Applying Deep Learning To Identify Imaging Biomarkers To Predict Cardiac Outcomes In Cancer Patients

Cancer patients are a unique population with increased mortality from cardiovascular disease, however only half of high-risk patients are medically optimized. Physicians ascertain cardiovascular risk from several risk predictors using demographic information, family history, and imaging data. The Agatston score, a measure of total calcium burden in coronary arteries on CT scans, is the current best predictor for major adverse cardiac events (MACE). Yet, the score is limited as it does not provide information on atherosclerotic plaque characteristics or distribution. In this study, we use deep learning techniques to develop an imaging-based biomarker that can robustly predict MACE in lung cancer patients. We selected participants with screen-detected lung cancer from the National Lung Screening Trial (NLST) and used cardiovascular mortality as our primary outcome. We applied automated segmentation algorithms to low-dose chest CT scans from NLST participants to segment cardiac substructures. Following segmentation, we extracted radiomic features from selected cardiac structures. We then used this dataset to train a regression model to predict cardiovascular death. We used a pre-trained nnU-Net model to successfully segment large cardiac structures on CT scans. These automated large cardiac structures had features that were predictive of MACE. We then successfully extract radiomic features from our areas of interest and use this high-dimensional dataset to train a regression model to predict MACE. We demonstrated that automated segmentation algorithms can result in low-cost non-invasive predictive biomarkers for MACE. We were able to demonstrate that radiomic feature extraction from segmented substructures can be used to develop a high-dimensional biomarker. We hope that such a scoring system can help physicians adequately determine cardiovascular risk and intervene, resulting in better patient outcomes

Human iPSC-Derived Cerebral Organoids Model Cellular Features of Lissencephaly and Reveal Prolonged Mitosis of Outer Radial Glia

Classical lissencephaly is a genetic neurological disorder associated with mental retardation and intractable epilepsy, and Miller-Dieker syndrome (MDS) is the most severe form of the disease. In this study, to investigate the effects of MDS on human progenitor subtypes that control neuronal output and influence brain topology, we analyzed cerebral organoids derived from control and MDS-induced pluripotent stem cells (iPSCs) using time-lapse imaging, immunostaining, and single-cell RNA sequencing. We saw a cell migration defect that was rescued when we corrected the MDS causative chromosomal deletion and severe apoptosis of the founder neuroepithelial stem cells, accompanied by increased horizontal cell divisions. We also identified a mitotic defect in outer radial glia, a progenitor subtype that is largely absent from lissencephalic rodents but critical for human neocortical expansion. Our study, therefore, deepens our understanding of MDS cellular pathogenesis and highlights the broad utility of cerebral organoids for modeling human neurodevelopmental disorders

Effects of N-terminal acetylation on the aggregation of disease-related α-synuclein variants

Mutations in the SCNA gene, which encodes the protein α-synuclein, have been linked with early onset Parkinson’s disease. The nature of this association, however, is still poorly understood. To investigate this problem, we started from the observation that α-synuclein is constitutively N-terminally acetylated, a post-translational modification that alters the charge and structure of α-synuclein molecules and affects their interaction with lipid membranes and their aggregation process. We thus studied five N-terminal acetylated familial variants (A30P, E46K, H50Q, G51D and A53T) of α-synuclein through a wide range of biophysical assays to probe the microscopic steps in their aggregation process and the structures of the resulting aggregates. Our results reveal a great complexity in the combined effects of the disease-related mutations with N-terminal acetylation on the aggregation of α-synuclein, which underscores the high sensitivity to chemical modifications in the behaviour of this protein

Human iPSC-Derived Cerebral Organoids Model Cellular Features of Lissencephaly and Reveal Prolonged Mitosis of Outer Radial Glia

Classical lissencephaly is a genetic neurological disorder associated with mental retardation and intractable epilepsy, and Miller-Dieker syndrome (MDS) is the most severe form of the disease. In this study, to investigate the effects of MDS on human progenitor subtypes that control neuronal output and influence brain topology, we analyzed cerebral organoids derived from control and MDS-induced pluripotent stem cells (iPSCs) using time-lapse imaging, immunostaining, and single-cell RNA sequencing. We saw a cell migration defect that was rescued when we corrected the MDS causative chromosomal deletion and severe apoptosis of the founder neuroepithelial stem cells, accompanied by increased horizontal cell divisions. We also identified a mitotic defect in outer radial glia, a progenitor subtype that is largely absent from lissencephalic rodents but critical for human neocortical expansion. Our study, therefore, deepens our understanding of MDS cellular pathogenesis and highlights the broad utility of cerebral organoids for modeling human neurodevelopmental disorders

Additional file 2: of Aldehyde dehydrogenase 2 activation and coevolution of its εPKC-mediated phosphorylation sites

The table shows the 10 species with εPKC (left panel), the 10 species without εPKC (right panel) and their amino acid residues at the three human ALDH2 phosphorylation sites, T185, S279 and T412. (PDF 313 kb

Additional file 1: of Aldehyde dehydrogenase 2 activation and coevolution of its εPKC-mediated phosphorylation sites

Phylogenetic Tree of the 20 species for ALDH2 and εPKC coevolution comparison. Species in green letters are those with a homology of εPKC. Species in red letters are those without a homology of εPKC. (PDF 73 kb

Deciphering the Structural Basis of Eukaryotic Protein Kinase Regulation

<div><p>Eukaryotic protein kinases (EPKs) regulate numerous signaling processes by phosphorylating targeted substrates through the highly conserved catalytic domain. Our previous computational studies proposed a model stating that a properly assembled nonlinear motif termed the Regulatory (R) spine is essential for catalytic activity of EPKs. Here we define the required intramolecular interactions and biochemical properties of the R-spine and the newly identified “Shell” that surrounds the R-spine using site-directed mutagenesis and various <i>in vitro</i> phosphoryl transfer assays using cyclic AMP-dependent protein kinase as a representative of the entire kinome. Analysis of the 172 available Apo EPK structures in the protein data bank (PDB) revealed four unique structural conformations of the R-spine that correspond with catalytic inactivation of various EPKs. Elucidating the molecular entities required for the catalytic activation of EPKs and the identification of these inactive conformations opens new avenues for the design of efficient therapeutic EPK inhibitors.</p></div

Understanding the properties required for a catalytically active R-spine.

<p>PKA mutants were expressed in <i>E. coli</i> and the catalytic activity was analyzed using Western blot assay to determine the effect of (A) aromatic and aliphatic properties of the R-spine and (B) specific interactions of RS1. A qualitative Western blot assay (C) and quantitative radioactive phosphoryl transfer assay (D) were carried out for PKA mutants containing hydrophilic R-spine mutations. A qualitative Western blot assay (E) and quantitative radioactive phosphoryl transfer assay (F) were carried out for PKA mutants containing removal of side chain atoms of the R-spine residues. (G) Cartoon summary of the R-spine mutants (orange circle represents introducing a hydrophobic residue, red circle represents introducing a hydrophilic residue, and white circle represents removal of side chain atoms) along with a summary of their catalytic activity (green label indicates active and red label indicates inactive).</p

The R-spine and Shell configuration in the inactive state of EPKs.

<p>The four inactive conformations of the EPKs are shown with representative structures as well as cartoons in order to illustrate the configurations of the R-spine and Shell. The structures are inactive I (AKT; PDB ID: 1GZK), representing the DFG-out configuration; inactive II (Src; PDB ID: 1FMK), representing the C-helix out configuration; inactive III (AMPK; PDB ID: 3H4J), representing the HRD-out configuration; inactive IV (P38 MAPK; PDB ID: 1WFC), representing the twisted lobe configuration. The active EPK conformation (PKA; PDB ID: 1ATP) is shown for comparison (center).</p

Summary of the alignment of the more than 13,000 EPK sequences.

<p>Percentile of aromatic, aliphatic, hydrophobic (bold/italics), and representative amino acids for each R-spine and Shell residues from alignment of more than 13,000 EPK protein sequences.</p