Advanced aeroservoelastic stabilization techniques for hypersonic flight vehicles

Advanced high performance vehicles, including Single-Stage-To-Orbit (SSTO) hypersonic flight vehicles, that are statically unstable, require higher bandwidth flight control systems to compensate for the instability resulting in interactions between the flight control system, the engine/propulsion dynamics, and the low frequency structural modes. Military specifications, such as MIL-F-9490D and MIL-F-87242, tend to limit treatment of structural modes to conventional gain stabilization techniques. The conventional gain stabilization techniques, however, introduce low frequency effective time delays which can be troublesome from a flying qualities standpoint. These time delays can be alleviated by appropriate blending of gain and phase stabilization techniques (referred to as Hybrid Phase Stabilization or HPS) for the low frequency structural modes. The potential of using HPS for compensating structural mode interaction was previously explored. It was shown that effective time delay was significantly reduced with the use of HPS; however, the HPS design was seen to have greater residual response than a conventional gain stablized design. Additional work performed to advance and refine the HPS design procedure, to further develop residual response metrics as a basis for alternative structural stability specifications, and to develop strategies for validating HPS design and specification concepts in manned simulation is presented. Stabilization design sensitivity to structural uncertainties and aircraft-centered requirements are also assessed

Tissue enrichment analysis for C. elegans genomics

Background: Over the last ten years, there has been explosive development in methods for measuring gene expression. These methods can identify thousands of genes altered between conditions, but understanding these datasets and forming hypotheses based on them remains challenging. One way to analyze these datasets is to associate ontologies (hierarchical, descriptive vocabularies with controlled relations between terms) with genes and to look for enrichment of specific terms. Although Gene Ontology (GO) is available for Caenorhabditis elegans, it does not include anatomical information. Results: We have developed a tool for identifying enrichment of C. elegans tissues among gene sets and generated a website GUI where users can access this tool. Since a common drawback to ontology enrichment analyses is its verbosity, we developed a very simple filtering algorithm to reduce the ontology size by an order of magnitude. We adjusted these filters and validated our tool using a set of 30 gold standards from Expression Cluster data in WormBase. We show our tool can even discriminate between embryonic and larval tissues and can even identify tissues down to the single-cell level. We used our tool to identify multiple neuronal tissues that are down-regulated due to pathogen infection in C. elegans. Conclusions: Our Tissue Enrichment Analysis (TEA) can be found within WormBase, and can be downloaded using Python’s standard pip installer. It tests a slimmed-down C. elegans tissue ontology for enrichment of specific terms and provides users with a text and graphic representation of the results

Two new functions in the WormBase Enrichment Suite

Genome-wide experiments routinely generate large amounts of data that can be hard to interpret biologically. A common approach to interpreting these results is to employ enrichment analyses of controlled languages, known as ontologies, that describe various biological parameters such as gene molecular or biological function. In C. elegans, three distinct ontologies, the Gene Ontology (GO), Anatomy Ontology (AO), and the Worm Phenotype Ontology (WPO) are used to annotate gene function, expression and phenotype, respectively (Ashburner et al. 2000; Lee and Sternberg, 2003; Schindelman et al. 2011). Previously, we developed software to test datasets for enrichment of anatomical terms, called the Tissue Enrichment Analysis (TEA) tool (Angeles-Albores and Sternberg, 2016). Using the same hypergeometric statistical method, we extend enrichment testing to include WPO and GO, offering a unified approach to enrichment testing in C. elegans. The WormBase Enrichment Suite can be accessed via a user-friendly interface at http://www.wormbase.org/tools/enrichment/tea/tea.cgi. To validate the tools, we analyzed a previously published extracellular vesicle (EV)-releasing neuron (EVN) signature gene set derived from dissociated ciliated EV neurons (Wang et al. 2015) using WormBase Enrichment Suite based on the WS262 WormBase release. TEA correctly identified the CEM, hook sensillum and IL2 neuron as enriched tissues. The top phenotype associated with the EVN signature was chemosensory behavior. Gene Ontology enrichment analysis showed that cell projection and cell body were the most enriched cellular components in this gene set, followed by the biological processes neuropeptide signaling pathway and vesicle localization further down. The tutorial script used to generate the figure above can be viewed at: https://github.com/dangeles/TissueEnrichmentAnalysis/blob/master/tutorial/Tutorial.ipynb The addition of Gene Enrichment Analysis (GEA) and Phenotype Enrichment Analysis (PEA) to WormBase marks an important step towards a unified set of analyses that can help researchers to understand genomic datasets. These enrichment analyses will allow the community to fully benefit from the data curation ongoing at WormBase

A staged approach with vincristine, adriamycin, and dexamethasone followed by bortezomib, thalidomide, and dexamethasone before autologous hematopoietic stem cell transplantation in the treatment of newly diagnosed multiple myeloma

Bortezomib-based regimens have significant activities in multiple myeloma (MM). In this study, we tested the efficacy of a total therapy with a staged approach where newly diagnosed MM patients received vincristine/adriamycin/dexamethsone (VAD). VAD-sensitive patients (≥75% paraprotein reduction) received autologous hematopoietic stem cell transplantation (auto-HSCT), whereas less VAD-sensitive patients (<75% paraprotein reduction) received bortezomib/thalidomide/dexamethasone (VTD) for further cytoreduction prior to auto-HSCT. On an intention-to-treat analysis, a progressive increase of complete remission (CR) rates was observed, with cumulative CR rates of 48% after HSCT. Seven patients progressed leading to three fatalities, of which two had central nervous system disease. The 3-year overall survival and event-free survival were 75.1% and 48.3%, respectively. Six patients developed oligoclonal reconstitution with new paraproteins. In the absence of anticoagulant prophylaxis, no patients developed deep vein thrombosis. The staged application of VAD+/–VTD/auto-HSCT resulted in an appreciable response rate and promising survivals. Our approach reduced the use of bortezomib without compromising the ultimate CR rate and is of financial significance for less affluent communities

Transcription Factor Nrf1 Mediates the Proteasome Recovery Pathway after Proteasome Inhibition in Mammalian Cells

In Saccharomyces cerevisiae, chemical or genetic inhibition of proteasome activity induces new proteasome synthesis promoted by the transcription factor RPN4. This ensures that proteasome activity is matched to demand. This transcriptional feedback loop is conserved in mammals, but its molecular basis is not understood. Here, we report that nuclear factor erythroid-derived 2-related factor 1 (Nrf1), a transcription factor of the cap “n” collar basic leucine zipper family, but not the related Nrf2, is necessary for induced proteasome gene transcription in mouse embryonic fibroblasts (MEFs). Promoter-reporter assays revealed the importance of antioxidant response elements in Nrf1-mediated upregulation of proteasome subunit genes. Nrf1^(−/−) MEFs were impaired in the recovery of proteasome activity after transient treatment with the covalent proteasome inhibitor YU101, and knockdown of Nrf1 in human cancer cells enhanced cell killing by YU101. Taken together, our results suggest that Nrf1-mediated proteasome homeostasis could be an attractive target for therapeutic intervention in cancer

Improvement of myocardial perfusion reserve detected by cardiovascular magnetic resonance after direct endomyocardial implantation of autologous bone marrow cells in patients with severe coronary artery disease

<p>Abstract</p> <p>Background</p> <p>Recent studies suggested that bone marrow (BM) cell implantation in patients with severe chronic coronary artery disease (CAD) resulted in modest improvement in symptoms and cardiac function. This study sought to investigate the functional changes that occur within the chronic human ischaemic myocardium after direct endomyocardial BM cells implantation by cardiovascular magnetic resonance (CMR).</p> <p>Methods and Results</p> <p>We compared the interval changes of left ventricular ejection fraction (LVEF), myocardial perfusion reserve and the extent of myocardial scar by using late gadolinium enhancement CMR in 12 patients with severe CAD. CMR was performed at baseline and at 6 months after catheter-based direct endomyocardial autologous BM cell (n = 12) injection to viable ischaemic myocardium as guided by electromechanical mapping. In patients randomized to receive BM cell injection, there was significant decrease in percentage area of peri-infarct regions (-23.6%, <it>P </it>= <it>0.04</it>) and increase in global LVEF (+9.0%, <it>P </it>= <it>0.02</it>), the percentage of regional wall thickening (+13.1%, <it>P= 0.04</it>) and MPR (+0.25%, <it>P </it>= <it>0.03</it>) over the target area at 6-months compared with baseline.</p> <p>Conclusions</p> <p>Direct endomyocardial implantation of autologous BM cells significantly improved global LVEF, regional wall thickening and myocardial perfusion reserve, and reduced percentage area of peri-infarct regions in patients with severe CAD.</p

Improved navigator-gated motion compensation in cardiac MR using additional constraint of magnitude of motion-corrupted data

Background. In conventional prospective respiratory navigator (NAV) acquisitions, 40-60% of the acquired data are discarded resulting in low efficiency and long scan times [1,2].Compressed-sensing Motion Compensation (CosMo) has a shorter fixed scan time by acquiring the full inner k-space and estimating the NAV-rejected outer k-space lines [3]. Respiratory motion will mainly manifest itself as phase variation in the acquired k-space data. We sought to determine if the addition of the magnitude of the rejected k-space lines as a constraint in image reconstruction will improve the performance of CosMo. Methods. To investigate the variability of the magnitude of kspace lines at different respiratory phases, free-breathing, ECG-triggered, targeted right coronary images with multiple averages were acquired from 10 healthy adult subjects. Magnitude variability was investigated quantitatively by calculating the cross-correlation between accepted and rejected k-space lines. CosMo was implemented retrospectively on one acquisition from each subject. The inner k-space (31 ky by 7 kz lines) was filled with lines acquired within the 5mm gating window from all acquisitions. The outer kspace was then filled only with lines from the first average acquired within the 5 mm gating window, resulting in an undersampled k-space with a fully sampled center. For reliable image reconstruction with CosMo, 10-20% of the inner k-space must be fully-sampled. The missing outer k-space lines were then estimated using LOST with an additional magnitude constraint within each estimation iteration or in the final iteration for each coil [4]. The results were compared with prospective NAVgating with a gating window of 5 mm and CosMo reconstruction without the magnitude constraint. Results. Figure 1 shows the cross-correlation between the accepted and worst rejected k-space lines for each position. The correlation is close to 1 at the center of kspace where the majority of image information is contained, indicating low variability in magnitude information at different respiratory phases. Figure 2 shows right coronary images acquired using a) fully-sampled, 5-mm gated data, b) the original CosMo, and CosMo with the additional magnitude constraint c) inside each iteration and d) in the final iteration. The relative signal-to-noise in the left ventricle blood pool is: $30.71 \pm 6.5; 40.32 \pm 14.2; 53.9 \pm 26.8; 56.8 \pm 25.9$ for each reconstruction, respectively. Significant differences (p<0.05) are present for all measurements except between the original CosMo and the CosMo image with the magnitude constraint in each iteration (p=0.09). Conclusions. The addition of the magnitude of rejected lines, readily available in all navigator-gated scans, as a constraint in CosMo results in improved image quality as measured by relative SNR. Funding. NIH R01EB008743-01A2

Directly Comparing Handoff Protocols for Pediatric Hospitalists

BACKGROUND AND OBJECTIVES: Handoff protocols are often developed by brainstorming and consensus, and few are directly compared. We hypothesized that a handoff protocol (Flex 11) developed using a rigorous methodology would be more favorable in terms of clinicians’ attitudes, behaviors, cognitions, or time-on-task when performing handoffs compared with a prevalent protocol (Situation Background Assessment Recommendation [SBAR]). METHODS: Using a between-groups, randomized control trial design (Flex 11 versus SBAR) during a pilot study in a simulated environment, 20 clinicians (13 attending physicians and 7 residents) received 3 patient handoffs from a standardized physician, managed the patients, and handed off the patients to the same standardized physician. Participants completed surveys assessing their attitudes and cognitions, and behaviors and handoff duration were assessed through observations. RESULTS: All data were analyzed using independent samples t tests. For attitudes, “ease of use” ratings were lower for SBAR participants than Flex 11 participants (P , .01), and “being helpful” ratings were lower for SBAR participants than Flex 11 participants (P 5 .02). For behaviors, results indicate no significant difference in the information acquired between the SBAR and Flex 11 protocols. However, SBAR participants gave significantly less information than Flex 11 participants (P , .01). For cognitions, SBAR and Flex 11 participants reported similar workload except for frustration. For handoff duration, there were no significant differences between the protocols (P 5 .36). CONCLUSIONS: The results suggest that Flex 11 is an efficient, beneficial tool in a simulated environment with pediatric clinicians. Future studies should evaluate this protocol in the inpatient setting

Two new functions in the WormBase Enrichment Suite

Genome-wide experiments routinely generate large amounts of data that can be hard to interpret biologically. A common approach to interpreting these results is to employ enrichment analyses of controlled languages, known as ontologies, that describe various biological parameters such as gene molecular or biological function. In C. elegans, three distinct ontologies, the Gene Ontology (GO), Anatomy Ontology (AO), and the Worm Phenotype Ontology (WPO) are used to annotate gene function, expression and phenotype, respectively (Ashburner et al. 2000; Lee and Sternberg, 2003; Schindelman et al. 2011). Previously, we developed software to test datasets for enrichment of anatomical terms, called the Tissue Enrichment Analysis (TEA) tool (Angeles-Albores and Sternberg, 2016). Using the same hypergeometric statistical method, we extend enrichment testing to include WPO and GO, offering a unified approach to enrichment testing in C. elegans. The WormBase Enrichment Suite can be accessed via a user-friendly interface at http://www.wormbase.org/tools/enrichment/tea/tea.cgi. To validate the tools, we analyzed a previously published extracellular vesicle (EV)-releasing neuron (EVN) signature gene set derived from dissociated ciliated EV neurons (Wang et al. 2015) using WormBase Enrichment Suite based on the WS262 WormBase release. TEA correctly identified the CEM, hook sensillum and IL2 neuron as enriched tissues. The top phenotype associated with the EVN signature was chemosensory behavior. Gene Ontology enrichment analysis showed that cell projection and cell body were the most enriched cellular components in this gene set, followed by the biological processes neuropeptide signaling pathway and vesicle localization further down. The tutorial script used to generate the figure above can be viewed at: https://github.com/dangeles/TissueEnrichmentAnalysis/blob/master/tutorial/Tutorial.ipynb The addition of Gene Enrichment Analysis (GEA) and Phenotype Enrichment Analysis (PEA) to WormBase marks an important step towards a unified set of analyses that can help researchers to understand genomic datasets. These enrichment analyses will allow the community to fully benefit from the data curation ongoing at WormBase

Neurological Soft Signs Are Not "Soft" in Brain Structure and Functional Networks: Evidence From ALE Meta-Analysis

Background: Neurological soft signs (NSS) are associated with schizophrenia and related psychotic disorders. NSS have been conventionally considered as clinical neurological signs without localized brain regions. However, recent brain imaging studies suggest that NSS are partly localizable and may be associated with deficits in specific brain areas. Method: We conducted an activation likelihood estimation meta-analysis to quantitatively review structural and functional imaging studies that evaluated the brain correlates of NSS in patients with schizophrenia and other psychotic disorders. Six structural magnetic resonance imaging (sMRI) and 15 functional magnetic -resonance imaging (fMRI) studies were included. Results: The results from meta-analysis of the sMRI studies-indicated that NSS were associated with atrophy of the precentral gyrus, the cerebellum, the inferior frontal gyrus, and the thalamus. The results from meta-analysis of the fMRI studies demonstrated that the NSS-related task was significantly associated with altered brain activation in the inferior frontal gyrus, bilateral putamen, the cerebellum, and the superior temporal gyrus. Conclusions: Ourfindings from both sMRI and fMRI meta-analyses further support the conceptualization of NSS as a manifestation of the &quot;cerebello-thalamo-prefrontal&quot; brain network model of schizophrenia and related psychotic disorders