Geographic risk assessment of Batrachochytrium salamandrivorans invasion in Costa Rica as a means of informing emergence management and mitigation.

Remotely-sensed risk assessments of emerging, invasive pathogens are key to targeted surveillance and outbreak responses. The recent emergence and spread of the fungal pathogen, Batrachochytrium salamandrivorans (Bsal), in Europe has negatively impacted multiple salamander species. Scholars and practitioners are increasingly concerned about the potential consequences of this lethal pathogen in the Americas, where salamander biodiversity is higher than anywhere else in the world.

Denoising low-field MR images with a deep learning algorithm based on simulated data from easily accessible open-source software.

In this study, we introduce a denoising method aimed at improving the contrast ratio in low-field MRI (LFMRI) using an advanced 3D deep convolutional residual network model. Our approach employs synthetic brain imaging datasets that closely mimic the contrast and noise characteristics of LFMRI scans, addressing the limitation of available in-vivo LFMRI datasets for training deep learning models. In the simulation data, the Relative Contrast Ratio (RCR) increased, and similar improvements were observed in the in-vivo data across different imaging conditions.

Functional analysis of fibroblasts and macrophages in head and neck paragangliomas.

Background And Aim: Head and neck paragangliomas (HNPGN) are tumours that carry significant morbidity The role of the stroma in the pathogenesis of HNPGN is not completely understood. This study explores the profile of fibroblasts and macrophages in HNPGN.

Methods: Ten patients undergoing HNPGN surgery were recruited.