A New Chamber for Studying the Behavior of Drosophila

Methods available for quickly and objectively quantifying the behavioral phenotypes of the fruit fly, Drosophila melanogaster, lag behind in sophistication the tools developed for manipulating their genotypes. We have developed a simple, easy-to-replicate, general-purpose experimental chamber for studying the ground-based behaviors of fruit flies. The major innovative feature of our design is that it restricts flies to a shallow volume of space, forcing all behavioral interactions to take place within a monolayer of individuals. The design lessens the frequency that flies occlude or obscure each other, limits the variability in their appearance, and promotes a greater number of flies to move throughout the center of the chamber, thereby increasing the frequency of their interactions. The new chamber design improves the quality of data collected by digital video and was conceived and designed to complement automated machine vision methodologies for studying behavior. Novel and improved methodologies for better quantifying the complex behavioral phenotypes of Drosophila will facilitate studies related to human disease and fundamental questions of behavioral neuroscience

Machine Learning Classification of Repeating FRBs from FRB121102

Fast Radio Bursts (FRBs) are mysterious bursts in the millisecond timescale at radio wavelengths. Currently, there is little understanding about the classification of repeating FRBs, based on difference in physics, which is of great importance in understanding their origin. Recent works from the literature focus on using specific parameters to classify FRBs to draw inferences on the possible physical mechanisms or properties of these FRB subtypes. In this study, we use publicly available 1652 repeating FRBs from FRB121102 detected with the Five-hundred-meter Aperture Spherical Telescope (FAST), and studied them with an unsupervised machine learning model. By fine-tuning the hyperparameters of the model, we found that there is an indication for four clusters from the bursts of FRB121102 instead of the two clusters ("Classical" and "Atypical") suggested in the literature. Wherein, the "Atypical" cluster can be further classified into three sub-clusters with distinct characteristics. Our findings show that the clustering result we obtained is more comprehensive not only because our study produced results which are consistent with those in the literature but also because our work uses more physical parameters to create these clusters. Overall, our methods and analyses produced a more holistic approach in clustering the repeating FRBs of FRB121102.Comment: 24 pages, 14 figure

A network analysis to identify pathophysiological pathways distinguishing ischaemic from non-ischaemic heart failure

Aims Heart failure (HF) is frequently caused by an ischaemic event (e.g. myocardial infarction) but might also be caused by a primary disease of the myocardium (cardiomyopathy). In order to identify targeted therapies specific for either ischaemic or non‐ischaemic HF, it is important to better understand differences in underlying molecular mechanisms. Methods and results We performed a biological physical protein–protein interaction network analysis to identify pathophysiological pathways distinguishing ischaemic from non‐ischaemic HF. First, differentially expressed plasma protein biomarkers were identified in 1160 patients enrolled in the BIOSTAT‐CHF study, 715 of whom had ischaemic HF and 445 had non‐ischaemic HF. Second, we constructed an enriched physical protein–protein interaction network, followed by a pathway over‐representation analysis. Finally, we identified key network proteins. Data were validated in an independent HF cohort comprised of 765 ischaemic and 100 non‐ischaemic HF patients. We found 21/92 proteins to be up‐regulated and 2/92 down‐regulated in ischaemic relative to non‐ischaemic HF patients. An enriched network of 18 proteins that were specific for ischaemic heart disease yielded six pathways, which are related to inflammation, endothelial dysfunction superoxide production, coagulation, and atherosclerosis. We identified five key network proteins: acid phosphatase 5, epidermal growth factor receptor, insulin‐like growth factor binding protein‐1, plasminogen activator urokinase receptor, and secreted phosphoprotein 1. Similar results were observed in the independent validation cohort. Conclusions Pathophysiological pathways distinguishing patients with ischaemic HF from those with non‐ischaemic HF were related to inflammation, endothelial dysfunction superoxide production, coagulation, and atherosclerosis. The five key pathway proteins identified are potential treatment targets specifically for patients with ischaemic HF

Coherent multi-flavour spin dynamics in a fermionic quantum gas

Microscopic spin interaction processes are fundamental for global static and dynamical magnetic properties of many-body systems. Quantum gases as pure and well isolated systems offer intriguing possibilities to study basic magnetic processes including non-equilibrium dynamics. Here, we report on the realization of a well-controlled fermionic spinor gas in an optical lattice with tunable effective spin ranging from 1/2 to 9/2. We observe long-lived intrinsic spin oscillations and investigate the transition from two-body to many-body dynamics. The latter results in a spin-interaction driven melting of a band insulator. Via an external magnetic field we control the system's dimensionality and tune the spin oscillations in and out of resonance. Our results open new routes to study quantum magnetism of fermionic particles beyond conventional spin 1/2 systems.Comment: 9 pages, 5 figure

Prior Mating Experience Modulates the Dispersal of Drosophila in Males More Than in Females

Cues from both an animal’s internal physiological state and its local environment may influence its decision to disperse. However, identifying and quantifying the causative factors underlying the initiation of dispersal is difficult in uncontrolled natural settings. In this study, we automatically monitored the movement of fruit flies and examined the influence of food availability, sex, and reproductive status on their dispersal between laboratory environments. In general, flies with mating experience behave as if they are hungrier than virgin flies, leaving at a greater rate when food is unavailable and staying longer when it is available. Males dispersed at a higher rate and were more active than females when food was unavailable, but tended to stay longer in environments containing food than did females. We found no significant relationship between weight and activity, suggesting the behavioral differences between males and females are caused by an intrinsic factor relating to the sex of a fly and not simply its body size. Finally, we observed a significant difference between the dispersal of the natural isolate used throughout this study and the widely-used laboratory strain, Canton-S, and show that the difference cannot be explained by allelic differences in the foraging gene

Advancing Our Understanding of Martian Proton Aurora through a Coordinated Multi-Model Comparison Campaign

Proton aurora are the most commonly observed yet least studied type of aurora at Mars. In order to better understand the physics and driving processes of Martian proton aurora, we undertake a multi-model comparison campaign. We compare results from four different proton/hydrogen precipitation models with unique abilities to represent Martian proton aurora: Jolitz model (3-D Monte Carlo), Kallio model (3-D Monte Carlo), Bisikalo/Shematovich et al. model (1-D kinetic Monte Carlo), and Gronoff et al. model (1-D kinetic). This campaign is divided into two steps: an inter-model comparison and a data-model comparison. The inter-model comparison entails modeling five different representative cases using similar constraints in order to better understand the capabilities and limitations of each of the models. Through this step we find that the two primary variables affecting proton aurora are the incident solar wind particle flux and velocity. In the data-model comparison, we assess the robustness of each model based on its ability to reproduce a MAVEN/IUVS proton aurora observation. All models are able to effectively simulate the data. Variations in modeled intensity and peak altitude can be attributed to differences in model capabilities/solving techniques and input assumptions (e.g., cross sections, 3-D versus 1-D solvers, and implementation of the relevant physics and processes). The good match between the observations and multiple models gives a measure of confidence that the appropriate physical processes and their associated parameters have been correctly identified and provides insight into the key physics that should be incorporated in future models

Microbiome-derived carnitine mimics as previously unknown mediators of gut-brain axis communication

Alterations to the gut microbiome are associated with various neurological diseases, yet evidence of causality and identity of microbiome-derived compounds that mediate gut-brain axis interaction remain elusive. Here, we identify two previously unknown bacterial metabolites 3-methyl-4-(trimethylammonio)butanoate and 4-(trimethylammonio)pentanoate, structural analogs of carnitine that are present in both gut and brain of specific pathogen–free mice but absent in germ-free mice. We demonstrate that these compounds are produced by anaerobic commensal bacteria from the family Lachnospiraceae (Clostridiales) family, colocalize with carnitine in brain white matter, and inhibit carnitine-mediated fatty acid oxidation in a murine cell culture model of central nervous system white matter. This is the first description of direct molecular inter-kingdom exchange between gut prokaryotes and mammalian brain cells, leading to inhibition of brain cell function

Observation of viscosity transition in alpha-pinene secondary organic aerosol

Under certain conditions, secondary organic aerosol (SOA) particles can exist in the atmosphere in an amorphous solid or semi-solid state. To determine their relevance to processes such as ice nucleation or chemistry occurring within particles requires knowledge of the temperature and relative humidity (RH) range for SOA to exist in these states. In the Cosmics Leaving Outdoor Droplets (CLOUD) experiment at The European Organisation for Nuclear Research (CERN), we deployed a new in situ optical method to detect the viscous state of alpha-pinene SOA particles and measured their transition from the amorphous highly viscous state to states of lower viscosity. The method is based on the depolarising properties of laboratory-produced non-spherical SOA particles and their transformation to non-depolarising spherical particles at relative humidities near the deliquescence point. We found that particles formed and grown in the chamber developed an asymmetric shape through coagulation. A transition to a spherical shape was observed as the RH was increased to between 35aEuro-% at -10aEuro-A degrees C and 80aEuro-% at -38aEuro-A degrees C, confirming previous calculations of the viscosity-transition conditions. Consequently, alpha-pinene SOA particles exist in a viscous state over a wide range of ambient conditions, including the cirrus region of the free troposphere. This has implications for the physical, chemical, and ice-nucleation properties of SOA and SOA-coated particles in the atmosphere.Peer reviewe

Formation of Highly Oxygenated Organic Molecules from alpha-Pinene Ozonolysis : Chemical Characteristics, Mechanism, and Kinetic Model Development

Terpenes are emitted by vegetation, and their oxidation in the atmosphere is an important source of secondary organic aerosol (SOA). A part of this oxidation can proceed through an autoxidation process, yielding highly oxygenated organic molecules (HOMs) with low saturation vapor pressure. They can therefore contribute, even in the absence of sulfuric acid, to new particle formation (NPF). The understanding of the autoxidation mechanism and its kinetics is still far from complete. Here, we present a mechanistic and kinetic analysis of mass spectrometry data from α-pinene (AP) ozonolysis experiments performed during the CLOUD 8 campaign at CERN. We grouped HOMs in classes according to their identified chemical composition and investigated the relative changes of these groups and their components as a function of the reagent concentration. We determined reaction rate constants for the different HOM peroxy radical reaction pathways. The accretion reaction between HOM peroxy radicals was found to be extremely fast. We developed a pseudo-mechanism for HOM formation and added it to the AP oxidation scheme of the Master Chemical Mechanism (MCM). With this extended model, the observed concentrations and trends in HOM formation were successfully simulated.Peer reviewe