نتایج جستجو برای: electron transport system ets activity
تعداد نتایج: 3627471 فیلتر نتایج به سال:
Brain catecholamines are involved in the regulation of biological functions, including cardiovascular activity. The hypothalamus presents areas with high density of catecholaminergic neurons and the endothelin system. Two hypothalamic regions intimately related with the cardiovascular control are distinguished: the anterior (AHR) and posterior (PHR) hypothalamus, considered to be sympathoinhibi...
In this research, we have investigated the effect of increasing length on the electronic transport of an armchair graphene nano-ribbons with nitrogen atom impurity and without impurity. The semi-infinite, one-dimensional molecular systems are connected to two electrodes and the electron-electron interaction is ignored. The system is described by a simple tight binding model. All calculations ar...
In recent years, semiconductor nanostructures have become the model systems of choice for investigation of electrical conduction on short length scales. Quantum transport is studied in a two dimensional electron gas because of the combination of a large Fermi wavelength and large mean free path. In the present work, a numerical method is implemented in order to contribute to the understanding ...
The ETS transcription factor Ets-1 (E26 transformation-specific-1) plays a critical role in many physiological processes including angiogenesis, haematopoietic development and tumour progression. Its activity can be regulated by post-translational modifications, such as phosphorylation. Recently, we showed that Ets-1 is a target for SUMO (small ubiquitin-like modifier) modification and that PIA...
PURPOSE High-intensity short-duration interval training (HIT) stimulates functional and metabolic adaptation in skeletal muscle, but the influence of HIT on mitochondrial function remains poorly studied in humans. Mitochondrial metabolism as well as mitochondrial-associated protein expression were tested in untrained participants performing HIT over a 2-week period. METHODS Eight males perfor...
Abstract We present PEdestal Neural Network (PENN) as a machine learning model for tokamak pedestal predictions. Here, the is trained using EUROfusion JET database to predict electron temperature and density from set of global engineering plasma parameters. Results show that PENN makes accurate predictions on test database, with R 2 = 0.93 temperature, 0.91 density. To demonstrate applicability...
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