Characterization of angiotensin-converting enzymes 1 and 2 in the soleus and plantaris muscles of rats

Angiotensin-converting enzymes 1 (ACE1) and 2 (ACE2) are key enzymes of the renin-angiotensin system, which act antagonistically to regulate the levels of angiotensin II (Ang II) and Ang-(1-7). Considerable data show that ACE1 acts on normal skeletal muscle functions and architecture. However, little is known about ACE1 levels in muscles with different fiber compositions. Furthermore, ACE2 levels in skeletal muscle are not known. Therefore, the purpose of this study was to characterize protein expression and ACE1 and ACE2 activities in the soleus and plantaris muscles. Eight-week-old female Wistar rats (N = 8) were killed by decapitation and the muscle tissues harvested for biochemical and molecular analyses. ACE1 and ACE2 activities were investigated by a fluorometric method using Abz-FRK(Dnp)P-OH and Mca-YVADAPK(Dnp)-OH fluorogenic substrates, respectively. ACE1 and ACE2 protein expression was analyzed by Western blot. ACE2 was expressed in the skeletal muscle of rats. There was no difference between the soleus (type I) and plantaris (type II) muscles in terms of ACE2 activity (17.35 ± 1.7 vs 15.09 ± 0.8 uF·min-1·mg-1, respectively) and protein expression. ACE1 activity was higher in the plantaris muscle than in the soleus (71.5 ± 3.9 vs 57.9 ± 1.1 uF·min-1·mg-1, respectively). Moreover, a comparative dose-response curve of protein expression was established in the soleus and plantaris muscles, which indicated higher ACE1 levels in the plantaris muscle. The present findings showed similar ACE2 levels in the soleus and plantaris muscles that might result in a similar Ang II response; however, lower ACE1 levels could attenuate Ang II production and reduce bradykinin degradation in the soleus muscle compared to the plantaris. These effects should enhance the aerobic capacity necessary for oxidative muscle activity

Effect of Austenite Deformation on the Microstructure Evolution and Grain Refinement Under Accelerated Cooling Conditions

Although there has been much research regarding the effect of austenite deformation on accelerated cooled microstructures in microalloyed steels, there is still a lack of accurate data on boundary densities and effective grain sizes. Previous results observed from optical micrographs are not accurate enough, because, for displacive transformation products, a substantial part of the boundaries have disorientation angles below 15 deg. Therefore, in this research, a niobium microalloyed steel was used and electron backscattering diffraction mappings were performed on all of the transformed microstructures to obtain accurate results on boundary densities and grain refinement. It was found that with strain rising from 0 to 0.5, a transition from bainitic ferrite to acicular ferrite occurs and the effective grain size reduces from 5.7 to 3.1 μm. When further increasing strain from 0.5 to 0.7, dynamic recrystallization was triggered and postdynamic softening occurred during the accelerated cooling, leading to an inhomogeneous and coarse transformed microstructure. In the entire strain range, the density changes of boundaries with different disorientation angles are distinct, due to different boundary formation mechanisms. Finally, the controversial influence of austenite deformation on effective grain size of low-temperature transformation products was argued to be related to the differences in transformation conditions and final microstructures

Discovery of widespread transcription initiation at microsatellites predictable by sequence-based deep neural network

Using the Cap Analysis of Gene Expression (CAGE) technology, the FANTOM5 consortium provided one of the most comprehensive maps of transcription start sites (TSSs) in several species. Strikingly, ~72% of them could not be assigned to a specific gene and initiate at unconventional regions, outside promoters or enhancers. Here, we probe these unassigned TSSs and show that, in all species studied, a significant fraction of CAGE peaks initiate at microsatellites, also called short tandem repeats (STRs). To confirm this transcription, we develop Cap Trap RNA-seq, a technology which combines cap trapping and long read MinION sequencing. We train sequence-based deep learning models able to predict CAGE signal at STRs with high accuracy. These models unveil the importance of STR surrounding sequences not only to distinguish STR classes, but also to predict the level of transcription initiation. Importantly, genetic variants linked to human diseases are preferentially found at STRs with high transcription initiation level, supporting the biological and clinical relevance of transcription initiation at STRs. Together, our results extend the repertoire of non-coding transcription associated with DNA tandem repeats and complexify STR polymorphism