Silanized surfaces for in vitro studies of actomyosin function and nanotechnology applications

We have previously shown that selective heavy meromyosin (HMM) adsorption to predefined regions of nanostructured polymer resist surfaces may be used to produce a nanostructured in vitro motility assay. However, actomyosin function was of lower quality than on conventional nitrocellulose films. We have therefore studied actomyosin function on differently derivatized glass surfaces with the aim to find a substitute for the polymer resists. We have found that surfaces derivatized with trimethylchlorosilane (TMCS) were superior to all other surfaces tested, including nitrocellulose. High-quality actin filament motility was observed up to 6 days after incubation with HMM and the fraction of motile actin filaments and the velocity of smooth sliding were generally higher on TMCS than on nitrocellulose. The actomyosin function on TMCS-derivatized glass and nitrocellulose is considered in relation to roughness and hydrophobicity of these surfaces. The results suggest that TMCS is an ideal substitute for polymer resists in the nanostructured in vitro motility assay. Furthermore, TMCS derivatized glass also seems to offer several advantages over nitrocellulose for HMM adsorption in the ordinary in vitro motility assay.     

Statistical modeling of biomedical corpora: mining the Caenorhabditis Genetic Center Bibliography for genes related to life span

Background  

The statistical modeling of biomedical corpora could yield integrated, coarse-to-fine views of biological phenomena that complement discoveries made from analysis of molecular sequence and profiling data. Here, the potential of such modeling is demonstrated by examining the 5,225 free-text items in the Caenorhabditis Genetic Center (CGC) Bibliography using techniques from statistical information retrieval. Items in the CGC biomedical text corpus were modeled using the Latent Dirichlet Allocation (LDA) model. LDA is a hierarchical Bayesian model which represents a document as a random mixture over latent topics; each topic is characterized by a distribution over words.     

Characterization of JG024, a pseudomonas aeruginosa PB1-like broad host range phage under simulated infection conditions

Background  

Pseudomonas aeruginosa causes lung infections in patients suffering from the genetic disorder Cystic Fibrosis (CF). Once a chronic lung infection is established, P. aeruginosa cannot be eradicated by antibiotic treatment. Phage therapy is an alternative to treat these chronic P. aeruginosa infections. However, little is known about the factors which influence phage infection of P. aeruginosa under infection conditions and suitable broad host range phages.     

Label-free live-cell imaging with confocal Raman microscopy

Confocal Raman spectroscopy is a noninvasive alternative to established cell imaging methods because it does not require chemical fixation, the use of fluorescent markers, or genetic engineering. In particular, single live-cell, high-resolution imaging by confocal Raman microscopy is desirable because it allows further experiments concerning the individually investigated cells. However, to derive meaningful images from the spectroscopic data, one must identify cell components within the dataset. Using immunofluorescence images as a reference, we derive Raman spectral signatures by means of information measures to identify cell components such as the nucleus, the endoplasmic reticulum, the Golgi apparatus, and mitochondria. The extracted signatures allow us to generate representations equivalent to conventional (immuno)fluorescence images with more than three cell components at a time, exploiting the Raman spectral information alone.     

Radiographic joint damage in rheumatoid arthritis is associated with differences in cartilage turnover and can be predicted by serum biomarkers: an evaluation from 1 to 4 years after diagnosis

Introduction  

The objective of this study was to determine whether serum biomarkers for degradation and synthesis of the extracellular matrix of cartilage are associated with, and can predict, radiographic damage in patients with rheumatoid arthritis (RA).