NNeurite: artificial neuronal networks for the unsupervised extraction of axonal and dendritic time-lapse signals

Fluorescence microscopy of Ca2+ transients in small neurites of the behaving mouse provides an unprecedented view of the micrometer-scale mechanisms supporting neuronal communication and computation, and therefore opens the way to understanding their role in cognition. However, the exploitation of this growing and precious experimental data is impeded by the scarcity of methods dedicated to the analysis of images of neurites activity in vivo. We present NNeurite, a set of mathematical and computational techniques specialized for the analysis of time-lapse microscopy images of neurite activity in small behaving animals. Starting from noisy and unstable microscopy images containing an unknown number of small neurites, NNeurite simultaneously aligns images, denoises signals and extracts the location and the temporal activity of the sources of Ca2+ transients. At the core of NNeurite is a novel artificial neuronal network(NN) which we have specifically designed to solve the non-negative matrix factorization (NMF)problem modeling source separation in fluorescence microscopy images. For the first time, we have embedded non-rigid image alignment in the NMF optimization procedure, hence allowing to stabilize images based on the transient and weak neurite signals. NNeurite processing is free of any human intervention as NN training is unsupervised and the unknown number of Ca2+ sources is automatically obtained by the NN-based computation of a low-dimensional representation of time-lapse images. Importantly, the spatial shapes of the sources of Ca2+ fluorescence are not constrained in NNeurite, which allowed to automatically extract the micrometer-scale details of dendritic and axonal branches, such dendritic spines and synaptic boutons, in the cortex of behaving mice. We provide NNeurite as a free and open-source library to support the efforts of the community in advancing in vivo microscopy of neurite activity.

Effects of Te- and Fe-doping on the superconducting properties in FeySe1−xTex thin films

High quality FeySe1−xTex epitaxial thin films have been fabricated on TiO2-buffered SrTiO3 substrates by pulsed laser deposition technology. There is a significant composition deviation between the nominal target and the thin film. Te doping can affect the Se/Te ratio and Fe content in chemical composition. The superconducting transition temperature Tc is closely related to the chemical composition. Fe vacancies are beneficial for the FeySe1−xTex films to exhibit the higher Tc. A 3D phase diagram is given that the optimize range is x = 0.13–0.15 and y = 0.73–0.78 for FeySe1−xTex films. The anisotropic, effective pining energy, and critical current density for the Fe0.72Se0.94Te0.06, Fe0.76Se0.87Te0.13 and Fe0.91Se0.77Te0.23 films were studied in detail. The scanning transmission electron microscopy images display a regular atomic arrangement at the interfacial structure.

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

We present a new, carefully designed and well-annotated dataset of images and image-based profiles of cells that have been treated with chemical compounds and genetic perturbations. Each gene that is perturbed is a known target of at least two compounds in the dataset. The dataset can thus serve as a benchmark to evaluate methods for predicting similarities between compounds and between genes and compounds, measuring the effect size of a perturbation, and more generally, learning effective representations for measuring cellular state from microscopy images. Advancements in these applications can accelerate the development of new medicines.

Morphology, composition and structure of the fibers of a Chimu culture textile

In this work we studied the microfibers of a textile (T-shirt) of the Chimú culture. This culture developed on the northern coast of Peru. To determine the raw material and structural quality of the microfibers, the results of the Chimú textile were compared with the corresponding results for the microfibers of cotton from the northern coast of Peru (native cotton). Scanning electron microscopy images revealed that the Chimú textile yarns are composed of a set of interwoven microfibers. Energy dispersive X-ray spectroscopy and pulsed laser-induced plasma spectroscopy techniques allowed the identification of characteristic cellulose atoms in the microfibers of Chimú textile and native cotton. Only for the Chimú textile, these spectroscopic techniques allowed the identification of atoms corresponding to natural dyes and powder residues. Attenuated total reflection Fourier transform infrared spectroscopy identified the same molecular bonds for the microfibers of Chimú textile and native cotton. For the microfibers of Chimú textile and native cotton, the X-ray diffractograms showed peaks characteristic of the cellulose Iβ polymorphism of of monoclinic P21 structure. The raw material of the Chimú textile is cotton and the microfibers of this material show significant structural stability.