Results 61 to 70 of about 552,020 (340)

Interpreting Electrical-Resistivity Tomography measurements using Neural Network [PDF]

arXiv, 2018
Electrical Resistivity Tomography (ERT) has been extensively used for imaging the subsurface resistivity distribution and structure. Over the years, many algorithms have been developed in order to solve the subsurface resistivity distribution from the ERT measurements. In this paper a new method for interpreting the ERT measurements is presented. Using
arxiv  

On resistive spiking of fungi [PDF]

arXiv, 2020
We study long-term electrical resistance dynamics in mycelium and fruit bodies of oyster fungi P. ostreatus. A nearly homogeneous sheet of mycelium on the surface of a growth substrate exhibits trains of resistance spikes. The average width of spikes is c.~23~min and the average amplitude is c.~1~kOhm.
arxiv  

Effectiveness of combining microcurrent with resistance training in trained males [PDF]

European Journal of Applied Physiology, 2019
Abstract Introduction Microcurrent has been used to promote tissue healing after injury or to hasten muscle remodeling post exercise post exercise. Purpose To compare the effects of resistance training in combination with either, microcurrent or
Naclerio, Fernando, Seijo, Marcos, Karsten, Bettina, Brooker, George, Carbone, Leandro, Thirkell, Jack, Larumbe-Zabala, Eneko   +6 more
openaire   +3 more sources

Classification of acute myeloid leukemia based on multi‐omics and prognosis prediction value

Molecular Oncology, EarlyView.
The Unsupervised AML Multi‐Omics Classification System (UAMOCS) integrates genomic, methylation, and transcriptomic data to categorize AML patients into three subtypes (UAMOCS1‐3). This classification reveals clinical relevance, highlighting immune and chromosomal characteristics, prognosis, and therapeutic vulnerabilities.
Yang Song, Zhe Wang, Guangji Zhang, Jiangxue Hou, Kaiqi Liu, Shuning Wei, Yan Li, Chunlin Zhou, Dong Lin, Min Wang, Hui Wei, Jianxiang Wang, Tao Cheng, Yingchang Mi   +13 more
wiley   +1 more source

Spatiotemporal and genomic analysis of carbapenem resistance elements in Enterobacterales from hospital inpatients and natural water ecosystems of an Irish city

Microbiology Spectrum
Carbapenemase-producing Enterobacterales (CPE) is a diverse group of often multidrug-resistant organisms. Surveillance and control of infections are complicated due to the inter-species spread of carbapenemase-encoding genes (CEGs) on mobile genetic ...
Mark Maguire, Carlos Serna, Natalia Montero Serra, Aneta Kovarova, Louise O’Connor, Niamh Cahill, Brigid Hooban, Niall DeLappe, Wendy Brennan, Genevieve Devane, Martin Cormican, Dearbháile Morris, Simone C. Coughlan, Georgios Miliotis, Bruno Gonzalez-Zorn, Liam P. Burke   +15 more
doaj   +1 more source

Reliable uncertainty estimate for antibiotic resistance classification with Stochastic Gradient Langevin Dynamics [PDF]

arXiv, 2018
Antibiotic resistance monitoring is of paramount importance in the face of this on-going global epidemic. Deep learning models trained with traditional optimization algorithms (e.g. Adam, SGD) provide poor posterior estimates when tested against out-of-distribution (OoD) antibiotic resistant/non-resistant genes.
arxiv  

Microvascular adaptations to resistance training are independent of load in resistance-trained young men [PDF]

American Journal of Physiology-Regulatory, Integrative and Comparative Physiology, 2018
Resistance training promotes microvasculature expansion; however, it remains unknown how different resistance training programs contribute to angiogenesis. Thus, we recruited experienced resistance-trained participants and determined the effect of 12 wk of either high-repetition/low-load or low-repetition/high-load resistance training performed to ...
Steven K. Baker, Stuart M. Phillips, Sara Y. Oikawa, Sean R McKellar, Tanya M. Holloway, Robert W. Morton   +5 more
openaire   +3 more sources

Enhancing patient engagement in cancer research: a focus on patient‐centric approaches to scientific discovery

Molecular Oncology, EarlyView.
Patient engagement involves actively including patients in healthcare decisions and research to ensure care and studies align with their needs. This approach improves outcomes, trust, and communication while fostering collaboration between patients and professionals.
Estela Cepeda, Marina Reguero, Vanesa Abón, Marta Puyol   +3 more
wiley   +1 more source

Machine learning techniques to identify antibiotic resistance in patients diagnosed with various skin and soft tissue infections [PDF]

arXiv, 2022
Skin and soft tissue infections (SSTIs) are among the most frequently observed diseases in ambulatory and hospital settings. Resistance of diverse bacterial pathogens to antibiotics is a significant cause of severe SSTIs, and treatment failure results in morbidity, mortality, and increased cost of hospitalization.
arxiv  

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source