Enhancing Diagnostic Capabilities for Occupational Lung Diseases Using LIBS Imaging on Biopsy Tissue.

Laser-induced breakdown spectroscopy (LIBS) imaging continues to gain strength as an influential bioanalytical technique, showing intriguing potential in the field of clinical analysis. This is because hyperspectral LIBS imaging allows for rapid, comprehensive elemental analysis, covering elements from major to trace levels consistently year after year. In this study, we estimated the potential of a multivariate spectral data treatment approach based on a so-called convex envelope method to detect exotic elements (whether they are minor or in trace amounts) in biopsy tissues of patients with occupational exposure-related diseases. More precisely, we have developed an approach called Interesting Features Finder (IFF), which initially allowed us to identify unexpected elements without any preconceptions, considering only the set of spectra contained in a LIBS hyperspectral data cube. This task is, in fact, almost impossible with conventional chemometric tools, as it entails identifying a few exotic spectra among several hundred thousand others. Once this detection was performed, a second approach based on correlation was used to locate their distribution in the biopsies. Through this unique data analysis pipeline to processing massive LIBS spectroscopic data, it was possible to detect and locate exotic elements such as tin and rhodium in a patient's tissue section, ultimately leading to a possible reclassification of their lung condition as an occupational disease. This review will thus demonstrate the potential of this new diagnostic tool based on LIBS imaging in addressing the shortcomings of approaches developed thus far. The proposed data processing approach naturally transcends this specific framework and can be leveraged across various domains of analytical chemistry, where the detection of rare events is concealed within extensive data sets.

When Social Media Empowers Analytical Chemists to Explore Millions of Spectra Derived from a Complex Sample.

Analytical chemistry has never yielded such a wealth of experimental data as it does today, and this exponential trend shows no sign of abating. We continually advance the capabilities of our instruments and conceive innovative concepts, all in a concerted effort to naturally push the boundaries of our understanding regarding intricate sample matrices. Spectroscopic imaging, in the broadest sense, is certainly the field where we observe this acceleration even more pronouncedly. Analytical chemistry swiftly grasped the significance of processing acquired data for comprehensive exploration through utilization of chemometrics or machine learning tools. One can assert today that chemometrics undeniably constitutes an integral facet in the advancement of an analytical approach. However, we are now faced with a new challenge, as the experimental data accumulated for certain analytical techniques are so vast and massive that exploring them with such tools has become unfeasible, and this is by no means a computational capacity issue. Analytical chemistry is far from being the sole field affected by this issue, and one could argue that others have grappled with it long before us, such as, for instance, social media, to name just one. The purpose of this paper is to demonstrate that such a domain, which may initially seem distant from our concerns, can offer novel tools capable of overcoming these barriers, even though we are not necessarily dealing with the same objects. More specifically, we delve into the clustering of over 10 million LIBS spectra acquired as part of an imaging experiment aimed at exploring a singular rock sample. This will serve to demonstrate that an open-source library developed by Meta (formerly known as Facebook) can enable us to conduct a comprehensive exploration of this sample, a feat deemed impossible with conventional data analysis approaches.

Use of color based chromatographic images obtained from comprehensive two-dimensional gas chromatography in authentication analyses.

Comprehensive two-dimensional gas chromatography (GC×GC) has been an important technique used to acquire as much information as possible from a wide variety of samples. Qualitative contour plots analysis provides useful information and in daily use it ends up being handled as images of the volatile organic compounds by analysts. Cachaça samples are used in this paper to showcase the use of two-dimensional chromatographic images as the main source for authentication purposes through one-class classifiers, such as data-driven soft independent modeling of class analogy (DD-SIMCA). The proposed workflow summarizes this fast and easy process, which can be used to certify a specific brand in comparison to other brands, as well as to authenticate if samples have been adulterated. Lower quality cachaças, non-aged cachaças and cachaças aged in different wooden barrels were tested as adulterants. Chromatographic images allowed for the distinction of all brands and nearly every adulteration tested. Sensitivity was estimated at 100% for all models and specificity ranged from 96% to 100%. Different approaches were used, alternating from working with whole-sized images to working with smaller resized versions of those images. Resized chromatographic images could be potentially useful to easily compensate for slight chromatographic misalignments, allowing for faster calculations and the use of simpler software. Reductions to 50% and 25% of the original size were tested and the results did not greatly differ from whole images model. As such, 2D chromatographic images have been found to be an interesting form of evaluating a product's authenticity.

Characterization of the aroma profile of novel Brazilian wines by solid-phase microextraction using polymeric ionic liquid sorbent coatings.

In this study, a series of polymeric ionic liquid (PIL) sorbent coatings is evaluated for the extraction of polar volatile organic compounds (VOCs) from Brazilian wines using headspace solid-phase microextraction (HS-SPME), including samples from 'Isabella' and 'BRS Magna' cultivars-the latter was recently introduced by the Brazilian Agricultural Research Corporation - National Grape & Wine Research Center. The structurally tuned SPME coatings were compared to the commercial SPME phases, namely poly(acrylate) (PA) and divinylbenzene/carboxen/poly(dimethylsiloxane) (DVB/CAR/PDMS). The separation, detection and identification of the aroma profiles were obtained using comprehensive two-dimensional gas chromatography mass spectrometry (GC×GC-MS). The best performing PIL-based SPME fiber, namely 1-hexadecyl-3-vinylimidazolium bis[(trifluoromethyl)sulfonyl]imide with 1,12-di(3-vinylimidazolium)dodecane dibis[(trifluoromethyl)sulfonyl]imide incorporated cross-linker supported on an elastic nitinol wire, exhibited superior performance to DVB/CAR/PDMS regarding the average number of extracted peaks and extracted more polar analytes providing additional insight into the aroma profile of 'BRS Magna' wines. Four batches of wine were evaluated, namely 'Isabella' and 'BRS Magna' vintages 2015 and 2016, using highly selective PIL-based SPME coatings and enabled the detection of 350+ peaks. Furthermore, this is the first report evaluating the aroma of 'BRS Magna' wines. A hybrid approach that combined pixel-based Fisher ratio and peak table-based data comparison was used for data handling. This proof-of-concept experiment provided reliable and statistically valid distinction of wines that may guide regulation agencies to create high sample throughput protocols to screen wines exported by Brazilian vintners. Graphical abstract Highly selective extraction of wine aroma using polymeric ionic liquid.

Cell-permeable gomesin peptide promotes cell death by intracellular Ca(2+) overload.

In recent years, the antitumoral activity of antimicrobial peptides (AMPs) has been the goal of many research studies. Among AMPs, gomesin (Gm) displays antitumor activity by unknown mechanisms. Herein, we studied the cytotoxicity of Gm in the Chinese hamster ovary (CHO) cell line. Furthermore, we investigated the temporal ordering of organelle changes and the dynamics of Ca(2+) signaling during Gm-induced cell death. The results indicated that Gm binds to the plasma membrane and rapidly translocates into the cytoplasm. Moreover, 20 µM Gm increases the cytosolic Ca(2+) and induces membrane permeabilization after 30 min of treatment. Direct Ca(2+) measurements in CHO cells transfected with the genetically encoded D1-cameleon to the endoplasmic reticulum (ER) revealed that Gm induces ER Ca(2+) depletion, which in turn resulted in oscillatory mitochondrial Ca(2+) signal, as measured in cells expressing the genetically encoded probe to the mitochondrial matrix (mit)Pericam. This leads to mitochondria disruption, loss of mitochondrial membrane potential and increased reactive oxygen species prior to membrane permeabilization. Gm-induced membrane permeabilization by a Ca(2+)-dependent pathway involving Gm translocation into the cell, ER Ca(2+) depletion and disruption, mitochondrial Ca(2+) overload and oxidative stress.