Discerning Aggregation in Homogeneous Ensembles: A General Description of Photon Counting Spectroscopy in Diffusing Systems

In order to discern aggregation in solutions, we present a quantum mechanical analog of the photon statistics from fluorescent molecules diffusing through a focused beam. A generating functional is developed to fully describe the experimental physical system as well as the statistics. Histograms of the measured time delay between photon counts are fit by an analytical solution describing the static as well as diffusing regimes. To determine empirical fitting parameters, fluorescence correlation spectroscopy is used in parallel to the photon counting. For expedient analysis, we find that the distribution's deviation from a single Poisson shows a difference between two single fluor moments or a double fluor aggregate of the same total intensities. Initial studies were performed on fixed-state aggregates limited to dimerization. However preliminary results on reactive species suggest that the method can be used to characterize any aggregating system.Comment: 30 pages, 5 figure

Proinsulin C-peptide elicits disaggregation of insulin resulting in enhanced physiological insulin effects

Using surface plasmon resonance (SPR) and electrospray mass spectrometry (ESI-MS), proinsulin C-peptide was found to influence insulin-insulin interactions. In SPR with chip-bound insulin, C-peptide mixed with analyte insulin increased the binding, while alone C-peptide did not. A control peptide with the same residues in random sequence had little effect. In ESI-MS, C-peptide lowered the presence of insulin hexamer. The data suggest that C-peptide promotes insulin disaggregation. Insulin/insulin oligomer μM dissociation constants were determined. Compatible with these findings, type 1 diabetic patients receiving insulin and C-peptide developed 66% more stimulation of glucose metabolism than when given insulin alone. A role of C-peptide in promoting insulin disaggregation may be important physiologically during exocytosis of pancreatic β-cell secretory granulae and pharmacologically at insulin injection sites. It is compatible with the normal co-release of C-peptide and insulin and may contribute to the beneficial effect of C-peptide and insulin replacement in type 1 diabetics

Uptake and depuration of gold nanoparticles in Daphnia magna

This study presents a series of short-term studies (total duration 48 h) of uptake and depuration of engineered nanoparticles (ENP) in neonate Daphnia magna. Gold nanoparticles (Au NP) were used to study the influence of size, stabilizing agent and feeding on uptake and depuration kinetics and animal body burdens. 10 and 30 nm Au NP with different stabilizing agents [citrate (CIT) and mercaptoundecanoic acid (MUDA)] were tested in concentrations around 0.5 mg Au/L. Fast initial uptake was observed for all studied Au NP, with CIT stabilized Au NP showing similar rates independent of size and MUDA showing increased uptake for the smaller Au NP (MUDA 10 nm > CIT 10 nm, 30 nm > MUDA 30 nm). However, upon transfer to clean media no clear trend on depuration rates was found in terms of stabilizing agent or size. Independent of stabilizing agent, 10 nm Au NP resulted in higher residual whole-animal body burdens after 24 h depuration than 30 nm Au NP with residual body burdens about one order of magnitude higher of animals exposed to 10 nm Au NP. The presence of food (P. subcapitata) did not significantly affect the body burden after 24 h of exposure, but depuration was increased. While food addition is not necessary to ensure D. magna survival in the presented short-term test design, the influence of food on uptake and depuration kinetics is essential to consider in long term studies of ENP where food addition is necessary. This study demonstrates the feasibility of a short-term test design to assess the uptake and depuration of ENP in D. magna. The findings underlines that the assumptions behind the traditional way of quantifying bioconcentration are not fulfilled when ENPs are studied.Peer reviewed: YesNRC publication: Ye

C-Peptide Increases Na,K-ATPase Expression via PKC- and MAP Kinase-Dependent Activation of Transcription Factor ZEB in Human Renal Tubular Cells

Replacement of proinsulin C-peptide in type 1 diabetes ameliorates nerve and kidney dysfunction, conditions which are associated with a decrease in Na,K-ATPase activity. We determined the molecular mechanism by which long term exposure to C-peptide stimulates Na,K-ATPase expression and activity in primary human renal tubular cells (HRTC) in control and hyperglycemic conditions.HRTC were cultured from the outer cortex obtained from patients undergoing elective nephrectomy. Ouabain-sensitive rubidium ((86)Rb(+)) uptake and Na,K-ATPase activity were determined. Abundance of Na,K-ATPase was determined by Western blotting in intact cells or isolated basolateral membranes (BLM). DNA binding activity was determined by electrical mobility shift assay (EMSA). Culturing of HRTCs for 5 days with 1 nM, but not 10 nM of human C-peptide leads to increase in Na,K-ATPase α(1)-subunit protein expression, accompanied with increase in (86)Rb(+) uptake, both in normal- and hyperglycemic conditions. Na,K-ATPase α(1)-subunit expression and Na,K-ATPase activity were reduced in BLM isolated from cells cultured in presence of high glucose. Exposure to1 nM, but not 10 nM of C-peptide increased PKCε phosphorylation as well as phosphorylation and abundance of nuclear ERK1/2 regardless of glucose concentration. Exposure to 1 nM of C-peptide increased DNA binding activity of transcription factor ZEB (AREB6), concomitant with Na,K-ATPase α(1)-subunit mRNA expression. Effects of 1 nM C-peptide on Na,K-ATPase α(1)-subunit expression and/or ZEB DNA binding activity in HRTC were abolished by incubation with PKC or MEK1/2 inhibitors and ZEB siRNA silencing.Despite activation of ERK1/2 and PKC by hyperglycemia, a distinct pool of PKCs and ERK1/2 is involved in regulation of Na,K-ATPase expression and activity by C-peptide. Most likely C-peptide stimulates sodium pump expression via activation of ZEB, a transcription factor that has not been previously implicated in C-peptide-mediated signaling. Importantly, only physiological concentrations of C-peptide elicit this effect

How does community context influence coalitions in the formation stage? a multiple case study based on the Community Coalition Action Theory

<p>Abstract</p> <p>Background</p> <p>Community coalitions are rooted in complex and dynamic community systems. Despite recognition that environmental factors affect coalition behavior, few studies have examined how community context impacts coalition formation. Using the Community Coalition Action theory as an organizing framework, the current study employs multiple case study methodology to examine how five domains of community context affect coalitions in the formation stage of coalition development. Domains are history of collaboration, geography, community demographics and economic conditions, community politics and history, and community norms and values.</p> <p>Methods</p> <p>Data were from 8 sites that participated in an evaluation of a healthy cities and communities initiative in California. Twenty-three focus groups were conducted with coalition members, and 76 semi-structured interviews were conducted with local coordinators and coalition leaders. Cross-site analyses were conducted to identify the ways contextual domains influenced selection of the lead agency, coalition membership, staffing and leadership, and coalition processes and structures.</p> <p>Results</p> <p>History of collaboration influenced all four coalition factors examined, from lead agency selection to coalition structure. Geography influenced coalition formation largely through membership and staffing, whereas the demographic and economic makeup of the community had an impact on coalition membership, staffing, and infrastructure for coalition processes. The influence of community politics, history, norms and values was most noticeable on coalition membership.</p> <p>Conclusions</p> <p>Findings contribute to an ecologic and theory-based understanding of the range of ways community context influences coalitions in their formative stage.</p

Proposed nomenclature for Pseudallescheria, Scedosporium and related genera

As a result of fundamental changes in the International Code of Nomenclature on the use of separate names for sexual and asexual stages of fungi, generic names of many groups should be reconsidered. Members of the ECMM/ISHAM working group on Pseudallescheria/Scedosporium infections herein advocate a novel nomenclature for genera and species in Pseudallescheria, Scedosporium and allied taxa. The generic names Parascedosporium, Lomentospora, Petriella, Petriellopsis, and Scedosporium are proposed for a lineage within Microascaceae with mostly Scedosporium anamorphs producing slimy, annellidic conidia. Considering that Scedosporium has priority over Pseudallescheria and that Scedosporium prolificans is phylogenetically distinct from the other Scedosporium species, some name changes are proposed. Pseudallescheria minutispora and Petriellidium desertorum are renamed as Scedosporium minutisporum and S. desertorum, respectively. Scedosporium prolificans is renamed as Lomentospora prolificans

Cellular mechanisms by which proinsulin C-peptide prevents insulin-induced neointima formation in human saphenous vein

AIMS/HYPOTHESIS: Endothelial cells (ECs) and smooth muscle cells (SMCs) play key roles in the development of intimal hyperplasia in saphenous vein (SV) bypass grafts. In diabetic patients, insulin administration controls hyperglycaemia but cardiovascular complications remain. Insulin is synthesised as a pro-peptide, from which C-peptide is cleaved and released into the circulation with insulin; exogenous insulin lacks C-peptide. Here we investigate modulation of human SV neointima formation and SV-EC and SV-SMC function by insulin and C-peptide. METHODS: Effects of insulin and C-peptide on neointima formation (organ cultures), EC and SMC proliferation (cell counting), EC migration (scratch wound), SMC migration (Boyden chamber) and signalling (immunoblotting) were examined. A real-time RT-PCR array identified insulin-responsive genes, and results were confirmed by real-time RT-PCR. Targeted gene silencing (siRNA) was used to assess functional relevance. RESULTS: Insulin (100 nmol/l) augmented SV neointimal thickening (70% increase, 14 days), SMC proliferation (55% increase, 7 days) and migration (150% increase, 6 h); effects were abrogated by 10 nmol/l C-peptide. C-peptide did not affect insulin-induced Akt or extracellular signal-regulated kinase signalling (15 min), but array data and gene silencing implicated sterol regulatory element binding transcription factor 1 (SREBF1). Insulin (1-100 nmol/l) did not modify EC proliferation or migration, whereas 10 nmol/l C-peptide stimulated EC proliferation by 40% (5 days). CONCLUSIONS/INTERPRETATION: Our data support a causative role for insulin in human SV neointima formation with a novel counter-regulatory effect of proinsulin C-peptide. Thus, C-peptide can limit the detrimental effects of insulin on SMC function. Co-supplementing insulin therapy with C-peptide could improve therapy in insulin-treated patients

Diffusion in Model Networks as Studied by NMR and Fluorescence Correlation Spectroscopy

We have studied the diffusion of small solvent molecules (octane) and larger hydrophobic dye probes in octane-swollen poly(dimethyl siloxane) linear-chain solutions and end-linked model networks, using pulsed-gradient nuclear magnetic resonance (NMR) and fluorescence correlation spectroscopy (FCS), respectively, focusing on diffusion in the bulk polymer up to the equilibrium degree of swelling of the networks, that is, 4.8 at most. The combination of these results allows for new conclusions on the feasibility of different theories describing probe diffusion in concentrated polymer systems. While octane diffusion shows no cross-link dependence, the larger dyes are increasingly restricted by fixed chemical meshes. The simple Fujita free-volume theory proved most feasible to describe probe diffusion in linear long-chain solutions with realistic parameters, while better fits were obtained assuming a stretched exponential dependence on concentration. Importantly, we have analyzed the cross-link specific effect on probe diffusion independently of any specific model by comparing the best-fit interpolation of the solution data with the diffusion in the networks. The most reasonable description is obtained by assuming that the cross-link effect is additive in the effective friction coefficient of the probes. The concentration dependences as well as the data compared at the equilibrium degrees of swelling indicate that swelling heterogeneities and diffusant shape have a substantial influence on small-molecule diffusion in networks.

HLA Genes, Islet Autoantibodies and Residual C-Peptide at the Clinical Onset of Type 1 Diabetes Mellitus and the Risk of Retinopathy 15 Years Later

HLA genes, islet autoantibodies and residual C-peptide were studied to determine the independent association of each exposure with diabetic retinopathy (DR), 15 years after the clinical onset of type 1 diabetes in 15-34 year old individuals.The cohort was identified in 1992 and 1993 by the Diabetes Incidence Study in Sweden (DISS), which investigates incident cases of diabetes for patients between 15 and 34 years of age. Blood samples at diagnosis were analyzed to determine HLA genotype, islet autoantibodies and serum C-peptide. In 2009, fundus photographs were obtained from patient records. Study measures were supplemented with data from the Swedish National Diabetes Registry.The prevalence of DR was 60.2% (148/246). Autoantibodies against the 65 kD isoform of glutamate decarboxylase (GADA) at the onset of clinical diabetes increased the risk of DR 15 years later, relative risk 1.12 for each 100 WHO units/ml, [95% CI 1.02 to 1.23]. This equates to risk estimates of 1.27, [95% CI 1.04 to 1.62] and 1.43, [95% CI 1.06 to 1.94] for participants in the highest 25(th) (GADA>233 WHO units/ml) and 5(th) percentile (GADA>319 WHO units/ml) of GADA, respectively. These were adjusted for duration of diabetes, HbA(1c), treated hypertension, sex, age at diagnosis, HLA and C-peptide. Islet cell autoantibodies, insulinoma-antigen 2 autoantibodies, residual C-peptide and the type 1 diabetes associated haplotypes DQ2, DQ8 and DQ6 were not associated with DR.Increased levels of GADA at the onset of type 1 diabetes were associated with DR 15 years later. These results, if confirmed, could provide additional insights into the pathogenesis of the most common microvascular complication of diabetes and lead to better risk stratification for both patient screenings and DR treatment trials

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p