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At least 235 records · Page 13

Retrospective Analysis of Inflight Exercise Loading and Physiological Outcomes

Astronauts perform exercise throughout their missions to counter the health declines that occur as a result of long-term exposure to weightlessness. Although all astronauts perform exercise during their missions, the specific prescriptions, and thus the mechanical loading, differs among individuals. For example, inflight ground reaction force data indicate that subject-specific differences exist in foot forces created when exercising on the second-generation treadmill (T2) [1]. The current exercise devices allow astronauts to complete prescriptions at higher intensities, resulting in greater benefits with increased efficiency. Although physiological outcomes have improved, the specific factors related to the increased benefits are unknown. In-flight exercise hardware collect data that allows for exploratory analyses to determine if specific performance factors relate to physiological outcomes. These analyses are vital for understanding which components of exercise are most critical for optimal human health and performance. The relationship between exercise performance variables and physiological changes during flight has yet to be fully investigated. Identifying the critical performance variables that relate to improved physiological outcomes is vital for creating current and future exercise prescriptions to optimize astronaut health. The specific aims of this project are: 1) To quantify the exercise-related mechanical loading experienced by crewmembers on T2 and ARED during their mission on ISS; 2) To explore relationships between exercise loading variables, bone, and muscle health changes during the mission; 3) To determine if specific mechanical loading variables are more critical than others in protecting physiology; 4) To develop methodology for operational use in monitoring accumulated training loads during crew exercise programs. This retrospective analysis, which is currently in progress, is being conducted using data from astronauts that have flown long-duration missions onboard the ISS and have had access to exercise on the T2 and the Advanced Resistive Exercise Device (ARED). The specific exercise prescriptions vary for each astronaut. General exercise summary metrics will be developed to quantify exercise intensities, volumes, and durations for each subject. Where available, ground reaction force data will be used to quantify mechanical loading experienced by each astronaut. These inflight exercise metrics will be investigated relative to changes in pre- to post-flight bone and muscle health to identify which specific variables are related with improved or degraded physiological outcomes. The information generated from this analysis will fill gaps related to typical bone loading characterization, exercise performance capability, exercise volume and efficiency, and importance of exercise hardware. In addition, methods for quantification of exercise loading for use in monitoring the exercise programs during future space missions will be explored with the intent to inform exercise scientists and trainers as to the critical aspects of inflight exercise prescriptions.

Ploutz-Snyder, L. L.↗

Comparison of satellite and in situ data

A variety of data sets were available and analyzed. The data sets discussed here are: (1) SMMR-A: The Nimbus Project data release; (2) SMMR-D: The revised SMMR version produced by Wilheit and Milman; (3) SMMR-C: The SMMR version produced by Prabhakara; (4) Fleet Numerical Oceanography Center (PNOC): The individual ship reports; and (5) Reynolds Climatology. Data from SMMR and PNOC ships were compared in three different ways: (1) The difference between individual ship and SMMR observations which were close in space and time. (2) The difference between the 20 degree lat-lon one month averages for SMMR and ship, respectively. (3) The difference between the 20 degree averages and climatology, for both SMMR and ship.

Bernstein, R. L.↗

Comparison between Brewer spectrometer, M 124 filter ozonometer and Dobson spectrophotometer

Concurrent measurements were taken using the Brewer spectrometer no. 30, the filter ozonometer M 124 no. 200 and the Dobson spectrophotometer no. 71 from September 1987 to December 1988 at Potsdam. The performance of the instrument types and the compatibility of ozone data was checked under the conditions of a field measuring station. Total ozone values derived from Dobson AD direct sun measurements were considered as standard. The Dobson instrument had been calibrated at intercomparisons with the World Standard Dobson instrument no. 83 (Boulder) and with the Regional Standard instrument no. 64 (Potsdam), while the Brewer instrument was calibrated several times with the Travelling Standard Brewer no. 17 (Canada). The differences between individual Brewer DS (direct sun) ozone data and Dobson ADDS are within plus or minus 3 percent with half of all differences within plus or minus 1 percent. Less than 0.7 percent of the systematic difference can be due to atmospheric SO2. Due to inadequate regression coefficients Brewer ZB (zenith blue) ozone measurements are by (3...4) percent higher than Dobson ADDS ozone values. M124 DS ozone data are systematically by (1...2) percent higher than Dobson ADDS ozone with 50 percent of the differences within plus or minus 4 percent, but with extreme differences up to plus or minus (20...25) percent. M124 ZB ozone values are by (3...5) percent higher than Dobson ADDS with all the differences within plus or minus 10 percent, i.e. the scatter of differences is smaller for ZB than for M 124 DS measurements, Results for differences in the daily mean ozone values are also addressed. The differences include the uncertainties in the ozone values derived from both types of measurements. They provide an indication of the uncertainty in ozone data and the comparability of ozone values derived from different types of instruments.

Feister, U.↗

Two distinct regions of response drive differential growth in Vigna root electrotropism

Although exogenous electric fields have been reported to influence the orientation of plant root growth, reports of the ultimate direction of differential growth have been contradictory. Using a high-resolution image analysis approach, the kinetics of electrotropic curvature in Vigna mungo L. roots were investigated. It was found that curvature occurred in the same root toward both the anode and cathode. However, these two responses occurred in two different regions of the root, the central elongation zone (CEZ) and distal elongation zone (DEZ), respectively. These oppositely directed responses could be reproduced individually by a localized electric field application to the region of response. This indicates that both are true responses to the electric field, rather than one being a secondary response to an induced gravitropic stimulation. The individual responses differed in the type of differential growth giving rise to curvature. In the CEZ, curvature was driven by inhibition of elongation, whereas curvature in the DEZ was primarily due to stimulation of elongation. This stimulation of elongation is consistent with the growth response of the DEZ to other environmental stimuli.

Non-NASA Center↗

Quantitative Predictive Theories through Integrating Quantum, Statistical, Equilibrium, and Nonequilibrium Thermodynamics

Today's thermodynamics is largely based on the combined law for equilibrium systems and statistical mechanics derived by Gibbs in 1873 and 1901, respectively, while irreversible thermodynamics for nonequilibrium systems resides essentially on the Onsager Theorem as a separate branch of thermodynamics developed in 1930s. Between them, quantum mechanics was invented and was quantitatively solved in terms of density functional theory (DFT) in 1960s. Furthermore, these three scientific domains operate based on different principles and are very much separated from each other. In analogy to the parable of the blind men and the elephant articulated by Perdew, they individually represent different portions of a complex system and thus are incomplete by themselves alone, resulting in the lack of quantitative agreement between their predictions and experimental observations. Over the last two decades, the author's group has developed a multiscale entropy approach (recently termed as zentropy theory) that integrates DFT-based quantum mechanics and Gibbs statistical mechanics and is capable of accurately predicting entropy and free energy of complex systems. Furthermore, in combination with the combined law for nonequilibrium systems developed by Hillert, the author developed the theory of cross phenomena beyond the phenomenological Onsager Theorem. The zentropy theory and theory of cross phenomena jointly provide quantitative predictive theories for systems from electronic to any observable scales as reviewed in the present work.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Improved Method of Manufacturing SiC Devices

The phrase, "common-layered architecture for semiconductor silicon carbide" ("CLASSiC") denotes a method of batch fabrication of microelectromechanical and semiconductor devices from bulk silicon carbide. CLASSiC is the latest in a series of related methods developed in recent years in continuing efforts to standardize SiC-fabrication processes. CLASSiC encompasses both institutional and technological innovations that can be exploited separately or in combination to make the manufacture of SiC devices more economical. Examples of such devices are piezoresistive pressure sensors, strain gauges, vibration sensors, and turbulence-intensity sensors for use in harsh environments (e.g., high-temperature, high-pressure, corrosive atmospheres). The institutional innovation is to manufacture devices for different customers (individuals, companies, and/or other entities) simultaneously in the same batch. This innovation is based on utilization of the capability for fabrication, on the same substrate, of multiple SiC devices having different functionalities (see figure). Multiple customers can purchase shares of the area on the same substrate, each customer s share being apportioned according to the customer s production-volume requirement. This makes it possible for multiple customers to share costs in a common foundry, so that the capital equipment cost per customer in the inherently low-volume SiC-product market can be reduced significantly. One of the technological innovations is a five-mask process that is based on an established set of process design rules. The rules provide for standardization of the fabrication process, yet are flexible enough to enable multiple customers to lay out masks for their portions of the SiC substrate to provide for simultaneous batch fabrication of their various devices. In a related prior method, denoted multi-user fabrication in silicon carbide (MUSiC), the fabrication process is based largely on surface micromachining of poly SiC. However, in MUSiC one cannot exploit the superior sensing, thermomechanical, and electrical properties of single-crystal 6H-SiC or 4H-SiC. As a complement to MUSiC, the CLASSiC five-mask process can be utilized to fabricate multiple devices in bulk single-crystal SiC of any polytype. The five-mask process makes fabrication less complex because it eliminates the need for large-area deposition and removal of sacrificial material. Other innovations in CLASSiC pertain to selective etching of indium tin oxide and aluminum in connection with multilayer metallization. One major characteristic of bulk micromachined microelectromechanical devices is the presence of three-dimensional (3D) structures. Any 3D recesses that already exist at a given step in a fabrication process usually make it difficult to apply a planar coat of photoresist for metallization and other subsequent process steps. To overcome this difficulty, the CLASSiC process includes a reversal of part of the conventional flow: Metallization is performed before the recesses are etched.

Okojie, Robert S.↗

3D Source Reconstruction Using Coded Aperture Gamma-Ray Imaging

Recent measurements with coded-aperture imagers demonstrate material mass determination in a holdup setting to an accuracy within a few percent. This capability is of particular interest to the Surplus Plutonium Disposition (SPD) project, which aims to dilute and dispose of surplus plutonium oxide. Gamma-ray imagers can be used to determine holdup without interrupting normal operations. In this work, we examine techniques for 3D source localization and mass determination using gamma-ray imagers. Coded-aperture imagers provide excellent source localization within the 2D image plane; however, multiple imagers operating in tandem are necessary to identify source location in 3D space. A Maximum Likelihood Expectation-Maximization (MLEM) method for fitting detector mappings is a powerful tool for accomplishing this task. MLEM allows 3D source localization to be simultaneously constrained using multiple gamma-ray imagers by constructing the basis for the MLEM fit using detector mappings from different detector locations stitched together. Each of these basis points represents a singular response from a source in 3D space and is generated using Monte Carlo simulations of sources placed individually at different locations throughout the imager’s field of view. Additionally, implementing knowledge of the physical equipment in the simulations of the glovebox used for the SPD project incorporates attenuation effects that are needed to calculate material holdup.

Laminack, Alex↗

Best practices mobile application for D and D KM-IT - 15712

The Deactivation and Decommissioning Knowledge Management Information Tool (D and D KM-IT) is the repository of useful information built specifically for D and D community. The knowledge provided by the D and D KM-IT is the experience and expertise gained by people within the field and fellow employees of the Department of Energy (DOE). This information has been the result of gathering, analyzing, storing, and sharing knowledge to help reduce time spent on discovering previously found data. In order to help in organizing all the data from all the professional contributors, the D and D KM-IT has been divided into 12 different modules. Each individual module pertains to a different area of information for users, such as vendor and technology information, collaboration tools, and even a hotline that contains problems posted by the users. Purpose: - Design and develop the module for the Best Practices on D and D KM-IT mobile platform deployed at https://m.dndkm.org; - The Best Practices mobile module should integrate with existing modules seamlessly; - Use the D and D KM-IT existing database to consume information for the mobile system. jQuery Mobile framework was used to develop Best Practices module for mobile devices. jQuery Mobile framework provides support for responsive web design (RWD). RWD allows adaptation of the layout and user interface of web sites and web apps to different device resolutions, screen densities, and views. UI design was implemented with three fundamental elements: CSS media queries, An adaptable grid, Flexible images and media. Advantages/benefits: - A responsive web design adapts to any-sized screen / resolution and orientation view; - ASP.NET compatible which allows the D and D KM-IT database to support all platforms accessing the system; - Navigating pages is more bandwidth efficient by refreshing data in small section with Ajax instead of reloading the entire page; - Multiple parts of a page can perform different tasks resulting in improved user's experience. Results: - Mobile system is accessible on compatible devices running Android, Apple, Blackberry, Palm, and Windows devices; - Best Practices searches through Characterization, Decontamination, Dismantlement, Material Disposition, and Worker Safety; - Keyword search is enabled for the best practices that are available on both the desktop and mobile systems - Documents are formatted into a PDF file format to ensure compatibility on any device. Conclusion: - Fully integrated with the desktop Best Practices module and displays documents that are uploaded on web platform; - Fast-loading with D and D KM-IT mobile system and downloadable documents; - Responsive design which gives the same user experience when either viewed on smart phone or tablet.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

How Do Various Maize Crop Models Vary in Their Responses to Climate Change Factors?

Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha(sup 1) per degC. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

carbon dioxide↗

Eight decades of research on the long-term health effects of radiation in atomic bomb survivors and their offspring

Abstract This year marks the 80th anniversary of the atomic bombings of Hiroshima and Nagasaki. Over the past eight decades, large-scale cohort studies of atomic bomb survivors and their offspring conducted by the Radiation Effects Research Foundation and its predecessor, the Atomic Bomb Casualty Commission, have provided critical insights into the long-term health effects of radiation exposure. Key findings include early identification of radiation-associated leukemia, as well as excess risks of all solid cancers combined, and most individual cancer sites. Observed radiation dose–response relationships have generally followed a linear-quadratic model for leukemia and a linear model for all solid cancers. Recent findings indicating possible upward curvature in the dose–response for all solid cancers may reflect underlying heterogeneity in factors related to individual cancer sites and should be explored further. Generally, younger age at exposure, lower attained age, and female sex appear to show greater radiation sensitivity for all solid cancers combined but results differ by individual cancer site. Recent studies have also identified potential radiation-related excesses for non-cancer diseases such as cataracts, various circulatory diseases, and others. Studies of heritable effects on the offspring of exposed atomic bomb survivors, in contrast, have shown no elevated risk to date in offspring from parental radiation exposure, either at the molecular or disease level. With the cooperation of the atomic bomb survivors and their families, Radiation Effects Research Foundation’s research will continue to play a crucial role in informing the health of survivors, their families, and global radiation protection in the decades to come.

Oncology↗

A side‐by‐side comparison of CPV module and system performance

Abstract A side‐by‐side comparison is made between concentrator photovoltaic module and system direct current aperture efficiency data with a focus on quantifying system performance losses. The individual losses measured/calculated, when combined, are in good agreement with the total loss seen between the module and the system. Results indicate that for the given test period, the largest individual loss of 3.7% relative is due to the baseline performance difference between the individual module and the average for the 200 modules in the system. A basic empirical model is derived based on module spectral performance data and the tabulated losses between the module and the system. The model predicts instantaneous system direct current aperture efficiency with a root mean square error of 2.3% relative. Copyright © 2016 John Wiley & Sons, Ltd.

Muller, Matthew↗

Arctic sea ice concentrations from special sensor microwave imager and advanced very high resolution radiometer satellite data

Nearly coincident data from the special sensor microwave imager (SSM/I) and the advanced very high resolution radiometer (AVHRR) are used to compute and compare Arctic sea ice concentrations for different regions and times of the year. To help determine overall accuracies and to highlight sources of differences between passive microwave, optical wavelength, and thermal wavelength data, ice concentrations are estimated using two operational SSM/I ice concentration algorithms and with visible- and thermal-infrared wavelength AVHRR data. All algorithms capture the seasonal patterns of ice growth and melt. The ranges of differences fall within the general levels of uncertainty expected for each method and are similar to previous accuracy estimates. The estimated ice concentrations are all highly correlated, with uniform biases, although differences between individual pairs of observations can be large. On average, the NASA Team algorithm yielded 5% higher ice concentrations than the Bootstrap algorithm, while during nonmelt periods the two SSM/I algorithms agree to within 0.5%. These seasonal differences are consistent with the ways that the 19-GHz and 37-GHz microwave channels are used in the algorithms. When compared to the AVHRR-derived ice concentrations, the Team-algorithm results are more similar on average in terms of correlation and mean differences. However, the Team algorithm underestimates concentrations relative to the AVHRR output by 6% during cold months and overestimates by 3% during summer. Little seasonal difference exists between the Bootstrap and AVHRR results, with a mean difference of about 5%. Although the mean differences are less between the SSM/I-derived concentrations and concentrations estimated using AVHRR channel 1, the correlations appear substantially better between the SSM/I data and concentrations derived from AVHRR channel 4, particularly for the Team algorithm output.

Emery, W. J.↗

Geometrical defect detection for additive manufacturing with machine learning models

This study proposed a scheme based on Machine Learning (ML) models to detect geometric defects of additively manufactured objects. The ML models are trained with synthetic 3D point clouds with defects and then applied to detect defects in actual production. Using synthetic 3D point clouds rather than experimental data could save a huge amount of training time and costs associated with many prints for each design. Besides distance differences of individual points between source and target point clouds, this scheme uses a new concept called “patch” to capture macro-level information about nearby points for ML training and implementation. Numerical comparisons of prediction results on experimental data with different shapes showed that the proposed scheme outperformed the existing Z-difference method in the literature. Five ML methods (Bagging of Trees, Gradient Boosting, Random Forest, K-nearest Neighbors and Linear Supported Vector Machine) were compared under various conditions, such as different point cloud densities and defect sizes. Bagging and Random Forest were found the two best models regarding predictability; and the right patch size was found to be at 20. The proposed ML-based scheme is applicable to in-situ defect detection during additive manufacturing with the aid of a proper 3D data acquisition system.

Additive manufacturing↗

Some Long-Standing Issues Arising From Comparisons Between TOMS and The Ground-Based Ozone Network

Data from the series of Total Ozone Mapping Spectrometers (TOMS) have been compared to column ozone measurements taken by ground-based systems (Dobsons, Brewers and Filtermeters). On average, the comparisons show good agreement, with approximately 80% of the ground stations having less than a 2.5% standard deviation when compared to TOMS on a monthly mean basis. There are, however, differences that imply possible errors either in the TOMS ozone retrieval algorithm or in the basic assumptions used by the ground-based instruments. Some of the issues arising from these differences are: What are the relative calibrations of TOMS instruments? Why do the calibrations of the ground-based stations vary as much as they do with respect to TOMS as a transfer standard? Why are the TOMS data so much larger (approximately 6%) than the ground-based data in Antarctica and other ice-covered locations? Why is there seasonality in the difference between TOMS and ground-based stations in the Southern Hemisphere? Why are the differences a function of total ozone? Where and why are the differences a function of reflectivity? Why do some terrain and land-sea boundary features appear in the TOMS ozone data? The above issues will be highlighted by using data from TOMS and the ground stations. Plots of the individual station differences will be available.

Labow, Gordon J.↗

Sociocultural Behavior Influence Modelling & Assessment: Current Work and Research Frontiers.

A common problem associated with the effort to better assess potential behaviors of various individuals within different countries is the shear difficulty in comprehending the dynamic nature of populations, particularly over time and considering feedback effects. This paper discusses a theory-based analytical capability designed to enable analysts to better assess the influence of events on individuals interacting within a country or region. These events can include changes in policy, man-made or natural disasters, migration, war, or other changes in environmental/economic conditions. In addition, this paper describes potential extensions of this type of research to enable more timely and accurate assessments.

99 GENERAL AND MISCELLANEOUS↗

Kinship, inbreeding and fine‐scale spatial structure influence gut microbiota in a hindgut‐fermenting tortoise

Abstract Herbivorous vertebrates rely on complex communities of mutualistic gut bacteria to facilitate the digestion of celluloses and hemicelluloses. Gut microbes are often convergent based on diet and gut morphology across a phylogenetically diverse group of mammals. However, little is known about microbial communities of herbivorous hindgut‐fermenting reptiles. Here, we investigate how factors at the individual level might constrain the composition of gut microbes in an obligate herbivorous reptile. Using multiplexed 16S rRNA gene sequencing, we characterized the faecal microbial community of a population of gopher tortoises ( Gopherus polyphemus ) and examined how age, genetic diversity, spatial structure and kinship influence differences among individuals. We recovered phylotypes associated with known cellulolytic function, including candidate phylum Termite Group 3, suggesting their importance for gopher tortoise digestion. Although host genetic structure did not explain variation in microbial composition and community structure, we found that fine‐scale spatial structure, inbreeding, degree of relatedness and possibly ontogeny shaped patterns of diversity in faecal microbiomes of gopher tortoises. Our findings corroborate widespread convergence of faecal‐associated microbes based on gut morphology and diet and demonstrate the role of spatial and demographic structure in driving differentiation of gut microbiota in natural populations.

Yuan, Michael L.↗

Commissioning the neutron production of a Linac: Development of a simple tool for second cancer risk estimation

Purpose: Knowing the contribution of neutron to collateral effects in treatments is both a complex and a mandatory task. This work aims to present an operative procedure for neutron estimates in any facility using a neutron digital detector. Methods: The authors’ previous work established a linear relationship between the total second cancer risk due to neutrons (TR{sup n}) and the number of MU of the treatment. Given that the digital detector also presents linearity with MU, its response can be used to determine the TR{sup n} per unit MU, denoted as m, normally associated to a generic Linac model and radiotherapy facility. Thus, from the number of MU of each patient treatment, the associated risk can be estimated. The feasibility of the procedure was tested by applying it in eight facilities; patients were evaluated as well. Results: From the reading of the detector under selected irradiation conditions, m values were obtained for different machines, ranging from 0.25 × 10{sup −4}% per MU for an Elekta Axesse at 10 MV to 6.5 × 10{sup −4}% per MU for a Varian Clinac at 18 MV. Using these values, TR{sup n} of patients was estimated in each facility and compared to that from the individual evaluation. Differences were within the range of uncertainty of the authors’ methodology of equivalent dose and risk estimations. Conclusions: The procedure presented here allows an easy estimation of the second cancer risk due to neutrons for any patient, given the number of MU of the treatment. It will enable the consideration of this information when selecting the optimal treatment for a patient by its implementation in the treatment planning system.

60 APPLIED LIFE SCIENCES↗

RNA Splicing Events in Circulation Distinguish Individuals With and Without New-onset Type 1 Diabetes

Context: Alterations in RNA splicing may influence protein isoform diversity that contributes to or reflects the pathophysiology of certain diseases. Whereas specific RNA splicing events in pancreatic islets have been investigated in models of inflammation in vitro, how RNA splicing in the circulation correlates with or is reflective of type 1 diabetes (T1D) disease pathophysiology in humans remains unexplored. Objective: To use machine learning to investigate if alternative RNA splicing events differ between individuals with and without new-onset T1D and to determine if these splicing events provide insight into T1D pathophysiology. Methods: RNA deep sequencing was performed on whole blood samples from 2 independent cohorts: a training cohort consisting of 12 individuals with new-onset T1D and 12 age- and sex-matched nondiabetic controls and a validation cohort of the same size and demographics. Machine learning analysis was used to identify specific isoforms that could distinguish individuals with T1D from controls. Results: Distinct patterns of RNA splicing differentiated participants with T1D from unaffected controls. Notably, certain splicing events, particularly involving retained introns, showed significant association with T1D. Machine learning analysis using these splicing events as features from the training cohort demonstrated high accuracy in distinguishing between T1D subjects and controls in the validation cohort. Gene Ontology pathway enrichment analysis of the retained intron category showed evidence for a systemic viral response in T1D subjects. Conclusion: Alternative RNA splicing events in whole blood are significantly enriched in individuals with new-onset T1D and can effectively distinguish these individuals from unaffected controls. Further, our findings also suggest that RNA splicing profiles offer the potential to provide insights into disease pathogenesis.

60 APPLIED LIFE SCIENCES↗