Sexual behaviors in animals are governed by inputs from multiple external sensory modalities. However, how these inputs are integrated to jointly control animal behavior is still poorly understood. Whereas visual information alone is not sufficient to induce courtship behavior in Drosophila melanogaster males, when a subset of male-specific fruitless (fru)- and doublesex (dsx)-expressing neurons that respond to chemosensory cues (P1 neurons) were artificially activated via a temperature-sensitive cation channel (dTRPA1), males followed and extended their wing toward moving objects (even a moving piece of rubber band) intensively. When stationary, these objects were not courted. Our results indicate that motion input and activation of P1 neurons are individually necessary, and under our assay conditions, jointly sufficient to elicit early courtship behaviors, and provide insights into how courtship decisions are made via sensory integration.

Large electron microscopy image datasets for connectomics are typically composed of thousands to millions of partially overlapping two-dimensional images (tiles), which must be registered into a coherent volume prior to further analysis. A common registration strategy is to find matching features between neighboring and overlapping image pairs, followed by a numerical estimation of optimal image deformation using a so-called solver program. 
Existing solvers are inadequate for large data volumes, and inefficient for small-scale image registration. 
In this work, an efficient and accurate matrix-based solver method is presented. A linear system is constructed that combines minimization of feature-pair square distances with explicit constraints in a regularization term. In absence of reliable priors for regularization, we show how to construct a rigid-model approximation to use as prior. The linear system is solved using available computer programs, whose performance on typical registration tasks we briefly compare, and to which future scale-up is delegated. Our method is applied to the joint alignment of 2.67 million images, with more than 200 million point-pairs and has been used for successfully aligning the first full adult fruit fly brain.

The correction of bias in magnetic resonance images is an important problem in medical image processing. Most previous approaches have used a maximum likelihood method to increase the likelihood of the pixels in a single image by adaptively estimating a correction to the unknown image bias field. The pixel likelihoods are defined either in terms of a pre-existing tissue model, or non-parametrically in terms of the image’s own pixel values. In both cases, the specific location of a pixel in the image is not used to calculate the likelihoods. We suggest a new approach in which we simultaneously eliminate the bias from a set of images of the same anatomy, but from different patients. We use the statistics from the same location across different images, rather than within an image, to eliminate bias fields from all of the images simultaneously. The method builds a multi-resolution non-parametric tissue model conditioned on image location while eliminating the bias fields associated with the original image set. We present experiments on both synthetic and real MR data sets, and present comparisons with other methods.

To compare spatial patterns of gene expression, one must analyze a large number of images as current methods are only able to measure a small number of genes at a time. Bringing images of corresponding tissues into alignment is a critical first step in making a meaningful comparative analysis of these spatial patterns. Significant image noise and variability in the shapes make it hard to pick a canonical shape model. In this paper, we address these problems by combining segmentation and unsupervised shape learning algorithms. We first segment images to acquire structures of interest, then jointly align the shapes of these acquired structures using an unsupervised nonparametric maximum likelihood algorithm along the lines of congealing, while simultaneously learning the underlying shape model and associated transformations. The learned transformations are applied to corresponding images to bring them into alignment in one step. We demonstrate the results for images of various classes of Drosophila imaginal discs and discuss the methodology used for a quantitative analysis of spatial gene expression patterns.

Infective juveniles of the insect-parastic nematode canjump greater than 6 times their height, a striking evolved novelty in some species of this genus. Using high-speed videography, we observed the kinematics of spontaneousjumping behavior. Our analysis places a lower bound on the velocity and acceleration of these worms.

Aquaporins (AQPs) are a family of ubiquitous membrane channels that conduct water and solutes across membranes. This review focuses on AQP0 and AQP4, which in addition to forming water channels also appear to play a role in cell adhesion. We discuss the recently determined structures of the membrane junctions mediated by these two AQPs, the mechanisms that regulate junction formation, and evidence that supports a role for AQP0 and AQP4 in cell adhesion.

Juvenile hormone (JH) is a key hormone in regulation of the insect’s life history, both in maintaining the larval state during molts and in directing reproductive maturation. This short review highlights the recent papers of the past year that lend new insight into the role of this hormone in the larva and the mechanisms whereby it achieves this role.

Tsetse flies are viviparous insects that nurture a single intrauterine progeny per gonotrophic cycle. The developing larva is nourished by the lipid-rich, milk-like secretions from a modified female accessory gland (milk gland). An essential feature of the lactation process involves lipid mobilization for incorporation into the milk. In this study, we examined roles for juvenile hormone (JH) and insulin/IGF-like (IIS) signaling pathways during tsetse pregnancy. In particular, we examined the roles for these pathways in regulating lipid homeostasis during transitions between non-lactating (dry) and lactating periods. The dry period occurs over the course of oogenesis and embryogenesis, while the lactation period spans intrauterine larvigenesis. Genes involved in the JH and IIS pathways were upregulated during dry periods, correlating with lipid accumulation between bouts of lactation. RNAi suppression of Forkhead Box Sub Group O (FOXO) expression impaired lipolysis during tsetse lactation and reduced fecundity. Similar reduction of the JH receptor Methoprene tolerant (Met), but not its paralog germ cell expressed (gce), reduced lipid accumulation during dry periods, indicating functional divergence between Met and gce during tsetse reproduction. Reduced lipid levels following Met knockdown led to impaired fecundity due to inadequate fat reserves at the initiation of milk production. Both the application of the JH analog (JHA) methoprene and injection of insulin into lactating females increased stored lipids by suppressing lipolysis and reduced transcripts of lactation-specific genes, leading to elevated rates of larval abortion. To our knowledge, this study is the first to address the molecular physiology of JH and IIS in a viviparous insect, and specifically to provide a role for JH signaling through Met in the regulation of lipid metabolism during insect lactation.

In starved larvae of the tobacco hornworm moth Manduca sexta, larval and imaginal tissues stop growing, the former because they lack nutrient-dependent signals but the latter because of suppression by juvenile hormone. Without juvenile hormone, imaginal discs form and grow despite severe starvation. This hormone inhibits the intrinsic signaling needed for disc morphogenesis and does so independently of ecdysteroid action. Starvation and juvenile hormone treatments allowed the separation of intrinsic and nutrient-dependent aspects of disc growth and showed that both aspects must occur during the early phases of disc morphogenesis to ensure normal growth leading to typical-sized adults.