We present a method for microtubule tracking in electron microscopy volumes. Our method first identifies a sparse set of voxels that likely belong to microtubules. Similar to prior work, we then enumerate potential edges between these voxels, which we represent in a candidate graph. Tracks of microtubules are found by selecting nodes and edges in the candidate graph by solving a constrained optimization problem incorporating biological priors on microtubule structure. For this, we present a novel integer linear programming formulation, which results in speed-ups of three orders of magnitude and an increase of 53% in accuracy compared to prior art (evaluated on three 1 . 2 × 4 × 4µm volumes of Drosophila neural tissue). We also propose a scheme to solve the optimization problem in a block-wise fashion, which allows distributed tracking and is necessary to process very large electron microscopy volumes. Finally, we release a benchmark dataset for microtubule tracking, here used for training, testing and validation, consisting of eight 30 x 1000 x 1000 voxel blocks (1 . 2 × 4 × 4µm) of densely annotated microtubules in the CREMI data set (https://github.com/nilsec/micron).

We studied two aspects of vimentin intermediate filament dynamics-transport of filaments and subunit exchange. We observed transport of long filaments in the periphery of cells using live-cell structured illumination microscopy. We studied filament transport elsewhere in cells using a photoconvertible-vimentin probe and total internal reflection microscopy. We found that filaments were rapidly transported along linear tracks in both anterograde and retrograde directions. Filament transport was microtubule dependent but independent of microtubule polymerization and/or an interaction with the plus end-binding protein APC. We also studied subunit exchange in filaments by long-term imaging after photoconversion. We found that converted vimentin remained in small clusters along the length of filaments rather than redistributing uniformly throughout the network, even in cells that divided after photoconversion. These data show that vimentin filaments do not depolymerize into individual subunits; they recompose by severing and reannealing. Together these results show that vimentin filaments are very dynamic and that their transport is required for network maintenance.

Using imidazole as promotion agent, primary, secondary and phenolic alcohol compounds were esterified with aliphatic and aromatic carboxylic acid anhydrides. Heating a ternary mixture of alcohol, anhydride and imidazole in an unmodified microwave oven produced esters in low to high yields, depending on the steric bulk of the alcohol.

Tethered midbody remnants dancing across apical microvilli, encountering the centrosome, and beckoning forth a cilium-who would have guessed this is how polarized epithelial cells coordinate the end of mitosis and the beginning of ciliogenesis? New evidence from Bernabé-Rubio et al. (2016. J. Cell Biol http://dx.doi.org/10.1083/jcb.201601020) supports this emerging model.

Although nervous system sexual dimorphisms are known in many species, relatively little is understood about the molecular mechanisms generating these dimorphisms. Recent findings in Drosophila provide the tools for dissecting how neurogenesis and neuronal differentiation are modulated by the Drosophila sex-determination regulatory genes to produce nervous system sexual dimorphisms. Here we report studies aimed at illuminating the basis of the sexual dimorphic axonal projection patterns of foreleg gustatory receptor neurons (GRNs): only in males do GRN axons project across the midline of the ventral nerve cord. We show that the sex determination genes fruitless (fru) and doublesex (dsx) both contribute to establishing this sexual dimorphism. Male-specific Fru (Fru(M)) acts in foreleg GRNs to promote midline crossing by their axons, whereas midline crossing is repressed in females by female-specific Dsx (Dsx(F)). In addition, midline crossing by these neurons might be promoted in males by male-specific Dsx (Dsx(M)). Finally, we (1) demonstrate that the roundabout (robo) paralogs also regulate midline crossing by these neurons, and (2) provide evidence that Fru(M) exerts its effect on midline crossing by directly or indirectly regulating Robo signaling.

Since the demonstration that the sequence of a protein encodes its structure, the prediction of structure from sequence remains an outstanding problem that impacts numerous scientific disciplines, including many genome projects. By iteratively fixing secondary structure assignments of residues during Monte Carlo simulations of folding, our coarse-grained model without information concerning homology or explicit side chains can outperform current homology-based secondary structure prediction methods for many proteins. The computationally rapid algorithm using only single (phi,psi) dihedral angle moves also generates tertiary structures of accuracy comparable with existing all-atom methods for many small proteins, particularly those with low homology. Hence, given appropriate search strategies and scoring functions, reduced representations can be used for accurately predicting secondary structure and providing 3D structures, thereby increasing the size of proteins approachable by homology-free methods and the accuracy of template methods that depend on a high-quality input secondary structure.

The use of chronically implanted electrodes for neural recordings in small, freely behaving animals poses several unique technical challenges. Because of the need for an extremely lightweight apparatus, chronic recording technology has been limited to manually operated microdrives, despite the advantage of motorized manipulators for positioning electrodes. Here we describe a motorized, miniature chronically implantable microdrive for independently positioning three electrodes in the brain. The electrodes are controlled remotely, avoiding the need to disturb the animal during electrode positioning. The microdrive is approximately 6 mm in diameter, 17 mm high and weighs only 1.5 g, including the headstage preamplifier. Use of the motorized microdrive has produced a ten-fold increase in our data yield compared to those experiments done using a manually operated drive. In addition, we are able to record from multiple single neurons in the behaving animal with signal quality comparable to that seen in a head-fixed anesthetized animal. We also describe a motorized commutator that actively tracks animal rotation based on a measurement of torque in the tether.

The ability to image neurons anywhere in the mammalian brain is a major goal of optical microscopy. Here we describe a minimally invasive microendoscopy system for studying the morphology and function of neurons at depth. Utilizing a guide cannula with an ultrathin wall, we demonstrated in vivo two-photon fluorescence imaging of deeply buried nuclei such as the striatum (2.5 mm depth), substantia nigra (4.4 mm depth) and lateral hypothalamus (5.0 mm depth) in mouse brain. We reported, for the first time, the observation of neuronal activity with subcellular resolution in the lateral hypothalamus and substantia nigra of head-fixed awake mice.

The ability to automatically segment an image into distinct regions is a critical aspect in many visual processing applications. Because inaccuracies often exist in automatic segmentation, manual segmentation is necessary in some application domains to correct mistakes, such as required in the reconstruction of neuronal processes from microscopic images. The goal of the automated segmentation tool is traditionally to produce the highest-quality segmentation, where quality is measured by the similarity to actual ground truth, so as to minimize the volume of manual correction necessary. Manual correction is generally orders-of-magnitude more time consuming than automated segmentation, often making handling large images intractable. Therefore, we propose a more relevant goal: minimizing the turn-around time of automated/manual segmentation while attaining a level of similarity with ground truth. It is not always necessary to inspect every aspect of an image to generate a useful segmentation. As such, we propose a strategy to guide manual segmentation to the most uncertain parts of segmentation. Our contributions include 1) a probabilistic measure that evaluates segmentation without ground truth and 2) a methodology that leverages these probabilistic measures to significantly reduce manual correction while maintaining segmentation quality.

How to selecting a small subset out of the thousands of genes in microarray data is important for accurate classification of phenotypes. Widely used methods typically rank genes according to their differential expressions among phenotypes and pick the top-ranked genes. We observe that feature sets so obtained have certain redundancy and study methods to minimize it. We propose a minimum redundancy - maximum relevance (MRMR) feature selection framework. Genes selected via MRMR provide a more balanced coverage of the space and capture broader characteristics of phenotypes. They lead to significantly improved class predictions in extensive experiments on 6 gene expression data sets: NCI, Lymphoma, Lung, Child Leukemia, Leukemia, and Colon. Improvements are observed consistently among 4 classification methods: Naive Bayes, Linear discriminant analysis, Logistic regression, and Support vector machines. SUPPLIMENTARY: The top 60 MRMR genes for each of the datasets are listed in http://crd.lbl.gov/ cding/MRMR/. More information related to MRMR methods can be found at http://www.hpeng.net/.