MORE: A multi‐objective refactoring recommendation approach to introducing design patterns and fixing code smells

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137556/1/smr1843.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137556/2/smr1843_am.pd

Comparative proteomic analysis in microdissected renal vessels from hypertensive SHR and WKY normotensive rats

Systemic hypertension leads to renal damage known as hypertensive nephrosclerosis without obvious clinical symptoms in the initial stages and it has a profound impact on the renal vascular physiology. Despite its major role in End Stage Renal Disease, many aspects of hypertensive nephrosclerosis remain unknown. In order to elucidate the biological pathways and macromolecules deregulated by hypertension, renal vessels were obtained by Laser Capture Microdissection (LCM) from Spontaneously Hypertensive Rats (SHR) and age-matched controls (20 weeks). Proteomic analysis was performed aiming to detect molecular alterations associated with hypertension at the renal vessels before the onset of vascular damage. This analysis identified 688 proteins, of which 58 were differentially expressed (15 up-regulated and 43 down-regulated) in SHR. Many of these proteins are involved in vascular tone regulation by modulating the activity of endothelial Nitric Oxide Synthase (eNOS) (Xaa-Pro aminopeptidase 1 (XPP1), N(G) N(G)-dimethylarginine dimethylaminohydrolase 1 (DDAH1), Dehydropteridine reductase (DHPR)) or in blood pressure control by regulating the renin-angiotensin system (Glutamyl aminopeptidase/Aminopeptidase A (AMPE), Aminopeptidase N (AMPN)). Moreover, pathway enrichment analysis revealed that the eNOS activation pathway is deregulated only in SHR. Our study demonstrates that hypertension causes early proteomic changes in the renal vessels of SHR. These changes are relevant to vascular tone regulation and consequently may be involved in the development of vascular damage and hypertensive nephrosclerosis. Further validation and interference studies to investigate potential therapeutic impact of these findings are warranted

Refactoring clustering in Java software networks

We present a study on the refactoring activities performed during the evolution of 7 popular Java open source software systems, using a complex network approach. We find that classes affected by refactorings are more likely to be interlinked than others, forming connected subgraphs. Our results show that in a software network, classes linked to refactored classes are likely to be refactored themselves. This result is meaningful because knowing how refactored classes are arranged inside a network could be useful to support developers in maintenance and refactoring activities