Highlights d Two network models of the mouse primary visual cortex are developed and released d One uses compartmental-neuron models and the other pointneuron models d The models recapitulate observations from in vivo experimental data d Simulations identify experimentally testable predictions about cortex circuitry

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A three dimensional graphene network (3DGN)@WO3 nanowire (NW) sensor is proposed which can perform colorimetric and electrochemical sensing techniques to detect H2O2, ascorbic acid and dopamine. The 3DGN provides three functions: anchoring, separating, conducting, while the WO3 NWs maximize surface area and catalyse reactions.

Recently; one-dimensional (1D) nanostructure field-effect transistors (FETs) have attracted much attention because of their potential application in gas sensing. Micro/nanoscaled field-effect sensors combine the advantages of 1D nanostructures and the characteristic of field modulation. 1D nanostructures provide a large surface area-volume ratio; which is an outstanding advantage for gas sensors with high sensitivity and fast response. In addition; the nature of the single crystals is favorable for the studies of the response mechanism. On the other hand; one main merit of the field-effect sensors is to provide an extra gate electrode to realize the current modulation; so that the sensitivity can be dramatically enhanced by changing the conductivity when operating the sensors in the subthreshold regime. This article reviews the recent developments in the field of 1D nanostructure FET for gas detection. The sensor configuration; the performance as well as their sensing mechanism are evaluated.

Bioinspired by the morphology of dandelion pollen grains, we successfully prepared a template-free solution-based method for the large-scale preparation of three-dimensional (3D) hierarchical CoFe2O4 porous microspheres. Besides, on the basis of the effect of the reaction time on the morphology evolution of the precursor, we proposed an in situ dissolution-recrystallization growth mechanism with morphology and phase change to understand the formation of dandelion pollenlike microspheres. Doxorubicin hydrochloride, an anticancer drug, is efficiently loaded into the CoFe2O4 microspheres. The magnetic nanoparticles as field-controlled drug carriers offer a unique power of magnetic guidance and field-triggered drug-release behavior. Therefore, 3D hierarchical CoFe2O4 porous microspheres demonstrate the great potential for drug encapsulation and controlled drug-release applications.

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability or formation of interactions; these may explain the effect of mutations and in some cases even open a path for targeted drug development. To accelerate progress in the integration of these data types, we held a two-day Gene Variation to 3D (GVto3D) workshop to report on the latest advances and to discuss unmet needs. The overarching goal of the workshop was to address the question: what can be done together as a community to advance the integration of genetic variants and 3D protein structures that could not be done by a single investigator or laboratory? Here we describe the workshop outcomes, review the state of the field, and propose the development of a framework with which to promote progress in this arena. The framework will include a set of standard formats, common ontologies, a common application programming interface to enable interoperation of the resources, and a Tool Registry to make it easy to find and apply the tools to specific analysis problems. Interoperability will enable integration of diverse data sources and tools and collaborative development of variant effect prediction methods.Electronic supplementary materialThe online version of this article (doi:10.1186/s13073-017-0509-y) contains supplementary material, which is available to authorized users.

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