Differential Regulation of PDE5 Expression in Left and Right Ventricles of Feline Hypertrophy Models

Though long known to affect smooth muscle biology, recent studies indicate that phosphodiesterase 5 (PDE5) is also expressed in myocardium. Recognizing that the regulation of PDE5 in hypertrophy is not well understood, we assessed the response of PDE5 expression and the level of cGMP-dependent kinase I (cGKI) in the left and right ventricles of feline hypertrophy models.Using a cDNA library of feline aortic smooth muscle cells, we identified and cloned PDE5 cDNA for the first time in this species. The sequence shares 98% identity with its human orthologue at the amino acid level. E. coli expression of the cloned allele allowed selection of antibodies with appropriate specificity, facilitating the analysis of PDE5 expression in feline models created by selective proximal aortic (Ao) or pulmonary artery (PA) banding that resulted in hypertrophy of the left ventricle (LV) and right ventricle (RV), respectively. We demonstrated that PDE5 expression responded differentially with a decreased expression in the LV and an increased expression in the RV in the Ao-banded model. Similarly, in the PA-banded model, LV showed reduced expression while the RV expression was unaltered. In addition, the expression of cGKI was significantly decreased in the RV of Ao-banded group, correlating inversely with the increase in PDE5 expression.The differential regulation of PDE5 and cGKI expression suggests that the mechanisms involved in hypertrophy could be different in RV vs. LV. Reciprocal PDE5 and cGKI expression in the RV of Ao-banded model suggests functional significance for PDE5 up-regulation

Discovery of Genetic Variation on Chromosome 5q22 Associated with Mortality in Heart Failure

Failure of the human heart to maintain sufficient output of blood for the demands of the body, heart failure, is a common condition with high mortality even with modern therapeutic alternatives. To identify molecular determinant

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press