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Left-Right model with radiative double seesaw mechanism

We propose an extended Left-Right symmetric model with an additional global U(1)X symmetry, which collapses to a residual subgroup ℤ2 after spontaneous symmetry breaking. In this model, the light active neutrino masses are generated via a double seesaw mechanism with the Dirac submatrix arising at one loop. In addition, the masses of the charged fermions of the Standard Model (SM) that are lighter

Folding lattice proteins confined on minimal grids using a quantum-inspired encoding

Steric clashes pose a challenge when exploring dense protein systems using conventional explicit-chain methods. A minimal example is a single lattice protein confined on a minimal grid, with no free sites. Finding its minimum energy is a hard optimization problem, with similarities to scheduling problems. It can be recast as a quadratic unconstrained binary optimization (QUBO) problem amenable to

Taurine Intake, Plasma Taurine Concentration, and Dementia Risk : Findings From the Malmö Diet and Cancer Study

Preclinical studies suggest that taurine may exert neuroprotective effects. However, its relevance to dementia risk in human populations remains unclear. We investigated the associations between mid-life dietary taurine intake, circulating taurine concentrations, and the risk of late-life all-cause dementia, Alzheimer's disease (AD), and vascular dementia (VaD) in a large prospective cohort. This

Phosphorylated tau in cerebrospinal fluid-derived extracellular vesicles in Alzheimer’s disease: a pilot study

Alzheimer’s disease (AD) is a debilitating neurodegenerative disorder characterized by brain aggregation of β-amyloid (Aβ) peptides and phosphorylated tau (P-tau) proteins. Extracellular vesicles (EVs) can be isolated and studied for potential roles in disease. While several studies have tested plasma-derived EVs in AD, few have analyzed EVs from cerebrospinal fluid (CSF), which are potentially mo

An annotated high-content fluorescence microscopy dataset with EGFP-Galectin-3-stained cells and manually labelled outlines

Many forms of bioimage analysis involve the detection of objects and their outlines. In the context of microscopy-based high-throughput drug and genomic screening and even in smaller scale microscopy experiments, the objects that most often need to be detected are cells. In order to develop and benchmark algorithms and neural networks that can perform this task, high-quality datasets with annotate

Collagen VII is associated with airway remodeling, honeycombing and fibroblast foci in UIP/IPF

Collagen VII is an essential anchoring protein in the basement membrane zone, maintaining the attachment of stratified and pseudostratified epithelia to the underlying interstitial matrix. However, collagen VII is largely unexplored in normal lungs and idiopathic pulmonary fibrosis (IPF), a disease characterized by excessive accumulation of extracellular matrix (ECM) and aberrant re-epithelializat

In Vivo Photopolymerization : Achieving Detailed Conducting Patterns for Bioelectronics

Bioelectronics holds great potential as therapeutics, but introducing conductive structures within the body poses great challenges. While implanted rigid and substrate-bound electrodes often result in inflammation and scarring in vivo, they outperform the in situ-formed, more biocompatible electrodes by providing superior control over electrode geometry. For example, one of the most researched met

Synovial fibroblasts from children with oligoarticular juvenile idiopathic arthritis induce migration and prolong viability of neutrophils

Introduction: Little is known of the processes that trigger neutrophil activation in the joint of patients with oligoarticular juvenile idiopathic arthritis (oJIA), and if synovial fibroblasts (S-Fib) play an important role in the activation. Therefore, we aimed to investigate whether S-Fib derived from oJIA patients drive neutrophil activation. Methods: Synovial fluid (SF) was collected from pati

Clustering Methods for the Characterization of Synchrotron Radiation X-Ray Fluorescence Images of Human Carotid Atherosclerotic Plaque

This study employs computational algorithms to automatically identify and classify features in X-Ray fluorescence (XRF) microscopy images. Principal component analysis (PCA) and unsupervised machine learning algorithms, such as Gaussian mixture (GM) clustering, are implemented to label features on a collection of XRF maps of human atherosclerotic plaque samples. The investigation involves the hard