Detection of Endoleaks Following Thoracic and Abdominal Aortic Endovascular Aortic Repair—: A Comparison of Standard and Dynamic 4D-Computed Tomography Angiography

Purpose: Endoleaks are a common complication after endovascular aortic repair (EVAR) and thoracic endovascular aortic repair (TEVAR). The detection and correct classification of endoleaks is essential for the further treatment of affected patients. However, standard computed tomography angiography (CTA) provides no hemodynamic information on endoleaks, which can result in misclassification in complex cases. The aim of this study was to compare standard CTA (sCTA) with dynamic, dual-energy CTA (dCTA) for detection and classification of endoleaks following EVAR or TEVAR. Materials and Methods: This retrospective evaluation compared 69 sCTA diagnostic examinations performed on 50 different patients with 89 dCTA diagnostic examinations performed on 69 different patients. Results: In total, 15.9% of sCTA examinations and 49.4% of dCTA examinations led to the detection of endoleaks. With sCTA, 20.0% of patients were diagnosed with endoleaks, while with dCTA, 37.7% of patients were diagnosed with endoleaks. With sCTA, mainly Type 1 endoleaks were detected, whereas, with dCTA, the types of detected endoleaks were more evenly distributed. In comparison with the literature, the frequencies of endoleak types detected with dCTA better reflect the natural distribution than the frequencies detected with standard CTA. Conclusion: Based on the retrospective comparative evaluation, dCTA could pose a valuable supplementary diagnostic tool resulting in a more accurate and realistic detection and classification of suspected endoleaks

Numerical implementation and oceanographic application of the thermodynamic potentials of liquid water, water vapour, ice, seawater and humid air – Part 2: The library routines

The SCOR/IAPSO<sup>1</sup> Working Group 127 on Thermodynamics and Equation of State of Seawater has prepared recommendations for new methods and algorithms for numerical estimation of the the thermophysical properties of seawater. As an outcome of this work, a new International Thermodynamic Equation of Seawater (TEOS–10) was endorsed by IOC/UNESCO<sup>2</sup> in June 2009 as the official replacement and extension of the 1980 International Equation of State, EOS-80. As part of this new standard a source code package has been prepared that is now made freely available to users via the World Wide Web. This package includes two libraries referred to as the SIA (Sea-Ice-Air) library and the GSW (Gibbs SeaWater) library. Information on the GSW library may be found on the TEOS-10 web site (<a href="http://www.TEOS-10.org" target="_blank">http://www.TEOS-10.org</a>). This publication provides an introduction to the SIA library which contains routines to calculate various thermodynamic properties as discussed in the companion paper. The SIA library is very comprehensive, including routines to deal with fluid water, ice, seawater and humid air as well as equilibrium states involving various combinations of these, with equivalent code developed in different languages. The code is hierachically structured in modules that support (i) almost unlimited extension with respect to additional properties or relations, (ii) an extraction of self-contained sub-libraries, (iii) separate updating of the empirical thermodynamic potentials, and (iv) code verification on different platforms and between different languages. Error trapping is implemented to identify when one or more of the primary routines are accessed significantly beyond their established range of validity. The initial version of the SIA library is available in Visual Basic and FORTRAN as a supplement to this publication and updates will be maintained on the TEOS-10 web site. <br><br> <sup>1</sup>SCOR/IAPSO: Scientific Committee on Oceanic Research/International Association for the Physical Sciences of the Oceans<br> <sup>2</sup>IOC/UNESCO: Intergovernmental Oceanographic Commission/United Nations Educational, Scientific and Cultural Organizatio

Autophagy lipidation machinery regulates axonal microtubule dynamics but is dispensable for survival of mammalian neurons.

Neurons maintain axonal homeostasis via employing a unique organization of the microtubule (MT) cytoskeleton, which supports axonal morphology and provides tracks for intracellular transport. Abnormal MT-based trafficking hallmarks the pathology of neurodegenerative diseases, but the exact mechanism regulating MT dynamics in axons remains enigmatic. Here we report on a regulation of MT dynamics by AuTophaGy(ATG)-related proteins, which previously have been linked to the autophagy pathway. We find that ATG proteins required for LC3 lipid conjugation are dispensable for survival of excitatory neurons and instead regulate MT stability via controlling the abundance of the MT-binding protein CLASP2. This function of ATGs is independent of their role in autophagy and requires the active zone protein ELKS1. Our results highlight a non-canonical role of ATG proteins in neurons and suggest that pharmacological activation of autophagy may not only promote the degradation of cytoplasmic material, but also impair axonal integrity via altering MT stability

Myelin dysfunction drives amyloid-β deposition in models of Alzheimer's disease

The incidence of Alzheimer's disease (AD), the leading cause of dementia, increases rapidly with age, but why age constitutes the main risk factor is still poorly understood. Brain ageing affects oligodendrocytes and the structural integrity of myelin sheaths(1), the latter of which is associated with secondary neuroinflammation(2,3). As oligodendrocytes support axonal energy metabolism and neuronal health(4-7), we hypothesized that loss of myelin integrity could be an upstream risk factor for neuronal amyloid-beta (A beta) deposition, the central neuropathological hallmark of AD. Here we identify genetic pathways of myelin dysfunction and demyelinating injuries as potent drivers of amyloid deposition in mouse models of AD. Mechanistically, myelin dysfunction causes the accumulation of the A beta-producing machinery within axonal swellings and increases the cleavage of cortical amyloid precursor protein. Suprisingly, AD mice with dysfunctional myelin lack plaque-corralling microglia despite an overall increase in their numbers. Bulk and single-cell transcriptomics of AD mouse models with myelin defects show that there is a concomitant induction of highly similar but distinct disease-associated microglia signatures specific to myelin damage and amyloid plaques, respectively. Despite successful induction, amyloid disease-associated microglia (DAM) that usually clear amyloid plaques are apparently distracted to nearby myelin damage. Our data suggest a working model whereby age-dependent structural defects of myelin promote A beta plaque formation directly and indirectly and are therefore an upstream AD risk factor. Improving oligodendrocyte health and myelin integrity could be a promising target to delay development and slow progression of AD

An accurate and interpretable model for siRNA efficacy prediction

BACKGROUND: The use of exogenous small interfering RNAs (siRNAs) for gene silencing has quickly become a widespread molecular tool providing a powerful means for gene functional study and new drug target identification. Although considerable progress has been made recently in understanding how the RNAi pathway mediates gene silencing, the design of potent siRNAs remains challenging. RESULTS: We propose a simple linear model combining basic features of siRNA sequences for siRNA efficacy prediction. Trained and tested on a large dataset of siRNA sequences made recently available, it performs as well as more complex state-of-the-art models in terms of potency prediction accuracy, with the advantage of being directly interpretable. The analysis of this linear model allows us to detect and quantify the effect of nucleotide preferences at particular positions, including previously known and new observations. We also detect and quantify a strong propensity of potent siRNAs to contain short asymmetric motifs in their sequence, and show that, surprisingly, these motifs alone contain at least as much relevant information for potency prediction as the nucleotide preferences for particular positions. CONCLUSION: The model proposed for prediction of siRNA potency is as accurate as a state-of-the-art nonlinear model and is easily interpretable in terms of biological features. It is freely available on the web a

Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features

<p>Abstract</p> <p>Background</p> <p>RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathways. To dissect the factors that result in effective siRNA sequences a regression kernel Support Vector Machine (SVM) approach was used to quantitatively model RNA interference activities.</p> <p>Results</p> <p>Eight overall feature mapping methods were compared in their abilities to build SVM regression models that predict published siRNA activities. The primary factors in predictive SVM models are position specific nucleotide compositions. The secondary factors are position independent sequence motifs (<it>N</it>-grams) and guide strand to passenger strand sequence thermodynamics. Finally, the factors that are least contributory but are still predictive of efficacy are measures of intramolecular guide strand secondary structure and target strand secondary structure. Of these, the site of the 5' most base of the guide strand is the most informative.</p> <p>Conclusion</p> <p>The capacity of specific feature mapping methods and their ability to build predictive models of RNAi activity suggests a relative biological importance of these features. Some feature mapping methods are more informative in building predictive models and overall <it>t</it>-test filtering provides a method to remove some noisy features or make comparisons among datasets. Together, these features can yield predictive SVM regression models with increased predictive accuracy between predicted and observed activities both within datasets by cross validation, and between independently collected RNAi activity datasets. Feature filtering to remove features should be approached carefully in that it is possible to reduce feature set size without substantially reducing predictive models, but the features retained in the candidate models become increasingly distinct. Software to perform feature prediction and SVM training and testing on nucleic acid sequences can be found at the following site: <url>ftp://scitoolsftp.idtdna.com/SEQ2SVM/</url>.</p

Anhydrobiosis and Freezing-Tolerance:Adaptations That Facilitate the Establishment of Panagrolaimus Nematodes in Polar Habitats

<div><p>Anhydrobiotic animals can survive the loss of both free and bound water from their cells. While in this state they are also resistant to freezing. This physiology adapts anhydrobiotes to harsh environments and it aids their dispersal. <i>Panagrolaimus davidi</i>, a bacterial feeding anhydrobiotic nematode isolated from Ross Island Antarctica, can survive intracellular ice formation when fully hydrated. A capacity to survive freezing while fully hydrated has also been observed in some other Antarctic nematodes. We experimentally determined the anhydrobiotic and freezing-tolerance phenotypes of 24 <i>Panagrolaimus</i> strains from tropical, temperate, continental and polar habitats and we analysed their phylogenetic relationships. We found that several other <i>Panagrolaimus</i> isolates can also survive freezing when fully hydrated and that tissue extracts from these freezing-tolerant nematodes can inhibit the growth of ice crystals. We show that <i>P. davidi</i> belongs to a clade of anhydrobiotic and freezing-tolerant panagrolaimids containing strains from temperate and continental regions and that <i>P. superbus</i>, an early colonizer at Surtsey island, Iceland after its volcanic formation, is closely related to a species from Pennsylvania, USA. Ancestral state reconstructions show that anhydrobiosis evolved deep in the phylogeny of <i>Panagrolaimus</i>. The early-diverging <i>Panagrolaimus</i> lineages are strongly anhydrobiotic but weakly freezing-tolerant, suggesting that freezing tolerance is most likely a derived trait. The common ancestors of the <i>davidi</i> and the <i>superbus</i> clades were anhydrobiotic and also possessed robust freezing tolerance, along with a capacity to inhibit the growth and recrystallization of ice crystals. Unlike other endemic Antarctic nematodes, the life history traits of <i>P. davidi</i> do not show evidence of an evolved response to polar conditions. Thus we suggest that the colonization of Antarctica by <i>P. davidi</i> and of Surtsey by <i>P. superbus</i> may be examples of recent “ecological fitting” of freezing-tolerant anhydrobiotic propagules to the respective abiotic conditions in Ross Island and Surtsey.</p></div

RNAi Methodologies for the Functional Study of Signaling Molecules

RNA interference (RNAi) was investigated with the aim of achieving gene silencing with diverse RNAi platforms that include small interfering RNA (siRNA), short hairpin RNA (shRNA) and antisense oligonucleotides (ASO). Different versions of each system were used to silence the expression of specific subunits of the heterotrimeric signal transducing G-proteins, G alpha i2 and G beta 2, in the RAW 264.7 murine macrophage cell line. The specificity of the different RNA interference (RNAi) platforms was assessed by DNA microarray analysis. Reliable RNAi methodologies against the genes of interest were then developed and applied to functional studies of signaling networks. This study demonstrates a successful knockdown of target genes and shows the potential of RNAi for use in functional studies of signaling molecules