XIANGYU QUAN¹, XUETING MA¹, GUODONG LI², XUEQI FU¹, JIANGTAO LI¹, LINLIN ZENG^1,*

BIOCELL, Vol.47, No.10, pp. 2163-2176, 2023, DOI:10.32604/biocell.2023.031226 - 08 November 2023

Abstract Exosomes are extracellular vesicles with a 30–150 nm diameter originating from endosomes. In recent years, scientists have regarded exosomes as an ideal small molecule carrier for the targeted treatment of Alzheimer’s disease (AD) across the blood-brain barrier due to their nanoscale size and low immunogenicity. A large amount of evidence shows that exosomes are rich in biomarkers, and it has been found that the changes in biomarker content in blood, cerebrospinal fluid, and urine are often associated with the onset of AD patients. In this paper, some recent advances in the use of exosomes in More > Graphic Abstract

Raisa Nazir Ahmed Kazi^1,*, Manjur Kolhar², Faiza Rizwan²

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1237-1250, 2021, DOI:10.32604/cmc.2020.012707 - 26 November 2020

Abstract The widespread use of smartwatches has increased their specific and complementary activities in the health sector for patient’s prognosis. In this study, we propose a framework referred to as smart forecasting CardioWatch (SCW) to measure the heart-rate variation (HRV) for patients with myocardial infarction (MI) who live alone or are outside their homes. In this study, HRV is used as a vital alarming sign for patients with MI. The performance of the proposed framework is measured using machine learning and deep learning techniques, namely, support vector machine, logistic regression, and decision-tree classification techniques. The results More >