A review of coastal anthropogenic impacts on mytilid mussel beds: Effects on mussels and their associated assemblages

Mussel beds are an important habitat in many coastal systems, harboring a high diversity of biota. They are threatened by anthropogenic impacts that affect mussels and their associated assemblages. Pollution, harvesting, trampling, dredging and trawling are major threats faced by these communities. Most of the studies on the effects of such impacts on the mussel beds overlook the associated fauna. Since mussels are very resilient, especially to pollution, the associated fauna can provide a better footprint of the impacts’ effects. In this review, we looked into the main remarks regarding the effects of anthropogenic impacts in mussel bed communities. Organic pollution was the best studied impact and the Atlantic region was the best studied zone. Low values of abundance, biomass, diversity, evenness and species richness were reported for all categories of impacts, with some studies describing declines in at least three of these descriptors. Among the associated fauna, some tolerant species benefited from the impacts, particularly organic enrichment, and became more abundant, but sensitive species suffered considerable declines in density, mainly in dredging and trawling impacts. Therefore, fauna associated with mussel beds is a suitable indicator of anthropogenic disturbance

Estudio técnico de viabilidad de conversión de vehículo convencional a eléctrico

En este trabajo de fin de grado (TFG), se analizan los elementos principales eléctricos y electrónicosde un vehículo eléctrico para su posible instalación en vehículos que fueron construidos inicialmente conun motor de combustión interna y pensados para su conducción con dicho Motor. Para realizar el estudio,se ha tomado como referencia un vehículo antiguo (Renault 4 TL), que por su características físicas yestructurales podía ser adecuado para una conversión.Para la realización del TFG se realiza inicialmente un modelo dinámico y energético del vehículo conlos ciclos estandarizados, así como con ciclos que realizaría el vehículo de manera cotidiana. Con lapotencia y energía necesarias calculadas a partir de este modelo, se procede a la selección y modelado enel programa de simulación Matlab & Simulink de la compañía MathWorks® del motor eléctrico y la bateríaque se instalarían en el vehículo.La selección de ambos elementos se realiza mediante la comparación de las características de losdiferentes motores y baterías que se instalan en los vehículos eléctricos y decidiendo por el precio y dichascaracterísticas cual es el más adecuado para el vehículo propuesto. Una vez seleccionado amboselementos se seleccionan los elementos necesarios para la alimentación del motor a partir de la batería ysu control siguiendo un criterio similar.Tras la selección de la batería se estudian los sistemas que se utilizan para el correcto funcionamientode la batería para que no sufra daños durante su vida útil y diferentes tipos de carga que ese tipo debatería en específico puede utilizar y se estiman los tiempos de carga necesarios según el tipo de cargautilizada.Con los elementos que componen el vehículo seleccionados, se procede a elegir el tipo de cable yprotecciones necesarias para la conexión de los diferentes elementos del vehículo.Finalmente se analizan las características principales que tendría el vehículo tras su conversión,Potencia, Energía consumida, Autonomía, Velocidad máxima, emisiones de Co2 y precio aproximado dela conversión y se comparan con vehículos, de similar potencia a la que tendría el vehículo tras laconversión, que a fecha de 2018 se encontraban y eran representativos del mercado.Con los resultados obtenidos de la realización del TFG se realizan las conclusiones pertinentes y seproponen diferentes posibles trabajos a realizar de desarrollos y aspectos de investigación con relación altema tratado en el TFG que serían interesantes de tratar.<br /

Recent changes on the abundance and distribution of non-indigenous macroalgae along the southwest coast of the Bay of Biscay

Twenty-three rocky shores along approximately 225 km on the southwest coast of the Bay of Biscay were sampled during the springs of 2014 and 2021, to explore changes in the distribution and abundance of four non-indigenous species (NIS) macroalgae (i.e., Asparagopsis armata, Grateloupia turuturu, Sargassum muticum, and Undaria pinnatifida) by using a semi-quantitative scale. Results showed relevant changes in the distribution and abundance of NIS. The kelp U. pinnatifida was recorded in 2021 for the first time on two shores. The distribution of G. turuturu showed an extension in its range of distribution of 200 km to the east. The other two target species S. muticum and A. armata were widely distributed along the whole 225 km of the studied area in 2014 and 2021, with higher abundance in 2021. Therefore, we strongly advise the necessity of future monitoring programs for these four NIS species. These monitoring programs will explore the progress of invasion and resilience of native species.This study was supported by the project ATLANTIDA (ref. NORTE-01-0145-FEDER-000040), supported by the Norte Portugal Regional Operational Program (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement and through the European Regional Development Fund (ERDF). This study was supported by the FCT-Foundation for Science and Technology through national funds within the scope of Contrato-Programa” UIDB/04050/2020 funded by national funds through the FCT I.P and, UIDB/04423/2020, UIDP/04423/2020. L. Guerrero-Meseguer was financed thanks to a grant from the Department of European Funds, University, and Culture of the Government of the Balearic Islands. P. Veiga was hired through the Regulamento do Emprego Científico e Tecnológico-RJEC from the Portuguese Foundation for Science and Technology (FCT) program (CEECIND/03893/2018)

Novel and conventional embryo parameters as input data for artificial neural networks: an artificial intelligence model applied for prediction of the implantation potential

[ES] Objetivo: Describir nuevas características de embriones capaces de predecir el potencial de implantación como datos de entrada para un modelo de red neuronal artificial (ANN). Diseño: Estudio de cohorte retrospectivo. Entorno: Centro de FIV privado afiliado a la universidad. Paciente (s): Este estudio incluyó a 637 pacientes del programa de donación de ovocitos que se sometieron a transferencia de un solo blastocisto durante dos años consecutivos. Intervención (es): Ninguna. Principales medidas de resultado: La investigación se dividió en dos fases. La fase 1 consistió en la descripción y análisis de las siguientes características embrionarias en embriones implantados y no implantados: distancia y velocidad de migración pronuclear, diámetro del blastocisto expandido, área de masa celular interna y duración del ciclo celular del trofoectodermo. La fase 2 consistió en el desarrollo de un algoritmo ANN para la predicción de la implantación. Se obtuvieron resultados para cuatro modelos alimentados con diferentes datos de entrada. El poder predictivo se midió con el uso del área bajo la curva característica operativa del receptor (AUC). Resultado (s): De los cinco nuevos parámetros descritos, el diámetro expandido del blastocisto y la duración del ciclo celular del trofoectodermo tenían valores estadísticamente diferentes en los embriones implantados y no implantados. Después de que los modelos ANN fueron entrenados y validados mediante validación cruzada cinco veces, estos fueron capaces de predecir la implantación en los datos de prueba con AUC de 0,64 para ANN1 (morfocinética convencional), 0,73 para ANN2 (morfodinámica novedosa), 0,77 para ANN3 (morfocinética convencional þ morfodinámica novedosa) y 0,68 para ANN4 (variables discriminatorias de prueba estadística). Conclusión (es): Las nuevas características embrionarias propuestas afectan al potencial de implantación y su combinación con parámetros morfocinéticos convencionales es eficaz como datos de entrada para un modelo predictivo basado en inteligencia artificial.[EN] Objective: To describe novel embryo features capable of predicting implantation potential as input data for an artificial neural network (ANN) model. Design: Retrospective cohort study. Setting: University-affiliated private IVF center. Patient(s): This study included 637 patients from the oocyte donation program who underwent single-blastocyst transfer during two consecutive years. Intervention(s): None. Main Outcome Measure(s): The research was divided into two phases. Phase 1 consisted of the description and analysis of the following embryo features in implanted and nonimplanted embryos: distance and speed of pronuclear migration, blastocyst expanded diameter, inner cell mass area, and trophectoderm cell cycle length. Phase 2 consisted of the development of an ANN algorithm for implantation prediction. Results were obtained for four models fed with different input data. The predictive power was measured with the use of the area under the receiver operating characteristic curve (AUC). Result(s): Out of the five novel described parameters, blastocyst expanded diameter and trophectoderm cell cycle length had statistically different values in implanted and nonimplanted embryos. After the ANN models were trained and validated using fivefold cross validation, they were capable of predicting implantation on testing data with AUCs of 0.64 for ANN1 (conventional morphokinetics), 0.73 for ANN2 (novel morphodynamics), 0.77 for ANN3 (conventional morphokinetics thorn novel morphodynamics), and 0.68 for ANN4 (discriminatory variables from statistical test). Conclusion(s): The novel proposed embryo features affect the implantation potential, and their combination with conventional morphokinetic parameters is effective as input data for a predictive model based on artificial intelligence. ((c) 2020 by American Society for Reproductive Medicine.)Supported by the Ministry of Science, Innovation, and Universities CDTI (IDI-20191102), an Industrial Ph.D. grant (DIN2018-009911), and Agencia Valenciana de Innovacio (INNCAD00-18-009) to E.P. and M.M.Bori, L.; Paya-Bosch, E.; Alegre, L.; Viloria, T.; Remohí, J.; Naranjo Ornedo, V.; Meseguer, M. (2020). Novel and conventional embryo parameters as input data for artificial neural networks: an artificial intelligence model applied for prediction of the implantation potential. Fertility and Sterility. 114(6):1232-1241. https://doi.org/10.1016/j.fertnstert.2020.08.023S123212411146De Geyter, C., Calhaz-Jorge, C., Kupka, M. S., Wyns, C., Mocanu, E., Motrenko, T., … Goossens, V. (2018). ART in Europe, 2014: results generated from European registries by ESHRE†. Human Reproduction, 33(9), 1586-1601. doi:10.1093/humrep/dey242Edwards, R. G., Fishel, S. B., Cohen, J., Fehilly, C. B., Purdy, J. M., Slater, J. M., … Webster, J. M. (1984). Factors influencing the success of in vitro fertilization for alleviating human infertility. Journal of In Vitro Fertilization and Embryo Transfer, 1(1), 3-23. doi:10.1007/bf01129615Ferraretti, A. P., Goossens, V., de Mouzon, J., Bhattacharya, S., Castilla, J. A., … Korsak, V. (2012). Assisted reproductive technology in Europe, 2008: results generated from European registers by ESHRE†. Human Reproduction, 27(9), 2571-2584. doi:10.1093/humrep/des255Zhang, J. Q., Li, X. L., Peng, Y., Guo, X., Heng, B. C., & Tong, G. Q. (2010). Reduction in exposure of human embryos outside the incubator enhances embryo quality and blastulation rate. Reproductive BioMedicine Online, 20(4), 510-515. doi:10.1016/j.rbmo.2009.12.027Cruz, M., Garrido, N., Herrero, J., Pérez-Cano, I., Muñoz, M., & Meseguer, M. (2012). Timing of cell division in human cleavage-stage embryos is linked with blastocyst formation and quality. Reproductive BioMedicine Online, 25(4), 371-381. doi:10.1016/j.rbmo.2012.06.017Kirkegaard, K., Agerholm, I. E., & Ingerslev, H. J. (2012). Time-lapse monitoring as a tool for clinical embryo assessment. Human Reproduction, 27(5), 1277-1285. doi:10.1093/humrep/des079Montag, M., Liebenthron, J., & Köster, M. (2011). Which morphological scoring system is relevant in human embryo development? Placenta, 32, S252-S256. doi:10.1016/j.placenta.2011.07.009Aparicio, B., Cruz, M., & Meseguer, M. (2013). Is morphokinetic analysis the answer? Reproductive BioMedicine Online, 27(6), 654-663. doi:10.1016/j.rbmo.2013.07.017Gallego, R. D., Remohí, J., & Meseguer, M. (2019). Time-lapse imaging: the state of the art†. Biology of Reproduction, 101(6), 1146-1154. doi:10.1093/biolre/ioz035Zaninovic, N., Irani, M., & Meseguer, M. (2017). Assessment of embryo morphology and developmental dynamics by time-lapse microscopy: is there a relation to implantation and ploidy? Fertility and Sterility, 108(5), 722-729. doi:10.1016/j.fertnstert.2017.10.002Athayde Wirka, K., Chen, A. A., Conaghan, J., Ivani, K., Gvakharia, M., Behr, B., … Shen, S. (2014). Atypical embryo phenotypes identified by time-lapse microscopy: high prevalence and association with embryo development. Fertility and Sterility, 101(6), 1637-1648.e5. doi:10.1016/j.fertnstert.2014.02.050Zhan, Q., Ye, Z., Clarke, R., Rosenwaks, Z., & Zaninovic, N. (2016). Direct Unequal Cleavages: Embryo Developmental Competence, Genetic Constitution and Clinical Outcome. PLOS ONE, 11(12), e0166398. doi:10.1371/journal.pone.0166398Goodman, L. R., Goldberg, J., Falcone, T., Austin, C., & Desai, N. (2016). Does the addition of time-lapse morphokinetics in the selection of embryos for transfer improve pregnancy rates? A randomized controlled trial. Fertility and Sterility, 105(2), 275-285.e10. doi:10.1016/j.fertnstert.2015.10.013Desai, N., Ploskonka, S., Goodman, L., Attaran, M., Goldberg, J. M., Austin, C., & Falcone, T. (2016). Delayed blastulation, multinucleation, and expansion grade are independently associated with live-birth rates in frozen blastocyst transfer cycles. Fertility and Sterility, 106(6), 1370-1378. doi:10.1016/j.fertnstert.2016.07.1095Aguilar, J., Rubio, I., Muñoz, E., Pellicer, A., & Meseguer, M. (2016). Study of nucleation status in the second cell cycle of human embryo and its impact on implantation rate. Fertility and Sterility, 106(2), 291-299.e2. doi:10.1016/j.fertnstert.2016.03.036Rubio, I., Kuhlmann, R., Agerholm, I., Kirk, J., Herrero, J., Escribá, M.-J., … Meseguer, M. (2012). Limited implantation success of direct-cleaved human zygotes: a time-lapse study. Fertility and Sterility, 98(6), 1458-1463. doi:10.1016/j.fertnstert.2012.07.1135Desai, N., Ploskonka, S., Goodman, L. R., Austin, C., Goldberg, J., & Falcone, T. (2014). Analysis of embryo morphokinetics, multinucleation and cleavage anomalies using continuous time-lapse monitoring in blastocyst transfer cycles. Reproductive Biology and Endocrinology, 12(1), 54. doi:10.1186/1477-7827-12-54Ebner, T., Höggerl, A., Oppelt, P., Radler, E., Enzelsberger, S.-H., Mayer, R. B., … Shebl, O. (2017). Time-lapse imaging provides further evidence that planar arrangement of blastomeres is highly abnormal. Archives of Gynecology and Obstetrics, 296(6), 1199-1205. doi:10.1007/s00404-017-4531-5Azzarello, A., Hoest, T., Hay-Schmidt, A., & Mikkelsen, A. L. (2017). Live birth potential of good morphology and vitrified blastocysts presenting abnormal cell divisions. Reproductive Biology, 17(2), 144-150. doi:10.1016/j.repbio.2017.03.004Desch, L., Bruno, C., Luu, M., Barberet, J., Choux, C., Lamotte, M., … Fauque, P. (2017). Embryo multinucleation at the two-cell stage is an independent predictor of intracytoplasmic sperm injection outcomes. Fertility and Sterility, 107(1), 97-103.e4. doi:10.1016/j.fertnstert.2016.09.022Kirkegaard, K., Hindkjaer, J. J., Grøndahl, M. L., Kesmodel, U. S., & Ingerslev, H. J. (2012). A randomized clinical trial comparing embryo culture in a conventional incubator with a time-lapse incubator. Journal of Assisted Reproduction and Genetics, 29(6), 565-572. doi:10.1007/s10815-012-9750-xWong, C. C., Loewke, K. E., Bossert, N. L., Behr, B., De Jonge, C. J., Baer, T. M., & Pera, R. A. R. (2010). Non-invasive imaging of human embryos before embryonic genome activation predicts development to the blastocyst stage. Nature Biotechnology, 28(10), 1115-1121. doi:10.1038/nbt.1686Conaghan, J., Chen, A. A., Willman, S. P., Ivani, K., Chenette, P. E., Boostanfar, R., … Shen, S. (2013). Improving embryo selection using a computer-automated time-lapse image analysis test plus day 3 morphology: results from a prospective multicenter trial. Fertility and Sterility, 100(2), 412-419.e5. doi:10.1016/j.fertnstert.2013.04.021Milewski, R., Kuć, P., Kuczyńska, A., Stankiewicz, B., Łukaszuk, K., & Kuczyński, W. (2015). A predictive model for blastocyst formation based on morphokinetic parameters in time-lapse monitoring of embryo development. Journal of Assisted Reproduction and Genetics, 32(4), 571-579. doi:10.1007/s10815-015-0440-3Chamayou, S., Patrizio, P., Storaci, G., Tomaselli, V., Alecci, C., Ragolia, C., … Guglielmino, A. (2013). The use of morphokinetic parameters to select all embryos with full capacity to implant. Journal of Assisted Reproduction and Genetics, 30(5), 703-710. doi:10.1007/s10815-013-9992-2Milewski, R., Czerniecki, J., Kuczyńska, A., Stankiewicz, B., & Kuczyński, W. (2016). Morphokinetic parameters as a source of information concerning embryo developmental and implantation potential. Ginekologia Polska, 87(10), 677-684. doi:10.5603/gp.2016.0067Motato, Y., de los Santos, M. J., Escriba, M. J., Ruiz, B. A., Remohí, J., & Meseguer, M. (2016). Morphokinetic analysis and embryonic prediction for blastocyst formation through an integrated time-lapse system. Fertility and Sterility, 105(2), 376-384.e9. doi:10.1016/j.fertnstert.2015.11.001Petersen, B. M., Boel, M., Montag, M., & Gardner, D. K. (2016). Development of a generally applicable morphokinetic algorithm capable of predicting the implantation potential of embryos transferred on Day 3. Human Reproduction, 31(10), 2231-2244. doi:10.1093/humrep/dew188Meseguer, M., Herrero, J., Tejera, A., Hilligsoe, K. M., Ramsing, N. B., & Remohi, J. (2011). The use of morphokinetics as a predictor of embryo implantation. Human Reproduction, 26(10), 2658-2671. doi:10.1093/humrep/der256Liu, Y., Chapple, V., Feenan, K., Roberts, P., & Matson, P. (2016). Time-lapse deselection model for human day 3 in vitro fertilization embryos: the combination of qualitative and quantitative measures of embryo growth. Fertility and Sterility, 105(3), 656-662.e1. doi:10.1016/j.fertnstert.2015.11.003VerMilyea, M. D., Tan, L., Anthony, J. T., Conaghan, J., Ivani, K., Gvakharia, M., … Shen, S. (2014). Computer-automated time-lapse analysis results correlate with embryo implantation and clinical pregnancy: A blinded, multi-centre study. Reproductive BioMedicine Online, 29(6), 729-736. doi:10.1016/j.rbmo.2014.09.005Basile, N., Vime, P., Florensa, M., Aparicio Ruiz, B., García Velasco, J. A., Remohí, J., & Meseguer, M. (2014). The use of morphokinetics as a predictor of  implantation: a multicentric study to define and validate an algorithm for embryo selection. Human Reproduction, 30(2), 276-283. doi:10.1093/humrep/deu331Aparicio-Ruiz, B., Romany, L., & Meseguer, M. (2018). Selection of preimplantation embryos using time-lapse microscopy in in vitro fertilization: State of the technology and future directions. Birth Defects Research, 110(8), 648-653. doi:10.1002/bdr2.1226Barrie, A., Homburg, R., McDowell, G., Brown, J., Kingsland, C., & Troup, S. (2017). Preliminary investigation of the prevalence and implantation potential of abnormal embryonic phenotypes assessed using time-lapse imaging. Reproductive BioMedicine Online, 34(5), 455-462. doi:10.1016/j.rbmo.2017.02.011Campbell, A., Fishel, S., Bowman, N., Duffy, S., Sedler, M., & Hickman, C. F. L. (2013). Modelling a risk classification of aneuploidy in human embryos using non-invasive morphokinetics. Reproductive BioMedicine Online, 26(5), 477-485. doi:10.1016/j.rbmo.2013.02.006Desai, N., Goldberg, J. M., Austin, C., & Falcone, T. (2018). Are cleavage anomalies, multinucleation, or specific cell cycle kinetics observed with time-lapse imaging predictive of embryo developmental capacity or ploidy? Fertility and Sterility, 109(4), 665-674. doi:10.1016/j.fertnstert.2017.12.025Amir, H., Barbash-Hazan, S., Kalma, Y., Frumkin, T., Malcov, M., Samara, N., … Ben-Yosef, D. (2018). Time-lapse imaging reveals delayed development of embryos carrying unbalanced chromosomal translocations. Journal of Assisted Reproduction and Genetics, 36(2), 315-324. doi:10.1007/s10815-018-1361-8Del Carmen Nogales, M., Bronet, F., Basile, N., Martínez, E. M., Liñán, A., Rodrigo, L., & Meseguer, M. (2017). Type of chromosome abnormality affects embryo morphology dynamics. Fertility and Sterility, 107(1), 229-235.e2. doi:10.1016/j.fertnstert.2016.09.019Dyer, S., Chambers, G. M., de Mouzon, J., Nygren, K. G., Zegers-Hochschild, F., Mansour, R., … Adamson, G. D. (2016). International Committee for Monitoring Assisted Reproductive Technologies world report: Assisted Reproductive Technology 2008, 2009 and 2010. Human Reproduction, 31(7), 1588-1609. doi:10.1093/humrep/dew082Simopoulou, M., Sfakianoudis, K., Maziotis, E., Antoniou, N., Rapani, A., Anifandis, G., … Koutsilieris, M. (2018). Are computational applications the «crystal ball» in the IVF laboratory? The evolution from mathematics to artificial intelligence. Journal of Assisted Reproduction and Genetics, 35(9), 1545-1557. doi:10.1007/s10815-018-1266-6Milewski, R., Kuczyńska, A., Stankiewicz, B., & Kuczyński, W. (2017). How much information about embryo implantation potential is included in morphokinetic data? A prediction model based on artificial neural networks and principal component analysis. Advances in Medical Sciences, 62(1), 202-206. doi:10.1016/j.advms.2017.02.001Curchoe, C. L., & Bormann, C. L. (2019). Artificial intelligence and machine learning for human reproduction and embryology presented at ASRM and ESHRE 2018. Journal of Assisted Reproduction and Genetics, 36(4), 591-600. doi:10.1007/s10815-019-01408-xTran, D., Cooke, S., Illingworth, P. J., & Gardner, D. K. (2019). Deep learning as a predictive tool for fetal heart pregnancy following time-lapse incubation and blastocyst transfer. Human Reproduction, 34(6), 1011-1018. doi:10.1093/humrep/dez064Khosravi, P., Kazemi, E., Zhan, Q., Malmsten, J. E., Toschi, M., Zisimopoulos, P., … Hajirasouliha, I. (2019). Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization. npj Digital Medicine, 2(1). doi:10.1038/s41746-019-0096-yCerrillo, M., Herrero, L., Guillén, A., Mayoral, M., & García-Velasco, J. A. (2017). Impact of Endometrial Preparation Protocols for Frozen Embryo Transfer on Live Birth Rates. Rambam Maimonides Medical Journal, 8(2), e0020. doi:10.5041/rmmj.10297Panchal, G., Ganatra, A., Kosta, Y. P., & Panchal, D. (2011). Behaviour Analysis of Multilayer Perceptronswith Multiple Hidden Neurons and Hidden Layers. International Journal of Computer Theory and Engineering, 332-337. doi:10.7763/ijcte.2011.v3.328Azzarello, A., Hoest, T., & Mikkelsen, A. L. (2012). The impact of pronuclei morphology and dynamicity on live birth outcome after time-lapse culture. Human Reproduction, 27(9), 2649-2657. doi:10.1093/humrep/des210Dal Canto, M., Coticchio, G., Mignini Renzini, M., De Ponti, E., Novara, P. V., Brambillasca, F., … Fadini, R. (2012). Cleavage kinetics analysis of human embryos predicts development to blastocyst and implantation. Reproductive BioMedicine Online, 25(5), 474-480. doi:10.1016/j.rbmo.2012.07.016Barrie, A., Homburg, R., McDowell, G., Brown, J., Kingsland, C., & Troup, S. (2017). Examining the efficacy of six published time-lapse imaging embryo selection algorithms to predict implantation to demonstrate the need for the development of specific, in-house morphokinetic selection algorithms. Fertility and Sterility, 107(3), 613-621. doi:10.1016/j.fertnstert.2016.11.014Coticchio, G., Mignini Renzini, M., Novara, P. V., Lain, M., De Ponti, E., Turchi, D., … Dal Canto, M. (2017). Focused time-lapse analysis reveals novel aspects of human fertilization and suggests new parameters of embryo viability. Human Reproduction, 33(1), 23-31. doi:10.1093/humrep/dex344Aguilar, J., Motato, Y., Escribá, M. J., Ojeda, M., Muñoz, E., & Meseguer, M. (2014). The human first cell cycle: impact on implantation. Reproductive BioMedicine Online, 28(4), 475-484. doi:10.1016/j.rbmo.2013.11.014Barberet, J., Bruno, C., Valot, E., Antunes-Nunes, C., Jonval, L., Chammas, J., … Fauque, P. (2019). Can novel early non-invasive biomarkers of embryo quality be identified with time-lapse imaging to predict live birth? Human Reproduction, 34(8), 1439-1449. doi:10.1093/humrep/dez085Richter, K. S., Harris, D. C., Daneshmand, S. T., & Shapiro, B. S. (2001). Quantitative grading of a human blastocyst: optimal inner cell mass size and shape. Fertility and Sterility, 76(6), 1157-1167. doi:10.1016/s0015-0282(01)02870-9Shapiro, B. S., Daneshmand, S. T., Garner, F. C., Aguirre, M., & Thomas, S. (2008). Large blastocyst diameter, early blastulation, and low preovulatory serum progesterone are dominant predictors of clinical pregnancy in fresh autologous cycles. Fertility and Sterility, 90(2), 302-309. doi:10.1016/j.fertnstert.2007.06.062Almagor, M., Harir, Y., Fieldust, S., Or, Y., & Shoham, Z. (2016). Ratio between inner cell mass diameter and blastocyst diameter is correlated with successful pregnancy outcomes of single blastocyst transfers. Fertility and Sterility, 106(6), 1386-1391. doi:10.1016/j.fertnstert.2016.08.009Shapiro, B. S., Harris, D. C., & Richter, K. S. (2000). Predictive value of 72-hour blastomere cell number on blastocyst development and success of subsequent transfer based on the degree of blastocyst development. Fertility and Sterility, 73(3), 582-586. doi:10.1016/s0015-0282(99)00586-5Coello, A., Meseguer, M., Galán, A., Alegre, L., Remohí, J., & Cobo, A. (2017). Analysis of the morphological dynamics of blastocysts after vitrification/warming: defining new predictive variables of implantation. Fertility and Sterility, 108(4), 659-666.e4. doi:10.1016/j.fertnstert.2017.07.1157Huang, T. T., Huang, D. H., Ahn, H. J., Arnett, C., & Huang, C. T. (2019). Early blastocyst expansion in euploid and aneuploid human embryos: evidence for a non-invasive and quantitative marker for embryo selection. Reproductive BioMedicine Online, 39(1), 27-39. doi:10.1016/j.rbmo.2019.01.010Sundvall, L., Ingerslev, H. J., Breth Knudsen, U., & Kirkegaard, K. (2013). Inter- and intra-observer variability of time-lapse annotations. Human Reproduction, 28(12), 3215-3221. doi:10.1093/humrep/det36

Transmembrane and truncated (SEC) isoforms of MUC1 in the human endometrium and Fallopian tube

The cell surface mucin MUC1 is expressed by endometrial epithelial cells with increased abundance in the secretory phase of the menstrual cycle, when it is found both at the apical cell surface and in secretions. This suggests the presence of a maternal cell surface glycoprotein barrier to embryo implantation, arising from the anti-adhesive property of MUC1. In previous work, we demonstrated alternatively spliced MUC1 variant forms in tumour cells. The variant MUC1/SEC lacks the transmembrane and cytoplasmic sequences found in the full-length variant. We now show that MUC1/SEC mRNA is present in endometrial carcinoma cell lines, endometrial tissue and primary cultured endometrial epithelial cells. The protein can be detected using isoform-specific antibodies in uterine flushings, suggesting release from endometrium in vivo. However, on the basis of immunolocalisation studies, MUC1/SEC also remains associated with the apical epithelial surface both in tissue and in cultured cells. Transmembrane MUC1 and MUC1/SEC are both strikingly localised to the apical surface of tubal epithelium. Thus MUC1 may contribute to the anti-adhesive character of the tubal surface, inhibiting ectopic implantation. The mechanism by which this barrier is overcome in endometrium at implantation is the subject of ongoing investigation

Los otros dinosaurios de la comarca de Els Ports (Castellón)

Els jaciments de vertebrats mesozoics, especialment de dinosaures, descoberts i estudiats en la comarca d’Els Ports han estat lligats històricament a la Formació Argiles de Morella (Barremià tardà, Cretaci primerenc). No obstant això, en els últims anys s’ha posat en marxa un projecte en el qual treballen geòlegs i paleontòlegs de la Universitat de València, la Universitat Jaume I de Castelló i el Grup Guix de Vila-real, la finalitat del qual és localitzar, estudiar i investigar nous jaciments de vertebrats en altres formacions de la comarca. S’han estudiat vint-i-quatre afloraments, dels quals vint-i-dos es situen a la Fm. Mirambell (Barremià primerenc - part inicial del Barremià tardà, Cretaci primerenc) i dos d’ells es situen a la Fm. Els Mangraners (Valanginià primerenc - Hauterivià tardà) i a la Fm. Artoles (Barremià) respectivament.Los yacimientos de vertebrados mesozoicos, especialmente de dinosaurios, descubiertos y estudiados en la comarca de Els Ports han estado ligados históricamente a la Formación Arcillas de Morella (Barremiense tardío, Cretácico Temprano). Sin embargo, en los últimos años se ha puesto en marcha un proyecto en el que trabajan geólogos y paleontólogos de la Universidad de Valencia, la Universitat Jaume I de Castelló y el Grup Guix de Vila-real, cuya finalidad es localizar, estudiar e investigar nuevos yacimientos de vertebrados en otras formaciones de la comarca. Se han estudiado veinticuatro afloramientos, veintidós de los cuales se sitúan en la Fm. Mirambell (Barremiense temprano - parte inicial del Barremiense tardío, Cretácico Temprano) y dos de ellos se sitúan en la Fm. Els Mangraners (Valanginiense temprano - Hauteriviense tardío) y en la Fm. Artoles (Barremiense) respectivamente.Deposits of Mesozoic vertebrates, especially dinosaurs, discovered and studied in the region of Els Ports have been linked historically to the Morella Fm. (late Barremian, Early Cretaceous) formation. However, in recent years it has been launched a project from the University of Valencia, the Universitat Jaume I of Castelló and Grup Guix of Vila-real, whose purpose is to locate, study and research new sites of vertebrates in other formations of the region. Twenty four outcrops have been studied, twenty two of which are in the Mirambell Fm. (early Barremian - early part of late Barremian, Early Cretaceous) and two of them are in the Els Mangraners Fm. (early Valanginian - late Hauterivian) and the Artoles Fm. (Barremian) respectively

Good practice recommendations for the use of time-lapse technology†

STUDY QUESTION: What recommendations can be provided on the approach to and use of time-lapse technology (TLT) in an IVF laboratory?SUMMARY ANSWER: The present ESHRE document provides 11 recommendations on how to introduce TLT in the IVF laboratory. WHAT IS KNOWN ALREADY: Studies have been published on the use of TLT in clinical embryology. However, a systematic assessmentof how to approach and introduce this technology is currently missing.STUDY DESIGN, SIZE, DURATION: A working group of members of the Steering Committee of the ESHRE Special Interest Group in Embryology and selected ESHRE members was formed in order to write recommendations on the practical aspects of TLT for the IVF laboratory.PARTICIPANTS/MATERIALS, SETTING, METHODS: The working group included 11 members of different nationalities with internationally recognized experience in clinical embryology and basic science embryology, in addition to TLT. This document is developed according to the manual for development of ESHRE recommendations for good practice. Where possible, the statements are supported by studies retrieved from a PUBMED literature search on ‘time-lapse’ and ART.MAIN RESULTS AND THE ROLE OF CHANCE: A clear clinical benefit of the use of TLT, i.e. an increase in IVF success rates, remains to be proven. Meanwhile, TLT systems are being introduced in IVF laboratories. The working group listed 11 recommendations on what to do before introducing TLT in the lab. These statements include an assessment of the pros and cons of acquiring a TLT system, selection of relevant morphokinetic parameters, selection of an appropriate TLT system with technical and customer support, development of an internal checklist and education of staff. All these aspects are explained further here, based on the current literature and expert opinion.LIMITATIONS, REASONS FOR CAUTION: Owing to the limited evidence available, recommendations are mostly based on clinical and technical expertise. The paper provides technical advice, but leaves any decision on whether or not to use TLT to the individual centres.WIDER IMPLICATIONS OF THE FINDINGS: This document is expected to have a significant impact on future developments of clinical embryology, considering the increasing role and impact of TLT

Air pollution from traffic during pregnancy impairs newborn's cord blood immune cells: The NELA cohort

©2020. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the Accepted version of a Published Work that appeared in final form in Environmental Research. To access the final edited and published work see https:// doi.org/10.1016/j.envres.2020.110468Background: Hazards of traffic-related air pollution (TRAP) on the developing immune system are poorly understood. We sought to investigate the effects of prenatal exposure to TRAP on cord blood immune cell distributions; and to identify gestational windows of susceptibility. Methods: In-depth immunophenotyping of cord blood leukocyte and lymphocyte subsets was performed by flow cytometry in 190 newborns embedded in the Nutrition in Early Life and Asthma (NELA) birth cohort (2015-2018). Long-term (whole pregnancy and trimesters) and short-term (15-days before delivery) residential exposures to traffic-related nitrogen dioxide (NO2), particulate matter (PM2.5 and PM10), and ozone (O3) were estimated using dispersion/chemical transport modelling. Associations between TRAP concentrations and cord blood immune cell counts were assessed using multivariate Poisson regression models. Results: Mean number of natural killer (NK) cells decreased 15% in relation to higher NO2 concentrations (≥36.4 μg/m3) during whole pregnancy (incidence relative risk (IRR), 0.85; 95% CI, 0.72, 0.99), with stronger associations in the first trimester. Higher PM2.5 concentrations (≥13.3 μg/m3) during whole pregnancy associated with a reduced mean number of cytotoxic T cells (IRR, 0.88; 95% CI, 0.78, 0.99). Newborns exposed to higher PM10 (≥23.6 μg/m3) and PM2.5 concentrations during the first and third trimester showed greater mean number of helper T type 1 (Th1) cells (P < 0.05). Decreased number of regulatory T (Treg) cells was associated with greater short-term NO2 (IRR, 0.90; 95% CI, 0.80, 1.01) and PM10 (IRR, 0.88; 95% CI, 0.77, 0.99) concentrations. Conclusions: Prenatal exposure to TRAP, particularly in early and late gestation, impairs fetal immune system development through disturbances in cord blood leukocyte and lymphocyte distributions

Compartir saberes para cuidar mejor: "aulas invertidas" y producción colaborativa de conocimiento

Depto. de Sociología: Metodología y TeoríaFac. de Ciencias Políticas y SociologíaFALSEsubmitte