Paleogeografía sísmica de zonas costeras en la Península Ibérica: su impacto en el análisis de terremotos antiguos e históricos en España

This paper presents three examples of ancient earthquakes occurring in coastal areas of the S and SE of the Iberian Peninsula (218 BC, AD 40-60 and AD 1048) with the aim of illustrating the use of geological and archaeological data in their macroseismic characterization. Historical information for ancient earthquakes that occurred in Spain prior to the 10th century is scarce or non-existent. This paper shows that the current state of knowledge on palaeoseismology and archaeoseismology on these ancient events clearly exceeds the existing historical information allowing the increase of macroseismic information points by using the ESI-07 scale (Environmental Seismic Intensity). Consequently, the geologic analyses of ancient earthquakes contribute to their understanding and parametric evaluations, and improve further advances in seismic hazard assessments. The most significant issue outlined in the present paper is the analysis of the ancient palaeogeography of the affected areas. The studied examples analysed were located in open estuarine areas that have been filled by fluvial sediments or anthropogenic fills over time. The effects of the 218 BC earthquake-tsunami event in the Gulf of Cadiz are analysed in estuarine areas, and especially in the ancient Roman Lagus Ligustinus (Guadalquivir Depression marshes); the effects of the earthquake in AD 40-60 is analysed in the old Roman city of Baelo Claudia located in the Bolonia Bay (Strait of Gibraltar); and the effects of the earthquake of AD 1048on the ancient Sinus Ilicitanus (Bajo Segura Depression) during Muslim times. Descriptions from Roman and Arabic geographers are cross-checked with existing palaeogeographic models based on geological data. This type of analysis results in ancient macroseismic scenarios for the interpretation of theoretical distributions of intensities and environmental effects supporting the concept of “seismic palaeogeography” proposed in this paperEl presente trabajo recoge tres ejemplos de terremotos antiguos (218 AC, 40-60 AD y 1048 AD) ocurridos en zonas litorales del S y SO de la Península Ibérica con la intención de ilustrar el uso de datos geológicos y ar¬queológicos en la caracterización macrosísmica de los mismos. En la mayor parte de los sísmos ocurridos con anterioridad al siglo X d.C. la información documental histórica que se posee es muy escasa o inexistente. El presente trabajo muestra que el actual estado de conocimiento en paleosismología y arqueosismologia sobre este tipo de terremotos sobrepasa con creces la información documental histórica, permitiendo la multiplica¬ción de los puntos de información macrosísmica mediante el uso de la escala ESI-07 (Environmental Seismic Intensity). Consecuentemente, el análisis geológico de los terremotos antiguos mejora su conocimiento y análisis paramétrico, permitiendo avanzar la evaluación de la peligrosidad sísmica de las zonas afectadas. El aspecto que se pone de especial relieve en este trabajo es el análisis de la paleogeografía existente en la antigüedad, ya que todas las zonas (afectadas) analizadas en este trabajo corresponden a zonas estuarinas abiertas que se han ido rellenado por aportes fluviales o de forma artificial con el tiempo. Se analizan los efectos del terremoto de 218 AC en las zonas estuarinas del Golfo de Cádiz y muy especialmente en el antiguo Lacus Ligustinus (marismas del Guadalquivir) durante época romana; los efectos del terremoto de 40-60 AD en la antigua Bahía de Baelo Claudia (Estrecho de Gibraltar); y los efectos del terremoto de 1048 AD en el antiguo Sinus ilicitanus (Depresión del Bajo Segura) durante época musulmana. Se han cotejado descripciones de geógrafos romanos y árabes con modelos basados en datos geológicos. Este tipo de análisis ha permitido generar antiguos escenarios macrosísmicos basados en la paleogeografía y reinterpretar las distribuciones teóricas de intensidades y los efectos ambientales de los terremotos estudiados que es a lo que se refiere el concepto de “paleogeografía sísmica” propuesto en este trabajoThis work has been funded by the Spanish-FEDER research projects CGL2012-37281 C02.01 (QTECTBETICA-USAL), CGL2012-33430 (CSIC) and CGL2013-42847-R (UNED

Introducción al patrimonio geológico de interés turístico de la Red Española de Reservas de la Biosfera

160 p.Esta publicación se ha realizado con el objetivo de describir el origen y formación de una buena parte del patrimonio geológico de interés turístico de la Red Española de Reservas de la Biosfera para que éste sea conocido y pueda ser utilizado como motor de desarrollo económico local. La necesidad de dar a conocer este sorprendente patrimonio natural de la Red español de Reservas de la Biosfera fue constatada por su Consejo de Gestores que encargó el trabajo a su Consejo Científico. La publicación tiene la vocación de ser accesible para todos los públicos. Sin embargo, parte de un trabajo bibliográfico profundo abordado con una rigurosa metodología científica. Es además el fruto de una continua colaboración de los editores con las personas gestoras de las Reservas de la Biosfera españolas, así como con varios miembros de su Consejo Científico asesor.Instituto Geológico y Minero de España, Españ

Computational Approaches to Explainable Artificial Intelligence:Advances in Theory, Applications and Trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9 International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications

How can Tourist Attractions profit from Augmented Reality?

The benefits, value and potential of Augmented Reality (AR) are widely researched. However, the value of AR is most commonly discussed in relation to enhancing the tourist experience, rather than generating revenue or economic returns. Although AR promises to add value to the visitor experience and generate associated benefits, the financial implications and revenue model for AR implementation remain uncertain and therefore too much of a financial risk for most tourist organisations, typically Small to Medium Sized Enterprises (SMEs) characterised by limited funding. Thus, using the case of UNESCO recognised Geevor Tin Mine Museum, in Cornwall, UK, this study identifies ways in which tourism organisations can profit from AR implementation. Fifty semi-structured interviews with Geevor stakeholders, analysed using content analysis reveal a number of ways AR can be introduced to increase revenue generation and profits, therefore filling a gap in research and minimising the risk for managers and practitioners considering AR implementation

Computational approaches to explainable artificial intelligence: Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.MCIU - Nvidia(UMA18-FEDERJA-084

Computational approaches to Explainable Artificial Intelligence:Advances in theory, applications and trends

Deep Learning (DL), a groundbreaking branch of Machine Learning (ML), has emerged as a driving force in both theoretical and applied Artificial Intelligence (AI). DL algorithms, rooted in complex and non-linear artificial neural systems, excel at extracting high-level features from data. DL has demonstrated human-level performance in real-world tasks, including clinical diagnostics, and has unlocked solutions to previously intractable problems in virtual agent design, robotics, genomics, neuroimaging, computer vision, and industrial automation. In this paper, the most relevant advances from the last few years in Artificial Intelligence (AI) and several applications to neuroscience, neuroimaging, computer vision, and robotics are presented, reviewed and discussed. In this way, we summarize the state-of-the-art in AI methods, models and applications within a collection of works presented at the 9th International Conference on the Interplay between Natural and Artificial Computation (IWINAC). The works presented in this paper are excellent examples of new scientific discoveries made in laboratories that have successfully transitioned to real-life applications.</p

Artificial intelligence within the interplay between natural and artificial computation:Advances in data science, trends and applications

Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general.BMS - Pfizer(U01 AG024904). Spanish Ministry of Science, projects: TIN2017-85827-P, RTI2018-098913-B-I00, PSI2015-65848-R, PGC2018-098813-B-C31, PGC2018-098813-B-C32, RTI2018-101114-B-I, TIN2017-90135-R, RTI2018-098743-B-I00 and RTI2018-094645-B-I00; the FPU program (FPU15/06512, FPU17/04154) and Juan de la Cierva (FJCI-2017–33022). Autonomous Government of Andalusia (Spain) projects: UMA18-FEDERJA-084. Consellería de Cultura, Educación e Ordenación Universitaria of Galicia: ED431C2017/12, accreditation 2016–2019, ED431G/08, ED431C2018/29, Comunidad de Madrid, Y2018/EMT-5062 and grant ED431F2018/02. PPMI – a public – private partnership – is funded by The Michael J. Fox Foundation for Parkinson’s Research and funding partners, including Abbott, Biogen Idec, F. Hoffman-La Roche Ltd., GE Healthcare, Genentech and Pfizer Inc

Stratification of radiosensitive brain metastases based on an actionable S100A9/RAGE resistance mechanism

Whole-brain radiotherapy (WBRT) is the treatment backbone for many patients with brain metastasis; however, its efficacy in preventing disease progression and the associated toxicity have questioned the clinical impact of this approach and emphasized the need for alternative treatments. Given the limited therapeutic options available for these patients and the poor understanding of the molecular mechanisms underlying the resistance of metastatic lesions to WBRT, we sought to uncover actionable targets and biomarkers that could help to refine patient selection. Through an unbiased analysis of experimental in vivo models of brain metastasis resistant to WBRT, we identified activation of the S100A9–RAGE–NF-κB–JunB pathway in brain metastases as a potential mediator of resistance in this organ. Targeting this pathway genetically or pharmacologically was sufficient to revert the WBRT resistance and increase therapeutic benefits in vivo at lower doses of radiation. In patients with primary melanoma, lung or breast adenocarcinoma developing brain metastasis, endogenous S100A9 levels in brain lesions correlated with clinical response to WBRT and underscored the potential of S100A9 levels in the blood as a noninvasive biomarker. Collectively, we provide a molecular framework to personalize WBRT and improve its efficacy through combination with a radiosensitizer that balances therapeutic benefit and toxicity.We thank all members of the Brain Metastasis Group and A. Chalmers, E. Wagner, O. Fernández-Capetillo, R. Ciérvide and A. Hidalgo for critical discussion of the manuscript; the CNIO Core Facilities for their excellent assistance; and Fox Chase Cancer Center Transgenic Facility for generation of S100A9 mice. We thank EuCOMM repository for providing S100A9 targeted embryonic stem cells. We also thank J. Massagué (MSKCC) for some of the BrM cell lines and M. Bosenberg (Yale) for the YUMM1.1 cell line. Samples from patients included in this study that provided by the Girona Biomedical Research Institute (IDIBGI) (Biobanc IDIBGI, B.0000872) are integrated into the Spanish National Biobanks Network and in the Xarxa de Bancs de Tumors de Catalunya (XBTC) financed by the Pla Director d’Oncologia de Catalunya. All patients consented to the storage of these samples in the biobank and for their use in research projects. This study was funded by MINECO (SAF2017-89643-R) (M.V.), Fundació La Marató de TV3 (201906-30-31-32) (J.B.-B., M.V. and A.C.), Fundación Ramón Areces (CIVP19S8163) (M.V.) and CIVP20S10662 (E.O.P.), Worldwide Cancer Research (19-0177) (M.V. and E.C.-J.M.), Cancer Research Institute (Clinic and Laboratory Integration Program CRI Award 2018 (54545) (M.V.), AECC (Coordinated Translational Groups 2017 (GCTRA16015SEOA) (M.V.), LAB AECC 2019 (LABAE19002VALI) (M.V.), ERC CoG (864759) (M.V.), Portuguese Foundation for Science and Technology (SFRH/bd/100089/2014) (C.M.), Boehringer-Ingelheim Fonds MD Fellowship (L.M.), La Caixa International PhD Program Fellowship-Marie Skłodowska-Curie (LCF/BQ/DI17/11620028) (P.G.-G.), La Caixa INPhINIT Fellowship (LCF/BQ/DI19/11730044) (A.P.-A.), MINECO-Severo Ochoa PhD Fellowship (BES-2017-081995) (L.A.-E.) and an AECC postdoctoral fellowship (POSTD19016PRIE) (N.P.). M.V. is an EMBO YIP member (4053). Additional support was provided by Gertrud and Erich Roggenbuck Stiftung (M.M.), Science Foundation Ireland Frontiers for the Future Award (19/FFP/6443) (L.Y.), Science Foundation Ireland Strategic Partnership Programme, Precision Oncology Ireland (18/SPP/3522) (L.Y.), Breast Cancer Now Fellowship Award with the generous support of Walk the Walk (2019AugSF1310) (D.V.), Science Foundation Ireland (20/FFP-P/8597) (D.V.), Paradifference Foundation (C.F.-T.), “la Caixa” Foundation (ID 100010434) (A.I.), European Union’s Horizon 2020 research and innovation programme under Marie Skłodowska-Curie grant agreement 847648 (CF/BQ/PI20/11760029) (A.I.), Champalimaud Centre for the Unknown (N.S.), Lisboa Regional Operational Programme (Lisboa 2020) (LISBOA01-0145-FEDER-022170) (N.S.), NCI (R01 CA227629; R01 CA218133) (S.I.G.), Fundació Roses Contra el Càncer (J.B.-B.), Ministerio de Universidades FPU Fellowship (FPU 18/00069) (P.T.), MICIN-Agencia Estatal de Investigación Fellowships (PRE2020-093032 and BES-2017-080415) (P.M. and E. Cintado, respectively), Ministerio de Ciencia, Innovación y Universidades-E050251 (PID2019-110292RB-I00) (J.L.T.), FCT (PTDC/MED-ONC/32222/2017) (C.C.F.), Fundação Millennium bcp (C.C.F.), private donations (C.C.F.) and the Foundation for Applied Cancer Research in Zurich (E.L.R. and M.W.)

Integrative multi-omics analysis identifies a prognostic miRNA signature and a targetable miR-21-3p/TSC2/mTOR axis in metastatic pheochromocytoma/paraganglioma

Pheochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumors that present variable outcomes. To date, no effective therapies or reliable prognostic markers are available for patients who develop metastatic PPGL (mPPGL). Our aim was to discover robust prognostic markers validated through models, and define specific therapeutic options according to tumor genomic features. : We analyzed three PPGL miRNome datasets (n=443), validated candidate markers and assessed them in serum samples (n=36) to find a metastatic miRNA signature. An integrative study of miRNome, transcriptome and proteome was performed to find miRNA targets, which were further characterized . : A signature of six miRNAs (miR-21-3p, miR-183-5p, miR-182-5p, miR-96-5p, miR-551b-3p, and miR-202-5p) was associated with metastatic risk and time to progression. A higher expression of five of these miRNAs was also detected in PPGL patients' liquid biopsies compared with controls. The combined expression of miR-21-3p/miR-183-5p showed the best power to predict metastasis (AUC=0.804, =4.67·10), and was found associated with pro-metastatic features, such as neuroendocrine-mesenchymal transition phenotype, and increased cell migration rate. A pan-cancer multi-omic integrative study correlated miR-21-3p levels with TSC2 expression, mTOR pathway activation, and a predictive signature for mTOR inhibitor-sensitivity in PPGLs and other cancers. Likewise, we demonstrated a repression and an enhanced rapamycin sensitivity upon miR-21-3p expression. : Our findings support the assessment of miR-21-3p/miR-183-5p, in tumors and liquid biopsies, as biomarkers for risk stratification to improve the PPGL patients' management. We propose miR-21-3p to select mPPGL patients who may benefit from mTOR inhibitors