The fall of a symbol? A high predation rate by the introduced horseshoe whip snake Hemorrhois hippocrepis paints a bleak future for the endemic Ibiza wall lizard Podarcis pityusensis

Invasive species currently account for a major threat to global biodiversity, and island ecosystems are among the most vulnerable, because of the frequency and success of species introductions on islands. Within Mediterranean islands, reptiles not only are frequently introduced species but are also among the most threatened because of these introductions. The Balearic archipelago is a good example of this, since only two of its current 16 species of reptiles are native. Thirteen years ago, the snake Hemorrhois hippocrepis was introduced by cargo in Ibiza island, and it is in expansion. Individuals obtained from an early eradication campaign showed a fast expression of phenotypic plasticity and acquired larger sizes than those of the source population, probably due to a high prey availability and predator scarcity. The species is thriving at the expense of a small variety of native and non-native prey, but the predation pressure on the endemic Podarcis pityusensis, the only native reptile in the island, is very high, as this lizard represents 56% of the prey in frequency, which might threaten its survival on the long term. Our results on the feeding ecology of the snake are of sufficient concern to justify the maintenance of actions to eradicate this invader.Peer reviewe

Hollow Microcrystals of Copper Hexafluoroacetylacetonate-Pyridine Derivative Adducts via Supercritical CO2 Recrystallization

An innovative crystallization process, based in the use of the eco-friendly supercritical carbon dioxide (scCO2) solvent, is presented for the production of coordination compounds macrocrystals of general formula [Cu(hfacac)2(dPy)2], with intriguing prismatic hollow structures and single polymorphic forms. On the contrary, conventional solvents yielded compact microstructures. Studied pyridine derivatives (dPy) were 4-phenylpyridine, PhPy; 4-benzylylpyridine, BzPy; and 4-acetylpyridine, AcPy. In the specific case of the [Cu(hfacac)2(AcPy)2] adduct, the use of scCO2 as a solvent allows obtaining a pure polymorph, while the conventional solvent trials yielded a mixture of two polymorphs. Four new crystalline structures have been resolved from single crystal X-ray diffraction. All the structures consist in mononuclear complexes connected through intermolecular interactions, including H···H, H···O, F···F, C-F···Caromatic and/or C-F··· interactions, generating bidimensional networks that determine their crystallization mode in scCO2.This work was partially financed by the Spanish National Plan of Research CTQ2014-56324 and Severo Ochoa SEV-2015-0496, and by the Generalitat de Catalunya 2014SGR377. A. López-Periago acknowledges the RyC-2012-11588 contract. ALBA synchrotron is acknowledged for the provision of beamtime.Peer Reviewe

Validación de las redes neuronales artificiales como metodología para la asignación donante-receptor en el trasplante hepático

1. Introducción o motivación de la tesis. El trasplante hepático constituye la mejor opción terapéutica para un gran número de patologías hepáticas en fase terminal. Desafortunadamente, existe un disbalance entre el número de candidatos y el número de donantes disponibles, lo que conlleva a muertes y exclusiones en lista de espera. En los últimos años se han realizado numerosos esfuerzos para incrementar el pool de donantes, así como para optimizar la priorización en lista de los posibles receptores. Entre ellos, destacan la utilización de los denominados “donantes con criterios extendidos” (ECD, extended criteria donors) y la adopción de un sistema de priorización mediante un score basado en la gravedad del candidato (MELD, Mayo Model for End Stage Liver Disease). La asignación donante-receptor es un factor determinante en los resultados del trasplante hepático, para lo cual se han propuesto múltiples “scores” en la literatura. Sin embargo, ninguno de ellos se considera óptimo para realizar este emparejamiento. En 2014, nuestro grupo publicó la utilidad de las redes neuronales artificiales (RNA) como una herramienta óptima para el matching donante-receptor en el trasplante hepático. Para ello se realizó un estudio multicéntrico a nivel nacional, en el que se demostró la superioridad de este modelo para predecir la supervivencia post-trasplante. El objetivo de nuestro estudio es analizar si las redes neuronales tienen un comportamiento similar al demostrado en España en un sistema de salud diferente, y si son una herramienta superior a los modelos actuales utilizados para el matching donante-receptor. 2. Contenido de la investigación. Se recogieron 822 pares donante-receptor (D-R) de trasplantes hepáticos realizados de forma consecutiva en el hospital King’s College de Londres durante los años 2002 a 2010, teniendo en cuenta variables del donante, del receptor y del trasplante. Para cada par, se calcularon dos probabilidades: la probabilidad de supervivencia (CCR) y la probabilidad de pérdida del injerto (MS) a los 3 meses del trasplante. Para ello se construyeron dos modelos de redes neuronales artificiales diferentes y no complementarios: el modelo de aceptación y el modelo de rechazo. Se construyeron varios modelos: 1) Entrenamiento y generalización con los pares D-R del hospital británico (a 3 y a 12 meses post-trasplante) , 2) Entrenamiento con pares D-R españoles y generalización con los británicos y 3) Modelo combinado: entrena y generaliza con pares españoles y británicos. Además, para ayudar en la toma de decisiones según los resultados obtenidos por la red neuronal, se construyó un sistema basado en reglas. Los modelos diseñados para el hospital King’s College demostraron una excelente capacidad de predicción para ambos: 3 meses (CCR-AUC=0,9375; MS-AUC=0,9374) y 12 meses (CCR-AUC=0,7833; MS-AUC=0,8153), casi un 15% superior a la mejor capacidad de predicción obtenida por otros scores como MELD o BAR (Balance of Risk). Además, estos resultados mejoran los publicados previamente en el modelo multicéntrico español. Sin embargo, esta capacidad de predicción no es tan buena cuando el modelo entrena y generaliza con pares D-R procedentes de sistemas de salud diferentes, ni tampoco en el modelo combinado. 3.Conclusiones. 1. El empleo de Redes Neuronales Artificiales para la Asignación Donante-Receptor en el Trasplante Hepático ha demostrado excelentes capacidades de predicción de Supervivencia y No Supervivencia del injerto, al ser validadas en un sistema de salud distinto de otro país, por lo tanto la metodología de la Inteligencia Artificial ha quedado claramente validada como herramienta óptima para el “matching D-R”. 2. Nuestros resultados apoyan que los distintos equipos de Trasplante Hepático consideren las Redes Neuronales Artificiales como el método más exhaustivo y objetivo descrito hasta la fecha para el manejo de la lista de espera del Trasplante Hepático, evitando criterios subjetivos y arbitrarios y maximizando los principios de equidad, utilidad y eficiencia. 3. Nuestro modelo de validación, es decir, la RNA generada con pares D-R del Hospital King’s College de Londres ha logrado la máxima capacidad de predicción, superando el resto de modelos y apoyando el hecho de que cada RNA debe ser entrenada, testada y optimizada para un propósito específico, en una única población. Así, cada programa de TH debería disponer de su propio modelo construido con sus propios datos, para apoyar la decisión del “matching D-R”. 4. El modelo de Asignación D-R generado por las RNAs combina lo mejor del sistema MELD con el Beneficio de Supervivencia Global, usando para ello un sistema basado en reglas, maximizando la utilidad de los injertos disponibles. Esto los convierte en sistemas complementarios para un mismo fin, en lugar de considerarlos competitivos

Exploring a novel preparation method of 1D metal organic frameworks based on supercritical CO2

The preparation of copper(II) one-dimensional MOFs using an eco-efficient method is reported here. This method is based exclusively on using supercritical CO2 as a solvent, without the addition of any other additive or co-solvent. Neutral acetylacetonate copper complexes and two linear linkers, namely, the bidentate 4,4¿-bipyridine and 4,4¿-trimethylenedipyridine molecules, were reacted under compressed CO2 at 60 °C and 20 MPa for periods of 4 or 24 h. The success achieved in the synthesis of the different studied 1D-MOFs was related to the solubility of the reagents in supercritical CO2. The reaction yield of the synthesized coordination polymers via the supercritical route was close to 100% because both the reactants were almost completely depleted in the performed experiments. © The Royal Society of Chemistry 2015.This work was partially financed by EU COST project MP1202 OC-2011-2-10820 and by the Generalitat de Catalunya 2014SGR377. A. López-Periago acknowledges the RyC-2012- 11588 contract. We acknowledge support by the CSIC Open Access Publication Initiative through its Unit of Information Resources for Research (URICI)Peer Reviewe

Nature s Top 100 Re-Revisited

"This is the peer reviewed version of the following article: Martín-Martín, A., Ayllon, J. M., López-Cózar, E. D., & Orduna-Malea, E. (2015). Nature's top 100 Re-revisited. JASIST, 66(12), 2714., which has been published in final form at http://doi.org/10.1002/asi.23570. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving."To mark the 50th anniversary of the Science Citation Index, Nature published a list of the 100 most-cited papers of all time. It also included an alternative ranking from data provided by Google Scholar, which, as this letter illustrates, contains certain inconsistencies. This does not, however, diminish the usefulness of Google Scholar, not only in identifying the most-cited articles of all time, but also in reflecting the impact of other document types (especially books), thus redefining the concept of academic impact. Keywords:Martín-Martín, A.; Ayllón, JM.; Delgado López-Cózar, E.; Orduña Malea, E. (2015). Nature s Top 100 Re-Revisited. Journal of the American Society for Information Science and Technology. 66(12):2714-2714. doi:10.1002/asi.23570271427146612Bornmann , L. Nature's top 100 revisited. Journal of the Association for Information Science and Technology http://www.lutz-bornmann.de/icons/top_100.pdfGarfield , E. 2005 The agony and the ecstasy-the history and meaning of the Journal Impact Factor http://www.garfield.library.upenn.edu/papers/jifchicago2005.pdfMartin-Martin , A. Orduna-Malea , E. Ayllon , J.M. Delgado Lopez-Cozar , E. 2014 Does Google Scholar contain all highly cited documents (1950-2013)? http://arxiv.org/abs/1410.8464Van Noorden, R., Maher, B., & Nuzzo, R. (2014). The top 100 papers. Nature, 514(7524), 550-553. doi:10.1038/514550

The lost academic home: institutional affiliation links in Google Scholar Citations

This article is (c) Emerald Group Publishing and permission has been granted for this version to appear here (please insert the web address here). Emerald does not grant permission for this article to be further copied/distributed or hosted elsewhere without the express permission from Emerald Group Publishing Limited[EN] Purpose - Google Scholar Citations (GSC) provides an institutional affiliation link which groups together authors who belong to the same institution. The purpose of this paper is to ascertain whether this feature is able to identify and normalize all the institutions entered by the authors, and whether it is able to assign all researchers to their own institution correctly. Design/methodology/approach - Systematic queries to GSC's internal search box were performed under two different forms (institution name and institutional e-mail web domain) in September 2015. The whole Spanish academic system (82 institutions) was used as a test. Additionally, specific searches to companies (Google) and world-class universities were performed to identify and classify potential errors in the functioning of the feature. Findings - Although the affiliation tool works well for most institutions, it is unable to detect all existing institutions in the database, and it is not always able to create a unique standardized entry for each institution. Additionally, it also fails to group all the authors who belong to the same institution. A wide variety of errors have been identified and classified. Research limitations/implications - Even though the analyzed sample is good enough to empirically answer the research questions initially proposed, a more comprehensive study should be performed to calibrate the real volume of the errors. Practical implications - The discovered affiliation link errors prevent institutions from being able to access the profiles of all their respective authors using the institutions lists offered by GSC. Additionally, it introduces a shortcoming in the navigation features of Google Scholar which may impair web user experience. Social implications - Some institutions (mainly universities) are under-represented in the affiliation feature provided by GSC. This fact might jeopardize the visibility of institutions as well as the use of this feature in bibliometric or webometric analyses. Originality/value - This work proves inconsistencies in the affiliation feature provided by GSC. A whole national university system is systematically analyzed and several queries have been used to reveal errors in its functioning. The completeness of the errors identified and the empirical data examined are the most exhaustive to date regarding this topic. Finally, some recommendations about how to correctly fill in the affiliation data (both for authors and institutions) and how to improve this feature are provided as well.Orduña Malea, E.; Ayllón, JM.; Martín-Martín, A.; Delgado-López-Cózar, E. (2017). The lost academic home: institutional affiliation links in Google Scholar Citations. Online Information Review. 41(6):762-781. doi:10.1108/OIR-10-2016-0302S76278141