Bose-Einstein condensates: microscopic magnetic-field imaging

Today's magnetic-field sensors are not capable of making measurements with both high spatial resolution and good field sensitivity. For example, magnetic force microscopy allows the investigation of magnetic structures with a spatial resolution in the nanometre range, but with low sensitivity, whereas SQUIDs and atomic magnetometers enable extremely sensitive magnetic-field measurements to be made, but at low resolution. Here we use one-dimensional Bose-Einstein condensates in a microscopic field-imaging technique that combines high spatial resolution (within 3 micrometres) with high field sensitivity (300 picotesla).     

Bird song: superfast muscles control dove's trill

Bird songs frequently contain trilling sounds that demand extremely fast vocalization control. Here we show that doves control their syrinx, a vocal organ that is unique to birds, by using superfast muscles. These muscles, which are similar to those that operate highly specialist acoustic organs such as the rattle of the rattlesnake, are among the fastest vertebrate muscles known and could be much more widespread than previously thought if they are the principal muscle type used to control bird songs.     

A subset of dopamine neurons signals reward for odour memory in Drosophila

Animals approach stimuli that predict a pleasant outcome. After the paired presentation of an odour and a reward, Drosophila melanogaster can develop a conditioned approach towards that odour. Despite recent advances in understanding the neural circuits for associative memory and appetitive motivation, the cellular mechanisms for reward processing in the fly brain are unknown. Here we show that a group of dopamine neurons in the protocerebral anterior medial (PAM) cluster signals sugar reward by transient activation and inactivation of target neurons in intact behaving flies. These dopamine neurons are selectively required for the reinforcing property of, but not a reflexive response to, the sugar stimulus. In vivo calcium imaging revealed that these neurons are activated by sugar ingestion and the activation is increased on starvation. The output sites of the PAM neurons are mainly localized to the medial lobes of the mushroom bodies (MBs), where appetitive olfactory associative memory is formed. We therefore propose that the PAM cluster neurons endow a positive predictive value to the odour in the MBs. Dopamine in insects is known to mediate aversive reinforcement signals. Our results highlight the cellular specificity underlying the various roles of dopamine and the importance of spatially segregated local circuits within the MBs.     

A Study of Melt Flow Analysis of an ABS-Iron Composite in Fused Deposition Modelling Process

Fused deposition modelling (FDM) is a filament based rapid prototyping system which offers the possibility of introducing new composite material for the FDM process as long as the new material can be made in feedstock filament form. Swinburne has been undertaking extensive research in development of new composite materials involving acrylonitrile-butadiene-styrene (ABS) and other materials including metals. In order to predict the behaviour of new ABS based composite materials in the course of FDM process, it is necessary to investigate the flow of the composite material in liquefier head. No such study is available considering the geometry of the liquefier head. This paper presents 2-D and 3-D numerical analysis of melt flow behaviour of a representative ABS-iron composite through the 90-degree bent tube of the liquefier head of the fused deposition modelling process using ANSYS FLOTRAN and CFX finite element packages. Main flow parameters including temperature, velocity, and pressure drop have been investigated. Filaments of the filled ABS have been fabricated and characterized to verify the possibility of prototyping using the new material on the current FDM machine. Results provide promising information in developing the melt flow modelling of metal-plastic composites and in optimising the FDM parameters for better part quality with such composites.     

Common variation near CDKN1A, POLD3 and SHROOM2 influences colorectal cancer risk

We performed a meta-analysis of five genome-wide association studies to identify common variants influencing colorectal cancer (CRC) risk comprising 8,682 cases and 9,649 controls. Replication analysis was performed in case-control sets totaling 21,096 cases and 19,555 controls. We identified three new CRC risk loci at 6p21 (rs1321311, near CDKN1A; P = 1.14 × 10(-10)), 11q13.4 (rs3824999, intronic to POLD3; P = 3.65 × 10(-10)) and Xp22.2 (rs5934683, near SHROOM2; P = 7.30 × 10(-10)) This brings the number of independent loci associated with CRC risk to 20 and provides further insight into the genetic architecture of inherited susceptibility to CRC.     

Glial versus melanocyte cell fate choice: Schwann cell precursors as a cellular origin of melanocytes

Melanocytes and Schwann cells are derived from the multipotent population of neural crest cells. Although both cell types were thought to be generated through completely distinct pathways and molecular processes, a recent study has revealed that these different cell types are intimately interconnected far beyond previously postulated limits in that they share a common post-neural crest progenitor, i.e. the Schwann cell precursor. This finding raises interesting questions about the lineage relationships of hitherto unrelated cell types such as melanocytes and Schwann cells, and may provide clinical insights into mechanisms of pigmentation disorders and for cancer involving Schwann cells and melanocytes.     

Density dependence explains tree species abundance and diversity in tropical forests

The recurrent patterns in the commonness and rarity of species in ecological communities--the relative species abundance--have puzzled ecologists for more than half a century. Here we show that the framework of the current neutral theory in ecology can easily be generalized to incorporate symmetric density dependence. We can calculate precisely the strength of the rare-species advantage that is needed to explain a given RSA distribution. Previously, we demonstrated that a mechanism of dispersal limitation also fits RSA data well. Here we compare fits of the dispersal and density-dependence mechanisms for empirical RSA data on tree species in six New and Old World tropical forests and show that both mechanisms offer sufficient and independent explanations. We suggest that RSA data cannot by themselves be used to discriminate among these explanations of RSA patterns--empirical studies will be required to determine whether RSA patterns are due to one or the other mechanism, or to some combination of both.