1,721,076 research outputs found
Ghrelin anticonvulsive properties: is it matter of desacylation?
No full textWe have read the article by Portelli et al. (2012) that thoroughly reviews the still scarce literature existing on the role of ghrelin and its receptor (GHSR1a) in epilepsy. As the authors recognize, clinical studies on the relationship between ghrelin and epilepsy are largely contradictory, since some of them show increased ghrelin levels, other no changes or even a decrease in patients affected by epilepsy: so, factors causing such variability need to be carefully addressed in future investigations. On the other hand, Portelli and coworkers look at data coming from animal studies as clearly demonstrating a role for ghrelin as anticonvulsant. Supporting this view, they cite two different studies showing that ghrelin is able to counteract the convulsive effects of pentylenetetrazole (Obay et al., 2007) or kainic acid (Lee et al., 2010), and a third one that reports negative findings both in pilocarpine and kainate models (Biagini et al, 2001). In our opinion, these discrepancies are only apparent, since Lee and coworkers (2010) reported beneficial effects not on seizure prevention, but on seizure severity, whereas we evaluated just seizure induction. More intriguingly, Obay and coworkers (2007) found that ghrelin dose-dependently increased latency to (but did not prevent) myoclonic jerks, tonic generalized extension and generalized clonic seizures. Duration of tonic generalized extension was also decreased by ghrelin, but duration of the initial myoclonic jerk was increased as well as the duration of clonic generalized seizures. Furthermore, a small effect on overall seizure duration was obtained only with the highest ghrelin dose. Alternatively, we have reported that GHSR1a ligands other than ghrelin prevent seizures in pilocarpine-treated rats, and that desacyl ghrelin increases the latency to first generalized seizures in the kainate model.A key observation to understand these discrepancies is that “...In human plasma, acylated ghrelin was found to disappear more quickly than total ghrelin, with elimination half-lives of 9-13 and 27-31 min, respectively (Akamizu et al., 2004)”, as cited by Portelli and coauthors (page 586 of the review). In spite that ghrelin was always administered 30 min before the tested convulsant (Obay et al., 2007; Lee et al., 2010), in no one of the mentioned studies circulating levels of ghrelin and desacyl ghrelin were assessed. In view of the probable conversion of ghrelin to desacyl ghrelin by butyrylcholinesterase (De Vriese et al., 2004) during latency to convulsions, it cannot be excluded that the anticonvulsive effects attributed to ghrelin could be due to desacyl ghrelin. Accordingly, the highly effective GHSR1a agonist JMV-1843 (also known as EP01572 or ARD-07), which has a better kinetics than ghrelin, in our hands failed to counteract the pilocarpine effects. We believe that the present evidence is still too poor to suggest a role for GHSR1a agonists in seizure prevention, at least in animal models. The same questions apply to clinical investigations, in which the balance between ghrelin and desacyl ghrelin is not clearly addressed
Estimation of distribution parameters as a tool for model-based system engineering and model identification
Full text linkThe estimation of the parameters of a probability distribution (e.g., moments) plays an important role both in the model-based system engineering (e.g., analysis and verification through Statistical Model Checking (SMC)) and in the identification of parameters of predictive models (e.g., systems biology, social networks). The contribution of this PhD thesis is both on the algorithm side and on the modeling side. On the algorithm side, we overview a set of Monte Carlo-based Statistical Model Checking tools and algorithms for the verification of Cyber-Physical Systems, and we provide selection criteria for the verification problem at hand. Furthermore, we present an efficient Monte Carlo-based algorithm to estimate the expected value of a multivariate random variable, when marginal density functions are not known. We prove the correctness of our algorithm, we give an Upper Bound and a Lower Bound to its complexity and we present experimental results confirming our evaluations. On the modeling side, we present a mechanistic and identifiable model to predict, at the node level and at a set of nodes level, the expected value of the retweeting rate of a message inside a social network, at a certain time. Our model parameters are random variables, whose distribution parameters are estimated from an available dataset. We experimentally show that our model reliably predicts both the qualitative and the quantitative time behavior of retweeting rates. This is confirmed by the high correlation between the predicted and the observed data. These results enable a simulation-based analysis of users or of a set of users' behaviors inside a network
Artificial intelligence and model checking methods for in silico clinical trials
Full text linkModel-based approaches to safety and efficacy assessment of pharmacological treatments (In Silico Clinical Trials, ISCT) hold the promise to decrease time and cost for the needed experimentations, reduce the need for animal and human testing, and enable personalised medicine, where treatments tailored for each single patient can be designed before being actually administered.
Research in Virtual Physiological Human (VPH) is harvesting such promise by developing quantitative mechanistic models of patient physiology and drugs. Depending on many parameters, such models define physiological differences among different individuals and different reactions to drug administrations. Value assignments to model parameters can be regarded as Virtual Patients (VPs). Thus, as in vivo clinical trials test relevant drugs against suitable candidate patients, ISCT simulate effect of relevant drugs against VPs covering possible behaviours that might occur in vivo.
Having a population of VPs representative of the whole spectrum of human patient behaviours is a key enabler of ISCT.
However, VPH models of practical relevance are typically too complex to be solved analytically or to be formally analysed. Thus, they are usually solved numerically within simulators. In this setting, Artificial Intelligence and Model Checking methods are typically devised. Indeed, a VP coupled together with a pharmacological treatment represents a closed-loop model where the VP plays the role of a physical subsystem and the treatment strategy plays the role of the control software. Systems with this structure are known as Cyber-Physical Systems (CPSs). Thus, simulation-based methodologies for CPSs can be employed within personalised medicine in order to compute representative VP populations and to conduct ISCT.
In this thesis, we advance the state of the art of simulation-based Artificial Intelligence and Model Checking methods for ISCT in the following directions.
First, we present a Statistical Model Checking (SMC) methodology based on hypothesis testing that, given a VPH model as input, computes a population of VPs which is representative (i.e., large enough to represent all relevant phenotypes, with a given degree of statistical confidence) and stratified (i.e., organised as a multi-layer hierarchy of homogeneous sub-groups). Stratification allows ISCT to adaptively focus on specific phenotypes, also supporting prioritisation of patient sub-groups in follow-up in vivo clinical trials.
Second, resting on a representative VP population, we design an ISCT aiming at optimising a complex treatment for a patient digital twin, that is the virtual counterpart of that patient physiology defined by means of a set of VPs. Our ISCT employs an intelligent search driving a VPH model simulator to seek the lightest but still effective treatment for the input patient digital twin.
Third, to enable interoperability among VPH models defined with different modelling and simulation environments and to increase efficiency of our ISCT, we also design an optimised simulator driver to speed-up backtracking-based search algorithms driving simulators.
Finally, we evaluate the effectiveness of our presented methodologies on state-of-the-art use cases and validate our results on retrospective clinical data
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Moexipril and quinapril inhibition of tissue angiotensin-converting enzyme activity in the rat: evidence for direct effects in heart, lung and kidney and stimulation of prostacyclin generation
No full textThe activation of angiotensin converting enzyme (ACE) may contribute to the development of vascular and myocardial structural changes. The level of ACE is stable in human plasma, and only limited data are available on its regulation at the tissue level. The aim of this study was to characterize the effects of two ACE inhibitors, moexipril and quinapril on tissue ACE activity. Adult male rats were treated intragastrically once daily for 6 days either with 2 mg/kg moexipril or quinapril. After single treatment, moexipril and quinapril effectively inhibited ACE activity in plasma and slightly in heart and aorta, whereas after 6 days of treatment they inhibited ACE activity in plasma (87% and 94%, respectively), lung (92% and 93%), myocardium (26% and 23%), kidney (21% and 20%), and aorta (39% and 40%), but not in skeletal muscle. Interestingly, the two ACE-inhibitors also induced a significant increase in cardiac homogenates of 6-keto-PGF(1alpha) levels, an important index of PGl(2) generation. To test whether the reduced effects of ACE inhibitors in heart and kidney were caused by a limited availability of the drugs, 100 mul of lung, heart and kidney homogenates from control rats were incubated in vitro with moexipril and quinapril immediately before assay. Both drugs were more effective in lung than heart and kidney homogenates, with inhibition values superimposable to those obtained in vivo. These results clearly indicate that inhibition of tissue ACE activity does not depend primarily on the availability of ACE inhibitors in each organ
A Web personalization system based on a neuro-fuzzy strategy
No full textIn this paper we investigate the use of a neuro-fuzzy strategy to develop a Web personalization system that
dynamically suggests interesting URLs for the current user. As a preliminary step, user access logs are
analyzed to identify user sessions. Then, groups of users which exhibit a common browser behavior (i.e. user
profiles) are discovered by applying a fuzzy clustering algorithm to the user sessions. Finally, a knowledge
extraction process is carried out to derive associations between user profiles and relevant Web pages to be
suggested to users. In particular, a hybrid approach based on the combination of the fuzzy reasoning and the
connectionist paradigm is proposed in order to derive knowledge from session data and represent it in the
comprehensible form of fuzzy rules. The derived knowledge is ultimately used by an online recommendation
module to dynamically suggest links to Web pages judged interesting for the current user
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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