El trastorno por estrés postraumático en los supervivientes al cáncer: una revisión de los tratamientos psicológicos disponibles

Objective: Posttraumatic stress disorder (PTSD) appears frequently in cancer survivors, but not all survivors meet the criteria propo­sed by the DSM-V to be diagnosed with PTSD. This situation may lead an underestimation of the problem and furthermore, in this patient group, PTSD is related with different aspects of psychological well-being, such as depres­sion, anxiety or quality of life, However, the­re are only a few psychological interventions designed to reduce these symptoms in cancer survivors. Method: A review of the psychological treatments available for PTSD in cancer sur­vivors in the last 10 years was performed. The data bases used were PubMed, Web of Science (WOS) and PsycInfo with the following des­criptors: PTSD (posttraumatic stress disorder) treatment cancer survivors y PTSS (posttrau­matic stress symptoms) treatment cancer sur­vivors. Results: The psychological interventions with more evidence are: cognitive-behavioral therapy and mindfulness, ahead other strate­gies such as stress management training, neu­ro-emotional therapy, coping skills training and counseling. Conclusions: Despite the relevance of PTSD in this patients group, psychological interventions needs more evidence to establish their efficacy to reduce these symptoms in survivors.Objetivo: El trastorno por estrés postrau­mático (TEP) aparece con frecuencia en los su­pervivientes al cáncer, pero no todos los super­vivientes cumplen con los criterios propuestos por el DSM-V para ser diagnosticados. Esta situación puede provocar la subestimación del problema y además, en este grupo de pacien­tes el TEP se relaciona con diferentes aspectos del bienestar psicológico, como la depresión, la ansiedad o la calidad de vida. Sin embargo, solo hay unas pocas intervenciones psicológi­cas diseñadas para reducir estos síntomas en los supervivientes al cáncer. Método: Se realizó una revisión de los tra­tamientos psicológicos disponibles para el TEP en los supervivientes al cáncer en los últimos 10 años. Las bases de datos utilizadas fueron PubMed, Web of Science (WOS) y PsycInfo con los siguientes descriptores: PTSD (post­traumatic stress disorder), treatment cancer survivors y PTSS (posttraumatic stress symp­toms) treatment cancer survivors. Resultados: Las intervenciones psicológi­cas con una mayor evidencia son: la terapia de tipo cognitivo-conductual y el mindfulness, por delante del entrenamiento en el manejo del estrés, la terapia neuro-emocional, el en­trenamiento en habilidades de afrontamiento y el counseling. Conclusiones: A pesar de la relevancia del TEP en este grupo de pacientes, las interven­ciones psicológicas necesitan de una mayor evidencia para establecer su eficacia para re­ducir estos síntomas en los supervivientes

Methods for autonomous wristband placement with a search-and-rescue aerial manipulator

A new robotic system for Search And Rescue (SAR) operations based on the automatic wristband placement on the victims’ arm, which may provide identification, beaconing and remote sensor readings for continuous health monitoring. This paper focuses on the development of the automatic target localization and the device placement using an unmanned aerial manipulator. The automatic wrist detection and localization system uses an RGB-D camera and a convolutional neural network based on the region faster method (Faster R-CNN). A lightweight parallel delta manipulator with a large workspace has been built, and a new design of a wristband in the form of a passive detachable gripper, is presented, which under contact, automatically attaches to the human, while disengages from the manipulator. A new trajectory planning method has been used to minimize the torques caused by the external forces during contact, which cause attitude perturbations. Experiments have been done to evaluate the machine learning method for detection and location, and for the assessment of the performance of the trajectory planning method. The results show how the VGG-16 neural network provides a detection accuracy of 67.99%. Moreover, simulation experiments have been done to show that the new trajectories minimize the perturbations to the aerial platform.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Mitochondrial DNA in Osteoarthritis Disease

[Abstract] Osteoarthritis (OA) is the most prevalent chronic joint disease, and we actually know that the activation of maladaptive responses to injury, including pro-inflammatory pathways, leads to the loss of normal joint function characterized by cartilage degradation, bone remodeling, osteophyte formation, and joint inflammation [1]. Recent insights into the epidemiology and impact of OA on patients have clearly established that OA is a severe disease of the whole joint as an organ, with large unmet medical needs. OA has a complex etiology that comprises the combination of multiple factors, including gender, age, occupation, trauma, body mass index, and genetics. Approximately, between 30 and 65% of the risk of OA is genetically determined [2] with evidence accumulated from different genome-wide association studies (GWAS) [3]. Most of these studies focused on nuclear genetic variants; however, over the last decade, evidence has accumulated for an association between specific mitochondrial DNA (mtDNA) genetic variants, called haplogroups, and different OA-related features, including prevalence, progression, and incidence [4].Instituto de Salud Carlos III; CIBERCB06/01/0040Instituto de Salud Carlos III; RETIC-RIER-RD16/0012/0002Instituto de Salud Carlos III; PRB2-ISCIII-PT17/0019/0014Instituto de Salud Carlos III; PI14/01254Instituto de Salud Carlos III; PI16/02124Instituto de Salud Carlos III; PI17/0021

Mitochondria and Mitophagy: Biosensors for Cartilage Degradation and Osteoarthritis

Editoria

Combined therapies of antithrombotics and antioxidants delay in silico brain tumor progression

Glioblastoma multiforme, the most frequent type of primary brain tumor, is a rapidly evolving and spatially heterogeneous high-grade astrocytoma that presents areas of necrosis, hypercellularity and microvascular hyperplasia. The aberrant vasculature leads to hypoxic areas and results in an increase of the oxidative stress selecting for more invasive tumor cell phenotypes. In our study we assay in silico different therapeutic approaches which combine antithrombotics, antioxidants and standard radiotherapy. To do so, we have developed a biocomputational model of glioblastoma multiforme that incorporates the spatio-temporal interplay among two glioma cell phenotypes corresponding to oxygenated and hypoxic cells, a necrotic core and the local vasculature whose response evolves with tumor progression. Our numerical simulations predict that suitable combinations of antithrombotics and antioxidants may diminish, in a synergetic way, oxidative stress and the subsequent hypoxic response. This novel therapeutical strategy, with potentially low or no toxicity, might reduce tumor invasion and further sensitize glioblastoma multiforme to conventional radiotherapy or other cytotoxic agents, hopefully increasing median patient overall survival time.Comment: 8 figure

IoT platform for failure management in water transmission systems

In aging water supply systems, many components have exceeded their service life. Consequently, tools are needed to efficiently manage the failures in these systems. This work describes the development and implementation of a web tool for the management of breakdowns in water transmission networks. The proposed tool, called wAIter, consists of a network of wireless water pressure sensors that send real-time data to an IoT platform. The core of the platform consists of a rule-based decision algorithm, which detects and classifies failures based on the recorded pressure values and then sends an alert to repair them. In addition, wAIter uses the mathematical model of the hydraulic network to estimate the maximum repair time without causing supply interruptions. This information is key in the decision-making process to repair breakdowns and facilitate repair work management. Finally, the results of the implementation in a real water transmission network are presented

What did we learn from 'omics' studies in osteoarthritis

Review article[Abstract] Purpose of review: 'Omics' technologies developed for the massive analysis of the major biologically relevant molecules (genes, proteins, metabolites) have been applied to the study of osteoarthritis (OA) for more than a decade. Recent findings: 'Omics' studies have undoubtedly contributed to increase the knowledge on pathogenic processes related with OA and have provided hundreds to thousands of molecules that might have a putative biomarker utility for this disease. Summary: This review describes the most recent 'omics' studies in OA research, their conclusions, and discuss those remaining challenges. Still many validation studies must be performed in large and well-characterized cohorts for the translation of the findings from 'omics' strategies to clinical applications. The development of tools for the intelligent integration of 'omics' data with clinical and imaging information is also mandatory to take full profit of the work that has been already performed.Instituto de Salud Carlos III; PI14/01707Instituto de Salud Carlos III; PI14/01254Instituto de Salud Carlos III; PI16/02124Instituto de Salud Carlos III; CIBERCB06/ 01/0040Instituto de Salud Carlos III; RETIC-RIER-RD12/0009/0018Instituto de Salud Carlos III; PT13/000

Tumores en ganado ovino sacrificado en matadero

Trabajo presentado al: XL Congreso Nacional y el XVI Congreso Internacional de la Sociedad Española de Ovinotecnia y Caprinotecnia. (Castellón de la Plana, España, 16-18 septiembre 2015).Peer Reviewe

Detection of Temporality at Discourse Level on Financial News by Combining Natural Language Processing and Machine Learning

Finance-related news such as Bloomberg News, CNN Business and Forbes are valuable sources of real data for market screening systems. In news, an expert shares opinions beyond plain technical analyses that include context such as political, sociological and cultural factors. In the same text, the expert often discusses the performance of different assets. Some key statements are mere descriptions of past events while others are predictions. Therefore, understanding the temporality of the key statements in a text is essential to separate context information from valuable predictions. We propose a novel system to detect the temporality of finance-related news at discourse level that combines Natural Language Processing and Machine Learning techniques, and exploits sophisticated features such as syntactic and semantic dependencies. More specifically, we seek to extract the dominant tenses of the main statements, which may be either explicit or implicit. We have tested our system on a labelled dataset of finance-related news annotated by researchers with knowledge in the field. Experimental results reveal a high detection precision compared to an alternative rule-based baseline approach. Ultimately, this research contributes to the state-of-the-art of market screening by identifying predictive knowledge for financial decision making

Documenting models and workflows: the next challenge in the field of ecological data management

Los modelos ecológicos se han convertido en una pieza clave de esta ciencia. La generación de conocimiento se consigue en buena medida mediante procesos analíticos más o menos complejos aplicados sobre conjuntos de datos diversos. Pero buena parte del conocimiento necesario para diseñar e implementar esos modelos no está accesible a la comunidad científica. Proponemos la creación de herramientas informáticas para documentar, almacenar y ejecutar modelos ecológicos y flujos de trabajo. Estas herramientas (repositorios de modelos) están siendo desarrolladas por otras disciplinas como la biología molecular o las ciencias de la Tierra. Presentamos un repositorio de modelos (ModeleR) desarrollado en el contexto del Observatorio de seguimiento del cambio global de Sierra Nevada (Granada-Almería). Creemos que los repositorios de modelos fomentarán la cooperación entre científicos, mejorando la creación de conocimiento relevante que podría ser transferido a los tomadores de decisiones.Ecological models have become a key part of this scientific discipline. Most of the knowledge created by ecologists is obtained by applying analytical processes to primary data. But most of the information underlying how to create models or use analytic techniques already published in the scientific literature is not readily available to scientists. We are proposing the creation of computer tools that help to document, store and execute ecological models and scientific workflows. These tools (called model repositories) are being developed by other disciplines such as molecular biology and earth science. We are presenting a model repository (called ModeleR) that has been developed in the context of the Sierra Nevada Global Change Observatory (Granada-Almería. Spain). We believe that model repositories will foster cooperation among scientists, enhancing the creation of relevant knowledge that could be transferred to environmental managers.El desarrollo de ModeleR ha sido financiado por la Consejería de Medio Ambiente y Ordenación del Territorio de la Junta de Andalucía a través de la Red de Información Ambiental (REDIAM), gracias a un convenio llamado “Diseño y creación de un repositorio de modelos para la red de información ambiental de Andalucía”. A.J. Pérez-Luque agradece al MICINN por el contrato PTA 2011-6322-I