DE-STRESS:A user-friendly web application for the evaluation of protein designs

De novo protein design is a rapidly growing field, and there are now many interesting and useful examples of designed proteins in the literature. However, most designs could be classed as failures when characterised in the lab, usually as a result of low expression, misfolding, aggregation or lack of function. This high attrition rate makes protein design unreliable and costly. It is possible that some of these failures could be caught earlier in the design process if it were quick and easy to generate information and a set of high-quality metrics regarding designs, which could be used to make reproducible and data-driven decisions about which designs to characterise experimentally. We present DE-STRESS (DEsigned STRucture Evaluation ServiceS), a web application for evaluating structural models of designed and engineered proteins. DE-STRESS has been designed to be simple, intuitive to use and responsive. It provides a wealth of information regarding designs, as well as tools to help contextualise the results and formally describe the properties that a design requires to be fit for purpose

Using Geographic Information System (Gis) Doing Cba On New Bus-Route Systems – An Empirical Example Of The City Of Linköping

Institute of Transport and Logistics Studies. Faculty of Economics and Business. The University of Sydne

Quantum properties of classical Fisher information

The Fisher information of a quantum observable is shown to be proportional to both (i) the difference of a quantum and a classical variance, thus providing a measure of nonclassicality; and (ii) the rate of entropy increase under Gaussian diffusion, thus providing a measure of robustness. The joint nonclassicality of position and momentum observables is shown to be complementary to their joint robustness in an exact sense.Comment: 16 page

A behavioural intervention increases physical activity in people with subacute spinal cord injury: a randomised trial

AbstractQuestions: For people with subacute spinal cord injury, does rehabilitation that is reinforced with the addition of a behavioural intervention to promote physical activity lead to a more active lifestyle than rehabilitation alone? Design: Randomised, controlled trial with concealed allocation, intention-to-treat analysis, and blinded assessors. Participants: Forty-five adults with subacute spinal cord injury who were undergoing inpatient rehabilitation and were dependent on a manual wheelchair. The spinal cord injuries were characterised as: tetraplegia 33%; motor complete 62%; mean time since injury 150 days (SD 74). Intervention: All participants received regular rehabilitation, including handcycle training. Only the experimental group received a behavioural intervention promoting an active lifestyle after discharge. This intervention involved 13 individual sessions delivered by a coach who was trained in motivational interviewing; it began 2 months before and ended 6 months after discharge from inpatient rehabilitation. Outcome measures: The primary outcome was physical activity, which was objectively measured with an accelerometer-based activity monitor 2 months before discharge, at discharge, and 6 and 12 months after discharge from inpatient rehabilitation. The accelerometry data were analysed as total wheeled physical activity, sedentary time and motility. Self-reported physical activity was a secondary outcome. Results: The behavioural intervention significantly increased wheeled physical activity (overall between-group difference from generalised estimating equation 21minutes per day, 95% CI 8 to 35). This difference was evident 6 months after discharge (28minutes per day, 95% CI 8 to 48) and maintained at 12 months after discharge (25minutes per day, 95% CI 1 to 50). No significant intervention effect was found for sedentary time or motility. Self-reported physical activity also significantly improved. Conclusion: The behavioural intervention was effective in eliciting a behavioural change toward a more active lifestyle among people with subacute spinal cord injury. Trial registration: NTR2424. [Nooijen CFJ, Stam H, Bergen MP, Bongers-Janssen HMH, Valent L, van Langeveld S, Twisk J, Act-Active Research Group, van den Berg-Emons RJG (2016) A behavioural intervention increases physical activity in people with subacute spinal cord injury: a randomised trial. Journal of Physiotherapy 62: 35–41

Magnetoencephalography as a Putative Biomarker for Alzheimer's Disease

Alzheimer's Disease (AD) is the most common dementia in the elderly and is estimated to affect tens of millions of people worldwide. AD is believed to have a prodromal stage lasting ten or more years. While amyloid deposits, tau filaments, and loss of brain cells are characteristics of the disease, the loss of dendritic spines and of synapses predate such changes. Popular preclinical detection strategies mainly involve cerebrospinal fluid biomarkers, magnetic resonance imaging, metabolic PET scans, and amyloid imaging. One strategy missing from this list involves neurophysiological measures, which might be more sensitive to detect alterations in brain function. The Magnetoencephalography International Consortium of Alzheimer's Disease arose out of the need to advance the use of Magnetoencephalography (MEG), as a tool in AD and pre-AD research. This paper presents a framework for using MEG in dementia research, and for short-term research priorities

Exact uncertainty relations: physical significance

The Heisenberg inequality \Delta X \Delta P \geq \hbar/2 can be replaced by an exact equality, for suitably chosen measures of position and momentum uncertainty, which is valid for all wavefunctions. The statistics of complementary observables are thus connected by an ``exact'' uncertainty relation.Comment: Latex, 24 pages. This a substantially shortened version of quant-ph/0103072, with less technical detail and focusing on physical conten

Robust Detection and Genotyping of Single Feature Polymorphisms from Gene Expression Data

It is well known that Affymetrix microarrays are widely used to predict genome-wide gene expression and genome-wide genetic polymorphisms from RNA and genomic DNA hybridization experiments, respectively. It has recently been proposed to integrate the two predictions by use of RNA microarray data only. Although the ability to detect single feature polymorphisms (SFPs) from RNA microarray data has many practical implications for genome study in both sequenced and unsequenced species, it raises enormous challenges for statistical modelling and analysis of microarray gene expression data for this objective. Several methods are proposed to predict SFPs from the gene expression profile. However, their performance is highly vulnerable to differential expression of genes. The SFPs thus predicted are eventually a reflection of differentially expressed genes rather than genuine sequence polymorphisms. To address the problem, we developed a novel statistical method to separate the binding affinity between a transcript and its targeting probe and the parameter measuring transcript abundance from perfect-match hybridization values of Affymetrix gene expression data. We implemented a Bayesian approach to detect SFPs and to genotype a segregating population at the detected SFPs. Based on analysis of three Affymetrix microarray datasets, we demonstrated that the present method confers a significantly improved robustness and accuracy in detecting the SFPs that carry genuine sequence polymorphisms when compared to its rivals in the literature. The method developed in this paper will provide experimental genomicists with advanced analytical tools for appropriate and efficient analysis of their microarray experiments and biostatisticians with insightful interpretation of Affymetrix microarray data

A Graph Algorithmic Approach to Separate Direct from Indirect Neural Interactions

Network graphs have become a popular tool to represent complex systems composed of many interacting subunits; especially in neuroscience, network graphs are increasingly used to represent and analyze functional interactions between neural sources. Interactions are often reconstructed using pairwise bivariate analyses, overlooking their multivariate nature: it is neglected that investigating the effect of one source on a target necessitates to take all other sources as potential nuisance variables into account; also combinations of sources may act jointly on a given target. Bivariate analyses produce networks that may contain spurious interactions, which reduce the interpretability of the network and its graph metrics. A truly multivariate reconstruction, however, is computationally intractable due to combinatorial explosion in the number of potential interactions. Thus, we have to resort to approximative methods to handle the intractability of multivariate interaction reconstruction, and thereby enable the use of networks in neuroscience. Here, we suggest such an approximative approach in the form of an algorithm that extends fast bivariate interaction reconstruction by identifying potentially spurious interactions post-hoc: the algorithm flags potentially spurious edges, which may then be pruned from the network. This produces a statistically conservative network approximation that is guaranteed to contain non-spurious interactions only. We describe the algorithm and present a reference implementation to test its performance. We discuss the algorithm in relation to other approximative multivariate methods and highlight suitable application scenarios. Our approach is a tractable and data-efficient way of reconstructing approximative networks of multivariate interactions. It is preferable if available data are limited or if fully multivariate approaches are computationally infeasible.Comment: 24 pages, 8 figures, published in PLOS On

Film remakes, the black sheep of translation

Film remakes have often been neglected by translation studies in favour of other forms of audiovisual translation such as subtitling and dubbing. Yet, as this article will argue, remakes are also a form of cinematic translation. Beginning with a survey of previous, ambivalent approaches to the status of remakes, it proposes that remakes are multimodal, adaptive translations: they translate the many modes of the film being remade and offer a reworking of that source text. The multimodal nature of remakes is explored through a reading of Breathless, Jim McBride's 1983 remake of Jean-Luc Godard's À bout de souffle (1959), which shows how remade films may repeat the narrative of, but differ on multiple levels from, their source films. Due to the collaborative nature of film production, remakes involve multiple agents of translation. As such, remakes offer an expanded understanding of audiovisual translation