Background— It is well known that patients with type 2 diabetes have increased risk of cardiovascular disease, but it is not known whether they have underlying abnormalities in cardiac or skeletal muscle high-energy phosphate metabolism. Methods and Results— We studied 21 patients with type 2 diabetes with no evidence of coronary artery disease or impaired cardiac function, as determined by echocardiography, and 15 age-, sex-, and body mass index-matched control subjects. Cardiac high-energy phosphate metabolites were measured at rest using ³¹ P nuclear magnetic resonance spectroscopy (MRS). Skeletal muscle high-energy phosphate metabolites, intracellular pH, and oxygenation were measured using ³¹ P MRS and near infrared spectrophotometry, respectively, before, during, and after exercise. Although their cardiac morphology, mass, and function appeared to be normal, the patients with diabetes had significantly lower phosphocreatine (PCr)/ATP ratios, at 1.50±0.11, than the healthy volunteers, at 2.30±0.12. The cardiac PCr/ATP ratios correlated negatively with the fasting plasma free fatty acid concentrations. Although skeletal muscle energetics and pH were normal at rest, PCr loss and pH decrease were significantly faster during exercise in the patients with diabetes, who had lower exercise tolerance. After exercise, PCr recovery was slower in the patients with diabetes and correlated with tissue reoxygenation times. The exercise times correlated negatively with the deoxygenation rates and the hemoglobin (Hb)A _1c levels and the reoxygenation times correlated positively with the HbA _1c levels. Conclusions— Type 2 diabetic patients with apparently normal cardiac function have impaired myocardial and skeletal muscle energy metabolism related to changes in circulating metabolic substrates.

Friedreich ataxia (FRDA), the most common of the inherited ataxias, is an autosomal recessive degenerative disorder, characterized clinically by onset before the age of 25 of progressive gait and limb ataxia, absence of deep tendon reflexes, extensor plantar responses, and loss of position and vibration sense in the lower limbs. FRDA is caused by a GAA triplet expansion in the first intron of the FRDA gene on chromosome 9q13 in 97% of patients. The FRDA gene encodes a widely expressed 210-aa protein, frataxin, which is located in mitochondria and is severely reduced in FRDA patients. Frataxin function is still unknown but the knockout of the yeast frataxin homologue gene ( YFH1 ) showed a severe defect of mitochondrial respiration and loss of mtDNA associated with elevated intramitochondrial iron. Here we report in vivo evidence of impaired mitochondrial respiration in skeletal muscle of FRDA patients. Using phosphorus magnetic resonance spectroscopy we demonstrated a maximum rate of muscle mitochondrial ATP production ( V _max ) below the normal range in all 12 FRDA patients and a strong negative correlation between mitochondrial V _max and the number of GAA repeats in the smaller allele. Our results show that FRDA is a nuclear-encoded mitochondrial disorder affecting oxidative phosphorylation and give a rationale for treatments aimed to improve mitochondrial function in this condition.

Clinical differentiation of parkinsonian syndromes such as the Parkinson variant of multiple system atrophy (MSA-P) and progressive supranuclear palsy (PSP) from Parkinson's disease is difficult in the early stage of the disease. In order to identify objective markers for differential diagnosis, we studied these three groups of patients with diffusion-weighted MRI (DWI). Sixteen MSA-P patients, 16 with PSP, 16 with Parkinson's disease and 15 healthy volunteers were studied. Regional apparent diffusion coefficients (rADC) were determined in different brain regions including basal ganglia, thalamus, white matter, pons and middle cerebellar peduncles (MCPs). rADC calculated in the MCP completely differentiated MSA-P patients (median: 0.93 × 10⁻³ mm²/s) from PSP patients (median: 0.82 × 10⁻³ mm²/s, P < 0.001), Parkinson's disease patients (median: 0.79 × 10⁻³ mm²/s, P < 0.001) and healthy volunteers (median: 0.81 × 10⁻³ mm²/s, P < 0.001). Other regions considered showed an overlapping among groups. DWI discriminates MSA-P from PSP and Parkinson's disease and healthy volunteers on the basis of MCP rADC values. These in vivo results confirm the pathological findings that the majority of MSA-P patients have moderate or severe degenerative changes not only in the nigrostriatal but also in the olivopontocerebellar systems. Our findings indicate that, in order to substantially contribute to the in vivo differential diagnosis of MSA-P, PSP and Parkinson's disease, rADC measurements should not be limited to the basal ganglia but should also include the MCP.

Optic neuropathy is common in mitochondrial disorders, but poorly characterized in Friedreich's ataxia (FRDA), a recessive condition caused by lack of the mitochondrial protein frataxin. We investigated 26 molecularly confirmed FRDA patients by studying both anterior and posterior sections of the visual pathway using a new, integrated approach. This included visual field testing and optical coherence tomography (OCT), pattern visual evoked potentials (P-VEPs) and diffusion-weighted imaging. The latter was used to study optic radiation by calculating water apparent diffusion coefficients (ADC). All patients suffered optic nerve involvement with their disorder. Different patterns of visual field defects were observed and a variably reduced retinal nerve fiber layer thickness was seen by OCT in all cases. P-VEPs were abnormal in approximately half of the patients. Decreased visual acuity and temporal optic disc pallor were present in advanced stages of the disease, but only five patients were symptomatic. Two of these patients suffered a sudden loss of central vision, mimicking Leber's hereditary optic neuropathy (LHON), and of the other three symptomatic patients two were noted to be compound heterozygotes. ADC values of optic radiations in patients were significantly higher than controls (P< 0.01). Retinal nerve fiber layer thickness at OCT and P-VEPs correlated with age at onset and ICARS total score. ADC values correlated with age at onset, disease duration, GAA triplet expansion size, ICARS total score and P-VEPs. Visual pathway involvement is found consistently in FRDA, being previously underestimated, and we here document that it also involves the optic radiations. Occasional LHON-like cases may occur. However, optic neuropathy in FRDA substantially differs from classic mitochondrial optic neuropathies implying a different pathophysiology of visual system degeneration in this mitochondrial disease.

Research from JAMA Neurology — Antioxidant Treatment of Patients With Friedreich Ataxia — Four-Year Follow-up

Convolutional neural networks (CNNs) constitute a widely used deep learning approach that has frequently been applied to the problem of brain tumor diagnosis. Such techniques still face some critical challenges in moving towards clinic application. The main objective of this work is to present a comprehensive review of studies using CNN architectures to classify brain tumors using MR images with the aim of identifying useful strategies for and possible impediments in the development of this technology. Relevant articles were identified using a predefined, systematic procedure. For each article, data were extracted regarding training data, target problems, the network architecture, validation methods, and the reported quantitative performance criteria. The clinical relevance of the studies was then evaluated to identify limitations by considering the merits of convolutional neural networks and the remaining challenges that need to be solved to promote the clinical application and development of CNN algorithms. Finally, possible directions for future research are discussed for researchers in the biomedical and machine learning communities. A total of 83 studies were identified and reviewed. They differed in terms of the precise classification problem targeted and the strategies used to construct and train the chosen CNN. Consequently, the reported performance varied widely, with accuracies of 91.63–100% in differentiating meningiomas, gliomas, and pituitary tumors (26 articles) and of 60.0–99.46% in distinguishing low-grade from high-grade gliomas (13 articles). The review provides a survey of the state of the art in CNN-based deep learning methods for brain tumor classification. Many networks demonstrated good performance, and it is not evident that any specific methodological choice greatly outperforms the alternatives, especially given the inconsistencies in the reporting of validation methods, performance metrics, and training data encountered. Few studies have focused on clinical usability.