Nonequilibrium Time Reversibility with Maps and Walks

Time-reversible dynamical simulations of nonequilibrium systems exemplify both Loschmidt’s and Zermélo’s paradoxes. That is, computational time-reversible simulations invariably produce solutions consistent with the irreversible Second Law of Thermodynamics (Loschmidt’s) as well as periodic in the time (Zermélo’s, illustrating Poincaré recurrence). Understanding these paradoxical aspects of time-reversible systems is enhanced here by studying the simplest pair of such model systems. The first is time-reversible, but nevertheless dissipative and periodic, the piecewise-linear compressible Baker Map. The fractal properties of that two-dimensional map are mirrored by an even simpler example, the one-dimensional random walk, confined to the unit interval. As a further puzzle the two models yield ambiguities in determining the fractals’ information dimensions. These puzzles, including the classical paradoxes, are reviewed and explored here.EPSR

Uncertainty quantification in medical image segmentation with normalizing flows

Medical image segmentation is inherently an ambiguous task due to factors such as partial volumes and variations in anatomical definitions. While in most cases the segmentation uncertainty is around the border of structures of interest, there can also be considerable inter-rater differences. The class of conditional variational autoencoders (cVAE) offers a principled approach to inferring distributions over plausible segmentations that are conditioned on input images. Segmentation uncertainty estimated from samples of such distributions can be more informative than using pixel level probability scores. In this work, we propose a novel conditional generative model that is based on conditional Normalizing Flow (cFlow). The basic idea is to increase the expressivity of the cVAE by introducing a cFlow transformation step after the encoder. This yields improved approximations of the latent posterior distribution, allowing the model to capture richer segmentation variations. With this we show that the quality and diversity of samples obtained from our conditional generative model is enhanced. Performance of our model, which we call cFlow Net, is evaluated on two medical imaging datasets demonstrating substantial improvements in both qualitative and quantitative measures when compared to a recent cVAE based model.Comment: 12 pages. Accepted to be presented at 11th International Workshop on Machine Learning in Medical Imaging. Source code will be updated at https://github.com/raghavian/cFlo

Prelimbic and Infralimbic Prefrontal Cortex Interact during Fast Network Oscillations

Background: The medial prefrontal cortex has been implicated in a variety of cognitive and executive processes such as decision making and working memory. The medial prefrontal cortex of rodents consists of several areas including the prelimbic and infralimbic cortex that are thought to be involved in different aspects of cognitive performance. Despite the distinct roles in cognitive behavior that have been attributed to prelimbic and infralimbic cortex, little is known about neuronal network functioning of these areas, and whether these networks show any interaction during fast network oscillations. Methodology/Principal Findings: Here we show that fast network oscillations in rat infralimbic cortex slices occur at higher frequencies and with higher power than oscillations in prelimbic cortex. The difference in oscillation frequency disappeared when prelimbic and infralimbic cortex were disconnected. Conclusions/Significance: Our data indicate that neuronal networks of prelimbic and infralimbic cortex can sustain fast network oscillations independent of each other, but suggest that neuronal networks of prelimbic and infralimbic cortex ar

Direct evidence for sequence-dependent attraction between double-stranded DNA controlled by methylation

Although proteins mediate highly ordered DNA organization in vivo, theoretical studies suggest that homologous DNA duplexes can preferentially associate with one another even in the absence of proteins. Here we combine molecular dynamics simulations with single-molecule fluorescence resonance energy transfer experiments to examine the interactions between duplex DNA in the presence of spermine, a biological polycation. We find that AT-rich DNA duplexes associate more strongly than GC-rich duplexes, regardless of the sequence homology. Methyl groups of thymine acts as a steric block, relocating spermine from major grooves to interhelical regions, thereby increasing DNA-DNA attraction. Indeed, methylation of cytosines makes attraction between GC-rich DNA as strong as that between AT-rich DNA. Recent genome-wide chromosome organization studies showed that remote contact frequencies are higher for AT-rich and methylated DNA, suggesting that direct DNA-DNA interactions that we report here may play a role in the chromosome organization and gene regulationopen

Effects of Insemination Quantity on Honey Bee Queen Physiology

Mating has profound effects on the physiology and behavior of female insects, and in honey bee (Apis mellifera) queens, these changes are permanent. Queens mate with multiple males during a brief period in their early adult lives, and shortly thereafter they initiate egg-laying. Furthermore, the pheromone profiles of mated queens differ from those of virgins, and these pheromones regulate many different aspects of worker behavior and colony organization. While it is clear that mating causes dramatic changes in queens, it is unclear if mating number has more subtle effects on queen physiology or queen-worker interactions; indeed, the effect of multiple matings on female insect physiology has not been broadly addressed. Because it is not possible to control the natural mating behavior of queens, we used instrumental insemination and compared queens inseminated with semen from either a single drone (single-drone inseminated, or SDI) or 10 drones (multi-drone inseminated, or MDI). We used observation hives to monitor attraction of workers to SDI or MDI queens in colonies, and cage studies to monitor the attraction of workers to virgin, SDI, and MDI queen mandibular gland extracts (the main source of queen pheromone). The chemical profiles of the mandibular glands of virgin, SDI, and MDI queens were characterized using GC-MS. Finally, we measured brain expression levels in SDI and MDI queens of a gene associated with phototaxis in worker honey bees (Amfor). Here, we demonstrate for the first time that insemination quantity significantly affects mandibular gland chemical profiles, queen-worker interactions, and brain gene expression. Further research will be necessary to elucidate the mechanistic bases for these effects: insemination volume, sperm and seminal protein quantity, and genetic diversity of the sperm may all be important factors contributing to this profound change in honey bee queen physiology, queen behavior, and social interactions in the colony

Design Novel Dual Agonists for Treating Type-2 Diabetes by Targeting Peroxisome Proliferator-Activated Receptors with Core Hopping Approach

Owing to their unique functions in regulating glucose, lipid and cholesterol metabolism, PPARs (peroxisome proliferator-activated receptors) have drawn special attention for developing drugs to treat type-2 diabetes. By combining the lipid benefit of PPAR-alpha agonists (such as fibrates) with the glycemic advantages of the PPAR-gamma agonists (such as thiazolidinediones), the dual PPAR agonists approach can both improve the metabolic effects and minimize the side effects caused by either agent alone, and hence has become a promising strategy for designing effective drugs against type-2 diabetes. In this study, by means of the powerful “core hopping” and “glide docking” techniques, a novel class of PPAR dual agonists was discovered based on the compound GW409544, a well-known dual agonist for both PPAR-alpha and PPAR-gamma modified from the farglitazar structure. It was observed by molecular dynamics simulations that these novel agonists not only possessed the same function as GW409544 did in activating PPAR-alpha and PPAR-gamma, but also had more favorable conformation for binding to the two receptors. It was further validated by the outcomes of their ADME (absorption, distribution, metabolism, and excretion) predictions that the new agonists hold high potential to become drug candidates. Or at the very least, the findings reported here may stimulate new strategy or provide useful insights for discovering more effective dual agonists for treating type-2 diabetes. Since the “core hopping” technique allows for rapidly screening novel cores to help overcome unwanted properties by generating new lead compounds with improved core properties, it has not escaped our notice that the current strategy along with the corresponding computational procedures can also be utilized to find novel and more effective drugs for treating other illnesses

Role of Lipids in Spheroidal High Density Lipoproteins

We study the structure and dynamics of spherical high density lipoprotein (HDL) particles through coarse-grained multi-microsecond molecular dynamics simulations. We simulate both a lipid droplet without the apolipoprotein A-I (apoA-I) and the full HDL particle including two apoA-I molecules surrounding the lipid compartment. The present models are the first ones among computational studies where the size and lipid composition of HDL are realistic, corresponding to human serum HDL. We focus on the role of lipids in HDL structure and dynamics. Particular attention is paid to the assembly of lipids and the influence of lipid-protein interactions on HDL properties. We find that the properties of lipids depend significantly on their location in the particle (core, intermediate region, surface). Unlike the hydrophobic core, the intermediate and surface regions are characterized by prominent conformational lipid order. Yet, not only the conformations but also the dynamics of lipids are found to be distinctly different in the different regions of HDL, highlighting the importance of dynamics in considering the functionalization of HDL. The structure of the lipid droplet close to the HDL-water interface is altered by the presence of apoA-Is, with most prominent changes being observed for cholesterol and polar lipids. For cholesterol, slow trafficking between the surface layer and the regimes underneath is observed. The lipid-protein interactions are strongest for cholesterol, in particular its interaction with hydrophobic residues of apoA-I. Our results reveal that not only hydrophobicity but also conformational entropy of the molecules are the driving forces in the formation of HDL structure. The results provide the first detailed structural model for HDL and its dynamics with and without apoA-I, and indicate how the interplay and competition between entropy and detailed interactions may be used in nanoparticle and drug design through self-assembly

Queen mandibular pheromone: questions that remain to be resolved

The discovery of ‘queen substance’, and the subsequent identification and synthesis of keycomponents of queen mandibular pheromone, has been of significant importance to beekeepers and to thebeekeeping industry. Fifty years on, there is greater appreciation of the importance and complexity of queenpheromones, but many mysteries remain about the mechanisms through which pheromones operate. Thediscovery of sex pheromone communication in moths occurred within the same time period, but in this case,intense pressure to find better means of pest management resulted in a remarkable focusing of research activityon understanding pheromone detection mechanisms and the central processing of pheromone signals in themoth. We can benefit from this work and here, studies on moths are used to highlight some of the gaps in ourknowledge of pheromone communication in bees. A better understanding of pheromone communication inhoney bees promises improved strategies for the successful management of these extraordinary animals