Mission and space vehicle sizing data for a chemical propulsion/aerobraking option

Sizing data is presented for various combinations of Mars missions and chemical-propulsion/aerobraking vehicles. Data is compared for vehicles utilizing opposition (2-year mission) and conjunction (3-year mission) trajectories for 1999 and 2001 opportunities, for various sizes of vehicles. Payload capabilities for manned and unmanned missions vehicles and for propulsive-braking and aerobraking cases are shown. The effect of scaling up a reference vehicle is compared to the case of utilizing two identical vehicles, for growth in payload capability. The rate of cumulative build up of weight on the surface of Mars is examined for various mission/vehicle combinations, and is compared to the landed-weight requirements for sortie missions, moving-base missions, and fixed-base missions. Also, the required buildup of weight in low Earth orbit (LEO) for various mission/vehicle combinations is presented and discussed

Characterizing and reassembling the COPD and ILD transcriptome using RNA-Seq

Chronic Obstructive Pulmonary Disease (COPD) is the 3rd leading cause of death in the US, and idiopathic pulmonary fibrosis (IPF), a type of Interstitial Lung Disease (ILD), is a fast acting, irreversible disease that leads to mortality within 3-5 years. RNA-sequencing provides the opportunity to quantitatively examine the sequences of millions mRNAs, and offers the potential to gain unprecedented insights into the structure of chronic non-malignant lung disease transcriptome. By identifying changes in splicing and novel loci expression associated with disease, we may be able to gain a better understanding of their pathogenesis, identify novel disease-specific biomarkers, and find better targets for therapy. Using RNA-seq data that our group generated on 281 human lung tissue samples (47=Control, 131=COPD, 103=ILD), I initially defined the transcriptomic landscape of lung tissue by identifying which genes were expressed in each tissue sample. I used a mixture model to separate genes into reliable and not reliable expression. Next, I employed reads that overlapped splice junctions in a linear model interaction term to identify disease-specific differential splicing. I identified alternatively spliced genes between control and disease tissues and validated three (PDGFA, NUMB, SCEL) of these genes with qPCR and nanostring (a hybridization-based barcoding technique used to quantify transcripts). Finally, I implemented and improved a pipeline to perform transcriptome assembly using Cufflinks that led to the identification of 1,855 novel loci that did not overlap with UCSC, Vega, and Ensembl annotations. The loci were classified into potential coding and non-coding loci (191 and 1,664, respectively). Expression analysis revealed that there were 120 IPF-associated and 10 emphysema-associated differentially expressed (q < 0.01) novel loci. RNA-seq provides a high-resolution transcript-level view of the pulmonary transcriptome and its modification in lung disease. It has enabled a new understanding of the lung transcriptome structure because it measures not only the transcripts we know but also the ones we do not know. The approaches and improvements I have employed have identified these novel targets and make possible further downstream functional analysis that could identify better targets for therapy and lead to an even better understanding of chronic lung disease pathogenesis.2031-01-01T00:00:00

FPGA-Based CNN Inference Accelerator Synthesized from Multi-Threaded C Software

A deep-learning inference accelerator is synthesized from a C-language software program parallelized with Pthreads. The software implementation uses the well-known producer/consumer model with parallel threads interconnected by FIFO queues. The LegUp high-level synthesis (HLS) tool synthesizes threads into parallel FPGA hardware, translating software parallelism into spatial parallelism. A complete system is generated where convolution, pooling and padding are realized in the synthesized accelerator, with remaining tasks executing on an embedded ARM processor. The accelerator incorporates reduced precision, and a novel approach for zero-weight-skipping in convolution. On a mid-sized Intel Arria 10 SoC FPGA, peak performance on VGG-16 is 138 effective GOPS

Investigating the Relationship Between Peripheral Microvascular and Cerebral Vascular Vasodilator Function in College-Aged Individuals

Peripheral vascular dysfunction is predictive of numerous conditions including hypertension, type II diabetes, and coronary heart disease. Likewise, impaired cerebral vascular function is linked to neurocognitive conditions including Alzheimer’s disease and related dementias, cognitive dysfunction, and stroke. Previous research has reported no relationship between peripheral and extracranial macrovascular function within individuals. However, to our knowledge, no studies have examined the relationship between peripheral microvascular and cerebral vascular function within individuals. PURPOSE: To test the hypothesis that peripheral microvascular and cerebral vascular function would not be similar within young healthy individuals. METHODS: Data was collected in 59 participants (45 female; age: 22±5 yr; BMI: 24±4 kg·m-2). Peripheral macro- and microvascular function were assessed as brachial artery flow-mediated dilation (FMD) and peak blood velocity during post-occlusive reactive hyperemia (Vmean Peak), respectively. Briefly, brachial artery diameter and blood velocity were continuously measured (Doppler ultrasound) throughout a 2 min baseline, 5 min suprasystolic forearm cuff occlusion, and 3 min recovery. Cerebral vascular function was assessed as the % increase in middle cerebral artery (MCA) vascular conductance (CVCi = MCA blood velocity/mean arterial pressure) during hypercapnia (Δ end-tidal CO2 = 11±2 mmHg) induced by breathing 6% CO2 (N=39) or rebreathing expired air (N=20). RESULTS: Peripheral macrovascular function assessed as FMD was 6.9±3.9%, peripheral microvascular function assessed as Vmean Peak was 77±19 cm·s-1, and cerebral vascular function assessed as %CVCi during hypercapnia was 29±11%. There was no significant correlation between FMD and %CVCi (r=0.15, P=0.26) or Vmean Peak and %CVCi (r=-0.04, P=0.77). CONCLUSION: These preliminary data suggest that, in young, healthy individuals, there is not a significant relationship between peripheral macro- or microvascular function and cerebral vascular function. Future research should determine if relationships emerge with advancing age or conditions that are associated with overt vascular dysfunction

Whittier Alliance Home-Based Business Results.

Conducted on behalf of Whittier Alliance, 612/871-7756. Sponsored by Neighborhood Planning for Community Revitalization, Center for Urban and Regional Affairs, University of Minnesota

Genetic Variation and Antioxidant Response Gene Expression in the Bronchial Airway Epithelium of Smokers at Risk for Lung Cancer

Prior microarray studies of smokers at high risk for lung cancer have demonstrated that heterogeneity in bronchial airway epithelial cell gene expression response to smoking can serve as an early diagnostic biomarker for lung cancer. As a first step in applying functional genomic analysis to population studies, we have examined the relationship between gene expression variation and genetic variation in a central molecular pathway (NRF2-mediated antioxidant response) associated with smoking exposure and lung cancer. We assessed global gene expression in histologically normal airway epithelial cells obtained at bronchoscopy from smokers who developed lung cancer (SC, n=20), smokers without lung cancer (SNC, n=24), and never smokers (NS, n=8). Functional enrichment analysis showed that the NRF2-mediated, antioxidant response element (ARE)-regulated genes, were significantly lower in SC, when compared with expression levels in SNC. Importantly, we found that the expression of MAFG (a binding partner of NRF2) was correlated with the expression of ARE genes, suggesting MAFG levels may limit target gene induction. Bioinformatically we identified single nucleotide polymorphisms (SNPs) in putative ARE genes and to test the impact of genetic variation, we genotyped these putative regulatory SNPs and other tag SNPs in selected NRF2 pathway genes. Sequencing MAFG locus, we identified 30 novel SNPs and two were associated with either gene expression or lung cancer status among smokers. This work demonstrates an analysis approach that integrates bioinformatics pathway and transcription factor binding site analysis with genotype, gene expression and disease status to identify SNPs that may be associated with individual differences in gene expression and/or cancer status in smokers. These polymorphisms might ultimately contribute to lung cancer risk via their effect on the airway gene expression response to tobacco-smoke exposure.Intramural Research Program of the National Institute of Environmental Health Sciences; National Institutes of Health (Z01 ES100475, U01ES016035, R01CA124640