Digital image analysis and artificial intelligence in pathology diagnostics-the Swiss view.

Digital pathology (DP) is increasingly entering routine clinical pathology diagnostics. As digitization of the routine caseload advances, implementation of digital image analysis algorithms and artificial intelligence tools becomes not only attainable, but also desirable in daily sign out. The Swiss Digital Pathology Consortium (SDiPath) has initiated a Delphi process to generate best-practice recommendations for various phases of the process of digitization in pathology for the local Swiss environment, encompassing the following four topics: i) scanners, quality assurance, and validation of scans; ii) integration of scanners and systems into the pathology laboratory information system; iii) the digital workflow; and iv) digital image analysis (DIA)/artificial intelligence (AI).

Computer-Assisted Diagnosis of Lymph Node Metastases in Colorectal Cancers Using Transfer Learning With an Ensemble Model.

Screening of lymph node metastases in colorectal cancer (CRC) can be a cumbersome task, but it is amenable to artificial intelligence (AI)-assisted diagnostic solution. Here, we propose a deep learning-based workflow for the evaluation of CRC lymph node metastases from digitized hematoxylin and eosin-stained sections. A segmentation model was trained on 100 whole-slide images (WSIs).

Incidence of Venous Thromboembolism in Multiple Myeloma Patients across Different Regimens: Role of Procoagulant Microparticles and Cytokine Release.

Introduction: Multiple myeloma (MM) is characterized by a high prevalence of thrombotic complications. Microvesicles (MVs) are small membrane vesicles released from activated cells, and they may potentially contribute to thrombosis. Methods: We have evaluated the plasma levels of MVs and cytokines (IL-10, IL-17, and TGF-β in MM and Watch and Wait Smoldering MM (WWSMM) from patients and related them to thrombotic complications.

Multiple ways to evade the bacteriostatic action of glyphosate in rhizobia include the mutation of the conserved serine 90 of the nitrogenase subunit NifH to alanine.

The genome resequencing of spontaneous glyphosate-resistant mutants derived from the soybean inoculant E109 allowed identifying genes most likely associated with the uptake (gltL and cya) and metabolism (zigA and betA) of glyphosate, as well as with nitrogen fixation (nifH). Mutations in these genes reduce the lag phase and improve nodulation under glyphosate stress. In addition to providing glyphosate resistance, the amino acid exchange Ser90Ala in NifH increased the citrate synthase activity, growth rate and plant growth-promoting efficiency of E109 in the absence of glyphosate stress, suggesting roles for this site during both the free-living and symbiotic growth stages.