A stressz rendszer szerepe az ópiát függőség kialakulásában: idegi, sejtszintű és molekuláris mechanizmusok = Involvement of brain stress system in opiate addiction: neuronal substrates, cellular and molecular mechanisms

1. A morfium függőség és megvonás aktiválja a neuroendokrin és az agyi stresszrendszert. 2. A hipotalamusz paravntrikuláris magjában illetve az ""extended"" amigdalában expresszálódó kortikotropin-releasing hormon (CRH) különböző módon szabályozza a morfium addikciót és megvonást kísérő hormonális, élettani és magatartási (érzelmi) reakciókat. 3. Sejtszinten a cAMP-reponse element binding protein (CREB) és a hozzá csatlakozó ko-regulátor fehérjék, mint pl a foszforilált TORC fontos szerepet játszanak a drogmegvonás kapcsán aktiválódó CRH gén szabályozásában mind a hipotalamuszban, mind az ""extended"" amigdalában. 4. A hipotalamikus és extrahipotalamikus területeket beidegző felszálló noradrenerg és orexinerg pályák különböző mechanizmussal vesznek részt a drogfüggőséggel és a drogmegvonással járó megvonási tünetek kialakításában. 5. A morfium függőséggel és a naloxonnal történő morfium megvonás okozta anyagcsere változások a hipotalamuszban eltérő módon befolyásolják a stresszel és a metabolikus szabályozássaél kapcsolatos neuropaptid gének expresszióját. | 1. Morphine dependence and naloxone-precipitated morphine withdrawal results in activation of the neuroendocrine and brain stress systems in the rat brain. 2. Corticotropin-releasing hormone expressed in the hypophyseotropic cells of the hypothalamus as well as in the extended amygdala plays a differential role in the development of hormonal, physiological, emotional and behavioral changes in addicted animals. 3. cAMP-response element binding protein (CREB) and its co-activators (such as pTORC) play a critical role in activation of corticotropin-releasing hormone gene expression both in the hypothalamus and in the extended amygdala. 4. Ascending noradrenergic and orexinergic pathways innervating hypothalamic and extrahypothalamic sites differentially regulate the development of hormonal, somatic and psychological symptoms of morphine withdrawal. 5. Metabolic changes associated by drug dependence and withdrawal result in differential changes of metabolic and stress-related neuropeptides in the hypothalamus

A search for ultra-high-energy photons at the Pierre Auger Observatory exploiting air-shower universality

The Pierre Auger Observatory is the most sensitive detector to primary photons with energies above ∼0.2 EeV. It measures extensive air showers using a hybrid technique that combines a fluorescence detector (FD) with a ground array of particle detectors (SD). The signatures of a photon-induced air shower are a larger atmospheric depth at the shower maximum (X$_{max}$) and a steeper lateral distribution function, along with a lower number of muons with respect to the bulk of hadron-induced background. Using observables measured by the FD and SD, three photon searches in different energy bands are performed. In particular, between threshold energies of 1-10 EeV, a new analysis technique has been developed by combining the FD-based measurement of X$_{max}$ with the SD signal through a parameter related to its muon content, derived from the universality of the air showers. This technique has led to a better photon/hadron separation and, consequently, to a higher search sensitivity, resulting in a tighter upper limit than before. The outcome of this new analysis is presented here, along with previous results in the energy ranges below 1 EeV and above 10 EeV. From the data collected by the Pierre Auger Observatory in about 15 years of operation, the most stringent constraints on the fraction of photons in the cosmic flux are set over almost three decades in energy

Study on multi-ELVES in the Pierre Auger Observatory

Since 2013, the four sites of the Fluorescence Detector (FD) of the Pierre Auger Observatory record ELVES with a dedicated trigger. These UV light emissions are correlated to distant lightning strikes. The length of recorded traces has been increased from 100 μs (2013), to 300 μs (2014-16), to 900 μs (2017-present), to progressively extend the observation of the light emission towards the vertical of the causative lightning and beyond. A large fraction of the observed events shows double ELVES within the time window, and, in some cases, even more complex structures are observed. The nature of the multi-ELVES is not completely understood but may be related to the different types of lightning in which they are originated. For example, it is known that Narrow Bipolar Events can produce double ELVES, and Energetic In-cloud Pulses, occurring between the main negative and upper positive charge layer of clouds, can induce double and even quadruple ELVES in the ionosphere. This report shows the seasonal and daily dependence of the time gap, amplitude ratio, and correlation between the pulse widths of the peaks in a sample of 1000+ multi-ELVES events recorded during the period 2014-20. The events have been compared with data from other satellite and ground-based sensing devices to study the correlation of their properties with lightning observables such as altitude and polarity

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration