Parameterizations of the linear energy transfer spectrum for the CRaTER instrument during the LRO mission

[1] The Cosmic Ray Telescope for the Effects of Radiation (CRaTER) instrument was launched as part of the Lunar Reconnaissance Orbiter (LRO) spacecraft in June 2009. Its purpose is to measure the linear energy transfer (LET) spectrum in lunar orbit as an aid in determining risks to human crews on future lunar missions. Part of the preparations for the mission involved estimating the LET spectrum for the anticipated environment that the instrument is likely to see during the 1 year operational phase of the LRO mission. Detailed estimates of LET spectra in the six silicon detectors and two tissue equivalent plastic segments were made using the beta version of the HETC-HEDS Monte Carlo transport code. Tables of LET in each detector component, for incident particle elemental species from hydrogen through iron, were carried out at incident particle energies from 20 MeV per nucleon to 3 GeV per nucleon. The LET values in these tables have been parameterized by elemental species and energy for ease in quickly and accurately estimating the LET response for any input solar or galactic cosmic ray spectrum likely to be encountered during the lifetime of the instrument. The parameterized LET values are in excellent agreement with the HETC-HEDS calculations. Typical differences are on the order of a few percent. These parameterizations will also be useful in validation studies of the Earth-Moon-Mars Radiation Environment Module using CRaTER measurements in lunar orbit

Earth‐Moon‐Mars Radiation Environment Module framework

[1] We are preparing to return humans to the Moon and setting the stage for exploration to Mars and beyond. However, it is unclear if long missions outside of low-Earth orbit can be accomplished with acceptable risk. The central objective of a new modeling project, the Earth-Moon-Mars Radiation Exposure Module (EMMREM), is to develop and validate a numerical module for characterizing time-dependent radiation exposure in the Earth-Moon-Mars and interplanetary space environments. EMMREM is being designed for broad use by researchers to predict radiation exposure by integrating over almost any incident particle distribution from interplanetary space. We detail here the overall structure of the EMMREM module and study the dose histories of the 2003 Halloween storm event and a June 2004 event. We show both the event histories measured at 1 AU and the evolution of these events at observer locations beyond 1 AU. The results are compared to observations at Ulysses. The model allows us to predict how the radiation environment evolves with radial distance from the Sun. The model comparison also suggests areas in which our understanding of the physics of particle propagation and energization needs to be improved to better forecast the radiation environment. Thus, we introduce the suite of EMMREM tools, which will be used to improve risk assessment models so that future human exploration missions can be adequately planned for

Lunar radiation environment and space weathering from the Cosmic Ray Telescope for the Effects of Radiation (CRaTER)

[1] The Cosmic Ray Telescope for the Effects of Radiation (CRaTER) measures linear energy transfer by Galactic Cosmic Rays (GCRs) and Solar Energetic Particles (SEPs) on the Lunar Reconnaissance Orbiter (LRO) Mission in a circular, polar lunar orbit. GCR fluxes remain at the highest levels ever observed during the space age. One of the largest SEP events observed by CRaTER during the LRO mission occurred on June 7, 2011. We compare model predictions by the Earth-Moon-Mars Radiation Environment Module (EMMREM) for both dose rates from GCRs and SEPs during this event with results from CRaTER. We find agreement between these models and the CRaTER dose rates, which together demonstrate the accuracy of EMMREM, and its suitability for a real-time space weather system. We utilize CRaTER to test forecasts made by the Relativistic Electron Alert System for Exploration (REleASE), which successfully predicts the June 7th event. At the maximum CRaTER-observed GCR dose rate (∼11.7 cGy/yr where Gy is a unit indicating energy deposition per unit mass, 1 Gy = 1 J/kg), GCRs deposit ∼88 eV/molecule in water over 4 billion years, causing significant change in molecular composition and physical structure (e.g., density, color, crystallinity) of water ice, loss of molecular hydrogen, and production of more complex molecules linking carbon and other elements in the irradiated ice. This shows that space weathering by GCRs may be extremely important for chemical evolution of ice on the Moon. Thus, we show comprehensive observations from the CRaTER instrument on the Lunar Reconnaissance Orbiter that characterizes the radiation environment and space weathering on the Moon

Substrate Effect on the High Temperature Oxidation Behavior of a Pt-modified Aluminide Coating. Part II: Long-term Cyclic-oxidation Tests at 1,050 C

This second part of a two-part study is devoted to the effect of the substrate on the long-term, cyclic-oxidation behavior at 1,050 C of RT22 industrial coating deposited on three Ni-base superalloys (CMSX-4, SCB, and IN792). Cyclicoxidation tests at 1,050 C were performed for up to 58 cycles of 300 h (i.e., 17,400 h of heating at 1,050 C). For such test conditions, interdiffusion between the coating and its substrate plays a larger role in the damage process of the system than during isothermal tests at 900, 1,050, and 1,150 C for 100 h and cyclicoxidation tests at 900 C which were reported in part I [N. Vialas and D. Monceau, Oxidation of Metals 66, 155 (2006)]. The results reported in the present paper show that interdiffusion has an important effect on long-term, cyclic-oxidation resistance, so that clear differences can be observed between different superalloys protected with the same aluminide coating. Net-mass-change (NMC) curves show the better cyclic-oxidation behavior of the RT22/IN792 system whereas uncoated CMSX-4 has the best cyclic-oxidation resistance among the three superalloys studied. The importance of the interactions between the superalloy substrate and its coating is then demonstrated. The effect of the substrate on cyclic-oxidation behavior is related to the extent of oxide scale spalling and to the evolution of microstructural features of the coatings tested. SEM examinations of coating surfaces and cross sections show that spalling on RT22/CMSX-4 and RT22/SCB was favored by the presence of deep voids localized at the coating/oxide interface. Some of these voids can act as nucleation sites for scale spallation. The formation of such interfacial voids was always observed when the b to c0 transformation leads to the formation of a two-phase b/c0 layer in contact with the alumina scale. On the contrary, no voids were observed in RT22/IN792, since this b to c0 transformation occurs gradually by an inward transformation of b leading to the formation of a continuous layer of c0 phase, parallel to the metal/scale interface

Bayesian inference of biochemical kinetic parameters using the linear noise approximation

Background Fluorescent and luminescent gene reporters allow us to dynamically quantify changes in molecular species concentration over time on the single cell level. The mathematical modeling of their interaction through multivariate dynamical models requires the deveopment of effective statistical methods to calibrate such models against available data. Given the prevalence of stochasticity and noise in biochemical systems inference for stochastic models is of special interest. In this paper we present a simple and computationally efficient algorithm for the estimation of biochemical kinetic parameters from gene reporter data. Results We use the linear noise approximation to model biochemical reactions through a stochastic dynamic model which essentially approximates a diffusion model by an ordinary differential equation model with an appropriately defined noise process. An explicit formula for the likelihood function can be derived allowing for computationally efficient parameter estimation. The proposed algorithm is embedded in a Bayesian framework and inference is performed using Markov chain Monte Carlo. Conclusion The major advantage of the method is that in contrast to the more established diffusion approximation based methods the computationally costly methods of data augmentation are not necessary. Our approach also allows for unobserved variables and measurement error. The application of the method to both simulated and experimental data shows that the proposed methodology provides a useful alternative to diffusion approximation based methods

Biclustering reveals potential knee OA phenotypes in exploratory analyses: Data from the Osteoarthritis Initiative

Objective To apply biclustering, a methodology originally developed for analysis of gene expression data, to simultaneously cluster observations and clinical features to explore candidate phenotypes of knee osteoarthritis (KOA) for the first time. Methods Data from the baseline Osteoarthritis Initiative (OAI) visit were cleaned, transformed, and standardized as indicated (leaving 6461 knees with 86 features). Biclustering produced submatrices of the overall data matrix, representing similar observations across a subset of variables. Statistical validation was determined using the novel SigClust procedure. After identifying biclusters, relationships with key outcome measures were assessed, including progression of radiographic KOA, total knee arthroplasty, loss of joint space width, and worsening Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, over 96 months of follow-up. Results The final analytic set included 6461 knees from 3330 individuals (mean age 61 years, mean body mass index 28 kg/m2, 57% women and 86% White). We identified 6 mutually exclusive biclusters characterized by different feature profiles at baseline, particularly related to symptoms and function. Biclusters represented overall better (#1), similar (#2, 3, 6), and poorer (#4, 5) prognosis compared to the overall cohort of knees, respectively. In general, knees in biclusters #4 and 5 had more structural progression (based on Kellgren-Lawrence grade, total knee arthroplasty, and loss of joint space width) but tended to have an improvement in WOMAC pain scores over time. In contrast, knees in bicluster #1 had less incident and progressive KOA, fewer total knee arthroplasties, less loss of joint space width, and stable pain scores compared with the overall cohort. Significance We identified six biclusters within the baseline OAI dataset which have varying relationships with key outcomes in KOA. Such biclusters represent potential phenotypes within the larger cohort and may suggest subgroups at greater or lesser risk of progression over time

Racial Differences in Knee Osteoarthritis Pain: Potential Contribution of Occupational and Household Tasks

We examined whether occupational and household tasks contributed to differences in pain between African Americans and whites with radiographic knee osteoarthritis (OA)

UK consensus recommendations for clinical management of cancer risk for women with germline pathogenic variants in cancer predisposition genes: RAD51C, RAD51D, BRIP1 and PALB2.

Germline pathogenic variants (GPVs) in the cancer predisposition genes BRCA1, BRCA2, MLH1, MSH2, MSH6, BRIP1, PALB2, RAD51D and RAD51C are identified in approximately 15% of patients with ovarian cancer (OC). While there are clear guidelines around clinical management of cancer risk in patients with GPV in BRCA1, BRCA2, MLH1, MSH2 and MSH6, there are few guidelines on how to manage the more moderate OC risk in patients with GPV in BRIP1, PALB2, RAD51D and RAD51C, with clinical questions about appropriateness and timing of risk-reducing gynaecological surgery. Furthermore, while recognition of RAD51C and RAD51D as OC predisposition genes has been established for several years, an association with breast cancer (BC) has only more recently been described and clinical management of this risk has been unclear. With expansion of genetic testing of these genes to all patients with non-mucinous OC, new data on BC risk and improved estimates of OC risk, the UK Cancer Genetics Group and CanGene-CanVar project convened a 2-day meeting to reach a national consensus on clinical management of BRIP1, PALB2, RAD51D and RAD51C carriers in clinical practice. In this paper, we present a summary of the processes used to reach and agree on a consensus, as well as the key recommendations from the meeting

Composite measures of multi-joint symptoms, but not of radiographic osteoarthritis, are associated with functional outcomes: the Johnston County Osteoarthritis Project

To determine associations between multiple joint symptoms and radiographic osteoarthritis (rOA) and functional outcomes

A cross-institutional analysis of the effects of broadening trainee professional development on research productivity

© The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Brandt, P. D., Sturzenegger Varvayanis, S., Baas, T., Bolgioni, A. F., Alder, J., Petrie, K. A., Dominguez, I., Brown, A. M., Stayart, C. A., Singh, H., Van Wart, A., Chow, C. S., Mathur, A., Schreiber, B. M., Fruman, D. A., Bowden, B., Wiesen, C. A., Golightly, Y. M., Holmquist, C. E., Arneman, D., Hall, J. D., Hyman, L. E., Gould, K. L., Chalkley, R., Brennwald, P. J., Layton, R. L. A cross-institutional analysis of the effects of broadening trainee professional development on research productivity. Plos Biology, 19(7), (2021): e3000956, https://doi.org/10.1371/journal.pbio.3000956.PhD-trained scientists are essential contributors to the workforce in diverse employment sectors that include academia, industry, government, and nonprofit organizations. Hence, best practices for training the future biomedical workforce are of national concern. Complementing coursework and laboratory research training, many institutions now offer professional training that enables career exploration and develops a broad set of skills critical to various career paths. The National Institutes of Health (NIH) funded academic institutions to design innovative programming to enable this professional development through a mechanism known as Broadening Experiences in Scientific Training (BEST). Programming at the NIH BEST awardee institutions included career panels, skill-building workshops, job search workshops, site visits, and internships. Because doctoral training is lengthy and requires focused attention on dissertation research, an initial concern was that students participating in additional complementary training activities might exhibit an increased time to degree or diminished research productivity. Metrics were analyzed from 10 NIH BEST awardee institutions to address this concern, using time to degree and publication records as measures of efficiency and productivity. Comparing doctoral students who participated to those who did not, results revealed that across these diverse academic institutions, there were no differences in time to degree or manuscript output. Our findings support the policy that doctoral students should participate in career and professional development opportunities that are intended to prepare them for a variety of diverse and important careers in the workforce.Funding sources included the Common Fund NIH Director’s Biomedical Research Workforce Innovation Broadening Experiences in Scientific Training (BEST) Award. The following institutional NIH BEST awards (alphabetical by institution) included: DP7OD020322 (Boston University; AFB, ID, BMS, LEH); DP7OD020316 (University of Chicago; CAS); DP7OD018425 (Cornell University; SSV); DP7OD018428 (Virginia Polytechnic Institute; AVW, BB); DP7OD020314 (Rutgers University; JA); DP7OD020315 (University of Rochester; TB); DP7OD018423 (Vanderbilt University; KAP, AMB, KLG, RC); DP7OD020321 (University of California, Irvine; HS, DAF); DP7OD020317 (University of North Carolina, Chapel Hill; PDB, PJB, RLL); DP7 OD018427 (Wayne State University; CSC, AM). National Institutes of Health (NIH) General Medical Sciences - Science of Science Policy Approach to Analyzing and Innovating the Biomedical Research Enterprise (SCISIPBIO) Award (GM-19-011) - 1R01GM140282-01 (University of North Carolina at Chapel Hill; RLL, PDB, PJB)