scholarly journals The dual distinct role of telomerase in repression of senescence and myofibroblast differentiation

Aging ◽  
2021 ◽  
Author(s):  
Masanori Harada ◽  
Biao Hu ◽  
Jeffrey Lu ◽  
Jing Wang ◽  
Andrew E. Rinke ◽  
...  
Molecules ◽  
2021 ◽  
Vol 26 (8) ◽  
pp. 2231
Author(s):  
Qingjun Lu ◽  
Hao Shen ◽  
Han Yu ◽  
Jing Fu ◽  
Hui Dong ◽  
...  

The role of Kupffer cells (KCs) in liver regeneration is complicated and controversial. To investigate the distinct role of F4/80+ KCs at the different stages of the regeneration process, two-thirds partial hepatectomy (PHx) was performed in mice to induce physiological liver regeneration. In pre- or post-PHx, the clearance of KCs by intraperitoneal injection of the anti-F4/80 antibody (α-F4/80) was performed to study the distinct role of F4/80+ KCs during the regenerative process. In RNA sequencing of isolated F4/80+ KCs, the initiation phase was compared with the progression phase. Immunohistochemistry and immunofluorescence staining of Ki67, HNF-4α, CD-31, and F4/80 and Western blot of the TGF-β2 pathway were performed. Depletion of F4/80+ KCs in pre-PHx delayed the peak of hepatocyte proliferation from 48 h to 120 h, whereas depletion in post-PHx unexpectedly led to persistent inhibition of hepatocyte proliferation, indicating the distinct role of F4/80+ KCs in the initiation and progression phases of liver regeneration. F4/80+ KC depletion in post-PHx could significantly increase TGF-β2 serum levels, while TGF-βRI partially rescued the impaired proliferation of hepatocytes. Additionally, F4/80+ KC depletion in post-PHx significantly lowered the expression of oncostatin M (OSM), a key downstream mediator of interleukin-6, which is required for hepatocyte proliferation during liver regeneration. In vivo, recombinant OSM (r-OSM) treatment alleviated the inhibitory effect of α-F4/80 on the regenerative progression. Collectively, F4/80+ KCs release OSM to inhibit TGF-β2 activation, sustaining hepatocyte proliferation by releasing a proliferative brake.


2018 ◽  
Vol 94 (6) ◽  
Author(s):  
Constantina Rousidou ◽  
Dionysis Karaiskos ◽  
Despoina Myti ◽  
Evangelos Karanasios ◽  
Panagiotis A Karas ◽  
...  
Keyword(s):  
Soil Ph ◽  

2015 ◽  
Vol 12 (Supplement 1) ◽  
pp. S74-S75
Author(s):  
Shaik O. Rahaman ◽  
Lisa M. Grove ◽  
Brian D. Southern ◽  
Rachel G. Scheraga ◽  
Susamma Abraham ◽  
...  

2009 ◽  
Vol 41 (3) ◽  
pp. 332-338 ◽  
Author(s):  
Nathan Sandbo ◽  
Steven Kregel ◽  
Sebastien Taurin ◽  
Sangeeta Bhorade ◽  
Nickolai O. Dulin

Aquaculture ◽  
2007 ◽  
Vol 267 (1-4) ◽  
pp. 188-198 ◽  
Author(s):  
Núria Montserrat ◽  
Pedro Gómez-Requeni ◽  
Giovanni Bellini ◽  
Encarnación Capilla ◽  
Jaume Pérez-Sánchez ◽  
...  

Metabolism ◽  
2002 ◽  
Vol 51 (6) ◽  
pp. 716-723 ◽  
Author(s):  
Asako Kageyama ◽  
Tsutomu Hirano ◽  
Haruaki Kageyama ◽  
Toshimasa Osaka ◽  
Yoshio Namba ◽  
...  

2016 ◽  
Vol 24 (4) ◽  
pp. 667-694 ◽  
Author(s):  
Stjepan Picek ◽  
Claude Carlet ◽  
Sylvain Guilley ◽  
Julian F. Miller ◽  
Domagoj Jakobovic

The role of Boolean functions is prominent in several areas including cryptography, sequences, and coding theory. Therefore, various methods for the construction of Boolean functions with desired properties are of direct interest. New motivations on the role of Boolean functions in cryptography with attendant new properties have emerged over the years. There are still many combinations of design criteria left unexplored and in this matter evolutionary computation can play a distinct role. This article concentrates on two scenarios for the use of Boolean functions in cryptography. The first uses Boolean functions as the source of the nonlinearity in filter and combiner generators. Although relatively well explored using evolutionary algorithms, it still presents an interesting goal in terms of the practical sizes of Boolean functions. The second scenario appeared rather recently where the objective is to find Boolean functions that have various orders of the correlation immunity and minimal Hamming weight. In both these scenarios we see that evolutionary algorithms are able to find high-quality solutions where genetic programming performs the best.


2010 ◽  
Vol 24 (S1) ◽  
Author(s):  
Biao Hu ◽  
Mehrnaz Gharaee‐Kermani ◽  
Zhe Wu ◽  
Sem H. Phan

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