1,720,960 research outputs found
Optimising migraine treatment. From drug-drug interactions to personalized medicine
Full text linkMigraine is the most disabling and expensive chronic disorders, the etiology of which is still not fully known. The neuronal systems, (glutammatergic, dopaminergic, serotoninergic and GABA-ergic) whose functionality is partly attributable to genetically determined factors, has been suggested to play an important role. The treatment of acute attacks and the prophylactic management of chronic forms include the use of different category of drugs, and it is demonstrated that not each subject has the same clinical answer to them. The reason of this is to be searched in different functional capacity and quantity of phase I enzymes (such as different isoforms of CYP P450), phase II enzymes (such as UDP-glucuronosyltransferases), receptors (such as OPRM1 for opioids) and transporters (such as ABCB1) involved in the metabolic destiny of each drug, all of these dictated by DNA and RNA variations. The general picture is further exacerbated by the need for polytherapies, often also to treat comorbidities, which may interfere with the pharmacological action of anti-migraine drugs. Personalized medicine has the objective of setting the optimal therapies in the light of the functional biochemical asset and of the comorbidities of the individual patient, in order to obtain the best clinical response. Novel therapeutic perspectives in migraine includes biotechnological drugs directed against molecules (such as CGRP and its receptor) that cause vasodilatation at the peripheral level of the meningeal blood vessels and reflex stimulation of the parasympathetic system. Drug-drug interactions and the possible competitive metabolic destiny should be studied by the application of pharmacogenomics in large scale. Drug-drug interactions and their possible competitive metabolic destiny should be studied by the application of pharmacogenomics in large scale
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
Drug–drug interactions and pharmacogenomic evaluation in colorectal cancer patients. The new drug-pin® system comprehensive approach
Full text linkDrug–drug interactions (DDIs) can affect both treatment efficacy and toxicity. We used Drug-PIN® (Personalized Interactions Network) software in colorectal cancer (CRC) patients to evaluate drug–drug–gene interactions (DDGIs), defined as the combination of DDIs and individual genetic polymorphisms. Inclusion criteria were: (i) stage II-IV CRC; (ii) ECOG PS (Performance status sec. Eastern coperative oncology group) ≤2; (iii) ≥5 concomitant drugs; and (iv) adequate renal, hepatic, and bone marrow function. The Drug-PIN® system analyzes interactions between active and/or pro-drug forms by integrating biochemical, demographic, and genomic data from 110 SNPs. We selected DDI, DrugPin1, and DrugPin2 scores, resulting from concomitant medication interactions, concomitant medications, and SNP profiles, and DrugPin1 added to chemotherapy drugs, respectively. Thirty-four patients, taking a median of seven concomitant medications, were included. The median DrugPin1 and DrugPin2 scores were 42.6 and 77.7, respectively. In 13 patients, the DrugPin2 score was two-fold higher than the DrugPin1 score, with 7 (54%) of these patients experiencing severe toxicity that required hospitalization. On chi-squared testing for any toxic-ity, a doubled DrugPin2 score (p = 0.001) was significantly related to G3–G4 toxicity. Drug-PIN® software may prevent severe adverse events, decrease hospitalizations, and improve survival in cancer patients
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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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