Metabolic enzymes have been shown to function as transcriptional regulators. p53, a tumor-suppressive transcription factor, was recently found to regulate energy metabolism. These combined facts raise the possibility that metabolic enzymes may directly regulate p53 function. Here, we discover that nucleocytoplasmic malate dehydrogenase-1 (MDH1) physically associates with p53. Upon glucose deprivation, MDH1 stabilizes and transactivates p53 by binding to p53-responsive elements in the promoter of downstream genes. Knockdown of MDH1 significantly reduces binding of acetylated-p53 and transcription-active histone codes to the promoter upon glucose depletion. MDH1 regulates p53-dependent cell-cycle arrest and apoptosis in response to glucose deprivation, suggesting that MDH1 functions as a transcriptional regulator for a p53-dependent metabolic checkpoint. Our findings provide insight into how metabolism is directly linked to gene expression for controlling cellular events in response to metabolic stress. Two fundamental processes-energy metabolism and gene regulation-in living organisms are considered indirectly linked to each other due to their different functional locations. Recent findings that some metabolic enzymes function as transcriptional regulators have implicated direct coupling of energy metabolism with gene regulation. [1][2][3] For instance, glyceraldehyde-3-phosphate dehydrogenase (GAPDH) serves as a co-activator to regulate the expression of histone H2B. 4 Nuclear GAPDH also activates p300/CBP and induces apoptotic genes. 5 In addition, Arg5/6, a yeast metabolic enzyme involved in arginine biosynthesis, regulates the transcription of nuclear and mitochondrial target genes, 6 and plant hexokinase 1 forms a nuclear glucose signaling complex core that directly modulates specific target gene transcription. 7 Glucose is the central molecule for energy metabolism in glycolysis and in the tricarboxylic acid (TCA) cycle and mitochondrial respiration. Interestingly, cancer cells have long been known to have altered glucose metabolism by preferentially acquiring energy from glycolysis rather than from mitochondrial respiration. 8 This metabolic shift to aerobic glycolysis in cancer cells is commonly referred to as the Warburg effect. 9,10 Recently, pyruvate kinase M2 isoform was found to be important for aerobic glycolysis and cancer metabolism. 11 But the molecular mechanism underlying the Warburg effect is still unclear. Because tumor formation is basically caused by dysregulation of gene expression by a genetic or epigenetic alteration, the Warburg effect may be caused by dysregulated transcription.p53 is the best-known transcription factor that controls cell-cycle arrest and cell death in response to a wide range of stresses. 12,13 However, the tumor-suppressive function of p53 has been mainly studied under conditions of DNA damage with g-irradiation, UV and free radicals. Intriguingly, recent findings that p53 regulates glucose metabolism have invoked vigorous interest in the direct linkage between metab...

3 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1037-1044.

Synthetic T1- and T2-weighted images were diagnostically acceptable, but synthetic FLAIR images were not. Lesion conspicuity and gray/white matter differentiation were comparable to conventional MRI.

Objectives The properties of brain tissue undergo dynamic changes during maturation. T1 relaxation time (T1), T2 relaxation time (T2), and proton density (PD) are now simultaneously quantifiable within a clinically acceptable time, using a synthetic magnetic resonance imaging (MRI) sequence. This study aimed to provide age-specific reference values for T1, T2, and PD in children, using synthetic MRI. Materials and Methods We included 89 children (median age, 18 months; range, 34 weeks of gestational age to 17 years) who underwent quantitative MRI, using a multidynamic, multiecho sequence on 3 T MRI, between December 2015 and November 2016, and had no abnormal MRI/neurologic assessment findings. T1, T2, and PD were simultaneously measured in each of the 22 defined white matter and gray matter regions of interest. The measured values were plotted against age, and a curve fitting model that best explained the age dependence of tissue values was identified. Age-specific regional tissue values were calculated using a fit equation. Results The tissue values of all brain regions, except cortical PD, decreased with increasing age, and the robust negative association was best explained by modified biexponential model of the form Tissue values = T1 × exp (−C1 × age) + T2 × exp (−C2 × age). The quality of fit to the modified biexponential model was high in white matter and deep gray matter (white matter, R 2 = 97%–99% [T1], 88%–95% [T2], 88%–97% [PD]; deep gray matter, R 2 = 96%–97% [T1], 96% [T2], 49%–88% [PD]; cortex, 70%–83% [T1], 87%–90% [T2], 5%–27% [PD]). The white matter and deep gray matter changed the most dynamically within the first year of life. Conclusions Our study provides age-specific regional reference values, from the neonate to adolescent, of T1, T2, and PD, which could be objective tools for assessment of normal/abnormal brain development using synthetic MRI.

ObjectiveTo assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA).Materials and MethodsFrom March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups.ResultsMultivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100).ConclusionAbnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.