Red Dragon: Low-cost Access to the Surface of Mars using Commercial Capabilities

We will discuss the feasibility of using a minimally-modified variant of a SpaceX Dragon capsule as a low-cost, large-capacity, near-term, Mars lander for scientific and human-precursor missions. We have been evaluating such a Red Dragon platform as an option for a Discovery Program mission concept. A Red Dragon lander has the potential to be low cost primarily because it would be derived from a routinely-flying spacecraft. Dragon is being developed to ferry cargo and crew to and from the International Space Station (ISS). The cargo variant is currently undergoing test flights, which will be followed by standard ISS cargo missions and, eventually, crewed flights. The human variant, unlike other Earth-return vehicles, appears to also have most of the capabilities necessary to land on Mars. In particular, it has a set of high-thrust, throttleable, storable bi-propellant Super- Draco engines integrated directly into the capsule which are intended for launch abort and powered landings on Earth. These thrusters suggest the possibility of a parachute-free, fully-propulsive deceleration at Mars from supersonic speeds to the surface. Concepts for large, human-relevant landers (see, e.g., [1]) also often employ supersonic retro-propulsion; Red Dragon's entry, descent, and landing approach would scale to those landers. Further, SpaceX's Falcon Heavy launch vehicle, currently under development and expected to have its first flight in 2013, will be capable of sending Dragon on a trajectory to Mars. We will discuss our motivation for exploring a Red Dragon lander, the primary technical questions which determine its feasibility, and the current results of our analysis. In particular, we will examine entry, descent, and landing (EDL) in detail. We will describe the modifications to Dragon necessary for interplanetary cruise, EDL, and operations on the Martian surface

Adaptable, Deployable Entry and Placement Technology (ADEPT) Overview of FY15 Accomplishments

ADEPT is an atmospheric entry architecture for missions to most planetary bodies with atmospheres: Current Technology development project funded under STMD Game Changing Development Program (FY12 start); stowed inside the launch vehicle shroud and deployed in space prior to entry; low ballistic coefficient (less than 50 kilograms per square meter) provides a benign deceleration and thermal environment to the payload; High-temperature ribs support three dimensional woven carbon fabric to generate drag and withstand high heating

Angiotensin-converting enzyme genotype and late respiratory complications of mustard gas exposure

<p>Abstract</p> <p>Background</p> <p>Exposure to mustard gas frequently results in long-term respiratory complications. However the factors which drive the development and progression of these complications remain unclear. The Renin Angiotensin System (RAS) has been implicated in lung inflammatory and fibrotic responses. Genetic variation within the gene coding for the Angiotensin Converting Enzyme (ACE), specifically the Insertion/Deletion polymorphism (I/D), is associated with variable levels of ACE and with the severity of several acute and chronic respiratory diseases. We hypothesized that the ACE genotype might influence the severity of late respiratory complications of mustard gas exposure.</p> <p>Methods</p> <p>208 Kurdish patients who had suffered high exposure to mustard gas, as defined by cutaneous lesions at initial assessment, in Sardasht, Iran on June 29 1987, underwent clinical examination, spirometric evaluation and ACE Insertion/Deletion genotyping in September 2005.</p> <p>Results</p> <p>ACE genotype was determined in 207 subjects. As a continuous variable, FEV₁% predicted tended to be higher in association with the D allele 68.03 ± 20.5%, 69.4 ± 21.4% and 74.8 ± 20.1% for II, ID and DD genotypes respectively. Median FEV₁% predicted was 73 and this was taken as a cut off between groups defined as having better or worse lung function. The ACE DD genotype was overrepresented in the better spirometry group (Chi²4.9 p = 0.03). Increasing age at the time of exposure was associated with reduced FEV₁%predicted (p = 0.001), whereas gender was not (p = 0.43).</p> <p>Conclusion</p> <p>The ACE D allele is associated with higher FEV₁% predicted when assessed 18 years after high exposure to mustard gas.</p

Ovarian carcinoma associated with pregnancy: A clinicopathologic analysis of 23 cases and review of the literature

<p>Abstract</p> <p>Background</p> <p>The aim of this study was to analyze and describe cases of ovarian cancer in pregnant women treated at our center and to review the literature concerned, and to discuss the rationale for therapy.</p> <p>Methods</p> <p>Twenty-Three patients of ovarian malignancies during pregnancy were treated at Vali- Asr Hospital between 1991 and 2002. Data on treatment and follow-up were evaluated.</p> <p>Results</p> <p>The incidence of ovarian carcinoma associated with pregnancy in our series was 0.083/1000 deliveries. Eleven (47.8%) were found with ovarian malignant germ cell tumors, five (21.7%) with low malignant potential tumors, four (17.4%) with invasive epithelial tumors, and three (13%) with sex cord stromal tumors. Seventeen (73.9%) of the patients were diagnosed in stage I and had complete remission. Five of the six in advanced stage died. The mean follow-up was 36.3 months. The prognosis was significantly related with stage and histological type (<it>P </it>< 0.05). Sixteen healthy live babies were recorded in this group, and two premature newborn died of respiratory distress syndrome. Chemotherapy was administered to 44% of the patients, in two cases during pregnancy. Overall survival at 5 years was 61%. In most of case conservative surgical treatment could be performed with adequate staging and debulking.</p> <p>Conclusion</p> <p>Early finding of ascitis by ultrasound and persistent large ovarian mass during pregnancy may be related to malignancy and advanced stage. Pregnant women in advanced stage of ovarian cancer seem to have poor prognosis.</p

Anxiety Disorders in Williams Syndrome Contrasted with Intellectual Disability and the General Population: A Systematic Review and Meta-Analysis

Individuals with specific genetic syndromes associated with intellectual disability (ID), such as Williams syndrome (WS), are at increased risk for developing anxiety disorders. A systematic literature review identified sixteen WS papers that could generate pooled prevalence estimates of anxiety disorders for WS. A meta-analysis compared these estimates with prevalence estimates for the heterogeneous ID population and the general population. Estimated rates of anxiety disorders in WS were high. WS individuals were four times more likely to experience anxiety than individuals with ID, and the risk was also heightened compared to the general population. The results provide further evidence of an unusual profile of high anxiety in WS

Inferring causal molecular networks: empirical assessment through a community-based effort

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess inferred molecular networks in a causal sense

Inferring causal molecular networks: empirical assessment through a community-based effort

Inferring molecular networks is a central challenge in computational biology. However, it has remained unclear whether causal, rather than merely correlational, relationships can be effectively inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge that focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. Using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective and incorporating known biology was generally advantageous. Additional sub-challenges considered time-course prediction and visualization. Our results constitute the most comprehensive assessment of causal network inference in a mammalian setting carried out to date and suggest that learning causal relationships may be feasible in complex settings such as disease states. Furthermore, our scoring approach provides a practical way to empirically assess the causal validity of inferred molecular networks