Reciprocal regulation of A-to-I RNA editing and the vertebrate nervous system

The fine control of molecules mediating communication in the nervous system is key to adjusting neuronal signaling during development and in maintaining the stability of established networks in the face of altered sensory input. To prevent the culmination of pathological recurrent network excitation or debilitating periods of quiescence, adaptive alterations occur in the signaling molecules and ion channels that control membrane excitability and synaptic transmission. However, rather than encoding (and thus "hardwiring") modified gene copies, the nervous systems of metazoa have opted for expanding on post-transcriptional pre-mRNA splicing by altering key encoded amino acids using a conserved mechanism of A-to-I RNA editing: the enzymatic deamination of adenosine to inosine. Inosine exhibits similar base-pairing properties to guanosine with respect to tRNA codon recognition, replication by polymerases, and RNA secondary structure (i.e.,: forming-capacity). In addition to recoding within the open reading frame, adenosine deamination also occurs with high frequency throughout the non-coding transcriptome, where it affects multiple aspects of RNA metabolism and gene expression. Here, we describe the recoding function of key RNA editing targets in the mammalian central nervous system and their potential to be regulated. We will then discuss how interactions of A-to-I editing with gene expression and alternative splicing could play a wider role in regulating the neuronal transcriptome. Finally, we will highlight the increasing complexity of this multifaceted control hub by summarizing new findings from high-throughput studies. © 2013 Penn, Balik and Greger

Modelling the effects of mall atmospherics on shoppers' approach behaviors [Brunel Business School Working Paper series: special issue on marketing, volume 2, 2005]

Despite previous work, researchers still do not fully understand the mechanisms by which environmental stimuli influence emotions and affect behavior. This paper attempts to address this knowledge gap by modelling the effects of a stimulus on emotions and behavior within the context of a shopping mall and retail stores. We evaluate a stimulus-response model based on the influence of perceptions on shoppers’ moods, which in turn influence approach behaviors. A structured questionnaire survey of actual shoppers in a real mall environment (n=315) was analysed by structural equation analysis. The exemplar stimulus consisted of a Captive Audience Network (CAN or private plasma screen network) – a topic that has been little researched to date. The influence of the CAN was small but significant. The findings have implications for practitioners as even small changes in image can have a substantial effect on profitability

Memantine for prevention of migraine: a retrospective study of 60 cases.

The objective was to retrospectively characterise the efficacy of memantine as preventive therapy in a series of patients with frequent migraine. Patients in a university headache clinic completed a survey regarding their experience with memantine, and medical records were reviewed. All patients who received memantine as preventive therapy for migraine over a 15-month period were mailed surveys and consent forms for record review. Patients were treated with memantine beginning at a dose of 5 mg/day, increasing if needed by 5 mg/week up to 10 mg twice a day. The majority of patients (36 out of 54) treated with memantine for at least 2 months reported a significant reduction in estimated headache frequency, and improved function. Side effects were uncommon and generally mild. This limited retrospective case review suggests that memantine may be an effective preventive therapy for patients with frequent migraine. A prospective trial is warranted

Adaptive Optics Simulations for Siding Spring

Using an observational derived model optical turbulence profile (model-OTP) we have investigated the performance of Adaptive Optics (AO) at Siding Spring Observatory (SSO), Australia. The simulations cover the performance for AO techniques of single conjugate adaptive optics (SCAO), multi-conjugate adaptive optics (MCAO) and ground-layer adaptive optics (GLAO). The simulation results presented in this paper predict the performance of these AO techniques as applied to the Australian National University (ANU) 2.3 m and Anglo-Australian Telescope (AAT) 3.9 m telescopes for astronomical wavelength bands J, H and K. The results indicate that AO performance is best for the longer wavelengths (K-band) and in the best seeing conditions (sub 1-arcsecond). The most promising results are found for GLAO simulations (field of view of 180 arcsecs), with the field RMS for encircled energy 50% diameter (EE50d) being uniform and minimally affected by the free-atmosphere turbulence. The GLAO performance is reasonably good over the wavelength bands of J, H and K. The GLAO field mean of EE50d is between 200 mas to 800 mas, which is a noticeable improvement compared to the nominal astronomical seeing (870 to 1700 mas).Comment: 15 pages; accepted for publication in PAS

Flowing ConvNets for Human Pose Estimation in Videos

The objective of this work is human pose estimation in videos, where multiple frames are available. We investigate a ConvNet architecture that is able to benefit from temporal context by combining information across the multiple frames using optical flow. To this end we propose a network architecture with the following novelties: (i) a deeper network than previously investigated for regressing heatmaps; (ii) spatial fusion layers that learn an implicit spatial model; (iii) optical flow is used to align heatmap predictions from neighbouring frames; and (iv) a final parametric pooling layer which learns to combine the aligned heatmaps into a pooled confidence map. We show that this architecture outperforms a number of others, including one that uses optical flow solely at the input layers, one that regresses joint coordinates directly, and one that predicts heatmaps without spatial fusion. The new architecture outperforms the state of the art by a large margin on three video pose estimation datasets, including the very challenging Poses in the Wild dataset, and outperforms other deep methods that don't use a graphical model on the single-image FLIC benchmark (and also Chen & Yuille and Tompson et al. in the high precision region).Comment: ICCV'1