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Propionate, 3-hydroxypropionate (3HP), methylcitrate, related compounds, and ammonium accumulate in body fluids of patients with disorders of propionyl-CoA metabolism, such as propionic acidemia. Although liver transplantation alleviates hyperammonemia, high concentrations of propionate, 3HP, and methylcitrate persist in body fluids. We hypothesized that conserved metabolic perturbations occurring in transplanted patients result from the simultaneous presence of propionate and 3HP in body fluids. We investigated the inter-relations of propionate and 3HP metabolism in perfused livers from normal rats using metabolomic and stable isotopic technologies. In the presence of propionate, 3HP, or both, we observed the following metabolic perturbations. First, the citric acid cycle (CAC) is overloaded but does not provide sufficient reducing equivalents to the respiratory chain to maintain the homeostasis of adenine nucleotides. Second, there is major CoA trapping in the propionyl-CoA pathway and a tripling of liver total CoA within 1 h. Third, liver proteolysis is stimulated. Fourth, propionate inhibits the conversion of 3HP to acetyl-CoA and its oxidation in the CAC. Fifth, some propionate and some 3HP are converted to nephrotoxic maleate by different processes. Our data have implications for the clinical management of propionic acidemia. They also emphasize the perturbations of the liver intermediary metabolism induced by supraphysiological, i.e., millimolar, concentrations of labeled propionate used to trace the intermediary metabolism, in particular, inhibition of CAC flux and major decreases in the [ATP]/[ADP] and [ATP]/[AMP] ratios.

Background and purposePrevious studies have reported about inflammation processes (IPs) that play important roles in aneurysm formation and rupture, which could be driven by blood flow. IPs can be identified using aneurysmal wall enhancement (AWE) on high-resolution black-blood MRI (BB-MRI) and blood flow haemodynamics can be demonstrated by four-dimensional-flow MRI (4D-flow MRI). Thus, this study investigated the associations between AWE and haemodynamics in unruptured intracranial aneurysms (IA) by combining 4D-flow MRI and high-resolution BB-MRI.Materials and methodsBetween April 2014 and October 2017, 48 patients with 49 unruptured IA who underwent both 4D-flow MRI and high-resolution BB-MRI were retrospectively included in this study. The haemodynamic parameters demonstrated using 4D-flow MRI were compared between different AWE patterns using the Kruskal-Wallis test and ordinal regression.ResultsThe results of Kruskal-Wallis test showed that the average wall shear stress in the IA (WSSavg-IA), maximum through-plane velocity in the adjacent parent artery, inflow jet patterns and the average vorticity in IA (vorticityavg-IA) were significantly associated with the AWE patterns. Ordinal regression analysis identified WSSavg-IA (p=0.002) and vorticityavg-IA (p=0.033) as independent predictors of AWE patterns.ConclusionA low WSS and low average vorticity were independently associated with a high AWE grade for IAs larger than 4 mm. Therefore, WSS and average vorticity could predict AWE and circumferential AWE.

Background: Previous studies have hypothesized that intracranial aneurysm (IA) morphology interacts with hemodynamic conditions. Magnetic resonance imaging (MRI) provides a single image modality solution for both morphological and hemodynamic measurements for IA. This study aimed to explore the interaction between the morphology and hemodynamics of IA using black-blood MRI (BB-MRI) and 4D flow MRI.Methods: A total of 97 patients with unruptured IA were recruited for this study. The IA size, size ratio (SR), and minimum wall thickness (mWT) were measured using BB-MRI. Velocity, blood flow, pulsatility index (PI), and wall shear stress (WSS) were measured with 4D flow MRI. The relationship between hemodynamic parameters and morphological indices was investigated by linear regression analysis and unpaired two-sample t-test. To determine the independent interaction, multiple linear regression analysis was further performed.Results: The findings showed that mWT was negatively correlated with IA size (r=−0.665, P<0.001).Maximum blood flow in IA (Flow IA ) was positively correlated with IA size (r=0.458, P<0.001). The average WSS (WSS avg ) was negatively correlated with IA size (r=−0.650, P<0.001). The relationships remained the same after the multivariate analysis was adjusted for hemodynamic, morphologic, and demographic confounding factors. The WSS avg was positively correlated with mWT (r=0.528, P<0.001). In the unpaired two-sample t-test, mWT, WSS avg , and Flow IA were statistically significantly associated with the size and SR of IAs. Conclusions:There is potential for BB-MRI and 4D flow MRI to provide morphological and hemodynamic information regarding IA. Blood flow, WSS, and mWT may serve as non-invasive biomarkers for IA assessments, and may contribute to a more comprehensive understanding of the mechanism of IA.

Background: Inflammation and hemodynamics are interrelated risk factors for intracranial aneurysm rupture. This study aimed to identify the relationship between these risk factors from an individual-patient perspective using biomarkers of aneurysm wall enhancement (AWE) derived from high-resolution magnetic resonance imaging (HR-MRI) and hemodynamic parameters by four-dimensional flow MRI (4D-flow MRI).Methods: A total of 29 patients with 29 unruptured intracranial aneurysms larger than 4 mm were included in this prospective cross-sectional study. A total of 24 aneurysms had AWE and 5 did not have AWE. A three-dimensional (3D) vessel model of each individual aneurysm was generated with 3D time-of-flight magnetic resonance angiography (3D TOF-MRA). Quantification of AWE was sampled with HR-MRI.Time-averaged wall shear stress (WSS) and oscillatory shear index (OSI) were calculated from the 4D-flow MRI. The correlation between spatial distribution of AWE and hemodynamic parameters measured at pixellevel was evaluated for each aneurysm.Results: In aneurysms with AWE, the spatial distribution of WSS was negatively correlated with AWE in 100% (24/24) of aneurysms, though 2 had an absolute value of the correlation coefficient <0.1. The OSI was positively correlated with AWE in 91.7% (22/24) of aneurysms; the other 2 aneurysms showed a negative correlation with AWE. In aneurysms with no AWE, there was no correlation between WSS (100%, 5/5), OSI (80%, 4/5), and wall inflammation. Conclusions:The spatial distribution of WSS was negatively correlated with AWE in aneurysms with AWE, and OSI was positively correlated with AWE in most aneurysms with AWE. While aneurysms that did not contain AWE showed no correlation between hemodynamics and wall inflammation.