La paradoja del voto: un efecto perverso del sistema de votación de mayorías

Not available.<br><br>La paradoja del voto cuenta con más de dos siglos de historia, pero esta larga vida no corre pareja con la atención que se le ha dedicado por parte de los teóricos de la política; si exceptuamos al marqués de Condorcet y al reverendo Dogson, tuvo que llegar la década de los cincuenta para que se rescatara del olvido el estudio de un fenómeno que es consustancial a nuestra regla de votación más importante, la regla de elección de mayorías. Es posible que parte de esa falta de interés sea debida a que ha sido considerada más una paradoja lógica que algo que realmente afecte a nuestras elecciones, pero su clarificación, que es lo que se pretende en este artículo, se vuelve inexcusable desde que puede constituirse como una forma de manipulación de los resultados en una elección social

Laelia anceps Lindl. (Orchidaceae) adaptation on phorophytes within an anthropized landscape

Objective: To determine the best phorophyte species for the adaptation of the Laelia anceps Lindl. orchid (Orchidaceae) in an anthropized landscape.Design/Methodology/Approach: A completely randomized experimental design with four treatments (phorophytes) was used: Swietenia macrophylla King., Fraxinus sp., Persea schiedeana Nees., and Tecoma stans. (L.) Juss. ex Kunth), with five repetitions per phorophyte and with three L. anceps orchid plants in each phorophyte. The following variables were measured: day to emergence, root length and thickness, and survival at 28 weeks after tying them in phorophytes.Results: Root emergence of L. anceps took place in less time in S. macrophylla and in Fraxinus sp. at 52 and 54 days, respectively. The longest root length (19.11 cm) and number of roots (32.45) were observed in S. macrophylla; however, the root thickness was greater in Fraxinus sp. (0.28 cm). After 28 weeks of establishing the L. anceps plants, 100% survival was obtained in the phorophytes S. macrophylla and Fraxinus sp., 77% in P. schiedeana, and 33% in T. stans.Study Limitations/Implications: The amount of light received by L. anceps in each phorophyte was not measured.Findings/Conclusions: The best phorophytes observed for the establishment of L. anceps were S. macrophylla and Fraxinus sp., with the best development and strength of the roots and 100% survival at 28 weeks

Information retrieval and text mining technologies for chemistry

Efficient access to chemical information contained in scientific literature, patents, technical reports, or the web is a pressing need shared by researchers and patent attorneys from different chemical disciplines. Retrieval of important chemical information in most cases starts with finding relevant documents for a particular chemical compound or family. Targeted retrieval of chemical documents is closely connected to the automatic recognition of chemical entities in the text, which commonly involves the extraction of the entire list of chemicals mentioned in a document, including any associated information. In this Review, we provide a comprehensive and in-depth description of fundamental concepts, technical implementations, and current technologies for meeting these information demands. A strong focus is placed on community challenges addressing systems performance, more particularly CHEMDNER and CHEMDNER patents tasks of BioCreative IV and V, respectively. Considering the growing interest in the construction of automatically annotated chemical knowledge bases that integrate chemical information and biological data, cheminformatics approaches for mapping the extracted chemical names into chemical structures and their subsequent annotation together with text mining applications for linking chemistry with biological information are also presented. Finally, future trends and current challenges are highlighted as a roadmap proposal for research in this emerging field.A.V. and M.K. acknowledge funding from the European Community’s Horizon 2020 Program (project reference: 654021 - OpenMinted). M.K. additionally acknowledges the Encomienda MINETAD-CNIO as part of the Plan for the Advancement of Language Technology. O.R. and J.O. thank the Foundation for Applied Medical Research (FIMA), University of Navarra (Pamplona, Spain). This work was partially funded by Consellería de Cultura, Educación e Ordenación Universitaria (Xunta de Galicia), and FEDER (European Union), and the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit and COMPETE 2020 (POCI-01-0145-FEDER-006684). We thank Iñigo Garciá -Yoldi for useful feedback and discussions during the preparation of the manuscript.info:eu-repo/semantics/publishedVersio

CHEMDNER: The drugs and chemical names extraction challenge

Natural language processing (NLP) and text mining technologies for the chemical domain (ChemNLP or chemical text mining) are key to improve the access and integration of information from unstructured data such as patents or the scientific literature. Therefore, the BioCreative organizers posed the CHEMDNER (chemical compound and drug name recognition) community challenge, which promoted the development of novel, competitive and accessible chemical text mining systems. This task allowed a comparative assessment of the performance of various methodologies using a carefully prepared collection of manually labeled text prepared by specially trained chemists as Gold Standard data. We evaluated two important aspects: one covered the indexing of documents with chemicals (chemical document indexing - CDI task), and the other was concerned with finding the exact mentions of chemicals in text (chemical entity mention recognition - CEM task). 27 teams (23 academic and 4 commercial, a total of 87 researchers) returned results for the CHEMDNER tasks: 26 teams for CEM and 23 for the CDI task. Top scoring teams obtained an F-score of 87.39% for the CEM task and 88.20% for the CDI task, a very promising result when compared to the agreement between human annotators (91%). The strategies used to detect chemicals included machine learning methods (e.g. conditional random fields) using a variety of features, chemistry and drug lexica, and domain-specific rules. We expect that the tools and resources resulting from this effort will have an impact in future developments of chemical text mining applications and will form the basis to find related chemical information for the detected entities, such as toxicological or pharmacogenomic properties

Immunomodulatory properties of carvone inhalation and Its effects on contextual fear memory in mice

A complex network of interactions exists between the immune, the olfactory, and the central nervous system (CNS). Inhalation of different fragrances can affect immunological reactions in response to an antigen but also may have effects on the CNS and cognitive activity. We performed an exploratory study of the immunomodulatory ability of a series of compounds representing each of the 10 odor categories or clusters described previously. We evaluated the impact of each particular odor on the immune response after immunization with the model antigen ovalbumin in combination with the TLR3 agonist poly I:C. We found that some odors behave as immunostimulatory agents, whereas others might be considered as potential immunosuppressant odors. Interestingly, the immunomodulatory capacity was, in some cases, strain-specific. In particular, one of the fragrances, carvone, was found to be immunostimulatory in BALB/c mice and immunosuppressive in C57BL/6J mice, facilitating or impairing viral clearance, respectively, in a model of a viral infection with a recombinant adenovirus. Importantly, inhalation of the odor improved the memory capacity in BALB/c mice in a fear-conditioning test, while it impaired this same capacity in C57BL/6J mice. The improvement in memory capacity in BALB/c was associated with higher CD3+ T cell infiltration into the hippocampus and increased local expression of mRNA coding for IL-1β, TNF-α, and IL-6 cytokines. In contrast, the memory impairment in C57BL/6 was associated with a reduction in CD3 numbers and an increase in IFN-γ. These data suggest an association between the immunomodulatory capacity of smells and their impact on the cognitive functions of the animals. These results highlight the potential of studying odors as therapeutic agents for CNS-related diseases

Discovery of first-in-class reversible dual small molecule inhibitors against G9a and DNMTs in hematological malignancies

The indisputable role of epigenetics in cancer and the fact that epigenetic alterations can be reversed have favoured development of epigenetic drugs. In this study, we design and synthesize potent novel, selective and reversible chemical probes that simultaneously inhibit the G9a and DNMTs methyltransferase activity. In vitro treatment of haematological neoplasia (acute myeloid leukaemia-AML, acute lymphoblastic leukaemia-ALL and diffuse large B-cell lymphoma-DLBCL) with the lead compound CM-272, inhibits cell proliferation and promotes apoptosis, inducing interferon-stimulated genes and immunogenic cell death. CM-272 significantly prolongs survival of AML, ALL and DLBCL xenogeneic models. Our results represent the discovery of first-in-class dual inhibitors of G9a/DNMTs and establish this chemical series as a promising therapeutic tool for unmet needs in haematological tumours.We particularly acknowledge the Biobank of the University of Navarra for its collaboration. We thank Dr Edorta Martínez de Marigorta and Dr Francisco Palacios from Departamento de Química Orgánica I, Facultad de Farmacia, Universidad del Pais Vasco for 13C NMR determination and Angel Irigoyen Barrio and Dr Ana Romo Hualde, from University of Navarra, for HRMS determination. Dr. Irene de Miguel Turrullols from Small Molecule Discovery Platform, CIMA, University of Navarra is acknowledged for NMR data interpretation. This work was funded by grants from Instituto de Salud Carlos III (ISCIII) PI10/01691, PI13/01469, PI14/01867, PI10/2983, TRASCAN (EPICA), CIBERONC, cofinanciacion FEDER, RTICC RD12/0036/0068, Fundació La Marató de TV3 (20132130-31-32) and ‘Fundación Fuentes Dutor’. B.P. is supported by a Sara Borrell fellowship CD13/00340 and X.A. is a Marie Curie researcher under contract ‘LincMHeM-330598’.S

The effect of excess weight on circulating inflammatory cytokines in drug-naïve first-episode psychosis individuals

Background: Low-grade inflammation has been repeatedly associated with both excess weight and psychosis. However, no previous studies have addressed the direct effect of body mass index (BMI) on basal serum cytokines in individuals with first-episode psychosis (FEP). Objectives: The aim of this study is to analyze the effect of BMI on basal serum cytokine levels in FEP patients and control subjects, separating the total sample into two groups: normal-weight and overweight individuals. Methods: This is a prospective and open-label study. We selected 75 FEP patients and 75 healthy controls with similar characteristics to patients according to the following variables: sex, age, and cannabis and tobacco consumption. Both controls and patients were separated into two groups according to their BMI: subjects with a BMI under 25 were considered as normal weight and those with a BMI equal to or more than 25 were considered as overweight. Serum levels of 21 cytokines/chemokines were measured at baseline using the Human High Sensitivity T Cell Magnetic Bead Panel protocol from the Milliplex® Map Kit. We compared the basal serum levels of the 21 cytokines between control and patient groups according to their BMI. Results: In the normal-weight group, IL-8 was the only cytokine that was higher in patients than in the control group (p = 0.001), whereas in the overweight group, serum levels of two pro-inflammatory cytokines (IL-6, p = 0.000; IL-1?, p = 0.003), two chemokines (IL-8, p = 0.001; MIP-1?, p = 0.001), four Th-1 and Th-2 cytokines (IL-13, p = 0.009; IL-2, p = 0.001; IL-7, p = 0.001; IL-12p70, p = 0.010), and one Type-3 cytokine (IL-23, p = 0.010) were higher in patients than in controls. Conclusions: Most differences in the basal serum cytokine levels between patients and healthy volunteers were found in the overweight group. These findings suggest that excess weight can alter the homeostasis of the immune system and therefore may have an additive pro-inflammatory effect on the one produced by psychosis in the central nervous system.Funding: The present study was carried out at the Hospital Marqués de Valdecilla, University of Cantabria, Santander, Spain, under the following grant support from MINECO SAF2013-46292-R, Instituto de Salud Carlos III, and Fundación Marqués de Valdecilla. No pharmaceutical company has participated in the study concept and design, data collection, analysis and interpretation of the results, and drafting of the manuscript. We thank the Valdecilla Biobank for blood sampling handling and storage. We also wish to thank the participants and their families for enrolling in this study. The study, designed and directed by B C-F, conformed to international standards for research ethics and was approved by the local institutional review board

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery