Diagnostic and prognostic perspectives of fabry disease via fiber evanescent wave spectroscopy advanced by machine learning.

Fabry disease (FD) is a rare disorder resulting from a genetic mutation characterized by the accumulation of sphingolipids in various cells throughout the human body, leading to progressive and irreversible organ damage, particularly in males. Genetically-determined deficiency or reduced activity of the enzyme (alpha - Galactosidase; α-Gal) leads to the accumulation of sphingolipids in the lysosomes of various cell types, including the heart, kidneys, skin, eyes, central nervous system, and digestive system, triggering damage, leading to the failure of vital organs, and resulting in progressive disability and premature death. FD diagnostics currently depend on costly and time-intensive genetic tests and enzymatic analysis, often leading to delayed or inaccurate diagnoses, which contribute to rapid disease progression.

Coupling mechanisms of plasmon resonance and Bi3+ emission in YAG: Bi, Ce, Yb epitaxial films at low temperatures.

This paper is devoted to the investigation of the plasmonic effect of metal nanoparticles (NPs) formed on the surface of the YAG: Bi, Ce, Yb phosphors in a temperature range between 4 and 300 K. Combination of a thin conversion layer with silver plasmonic nanostructures leads to increase of sensitizer absorption and emission efficiency. Enhancement of Bi luminescence in YAG epitaxial films with Ag NPs was observed upon cooling the samples below 200 K.

Determination of platinum-resistance of women with ovarian cancer by FTIR spectroscopy combined with multivariate analyses and machine learning methods.

Patients with high-grade ovarian cancer have a poor prognosis, thus effective treatment remains an unmet medical issue of high importance. Moreover, finding the reason for resistance to cisplatin is a crucial task for the improvement of anti-cancer drugs. In this study, we showed for the first time a chemical difference in a serum collected from platinum-resistance and platinum-sensitive women suffering from ovarian cancer using Fourier Transform InfraRed (FTIR) spectroscopy followed by a data analysis by Principal Component Analysis (PCA), Hierarchical Component Analysis (HCA) and 4 different machine learning algorithms.

Nanostructured Molecular-Network Arsenoselenides from the Border of a Glass-Forming Region: A Disproportionality Analysis Using Complementary Characterization Probes.

Binary AsSe alloys from the border of a glass-forming region (65 < < 70) subjected to nanomilling in dry and dry-wet modes are characterized by the XRPD, micro-Raman scattering (micro-RS) and revised positron annihilation lifetime (PAL) methods complemented by a disproportionality analysis using the quantum-chemical cluster modeling approach. These alloys are examined with respect to tetra-arsenic biselenide AsSe stoichiometry, realized in glassy g-AsSe, glassy-crystalline g/c-AsSe and glassy-crystalline g/c-AsSe. From the XRPD results, the number of rhombohedral As and cubic arsenolite AsO phases in As-Se alloys increases after nanomilling, especially in the wet mode realized in a PVP water solution.

Molecular-Network Transformations in Tetra-Arsenic Triselenide Glassy Alloys Tuned within Nanomilling Platform.

Polyamorphic transformations driven by high-energy mechanical ball milling (nanomilling) are recognized in a melt-quenched glassy alloy of tetra-arsenic triselenide (AsSe). We employed XRPD analysis complemented by thermophysical heat-transfer and micro-Raman spectroscopy studies. A straightforward interpretation of the medium-range structural response to milling-driven reamorphization is developed within a modified microcrystalline model by treating diffuse peak-halos in the XRPD patterns of this alloy as a superposition of the Bragg-diffraction contribution from inter-planar correlations, which are supplemented by the Ehrenfest-diffraction contribution from inter-atomic and/or inter-molecular correlations related to derivatives of thioarsenide AsSe molecules, mainly dimorphite-type AsSe ones.