Machine Learning Improves Risk Stratification in Myelofibrosis: An Analysis of the Spanish Registry of Myelofibrosis

Myelofibrosis (MF) is a myeloproliferative neoplasm (MPN) with heterogeneous clinical course. Allogeneic hematopoietic cell transplantation remains the only curative therapy, but its morbidity and mortality require careful candidate selection. Therefore, accurate disease risk prognostication is critical for treatment decision-making. We obtained registry data from patients diagnosed with MF in 60 Spanish institutions (N = 1386). These were randomly divided into a training set (80%) and a test set (20%). A machine learning (ML) technique (random forest) was used to model overall survival (OS) and leukemia-free survival (LFS) in the training set, and the results were validated in the test set. We derived the AIPSS-MF (Artificial Intelligence Prognostic Scoring System for Myelofibrosis) model, which was based on 8 clinical variables at diagnosis and achieved high accuracy in predicting OS (training set c-index, 0.750; test set c-index, 0.744) and LFS (training set c-index, 0.697; test set c-index, 0.703). No improvement was obtained with the inclusion of MPN driver mutations in the model. We were unable to adequately assess the potential benefit of including adverse cytogenetics or high-risk mutations due to the lack of these data in many patients. AIPSS-MF was superior to the IPSS regardless of MF subtype and age range and outperformed the MYSEC-PM in patients with secondary MF. In conclusion, we have developed a prediction model based exclusively on clinical variables that provides individualized prognostic estimates in patients with primary and secondary MF. The use of AIPSS-MF in combination with predictive models that incorporate genetic information may improve disease risk stratification

4to. Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad. Memoria académica

Este volumen acoge la memoria académica de la Cuarta edición del Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad, CITIS 2017, desarrollado entre el 29 de noviembre y el 1 de diciembre de 2017 y organizado por la Universidad Politécnica Salesiana (UPS) en su sede de Guayaquil. El Congreso ofreció un espacio para la presentación, difusión e intercambio de importantes investigaciones nacionales e internacionales ante la comunidad universitaria que se dio cita en el encuentro. El uso de herramientas tecnológicas para la gestión de los trabajos de investigación como la plataforma Open Conference Systems y la web de presentación del Congreso http://citis.blog.ups.edu.ec/, hicieron de CITIS 2017 un verdadero referente entre los congresos que se desarrollaron en el país. La preocupación de nuestra Universidad, de presentar espacios que ayuden a generar nuevos y mejores cambios en la dimensión humana y social de nuestro entorno, hace que se persiga en cada edición del evento la presentación de trabajos con calidad creciente en cuanto a su producción científica. Quienes estuvimos al frente de la organización, dejamos plasmado en estas memorias académicas el intenso y prolífico trabajo de los días de realización del Congreso Internacional de Ciencia, Tecnología e Innovación para la Sociedad al alcance de todos y todas

Apicobasal Polarity Controls Lymphocyte Adhesion to Hepatic Epithelial Cells

Loss of apicobasal polarity is a hallmark of epithelial pathologies. Leukocyte infiltration and crosstalk with dysfunctional epithelial barriers are crucial for the inflammatory response. Here, we show that apicobasal architecture regulates the adhesion between hepatic epithelial cells and lymphocytes. Polarized hepatocytes and epithelium from bile ducts segregate the intercellular adhesion molecule 1 (ICAM-1) adhesion receptor onto their apical, microvilli-rich membranes, which are less accessible by circulating immune cells. Upon cell depolarization, hepatic ICAM-1 becomes exposed and increases lymphocyte binding. Polarized hepatic cells prevent ICAM-1 exposure to lymphocytes by redirecting basolateral ICAM-1 to apical domains. Loss of ICAM-1 polarity occurs in human inflammatory liver diseases and can be induced by the inflammatory cytokine tumor necrosis factor alpha (TNF-α). We propose that adhesion receptor polarization is a parenchymal immune checkpoint that allows functional epithelium to hamper leukocyte binding. This contributes to the haptotactic guidance of leukocytes toward neighboring damaged or chronically inflamed epithelial cells that expose their adhesion machinery