metabolic alterations in a slow-paced model of pancreatic cancer-induced wasting

Clicks: 126
ID: 226231
2018
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #225 of 359 articles by views in journal of aoac international

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 359 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
Cancer cachexia is a devastating syndrome occurring in the majority of terminally ill cancer patients. Notably, skeletal muscle atrophy is a consistent feature affecting the quality of life and prognosis. To date, limited therapeutic options are available, and research in the field is hampered by the lack of satisfactory models to study the complexity of wasting in cachexia-inducing tumors, such as pancreatic cancer. Moreover, currently used in vivo models are characterized by an explosive cachexia with a lethal wasting within few days, while pancreatic cancer patients might experience alterations long before the onset of overt wasting. In this work, we established and characterized a slow-paced model of pancreatic cancer-induced muscle wasting that promotes efficient muscular wasting in vitro and in vivo. Treatment with conditioned media from pancreatic cancer cells led to the induction of atrophy in vitro, while tumor-bearing mice presented a clear reduction in muscle mass and functionality. Intriguingly, several metabolic alterations in tumor-bearing mice were identified, paving the way for therapeutic interventions with drugs targeting metabolism.
Reference Key
wyart2018oxidativemetabolic Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Elisabeth Wyart;Simone Reano;Myriam Y. Hsu;Dario Livio Longo;Mingchuan Li;Emilio Hirsch;Nicoletta Filigheddu;Alessandra Ghigo;Chiara Riganti;Paolo Ettore Porporato
Journal journal of aoac international
Year 2018
DOI
10.1155/2018/6419805
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.