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The Effect Of Liver X Receptor Α Deficiency In Skeletal Muscle On Lipid Content In Mice, Yishu Ding
The Effect Of Liver X Receptor Α Deficiency In Skeletal Muscle On Lipid Content In Mice, Yishu Ding
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Liver X receptors (LXRs) are important regulators of cholesterol, fatty acid, and glucose homeostasis. Many researchs focus on the liver, but tissue-specific roles of LXRs in other tissues remain elusive. Based on in vitro studies on cultured cells, the roles of LXRs in skeletal muscle have been proposed. Nevertheless, the in vivo roles of LXRs in skeletal muscle remain lacking. Skeletal muscle is an important insulin targeting tissue, which plays a key role in regulating insulin sensitivity. Abnormal lipid metabolism and homeostasis have been demonstrated to play a crucial role in the development of insulin resistance in skeletal muscle. To …
A Pilot Study To Determine The Effectiveness Of Bioelectrical Impedance Analysis As A Clinical Assessment Tool Of Nutrition Status In Glioblastoma Multiforme Patients (The Beam Study [Bia Effectiveness As Assessment Tool For Gbm Patients]), Rebecca V. Barnhill
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Glioblastoma multiforme (GBM) is a rare brain tumor, yet accounts for 80% of malignant brain tumors and has a five-year survival rate of < 5%. Few studies have evaluated nutrition recommendations and outcomes of this disease, including caloric needs. The purpose of this study was to find the best predictive equation for resting energy expenditure (REE) for GBM patients and evaluate bioelectrical impedance analysis (BIA) as a clinical tool for estimating REE and fat free mass (FFM) of GBM patients. REE was measured with indirect calorimetry. FFM was measured with DXA and estimated with BIA. Published predictive equations for REE were calculated to compare to measured REE. Six equations used variables easily attained in a clinical setting and three used FFM. Correlation analysis was used to evaluate the strength of the relationships between measured and predicted REE. Agreement between methods on the group level was assessed by comparing the group means of measured and predicted REE with paired t-tests. The Bland-Altman approach was used to find agreement between the methods on the individual level. Analysis included fifteen newly diagnosed GBM patients (7 male and 8 female; mean age 57.1±11.6 years) to evaluate equations using clinical variables and a subsample of eight to evaluate predictive equations using FFM. All the predictive equations overestimated measured REE. The Mifflin-St Jeor was the only equation using clinical variables which was not significantly different from measured REE (p=0.054) and had the lowest bias (73 kcal/day) and narrowest limits of agreement. Likewise, Cunningham and Wang equations using FFM from DXA were not significantly different from measured (p=0.261 and p=0.072, respectively). BIA overestimated FFM compared to DXA, 54.1 kg and 49.2 kg, respectively (p<0.001). More visits with both DXA and BIA measurements available are needed before predictive equations with clinical variables and predictive equations with FFM can be compared. Due to the ease of obtaining clinical variables and the low bias and narrow limits of agreement found for the Mifflin equation, at this time it appears to be the best predictive equation for individuals with GBM.