An inner ring and the micro lensing toward the Bulge

All current Bulge-Disk models for the inner Galaxy fall short of reproducing self-consistently the observed micro-lensing optical depth by a factor of two ($> 2\sigma$). We show that the least mass-consuming way to increase the optical depth is to add density roughly half-way the observer and the highest micro-lensing-source density. We present evidence for the existence of such a density structure in the Galaxy: an inner ring, a standard feature of barred galaxies. Judging from data on similar rings in external galaxies, an inner ring can contribute more than 50% of a pure Bulge-Disk model to the micro-lensing optical depth. We may thus eliminate the need for a small viewing angle of the Bar. The influence of an inner ring on the event-duration distribution, for realistic viewing angles, would be to increase the fraction of long-duration events toward Baade's window. The longest events are expected toward the negative-longitude tangent point at $\ell\sim$ -22\degr . A properly sampled event-duration distribution toward this tangent point would provide essential information about viewing angle and elongation of the over-all density distribution in the inner Galaxy.Comment: 9 pages, 7(15) figs, LaTeX, AJ (accepted

tRNA‐guanine transglycosylase from Escherichia coli: recognition of full‐length ‘queuine‐cognate' tRNAs

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/117048/1/feb2s0014579398008011.pd

Using virtual experiences of older age: exploring pedagogical and psychological experiences of students

Fostering intergenerational empathy is vital for creating an age-friendly society and an important aim for Sport and Exercise Science (SES) degree programmes given that graduates are increasingly entering the healthcare workforce supporting older adults (British Association of Sport and Exercise Sciences; BASES, 2018). Interventions to challenge negative stereotypes of ageing, generate empathy for older adults, and help University students gain experience of ‘being’ an older person have demonstrated mixed success (e.g., Prior & Sargent-Cox, 2014). Recent studies indicate the promise of virtual reality in this context but do not present conclusive evidence for this effect (e.g., Banakou, Kishore, & Slater, 2018). Thus this study explored SES students’ responses to virtual experiences of being an older person in a workshop. Participants completed the “Become Victor” module of the FrailtySIM© application, based on real life experience of an older person in their home, and, a University-developed immersive experience of being an older person in a social situation. Fifty-two students completed questionnaires about their experience of “Become Victor” and 15 students were interviewed (12 in 2 focus groups, 3 individually) about their experiences of both simulations. Data indicated that “Become Victor” offered students insight into being an older person that was “eye-opening” and realistic but frustrating and stressful. The social situation effectively simulated the isolation felt by some older people to an extent, but needed to be more interactive. Students felt that the simulations were important for contextualising previously delivered lecture material on older adults. Future workshop iterations will integrate lecture and virtual experiences using opportunities for student reflection on their experiences

BSL-1K: Scaling up co-articulated sign language recognition using mouthing cues

Recent progress in fine-grained gesture and action classification, and machine translation, point to the possibility of automated sign language recognition becoming a reality. A key stumbling block in making progress towards this goal is a lack of appropriate training data, stemming from the high complexity of sign annotation and a limited supply of qualified annotators. In this work, we introduce a new scalable approach to data collection for sign recognition in continuous videos. We make use of weakly-aligned subtitles for broadcast footage together with a keyword spotting method to automatically localise sign-instances for a vocabulary of 1,000 signs in 1,000 hours of video. We make the following contributions: (1) We show how to use mouthing cues from signers to obtain high-quality annotations from video data - the result is the BSL-1K dataset, a collection of British Sign Language (BSL) signs of unprecedented scale; (2) We show that we can use BSL-1K to train strong sign recognition models for co-articulated signs in BSL and that these models additionally form excellent pretraining for other sign languages and benchmarks - we exceed the state of the art on both the MSASL and WLASL benchmarks. Finally, (3) we propose new large-scale evaluation sets for the tasks of sign recognition and sign spotting and provide baselines which we hope will serve to stimulate research in this area.Comment: Appears in: European Conference on Computer Vision 2020 (ECCV 2020). 28 page

Dynamics of the Galactic Bulge using Planetary Nebulae

Evidence for a bar at the center of the Milky Way triggered a renewed enthusiasm for dynamical modelling of the Galactic bar-bulge. Our goal is to compare the kinematics of a sample of tracers, planetary nebulae, widely distributed over the bulge with the corresponding kinematics for a range of models of the inner Galaxy. Three of these models are N-body barred systems arising from the instabilities of a stellar disk (Sellwood, Fux and Kalnajs), and one is a Schwarzschild system constructed to represent the 3D distribution of the COBE/DIRBE near-IR light and then evolved as an N-body system for a few dynamical times (Zhao). For the comparison of our data with the models, we use a new technique developed by Saha (1998). The procedure finds the parameters of each model, i.e. the solar galactocentric distance R_o in model units, the orientation angle phi, the velocity scale (in km/s per model unit), and the solar tangential velocity which best fit the data.Comment: 48 pages (Latex), 30 figures (PS), accepted for pub. in A

Translational Selection Is Ubiquitous in Prokaryotes

Codon usage bias in prokaryotic genomes is largely a consequence of background substitution patterns in DNA, but highly expressed genes may show a preference towards codons that enable more efficient and/or accurate translation. We introduce a novel approach based on supervised machine learning that detects effects of translational selection on genes, while controlling for local variation in nucleotide substitution patterns represented as sequence composition of intergenic DNA. A cornerstone of our method is a Random Forest classifier that outperformed previous distance measure-based approaches, such as the codon adaptation index, in the task of discerning the (highly expressed) ribosomal protein genes by their codon frequencies. Unlike previous reports, we show evidence that translational selection in prokaryotes is practically universal: in 460 of 461 examined microbial genomes, we find that a subset of genes shows a higher codon usage similarity to the ribosomal proteins than would be expected from the local sequence composition. These genes constitute a substantial part of the genome—between 5% and 33%, depending on genome size—while also exhibiting higher experimentally measured mRNA abundances and tending toward codons that match tRNA anticodons by canonical base pairing. Certain gene functional categories are generally enriched with, or depleted of codon-optimized genes, the trends of enrichment/depletion being conserved between Archaea and Bacteria. Prominent exceptions from these trends might indicate genes with alternative physiological roles; we speculate on specific examples related to detoxication of oxygen radicals and ammonia and to possible misannotations of asparaginyl–tRNA synthetases. Since the presence of codon optimizations on genes is a valid proxy for expression levels in fully sequenced genomes, we provide an example of an “adaptome” by highlighting gene functions with expression levels elevated specifically in thermophilic Bacteria and Archaea

Kissing G Domains of MnmE Monitored by X-Ray Crystallography and Pulse Electron Paramagnetic Resonance Spectroscopy

The authors of this research article demonstrate the nature of the conformational changes MnmE was previously suggested to undergo during its GTPase cycle, and show the nucleotide-dependent dynamic movements of the G domains around two swivel positions relative to the rest of the protein. These movements are of crucial importance for understanding the mechanistic principles of this GAD

tRNA structural and functional changes induced by oxidative stress

Oxidatively damaged biomolecules impair cellular functions and contribute to the pathology of a variety of diseases. RNA is also attacked by reactive oxygen species, and oxidized RNA is increasingly recognized as an important contributor to neurodegenerative complications in humans. Recently, evidence has accumulated supporting the notion that tRNA is involved in cellular responses to various stress conditions. This review focuses on the intriguing consequences of oxidative modification of tRNA at the structural and functional level

Effect of Correlated tRNA Abundances on Translation Errors and Evolution of Codon Usage Bias

Despite the fact that tRNA abundances are thought to play a major role in determining translation error rates, their distribution across the genetic code and the resulting implications have received little attention. In general, studies of codon usage bias (CUB) assume that codons with higher tRNA abundance have lower missense error rates. Using a model of protein translation based on tRNA competition and intra-ribosomal kinetics, we show that this assumption can be violated when tRNA abundances are positively correlated across the genetic code. Examining the distribution of tRNA abundances across 73 bacterial genomes from 20 different genera, we find a consistent positive correlation between tRNA abundances across the genetic code. This work challenges one of the fundamental assumptions made in over 30 years of research on CUB that codons with higher tRNA abundances have lower missense error rates and that missense errors are the primary selective force responsible for CUB

THUMP from archaeal tRNA:m(2)(2)G10 methyltransferase, a genuine autonomously folding domain

The tRNA:m(2)(2)G10 methyltransferase of Pyrococus abyssi (PAB1283, a member of COG1041) catalyzes the N(2),N(2)-dimethylation of guanosine at position 10 in tRNA. Boundaries of its THUMP (THioUridine synthases, RNA Methyltransferases and Pseudo-uridine synthases)—containing N-terminal domain [1–152] and C-terminal catalytic domain [157–329] were assessed by trypsin limited proteolysis. An inter-domain flexible region of at least six residues was revealed. The N-terminal domain was then produced as a standalone protein (THUMPα) and further characterized. This autonomously folded unit exhibits very low affinity for tRNA. Using protein fold-recognition (FR) methods, we identified the similarity between THUMPα and a putative RNA-recognition module observed in the crystal structure of another THUMP-containing protein (ThiI thiolase of Bacillus anthracis). A comparative model of THUMPα structure was generated, which fulfills experimentally defined restraints, i.e. chemical modification of surface exposed residues assessed by mass spectrometry, and identification of an intramolecular disulfide bridge. A model of the whole PAB1283 enzyme docked onto its tRNA(Asp) substrate suggests that the THUMP module specifically takes support on the co-axially stacked helices of T-arm and acceptor stem of tRNA and, together with the catalytic domain, screw-clamp structured tRNA. We propose that this mode of interactions may be common to other THUMP-containing enzymes that specifically modify nucleotides in the 3D-core of tRNA