Synaptic dependence of dynamic regimes when coupling neural populations.

In this article we focus on the study of the collective dynamics of neural networks. The analysis of two recent models of coupled "next-generation" neural mass models allows us to observe different global mean dynamics of large neural populations. These models describe the mean dynamics of all-to-all coupled networks of quadratic integrate-and-fire spiking neurons. In addition, one of these models considers the influence of the synaptic adaptation mechanism on the macroscopic dynamics. We show how both models are related through a parameter and we study the evolution of the dynamics when switching from one model to the other by varying that parameter. Interestingly, we have detected three main dynamical regimes in the coupled models: Rössler-type (funnel type), bursting-type, and spiking-like (oscillator-type) dynamics. This result opens the question of which regime is the most suitable for realistic simulations of large neural networks and shows the possibility of the emergence of chaotic collective dynamics when synaptic adaptation is very weak.

Deep Learning for chaos detection.

In this article, we study how a chaos detection problem can be solved using Deep Learning techniques. We consider two classical test examples: the Logistic map as a discrete dynamical system and the Lorenz system as a continuous dynamical system. We train three types of artificial neural networks (multi-layer perceptron, convolutional neural network, and long short-term memory cell) to classify time series from the mentioned systems into regular or chaotic. This approach allows us to study biparametric and triparametric regions in the Lorenz system due to their low computational cost compared to traditional techniques.

Comparative safety of BRAF and MEK inhibitors (vemurafenib, dabrafenib and trametinib) in first-line therapy for BRAF-mutated metastatic melanoma.

A retrospective observational study was conducted on patients diagnosed with serine/threonine-protein kinase B-Raf (BRAF)-mutated metastatic melanoma, who underwent first-line therapy with BRAF and mitogen-activated protein kinase kinase (MEK) inhibitors (vemurafenib, dabrafenib or a combination of dabrafenib and trametinib) at the Miguel Servet University Hospital (Zaragoza, Spain) between November, 2011 and August, 2015. The aim of this study was to analyse the toxicity produced by BRAF and MEK inhibitors. The most common toxicities were similar to those published in clinical trials, particularly arthralgia, alopecia and photosensitivity in the vemurafenib group; asthenia, hyperkeratosis and dry skin in the dabrafenib group; and diarrhoea and dry skin in the dabrafenib plus trametinib group. Toxicities that had not been described in clinical trials were also identified. Thus, the present study confirmed that the results obtained in clinical trials are similar to those obtained in clinical practice.

Response to trabectedin treatment in a highly pretreated patient with an advanced meningeal hemangiopericytoma.

Meningeal hemangiopericytoma is an uncommon and aggressive malignancy that, in contrast to meningiomas, shows a high propensity for local recurrence and the development of late extraneural metastases. The results of chemotherapy in advanced hemangiopericytoma have been disappointing, and they have been particularly poor in cases located in the meninges. We report a case of a heavily pretreated metastatic meningeal hemangiopericytoma in which fourth-line chemotherapy with trabectedin, a marine-derived antineoplastic agent effective in treating advanced soft tissue sarcomas, resulted in clinical benefit.