Dosing regimen of gentamicin in neonates: evaluation of current guidelines based on a large population pharmacokinetic analysis

Objectives: Gentamicin is among the most commonly prescribed antibiotics in newborns, but large interindividual variability in exposure levels exists. Based on a population pharmacokinetic analysis of a cohort of unselected neonates, we aimed to validate current dosing recommendations from a recent reference guideline (Neofax®). Methods: From 3039 concentrations collected in 994 preterm (median gestational age 32.3 weeks, range 24.2-36.5) and 455 term newborns, treated at the University Hospital of Lausanne between 2006 and 2011, a population pharmacokinetic analysis was performed with NONMEM®. Model-based simulations were used to assess the ability of dosing regimens to bring concentrations into targets: trough ≤ 1mg/L and peak ~ 8mg/L. Results: A two-compartment model best characterized gentamicin pharmacokinetics. Model parameters are presented in the table. Body weight, gestational age and postnatal age positively influence clearance, which decreases under dopamine administration. Body weight and gestational age influence the distribution volume. Model based simulations confirm that preterm infants need doses superior to 4 mg/kg, and extended dosage intervals, up to 48 hours for very preterm newborns, whereas most term newborns would achieve adequate exposure under 4 mg/kg q. 24 h. More than 90% of neonates would achieve trough concentrations below 2 mg/L and peaks above 6 mg/L following most recent guidelines. Conclusions: Simulated gentamicin exposure demonstrates good accordance with recent dosing recommendations for target concentration achievement.

Comparing Multilevel Clustering Methods on Weighted Graphs : The Case of Worldwide Air Passenger Traffic 2000-2004

Specific properties emerge from the structure of large networks, such as that of worldwide air traffic, including a highly hierarchical node structure and multi-level small world sub-groups that strongly influence future dynamics. We have developed clustering methods to understand the form of these structures, to identify structural properties, and to evaluate the effects of these properties. Graph clustering methods are often constructed from different components: a metric, a clustering index, and a modularity measure to assess the quality of a clustering method. To understand the impact of each of these components on the clustering method, we explore and compare different combinations. These different combinations are used to compare multilevel clustering methods to delineate the effects of geographical distance, hubs, network densities, and bridges on worldwide air passenger traffic. The ultimate goal of this methodological research is to demonstrate evidence of combined effects in the development of an air traffic network. In fact, the network can be divided into different levels of âeurooecohesionâeuro, which can be qualified and measured by comparative studies (Newman, 2002; Guimera et al., 2005; Sales-Pardo et al., 2007).

Strategies to promote translational research within the European Organisation for Research and Treatment of Cancer (EORTC) Head and Neck Cancer Group: a report from the Translational Research Subcommittee.

Head and neck squamous cell cancer (HNSCC) is the sixth leading cause of cancer-related deaths worldwide. These tumors are commonly diagnosed at advanced stages and mortality rates remain high. Even cured patients suffer the consequences of aggressive treatment that includes surgery, chemotherapy, and radiotherapy. In the past, in clinical trials, HNSCC was considered as a single disease entity. Advances in molecular biology with the development of genomic and proteomic approaches have demonstrated distinct prognostic HNSCC patient subsets beyond those defined by traditional clinical-pathological factors such as tumor subsite and stage [Cho W (ed). An Omics Perspective on Cancer Research. New York/Berlin: Springer 2010]. Validation of these biomarkers in large prospective clinical trials is required before their clinical implementation. To promote this research, the European Organisation for Research and Treatment of Cancer (EORTC) Head and Neck Cancer Program will develop the following strategies-(i) biobanking: prospective tissue collection from uniformly treated patients in the setting of clinical trials; (ii) a group of physicians, physician-scientists, and EORTC Headquarters staff devoted to patient-oriented head and neck cancer research; (iii) a collaboration between the basic scientists of the Translational Research Division interested in head and neck cancer research and the physicians of the Head and Neck Cancer Group; and (iv) funding through the EORTC Grant Program and the Network Core Institutions Consortium. In the present report, we summarize our strategic plans to promote head and neck cancer research within the EORTC framework.

Thymic selection generates a large T cell pool recognizing a self-peptide in humans.

The low frequency of self-peptide-specific T cells in the human preimmune repertoire has so far precluded their direct evaluation. Here, we report an unexpected high frequency of T cells specific for the self-antigen Melan-A/MART-1 in CD8 single-positive thymocytes from human histocompatibility leukocyte antigen-A2 healthy individuals, which is maintained in the peripheral blood of newborns and adults. Postthymic replicative history of Melan-A/MART-1-specific CD8 T cells was independently assessed by quantifying T cell receptor excision circles and telomere length ex vivo. We provide direct evidence that the large T cell pool specific for the self-antigen Melan-A/MART-1 is mostly generated by thymic output of a high number of precursors. This represents the only known naive self-peptide-specific T cell repertoire directly accessible in humans.

A Study of a Staff Alcohol Policy in a Large Public Health Organisation, Looking at the Policy Content, the Policy Development and the Implementation Process, and the Policy Impact

There are different approaches to dealing with alcohol related problems in the workplace. A literature review indicates that two of the models that underpin programmes to deal with alcohol related problems in the workplace are the disease model and the health promotion model. The disease model considers alcoholism as an illness and uses curative techniques to restore the individual to sobriety. The health promotion model looks at the determinants of health and promotes changes in the environment and structures, which would support healthy behaviour in relation to alcohol. Employee Assistance Programmes (EAPs) may have elements of both theses models. Dealing with alcohol problems at work involves a captive audience and the workplace as a setting can be used to influence healthier lifestyles. A workplace alcohol policy is a mechanism through which alcohol related issues might be dealt with, and the necessary resources and commitment of managers and staff channelled to this end. The policy aims should be clear and unambiguous, and specific plans put in place for implementing all aspects of the policy. In the case of the alcohol policy in the organisation under study, the policy was underpinned by a health promotion ethos and the policy document reflects broad aims and objectives to support this. The steering group that oversaw the development of the policy had particular needs of their own which they brought to the development process. The common theme in their needs was how to identify and support employees with alcohol related problems within an equitable staff welfare system. The role of the supervisor was recognised as crucial and training was provided to introduce the skills needed for an early intervention and constructive confrontation with employees who had alcohol related problems. Opportunities provided by this policy initiative to deal with broader issues around alcohol and to consider the determinants of health in relation to alcohol were not fully utilised. The policy formalised the procedures for dealing with people who have alcohol related problems in an equitable and supportive manner. The wider aspect of the health promotion approach does not appear to have been a priority in the development and implementation of the policy.This resource was contributed by The National Documentation Centre on Drug Use.

Gene finding in the chicken genome.

BACKGROUND: Despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. We used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method. RESULTS: We performed experimental evaluation by RT-PCR of three different computational gene finders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was computed and each component of it was evaluated. The results showed that de novo comparative methods can identify up to about 700 chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end. CONCLUSIONS: De novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods.

La gestió del document electrònic : l'experiència de la Biblioteca de la UOC

En aquest treball es fa una aproximació al tractament dels documents electrònics (sobretot recursos d'Internet) en el context de la biblioteca d'una universitat a distància. També es relata l'experiència de la Biblioteca de la Universitat Oberta de Catalunya en el procés de creació de pàgines electròniques de sumaris de revistes i monografies que formen part de la col·lecció de la biblioteca. Tots aquests serveis de valor afegit estan directament orientats vers uns usuaris que es posen en contacte amb la biblioteca des del Campus Virtual de la UOC.

Population pharmacokinetic study of gentamicin: A retrospective analysis in a large cohort of neonate patients

Objectives: Gentamicin is one of the most commonly prescribed antibiotics for suspected or proven infection in newborns. Because of age-associated (pre- and post- natal) changes in body composition and organ function, large interindividual variability in gentamicin drug levels exists, thus requiring a close monitoring of this drug due to its narrow therapeutic index. We aimed to investigate clinical and demographic factors influencing gentamicin pharmacokinetics (PK) in a large cohort of unselected newborns and to explore optimal regimen based on simulation. Methods: All gentamicin concentration data from newborns treated at the University Hospital Center of Lausanne between December 2006 and October 2011 were retrieved. Gentamicin concentrations were measured within the frame of a routine therapeutic drug monitoring program, in which 2 concentrations (at 1h and 12h) are systematically collected after the first administered dose, and a few additional concentrations are sampled along the treatment course. A population PK analysis was performed by comparing various structural models, and the effect of clinical and demographic factors on gentamicin disposition was explored using NONMEM®. Results: A total of 3039 concentrations collected in 994 preterm (median gestational age 32.3 weeks, range 24.2-36.5 weeks) and 455 term newborns were used in the analysis. Most of the data (86%) were sampled after the first dose (C1 h and C12 h). A two-compartment model best characterized gentamicin PK. Average clearance (CL) was 0.044 L/h/kg (CV 25%), central volume of distribution (Vc) 0.442 L/kg (CV 18%), intercompartmental clearance (Q) 0.040 L/h/kg and peripheral volume of distribution (Vp) 0.122 L/kg. Body weight, gestational age and postnatal age positively influenced CL. The use of both gestational age and postnatal age better predicted CL than postmenstrual age alone. CL was affected by dopamine and furosemide administration and non-significantly by indometacin. Body weight, gestational age and dopamine coadminstration significantly influenced Vc. Model based simulation confirms that preterm infants need higher dose, superior to 4 mg/kg, and extended interval dosage regimen to achieve adequate concentration. Conclusions: This study, performed on a very large cohort of neonates, identified important factors influencing gentamicin PK. The model will serve to elaborate a Bayesian tool for dosage individualization based on a single measurement.

GLUT3 is induced during epithelial-mesenchymal transition and promotes tumor cell proliferation in non-small cell lung cancer.

BACKGROUND: Alterations in glucose metabolism and epithelial-mesenchymal transition (EMT) constitute two important characteristics of carcinoma progression toward invasive cancer. Despite an extensive characterization of each of them separately, the links between EMT and glucose metabolism of tumor cells remain elusive. Here we show that the neuronal glucose transporter GLUT3 contributes to glucose uptake and proliferation of lung tumor cells that have undergone an EMT. RESULTS: Using a panel of human non-small cell lung cancer (NSCLC) cell lines, we demonstrate that GLUT3 is strongly expressed in mesenchymal, but not epithelial cells, a finding corroborated in hepatoma cells. Furthermore, we identify that ZEB1 binds to the GLUT3 gene to activate transcription. Importantly, inhibiting GLUT3 expression reduces glucose import and the proliferation of mesenchymal lung tumor cells, whereas ectopic expression in epithelial cells sustains proliferation in low glucose. Using a large microarray data collection of human NSCLCs, we determine that GLUT3 expression correlates with EMT markers and is prognostic of poor overall survival. CONCLUSIONS: Altogether, our results reveal that GLUT3 is a transcriptional target of ZEB1 and that this glucose transporter plays an important role in lung cancer, when tumor cells loose their epithelial characteristics to become more invasive. Moreover, these findings emphasize the development of GLUT3 inhibitory drugs as a targeted therapy for the treatment of patients with poorly differentiated tumors.

Prevalence and Clinical Features of Isolated Clinical Hypertension and Dipping Profile in a Large Cohort of Untreated Hypertensive Subjects

Aim: To examine the prevalence and clinical features of isolated clinical hypertension (ICH) and the dipping patterns in a large cohort of untreated hypertensive subjects form the Spanish ABPM registry

Social inequalities and mortality in Europe-results from a large multi-national cohort

BACKGROUND Socio-economic inequalities in mortality are observed at the country level in both North America and Europe. The purpose of this work is to investigate the contribution of specific risk factors to social inequalities in cause-specific mortality using a large multi-country cohort of Europeans. METHODS A total of 3,456,689 person/years follow-up of the European Prospective Investigation into Cancer and Nutrition (EPIC) was analysed. Educational level of subjects coming from 9 European countries was recorded as proxy for socio-economic status (SES). Cox proportional hazard model's with a step-wise inclusion of explanatory variables were used to explore the association between SES and mortality; a Relative Index of Inequality (RII) was calculated as measure of relative inequality. RESULTS Total mortality among men with the highest education level is reduced by 43% compared to men with the lowest (HR 0.57, 95% C.I. 0.52-0.61); among women by 29% (HR 0.71, 95% C.I. 0.64-0.78). The risk reduction was attenuated by 7% in men and 3% in women by the introduction of smoking and to a lesser extent (2% in men and 3% in women) by introducing body mass index and additional explanatory variables (alcohol consumption, leisure physical activity, fruit and vegetable intake) (3% in men and 5% in women). Social inequalities were highly statistically significant for all causes of death examined in men. In women, social inequalities were less strong, but statistically significant for all causes of death except for cancer-related mortality and injuries. DISCUSSION In this European study, substantial social inequalities in mortality among European men and women which cannot be fully explained away by accounting for known common risk factors for chronic diseases are reported.

Integració a la plataforma webDTI de tècniques de clustering de fibres i visualització de clústers

Estudi, disseny i implementació de diferents tècniques d’agrupament defibres (clustering) per tal d’integrar a la plataforma DTIWeb diferentsalgorismes de clustering i tècniques de visualització de clústers de fibres de forma quefaciliti la interpretació de dades de DTI als especialistes

Effective diagnosis of Alzheimer's disease by means of large margin-based methodology.

BACKGROUND Functional brain images such as Single-Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) have been widely used to guide the clinicians in the Alzheimer's Disease (AD) diagnosis. However, the subjectivity involved in their evaluation has favoured the development of Computer Aided Diagnosis (CAD) Systems. METHODS It is proposed a novel combination of feature extraction techniques to improve the diagnosis of AD. Firstly, Regions of Interest (ROIs) are selected by means of a t-test carried out on 3D Normalised Mean Square Error (NMSE) features restricted to be located within a predefined brain activation mask. In order to address the small sample-size problem, the dimension of the feature space was further reduced by: Large Margin Nearest Neighbours using a rectangular matrix (LMNN-RECT), Principal Component Analysis (PCA) or Partial Least Squares (PLS) (the two latter also analysed with a LMNN transformation). Regarding the classifiers, kernel Support Vector Machines (SVMs) and LMNN using Euclidean, Mahalanobis and Energy-based metrics were compared. RESULTS Several experiments were conducted in order to evaluate the proposed LMNN-based feature extraction algorithms and its benefits as: i) linear transformation of the PLS or PCA reduced data, ii) feature reduction technique, and iii) classifier (with Euclidean, Mahalanobis or Energy-based methodology). The system was evaluated by means of k-fold cross-validation yielding accuracy, sensitivity and specificity values of 92.78%, 91.07% and 95.12% (for SPECT) and 90.67%, 88% and 93.33% (for PET), respectively, when a NMSE-PLS-LMNN feature extraction method was used in combination with a SVM classifier, thus outperforming recently reported baseline methods. CONCLUSIONS All the proposed methods turned out to be a valid solution for the presented problem. One of the advances is the robustness of the LMNN algorithm that not only provides higher separation rate between the classes but it also makes (in combination with NMSE and PLS) this rate variation more stable. In addition, their generalization ability is another advance since several experiments were performed on two image modalities (SPECT and PET).

Discrepancies between Aedes aegypti identification in the field and in the laboratory after collection with a sticky trap

Currently, sticky traps are regularly employed to assist in the surveillance of Aedes aegypti infestation. We tested two alternative procedures for specimen identification performed by local health agents: directly in the field, as recommended by certain manufacturers, or after transportation to the laboratory. A total of 384 sticky traps (MosquiTRAP) were monitored monthly during one year in four geographically representative Brazilian municipalities. When the same samples were inspected in the field and in the laboratory, large differences were noted in the total number of mosquitoes recorded and in the number of specimens identified as Ae. aegypti by both procedures. Although field identification has the potential to speed vector surveillance, these results point to uncertainties in the evaluated protocol.

Clustering algorithms for anti-money laundering using graph theory and social network analysis

HEMOLIA (a project under European community’s 7th framework programme) is a new generation Anti-Money Laundering (AML) intelligent multi-agent alert and investigation system which in addition to the traditional financial data makes extensive use of modern society’s huge telecom data source, thereby opening up a new dimension of capabilities to all Money Laundering fighters (FIUs, LEAs) and Financial Institutes (Banks, Insurance Companies, etc.). This Master-Thesis project is done at AIA, one of the partners for the HEMOLIA project in Barcelona. The objective of this thesis is to find the clusters in a network drawn by using the financial data. An extensive literature survey has been carried out and several standard algorithms related to networks have been studied and implemented. The clustering problem is a NP-hard problem and several algorithms like K-Means and Hierarchical clustering are being implemented for studying several problems relating to sociology, evolution, anthropology etc. However, these algorithms have certain drawbacks which make them very difficult to implement. The thesis suggests (a) a possible improvement to the K-Means algorithm, (b) a novel approach to the clustering problem using the Genetic Algorithms and (c) a new algorithm for finding the cluster of a node using the Genetic Algorithm.