The ubiquitous eolian dust on Mars plays important roles in the current sedimentary and atmospheric processes of the planet. The ChemCam instrument retrieves a consistent eolian dust composition at the submillimeter scale from every first laser shot on Mars targets. Its composition presents significant differences with the Aeolis Palus soils and the Bagnold dunes as it contains lower CaO and higher SiO₂. The dust FeO and TiO₂ contents are also higher, probably associated with nanophase oxide components. The dust spectra show the presence of volatile elements (S and Cl), and the hydrogen content is similar to Bagnold sands but lower than Aeolis Palus soils. Consequently, the dust may be a contributor to the amorphous component of soils, but differences in composition indicate that the two materials are not equivalent.

The impact of altering laser focusing conditions on laser-induced breakdown spectroscopy experiments is investigated under ambient Earth laboratory and simulated Martian atmospheres. Experiments were performed in which the focal spot size was varied on a sample by altering the lens to sample distance with respect to targets of interest. Samples investigated include aluminum, copper, and steel. Specific neutral and ionic transitions of each sample were monitored. Atomic and ionic emissions show different intensity peak distributions along the varying lens to sample distance. Ionic species have peak emissions when laser plasma is initiated with a focused spot within the sample in ambient Earth laboratory air, while atomic emissions have peak intensities several millimeters deeper into a sample. In simulated Martian atmospheres, atomic emissions are observed to peak when the laser is focused within the sample, while ionic emissions have peak intensities when the laser is focused near the surface of a sample.

Early detection of Alzheimer's disease is essential for effective treatment and the development of therapies that modify disease progression. Developing sensitive and specific noninvasive diagnostic tools is crucial for improving clinical outcomes and advancing our understanding of this condition. Liquid biopsy techniques, especially those involving plasma biomarkers, provide a promising noninvasive method for early diagnosis and disease monitoring. In this study, we analyzed the plasma proteomic profiles of 38 healthy individuals, with an average age of 66.5 years, and 22 patients with Alzheimer's disease, with an average age of 79.7 years. Proteins in the plasma were quantified using specialized panels designed for proteomic extension assays. Through computational analysis using a linear support vector machine algorithm, we identified 82 differentially expressed proteins between the two groups. From these, we calculated 6642 possible protein ratios and identified specific combinations of these ratios as significant features for distinguishing between individuals with Alzheimer's disease and healthy individuals. Notably, the protein ratios kynureninase to macrophage scavenger receptor type 1, Neurocan to protogenin, and interleukin-5 receptor alpha to glial cell line-derived neurotrophic factor receptor alpha 1 achieving accuracy up to 98 % in differentiating between the two groups. This study underscores the potential of leveraging protein relationships, expressed as ratios, in advancing Alzheimer's disease diagnostics. Furthermore, our findings highlight the promise of liquid biopsy techniques as a noninvasive and accurate approach for early detection and monitoring of Alzheimer's disease using blood plasma.