Uniform Foam Crush Testing for Multi-Mission Earth Entry Vehicle Impact Attenuation

Multi-Mission Earth Entry Vehicles (MMEEVs) are blunt-body vehicles designed with the purpose of transporting payloads from outer space to the surface of the Earth. To achieve high-reliability and minimum weight, MMEEVs avoid use of limited-reliability systems, such as parachutes and retro-rockets, instead using built-in impact attenuators to absorb energy remaining at impact to meet landing loads requirements. The Multi-Mission Systems Analysis for Planetary Entry (M-SAPE) parametric design tool is used to facilitate the design of MMEEVs and develop the trade space. Testing was conducted to characterize the material properties of several candidate impact foam attenuators to enhance M-SAPE analysis. In the current effort, four different Rohacell foams are tested at three different, uniform, strain rates (approximately 0.17, approximately 100, approximately 13,600%/s). The primary data analysis method uses a global data smoothing technique in the frequency domain to remove noise and system natural frequencies. The results from the data indicate that the filter and smoothing technique are successful in identifying the foam crush event and removing aberrations. The effect of strain rate increases with increasing foam density. The 71-WF-HT foam may support Mars Sample Return requirements. Several recommendations to improve the drop tower test technique are identified

Safe2Ditch Autonomous Crash Management System for Small Unmanned Aerial Systems: Concept Definition and Flight Test Results

Small unmanned aerial systems (sUAS) have the potential for a large array of highly-beneficial applications. These applications are too numerous to comprehensively list, but include search and rescue, fire spotting, precision agriculture, etc. to name a few. Typically sUAS vehicles weigh less than 55 lbs and will be performing flight operations in the National Air Space (NAS). Certain sUAS applications, such as package delivery, will include operations in the close proximity of the general public. The full benefit from sUAS is contingent upon the resolution of several technological areas in order to provide an acceptable level of risk for widespread sUAS operations. Operations of sUAS vehicles pose risks to people and property on the ground as well as manned aviation. Several of the more significant sUAS technological areas include, but are not limited to: autonomous sense and avoid and deconfliction of sUAS from other sUAS and manned aircraft, communications and interfaces between the vehicle and human operators, and the overall reliability of the sUAS and constituent subsystems. While all of the technological areas listed contribute significantly to the safe execution of the sUAS flight operations, contingency or emergency systems can greatly contribute to sUAS risk mitigations to manage situations where the vehicle is in distress. The Safe2Ditch (S2D) system is an autonomous crash management system for sUAS. Its function is to enable sUAS to execute emergency landings and avoid injuring people on the ground, damaging property, and lastly preserving the sUAS and payload. A sUAS flight test effort was performed to test the integration of sub-elements of the S2D system with a representative sUAS multi-rotor

Systems Analysis of miRNA Biomarkers to Inform Drug Safety

microRNAs (miRNAs or miRs) are short non-coding RNA molecules which have been shown to be dysregulated and released into the extracellular milieu as a result of many drug and non-drug-induced pathologies in different organ systems. Consequently, circulating miRs have been proposed as useful biomarkers of many disease states, including drug-induced tissue injury. miRs have shown potential to support or even replace the existing traditional biomarkers of drug-induced toxicity in terms of sensitivity and specificity, and there is some evidence for their improved diagnostic and prognostic value. However, several pre-analytical and analytical challenges, mainly associated with assay standardization, require solutions before circulating miRs can be successfully translated into the clinic. This review will consider the value and potential for the use of circulating miRs in drug-safety assessment and describe a systems approach to the analysis of the miRNAome in the discovery setting, as well as highlighting standardization issues that at this stage prevent their clinical use as biomarkers. Highlighting these challenges will hopefully drive future research into finding appropriate solutions, and eventually circulating miRs may be translated to the clinic where their undoubted biomarker potential can be used to benefit patients in rapid, easy to use, point-of-care test systems

Overexpression of cathepsin K in mice decreases collagen deposition and lung resistance in response to bleomycin-induced pulmonary fibrosis

<p>Abstract</p> <p>Background</p> <p>Lung fibrosis is a devastating pulmonary disorder characterized by alveolar epithelial injury, extracellular matrix deposition and scar tissue formation. Due to its potent collagenolytic activity, cathepsin K, a lysosomal cysteine protease is an interesting target molecule with therapeutic potential to attenuate bleomycin-induced pulmonary fibrosis in mice. We here tested the hypothesis that over-expression of cathepsin K in the lungs of mice is protective in bleomycin-induced pulmonary fibrosis.</p> <p>Methods</p> <p>Wild-type and cathepsin K overexpressing (cathepsin K transgenic; cath K tg) mice were challenged intratracheally with bleomycin and sacrificed at 1, 2, 3 and 4 weeks post-treatment followed by determination of lung fibrosis by estimating lung collagen content, lung histopathology, leukocytic infiltrates and lung function. In addition, changes in cathepsin K protein levels in the lung were determined by immunohistochemistry, real time RT-PCR and western blotting.</p> <p>Results</p> <p>Cathepsin K protein levels were strongly increased in alveolar macrophages and lung parenchymal tissue of mock-treated cathepsin K transgenic (cath K tg) mice relative to wild-type mice and further increased particularly in cath K tg but also wild-type mice in response to bleomycin. Moreover, cath K tg mice responded with a lower collagen deposition in their lungs, which was accompanied by a significantly lower lung resistance (R_L) compared to bleomycin-treated wild-type mice. In addition, cath K tg mice responded with a lower degree of lung fibrosis than wild-type mice, a process that was found to be independent of inflammatory leukocyte mobilization in response to bleomycin challenge.</p> <p>Conclusion</p> <p>Over-expression of cathepsin K reduced lung collagen deposition and improved lung function parameters in the lungs of transgenic mice, thereby providing at least partial protection against bleomycin-induced lung fibrosis.</p

Empirical comparison of cross-platform normalization methods for gene expression data

<p>Abstract</p> <p>Background</p> <p>Simultaneous measurement of gene expression on a genomic scale can be accomplished using microarray technology or by sequencing based methods. Researchers who perform high throughput gene expression assays often deposit their data in public databases, but heterogeneity of measurement platforms leads to challenges for the combination and comparison of data sets. Researchers wishing to perform cross platform normalization face two major obstacles. First, a choice must be made about which method or methods to employ. Nine are currently available, and no rigorous comparison exists. Second, software for the selected method must be obtained and incorporated into a data analysis workflow.</p> <p>Results</p> <p>Using two publicly available cross-platform testing data sets, cross-platform normalization methods are compared based on inter-platform concordance and on the consistency of gene lists obtained with transformed data. Scatter and ROC-like plots are produced and new statistics based on those plots are introduced to measure the effectiveness of each method. Bootstrapping is employed to obtain distributions for those statistics. The consistency of platform effects across studies is explored theoretically and with respect to the testing data sets.</p> <p>Conclusions</p> <p>Our comparisons indicate that four methods, DWD, EB, GQ, and XPN, are generally effective, while the remaining methods do not adequately correct for platform effects. Of the four successful methods, XPN generally shows the highest inter-platform concordance when treatment groups are equally sized, while DWD is most robust to differently sized treatment groups and consistently shows the smallest loss in gene detection. We provide an R package, CONOR, capable of performing the nine cross-platform normalization methods considered. The package can be downloaded at <url>http://alborz.sdsu.edu/conor</url> and is available from CRAN.</p

Identification of a gene signature for discriminating metastatic from primary melanoma using a molecular interaction network approach

Understanding the biological factors that are characteristic of metastasis in melanoma remains a key approach to improving treatment. In this study, we seek to identify a gene signature of metastatic melanoma. We configured a new network-based computational pipeline, combined with a machine learning method, to mine publicly available transcriptomic data from melanoma patient samples. Our method is unbiased and scans a genome-wide protein-protein interaction network using a novel formulation for network scoring. Using this, we identify the most influential, differentially expressed nodes in metastatic as compared to primary melanoma. We evaluated the shortlisted genes by a machine learning method to rank them by their discriminatory capacities. From this, we identified a panel of 6 genes, ALDH1A1, HSP90AB1, KIT, KRT16, SPRR3 and TMEM45B whose expression values discriminated metastatic from primary melanoma (87% classification accuracy). In an independent transcriptomic data set derived from 703 primary melanomas, we showed that all six genes were significant in predicting melanoma specific survival (MSS) in a univariate analysis, which was also consistent with AJCC staging. Further, 3 of these genes, HSP90AB1, SPRR3 and KRT16 remained significant predictors of MSS in a joint analysis (HR = 2.3, P = 0.03) although, HSP90AB1 (HR = 1.9, P = 2 × 10−4) alone remained predictive after adjusting for clinical predictors

Lung function associated gene Integrator Complex subunit 12 regulates protein synthesis pathways

Background: Genetic studies of human lung function and Chronic Obstructive Pulmonary Disease have identified a highly significant and reproducible signal on 4q24. It remains unclear which of the two candidate genes within this locus may regulate lung function: GSTCD, a gene with unknown function, and/or INTS12, a member of the Integrator Complex which is currently thought to mediate 3'end processing of small nuclear RNAs.Results: We found that, in lung tissue, 4q24 polymorphisms associated with lung function correlate with INTS12 but not neighbouring GSTCD expression. In contrast to the previous reports in other species, we only observed a minor alteration of snRNA processing following INTS12 depletion. RNAseq analysis of knockdown cells instead revealed dysregulation of a core subset of genes relevant to airway biology and a robust downregulation of protein synthesis pathways. Consistent with this, protein translation was decreased in INTS12 knockdown cells. In addition, ChIPseq experiments demonstrated INTS12 binding throughout the genome, which was enriched in transcriptionally active regions. Finally, we defined the INTS12 regulome which includes genes belonging to the protein synthesis pathways.Conclusion: INTS12 has functions beyond the canonical snRNA processing. We show that it regulates translation by regulating the expression of genes belonging to protein synthesis pathways. This study provides a detailed analysis of INTS12 activities on a genome-wide scale and contributes to the biology behind the genetic association for lung function at 4q24.</p