The consumers' interest towards beer consumption has been on the rise during the past decade: new approaches and ingredients get tested, expanding the traditional recipe for brewing beer. As a consequence, the field of "beeromics" has also been constantly growing, as well as the demand for quick and exhaustive analytical methods. In this study, we propose a combination of nuclear magnetic resonance (NMR) spectroscopy and chemometrics to characterize beer. H-NMR spectra were collected and then analyzed using chemometric tools. An interval-based approach was applied to extract chemical features from the spectra to build a dataset of resolved relative concentrations. One aim of this work was to compare the results obtained using the full spectrum and the resolved approach: with a reasonable amount of time needed to obtain the resolved dataset, we show that the resolved information is comparable with the full spectrum information, but interpretability is greatly improved.
Whole slide images (WSI), obtained by high-resolution digital scanning of microscope slides at multiple scales, are the cornerstone of modern Digital Pathology. However, they represent a particular challenge to artificial intelligence (AI)-based/AI-mediated analysis because pathology labeling is typically done at slide-level, instead of tile-level. It is not just that medical diagnostics is recorded at the specimen level, the detection of oncogene mutation is also experimentally obtained, and recorded by initiatives like The Cancer Genome Atlas (TCGA), at the slide level.
Tardigrada, the water bears, are microscopic animals with walking appendages, that are members of Ecdysozoa, the clade of moulting animals that also includes Nematoda (round worms), Nematomorpha (horsehair worms), Priapulida (penis worms), Kinorhyncha (mud dragons), Loricifera (loricated animals), Arthropoda (insects, spiders centipedes, crustaceans and their allies) and Onychophora (velvet worms). The phylogenetic relationships within Ecdysozoa are still unclear, with analyses of molecular and morphological data yielding incongruent results. Here we use CAT-posterior mean site frequencies (CAT-PMSF), a new method to export dataset-specific mixture models (CAT-Poisson and CAT-GTR) parameterized using Bayesian methods to maximum likelihood software.
Diabetic cardiomyopathy (DCM) is a leading cause of death in diabetic patients. Current therapies do not adequately resolve this problem and focus only on the optimal level of blood glucose for patients. Ferroptosis plays an important role in diabetes mellitus and cardiovascular diseases.
This retrospective, real-life cohort was analyzed to detect the frequency of different HRM evolution patterns and their correlation with MNV types, morphological and functional changes in exudative nAMD under long-term anti-VEGF therapy. We evaluated optical coherence tomography (OCT) volume scans in 143 eyes of 94 nAMD patients (start of anti-VEGF therapy 2009-2018, therapy until the last visit) and recorded the VA at all visits. HRM evolution patterns were differentiated: pattern 1 = no HRM, pattern 2 = subretinal HRM resolved during follow-up, pattern 3 = persistent subretinal HRM with new HRM-boundary remodeling [BR], pattern 4 = persistent subretinal HRM without HRM-BR.
Background: Coherent diffraction imaging (CDI) is an important lens-free imaging method. As a variant of CDI, ptychography enables the imaging of objects with arbitrary lateral sizes. However, traditional phase retrieval methods are time-consuming for ptychographic imaging of large-size objects, e.
