Cardiac myxoma as a potential trigger of takotsubo cardiomyopathy: A brief review on mechanistic and clinical perspectives

In clinical practice, cardiac myxomas constitute the majority of benign cardiac neoplasms, and might potentially present with a variety of embolic, obstructive as well as constitutional symptoms. On the other hand, these neoplasms might be potentially associated with the evolution of takotsubo cardiomyopathy (TTC) that is universally considered as a transient form of acute myocardial dysfunction. Accordingly, the present paper primarily aims to focus on potential mechanisms and associated clinical implications of TTC evolution in the setting of cardiac myxomas.

Transient neonatal hypothyroidism in a boy with unbalanced translocation t(8;16)

Genetic defects resulting in deficiency of thyroid hormone synthesis can be found in about 10% of the patients with permanent congenital hypothyroidism, but the identification of genetic abnormalities in association with the transient form of the disease is extremely rare. We report the case of a boy with transient neonatal hypothyroidism that was undiagnosed in the neonatal screening, associated with extrathyroid malformations and mental retardation. The boy carries an unbalanced translocation t(8;16), and his maternal uncle had a similar phenotype. Chromosomal analysis defined the patient's karyotype as 46,XY,der(8)t(8;16)(q24.3;q22)mat,16qh+. Array-CGH with patient's DNA revealed a ~80 kb terminal deletion on chromosome 8q24.3qter, and a ~21 Mb duplication on chromosome 16q22qter. ZNF252 gene, mapped to the deleted region on patient's chromosome 8, is highly expressed in the thyroid, and may be a candidate gene for our patient's transient neonatal thyroid dysfunction. This is the first report on the association of a chromosomal translocation with the transient form of congenital hypothyroidism. This description creates new hypothesis for the physiopathology of transient congenital hypothyroidism, and may also contribute to the definition of the unbalanced translocation t(8;16)(q24.3;q22) phenotype, which has never been described before. Arq Bras Endocrinol Metab. 2012;56(8):564-9

Querical Data Networks

Recently, a family of massive self-organizing data networks has emerged. These networks mainly serve as large-scale distributed query processing systems. We term these networks Querical Data Networks (QDN). A QDN is a federation of a dynamic set of peer, autonomous nodes communicating through a transient-form interconnection. Data is naturally distributed among the QDN nodes in extra-fine grain, where a few data items are dynamically created, collected, and/or stored at each node. Therefore, the network scales linearly to the size of the dataset. With a dynamic dataset, a dynamic and large set of nodes, and a transient-form communication infrastructure, QDNs should be considered as the new generation of distributed database systems with significantly less constraining assumptions as compared to their ancestors. Peer-to-peer networks (Daswani, 2003) and sensor networks (Estrin, 1999, Akyildiz, 2002) are well-known examples of QDN.

Querical Data Networks

Recently, a family of massive self-organizing data networks has emerged. These networks mainly serve as large-scale distributed query-processing systems. We term these networks querical data networks (QDN). A QDN is a federation of a dynamic set of peer, autonomous nodes communicating through a transient-form interconnection. Data is naturally distributed among the QDN nodes in extra-fine grain, where a few data items are dynamically created, collected, and/or stored at each node. Therefore, the network scales linearly to the size of the data set. With a dynamic data set, a dynamic and large set of nodes, and a transient-form communication infrastructure, QDNs should be considered as the new generation of distributed database systems with significantly less constraining assumptions as compared to their ancestors. Peer-to-peer networks (Daswani, Garcia-Molina, & Yang, 2003) and sensor networks (Akyildiz, Su, Sankarasubramaniam, & Cayirci, 2002; Estrin, Govindan, Heidemann, & Kumar, 1999) are well-known examples of QDNs.