Images can be segmented by first using a classifier to predict an affinity graph that reflects the degree to which image pixels must be grouped together and then partitioning the graph to yield a segmentation. Machine learning has been applied to the affinity classifier to produce affinity graphs that are good in the sense of minimizing edge misclassification rates. However, this error measure is only indirectly related to the quality of segmentations produced by ultimately partitioning the affinity graph. We present the first machine learning algorithm for training a classifier to produce affinity graphs that are good in the sense of producing segmentations that directly minimize the Rand index, a well known segmentation performance measure. The Rand index measures segmentation performance by quantifying the classification of the connectivity of image pixel pairs after segmentation. By using the simple graph partitioning algorithm of finding the connected components of the thresholded affinity graph, we are able to train an affinity classifier to directly minimize the Rand index of segmentations resulting from the graph partitioning. Our learning algorithm corresponds to the learning of maximin affinities between image pixel pairs, which are predictive of the pixel-pair connectivity.

The shapes of dendritic arbors are fascinating and important, yet the principles underlying these complex and diverse structures remain unclear. Here, we analyzed basal dendritic arbors of 2,171 pyramidal neurons sampled from mammalian brains and discovered 3 statistical properties: the dendritic arbor size scales with the total dendritic length, the spatial correlation of dendritic branches within an arbor has a universal functional form, and small parts of an arbor are self-similar. We proposed that these properties result from maximizing the repertoire of possible connectivity patterns between dendrites and surrounding axons while keeping the cost of dendrites low. We solved this optimization problem by drawing an analogy with maximization of the entropy for a given energy in statistical physics. The solution is consistent with the above observations and predicts scaling relations that can be tested experimentally. In addition, our theory explains why dendritic branches of pyramidal cells are distributed more sparsely than those of Purkinje cells. Our results represent a step toward a unifying view of the relationship between neuronal morphology and function.

Command-like descending neurons can induce many behaviors, such as backward locomotion, escape, feeding, courtship, egg-laying, or grooming (we define 'command-like neuron' as a neuron whose activation elicits or 'commands' a specific behavior). In most animals it remains unknown how neural circuits switch between antagonistic behaviors: via top-down activation/inhibition of antagonistic circuits or via reciprocal inhibition between antagonistic circuits. Here we use genetic screens, intersectional genetics, circuit reconstruction by electron microscopy, and functional optogenetics to identify a bilateral pair of larval 'mooncrawler descending neurons' (MDNs) with command-like ability to coordinately induce backward locomotion and block forward locomotion; the former by stimulating a backward-active premotor neuron, and the latter by disynaptic inhibition of a forward-specific premotor neuron. In contrast, direct monosynaptic reciprocal inhibition between forward and backward circuits was not observed. Thus, MDNs coordinate a transition between antagonistic larval locomotor behaviors. Interestingly, larval MDNs persist into adulthood, where they can trigger backward walking. Thus, MDNs induce backward locomotion in both limbless and limbed animals.

Mean-Field theory is extended to recurrent networks of spiking neurons endowed with short-term depression (STD) of synaptic transmission. The extension involves the use of the distribution of interspike intervals of an integrate-and-fire neuron receiving a Gaussian current, with a given mean and variance, in input. This, in turn, is used to obtain an accurate estimate of the resulting postsynaptic current in presence of STD. The stationary states of the network are obtained requiring self-consistency for the currents-those driving the emission processes and those generated by the emitted spikes. The model network stores in the distribution of two-state efficacies of excitatory-to-excitatory synapses, a randomly composed set of external stimuli. The resulting synaptic structure allows the network to exhibit selective persistent activity for each stimulus in the set. Theory predicts the onset of selective persistent, or working memory (WM) activity upon varying the constitutive parameters (e.g. potentiated/depressed long-term efficacy ratio, parameters associated with STD), and provides the average emission rates in the various steady states. Theoretical estimates are in remarkably good agreement with data "recorded" in computer simulations of the microscopic model.

We use super-resolution interferometric photoactivation and localization microscopy (iPALM) and a constrained photoactivatable fluorescent protein integrin fusion to measure the displacement of the head of integrin lymphocyte function-associated 1 (LFA-1) resulting from integrin conformational change on the cell surface. We demonstrate that the distance of the LFA-1 head increases substantially between basal and ligand-engaged conformations, which can only be explained at the molecular level by integrin extension. We further demonstrate that one class of integrin antagonist maintains the bent conformation, while another antagonist class induces extension. Our molecular scale measurements on cell-surface LFA-1 are in excellent agreement with distances derived from crystallographic and electron microscopy structures of bent and extended integrins. Our distance measurements are also in excellent agreement with a previous model of LFA-1 bound to ICAM-1 derived from the orientation of LFA-1 on the cell surface measured using fluorescence polarization microscopy.

Among the proteins required for lipid metabolism in Mycobacterium tuberculosis are a significant number of uncharacterized serine hydrolases, especially lipases and esterases. Using a streamlined synthetic method, a library of immolative fluorogenic ester substrates was expanded to better represent the natural lipidomic diversity of Mycobacterium. This expanded fluorogenic library was then used to rapidly characterize the global structure activity relationship (SAR) of mycobacterial serine hydrolases in M. smegmatis under different growth conditions. Confirmation of fluorogenic substrate activation by mycobacterial serine hydrolases was performed using nonspecific serine hydrolase inhibitors and reinforced the biological significance of the SAR. The hydrolases responsible for the global SAR were then assigned using gel-resolved activity measurements, and these assignments were used to rapidly identify the relative substrate specificity of previously uncharacterized mycobacterial hydrolases. These measurements provide a global SAR of mycobacterial hydrolase activity, a picture of cycling hydrolase activity, and a detailed substrate specificity profile for previously uncharacterized hydrolases.

Biological specimens suffer radiation damage when imaged in an electron microscope, ultimately limiting the attainable resolution. At a given resolution, an optimal exposure can be defined that maximizes the signal-to-noise ratio in the image. Using a 2.6 Å resolution single particle cryo-EM reconstruction of rotavirus VP6, determined from movies recorded with a total exposure of 100 electrons/Å(2), we obtained accurate measurements of optimal exposure values over a wide range of resolutions. At low and intermediate resolutions our measured values are considerably higher than obtained previously for crystalline specimens, indicating that both images and movies should be collected with higher exposures than are generally used. We demonstrate a method of using our optimal exposure values to filter movie frames, yielding images with improved contrast that lead to higher resolution reconstructions. This 'high-exposure' technique should benefit cryo-EM work on all types of samples, especially those of relatively low molecular mass.

Cells rely on a diverse array of engulfment processes to sense, exploit, and adapt to their environments. Among these, macropinocytosis enables indiscriminate and rapid uptake of large volumes of fluid and membrane, rendering it a highly versatile engulfment strategy. Much of the molecular machinery required for macropinocytosis has been well established, yet how this process is regulated in the context of organs and organisms remains poorly understood. Here, we report the discovery of extensive macropinocytosis in the outer epithelium of the cnidarian . Exploiting 's relatively simple body plan, we developed approaches to visualize macropinocytosis over extended periods of time, revealing constitutive engulfment across the entire body axis. We show that the direct application of planar stretch leads to calcium influx and the inhibition of macropinocytosis. Finally, we establish a role for stretch-activated channels in inhibiting this process. Together, our approaches provide a platform for the mechanistic dissection of constitutive macropinocytosis in physiological contexts and highlight a potential role for macropinocytosis in responding to cell surface tension. [Media: see text] [Media: see text] [Media: see text] [Media: see text].

Although Hedgehog (Hh) signaling is essential for morphogenesis of the Drosophila eye, its exact link to the network of tissue-specific genes that regulate retinal determination has remained elusive. In this report, we demonstrate that the retinal determination gene eyes absent (eya) is the crucial link between the Hedgehog signaling pathway and photoreceptor differentiation. Specifically, we show that the mechanism by which Hh signaling controls initiation of photoreceptor differentiation is to alleviate repression of eya and decapentaplegic (dpp) expression by the zinc-finger transcription factor Cubitus interruptus (Ci(rep)). Furthermore, our results suggest that stabilized, full length Ci (Ci(act)) plays little or no role in Drosophila eye development. Moreover, while the effects of Hh are primarily concentration dependent in other tissues, hh signaling in the eye acts as a binary switch to initiate retinal morphogenesis by inducing expression of the tissue-specific factor Eya.

Ligand-gated ion channels involved in the modulation of synaptic strength are the AMPA, kainate, and NMDA glutamate receptors. Small molecules that potentiate AMPA receptor currents relieve cognitive deficits caused by neurodegenerative diseases such as Alzheimer’s disease and show promise in the treatment of depression. Previously, there has been limited understanding of the molecular mechanism of action for AMPA receptor potentiators. Here we present cocrystal structures of the glutamate receptor GluR2 S1S2 ligand-binding domain in complex with aniracetam [1-(4-methoxybenzoyl)-2-pyrrolidinone] or CX614 (pyrrolidino-1,3-oxazino benzo-1,4-dioxan-10-one), two AMPA receptor potentiators that preferentially slow AMPA receptor deactivation. Both potentiators bind within the dimer interface of the nondesensitized receptor at a common site located on the twofold axis of molecular symmetry. Importantly, the potentiator binding site is adjacent to the "hinge" in the ligand-binding core "clamshell" that undergoes conformational rearrangement after glutamate binding. Using rapid solution exchange, patch-clamp electrophysiology experiments, we show that point mutations of residues that interact with potentiators in the cocrystal disrupt potentiator function. We suggest that the potentiators slow deactivation by stabilizing the clamshell in its closed-cleft, glutamate-bound conformation.