Myocardial infarction in a 33-year-old with inflammatory bowel disease: a case report.

BACKGROUND: ST elevation myocardial infarction is defined as acute myocardial injury with necrosis due to myocardial ischemia. The frequent cause is thrombotic occlusion of atherosclerotic coronary arteries. In particular situations, thromboembolism can cause myocardial infarction in patients with normal coronary arteries. CASE PRESENTATION: We report a particular case of myocardial infarction in a young, previously healthy patient with non-atherosclerotic coronary arteries and inflammatory bowel disease. Although we performed an extensive work up, no clear pathophysiological cause could be diagnosed. Most likely, myocardial infarction was associated with a hypercoagulative state related to systemic inflammation. CONCLUSION: The mechanisms of coagulation disturbances in the context of acute and chronic inflammation are not yet fully understood. A better understanding of cardiovascular events in patients with inflammatory bowel disease might lead to new treatment approaches of cardiovascular disease.

A report of two cases of myocarditis following mRNA coronavirus disease 2019 vaccination.

BACKGROUND: Vaccination is the most important measure to control the coronavirus disease 2019 (COVID-19) pandemic. Myocarditis has been reported as a rare adverse reaction to COVID-19 vaccines. The clinical presentation of myocarditis in such cases can range from mild general symptoms to acute heart failure. CASE SUMMARY: We report the cases of two young men who presented with chest pain and dyspnoea following the administration of the mRNA COVID-19 vaccine. Cardiac investigations revealed findings typical of acute myocarditis. DISCUSSION: Myocarditis is a rare complication following mRNA COVID-19 vaccination. In this case series, the temporal proximity of the development of acute myocarditis and the administration of the mRNA COVID-19 vaccine was acknowledged. In the absence of other causative factors, myocarditis in these patients potentially occurred due to an adverse reaction to the mRNA COVID-19 vaccine. However, a causal relationship remains speculative. Clinical suspicion of myocarditis should be high if patients present with chest pain or dyspnoea after receiving COVID-19 vaccination.

Utilizing the Switching Stochasticity of HfO2/TiOx-Based ReRAM Devices and the Concept of Multiple Device Synapses for the Classification of Overlapping and Noisy Patterns.

With the arrival of the Internet of Things (IoT) and the challenges arising from Big Data, neuromorphic chip concepts are seen as key solutions for coping with the massive amount of unstructured data streams by moving the computation closer to the sensors, the so-called "edge computing." Augmenting these chips with emerging memory technologies enables these edge devices with non-volatile and adaptive properties which are desirable for low power and online learning operations. However, an energy- and area-efficient realization of these systems requires disruptive hardware changes. Memristor-based solutions for these concepts are in the focus of research and industry due to their low-power and high-density online learning potential. Specifically, the filamentary-type valence change mechanism (VCM memories) have shown to be a promising candidate In consequence, physical models capturing a broad spectrum of experimentally observed features such as the pronounced cycle-to-cycle (c2c) and device-to-device (d2d) variability are required for accurate evaluation of the proposed concepts. In this study, we present an in-depth experimental analysis of d2d and c2c variability of filamentary-type bipolar switching HfO2/TiOx nano-sized crossbar devices and match the experimentally observed variabilities to our physically motivated JART VCM compact model. Based on this approach, we evaluate the concept of parallel operation of devices as a synapse both experimentally and theoretically. These parallel synapses form a synaptic array which is at the core of neuromorphic chips. We exploit the c2c variability of these devices for stochastic online learning which has shown to increase the effective bit precision of the devices. Finally, we demonstrate that stochastic switching features for a pattern classification task that can be employed in an online learning neural network.

The unique complexity of the CYP3A4 upstream region suggests a nongenetic explanation of its expression variability.

OBJECTIVE: The individually variable and unpredictable expression of CYP3A4 compromises therapies with 50% of contemporary drugs. Gene variants explain only a fraction of this variability. METHODS: We investigated the evolution of CYP3A4 transcriptional regulation by nuclear receptors such as the xenobiotics sensors PXR and CAR. RESULTS: The combination of a proximal ER6 element with XREM and CLEM represents the original scheme of CYP3A regulation by nuclear receptors in placental mammals. Among human CYP3A genes, this scheme is retained only in CYP3A4, whereas non-CYP3A4 genes lost these elements to a variable extent during primate evolution. In parallel, the number of elements outside XREM and CLEM potentially responsive to PXR and CAR increased in primate CYP3A4 orthologs, which led to enhanced CYP3A4 inducibility. Additions to the other primate CYP3A genes were more restricted and specific, as exemplified by a CYP3A5 DR4 site responsive to CAR, but not to PXR. All these changes resulted in human CYP3A4 having a much more complex upstream regulatory region in comparison to its paralogs. CONCLUSION: Instead of gene variants, the intraindividual CYP3A4 expression variability in humans may be primarily caused by particular sensitivity of this gene to endogenous and exogenous PXR and CAR ligands conferred by the unique complexity of its upstream regulatory region.