La UC3M impartirá ocho nuevos másteres y tres nuevos títulos propios para el curso 2016-2017

El número de estudiantes universitarios en España que tras graduarse decide ampliar su formación cursando un máster se ha ido incrementando año, tras año. La UC3M atiende a esta demanda social ofreciendo una enseñanza de calidad, innovación y con vocación internacional. El Centro de Postgrado organiza y coordina los estudios de máster, títulos propios y formación continua.Contiene: Entrevista a José Miguel Rodríguez-Pardo del Castillo (pp. 17-18). -- Entrevista a Cristina Leal (p. 19). -- Entrevista a Nicolás García (p. 20). -- Entrevista a David Ramos (p. 21). -- Entrevista a David Marcos (p. 22). -- Entrevista a Alberto Ceña (p. 23). -- Entrevista a Alessandro Serino (p. 24). -- Entrevista a Gabriella Németh (p. 25)

KIT/PDGFRA Variant Allele Frequency as Prognostic Factor in Gastrointestinal Stromal Tumors (GISTs): Results From a Multi-Institutional Cohort Study

Background: The patient selection for optimal adjuvant therapy in gastrointestinal stromal tumors (GISTs) is provided by nomogram based on tumor size, mitotic index, tumor location, and tumor rupture. Although mutational status is not currently used to risk assessment, tumor genotype showed a prognostic influence on natural history and tumor relapse. Innovative measures, such as KIT/PDGFRA-mutant-specific variant allele frequency (VAF) levels detection from next-generation sequencing (NGS), may act as a surrogate of tumor burden and correlate with prognosis and overall survival of patients with GIST, helping the choice for adjuvant treatment. Patients and methods: This was a multicenter, hospital-based, retrospective/prospective cohort study to investigate the prognostic role of KIT or PDGFRA-VAF of GIST in patients with radically resected localized disease. In the current manuscript, we present the results from the retrospective phase of the study. Results: Two-hundred (200) patients with GIST between 2015 and 2022 afferent to 6 Italian Oncologic Centers in the EURACAN Network were included in the study. The receiver operating characteristic (ROC) curves analysis was used to classify "low" vs. "high" VAF values, further normalized on neoplastic cellularity (nVAF). When RFS between the low and high nVAF groups were compared, patients with GIST with KIT/PDGFRA nVAF > 50% showed less favorable RFS than patients in the group of nVAF ≤ 50% (2-year RFS, 72.6% vs. 93%, respectively; P = .003). The multivariable Cox regression model confirmed these results. In the homogeneous sub-population of intermediate-risk, patients with KIT-mutated GIST, the presence of nVAF >50% was statistically associated with higher disease recurrence. Conclusion: In our study, we demonstrated that higher nVAF levels were independent predictors of GIST prognosis and survival in localized GIST patients with tumors harboring KIT or PDGFRA mutations. In the cohort of intermediate-risk patients, nVAF could be helpful to improve prognostication and the use of adjuvant imatinib

EEG paradigms as a supplemental tool to behavioral assessments of DOC

Introduction Diagnosis and prediction of recovery in the acute phase of disorders of consciousness (DOC) are critical for subsequent medical decisions. However, reliable assessment remains elusive due to the inability of current validated clinical scales to take into account motor and drive deficits. Recently, the Motor Behaviour Tool (MBT), a novel clinical scale, has been developed to address this caveat (1). In this context, neuroimaging and brain-computer interface (BCI) have also been proposed to improve the diagnosis and prognosis of these patients.(2). Objectives This pilot study aims to investigate the diagnostic and prognostic value of two electroencephalography (EEG)-based paradigms in patients with DOC, i.e., coma, Unresponsive Awareness Syndrome (UWS) or Minimally Conscious State (MCS). As a second step, we will employ them as evidence to further establish the added value of the MBT (i.e., assessment of minimal responses suggesting remaining conscious processing) combined with the Coma Recovery Scale-Revised (CRS-R), a standardized validated scale commonly used to assess consciousness in this population (3). Patients & Methods Acute DOC patients undergo CRS-R and MBT assessment prior to two EEG paradigms. Firstly, a motor attempt EEG-BCI coupled with Functional Electrical Stimulation (FES) is used (4). We hypothesize that replacing the need for overt movements with motor attempt can alleviate the tendency of CRS-R to underestimate the level of awareness in case of cognitive-motor dissociation (CMD) (5). In addition, a second EEG protocol presents patients with FES-tactile (T), auditory (A), and audio-tactile (AT) stimuli both in actionable and non-actionable space. EEG evoked potentials observed in the actionable space are expected to show a non-linear addition of sensory stimuli (i.e., A+T ≠ AT) indicating multisensory integration and the capacity of conscious processing (6). Results Pending elaborate analysis, preliminary findings show (Fig. 1) that BCI accuracy is significantly above chance only for a patient who was diagnosed as UWS by the CRS-R evaluation, but exhibited a motor behavior classified as CMD confirmed by the MBT tool, and not for one in real UWS (same diagnosis based on CRS-R and MBT), implying the presence of the hypothesized relation between motor EEG correlates and awareness (7). Average EEG evoked potentials of 8 patients during the second EEG paradigm highlight a difference between within (solid line) vs. outside (dashed line) the actionable space (Fig. 2), suggesting awareness-dependent modulation. Future analyses will explore correlations of such EEG descriptors with the clinical outcomes. Conclusion EEG correlates extracted from these EEG paradigms are promising tools for diagnosis of DOC and may supplement current clinical scales to help the validation of new tools like the MBT. References J. M. Pignat, E. Mauron, J. Jöhr, C. Gilart De Keranflec'h, D. Van De Ville, M. G. Preti, D. E. Meskaldji, V. Hörnberg, S. Laureys, B. Draganski, R. Frackowiak, K. Diserens, Outcome prediction of consciousness disorders in the acute stage based on a complementary motor behavioural tool, PLOS ONE 11(6), e0156882 (2016). A. M. Owen, M. R. Coleman, M. Boly, M. H. Davis, S. Laureys, J. D. Pickard, Detecting awareness in the vegetative state, Science, 313, 1402 (2006). J. T. Giacino, K. Kalmar, J. Whyte, The JFK Coma Recovery Scale-Revised: measurement characteristics and diagnostic utility, Arch. Phys. Med. Rehabil. 85(12), 2020-9 (2004). T. Corbet, R. Leeb, A. Biasiucci, S. Perdikis, J. del R. Millán et al. BCI-NMES therapy enhances effective connectivity in the damaged hemisphere in stroke patients. 6th International Brain-Computer Interface Meeting, Asilomar, California, USA (2016). N. D. Schiff, Cognitive motor dissociation following severe brain injuries, JAMA Neurol. 72(12), 1413–1415 (2015). J. P. Noel, C. Pfeiffer, O. Blanke, A. Serino, Full body peripersonal space as the space of the bodily self, Cognition 144, 49-57 (2015). A. M . Goldfine, J. D. Victor, M. M. Conte, J. C. Bardin, N. D. Schiff, Determination of awareness in patients with severe brain injury using EEG power spectral analysis, Clin. Neurophysiol. 122(11), 2157-68 (2011)

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research

Introduction: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several studies have been aimed at identifying biomarkers able to predict benefit from these therapies and create a prediction model of response, despite this there is a lack of information to help clinicians in the choice of therapy for lung cancer patients with advanced disease. This is primarily due to the complexity of lung cancer biology, where a single or few biomarkers are not sufficient to provide enough predictive capability to explain biologic differences; other reasons include the paucity of data collected by single studies performed in heterogeneous unmatched cohorts and the methodology of analysis. In fact, classical statistical methods are unable to analyze and integrate the magnitude of information from multiple biological and clinical sources (eg, genomics, transcriptomics, and radiomics). Methods and objectives: APOLLO11 is an Italian multicentre, observational study involving patients with a diagnosis of advanced lung cancer (NSCLC and SCLC) treated with innovative therapies. Retrospective and prospective collection of multiomic data, such as tissue- (eg, for genomic, transcriptomic analysis) and blood-based biologic material (eg, ctDNA, PBMC), in addition to clinical and radiological data (eg, for radiomic analysis) will be collected. The overall aim of the project is to build a consortium integrating different datasets and a virtual biobank from participating Italian lung cancer centers. To face with the large amount of data provided, AI and ML techniques will be applied will be applied to manage this large dataset in an effort to build an R-Model, integrating retrospective and prospective population-based data. The ultimate goal is to create a tool able to help physicians and patients to make treatment decisions. Conclusion: APOLLO11 aims to propose a breakthrough approach in lung cancer research, replacing the old, monocentric viewpoint towards a multicomprehensive, multiomic, multicenter model. Multicenter cancer datasets incorporating common virtual biobank and new methodologic approaches including artificial intelligence, machine learning up to deep learning is the road to the future in oncology launched by this project

The global meningitis genome partnership.

Genomic surveillance of bacterial meningitis pathogens is essential for effective disease control globally, enabling identification of emerging and expanding strains and consequent public health interventions. While there has been a rise in the use of whole genome sequencing, this has been driven predominately by a subset of countries with adequate capacity and resources. Global capacity to participate in surveillance needs to be expanded, particularly in low and middle-income countries with high disease burdens. In light of this, the WHO-led collaboration, Defeating Meningitis by 2030 Global Roadmap, has called for the establishment of a Global Meningitis Genome Partnership that links resources for: N. meningitidis (Nm), S. pneumoniae (Sp), H. influenzae (Hi) and S. agalactiae (Sa) to improve worldwide co-ordination of strain identification and tracking. Existing platforms containing relevant genomes include: PubMLST: Nm (31,622), Sp (15,132), Hi (1935), Sa (9026); The Wellcome Sanger Institute: Nm (13,711), Sp (> 24,000), Sa (6200), Hi (1738); and BMGAP: Nm (8785), Hi (2030). A steering group is being established to coordinate the initiative and encourage high-quality data curation. Next steps include: developing guidelines on open-access sharing of genomic data; defining a core set of metadata; and facilitating development of user-friendly interfaces that represent publicly available data

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Multi-messenger Observations of a Binary Neutron Star Merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ∼ 1.7 {{s}} with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of {40}-8+8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 {M}ȯ . An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ∼ 40 {{Mpc}}) less than 11 hours after the merger by the One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ∼10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ∼ 9 and ∼ 16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta.</p

Peripersonal space: A special way of representing space

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