Dystroglycan mediates clustering of essential GABAergic components in cerebellar Purkinje cells

Muscle dystrophin–glycoprotein complex (DGC) links the intracellular cytoskeleton to the extracellular matrix. In neurons, dystroglycan and dystrophin, two major components of the DGC, localize in a subset of GABAergic synapses, where their function is unclear. Here we used mouse models to analyze the specific role of the DGC in the organization and function of inhibitory synapses. Loss of full-length dystrophin in mdx mice resulted in a selective depletion of the transmembrane β-dystroglycan isoform from inhibitory post-synaptic sites in cerebellar Purkinje cells. Remarkably, there were no differences in the synaptic distribution of the extracellular α-dystroglycan subunit, of GABAA receptors and neuroligin 2. In contrast, conditional deletion of the dystroglycan gene from Purkinje cells caused a disruption of the DGC and severely impaired post-synaptic clustering of neuroligin 2, GABAA receptors and scaffolding proteins. Accordingly, whole-cell patch-clamp analysis revealed a significant reduction in the frequency and amplitude of spontaneous IPSCs recorded from Purkinje cells. In the long-term, deletion of dystroglycan resulted in a significant decrease of GABAergic innervation of Purkinje cells and caused an impairment of motor learning functions. These results show that dystroglycan is an essential synaptic organizer at GABAergic synapses in Purkinje cells

Framework SDF Machine Learning en transacciones financieras y detección temprana de fraudes

En la actualidad, con el crecimiento exponencial de transacciones financieras de tarjetas de crédito y débito, la disminución de barreras de acceso, la globalización y la inclusión financiera se ha incrementado en mayor medida el fraude y la inteligencia creativa para la mutación del comportamiento fraudulento. Es de vital importancia la detección temprana de fraude aplicando distintas estrategias basadas en inteligencia artificial que puedan mitigar, disminuir, y prevenir este flagelo. El objetivo de este trabajo es estudiar, analizar los fundamentos, técnicas, estrategias y herramientas de machine learning que nos permitan dar el paso necesario para abordar el tema de autorizaciones financieras y detección de fraude, cuyo abordaje se hace inalcanzable con estrategias determinísticas o algoritmia tradicional. A partir del estudio mencionando se construirá un framework consolidado aplicable en cada etapa del proceso, desde la adquisición de datos, tanto en línea como históricos, el pre-procesamiento, la clasificación y los aportes al modelo predictivo para la detección de fraude.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informátic

Framework SDF Machine Learning en transacciones financieras y detección temprana de fraudes

En la actualidad, con el crecimiento exponencial de transacciones financieras de tarjetas de crédito y débito, la disminución de barreras de acceso, la globalización y la inclusión financiera se ha incrementado en mayor medida el fraude y la inteligencia creativa para la mutación del comportamiento fraudulento. Es de vital importancia la detección temprana de fraude aplicando distintas estrategias basadas en inteligencia artificial que puedan mitigar, disminuir, y prevenir este flagelo. El objetivo de este trabajo es estudiar, analizar los fundamentos, técnicas, estrategias y herramientas de machine learning que nos permitan dar el paso necesario para abordar el tema de autorizaciones financieras y detección de fraude, cuyo abordaje se hace inalcanzable con estrategias determinísticas o algoritmia tradicional. A partir del estudio mencionando se construirá un framework consolidado aplicable en cada etapa del proceso, desde la adquisición de datos, tanto en línea como históricos, el pre-procesamiento, la clasificación y los aportes al modelo predictivo para la detección de fraude.Eje: Agentes y Sistemas Inteligentes.Red de Universidades con Carreras en Informátic

Endovascular Abdominal Aortic Aneurysm Repair With Ovation Alto Stent Graft: Protocol for the ALTAIR (ALTo endogrAft Italian Registry) Study

Background: Since 2010, the Ovation Abdominal Stent Graft System has offered an innovative sealing option for abdominal aortic aneurysm (AAA) by including a sealing ring filled with polymer 13 mm from the renal arteries. In August 2020, the redesigned Ovation Alto, with a sealing ring 6 mm closer to the top of the fabric, received CE Mark approval. Objective: This registry study aims to evaluate intraoperative, perioperative, and postoperative results in patients treated by the Alto stent graft (Endologix Inc.) for elective AAA repair in a multicentric consecutive experience. Methods: All consecutive eligible patients submitted to endovascular aneurysm repair (EVAR) by Alto Endovascular AAA implantation will be included in this analysis. Patients will be submitted to EVAR procedures based on their own preferences, anatomical features, and operators experience. An estimated number of 300 patients submitted to EVAR with Alto stent graft should be enrolled. It is estimated that the inclusion period will be 24 months. The follow-up period is set to be 5 years. Full data sets and cross-sectional images of contrast-enhanced computed tomography scan performed before EVAR, at the first postoperative month, at 24 or 36 months, and at 5-year follow-up interval will be reported in the central database for a centralized core laboratory review of morphological changes. The primary endpoint of the study is to evaluate the technical and clinical success of EVAR with the Alto stent graft in short- (90-day), mid- (1-year), and long-term (5-year) follow-up periods. The following secondary endpoints will be also addressed: operative time; intraoperative radiation exposure; contrast medium usage; AAA sac shrinkage at 12-month and 5-year follow-up; any potential role of patients' baseline characteristics, valuated on preoperative computed tomography angiographic study, and of device configuration (number of component) in the primary endpoint. Results: The study is currently in the recruitment phase and the final patient is expected to be treated by the end of 2023 and then followed up for 5 years. A total of 300 patients will be recruited. Analyses will focus on primary and secondary endpoints. Updated results will be shared at 1- and 3-5-year follow-ups. Conclusions: The results from this registry study could validate the safety and effectiveness of the new design of the Ovation Alto Stent Graft. The technical modifications to the endograft could allow for accommodation of a more comprehensive range of anatomies on-label