GAN-based Virtual Re-Staining: A Promising Solution for Whole Slide Image Analysis

Histopathological cancer diagnosis is based on visual examination of stained tissue slides. Hematoxylin and eosin (H\&E) is a standard stain routinely employed worldwide. It is easy to acquire and cost effective, but cells and tissue components show low-contrast with varying tones of dark blue and pink, which makes difficult visual assessments, digital image analysis, and quantifications. These limitations can be overcome by IHC staining of target proteins of the tissue slide. IHC provides a selective, high-contrast imaging of cells and tissue components, but their use is largely limited by a significantly more complex laboratory processing and high cost. We proposed a conditional CycleGAN (cCGAN) network to transform the H\&E stained images into IHC stained images, facilitating virtual IHC staining on the same slide. This data-driven method requires only a limited amount of labelled data but will generate pixel level segmentation results. The proposed cCGAN model improves the original network \cite{zhu_unpaired_2017} by adding category conditions and introducing two structural loss functions, which realize a multi-subdomain translation and improve the translation accuracy as well. % need to give reasons here. Experiments demonstrate that the proposed model outperforms the original method in unpaired image translation with multi-subdomains. We also explore the potential of unpaired images to image translation method applied on other histology images related tasks with different staining techniques

Processing unit resources in a distributed computing systems

The described program is designed for collecting, storing and processing data of distributed file system

Proteomic Analysis of Pleural Effusions from COVID-19 Deceased Patients: Enhanced Inflammatory Markers

Critically ill COVID-19 patients with pleural effusion experience longer hospitalization, multisystem inflammatory syndrome, and higher rates of mortality. Generally, pleural effusion can serve as a diagnostic value to differentiate cytokine levels. This study aimed to evaluate the pleural effusions of COVID-19 deceased patients for 182 protein markers. Olink® Inflammation and Organ Damage panels were used to determine the level of 184 protein markers, e.g., ADA, BTC, CA12, CAPG, CD40, CDCP1, CXCL9, ENTPD2, Flt3L, IL-6, IL-8, LRP1, OSM, PD-L1, PTN, STX8, and VEGFA, which were raised significantly in COVID-19 deceased patients, showing over-stimulation of the immune system and ravaging cytokine storm. The rises of DPP6 and EDIL3 also indicate damage caused to arterial and cardiovascular organs. Overall, this study confirms the elevated levels of CA12, CD40, IL-6, IL-8, PD-L1, and VEGFA, proposing their potential either as biomarkers for the severity and prognosis of the disease or as targets for therapy. Particularly, this study reports upregulated ADA, BTC, DPP6, EDIL3, LIF, ENTPD2, Flt3L, and LRP1 in severe COVID-19 patients for the first time. Pearson’s correlation coefficient analysis indicates the involvement of JAK/STAT pathways as a core regulator of hyperinflammation in deceased COVID-19 patients, suggesting the application of JAK inhibitors as a potential efficient treatment