Jagiellonian University

About: Jagiellonian University is a education organization based out in Krakow, Poland. It is known for research contribution in the topics: Population & Catalysis. The organization has 17438 authors who have published 44092 publications receiving 862633 citations. The organization is also known as: Academia Cracoviensis & Akademia Krakowska.

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

A catalog of white light coronal mass ejections observed by the SOHO spacecraft

Abstract: [1] The Solar and Heliospheric Observatory (SOHO) mission's white light coronagraphs have observed nearly 7000 coronal mass ejections (CMEs) between 1996 and 2002. We have documented the measured properties of all these CMEs in an online catalog. We describe this catalog and present a summary of the statistical properties of the CMEs. The primary measurements made on each CME are the apparent central position angle, the angular width in the sky plane, and the height (heliocentric distance) as a function of time. The height-time measurements are then fitted to first- and second-order polynomials to derive the average apparent speed and acceleration of the CMEs. The statistical properties of CMEs are (1) the average width of normal CMEs (20° 900 km s−1) show deceleration. Solar cycle variation and statistical properties of CMEs are revealed with greater clarity in this study as compared with previous studies. Implications of our findings for CME models are discussed.

A closer look at memorization in deep networks

Abstract: We examine the role of memorization in deep learning, drawing connections to capacity, generalization, and adversarial robustness. While deep networks are capable of memorizing noise data, our results suggest that they tend to prioritize learning simple patterns first. In our experiments, we expose qualitative differences in gradient-based optimization of deep neural networks (DNNs) on noise vs. real data. We also demonstrate that for appropriately tuned explicit regularization (e.g., dropout) we can degrade DNN training performance on noise datasets without compromising generalization on real data. Our analysis suggests that the notions of effective capacity which are dataset independent are unlikely to explain the generalization performance of deep networks when trained with gradient based methods because training data itself plays an important role in determining the degree of memorization.

COVID-19 and the cardiovascular system: implications for risk assessment, diagnosis, and treatment options.

Abstract: The novel coronavirus disease (COVID-19) outbreak, caused by SARS-CoV-2, represents the greatest medical challenge in decades. We provide a comprehensive review of the clinical course of COVID-19, its comorbidities, and mechanistic considerations for future therapies. While COVID-19 primarily affects the lungs, causing interstitial pneumonitis and severe acute respiratory distress syndrome (ARDS), it also affects multiple organs, particularly the cardiovascular system. Risk of severe infection and mortality increase with advancing age and male sex. Mortality is increased by comorbidities: cardiovascular disease, hypertension, diabetes, chronic pulmonary disease, and cancer. The most common complications include arrhythmia (atrial fibrillation, ventricular tachyarrhythmia, and ventricular fibrillation), cardiac injury [elevated highly sensitive troponin I (hs-cTnI) and creatine kinase (CK) levels], fulminant myocarditis, heart failure, pulmonary embolism, and disseminated intravascular coagulation (DIC). Mechanistically, SARS-CoV-2, following proteolytic cleavage of its S protein by a serine protease, binds to the transmembrane angiotensin-converting enzyme 2 (ACE2) -a homologue of ACE-to enter type 2 pneumocytes, macrophages, perivascular pericytes, and cardiomyocytes. This may lead to myocardial dysfunction and damage, endothelial dysfunction, microvascular dysfunction, plaque instability, and myocardial infarction (MI). While ACE2 is essential for viral invasion, there is no evidence that ACE inhibitors or angiotensin receptor blockers (ARBs) worsen prognosis. Hence, patients should not discontinue their use. Moreover, renin-angiotensin-aldosterone system (RAAS) inhibitors might be beneficial in COVID-19. Initial immune and inflammatory responses induce a severe cytokine storm [interleukin (IL)-6, IL-7, IL-22, IL-17, etc.] during the rapid progression phase of COVID-19. Early evaluation and continued monitoring of cardiac damage (cTnI and NT-proBNP) and coagulation (D-dimer) after hospitalization may identify patients with cardiac injury and predict COVID-19 complications. Preventive measures (social distancing and social isolation) also increase cardiovascular risk. Cardiovascular considerations of therapies currently used, including remdesivir, chloroquine, hydroxychloroquine, tocilizumab, ribavirin, interferons, and lopinavir/ritonavir, as well as experimental therapies, such as human recombinant ACE2 (rhACE2), are discussed.

Astrocyte-mediated control of cerebral blood flow.

Abstract: Local increase in blood flow during neural activity forms the basis for functional brain imaging, but its mechanism remains poorly defined. Here we show that cortical astrocytes in vivo possess a powerful mechanism for rapid vasodilation. We imaged the activity of astrocytes labeled with the calcium (Ca(2+))-sensitive indicator rhod-2 in somatosensory cortex of adult mice. Photolysis of caged Ca(2+) in astrocytic endfeet ensheathing the vessel wall was associated with an 18% increase in arterial cross-section area that corresponded to a 37% increase in blood flow. Vasodilation occurred with a latency of only 1-2 s, and both indomethacin and the cyclooxygenase-1 inhibitor SC-560 blocked the photolysis-induced hyperemia. These observations implicate astrocytes in the control of local microcirculation and suggest that one of their physiological roles is to mediate vasodilation in response to increased neural activity.