51 research outputs found

    Las terrazas fluviales de Córdoba y su influencia en el emplazamiento de la ciudad en época prerromana y romana

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    Se presenta la cartografía geológica de la Sierra de Córdoba, que incluye las terrazas fluviales del río Guadalquivir estudiadas por Liñán Guijarro (1978) entre Villafranca de Córdoba y Almodóvar del Río. La natural prolongación de estas terrazas bajo el casco antiguo de la actual ciudad de Córdoba, el análisis de la topografía urbana y las recientes aportaciones realizadas por otros autores, permiten inferir los vestigios de las tres terrazas inferiores a su paso por la ciudad. Se analiza cómo esta peculiar estructura geomorfológica pudo ser uno de los factores importantes que condicionaron la fundación y el desarrollo urbano tanto de la Corduba prerromana como de la Córdoba romana. The geological cartography of the Sierra de Cordoba, including the fluvial terraces of the Guadalquivir river defined by Linan Guijarro (1978) between Villafranca de Cordoba and Almodovar del Rio, is presented. The natural extension of the terraces under the historic centre of Cordoba, the study of the urban topography and the recent discoveries of other authors, have allowed us to study the remains of the lowermost three terraces in the city. In this paper, it is shown how this particular geomorphic structure could have been a key factor that determined the foundation and the urban development of the Pre-Roman Corduba as well as the Roman Corduba

    Inhibition of Piezo1 attenuates demyelination in the central nervous system

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    Piezo1 is a mechanosensitive ion channel that facilitates the translation of extracellular mechanical cues to intracellular molecular signaling cascades through a process termed, mechanotransduction. In the central nervous system (CNS), mechanically gated ion channels are important regulators of neurodevelopmental processes such as axon guidance, neural stem cell differentiation, and myelination of axons by oligodendrocytes. Here, we present evidence that pharmacologically mediated overactivation of Piezo1 channels negatively regulates CNS myelination. Moreover, we found that the peptide GsMTx4, an antagonist of mechanosensitive cation channels such as Piezo1, is neuroprotective and prevents chemically induced demyelination. In contrast, the positive modulator of Piezo1 channel opening, Yoda‐1, induces demyelination and neuronal damage. Using an ex vivo murine‐derived organotypic cerebellar slice culture model, we demonstrate that GsMTx4 attenuates demyelination induced by the cytotoxic lipid, psychosine. Importantly, we confirmed the potential therapeutic effects of GsMTx4 peptide in vivo by co‐administering it with lysophosphatidylcholine (LPC), via stereotactic injection, into the cerebral cortex of adult mice. GsMTx4 prevented both demyelination and neuronal damage usually caused by the intracortical injection of LPC in vivo; a well‐characterized model of focal demyelination. GsMTx4 also attenuated both LPC‐induced astrocyte toxicity and microglial reactivity within the lesion core. Overall, our data suggest that pharmacological activation of Piezo1 channels induces demyelination and that inhibition of mechanosensitive channels, using GsMTx4, may alleviate the secondary progressive neurodegeneration often present in the latter stages of demyelinating diseases

    Modelagem e controle avançado não-linear multivariável por lógica nebulosa : aplicação para um processo de copolimerização

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    A obtenção de um modelo matemático confiável de um dado processo é um pré-requisito fundamental para o projeto de controladores. Contudo, particularmente para sistemas poliméricos que são intrinsecamente caracterizados por dinâmicas complexas, o delineamento de uma aproximação a partir dos primeiros princípios é uma tarefa bastante árdua e, por vezes, não realizável. Logo, representações matemáticas mais simples, porém reprodutivas das principais peculiaridades do sistema, são bem-vindas. Assim sendo, este trabalho apresenta o desenvolvimento e a implementação de dois esquemas de controle preditivo não-linear multivariável baseado em modelo nebuloso para um processo de copolimerização. Modelos MISO (Multi-Input/Single-Output) lineares e exponenciais são construídos a partir da lógica nebulosa, combinados e aplicados para simulação e predição on-line. Os desempenhos das estruturas de controle propostas foram comparados ao DMC (Dynamic Matrix Control) e a um típico NMPC (Nonlinear Model-based Predictive Control) para o problema servo. Os resultados obtidos comprovaram a eficácia das configurações projetadas

    Multivariable nonlinear advanced control of copolymerization processes

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    A reliable multivariable model of a process is a fundamental prerequisite for the design of an efficient control strategy. Though, such a model is often very hard to obtain via a first-principles approach. The development of two fuzzy model-based multivariable nonlinear predictive control schemes and their implementation on a copolymerization process are described in this paper. Multi-input/single-output models are developed using fuzzy logic and combined to form a parallel system model for simulation and online prediction. The behavior of the outlined controllers were compared to the dynamic matrix control (DMC) and to a typical nonlinear model-based predictive control (NMPC) for regulatory problem and the obtained results showed the effectiveness of the proposed structures

    Understanding the design-space of sparse/dense multiphase GNN dataflows on spatial accelerators

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    Graph Neural Networks (GNNs) have garnered a lot of recent interest because of their success in learning representations from graph-structured data across several critical applications in cloud and HPC. Owing to their unique compute and memory characteristics that come from an interplay between dense and sparse phases of computations, the emergence of recon-figurable dataflow (aka spatial) accelerators offers promise for acceleration by mapping optimized dataflows (i.e., computation order and parallelism) for both phases. The goal of this work is to characterize and understand the design-space of dataflow choices for running GNNs on spatial accelerators in order for mappers or design-space exploration tools to optimize the dataflow based on the workload. Specifically, we propose a taxonomy to describe all possible choices for mapping the dense and sparse phases of GNN inference, spatially and temporally over a spatial accelerator, capturing both the intra-phase dataflow and the inter-phase (pipelined) dataflow. Using this taxonomy, we do deep-dives into the cost and benefits of several dataflows and perform case studies on implications of hardware parameters for dataflows and value of flexibility to support pipelined execution.Parts of this work were supported through a fellowship by NEC Laboratories Europe, Project grant PID2020-112827GB-I00 funded by MCIN/AEI/ 10.13039/501100011033, RTI2018-098156-B-C53 (MCIU/AEI/FEDER,UE) and grant 20749/FPI/18 from Fundación Séneca.Peer ReviewedPostprint (author's final draft

    Determinants of enhanced vulnerability to COVID-19 in UK cancer patients: a European Study

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    Background: Despite high contagiousness and rapid spread, SARS-CoV-2 has led to heterogeneous outcomes across affected nations. Within Europe, the United Kingdom (UK) is the most severely affected country, with a death toll in excess of 100.000 as of January 2021. We aimed to compare the national impact of COVID-19 on the risk of death in UK cancer patients versus those in continental Europe (EU). / Methods: We performed a retrospective analysis of the OnCovid study database, a European registry of cancer patients consecutively diagnosed with COVID-19 in 27 centres from February 27 to September 10, 2020. We analysed case fatality rates and risk of death at 30 days and 6 months stratified by region of origin (UK versus EU). We compared patient characteristics at baseline, including oncological and COVID-19 specific therapy across UK and EU cohorts and evaluated the association of these factors with the risk adverse outcome in multivariable Cox regression models. / Findings: Compared to EU (n=924), UK patients (n=468) were characterised by higher case fatality rates (40.38% versus 26.5%, p<0.0001), higher risk of death at 30 days (hazard ratio, HR 1.64 [95%CI 1.36-1.99]) and 6 months after COVID-19 diagnosis (47.64% versus 33.33%, p<0.0001, HR 1.59 [95%CI 1.33-1.88]). UK patients were more often males, of older age and more co-morbid than EU counterparts (p<0.01). Receipt of anticancer therapy was lower in UK versus EU patients (p<0.001). Despite equal proportions of complicated COVID-19, rates of intensive care admission and use of mechanical ventilation, UK cancer patients were less likely to receive anti-COVID-19 therapies including corticosteroids, anti-virals and interleukin-6 antagonists (p<0.0001). Multivariable analyses adjusted for imbalanced prognostic factors confirmed the UK cohort to be characterised by worse risk of death at 30 days and 6 months, independent of patient’s age, gender, tumour stage and status, number of co-morbidities, COVID-19 severity, receipt of anticancer and anti-COVID-19 therapy. Rates of permanent cessation of anticancer therapy post COVID-19 were similar in UK versus EU. / Interpretation: UK cancer patients have been more severely impacted by the unfolding of the COVID-19 pandemic despite societal risk mitigation factors and rapid deferral of anticancer therapy. The increased frailty of UK cancer patients highlights high-risk groups that should be prioritised for anti-SARS-CoV-2 vaccination. Continued evaluation of long-term outcomes is warranted

    Specialist palliative and end-of-life care for patients with cancer and SARS-CoV-2 infection: a European perspective

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    Background: Specialist palliative care team (SPCT) involvement has been shown to improve symptom control and end-of-life care for patients with cancer, but little is known as to how these have been impacted by the COVID-19 pandemic. Here, we report SPCT involvement during the first wave of the pandemic and compare outcomes for patients with cancer who received and did not receive SPCT input from multiple European cancer centres. Methods: From the OnCovid repository (N = 1318), we analysed cancer patients aged ⩾18 diagnosed with COVID-19 between 26 February and 22 June 2020 who had complete specialist palliative care team data (SPCT+ referred; SPCT− not referred). Results: Of 555 eligible patients, 317 were male (57.1%), with a median age of 70 years (IQR 20). At COVID-19 diagnosis, 44.7% were on anti-cancer therapy and 53.3% had ⩾1 co-morbidity. Two hundred and six patients received SPCT input for symptom control (80.1%), psychological support (54.4%) and/or advance care planning (51%). SPCT+ patients had more ‘Do not attempt cardio-pulmonary resuscitation’ orders completed prior to (12.6% versus 3.7%) and during admission (50% versus 22.1%, p < 0.001), with more SPCT+ patients deemed suitable for treatment escalation (50% versus 22.1%, p < 0.001). SPCT involvement was associated with higher discharge rates from hospital for end-of-life care (9.7% versus 0%, p < 0.001). End-of-life anticipatory prescribing was higher in SPCT+ patients, with opioids (96.3% versus 47.1%) and benzodiazepines (82.9% versus 41.2%) being used frequently for symptom control. Conclusion: SPCT referral facilitated symptom control, emergency care and discharge planning, as well as high rates of referral for psychological support than previously reported. Our study highlighted the critical need of SPCTs for patients with cancer during the pandemic and should inform service planning for this population

    Prevalence and impact of COVID-19 sequelae on treatment and survival of patients with cancer who recovered from SARS-CoV-2 infection: evidence from the OnCovid retrospective, multicentre registry study

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    Background: The medium-term and long-term impact of COVID-19 in patients with cancer is not yet known. In this study, we aimed to describe the prevalence of COVID-19 sequelae and their impact on the survival of patients with cancer. We also aimed to describe patterns of resumption and modifications of systemic anti-cancer therapy following recovery from SARS-CoV-2 infection. Methods: OnCovid is an active European registry study enrolling consecutive patients aged 18 years or older with a history of solid or haematological malignancy and who had a diagnosis of RT-PCR confirmed SARS-CoV-2 infection. For this retrospective study, patients were enrolled from 35 institutions across Belgium, France, Germany, Italy, Spain, and the UK. Patients who were diagnosed with SARS-CoV-2 infection between Feb 27, 2020, and Feb 14, 2021, and entered into the registry at the point of data lock (March 1, 2021), were eligible for analysis. The present analysis was focused on COVID-19 survivors who underwent clinical reassessment at each participating institution. We documented prevalence of COVID-19 sequelae and described factors associated with their development and their association with post-COVID-19 survival, which was defined as the interval from post-COVID-19 reassessment to the patients’ death or last follow-up. We also evaluated resumption of systemic anti-cancer therapy in patients treated within 4 weeks of COVID-19 diagnosis. The OnCovid study is registered in ClinicalTrials.gov, NCT04393974. Findings: 2795 patients diagnosed with SARS-CoV-2 infection between Feb 27, 2020, and Feb 14, 2021, were entered into the study by the time of the data lock on March 1, 2021. After the exclusion of ineligible patients, the final study population consisted of 2634 patients. 1557 COVID-19 survivors underwent a formal clinical reassessment after a median of 22·1 months (IQR 8·4–57·8) from cancer diagnosis and 44 days (28–329) from COVID-19 diagnosis. 234 (15·0%) patients reported COVID-19 sequelae, including respiratory symptoms (116 [49·6%]) and residual fatigue (96 [41·0%]). Sequelae were more common in men (vs women; p=0·041), patients aged 65 years or older (vs other age groups; p=0·048), patients with two or more comorbidities (vs one or none; p=0·0006), and patients with a history of smoking (vs no smoking history; p=0·0004). Sequelae were associated with hospitalisation for COVID-19 (p<0·0001), complicated COVID-19 (p<0·0001), and COVID-19 therapy (p=0·0002). With a median post-COVID-19 follow-up of 128 days (95% CI 113–148), COVID-19 sequelae were associated with an increased risk of death (hazard ratio [HR] 1·80 [95% CI 1·18–2·75]) after adjusting for time to post-COVID-19 reassessment, sex, age, comorbidity burden, tumour characteristics, anticancer therapy, and COVID-19 severity. Among 466 patients on systemic anti-cancer therapy, 70 (15·0%) permanently discontinued therapy, and 178 (38·2%) resumed treatment with a dose or regimen adjustment. Permanent treatment discontinuations were independently associated with an increased risk of death (HR 3·53 [95% CI 1·45–8·59]), but dose or regimen adjustments were not (0·84 [0·35–2·02]). Interpretation: Sequelae post-COVID-19 affect up to 15% of patients with cancer and adversely affect survival and oncological outcomes after recovery. Adjustments to systemic anti-cancer therapy can be safely pursued in treatment-eligible patients. Funding: National Institute for Health Research Imperial Biomedical Research Centre and the Cancer Treatment and Research Trust
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