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4 Publications visible to you, out of a total of 4
A liver digital twin for in silico testing of cellular and inter-cellular mechanisms in regeneration after drug-induced damage

Abstract

Not specified

Authors: Jieling Zhao, Ahmed Ghallab, Reham Hassan, Steven Dooley, Jan Georg Hengstler, Dirk Drasdo

Date Published: 1st Feb 2024

Publication Type: Journal

Gene regulatory network inference in the era of single-cell multi-omics

Abstract

Not specified

Authors: Pau Badia-i-Mompel, Lorna Wessels, Sophia Müller-Dott, Rémi Trimbour, Ricardo O. Ramirez Flores, Ricard Argelaguet, Julio Saez-Rodriguez

Date Published: 1st Nov 2023

Publication Type: Journal

Guided interactive image segmentation using machine learning and color-based image set clustering

Abstract (Expand)

Abstract Motivation Over the last decades, image processing and analysis have become one of the key technologies in systems biology and medicine. The quantification of anatomical structures and dynamic …The quantification of anatomical structures and dynamic processes in living systems is essential for understanding the complex underlying mechanisms and allows, i.e. the construction of spatio-temporal models that illuminate the interplay between architecture and function. Recently, deep learning significantly improved the performance of traditional image analysis in cases where imaging techniques provide large amounts of data. However, if only a few images are available or qualified annotations are expensive to produce, the applicability of deep learning is still limited. Results We present a novel approach that combines machine learning-based interactive image segmentation using supervoxels with a clustering method for the automated identification of similarly colored images in large image sets which enables a guided reuse of interactively trained classifiers. Our approach solves the problem of deteriorated segmentation and quantification accuracy when reusing trained classifiers which is due to significant color variability prevalent and often unavoidable in biological and medical images. This increase in efficiency improves the suitability of interactive segmentation for larger image sets, enabling efficient quantification or the rapid generation of training data for deep learning with minimal effort. The presented methods are applicable for almost any image type and represent a useful tool for image analysis tasks in general. Availability and implementation The presented methods are implemented in our image processing software TiQuant which is freely available at tiquant.hoehme.com. Supplementary information Supplementary data are available at Bioinformatics online.

Authors: Adrian Friebel, Tim Johann, Dirk Drasdo, Stefan Hoehme

Date Published: 1st Oct 2022

Publication Type: Journal

Non-Invasive Detection of Fibrotic NASH in NAFLD Patients with Low or Intermediate FIB-4

Abstract (Expand)

Background: Non-alcoholic steatohepatitis (NASH) and fibrosis are the main prognostic factors in non-alcoholic fatty liver disease (NAFLD). The FIB-4 score has been suggested as an initial test for the …l test for the exclusion of progressed fibrosis. However, increasing evidence suggests that also NASH patients with earlier fibrosis stages are at risk of disease progression, emphasizing the need for improved non-invasive risk stratification. Methods: We evaluated whether the apoptosis biomarker M30 can identify patients with fibrotic NASH despite low or intermediate FIB-4 values. Serum M30 levels were assessed by ELISA, and FIB-4 was calculated in an exploration (n = 103) and validation (n = 100) cohort of patients with histologically confirmed NAFLD. Results: The majority of patients with low FIB-4 (cut-off value < 1.3) in the exploration cohort revealed increased M30 levels (>200 U/L) and more than 80% of them had NASH, mostly with fibrosis. NASH was also detected in all patients with intermediate FIB-4 (1.3 to 2.67) and elevated M30, from which ~80% showed fibrosis. Importantly, in the absence of elevated M30, most patients with FIB-4 < 1.3 and NASH showed also no fibrosis. Similar results were obtained in the validation cohort. Conclusions: The combination of FIB-4 with M30 enables a more reliable identification of patients at risk for progressed NAFLD and might, therefore, improve patient stratification.

Authors: Katharina John, Martin Franck, Sherin Al Aoua, Monika Rau, Yvonne Huber, Joern M. Schattenberg, Andreas Geier, Matthias J. Bahr, Heiner Wedemeyer, Klaus Schulze-Osthoff, Heike Bantel

Date Published: 1st Aug 2022

Publication Type: Journal

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