SMART-PET: a Self-SiMilARiTy-aware generative adversarial framework for reconstructing low-count [18F]-FDG-PET brain imaging.

Introduction: In Positron Emission Tomography (PET) imaging, the use of tracers increases radioactive exposure for longitudinal evaluations and in radiosensitive populations such as pediatrics. However, reducing injected PET activity potentially leads to an unfavorable compromise between radiation exposure and image quality, causing lower signal-to-noise ratios and degraded images. Deep learning-based denoising approaches can be employed to recover low count PET image signals: nonetheless, most of these methods rely on structural or anatomic guidance from magnetic resonance imaging (MRI) and fails to effectively preserve global spatial features in denoised PET images, without impacting signal-to-noise ratios.

Myeloproliferative Neoplasm-like Mutations of Calreticulin Induce Phenotypes Associated with Calreticulin Dysfunction in .

In previous research, we created a model with homozygous mutations in calreticulin similar to those found in patients with essential thrombocythemia (ET) and primary myelofibrosis (PMF), two myeloproliferative neoplasms (MPNs). This model, lacking JAK orthologs, enabled us to examine the transcriptomic effects caused by mutant calreticulin without the influence of JAK/STAT activation, the primary pathogenic mechanism associated with calreticulin mutations known to date. Most of the gene expression changes observed seemed to be due to a partial loss of protein function, with the alteration of the extracellular matrix being particularly notable.

Isolates of species in the marine environment in the Philippines.

spp. are considered the most commonly occurring free-living amoebae (FLA) in the environment. Their high resilience enables them to thrive in different types of environments.