The Prevalence of TNFα-Induced Necrosis over Apoptosis Is Determined by TAK1-RIP1 Interplay

Death receptor-induced programmed necrosis is regarded as a secondary death mechanism dominating only in cells that cannot properly induce caspase-dependent apoptosis. Here, we show that in cells lacking TGFβ-activated Kinase-1 (TAK1) expression, catalytically active Receptor Interacting Protein 1 (RIP1)-dependent programmed necrosis overrides apoptotic processes following Tumor Necrosis Factor-α (TNFα) stimulation and results in rapid cell death. Importantly, the activation of the caspase cascade and caspase-8-mediated RIP1 cleavage in TNFα-stimulated TAK1 deficient cells is not sufficient to prevent RIP1-dependent necrosome formation and subsequent programmed necrosis. Our results demonstrate that TAK1 acts independently of its kinase activity to prevent the premature dissociation of ubiquitinated-RIP1 from TNFα-stimulated TNF-receptor I and also to inhibit the formation of TNFα-induced necrosome complex consisting of RIP1, RIP3, FADD, caspase-8 and cFLIPL. The surprising prevalence of catalytically active RIP1-dependent programmed necrosis over apoptosis despite ongoing caspase activity implicates a complex regulatory mechanism governing the decision between both cell death pathways following death receptor stimulation

Classification of stroke using neural networks in electrical impedance tomography

Electrical impedance tomography (EIT) is an emerging non-invasive medical imaging modality. It is based on feeding electrical currents into the patient, measuring the resulting voltages at the skin, and recovering the internal conductivity distribution. The mathematical task of EIT image reconstruction is a nonlinear and ill-posed inverse problem. Therefore any EIT image reconstruction method needs to be regularized, typically resulting in blurred images. One promising application is stroke-EIT, or classification of stroke into either ischemic or hemorrhagic. Ischemic stroke involves a blood clot, preventing blood flow to a part of the brain causing a low-conductivity region. Hemorrhagic stroke means bleeding in the brain causing a high-conductivity region. In both cases the symptoms are identical, so a cost-effective and portable classification device is needed. Typical EIT images are not optimal for stroke-EIT because of blurriness. This paper explores the possibilities of machine learning in improving the classification results. Two paradigms are compared: (a) learning from the EIT data, that is Dirichlet-to-Neumann maps and (b) extracting robust features from data and learning from them. The features of choice are virtual hybrid edge detection (VHED) functions (Greenleaf et al 2018 Anal. PDE 11) that have a geometric interpretation and whose computation from EIT data does not involve calculating a full image of the conductivity. We report the measures of accuracy, sensitivity and specificity of the networks trained with EIT data and VHED functions separately. Computational evidence based on simulated noisy EIT data suggests that the regularized grey-box paradigm (b) leads to significantly better classification results than the black-box paradigm (a).Peer reviewe

A Nuclear Poly(ADP-Ribose)-Dependent Signalosome Confers DNA Damage-Induced IκB Kinase Activation

Upon genotoxic stresses, cells activate I{kappa}B kinases (IKKs) and the transcription factor NF-{kappa}B to modulate apoptotic responses. The SUMO-1 ligase PIASy and the kinase ataxia talengiectasia mutated (ATM) have been implicated to SUMOylate and phosphorylate nuclear IKK{gamma} (NEMO) in a consecutive mode of action, which in turn results in activation of cytoplasmic IKK holocomplexes. However, the nuclear signals and scaffold structures that initiate IKK{gamma} recruitment and activation are unknown. Here, we show that poly(ADP-ribose)-polymerase-1 (PARP-1) is the DNA proximal regulator, which senses DNA strand breaks and, through poly(ADP-ribose) (PAR) synthesis, assembles IKK{gamma}, PIASy, and ATM in a dynamic manner. Signalosome formation involves direct protein-protein interactions and binding to ADP-ribose polymers through PAR binding motifs (PARBM). Activated PARP-1 and a PARBM in PIASy are required to trigger IKK{gamma} SUMOylation, which in turn permits IKK and NF-{kappa}B activation, as well as NF-{kappa}B-regulated resistance to apoptosis