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All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Medical impact analysis for the Space Station

In this study, Space Station medical care priorities were determined by a medical impact analysis of two analog populations, U.S. Army and U.S. Navy personnel. Diseases and injuries in the International Classification of Disease, 9th Revision, Clinical Modification (ICD-9-CM) were ranked, using a Medical Impact Score (MIS) combining modified incidence rate and a function of disease outcome. The validity of the analysis method was tested by measuring rank order correlation between the two analog populations. Despite virtually identical age and sex distributions, Army and Navy incidence rates differed significantly for half of the ICD-9-CM categories, p less than 0.05. Disability rates differed for 76 percent, p less than 0.05. Nevertheless, Army and Navy MIS rank orders for categories and sections were not significantly different, p less than 0.001. In critical ways, the Space Station will be a safer environment than earth. Cardiac events, musculoskeletal injuries, affective psychoses, and renal calculi were among the highest scoring categories.

Nelson, Brent D.↗
NASA NTRS1990

Space station automation of common module power management and distribution, volume 2

The new Space Station Module Power Management and Distribution System (SSM/PMAD) testbed automation system is described. The subjects discussed include testbed 120 volt dc star bus configuration and operation, SSM/PMAD automation system architecture, fault recovery and management expert system (FRAMES) rules english representation, the SSM/PMAD user interface, and the SSM/PMAD future direction. Several appendices are presented and include the following: SSM/PMAD interface user manual version 1.0, SSM/PMAD lowest level processor (LLP) reference, SSM/PMAD technical reference version 1.0, SSM/PMAD LLP visual control logic representation's (VCLR's), SSM/PMAD LLP/FRAMES interface control document (ICD) , and SSM/PMAD LLP switchgear interface controller (SIC) ICD.

Ashworth, B.↗
NASA NTRS2008

Aquarius's Instrument Science Data System (ISDS) Automated to Acquire, Process, Trend Data and Produce Radiometric System Assessment Reports

The Aquarius Radiometer, a subsystem of the Aquarius Instrument required a data acquisition ground system to support calibration and radiometer performance assessment. To support calibration and compose performance assessments, we developed an automated system which uploaded raw data to a ftp server and saved raw and processed data to a database. This paper details the overall functionalities of the Aquarius Instrument Science Data System (ISDS) and the individual electrical ground support equipment (EGSE) which produced data files that were infused into the ISDS. Real time EGSEs include an ICDS Simulator, Calibration GSE, Labview controlled power supply, and a chamber data acquisition system. ICDS Simulator serves as a test conductor primary workstation, collecting radiometer housekeeping (HK) and science data and passing commands and HK telemetry collection request to the radiometer. Calibration GSE (Radiometer Active Test Source) provides source choice from multiple targets for the radiometer external calibration. Power Supply GSE, controlled by labview, provides real time voltage and current monitoring of the radiometer. And finally the chamber data acquisition system produces data reflecting chamber vacuum pressure, thermistor temperatures, AVG and watts. Each GSE system produce text based data files every two to six minutes and automatically copies the data files to the Central Archiver PC. The Archiver PC stores the data files, schedules automated uploads of these files to an external FTP server, and accepts request to copy all data files to the ISDS for offline data processing and analysis. Aquarius Radiometer ISDS contains PHP and MATLab programs to parse, process and save all data to a MySQL database. Analysis tools (MATLab programs) in the ISDS system are capable of displaying radiometer science, telemetry and auxiliary data in near real time as well as performing data analysis and producing automated performance assessment reports of the Aquarius Radiometer.

Source record↗
NASA NTRS2010

Phased Array Noise Source Localization Measurements Made on a Williams International FJ44 Engine

A 48-microphone planar phased array system was used to acquire noise source localization data on a full-scale Williams International FJ44 turbofan engine. Data were acquired with the array at three different locations relative to the engine, two on the side and one in front of the engine. At the two side locations the planar microphone array was parallel to the engine centerline; at the front location the array was perpendicular to the engine centerline. At each of the three locations, data were acquired at eleven different engine operating conditions ranging from engine idle to maximum (take off) speed. Data obtained with the array off to the side of the engine were spatially filtered to separate the inlet and nozzle noise. Tones occurring in the inlet and nozzle spectra were traced to the low and high speed spools within the engine. The phased array data indicate that the Inflow Control Device (ICD) used during this test was not acoustically transparent; instead, some of the noise emanating from the inlet reflected off of the inlet lip of the ICD. This reflection is a source of error for far field noise measurements made during the test. The data also indicate that a total temperature rake in the inlet of the engine is a source of fan noise.

Podboy, Gary G.↗
NASA NTRS2010

J-2X Turbopump Cavitation Diagnostics

The J-2X is the upper stage engine currently being designed by Pratt & Whitney Rocketdyne (PWR) for the Ares I Crew Launch Vehicle (CLV). Propellant supply requirements for the J-2X are defined by the Ares Upper Stage to J-2X Interface Control Document (ICD). Supply conditions outside ICD defined start or run boxes can induce turbopump cavitation leading to interruption of J-2X propellant flow during hot fire operation. In severe cases, cavitation can lead to uncontained engine failure with the potential to cause a vehicle catastrophic event. Turbopump and engine system performance models supported by system design information and test data are required to predict existence, severity, and consequences of a cavitation event. A cavitation model for each of the J-2X fuel and oxidizer turbopumps was developed using data from pump water flow test facilities at Pratt & Whitney Rocketdyne (PWR) and Marshall Space Flight Center (MSFC) together with data from Powerpack 1A testing at Stennis Space Center (SSC) and from heritage systems. These component models were implemented within the PWR J-2X Real Time Model (RTM) to provide a foundation for predicting system level effects following turbopump cavitation. The RTM serves as a general failure simulation platform supporting estimation of J-2X redline system effectiveness. A study to compare cavitation induced conditions with component level structural limit thresholds throughout the engine was performed using the RTM. Results provided insight into system level turbopump cavitation effects and redline system effectiveness in preventing structural limit violations. A need to better understand structural limits and redline system failure mitigation potential in the event of fuel side cavitation was indicated. This paper examines study results, efforts to mature J-2X turbopump cavitation models and structural limits, and issues with engine redline detection of cavitation and the use of vehicle-side abort triggers to augment the engine redline system.

Santi, I. Michael↗
NASA NTRS2010

Lessons Learned on Implementing Fault Detection, Isolation, and Recovery (FDIR) in a Ground Launch Environment

This paper's main purpose is to detail issues and lessons learned regarding designing, integrating, and implementing Fault Detection Isolation and Recovery (FDIR) for Constellation Exploration Program (CxP) Ground Operations at Kennedy Space Center (KSC). Part of the0 overall implementation of National Aeronautics and Space Administration's (NASA's) CxP, FDIR is being implemented in three main components of the program (Ares, Orion, and Ground Operations/Processing). While not initially part of the design baseline for the CxP Ground Operations, NASA felt that FDIR is important enough to develop, that NASA's Exploration Systems Mission Directorate's (ESMD's) Exploration Technology Development Program (ETDP) initiated a task for it under their Integrated System Health Management (ISHM) research area. This task, referred to as the FDIIR project, is a multi-year multi-center effort. The primary purpose of the FDIR project is to develop a prototype and pathway upon which Fault Detection and Isolation (FDI) may be transitioned into the Ground Operations baseline. Currently, Qualtech Systems Inc (QSI) Commercial Off The Shelf (COTS) software products Testability Engineering and Maintenance System (TEAMS) Designer and TEAMS RDS/RT are being utilized in the implementation of FDI within the FDIR project. The TEAMS Designer COTS software product is being utilized to model the system with Functional Fault Models (FFMs). A limited set of systems in Ground Operations are being modeled by the FDIR project, and the entire Ares Launch Vehicle is being modeled under the Functional Fault Analysis (FFA) project at Marshall Space Flight Center (MSFC). Integration of the Ares FFMs and the Ground Processing FFMs is being done under the FDIR project also utilizing the TEAMS Designer COTS software product. One of the most significant challenges related to integration is to ensure that FFMs developed by different organizations can be integrated easily and without errors. Software Interface Control Documents (ICDs) for the FFMs and their usage will be addressed as the solution to this issue. In particular, the advantages and disadvantages of these ICDs across physically separate development groups will be delineated.

Ferrell, Bob A.↗
NASA NTRS2015

The Rapid Response Radiation Survey (R3S) Mission Using the HiSat Conformal Satellite Architecture

The Rapid Response Radiation Survey (R3S) experiment, designed as a quick turnaround mission to make radiation measurements in Low Earth Orbit (LEO), will fly as a hosted payload in partnership with NovaWurks using their Hyper-integrated Satlet (HISat) architecture. The need for the mission arises as the Nowcast of Atmospheric Ionization Radiation for Aviation Safety (NAIRAS) model moves from a research effort into an operational radiation assessment tool. Currently, airline professionals are the second largest demographic of radiation workers and to date their radiation exposure is undocumented in the USA. The NAIRAS model seeks to fill this information gap. The data collected by R3S, in addition to the complementary data from a NASA Langley Research Center (LaRC) atmospheric balloon mission entitled Radiation Dosimetry Experiment (RaD-X), will validate exposure prediction capabilities of NAIRAS. The R3S mission collects total dose and radiation spectrum measurements using a Teledyne μDosimeter and a Liulin-6SA2 LED spectrometer. These two radiation sensors provide a cross correlated radiometric measurement in combination with the Honeywell HMR2300 Smart Digital Magnetometer. The magnetometer assesses the Earth's magnetic field in the LEO environment and allows radiation dose to be mapped as a function of the Earth's magnetic shielding. R3S is also unique in that the radiation sensors will be exposed on the outer surface of the spacecraft, possibly making this the first measurements of the LEO radiation environment with bare sensors. Viability of R3S as an extremely fast turnaround mission is due, in part, to the nature of the robust, well-defined interfaces of the conformal satellite HiSat Architecture. The HiSat architecture, which was developed with the support of the Defense Advanced Research Projects Agency's (DARPA's) Phoenix Program, enabled the R3S system to advance from the first concept to delivery of preliminary design review (PDR) level documents in 29 calendar days. The architecture allows for interface complexities between the specific devices and the satellite bus to be resolved in a standardized interface control document (ICD). The ICD provided a readymade framework to interface to the modular satellite bus. This modularity allowed for approximately 90% of the R3S system to be designed and fabricated in two months without constraint of the hosting satellite's development cycle. This paper discusses the development of the R3S experiment as made possible by use of the HiSat architecture. The system design and operational modes of the experiment are described, as well as the experiment interfaces to the HiSat satellite via the user defined adapter (UDA) provided by NovaWurks. This paper outlines the steps taken by the project to execute the R3S mission in the 4 months of design, build, and test. Additionally portrayed is the ground work done at LaRC to posture the organization for a fast response and the process by which the opportunity was identified as aligning with key strategic goals. Finally, a description of the engineering process is provided, including the use of facilitated rapid/concurrent engineering sessions, the associated documentation, and the review process employed.

Miller, Nathanael A.↗
NASA NTRS2019

Predictive Modeling for Differential Diagnosis and Mortality Risk Assessment

The prevalence of electronic health record (EHR) systems has brought prodigious biomedical informatics opportunity. Automated machine learning methods can effectively utilize such data and have become common tools for healthcare predictive modeling. Researches in medical informatics have explored the potential of deep learning and classical models in emergent care scenarios. In particular, predicting differential diagnoses for admissions have proven useful in decreasing unnecessary lab tests and improving inpatient triage decision-making. Moreover, identification of high-risk patients for in-hospital mortality is vitally important to maximize allocation of medical resources.The Medical Information Mart for Intensive Care (MIMIC-III) database, containing de-identified critical care inpatient was used in our study. This data set captures hospital patient laboratory measurements, pharmacologic prescriptions, diagnostic data and procedure event recordings. When considering adult patients and discounting admissions with ICU length of stay less than 24 hours, there were 37,787 unique admissions and 30,414 total patients. We examined the top 25 most prevalent ICD-9 group-level disease specificities in MIMIC-III using a multi-label classification model. In-hospital mortality was modeled as binary classification with 4,155 (13%) adult patients that expired, of which 3,138 (75.5%) were in the ICU setting. The metrics AUC, F1 score, sensitivity and specificity values calculated for each disease label measured prediction performance.The usage of ICD-9 group codes reduced feature dimension from 14,567 to 942 and greatly improved distribution of patient diagnostic categories. Disease temporal patterns were captured by considering the most frequently sampled 6 vital signs and 13 laboratory values. Missing data were imputed at each time-stamp. Time-series raw hourly average values were converted into 5 summary features (mean, standard deviation, number of observations, min & max values). Patient demographic variables such as age, gender, marital status and ethnicity were also factored into the modeling. Choi et al showed that contextual embedding of medical data, diagnostic and procedural codes alone can predict future diagnoses with sensitivity as high as 0.79. We utilized an embedding technique called word2vec which allowed sparse representations of medical history to be transformed into dense word vectors. The mappings captured contextual information by treating each admission as a sentence and learning the most likely neighboring words in a sliding window fashion. Binary and multi-label classification was achieved via collapse models, which do not consider temporal information, as well as recurrent neural networks with regularization, Softmax output layer activation together with categorical cross-entropy as the loss function.

US Army collaboration↗
NASA NTRSDate not supplied

Risk-Reduction Autonomy Implementation to Enable NASA Artemis Missions

To achieve NASA’s Artemis program mission objectives a high level of autonomy that is ubiquitous throughout the systems that are being developed will be necessary. The autonomous systems of Artemis will require a distributed autonomy capability, with autonomous systems organized functionally in a hierarchical architecture, where systems at higher levels of the hierarchy have authority over systems at lower levels. The challenge of developing autonomy technologies and Concepts of Operations (ConOps) for Artemis has been undertaken by the NASA Gateway Working Group. This group has developed requirements, architectures, ConOps, and interface control documents (ICDs), in the context of a hierarchical distributed architecture that includes the following: a Vehicle System Manager (VSM) that autonomously manages the entire Gateway; Module System Managers (MSMs) that autonomously manage each module; and System Managers (SMs) that autonomously manage systems within a module (i.e. ECLSS). A substantially high level of autonomy needs to be achieved by each element of the hierarchy (VSM, MSM, SM) to meet requirements for uncrewed operations; this includes conditions that will have minimal and/or delayed ground intervention (i.e. requirements for sustainability for months of operation without crew or ground support). To advance an implementation of this autonomy design (Gateway Autonomy Design – GAD), a collaboration was established between the Autonomous Systems Laboratory (ASL) at NASA Stennis Space Center and Lockheed Martin. The objectives of this partnership were the following: (1) to implement autonomy at the VSM, MSM, and SM levels; (2) to implement communications among a VSM, 2 MSMs, ORION (a visiting vehicle somewhat equivalent to a module) and 1 SM (a power system), and (3) test autonomous operations with representative use cases. A SM backed by a high-fidelity simulation was created to facilitate demonstrations of use cases that originated in a system of a module. Communication between the VSM and MSMs was implemented according to Concepts of Operations and Interface Control Documents (ICDs). Demonstrations were conducted to address nominal and off-nominal operations and multi-module interactions with the VSM. Additionally, user interfaces were created to provide awareness about ongoing processes and results while enhancing the demonstration. Demonstrations included the following use cases: (1) Orion as visiting vehicle registers with VSM; (2) VSM reschedules a module’s timelines when another module’s MSM task fails; and (3) a module’s Power System Manager (PSM) demonstration that included component failure diagnostics, tracing component failure to effected components, which in turn, reports failure information up to the VSM for acknowledgement and display. This paper will describe the detailed technology and autonomous systems developed, and the integrated multi-module demonstrations conducted. Also, challenges that must be met to fully implement the GAD defined by Gateway will be addressed.

Fernando Figueroa↗
NASA NTRS2017

Future ATM Concepts Evaluation Tool (FACET) Interface Control Document

This Interface Control Document (ICD) documents the airspace adaptation and air traffic inputs of NASA's Future ATM Concepts and Evaluation Tool (FACET). Its intended audience is the project manager, project team, development team, and stakeholders interested in interfacing with the system. FACET equips Air Traffic Management (ATM) researchers and service providers with a way to explore, develop and evaluate advanced air transportation concepts before they are field-tested and eventually deployed. FACET is a flexible software tool that is capable of quickly generating and analyzing thousands of aircraft trajectories. It provides researchers with a simulation environment for preliminary testing of advanced ATM concepts. Using aircraft performance profiles, airspace models, weather data, and flight schedules, the tool models trajectories for the climb, cruise, and descent phases of flight for each type of aircraft. An advanced graphical interface displays traffic patterns in two and three dimensions, under various current and projected conditions for specific airspace regions or over the entire continental United States. The system is able to simulate a full day's dynamic national airspace system (NAS) operations, model system uncertainty, measure the impact of different decision-makers in the NAS, and provide analysis of the results in graphical form, including sector, airport, fix, and airway usage statistics. NASA researchers test and analyze the system-wide impact of new traffic flow management algorithms under anticipated air traffic growth projections on the nation's air traffic system. In addition to modeling the airspace system for NASA research, FACET has also successfully transitioned into a valuable tool for operational use. Federal Aviation Administration (FAA) traffic flow managers and commercial airline dispatchers have used FACET technology for real-time operations planning. FACET integrates live air traffic data from FAA radar systems and weather data from the National Weather Service to summarize NAS performance. This information allows system operators to reroute flights around congested airspace and severe weather to maintain safety and minimize delay. FACET also supports the planning and post-operational evaluation of reroute strategies at the national level to maximize system efficiency. For the commercial airline passenger, strategic planning with FACET can result in fewer flight delays and cancellations. The performance capabilities of FACET are largely due to its architecture, which strikes a balance between flexibility and fidelity. FACET is capable of modeling the airspace operations for the continental United States, processing thousands of aircraft on a single computer. FACET was written in Java and C, enabling the portability of its software to a variety of operating systems. In addition, FACET was designed with a modular software architecture to facilitate rapid prototyping of diverse ATM concepts. Several advanced ATM concepts have already been implemented in FACET, including aircraft self-separation, prediction of aircraft demand and sector congestion, system-wide impact assessment of traffic flow management constraints, and wind-optimal routing.

FACET↗
DOE OSTI2019

Comparison of Endovascular and Open Carotid Artery Treatment in Germany: A Retrospective Analysis from 2010 to 2015

Introduction: We analyzed trends in carotid artery stenting (CAS) and carotid endarterectomy (CEA) in hospitalized cases in Germany in the years 2010–2015. Methods: Data from national statistics (DRG statistics) published by the Federal Statistical Office in Germany describing the number of hospitalized patients treated with CEA and CAS were used. In addition, numbers of patients hospitalized with the principal diagnosis stroke associated with precerebral lesions (ICD code I63), transitory cerebral ischemic attacks (G45) and precerebral carotid artery stenosis (I65) treated by CEA and CAS were analyzed for the year 2015. Results: Total number of CEA decreased by 4.0% from 24.067 (2010) to 23.104 (2015) and CAS increased by 5.1% from 5.703 to 5.992. In 2015, 79.4% of all procedures coded concerning the internal carotid artery were CEA and 21.6% CAS. From 27.798 cases hospitalized with the principal diagnosis stroke associated with precerebral lesions, CEA was performed in 3.921 (14.1%) and in 2.132 (7.7%) CAS was documented, with CAS making up one-third of all treatments within the stroke group. In 28.273 cases hospitalized with a TIA, CEA was specified in 853 (3.0%) and CAS in 255 (0.9%) cases. In 27.553 cases with an occlusion and stenosis of precerebral arteries, not resulting in cerebral infarction, 17.036 (61.8%) had a CEA and 3.156 (11.5%) a CAS procedure. Conclusion: CEA is still the primary treatment of extracranial artery stenosis. The impact of CAS becomes mainly apparent in cases presenting with acute strokes.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Standard Lexicons, Coding Systems and Ontologies for Interoperability and Semantic Computation in Imaging

Standard clinical terms, codes, and ontologies promote clarity and interoperability. Within radiology, there is a variety of relevant content resources, tools and technologies. These provide the basis for fundamental imaging workflows such as reporting and billing, and also facilitate a range of applications in quality improvement and research. This article reviews the key characteristics of lexicons, coding systems, and ontologies. A number of standards are described, including International Classification of Diseases-10-Clinical Modification (ICD-10-CM), Current Procedural Terminology (CPT), Systematized Nomenclature of Medicine—Clinical Terms (SNOMED CT), Logical Observation Identifiers Names and Codes (LOINC), and RadLex. Tools for accessing this material are reviewed, such as the National Center for Biomedical Ontology BioPortal system. Web services are discussed as a mechanism for semantic application development. Several example systems, workflows, and research applications using semantic technology are also surveyed.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

Outcomes of hypercalcemia of malignancy in patients with solid cancer: a national inpatient analysis

Hypercalcemia of malignancy (HCM) is present in one-third of cancer patients and is associated with a significant mortality risk of 50% within 1 month of diagnosis. We aimed to study the impact and outcomes of HCM in hospitalized patients with solid cancer. We analyzed data captured in the National Inpatient Sample database of the Agency of Healthcare Research and Quality. The study included all hospitalizations in adult solid cancer patients between January 2012 and September 2015 with hypercalcemia. All encounters associated with HCM were identified using the ICD-9 code (275.42) for hypercalcemia. Encounters with other known causes of hypercalcemia were excluded. The co-primary outcomes were incidence of HCM and inpatient mortality. During the study period, 7,501,209 hospitalizations met our inclusion criteria. Approximately 1.7% (n = 126,875) of these hospitalizations were related to HCM. This corresponds to approximately 1 in 59 solid malignancy associated hospitalizations. The mean age of patients with HCM was 65.7 years; 49% were females; 69% were Caucasians; 73% had metastatic disease and 22% received a palliative care consult. When compared to those without HCM, those hospitalized with HCM had a significantly longer mean hospital length of stay (7.3 days vs. 5.6 days, p < 0.001), higher inpatient mortality (12.3% vs. 5.5%, adjusted OR 1.76 (95% CI 1.69–1.84), p < 0·0001), and a greater likelihood of discharge to other facilities (27.4% vs. 16.2%, p < 0.0001). Although HCM accounts for < 2% of all hospitalizations in patients with solid cancer, those with HCM display higher mortality than those without HCM.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Dll4-Notch1 signaling but not VEGF-A is essential for hyperoxia induced vessel regression in retina

Highlights: • Our study find that VEGF-A is not an indispensable factor in hyperoxia induced vessel regression. • Hyperoxia exposure inactivated Dll4-Notch1 signaling in vessel regression region. • Inhibition of Dll4-Notch1 signaling by short-time administration of Dll4 neutralizing antibodies or DAPT exaggerates hyperoxia induced vascular regression. It is well recognized that decreased vascular endothelial growth factor A (VEGF-A) mRNA plays an important role in retinal vessel regression induced by hyperoxia. However, this concept has been challenged by increasing new evidence. Furthermore, VEGF-A strongly enhances Dll4 expression and inhibition of Dll4-Notch signaling leads to excessive sprouting angiogenesis. Recently, it is shown that inactivation of Dll4-Notch1 signaling reduce hyperoxia induced vessel regression. It is unknown whether sprouting angiogenesis contributes to the protective effect or not and further investigations are needed. Moreover, the expression of Dll4 or Notch1 activation in the regressing plexus remains elucidated. To determine the role of VEGF-A and Dll4-Notch1 signaling in hyperoxia induced vascular regression in the retina, we used mice at postnatal day 5 (P5) - P7. Hyperoxia induced massive vascular regression in the central plexus but not in the angiogenic plexus and had no effect on sprouting angiogenesis. Immunostaining showed that VEGF-A was significantly repressed in the angiogenic front region after hyperoxia exposure but not detectable in the central area of both normoxia and hyperoxia treated retinas. In contrast, Notch ligand Delta-like 4 (Dll4) and Notch1 intracellular domain (N1-ICD) expression were inhibited in the regressing capillaries of central retina but comparable in the angiogenic plexus after high oxygen treatment. Moreover, administration of Dll4 neutralizing antibody or γ-Secretase inhibitor DAPT significantly aggravated vessel regression induced by short-time hyperoxia administration. Our data show that repressed Dll4-Notch1 signaling pathway but not downregulation of VEGF-A expression are responsible for hyperoxia induced pervasive vessel regression.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Cause-specific stillbirth and exposure to chemical constituents and sources of fine particulate matter

Highlights: • Explored associations between cause-specific stillbirth and PM{sub 2.5} sources. • Gestational age-adjusted exposure was estimated in nested case-control study design. • Different causes of stillbirth were associated with different pollutants. • Highlighted the importance of investigating cause-specific stillbirth. The stillbirth rate in the United States is relatively high, but limited evidence is available linking stillbirth with fine particulate matter (PM{sub 2.5}), its chemical constituents and sources. In this study, we explored associations between cause-specific stillbirth and prenatal exposures to those pollutants with using live birth and stillbirth records from eight California locations during 2002–2009. ICD-10 codes were used to identify cause of stillbirth from stillbirth records. PM{sub 2.5} total mass and chemical constituents were collected from ambient monitors and PM{sub 2.5} sources were quantified using Positive Matrix Factorization. Conditional logistic regression was applied using a nested case-control study design (N = 32,262). We found that different causes of stillbirth were associated with different PM{sub 2.5} sources and/or chemical constituents. For stillbirths due to fetal growth, the odds ratio (OR) per interquartile range increase in gestational age-adjusted exposure to PM{sub 2.5} total mass was 1.23 (95% confidence interval (CI): 1.06, 1.44). Similar associations were found with resuspended soil (OR=1.25, 95% CI: 1.10, 1.42), and secondary ammonium sulfate (OR=1.45, 95% CI: 1.18, 1.78). No associations were found between any pollutants and stillbirths caused by maternal complications. This study highlighted the importance of investigating cause-specific stillbirth and the differential toxicity levels of specific PM{sub 2.5} sources and chemical constituents.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

PM10 exposure is associated with increased hospitalizations for respiratory syncytial virus bronchiolitis among infants in Lombardy, Italy

Highlights: • Respiratory syncytial virus bronchiolitis (RSV-B) might be influenced by air pollution. • PM10 was associated with RSV-B hospitalizations among infants in Lombardy, Italy. • The most relevant exposure windows were the 2 weeks preceding hospitalization. Respiratory syncytial virus (RSV) is the primary cause of acute lower respiratory infections in children, bronchiolitis in particular. Airborne particulate matter (PM) may influence the children's immune system and foster the spread of RSV infection. We aimed to verify whether PM10 exposure is associated with hospitalization due to RSV bronchiolitis. We selected hospital discharge records (HRD) with ICD-9-CM code 466.11 of infants < 1 year of age, occurring in the epidemic seasons of two years (2012–2013) in Lombardy, Italy. Cases were assigned daily PM10 and apparent temperature levels of the capital city of their residential province. Different exposure windows were considered: single days preceding hospitalization (lag 0 to 30), their average estimates (lag 0–1 to 0–30), and the four weeks preceding hospitalization (week 1 to 4). Negative binomial regression models adjusted for apparent temperature and season were applied to the daily counts of hospitalizations in each province. Results were expressed as incidence rate ratios (IRR) and 95% confidence intervals (95%CI) per 10 µg/m{sup 3} increase in PM10 concentration. Random effects meta-analyses of province-specific IRR were performed to obtain regional estimates. 2814 HRD met our inclusion criteria; males represented about 55% of the cases. A 6% increased risk of hospitalization (95%CI: 1.03–1.10) was found at lag 0 and an almost overlapping 7% increase at lag 1. IRR ranged from 1.03 to 1.05 between lags 2 and 11. No increased risk was observed from lag 12. When considering averaged daily lags, risk estimates gradually increased in the two weeks preceding hospitalization from 1.08 (1.04–1.12) at lag 0–1 to 1.15 (1.08–1.23) between lags 0–11 and 0–13. Analyses on weekly lags showed a risk increase of 6% (1.01–1.12) during week 1 and of 7% (1.02–1.13) during week 2. Our study found a clear association between short- and medium-term PM10 exposures and increased risk of hospitalization due to RSV bronchiolitis among infants.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

CD147-induced cell proliferation is associated with Smad4 signal inhibition

CD147 is a multifunctional trans-membrane glycoprotein, which is highly expressed in many cancers. However, the mechanism by which CD147 modulates cell proliferation is not fully understood. The aim of this study is to investigate the role of CD147 in cell proliferation associated with the TGF-β/Smad4 signaling pathway. Here, we used cell viability and clone formation assays in LNCaP prostate cancer cells to demonstrate that CD147 promotes cell proliferation. The luciferase assay and western blotting show that silencing CD147 using shRNA enhances transcription and expression of p21{sup WAF1}. Using immunofluorescence and nuclear-cytoplasmic separation, we show that this is primarily attributed to transport of Smad4 from the cytoplasm to nucleus. Other assays (GST pull-down, co-immunoprecipitation and immunofluorescence) demonstrate that Smad4 is a new interaction partner of CD147, with the Smad4 MH2 domain and CD147 intracellular domain (CD147-ICD) being involved in the interaction. Furthermore, we report that a phosphoserine (pSer) in CD147 (pSer252) is responsible for this interaction and inhibition of the Smad4/p21{sup WAF1} signal that promotes cell proliferation. Our results provide a novel molecular mechanism for CD147-induced cell proliferation associated with Smad4 signal inhibition. - Highlights: • Smad4 interacts with CD147 via the MH2 domain. • CD147 prevents Smad4 translocation into the nuclear to regulate p21 transcription. • CD147 inhibits p21 transcription and expression independent on p53. • pCD147-S252 is responsible for interaction with Smad4 and p21 down-regulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Machine learning prediction of incidence of Alzheimer’s disease using large-scale administrative health data

Nationwide population-based cohort provides a new opportunity to build an automated risk prediction model based on individuals’ history of health and healthcare beyond existing risk prediction models. We tested the possibility of machine learning models to predict future incidence of Alzheimer’s disease (AD) using large-scale administrative health data. From the Korean National Health Insurance Service database between 2002 and 2010, we obtained de-identified health data in elders above 65 years (N = 40,736) containing 4,894 unique clinical features including ICD-10 codes, medication codes, laboratory values, history of personal and family illness and socio-demographics. To define incident AD we considered two operational definitions: “definite AD” with diagnostic codes and dementia medication (n = 614) and “probable AD” with only diagnosis (n = 2026). We trained and validated random forest, support vector machine and logistic regression to predict incident AD in 1, 2, 3, and 4 subsequent years. For predicting future incidence of AD in balanced samples (bootstrapping), the machine learning models showed reasonable performance in 1-year prediction with AUC of 0.775 and 0.759, based on “definite AD” and “probable AD” outcomes, respectively; in 2-year, 0.730 and 0.693; in 3-year, 0.677 and 0.644; in 4-year, 0.725 and 0.683. The results were similar when the entire (unbalanced) samples were used. Important clinical features selected in logistic regression included hemoglobin level, age and urine protein level. This study may shed a light on the utility of the data-driven machine learning model based on large-scale administrative health data in AD risk prediction, which may enable better selection of individuals at risk for AD in clinical trials or early detection in clinical settings.

97 MATHEMATICS AND COMPUTING↗