Brain tissue is highly vulnerable to ischemia/hypoxia, and real-time monitoring of its viability is important. By fiber-based measurements for rat brain, we previously observed a unique triphasic reflectance change (TRC) after a certain period of time after hypoxia. After TRC, rats could not be rescued, suggesting that TRC can be used as an indicator of loss of brain tissue viability. In this study, we investigated this diffuse-reflectance change due to hypoxia in three parts. First, we developed and validated a theoretical method to quantify changes in the absorption and reduced scattering coefficients involved in TRC. Second, we performed charge-coupled-device-based reflectance imaging of the rat brain during hypoxia followed by reoxygenation to examine spatiotemporal characteristics of the reflectance and its correlation with reversibility of brain tissue damage. Third, we made simultaneous imaging and fiber-based measurement of the reflectance for the rat to compare signals obtained by these two modalities. We observed a nontriphasic reflectance change by the imaging, and it was associated with brain tissue viability. We found that TRC measured by the fibers preceded the reflectance-signal change captured by the imaging. This time difference is attributable to the different observation depths in the brain with these two methods.
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http://dx.doi.org/10.1117/1.JBO.18.1.015003 | DOI Listing |
Clin Epigenetics
January 2025
Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
Alcohol consumption is an important risk factor for multiple diseases. It is typically assessed via self-report, which is open to measurement error through recall bias. Instead, molecular data such as blood-based DNA methylation (DNAm) could be used to derive a more objective measure of alcohol consumption by incorporating information from cytosine-phosphate-guanine (CpG) sites known to be linked to the trait.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Electrical Electronical Engineering, Yaşar University, Bornova, İzmir, Turkey.
We aimed to build a robust classifier for the MGMT methylation status of glioblastoma in multiparametric MRI. We focused on multi-habitat deep image descriptors as our basic focus. A subset of the BRATS 2021 MGMT methylation dataset containing both MGMT class labels and segmentation masks was used.
View Article and Find Full Text PDFEur J Pharmacol
January 2025
College of Life Science, Yangtze University, Jingzhou 434025, China. Electronic address:
Cellular senescence precipitates a decline in physiological activities and metabolic functions, often accompanied by heightened inflammatory responses, diminished immune function, and impaired tissue and organ performance. Despite extensive research, the mechanisms underpinning cellular senescence remain incompletely elucidated. Emerging evidence implicates circadian rhythm and hypoxia as pivotal factors in cellular senescence.
View Article and Find Full Text PDFJ Biol Chem
January 2025
Key Laboratory of Medicine, Ministry of Education, School of Laboratory Medicine and Life Sciences, Wenzhou Medical University; Wenzhou, Zhejiang 325035, China; Oujiang Laboratory (Zhejiang Lab for Regenerative Medicine, Vision and Brain Health), Wenzhou, Zhejiang 325053, China. Electronic address:
Cigarette smoking (CS) is one of the greatest health concerns, which can cause lung cancer. 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), a tobacco-specific nitrosamine, and has been well-documented for its carcinogenic activity in both epidemiological and laboratory studies. PH domain leucine-rich repeat protein phosphatase 1 (PHLPP1) and phosphatase and tensin homolog (PTEN) are two well-known phosphatase tumor suppressors that have been reported to be downregulated in human lung cancer tissues.
View Article and Find Full Text PDFNeuroimage
January 2025
Department of Electrical and Electronic Engineering, Yonsei University, Seoul, Republic of Korea. Electronic address:
Magnetic resonance electrical properties tomography can extract the electrical properties of in-vivo tissue. To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact.
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