Galactic Accessibility: An Introduction to Interplanetary Human Rights Law Through Crip Legal Theory

The possibilities within the realm of outer space and future space exploration have always been limitless. There has been renewed interest in space over the last decade, largely fueled by the private commercial space sector. As more and more people become interested in space and connected to the space industry, we must take care not to repeat the mistakes of the distant and recent past. Space should be accessible to all who wish to travel amongst the stars. We should not discriminate or bar individuals from going to space based on race, gender, gender identity or expression, nationality, religion, disability, financial means, or any other characteristic. We should work to build systems that are as inclusive and accessible as possible. That includes allowing folks equitable access to outer space, to their rights in space, and to the benefits of resources found in space. This Article explores a proposal for interplanetary human rights protections that are rooted in Crip Legal Theory. A “post-realist” disability perspective centered on accessibility provides an opportunity to be as inclusive as possible as humanity continues its journey of space exploration

Effects of deletion of the Streptococcus pneumoniae lipoprotein diacylglyceryl transferase gene lgt on ABC transporter function and on growth in vivo

Lipoproteins are an important class of surface associated proteins that have diverse roles and frequently are involved in the virulence of bacterial pathogens. As prolipoproteins are attached to the cell membrane by a single enzyme, prolipoprotein diacylglyceryl transferase (Lgt), deletion of the corresponding gene potentially allows the characterisation of the overall importance of lipoproteins for specific bacterial functions. We have used a Δlgt mutant strain of Streptococcus pneumoniae to investigate the effects of loss of lipoprotein attachment on cation acquisition, growth in media containing specific carbon sources, and virulence in different infection models. Immunoblots of triton X-114 extracts, flow cytometry and immuno-fluorescence microscopy confirmed the Δlgt mutant had markedly reduced lipoprotein expression on the cell surface. The Δlgt mutant had reduced growth in cation depleted medium, increased sensitivity to oxidative stress, reduced zinc uptake, and reduced intracellular levels of several cations. Doubling time of the Δlgt mutant was also increased slightly when grown in medium with glucose, raffinose and maltotriose as sole carbon sources. These multiple defects in cation and sugar ABC transporter function for the Δlgt mutant were associated with only slightly delayed growth in complete medium. However the Δlgt mutant had significantly reduced growth in blood or bronchoalveolar lavage fluid and a marked impairment in virulence in mouse models of nasopharyngeal colonisation, sepsis and pneumonia. These data suggest that for S. pneumoniae loss of surface localisation of lipoproteins has widespread effects on ABC transporter functions that collectively prevent the Δlgt mutant from establishing invasive infection

Cell-selective metabolic labeling of proteins

Metabolic labeling of proteins with the methionine surrogate azidonorleucine can be targeted exclusively to specified cells through expression of a mutant methionyl-tRNA synthetase (MetRS). In complex cellular mixtures, proteins made in cells that express the mutant synthetase can be tagged with affinity reagents (for detection or enrichment) or fluorescent dyes (for imaging). Proteins made in cells that do not express the mutant synthetase are neither labeled nor detected

Visual parameter optimisation for biomedical image processing

Background: Biomedical image processing methods require users to optimise input parameters to ensure high quality output. This presents two challenges. First, it is difficult to optimise multiple input parameters for multiple input images. Second, it is difficult to achieve an understanding of underlying algorithms, in particular, relationships between input and output. Results: We present a visualisation method that transforms users’ ability to understand algorithm behaviour by integrating input and output, and by supporting exploration of their relationships. We discuss its application to a colour deconvolution technique for stained histology images and show how it enabled a domain expert to identify suitable parameter values for the deconvolution of two types of images, and metrics to quantify deconvolution performance. It also enabled a breakthrough in understanding by invalidating an underlying assumption about the algorithm. Conclusions: The visualisation method presented here provides analysis capability for multiple inputs and outputs in biomedical image processing that is not supported by previous analysis software. The analysis supported by our method is not feasible with conventional trial-and-error approaches

Collective Animal Behavior from Bayesian Estimation and Probability Matching

Animals living in groups make movement decisions that depend, among other factors, on social interactions with other group members. Our present understanding of social rules in animal collectives is based on empirical fits to observations and we lack first-principles approaches that allow their derivation. Here we show that patterns of collective decisions can be derived from the basic ability of animals to make probabilistic estimations in the presence of uncertainty. We build a decision-making model with two stages: Bayesian estimation and probabilistic matching.
In the first stage, each animal makes a Bayesian estimation of which behavior is best to perform taking into account personal information about the environment and social information collected by observing the behaviors of other animals. In the probability matching stage, each animal chooses a behavior with a probability given by the Bayesian estimation that this behavior is the most appropriate one. This model derives very simple rules of interaction in animal collectives that depend only on two types of reliability parameters, one that each animal assigns to the other animals and another given by the quality of the non-social information. We test our model by obtaining theoretically a rich set of observed collective patterns of decisions in three-spined sticklebacks, Gasterosteus aculeatus, a shoaling fish species. The quantitative link shown between probabilistic estimation and collective rules of behavior allows a better contact with other fields such as foraging, mate selection, neurobiology and psychology, and gives predictions for experiments directly testing the relationship between estimation and collective behavior

In situ visualization and dynamics of newly synthesized proteins in rat hippocampal neurons

Protein translation has been implicated in different forms of synaptic plasticity, but direct in situ visualization of new proteins is limited to one or two proteins at a time. Here we describe a metabolic labeling approach based on incorporation of noncanonical amino acids into proteins followed by chemoselective fluorescence tagging by means of 'click chemistry'. After a brief incubation with azidohomoalanine or homopropargylglycine, a robust fluorescent signal was detected in somata and dendrites. Pulse-chase application of azidohomoalanine and homopropargylglycine allowed visualization of proteins synthesized in two sequential time periods. This technique can be used to detect changes in protein synthesis and to evaluate the fate of proteins synthesized in different cellular compartments. Moreover, using strain-promoted cycloaddition, we explored the dynamics of newly synthesized membrane proteins using single-particle tracking and quantum dots. The newly synthesized proteins showed a broad range of diffusive behaviors, as would be expected for a pool of labeled proteins that is heterogeneous

Feature selection in the reconstruction of complex network representations of spectral data

Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitud

Cluster Lenses

Clusters of galaxies are the most recently assembled, massive, bound structures in the Universe. As predicted by General Relativity, given their masses, clusters strongly deform space-time in their vicinity. Clusters act as some of the most powerful gravitational lenses in the Universe. Light rays traversing through clusters from distant sources are hence deflected, and the resulting images of these distant objects therefore appear distorted and magnified. Lensing by clusters occurs in two regimes, each with unique observational signatures. The strong lensing regime is characterized by effects readily seen by eye, namely, the production of giant arcs, multiple-images, and arclets. The weak lensing regime is characterized by small deformations in the shapes of background galaxies only detectable statistically. Cluster lenses have been exploited successfully to address several important current questions in cosmology: (i) the study of the lens(es) - understanding cluster mass distributions and issues pertaining to cluster formation and evolution, as well as constraining the nature of dark matter; (ii) the study of the lensed objects - probing the properties of the background lensed galaxy population - which is statistically at higher redshifts and of lower intrinsic luminosity thus enabling the probing of galaxy formation at the earliest times right up to the Dark Ages; and (iii) the study of the geometry of the Universe - as the strength of lensing depends on the ratios of angular diameter distances between the lens, source and observer, lens deflections are sensitive to the value of cosmological parameters and offer a powerful geometric tool to probe Dark Energy. In this review, we present the basics of cluster lensing and provide a current status report of the field.Comment: About 120 pages - Published in Open Access at: http://www.springerlink.com/content/j183018170485723/ . arXiv admin note: text overlap with arXiv:astro-ph/0504478 and arXiv:1003.3674 by other author

Постать Тараса Шевченка в рецепції Ліни Костенко

У статті розглядається поетика творення Ліною Костенко образу Кобзаря крізь призму власного "я", через пережиті відчуття поета-шістдесятника, що своєю проекцією нагадують душевні терзання великого поета.В статье рассмотрена поэтика создания Линой Костенко образа Тараса Шевченко сквозь призму собственного "я", через пережитые ощущения поэта-шестидесятника, своей проекцией напоминающие душевные терзания великого поэта.The article deals with the problem of the poetics creation by Lina Kostenko Taras Shevchenko’ image through a prism her own mind, through sensations of the poet-sixtier, by the projection reminding sincere torments the great poet is considered

Depsipeptide substrates for sortase-mediated N-terminal protein ligation

Technologies that allow the efficient chemical modification of proteins under mild conditions are widely sought after. Sortase-mediated peptide ligation provides a strategy for modifying the N or C terminus of proteins. This protocol describes the use of depsipeptide substrates (containing an ester linkage) with sortase A (SrtA) to completely modify proteins carrying a single N-terminal glycine residue under mild conditions in 4–6 h. The SrtA-mediated ligation reaction is reversible, so most labeling protocols that use this enzyme require a large excess of both substrate and sortase to produce high yields of ligation product. In contrast, switching to depsipeptide substrates effectively renders the reaction irreversible, allowing complete labeling of proteins with a small excess of substrate and catalytic quantities of sortase. Herein we describe the synthesis of depsipeptide substrates that contain an ester linkage between a threonine and glycolic acid residue and an N-terminal FITC fluorophore appended via a thiourea linkage. The synthesis of the depsipeptide substrate typically takes 2–3 d