Results 131 to 140 of about 764,924 (322)

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

open access: yesMolecular 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   +2 more
wiley   +1 more source

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

open access: yesMolecular 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   +8 more
wiley   +1 more source

Hydrodynamic equations for microscopic phase densities

open access: yesOpen Physics, 2011
Gerasimenko Viktor   +2 more
doaj   +1 more source

Integrative analysis of circulating tumor cells (CTCs) and exosomes from small‐cell lung cancer (SCLC) patients: a comprehensive approach

open access: yesMolecular Oncology, EarlyView.
This study simultaneously investigated circulating tumor cells (CTCs) and exosomes from small‐cell lung cancer (SCLC) patients. The elevated expression of JUNB and CXCR4 in CTCs was a poor prognostic factor for SCLC patients, whereas exosomal overexpression of these biomarkers revealed a high discrimination ability of patients from healthy individuals,
Dimitrios Papakonstantinou   +13 more
wiley   +1 more source

A Data-Driven State Estimation Based on Sample Migration for Low-Observable Distribution Networks

open access: yesAlgorithms
This paper proposes a data-driven state estimation based on sample migration for low-observable distribution networks, addressing the challenge of traditional state estimators being unsuitable for distribution networks with low observability.
Hao Jiao   +5 more
doaj   +1 more source

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