Targeting anticancer therapy : clinical and preclinical approaches

AbstractCancer treatment has shifted from cytotoxic and nonspecific chemotherapy to chronic treatment with targeted molecular therapies. These new classes of drugs directed against cancer-specific molecules and signaling pathways, act at a particular level of the tumor cell development. However, in both types of therapeutic approaches (standard cytotoxic chemotherapy and targeted signal transduction inhibitions), toxicity and side effects can occur. The aim of this thesis was to investigate various approaches to improve the activity and tolerability of cancer treatment, in a clinical setting, a) by molecular targeting through the use of tyrosine kinase inhibitors (TKIs), whose dosage can be adapted to each patient according to plasma levels, and, b) in a preclinical model, by tissue targeting with locoregional administration of cytotoxic chemotherapy to increase drug exposure in the target tissue while reducing systemic toxicity of the treatment.A comprehensive program for the Therapeutic Drug Monitoring (TDM) of the new class of targeted anticancer drugs of TKIs in patient's blood has been therefore initiated comprising the setting up, validation and clinical application of a multiplex assay by liquid chromatography coupled to tandem mass spectrometry of TKIs in plasma from cancer patients. Information on drugs exposure may be clinically useful for an optimal follow-up of patients' anticancer treatment, especially in case of less than optimal clinical response, occurrence of adverse drug reaction effects and the numerous risks of drug-drug interactions. In this context, better knowledge of the potential drug interactions between TKIs and widely prescribed co- medications is of critical importance for clinicians, to improve their daily care of cancer patients. For one of the first TKI imatinib, TDM interpretation is nowadays based on total plasma concentrations but, only the unbound (free) form is likely to enter cell to exert its pharmacological action. Pharmacokinetic analysis of the total and free plasma level of imatinib measured simultaneously in patients have allowed to refine and validate a population pharmacokinetic model integrating factors influencing in patients the exposure of pharmacological active species. The equation developed from this model may be used for extrapolating free imatinib plasma concentration based on the total plasma levels that are currently measured in TDM from patients. Finally, the specific influence of Pglycoprotein on the intracellular disposition of TKIs has been studies in cell systems using the siRNA silencing approach.Another approach to enhance the selectivity of anticancer treatment may be achieved by the loco-regional administration of a cytostatic agent to the target organ while sparing non- affected tissues. Isolated lung perfusion (ILP) was designed for the treatment of loco-regional malignancies of the lung but clinical results have been so far disappointing. It has been shown in a preclinical model in rats that ILP with the cytotoxic agent doxorubicin alone allows a high drug uptake in lung tissue, and a low systemic toxicity, but was characterized by a high spatial tissular heterogeneity in drug exposure and doxorubicin uptake in tumor was comparatively smaller than in normal lung tissue. Photodynamic therapy (PDT) is a new approach for the treatment of superficial tumors, and implies the application of a sensitizer activated by a laser light at a specific wavelength, that disrupts endothelial barrier of tumor vessels to increase locally the distribution of cytostatics into the tumor tissue. PDT pre-treatment before intravenous administration of liposomal doxorubicin was indeed shown to selectively increase drug uptake in tumors in a rat model of sarcoma tumors to the lung.RésuméLe traitement de certains cancers s'est progressivement transformé et est passé de la chimiothérapie, cytotoxique et non spécifique, au traitement chronique des patients avec des thérapies moléculaires ciblées. Ces médicaments ont une action ciblée en interférant à un niveau spécifique du développement de la cellule tumorale. Dans les deux types d'approches thérapeutiques (chimiothérapie cytotoxique et traitements ciblés), on est confronté à la présence de toxicité et aux effets secondaires du traitement anticancéreux. Le but de cette thèse a donc été d'étudier diverses approches visant à améliorer l'efficacité et la tolérabilité du traitement anticancéreux, a) dans le cadre d'une recherche clinique, par le ciblage moléculaire grâce aux inhibiteurs de tyrosines kinases (TKIs) dont la posologie est adaptée à chaque patient, et b) dans un modèle préclinique, par le ciblage tissulaire grâce à l'administration locorégionale de chimiothérapie cytotoxique, afin d'augmenter l'exposition dans le tissu cible et de réduire la toxicité systémique du traitement.Un programme de recherche sur le suivi thérapeutique (Therapeutic Drug Monitoring, TDM) des inhibiteurs de tyrosine kinases a été ainsi mis en place et a impliqué le développement, la validation et l'application clinique d'une méthode multiplex par chromatographie liquide couplée à la spectrométrie de masse en tandem des TKIs chez les patients souffrant de cancer. L'information fournie par le TDM sur l'exposition des patients aux traitements ciblés est cliniquement utile et est susceptible d'optimiser la dose administrée, notamment dans les cas où la réponse clinique au traitement des patients est sous-optimale, en présence d'effets secondaires du traitement ciblé, ou lorsque des risques d'interactions médicamenteuses sont suspectés. Dans ce contexte, l'étude des interactions entre les TKIs et les co-médications couramment associées est utile pour les cliniciens en charge d'améliorer au jour le jour la prise en charge du traitement anticancéreux. Pour le premier TKI imatinib, l'interprétation TDM est actuellement basée sur la mesure des concentrations plasmatiques totales alors que seule la fraction libre (médicament non lié aux protéines plasmatiques circulantes) est susceptible de pénétrer dans la cellule pour exercer son action pharmacologique. L'analyse pharmacocinétique des taux plasmatiques totaux et libres d'imatinib mesurés simultanément chez les patients a permis d'affiner et de valider un modèle de pharmacocinétique de population qui intègre les facteurs influençant l'exposition à la fraction de médicament pharmacologiquement active. L'équation développée à partir de ce modèle permet d'extrapoler les concentrations libres d'imatinib à partir des concentrations plasmatiques totales qui sont actuellement mesurées lors du TDM des patients. Finalement, l'influence de la P-glycoprotéine sur la disposition cellulaire des TKIs a été étudiée dans un modèle cellulaire utilisant l'approche par la technologie du siRNA permettant de bloquer sélectivement l'expression du gène de cette protéine d'efflux des médicaments.Une autre approche pour augmenter la sélectivité du traitement anticancéreux consiste en une administration loco-régionale d'un agent cytostatique directement au sein de l'organe cible tout en préservant les tissus sains. La perfusion isolée du poumon (ILP) a été conçue pour le traitement loco-régional des cancers affectant les tissus pulmonaires mais les résultats cliniques ont été jusqu'à ce jour décevants. Dans des modèles précliniques chez le rat, il a pu être démontré que l'ILP avec la doxorubicine, un agent cytotoxique, administré seul, permet une exposition élevée au niveau du tissu pulmonaire, et une faible toxicité systémique. Toutefois, cette technique est caractérisée par une importante variabilité de la distribution dans les tissus pulmonaires et une pénétration du médicament au sein de la tumeur comparativement plus faible que dans les tissus sains.La thérapie photodynamique (PDT) est une nouvelle approche pour le traitement des tumeurs superficielles, qui consiste en l'application d'un agent sensibilisateur activé par une lumière laser de longueur d'onde spécifique, qui perturbe l'intégrité physiologique de la barrière endothéliale des vaisseaux alimentant la tumeur et permet d'augmenter localement la pénétration des agents cytostatiques.Nos études ont montré qu'un pré-traitement par PDT permet d'augmenter sélectivement l'absorption de doxorubicine dans les tumeurs lors d'administration i.v. de doxorubicine liposomale dans un modèle de sarcome de poumons de rongeurs.Résumé large publicDepuis une dizaine d'année, le traitement de certains cancers s'est progressivement transformé et les patients qui devaient jusqu'alors subir des chimiothérapies, toxiques et non spécifiques, peuvent maintenant bénéficier de traitements chroniques avec des thérapies ciblées. Avec les deux types d'approches thérapeutiques, on reste cependant confronté à la toxicité et aux effets secondaires du traitement.Le but de cette thèse a été d'étudier chez les patients et dans des modèles précliniques les diverses approches visant à améliorer l'activité et la tolérance des traitements à travers un meilleur ciblage de la thérapie anticancéreuse. Cet effort de recherche nous a conduits à nous intéresser à l'optimisation du traitement par les inhibiteurs de tyrosines kinases (TKIs), une nouvelle génération d'agents anticancéreux ciblés agissant sélectivement sur les cellules tumorales, en particulier chez les patients souffrant de leucémie myéloïde chronique et de tumeurs stromales gastro-intestinales. L'activité clinique ainsi que la toxicité de ces TKIs paraissent dépendre non pas de la dose de médicament administrée, mais de la quantité de médicaments circulant dans le sang auxquelles les tumeurs cancéreuses sont exposées et qui varient beaucoup d'un patient à l'autre. A cet effet, nous avons développé une méthode par chromatographie couplée à la spectrométrie de masse pour mesurer chez les patients les taux de médicaments de la classe des TKIs dans la perspective de piloter le traitement par une approche de suivi thérapeutique (Therapeutic Drug Monitoring, TDM). Le TDM repose sur la mesure de la quantité de médicament dans le sang d'un patient dans le but d'adapter individuellement la posologie la plus appropriée: des quantités insuffisantes de médicament dans le sang peuvent conduire à un échec thérapeutique alors qu'un taux sanguin excessif peut entraîner des manifestations toxiques.Dans une seconde partie préclinique, nous nous sommes concentrés sur l'optimisation de la chimiothérapie loco-régionale dans un modèle de sarcome du poumon chez le rat, afin d'augmenter l'exposition dans la tumeur tout en réduisant la toxicité dans les tissus non affectés.La perfusion isolée du poumon (ILP) permet d'administrer un médicament anticancéreux cytotoxique comme la doxorubicine, sélectivement au niveau le tissu pulmonaire où sont généralement localisées les métastases de sarcome. L'administration par ILP de doxorubicine, toxique pour le coeur, a permis une forte accumulation des médicaments dans le poumon, tout en épargnant le coeur. Il a été malheureusement constaté que la doxorubicine ne pénètre que faiblement dans la tumeur sarcomateuse, témoignant des réponses cliniques décevantes observées avec cette approche en clinique. Nous avons ainsi étudié l'impact sur la pénétration tumorale de l'association d'une chimiothérapie cytotoxique avec la thérapie photodynamique (PDT) qui consiste en l'irradiation spécifique du tissu-cible cancéreux, après l'administration d'un agent photosensibilisateur. Dans ce modèle animal, nous avons observé qu'un traitement par PDT permet effectivement d'augmenter de façon sélective l'accumulation de doxorubicine dans les tumeurs lors d'administration intraveineuse de médicament.

Acute experimental Trypanosoma cruzi infection: establishing a murine model that utilises non-invasive measurements of disease parameters

Trypanosoma cruzi infection has a large public health impact in Latin American countries. Although the transmission rates via blood transfusions and insect vectors have declined sharply in the past 20 years due to policies of the Southern Cone countries, a large number of people are still at risk for infection. Currently, no accepted experimental model or descriptions of the clinical signs that occur during the course of acute murine infection are available. The aim of this work was to use non-invasive methods to evaluate the clinical signs of Balb/c mice infected with the Y strain of T. cruzi. The infected mice displayed evident clinical changes beginning in the third week of infection. The mice were evaluated based on physical characteristics, spontaneous activity, exploratory behaviour and physiological alterations. We hope that the results presented in this report provide parameters that complement the effective monitoring of trypanocidal treatment and other interventions used to treat experimental Chagas disease.

Delimitation of kala-azar risk areas in the district of Vaishali in Bihar (India) using a geo-environmental approach

Remote sensing and geographical information technologies were used to discriminate areas of high and low risk for contracting kala-azar or visceral leishmaniasis. Satellite data were digitally processed to generate maps of land cover and spectral indices, such as the normalised difference vegetation index and wetness index. To map estimated vector abundance and indoor climate data, local polynomial interpolations were used based on the weightage values. Attribute layers were prepared based on illiteracy and the unemployed proportion of the population and associated with village boundaries. Pearson's correlation coefficient was used to estimate the relationship between environmental variables and disease incidence across the study area. The cell values for each input raster in the analysis were assigned values from the evaluation scale. Simple weighting/ratings based on the degree of favourable conditions for kala-azar transmission were used for all the variables, leading to geo-environmental risk model. Variables such as, land use/land cover, vegetation conditions, surface dampness, the indoor climate, illiteracy rates and the size of the unemployed population were considered for inclusion in the geo-environmental kala-azar risk model. The risk model was stratified into areas of "risk"and "non-risk"for the disease, based on calculation of risk indices. The described approach constitutes a promising tool for microlevel kala-azar surveillance and aids in directing control efforts.

The diamine oxidase gene is associated with hypersensitivity response to non-steroidal anti-inflammatory drugs.

Non-steroidal anti-inflammatory drugs (NSAIDs) are the drugs most frequently involved in hypersensitivity drug reactions. Histamine is released in the allergic response to NSAIDs and is responsible for some of the clinical symptoms. The aim of this study is to analyze clinical association of functional polymorphisms in the genes coding for enzymes involved in histamine homeostasis with hypersensitivity response to NSAIDs. We studied a cohort of 442 unrelated Caucasian patients with hypersensitivity to NSAIDs. Patients who experienced three or more episodes with two or more different NSAIDs were included. If this requirement was not met diagnosis was established by challenge. A total of 414 healthy unrelated controls ethnically matched with patients and from the same geographic area were recruited. Analyses of the SNPs rs17740607, rs2073440, rs1801105, rs2052129, rs10156191, rs1049742 and rs1049793 in the HDC, HNMT and DAO genes were carried out by means of TaqMan assays. The detrimental DAO 16 Met allele (rs10156191), which causes decreased metabolic capacity, is overrepresented among patients with crossed-hypersensitivity to NSAIDs with an OR  = 1.7 (95% CI  = 1.3-2.1; Pc  = 0.0003) with a gene-dose effect (P = 0.0001). The association was replicated in two populations from different geographic areas (Pc  = 0.008 and Pc  = 0.004, respectively). CONCLUSIONS AND IMPLICATIONS: The DAO polymorphism rs10156191 which causes impaired metabolism of circulating histamine is associated with the clinical response in crossed-hypersensitivity to NSAIDs and could be used as a biomarker of response.

Candidate gene study of TRAIL and TRAIL receptors: association with response to interferon beta therapy in multiple sclerosis patients.

TRAIL and TRAIL Receptor genes have been implicated in Multiple Sclerosis pathology as well as in the response to IFN beta therapy. The objective of our study was to evaluate the association of these genes in relation to the age at disease onset (AAO) and to the clinical response upon IFN beta treatment in Spanish MS patients. We carried out a candidate gene study of TRAIL, TRAILR-1, TRAILR-2, TRAILR-3 and TRAILR-4 genes. A total of 54 SNPs were analysed in 509 MS patients under IFN beta treatment, and an additional cohort of 226 MS patients was used to validate the results. Associations of rs1047275 in TRAILR-2 and rs7011559 in TRAILR-4 genes with AAO under an additive model did not withstand Bonferroni correction. In contrast, patients with the TRAILR-1 rs20576-CC genotype showed a better clinical response to IFN beta therapy compared with patients carrying the A-allele (recessive model: p = 8.88×10(-4), pc = 0.048, OR = 0.30). This SNP resulted in a non synonymous substitution of Glutamic acid to Alanine in position 228 (E228A), a change previously associated with susceptibility to different cancer types and risk of metastases, suggesting a lack of functionality of TRAILR-1. In order to unravel how this amino acid change in TRAILR-1 would affect to death signal, we performed a molecular modelling with both alleles. Neither TRAIL binding sites in the receptor nor the expression levels of TRAILR-1 in peripheral blood mononuclear cell subsets (monocytes, CD4+ and CD8+ T cells) were modified, suggesting that this SNP may be altering the death signal by some other mechanism. These findings show a role for TRAILR-1 gene variations in the clinical outcome of IFN beta therapy that might have relevance as a biomarker to predict the response to IFN beta in MS.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Response of embryonic heart to hypoxia and reoxygenation: an in vitro model

OBJECTIVES: To define properly the consequences of oxygen deprivation and readmission for the functioning of the developing heart. METHODS: Spontaneously beating hearts excised from three-day-old chick embryos were loaded with a drop of viscous nontoxic silicone oil and cultured in a special chamber in which variations of PO2 at the tissue level could be strictly controlled. All parts of the hearts were simultaneously submitted to identical changes in PO2. Instantaneous heart rate, myocardial shortening, velocities of contraction and relaxation, and mechanical propagation along the heart tube were determined photometrically. RESULTS: The hearts, submitted to a PO2 ramp (0 to 9.3 kPa) or absolute anoxia, reacted rapidly, reversibly and reproducibly. Under sustained anoxia, ventricular activity stopped after 3.8±0.7 mins (n=4) and then resumed intermittently in the form of tachycardic bursts. Brief anoxia (1 min) provoked tachycardia followed by bradycardia, induced contracture, depressed contractility and retarded atrioventricular propagation. Upon reoxygenation, ventricular contractions ceased suddently for 20±11 s (n=5), whereas a residual atrial activity could persist. The duration of this arrest and the rate of recovery depended on duration of the preceding anoxia. Such a dysfunction constitutes the embryonic analogue of the oxygen paradox observed in adult hearts. Initial impulses, including arrhythmic activity, originated exclusively from the atrium, and no ventricular ectopic beats were detected whatever the conditions of oxygenation. CONCLUSIONS: This in vitro model seems promising for studying the pathophysiological mechanisms associated with hypoxia and reoxygenation in the developing heart.

Inoculum effect on the efficacies of amoxicillin-clavulanate, piperacillin-tazobactam, and imipenem against extended-spectrum β-lactamase (ESBL)-producing and non-ESBL-producing Escherichia coli in an experimental murine sepsis model.

Escherichia coli is commonly involved in infections with a heavy bacterial burden. Piperacillin-tazobactam and carbapenems are among the recommended empirical treatments for health care-associated complicated intra-abdominal infections. In contrast to amoxicillin-clavulanate, both have reduced in vitro activity in the presence of high concentrations of extended-spectrum β-lactamase (ESBL)-producing and non-ESBL-producing E. coli bacteria. Our goal was to compare the efficacy of these antimicrobials against different concentrations of two clinical E. coli strains, one an ESBL-producer and the other a non-ESBL-producer, in a murine sepsis model. An experimental sepsis model {~5.5 log10 CFU/g [low inoculum concentration (LI)] or ~7.5 log(10) CFU/g [high inoculum concentration (HI)]} using E. coli strains ATCC 25922 (non-ESBL producer) and Ec1062 (CTX-M-14 producer), which are susceptible to the three antimicrobials, was used. Amoxicillin-clavulanate (50/12.5 mg/kg given intramuscularly [i.m.]), piperacillin-tazobactam (25/3.125 mg/kg given intraperitoneally [i.p.]), and imipenem (30 mg/kg i.m.) were used. Piperacillin-tazobactam and imipenem reduced spleen ATCC 25922 strain concentrations (-2.53 and -2.14 log10 CFU/g [P < 0.05, respectively]) in the HI versus LI groups, while amoxicillin-clavulanate maintained its efficacy (-1.01 log10 CFU/g [no statistically significant difference]). Regarding the Ec1062 strain, the antimicrobials showed lower efficacy in the HI than in the LI groups: -0.73, -1.89, and -1.62 log10 CFU/g (P < 0.05, for piperacillin-tazobactam, imipenem, and amoxicillin-clavulanate, respectively, although imipenem and amoxicillin-clavulanate were more efficacious than piperacillin-tazobactam). An adapted imipenem treatment (based on the time for which the serum drug concentration remained above the MIC obtained with a HI of the ATCC 25922 strain) improved its efficacy to -1.67 log10 CFU/g (P < 0.05). These results suggest that amoxicillin-clavulanate could be an alternative to imipenem treatment of infections caused by ESBL- and non-ESBL-producing E. coli strains in patients with therapeutic failure with piperacillin-tazobactam.

Use of Two-Part Regression Calibration Model to Correct for Measurement Error in Episodically Consumed Foods in a Single-Replicate Study Design: EPIC Case Study.

In epidemiologic studies, measurement error in dietary variables often attenuates association between dietary intake and disease occurrence. To adjust for the attenuation caused by error in dietary intake, regression calibration is commonly used. To apply regression calibration, unbiased reference measurements are required. Short-term reference measurements for foods that are not consumed daily contain excess zeroes that pose challenges in the calibration model. We adapted two-part regression calibration model, initially developed for multiple replicates of reference measurements per individual to a single-replicate setting. We showed how to handle excess zero reference measurements by two-step modeling approach, how to explore heteroscedasticity in the consumed amount with variance-mean graph, how to explore nonlinearity with the generalized additive modeling (GAM) and the empirical logit approaches, and how to select covariates in the calibration model. The performance of two-part calibration model was compared with the one-part counterpart. We used vegetable intake and mortality data from European Prospective Investigation on Cancer and Nutrition (EPIC) study. In the EPIC, reference measurements were taken with 24-hour recalls. For each of the three vegetable subgroups assessed separately, correcting for error with an appropriately specified two-part calibration model resulted in about three fold increase in the strength of association with all-cause mortality, as measured by the log hazard ratio. Further found is that the standard way of including covariates in the calibration model can lead to over fitting the two-part calibration model. Moreover, the extent of adjusting for error is influenced by the number and forms of covariates in the calibration model. For episodically consumed foods, we advise researchers to pay special attention to response distribution, nonlinearity, and covariate inclusion in specifying the calibration model.

Expression profiling of rectal tumors defines response to neoadjuvant treatment related genes.

To date, no effective method exists that predicts the response to preoperative chemoradiation (CRT) in locally advanced rectal cancer (LARC). Nevertheless, identification of patients who have a higher likelihood of responding to preoperative CRT could be crucial in decreasing treatment morbidity and avoiding expensive and time-consuming treatments. The aim of this study was to identify signatures or molecular markers related to response to pre-operative CRT in LARC. We analyzed the gene expression profiles of 26 pre-treatment biopsies of LARC (10 responders and 16 non-responders) without metastasis using Human WG CodeLink microarray platform. Two hundred and fifty seven genes were differentially over-expressed in the responder patient subgroup. Ingenuity Pathway Analysis revealed a significant ratio of differentially expressed genes related to cancer, cellular growth and proliferation pathways, and c-Myc network. We demonstrated that high Gng4, c-Myc, Pola1, and Rrm1 mRNA expression levels was a significant prognostic factor for response to treatment in LARC patients (p<0.05). Using this gene set, we were able to establish a new model for predicting the response to CRT in rectal cancer with a sensitivity of 60% and 100% specificity. Our results reflect the value of gene expression profiling to gain insight about the molecular pathways involved in the response to treatment of LARC patients. These findings could be clinically relevant and support the use of mRNA levels when aiming to identify patients who respond to CRT therapy.

Efficacy of prescribed injectable diacetylmorphine in the Andalusian trial: Bayesian analysis of responders and non-responders according to a multi domain outcome index.

BACKGROUND The objective of this research was to evaluate data from a randomized clinical trial that tested injectable diacetylmorphine (DAM) and oral methadone (MMT) for substitution treatment, using a multi-domain dichotomous index, with a Bayesian approach. METHODS Sixty two long-term, socially-excluded heroin injectors, not benefiting from available treatments were randomized to receive either DAM or MMT for 9 months in Granada, Spain. Completers were 44 and data at the end of the study period was obtained for 50. Participants were determined to be responders or non responders using a multi-domain outcome index accounting for their physical and mental health and psychosocial integration, used in a previous trial. Data was analyzed with Bayesian methods, using information from a similar study conducted in The Netherlands to select a priori distributions. On adding the data from the present study to update the a priori information, the distribution of the difference in response rates were obtained and used to build credibility intervals and relevant probability computations. RESULTS In the experimental group (n = 27), the rate of responders to treatment was 70.4% (95% CI 53.287.6), and in the control group (n = 23), it was 34.8% (95% CI 15.354.3). The probability of success in the experimental group using the a posteriori distributions was higher after a proper sensitivity analysis. Almost the whole distribution of the rates difference (the one for diacetylmorphine minus methadone) was located to the right of the zero, indicating the superiority of the experimental treatment. CONCLUSION The present analysis suggests a clinical superiority of injectable diacetylmorphine compared to oral methadone in the treatment of severely affected heroin injectors not benefiting sufficiently from the available treatments. TRIAL REGISTRATION Current Controlled Trials ISRCTN52023186.

The generation and re-generation of social capital and enterprises in multi-stakeholders social cooperative enterprises: a system dynamic approach

Theories on social capital and on social entrepreneurship have mainly highlighted the attitude of social capital to generate enterprises and to foster good relations between third sector organizations and the public sector. This paper considers the social capital in a specific third sector enterprise; here, multi-stakeholder social cooperatives are seen, at the same time, as social capital results, creators and incubators. In the particular enterprises that identify themselves as community social enterprises, social capital, both as organizational and relational capital, is fundamental: SCEs arise from but also produce and disseminate social capital. This paper aims to improve the building of relational social capital and the refining of helpful relations drawn from other arenas, where they were created and from where they are sometimes transferred to other realities, where their role is carried on further (often working in non-profit, horizontally and vertically arranged groups, where they share resources and relations). To represent this perspective, we use a qualitative system dynamic approach in which social capital is measured using proxies. Cooperation of volunteers, customers, community leaders and third sector local organizations is fundamental to establish trust relations between public local authorities and cooperatives. These relations help the latter to maintain long-term contracts with local authorities as providers of social services and enable them to add innovation to their services, by developing experiences and management models and maintaining an interchange with civil servants regarding these matters. The long-term relations and the organizational relations linking SCEs and public organizations help to create and to renovate social capital. Thus, multi-stakeholder cooperatives originated via social capital developed in third sector organizations produce new social capital within the cooperatives themselves and between different cooperatives (entrepreneurial components of the third sector) and the public sector. In their entrepreneurial life, cooperatives have to contrast the "working drift," as a result of which only workers remain as members of the cooperative, while other stakeholders leave the organization. Those who are not workers in the cooperative are (stake)holders with "weak ties," who are nevertheless fundamental in making a worker's cooperative an authentic social multi-stakeholders cooperative. To maintain multi-stakeholder governance and the relations with third sector and civil society, social cooperatives have to reinforce participation and dialogue with civil society through ongoing efforts to include people that provide social proposals. We try to represent these processes in a system dynamic model applied to local cooperatives, measuring the social capital created by the social cooperative through proxies, such as number of volunteers and strong cooperation with public institutions. Using a reverse-engineering approach, we can individuate the determinants of the creation of social capital and thereby give support to governance that creates social capital.

Ab initio absorption spectrum of NiO combining molecular dynamics with the embedded cluster approach in a discrete reaction field

We developed a procedure that combines three complementary computational methodologies to improve the theoretical description of the electronic structure of nickel oxide. The starting point is a Car-Parrinello molecular dynamics simulation to incorporate vibrorotational degrees of freedom into the material model. By means ofcomplete active space self-consistent field second-order perturbation theory (CASPT2) calculations on embedded clusters extracted from the resulting trajectory, we describe localized spectroscopic phenomena on NiO with an efficient treatment of electron correlation. The inclusion of thermal motion into the theoretical description allowsus to study electronic transitions that, otherwise, would be dipole forbidden in the ideal structure and results in a natural reproduction of the band broadening. Moreover, we improved the embedded cluster model by incorporating self-consistently at the complete active space self-consistent field (CASSCF) level a discrete (or direct) reaction field (DRF) in the cluster surroundings. The DRF approach offers an efficient treatment ofelectric response effects of the crystalline embedding to the electronic transitions localized in the cluster. We offer accurate theoretical estimates of the absorption spectrum and the density of states around the Fermi level of NiO, and a comprehensive explanation of the source of the broadening and the relaxation of the charge transferstates due to the adaptation of the environment

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.