The structure of Pavlovian fear conditioning in the amygdala

Do different brains forming a specific memory allocate the same groups of neurons to encode it? One way to test this question is to map neurons encoding the same memory and quantitatively compare their locations across individual brains. In a previous study, we used this strategy to uncover a common topography of neurons in the dorsolateral amygdala (LAd) that expressed a learning-induced and plasticity-related kinase (p42/44 mitogen-activated protein kinase; pMAPK), following auditory Pavlovian fear conditioning. In this series of experiments, we extend our initial findings to ask to what extent this functional topography depends upon intrinsic neuronal structure. We first showed that the majority (87 %) of pMAPK expression in the lateral amygdala was restricted to principal-type neurons. Next, we verified a neuroanatomical reference point for amygdala alignment using in vivo magnetic resonance imaging and in vitro morphometrics. We then determined that the topography of neurons encoding auditory fear conditioning was not exclusively governed by principal neuron cytoarchitecture. These data suggest that functional patterning of neurons undergoing plasticity in the amygdala following Pavlovian fear conditioning is specific to memory formation itself. Further, the spatial allocation of activated neurons in the LAd was specific to cued (auditory), but not contextual, fear conditioning. Spatial analyses conducted at another coronal plane revealed another spatial map unique to fear conditioning, providing additional evidence that the functional topography of fear memory storing cells in the LAd is non-random and stable. Overall, these data provide evidence for a spatial organizing principle governing the functional allocation of fear memory in the amygdala.

Visual function and CFH/ARMS2 risk genotypes in macular dystrophy due to maternally inherited diabetes and deafness

Maternally inherited diabetes and deafness (MIDD) is an autosomal dominant inherited syndrome caused by the mitochondrial DNA (mtDNA) nucleotide mutation A3243G. It affects various organs including the eye with external ophthalmoparesis, ptosis, and bilateral macular pattern dystrophy.1, 2 The prevalence of retinal involvement in MIDD is high, with 50% to 85% of patients exhibiting some macular changes.1 Those changes, however, can vary between patients and within families dramatically based on the percentage of retinal mtDNA mutations, making it difficult to give predictions on an individual’s visual prognosis...

Publicly verifiable ciphertexts

In many applications, where encrypted traffic flows from an open (public) domain to a protected (private) domain, there exists a gateway that bridges the two domains and faithfully forwards the incoming traffic to the receiver. We observe that indistinguishability against (adaptive) chosen-ciphertext attacks (IND-CCA), which is a mandatory goal in face of active attacks in a public domain, can be essentially relaxed to indistinguishability against chosen-plaintext attacks (IND-CPA) for ciphertexts once they pass the gateway that acts as an IND-CCA/CPA filter by first checking the validity of an incoming IND-CCA ciphertext, then transforming it (if valid) into an IND-CPA ciphertext, and forwarding the latter to the recipient in the private domain. “Non-trivial filtering'' can result in reduced decryption costs on the receivers' side. We identify a class of encryption schemes with publicly verifiable ciphertexts that admit generic constructions of (non-trivial) IND-CCA/CPA filters. These schemes are characterized by existence of public algorithms that can distinguish between valid and invalid ciphertexts. To this end, we formally define (non-trivial) public verifiability of ciphertexts for general encryption schemes, key encapsulation mechanisms, and hybrid encryption schemes, encompassing public-key, identity-based, and tag-based encryption flavours. We further analyze the security impact of public verifiability and discuss generic transformations and concrete constructions that enjoy this property.

A RBF meshless approach for modeling a fractal mobile/immobile transport model

A fractional differential equation is used to describe a fractal model of mobile/immobile transport with a power law memory function. This equation is the limiting equation that governs continuous time random walks with heavy tailed random waiting times. In this paper, we firstly propose a finite difference method to discretize the time variable and obtain a semi-discrete scheme. Then we discuss its stability and convergence. Secondly we consider a meshless method based on radial basis functions (RBFs) to discretize the space variable. In contrast to conventional FDM and FEM, the meshless method is demonstrated to have distinct advantages: calculations can be performed independent of a mesh, it is more accurate and it can be used to solve complex problems. Finally the convergence order is verified from a numerical example which is presented to describe a fractal model of mobile/immobile transport process with different problem domains. The numerical results indicate that the present meshless approach is very effective for modeling and simulating fractional differential equations, and it has good potential in the development of a robust simulation tool for problems in engineering and science that are governed by various types of fractional differential equations.

DRB2, DRB3 and DRB5 function in a non-canonical microRNA pathway in Arabidopsis thaliana

DOUBLE-STRANDED RNA BIN DIN G (DRB) proteins have been functionally characterized in viruses, prokaryotes and eukaryotes and are involved in all aspects of RNA biology. Arabidopsis thaliana (Arabidopsis) encodes five closely related DRB proteins, DRB1 to DRB5. DRB1 and DRB4 are required by DICER-LIKE (DCL) proteins DCL1 and DCL4 to accurately and efficiently process structurally distinct double-stranded RNA (dsRNA) precursor substrates in the microRNA (miRNA) and trans-acting small-interfering RNA (tasiRNA) biogenesis pathways respectively. We recently reported that DRB2 is also involved in the biogenesis of specific miRNA subsets. Furthermore, the severity of the developmental phenotype displayed by the drb235 triple mutant plant, compared with those expressed by either drb2, drb3 and drb5 single mutants, or double mutant combinations thereof, indicates that DRB3 and DRB5 function in the same non-canonical miRNA pathway as DRB2. Through the use of our artificial miRNA (amiRNA) plant expression vector, pBlueGreen 2,3 we demonstrate here that unlike DRB2, DRB3 and DRB5 are not involved in the dsRNA processing stages of the miRNA biogenesis pathway, but are required to mediate RNA silencing of target genes of DRB2-associated miRNA s. © 2012 Landes Bioscience.

The impact of spatial scales and spatial smoothing on the outcome of Bayesian spatial model

Discretization of a geographical region is quite common in spatial analysis. There have been few studies into the impact of different geographical scales on the outcome of spatial models for different spatial patterns. This study aims to investigate the impact of spatial scales and spatial smoothing on the outcomes of modelling spatial point-based data. Given a spatial point-based dataset (such as occurrence of a disease), we study the geographical variation of residual disease risk using regular grid cells. The individual disease risk is modelled using a logistic model with the inclusion of spatially unstructured and/or spatially structured random effects. Three spatial smoothness priors for the spatially structured component are employed in modelling, namely an intrinsic Gaussian Markov random field, a second-order random walk on a lattice, and a Gaussian field with Matern correlation function. We investigate how changes in grid cell size affect model outcomes under different spatial structures and different smoothness priors for the spatial component. A realistic example (the Humberside data) is analyzed and a simulation study is described. Bayesian computation is carried out using an integrated nested Laplace approximation. The results suggest that the performance and predictive capacity of the spatial models improve as the grid cell size decreases for certain spatial structures. It also appears that different spatial smoothness priors should be applied for different patterns of point data.

Rice ragged stunt oryzavirus genome segment S4 could encode an RNA dependent RNA polymerase and a second protein of unknown function

The complete nucleotide sequence of genome segment S4 of rice ragged stunt oryzavirus (RRSV, Thai-isolate) was determined. The 3823 bp sequence contains two large open reading frames (ORFs). ORF1, spanning nucleotides 12 to 3776, is capable of encoding a protein of M(r) 141,380 (P4a). The P4a amino acid sequence predicted from the nucleotide sequence contains sequence motifs conserved in RNA-dependent RNA polymerases (RDRPs). When compared for evolutionary relationships with RDRPs of other reoviruses using the amino acid sequences around the conserved GDD motif, P4a was shown to be more related to Nilaparvata lugens reovirus and reovirus serotype 3 than to rice dwarf phytoreovirus, bovine rotavirus or bluetongue virus. The ORF2, spanning nucleotides 491 to 1468, is out of frame with ORF1 and is capable of encoding a protein of 36, 920 (P4b). Coupled in vitro transcription-translation from cloned ORF2 in wheat germ extract confirmed the existence of ORF2 but in vivo production and possible function of P4b is yet to be determined.

Delineating breast cancer cell interactions with engineered bone microenvironments

The mechanisms leading to colonization of metastatic breast cancer cells (BCa) in the skeleton are still not fully understood. Here, we demonstrate that mineralized extracellular matrices secreted by primary human osteoblasts (hOBM) modulate cellular processes associated with BCa colonization of bone. A panel of four BCa cell lines of different bone-metastatic potential (T47D, SUM1315, MDA-MB-231, and the bone-seeking subline MDA-MB-231BO) was cultured on hOBM. After 3 days, the metastatic BCa cells had undergone morphological changes on hOBM and were aligned along the hOBM's collagen type I fibrils that were decorated with bone-specific proteins. In contrast, nonmetastatic BCa cells showed a random orientation on hOBM. Atomic force microscopy-based single-cell force spectroscopy revealed that the metastatic cell lines adhered more strongly to hOBM compared with nonmetastatic cells. Function-blocking experiments indicated that β1-integrins mediated cell adhesion to hOBM. In addition, metastatic BCa cells migrated directionally and invaded hOBM, which was accompanied by enhanced MMP-2 and -9 secretion. Furthermore, we observed gene expression changes associated with osteomimickry in BCa cultured on hOBM. As such, osteopontin mRNA levels were significantly increased in SUM1315 and MDA-MB-231BO cells in a β1-integrin-dependent manner after growing for 3 days on hOBM compared with tissue culture plastic. In conclusion, our results show that extracellular matrices derived from human osteoblasts represent a powerful experimental platform to dissect mechanisms underlying critical steps in the development of bone metastases.

The α5 subunit regulates the expression and function of α4*-containing neuronal nicotinic acetylcholine receptors in the ventral-tegmental area

Human genetic association studies have shown gene variants in the α5 subunit of the neuronal nicotinic receptor (nAChR) influence both ethanol and nicotine dependence. The α5 subunit is an accessory subunit that facilitates α4* nAChRs assembly in vitro. However, it is unknown whether this occurs in the brain, as there are few research tools to adequately address this question. As the α4*-containing nAChRs are highly expressed in the ventral tegmental area (VTA) we assessed the molecular, functional and pharmacological roles of α5 in α4*-containing nAChRs in the VTA. We utilized transgenic mice α5+/+(α4YFP) and α5-/-(α4YFP) that allow the direct visualization and measurement of α4-YFP expression and the effect of the presence (α5+/+) and absence of α5 (-/-) subunit, as the antibodies for detecting the α4* subunits of the nAChR are not specific. We performed voltage clamp electrophysiological experiments to study baseline nicotinic currents in VTA dopaminergic neurons. We show that in the presence of the α5 subunit, the overall expression of α4 subunit is increased significantly by 60% in the VTA. Furthermore, the α5 subunit strengthens baseline nAChR currents, suggesting the increased expression of α4* nAChRs to be likely on the cell surface. While the presence of the α5 subunit blunts the desensitization of nAChRs following nicotine exposure, it does not alter the amount of ethanol potentiation of VTA dopaminergic neurons. Our data demonstrates a major regulatory role for the α5 subunit in both the maintenance of α4*-containing nAChRs expression and in modulating nicotinic currents in VTA dopaminergic neurons. Additionally, the α5α4* nAChR in VTA dopaminergic neurons regulates the effect of nicotine but not ethanol on currents. Together, the data suggest that the α5 subunit is critical for controlling the expression and functional role of a population of α4*-containing nAChRs in the VTA.

Distinguishing between mechanisms of cell aggregation using pair-correlation functions

Many cell types form clumps or aggregates when cultured in vitro through a variety of mechanisms including rapid cell proliferation, chemotaxis, or direct cell-to-cell contact. In this paper we develop an agent-based model to explore the formation of aggregates in cultures where cells are initially distributed uniformly, at random, on a two-dimensional substrate. Our model includes unbiased random cell motion, together with two mechanisms which can produce cell aggregates: (i) rapid cell proliferation, and (ii) a biased cell motility mechanism where cells can sense other cells within a finite range, and will tend to move towards areas with higher numbers of cells. We then introduce a pair-correlation function which allows us to quantify aspects of the spatial patterns produced by our agent-based model. In particular, these pair-correlation functions are able to detect differences between domains populated uniformly at random (i.e. at the exclusion complete spatial randomness (ECSR) state) and those where the proliferation and biased motion rules have been employed - even when such differences are not obvious to the naked eye. The pair-correlation function can also detect the emergence of a characteristic inter-aggregate distance which occurs when the biased motion mechanism is dominant, and is not observed when cell proliferation is the main mechanism of aggregate formation. This suggests that applying the pair-correlation function to experimental images of cell aggregates may provide information about the mechanism associated with observed aggregates. As a proof of concept, we perform such analysis for images of cancer cell aggregates, which are known to be associated with rapid proliferation. The results of our analysis are consistent with the predictions of the proliferation-based simulations, which supports the potential usefulness of pair correlation functions for providing insight into the mechanisms of aggregate formation.

An Artificial Neutral Network (ANN) model for predicting biodiesel kinetic viscosity as a function of temperature and chemical compositions

An Artificial Neural Network (ANN) is a computational modeling tool which has found extensive acceptance in many disciplines for modeling complex real world problems. An ANN can model problems through learning by example, rather than by fully understanding the detailed characteristics and physics of the system. In the present study, the accuracy and predictive power of an ANN was evaluated in predicting kinetic viscosity of biodiesels over a wide range of temperatures typically encountered in diesel engine operation. In this model, temperature and chemical composition of biodiesel were used as input variables. In order to obtain the necessary data for model development, the chemical composition and temperature dependent fuel properties of ten different types of biodiesels were measured experimentally using laboratory standard testing equipments following internationally recognized testing procedures. The Neural Networks Toolbox of MatLab R2012a software was used to train, validate and simulate the ANN model on a personal computer. The network architecture was optimised following a trial and error method to obtain the best prediction of the kinematic viscosity. The predictive performance of the model was determined by calculating the absolute fraction of variance (R2), root mean squared (RMS) and maximum average error percentage (MAEP) between predicted and experimental results. This study found that ANN is highly accurate in predicting the viscosity of biodiesel and demonstrates the ability of the ANN model to find a meaningful relationship between biodiesel chemical composition and fuel properties at different temperature levels. Therefore the model developed in this study can be a useful tool in accurately predict biodiesel fuel properties instead of undertaking costly and time consuming experimental tests.

Expression, regulation and putative nutrient-sensing function of taste GPCRs in the heart

G protein-coupled receptors (GPCRs) are critical for cardiovascular physiology. Cardiac cells express >100 nonchemosensory GPCRs, indicating that important physiological and potential therapeutic targets remain to be discovered. Moreover, there is a growing appreciation that members of the large, distinct taste and odorant GPCR families have specific functions in tissues beyond the oronasal cavity, including in the brain, gastrointestinal tract and respiratory system. To date, these chemosensory GPCRs have not been systematically studied in the heart. We performed RT-qPCR taste receptor screens in rodent and human heart tissues that revealed discrete subsets of type 2 taste receptors (TAS2/Tas2) as well as Tas1r1 and Tas1r3 (comprising the umami receptor) are expressed. These taste GPCRs are present in cultured cardiac myocytes and fibroblasts, and are enriched in myocytes, which we corroborated using in situ hybridization. Tas1r1 gene-targeted mice (Tas1r1Cre/Rosa26tdRFP) strikingly recapitulated these data. In vivo taste receptor expression levels were developmentally regulated in the postnatal period. Intriguingly, several Tas2rs were upregulated in cultured rat myocytes and in mouse heart in vivo following starvation. The discovery of taste GPCRs in the heart opens an exciting new field of cardiac research. We predict that these taste receptors may function as nutrient sensors in the heart.