35 research outputs found
Table_3_A nutritional assessment tool, GNRI, predicts sarcopenia and its components in type 2 diabetes mellitus: A Japanese cross-sectional study.pdf
BackgroundThere are few reports evaluating the relationship between undernutrition and the risk of sarcopenia in type 2 diabetes mellitus (T2DM) patients.ObjectiveWe investigated whether undernutritional status assessed by the geriatric nutritional risk index (GNRI) and controlling nutritional status (CONUT) were associated with the diagnosis of sarcopenia.MethodsThis was a cross-sectional study of Japanese individuals with T2DM. Univariate or multivariate logistic regression analysis was performed to assess the association of albumin, GNRI, and CONUT with the diagnosis of sarcopenia. The optimal cut-off values were determined by the receiver operating characteristic (ROC) curve to diagnose sarcopenia.ResultsIn 479 individuals with T2DM, the median age was 71 years [IQR 62, 77], including 264 (55.1%) men. The median duration of diabetes was 17 [11, 23] years. The prevalence of sarcopenia was 41 (8.6%) in all, 21/264 (8.0%) in men, and 20/215 (9.3%) in women. AUCs were ordered from largest to smallest as follows: GNRI > albumin > CONUT. The cut-off values of GNRI were associated with a diagnosis of sarcopenia in multiple logistic regression analysis (odds ratio 9.91, 95% confidential interval 5.72–17.2), P ConclusionsResults showed that GNRI shows a superior diagnostic power in the diagnosis of sarcopenia. Additionally, its optimal cut-off points were useful overall or in the subclasses. Future large and prospective studies will be required to confirm the utility of the GNRI cut-off for undernutrition individuals at risk for sarcopenia.</p
Table_1_A nutritional assessment tool, GNRI, predicts sarcopenia and its components in type 2 diabetes mellitus: A Japanese cross-sectional study.pdf
BackgroundThere are few reports evaluating the relationship between undernutrition and the risk of sarcopenia in type 2 diabetes mellitus (T2DM) patients.ObjectiveWe investigated whether undernutritional status assessed by the geriatric nutritional risk index (GNRI) and controlling nutritional status (CONUT) were associated with the diagnosis of sarcopenia.MethodsThis was a cross-sectional study of Japanese individuals with T2DM. Univariate or multivariate logistic regression analysis was performed to assess the association of albumin, GNRI, and CONUT with the diagnosis of sarcopenia. The optimal cut-off values were determined by the receiver operating characteristic (ROC) curve to diagnose sarcopenia.ResultsIn 479 individuals with T2DM, the median age was 71 years [IQR 62, 77], including 264 (55.1%) men. The median duration of diabetes was 17 [11, 23] years. The prevalence of sarcopenia was 41 (8.6%) in all, 21/264 (8.0%) in men, and 20/215 (9.3%) in women. AUCs were ordered from largest to smallest as follows: GNRI > albumin > CONUT. The cut-off values of GNRI were associated with a diagnosis of sarcopenia in multiple logistic regression analysis (odds ratio 9.91, 95% confidential interval 5.72–17.2), P ConclusionsResults showed that GNRI shows a superior diagnostic power in the diagnosis of sarcopenia. Additionally, its optimal cut-off points were useful overall or in the subclasses. Future large and prospective studies will be required to confirm the utility of the GNRI cut-off for undernutrition individuals at risk for sarcopenia.</p
Prediction of miRNA-378 targets <i>in silico</i>.
<p>The miRNA-378 targets were predicted using Targetscan (<a href="http://www.targetscan.org" target="_blank">www.targetscan.org</a>) and PicTar (<a href="http://www.pictar.org" target="_blank">www.pictar.org</a>).</p
Image_1_A nutritional assessment tool, GNRI, predicts sarcopenia and its components in type 2 diabetes mellitus: A Japanese cross-sectional study.tif
BackgroundThere are few reports evaluating the relationship between undernutrition and the risk of sarcopenia in type 2 diabetes mellitus (T2DM) patients.ObjectiveWe investigated whether undernutritional status assessed by the geriatric nutritional risk index (GNRI) and controlling nutritional status (CONUT) were associated with the diagnosis of sarcopenia.MethodsThis was a cross-sectional study of Japanese individuals with T2DM. Univariate or multivariate logistic regression analysis was performed to assess the association of albumin, GNRI, and CONUT with the diagnosis of sarcopenia. The optimal cut-off values were determined by the receiver operating characteristic (ROC) curve to diagnose sarcopenia.ResultsIn 479 individuals with T2DM, the median age was 71 years [IQR 62, 77], including 264 (55.1%) men. The median duration of diabetes was 17 [11, 23] years. The prevalence of sarcopenia was 41 (8.6%) in all, 21/264 (8.0%) in men, and 20/215 (9.3%) in women. AUCs were ordered from largest to smallest as follows: GNRI > albumin > CONUT. The cut-off values of GNRI were associated with a diagnosis of sarcopenia in multiple logistic regression analysis (odds ratio 9.91, 95% confidential interval 5.72–17.2), P ConclusionsResults showed that GNRI shows a superior diagnostic power in the diagnosis of sarcopenia. Additionally, its optimal cut-off points were useful overall or in the subclasses. Future large and prospective studies will be required to confirm the utility of the GNRI cut-off for undernutrition individuals at risk for sarcopenia.</p
Levels of miRNA-378, adiponectin, PPARγ<sub>2</sub>, PGC1α, ESRRG, PGC1β, ACSL1 and AGPAT6 during differentiation of 3T3-L1 adipocyte cells.
<p>The mouse 3T3-L1 cell line was cultured in DMEM/10% FBS and dispensed into 12-well plates (day 2) before induction of adipose differentiation. Once the cells had grown confluently, they were stimulated with insulin (10 µg/mL) dexamethasone (1 nM), and IBMX (500 µM) for 2 days (days 0–2), and the medium was changed every 2 days. At days 0, 2, and 6, RNA was extracted and levels of miRNA-378 and mRNAs of adiponectin, ACSL1, GPAT6, PPARγ2, PGC1α, PGC1β, and ESRRG were evaluated by qPCR. Expression levels normalized to those of β-actin were log-transformed. Individual values are shown with mean ± SE (n = 4).</p
Table_2_A nutritional assessment tool, GNRI, predicts sarcopenia and its components in type 2 diabetes mellitus: A Japanese cross-sectional study.pdf
BackgroundThere are few reports evaluating the relationship between undernutrition and the risk of sarcopenia in type 2 diabetes mellitus (T2DM) patients.ObjectiveWe investigated whether undernutritional status assessed by the geriatric nutritional risk index (GNRI) and controlling nutritional status (CONUT) were associated with the diagnosis of sarcopenia.MethodsThis was a cross-sectional study of Japanese individuals with T2DM. Univariate or multivariate logistic regression analysis was performed to assess the association of albumin, GNRI, and CONUT with the diagnosis of sarcopenia. The optimal cut-off values were determined by the receiver operating characteristic (ROC) curve to diagnose sarcopenia.ResultsIn 479 individuals with T2DM, the median age was 71 years [IQR 62, 77], including 264 (55.1%) men. The median duration of diabetes was 17 [11, 23] years. The prevalence of sarcopenia was 41 (8.6%) in all, 21/264 (8.0%) in men, and 20/215 (9.3%) in women. AUCs were ordered from largest to smallest as follows: GNRI > albumin > CONUT. The cut-off values of GNRI were associated with a diagnosis of sarcopenia in multiple logistic regression analysis (odds ratio 9.91, 95% confidential interval 5.72–17.2), P ConclusionsResults showed that GNRI shows a superior diagnostic power in the diagnosis of sarcopenia. Additionally, its optimal cut-off points were useful overall or in the subclasses. Future large and prospective studies will be required to confirm the utility of the GNRI cut-off for undernutrition individuals at risk for sarcopenia.</p
Additional file 5 of Clinical effects of a selective urate reabsorption inhibitor dotinurad in patients with hyperuricemia and treated hypertension: a multicenter, prospective, exploratory study (DIANA)
Additional file 5: Table S4. Estimated changes in blood pressures and laboratory biomarkers over 24Â weeks
Additional file 6 of Clinical effects of a selective urate reabsorption inhibitor dotinurad in patients with hyperuricemia and treated hypertension: a multicenter, prospective, exploratory study (DIANA)
Additional file 6: Table S5. Associations between changes in SUA and parameters of interest at week 24
Additional file 3 of Clinical effects of a selective urate reabsorption inhibitor dotinurad in patients with hyperuricemia and treated hypertension: a multicenter, prospective, exploratory study (DIANA)
Additional file 3: Table S2. SUA raw data at baseline and at weeks 4, 8, 12, and 24
Correlation between level of adiponectin vs levels of PPARγ<sub>2</sub>, PGC1α, ESRRG, ACSL1, AGPAT6 and TNFα in the adipose tissue of C57BL/6 and ob/ob mice.
<p>From normal C57BL/6 (♂, n = 10) or diabetic ob/ob (♂, n = 10) mice, epididymal adipose tissues were excised and used for gene expression analyses. Expression levels normalized to those of β-actin were log-transformed. Linear regression analysis was made on a combined group of C57BL/6 (○) and ob/ob (•) mice and, and r and p values are shown.</p