Background: To investigate the association between serum branched chain amino acids (BCAAs), mammalian target of rapamycin (mTOR) levels and the risk of gestational diabetes mellitus (GDM) in pregnant women.
Methods: 1:1 matched case-control study was conducted including 66 GDM patients and 66 matched healthy pregnant women (± 3 years) in 2019, in China. Fasting bloods of pregnant women were collected in pregnancy at 24 ~ 28 weeks gestation.
Objective: Nowadays, the prevalence of cognitive impairment in women has gradually increased, especially in postmenopausal women. There were few studies on the mechanistic effects of iron exposure on neurotoxicity in postmenopausal women. The aim of this study is to investigate the effect of iron accumulation on cognitive ability in ovariectomized mice and its possible mechanism and to provide a scientific basis for the prevention of cognitive dysfunction in postmenopausal women.
View Article and Find Full Text PDFAims: Previous studies have found that a single liver enzyme may predict gestational diabetes mellitus (GDM), but the results have been inconsistent. This study aimed to explore the associations of liver enzymes in early pregnancy with risk of GDM, as well as to independently rank risk factors.
Methods: This prospective cohort study included 1295 women who underwent liver enzyme measurements during early pregnancy and completed GDM assessment in mid-pregnancy.
Vitamin D was well-known to be associated with gestational diabetes mellitus (GDM). Insulin-like growth factor-I (IGF-I) has been linked to vitamin D and GDM, respectively. We hypothesize that changes in IGF-I metabolism induced by 25(OH)D might contribute to GDM.
View Article and Find Full Text PDFOptical microscopy techniques are a popular choice for visualizing micro-agents. They generate images with relatively high spatiotemporal resolution but do not reveal encoded information for distinguishing micro-agents and surroundings. This study presents multicolor fluorescence microscopy for rendering color-coded identification of mobile micro-agents and dynamic surroundings by spectral unmixing.
View Article and Find Full Text PDFSparse representation of information provides a powerful means to perform feature extraction on high-dimensional data and is of broad interest for applications in signal processing, computer vision, object recognition and neurobiology. Sparse coding is also believed to be a key mechanism by which biological neural systems can efficiently process a large amount of complex sensory data while consuming very little power. Here, we report the experimental implementation of sparse coding algorithms in a bio-inspired approach using a 32 × 32 crossbar array of analog memristors.
View Article and Find Full Text PDFIEEE Trans Signal Process
October 2012
Iterative image reconstruction can dramatically improve the image quality in X-ray computed tomography (CT), but the computation involves iterative steps of 3D forward- and back-projection, which impedes routine clinical use. To accelerate forward-projection, we analyze the CT geometry to identify the intrinsic parallelism and data access sequence for a highly parallel hardware architecture. To improve the efficiency of this architecture, we propose a water-filling buffer to remove pipeline stalls, and an out-of-order sectored processing to reduce the off-chip memory access by up to three orders of magnitude.
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