Results 151 to 160 of about 614,762 (328)

Integrative systems‐level analysis reveals a contextual crosstalk between hypoxia and global metabolism in human breast tumors

Molecular Oncology, EarlyView.
Breast tumor samples scored for metabolic deregulation (M1 to M3) were given a hypoxia score (HS). The highest HS occurred in patients with strongest metabolic deregulation (M3), supporting tumor aggressiveness. HS correlated with the highest number of metabolic pathways in M1. This suggests hypoxia to be an early event in metabolic deregulation.
Raefa Abou Khouzam, Salem Chouaib, Mohammad Askandar Iqbal   +2 more
wiley   +1 more source

Towards standardized and reproducible research in skin microbiomes. [PDF]

Environ Microbiol, 2022
Ruuskanen MO, Vats D, Potbhare R, RaviKumar A, Munukka E, Ashma R, Lahti L.   +6 more
europepmc   +1 more source

Crosstalk between gut microbiota and tumor: tumors could cause gut dysbiosis and metabolic imbalance

Molecular Oncology, EarlyView.
In this research, we analyzed the relationship between gut microbiota and tumor. We discovered that both subcutaneous and metastatic tumors would alter the composition and metabolic function of gut microbiota. Meanwhile, fecal microbiota transplantation also indicated the anti‐tumor role of the gut microbiota, revealing the crosstalk between tumor and ...
Siyuan Zhang, Haimei Wen, Ying Chen, Jingya Ning, Di Hu, Yujiao Dong, Chenyu Yao, Bo Yuan, Shuanying Yang   +8 more
wiley   +1 more source

Running a research group in the next generation: combining sustainable and reproducible research with values-driven leadership. [PDF]

J Exp Bot, 2023
Monaghan J, Brady SM, Haswell ES, Roy S, Schwessinger B, McFarlane HE.   +5 more
europepmc   +1 more source

Obesity alters the fitness of peritumoral adipose tissue, exacerbating tumor invasiveness in renal cancer through the induction of ADAM12 and CYP1B1

Molecular Oncology, EarlyView.
Tumor microenvironment drives cancer formation and progression. We analyzed the role of human cancer‐associated adipocytes from patients with renal cell carcinoma (RCC) stratified as lean, overweight, or obese. RNA‐seq demonstrated that, among the most altered genes involved in the tumor–stroma crosstalk, are ADAM12 and CYP1B1, which were proven to be ...
Sepehr Torabinejad, Caterina Miro, Annarita Nappi, Francesco Del Giudice, Annunziata Gaetana Cicatiello, Serena Sagliocchi, Lucia Acampora, Federica Restolfer, Melania Murolo, Emery Di Cicco, Federico Capone, Ciro Imbimbo, Monica Dentice, Felice Crocetto   +13 more
wiley   +1 more source

The evolution of eProtocols that enable reproducible clinical research and care methods [PDF]

, 2012
Denitza Blagev, Eliotte L. Hirshberg, Katherine Sward, Bruce Thompson, Roy G. Brower, Jonathon D. Truwit, Duncan Hite, Jay S. Steingrub, James F. Orme, Terry P. Clemmer, Lindell K. Weaver, Frank Thomas, Colin K. Grissom, Dean Sorenson, Dean F. Sittig, C. Jane Wallace, Thomas D. East, Homer R. Warner, Alan H. Morris   +18 more
openalex   +1 more source

Research Data Management and Data Sharing for Reproducible Research-Results of a Community Survey of the German National Research Data Infrastructure Initiative Neuroscience. [PDF]

eNeuro, 2023
Klingner CM, Denker M, Grün S, Hanke M, Oeltze-Jafra S, Ohl FW, Radny J, Rotter S, Scherberger H, Stein A, Wachtler T, Witte OW, Ritter P.   +12 more
europepmc   +1 more source

Transparency and reproducibility in evolutionary research [PDF]

Journal of Evolutionary Biology, 2016
Ruth G. Shaw, Allen J. Moore, Michael G. Ritchie, Mohamed A. F. Noor   +3 more
openaire   +7 more sources

Improving reproducibility in spine research [PDF]

JOR SPINE, 2020
Christine L. Le Maitre, Chitra Lekha Dahia, Chitra Lekha Dahia   +2 more
openaire   +5 more sources

Addressing persistent challenges in digital image analysis of cancer tissue: resources developed from a hackathon

Molecular Oncology, EarlyView.
Large multidimensional digital images of cancer tissue are becoming prolific, but many challenges exist to automatically extract relevant information from them using computational tools. We describe publicly available resources that have been developed jointly by expert and non‐expert computational biologists working together during a virtual hackathon
Sandhya Prabhakaran, Clarence Yapp, Gregory J. Baker, Johanna Beyer, Young Hwan Chang, Allison L. Creason, Robert Krueger, Jeremy Muhlich, Nathan Heath Patterson, Kevin Sidak, Damir Sudar, Adam J. Taylor, Luke Ternes, Jakob Troidl, Xie Yubin, Artem Sokolov, Darren R. Tyson   +16 more
wiley   +1 more source