Sensitivity Analysis of the Change of Renal Stone Occurrence Rates in Astronauts Using Urine Chemistries

Changes in urine chemistry, during and post-flight, potentially alter the likelihood of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidences of renal stones in US astronauts exist and the question How much does this risk change with space flight? remains difficult to accurately quantify. Previous work by our group has illustrated the application of multi-factor deterministic and probabilistic modeling to assess the change in predicted likelihood of renal stone. Utilizing 1517 astronaut urine chemistries to inform the renal stone occurrence rate forecasting model, we performed a sensitivity analysis on urine chemistry components for their influence on predictions of renal stone size and rate of renal stone occurrence

Metabolite Fingerprinting in Transgenic Nicotiana tabacum Altered by the Escherichia coli Glutamate Dehydrogenase Gene

With about 200 000 phytochemicals in existence, identifying those of biomedical significance is a mammoth task. In the postgenomic era, relating metabolite fingerprints, abundances, and profiles to genotype is also a large task. Ion analysis using Fourier transformed ion cyclotron resonance mass spectrometry (FT-ICR-MS) may provide a high-throughput approach to measure genotype dependency of the inferred metabolome if reproducible techniques can be established. Ion profile inferred metabolite fingerprints are coproducts. We used FT-ICR-MS-derived ion analysis to examine gdhA (glutamate dehydrogenase (GDH; EC 1.4.1.1)) transgenic Nicotiana tabacum (tobacco) carrying out altered glutamate, amino acid, and carbon metabolisms, that fundamentally alter plant productivity. Cause and effect between gdhA expression, glutamate metabolism, and plant phenotypes was analyzed by [Formula: see text] labeling of amino acid fractions, and by FT-ICR-MS analysis of metabolites. The gdhA transgenic plants increased (13)N labeling of glutamate and glutamine significantly. FT-ICR-MS detected 2 012 ions reproducible in 2 to 4 ionization protocols. There were 283 ions in roots and 98 ions in leaves that appeared to significantly change abundance due to the measured GDH activity. About 58% percent of ions could not be used to infer a corresponding metabolite. From the 42% of ions that inferred known metabolites we found that certain amino acids, organic acids, and sugars increased and some fatty acids decreased. The transgene caused increased ammonium assimilation and detectable ion variation. Thirty-two compounds with biomedical significance were altered in abundance by GDH including 9 known carcinogens and 14 potential drugs. Therefore, the GDH transgene may lead to new uses for crops like tobacco

Challenges Associated with Semen Quality While Collecting Beef Bulls for Semen Freezing

Objective: The objective of this study was to evaluate the frequency of failure to freeze semen due to semen quality. Study Description: Semen collection data from 2008 to 2018 were obtained from the Kansas Artificial Breeding Services Unit and consisted of 14,750 ejaculates from bulls. Bulls were collected twice weekly on Mondays and Thursdays with an artificial vagina. Bulls not receptive to the artificial vagina were subject to electro-ejaculation. A single technician was responsible for all pre-freeze and post-thaw semen analysis. Ejaculates were required to meet quality standards for both progressive motility and morphology. Results: Over the ten years, 21% of ejaculates met all freezing quality standards, 11% of all ejaculates collected did not have a high enough motility to be considered satisfactory for a breeding soundness exam (BSE), and 63% of all ejaculates did not reach the motility quality threshold for freezing. Ejaculates from bulls ≤ 12 months of age produced ejaculates that would not meet satisfactory levels of a BSE 15% of the time. Ejaculates from bulls 13–18 months of age produced unsatisfactory ejaculates for motility for a BSE 6% of the time. When evaluating primary sperm abnormalities, 87% of ejaculates had less than 20% primary sperm abnormalities. Ejaculates from bulls ≤ 12 months of age produced the highest amount of ejaculates failing due to primary abnormalities with 24%, while bulls ≥ 31 months of age produced the least amount of ejaculates failing due to primary abnormalities at 10% of ejaculates. When evaluating total sperm abnormalities per ejaculate, 77% of ejaculates met the threshold of less than 30% total abnormalities. Ejaculates from bulls ≤ 12 months of age failed to meet the total sperm abnormality threshold 28% of the time. These results highlight one of the main difficulties of collecting freezing quality semen, in which semen meets the standards of normal spermatozoa but where most samples do not meet needs for progressive motility. The Bottom Line: Of over 14,000 collections, only 21% met all requirements for freezing semen, approximately 63% did not meet progressive motility freezing standards, and 11% did not meet the satisfactory level of a BSE

The Effect of Method of Collection and Number of Sequential Ejaculates on Semen Characteristics of Beef Bulls

Objective: The objective of this study was to determine the effect of collection method and number of sequential ejaculates on beef bull ejaculate characteristics. Study Description: Semen collection data from 2008 to 2018 was obtained from the Kansas Artificial Breeding Services Unit and consisted of 11,642 ejaculates from 906 bulls. Bulls were collected twice weekly on Mondays and Thursdays with an artificial vagina. Bulls not receptive to the artificial vagina were subject to electro-ejaculation. A single technician was responsible for all pre-freeze and post-thaw semen analysis. Ejaculates were required to meet quality standards. Results: Progressive motility before freezing was greater (P \u3c 0.0001) for bulls collected with electro-ejaculate compared to artificial vagina. Ejaculate volume for electro-ejaculate collections was greater (P \u3c 0.0001) than those collected with artificial vagina. Percent spermatozoa with secondary abnormalities was greater (P \u3c 0.05) for bulls collected with electro-ejaculate compared to artificial vagina. Concentration of spermatozoa/mL was less (P \u3c 0.0001) for bulls collected with an electro-ejaculate (514 × 106) compared to artificial vagina (617 × 106). Total number of straws frozen/ejaculate was less (P \u3c 0.001) for bulls collected with electro ejaculate (94) compared to artificial vagina (108). The number of ejaculates collected/day was significant for the percent of spermatozoa with secondary abnormalities (P \u3c 0.001). As ejaculate number/day increased, the concentration of spermatozoa decreased (713, 580, 535, and 434 × 106/mL, respectively; P \u3c 0.0001) and the number of straws frozen/ejaculate decreased (123, 107, 93, and 82, respectively; P \u3c 0.0001). The Bottom Line: Producers and collection facilities should work together to balance collection method and number of ejaculates collected/day to maximize production while maintaining semen quality

Comparison of the Integrated Medical Model Predictions to Real World ISS and STS Observations

The Human Research Program funded the development of the integrated medical model (IMM) to quantify the medical component of overall mission risk. The IMM uses Monte Carlo methodology to integrate space flight and ground medical data to assess the probability of mission medical outcomes and resource utilization. To determine the credibility of IMM output the IMM project team completed two validation studies that compare IMM output to observed medical events from a selection of Shuttle Transportation System (STS) and International Space Station (ISS) missions

Quantitative Validation of the Integrated Medical Model (IMM) for ISS Missions

Lifetime Surveillance of Astronaut Health (LSAH) provided observed medical event data on 33 ISS and 111 STS person-missions for use in further improving and validating the Integrated Medical Model (IMM). Using only the crew characteristics from these observed missions, the newest development version, IMM v4.0, will simulate these missions to predict medical events and outcomes. Comparing IMM predictions to the actual observed medical event counts will provide external validation and identify areas of possible improvement. In an effort to improve the power of detecting differences in this validation study, the total over each program ISS and STS will serve as the main quantitative comparison objective, specifically the following parameters: total medical events (TME), probability of loss of crew life (LOCL), and probability of evacuation (EVAC). Scatter plots of observed versus median predicted TMEs (with error bars reflecting the simulation intervals) will graphically display comparisons while linear regression will serve as the statistical test of agreement. Two scatter plots will be analyzed 1) where each point reflects a mission and 2) where each point reflects a condition-specific total number of occurrences. The coefficient of determination (R2) resulting from a linear regression with no intercept bias (intercept fixed at zero) will serve as an overall metric of agreement between IMM and the real world system (RWS). In an effort to identify as many possible discrepancies as possible for further inspection, the -level for all statistical tests comparing IMM predictions to observed data will be set to 0.1. This less stringent criterion, along with the multiple testing being conducted, should detect all perceived differences including many false positive signals resulting from random variation. The results of these analyses will reveal areas of the model requiring adjustment to improve overall IMM output, which will thereby provide better decision support for mission critical applications

The case for an HIV cure and how to get there

In light of the increasing global burden of new HIV infections, growing financial requirements, and shifting funding landscape, the global health community must accelerate the development and delivery of an HIV cure to complement existing prevention modalities. An effective curative intervention could prevent new infections, overcome the limitations of antiretroviral treatment, combat stigma and discrimination, and provide a sustainable financial solution for pandemic control. We propose steps to plan for an HIV cure now, including defining a target product profile and establishing the HIV Cure Africa Acceleration Partnership (HCAAP), a multidisciplinary public-private partnership that will catalyse and promote HIV cure research through diverse stakeholder engagement. HCAAP will convene stakeholders, including people living with HIV, at an early stage to accelerate the design, social acceptability, and rapid adoption of HIV-cure products

Integrated Medical Model Project - Overview and Summary of Historical Application

Introduction: The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project. Methods: Figure 1 [see document] illustrates the IMM modeling system and scenario process. As illustrated, the IMM computational architecture is based on Probabilistic Risk Assessment techniques. Nineteen assumptions and limitations define the IMM application domain. Scenario definitions include crew medical attributes and mission specific details. The IMM forecasts probabilities of loss of crew life (LOCL), evacuation (EVAC), quality time lost during the mission, number of medical resources utilized and the number and type of medical events by combining scenario information with in-flight, analog, and terrestrial medical information stored in the iMED. In addition, the metrics provide the integrated information necessary to estimate optimized in-flight medical kit contents under constraints of mass and volume or acceptable level of mission risk. Results and Conclusions: Historically, IMM simulations support Science and Technology planning, Exploration mission planning, and ISS program operations by supplying simulation support, iMED data information, and subject matter expertise to Crew Health and Safety and the HRP. Upcoming release of IMM version 4.0 seeks to provide enhanced functionality to increase the quality of risk decisions made using the IMM through a more accurate representation of the real world system

Integrated Medical Model Overview

The Integrated Medical Model (IMM) Project represents one aspect of NASA's Human Research Program (HRP) to quantitatively assess medical risks to astronauts for existing operational missions as well as missions associated with future exploration and commercial space flight ventures. The IMM takes a probabilistic approach to assessing the likelihood and specific outcomes of one hundred medical conditions within the envelope of accepted space flight standards of care over a selectable range of mission capabilities. A specially developed Integrated Medical Evidence Database (iMED) maintains evidence-based, organizational knowledge across a variety of data sources. Since becoming operational in 2011, version 3.0 of the IMM, the supporting iMED, and the expertise of the IMM project team have contributed to a wide range of decision and informational processes for the space medical and human research community. This presentation provides an overview of the IMM conceptual architecture and range of application through examples of actual space flight community questions posed to the IMM project