Diagnosis of focal liver lesions from ultrasound using deep learning

PURPOSE: The purpose of this study was to create an algorithm that simultaneously detects and characterizes (benign vs. malignant) focal liver lesion (FLL) using deep learning. MATERIALS AND METHODS: We trained our algorithm on a dataset proposed during a data challenge organized at the 2018 Journées Francophones de Radiologie. The dataset was composed of 367 two-dimensional ultrasound images from 367 individual livers, captured at various institutions. The algorithm was guided using an attention mechanism with annotations made by a radiologist. The algorithm was then tested on a new data set from 177 patients. RESULTS: The models reached mean ROC-AUC scores of 0.935 for FLL detection and 0.916 for FLL characterization over three shuffled three-fold cross-validations performed with the training data. On the new dataset of 177 patients, our models reached a weighted mean ROC-AUC scores of 0.891 for seven different tasks. CONCLUSION: This study that uses a supervised-attention mechanism focused on FLL detection and characterization from liver ultrasound images. This method could prove to be highly relevant for medical imaging once validated on a larger independent cohort

Degradation analysis of tribologically loaded carbon nanotubes and carbon onions

Coating laser-patterned stainless-steel surfaces with carbon nanotubes (CNT) or carbon onions (CO) forms a tribological system that provides effective solid lubrication. Lubricant retention represents the fundamental mechanism of this system, as storing the particles inside the pattern prevents lubricant depletion in the contact area. In previous works, we used direct laser interference patterning to create line patterns with three different structural depths on AISI 304 stainless-steel platelets. Electrophoretic deposition subsequently coated the patterned surfaces with either CNTs or COs. Ball-on-disc friction tests were conducted to study the effect of structural depth on the solid lubricity of as-described surfaces. The results demonstrated that the shallower the textures, the lower the coefficient of friction, regardless of the applied particle type. This follow-up study examines the carbon nanoparticles’ structural degradation after friction testing on substrates patterned with different structural depths (0.24, 0.36, and 0.77 µm). Raman characterization shows severe degradation of both particle types and is used to classify their degradation state within Ferrari’s three-stage amorphization model. It was further shown that improving CNT lubricity translates into increasing particle defectivity. This is confirmed by electron microscopy, which shows decreasing crystalline domains. Compared to CNTs, COderived tribofilms show even more substantial structural degradation

Comprehensive analysis of the ErbB receptor family in pediatric nervous system tumors and rhabdomyosarcoma

Background: There is a paucity of knowledge regarding pediatric biomarkers, including the relevance of ErbB pathway aberrations in pediatric tumors. We investigated the occurrence of ErbB receptor aberrations across different pediatric malignancies, to identify patterns of ErbB dysregulation and define biomarkers suitable for patient enrichment in clinical studies. / Procedure: Tissue samples from 297 patients with nervous system tumors and rhabdomyosarcoma were analyzed for immunohistochemical expression or gene amplification of epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2). Exploratory analyses of HER3/HER4 expression, and mRNA expression of ErbB receptors/ligands (NanoString) were performed. Assay validation followed general procedures, with additional validation to address Clinical Laboratory Improvement Amendments (CLIA) requirements. / Results: In most tumor types, samples with high ErbB receptor expression were found with heterogeneous distribution. We considered increased/aberrant ErbB pathway activation when greater than or equal to two EGFR/HER2 markers were simultaneously upregulated. ErbB pathway dysregulation was identified in ∼20%–30% of samples for most tumor types (medulloblastoma/primitive neuroectodermal tumors 31.1%, high-grade glioma 27.1%, neuroblastoma 22.7%, rhabdomyosarcoma 23.1%, ependymoma 18.8%), 4.2% of diffuse intrinsic pontine gliomas, and no recurrent or refractory low-grade astrocytomas. In medulloblastoma/primitive neuroectodermal tumors and neuroblastoma, this was attributed mainly to high EGFR polysomy/HER2 amplification, whereas EGFR gene amplification was observed in some high-grade glioma samples. EGFR/HER2 overexpression was most prevalent in ependymoma. / Conclusions: Overexpression and/or amplification of EGFR/HER2 were identified as potential enrichment biomarkers for clinical trials of ErbB-targeted drugs

Microtubules as Platforms for Assaying Actin Polymerization In Vivo

The actin cytoskeleton is continuously remodeled through cycles of actin filament assembly and disassembly. Filaments are born through nucleation and shaped into supramolecular structures with various essential functions. These range from contractile and protrusive assemblies in muscle and non-muscle cells to actin filament comets propelling vesicles or pathogens through the cytosol. Although nucleation has been extensively studied using purified proteins in vitro, dissection of the process in cells is complicated by the abundance and molecular complexity of actin filament arrays. We here describe the ectopic nucleation of actin filaments on the surface of microtubules, free of endogenous actin and interfering membrane or lipid. All major mechanisms of actin filament nucleation were recapitulated, including filament assembly induced by Arp2/3 complex, formin and Spir. This novel approach allows systematic dissection of actin nucleation in the cytosol of live cells, its genetic re-engineering as well as screening for new modifiers of the process

Attribute evaluation after recovery from syntax error

SIGLEDEGerman

Invarianz der LR(k)-Eigenschaft beim Einfuegen von epsilon-Nichtterminalen

SIGLEDEGerman

Another error recovery algorithm for LR parsers

SIGLEDEGerman