Cardiac lipotoxicity is an important contributor to cardiovascular complications during obesity. Given the fundamental role of the endoplasmic reticulum (ER)-resident Selenoprotein T (SELENOT) for cardiomyocyte differentiation and protection and for the regulation of glucose metabolism, we took advantage of a small peptide (PSELT), derived from the SELENOT redox-active motif, to uncover the mechanisms through which PSELT could protect cardiomyocytes against lipotoxicity. To this aim, we modeled cardiac lipotoxicity by exposing H9c2 cardiomyocytes to palmitate (PA). The results showed that PSELT counteracted PA-induced cell death, lactate dehydrogenase release, and the accumulation of intracellular lipid droplets, while an inert form of the peptide (I-PSELT) lacking selenocysteine was not active against PA-induced cardiomyocyte death. Mechanistically, PSELT counteracted PA-induced cytosolic and mitochondrial oxidative stress and rescued SELENOT expression that was downregulated by PA through FAT/CD36 (cluster of differentiation 36/fatty acid translocase), the main transporter of fatty acids in the heart. Immunofluorescence analysis indicated that PSELT also relieved the PA-dependent increase in CD36 expression, while in SELENOT-deficient cardiomyocytes, PA exacerbated cell death, which was not mitigated by exogenous PSELT. On the other hand, PSELT improved mitochondrial respiration during PA treatment and regulated mitochondrial biogenesis and dynamics, preventing the PA-provoked decrease in PGC1-α and increase in DRP-1 and OPA-1. These findings were corroborated by transmission electron microscopy (TEM), revealing that PSELT improved the cardiomyocyte and mitochondrial ultrastructures and restored the ER network. Spectroscopic characterization indicated that PSELT significantly attenuated infrared spectral-related macromolecular changes (i.e., content of lipids, proteins, nucleic acids, and carbohydrates) and also prevented the decrease in membrane fluidity induced by PA. Our findings further delineate the biological significance of SELENOT in cardiomyocytes and indicate the potential of its mimetic PSELT as a protective agent for counteracting cardiac lipotoxicity.

The obsidian of Sierra de las Navajas is well known for its green color and gold hue. In order to relate these features with compositional and microtextural characteristics, we have carried out a microanalytical study by Wave Dispersion System associated to Electron Probe Micro-Analyzer, Scanning Electron Microscope observation, and X-rays micro-tomographic analyses of samples showing different colors (dark to light green, sometimes with bands of different color intensity) and hues (changing, uniform, no hue). In accordance with previous studies, the green color of the obsidian seems to be related to a high iron content, probably in its reduced state. However, no significant difference in composition occurs between dark and light green samples. The SEM observation and microtomographic study revealed the absence of microcrystals and the occurrence of vesicles of different size, shape, and orientation. Lighter green colors are shown by highly vesiculated surfaces, whereas non-vesiculated samples are darker. On the surfaces with a high concentration of coarse vesicles, a uniform golden hue is observed. Decreasing vesiculation gives a hue changing with the angle of incident light. However, when the vesicularity approaches zero, no hue is visible. The iso-orientation of vesicles along preferential directions and their distribution in bands determine the variation in color intensity and hue on differently oriented surfaces. Microvesiculation also influences other characteristics that were important features for the use of obsidian in the past, such as fracture, transparency, and roughness.

Multiple sclerosis (MS) is a neurodegenerative disease of the central nervous system that can lead to long-term disability. The diagnosis of MS is not simple and requires many instrumental and clinical tests. Sampling easily collected biofluids using spectroscopic approaches is becoming of increasing interest in the medical field to integrate and improve diagnostic procedures. Here we present a statistical approach where we combine a number of spectral biomarkers derived from the ATR-FTIR spectra of blood plasma samples of healthy control subjects and MS patients, to obtain a linear predictor useful for discriminating between the two groups of individuals. This predictor provides a simple tool in which the contribution of different molecular components is summarized and, as a result, the sensitivity (80%) and specificity (93%) of the identification are significantly improved compared to those obtained with typical classification algorithms. The strategy proposed can be very helpful when applied to the diagnosis of diseases whose presence is reflected in a minimal way in the analyzed biofluids (blood and its derivatives), as it is for MS as well as for other neurological disorders.