A summary of the users perspective of LANDSAT-D and reference document of LANDSAT users

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MicroRNA 7 Impairs Insulin Signaling and Regulates Aβ Levels through Posttranscriptional Regulation of the Insulin Receptor Substrate 2, Insulin Receptor, Insulin-Degrading Enzyme, and Liver X Receptor Pathway

Brain insulin resistance is a key pathological feature contributing to obesity, diabetes, and neurodegenerative disorders, including Alzheimer’s disease (AD). Besides the classic transcriptional mechanism mediated by hormones, posttranscriptional regulation has recently been shown to regulate a number of signaling pathways that could lead to metabolic diseases. Here, we show that microRNA 7 (miR-7), an abundant microRNA in the brain, targets insulin receptor (INSR), insulin receptor substrate 2 (IRS-2), and insulin-degrading enzyme (IDE), key regulators of insulin homeostatic functions in the central nervous system (CNS) and the pathology of AD. In this study, we found that insulin and liver X receptor (LXR) activators promote the expression of the intronic miR-7-1 in vitro and in vivo, along with its host heterogeneous nuclear ribonucleoprotein K (HNRNPK) gene, encoding an RNA binding protein (RBP) that is involved in insulin action at the posttranscriptional level. Our data show that miR-7 expression is altered in the brains of diet-induced obese mice. Moreover, we found that the levels of miR-7 are also elevated in brains of AD patients; this inversely correlates with the expression of its target genes IRS-2 and IDE. Furthermore, overexpression of miR-7 increased the levels of extracellular Aβ in neuronal cells and impaired the clearance of extracellular Aβ by microglial cells. Taken together, these results represent a novel branch of insulin action through the HNRNPK–miR-7 axis and highlight the possible implication of these posttranscriptional regulators in a range of diseases underlying metabolic dysregulation in the brain, from diabetes to Alzheimer’s disease

ORNL/IAT ARMATURE DIAGNOSTICS DEMONSTRATION TEST REPORT: PART TWO: BENCH DEMONSTRATION

The purpose of the present effort was to demonstrate 'on the fly' temperature measurement of railgun armatures on a bench top railgun. The effort builds on the previous test that utilized a portable unit with armature speeds ranging from 50 to 90 m/s. The tests described here involved higher speeds, ranging from 300 to 500 m/s. The method to accomplish the measurement involves pulsed laser illumination of a phosphor-coated armature. The duration of the ensuing fluorescence indicates temperature. The measured temperatures, obtained both inside the muzzle and outside in free flight, ranged between 80 to 110 C. The required pulsed fluorescence was made possible by successfully sensing the position of the armature while traveling within the laser illumination and fluorescence sensing fields-of-view. A high-speed camera also captured images of the moving armatures after exiting the railgun. These images sometimes included the fluorescing region of the phosphor coating

Circulating MicroRNA-122 Is Associated With the Risk of New-Onset Metabolic Syndrome and Type 2 Diabetes

MicroRNA-122 (miR-122) is abundant in the liver and involved in lipid homeostasis, but its relevance to the long-term risk of developing metabolic disorders is unknown. We therefore measured circulating miR-122 in the prospective population-based Bruneck Study (n = 810; survey year 1995). Circulating miR-122 was associated with prevalent insulin resistance, obesity, metabolic syndrome, type 2 diabetes, and an adverse lipid profile. Among 92 plasma proteins and 135 lipid subspecies quantified with mass spectrometry, it correlated inversely with zinc-α-2-glycoprotein and positively with afamin, complement factor H, VLDL-associated apolipoproteins, and lipid subspecies containing monounsaturated and saturated fatty acids. Proteomics analysis of livers from antagomiR-122–treated mice revealed novel regulators of hepatic lipid metabolism that are responsive to miR-122 inhibition. In the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT, n = 155), 12-month atorvastatin reduced circulating miR-122. A similar response to atorvastatin was observed in mice and cultured murine hepatocytes. Over up to 15 years of follow-up in the Bruneck Study, multivariable adjusted risk ratios per one-SD higher log miR-122 were 1.60 (95% CI 1.30–1.96; P < 0.001) for metabolic syndrome and 1.37 (1.03–1.82; P = 0.021) for type 2 diabetes. In conclusion, circulating miR-122 is strongly associated with the risk of developing metabolic syndrome and type 2 diabetes in the general population

A Fokker-Planck formalism for diffusion with finite increments and absorbing boundaries

Gaussian white noise is frequently used to model fluctuations in physical systems. In Fokker-Planck theory, this leads to a vanishing probability density near the absorbing boundary of threshold models. Here we derive the boundary condition for the stationary density of a first-order stochastic differential equation for additive finite-grained Poisson noise and show that the response properties of threshold units are qualitatively altered. Applied to the integrate-and-fire neuron model, the response turns out to be instantaneous rather than exhibiting low-pass characteristics, highly non-linear, and asymmetric for excitation and inhibition. The novel mechanism is exhibited on the network level and is a generic property of pulse-coupled systems of threshold units.Comment: Consists of two parts: main article (3 figures) plus supplementary text (3 extra figures

The Promise and Challenge of Therapeutic MicroRNA Silencing in Diabetes and Metabolic Diseases

MicroRNAs (miRNAs) are small, non-coding, RNA molecules that regulate gene expression. They have a long evolutionary history and are found in plants, viruses, and animals. Although initially discovered in 1993 in Caenorhabditis elegans, they were not appreciated as widespread and abundant gene regulators until the early 2000s. Studies in the last decade have found that miRNAs confer phenotypic robustness in the face of environmental perturbation, may serve as diagnostic and prognostic indicators of disease, underlie the pathobiology of a wide array of complex disorders, and represent compelling therapeutic targets. Pre-clinical studies in animal models have demonstrated that pharmacologic manipulation of miRNAs, mostly in the liver, can modulate metabolic phenotypes and even reverse the course of insulin resistance and diabetes. There is cautious optimism in the field about miRNA-based therapies for diabetes, several of which are already in various stages of clinical trials. This review will highlight both the promise and the most pressing challenges of therapeutic miRNA silencing in diabetes and related conditions

Surgical Data Science - from Concepts toward Clinical Translation

Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a new research field that aims to improve the quality of interventional healthcare through the capture, organization, analysis and modeling of data. While an increasing number of data-driven approaches and clinical applications have been studied in the fields of radiological and clinical data science, translational success stories are still lacking in surgery. In this publication, we shed light on the underlying reasons and provide a roadmap for future advances in the field. Based on an international workshop involving leading researchers in the field of SDS, we review current practice, key achievements and initiatives as well as available standards and tools for a number of topics relevant to the field, namely (1) infrastructure for data acquisition, storage and access in the presence of regulatory constraints, (2) data annotation and sharing and (3) data analytics. We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process

Relationship between circulating microRNA-30c with total- and LDL-cholesterol, their circulatory transportation and effect of statins

Background: Small non-coding microRNAs (miR) have important regulatory roles and are used as biomarkers of disease. We investigated the relationship between lipoproteins and circulating miR-30c, evaluated how they are transported in circulation and determined whether statins altered the circulating concentration of miR-30c. Methods: To determine the relationship between lipoproteins and circulating miR-30c, serum samples from 79 subjects recruited from a lipid clinic were evaluated. Ultracentrifugation and nanoparticle tracking analysis was used to evaluate the transportation of miR-30c in the circulation by lipoproteins and extracellular vesicles in three healthy volunteers. Using archived samples from previous studies, the effects of 40 mg rosuvastatin (n = 22) and 40 mg pravastatin (n = 24) on miR-30c expression was also examined. RNA extraction, reverse transcription-quantitative real-time polymerase chain reaction was carried out using standard procedures. Results: When stratified according to total cholesterol concentration, there was increased miR-30c expression in the highest compared to the lowest tertile (p = 0.035). There was significant positive correlation between miR- 30c and total- (r = 0.367; p = 0.002) and LDL-cholesterol (r = 0.391; p = 0.001). We found that miR-30c was transported in both exosomes and on HDL3. There was a 3.8-fold increased expression of circulating miR-30c after pravastatin treatment for 1 year (p = 0.005) but no significant change with atorvastatin after 8 weeks (p = 0.145). Conclusions: This study shows for the first-time in humans that circulating miR-30c is significantly, positively correlated with total- and LDL-cholesterol implicating regulatory functions in lipid homeostasis. We show miR-30c is transported in both exosomes and on HDL3 and pravastatin therapy significantly increased circulating miR-30c expression adding to the pleiotropic dimensions of statins

A reafferent and feed-forward model of song syntax generation in the Bengalese finch

Adult Bengalese finches generate a variable song that obeys a distinct and individual syntax. The syntax is gradually lost over a period of days after deafening and is recovered when hearing is restored. We present a spiking neuronal network model of the song syntax generation and its loss, based on the assumption that the syntax is stored in reafferent connections from the auditory to the motor control area. Propagating synfire activity in the HVC codes for individual syllables of the song and priming signals from the auditory network reduce the competition between syllables to allow only those transitions that are permitted by the syntax. Both imprinting of song syntax within HVC and the interaction of the reafferent signal with an efference copy of the motor command are sufficient to explain the gradual loss of syntax in the absence of auditory feedback. The model also reproduces for the first time experimental findings on the influence of altered auditory feedback on the song syntax generation, and predicts song- and species-specific low frequency components in the LFP. This study illustrates how sequential compositionality following a defined syntax can be realized in networks of spiking neurons

Prediction of LDL cholesterol response to statin using transcriptomic and genetic variation

BACKGROUND: Statins are widely prescribed for lowering LDL-cholesterol (LDLC) levels and risk of cardiovascular disease. There is, however, substantial inter-individual variation in the magnitude of statin-induced LDLC reduction. To date, analysis of individual DNA sequence variants has explained only a small proportion of this variability. The present study was aimed at assessing whether transcriptomic analyses could be used to identify additional genetic contributions to inter-individual differences in statin efficacy. RESULTS: Using expression array data from immortalized lymphoblastoid cell lines derived from 372 participants of the Cholesterol and Pharmacogenetics clinical trial, we identify 100 signature genes differentiating high versus low statin responders. A radial-basis support vector machine prediction model of these signature genes explains 12.3% of the variance in statin-mediated LDLC change. Addition of SNPs either associated with expression levels of the signature genes (eQTLs) or previously reported to be associated with statin response in genome-wide association studies results in a combined model that predicts 15.0% of the variance. Notably, a model of the signature gene associated eQTLs alone explains up to 17.2% of the variance in the tails of a separate subset of the Cholesterol and Pharmacogenetics population. Furthermore, using a support vector machine classification model, we classify the most extreme 15% of high and low responders with high accuracy. CONCLUSIONS: These results demonstrate that transcriptomic information can explain a substantial proportion of the variance in LDLC response to statin treatment, and suggest that this may provide a framework for identifying novel pathways that influence cholesterol metabolism. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13059-014-0460-9) contains supplementary material, which is available to authorized users