Unlocking biomedical data sharing: A structured approach with digital twins and artificial intelligence (AI) for open health sciences.

Objective: Data sharing promotes the scientific progress. However, not all data can be shared freely due to privacy issues. This work is intended to foster FAIR sharing of sensitive data exemplary in the biomedical domain, via an integrated computational approach for utilizing and enriching individual datasets by scientists without coding experience.

The underuse of AI in the health sector: Opportunity costs, success stories, risks and recommendations.

Purpose: This contribution explores the underuse of artificial intelligence (AI) in the health sector, what this means for practice, and how much the underuse can cost. Attention is drawn to the relevance of an issue that the European Parliament has outlined as a "major threat" in 2020. At its heart is the risk that research and development on trusted AI systems for medicine and digital health will pile up in lab centers without generating further practical relevance.

A historical perspective of biomedical explainable AI research.

The black-box nature of most artificial intelligence (AI) models encourages the development of explainability methods to engender trust into the AI decision-making process. Such methods can be broadly categorized into two main types: post hoc explanations and inherently interpretable algorithms. We aimed at analyzing the possible associations between COVID-19 and the push of explainable AI (XAI) to the forefront of biomedical research.

Assessment of Mitochondrial Ca Uptake.

Mitochondrial Ca uptake regulates mitochondrial function and contributes to cell signaling. Accordingly, quantifying mitochondrial Ca signals and elaborating the mechanisms that accomplish mitochondrial Ca uptake are essential to gain our understanding of cell biology. Here, we describe the benefits and drawbacks of various established old and new techniques to assess dynamic changes of mitochondrial Ca concentration ([Ca]) in a wide range of applications.

Mutation-based clustering and classification analysis reveals distinctive age groups and age-related biomarkers for glioma.

Background: Malignant brain tumor diseases exhibit differences within molecular features depending on the patient's age.

Methods: In this work, we use gene mutation data from public resources to explore age specifics about glioma. We use both an explainable clustering as well as classification approach to find and interpret age-based differences in brain tumor diseases.

Open Data for Differential Network Analysis in Glioma.

The complexity of cancer diseases demands bioinformatic techniques and translational research based on big data and personalized medicine. Open data enables researchers to accelerate cancer studies, save resources and foster collaboration. Several tools and programming approaches are available for analyzing data, including annotation, clustering, comparison and extrapolation, merging, enrichment, functional association and statistics.

The role of artificial intelligence and machine learning in harmonization of high-resolution post-mortem MRI (virtopsy) with respect to brain microstructure.

Enhanced resolution of 7 T magnetic resonance imaging (MRI) scanners has considerably advanced our knowledge of structure and function in human and animal brains. Post-industrialized countries are particularly prone to an ever-increasing number of ageing individuals and ageing-associated neurodegenerative diseases. Neurodegenerative diseases are associated with volume loss in the affected brain.

Use case driven evaluation of open databases for pediatric cancer research.

Background: A plethora of Web resources are available offering information on clinical, pre-clinical, genomic and theoretical aspects of cancer, including not only the comprehensive cancer projects as ICGC and TCGA, but also less-known and more specialized projects on pediatric diseases such as PCGP. However, in case of data on childhood cancer there is very little information openly available. Several web-based resources and tools offer general biomedical data which are not purpose-built, for neither pediatric nor cancer analysis.

In silico cancer research towards 3R.

Background: Improving our understanding of cancer and other complex diseases requires integrating diverse data sets and algorithms. Intertwining in vivo and in vitro data and in silico models are paramount to overcome intrinsic difficulties given by data complexity. Importantly, this approach also helps to uncover underlying molecular mechanisms.

In silico modeling for tumor growth visualization.

Background: Cancer is a complex disease. Fundamental cellular based studies as well as modeling provides insight into cancer biology and strategies to treatment of the disease. In silico models complement in vivo models.

Integrated web visualizations for protein-protein interaction databases.

Background: Understanding living systems is crucial for curing diseases. To achieve this task we have to understand biological networks based on protein-protein interactions. Bioinformatics has come up with a great amount of databases and tools that support analysts in exploring protein-protein interactions on an integrated level for knowledge discovery.

Assessment of mitochondrial Ca²⁺ uptake.

Mitochondrial Ca(2+) uptake regulates mitochondrial function and contributes to cell signaling. Accordingly, quantifying mitochondrial Ca(2+) signals and elaborating the mechanisms that accomplish mitochondrial Ca(2+) uptake are essential to gain our understanding of cell biology. Here, we describe the benefits and drawbacks of various established old and new techniques to assess dynamic changes of mitochondrial Ca(2+) concentration ([Ca(2+)]mito) in a wide range of applications.

Mitochondrial Ca(2+) uniporter (MCU)-dependent and MCU-independent Ca(2+) channels coexist in the inner mitochondrial membrane.

A protein referred to as CCDC109A and then renamed to mitochondrial calcium uniporter (MCU) has recently been shown to accomplish mitochondrial Ca(2+) uptake in different cell types. In this study, we investigated whole-mitoplast inward cation currents and single Ca(2+) channel activities in mitoplasts prepared from stable MCU knockdown HeLa cells using the patch-clamp technique. In whole-mitoplast configuration, diminution of MCU considerably reduced inward Ca(2+) and Na(+) currents.

Molecularly distinct routes of mitochondrial Ca2+ uptake are activated depending on the activity of the sarco/endoplasmic reticulum Ca2+ ATPase (SERCA).

The transfer of Ca(2+) across the inner mitochondrial membrane is an important physiological process linked to the regulation of metabolism, signal transduction, and cell death. While the definite molecular composition of mitochondrial Ca(2+) uptake sites remains unknown, several proteins of the inner mitochondrial membrane, that are likely to accomplish mitochondrial Ca(2+) fluxes, have been described: the novel uncoupling proteins 2 and 3, the leucine zipper-EF-hand containing transmembrane protein 1 and the mitochondrial calcium uniporter. It is unclear whether these proteins contribute to one unique mitochondrial Ca(2+) uptake pathway or establish distinct routes for mitochondrial Ca(2+) sequestration.

Characterization of distinct single-channel properties of Ca²⁺ inward currents in mitochondria.

Previous studies have demonstrated several molecularly distinct players involved in mitochondrial Ca(2+) uptake. In the present study, electrophysiological recordings on mitoplasts that were isolated from HeLa cells were performed in order to biophysically and pharmacologically characterize Ca(2+) currents across the inner mitochondrial membrane. In mitoplast-attached configuration with 105 mM Ca(2+) as a charge carrier, three distinct channel conductances of 11, 23, and 80 pS were observed.

Studying mitochondrial Ca(2+) uptake - a revisit.

Mitochondrial Ca(2+) sequestration is a well-known process that is involved in various physiological and pathological mechanisms. Using isolated suspended mitochondria one unique mitochondrial Ca(2+) uniporter was considered to account ubiquitously for the transfer of Ca(2+) into these organelles. However, by applying alternative techniques for measuring mitochondrial Ca(2+) uptake evidences for molecularly distinct mitochondrial Ca(2+) carriers accumulated recently.

Leucine zipper EF hand-containing transmembrane protein 1 (Letm1) and uncoupling proteins 2 and 3 (UCP2/3) contribute to two distinct mitochondrial Ca2+ uptake pathways.

Cytosolic Ca(2+) signals are transferred into mitochondria over a huge concentration range. In our recent work we described uncoupling proteins 2 and 3 (UCP2/3) to be fundamental for mitochondrial uptake of high Ca(2+) domains in mitochondria-ER junctions. On the other hand, the leucine zipper EF hand-containing transmembrane protein 1 (Letm1) was identified as a mitochondrial Ca(2+)/H(+) antiporter that achieved mitochondrial Ca(2+) sequestration at small Ca(2+) increases.