Computational drug design strategies applied to the modelling of human immunodeficiency virus-1 reverse transcriptase inhibitors

Reverse transcriptase (RT) is a multifunctional enzyme in the human immunodeficiency virus (HIV)-1 life cycle and represents a primary target for drug discovery efforts against HIV-1 infection. Two classes of RT inhibitors, the nucleoside RT inhibitors (NRTIs) and the nonnucleoside transcriptase inhibitors are prominently used in the highly active antiretroviral therapy in combination with other anti-HIV drugs. However, the rapid emergence of drug-resistant viral strains has limited the successful rate of the anti-HIV agents. Computational methods are a significant part of the drug design process and indispensable to study drug resistance. In this review, recent advances in computer-aided drug design for the rational design of new compounds against HIV-1 RT using methods such as molecular docking, molecular dynamics, free energy calculations, quantitative structure-activity relationships, pharmacophore modelling and absorption, distribution, metabolism, excretion and toxicity prediction are discussed. Successful applications of these methodologies are also highlighted.

Immunotherapy for ovarian cancer: recent advances and perspectives.

PURPOSE OF REVIEW: Epithelial ovarian cancer is the most frequent cause of gynecologic cancer-related mortality in women, and prognosis for patients with recurrent or metastatic disease is extremely poor. Therefore, there is an enormous unmet need for the development of novel therapies in this indication. Although surgery and chemotherapy can improve survival rates, it is necessary to integrate alternative strategies, such as immunotherapy to improve the outcomes for patients with advanced ovarian cancer. RECENT FINDINGS: We will discuss the rationale of immunotherapy and some of the mechanisms of immunogenicity in ovarian cancer. We will highlight current results with cancer vaccines, adoptive T-cell therapy and immunomodulatory agents and will summarize the immune effects of selected chemotherapeutic agents, radiotherapy and recent results with combinatorial approaches in this disease setting. We will also discuss recent and potential future therapeutic interventions that might circumvent tumor-mediated immunosuppression. SUMMARY: Dramatic increase in the number of immunotherapy clinical trials was seen in the past decade with promising results in enhancing antitumor immune response and cancer vaccine efficacy. The future challenge for immunotherapy against ovarian cancer is to use a combinatorial approach to test rational, potentially synergistic immunotherapy combinations that can induce efficient antitumor immunity and prolong patients' survival.

Two-sided learning in new keynesian models: dynamics, (lack of) convergence and the value of information

This paper investigates the role of learning by private agents and the central bank (two-sided learning) in a New Keynesian framework in which both sides of the economy have asymmetric and imperfect knowledge about the true data generating process. We assume that all agents employ the data that they observe (which may be distinct for different sets of agents) to form beliefs about unknown aspects of the true model of the economy, use their beliefs to decide on actions, and revise these beliefs through a statistical learning algorithm as new information becomes available. We study the short-run dynamics of our model and derive its policy recommendations, particularly with respect to central bank communications. We demonstrate that two-sided learning can generate substantial increases in volatility and persistence, and alter the behavior of the variables in the model in a signifficant way. Our simulations do not converge to a symmetric rational expectations equilibrium and we highlight one source that invalidates the convergence results of Marcet and Sargent (1989). Finally, we identify a novel aspect of central bank communication in models of learning: communication can be harmful if the central bank's model is substantially mis-specified

Uncertainty, electoral Incentives and political myopia

In this paper, we study the determinants of political myopia in a rational model of electoral accountability where the key elements are informational frictions and uncertainty. We build a framework where political ability is ex-ante unknown and policy choices are not perfectly observable. On the one hand, elections improve accountability and allow to keep well-performing incumbents. On the other, politicians invest too little in costly policies with future returns in an attempt to signal high ability and increase their reelection probability. Contrary to the conventional wisdom, uncertainty reduces political myopia and may, under some conditions, increase social welfare. We use the model to study how political rewards can be set so as to maximise social welfare and the desirability of imposing a one-term limit to governments. The predictions of our theory are consistent with a number of stylised facts and with a new empirical observation documented in this paper: aggregate uncertainty, measured by economic volatility, is associated to better ...scal discipline in a panel of 20 OECD countries.

Genetic dissection of sodium and potassium transport along the aldosterone-sensitive distal nephron: Importance in the control of blood pressure and hypertension.

In this review, we discuss genetic evidence supporting Guyton's hypothesis stating that blood pressure control is critically depending on fluid handling by the kidney. The review is focused on the genetic dissection of sodium and potassium transport in the distal nephron and the collecting duct that are the most important sites for the control of sodium and potassium balance by aldosterone and angiotensin II. Thanks to the study of Mendelian forms of hypertension and their corresponding transgenic mouse models, three main classes of diuretic receptors (furosemide, thiazide, amiloride) and the main components of the aldosterone- and angiotensin-dependent signaling pathways were molecularly identified over the past 20years. This will allow to design rational strategies for the treatment of hypertension and for the development of the next generation of diuretics.

CD44 attenuates activation of the hippo signaling pathway and is a prime therapeutic target for glioblastoma.

Glioblastoma multiforme (GBM) is the most aggressive brain tumor that, by virtue of its resistance to chemotherapy and radiotherapy, is currently incurable. Identification of molecules whose targeting may eliminate GBM cells and/or sensitize glioblastoma cells to cytotoxic drugs is therefore urgently needed. CD44 is a major cell surface hyaluronan receptor and cancer stem cell marker that has been implicated in the progression of a variety of cancer types. However, the major downstream signaling pathways that mediate its protumor effects and the role of CD44 in the progression and chemoresponse of GBM have not been established. Here we show that CD44 is upregulated in GBM and that its depletion blocks GBM growth and sensitizes GBM cells to cytotoxic drugs in vivo. Consistent with this observation, CD44 antagonists potently inhibit glioma growth in preclinical mouse models. We provide the first evidence that CD44 functions upstream of the mammalian Hippo signaling pathway and that CD44 promotes tumor cell resistance to reactive oxygen species-induced and cytotoxic agent-induced stress by attenuating activation of the Hippo signaling pathway. Together, our results identify CD44 as a prime therapeutic target for GBM, establish potent antiglioma efficacy of CD44 antagonists, uncover a novel CD44 signaling pathway, and provide a first mechanistic explanation as to how upregulation of CD44 may constitute a key event in leading to cancer cell resistance to stresses of different origins. Finally, our results provide a rational explanation for the observation that functional inhibition of CD44 augments the efficacy of chemotherapy and radiation therapy.

Monitoring compliance in resistant hypertension: an important step in patient management.

Poor compliance with antihypertensive drug regimens is one recognized cause of inadequate blood pressure control. Compliance is difficult to measure, so poor adherence to treatment remains largely undiagnosed in clinical practice. When the therapeutic response to a drug is not the one expected, it is a major challenge for many physicians to decide whether the patient is a non-responder or a non-complier. Poor compliance is therefore often incorrectly interpreted as a lack of response to treatment. Not detecting non-compliance can lead to the wrong measures being taken. Electronic monitoring of compliance provides important longitudinal information about drug-intake behaviour that cannot be obtained in the clinic. Such monitoring can improve both compliance and blood pressure control, and help physicians to make more rational therapeutic decisions. A reliable assessment of compliance could have a great impact on medical costs by preventing unnecessary investigations or dose adaptations in patients who are not taking their drugs adequately, or potentially reducing the number of hospitalizations. Side-effects and lack of effectiveness are two frequent causes of poor compliance. The right choice of antihypertensive drug can therefore contribute to compliance. In this respect, it is important to find a drug regimen that is effective, long-acting and well tolerated. Long-acting antihypertensive drugs that provide good blood pressure control beyond the 24-h dosing period should perhaps be considered as drugs of choice in non-compliant patients with hypertension because they help to prevent the consequences of occasional drug omissions.

Comment faire de la surveillance sanitaire? L'exemple de l'Observatoire Valaisan de la Santé en Suisse [How to conduct public health surveillance? The example of the Observatoire Valaisan de la Santé in Switzerland].

OBJECTIVE: To describe the goals and methods of contemporary public health surveillance and to present the activities of the Observatoire Valaisan de la Santé (OVS), a tool unique in Switzerland to conduct health surveillance for the population of a canton. METHODS: Narrative review and presentation of the OVS. RESULTS: Public health surveillance consists of systematic and continuous collection, analysis, interpretation and dissemination of health data necessary for public health planning. Surveillance is organized according to contemporary public health issues. Switzerland is currently in an era dominated by chronic diseases due to ageing of the population. This "new public health" era is also characterized by the growing importance of health technology, rational risk management, preventive medicine and health promotion, and the central role of the citizen/patient. Information technologies provide access to new health data, but public health surveillance methods need to be adapted. In Switzerland, health surveillance activities are conducted by several public and private bodies, at federal and cantonal levels. The Valais canton has set up the OVS, an integrative, regional, and reactive system to conduct surveillance. CONCLUSION: Public health surveillance provides information useful for public health decisions and actions. It constitutes a key element for public health planning.

Evaluation of melanoma vaccines with molecularly defined antigens by ex vivo monitoring of tumor-specific T cells.

Immunotherapy of melanoma is aimed to mobilize cytolytic CD8+ T cells playing a central role in protective immunity. Despite numerous clinical vaccine trials, only few patients exhibited strong antigen-specific T-cell activation, stressing the need to improve vaccine strategies. For a rational development, we propose to focus on molecularly defined vaccine components, and evaluate their immunogenicity with highly reproducible and standardized methods for ex vivo immune monitoring. Careful immunogenicity comparison of vaccine formulations in phase I/II studies allow to select optimized vaccines for subsequent clinical efficacy testing in large scale phase III trials.

Multifunctional ligands for application in Alzheimer’s Disease: molecular modelling and biological evaluation

Projecte de recerca elaborat a partir d’una estada a la University of British Columbia, Canadà, entre 2010 i 2012 La malaltia d'Alzheimer (MA) representa avui la forma més comuna de demència en la població envellida. Malgrat fa 100 anys que va ser descoberta, encara avui no existeix cap tractament preventiu i/o curatiu ni cap agent de diagnòstic que permeti valorar quantitativament l'evolució d'aquesta malaltia. L'objectiu en el que s'emmarca aquest treball és contribuir a aportar solucions al problema de la manca d'agents terapèutics i de diagnosi, unívocs i rigorosos, per a la MA. Des del camp de la química bioinorgànica és fàcil fixar-se en l'excessiva concentració d'ions Zn(II) i Cu(II) en els cervells de malalts de MA, plantejar-se la seva utilització com a dianes terapèutica i, en conseqüència, cercar agents quelants que evitin la formació de plaques senils o contribueixin a la seva dissolució. Si bé aquest va ser el punt de partida d’aquest projecte, els múltiples factors implicats en la patogènesi de la MA fan que el clàssic paradigma d’ ¨una molècula, una diana¨ limiti la capacitat de la molècula de combatre aquesta malaltia tan complexa. Per tant, un esforç considerable s’ha dedicat al disseny d’agentsmultifuncionals que combatin els múltiples factors que caracteritzen el desenvolupament de la MA. En el present treball s’han dissenyat agents multifuncionals inspirats en dos esquelets moleculars ben establers i coneguts en el camp de la química medicinal: la tioflavina-T (ThT) i la deferiprona (DFP). La utilització de tècniques in silico que inclouen càlculs farmacocinètics i modelatge molecular ha estat un procés cabdal per a l’avaluació dels millors candidats en base als següents requeriments: (a) compliment de determinades propietats farmacocinètiques que estableixin el seu possible ús com a fàrmac (b) hidrofobicitat adequada per travessar la BBB i (c) interacció amb el pèptid Aen solució.

On the foundations of well-being economics and policy

When one wishes to implement public policies, there is a previous need of comparing different actions and valuating and evaluating them to assess their social attractiveness. Recently the concept of well-being has been proposed as a multidimensional proxy for measuring societal prosperity and progress; a key research topic is then on how we can measure and evaluate this plurality of dimensions for policy decisions. This paper defends the thesis articulated in the following points: 1. Different metrics are linked to different objectives and values. To use only one measurement unit (on the grounds of the so-called commensurability principle) for incorporating a plurality of dimensions, objectives and values, implies reductionism necessarily. 2. Point 1) can be proven as a matter of formal logic by drawing on the work of Geach about moral philosophy. This theoretical demonstration is an original contribution of this article. Here the distinction between predicative and attributive adjectives is formalised and definitions are provided. Predicative adjectives are further distinguished into absolute and relative ones. The new concepts of set commensurability and rod commensurability are introduced too. 3. The existence of a plurality of social actors, with interest in the policy being assessed, causes that social decisions involve multiple types of values, of which economic efficiency is only one. Therefore it is misleading to make social decisions based only on that one value. 4. Weak comparability of values, which is grounded on incommensurability, is proved to be the main methodological foundation of policy evaluation in the framework of well-being economics. Incommensurability does not imply incomparability; on the contrary incommensurability is the only rational way to compare societal options under a plurality of policy objectives. 5. Weak comparability can be implemented by using multi-criteria evaluation, which is a formal framework for applied consequentialism under incommensurability. Social Multi-Criteria Evaluation, in particular, allows considering both technical and social incommensurabilities simultaneously.

Education, Equity and Distributive Beliefs: Evidences from the Chilean Case

During the year 2011, Chile has been scenario of several student's demonstrations claiming for more equity in the access to the higher education. The high support to the protests by the side of the general population (nearly 89% of approval in public opinion polls) seems to suggest the existence of a large consensus about the weaknesses of the Chilean educative model, a model that would challenge the traditional ideals of meritocracy and social mobility that are at the core of the educational systems in modern societies. In this context, a question that remains open is to what extent these claims are mostly based on consensual equality ideals, or whether they are influenced by individual socio-economic determinants vis-à-vis rational motives. Using data of the social inequality module International Social Survey Program (ISSP) of 2009, this research analyzes perceptions and beliefs about education and the distributive system as well as the influence of income and educational variables, through a structural equation modeling framework. Preliminary results indicate the presence of socioeconomic cleavages in relation to the fairness of the educational system, questioning the assumption about a normative consensus.

U.S. Farm Policy and the Variability of Commodity Prices and Farm Revenues, February 2000

A dynamic, three-commodity rational-expectations storage model is used to compare the impact of the Federal Agricultural Improvement and Reform (FAIR) Act of 1996 with a freemarket policy and with the agricultural policies that preceded the FAIR Act. Results support the hypothesis that the changes made when FAIR was enacted did not lead to permanent significant increases in the volatility of farm prices or revenues. An important finding is that the main economic impacts of the Pre-FAIR scenario, relative to the free-market regime were to transfer income to farmers and to substitute government storage for private storage in a way that did little to support prices or to stabilize farm incomes.

Evolving from inferences to decisions in the interpretation of scientific evidence

Le travail d'un(e) expert(e) en science forensique exige que ce dernier (cette dernière) prenne une série de décisions. Ces décisions sont difficiles parce qu'elles doivent être prises dans l'inévitable présence d'incertitude, dans le contexte unique des circonstances qui entourent la décision, et, parfois, parce qu'elles sont complexes suite à de nombreuse variables aléatoires et dépendantes les unes des autres. Etant donné que ces décisions peuvent aboutir à des conséquences sérieuses dans l'administration de la justice, la prise de décisions en science forensique devrait être soutenue par un cadre robuste qui fait des inférences en présence d'incertitudes et des décisions sur la base de ces inférences. L'objectif de cette thèse est de répondre à ce besoin en présentant un cadre théorique pour faire des choix rationnels dans des problèmes de décisions rencontrés par les experts dans un laboratoire de science forensique. L'inférence et la théorie de la décision bayésienne satisfont les conditions nécessaires pour un tel cadre théorique. Pour atteindre son objectif, cette thèse consiste de trois propositions, recommandant l'utilisation (1) de la théorie de la décision, (2) des réseaux bayésiens, et (3) des réseaux bayésiens de décision pour gérer des problèmes d'inférence et de décision forensiques. Les résultats présentent un cadre uniforme et cohérent pour faire des inférences et des décisions en science forensique qui utilise les concepts théoriques ci-dessus. Ils décrivent comment organiser chaque type de problème en le décomposant dans ses différents éléments, et comment trouver le meilleur plan d'action en faisant la distinction entre des problèmes de décision en une étape et des problèmes de décision en deux étapes et en y appliquant le principe de la maximisation de l'utilité espérée. Pour illustrer l'application de ce cadre à des problèmes rencontrés par les experts dans un laboratoire de science forensique, des études de cas théoriques appliquent la théorie de la décision, les réseaux bayésiens et les réseaux bayésiens de décision à une sélection de différents types de problèmes d'inférence et de décision impliquant différentes catégories de traces. Deux études du problème des deux traces illustrent comment la construction de réseaux bayésiens permet de gérer des problèmes d'inférence complexes, et ainsi surmonter l'obstacle de la complexité qui peut être présent dans des problèmes de décision. Trois études-une sur ce qu'il faut conclure d'une recherche dans une banque de données qui fournit exactement une correspondance, une sur quel génotype il faut rechercher dans une banque de données sur la base des observations faites sur des résultats de profilage d'ADN, et une sur s'il faut soumettre une trace digitale à un processus qui compare la trace avec des empreintes de sources potentielles-expliquent l'application de la théorie de la décision et des réseaux bayésiens de décision à chacune de ces décisions. Les résultats des études des cas théoriques soutiennent les trois propositions avancées dans cette thèse. Ainsi, cette thèse présente un cadre uniforme pour organiser et trouver le plan d'action le plus rationnel dans des problèmes de décisions rencontrés par les experts dans un laboratoire de science forensique. Le cadre proposé est un outil interactif et exploratoire qui permet de mieux comprendre un problème de décision afin que cette compréhension puisse aboutir à des choix qui sont mieux informés. - Forensic science casework involves making a sériés of choices. The difficulty in making these choices lies in the inévitable presence of uncertainty, the unique context of circumstances surrounding each décision and, in some cases, the complexity due to numerous, interrelated random variables. Given that these décisions can lead to serious conséquences in the admin-istration of justice, forensic décision making should be supported by a robust framework that makes inferences under uncertainty and décisions based on these inferences. The objective of this thesis is to respond to this need by presenting a framework for making rational choices in décision problems encountered by scientists in forensic science laboratories. Bayesian inference and décision theory meets the requirements for such a framework. To attain its objective, this thesis consists of three propositions, advocating the use of (1) décision theory, (2) Bayesian networks, and (3) influence diagrams for handling forensic inference and décision problems. The results present a uniform and coherent framework for making inferences and décisions in forensic science using the above theoretical concepts. They describe how to organize each type of problem by breaking it down into its différent elements, and how to find the most rational course of action by distinguishing between one-stage and two-stage décision problems and applying the principle of expected utility maximization. To illustrate the framework's application to the problems encountered by scientists in forensic science laboratories, theoretical case studies apply décision theory, Bayesian net-works and influence diagrams to a selection of différent types of inference and décision problems dealing with différent catégories of trace evidence. Two studies of the two-trace problem illustrate how the construction of Bayesian networks can handle complex inference problems, and thus overcome the hurdle of complexity that can be present in décision prob-lems. Three studies-one on what to conclude when a database search provides exactly one hit, one on what genotype to search for in a database based on the observations made on DNA typing results, and one on whether to submit a fingermark to the process of comparing it with prints of its potential sources-explain the application of décision theory and influ¬ence diagrams to each of these décisions. The results of the theoretical case studies support the thesis's three propositions. Hence, this thesis présents a uniform framework for organizing and finding the most rational course of action in décision problems encountered by scientists in forensic science laboratories. The proposed framework is an interactive and exploratory tool for better understanding a décision problem so that this understanding may lead to better informed choices.

Identification of cancer stem cells in Ewing's sarcoma.

Cancer stem cells that display tumor-initiating properties have recently been identified in several distinct types of malignancies, holding promise for more effective therapeutic strategies. However, evidence of such cells in sarcomas, which include some of the most aggressive and therapy-resistant tumors, has not been shown to date. Here, we identify and characterize cancer stem cells in Ewing's sarcoma family tumors (ESFT), a highly aggressive pediatric malignancy believed to be of mesenchymal stem cell (MSC) origin. Using magnetic bead cell separation of primary ESFT, we have isolated a subpopulation of CD133+ tumor cells that display the capacity to initiate and sustain tumor growth through serial transplantation in nonobese diabetic/severe combined immunodeficiency mice, re-establishing at each in vivo passage the parental tumor phenotype and hierarchical cell organization. Consistent with the plasticity of MSCs, in vitro differentiation assays showed that the CD133+ cell population retained the ability to differentiate along adipogenic, osteogenic, and chondrogenic lineages. Quantitative real-time PCR analysis of genes implicated in stem cell maintenance revealed that CD133+ ESFT cells express significantly higher levels of OCT4 and NANOG than their CD133- counterparts. Taken together, our observations provide the first identification of ESFT cancer stem cells and demonstration of their MSC properties, a critical step towards a better biological understanding and rational therapeutic targeting of these tumors.