Artificial neural networks for 3D cell shape recognition from confocal images

We present a dual-stage neural network architecture for analyzing fine shape details from microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification for diagnostic and theragnostic use.Comment: 17 pages, 8 figure

Dynamics of pearling instability in polymersomes: the role of shear membrane viscosity and spontaneous curvature

The stability of copolymer tethers is investigated theoretically. Self-assembly of diblockor triblock copolymers can lead to tubular polymersomes which are known experimentallyto undergo shape instability under thermal, chemical and tension stresses. It leads to aperiodic modulation of the radius which evolves to assembly-line pearls connected by tinytethers. We study the contributions of shear surface viscosity and spontaneous curvatureand their interplay to understand the pearling instability. The performed linear analysisof stability of this cylinder-to-pearls transition shows that such systems are unstable if themembrane tension is larger than a finite critical value contrary to the Rayleigh-Plateauinstability, an already known result or if the spontaneous curvature is in a specific rangewhich depends on membrane tension. For the case of spontaneous curvature-induced shapeinstability, two dynamical modes are identified. The first one is analog to the tension-induced instability with a marginal mode. Its wavenumber associated with the most un-stable mode decreases continuously to zero as membrane viscosity increases. The secondone has a finite range of unstable wavenumbers. The wavenumber of the most unstablemode tends redto be constant as membrane viscosity increases. In this mode, its growthrate becomes independent of the bulk viscosity in the limit of high membrane viscosity andbehaves as a pure viscous surface

Dynamics of pearling instability in polymersomes: the role of shear membrane viscosity and spontaneous curvature

International audienceThe stability of copolymer tethers is investigated theoretically. Self-assembly of diblockor triblock copolymers can lead to tubular polymersomes which are known experimentallyto undergo shape instability under thermal, chemical and tension stresses. It leads to aperiodic modulation of the radius which evolves to assembly-line pearls connected by tinytethers. We study the contributions of shear surface viscosity and spontaneous curvatureand their interplay to understand the pearling instability. The performed linear analysisof stability of this cylinder-to-pearls transition shows that such systems are unstable if themembrane tension is larger than a finite critical value contrary to the Rayleigh-Plateauinstability, an already known result or if the spontaneous curvature is in a specific rangewhich depends on membrane tension. For the case of spontaneous curvature-induced shapeinstability, two dynamical modes are identified. The first one is analog to the tension-induced instability with a marginal mode. Its wavenumber associated with the most un-stable mode decreases continuously to zero as membrane viscosity increases. The secondone has a finite range of unstable wavenumbers. The wavenumber of the most unstablemode tends redto be constant as membrane viscosity increases. In this mode, its growthrate becomes independent of the bulk viscosity in the limit of high membrane viscosity andbehaves as a pure viscous surface

Artificial neural networks for 3D cell shape recognition from confocal images

17 pages, 8 figuresWe present a dual-stage neural network architecture for analyzing fine shape details from microscopy recordings in 3D. The system, tested on red blood cells, uses training data from both healthy donors and patients with a congenital blood disease. Characteristic shape features are revealed from the spherical harmonics spectrum of each cell and are automatically processed to create a reproducible and unbiased shape recognition and classification for diagnostic and theragnostic use