期刊文献+
共找到5篇文章
< 1 >
每页显示 20 50 100
Protective Effect of Silent Mating Type Information Regulation 2 Homolog 1 on TGF-β1 Pathway via mTOR in Diabetic Nephropathy
1
作者 Yanting Gu Dechun Jiang +1 位作者 Pengcheng Xu Yanchun Wang 《Journal of Biosciences and Medicines》 CAS 2023年第2期194-207,共14页
Objective: To demonstrate whether the expression of silent mating type information regulation 2 homolog 1 (SIRT1) affects the level of TGF-β1 and Smad3 in HEK293 cells through regulating mTOR. Methods: First, recombi... Objective: To demonstrate whether the expression of silent mating type information regulation 2 homolog 1 (SIRT1) affects the level of TGF-β1 and Smad3 in HEK293 cells through regulating mTOR. Methods: First, recombinant plasmids DNA (rSIRT1) and siRNA targeting SIRT1 were constructed which were transfected into Human Embryonic Kidney 293 cell (HEK293) cells, respectively. Then, the generation of intracellular ROS in cells was examined by flow cytometry using the oxidation-sensitive probe. Last, the expressions of TGF-β1, smad3, P53, mTOR, p-mTOR, LC3-I and LC3-II in cells were detected to observe the effect of SIRT1 on TGF-β1 Pathway by western blot analysis. Results: We demonstrated that overexpressing of SIRT1 may decrease TGF-β1 and Smad3 expression in HEK293 cells through regulating mTOR. In addition, the result is the opposite when SIRT1 was silent in HEK293 cells. Conclusions: SIRT1 is closely related to TGF-β1/Smad3 pathway that correlates with the regulation of mTOR and ROS generation and causes diabetic nephropathy. The available evidence implies that SIRT1 has great potential as a clinical target for the prevention and treatment of renal fibrosis in the development of DN. 展开更多
关键词 Silent Mating Type information Regulation 2 Homolog 1 MTOR Diabetic Nephropathy AUTOPHAGY Oxidative Stress
下载PDF
Targeting the core of neurodegeneration:FoxO,mTOR,and SIRT1 被引量:8
2
作者 Kenneth Maiese 《Neural Regeneration Research》 SCIE CAS CSCD 2021年第3期448-455,共8页
The global increase in lifespan noted not only in developed nations,but also in large developing countries parallels an observed increase in a significant number of noncommunicable diseases,most notable neurodegenerat... The global increase in lifespan noted not only in developed nations,but also in large developing countries parallels an observed increase in a significant number of noncommunicable diseases,most notable neurodegenerative disorders.Neurodegenerative disorders present a number of challenges for treatment options that do not resolve disease progression.Furthermore,it is believed by the year 2030,the services required to treat cognitive disorders in the United States alone will exceed$2 trillion annually.Mammalian forkhead transcription factors,silent mating type information regulation 2 homolog 1(Saccharomyces cerevisiae),the mechanistic target of rapamycin,and the pathways of autophagy and apoptosis offer exciting avenues to address these challenges by focusing upon core cellular mechanisms that may significantly impact nervous system disease.These pathways are intimately linked such as through cell signaling pathways involving protein kinase B and can foster,sometimes in conjunction with trophic factors,enhanced neuronal survival,reduction in toxic intracellular accumulations,and mitochondrial stability.Feedback mechanisms among these pathways also exist that can oversee reparative processes in the nervous system.However,mammalian forkhead transcription factors,silent mating type information regulation 2 homolog 1,mechanistic target of rapamycin,and autophagy can lead to cellular demise under some scenarios that may be dependent upon the precise cellular environment,warranting future studies to effectively translate these core pathways into successful clinical treatment strategies for neurodegenerative disorders. 展开更多
关键词 Alzheimer's disease apoptosis autophagy ERYTHROPOIETIN FORKHEAD FOXO mechanistic target of rapamycin silent mating type information regulation 2 homolog 1
下载PDF
Novel nervous and multi-system regenerative therapeutic strategies for diabetes mellitus with mTOR 被引量:13
3
作者 Kenneth Maiese 《Neural Regeneration Research》 SCIE CAS CSCD 2016年第3期372-385,共14页
Throughout the globe,diabetes mellitus(DM) is increasing in incidence with limited therapies presently available to prevent or resolve the significant complications of this disorder.DM impacts multiple organs and af... Throughout the globe,diabetes mellitus(DM) is increasing in incidence with limited therapies presently available to prevent or resolve the significant complications of this disorder.DM impacts multiple organs and affects all components of the central and peripheral nervous systems that can range from dementia to diabetic neuropathy.The mechanistic target of rapamycin(m TOR) is a promising agent for the development of novel regenerative strategies for the treatment of DM.m TOR and its related signaling pathways impact multiple metabolic parameters that include cellular metabolic homeostasis,insulin resistance,insulin secretion,stem cell proliferation and differentiation,pancreatic β-cell function,and programmed cell death with apoptosis and autophagy.m TOR is central element for the protein complexes m TOR Complex 1(m TORC1) and m TOR Complex 2(m TORC2) and is a critical component for a number of signaling pathways that involve phosphoinositide 3-kinase(PI 3-K),protein kinase B(Akt),AMP activated protein kinase(AMPK),silent mating type information regulation 2 homolog 1(Saccharomyces cerevisiae)(SIRT1),Wnt1 inducible signaling pathway protein 1(WISP1),and growth factors.As a result,m TOR represents an exciting target to offer new clinical avenues for the treatment of DM and the complications of this disease.Future studies directed to elucidate the delicate balance m TOR holds over cellular metabolism and the impact of its broad signaling pathways should foster the translation of these targets into effective clinical regimens for DM. 展开更多
关键词 Akt AMP activated protein kinase(AMPK) apoptosis Alzheimer’s disease autophagy β-cell cancer cardiovascular disease caspase CCN family diabetes mellitus epidermal growth factor erythropoietin fibroblast growth factor forkhead transcription factors Fox O FRAP1 hamartin(tuberous sclerosis 1)/tuberin(tuberous sclerosis 2)(TSC1/TSC2) insulin mechanistic target of rapamycin(mTOR) m TOR Complex 1(m T ORC1) m TOR Complex 2(m TORC2) nicotinamide nicotinamide adenine dinucleotide(NAD+) non-communicable diseases oxidative stress phosphoinositide 3-kinase(PI 3-K) programmed cell death silent mating type information regulation 2 homolog 1(Saccharomyces cerevisiae)(SIRT1) sirtuin stem cells wingless Wnt Wnt1 inducible signaling pathway protein 1(WISP1)
下载PDF
STRONG CODING THEOREM AND ASYMPTOTIC ERROR EXPONENT OF ARBITRARILY VARYING SOURCE
4
作者 符方伟 沈世镒 《Acta Mathematica Scientia》 SCIE CSCD 1996年第1期23-30,共8页
Csiszar's strong coding theorem for discrete memoryless scarce is generalized to arbitrarily varying source.We also determine the asymptotic error exponent for arbitrarily wrying source.
关键词 arbitrarily varying source coding theorem error exponent information quantity types.
下载PDF
Type-Augmented Link Prediction Based on Bayesian Formula
5
作者 Ye Wang Enze Luo +1 位作者 Lijie Li Wenjian Tao 《国际计算机前沿大会会议论文集》 EI 2023年第2期304-317,共14页
Knowledge graphs(KGs)play a pivotal role in various real-world applications,but they are frequently plagued by incomplete information,which manifests in the form of missing entities.Link prediction,which aims to infer... Knowledge graphs(KGs)play a pivotal role in various real-world applications,but they are frequently plagued by incomplete information,which manifests in the form of missing entities.Link prediction,which aims to infer missing entities given existing facts,has been mostly addressed by maximizing the likelihood of observed triplets at the instance level.However,they ignore the semantic information most KGs contain and the prior knowledge implied by the semantic information.To address this limitation,we propose a Type-Augmented Link Prediction(TALP)approach,which builds a hierarchical feature model,computes type feature weights,trains them to be specific to different relations,encodes weights into prior probabilities and convolutional encodes instance-level information into likelihood probabilities;finally,combining them via Bayes rule to compute the posterior probabilities of entity prediction.Our proposed TALP approach achieves significantly better performance than existing methods on link prediction benchmark datasets. 展开更多
关键词 Knowledge Graph Link Prediction Bayes Formula Type information
原文传递
上一页 1 下一页 到第
使用帮助 返回顶部