Antiangiogenic peptides and proteins: from experimental tools to clinical drugs.

The formation of a 'tumor-associated vasculature', a process referred to as tumor angiogenesis, is a stromal reaction essential for tumor progression. Inhibition of tumor angiogenesis suppresses tumor growth in many experimental models, thereby indicating that tumor-associated vasculature may be a relevant target to inhibit tumor progression. Among the antiangiogenic molecules reported to date many are peptides and proteins. They include cytokines, chemokines, antibodies to vascular growth factors and growth factor receptors, soluble receptors, fragments derived from extracellular matrix proteins and small synthetic peptides. The polypeptide tumor necrosis factor (TNF, Beromun) was the first drug registered for the regional treatment of human cancer, whose mechanisms of action involved selective disruption of the tumor vasculature. More recently, bevacizumab (Avastin), an antibody against vascular endothelial growth factor (VEGF)-A, was approved as the first systemic antiangiogenic drug that had a significant impact on the survival of patients with advanced colorectal cancer, in combination with chemotherapy. Several additional peptides and antibodies with antiangiogenic activity are currently tested in clinical trials for their therapeutic efficacy. Thus, peptides, polypeptides and antibodies are emerging as leading molecules among the plethora of compounds with antiangiogenic activity. In this article, we will review some of these molecules and discuss their mechanism of action and their potential therapeutic use as anticancer agents in humans.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

Geostatistical determination of heavy-metal distribution in a contaminated site - A case study

A two stage sampling strategy is necessary in order to optimize the study of distribution of pollution in soils and groundwater. First, detailed sampling from a limited area coupled with statistical analysis of the data are used to determine the microvariability of the parameter(s). The results from this detailed analysis are then used to calculate the optimal spacing between samples for the larger scale study. This two stage sampling strategy can result in significant financial savings during subsequent soil or groundwater remediation. This combined sampling and statistical analysis approach is illustrated with an example from a heavy metal contaminated site.

Combinations of prognostic tools for identification of high-risk normotensive patients with acute symptomatic pulmonary embolism.

Background: In haemodynamically stable patients with acute symptomatic pulmonary embolism (PE), studies have not evaluated the usefulness of combining the measurement of cardiac troponin, transthoracic echocardiogram (TTE), and lower extremity complete compression ultrasound (CCUS) testing for predicting the risk of PE-related death. Methods: The study assessed the ability of three diagnostic tests (cardiac troponin I (cTnI), echocardiogram, and CCUS) to prognosticate the primary outcome of PE-related mortality during 30 days of follow-up after a diagnosis of PE by objective testing. Results: Of 591 normotensive patients diagnosed with PE, the primary outcome occurred in 37 patients (6.3%; 95% CI 4.3% to 8.2%). Patients with right ventricular dysfunction (RVD) by TTE and concomitant deep vein thrombosis (DVT) by CCUS had a PE-related mortality of 19.6%, compared with 17.1% of patients with elevated cTnI and concomitant DVT and 15.2% of patients with elevated cTnI and RVD. The use of any two-test strategy had a higher specificity and positive predictive value compared with the use of any test by itself. A combined three-test strategy did not further improve prognostication. For a subgroup analysis of high-risk patients, according to the pulmonary embolism severity index (classes IV and V), positive predictive values of the two-test strategies for PE-related mortality were 25.0%, 24.4% and 20.7%, respectively. Conclusions: In haemodynamically stable patients with acute symptomatic PE, a combination of echocardiography (or troponin testing) and CCUS improved prognostication compared with the use of any test by itself for the identification of those at high risk of PE-related death.

Two-step chromatographic purification of human plasma alpha(1)-acid glycoprotein: its application to the purification of rare phenotype samples of the protein and their study by chromatography on immobilized metal chelate affinity adsorbent.

Alpha1-Acid glycoprotein (AAG) or orosomucoid was purified to homogeneity from human plasma by a separate two-step method using chromatography on immobilized Cibacron Blue F3G-A to cross-linked agarose and chromatography on hydroxyapatite. The conditions for the pre-purification of AAG by chromatography on immobilized Cibacron Blue F3G-A were first optimized using different buffer systems with different pH values. The overall yield of the combined techniques was 80% and ca. 12 mg of AAG were purified from an initial total amount of ca. 15 mg in a ca. 40 ml sample of human plasma. This method was applied to the purification of AAG samples corresponding to the three main phenotypes of the protein (FI*S/A, F1/A and S/A), from individual human plasma previously phenotyped for AAG. A study by isoelectric focusing with carrier ampholytes showed that the microheterogeneity of the purified F1*S/A, F1/A and S/A AAG samples was similar to that of AAG in the corresponding plasma, thus suggesting that no apparent desialylation of the glycoprotein occurred during the purification steps. This method was also applied to the purification of AAG samples corresponding to rare phenotypes of the protein (F1/A*AD, S/A*X0 and F1/A*C1) and the interactions of these variants with immobilized copper(II) ions were then studied at pH 7, by chromatography on an iminodiacetate Sepharose-Cu(II) gel. It was found that the different variants encoded by the first of the two genes coding for AAG in humans (i.e. the F1 and S variants) interacted non-specifically with the immobilized ligand, whereas those encoded by the second gene of AAG (i.e. the A, AD, X0 and C1 variants) strongly bound to immobilized Cu(II) ions. These results suggested that chromatography on an immobilized affinity Cu(II) adsorbent could be helpful to distinguish between the respective products of the two highly polymorphic genes which code for human AAG.

E-tools for civic education : experiences from the election campaign in Switzerland 2007

Political participation is often very low in Switzerland especially among students and young citizens. In the run-up to the Swiss parliamentary election in October 2007 several online tools and campaigns were developed with the aim to increase not only the level of information about the political programs of parties and candidates, but also the electoral participation of younger citizens. From a practical point of view this paper will describe the development, marketing efforts and the distribution as well as the use of two of these tools : the so-called "Parteienkompass" (party compass) and the "myVote"-tool - an online voting assistance tool based on an issue-matching system comparing policy preferences between voters and candidates on an individual level. We also havea look at similar tools stemming from Voting Advice Applications (VAA) in other countries in Western Europe. The paper closes with the results of an evaluation and an outlook to further developments and on-going projects in the near future in Switzerland.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Introduction: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on measurement of blood concentrations. Maintaining concentrations within a target range requires pharmacokinetic and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. In the last decades computer programs have been developed to assist clinicians in this assignment. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Method: Literature and Internet search was performed to identify software. All programs were tested on common personal computer. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software's characteristics. Numbers of drugs handled vary widely and 8 programs offer the ability to the user to add its own drug model. 10 computer programs are able to compute Bayesian dosage adaptation based on a blood concentration (a posteriori adjustment) while 9 are also able to suggest a priori dosage regimen (prior to any blood concentration measurement), based on individual patient covariates, such as age, gender, weight. Among those applying Bayesian analysis, one uses the non-parametric approach. The top 2 software emerging from this benchmark are MwPharm and TCIWorks. Other programs evaluated have also a good potential but are less sophisticated (e.g. in terms of storage or report generation) or less user-friendly.¦Conclusion: Whereas 2 integrated programs are at the top of the ranked listed, such complex tools would possibly not fit all institutions, and each software tool must be regarded with respect to individual needs of hospitals or clinicians. Interest in computing tool to support therapeutic monitoring is still growing. Although developers put efforts into it the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capacity of data storage and report generation.

Benchmarking therapeutic drug monitoring software: A systematic evaluation of available computer tools

Objectives: Therapeutic drug monitoring (TDM) aims at optimizing treatment by individualizing dosage regimen based on blood concentrations measurement. Maintaining concentrations within a target range requires pharmacokinetic (PK) and clinical capabilities. Bayesian calculation represents a gold standard in TDM approach but requires computing assistance. The aim of this benchmarking was to assess and compare computer tools designed to support TDM clinical activities.¦Methods: Literature and Internet were searched to identify software. Each program was scored against a standardized grid covering pharmacokinetic relevance, user-friendliness, computing aspects, interfacing, and storage. A weighting factor was applied to each criterion of the grid to consider its relative importance. To assess the robustness of the software, six representative clinical vignettes were also processed through all of them.¦Results: 12 software tools were identified, tested and ranked. It represents a comprehensive review of the available software characteristics. Numbers of drugs handled vary from 2 to more than 180, and integration of different population types is available for some programs. Nevertheless, 8 programs offer the ability to add new drug models based on population PK data. 10 computer tools incorporate Bayesian computation to predict dosage regimen (individual parameters are calculated based on population PK models). All of them are able to compute Bayesian a posteriori dosage adaptation based on a blood concentration while 9 are also able to suggest a priori dosage regimen, only based on individual patient covariates. Among those applying Bayesian analysis, MM-USC*PACK uses a non-parametric approach. The top 2 programs emerging from this benchmark are MwPharm and TCIWorks. Others programs evaluated have also a good potential but are less sophisticated or less user-friendly.¦Conclusions: Whereas 2 software packages are ranked at the top of the list, such complex tools would possibly not fit all institutions, and each program must be regarded with respect to individual needs of hospitals or clinicians. Programs should be easy and fast for routine activities, including for non-experienced users. Although interest in TDM tools is growing and efforts were put into it in the last years, there is still room for improvement, especially in terms of institutional information system interfacing, user-friendliness, capability of data storage and automated report generation.

Metal concentrations in soils around the copper smelter and surrounding industrial complex of Port Kembla, NSW, Australia

Anthropogenic emissions of metals from sources such as smelters are an international problem, but there is limited published information on emissions from Australian smelters. The objective of this study was to investigate the regional distribution of heavy metals in soils in the vicinity of the industrial complex of Port Kembla, NSW, Australia, which comprises a copper smelter, steelworks and associated industries. Soil samples (n=25) were collected at the depths of 0-5 and 5-20 cm, air dried and sieved to < 2 mm. Aqua regia extractable amounts of As, Cr, Cu, Ph and Zn were analysed by inductively coupled plasma mass spectrometry (lCP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES). Outliers were identified from background levels by statistical methods. Mean background levels at a depth of 0-5 cm were estimated at 3.2 mg/kg As, 12 mg/kg Cr, 49 mg/kg Cu, 20 mg/kg Ph and 42 mg/kg Zn. Outliers for elevated As and Cu values were mainly present within 4 km from the Port Kembla industrial complex, but high Ph at two sites and high Zn concentrations were found at six sites up to 23 km from Port Kembla. Chromium concentrations were not anomalous close to the industrial complex. There was no significant difference of metal concentrations at depths of 0-5 and 5-20 cm, except for Ph and Zn. Copper and As concentrations in the soils are probably related to the concentrations in the parent rock. From this investigation, the extent of the contamination emanating from the Port Kembla industrial complex is limited to 1-13 km, but most likely <4 km, depending on the element; the contamination at the greater distance may not originate from the industrial complex. (C) 2003 Elsevier B.V. All rights reserved.

Evaluation of the toxicity of different metal compounds in the developing brain using aggregating cell cultures as a model.

To evaluate their toxicity in the developing brain, eight metal compounds, [bismuth sodium tartrate (BiNA-tartrate), CdCl(2), CoCl(2), HgCl(2), dimethyl mercury, NiCl(2), TlCl and triethyltin chloride (TET)] were tested in aggregating cell cultures of foetal rat telencephalon. The compounds were applied to the cultures continuously, either during an early developmental stage (between days 5 and 14) or during and advanced stage of maturation (between days 24 and 34). Changes in the activities of cell type-specific enzymes were used as a criterion for toxicity. A general cytotoxic effect was observed after treatment with either CdCl(2), HgCl(2) or TET at 10(-6)m, and with TlCl at 10(-5)m. Selective effects were found with BiNa-tartrate and dimethylmercury. CoCl(2) did not modify the parameters tested, whereas a stimulant effect was found with NiCl(2). The effects of several compounds were development dependent: HgCl(2), TET and TlCl were more toxic in immature cultures, whereas BiNa-tartrate, dimethylmercury and NiCl(2) were more effective in differentiated cultures.

Therapeutic drug monitoring and pharmacogenetic tests as tools in pharmacovigilance.

Therapeutic drug monitoring (TDM) and pharmacogenetic tests play a major role in minimising adverse drug reactions and enhancing optimal therapeutic response. The response to medication varies greatly between individuals, according to genetic constitution, age, sex, co-morbidities, environmental factors including diet and lifestyle (e.g. smoking and alcohol intake), and drug-related factors such as pharmacokinetic or pharmacodynamic drug-drug interactions. Most adverse drug reactions are type A reactions, i.e. plasma-level dependent, and represent one of the major causes of hospitalisation, in some cases leading to death. However, they may be avoidable to some extent if pharmacokinetic and pharmacogenetic factors are taken into consideration. This article provides a review of the literature and describes how to apply and interpret TDM and certain pharmacogenetic tests and is illustrated by case reports. An algorithm on the use of TDM and pharmacogenetic tests to help characterise adverse drug reactions is also presented. Although, in the scientific community, differences in drug response are increasingly recognised, there is an urgent need to translate this knowledge into clinical recommendations. Databases on drug-drug interactions and the impact of pharmacogenetic polymorphisms and adverse drug reaction information systems will be helpful to guide clinicians in individualised treatment choices.