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

Prevalence of inappropriate medication using Beers criteria in Japanese long-term care facilities

BACKGROUND: The prevalence and risk factors of potentially inappropriate medication use among the elderly patients have been studied in various countries, but because of the difficulty of obtaining data on patient characteristics and medications they have not been studied in Japan. METHODS: We conducted a retrospective cross-sectional study in 17 Japanese long-term care (LTC) facilities by collecting data from the comprehensive MDS assessment forms for 1669 patients aged 65 years and over who were assessed between January and July of 2002. Potentially inappropriate medications were identified on the basis of the 2003 Beers criteria. RESULTS: The patients in the sample were similar in terms of demographic characteristics to those in the national survey. Our study revealed that 356 (21.1%) of the patients were treated with potentially inappropriate medication independent of disease or condition. The most commonly inappropriately prescribed medication was ticlopidine, which had been prescribed for 107 patients (6.3%). There were 300 (18.0%) patients treated with at least 1 inappropriate medication dependent on the disease or condition. The highest prevalence of inappropriate medication use dependent on the disease or condition was found in patients with chronic constipation. Multiple logistic regression analysis revealed psychotropic drug use (OR = 1.511), medication cost of per day (OR = 1.173), number of medications (OR = 1.140), and age (OR = 0.981) as factors related to inappropriate medication use independent of disease or condition. Neither patient characteristics nor facility characteristics emerged as predictors of inappropriate prescription. CONCLUSION: The prevalence and predictors of inappropriate medication use in Japanese LTC facilities were similar to those in other countries

Double trouble at high density::Cross-level test of ressource-related adaptive plasticity and crowding-related fitness.

Population size is often regulated by negative feedback between population density and individual fitness. At high population densities, animals run into double trouble: they might concurrently suffer from overexploitation of resources and also from negative interference among individuals regardless of resource availability, referred to as crowding. Animals are able to adapt to resource shortages by exhibiting a repertoire of life history and physiological plasticities. In addition to resource-related plasticity, crowding might lead to reduced fitness, with consequences for individual life history. We explored how different mechanisms behind resource-related plasticity and crowding-related fitness act independently or together, using the water flea Daphnia magna as a case study. For testing hypotheses related to mechanisms of plasticity and crowding stress across different biological levels, we used an individual-based population model that is based on dynamic energy budget theory. Each of the hypotheses, represented by a sub-model, is based on specific assumptions on how the uptake and allocation of energy are altered under conditions of resource shortage or crowding. For cross-level testing of different hypotheses, we explored how well the sub-models fit individual level data and also how well they predict population dynamics under different conditions of resource availability. Only operating resource-related and crowding-related hypotheses together enabled accurate model predictions of D. magna population dynamics and size structure. Whereas this study showed that various mechanisms might play a role in the negative feedback between population density and individual life history, it also indicated that different density levels might instigate the onset of the different mechanisms. This study provides an example of how the integration of dynamic energy budget theory and individual-based modelling can facilitate the exploration of mechanisms behind the regulation of population size. Such understanding is important for assessment, management and the conservation of populations and thereby biodiversity in ecosystems

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

Challenges and opportunities for integrating lake ecosystem modelling approaches

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others (‘reinventing the wheel’). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available (‘having tunnel vision’). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its ‘leading principle’, there are many opportunities for combining approaches. We take the point of view that a single ‘right’ approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem model