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http://dx.doi.org/10.1042/bst0060487 | DOI Listing |
Mol Divers
January 2025
Data Science, Amity Institute of Integrative Sciences and Health, Amity University Haryana, Gurugram, India.
The ATP-binding cassette transporter superfamily plays a pivotal role in cellular detoxification and drug efflux. ATP-binding cassette subfamily G member 2 (ABCG2) referred to as the Breast cancer resistance protein has emerged as a key member involved in multidrug resistance displayed by cancer cells. Understanding the molecular basis of substrate and inhibitor recognition, and binding within the transmembrane domain of ABCG2 is crucial for the development of effective therapeutic strategies.
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December 2024
The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States.
Significant progress in determining the molecular origins and resistance mechanisms of mantle cell lymphoma (MCL) has improved our understanding of the disease's clinical diversity. These factors greatly impact prognosis in MCL patients. Given the dynamic alterations in MCL clones and disease evolution, it is crucial to recognize high-risk prognostic factors at diagnosis and relapse.
View Article and Find Full Text PDFBackground: Emerging research, underscored by the UK National Institute of Health and Care Excellence and the US National Institutes of Health, suggests that age-related hearing loss (ARHL) is linked to the development of dementias such as Alzheimer's disease (AD). In this study, we aim to investigate the neural correlates of ARHL and cognitive impairments based on the changes in white matter (WM) microstructures in a population of non-demented adults.
Method: 129 participants (94 female) aged between 20-79 years old (Mean = 51.
Alzheimers Dement
December 2024
Department of Psychiatry, University of Illinois at Chicago, Chicago, IL, USA.
Background: The APOE4 genotype appears to confer differential risk of Alzheimer's disease for women compared to men. As APOE4 effects in midlife women can be subtle (e.g.
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December 2024
Cognitive Neuroscience Center, University of San Andrés, Victoria, Buenos Aires, Argentina.
Background: Digital health research on Alzheimer's disease (AD) points to automated speech and language analysis (ASLA) as a globally scalable approach for diagnosis and monitoring. However, most studies target uninterpretable features in Anglophone samples, casting doubts on the approach's clinical utility and cross-linguistic validity. The present study was designed to tackle both issues.
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