This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting segments of patients. We highlight the validity of the classifiers developed to predict the mortality, reaching an appreciable accuracy. Finally, interpretable decision rules for estimating the risk of mortality of patients can be obtained from the decision tree, which can be crucial in the prioritization of medical care and resources.
Hypothalamic appetite regulation is a vital homeostatic process underlying global energy balance in animals and humans, its disturbances resulting in feeding disorders with high morbidity and mortality. The objective evaluation of appetite remains difficult, very often restricted to indirect measurements of food intake and body weight. We report here, the direct, non-invasive visualization of hypothalamic activation by fasting using diffusion weighted magnetic resonance imaging, in the mouse brain as well as in a preliminary study in the human brain. The brain of fed or fasted mice or humans were imaged at 7 or 1.5 Tesla, respectively, by diffusion weighted magnetic resonance imaging using a complete range of b values (10
Electronic nose technology -that exploits arrays of broadly-tuned chemical sensors -has matured to the point where it is routinely applied to the quality control of a wide range of commercial products, such as foods, beverages, and cosmetics. Even though a large number of companies exist that design, implement, and sell this technology, the issue of how a practical system is configured and optimized to a particular application domain is, at best, carried out using heuristic methods, or more often, completely ignored. The key theme of this chapter is how the selection of different chemical sensors is crucial to the overall system performance of these analytical instruments. By taking a geometric approach combined with simple linear algebra analysis, we demonstrate how the "tunings" of individual sensors affect the overall performance. New performance measures based on information theory are defined here that should be adopted for optimizing the performance of electronic nose systems. Handbook of Machine Olfaction,
We review the role of neuroglial compartmentation and transcellular neurotransmitter cycling during hypothalamic appetite regulation as detected by Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) methods. We address first the neurochemical basis of neuroendocrine regulation in the hypothalamus and the orexigenic and anorexigenic feed-back loops that control appetite. Then we examine the main MRI and MRS strategies that have been used to investigate appetite regulation. Manganese-enhanced magnetic resonance imaging (MEMRI), Blood oxygenation level-dependent contrast (BOLD), and Diffusion-weighted magnetic resonance imaging (DWI) have revealed Mn2+ accumulations, augmented oxygen consumptions, and astrocytic swelling in the hypothalamus under fasting conditions, respectively. High field 1H magnetic resonance in vivo, showed increased hypothalamic myo-inositol concentrations as compared to other cerebral structures. 1H and 13C high resolution magic angle spinning (HRMAS) revealed increased neuroglial oxidative and glycolytic metabolism, as well as increased hypothalamic glutamatergic and GABAergic neurotransmissions under orexigenic stimulation. We propose here an integrative interpretation of all these findings suggesting that the neuroendocrine regulation of appetite is supported by important ionic and metabolic transcellular fluxes which begin at the tripartite orexigenic clefts and become extended spatially in the hypothalamus through astrocytic networks becoming eventually MRI and MRS detectable.
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