An inverse modeling procedure to determine particle growth and nucleation rates from measured aerosol size distributions

Classical nucleation theory is unable to explain the ubiquity of nucleation events observed in the atmosphere. This shows a need for an empirical determination of the nucleation rate. Here we present a novel inverse modeling procedure to determine particle nucleation and growth rates based on consecutive measurements of the aerosol size distribution. The particle growth rate is determined by regression analysis of the measured change in the aerosol size distribution over time, taking into account the effects of processes such as coagulation, deposition and/or dilution. This allows the growth rate to be determined with a higher time-resolution than can be deduced from inspecting contour plots ('banana-plots''). Knowing the growth rate as a function of time enables the evaluation of the time of nucleation of measured particles of a certain size. The nucleation rate is then obtained by integrating the particle losses from time of measurement to time of nucleation. The regression analysis can also be used to determine or verify the optimum value of other parameters of interest, such as the wall loss or coagulation rate constants. As an example, the method is applied to smog chamber measurements. This program offers a powerful interpretive tool to study empirical aerosol population dynamics in general, and nucleation and growth in particular

Unbiased protein association study on the public human proteome reveals biological connections between co-occurring protein pairs

Mass-spectrometry-based, high-throughput proteomics experiments produce large amounts of data. While typically acquired to answer specific biological questions, these data can also be reused in orthogonal wayS to reveal new biological knowledge. We here present a novel method for such orthogonal data reuse of public proteomics data. Our method elucidates biological relationships between proteins based on the co-occurrence of these proteins across human experiments in the PRIDE database. The majority of the significantly co-occurring protein pairs that were detected by our method have been successfully mapped to existing biological knowledge. The validity of our novel method is substantiated by the extremely few pairs that can be mapped to existing knowledge based on random associations between the same set of proteins. Moreover, using literature searches and the STRING database, we were able to derive meaningful biological associations for unannotated protein pairs that were detected using our method, further illustrating that as-yet unknown associations present highly interesting targets for follow-up analysis

Volume-coupling in isotachophoresis

A new device for isotachophoretic analyses is described in which pre-separation columns with different inner diameters can simply be exchanged (so-called volume-coupling). The most important advantages compared to conventional equipment having a uniform column diameter are: the low end-voltages needed, a ready optimization of analysis time for a particular problem and the possibility of applying terminators with very low effective mobility. The application of Araldite® allows the use of non-aqueous solvents

sORFs.org : a repository of small ORFs identified by ribosome profiling

With the advent of ribosome profiling, a next generation sequencing technique providing a ‘snap-shot’ of translated mRNA in a cell, many short open reading frames (sORFs) with were identified. Follow-up studies revealed the existence of functional peptides, so-called micropeptides, translated from these ‘sORFs’, indicating a new class of bio-active peptides. Over the last few years, several micropeptides exhibiting important cellular functions were discovered. However, ribosome occupancy does not necessarily imply an actual function of the translated peptide, leading to the development of various tools assessing the coding potential of sORFs. Here, we introduce sORFs.org (http://www.sorfs.org), a novel database for sORFs identified using ribosome profiling. Starting from ribosome profiling, sORFs.org identifies sORFs, incorporates state-of-the-art tools and metrics and stores results in a public database. Two query interfaces are provided, a default one enabling quick lookup of sORFs and a BioMart interface providing advanced query and export possibilities. At present, sORFs.org harbors 263 354 sORFs that demonstrate ribosome occupancy, originating from three different cell lines: HCT116 (human), E14_mESC (mouse) and S2 (fruit fly). sORFs.org aims to provide an extensive sORFs database accessible to researchers with limited bioinformatics knowledge, thus enabling easy integration into personal projects

At the heart of the matter:imaging cardiac metabolism in insulin resistance

Overweight increases the risk of cancer, fatty liver disease, cardiovascular disease, and the development of diabetes. It is known that diabetes can lead to heart failure (diabetic cardiomyopathy). In prediabetes, a pre-stage of diabetes, the metabolism of the heart and therefore heart function may already be hampered. Using imaging techniques, changes in cardiac metabolism, energy status and cardiac function can be analyzed in patients with prediabetes. Although the energy status (PCr/ATP ratio) measured by a 31P-MRS scan did not appear to reflect mitochondrial function, energy status was related to cardiac function in prediabetes. Thereby, energy status was found to be already reduced in prediabetes, which proves that the heart in patients with prediabetes is already vulnerable to develop heart failure. It was also shown in this thesis that medication can influence the metabolism of the heart in prediabetes, without adverse effects on heart function or insulin sensitivity