1,721,022 research outputs found
Predicting and characterizing selective multiple drug treatments for metabolicdiseases and cancer
Full text linkBackground: In the field of drug discovery, assessing the potential of multidrug therapies is a difficult task because of the combinatorial complexity (both theoretical and experimental) and because of the requirements on the selectivity of the therapy. To cope with this problem, we have developed a novel method for the systematic in silico investigation of synergistic effects of currently available drugs on genome-scale metabolic networks. The algorithm finds the optimal combination of drugs which guarantees the inhibition of an objective function, while minimizing the side effect on the overall network. Results: Two different applications are considered: finding drug synergisms for human metabolic diseases (like diabetes, obesity and hypertension) and finding antitumoral drug combinations with minimal side effect on the normal human metabolism.The results we obtain are consistent with some of the available therapeutic indications and predict some new multiple drug treatments.A cluster analysis on all possible interactions among the currently available drugs indicates a limited variety on the metabolic targets for the approved drugs. Conclusion: The in silico prediction of drug synergism can represent an important tool for the repurposing of drug in a realistic perspective which considers also the selectivty of the therapy. Moreover, for a more profitable exploitation of drug-drug interactions, also drugs which show a too low efficacy but which have a non-common mechanism of action, can be reconsider as potential ingredients of new multicompound therapeutic indications.Needless to say the clues provided by a computational study like ours need in any case to be thoroughly evaluated experimentally
Partial inhibition and bilevel optimization in flux balance analysis
Full text linkMotivation: Within Flux Balance Analysis, the investigation of complex subtasks, such as finding the optimal perturbation of the network or finding an optimal combination of drugs, often requires to set up a bilevel optimization problem. In order to keep the linearity and convexity of these nested optimization problems, an ON/OFF description of the effect of the perturbation (i.e. Boolean variable) is normally used. This restriction may not be realistic when one wants, for instance, to describe the partial inhibition of a reaction induced by a drug.Results: In this paper we present a formulation of the bilevel optimization which overcomes the oversimplified ON/OFF modeling while preserving the linear nature of the problem. A case study is considered: the search of the best multi-drug treatment which modulates an objective reaction and has the minimal perturbation on the whole network. The drug inhibition is described and modulated through a convex combination of a fixed number of Boolean variables. The results obtained from the application of the algorithm to the core metabolism of E.coli highlight the possibility of finding a broader spectrum of drug combinations compared to a simple ON/OFF modeling.Conclusions: The method we have presented is capable of treating partial inhibition inside a bilevel optimization, without loosing the linearity property, and with reasonable computational performances also on large metabolic networks. The more fine-graded representation of the perturbation allows to enlarge the repertoire of synergistic combination of drugs for tasks such as selective perturbation of cellular metabolism. This may encourage the use of the approach also for other cases in which a more realistic modeling is required. © 2013 Facchetti and Altafini; licensee BioMed Central Ltd
Errors in Italian as Second Language
Full text linkThis essay deals with a series of strategies that second or foreign language learners adopt in an effort to avoid making predictable errors. One of the most significant and least studied aspects in the academic field is the type of strategies that are put in place to make changes in the planning of the discourse, when the elements are not available to cope with the event, the communication need or when a speaker wants to change subject from a little-known conversational or textual sector. We intend to examine the concept of competence with respect to performance, the role and type of errors, ending up eliciting a taxonomy of interventions by learners, aimed at avoiding errors in oral and written production
Exploring the low-energy landscape of large-scale signed social networks.
No full textAnalogously to a spin glass, a large-scale signed social network is characterized by the presence of disorder, expressed in this context (and in the social network literature) by the concept of structural balance. If, as we have recently shown, the signed social networks currently available have a limited amount of true disorder (or frustration), it is also interesting to investigate how this frustration is organized, by exploring the landscape of near-optimal structural balance. What we obtain in this paper is that while one of the networks analyzed shows a unique valley of minima, and a funneled landscape that gradually and smoothly worsens as we move away from the optimum, another network shows instead several distinct valleys of optimal or near-optimal structural balance, separated by energy barriers determined by internally balanced subcommunities of users, a phenomenon similar to the replica-symmetry breaking of spin glasses. Multiple, essentially isoenergetic, arrangements of these communities are possible. Passing from one valley to another requires one to destroy the internal arrangement of these balanced subcommunities and then to reform it again. It is essentially this process of breaking the internal balance of the subcommunities which gives rise to the energy barriers
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
New sp3diphosphine-based rhodium catalysts for the asymmetric conjugate addition of aryl boronic acids to 3-azaarylpropenones
Full text linkDifferent chiral diphosphine ligands were successfully applied to the rhodium catalyzed asymmetric conjugate addition of differently substituted boronic acids to 3-azaarylpropenones containing both pyridinyl and imidazolyl cores. Atropoisomeric (S)-TetraMe-BITIANP (L1) and (S)-BITIANP (L2), together with ligands bearing mixed chirality as in (S,S,Sax)-DIOPHEP (L3), (R,Rax)-ISAPHOS C1 (L4) and (S,Rax,Rax)-ISAPHOS C2 (L5), and the ones containing a stereogenic sp3carbon ((R,R)-ZEDPHOS (L6) and (R,R)-EPHOS (L8) and their derivativesL7andL9) have been employed as a source of chirality in rhodium complexes. Among this last class of diphosphines, the new phosphorus-based ligand called (R,R)-EPHOS (L8) has been synthesized and employed for the first time as a chiral ligand in rhodium complexes for its catalytic activity. Computational studies suggested aciscoordination with a wide bite angle. When applied to the asymmetric conjugate addition of phenyl boronic acid to 3-azaarylpropenone1, the catalytic system bearingL8afforded the product1ain a remarkable 94% e.e. in THF
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