Mitochondrial respiration - an important therapeutic target in melanoma

The importance of mitochondria as oxygen sensors as well as producers of ATP and reactive oxygen species (ROS) has recently become a focal point of cancer research. However, in the case of melanoma, little information is available to what extent cellular bioenergetics processes contribute to the progression of the disease and related to it, whether oxidative phosphorylation (OXPHOS) has a prominent role in advanced melanoma. In this study we demonstrate that compared to melanocytes, metastatic melanoma cells have elevated levels of OXPHOS. Furthermore, treating metastatic melanoma cells with the drug, Elesclomol, which induces cancer cell apoptosis through oxidative stress, we document by way of stable isotope labeling with amino acids in cell culture (SILAC) that proteins participating in OXPHOS are downregulated. We also provide evidence that melanoma cells with high levels of glycolysis are more resistant to Elesclomol. We further show that Elesclomol upregulates hypoxia inducible factor 1-α (HIF-1α), and that prolonged exposure of melanoma cells to this drug leads to selection of melanoma cells with high levels of glycolysis. Taken together, our findings suggest that molecular targeting of OXPHOS may have efficacy for advanced melanoma. © 2012 Barbi de Moura et al

Unbiased, High-Throughput Electron Microscopy Analysis of Experience-Dependent Synaptic Changes in the Neocortex

UNLABELLED: Neocortical circuits can be altered by sensory and motor experience, with experimental evidence supporting both anatomical and electrophysiological changes in synaptic properties. Previous studies have focused on changes in specific neurons or pathways-for example, the thalamocortical circuitry, layer 4-3 (L4-L3) synapses, or in the apical dendrites of L5 neurons- but a broad-scale analysis of experience-induced changes across the cortical column has been lacking. Without this comprehensive approach, a full understanding of how cortical circuits adapt during learning or altered sensory input will be impossible. Here we adapt an electron microscopy technique that selectively labels synapses, in combination with a machine-learning algorithm for semiautomated synapse detection, to perform an unbiased analysis of developmental and experience-dependent changes in synaptic properties across an entire cortical column in mice. Synapse density and length were compared across development and during whisker-evoked plasticity. Between postnatal days 14 and 18, synapse density significantly increases most in superficial layers, and synapse length increases in L3 and L5B. Removal of all but a single whisker row for 24 h led to an apparent increase in synapse density in L2 and a decrease in L6, and a significant increase in length in L3. Targeted electrophysiological analysis of changes in miniature EPSC and IPSC properties in L2 pyramidal neurons showed that mEPSC frequency nearly doubled in the whisker-spared column, a difference that was highly significant. Together, this analysis shows that data-intensive analysis of column-wide changes in synapse properties can generate specific and testable hypotheses about experience-dependent changes in cortical organization. SIGNIFICANCE STATEMENT: Development and sensory experience can change synapse properties in the neocortex. Here we use a semiautomated analysis of electron microscopy images for an unbiased, column-wide analysis of synapse changes. This analysis reveals new loci for synaptic change that can be verified by targeted electrophysiological investigation. This method can be used as a platform for generating new hypotheses about synaptic changes across different brain areas and experimental conditions

A high-throughput framework to detect synapses in electron microscopy images.

<p>MOTIVATION: Synaptic connections underlie learning and memory in the brain and are dynamically formed and eliminated during development and in response to stimuli. Quantifying changes in overall density and strength of synapses is an important pre-requisite for studying connectivity and plasticity in these cases or in diseased conditions. Unfortunately, most techniques to detect such changes are either low-throughput (e.g. electrophysiology), prone to error and difficult to automate (e.g. standard electron microscopy) or too coarse (e.g. magnetic resonance imaging) to provide accurate and large-scale measurements.</p> <p>RESULTS: To facilitate high-throughput analyses, we used a 50-year-old experimental technique to selectively stain for synapses in electron microscopy images, and we developed a machine-learning framework to automatically detect synapses in these images. To validate our method, we experimentally imaged brain tissue of the somatosensory cortex in six mice. We detected thousands of synapses in these images and demonstrate the accuracy of our approach using cross-validation with manually labeled data and by comparing against existing algorithms and against tools that process standard electron microscopy images. We also used a semi-supervised algorithm that leverages unlabeled data to overcome sample heterogeneity and improve performance. Our algorithms are highly efficient and scalable and are freely available for others to use.</p> <p>AVAILABILITY: Code is available at http://www.cs.cmu.edu/∼saketn/detect_synapses/</p

Physician Noncompliance With the 1993 National Cholesterol Education Program (NCEP-ATPII) Guidelines

Background —We sought to determine the frequency with which physicians follow National Cholesterol Education Program (NCEP-ATPII) guidelines in screening for cardiovascular risk factors and treating hyperlipidemia. Methods and Results —We conducted a retrospective chart review on randomly sampled charts of 225 patients admitted to the coronary care unit between January and June 1996. The main outcome measures were rates of physician screening for coronary heart disease risk factors; rates of counseling for cigarette cessation, diet, and exercise; and extent of use of NCEP algorithms for obtaining LDL cholesterol values and treating hypercholesterolemia. Screening rates for interns (who performed best) were: cigarette use (89%), known coronary heart disease (74%), hypertension (68%), hyperlipidemia (59%), family history (56%), diabetes (37%), postmenopausal hormone therapy (11%), and premature menopause (1%). Four percent of smokers were counseled to quit, 14% of patients were referred to dietitians, and 1% were encouraged to exercise. A full lipid panel was obtained in 50% of patients in whom it was indicated on the basis of NCEP criteria. Patients were more likely to receive lipid-lowering treatment if NCEP criteria indicated that they should, but 36% of hospitalized patients and 46% of patients who should have been treated on discharge were not. Conclusions —Physicians are poorly compliant with NCEP guidelines for risk factor assessment and counseling, even in patients at high risk for coronary heart disease. Physicians follow NCEP-ATPII algorithms for obtaining an LDL value, a key step in evaluating the need for treatment, only 50% of the time. NCEP criteria seem to influence the decision to initiate lipid-lowering therapy, but significant numbers of eligible patients remain untreated. </jats:p