Analysis of ischemic intestinal tissue composition based on visible and near-infrared reflectance hyperspectral imaging and multivariate curve resolution.

Acute mesenteric ischemia (AMI) is a life-threatening, rapidly progressive disease. Conventional diagnostic methods have their own limitations. Therefore, a non-invasive, real-time and efficient diagnostic method is needed.

Optimizing Nanofiltration Membrane Layer-by-Layer Modification: Chemometric and Morphological Insights.

Nanofiltration (NF) membranes are essential in wastewater treatment, battery industries, and brine management for selectively removing multivalent ions. However, fouling reduces their lifespan and necessitates harsh cleaning. The layer-by-layer (LBL) technique addresses this by modifying surface properties, enhancing rejection of divalent cations, such as magnesium and calcium, and minimizing fouling.

Multiscale and Multimodal Image Fusion. Coping with Differences in Scanned Area and Spatial Resolution for Raman/Fluorescence Images of Labeled Cells.

Multiscale and multimodal image fusion is a challenge derived from the diversity of chemical and spatial information provided by the current hyperspectral image platforms. Efficient image fusion approaches are essential to exploit the complementary chemical information across different zoom scales. Most current image fusion algorithms tend to work by equalizing the spatial characteristics of the platforms to be combined, i.

Probing the Intramolecular Folding of Nucleic Acids with Native Ion Mobility Mass Spectrometry: Strategies and Caveats.

The goal of native mass spectrometry is to obtain information on noncovalent interactions in solution through mass spectrometry measurements in the gas phase. Characterizing intramolecular folding requires using structural probing techniques such as ion mobility spectrometry. However, inferring solution structures of nucleic acids is difficult because the low-charge state ions produced from aqueous solutions at physiological ionic strength get compacted during electrospray.

Blind instrument response function identification from fluorescence decays.

Time-resolved fluorescence spectroscopy plays a crucial role when studying dynamic properties of complex photochemical systems. Nevertheless, the analysis of measured time decays and the extraction of exponential lifetimes often requires either the experimental assessment or the modeling of the instrument response function (IRF). However, the intrinsic nature of the IRF in the measurement process, which may vary across measurements due to chemical and instrumental factors, jeopardizes the results obtained by reconvolution approaches.

Analysing olive ripening with digital image RGB histograms.

Digital images are commonly used to monitor processes that are based on colour changes due to their simplicity and easy capture. Colour information in these images can be analysed objectively and accurately using colour histograms. One such process is olive ripening, which is characterized by changes in chemical composition, sensory properties and can be followed by changes in physical appearance, mainly colour.

Kernelizing: A way to increase accuracy in trilinear decomposition analysis of multiexponential signals.

The unmixing of multiexponential decay signals into monoexponential components using soft modelling approaches is a challenging task due to the strong correlation and complete window overlap of the profiles. To solve this problem, slicing methodologies, such as PowerSlicing, tensorize the original data matrix into a three-way data array that can be decomposed based on trilinear models providing unique solutions. Satisfactory results have been reported for different types of data, e.

Data fusion of LIBS and PIL hyperspectral imaging: Understanding the luminescence phenomenon of a complex mineral sample.

Laser-induced breakdown spectroscopy (LIBS) imaging is an innovative technique that associates the valuable atomic, ionic and molecular emission signals of the parent spectroscopy with spatial information. LIBS works using a powerful pulse laser as excitation source, to generate a plasma exhibiting emission lines of atoms, ions and molecules present in the ablated matter. The advantages of LIBS imaging are potential high sensitivity (in the order of ppm), easy sample preparation, fast acquisition rate (up to 1 kHz) and μm scale spatial resolution (weight of the ablated material in the order of ng).

Linear unmixing protocol for hyperspectral image fusion analysis applied to a case study of vegetal tissues.

Hyperspectral imaging (HSI) is a useful non-invasive technique that offers spatial and chemical information of samples. Often, different HSI techniques are used to obtain complementary information from the sample by combining different image modalities (Image Fusion). However, issues related to the different spatial resolution, sample orientation or area scanned among platforms need to be properly addressed.

SWiVIA - Sliding window variographic image analysis for real-time assessment of heterogeneity indices in blending processes monitored with hyperspectral imaging.

Controlling blending processes of solid material using advanced real-time sensing technologies tools is crucial to guarantee the quality attributes of manufactured products from diverse industries. The use of process analytical technology (PAT) tools based on chemical imaging systems are useful to assess heterogeneity information during mixing processes. Recently, a powerful procedure for heterogeneity assessment based on the combination of off-line acquired chemical images and variographic analysis has been proposed to provide specific heterogeneity indices related to global and distributional heterogeneity.

Multivariate Curve Resolution Slicing of Multiexponential Time-Resolved Spectroscopy Fluorescence Data.

Time-resolved fluorescence spectroscopy (TRFS), i.e., measurement of fluorescence decay curves for different excitation and/or emission wavelengths, provides specific and sensitive local information on molecules and on their environment.

Multivariate Curve Resolution: 50 years addressing the mixture analysis problem - A review.

Multivariate Curve Resolution (MCR) covers a wide span of algorithms designed to tackle the mixture analysis problem by expressing the original data through a bilinear model of pure component meaningful contributions. Since the seminal work by Lawton and Sylvestre in 1971, MCR methods are dynamically evolving to adapt to a wealth of diverse and demanding scientific scenarios. To do so, essential concepts, such as basic constraints, have been revisited and new modeling tasks, mathematical properties and domain-specific information have been incorporated; the initial underlying bilinear model has evolved into a flexible framework where hybrid bilinear/multilinear models can coexist, the regular data structures have undergone a turn of the screw and incomplete multisets and matrix and tensor combinations can be now analyzed.

Acid number, viscosity and end-point detection in a multiphase high temperature polymerisation process using an online miniaturised MEMS Fabry-Pérot interferometer.

Recent advances in the latest generation of MEMS (micro-electro-mechanical system) Fabry-Pérot interferometers (FPI) for near infrared (NIR) wavelengths has led to the development of ultra-fast and low cost NIR sensors with potential to be used by the process industry. One of these miniaturised sensors operating from 1350 to 1650 nm, was integrated into a software platform to monitor a multiphase solid-gas-liquid process, for the production of saturated polyester resins. Twelve batches were run in a 2 L reactor mimicking industrial conditions (24 h process, with temperatures ranging from 220 to 240 °C), using an immersion NIR transmission probe.

Design of Heterogeneity Indices for Blending Quality Assessment Based on Hyperspectral Images and Variographic Analysis.

Heterogeneity characterization is crucial to define the quality of end products and to describe the evolution of processes that involve blending of compounds. The heterogeneity concept describes both the diversity of physicochemical characteristics of sample fragments (constitutional heterogeneity) and the diversity of spatial distribution of the materials/compounds in the sample (distributional heterogeneity, DH). Hyperspectral images (HSIs) are unique analytical measurements that provide physicochemical and spatial information on samples and, hence, are ideal to perform heterogeneity studies.

3D and 4D Image Fusion: Coping with Differences in Spectroscopic Modes among Hyperspectral Images.

Image fusion is often oriented to solve differences in spatial scale and orientation among different spectroscopic platforms. However, an additional problem arises when the nature of the spectroscopic information differs in dimensionality as well. Indeed, most imaging systems, e.

Process Monitoring of Moisture Content and Mass Transfer Rate in a Fluidised Bed with a Low Cost Inline MEMS NIR Sensor.

Purpose: The current trend for continuous drug product manufacturing requires new, affordable process analytical techniques (PAT) to ensure control of processing. This work evaluates whether property models based on spectral data from recent Fabry-Pérot Interferometer based NIR sensors can generate a high-resolution moisture signal suitable for process control.

Methods: Spectral data and offline moisture content were recorded for 14 fluid bed dryer batches of pharmaceutical granules.

Understanding the Formation of Heartwood in Larch Using Synchrotron Infrared Imaging Combined With Multivariate Analysis and Atomic Force Microscope Infrared Spectroscopy.

Formation of extractive-rich heartwood is a process in live trees that make them and the wood obtained from them more resistant to fungal degradation. Despite the importance of this natural mechanism, little is known about the deposition pathways and cellular level distribution of extractives. Here we follow heartwood formation in var.

Data fusion strategies to combine sensor and multivariate model outputs for multivariate statistical process control.

Process analytical technologies (PAT) applied to process monitoring and control generally provide multiple outputs that can come from different sensors or from different model outputs generated from a single multivariate sensor. This paper provides a contribution to current data fusion strategies for the combination of sensor and/or model outputs in the development of multivariate statistical process control (MSPC) models. Data fusion is explored through three real process examples combining output from multivariate models coming from the same sensor uniquely (in the near-infrared (NIR)-based end point detection of a two-stage polyester production process) or the combination of these outputs with other process variable sensors (using NIR-based model outputs and temperature values in the end point detection of a fluidized bed drying process and in the on-line control of a distillation process).

Study of conformational transitions of i-motif DNA using time-resolved fluorescence and multivariate analysis methods.

Recently, the presence of i-motif structures at C-rich sequences in human cells and their regulatory functions have been demonstrated. Despite numerous steady-state studies on i-motif at neutral and slightly acidic pH, the number and nature of conformation of this biological structure are still controversial. In this work, the fluorescence lifetime of labelled molecular beacon i-motif-forming DNA sequences at different pH values is studied.

Assessment of tissue-specific multifactor effects in environmental -omics studies of heterogeneous biological samples: Combining hyperspectral image information and chemometrics.

The use of hyperspectral imaging techniques in biological studies has increased in the recent years. Hyperspectral images (HSI) provide chemical information and preserve the morphology and original structure of heterogeneous biological samples, which can be potentially useful in environmental -omics studies when effects due to several factors, e.g.

Study of light-induced formation of photodimers in the i-motif nucleic acid structure by rapid-scan FTIR difference spectroscopy and hybrid hard- and soft-modelling.

The i-motif is a DNA structure formed by cytosine-rich sequences, very relevant from a biochemical point of view and potentially useful in nanotechnology as pH-sensitive nanodevices or nanomotors. To provide a different view on the structural changes and dynamics of direct excitation processes involving i-motif structures, the use of rapid-scan FTIR spectroscopy is proposed. Hybrid hard- and soft-modelling based on the Multivariate Curve Resolution by Alternating Least Squares (MCR-ALS) algorithm has been used for the resolution of rapid-scan FTIR spectra and the interpretation of the photochemically induced time-dependent conformational changes of i-motif structures.

Multivariate unmixing approaches on Raman images of plant cell walls: new insights or overinterpretation of results?

Background: Plant cell walls are nanocomposites based on cellulose microfibrils embedded in a matrix of polysaccharides and aromatic polymers. They are optimized for different functions (e.g.

Handling Different Spatial Resolutions in Image Fusion by Multivariate Curve Resolution-Alternating Least Squares for Incomplete Image Multisets.

Data fusion of different imaging techniques allows a comprehensive description of chemical and biological systems. Yet, joining images acquired with different spectroscopic platforms is complex because of the different sample orientation and image spatial resolution. Whereas matching sample orientation is often solved by performing suitable affine transformations of rotation, translation, and scaling among images, the main difficulty in image fusion is preserving the spatial detail of the highest spatial resolution image during multitechnique image analysis.

Unravelling the Metabolic Progression of Breast Cancer Cells to Bone Metastasis by Coupling Raman Spectroscopy and a Novel Use of Mcr-Als Algorithm.

Raman spectroscopy (RS) has shown promise as a tool to reveal biochemical changes that occur in cancer processes at the cellular level. However, when analyzing clinical samples, RS requires improvements to be able to resolve biological components from the spectra. We compared the strengths of Multivariate Curve Resolution (MCR) versus Principal Component Analysis (PCA) to deconvolve meaningful biological components formed by distinct mixtures of biological molecules from a set of mixed spectra.