efficiency, , remains unchanged when the direction of the incident plane wave is reversed, even though the field distributions both inside and outside of the sample may be dramatically different. We find features in that are correlated with whispering gallery modes for one beam direction and correspond to completely different field distributions for the opposite beam direction.

Global biochemical profiling of fast-growing Antarctic bacteria isolated from meltwater ponds by high-throughput FTIR spectroscopy.

Fourier transform infrared (FTIR) spectroscopy is a biophysical technique used for non-destructive biochemical profiling of biological samples. It can provide comprehensive information about the total cellular biochemical profile of microbial cells. In this study, FTIR spectroscopy was used to perform biochemical characterization of twenty-nine bacterial strains isolated from the Antarctic meltwater ponds.

Prediction of Deoxynivalenol Contamination in Wheat via Infrared Attenuated Total Reflection Spectroscopy and Multivariate Data Analysis.

The climate crisis further exacerbates the challenges for food production. For instance, the increasingly unpredictable growth of fungal species in the field can lead to an unprecedented high prevalence of several mycotoxins, including the most important toxic secondary metabolite produced by spp., i.

Explorative characterization and taxonomy-aligned comparison of alterations in lipids and other biomolecules in Antarctic bacteria grown at different temperatures.

Temperature significantly impacts bacterial physiology, metabolism and cell chemistry. In this study, we analysed lipids and the total cellular biochemical profile of 74 fast-growing Antarctic bacteria grown at different temperatures. Fatty acid diversity and temperature-induced alterations aligned with bacterial classification-Gram-groups, phylum, genus and species.

Raman spectroscopy online monitoring of biomass production, intracellular metabolites and carbon substrates during submerged fermentation of oleaginous and carotenogenic microorganisms.

Background: Monitoring and control of both growth media and microbial biomass is extremely important for the development of economical bioprocesses. Unfortunately, process monitoring is still dependent on a limited number of standard parameters (pH, temperature, gasses etc.), while the critical process parameters, such as biomass, product and substrate concentrations, are rarely assessable in-line.

Fourier Transform Infrared microspectroscopy identifies single cancer cells in blood. A feasibility study towards liquid biopsy.

The management of cancer patients has markedly improved with the advent of personalised medicine where treatments are given based on tumour antigen expression amongst other. Within this remit, liquid biopsies will no doubt improve this personalised cancer management. Identifying circulating tumour cells in blood allows a better assessment for tumour screening, staging, response to treatment and follow up.

A Portable Infrared Attenuated Total Reflection Spectrometer for Food Analysis.

The analytical performance of a compact infrared attenuated total reflection spectrometer using a pyroelectric detector array has been evaluated and compared to a conventional laboratory Fourier transform infrared system for applications in food analysis. Analytical characteristics including sensitivity, repeatability, linearity of the calibration functions, signal-to-noise ratio, and spectral resolution have been derived for both approaches. Representative analytes of relevance in food industries (i.

Characterisation of Cartilage Damage via Fusing Mid-Infrared, Near-Infrared, and Raman Spectroscopic Data.

Mid-infrared spectroscopy (MIR), near-infrared spectroscopy (NIR), and Raman spectroscopy are all well-established analytical techniques in biomedical applications. Since they provide complementary chemical information, we aimed to determine whether combining them amplifies their strengths and mitigates their weaknesses. This study investigates the feasibility of the fusion of MIR, NIR, and Raman spectroscopic data for characterising articular cartilage integrity.

Sparse wavelengths data in mid-infrared spectroscopy: Modelling approaches and channel sampling.

Infrared instruments with smaller and cost-effective components such as bandpass filters, single channel detectors, and laser-based light sources are being developed to provide cheaper and faster analysis of biological samples. Such instruments often provide measurements in form of sparse data, which include a collection of single-frequency channels or a collection of channels covering very narrow spectral ranges, called here multi-frequency channels. To keep costs low, the number of channels needs to be kept at a minimum.

Diffraction-limited mid-infrared microspectroscopy to reveal a micron-thick interfacial water layer signature.

Mid-infrared microspectroscopy is a non-invasive tool for identifying the molecular structure and chemical composition at the scale of the probe, at the scale of the beam. Consequently, investigating small objects or domains (commensurable to the wavelength) requires high-resolution measurements, even down to the diffraction limit. Herein, different protocols and machines allowing high-resolution measurements in transmission mode (aperture size (, beam size) from 15 × 15 μm to 3 × 3 μm) are tested using the same sample.

Production of docosahexaenoic acid from spruce sugars using Aurantiochytrium limacinum.

In this study lignocellulosic sugars from Norway spruce were used for production of docosahexaenoic acid (DHA) by the marine thraustochytrid Aurantiochytrium limacinum SR21. Enzymatically prepared spruce hydrolysate was combined with a complex nitrogen source and different amounts of salts. Shake flask batch cultivations revealed that addition of extra salts was not needed for optimal growth.

Domes and semi-capsules as model systems for infrared microspectroscopy of biological cells.

It is well known that infrared microscopy of micrometer sized samples suffers from strong scattering distortions, attributed to Mie scattering. The state-of-the-art preprocessing technique for modelling and removing Mie scattering features from infrared absorbance spectra of biological samples is built on a meta model for perfect spheres. However, non-spherical cell shapes are the norm rather than the exception, and it is therefore highly relevant to evaluate the validity of this preprocessing technique for deformed spherical systems.

Deep learning-enabled Inference of 3D molecular absorption distribution of biological cells from IR spectra.

Infrared spectroscopy delivers abundant information about the chemical composition, as well as the structural and optical properties of intact samples in a non-destructive manner. We present a deep convolutional neural network which exploits all of this information and solves full-wave inverse scattering problems and thereby obtains the 3D optical, structural and chemical properties from infrared spectroscopic measurements of intact micro-samples. The proposed model encodes scatter-distorted infrared spectra and infers the distribution of the complex refractive index function of concentrically spherical samples, such as many biological cells.

Optimizing extraction solvents for deoxynivalenol analysis in maize infrared attenuated total reflection spectroscopy and chemometric methods.

Farmers, cereal suppliers and processors demand rapid techniques for the assessment of mould-associated contamination. Deoxynivalenol (DON) is among the most important toxins and related to human and animal diseases besides causing significant economic losses. Routine analytical techniques for the analysis of DON are either based on chromatographic or immunoanalytical techniques, which are time-consuming and frequently rely on hazardous consumables.

Effects of the coupling of dielectric spherical particles on signatures in infrared microspectroscopy.

Infrared microspectroscopy is a powerful tool in the analysis of biological samples. However, strong electromagnetic scattering may occur since the wavelength of the incident radiation and the samples may be of comparable size. Based on the Mie theory of single spheres, correction algorithms have been developed to retrieve pure absorbance spectra.

Temperature- and Nutrients-Induced Phenotypic Changes of Antarctic Green Snow Bacteria Probed by High-Throughput FTIR Spectroscopy.

Temperature fluctuations and nutrient composition are the main parameters influencing green snow microbiome. In this study we investigated the influence of temperature and nutrient conditions on the growth and cellular chemical profile of bacteria isolated from green snow. Chemical profiling of the green snow bacteria was done by high-throughput FTIR spectroscopy combined with multivariate data analysis.

Genetic variants associated with two major bovine milk fatty acids offer opportunities to breed for altered milk fat composition.

Background: Although bovine milk is regarded as healthy and nutritious, its high content of saturated fatty acids (FA) may be harmful to cardiovascular health. Palmitic acid (C16:0) is the predominant saturated FA in milk with adverse health effects that could be countered by substituting it with higher levels of unsaturated FA, such as oleic acid (C18:1cis-9). In this work, we performed genome-wide association analyses for milk fatty acids predicted from FTIR spectroscopy data using 1811 Norwegian Red cattle genotyped and imputed to a high-density 777k single nucleotide polymorphism (SNP)-array.

Preclassification of Broadband and Sparse Infrared Data by Multiplicative Signal Correction Approach.

Preclassification of raw infrared spectra has often been neglected in scientific literature. Separating spectra of low spectral quality, due to low signal-to-noise ratio, presence of artifacts, and low analyte presence, is crucial for accurate model development. Furthermore, it is very important for sparse data, where it becomes challenging to visually inspect spectra of different natures.

The Use of Constituent Spectra and Weighting in Extended Multiplicative Signal Correction in Infrared Spectroscopy.

Extended multiplicative signal correction (EMSC) is a widely used preprocessing technique in infrared spectroscopy. EMSC is a model-based method favored for its flexibility and versatility. The model can be extended by adding constituent spectra to explicitly model-known analytes or interferents.

Preprocessing Strategies for Sparse Infrared Spectroscopy: A Case Study on Cartilage Diagnostics.

The aim of the study was to optimize preprocessing of sparse infrared spectral data. The sparse data were obtained by reducing broadband Fourier transform infrared attenuated total reflectance spectra of bovine and human cartilage, as well as of simulated spectral data, comprising several thousand spectral variables into datasets comprising only seven spectral variables. Different preprocessing approaches were compared, including simple baseline correction and normalization procedures, and model-based preprocessing, such as multiplicative signal correction (MSC).

Exploring Dry-Film FTIR Spectroscopy to Characterize Milk Composition and Subclinical Ketosis throughout a Cow's Lactation.

The use of technologies for measurements of health parameters of individual cows may ensure early detection of diseases and maximization of individual cow and herd potential. In the present study, dry-film Fourier transform infrared spectroscopy (FTIR) was evaluated for the purpose of detecting and quantifying milk components during cows' lactation. This was done in order to investigate if these systematic changes can be used to identify cows experiencing subclinical ketosis.

A robust metabolomics approach for the evaluation of human embryos from fertilization.

The identification of the most competent embryos for transfer to the uterus constitutes the main challenge of fertilization (IVF). We established a metabolomic-based approach by applying Fourier transform infrared (FTIR) spectroscopy on 130 samples of 3-day embryo culture supernatants from 26 embryos that implanted and 104 embryos that failed. On examining the internal structure of the data by unsupervised multivariate analysis, we found that the supernatant spectra of nonimplanted embryos constituted a highly heterogeneous group.

An automated approach for fringe frequency estimation and removal in infrared spectroscopy and hyperspectral imaging of biological samples.

In infrared spectroscopy of thin film samples, interference introduces distortions in spectra, commonly referred to as fringes. Fringes may alter absorbance peak ratios, which hampers the spectral analysis. We have previously introduced extended multiplicative signal correction (EMSC) for fringes correction.