Improving Blind Spot Denoising for Microscopy

Many microscopy applications are limited by the total amount of usable light and are consequently challenged by the resulting levels of noise in the acquired images. This problem is often addressed via (supervised) deep learning based denoising. Recently, by making assumptions about the noise statistics, self-supervised methods have emerged. Such methods are trained directly on the images that are to be denoised and do not require additional paired training data. While achieving remarkable results, self-supervised methods can produce high-frequency artifacts and achieve inferior results compared to supervised approaches. Here we present a novel way to improve the quality of self-supervised denoising. Considering that light microscopy images are usually diffraction-limited, we propose to include this knowledge in the denoising process. We assume the clean image to be the result of a convolution with a point spread function (PSF) and explicitly include this operation at the end of our neural network. As a consequence, we are able to eliminate high-frequency artifacts and achieve self-supervised results that are very close to the ones achieved with traditional supervised methods.Comment: 15 pages, 4 figure

Stellar Coronal and Wind Models: Impact on Exoplanets

Surface magnetism is believed to be the main driver of coronal heating and stellar wind acceleration. Coronae are believed to be formed by plasma confined in closed magnetic coronal loops of the stars, with winds mainly originating in open magnetic field line regions. In this Chapter, we review some basic properties of stellar coronae and winds and present some existing models. In the last part of this Chapter, we discuss the effects of coronal winds on exoplanets.Comment: Chapter published in the "Handbook of Exoplanets", Editors in Chief: Juan Antonio Belmonte and Hans Deeg, Section Editor: Nuccio Lanza. Springer Reference Work

A Comprehensive Analysis of the Dynamic Biological Networks in HCV Induced Hepatocarcinogenesis

Hepatocellular carcinoma (HCC) is a primary malignancy of the liver, which is closely related to hepatitis C and cirrhosis. The molecular mechanisms underlying the hepatocarcinogenesis induced by HCV infection remain clarified from a standpoint of systems biology. By integrating data from protein-protein interactions, transcriptional regulation, and disease related microarray analysis, we carried out a dynamic biological network analysis on the progression of HCV induced hepatocarcinogenesis, and systematically explored the potentially disease-related mechanisms through a network view. The dysfunctional interactions among proteins and deregulatory relationships between transcription factors and their target genes could be causes for the occurrence and progression of this disease. The six pathologically defined disease stages in the development and progression of HCC after HCV infection were included in this study. We constructed disease-related biological networks for each disease stage, and identified progression-related sub-networks that potentially play roles in the developmental stage of the corresponding disease and participate in the later stage of cancer progression. In addition, we identified novel risk factors related to HCC based on the analysis of the progression-related sub-networks. The dynamic characteristics of the network reflect important features of the disease development and progression, which provide important information for us to further explore underlying mechanisms of the disease

Involvement in surface antigen expression by a moonlighting FG-repeat nucleoporin in trypanosomes

Components of the nuclear periphery coordinate a multitude of activities, including macromolecular transport, cell-cycle progression, and chromatin organization. Nuclear pore complexes (NPCs) mediate nucleocytoplasmic transport, mRNA processing, and transcriptional regulation, and NPC components can define regions of high transcriptional activity in some organisms at the nuclear periphery and nucleoplasm. Lineage-specific features underpin several core nuclear functions and in trypanosomatids, which branched very early from other eukaryotes, unique protein components constitute the lamina, kinetochores, and parts of the NPCs. Here we describe a phenylalanine-glycine (FG)-repeat nucleoporin, TbNup53b, that has dual localizations within the nucleoplasm and NPC. In addition to association with nucleoporins, TbNup53b interacts with a known trans-splicing component, TSR1, and has a role in controlling expression of surface proteins including the nucleolar periphery-located, procyclin genes. Significantly, while several nucleoporins are implicated in intranuclear transcriptional regulation in metazoa, TbNup53b appears orthologous to components of the yeast/human Nup49/Nup58 complex, for which no transcriptional functions are known. These data suggest that FG-Nups are frequently co-opted to transcriptional functions during evolution and extend the presence of FG-repeat nucleoporin control of gene expression to trypanosomes, suggesting that this is a widespread and ancient eukaryotic feature, as well as underscoring once more flexibility within nucleoporin function