Small molecule absorption by PDMS in the context of drug response bioassays

Stem cells & developmental biolog

Small molecule absorption by PDMS in the context of drug response bioassays

The polymer polydimethylsiloxane (PDMS) is widely used to build microfluidic devices compatible with cell culture. Whilst convenient in manufacture, PDMS has the disadvantage that it can absorb small molecules such as drugs. In microfluidic devices like "Organs-on-Chip", designed to examine cell behavior and test the effects of drugs, this might impact drug bioavailability. Here we developed an assay to compare the absorption of a test set of four cardiac drugs by PDMS based on measuring the residual non-absorbed compound by High Pressure Liquid Chromatography (HPLC). We showed that absorption was variable and time dependent and not determined exclusively by hydrophobicity as claimed previously. We demonstrated that two commercially available lipophilic coatings and the presence of cells affected absorption. The use of lipophilic coatings may be useful in preventing small molecule absorption by PDMS. (C) 2016 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license

Beyond altruism: British football and charity, 1877-1914

Football charity matches and tournaments played a significant part in the development of the sport in Britain, overlapping the era of friendly games and the advent of competitive leagues. The football community prided itself on its contributions to charity, raising more money than any other sport before 1914, and stakeholders within the game – associations, clubs, players and patrons – gained considerable kudos for this perceived altruism. However, this paper will demonstrate that amounts donated, though welcome, were relatively minor sources of revenue for both institutions and individuals, and that the charity match became less important to clubs in a professional, and increasingly commercial, era

Fitting the integrated Spectral Energy Distributions of Galaxies

Fitting the spectral energy distributions (SEDs) of galaxies is an almost universally used technique that has matured significantly in the last decade. Model predictions and fitting procedures have improved significantly over this time, attempting to keep up with the vastly increased volume and quality of available data. We review here the field of SED fitting, describing the modelling of ultraviolet to infrared galaxy SEDs, the creation of multiwavelength data sets, and the methods used to fit model SEDs to observed galaxy data sets. We touch upon the achievements and challenges in the major ingredients of SED fitting, with a special emphasis on describing the interplay between the quality of the available data, the quality of the available models, and the best fitting technique to use in order to obtain a realistic measurement as well as realistic uncertainties. We conclude that SED fitting can be used effectively to derive a range of physical properties of galaxies, such as redshift, stellar masses, star formation rates, dust masses, and metallicities, with care taken not to over-interpret the available data. Yet there still exist many issues such as estimating the age of the oldest stars in a galaxy, finer details ofdust properties and dust-star geometry, and the influences of poorly understood, luminous stellar types and phases. The challenge for the coming years will be to improve both the models and the observational data sets to resolve these uncertainties. The present review will be made available on an interactive, moderated web page (sedfitting.org), where the community can access and change the text. The intention is to expand the text and keep it up to date over the coming years.Comment: 54 pages, 26 figures, Accepted for publication in Astrophysics & Space Scienc

Consensus Statement on next-generation-sequencing-based diagnostic testing of hereditary phaeochromocytomas and paragangliomas

Genome Instability and Cance

Large-scale discovery of novel genetic causes of developmental disorders

Despite three decades of successful, predominantly phenotype-driven discovery of the genetic causes of monogenic disorders1, up to half of children with severe developmental disorders of probable genetic origin remain without a genetic diagnosis. Particularly challenging are those disorders rare enough to have eluded recognition as a discrete clinical entity, those with highly variable clinical manifestations, and those that are difficult to distinguish from other, very similar, disorders. Here we demonstrate the power of using an unbiased genotype-driven approach2 to identify subsets of patients with similar disorders. By studying 1,133 children with severe, undiagnosed developmental disorders, and their parents, using a combination of exome sequencing3,4,5,6,7,8,9,10,11 and array-based detection of chromosomal rearrangements, we discovered 12 novel genes associated with developmental disorders. These newly implicated genes increase by 10% (from 28% to 31%) the proportion of children that could be diagnosed. Clustering of missense mutations in six of these newly implicated genes suggests that normal development is being perturbed by an activating or dominant-negative mechanism. Our findings demonstrate the value of adopting a comprehensive strategy, both genome-wide and nationwide, to elucidate the underlying causes of rare genetic disorders

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

LASER-RAMAN STUDY OF THE STRUCTURE OF SILVER DOPED As40S60 GLASS

The Raman spectra of Ag doped a-As2S3 glass with compositions along the pseudo-binary line As2S3-Ag2S is presented. Small amounts of Ag have little effect on the structure of a-As2S3 whereas glasses containing larger amounts (> 21 atm %) contain structural units found in corresponding crystalline forms

SILVER IN PHOTODOPED ARSENIC SULFIDE FILMS : AN EXAFS STUDY

Nous avons mesurés le K-edge EXAFS de l'argent pour un nombre de films du sulfure d 'arsenic photodopé et déterminés la distance de coordination d'argent à soufre. C'est très semblable à la verre Ag25As25S50, comme le XANES. L'on a observé la séparation des phases dans quelques films par l'apparence d'une seconde couche dans la transformation de Fourier.We have measured the silver k-edge EXAFS for a number of photodoped arsenic sulphide films and determined the silver-sulphur coordination distance. This is very similar to the Ag25As25S50 glass, as is the near-edge region. Phase separation has been observed in some films by the appearance of a second shell in the Fourier transform