Aberrations and random scattering severely limit optical imaging in deep tissue. Adaptive optics can in principle drastically extend the penetration depth and improve the image quality. However, for random scattering media a large number of spatial modes need to be measured and controlled to restore a diffraction limited focus. Here, we present a parallel wavefront optimization method using backscattered light as a feedback. Spatial confinement of the feedback signal is realized with a confocal pinhole and coherence gating. We show in simulations and experiments that this approach enables focusing deep into tissue over up to six mean scattering path lengths. Experimentally the technique was tested on tissue phantoms and fixed brain slices.

Electrical coupling in circuits can produce non-intuitive circuit dynamics, as seen in both experimental work from the crustacean stomatogastric ganglion and in computational models inspired by the connectivity in this preparation. Ambiguities in interpreting the results of electrophysiological recordings can arise if sets of pre- or postsynaptic neurons are electrically coupled, or if the electrical coupling exhibits some specificity (e.g. rectifying, or voltage-dependent). Even in small circuits, electrical coupling can produce parallel pathways that can allow information to travel by monosynaptic and/or polysynaptic pathways. Consequently, similar changes in circuit dynamics can arise from entirely different underlying mechanisms. When neurons are coupled both chemically and electrically, modifying the relative strengths of the two interactions provides a mechanism for flexibility in circuit outputs. This, together with neuromodulation of gap junctions and coupled neurons is important both in developing and adult circuits. This article is protected by copyright. All rights reserved.

Electrical coupling in circuits can produce non-intuitive circuit dynamics, as seen in both experimental work from the crustacean stomatogastric ganglion and in computational models inspired by the connectivity in this preparation. Ambiguities in interpreting the results of electrophysiological recordings can arise if sets of pre- or postsynaptic neurons are electrically coupled, or if the electrical coupling exhibits some specificity (e.g. rectifying, or voltage-dependent). Even in small circuits, electrical coupling can produce parallel pathways that can allow information to travel by monosynaptic and/or polysynaptic pathways. Consequently, similar changes in circuit dynamics can arise from entirely different underlying mechanisms. When neurons are coupled both chemically and electrically, modifying the relative strengths of the two interactions provides a mechanism for flexibility in circuit outputs. This, together with neuromodulation of gap junctions and coupled neurons is important both in developing and adult circuits. This article is protected by copyright. All rights reserved.

Developmental genes can have complex cis-regulatory regions with multiple enhancers. Early work revealed remarkable modularity of enhancers, whereby distinct DNA regions drive gene expression in defined spatiotemporal domains. Nevertheless, a few reports have shown that enhancers function in multiple developmental stages, implying that enhancers can be pleiotropic. Here, we have studied the activity of the enhancers of the shavenbaby gene throughout D. melanogaster development. We found that all seven shavenbaby enhancers drive expression in multiple tissues and developmental stages. We explored how enhancer pleiotropy is encoded in two of these enhancers. In one enhancer, the same transcription factor binding sites contribute to embryonic and pupal expression, revealing site pleiotropy, whereas for a second enhancer, these roles are encoded by distinct sites. Enhancer pleiotropy may be a common feature of cis-regulatory regions of developmental genes, and site pleiotropy may constrain enhancer evolution in some cases.

Neural computations are implemented by activity in spatially distributed neural circuits. Cellular imaging fills a unique niche in linking activity of specific types of neurons to behavior, over spatial scales spanning single neurons to entire brain regions, and temporal scales from milliseconds to months. Imaging may soon make it possible to track activity of all neurons in a brain region, such as a cortical column. We review recent methodological advances that facilitate optical imaging of neuronal populations in vivo, with an emphasis on calcium imaging using protein indicators in mice. We point out areas that are particularly ripe for future developments.

Determining how neurons transform synaptic input and encode information in action potential (AP) firing output is required for understanding dendritic integration, neural transforms and encoding. Limitations in the speed of imaging 3D volumes of brain encompassing complex dendritic arbors using conventional galvanometer mirror-based laser-scanning microscopy has hampered fully capturing fluorescent sensors of activity throughout an individual neuron's entire complement of synaptic inputs and somatic APs. To address this problem, we have developed a two-photon microscope that achieves high-speed scanning by employing inertia-free acousto-optic deflectors (AODs) for laser beam positioning, enabling random-access sampling of hundreds to thousands of points-of-interest restricted to a predetermined neuronal structure, avoiding wasted scanning of surrounding extracellular tissue. This system is capable of comprehensive imaging of the activity of single neurons within the intact and awake vertebrate brain. Here, we demonstrate imaging of tectal neurons within the brains of albino tadpoles labeled using single-cell electroporation for expression of a red space-filling fluorophore to determine dendritic arbor morphology, and either the calcium sensor jGCaMP7s or the glutamate sensor iGluSnFR as indicators of neural activity. Using discrete, point-of-interest scanning we achieve sampling rates of 3 Hz for saturation sampling of entire arbors at 2 μm resolution, 6 Hz for sequentially sampling 3 volumes encompassing the dendritic arbor and soma, and 200-250 Hz for scanning individual planes through the dendritic arbor. This system allows investigations of sensory-evoked information input-output relationships of neurons within the intact and awake brain.

Aphids exhibit unique attributes, such as polyphenisms and specialized cells to house endosymbionts, that make them an interesting system for studies at the interface of ecology, evolution and development. Here we present a comprehensive characterization of the developmental genes in the pea aphid, Acyrthosiphon pisum, and compare our results to other sequenced insects. We investigated genes involved in fundamental developmental processes such as establishment of the body plan and organogenesis, focusing on transcription factors and components of signalling pathways. We found that most developmental genes were well conserved in the pea aphid, although many lineage-specific gene duplications and gene losses have occurred in several gene families. In particular, genetic components of transforming growth factor beta (TGFbeta) Wnt, JAK/STAT (Janus kinase/signal transducer and activator of transcription) and EGF (Epidermal Growth Factor) pathways appear to have been significantly modified in the pea aphid.

Inner ear cochlear spiral ganglion neurons (SGNs) transmit auditory information to the brainstem. Recent single cell RNA-Seq studies have revealed heterogeneities within SGNs. Nonetheless, much remains unknown about the transcriptome of SGNs, especially which genes are specifically expressed in SGNs. To address these questions we needed a deeper and broader gene coverage than that in previous studies. We performed bulk RNA-Seq on mouse SGNs at five ages, and on two reference cell types (hair cells and glia). Their transcriptome comparison identified genes previously unknown to be specifically expressed in SGNs. To validate our dataset and provide useful genetic tools for this research field, we generated two knockin mouse strains: and . Our comprehensive analysis confirmed the SGN-selective expression of the candidate genes, testifying to the quality of our transcriptome data. These two mouse strains can be used to temporally label SGNs or to sort them.

We present a compressed domain scheme that is able to recognize and localize actions in real-time. The recognition problem is posed as performing a video query on a test video sequence. Our method is based on computing motion similarity using compressed domain features which can be extracted with low complexity. We introduce a novel motion correlation measure that takes into account differences in motion magnitudes. Our method is appearance invariant, requires no prior segmentation, alignment or stabilization, and is able to localize actions in both space and time. We evaluated our method on a large action video database consisting of 6 actions performed by 25 people under 3 different scenarios. Our classification results compare favorably with existing methods at only a fraction of their computational cost.

Recent advances in computation-based protein engineering offer opportunities to introduce or modify the biophysical characteristics of proteins at will. The power of computational design comes from the ability to surpass the combinatorial and physical limitations inherent to laboratory-based high-throughput or trial-and-error methods. As a result, modifications that require significant changes to the amino acid sequence of a protein are now accessible to the protein engineering community. Hydrophobic cores of proteins have been repacked to increase their thermostability. Binding sites in proteins have been modified to increase affinity or alter specificity for proteins, peptides, and small molecules. Enzymes have been designed de novo. Non-natural protein folds have been created. For the most part, these achievements have been applied to proteins that make good model systems in academic settings. How can these computational methods be applied to therapeutically relevant proteins? This review will focus on the ground-breaking achievements of computation-based protein engineering and on recent applications of rational design to improve therapeutic proteins. - See more at: http://www.eurekaselect.com/90585/article/computation-based-design-and-engineering-protein-and-antibody-therapeutics#sthash.kSt3UaNE.dpuf