A Spatial Simulation Approach to Account for Protein Structure When Identifying Non-Random Somatic Mutations

Background: Current research suggests that a small set of "driver" mutations are responsible for tumorigenesis while a larger body of "passenger" mutations occurs in the tumor but does not progress the disease. Due to recent pharmacological successes in treating cancers caused by driver mutations, a variety of of methodologies that attempt to identify such mutations have been developed. Based on the hypothesis that driver mutations tend to cluster in key regions of the protein, the development of cluster identification algorithms has become critical. Results: We have developed a novel methodology, SpacePAC (Spatial Protein Amino acid Clustering), that identifies mutational clustering by considering the protein tertiary structure directly in 3D space. By combining the mutational data in the Catalogue of Somatic Mutations in Cancer (COSMIC) and the spatial information in the Protein Data Bank (PDB), SpacePAC is able to identify novel mutation clusters in many proteins such as FGFR3 and CHRM2. In addition, SpacePAC is better able to localize the most significant mutational hotspots as demonstrated in the cases of BRAF and ALK. The R package is available on Bioconductor at: http://www.bioconductor.org/packages/release/bioc/html/SpacePAC.html Conclusion: SpacePAC adds a valuable tool to the identification of mutational clusters while considering protein tertiary structureComment: 16 pages, 8 Figures, 4 Table

Privacy-Friendly Collaboration for Cyber Threat Mitigation

Sharing of security data across organizational boundaries has often been advocated as a promising way to enhance cyber threat mitigation. However, collaborative security faces a number of important challenges, including privacy, trust, and liability concerns with the potential disclosure of sensitive data. In this paper, we focus on data sharing for predictive blacklisting, i.e., forecasting attack sources based on past attack information. We propose a novel privacy-enhanced data sharing approach in which organizations estimate collaboration benefits without disclosing their datasets, organize into coalitions of allied organizations, and securely share data within these coalitions. We study how different partner selection strategies affect prediction accuracy by experimenting on a real-world dataset of 2 billion IP addresses and observe up to a 105% prediction improvement.Comment: This paper has been withdrawn as it has been superseded by arXiv:1502.0533

Exploiting 2D Floorplan for Building-scale Panorama RGBD Alignment

This paper presents a novel algorithm that utilizes a 2D floorplan to align panorama RGBD scans. While effective panorama RGBD alignment techniques exist, such a system requires extremely dense RGBD image sampling. Our approach can significantly reduce the number of necessary scans with the aid of a floorplan image. We formulate a novel Markov Random Field inference problem as a scan placement over the floorplan, as opposed to the conventional scan-to-scan alignment. The technical contributions lie in multi-modal image correspondence cues (between scans and schematic floorplan) as well as a novel coverage potential avoiding an inherent stacking bias. The proposed approach has been evaluated on five challenging large indoor spaces. To the best of our knowledge, we present the first effective system that utilizes a 2D floorplan image for building-scale 3D pointcloud alignment. The source code and the data will be shared with the community to further enhance indoor mapping research

Objective assessment of functional and motor-cognitive outcomes among asymptomatic primary hyperparathyroidism patients undergoing parathyroidectomy using wearable technologies: a pilot study towards better informed clinical decision-making

For the past 40 years, most patients with Primary Hyperparathyroidism (PHPT) have presented with the asymptomatic form of PHPT. Despite the dominance of the asymptomatic PHPT phenotype, current National Institutes of Health (NIH) indications for parathyroidectomy fail to identify as many as 80% of patients afflicted with asymptomatic PHPT. To date, studies of the therapeutic benefits of parathyroidectomy among asymptomatic PHPT patients have relied on general health questionnaires and patient reports of their satisfaction with the surgery. The purpose of the present study was to implement objective, quantifiable metrics in assessing whether or not asymptomatic PHPT patients experience improvements in domains salient to them such as mobility and cognitive function following parathyroidectomy. This information may help set the foundation for more accurately identifying patients who would benefit from parathyroidectomy. We hypothesized that asymptomatic patients would exhibit improvement in motor-cognitive outcomes following successful parathyroidectomy. We performed a single-center prospective assessment of gait, frailty, and motor-cognitive function among patients diagnosed with PHPT. Demographics, medical history, and perioperative labs were recorded. Pre- and post-surgical measures included the Fried frailty criteria, the PROMIS 10 Global Health Scale, and gait analysis under habitual (ST), walking while performing working memory test (dual-task: DT), and fast-walking conditions, an upper extremity frailty (UEF) test, and an interactive trail-making task (iTMT) . Descriptive statistics, Chi-squared, 2-sample t tests, and repeated measures analysis of variance were applied where appropriate. 22 parathyroidectomy patients (male 7; 31.8%); median age of 54.9 (standard deviation=15.5) years participated. The prevalence of frailty/pre-frailty was 60% at baseline and reduced to 33% at 3 weeks post-op. PROMIS 10 physical health improved significantly by 3 months post-op (d=0.93, p=0.010). DT and fast walk velocities were significantly increased by 3 weeks post-op (p<0.050) with highest effect size observed during DT conditions (24%, Cohen's effect size d=1.30 , p=0.017). ST velocity increased but not significantly (17.5%, d=0.46, p=0.422). Results from UEF tests and iTMT did not achieve statistical significance at any visit date. Asymptomatic PHPT patients experience significant resolution of motor-cognitive symptoms as measured by DT gait and PROMIS 10 Global Health Scale following parathyroidectomy performed by a skilled surgeon

Identification of Genes and Pathways Regulated by Lamin A in Heart

Background Mutations in the LMNA gene, encoding LMNA (lamin A/C), causes distinct disorders, including dilated cardiomyopathies, collectively referred to as laminopathies. The genes (coding and noncoding) and regulatory pathways controlled by LMNA in the heart are not completely defined. Methods and Results We analyzed cardiac transcriptome from wild-type, loss-of-function (Lmna-/-), and gain-of-function (Lmna-/- injected with adeno-associated virus serotype 9 expressing LMNA) mice with normal cardiac function. Deletion of Lmna (Lmna-/-) led to differential expression of 2193 coding and 629 long noncoding RNA genes in the heart (q<0.05). Re-expression of LMNA in the Lmna-/- mouse heart, completely rescued 501 coding and 208 non-coding and partially rescued 1862 coding and 607 lncRNA genes. Pathway analysis of differentially expressed genes predicted activation of transcriptional regulators lysine-specific demethylase 5A, lysine-specific demethylase 5B, tumor protein 53, and suppression of retinoblastoma 1, paired-like homeodomain 2, and melanocyte-inducing transcription factor, which were completely or partially rescued upon reexpression of LMNA. Furthermore, lysine-specific demethylase 5A and 5B protein levels were increased in the Lmna-/- hearts and were partially rescued upon LMNA reexpression. Analysis of biological function for rescued genes identified activation of tumor necrosis factor-α, epithelial to mesenchymal transition, and suppression of the oxidative phosphorylation pathway upon Lmna deletion and their restoration upon LMNA reintroduction in the heart. Restoration of the gene expression and transcriptional regulators in the heart was associated with improved cardiac function and increased survival of the Lmna-/- mice. Conclusions The findings identify LMNA-regulated cardiac genes and their upstream transcriptional regulators in the heart and implicate lysine-specific demethylase 5A and B as epigenetic regulators of a subset of the dysregulated genes in laminopathies

CMB-S4 Science Book, First Edition

This book lays out the scientific goals to be addressed by the next-generation ground-based cosmic microwave background experiment, CMB-S4, envisioned to consist of dedicated telescopes at the South Pole, the high Chilean Atacama plateau and possibly a northern hemisphere site, all equipped with new superconducting cameras. CMB-S4 will dramatically advance cosmological studies by crossing critical thresholds in the search for the B-mode polarization signature of primordial gravitational waves, in the determination of the number and masses of the neutrinos, in the search for evidence of new light relics, in constraining the nature of dark energy, and in testing general relativity on large scales

Integrated helicopter survivability

A high level of survivability is important to protect military personnel and equipment and is central to UK defence policy. Integrated Survivability is the systems engineering methodology to achieve optimum survivability at an affordable cost, enabling a mission to be completed successfully in the face of a hostile environment. “Integrated Helicopter Survivability” is an emerging discipline that is applying this systems engineering approach within the helicopter domain. Philosophically the overall survivability objective is ‘zero attrition’, even though this is unobtainable in practice. The research question was: “How can helicopter survivability be assessed in an integrated way so that the best possible level of survivability can be achieved within the constraints and how will the associated methods support the acquisition process?” The research found that principles from safety management could be applied to the survivability problem, in particular reducing survivability risk to as low as reasonably practicable (ALARP). A survivability assessment process was developed to support this approach and was linked into the military helicopter life cycle. This process positioned the survivability assessment methods and associated input data derivation activities. The system influence diagram method was effective at defining the problem and capturing the wider survivability interactions, including those with the defence lines of development (DLOD). Influence diagrams and Quality Function Deployment (QFD) methods were effective visual tools to elicit stakeholder requirements and improve communication across organisational and domain boundaries. The semi-quantitative nature of the QFD method leads to numbers that are not real. These results are suitable for helping to prioritise requirements early in the helicopter life cycle, but they cannot provide the quantifiable estimate of risk needed to demonstrate ALARP. The probabilistic approach implemented within the Integrated Survivability Assessment Model (ISAM) was developed to provide a quantitative estimate of ‘risk’ to support the approach of reducing survivability risks to ALARP. Limitations in available input data for the rate of encountering threats leads to a probability of survival that is not a real number that can be used to assess actual loss rates. However, the method does support an assessment across platform options, provided that the ‘test environment’ remains consistent throughout the assessment. The survivability assessment process and ISAM have been applied to an acquisition programme, where they have been tested to support the survivability decision making and design process. The survivability ‘test environment’ is an essential element of the survivability assessment process and is required by integrated survivability tools such as ISAM. This test environment, comprising of threatening situations that span the complete spectrum of helicopter operations requires further development. The ‘test environment’ would be used throughout the helicopter life cycle from selection of design concepts through to test and evaluation of delivered solutions. It would be updated as part of the through life capability management (TLCM) process. A framework of survivability analysis tools requires development that can provide probabilistic input data into ISAM and allow derivation of confidence limits. This systems level framework would be capable of informing more detailed survivability design work later in the life cycle and could be enabled through a MATLAB® based approach. Survivability is an emerging system property that influences the whole system capability. There is a need for holistic capability level analysis tools that quantify survivability along with other influencing capabilities such as: mobility (payload / range), lethality, situational awareness, sustainability and other mission capabilities. It is recommended that an investigation of capability level analysis methods across defence should be undertaken to ensure a coherent and compliant approach to systems engineering that adopts best practice from across the domains. Systems dynamics techniques should be considered for further use by Dstl and the wider MOD, particularly within the survivability and operational analysis domains. This would improve understanding of the problem space, promote a more holistic approach and enable a better balance of capability, within which survivability is one essential element. There would be value in considering accidental losses within a more comprehensive ‘survivability’ analysis. This approach would enable a better balance to be struck between safety and survivability risk mitigations and would lead to an improved, more integrated overall design

IST Austria Thesis

Synthesis of proteins – translation – is a fundamental process of life. Quantitative studies anchor translation into the context of bacterial physiology and reveal several mathematical relationships, called “growth laws,” which capture physiological feedbacks between protein synthesis and cell growth. Growth laws describe the dependency of the ribosome abundance as a function of growth rate, which can change depending on the growth conditions. Perturbations of translation reveal that bacteria employ a compensatory strategy in which the reduced translation capability results in increased expression of the translation machinery. Perturbations of translation are achieved in various ways; clinically interesting is the application of translation-targeting antibiotics – translation inhibitors. The antibiotic effects on bacterial physiology are often poorly understood. Bacterial responses to two or more simultaneously applied antibiotics are even more puzzling. The combined antibiotic effect determines the type of drug interaction, which ranges from synergy (the effect is stronger than expected) to antagonism (the effect is weaker) and suppression (one of the drugs loses its potency). In the first part of this work, we systematically measure the pairwise interaction network for translation inhibitors that interfere with different steps in translation. We find that the interactions are surprisingly diverse and tend to be more antagonistic. To explore the underlying mechanisms, we begin with a minimal biophysical model of combined antibiotic action. We base this model on the kinetics of antibiotic uptake and binding together with the physiological response described by the growth laws. The biophysical model explains some drug interactions, but not all; it specifically fails to predict suppression. In the second part of this work, we hypothesize that elusive suppressive drug interactions result from the interplay between ribosomes halted in different stages of translation. To elucidate this putative mechanism of drug interactions between translation inhibitors, we generate translation bottlenecks genetically using in- ducible control of translation factors that regulate well-defined translation cycle steps. These perturbations accurately mimic antibiotic action and drug interactions, supporting that the interplay of different translation bottlenecks partially causes these interactions. We extend this approach by varying two translation bottlenecks simultaneously. This approach reveals the suppression of translocation inhibition by inhibited translation. We rationalize this effect by modeling dense traffic of ribosomes that move on transcripts in a translation factor-mediated manner. This model predicts a dissolution of traffic jams caused by inhibited translocation when the density of ribosome traffic is reduced by lowered initiation. We base this model on the growth laws and quantitative relationships between different translation and growth parameters. In the final part of this work, we describe a set of tools aimed at quantification of physiological and translation parameters. We further develop a simple model that directly connects the abundance of a translation factor with the growth rate, which allows us to extract physiological parameters describing initiation. We demonstrate the development of tools for measuring translation rate. This thesis showcases how a combination of high-throughput growth rate mea- surements, genetics, and modeling can reveal mechanisms of drug interactions. Furthermore, by a gradual transition from combinations of antibiotics to precise genetic interventions, we demonstrated the equivalency between genetic and chemi- cal perturbations of translation. These findings tile the path for quantitative studies of antibiotic combinations and illustrate future approaches towards the quantitative description of translation