Results 41 to 50 of about 1,497,934 (318)
FEBS Letters, EarlyView.Low‐density lipoprotein receptor‐related protein 6 (LRP6) is a key receptor for the Wnt antagonist Dickkopf1 (DKK1). DKK1 protein expression is induced in a bleomycin (BLM)‐induced lung injury model. We show that DKK1 induces proinflammatory and profibrotic genes in lung fibroblasts.
Eun‐Ah Sung +6 more
wiley +1 more source
Animals, 2020 Avian influenza virus (AIV) remains one of the enzootic zoonotic diseases that challenges the poultry industry in Egypt. In the present study, a total of 500 tissue samples were collected from 100 chicken farms (broilers and layers) suspected to be ...
Samah Mosad Mosad +4 more
doaj +1 more source
SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology [PDF]
arXiv, 2023 Semantic segmentations of pathological entities have crucial clinical value in computational pathology workflows. Foundation models, such as the Segment Anything Model (SAM), have been recently proposed for universal use in segmentation tasks. SAM shows remarkable promise in instance segmentation on natural images.
arxiv
Characteristics of the Kelch domain containing (KLHDC) subfamily and relationships with diseases
FEBS Letters, EarlyView.The Kelch protein superfamily includes 63 members, with the KLHDC subfamily having 10 proteins. While their functions are not fully understood, recent advances in KLHDC2's structure and role in protein degradation have highlighted its potential for drug development, especially in PROTAC therapies.
Courtney Pilcher +6 more
wiley +1 more source
Unsupervised Pathology Image Segmentation Using Representation Learning with Spherical K-means [PDF]
Proc. SPIE 10581, Medical Imaging 2018: Digital Pathology, 1058111
(6 March 2018), 2018 This paper presents a novel method for unsupervised segmentation of pathology images. Staging of lung cancer is a major factor of prognosis. Measuring the maximum dimensions of the invasive component in a pathology images is an essential task. Therefore, image segmentation methods for visualizing the extent of invasive and noninvasive components on ...
arxiv +1 more source
Making tau amyloid models in vitro: a crucial and underestimated challenge
FEBS Letters, EarlyView.This review highlights the challenges of producing in vitro amyloid assemblies of the tau protein. We review how accurately the existing protocols mimic tau deposits found in the brain of patients affected with tauopathies. We discuss the important properties that should be considered when forming amyloids and the benchmarks that should be used to ...
Julien Broc, Clara Piersson, Yann Fichou
wiley +1 more source
Pathological EEG Findings in the Patients with the First Seizure Admitted to the Emergency Department [PDF]
Reviews in Clinical Medicine, 2019 Background: According to statistics, at least four percent of people experience one or more nonfebrile seizures in their life span. Continuous Electroencephalography (cEEG) Monitoring is a useful diagnostic tool for seizure detection. The purpose of this
Mohsen Ebrahimi +5 more
doaj +1 more source
Benchmarking Self-Supervised Learning on Diverse Pathology Datasets [PDF]
arXiv, 2022 Computational pathology can lead to saving human lives, but models are annotation hungry and pathology images are notoriously expensive to annotate. Self-supervised learning has shown to be an effective method for utilizing unlabeled data, and its application to pathology could greatly benefit its downstream tasks.
arxiv
Pathology Segmentation using Distributional Differences to Images of Healthy Origin [PDF]
In International MICCAI Brainlesion Workshop, pp. 228-238.
Springer, Cham, 2018, 2018 Fully supervised segmentation methods require a large training cohort of already segmented images, providing information at the pixel level of each image. We present a method to automatically segment and model pathologies in medical images, trained solely on data labelled on the image level as either healthy or containing a visual defect.
arxiv +1 more source