Aims/hypothesis Mitochondrial dysfunction and increased intramyocellular lipid (IMCL) content have both been implicated in the development of insulin resistance and type 2 diabetes mellitus, but the relative contributions of these two factors in the aetiology of diabetes are unknown. As obesity is an independent determinant of IMCL content, we examined mitochondrial function and IMCL content in overweight type 2 diabetes patients and BMI-matched normoglycaemic controls. Methods In 12 overweight type 2 diabetes patients and nine controls with similar BMI (29.4±1 and 29.3±0.9 kg/m 2 respectively) in vivo mitochondrial function was determined by measuring phosphocreatine recovery halftime (PCr half-time) immediately after exercise, using phosphorus-31 magnetic resonance spectroscopy. IMCL content was determined by proton magnetic resonance spectroscopic imaging and insulin sensitivity was measured with a hyperinsulinaemic-euglycaemic clamp. Results The PCr half-time was 45% longer in diabetic patients compared with controls (27.3±3.5 vs 18.7±0.9 s, p<0.05), whereas IMCL content was similar (1.37±0.30 vs 1.25±0.22% of the water resonance), and insulin sensitivity was reduced in type 2 diabetes patients (26.0±2.2 vs 18.9± 2.3 μmol min −1 kg −1 , p<0.05 [all mean±SEM]). PCr halftime correlated positively with fasting plasma glucose (r 2 =0.42, p < 0.01) and HbA 1c (r 2 = 0.48, p <0.05) in diabetic patients. Conclusions/interpretation The finding that in vivo mitochondrial function is decreased in type 2 diabetes patients compared with controls whereas IMCL content is similar suggests that low mitochondrial function is more strongly associated with insulin resistance and type 2 diabetes than a high IMCL content per se. Whether low mitochondrial function is a cause or consequence of the disease remains to be investigated.
Many children with frontal lobe epilepsy (FLE) have significant cognitive comorbidity, for which the underlying mechanism has not yet been unraveled, but is likely related to disturbed cerebral network integrity. Using resting-state fMRI, we investigated whether cerebral network characteristics are associated with epilepsy and cognitive comorbidity. We included 37 children with FLE and 41 healthy age-matched controls. Cognitive performance was determined by means of a computerized visual searching task. A connectivity matrix for 82 cortical and subcortical brain regions was generated for each subject by calculating the inter-regional correlation of the fMRI time signals. From the connectivity matrix, graph metrics were calculated and the anatomical configuration of aberrant connections and modular organization was investigated. Both patients and controls displayed efficiently organized networks. However, FLE patients displayed a higher modularity, implying that subnetworks are less interconnected. Impaired cognition was associated with higher modularity scores and abnormal modular organization of the brain, which was mainly expressed as a decrease in long-range and an increase in interhemispheric connectivity in patients. We showed that network modularity analysis provides a sensitive marker for cognitive impairment in FLE and suggest that abnormally interconnected functional subnetworks of the brain might underlie the cognitive problems in children with FLE.
Severe carotid artery stenosis or occlusion may put patients at risk for ischaemic stroke. Reduced cerebrovascular reserve capacity is a possible indicator of an imminent ischaemic event and can be determined by assessment of cerebrovascular reactivity to a vasodilative stimulus. However, little is known about the distribution of cerebrovascular reactivity in healthy individuals. In 13 healthy volunteers, dynamic T2* MR images, acquired at alternating inspiratory pCO2 levels, showed a high percentage of signal change in grey matter, with a strong linear correlation with end-tidal pCO2. The mean percentages of signal change for grey and white matter were 5.9 +/- 1.2% and 1.9 +/- 0.5%, respectively. The mean time lag between CO2 stimulus and haemodynamic response was 15 +/- 4 s for grey matter and 180 +/- 12 s for white matter. Parameter mapping revealed a hemispherically symmetrical and homogeneous distribution of cerebrovascular reactivity over the entire grey matter. These findings indicate that it may be feasible to detect exhausted cerebrovascular autoregulation in patients with a compromised cerebral vasculature.
Optimization of experimental settings of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), like the contrast administration protocol, is of great importance for reliable quantification of the microcirculatory properties, such as the volume transfer-constant K trans . Using system identification theory and computer simulations, the confounding effects of volume, rate and multiplicity of a contrast injection on the reliability of K trans estimation was assessed. A new tracer-distribution model (TDM), based on in vivo data from rectal cancer patients, served to describe the relationship between the contrast agent injection and the blood time-course. A pharmacokinetic model (PKM) was used to describe the relation between the blood and tumor tissue time-courses. By means of TDM and PKM in series, the tissue-transfer function of the PKM was analyzed. As both the TDM and PKM represented low-frequency-pass filters, the energy-density at low frequencies of the blood and tissue time-courses was larger than at high frequencies. The simulations, based on measurements in humans, predict that the K trans is most reliable with a high injection volume The development of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has led to the noninvasive characterization of tumor tissue (1,2). The volume transfer constant K trans , which describes the leakage rate of contrast agents into the tumor tissue, is a pharmacokinetic parameter that provides information on the physiological properties of the tumor, including the microvascular permeability and surface area, the relative blood volume, and the relative volume of the interstitial space (3-8). DCE-MRI has been recognized as a valuable tool for the evaluation of novel antiangiogenesis therapies (9 -12). Clinically, it is of importance to have a reliable and accurate quantitatively assessment of the progression or regression of tumor angiogenesis, as it may affect continuation of or changes to the treatment plan (13-15). The quality of the assessment is reflected in the accuracy of the determined pharmacokinetic parameters quantifying the wash-in and wash-out of the contrast agent. This accuracy is to a large extent determined by the experimental conditions (16). Unfortunately, where efforts have been directed to the standardization of the pharmacokinetic modeling (17), little is known on the most optimal experimental conditions. Previous investigations have focused on influences of sampling time, signal-to-noise ratio (SNR), and experiment duration (18 -22). In the present study it is hypothesized that the accuracy of the estimated pharmacokinetic parameters strongly depends on the dynamic shape of the arterial input function (AIF), which can be controlled by the contrast administration protocol.System identification theory is used to relate the reliability of the estimated K trans to the dynamics of the contrast agent injection and to find the optimal protocol for contrast agent administration. This theory states that the number of parameters involved in a ...
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