Finite element based model predictive control for active vibration suppression of a one-link flexible manipulator.

PubMed

Dubay, Rickey; Hassan, Marwan; Li, Chunying; Charest, Meaghan

2014-09-01

This paper presents a unique approach for active vibration control of a one-link flexible manipulator. The method combines a finite element model of the manipulator and an advanced model predictive controller to suppress vibration at its tip. This hybrid methodology improves significantly over the standard application of a predictive controller for vibration control. The finite element model used in place of standard modelling in the control algorithm provides a more accurate prediction of dynamic behavior, resulting in enhanced control. Closed loop control experiments were performed using the flexible manipulator, instrumented with strain gauges and piezoelectric actuators. In all instances, experimental and simulation results demonstrate that the finite element based predictive controller provides improved active vibration suppression in comparison with using a standard predictive control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Advancing Environmental Prediction Capabilities for the Polar Regions and Beyond during The Year of Polar Prediction

NASA Astrophysics Data System (ADS)

Werner, Kirstin; Goessling, Helge; Hoke, Winfried; Kirchhoff, Katharina; Jung, Thomas

2017-04-01

Environmental changes in polar regions open up new opportunities for economic and societal operations such as vessel traffic related to scientific, fishery and tourism activities, and in the case of the Arctic also enhanced resource development. The availability of current and accurate weather and environmental information and forecasts will therefore play an increasingly important role in aiding risk reduction and safety management around the poles. The Year of Polar Prediction (YOPP) has been established by the World Meteorological Organization's World Weather Research Programme as the key activity of the ten-year Polar Prediction Project (PPP; see more on www.polarprediction.net). YOPP is an internationally coordinated initiative to significantly advance our environmental prediction capabilities for the polar regions and beyond, supporting improved weather and climate services. Scheduled to take place from mid-2017 to mid-2019, the YOPP core phase covers an extended period of intensive observing, modelling, prediction, verification, user-engagement and education activities in the Arctic and Antarctic, on a wide range of time scales from hours to seasons. The Year of Polar Prediction will entail periods of enhanced observational and modelling campaigns in both polar regions. With the purpose to close the gaps in the conventional polar observing systems in regions where the observation network is sparse, routine observations will be enhanced during Special Observing Periods for an extended period of time (several weeks) during YOPP. This will allow carrying out subsequent forecasting system experiments aimed at optimizing observing systems in the polar regions and providing insight into the impact of better polar observations on forecast skills in lower latitudes. With various activities and the involvement of a wide range of stakeholders, YOPP will contribute to the knowledge base needed to managing the opportunities and risks that come with polar climate change.

Estimation of the Driving Style Based on the Users' Activity and Environment Influence.

PubMed

Sysoev, Mikhail; Kos, Andrej; Guna, Jože; Pogačnik, Matevž

2017-10-21

New models and methods have been designed to predict the influence of the user's environment and activity information to the driving style in standard automotive environments. For these purposes, an experiment was conducted providing two types of analysis: (i) the evaluation of a self-assessment of the driving style; (ii) the prediction of aggressive driving style based on drivers' activity and environment parameters. Sixty seven h of driving data from 10 drivers were collected for analysis in this study. The new parameters used in the experiment are the car door opening and closing manner, which were applied to improve the prediction accuracy. An Android application called Sensoric was developed to collect low-level smartphone data about the users' activity. The driving style was predicted from the user's environment and activity data collected before driving. The prediction was tested against the actual driving style, calculated from objective driving data. The prediction has shown encouraging results, with precision values ranging from 0.727 up to 0.909 for aggressive driving recognition rate. The obtained results lend support to the hypothesis that user's environment and activity data could be used for the prediction of the aggressive driving style in advance, before the driving starts.

Assessing and enhancing the utility of low-cost activity and location sensors for exposure studies.

PubMed

Asimina, Stamatelopoulou; Chapizanis, D; Karakitsios, S; Kontoroupis, P; Asimakopoulos, D N; Maggos, T; Sarigiannis, D

2018-02-20

Nowadays, the advancement of mobile technology in conjunction with the introduction of the concept of exposome has provided new dynamics to the exposure studies. Since the addressing of health outcomes related to environmental stressors is crucial, the improvement of exposure assessment methodology is of paramount importance. Towards this aim, a pilot study was carried out in the two major cities of Greece (Athens, Thessaloniki), investigating the applicability of commercially available fitness monitors and the Moves App for tracking people's location and activities, as well as for predicting the type of the encountered location, using advanced modeling techniques. Within the frame of the study, 21 individuals were using the Fitbit Flex activity tracker, a temperature logger, and the application Moves App on their smartphones. For the validation of the above equipment, participants were also carrying an Actigraph (activity sensor) and a GPS device. The data collected from Fitbit Flex, the temperature logger, and the GPS (speed) were used as input parameters in an Artificial Neural Network (ANN) model for predicting the type of location. Analysis of the data showed that the Moves App tends to underestimate the daily steps counts in comparison with Fitbit Flex and Actigraph, respectively, while Moves App predicted the movement trajectory of an individual with reasonable accuracy, compared to a dedicated GPS. Finally, the encountered location was successfully predicted by the ANN in most of the cases.

Predictive Suppression of Cortical Excitability and Its Deficit in Schizophrenia

PubMed Central

Schroeder, Charles E.; Leitman, David I.

2013-01-01

Recent neuroscience advances suggest that when interacting with our environment, along with previous experience, we use contextual cues and regularities to form predictions that guide our perceptions and actions. The goal of such active “predictive sensing” is to selectively enhance the processing and representation of behaviorally relevant information in an efficient manner. Since a hallmark of schizophrenia is impaired information selection, we tested whether this deficiency stems from dysfunctional predictive sensing by measuring the degree to which neuronal activity predicts relevant events. In healthy subjects, we established that these mechanisms are engaged in an effort-dependent manner and that, based on a correspondence between human scalp and intracranial nonhuman primate recordings, their main role is a predictive suppression of excitability in task-irrelevant regions. In contrast, schizophrenia patients displayed a reduced alignment of neuronal activity to attended stimuli, which correlated with their behavioral performance deficits and clinical symptoms. These results support the relevance of predictive sensing for normal and aberrant brain function, and highlight the importance of neuronal mechanisms that mold internal ongoing neuronal activity to model key features of the external environment. PMID:23843536

Pharmacological mechanism-based drug safety assessment and prediction.

PubMed

Abernethy, D R; Woodcock, J; Lesko, L J

2011-06-01

Advances in cheminformatics, bioinformatics, and pharmacology in the context of biological systems are now at a point that these tools can be applied to mechanism-based drug safety assessment and prediction. The development of such predictive tools at the US Food and Drug Administration (FDA) will complement ongoing efforts in drug safety that are focused on spontaneous adverse event reporting and active surveillance to monitor drug safety. This effort will require the active collaboration of scientists in the pharmaceutical industry, academe, and the National Institutes of Health, as well as those at the FDA, to reach its full potential. Here, we describe the approaches and goals for the mechanism-based drug safety assessment and prediction program.

Estimation of the Driving Style Based on the Users’ Activity and Environment Influence

PubMed Central

Sysoev, Mikhail; Kos, Andrej; Guna, Jože; Pogačnik, Matevž

2017-01-01

New models and methods have been designed to predict the influence of the user’s environment and activity information to the driving style in standard automotive environments. For these purposes, an experiment was conducted providing two types of analysis: (i) the evaluation of a self-assessment of the driving style; (ii) the prediction of aggressive driving style based on drivers’ activity and environment parameters. Sixty seven h of driving data from 10 drivers were collected for analysis in this study. The new parameters used in the experiment are the car door opening and closing manner, which were applied to improve the prediction accuracy. An Android application called Sensoric was developed to collect low-level smartphone data about the users’ activity. The driving style was predicted from the user’s environment and activity data collected before driving. The prediction was tested against the actual driving style, calculated from objective driving data. The prediction has shown encouraging results, with precision values ranging from 0.727 up to 0.909 for aggressive driving recognition rate. The obtained results lend support to the hypothesis that user’s environment and activity data could be used for the prediction of the aggressive driving style in advance, before the driving starts. PMID:29065476

Anti-tumour activity of platinum compounds in advanced prostate cancer-a systematic literature review.

PubMed

Hager, S; Ackermann, C J; Joerger, M; Gillessen, S; Omlin, A

2016-06-01

For men with advanced castration-resistant prostate cancer (CRPC), several treatment options are available, including androgen receptor (AR) pathway inhibitors (abiraterone acetate, enzalutamide), taxanes (docetaxel, cabazitaxel) and the radionuclide (radium-223). However, cross-resistance is a clinically relevant problem. Platinum compounds have been tested in a number of clinical trials in molecularly unselected prostate cancer patients. Advances in CRPC molecular profiling have shown that a significant proportion of patients harbour DNA repair defects, which may serve as predictive markers for sensitivity to platinum agents. To systematically identify and analyse clinical trials that have evaluated platinum agents in advanced prostate cancer patients. PubMed was searched to identify published clinical trials of platinum agents in advanced prostate cancer. The PRIMSA statement was followed for the systematic review process. Identified trials are analysed for study design, statistical plan, assessments of anti-tumour activity and the potential value of predictive biomarkers. A total of 163 references were identified by the literature search and 72 publications that met the selection criteria were included in this review; of these 33 used carboplatin, 27 cisplatin, 6 satraplatin, 4 oxaliplatin and 2 other platinum compounds. Overall, anti-tumour activity varies in the range of 10%-40% for objective response and 20%-70% for PSA decline ≥50%. Response seemed highest for the combinations of carboplatin with taxanes or oxaliplatin with gemcitabine. The interpretation of the clinical data is limited by differences in response criteria used and patient populations studied. Platinum compounds have moderate anti-tumour activity in molecularly unselected patients with advanced prostate cancer. Translational evidence of DNA repair deficiency should be leveraged in future studies to select prostate cancer patients most likely to benefit from platinum-based therapy. © The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Seasonal forecasting of lightning and thunderstorm activity in tropical and temperate regions of the world.

PubMed

Dowdy, Andrew J

2016-02-11

Thunderstorms are convective systems characterised by the occurrence of lightning. Lightning and thunderstorm activity has been increasingly studied in recent years in relation to the El Niño/Southern Oscillation (ENSO) and various other large-scale modes of atmospheric and oceanic variability. Large-scale modes of variability can sometimes be predictable several months in advance, suggesting potential for seasonal forecasting of lightning and thunderstorm activity in various regions throughout the world. To investigate this possibility, seasonal lightning activity in the world's tropical and temperate regions is examined here in relation to numerous different large-scale modes of variability. Of the seven modes of variability examined, ENSO has the strongest relationship with lightning activity during each individual season, with relatively little relationship for the other modes of variability. A measure of ENSO variability (the NINO3.4 index) is significantly correlated to local lightning activity at 53% of locations for one or more seasons throughout the year. Variations in atmospheric parameters commonly associated with thunderstorm activity are found to provide a plausible physical explanation for the variations in lightning activity associated with ENSO. It is demonstrated that there is potential for accurately predicting lightning and thunderstorm activity several months in advance in various regions throughout the world.

Seasonal forecasting of lightning and thunderstorm activity in tropical and temperate regions of the world

PubMed Central

Dowdy, Andrew J.

2016-01-01

Thunderstorms are convective systems characterised by the occurrence of lightning. Lightning and thunderstorm activity has been increasingly studied in recent years in relation to the El Niño/Southern Oscillation (ENSO) and various other large-scale modes of atmospheric and oceanic variability. Large-scale modes of variability can sometimes be predictable several months in advance, suggesting potential for seasonal forecasting of lightning and thunderstorm activity in various regions throughout the world. To investigate this possibility, seasonal lightning activity in the world’s tropical and temperate regions is examined here in relation to numerous different large-scale modes of variability. Of the seven modes of variability examined, ENSO has the strongest relationship with lightning activity during each individual season, with relatively little relationship for the other modes of variability. A measure of ENSO variability (the NINO3.4 index) is significantly correlated to local lightning activity at 53% of locations for one or more seasons throughout the year. Variations in atmospheric parameters commonly associated with thunderstorm activity are found to provide a plausible physical explanation for the variations in lightning activity associated with ENSO. It is demonstrated that there is potential for accurately predicting lightning and thunderstorm activity several months in advance in various regions throughout the world. PMID:26865431

Global precipitation measurement (GPM) preliminary design

NASA Astrophysics Data System (ADS)

Neeck, Steven P.; Kakar, Ramesh K.; Azarbarzin, Ardeshir A.; Hou, Arthur Y.

2008-10-01

The overarching Earth science mission objective of the Global Precipitation Measurement (GPM) mission is to develop a scientific understanding of the Earth system and its response to natural and human-induced changes. This will enable improved prediction of climate, weather, and natural hazards for present and future generations. The specific scientific objectives of GPM are advancing: Precipitation Measurement through combined use of active and passive remote-sensing techniques, Water/Energy Cycle Variability through improved knowledge of the global water/energy cycle and fresh water availability, Climate Prediction through better understanding of surface water fluxes, soil moisture storage, cloud/precipitation microphysics and latent heat release, Weather Prediction through improved numerical weather prediction (NWP) skills from more accurate and frequent measurements of instantaneous rain rates with better error characterizations and improved assimilation methods, Hydrometeorological Prediction through better temporal sampling and spatial coverage of highresolution precipitation measurements and innovative hydro-meteorological modeling. GPM is a joint initiative with the Japan Aerospace Exploration Agency (JAXA) and other international partners and is the backbone of the Committee on Earth Observation Satellites (CEOS) Precipitation Constellation. It will unify and improve global precipitation measurements from a constellation of dedicated and operational active/passive microwave sensors. GPM is completing the Preliminary Design Phase and is advancing towards launch in 2013 and 2014.

Aeromechanics and Aeroacoustics Predictions of the Boeing-SMART Rotor Using Coupled-CFD/CSD Analyses

NASA Technical Reports Server (NTRS)

Bain, Jeremy; Sim, Ben W.; Sankar, Lakshmi; Brentner, Ken

2010-01-01

This paper will highlight helicopter aeromechanics and aeroacoustics prediction capabilities developed by Georgia Institute of Technology, the Pennsylvania State University, and Northern Arizona University under the Helicopter Quieting Program (HQP) sponsored by the Tactical Technology Office of the Defense Advanced Research Projects Agency (DARPA). First initiated in 2004, the goal of the HQP was to develop high fidelity, state-of-the-art computational tools for designing advanced helicopter rotors with reduced acoustic perceptibility and enhanced performance. A critical step towards achieving this objective is the development of rotorcraft prediction codes capable of assessing a wide range of helicopter configurations and operations for future rotorcraft designs. This includes novel next-generation rotor systems that incorporate innovative passive and/or active elements to meet future challenging military performance and survivability goals.

Sleep Quality Prediction From Wearable Data Using Deep Learning.

PubMed

Sathyanarayana, Aarti; Joty, Shafiq; Fernandez-Luque, Luis; Ofli, Ferda; Srivastava, Jaideep; Elmagarmid, Ahmed; Arora, Teresa; Taheri, Shahrad

2016-11-04

The importance of sleep is paramount to health. Insufficient sleep can reduce physical, emotional, and mental well-being and can lead to a multitude of health complications among people with chronic conditions. Physical activity and sleep are highly interrelated health behaviors. Our physical activity during the day (ie, awake time) influences our quality of sleep, and vice versa. The current popularity of wearables for tracking physical activity and sleep, including actigraphy devices, can foster the development of new advanced data analytics. This can help to develop new electronic health (eHealth) applications and provide more insights into sleep science. The objective of this study was to evaluate the feasibility of predicting sleep quality (ie, poor or adequate sleep efficiency) given the physical activity wearable data during awake time. In this study, we focused on predicting good or poor sleep efficiency as an indicator of sleep quality. Actigraphy sensors are wearable medical devices used to study sleep and physical activity patterns. The dataset used in our experiments contained the complete actigraphy data from a subset of 92 adolescents over 1 full week. Physical activity data during awake time was used to create predictive models for sleep quality, in particular, poor or good sleep efficiency. The physical activity data from sleep time was used for the evaluation. We compared the predictive performance of traditional logistic regression with more advanced deep learning methods: multilayer perceptron (MLP), convolutional neural network (CNN), simple Elman-type recurrent neural network (RNN), long short-term memory (LSTM-RNN), and a time-batched version of LSTM-RNN (TB-LSTM). Deep learning models were able to predict the quality of sleep (ie, poor or good sleep efficiency) based on wearable data from awake periods. More specifically, the deep learning methods performed better than traditional logistic regression. “CNN had the highest specificity and sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional logistic regression (0.6463). Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep. ©Aarti Sathyanarayana, Shafiq Joty, Luis Fernandez-Luque, Ferda Ofli, Jaideep Srivastava, Ahmed Elmagarmid, Teresa Arora, Shahrad Taheri. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 04.11.2016.

Sleep Quality Prediction From Wearable Data Using Deep Learning

PubMed Central

Sathyanarayana, Aarti; Joty, Shafiq; Ofli, Ferda; Srivastava, Jaideep; Elmagarmid, Ahmed; Arora, Teresa; Taheri, Shahrad

2016-01-01

Background The importance of sleep is paramount to health. Insufficient sleep can reduce physical, emotional, and mental well-being and can lead to a multitude of health complications among people with chronic conditions. Physical activity and sleep are highly interrelated health behaviors. Our physical activity during the day (ie, awake time) influences our quality of sleep, and vice versa. The current popularity of wearables for tracking physical activity and sleep, including actigraphy devices, can foster the development of new advanced data analytics. This can help to develop new electronic health (eHealth) applications and provide more insights into sleep science. Objective The objective of this study was to evaluate the feasibility of predicting sleep quality (ie, poor or adequate sleep efficiency) given the physical activity wearable data during awake time. In this study, we focused on predicting good or poor sleep efficiency as an indicator of sleep quality. Methods Actigraphy sensors are wearable medical devices used to study sleep and physical activity patterns. The dataset used in our experiments contained the complete actigraphy data from a subset of 92 adolescents over 1 full week. Physical activity data during awake time was used to create predictive models for sleep quality, in particular, poor or good sleep efficiency. The physical activity data from sleep time was used for the evaluation. We compared the predictive performance of traditional logistic regression with more advanced deep learning methods: multilayer perceptron (MLP), convolutional neural network (CNN), simple Elman-type recurrent neural network (RNN), long short-term memory (LSTM-RNN), and a time-batched version of LSTM-RNN (TB-LSTM). Results Deep learning models were able to predict the quality of sleep (ie, poor or good sleep efficiency) based on wearable data from awake periods. More specifically, the deep learning methods performed better than traditional linear regression. CNN had the highest specificity and sensitivity, and an overall area under the receiver operating characteristic (ROC) curve (AUC) of 0.9449, which was 46% better as compared with traditional linear regression (0.6463). Conclusions Deep learning methods can predict the quality of sleep based on actigraphy data from awake periods. These predictive models can be an important tool for sleep research and to improve eHealth solutions for sleep. PMID:27815231

The atmospheric boundary layer — advances in knowledge and application

NASA Astrophysics Data System (ADS)

Garratt, J. R.; Hess, G. D.; Physick, W. L.; Bougeault, P.

1996-02-01

We summarise major activities and advances in boundary-layer knowledge in the 25 years since 1970, with emphasis on the application of this knowledge to surface and boundary-layer parametrisation schemes in numerical models of the atmosphere. Progress in three areas is discussed: (i) the mesoscale modelling of selected phenomena; (ii) numerical weather prediction; and (iii) climate simulations. Future trends are identified, including the incorporation into models of advanced cloud schemes and interactive canopy schemes, and the nesting of high resolution boundary-layer schemes in global climate models.

Predicting consumer behavior: using novel mind-reading approaches.

PubMed

Calvert, Gemma A; Brammer, Michael J

2012-01-01

Advances in machine learning as applied to functional magnetic resonance imaging (fMRI) data offer the possibility of pretesting and classifying marketing communications using unbiased pattern recognition algorithms. By using these algorithms to analyze brain responses to brands, products, or existing marketing communications that either failed or succeeded in the marketplace and identifying the patterns of brain activity that characterize success or failure, future planned campaigns or new products can now be pretested to determine how well the resulting brain responses match the desired (successful) pattern of brain activity without the need for verbal feedback. This major advance in signal processing is poised to revolutionize the application of these brain-imaging techniques in the marketing sector by offering greater accuracy of prediction in terms of consumer acceptance of new brands, products, and campaigns at a speed that makes them accessible as routine pretesting tools that will clearly demonstrate return on investment.

Mentalizing about emotion and its relationship to empathy.

PubMed

Hooker, Christine I; Verosky, Sara C; Germine, Laura T; Knight, Robert T; D'Esposito, Mark

2008-09-01

Mentalizing involves the ability to predict someone else's behavior based on their belief state. More advanced mentalizing skills involve integrating knowledge about beliefs with knowledge about the emotional impact of those beliefs. Recent research indicates that advanced mentalizing skills may be related to the capacity to empathize with others. However, it is not clear what aspect of mentalizing is most related to empathy. In this study, we used a novel, advanced mentalizing task to identify neural mechanisms involved in predicting a future emotional response based on a belief state. Subjects viewed social scenes in which one character had a False Belief and one character had a True Belief. In the primary condition, subjects were asked to predict what emotion the False Belief Character would feel if they had a full understanding about the situation. We found that neural regions related to both mentalizing and emotion were involved when predicting a future emotional response, including the superior temporal sulcus, medial prefrontal cortex, temporal poles, somatosensory related cortices (SRC), inferior frontal gyrus and thalamus. In addition, greater neural activity in primarily emotion-related regions, including right SRC and bilateral thalamus, when predicting emotional response was significantly correlated with more self-reported empathy. The findings suggest that predicting emotional response involves generating and using internal affective representations and that greater use of these affective representations when trying to understand the emotional experience of others is related to more empathy.

Refining Low Physical Activity Measurement Improves Frailty Assessment in Advanced Lung Disease and Survivors of Critical Illness.

PubMed

Baldwin, Matthew R; Singer, Jonathan P; Huang, Debbie; Sell, Jessica; Gonzalez, Wendy C; Pollack, Lauren R; Maurer, Mathew S; D'Ovidio, Frank F; Bacchetta, Matthew; Sonett, Joshua R; Arcasoy, Selim M; Shah, Lori; Robbins, Hilary; Hays, Steven R; Kukreja, Jasleen; Greenland, John R; Shah, Rupal J; Leard, Lorriana; Morrell, Matthew; Gries, Cynthia; Katz, Patricia P; Christie, Jason D; Diamond, Joshua M; Lederer, David J

2017-08-01

The frail phenotype has gained popularity as a clinically relevant measure in adults with advanced lung disease and in critical illness survivors. Because respiratory disease and chronic illness can greatly limit physical activity, the measurement of participation in traditional leisure time activities as a frailty component may lead to substantial misclassification of frailty in pulmonary and critical care patients. To test and validate substituting the Duke Activity Status Index (DASI), a simple 12-item questionnaire, for the Minnesota Leisure Time Physical Activity (MLTA) questionnaire, a detailed questionnaire covering 18 leisure time activities, as the measure of low activity in the Fried frailty phenotype (FFP) instrument. In separate multicenter prospective cohort studies of adults with advanced lung disease who were candidates for lung transplant and older survivors of acute respiratory failure, we assessed the FFP using either the MLTA or the DASI. For both the DASI and MLTA, we evaluated content validity by testing floor effects and construct validity through comparisons with conceptually related factors. We tested the predictive validity of substituting the DASI for the MLTA in the FFP assessment using Cox models to estimate associations between the FFP and delisting/death before transplant in those with advanced lung disease and 6-month mortality in older intensive care unit (ICU) survivors. Among 618 adults with advanced lung disease and 130 older ICU survivors, the MLTA had a substantially greater floor effect than the DASI (42% vs. 1%, and 49% vs. 12%, respectively). The DASI correlated more strongly with strength and function measures than did the MLTA in both cohorts. In models adjusting for age, sex, comorbidities, and illness severity, substitution of the DASI for the MLTA led to stronger associations of the FFP with delisting/death in lung transplant candidates (FFP-MLTA hazard ratio [HR], 1.42; 95% confidence interval [CI], 0.55-3.65; FFP-DASI HR, 2.99; 95% CI, 1.03-8.65) and with mortality in older ICU survivors (FFP-MLTA HR, 2.68; 95% CI, 0.62-11.6; FFP-DASI HR, 5.71; 95% CI, 1.34-24.3). The DASI improves the construct and predictive validity of frailty assessment in adults with advanced lung disease or recent critical illness. This simple questionnaire should replace the more complex MLTA in assessing the frailty phenotype in these populations.

Advancing Cyber Intelligence Practices Through the SEI’s Consortium

DTIC Science & Technology

2015-01-27

blogsjsocial media Extracurricular Activities Vu lnerabilities from these individuals roles with non-target entities-non-profits, activist groups, or...information to identify, track, and predict cyber capabilities, intentions, and activities to offer courses of action that enhance decision making 7 SEI...8 SEI Webinar Series January 27, 2015 © 2015 Carnegie Mellon University Offerings Steering Committee: Guide Consortium activities and plan for

Potential Collaborative Research topics with Korea’s Agency for Defense Development

DOE Office of Scientific and Technical Information (OSTI.GOV)

Farrar, Charles R.; Todd, Michael D.

2012-08-23

This presentation provides a high level summary of current research activities at the Los Alamos National Laboratory (LANL)-University of California Jacobs School of Engineering (UCSD) Engineering Institute that will be presented at Korea's Agency for Defense Development (ADD). These research activities are at the basic engineering science level with different level of maturity ranging from initial concepts to field proof-of-concept demonstrations. We believe that all of these activities are appropriate for collaborative research activities with ADD subject to approval by each institution. All the activities summarized herein have the common theme that they are multi-disciplinary in nature and typically involvedmore » the integration of high-fidelity predictive modeling, advanced sensing technologies and new development in information technology. These activities include: Wireless Sensor Systems, Swarming Robot sensor systems, Advanced signal processing (compressed sensing) and pattern recognition, Model Verification and Validation, Optimal/robust sensor system design, Haptic systems for large-scale data processing, Cyber-physical security for robots, Multi-source energy harvesting, Reliability-based approaches to damage prognosis, SHMTools software development, and Cyber-physical systems advanced study institute.« less

Collaborations for Arctic Sea Ice Information and Tools

NASA Astrophysics Data System (ADS)

Sheffield Guy, L.; Wiggins, H. V.; Turner-Bogren, E. J.; Rich, R. H.

2017-12-01

The dramatic and rapid changes in Arctic sea ice require collaboration across boundaries, including between disciplines, sectors, institutions, and between scientists and decision-makers. This poster will highlight several projects that provide knowledge to advance the development and use of sea ice knowledge. Sea Ice for Walrus Outlook (SIWO: https://www.arcus.org/search-program/siwo) - SIWO is a resource for Alaskan Native subsistence hunters and other interested stakeholders. SIWO provides weekly reports, during April-June, of sea ice conditions relevant to walrus in the northern Bering and southern Chukchi seas. Collaboration among scientists, Alaskan Native sea-ice experts, and the Eskimo Walrus Commission is fundamental to this project's success. Sea Ice Prediction Network (SIPN: https://www.arcus.org/sipn) - A collaborative, multi-agency-funded project focused on seasonal Arctic sea ice predictions. The goals of SIPN include: coordinate and evaluate Arctic sea ice predictions; integrate, assess, and guide observations; synthesize predictions and observations; and disseminate predictions and engage key stakeholders. The Sea Ice Outlook—a key activity of SIPN—is an open process to share and synthesize predictions of the September minimum Arctic sea ice extent and other variables. Other SIPN activities include workshops, webinars, and communications across the network. Directory of Sea Ice Experts (https://www.arcus.org/researchers) - ARCUS has undertaken a pilot project to develop a web-based directory of sea ice experts across institutions, countries, and sectors. The goal of the project is to catalyze networking between individual investigators, institutions, funding agencies, and other stakeholders interested in Arctic sea ice. Study of Environmental Arctic Change (SEARCH: https://www.arcus.org/search-program) - SEARCH is a collaborative program that advances research, synthesizes research findings, and broadly communicates the results to support informed decision-making. One of SEARCH's primary science topics is focused on Arctic sea ice; the SEARCH Sea Ice Action Team is leading efforts to advance understanding and awareness of the impacts of Arctic sea-ice loss.

Functional brain imaging predicts public health campaign success

PubMed Central

O’Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

2016-01-01

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a ‘self-localizer’ defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400 000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R2 up to 0.65) and (ii) this relationship depends on message content—self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. PMID:26400858

Advanced space power PEM fuel cell systems

NASA Technical Reports Server (NTRS)

Vanderborgh, N. E.; Hedstrom, J.; Huff, J. R.

1989-01-01

A model showing mass and heat transfer in proton exchange membrane (PEM) single cells is presented. For space applications, stack operation requiring combined water and thermal management is needed. Advanced hardware designs able to combine these two techniques are available. Test results are shown for membrane materials which can operate with sufficiently fast diffusive water transport to sustain current densities of 300 ma per square centimeter. Higher power density levels are predicted to require active water removal.

An interfacial mechanism for cloud droplet formation on organic aerosols.

PubMed

Ruehl, Christopher R; Davies, James F; Wilson, Kevin R

2016-03-25

Accurate predictions of aerosol/cloud interactions require simple, physically accurate parameterizations of the cloud condensation nuclei (CCN) activity of aerosols. Current models assume that organic aerosol species contribute to CCN activity by lowering water activity. We measured droplet diameters at the point of CCN activation for particles composed of dicarboxylic acids or secondary organic aerosol and ammonium sulfate. Droplet activation diameters were 40 to 60% larger than predicted if the organic was assumed to be dissolved within the bulk droplet, suggesting that a new mechanism is needed to explain cloud droplet formation. A compressed film model explains how surface tension depression by interfacial organic molecules can alter the relationship between water vapor supersaturation and droplet size (i.e., the Köhler curve), leading to the larger diameters observed at activation. Copyright © 2016, American Association for the Advancement of Science.

Locally Weighted Learning Methods for Predicting Dose-Dependent Toxicity with Application to the Human Maximum Recommended Daily Dose

DTIC Science & Technology

2012-09-10

Advanced Technology Research Center, U.S. Army Medical Research and Materiel Command, Fort Detrick, Maryland 21702, United States ABSTRACT: Toxicological ...species. Thus, it is more advantageous to predict the toxicological effects of a compound on humans directly from the human toxicological data of related...compounds. However, many popular quantitative structure−activity relationship ( QSAR ) methods that build a single global model by fitting all training

Targeting Epidermal Growth Factor Receptor-Related Signaling Pathways in Pancreatic Cancer.

PubMed

Philip, Philip A; Lutz, Manfred P

2015-10-01

Pancreatic cancer is aggressive, chemoresistant, and characterized by complex and poorly understood molecular biology. The epidermal growth factor receptor (EGFR) pathway is frequently activated in pancreatic cancer; therefore, it is a rational target for new treatments. However, the EGFR tyrosine kinase inhibitor erlotinib is currently the only targeted therapy to demonstrate a very modest survival benefit when added to gemcitabine in the treatment of patients with advanced pancreatic cancer. There is no molecular biomarker to predict the outcome of erlotinib treatment, although rash may be predictive of improved survival; EGFR expression does not predict the biologic activity of anti-EGFR drugs in pancreatic cancer, and no EGFR mutations are identified as enabling the selection of patients likely to benefit from treatment. Here, we review clinical studies of EGFR-targeted therapies in combination with conventional cytotoxic regimens or multitargeted strategies in advanced pancreatic cancer, as well as research directed at molecules downstream of EGFR as alternatives or adjuncts to receptor targeting. Limitations of preclinical models, patient selection, and trial design, as well as the complex mechanisms underlying resistance to EGFR-targeted agents, are discussed. Future clinical trials must incorporate translational research end points to aid patient selection and circumvent resistance to EGFR inhibitors.

Lifing of Engine Components

NASA Technical Reports Server (NTRS)

2005-01-01

The successful development of advanced aerospace engines depends greatly on the capabilities of high performance materials and structures. Advanced materials, such as nickel based single crystal alloys, metal foam, advanced copper alloys, and ceramics matrix composites, have been engineered to provide higher engine temperature and stress capabilities. Thermal barrier coatings have been developed to improve component durability and fuel efficiency, by reducing the substrate hot wall metal temperature and protecting against oxidation and blanching. However, these coatings are prone to oxidation and delamination failures. In order to implement the use of these materials in advanced engines, it is necessary to understand and model the evolution of damage of the metal substrate as well as the coating under actual engine conditions. The models and the understanding of material behavior are utilized in the development of a life prediction methodology for hot section components. The research activities were focused on determining the stress and strain fields in an engine environment under combined thermo-mechanical loads to develop life prediction methodologies consistent with the observed damage formation of the coating and the substrates.

Earthquake Hazards.

ERIC Educational Resources Information Center

Donovan, Neville

1979-01-01

Provides a survey and a review of earthquake activity and global tectonics from the advancement of the theory of continental drift to the present. Topics include: an identification of the major seismic regions of the earth, seismic measurement techniques, seismic design criteria for buildings, and the prediction of earthquakes. (BT)

An enhanced MMW and SMMW/THz imaging system performance prediction and analysis tool for concealed weapon detection and pilotage obstacle avoidance

NASA Astrophysics Data System (ADS)

Murrill, Steven R.; Jacobs, Eddie L.; Franck, Charmaine C.; Petkie, Douglas T.; De Lucia, Frank C.

2015-10-01

The U.S. Army Research Laboratory (ARL) has continued to develop and enhance a millimeter-wave (MMW) and submillimeter- wave (SMMW)/terahertz (THz)-band imaging system performance prediction and analysis tool for both the detection and identification of concealed weaponry, and for pilotage obstacle avoidance. The details of the MATLAB-based model which accounts for the effects of all critical sensor and display components, for the effects of atmospheric attenuation, concealment material attenuation, and active illumination, were reported on at the 2005 SPIE Europe Security and Defence Symposium (Brugge). An advanced version of the base model that accounts for both the dramatic impact that target and background orientation can have on target observability as related to specular and Lambertian reflections captured by an active-illumination-based imaging system, and for the impact of target and background thermal emission, was reported on at the 2007 SPIE Defense and Security Symposium (Orlando). Further development of this tool that includes a MODTRAN-based atmospheric attenuation calculator and advanced system architecture configuration inputs that allow for straightforward performance analysis of active or passive systems based on scanning (single- or line-array detector element(s)) or staring (focal-plane-array detector elements) imaging architectures was reported on at the 2011 SPIE Europe Security and Defence Symposium (Prague). This paper provides a comprehensive review of a newly enhanced MMW and SMMW/THz imaging system analysis and design tool that now includes an improved noise sub-model for more accurate and reliable performance predictions, the capability to account for postcapture image contrast enhancement, and the capability to account for concealment material backscatter with active-illumination- based systems. Present plans for additional expansion of the model's predictive capabilities are also outlined.

Recent Progress in Engine Noise Reduction Technologies

NASA Technical Reports Server (NTRS)

Huff, Dennis; Gliebe, Philip

2003-01-01

Highlights from NASA-funded research over the past ten years for aircraft engine noise reduction are presented showing overall technical plans, accomplishments, and selected applications to turbofan engines. The work was sponsored by NASA's Advanced Subsonic Technology (AST) Noise Reduction Program. Emphasis is given to only the engine noise reduction research and significant accomplishments that were investigated at Technology Readiness Levels ranging from 4 to 6. The Engine Noise Reduction sub-element was divided into four work areas: source noise prediction, model scale tests, engine validation, and active noise control. Highlights from each area include technologies for higher bypass ratio turbofans, scarf inlets, forward-swept fans, swept and leaned stators, chevron/tabbed nozzles, advanced noise prediction analyses, and active noise control for fans. Finally, an industry perspective is given from General Electric Aircraft Engines showing how these technologies are being applied to commercial products. This publication contains only presentation vu-graphs from an invited lecture given at the 41st AIAA Aerospace Sciences Meeting, January 6-9, 2003.

Broad Detection of Alterations Predicted to Confer Lack of Benefit From EGFR Antibodies or Sensitivity to Targeted Therapy in Advanced Colorectal Cancer.

PubMed

Rankin, Andrew; Klempner, Samuel J; Erlich, Rachel; Sun, James X; Grothey, Axel; Fakih, Marwan; George, Thomas J; Lee, Jeeyun; Ross, Jeffrey S; Stephens, Philip J; Miller, Vincent A; Ali, Siraj M; Schrock, Alexa B

2016-09-28

A KRAS mutation represented the first genomic biomarker to predict lack of benefit from anti-epidermal growth factor receptor (EGFR) antibody therapy in advanced colorectal cancer (CRC). Expanded RAS testing has further refined the treatment approach, but understanding of genomic alterations underlying primary and acquired resistance is limited and further study is needed. We prospectively analyzed 4,422 clinical samples from patients with advanced CRC, using hybrid-capture based comprehensive genomic profiling (CGP) at the request of the individual treating physicians. Comparison with prior molecular testing results, when available, was performed to assess concordance. We identified a RAS/RAF pathway mutation or amplification in 62% of cases, including samples harboring KRAS mutations outside of the codon 12/13 hotspot region in 6.4% of cases. Among cases with KRAS non-codon 12/13 alterations for which prior test results were available, 79 of 90 (88%) were not identified by focused testing. Of 1,644 RAS/RAF wild-type cases analyzed by CGP, 31% harbored a genomic alteration (GA) associated with resistance to anti-EGFR therapy in advanced CRC including mutations in PIK3CA, PTEN, EGFR, and ERBB2. We also identified other targetable GA, including novel kinase fusions, receptor tyrosine kinase amplification, activating point mutations, as well as microsatellite instability. Extended genomic profiling reliably detects alterations associated with lack of benefit to anti-EGFR therapy in advanced CRC, while simultaneously identifying alterations potentially important in guiding treatment. The use of CGP during the course of clinical care allows for the refined selection of appropriate targeted therapies and clinical trials, increasing the chance of clinical benefit and avoiding therapeutic futility. Comprehensive genomic profiling (CGP) detects diverse genomic alterations associated with lack of benefit to anti-epidermal growth factor receptor therapy in advanced colorectal cancer (CRC), as well as targetable alterations in many other genes. This includes detection of a broad spectrum of activating KRAS alterations frequently missed by focused molecular hotspot testing, as well as other RAS/RAF pathway alterations, mutations shown to disrupt antibody binding, RTK activating point mutations, amplifications, and rearrangements, and activating alterations in downstream effectors including PI3K and MEK1. The use of CGP in clinical practice is critical to guide appropriate selection of targeted therapies for patients with advanced CRC. ©AlphaMed Press.

Advanced composite vertical stabilizer for DC-10 transport aircraft

NASA Technical Reports Server (NTRS)

Stephens, C. O.

1979-01-01

Structural design, tooling, fabrication, and test activities are reported for a program to develop an advanced composite vertical stabilizer (CVS) for the DC 10 Commercial Transport Aircraft. Structural design details are described and the status of structural and weight analyses are reported. A structural weight reduction of 21.7% is currently predicted. Test results are discussed for sine wave stiffened shear webs containing representative of the CVS spar webs and for lightning current transfer and tests on a panel representative of the CVS skins.

CEAS/AIAA/ICASE/NASA Langley International Forum on Aeroelasticity and Structural Dynamics 1999. Pt. 1

NASA Technical Reports Server (NTRS)

Woodrow Whitlow, Jr. (Editor); Todd, Emily N. (Editor)

1999-01-01

These proceedings represent a collection of the latest advances in aeroelasticity and structural dynamics from the world community. Research in the areas of unsteady aerodynamics and aeroelasticity, structural modeling and optimization, active control and adaptive structures, landing dynamics, certification and qualification, and validation testing are highlighted in the collection of papers. The wide range of results will lead to advances in the prediction and control of the structural response of aircraft and spacecraft.

Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

PubMed

Ribay, Kathryn; Kim, Marlene T; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

2016-03-01

Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR models, particularly for the activity cliffs that induce prediction errors. The results of this study indicate that the response profile of chemicals from public data provides useful information for modeling and evaluation purposes. The public big data resources should be considered along with chemical structure information when predicting new compounds, such as unknown ERα binding agents.

Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Folkvord, Sigurd; Flatmark, Kjersti; Department of Cancer and Surgery, Norwegian Radium Hospital, Oslo University Hospital

2010-10-01

Purpose: Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials: Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatmentmore » as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results: In the patient population, 73% and 15% were scored as good responders (TRG 1-2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4-5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions: Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.« less

Functional brain imaging predicts public health campaign success.

PubMed

Falk, Emily B; O'Donnell, Matthew Brook; Tompson, Steven; Gonzalez, Richard; Dal Cin, Sonya; Strecher, Victor; Cummings, Kenneth Michael; An, Lawrence

2016-02-01

Mass media can powerfully affect health decision-making. Pre-testing through focus groups or surveys is a standard, though inconsistent, predictor of effectiveness. Converging evidence demonstrates that activity within brain systems associated with self-related processing can predict individual behavior in response to health messages. Preliminary evidence also suggests that neural activity in small groups can forecast population-level campaign outcomes. Less is known about the psychological processes that link neural activity and population-level outcomes, or how these predictions are affected by message content. We exposed 50 smokers to antismoking messages and used their aggregated neural activity within a 'self-localizer' defined region of medial prefrontal cortex to predict the success of the same campaign messages at the population level (n = 400,000 emails). Results demonstrate that: (i) independently localized neural activity during health message exposure complements existing self-report data in predicting population-level campaign responses (model combined R(2) up to 0.65) and (ii) this relationship depends on message content-self-related neural processing predicts outcomes in response to strong negative arguments against smoking and not in response to compositionally similar neutral images. These data advance understanding of the psychological link between brain and large-scale behavior and may aid the construction of more effective media health campaigns. © The Author (2015). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

THE FUTURE OF TOXICOLOGY-PREDICTIVE TOXICOLOGY ...

EPA Pesticide Factsheets

A chemistry approach to predictive toxicology relies on structure−activity relationship (SAR) modeling to predict biological activity from chemical structure. Such approaches have proven capabilities when applied to well-defined toxicity end points or regions of chemical space. These approaches are less well-suited, however, to the challenges of global toxicity prediction, i.e., to predicting the potential toxicity of structurally diverse chemicals across a wide range of end points of regulatory and pharmaceutical concern. New approaches that have the potential to significantly improve capabilities in predictive toxicology are elaborating the “activity” portion of the SAR paradigm. Recent advances in two areas of endeavor are particularly promising. Toxicity data informatics relies on standardized data schema, developed for particular areas of toxicological study, to facilitate data integration and enable relational exploration and mining of data across both historical and new areas of toxicological investigation. Bioassay profiling refers to large-scale high-throughput screening approaches that use chemicals as probes to broadly characterize biological response space, extending the concept of chemical “properties” to the biological activity domain. The effective capture and representation of legacy and new toxicity data into mineable form and the large-scale generation of new bioassay data in relation to chemical toxicity, both employing chemical stru

Overcoming misconceptions of graph interpretation of kinematics motion using calculator based rangers

NASA Astrophysics Data System (ADS)

Olson, John R.

This is a quasi-experimental study of 261 first year high school students that analyzes gains made through the use of calculator based rangers attached to calculators. The study has qualitative components but is based on quantitative tests. Biechner's TUG-K test was used for the pretest, posttest, and post-posttest. The population was divided into one group that predicted the results before using the CBRs and another that did not predict first but completed the same activities. The data for the groups was further disaggregated into learning style groups (based on Kolb's Learning Styles Inventory), type of class (advanced vs. general physics), and gender. Four instructors used the labs developed by the author for this study and created significant differences between the groups by instructor based on interviews, participant observation and one way ANOVA. No significant differences were found between learning styles based on MANOVA. No significant differences were found between predict and nonpredict groups for the one way ANOVAs or MANOVA, however, some differences do exist as measured by a survey and participant observation. Significant differences do exist between gender and type of class (advanced/general) based on one way ANOVA and MANOVA. The males outscored the females on all tests and the advanced physics scored higher than the general physics on all tests. The advanced physics scoring higher was expected but the difference between genders was not.

A community computational challenge to predict the activity of pairs of compounds.

PubMed

Bansal, Mukesh; Yang, Jichen; Karan, Charles; Menden, Michael P; Costello, James C; Tang, Hao; Xiao, Guanghua; Li, Yajuan; Allen, Jeffrey; Zhong, Rui; Chen, Beibei; Kim, Minsoo; Wang, Tao; Heiser, Laura M; Realubit, Ronald; Mattioli, Michela; Alvarez, Mariano J; Shen, Yao; Gallahan, Daniel; Singer, Dinah; Saez-Rodriguez, Julio; Xie, Yang; Stolovitzky, Gustavo; Califano, Andrea

2014-12-01

Recent therapeutic successes have renewed interest in drug combinations, but experimental screening approaches are costly and often identify only small numbers of synergistic combinations. The DREAM consortium launched an open challenge to foster the development of in silico methods to computationally rank 91 compound pairs, from the most synergistic to the most antagonistic, based on gene-expression profiles of human B cells treated with individual compounds at multiple time points and concentrations. Using scoring metrics based on experimental dose-response curves, we assessed 32 methods (31 community-generated approaches and SynGen), four of which performed significantly better than random guessing. We highlight similarities between the methods. Although the accuracy of predictions was not optimal, we find that computational prediction of compound-pair activity is possible, and that community challenges can be useful to advance the field of in silico compound-synergy prediction.

Contextual signals in visual cortex.

PubMed

Khan, Adil G; Hofer, Sonja B

2018-06-05

Vision is an active process. What we perceive strongly depends on our actions, intentions and expectations. During visual processing, these internal signals therefore need to be integrated with the visual information from the retina. The mechanisms of how this is achieved by the visual system are still poorly understood. Advances in recording and manipulating neuronal activity in specific cell types and axonal projections together with tools for circuit tracing are beginning to shed light on the neuronal circuit mechanisms of how internal, contextual signals shape sensory representations. Here we review recent work, primarily in mice, that has advanced our understanding of these processes, focusing on contextual signals related to locomotion, behavioural relevance and predictions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Biomarkers in inflammatory bowel disease: current practices and recent advances.

PubMed

Iskandar, Heba N; Ciorba, Matthew A

2012-04-01

Crohn's disease and ulcerative colitis represent the two main forms of the idiopathic chronic inflammatory bowel diseases (IBD). Currently available blood and stool based biomarkers provide reproducible, quantitative tools that can complement clinical assessment to aid clinicians in IBD diagnosis and management. C-reactive protein and fecal based leukocyte markers can help the clinician distinguish IBD from noninflammatory diarrhea and assess disease activity. The ability to differentiate between forms of IBD and predict risk for disease complications is specific to serologic tests including antibodies against Saccharomyces cerevisiae and perinuclear antineutrophil cytoplasmic proteins. Advances in genomic, proteomic, and metabolomic array based technologies are facilitating the development of new biomarkers for IBD. The discovery of novel biomarkers, which can correlate with mucosal healing or predict long-term disease course has the potential to significantly improve patient care. This article reviews the uses and limitations of currently available biomarkers and highlights recent advances in IBD biomarker discovery. Copyright © 2012 Mosby, Inc. All rights reserved.

Turbine blade tip durability analysis

NASA Technical Reports Server (NTRS)

Mcknight, R. L.; Laflen, J. H.; Spamer, G. T.

1981-01-01

An air-cooled turbine blade from an aircraft gas turbine engine chosen for its history of cracking was subjected to advanced analytical and life-prediction techniques. The utility of advanced structural analysis techniques and advanced life-prediction techniques in the life assessment of hot section components are verified. Three dimensional heat transfer and stress analyses were applied to the turbine blade mission cycle and the results were input into advanced life-prediction theories. Shortcut analytical techniques were developed. The proposed life-prediction theories are evaluated.

Assessment of Predictive Capabilities of L1 Orbiters using Realtime Solar Wind Data

NASA Astrophysics Data System (ADS)

Holmes, J.; Kasper, J. C.; Welling, D. T.

2017-12-01

Realtime measurements of solar wind conditions at L1 point allow us to predict geomagnetic activity at Earth up to an hour in advance. These predictions are quantified in the form of geomagnetic indices such as Kp and Ap, allowing for a concise, standardized prediction and measurement system. For years, the Space Weather Prediction Center used ACE realtime solar wind data to develop its one and four-hour Kp forecasts, but has in the past year switched to using DSCOVR data as its source. In this study, the performance of both orbiters in predicting Kp over the course of one month was assessed in an attempt to determine whether or not switching to DSCOVR data has resulted in improved forecasts. The period of study was chosen to encompass a time when the satellites were close to each other, and when moderate to high activity was observed. Kp predictions were made using the Geospace Model, part of the Space Weather Modeling Framework, to simulate conditions based on observed solar wind parameters. The performance of each satellite was assessed by comparing the model output to observed data.

Neuroimaging explanations of age-related differences in task performance.

PubMed

Steffener, Jason; Barulli, Daniel; Habeck, Christian; Stern, Yaakov

2014-01-01

Advancing age affects both cognitive performance and functional brain activity and interpretation of these effects has led to a variety of conceptual research models without always explicitly linking the two effects. However, to best understand the multifaceted effects of advancing age, age differences in functional brain activity need to be explicitly tied to the cognitive task performance. This work hypothesized that age-related differences in task performance are partially explained by age-related differences in functional brain activity and formally tested these causal relationships. Functional MRI data was from groups of young and old adults engaged in an executive task-switching experiment. Analyses were voxel-wise testing of moderated-mediation and simple mediation statistical path models to determine whether age group, brain activity and their interaction explained task performance in regions demonstrating an effect of age group. Results identified brain regions whose age-related differences in functional brain activity significantly explained age-related differences in task performance. In all identified locations, significant moderated-mediation relationships resulted from increasing brain activity predicting worse (slower) task performance in older but not younger adults. Findings suggest that advancing age links task performance to the level of brain activity. The overall message of this work is that in order to understand the role of functional brain activity on cognitive performance, analysis methods should respect theoretical relationships. Namely, that age affects brain activity and brain activity is related to task performance.

Lowered quality of life in mood disorders is associated with increased neuro-oxidative stress and basal thyroid-stimulating hormone levels and use of anticonvulsant mood stabilizers.

PubMed

Nunes, Caroline Sampaio; Maes, Michael; Roomruangwong, Chutima; Moraes, Juliana Brum; Bonifacio, Kamila Landucci; Vargas, Heber Odebrecht; Barbosa, Decio Sabbatini; Anderson, George; de Melo, Luiz Gustavo Piccoli; Drozdstoj, Stoyanov; Moreira, Estefania; Carvalho, André F; Nunes, Sandra Odebrecht Vargas

2018-04-17

Major affective disorders including bipolar disorder (BD) and major depressive disorder (MDD) are associated with impaired health-related quality of life (HRQoL). Oxidative stress and subtle thyroid abnormalities may play a pathophysiological role in both disorders. Thus, the current study was performed to examine whether neuro-oxidative biomarkers and thyroid-stimulating hormone (TSH) levels could predict HRQoL in BD and MDD. This cross-sectional study enrolled 68 BD and 37 MDD patients and 66 healthy controls. The World Health Organization (WHO) QoL-BREF scale was used to assess 4 QoL subdomains. Peripheral blood malondialdehyde (MDA), advanced oxidation protein products, paraoxonaxe/CMPAase activity, a composite index of nitro-oxidative stress, and basal TSH were measured. In the total WHOQoL score, 17.3% of the variance was explained by increased advanced oxidation protein products and TSH levels and lowered CMPAase activity and male gender. Physical HRQoL (14.4%) was associated with increased MDA and TSH levels and lowered CMPAase activity. Social relations HRQoL (17.4%) was predicted by higher nitro-oxidative index and TSH values, while mental and environment HRQoL were independently predicted by CMPAase activity. Finally, 73.0% of the variance in total HRQoL was explained by severity of depressive symptoms, use of anticonvulsants, lower income, early lifetime emotional neglect, MDA levels, the presence of mood disorders, and suicidal ideation. These data show that lowered HRQoL in major affective disorders could at least in part result from the effects of lipid peroxidation, protein oxidation, lowered antioxidant enzyme activities, and higher levels of TSH. © 2018 John Wiley & Sons, Ltd.

Thermal Transients Excite Neurons through Universal Intramembrane Mechanoelectrical Effects

NASA Astrophysics Data System (ADS)

Plaksin, Michael; Shapira, Einat; Kimmel, Eitan; Shoham, Shy

2018-01-01

Modern advances in neurotechnology rely on effectively harnessing physical tools and insights towards remote neural control, thereby creating major new scientific and therapeutic opportunities. Specifically, rapid temperature pulses were shown to increase membrane capacitance, causing capacitive currents that explain neural excitation, but the underlying biophysics is not well understood. Here, we show that an intramembrane thermal-mechanical effect wherein the phospholipid bilayer undergoes axial narrowing and lateral expansion accurately predicts a potentially universal thermal capacitance increase rate of ˜0.3 % /°C . This capacitance increase and concurrent changes in the surface charge related fields lead to predictable exciting ionic displacement currents. The new MechanoElectrical Thermal Activation theory's predictions provide an excellent agreement with multiple experimental results and indirect estimates of latent biophysical quantities. Our results further highlight the role of electro-mechanics in neural excitation; they may also help illuminate subthreshold and novel physical cellular effects, and could potentially lead to advanced new methods for neural control.

Solar activity prediction

NASA Technical Reports Server (NTRS)

Slutz, R. J.; Gray, T. B.; West, M. L.; Stewart, F. G.; Leftin, M.

1971-01-01

A statistical study of formulas for predicting the sunspot number several years in advance is reported. By using a data lineup with cycle maxima coinciding, and by using multiple and nonlinear predictors, a new formula which gives better error estimates than former formulas derived from the work of McNish and Lincoln is obtained. A statistical analysis is conducted to determine which of several mathematical expressions best describes the relationship between 10.7 cm solar flux and Zurich sunspot numbers. Attention is given to the autocorrelation of the observations, and confidence intervals for the derived relationships are presented. The accuracy of predicting a value of 10.7 cm solar flux from a predicted sunspot number is dicussed.

Baseline Assessment and Prioritization Framework for IVHM Integrity Assurance Enabling Capabilities

NASA Technical Reports Server (NTRS)

Cooper, Eric G.; DiVito, Benedetto L.; Jacklin, Stephen A.; Miner, Paul S.

2009-01-01

Fundamental to vehicle health management is the deployment of systems incorporating advanced technologies for predicting and detecting anomalous conditions in highly complex and integrated environments. Integrated structural integrity health monitoring, statistical algorithms for detection, estimation, prediction, and fusion, and diagnosis supporting adaptive control are examples of advanced technologies that present considerable verification and validation challenges. These systems necessitate interactions between physical and software-based systems that are highly networked with sensing and actuation subsystems, and incorporate technologies that are, in many respects, different from those employed in civil aviation today. A formidable barrier to deploying these advanced technologies in civil aviation is the lack of enabling verification and validation tools, methods, and technologies. The development of new verification and validation capabilities will not only enable the fielding of advanced vehicle health management systems, but will also provide new assurance capabilities for verification and validation of current generation aviation software which has been implicated in anomalous in-flight behavior. This paper describes the research focused on enabling capabilities for verification and validation underway within NASA s Integrated Vehicle Health Management project, discusses the state of the art of these capabilities, and includes a framework for prioritizing activities.

Macromolecular target prediction by self-organizing feature maps.

PubMed

Schneider, Gisbert; Schneider, Petra

2017-03-01

Rational drug discovery would greatly benefit from a more nuanced appreciation of the activity of pharmacologically active compounds against a diverse panel of macromolecular targets. Already, computational target-prediction models assist medicinal chemists in library screening, de novo molecular design, optimization of active chemical agents, drug re-purposing, in the spotting of potential undesired off-target activities, and in the 'de-orphaning' of phenotypic screening hits. The self-organizing map (SOM) algorithm has been employed successfully for these and other purposes. Areas covered: The authors recapitulate contemporary artificial neural network methods for macromolecular target prediction, and present the basic SOM algorithm at a conceptual level. Specifically, they highlight consensus target-scoring by the employment of multiple SOMs, and discuss the opportunities and limitations of this technique. Expert opinion: Self-organizing feature maps represent a straightforward approach to ligand clustering and classification. Some of the appeal lies in their conceptual simplicity and broad applicability domain. Despite known algorithmic shortcomings, this computational target prediction concept has been proven to work in prospective settings with high success rates. It represents a prototypic technique for future advances in the in silico identification of the modes of action and macromolecular targets of bioactive molecules.

Has climatic warming altered spring flowering date of Sonoran Desert shrubs?

USGS Publications Warehouse

Bowers, Janice E.

2007-01-01

With global warming, flowering at many locations has shifted toward earlier dates of bloom. A steady increase in average annual temperature since the late 1890s makes it likely that flowering also has advanced in the northern Sonoran Desert of the southwestern United States and northwestern Mexico. In this study, phenological models were used to predict annual date of spring bloom in the northern Sonoran Desert from 1894 to 2004; then, herbarium specimens were assessed for objective evidence of the predicted shift in flowering time. The phenological models were derived from known flowering requirements (triggers and heat sums) of Sonoran Desert shrubs. According to the models, flowering might have advanced by 20-41 d from 1894 to 2004. Analysis of herbarium specimens collected during the 20th century supported the model predictions. Over time, there was a significant increase in the proportion of shrub specimens collected in flower in March and a significant decrease in the proportion collected in May. Thus, the flowering curve - the proportion of individuals in flower in each spring month - shifted toward the start of the calendar year between 1900 and 1999. This shift could not be explained by collection activity: collectors showed no tendency to be active earlier in the year as time went on, nor did activity toward the end of spring decline in recent decades. Earlier bloom eventually could have substantial impacts on plant and animal communities in the Sonoran Desert, especially on migratory hummingbirds and population dynamics of shrubs.

Hyper-active gap filling

PubMed Central

Omaki, Akira; Lau, Ellen F.; Davidson White, Imogen; Dakan, Myles L.; Apple, Aaron; Phillips, Colin

2015-01-01

Much work has demonstrated that speakers of verb-final languages are able to construct rich syntactic representations in advance of verb information. This may reflect general architectural properties of the language processor, or it may only reflect a language-specific adaptation to the demands of verb-finality. The present study addresses this issue by examining whether speakers of a verb-medial language (English) wait to consult verb transitivity information before constructing filler-gap dependencies, where internal arguments are fronted and hence precede the verb. This configuration makes it possible to investigate whether the parser actively makes representational commitments on the gap position before verb transitivity information becomes available. A key prediction of the view that rich pre-verbal structure building is a general architectural property is that speakers of verb-medial languages should predictively construct dependencies in advance of verb transitivity information, and therefore that disruption should be observed when the verb has intransitive subcategorization frames that are incompatible with the predicted structure. In three reading experiments (self-paced and eye-tracking) that manipulated verb transitivity, we found evidence for reading disruption when the verb was intransitive, although no such reading difficulty was observed when the critical verb was embedded inside a syntactic island structure, which blocks filler-gap dependency completion. These results are consistent with the hypothesis that in English, as in verb-final languages, information from preverbal noun phrases is sufficient to trigger active dependency completion without having access to verb transitivity information. PMID:25914658

Hyper-active gap filling.

PubMed

Omaki, Akira; Lau, Ellen F; Davidson White, Imogen; Dakan, Myles L; Apple, Aaron; Phillips, Colin

2015-01-01

Much work has demonstrated that speakers of verb-final languages are able to construct rich syntactic representations in advance of verb information. This may reflect general architectural properties of the language processor, or it may only reflect a language-specific adaptation to the demands of verb-finality. The present study addresses this issue by examining whether speakers of a verb-medial language (English) wait to consult verb transitivity information before constructing filler-gap dependencies, where internal arguments are fronted and hence precede the verb. This configuration makes it possible to investigate whether the parser actively makes representational commitments on the gap position before verb transitivity information becomes available. A key prediction of the view that rich pre-verbal structure building is a general architectural property is that speakers of verb-medial languages should predictively construct dependencies in advance of verb transitivity information, and therefore that disruption should be observed when the verb has intransitive subcategorization frames that are incompatible with the predicted structure. In three reading experiments (self-paced and eye-tracking) that manipulated verb transitivity, we found evidence for reading disruption when the verb was intransitive, although no such reading difficulty was observed when the critical verb was embedded inside a syntactic island structure, which blocks filler-gap dependency completion. These results are consistent with the hypothesis that in English, as in verb-final languages, information from preverbal noun phrases is sufficient to trigger active dependency completion without having access to verb transitivity information.

Neuroforecasting Aggregate Choice

PubMed Central

Knutson, Brian; Genevsky, Alexander

2018-01-01

Advances in brain-imaging design and analysis have allowed investigators to use neural activity to predict individual choice, while emerging Internet markets have opened up new opportunities for forecasting aggregate choice. Here, we review emerging research that bridges these levels of analysis by attempting to use group neural activity to forecast aggregate choice. A survey of initial findings suggests that components of group neural activity might forecast aggregate choice, in some cases even beyond traditional behavioral measures. In addition to demonstrating the plausibility of neuroforecasting, these findings raise the possibility that not all neural processes that predict individual choice forecast aggregate choice to the same degree. We propose that although integrative choice components may confer more consistency within individuals, affective choice components may generalize more broadly across individuals to forecast aggregate choice. PMID:29706726

FY2016 Ceramic Fuels Development Annual Highlights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mcclellan, Kenneth James

Key challenges for the Advanced Fuels Campaign are the development of fuel technologies to enable major increases in fuel performance (safety, reliability, power and burnup) beyond current technologies, and development of characterization methods and predictive fuel performance models to enable more efficient development and licensing of advanced fuels. Ceramic fuel development activities for fiscal year 2016 fell within the areas of 1) National and International Technical Integration, 2) Advanced Accident Tolerant Ceramic Fuel Development, 3) Advanced Techniques and Reference Materials Development, and 4) Fabrication of Enriched Ceramic Fuels. High uranium density fuels were the focus of the ceramic fuels efforts.more » Accomplishments for FY16 primarily reflect the prioritization of identification and assessment of new ceramic fuels for light water reactors which have enhanced accident tolerance while also maintaining or improving normal operation performance, and exploration of advanced post irradiation examination techniques which will support more efficient testing and qualification of new fuel systems.« less

Predicting Persuasion-Induced Behavior Change from the Brain

PubMed Central

Falk, Emily B.; Berkman, Elliot T.; Mann, Traci; Harrison, Brittany; Lieberman, Matthew D.

2011-01-01

Although persuasive messages often alter people’s self-reported attitudes and intentions to perform behaviors, these self-reports do not necessarily predict behavior change. We demonstrate that neural responses to persuasive messages can predict variability in behavior change in the subsequent week. Specifically, an a priori region of interest (ROI) in medial prefrontal cortex (MPFC) was reliably associated with behavior change (r = 0.49, p < 0.05). Additionally, an iterative cross-validation approach using activity in this MPFC ROI predicted an average 23% of the variance in behavior change beyond the variance predicted by self-reported attitudes and intentions. Thus, neural signals can predict behavioral changes that are not predicted from self-reported attitudes and intentions alone. Additionally, this is the first functional magnetic resonance imaging study to demonstrate that a neural signal can predict complex real world behavior days in advance. PMID:20573889

World War II Mobilization in Men’s Work Lives: Continuity or Disruption for the Middle Class?1

PubMed Central

Dechter, Aimée R.; Elder, Glen H.

2016-01-01

The labor needs of World War II fueled a growing demand for both military and war industry personnel. This longitudinal study investigates mobilization into these competing activities and their work life effects among men from the middle class. Hazard estimates show significant differences in wartime activities across occupations, apart from other deferment criteria. By war’s end, critical employment, in contrast to military service, is positively associated with supervisory responsibility for younger men and with occupation change. This empoloyment does not predict postwar career advancement up to the 1970s. By comparison, men who were officers had a “pipeline” to advancement after the war, whereas other service men fared worse than nonveterans. PMID:27656001

Perspective on computational and structural aspects of kinase discovery from IPK2014.

PubMed

Martin, Eric; Knapp, Stefan; Engh, Richard A; Moebitz, Henrik; Varin, Thibault; Roux, Benoit; Meiler, Jens; Berdini, Valerio; Baumann, Alexander; Vieth, Michal

2015-10-01

Recent advances in understanding the activity and selectivity of kinase inhibitors and their relationships to protein structure are presented. Conformational selection in kinases is studied from empirical, data-driven and simulation approaches. Ligand binding and its affinity are, in many cases, determined by the predetermined active and inactive conformation of kinases. Binding affinity and selectivity predictions highlight the current state of the art and advances in computational chemistry as it applies to kinase inhibitor discovery. Kinome wide inhibitor profiling and cell panel profiling lead to a better understanding of selectivity and allow for target validation and patient tailoring hypotheses. This article is part of a Special Issue entitled: Inhibitors of Protein Kinases. Copyright © 2015 Elsevier B.V. All rights reserved.

Classroom Emotional Support Predicts Differences in Preschool Children's Cortisol and Alpha-Amylase Levels

ERIC Educational Resources Information Center

Hatfield, Bridget E.; Hestenes, Linda L.; Kintner-Duffy, Victoria L.; O'Brien, Marion

2013-01-01

Accumulating evidence suggests children enrolled in full-time child care often display afternoon elevations of the hormone cortisol, which is an indicator of stress. Recent advances in immunoassays allow for measurement of activity in the hypothalamic-pituitary-adrenal axis and the autonomic sympathetic nervous system from saliva, and measurement…

Individualized relapse prediction: Personality measures and striatal and insular activity during reward-processing robustly predict relapse.

PubMed

Gowin, Joshua L; Ball, Tali M; Wittmann, Marc; Tapert, Susan F; Paulus, Martin P

2015-07-01

Nearly half of individuals with substance use disorders relapse in the year after treatment. A diagnostic tool to help clinicians make decisions regarding treatment does not exist for psychiatric conditions. Identifying individuals with high risk for relapse to substance use following abstinence has profound clinical consequences. This study aimed to develop neuroimaging as a robust tool to predict relapse. 68 methamphetamine-dependent adults (15 female) were recruited from 28-day inpatient treatment. During treatment, participants completed a functional MRI scan that examined brain activation during reward processing. Patients were followed 1 year later to assess abstinence. We examined brain activation during reward processing between relapsing and abstaining individuals and employed three random forest prediction models (clinical and personality measures, neuroimaging measures, a combined model) to generate predictions for each participant regarding their relapse likelihood. 18 individuals relapsed. There were significant group by reward-size interactions for neural activation in the left insula and right striatum for rewards. Abstaining individuals showed increased activation for large, risky relative to small, safe rewards, whereas relapsing individuals failed to show differential activation between reward types. All three random forest models yielded good test characteristics such that a positive test for relapse yielded a likelihood ratio 2.63, whereas a negative test had a likelihood ratio of 0.48. These findings suggest that neuroimaging can be developed in combination with other measures as an instrument to predict relapse, advancing tools providers can use to make decisions about individualized treatment of substance use disorders. Published by Elsevier Ireland Ltd.

Gemcitabine-Based Chemotherapy in Adrenocortical Carcinoma: A Multicenter Study of Efficacy and Predictive Factors.

PubMed

Henning, Judith E K; Deutschbein, Timo; Altieri, Barbara; Steinhauer, Sonja; Kircher, Stefan; Sbiera, Silviu; Wild, Vanessa; Schlötelburg, Wiebke; Kroiss, Matthias; Perotti, Paola; Rosenwald, Andreas; Berruti, Alfredo; Fassnacht, Martin; Ronchi, Cristina L

2017-11-01

Adrenocortical carcinoma (ACC) is rare and confers an unfavorable prognosis in advanced stages. Other than combination chemotherapy with cisplatin, etoposide, doxorubicin, and mitotane, the second- and third-line regimens are not well-established. Gemcitabine (GEM)-based chemotherapy was suggested in a phase 2 clinical trial with 28 patients. In other solid tumors, human equilibrative nucleoside transporter type 1 (hENT1) and/or ribonucleotide reductase catalytic subunit M1 (RRM1) expression have been associated with resistance to GEM. To assess the efficacy of GEM-based chemotherapy in ACC in a real-world setting and the predictive role of molecular parameters. Retrospective multicenter study. Referral centers of university hospitals. A total of 145 patients with advanced ACC were treated with GEM-based chemotherapy (132 with concomitant capecitabine). Formalin-fixed paraffin-embedded tumor material was available for 70 patients for immunohistochemistry. The main outcome measures were progression-free survival (PFS) and an objective response to GEM-based chemotherapy. The secondary objective was the predictive role of hENT1 and RRM1. The median PFS for the patient population was 12 weeks (range, 1 to 94). A partial response or stable disease was achieved in 4.9% and 25.0% of cases, with a median duration of 26.8 weeks. Treatment was generally well tolerated, with adverse events of grade 3 or 4 occurring in 11.0% of cases. No substantial effect of hENT1 and/or RRM1 expression was observed in response to GEM-based chemotherapy. GEM-based chemotherapy is a well-tolerated, but modestly active, regimen against advanced ACC. No reliable molecular predictive factors could be identified. Owing to the scarce alternative therapeutic options, GEM-based chemotherapy remains an important option for salvage treatment for advanced ACC. Copyright © 2017 Endocrine Society

Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer.

PubMed

Xia, Shu; Kohli, Manish; Du, Meijun; Dittmar, Rachel L; Lee, Adam; Nandy, Debashis; Yuan, Tiezheng; Guo, Yongchen; Wang, Yuan; Tschannen, Michael R; Worthey, Elizabeth; Jacob, Howard; See, William; Kilari, Deepak; Wang, Xuexia; Hovey, Raymond L; Huang, Chiang-Ching; Wang, Liang

2015-06-30

Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer.

Advanced numerical models and material characterisation techniques for composite materials subject to impact and shock wave loading

NASA Astrophysics Data System (ADS)

Clegg, R. A.; White, D. M.; Hayhurst, C.; Ridel, W.; Harwick, W.; Hiermaier, S.

2003-09-01

The development and validation of an advanced material model for orthotropic materials, such as fibre reinforced composites, is described. The model is specifically designed to facilitate the numerical simulation of impact and shock wave propagation through orthotropic materials and the prediction of subsequent material damage. Initial development of the model concentrated on correctly representing shock wave propagation in composite materials under high and hypervelocity impact conditions [1]. This work has now been extended to further concentrate on the development of improved numerical models and material characterisation techniques for the prediction of damage, including residual strength, in fibre reinforced composite materials. The work is focussed on Kevlar-epoxy however materials such as CFRP are also being considered. The paper describes our most recent activities in relation to the implementation of advanced material modelling options in this area. These enable refined non-liner directional characteristics of composite materials to be modelled, in addition to the correct thermodynamic response under shock wave loading. The numerical work is backed by an extensive experimental programme covering a wide range of static and dynamic tests to facilitate derivation of model input data and to validate the predicted material response. Finally, the capability of the developing composite material model is discussed in relation to a hypervelocity impact problem.

The association of DNA-dependent protein kinase activity of peripheral blood lymphocytes with prognosis of cancer

PubMed Central

Someya, M; Sakata, K-i; Matsumoto, Y; Kamdar, R P; Kai, M; Toyota, M; Hareyama, M

2011-01-01

Background: Repair of various types of DNA damages is critical for genomic stability. DNA-dependent protein kinase (DNA-PK) has an important role in DNA double-strand break repair. We examined whether there may be a correlation between DNA-PK activity in peripheral blood lymphocytes (PBLs) and survival percentages in various cancer patients. We also investigated the changes of DNA-PK activity in PBLs after radiotherapy. Methods: A total of 167 of untreated cancer patients participated in this study. Peripheral blood was collected, separated, and centrifuged. DNA-PK activity was measured by DNA-pull-down assay. Chromosomal aberrations were examined by cytogenetic methods. Results: DNA-PK activity of PBLs in advanced cancer patients was significantly lower than that in early stage. The patients with lower DNA-PK activity in PBLs tended to have the lower disease-specific survivals and distant metastasis-free survivals than those with higher DNA-PK activity in advanced stages. There was also a tendency of inverse correlation between DNA-PK activity and excess fragments. The DNA-PK activity of PBLs in most patients decreased in response to radiation as the equivalent whole-body dose increased. Conclusion: Cancer patients in advanced stage, with lower DNA-PK activity of PBLs might have higher distant metastasis and exhibit poorer prognosis. Therefore, DNA-PK activity in PBLs could be used as a marker to predict the chromosomal instability and poorer prognosis. PMID:21559021

Levels of circulating soluble receptor activator of NF-κB and interleukins-1 predicting outcome of locally advanced basal cell carcinoma.

PubMed

Lin, Quan; Li, Yan; Zhang, Duo; Jin, Hongjuan

2016-12-01

Decreasing levels of cytokines are associated with better responses to therapies, while increasing levels are related to progression or recurrence and decreased survival. NF-κB's role in the cell cycle and its ubiquity are only stressed out by the evidence for the importance of activation (aberrant activation in the majority of cancers) of both canonical and non-canonical pathways in advanced basal cell carcinomas (aBCCs), a subset of basal cell carcinoma (BCC). NF-κB acts through its canonical, or classical, form activated by interleukin-1 (IL-1), regulates cytoprotective, innate, and adaptive immune responses. However, NF-κB2 often acts through its non-canonical or alternate pathway. During the two-year study period, we selected 21 patients presenting with aBCCs due to delay in accessing medical attention with an advanced form of BCCs (n = 19) and infiltrative BCCs (n = 2). Initial diagnosis of BCCs of head and neck was made clinically and verified by skin biopsy. Venous blood was drawn and serum was obtained. Samples were collected at baseline and every three days thereafter (days 3, 6, 9, etc. until surgery). Antigenes' quantities (cytokines) were determined by ELISA kits. Initially, the mean value of all cytokine subjects was significantly different related to the control group (P <0.05). Changes in serum levels of circulating soluble receptor activator of NF-κB and interleukins-1 (α and β) were observed following the surgery. Changes in serum levels of circulating soluble receptor activator of NF-κB and interleukins-1 (α and β) are evident throughout our study period and a certain regularity in its dynamics is evident as the follow-up period moves away. It was therefore concluded that measurement of these factors might be useful in predicting the overall outcome of patients with aBCCs. This study highlights the systemic effects of aBCCs, but further studies are required on this topic. © The Author(s) 2016.

Levels of circulating soluble receptor activator of NF-κB and interleukins-1 predicting outcome of locally advanced basal cell carcinoma

PubMed Central

Lin, Quan; Li, Yan; Zhang, Duo; Jin, Hongjuan

2016-01-01

Decreasing levels of cytokines are associated with better responses to therapies, while increasing levels are related to progression or recurrence and decreased survival. NF-κB’s role in the cell cycle and its ubiquity are only stressed out by the evidence for the importance of activation (aberrant activation in the majority of cancers) of both canonical and non-canonical pathways in advanced basal cell carcinomas (aBCCs), a subset of basal cell carcinoma (BCC). NF-κB acts through its canonical, or classical, form activated by interleukin-1 (IL-1), regulates cytoprotective, innate, and adaptive immune responses. However, NF-κB2 often acts through its non-canonical or alternate pathway. During the two-year study period, we selected 21 patients presenting with aBCCs due to delay in accessing medical attention with an advanced form of BCCs (n = 19) and infiltrative BCCs (n = 2). Initial diagnosis of BCCs of head and neck was made clinically and verified by skin biopsy. Venous blood was drawn and serum was obtained. Samples were collected at baseline and every three days thereafter (days 3, 6, 9, etc. until surgery). Antigenes’ quantities (cytokines) were determined by ELISA kits. Initially, the mean value of all cytokine subjects was significantly different related to the control group (P <0.05). Changes in serum levels of circulating soluble receptor activator of NF-κB and interleukins-1 (α and β) were observed following the surgery. Changes in serum levels of circulating soluble receptor activator of NF-κB and interleukins-1 (α and β) are evident throughout our study period and a certain regularity in its dynamics is evident as the follow-up period moves away. It was therefore concluded that measurement of these factors might be useful in predicting the overall outcome of patients with aBCCs. This study highlights the systemic effects of aBCCs, but further studies are required on this topic. PMID:27760847

Increased phosphorylation of ERK1/2 is associated with worse chemotherapeutic outcome and a poor prognosis in advanced lung adenocarcinoma.

PubMed

Tsujino, Ichiro; Nakanishi, Yoko; Hiranuma, Hisato; Shimizu, Tetsuo; Hirotani, Yukari; Ohni, Sumie; Ouchi, Yasushi; Takahashi, Noriaki; Nemoto, Norimichi; Hashimoto, Shu

2016-06-01

Constitutive activation of extracellular signal-regulated kinase (ERK)1/2 pathway, that is activated by various stimuli including growth factors and oncogenic driver mutations, is observed in various cancers. However, the difference of the activated levels of the pathway is still unclear in clinical significances. The aim of this study was to investigate the effect of different ERK1/2 pathway activation, assessed by the expression levels of phosphorylated (p) ERK1/2, on the prognosis of advanced lung adenocarcinoma patients. Paraffin-embedded lung biopsy samples were obtained from 85 lung adenocarcinoma patients. Correlation between pERK1/2 expression levels that were assessed by immunohistochemistry (IHC) analysis and oncogenic driver mutation status, clinicopathological factors, outcome from standard anticancer therapies, and prognosis was investigated. Varying levels of pERK1/2 expression were observed in 68 (80.0 %) patients. The overall survival was significantly reduced in patients with higher pERK1/2 expression in comparison to those with lower expression levels (P = 0.03). In particular, higher pERK1/2 expression levels correlated with worse performance status and worse clinical outcome. Thus, the IHC analysis of pERK1/2 expression levels may predict patient prognosis in advanced lung adenocarcinoma. Inhibition of ERK1/2 pathway activated by various signals may improve the effects of standard chemotherapies and the clinical condition of patients with advanced cancer.

GT-CATS: Tracking Operator Activities in Complex Systems

NASA Technical Reports Server (NTRS)

Callantine, Todd J.; Mitchell, Christine M.; Palmer, Everett A.

1999-01-01

Human operators of complex dynamic systems can experience difficulties supervising advanced control automation. One remedy is to develop intelligent aiding systems that can provide operators with context-sensitive advice and reminders. The research reported herein proposes, implements, and evaluates a methodology for activity tracking, a form of intent inferencing that can supply the knowledge required for an intelligent aid by constructing and maintaining a representation of operator activities in real time. The methodology was implemented in the Georgia Tech Crew Activity Tracking System (GT-CATS), which predicts and interprets the actions performed by Boeing 757/767 pilots navigating using autopilot flight modes. This report first describes research on intent inferencing and complex modes of automation. It then provides a detailed description of the GT-CATS methodology, knowledge structures, and processing scheme. The results of an experimental evaluation using airline pilots are given. The results show that GT-CATS was effective in predicting and interpreting pilot actions in real time.

Advancing alternatives analysis: The role of predictive toxicology in selecting safer chemical products and processes.

PubMed

Malloy, Timothy; Zaunbrecher, Virginia; Beryt, Elizabeth; Judson, Richard; Tice, Raymond; Allard, Patrick; Blake, Ann; Cote, Ila; Godwin, Hilary; Heine, Lauren; Kerzic, Patrick; Kostal, Jakub; Marchant, Gary; McPartland, Jennifer; Moran, Kelly; Nel, Andre; Ogunseitan, Oladele; Rossi, Mark; Thayer, Kristina; Tickner, Joel; Whittaker, Margaret; Zarker, Ken

2017-09-01

Alternatives analysis (AA) is a method used in regulation and product design to identify, assess, and evaluate the safety and viability of potential substitutes for hazardous chemicals. It requires toxicological data for the existing chemical and potential alternatives. Predictive toxicology uses in silico and in vitro approaches, computational models, and other tools to expedite toxicological data generation in a more cost-effective manner than traditional approaches. The present article briefly reviews the challenges associated with using predictive toxicology in regulatory AA, then presents 4 recommendations for its advancement. It recommends using case studies to advance the integration of predictive toxicology into AA, adopting a stepwise process to employing predictive toxicology in AA beginning with prioritization of chemicals of concern, leveraging existing resources to advance the integration of predictive toxicology into the practice of AA, and supporting transdisciplinary efforts. The further incorporation of predictive toxicology into AA would advance the ability of companies and regulators to select alternatives to harmful ingredients, and potentially increase the use of predictive toxicology in regulation more broadly. Integr Environ Assess Manag 2017;13:915-925. © 2017 SETAC. © 2017 SETAC.

The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.

PubMed

Weilnhammer, Veith A; Stuke, Heiner; Sterzer, Philipp; Schmack, Katharina

2018-05-23

Sensory information is inherently noisy, sparse, and ambiguous. In contrast, visual experience is usually clear, detailed, and stable. Bayesian theories of perception resolve this discrepancy by assuming that prior knowledge about the causes underlying sensory stimulation actively shapes perceptual decisions. The CNS is believed to entertain a generative model aligned to dynamic changes in the hierarchical states of our volatile sensory environment. Here, we used model-based fMRI to study the neural correlates of the dynamic updating of hierarchically structured predictions in male and female human observers. We devised a crossmodal associative learning task with covertly interspersed ambiguous trials in which participants engaged in hierarchical learning based on changing contingencies between auditory cues and visual targets. By inverting a Bayesian model of perceptual inference, we estimated individual hierarchical predictions, which significantly biased perceptual decisions under ambiguity. Although "high-level" predictions about the cue-target contingency correlated with activity in supramodal regions such as orbitofrontal cortex and hippocampus, dynamic "low-level" predictions about the conditional target probabilities were associated with activity in retinotopic visual cortex. Our results suggest that our CNS updates distinct representations of hierarchical predictions that continuously affect perceptual decisions in a dynamically changing environment. SIGNIFICANCE STATEMENT Bayesian theories posit that our brain entertains a generative model to provide hierarchical predictions regarding the causes of sensory information. Here, we use behavioral modeling and fMRI to study the neural underpinnings of such hierarchical predictions. We show that "high-level" predictions about the strength of dynamic cue-target contingencies during crossmodal associative learning correlate with activity in orbitofrontal cortex and the hippocampus, whereas "low-level" conditional target probabilities were reflected in retinotopic visual cortex. Our findings empirically corroborate theorizations on the role of hierarchical predictions in visual perception and contribute substantially to a longstanding debate on the link between sensory predictions and orbitofrontal or hippocampal activity. Our work fundamentally advances the mechanistic understanding of perceptual inference in the human brain. Copyright © 2018 the authors 0270-6474/18/385008-14$15.00/0.

Coupling of snow and permafrost processes using the Basic Modeling Interface (BMI)

NASA Astrophysics Data System (ADS)

Wang, K.; Overeem, I.; Jafarov, E. E.; Piper, M.; Stewart, S.; Clow, G. D.; Schaefer, K. M.

2017-12-01

We developed a permafrost modeling tool based by implementing the Kudryavtsev empirical permafrost active layer depth model (the so-called "Ku" component). The model is specifically set up to have a basic model interface (BMI), which enhances the potential coupling to other earth surface processes model components. This model is accessible through the Web Modeling Tool in Community Surface Dynamics Modeling System (CSDMS). The Kudryavtsev model has been applied for entire Alaska to model permafrost distribution at high spatial resolution and model predictions have been verified by Circumpolar Active Layer Monitoring (CALM) in-situ observations. The Ku component uses monthly meteorological forcing, including air temperature, snow depth, and snow density, and predicts active layer thickness (ALT) and temperature on the top of permafrost (TTOP), which are important factors in snow-hydrological processes. BMI provides an easy approach to couple the models with each other. Here, we provide a case of coupling the Ku component to snow process components, including the Snow-Degree-Day (SDD) method and Snow-Energy-Balance (SEB) method, which are existing components in the hydrological model TOPOFLOW. The work flow is (1) get variables from meteorology component, set the values to snow process component, and advance the snow process component, (2) get variables from meteorology and snow component, provide these to the Ku component and advance, (3) get variables from snow process component, set the values to meteorology component, and advance the meteorology component. The next phase is to couple the permafrost component with fully BMI-compliant TOPOFLOW hydrological model, which could provide a useful tool to investigate the permafrost hydrological effect.

Intrinsic resistance to EGFR tyrosine kinase inhibitors in advanced non-small-cell lung cancer with activating EGFR mutations

PubMed Central

Wang, Jun; Wang, Baocheng; Chu, Huili; Yao, Yunfeng

2016-01-01

Identifying activating EGFR mutations is a useful predictive strategy that helps select a population of advanced non-small-cell lung cancer (NSCLC) patients for treatment with EGFR tyrosine kinase inhibitors (TKIs). Patients with sensitizing EGFR mutations (predominantly an in-frame deletion in exon 19 and an L858R substitution) are highly responsive to first-generation EGFR TKIs, such as gefitinib and erlotinib, and show improved progression-free survival without serious side effects. However, all patients with activating EGFR mutations who are initially responsive to EGFR TKIs eventually develop acquired resistance after a median progression-free survival of 10–16 months, followed by disease progression. Moreover, ~20%–30% of NSCLC patients have no objective tumor regression on initial EGFR TKI treatment, although they harbor an activating EGFR mutation. These patients represent an NSCLC subgroup that is defined as having intrinsic or primary resistance to EGFR TKIs. Different mechanisms of acquired EGFR TKI resistance have been identified, and several novel compounds have been developed to reverse acquired resistance, but little is known about EGFR TKI intrinsic resistance. In this review, we summarize the latest findings involving mechanisms of intrinsic resistance to EGFR TKIs in advanced NSCLC with activating EGFR mutations and present possible therapeutic strategies to overcome this resistance. PMID:27382309

Predicting Post-Harvest Performance of Advance Red Oak Reproduction in the Southern Appalachians

Treesearch

David L. Loftis

1990-01-01

Models are presented for predicting: (1) height growth of red oak advance reproduction after clearcutting, and (2) the probability of stems becoming dominants or codominants in new stands as a function of preharvest size of advance reproduction andsitequafity. The second model permits silviculturists to predict, prior to harvest, the contribution to a new stand of an...

An Advanced Buffet Load Alleviation System

NASA Technical Reports Server (NTRS)

Burnham, Jay K.; Pitt, Dale M.; White, Edward V.; Henderson, Douglas A.; Moses, Robert W.

2001-01-01

This paper describes the development of an advanced buffet load alleviation (BLA) system that utilizes distributed piezoelectric actuators in conjunction with an active rudder to reduce the structural dynamic response of the F/A-18 aircraft vertical tails to buffet loads. The BLA system was defined analytically with a detailed finite-element-model of the tail structure and piezoelectric actuators. Oscillatory aerodynamics were included along with a buffet forcing function to complete the aeroservoelastic model of the tail with rudder control surface. Two single-input-single-output (SISO) controllers were designed, one for the active rudder and one for the active piezoelectric actuators. The results from the analytical open and closed loop simulations were used to predict the system performance. The objective of this BLA system is to extend the life of vertical tail structures and decrease their life-cycle costs. This system can be applied to other aircraft designs to address suppression of structural vibrations on military and commercial aircraft.

Joining and Integration of Advanced Carbon-Carbon Composites to Metallic Systems for Thermal Management Applications

NASA Technical Reports Server (NTRS)

Singh, M.; Asthana, R.

2008-01-01

Recent research and development activities in joining and integration of carbon-carbon (C/C) composites to metals such as Ti and Cu-clad-Mo for thermal management applications are presented with focus on advanced brazing techniques. A wide variety of carbon-carbon composites with CVI and resin-derived matrices were joined to Ti and Cu-clad Mo using a number of active braze alloys. The brazed joints revealed good interfacial bonding, preferential precipitation of active elements (e.g., Ti) at the composite/braze interface. Extensive braze penetration of the inter-fiber channels in the CVI C/C composites was observed. The chemical and thermomechanical compatibility between C/C and metals at elevated temperatures is assessed. The role of residual stresses and thermal conduction in brazed C/C joints is discussed. Theoretical predictions of the effective thermal resistance suggest that composite-to-metal brazed joints may be promising for lightweight thermal management applications.

Optogenetic activation of neocortical neurons in vivo with a sapphire-based micro-scale LED probe.

PubMed

McAlinden, Niall; Gu, Erdan; Dawson, Martin D; Sakata, Shuzo; Mathieson, Keith

2015-01-01

Optogenetics has proven to be a revolutionary technology in neuroscience and has advanced continuously over the past decade. However, optical stimulation technologies for in vivo need to be developed to match the advances in genetics and biochemistry that have driven this field. In particular, conventional approaches for in vivo optical illumination have a limitation on the achievable spatio-temporal resolution. Here we utilize a sapphire-based microscale gallium nitride light-emitting diode (μLED) probe to activate neocortical neurons in vivo. The probes were designed to contain independently controllable multiple μLEDs, emitting at 450 nm wavelength with an irradiance of up to 2 W/mm(2). Monte-Carlo stimulations predicted that optical stimulation using a μLED can modulate neural activity within a localized region. To validate this prediction, we tested this probe in the mouse neocortex that expressed channelrhodopsin-2 (ChR2) and compared the results with optical stimulation through a fiber at the cortical surface. We confirmed that both approaches reliably induced action potentials in cortical neurons and that the μLED probe evoked strong responses in deep neurons. Due to the possibility to integrate many optical stimulation sites onto a single shank, the μLED probe is thus a promising approach to control neurons locally in vivo.

A Primer In Advanced Fatigue Life Prediction Methods

NASA Technical Reports Server (NTRS)

Halford, Gary R.

2000-01-01

Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable more cost effective, and better performing products. In other words, as the envelop is expanded, components are then designed to operate just as close to the newly expanded envelop as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

Bazedoxifene exhibits antiestrogenic activity in animal models of tamoxifen-resistant breast cancer: implications for treatment of advanced disease.

PubMed

Wardell, Suzanne E; Nelson, Erik R; Chao, Christina A; McDonnell, Donald P

2013-05-01

There is compelling evidence to suggest that drugs that function as pure estrogen receptor (ER-α) antagonists, or that downregulate the expression of ER-α, would have clinical use in the treatment of advanced tamoxifen- and aromatase-resistant breast cancer. Although such compounds are currently in development, we reasoned, based on our understanding of ER-α pharmacology, that there may already exist among the most recently developed selective estrogen receptor modulators (SERM) compounds that would have usage as breast cancer therapeutics. Thus, our objective was to identify among available SERMs those with unique pharmacologic activities and to evaluate their potential clinical use with predictive models of advanced breast cancer. A validated molecular profiling technology was used to classify clinically relevant SERMs based on their impact on ER-α conformation. The functional consequences of these observed mechanistic differences on (i) gene expression, (ii) receptor stability, and (iii) activity in cellular and animal models of advanced endocrine-resistant breast cancer were assessed. The high-affinity SERM bazedoxifene was shown to function as a pure ER-α antagonist in cellular models of breast cancer and effectively inhibited the growth of both tamoxifen-sensitive and -resistant breast tumor xenografts. Interestingly, bazedoxifene induced a unique conformational change in ER-α that resulted in its proteasomal degradation, although the latter activity was dispensable for its antagonist efficacy. Bazedoxifene was recently approved for use in the European Union for the treatment of osteoporosis and thus may represent a near-term therapeutic option for patients with advanced breast cancer. ©2013 AACR.

Social tolerance in not-so-social pumas.

PubMed

Vonk, Jennifer

2018-06-01

Elbroch, Levy, Lubell, Quigley, and Caragiulo (2017, Science Advances, 3, e170218) used GPS and motion-activated camera technology to track and rate the interactions between solitary wild pumas. They found that tolerance at feeding sites was not predicted by kinship but, rather, indicated the ability to engage in direct reciprocity, challenging previous assumptions about social cognition in solitary species.

Emulation as an Integrating Principle for Cognition

PubMed Central

Colder, Brian

2011-01-01

Emulations, defined as ongoing internal representations of potential actions and the futures those actions are expected to produce, play a critical role in directing human bodily activities. Studies of gross motor behavior, perception, allocation of attention, response to errors, interoception, and homeostatic activities, and higher cognitive reasoning suggest that the proper execution of all these functions relies on emulations. Further evidence supports the notion that reinforcement learning in humans is aimed at updating emulations, and that action selection occurs via the advancement of preferred emulations toward realization of their action and environmental prediction. Emulations are hypothesized to exist as distributed active networks of neurons in cortical and sub-cortical structures. This manuscript ties together previously unrelated theories of the role of prediction in different aspects of human information processing to create an integrated framework for cognition. PMID:21660288

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

NASA Astrophysics Data System (ADS)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

Forensic DNA methylation profiling from evidence material for investigative leads

PubMed Central

Lee, Hwan Young; Lee, Soong Deok; Shin, Kyoung-Jin

2016-01-01

DNA methylation is emerging as an attractive marker providing investigative leads to solve crimes in forensic genetics. The identification of body fluids that utilizes tissue-specific DNA methylation can contribute to solving crimes by predicting activity related to the evidence material. The age estimation based on DNA methylation is expected to reduce the number of potential suspects, when the DNA profile from the evidence does not match with any known person, including those stored in the forensic database. Moreover, the variation in DNA implicates environmental exposure, such as cigarette smoking and alcohol consumption, thereby suggesting the possibility to be used as a marker for predicting the lifestyle of potential suspect. In this review, we describe recent advances in our understanding of DNA methylation variations and the utility of DNA methylation as a forensic marker for advanced investigative leads from evidence materials. [BMB Reports 2016; 49(7): 359-369] PMID:27099236

Acoustics Discipline Overview

NASA Technical Reports Server (NTRS)

Envia, Edmane; Thomas, Russell

2007-01-01

As part of the Fundamental Aeronautics Program Annual Review, a summary of the progress made in 2007 in acoustics research under the Subsonic Fixed Wing project is given. The presentation describes highlights from in-house and external activities including partnerships and NRA-funded research with industry and academia. Brief progress reports from all acoustics Phase 1 NRAs are also included as are outlines of the planned activities for 2008 and all Phase 2 NRAs. N+1 and N+2 technology paths outlined for Subsonic Fixed Wing noise targets. NRA Round 1 progressing with focus on prediction method advancement. NRA Round 2 initiating work focused on N+2 technology, prediction methods, and validation. Excellent partnerships in progress supporting N+1 technology targets and providing key data sets.

Prognostic value of DNA repair based stratification of hepatocellular carcinoma

PubMed Central

Lin, Zhuo; Xu, Shi-Hao; Wang, Hai-Qing; Cai, Yi-Jing; Ying, Li; Song, Mei; Wang, Yu-Qun; Du, Shan-Jie; Shi, Ke-Qing; Zhou, Meng-Tao

2016-01-01

Aberrant activation of DNA repair is frequently associated with tumor progression and response to therapy in hepatocellular carcinoma (HCC). Bioinformatics analyses of HCC data in the Cancer Genome Atlas (TCGA) were performed to define DNA repair based molecular classification that could predict the prognosis of patients with HCC. Furthermore, we tested its predictive performance in 120 independent cases. Four molecular subgroups were identified on the basis of coordinate DNA repair cluster (CDRC) comprising 15 genes in TCGA dataset. Increasing expression of CDRC genes were significantly associated with TP53 mutation. High CDRC was significantly correlated with advanced tumor grades, advanced pathological stage and increased vascular invasion rate. Multivariate Cox regression analysis indicated that the molecular subgrouping was an independent prognostic parameter for both overall survival (p = 0.004, hazard ratio (HR): 2.989) and tumor-free survival (p = 0.049, HR: 3.366) in TCGA dataset. Similar results were also obtained by analyzing the independent cohort. These data suggest that distinct dysregulation of DNA repair constituents based molecular classes in HCC would be useful for predicting prognosis and designing clinical trials for targeted therapy. PMID:27174663

Using internet searches for influenza surveillance.

PubMed

Polgreen, Philip M; Chen, Yiling; Pennock, David M; Nelson, Forrest D

2008-12-01

The Internet is an important source of health information. Thus, the frequency of Internet searches may provide information regarding infectious disease activity. As an example, we examined the relationship between searches for influenza and actual influenza occurrence. Using search queries from the Yahoo! search engine ( http://search.yahoo.com ) from March 2004 through May 2008, we counted daily unique queries originating in the United States that contained influenza-related search terms. Counts were divided by the total number of searches, and the resulting daily fraction of searches was averaged over the week. We estimated linear models, using searches with 1-10-week lead times as explanatory variables to predict the percentage of cultures positive for influenza and deaths attributable to pneumonia and influenza in the United States. With use of the frequency of searches, our models predicted an increase in cultures positive for influenza 1-3 weeks in advance of when they occurred (P < .001), and similar models predicted an increase in mortality attributable to pneumonia and influenza up to 5 weeks in advance (P < .001). Search-term surveillance may provide an additional tool for disease surveillance.

State-of-the-art of high-speed propeller noise prediction - A multidisciplinary approach and comparison with measured data

NASA Technical Reports Server (NTRS)

Dunn, Mark H.; Farassat, F.

1990-01-01

The results of NASA's Propeller Test Assessment program involving extensive flight tests of a large-scale advanced propeller are presented. This has provided the opportunity to evaluate the current capability of advanced propeller noise prediction utilizing principally the exterior acoustic measurements for the prediction of exterior noise. The principal object of this study was to evaluate the state-of-the-art of noise prediction for advanced propellers utilizing the best available codes of the disciplines involved. The effects of blade deformation on the aerodynamics and noise of advanced propellers were also studied. It is concluded that blade deformation can appreciably influence propeller noise and aerodynamics, and that, in general, centrifugal and blade forces must both be included in the calculation of blade forces. It is noted that the present capability for free-field noise prediction of the first three harmonics for advanced propellers is fairly good. Detailed data and diagrams of the test results are presented.

Subseasonal-to-Seasonal Science and Prediction Initiatives of the NOAA MAPP Program

NASA Astrophysics Data System (ADS)

Archambault, H. M.; Barrie, D.; Mariotti, A.

2016-12-01

There is great practical interest in developing predictions beyond the 2-week weather timescale. Scientific communities have historically organized themselves around the weather and climate problems, but the subseasonal-to-seasonal (S2S) timescale range overall is recognized as new territory for which a concerted shared effort is needed. For instance, the climate community, as part of programs like CLIVAR, has historically tackled coupled phenomena and modeling, keys to harnessing predictability on longer timescales. In contrast, the weather community has focused on synoptic dynamics, higher-resolution modeling, and enhanced model initialization, of importance at the shorter timescales and especially for the prediction of extremes. The processes and phenomena specific to timescales between weather and climate require a unified approach to science, modeling, and predictions. Internationally, the WWRP/WCRP S2S Prediction Project is a promising catalyzer for these types of activities. Among the various contributing U.S. research programs, the Modeling, Analysis, Predictions and Projections (MAPP) program, as part of the NOAA Climate Program Office, has launched coordinated research and transition activities that help to meet the agency's goals to fill the weather-to-climate prediction gap and will contribute to advance international goals. This presentation will describe ongoing MAPP program S2S science and prediction initiatives, specifically the MAPP S2S Task Force and the SubX prediction experiment.

NASA GRC Fatigue Crack Initiation Life Prediction Models

NASA Technical Reports Server (NTRS)

Arya, Vinod K.; Halford, Gary R.

2002-01-01

Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable, more cost effective, and better performing products. In other words, as the envelope is expanded, components are then designed to operate just as close to the newly expanded envelope as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

NASA GRC Fatigue Crack Initiation Life Prediction Models

NASA Astrophysics Data System (ADS)

Arya, Vinod K.; Halford, Gary R.

2002-10-01

Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable, more cost effective, and better performing products. In other words, as the envelope is expanded, components are then designed to operate just as close to the newly expanded envelope as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

The language of future-thought: an fMRI study of embodiment and tense processing.

PubMed

Gilead, Michael; Liberman, Nira; Maril, Anat

2013-01-15

The ability to comprehend and represent the temporal properties of an occurrence is a crucial aspect of human language and cognition. Despite advances in neurolinguistic research into semantic processing, surprisingly little is known regarding the mechanisms which support the comprehension of temporal semantics. We used fMRI to investigate neural activity associated with processing of concrete and abstract sentences across the three temporal categories: past, present, and future. Theories of embodied cognition predict that concreteness-related activity would be evident in sensory and motor areas regardless of tense. Contrastingly, relying upon construal level theory we hypothesized that: (1) the neural markers associated with concrete language processing would appear for past and present tense sentences, but not for future sentences; (2) future tense sentences would activate intention-processing areas. Consistent with our first prediction, the results showed that activation in the parahippocampal gyrus differentiated between concrete and abstract sentences for past and present tense sentences, but not for future sentences. Not consistent with our second prediction, future tense sentences did not activate most of the regions that are implicated in the processing of intentions, but only activated the vmPFC. We discuss the implications of the current results to theories of embodied cognition and tense semantics. Copyright © 2012 Elsevier Inc. All rights reserved.

Retrospective forecasting of the 2010-2014 Melbourne influenza seasons using multiple surveillance systems.

PubMed

Moss, R; Zarebski, A; Dawson, P; McCAW, J M

2017-01-01

Accurate forecasting of seasonal influenza epidemics is of great concern to healthcare providers in temperate climates, since these epidemics vary substantially in their size, timing and duration from year to year, making it a challenge to deliver timely and proportionate responses. Previous studies have shown that Bayesian estimation techniques can accurately predict when an influenza epidemic will peak many weeks in advance, and we have previously tailored these methods for metropolitan Melbourne (Australia) and Google Flu Trends data. Here we extend these methods to clinical observation and laboratory-confirmation data for Melbourne, on the grounds that these data sources provide more accurate characterizations of influenza activity. We show that from each of these data sources we can accurately predict the timing of the epidemic peak 4-6 weeks in advance. We also show that making simultaneous use of multiple surveillance systems to improve forecast skill remains a fundamental challenge. Disparate systems provide complementary characterizations of disease activity, which may or may not be comparable, and it is unclear how a 'ground truth' for evaluating forecasts against these multiple characterizations might be defined. These findings are a significant step towards making optimal use of routine surveillance data for outbreak forecasting.

Activity of Nivolumab and Utility of Neutrophil-to-Lymphocyte Ratio as a Predictive Biomarker for Advanced Non-Small-Cell Lung Cancer: A Prospective Observational Study.

PubMed

Fukui, Tomoya; Okuma, Yuriko; Nakahara, Yoshiro; Otani, Sakiko; Igawa, Satoshi; Katagiri, Masato; Mitsufuji, Hisashi; Kubota, Masaru; Hiyoshi, Yasuhiro; Ishihara, Mikiko; Kasajima, Masashi; Sasaki, Jiichiro; Naoki, Katsuhiko

2018-05-05

The immune checkpoint inhibitor nivolumab is entering routine oncologic practice. We investigated the safety and efficacy of nivolumab in the real world and alternative predictive factors for survival in patients with advanced non-small-cell lung cancer (NSCLC). We performed a prospective observational study to evaluate the activity of nivolumab treatment for chemotherapy-refractory NSCLC. Patients were treated with nivolumab once every 2 weeks, and the efficacy was assessed every 8 ± 2 weeks. Fifty-two patients were enrolled after nivolumab approval in Japan. These patients received a median of 4 (range, 1-43) cycles of nivolumab. Overall objective response was observed in 12 patients (23.1%). Median progression-free survival was 2.1 (95% confidence interval, 1.0-3.2) months, and 1-year overall survival rate was 59.9%. A total of 23 immune-related adverse events occurred in 20 patients, as follows: 7 cases of pneumonitis, 6 of oral mucositis, 5 of hypothyroidism, 2 of colitis, 2 of liver dysfunction, and 1 of arthritis. All patients recovered after appropriate management. A pretreatment neutrophil-to-lymphocyte ratio (NLR) of ≥ 5 was significantly associated with poor prognosis compared to NLR < 5 (hazard ratio, 4.52; 95% confidence interval, 1.84-11.14; P = .013), independently. Nivolumab showed promising activity with a manageable safety profile in clinical practice, consistent with effects of previous clinical trials. This drug could affect a specific population of patients with advanced NSCLC, and pretreatment NLR was a candidate for surrogate markers for survival benefit of patients with NSCLC treated with nivolumab. Copyright © 2018 Elsevier Inc. All rights reserved.

[The impact of the androgen receptor splice variant AR-V7 on the prognosis and treatment of advanced prostate cancer].

PubMed

Thelen, P; Taubert, H; Duensing, S; Kristiansen, G; Merseburger, A S; Cronauer, M V

2018-01-25

A recently discovered mechanism enabling prostate cancer cells to escape the effects of endocrine therapies consists in the synthesis of C-terminally truncated, constitutively active androgen receptor (AR) splice variants (AR-V). Devoid of a functional C-terminal hormone/ligand binding domain, various AR-Vs are insensitive to therapies targeting the androgen/AR signalling axis. Preliminary studies suggest that AR-V7, the most common AR-V, is a promising predictive tumour marker and a relevant selection marker for the treatment of advanced prostate cancer. This review critically outlines recent advances in AR-V7 diagnostics and presents an overview of current AR-V7 targeted therapies. © Georg Thieme Verlag KG Stuttgart · New York.

Remote sensing information for fire management and fire effects assessment

NASA Astrophysics Data System (ADS)

Chuvieco, Emilio; Kasischke, Eric S.

2007-03-01

Over the past decade, much research has been carried out on the utilization of advanced geospatial technologies (remote sensing and geographic information systems) in the fire science and fire management disciplines. Recent advances in these technologies were the focus of a workshop sponsored by the EARSEL special interest group (SIG) on forest fires (FF-SIG) and the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) fire implementation team. Here we summarize the framework and the key findings of papers submitted from this meeting and presented in this special section. These papers focus on the latest advances for near real-time monitoring of active fires, prediction of fire hazards and danger, monitoring of fuel moisture, mapping of fuel types, and postfire assessment of the impacts from fires.

CDK4/6 Inhibitors: Game Changers in the Management of Hormone Receptor–Positive Advanced Breast Cancer?

PubMed

Shah, Mirat; Nunes, Maria Raquel; Stearns, Vered

2018-05-15

The cyclin-dependent kinase 4 and 6 (CDK4/6) inhibitors palbociclib, ribociclib, and abemaciclib are rapidly transforming the care of patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2 (HER2)-negative (HR+/HER2-) advanced breast cancer. Current clinical questions include how to choose among these agents and how to sequence them with other therapies. Areas of active inquiry include identifying predictive biomarkers for CDK4/6 inhibitors, deciding whether to continue CDK4/6 inhibitors after disease progression, creating novel treatment combinations, and expanding use beyond HR+/HER2- advanced breast cancer. Here, we review the current use of and potential next directions for CDK4/6 inhibitors in the treatment of patients with HR+ breast cancer.

Understanding dopamine and reinforcement learning: the dopamine reward prediction error hypothesis.

PubMed

Glimcher, Paul W

2011-09-13

A number of recent advances have been achieved in the study of midbrain dopaminergic neurons. Understanding these advances and how they relate to one another requires a deep understanding of the computational models that serve as an explanatory framework and guide ongoing experimental inquiry. This intertwining of theory and experiment now suggests very clearly that the phasic activity of the midbrain dopamine neurons provides a global mechanism for synaptic modification. These synaptic modifications, in turn, provide the mechanistic underpinning for a specific class of reinforcement learning mechanisms that now seem to underlie much of human and animal behavior. This review describes both the critical empirical findings that are at the root of this conclusion and the fantastic theoretical advances from which this conclusion is drawn.

Understanding dopamine and reinforcement learning: The dopamine reward prediction error hypothesis

PubMed Central

Glimcher, Paul W.

2011-01-01

A number of recent advances have been achieved in the study of midbrain dopaminergic neurons. Understanding these advances and how they relate to one another requires a deep understanding of the computational models that serve as an explanatory framework and guide ongoing experimental inquiry. This intertwining of theory and experiment now suggests very clearly that the phasic activity of the midbrain dopamine neurons provides a global mechanism for synaptic modification. These synaptic modifications, in turn, provide the mechanistic underpinning for a specific class of reinforcement learning mechanisms that now seem to underlie much of human and animal behavior. This review describes both the critical empirical findings that are at the root of this conclusion and the fantastic theoretical advances from which this conclusion is drawn. PMID:21389268

Predictive value of diminutive colonic adenoma trial: the PREDICT trial.

PubMed

Schoenfeld, Philip; Shad, Javaid; Ormseth, Eric; Coyle, Walter; Cash, Brooks; Butler, James; Schindler, William; Kikendall, Walter J; Furlong, Christopher; Sobin, Leslie H; Hobbs, Christine M; Cruess, David; Rex, Douglas

2003-05-01

Diminutive adenomas (1-9 mm in diameter) are frequently found during colon cancer screening with flexible sigmoidoscopy (FS). This trial assessed the predictive value of these diminutive adenomas for advanced adenomas in the proximal colon. In a multicenter, prospective cohort trial, we matched 200 patients with normal FS and 200 patients with diminutive adenomas on FS for age and gender. All patients underwent colonoscopy. The presence of advanced adenomas (adenoma >or= 10 mm in diameter, villous adenoma, adenoma with high grade dysplasia, and colon cancer) and adenomas (any size) was recorded. Before colonoscopy, patients completed questionnaires about risk factors for adenomas. The prevalence of advanced adenomas in the proximal colon was similar in patients with diminutive adenomas and patients with normal FS (6% vs. 5.5%, respectively) (relative risk, 1.1; 95% confidence interval [CI], 0.5-2.6). Diminutive adenomas on FS did not accurately predict advanced adenomas in the proximal colon: sensitivity, 52% (95% CI, 32%-72%); specificity, 50% (95% CI, 49%-51%); positive predictive value, 6% (95% CI, 4%-8%); and negative predictive value, 95% (95% CI, 92%-97%). Male gender (odds ratio, 1.63; 95% CI, 1.01-2.61) was associated with an increased risk of proximal colon adenomas. Diminutive adenomas on sigmoidoscopy may not accurately predict advanced adenomas in the proximal colon.

The applications of machine learning algorithms in the modeling of estrogen-like chemicals.

PubMed

Liu, Huanxiang; Yao, Xiaojun; Gramatica, Paola

2009-06-01

Increasing concern is being shown by the scientific community, government regulators, and the public about endocrine-disrupting chemicals that, in the environment, are adversely affecting human and wildlife health through a variety of mechanisms, mainly estrogen receptor-mediated mechanisms of toxicity. Because of the large number of such chemicals in the environment, there is a great need for an effective means of rapidly assessing endocrine-disrupting activity in the toxicology assessment process. When faced with the challenging task of screening large libraries of molecules for biological activity, the benefits of computational predictive models based on quantitative structure-activity relationships to identify possible estrogens become immediately obvious. Recently, in order to improve the accuracy of prediction, some machine learning techniques were introduced to build more effective predictive models. In this review we will focus our attention on some recent advances in the use of these methods in modeling estrogen-like chemicals. The advantages and disadvantages of the machine learning algorithms used in solving this problem, the importance of the validation and performance assessment of the built models as well as their applicability domains will be discussed.

Compound activity prediction using models of binding pockets or ligand properties in 3D

PubMed Central

Kufareva, Irina; Chen, Yu-Chen; Ilatovskiy, Andrey V.; Abagyan, Ruben

2014-01-01

Transient interactions of endogenous and exogenous small molecules with flexible binding sites in proteins or macromolecular assemblies play a critical role in all biological processes. Current advances in high-resolution protein structure determination, database development, and docking methodology make it possible to design three-dimensional models for prediction of such interactions with increasing accuracy and specificity. Using the data collected in the Pocketome encyclopedia, we here provide an overview of two types of the three-dimensional ligand activity models, pocket-based and ligand property-based, for two important classes of proteins, nuclear and G-protein coupled receptors. For half the targets, the pocket models discriminate actives from property matched decoys with acceptable accuracy (the area under ROC curve, AUC, exceeding 84%) and for about one fifth of the targets with high accuracy (AUC > 95%). The 3D ligand property field models performed better than 95% in half of the cases. The high performance models can already become a basis of activity predictions for new chemicals. Family-wide benchmarking of the models highlights strengths of both approaches and helps identify their inherent bottlenecks and challenges. PMID:23116466

Examination of CRISPR/Cas9 design tools and the effect of target site accessibility on Cas9 activity.

PubMed

Lee, Ciaran M; Davis, Timothy H; Bao, Gang

2018-04-01

What is the topic of this review? In this review, we analyse the performance of recently described tools for CRISPR/Cas9 guide RNA design, in particular, design tools that predict CRISPR/Cas9 activity. What advances does it highlight? Recently, many tools designed to predict CRISPR/Cas9 activity have been reported. However, the majority of these tools lack experimental validation. Our analyses indicate that these tools have poor predictive power. Our preliminary results suggest that target site accessibility should be considered in order to develop better guide RNA design tools with improved predictive power. The recent adaptation of the clustered regulatory interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) system for targeted genome engineering has led to its widespread application in many fields worldwide. In order to gain a better understanding of the design rules of CRISPR/Cas9 systems, several groups have carried out large library-based screens leading to some insight into sequence preferences among highly active target sites. To facilitate CRISPR/Cas9 design, these studies have spawned a plethora of guide RNA (gRNA) design tools with algorithms based solely on direct or indirect sequence features. Here, we demonstrate that the predictive power of these tools is poor, suggesting that sequence features alone cannot accurately inform the cutting efficiency of a particular CRISPR/Cas9 gRNA design. Furthermore, we demonstrate that DNA target site accessibility influences the activity of CRISPR/Cas9. With further optimization, we hypothesize that it will be possible to increase the predictive power of gRNA design tools by including both sequence and target site accessibility metrics. © 2017 The Authors. Experimental Physiology © 2017 The Physiological Society.

Basophil-activation tests in Hymenoptera allergy.

PubMed

Dubois, Anthony E J; van der Heide, Sicco

2007-08-01

Despite recent advances in our understanding of basophil biology and discovery of new markers for basophil activation, tests measuring basophil activation are not widely utilized in Hymenoptera allergy. Studies of the basophil-activation test in Hymenoptera allergy were examined and the clinical utility of this test was assessed. It has been demonstrated that the results of basophil-activation tests correlate quite well with those of serum IgE testing or skin-prick tests. Many studies compare test outcomes with history in patients and nonallergic controls, so that specificity in sensitized but clinically nonreactive individuals remains unknown. Although one study showed that the basophil-activation test might predict immunotherapy side effects, this could not be confirmed in a second study, and no role has been established for the basophil-activation test in the monitoring of venom immunotherapy. The basophil-activation test has no extra value in assessing sting challenges, although experience is limited. The measurement of basophil-activation markers may be useful in detecting IgE-mediated sensitization but the relevance for application of the basophil-activation test in prediction of clinical reactivity in Hymenoptera allergy is very limited. For this reason, this test currently has no established role in the diagnosis and management of patients with insect sting allergy.

Applications of alignment-free methods in epigenomics.

PubMed

Pinello, Luca; Lo Bosco, Giosuè; Yuan, Guo-Cheng

2014-05-01

Epigenetic mechanisms play an important role in the regulation of cell type-specific gene activities, yet how epigenetic patterns are established and maintained remains poorly understood. Recent studies have supported a role of DNA sequences in recruitment of epigenetic regulators. Alignment-free methods have been applied to identify distinct sequence features that are associated with epigenetic patterns and to predict epigenomic profiles. Here, we review recent advances in such applications, including the methods to map DNA sequence to feature space, sequence comparison and prediction models. Computational studies using these methods have provided important insights into the epigenetic regulatory mechanisms.

NASA/LaRC jet plume research

NASA Technical Reports Server (NTRS)

Seiner, John M.; Ponton, Michael K.; Manning, James C.

1992-01-01

The following provides a summary for research being conducted by NASA/LaRC and its contractors and grantees to develop jet engine noise suppression technology under the NASA High Speed Research (HSR) program for the High Speed Civil Transport (HSCT). The objective of this effort is to explore new innovative concepts for reducing noise to Federally mandated guidelines with minimum compromise on engine performance both in take-off and cruise. The research program is divided into four major technical areas: (1) jet noise research on advanced nozzles; (2) plume prediction and validation; (3) passive and active control; and (4) methodology for noise prediction.

Developing a musculoskeletal model of the primate skull: predicting muscle activations, bite force, and joint reaction forces using multibody dynamics analysis and advanced optimisation methods.

PubMed

Shi, Junfen; Curtis, Neil; Fitton, Laura C; O'Higgins, Paul; Fagan, Michael J

2012-10-07

An accurate, dynamic, functional model of the skull that can be used to predict muscle forces, bite forces, and joint reaction forces would have many uses across a broad range of disciplines. One major issue however with musculoskeletal analyses is that of muscle activation pattern indeterminacy. A very large number of possible muscle force combinations will satisfy a particular functional task. This makes predicting physiological muscle recruitment patterns difficult. Here we describe in detail the process of development of a complex multibody computer model of a primate skull (Macaca fascicularis), that aims to predict muscle recruitment patterns during biting. Using optimisation criteria based on minimisation of muscle stress we predict working to balancing side muscle force ratios, peak bite forces, and joint reaction forces during unilateral biting. Validation of such models is problematic; however we have shown comparable working to balancing muscle activity and TMJ reaction ratios during biting to those observed in vivo and that peak predicted bite forces compare well to published experimental data. To our knowledge the complexity of the musculoskeletal model is greater than any previously reported for a primate. This complexity, when compared to more simple representations provides more nuanced insights into the functioning of masticatory muscles. Thus, we have shown muscle activity to vary throughout individual muscle groups, which enables them to function optimally during specific masticatory tasks. This model will be utilised in future studies into the functioning of the masticatory apparatus. Copyright © 2012 Elsevier Ltd. All rights reserved.

Aircraft engine hot section technology: An overview of the HOST Project

NASA Technical Reports Server (NTRS)

Sokolowski, Daniel E.; Hirschberg, Marvin H.

1990-01-01

NASA sponsored the Turbine Engine Hot Section (HOST) project to address the need for improved durability in advanced aircraft engine combustors and turbines. Analytical and experimental activities aimed at more accurate prediction of the aerothermal environment, the thermomechanical loads, the material behavior and structural responses to loads, and life predictions for cyclic high temperature operation were conducted from 1980 to 1987. The project involved representatives from six engineering disciplines who are spread across three work disciplines - industry, academia, and NASA. The HOST project not only initiated and sponsored 70 major activities, but also was the keystone in joining the multiple disciplines and work sectors to focus on critical research needs. A broad overview of the project is given along with initial indications of the project's impact.

Advanced flight control system study

NASA Technical Reports Server (NTRS)

Hartmann, G. L.; Wall, J. E., Jr.; Rang, E. R.; Lee, H. P.; Schulte, R. W.; Ng, W. K.

1982-01-01

A fly by wire flight control system architecture designed for high reliability includes spare sensor and computer elements to permit safe dispatch with failed elements, thereby reducing unscheduled maintenance. A methodology capable of demonstrating that the architecture does achieve the predicted performance characteristics consists of a hierarchy of activities ranging from analytical calculations of system reliability and formal methods of software verification to iron bird testing followed by flight evaluation. Interfacing this architecture to the Lockheed S-3A aircraft for flight test is discussed. This testbed vehicle can be expanded to support flight experiments in advanced aerodynamics, electromechanical actuators, secondary power systems, flight management, new displays, and air traffic control concepts.

Recent insight into potential acute respiratory distress syndrome.

PubMed

Amin, Zulkifli; Rahmawati, Fitriana N

2017-04-01

Acute respiratory distress syndrome (ARDS) is an acute inflammatory lung injury, characterized by increased pulmonary capillary endothelial cells and alveolar epithelial cells permeability leading to respiratory failure in the absence of cardiac failure. Despite recent advances in treatments, the overall mortality because of ARDS remains high. Biomarkers may help to diagnose, predict the severity, development, and outcome of ARDS in order to improve patient care and decrease morbidity and mortality. This review will focus on soluble receptor for advanced glycation end-products, soluble tumor necrosis factor-receptor 1, Interluken-6 (IL-6), IL-8, and plasminogen activator inhibitor-1, which have a greater potential based on recent studies.

Recent insight into potential acute respiratory distress syndrome

PubMed Central

Amin, Zulkifli; Rahmawati, Fitriana N.

2017-01-01

Acute respiratory distress syndrome (ARDS) is an acute inflammatory lung injury, characterized by increased pulmonary capillary endothelial cells and alveolar epithelial cells permeability leading to respiratory failure in the absence of cardiac failure. Despite recent advances in treatments, the overall mortality because of ARDS remains high. Biomarkers may help to diagnose, predict the severity, development, and outcome of ARDS in order to improve patient care and decrease morbidity and mortality. This review will focus on soluble receptor for advanced glycation end-products, soluble tumor necrosis factor-receptor 1, Interluken-6 (IL-6), IL-8, and plasminogen activator inhibitor-1, which have a greater potential based on recent studies. PMID:28397939

UV254 absorbance as real-time monitoring and control parameter for micropollutant removal in advanced wastewater treatment with powdered activated carbon.

PubMed

Altmann, Johannes; Massa, Lukas; Sperlich, Alexander; Gnirss, Regina; Jekel, Martin

2016-05-01

This study investigates the applicability of UV absorbance measurements at 254 nm (UVA254) to serve as a simple and reliable surrogate parameter to monitor and control the removal of organic micropollutants (OMPs) in advanced wastewater treatment applying powdered activated carbon (PAC). Correlations between OMP removal and corresponding UVA254 reduction were determined in lab-scale adsorption batch tests and successfully applied to a pilot-scale PAC treatment stage to predict OMP removals in aggregate samples with good accuracy. Real-time UVA254 measurements were utilized to evaluate adapted PAC dosing strategies and proved to be effective for online monitoring of OMP removal. Furthermore, active PAC dosing control according to differential UVA254 measurements was implemented and tested. While precise removal predictions based on real-time measurements were not accurate for all OMPs, UVA254-controlled dynamic PAC dosing was capable of achieving stable OMP removals. UVA254 can serve as an effective surrogate parameter for OMP removal in technical PAC applications. Even though the applicability as control parameter to adjust PAC dosing to water quality changes might be limited to applications with fast response between PAC adjustment and adsorptive removal (e.g. direct filtration), UVA254 measurements can also be used to monitor the adsorption efficiency in more complex PAC applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

An EEG Finger-Print of fMRI deep regional activation.

PubMed

Meir-Hasson, Yehudit; Kinreich, Sivan; Podlipsky, Ilana; Hendler, Talma; Intrator, Nathan

2014-11-15

This work introduces a general framework for producing an EEG Finger-Print (EFP) which can be used to predict specific brain activity as measured by fMRI at a given deep region. This new approach allows for improved EEG spatial resolution based on simultaneous fMRI activity measurements. Advanced signal processing and machine learning methods were applied on EEG data acquired simultaneously with fMRI during relaxation training guided by on-line continuous feedback on changing alpha/theta EEG measure. We focused on demonstrating improved EEG prediction of activation in sub-cortical regions such as the amygdala. Our analysis shows that a ridge regression model that is based on time/frequency representation of EEG data from a single electrode, can predict the amygdala related activity significantly better than a traditional theta/alpha activity sampled from the best electrode and about 1/3 of the times, significantly better than a linear combination of frequencies with a pre-defined delay. The far-reaching goal of our approach is to be able to reduce the need for fMRI scanning for probing specific sub-cortical regions such as the amygdala as the basis for brain-training procedures. On the other hand, activity in those regions can be characterized with higher temporal resolution than is obtained by fMRI alone thus revealing additional information about their processing mode. Copyright © 2013 Elsevier Inc. All rights reserved.

Predictive model for falling in Parkinson disease patients.

PubMed

Custodio, Nilton; Lira, David; Herrera-Perez, Eder; Montesinos, Rosa; Castro-Suarez, Sheila; Cuenca-Alfaro, Jose; Cortijo, Patricia

2016-12-01

Falls are a common complication of advancing Parkinson's disease (PD). Although numerous risk factors are known, reliable predictors of future falls are still lacking. The aim of this study was to develop a multivariate model to predict falling in PD patients. Prospective cohort with forty-nine PD patients. The area under the receiver-operating characteristic curve (AUC) was calculated to evaluate predictive performance of the purposed multivariate model. The median of PD duration and UPDRS-III score in the cohort was 6 years and 24 points, respectively. Falls occurred in 18 PD patients (30%). Predictive factors for falling identified by univariate analysis were age, PD duration, physical activity, and scores of UPDRS motor, FOG, ACE, IFS, PFAQ and GDS ( p -value < 0.001), as well as fear of falling score ( p -value = 0.04). The final multivariate model (PD duration, FOG, ACE, and physical activity) showed an AUC = 0.9282 (correctly classified = 89.83%; sensitivity = 92.68%; specificity = 83.33%). This study showed that our multivariate model have a high performance to predict falling in a sample of PD patients.

Using Recent Planetary Science Data to Develop Advanced Undergraduate Physics and Astronomy Activities

NASA Astrophysics Data System (ADS)

Steckloff, Jordan; Lindell, Rebecca

2016-10-01

Teaching science by having students manipulate real data is a popular trend in astronomy and planetary science education. However, many existing activities simply couple this data with traditional "cookbook" style verification labs. As with most topics within science, this instructional technique does not enhance the average students' understanding of the phenomena being studied. Here we present a methodology for developing "science by doing" activities that incorporate the latest discoveries in planetary science with up-to-date constructivist pedagogy to teach advanced concepts in Physics and Astronomy. In our methodology, students are first guided to understand, analyze, and plot real raw scientific data; develop and test physical and computational models to understand and interpret the data; finally use their models to make predictions about the topic being studied and test it with real data.To date, two activities have been developed according to this methodology: Understanding Asteroids through their Light Curves (hereafter "Asteroid Activity"), and Understanding Exoplanetary Systems through Simple Harmonic Motion (hereafter "Exoplanet Activity"). The Asteroid Activity allows students to explore light curves available on the Asteroid Light Curve Database (ALCDB) to discover general properties of asteroids, including their internal structure, strength, and mechanism of asteroid moon formation. The Exoplanet Activity allows students to investigate the masses and semi-major axes of exoplanets in a system by comparing the radial velocity motion of their host star to that of a coupled simple harmonic oscillator. Students then explore how noncircular orbits lead to deviations from simple harmonic motion. These activities will be field tested during the Fall 2016 semester in an advanced undergraduate mechanics and astronomy courses at a large Midwestern STEM-focused university. We will present the development methodologies for these activities, description of the activities, and results from the pre-tests.

Volcanology 2020: How will thermal remote sensing of volcanic surface activity evolve over the next decade?

NASA Astrophysics Data System (ADS)

Ramsey, Michael S.; Harris, Andrew J. L.

2013-01-01

Volcanological remote sensing spans numerous techniques, wavelength regions, data collection strategies, targets, and applications. Attempting to foresee and predict the growth vectors in this broad and rapidly developing field is therefore exceedingly difficult. However, we attempted to make such predictions at both the American Geophysical Union (AGU) meeting session entitled Volcanology 2010: How will the science and practice of volcanology change in the coming decade? held in December 2000 and the follow-up session 10 years later, Looking backward and forward: Volcanology in 2010 and 2020. In this summary paper, we assess how well we did with our predictions for specific facets of volcano remote sensing in 2000 the advances made over the most recent decade, and attempt a new look ahead to the next decade. In completing this review, we only consider the subset of the field focused on thermal infrared remote sensing of surface activity using ground-based and space-based technology and the subsequent research results. This review keeps to the original scope of both AGU presentations, and therefore does not address the entire field of volcanological remote sensing, which uses technologies in other wavelength regions (e.g., ultraviolet, radar, etc.) or the study of volcanic processes other than the those associated with surface (mostly effusive) activity. Therefore we do not consider remote sensing of ash/gas plumes, for example. In 2000, we had looked forward to a "golden age" in volcanological remote sensing, with a variety of new orbital missions both planned and recently launched. In addition, exciting field-based sensors such as hand-held thermal cameras were also becoming available and being quickly adopted by volcanologists for both monitoring and research applications. All of our predictions in 2000 came true, but at a pace far quicker than we predicted. Relative to the 2000-2010 timeframe, the coming decade will see far fewer new orbital instruments with direct applications to volcanology. However ground-based technologies and applications will continue to proliferate, and unforeseen technology promises many exciting possibilities that will advance volcano thermal monitoring and science far beyond what we can currently envision.

Overview of Advanced Space Propulsion Activities in the Space Environmental Effects Team at MSFC

NASA Technical Reports Server (NTRS)

Edwards, David; Carruth, Ralph; Vaughn, Jason; Schneider, Todd; Kamenetzky, Rachel; Gray, Perry

2000-01-01

Exploration of our solar system, and beyond, requires spacecraft velocities beyond our current technological level. Technologies addressing this limitation are numerous. The Space Environmental Effects (SEE) Team at the Marshall Space Flight Center (MSFC) is focused on three discipline areas of advanced propulsion; Tethers, Beamed Energy, and Plasma. This presentation will give an overview of advanced propulsion related activities in the Space Environmental Effects Team at MSFC. Advancements in the application of tethers for spacecraft propulsion were made while developing the Propulsive Small Expendable Deployer System (ProSEDS). New tether materials were developed to meet the specifications of the ProSEDS mission and new techniques had to be developed to test and characterize these tethers. Plasma contactors were developed, tested and modified to meet new requirements. Follow-on activities in tether propulsion include the Air-SEDS activity. Beamed energy activities initiated with an experimental investigation to quantify the momentum transfer subsequent to high power, 5J, ablative laser interaction with materials. The next step with this experimental investigation is to quantify non-ablative photon momentum transfer. This step was started last year and will be used to characterize the efficiency of solar sail materials before and after exposure to Space Environmental Effects (SEE). Our focus with plasma, for propulsion, concentrates on optimizing energy deposition into a magnetically confined plasma and integration of measurement techniques for determining plasma parameters. Plasma confinement is accomplished with the Marshall Magnetic Mirror (M3) device. Initial energy coupling experiments will consist of injecting a 50 amp electron beam into a target plasma. Measurements of plasma temperature and density will be used to determine the effect of changes in magnetic field structure, beam current, and gas species. Experimental observations will be compared to predictions from computer modeling.

Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

Cancer.gov

Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

Benchmark Simulations of the Thermal-Hydraulic Responses during EBR-II Inherent Safety Tests using SAM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Rui; Sumner, Tyler S.

2016-04-17

An advanced system analysis tool SAM is being developed for fast-running, improved-fidelity, and whole-plant transient analyses at Argonne National Laboratory under DOE-NE’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. As an important part of code development, companion validation activities are being conducted to ensure the performance and validity of the SAM code. This paper presents the benchmark simulations of two EBR-II tests, SHRT-45R and BOP-302R, whose data are available through the support of DOE-NE’s Advanced Reactor Technology (ART) program. The code predictions of major primary coolant system parameter are compared with the test results. Additionally, the SAS4A/SASSYS-1 code simulationmore » results are also included for a code-to-code comparison.« less

Ceramic technology for advanced heat engines project. Semiannual progress report, April-September 1985

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1986-05-01

An assessment of needs was completed, and a five-year project plan was developed with input from private industry. Objective is to develop the industrial technology base required for reliable ceramics for application in advanced automotive heat engines. Focus is on structural ceramics for advanced gas turbine and diesel engines, ceramic bearings and attachments, and ceramic coatings for thermal barrier and wear applications in these engines. The work described in this report is organized according to the following WBS project elements: management and coordination; materials and processing (monolithics, ceramic composites, thermal and wear coatings, joining); materials design methodology (contact interfaces, newmore » concepts); data base and life prediction (time-dependent behavior, environmental effects, fracture mechanics, NDE development); and technology transfer. This report includes contributions from all currently active project participants.« less

Young Zanzibari children with iron deficiency, iron deficiency anemia, stunting, or malaria have lower motor activity scores and spend less time in locomotion.

PubMed

Olney, Deanna K; Pollitt, Ernesto; Kariger, Patricia K; Khalfan, Sabra S; Ali, Nadra S; Tielsch, James M; Sazawal, Sunil; Black, Robert; Mast, Darrell; Allen, Lindsay H; Stoltzfus, Rebecca J

2007-12-01

Motor activity improves cognitive and social-emotional development through a child's exploration of his or her physical and social environment. This study assessed anemia, iron deficiency, hemoglobin (Hb), length-for-age Z-score (LAZ), and malaria infection as predictors of motor activity in 771 children aged 5-19 mo. Trained observers conducted 2- to 4-h observations of children's motor activity in and around their homes. Binary logistic regression assessed the predictors of any locomotion. Children who did not locomote during the observation (nonmovers) were excluded from further analyses. Linear regression evaluated the predictors of total motor activity (TMA) and time spent in locomotion for all children who locomoted during the observation combined (movers) and then separately for crawlers and walkers. Iron deficiency (77.0%), anemia (58.9%), malaria infection (33.9%), and stunting (34.6%) were prevalent. Iron deficiency with and without anemia, Hb, LAZ, and malaria infection significantly predicted TMA and locomotion in all movers. Malaria infection significantly predicted less TMA and locomotion in crawlers. In walkers, iron deficiency anemia predicted less activity and locomotion, whereas higher Hb and LAZ significantly predicted more activity and locomotion, even after controlling for attained milestone. Improvements in iron status and growth and prevention or effective treatment of malaria may improve children's motor, cognitive, and social-emotional development either directly or through improvements in motor activity. However, the relative importance of these factors is dependent on motor development, with malaria being important for the younger, less developmentally advanced children and Hb and LAZ becoming important as children begin to attain walking skills.

Advancements in Hydrology and Erosion Process Understanding and Post-Fire Hydrologic and Erosion Model Development for Semi-Arid Landscapes

NASA Astrophysics Data System (ADS)

Williams, C. Jason; Pierson, Frederick B.; Al-Hamdan, Osama Z.; Robichaud, Peter R.; Nearing, Mark A.; Hernandez, Mariano; Weltz, Mark A.; Spaeth, Kenneth E.; Goodrich, David C.

2017-04-01

Fire activity continues to increase in semi-arid regions around the globe. Private and governmental land management entities are challenged with predicting and mitigating post-fire hydrologic and erosion responses on these landscapes. For more than a decade, a team of scientists with the US Department of Agriculture has collaborated on extensive post-fire hydrologic field research and the application of field research to development of post-fire hydrology and erosion predictive technologies. Experiments funded through this research investigated the impacts of fire on vegetation and soils and the effects of these fire-induced changes on infiltration, runoff generation, erodibility, and soil erosion processes. The distribution of study sites spans diverse topography across grassland, shrubland, and woodland landscapes throughout the western United States. Knowledge gleaned from the extensive field experiments was applied to develop and enhance physically-based models for hillslope- to watershed-scale runoff and erosion prediction. Our field research and subsequent data syntheses have identified key knowledge gaps and challenges regarding post-fire hydrology and erosion modeling. Our presentation details some consistent trends across a diverse domain and varying landscape conditions based on our extensive field campaigns. We demonstrate how field data have advanced our understanding of post-fire hydrology and erosion for semi-arid landscapes and highlight remaining key knowledge gaps. Lastly, we briefly show how our well-replicated experimental methodologies have contributed to advancements in hydrologic and erosion model development for the post-fire environment.

Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs.

PubMed

Cherkasov, Artem; Hilpert, Kai; Jenssen, Håvard; Fjell, Christopher D; Waldbrook, Matt; Mullaly, Sarah C; Volkmer, Rudolf; Hancock, Robert E W

2009-01-16

Increased multiple antibiotic resistance in the face of declining antibiotic discovery is one of society's most pressing health issues. Antimicrobial peptides represent a promising new class of antibiotics. Here we ask whether it is possible to make small broad spectrum peptides employing minimal assumptions, by capitalizing on accumulating chemical biology information. Using peptide array technology, two large random 9-amino-acid peptide libraries were iteratively created using the amino acid composition of the most active peptides. The resultant data was used together with Artificial Neural Networks, a powerful machine learning technique, to create quantitative in silico models of antibiotic activity. On the basis of random testing, these models proved remarkably effective in predicting the activity of 100,000 virtual peptides. The best peptides, representing the top quartile of predicted activities, were effective against a broad array of multidrug-resistant "Superbugs" with activities that were equal to or better than four highly used conventional antibiotics, more effective than the most advanced clinical candidate antimicrobial peptide, and protective against Staphylococcus aureus infections in animal models.

A new account of the effect of probability on task switching: ERP evidence following the manipulation of switch probability, cue informativeness and predictability

PubMed Central

Nessler, Doreen; Friedman, David; Johnson, Ray

2012-01-01

This task-switching ERP study of 16 young participants investigated whether increased RT slowing on stay trials and faster RTs on switch trials for frequent than infrequent switching are explained by an activation or preparation account. The activation account proposes that task sets are maintained at a higher baseline activation level for frequent switching, necessitating increased task-set updating, as reflected by a larger and/or longer lasting early parietal positivity. The preparation account assumes advance (pre-cue) switch preparation (i.e., task-set reconfiguration), preceding stay and switch trials for frequent switching, as reflected by pre-cue and post-cue late parietal positivities. By and large, the data support the activation account. However, we also found increased, pre-cue task-set updating on frequent stay trials and pre-cue, task-set reconfiguration prior to predictable, frequent switches. These results lead us to propose an extended activation account to explain the effects of switch probability on the executive processes underlying task-switching behavior. PMID:22820040

Prostate-specific acid phosphatase versus acid phosphatase in monitoring patients with prostate cancer.

PubMed

Killian, C S; Vargas, F P; Slack, N H; Murphy, G P; Chu, T M

1982-01-01

Serial levels of PAP and AcP activity were compared for their relative values in monitoring 57 early and 33 advanced prostate cancer patients. Several findings regarding the patients' disease status and the enzyme levels have been observed that may be beneficial to therapeutic management of these patients. They are: [1] an elevated PAP activity in disease recurrence and disease progression generally precedes an elevated AcP activity, and thus represents a more sensitive index for patients with early and advanced disease; [2] serial mean levels of PAP activity greater than the mean + 3 SD are more predictive for disease recurrence and progression than are those of AcP activity in both groups of patients; [3] PAP activity is a more sensitive monitor for changes in objective treatment response than is AcP activity; and [4] PAP is more specific than AcP for prostate, thus offering a more reliable marker to identify metastasis of unknown origin, or to confirm metastasis derived from a primary prostate tumor that may have been suggested by other non-prostate-specific marker[s]. In addition, data suggest a favorable prognosis for patients receiving therapy as inferred by a serial mean of PAP activity that is less than mean + 3 SD.

Machine learning for epigenetics and future medical applications.

PubMed

Holder, Lawrence B; Haque, M Muksitul; Skinner, Michael K

2017-07-03

Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems with ML to develop a more efficient feature selection process and address the imbalance problem in all genomic data sets. The power of this novel ML approach and our ability to predict epigenetic phenomena and associated disease is suggested. The current approach requires extensive computation of features over the genome. A promising new approach is to introduce Deep Learning (DL) for the generation and simultaneous computation of novel genomic features tuned to the classification task. This approach can be used with any genomic or biological data set applied to medicine. The application of molecular epigenetic data in advanced machine learning analysis to medicine is the focus of this review.

Guiding Empirical and Theoretical Explorations of Organic Matter Decay By Synthesizing Temperature Responses of Enzyme Kinetics, Microbes, and Isotope Fluxes

NASA Astrophysics Data System (ADS)

Billings, S. A.; Ballantyne, F.; Lehmeier, C.; Min, K.

2014-12-01

Soil organic matter (SOM) transformation rates generally increase with temperature, but whether this is realized depends on soil-specific features. To develop predictive models applicable to all soils, we must understand two key, ubiquitous features of SOM transformation: the temperature sensitivity of myriad enzyme-substrate combinations and temperature responses of microbial physiology and metabolism, in isolation from soil-specific conditions. Predicting temperature responses of production of CO2 vs. biomass is also difficult due to soil-specific features: we cannot know the identity of active microbes nor the substrates they employ. We highlight how recent empirical advances describing SOM decay can help develop theoretical tools relevant across diverse spatial and temporal scales. At a molecular level, temperature effects on purified enzyme kinetics reveal distinct temperature sensitivities of decay of diverse SOM substrates. Such data help quantify the influence of microbial adaptations and edaphic conditions on decay, have permitted computation of the relative availability of carbon (C) and nitrogen (N) liberated upon decay, and can be used with recent theoretical advances to predict changes in mass specific respiration rates as microbes maintain biomass C:N with changing temperature. Enhancing system complexity, we can subject microbes to temperature changes while controlling growth rate and without altering substrate availability or identity of the active population, permitting calculation of variables typically inferred in soils: microbial C use efficiency (CUE) and isotopic discrimination during C transformations. Quantified declines in CUE with rising temperature are critical for constraining model CUE estimates, and known changes in δ13C of respired CO2 with temperature is useful for interpreting δ13C-CO2 at diverse scales. We suggest empirical studies important for advancing knowledge of how microbes respond to temperature, and ideas for theoretical work to enhance the relevance of such work to the world's soils.

Light and sound - emerging imaging techniques for inflammatory bowel disease

PubMed Central

Knieling, Ferdinand; Waldner, Maximilian J

2016-01-01

Patients with inflammatory bowel disease are known to have a high demand of recurrent evaluation for therapy and disease activity. Further, the risk of developing cancer during the disease progression is increasing from year to year. New, mostly non-radiant, quick to perform and quantitative methods are challenging, conventional endoscopy with biopsy as gold standard. Especially, new physical imaging approaches utilizing light and sound waves have facilitated the development of advanced functional and molecular modalities. Besides these advantages they hold the promise to predict personalized therapeutic responses and to spare frequent invasive procedures. Within this article we highlight their potential for initial diagnosis, assessment of disease activity and surveillance of cancer development in established techniques and recent advances such as wide-view full-spectrum endoscopy, chromoendoscopy, autofluorescence endoscopy, endocytoscopy, confocal laser endoscopy, multiphoton endoscopy, molecular imaging endoscopy, B-mode and Doppler ultrasound, contrast-enhanced ultrasound, ultrasound molecular imaging, and elastography. PMID:27433080

Simple Response Surface Methodology: Investigation on Advance Photocatalytic Oxidation of 4-Chlorophenoxyacetic Acid Using UV-Active ZnO Photocatalyst.

PubMed

Lee, Kian Mun; Hamid, Sharifah Bee Abd

2015-01-19

The performance of advance photocatalytic degradation of 4-chlorophenoxyacetic acid (4-CPA) strongly depends on photocatalyst dosage, initial concentration and initial pH. In the present study, a simple response surface methodology (RSM) was applied to investigate the interaction between these three independent factors. Thus, the photocatalytic degradation of 4-CPA in aqueous medium assisted by ultraviolet-active ZnO photocatalyst was systematically investigated. This study aims to determine the optimum processing parameters to maximize 4-CPA degradation. Based on the results obtained, it was found that a maximum of 91% of 4-CPA was successfully degraded under optimal conditions (0.02 g ZnO dosage, 20.00 mg/L of 4-CPA and pH 7.71). All the experimental data showed good agreement with the predicted results obtained from statistical analysis.

Intraseasonal variability of the West African monsoon and African easterly waves during boreal summer

NASA Astrophysics Data System (ADS)

Alaka, Ghassan J., Jr.

Substantial subseasonal variability in African easterly wave (AEW) activity and cyclogenesis frequency occurs in the main hurricane development region of the Atlantic during boreal summer. A complete understanding of intraseasonal variability in the Atlantic and west Africa during boreal summer requires analysis of how the Madden-Julian Oscillation (MJO) modulates the west African monsoon and consequently AEWs. Because the MJO is predictable a few weeks in advance, understanding how and why the MJO impacts the west African monsoon may have a profound influence on Atlantic tropical cyclone prediction. This study documents the MJO influence on the west African monsoon system during boreal summer using a variety of reanalysis and satellite datasets. This study aims to identify and explain the MJO teleconnection to the west African monsoon, and the processes that induce precipitation and AEW variability in this region. Intraseasonal west African and Atlantic convective anomalies on 30-90 day timescales are likely induced by equatorial Kelvin and Rossby waves generated in the Indian Ocean and west Pacific by the MJO. Previous studies have hypothesized that an area including the Darfur mountains and the Ethiopian highlands is an initiation region for AEWs. It is shown here that the initial MJO influence on precipitation and AEW activity in the African monsoon appears to occur in these regions, where eddy kinetic energy (EKE) anomalies first appear in advance of MJO-induced periods of enhanced and suppressed AEW activity. In the initiation region, upper tropospheric temperature anomalies are reduced, the atmosphere moistens by horizontal advection, and an eastward extension of the African easterly jet occurs in advance of the MJO wet phase of the African monsoon, when AEW activity is also enhanced. These factors all support strong precursor disturbances in the initiation region that seed the African easterly jet and contribute to downstream development of AEWs. Opposite behavior occurs in advance of the MJO dry phase. Moisture and eddy kinetic energy (EKE) budgets are examined to provide further insight as to how the MJO modulates and initiates precipitation and AEW variability in this region. In particular, meridional moisture advection anomalies foster moistening in the initiation region by anomalous flow acting across the mean moisture gradient. Additionally, positive (negative) upstream EKE tendency anomalies in advance of the MJO convective maximum (minimum) over tropical north Africa suggest wave growth (decay) near the entrance of the AEJ, while enhanced (suppressed) conversion of eddy available potential energy (EAPE) to EKE and barotropic conversion maintains downstream AEW growth (decay).

Advanced Concepts, Technologies and Flight Experiments for NASA's Earth Science Enterprise

NASA Technical Reports Server (NTRS)

Meredith, Barry D.

2000-01-01

Over the last 25 years, NASA Langley Research Center (LaRC) has established a tradition of excellence in scientific research and leading-edge system developments, which have contributed to improved scientific understanding of our Earth system. Specifically, LaRC advances knowledge of atmospheric processes to enable proactive climate prediction and, in that role, develops first-of-a-kind atmospheric sensing capabilities that permit a variety of new measurements to be made within a constrained enterprise budget. These advances are enabled by the timely development and infusion of new, state-of-the-art (SOA), active and passive instrument and sensor technologies. In addition, LaRC's center-of-excellence in structures and materials is being applied to the technological challenges of reducing measurement system size, mass, and cost through the development and use of space-durable materials; lightweight, multi-functional structures; and large deployable/inflatable structures. NASA Langley is engaged in advancing these technologies across the full range of readiness levels from concept, to components, to prototypes, to flight experiments, and on to actual science mission infusion. The purpose of this paper is to describe current activities and capabilities, recent achievements, and future plans of the integrated science, engineering, and technology team at Langley Research Center who are working to enable the future of NASA's Earth Science Enterprise.

Religious Coping and Behavioral Disengagement: Opposing Influences on Advance Care Planning and Receipt of Intensive Care Near Death

PubMed Central

Maciejewski, Paul K.; Phelps, Andrea C.; Kacel, Elizabeth L.; Balboni, Tracy A.; Balboni, Michael; Wright, Alexi A.; Pirl, William; Prigerson, Holly G.

2011-01-01

Objective This study examines the relationships between methods of coping with advanced cancer, completion of advance care directives, and receipt of intensive, life-prolonging care near death. Methods The analysis is based on a sample of 345 patients interviewed between January 1, 2003, and August 31, 2007, and followed until death as part of the Coping with Cancer Study, an NCI/NIMH-funded, multi-site, prospective, longitudinal, cohort study of patients with advanced cancer. The Brief COPE was used to assess active coping, use of emotional-support, and behavioral disengagement. The Brief RCOPE was used to assess positive and negative religious coping. The main outcome was intensive, life-prolonging care near death, defined as receipt of ventilation or resuscitation in the last week of life. Results Positive religious coping was associated with lower rates of having a living will (AOR=0.39, p=0.003) and predicted higher rates of intensive, life-prolonging care near death (AOR, 5.43; p<0.001), adjusting for other coping methods and potential socio-demographic and health status confounds. Behavioral disengagement was associated with higher rates of DNR order completion (AOR, 2.78; p=0.003) and predicted lower rates of intensive life-prolonging care near death (AOR, 0.20; p=0.036). Not having a living will partially mediated the influence of positive religious coping on receipt of intensive, life-prolonging care near death. Conclusion Positive religious coping and behavioral disengagement are important determinants of completion of advance care directives and receipt of intensive, life-prolonging care near death. PMID:21449037

A composite model including visfatin, tissue polypeptide-specific antigen, hyaluronic acid, and hematological variables for the diagnosis of moderate-to-severe fibrosis in nonalcoholic fatty liver disease: a preliminary study.

PubMed

Chwist, Alina; Hartleb, Marek; Lekstan, Andrzej; Kukla, Michał; Gutkowski, Krzysztof; Kajor, Maciej

2014-01-01

Histopathological risk factors for end-stage liver failure in patients with nonalcoholic fatty liver disease (NAFLD) include nonalcoholic steatohepatitis (NASH) and advanced liver fibrosis. There is a need for noninvasive diagnostic methods for these 2 conditions. The aim of this study was to investigate new laboratory variables with a predictive potential to detect advanced fibrosis (stages 2 and 3) in NAFLD. The study involved 70 patients with histologically proven NAFLD of varied severity. Additional laboratory variables included zonulin, haptoglobin, visfatin, adiponectin, leptin, tissue polypeptide-specific antigen (TPSA), hyaluronic acid, and interleukin 6. Patients with NASH (NAFLD activity score of ≥5) had significantly higher HOMA-IR values and serum levels of visfatin, haptoglobin, and zonulin as compared with those without NASH on histological examination. Advanced fibrosis was found in 16 patients (22.9%) and the risk factors associated with its prevalence were age, the ratio of erythrocyte count to red blood cell distribution width, platelet count, and serum levels of visfatin and TPSA. Based on these variables, we constructed a scoring system that differentiated between NAFLD patients with and without advanced fibrosis with a sensitivity of 75% and specificity of 100% (area under the receiver operating characteristic curve, 0.93). The scoring system based on the above variables allows to predict advanced fibrosis with high sensitivity and specificity. However, its clinical utility should be verified in further studies involving a larger number of patients.

In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

PubMed

Kleandrova, Valeria V; Luan, Feng; Speck-Planche, Alejandro; Cordeiro, M Natália D S

2015-01-01

The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of toxicity assays have been carried out on laboratory animals. In this sense, computational approaches involving models based on quantitative-structure activity/toxicity relationships (QSAR/QSTR) can help to rationalize time and financial costs. Here, we discuss the most significant advances in the last 6 years focused on the use of QSAR/QSTR models to predict acute toxicity of drugs/chemicals in laboratory animals, employing large and heterogeneous datasets. The advantages and drawbacks of the different QSAR/QSTR models are analyzed. As a contribution to the field, we introduce the first multitasking (mtk) QSTR model for simultaneous prediction of acute toxicity of compounds by considering different routes of administration, diverse breeds of laboratory animals, and the reliability of the experimental conditions. The mtk-QSTR model was based on artificial neural networks (ANN), allowing the classification of compounds as toxic or non-toxic. This model correctly classified more than 94% of the 1646 cases present in the whole dataset, and its applicability was demonstrated by performing predictions of different chemicals such as drugs, dietary supplements, and molecules which could serve as nanocarriers for drug delivery. The predictions given by the mtk-QSTR model are in very good agreement with the experimental results.

Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2009-06-01

We are working with our collaborators at the Applied Biotechnology Branch, A ir Force Research Lab, W right-Patterson Air Force Base, to accomplish...with systemic lupus erythematosus. Arthritis Rheum 2001;44:2350–7. 33. Zappitelli M, Duffy CM, Bernard C, Gupta IR . Evaluation of activity, chronicity...Children’s Hospital, Chicago, IL: Dr. Linda Wagner-Weiner (data collection); Becky Puplava (study coordinator). University of Okla- homa Health Sciences

A Review of Past Insights by Robert Forward and Current Advanced Propulsion Activities

NASA Technical Reports Server (NTRS)

Robertson, Tony; Norley, G. D.

2003-01-01

A review of various technologies discussed by Dr. Robert Forward is done as a tribute to Dr. Forward, and is based on selections from his writings. These speculations and predictions by Dr. Forward are used as a basis for discussing expected propulsion technology work over the next twenty years. Among the technologies to be discussed are antimatter propulsion, space elevators and tethers, and laser propulsion.

Development of Technologies for Early Detection and Stratification of Breast Cancer

DTIC Science & Technology

2013-10-01

advances made in breast cancer diagnostics and treatment, it has been estimated that in 2012 the United States will diagnose approximately 200,000 new cases...Task 3. Perform prospective clinical trial for predictive and prognostic markers in women with newly diagnosed breast cancer (Months 1-60...with newly diagnosed breast cancer, women who are being followed after completing treatment for localized breast cancer, and women with active

Overview of mechanics of materials branch activities in the computational structures area

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.

1992-01-01

Base programs and system programs are discussed. The base programs include fundamental research of composites and metals for airframes leading to characterization of advanced materials, models of behavior, and methods for predicting damage tolerance. Results from the base programs support the systems programs, which change as NASA's missions change. The National Aerospace Plane (NASP), Advanced Composites Technology (ACT), Airframe Structural Integrity Program (Aging Aircraft), and High Speed Research (HSR) programs are currently being supported. Airframe durability is one of the key issues in each of these system programs. The base program has four major thrusts, which will be reviewed subsequently. Additionally, several technical highlights will be reviewed for each thrust.

Actigraphy and motion analysis: new tools for psychiatry.

PubMed

Teicher, M H

1995-01-01

Altered locomotor activity is a cardinal sign of several psychiatric disorders. With advances in technology, activity can now be measured precisely. Contemporary studies quantifying activity in psychiatric patients are reviewed. Studies were located by a Medline search (1965 to present; English language only) cross-referencing motor activity and major psychiatric disorders. The review focused on mood disorders and attention-deficit hyperactivity disorder (ADHD). Activity levels are elevated in mania, agitated depression, and ADHD and attenuated in bipolar depression and seasonal depression. The percentage of low-level daytime activity is directly related to severity of depression, and change in this parameter accurately mirrors recovery. Demanding cognitive tasks elicit fidgeting in children with ADHD, and precise measures of activity and attention may provide a sensitive and specific marker for this disorder. Circadian rhythm analysis enhances the sophistication of activity measures. Affective disorders in children and adolescents are characterized by an attenuated circadian rhythm and an enhanced 12-hour harmonic rhythm (diurnal variation). Circadian analysis may help to distinguish between the activity patterns of mania (dysregulated) and ADHD (intact or enhanced). Persistence of hyperactivity or circadian dysregulation in bipolar patients treated with lithium appears to predict rapid relapse once medication is discontinued. Activity monitoring is a valuable research tool, with the potential to aid clinicians in diagnosis and in prediction of treatment response.

Programmable Nucleic Acid Based Polygons with Controlled Neuroimmunomodulatory Properties for Predictive QSAR Modeling.

PubMed

Johnson, Morgan Brittany; Halman, Justin R; Satterwhite, Emily; Zakharov, Alexey V; Bui, My N; Benkato, Kheiria; Goldsworthy, Victoria; Kim, Taejin; Hong, Enping; Dobrovolskaia, Marina A; Khisamutdinov, Emil F; Marriott, Ian; Afonin, Kirill A

2017-11-01

In the past few years, the study of therapeutic RNA nanotechnology has expanded tremendously to encompass a large group of interdisciplinary sciences. It is now evident that rationally designed programmable RNA nanostructures offer unique advantages in addressing contemporary therapeutic challenges such as distinguishing target cell types and ameliorating disease. However, to maximize the therapeutic benefit of these nanostructures, it is essential to understand the immunostimulatory aptitude of such tools and identify potential complications. This paper presents a set of 16 nanoparticle platforms that are highly configurable. These novel nucleic acid based polygonal platforms are programmed for controllable self-assembly from RNA and/or DNA strands via canonical Watson-Crick interactions. It is demonstrated that the immunostimulatory properties of these particular designs can be tuned to elicit the desired immune response or lack thereof. To advance the current understanding of the nanoparticle properties that contribute to the observed immunomodulatory activity and establish corresponding designing principles, quantitative structure-activity relationship modeling is conducted. The results demonstrate that molecular weight, together with melting temperature and half-life, strongly predicts the observed immunomodulatory activity. This framework provides the fundamental guidelines necessary for the development of a new library of nanoparticles with predictable immunomodulatory activity. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

New horizons in mouse immunoinformatics: reliable in silico prediction of mouse class I histocompatibility major complex peptide binding affinity.

PubMed

Hattotuwagama, Channa K; Guan, Pingping; Doytchinova, Irini A; Flower, Darren R

2004-11-21

Quantitative structure-activity relationship (QSAR) analysis is a main cornerstone of modern informatic disciplines. Predictive computational models, based on QSAR technology, of peptide-major histocompatibility complex (MHC) binding affinity have now become a vital component of modern day computational immunovaccinology. Historically, such approaches have been built around semi-qualitative, classification methods, but these are now giving way to quantitative regression methods. The additive method, an established immunoinformatics technique for the quantitative prediction of peptide-protein affinity, was used here to identify the sequence dependence of peptide binding specificity for three mouse class I MHC alleles: H2-D(b), H2-K(b) and H2-K(k). As we show, in terms of reliability the resulting models represent a significant advance on existing methods. They can be used for the accurate prediction of T-cell epitopes and are freely available online ( http://www.jenner.ac.uk/MHCPred).

Season-ahead water quality forecasts for the Schuylkill River, Pennsylvania

NASA Astrophysics Data System (ADS)

Block, P. J.; Leung, K.

2013-12-01

Anticipating and preparing for elevated water quality parameter levels in critical water sources, using weather forecasts, is not uncommon. In this study, we explore the feasibility of extending this prediction scale to a season-ahead for the Schuylkill River in Philadelphia, utilizing both statistical and dynamical prediction models, to characterize the season. This advance information has relevance for recreational activities, ecosystem health, and water treatment, as the Schuylkill provides 40% of Philadelphia's water supply. The statistical model associates large-scale climate drivers with streamflow and water quality parameter levels; numerous variables from NOAA's CFSv2 model are evaluated for the dynamical approach. A multi-model combination is also assessed. Results indicate moderately skillful prediction of average summertime total coliform and wintertime turbidity, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic Ocean. Models predicting the number of elevated turbidity events across the wintertime season are also explored.

Advanced Computational Modeling Approaches for Shock Response Prediction

NASA Technical Reports Server (NTRS)

Derkevorkian, Armen; Kolaini, Ali R.; Peterson, Lee

2015-01-01

Motivation: (1) The activation of pyroshock devices such as explosives, separation nuts, pin-pullers, etc. produces high frequency transient structural response, typically from few tens of Hz to several hundreds of kHz. (2) Lack of reliable analytical tools makes the prediction of appropriate design and qualification test levels a challenge. (3) In the past few decades, several attempts have been made to develop methodologies that predict the structural responses to shock environments. (4) Currently, there is no validated approach that is viable to predict shock environments overt the full frequency range (i.e., 100 Hz to 10 kHz). Scope: (1) Model, analyze, and interpret space structural systems with complex interfaces and discontinuities, subjected to shock loads. (2) Assess the viability of a suite of numerical tools to simulate transient, non-linear solid mechanics and structural dynamics problems, such as shock wave propagation.

Patterns of neural activity associated with honest and dishonest moral decisions

PubMed Central

Greene, Joshua D.; Paxton, Joseph M.

2009-01-01

What makes people behave honestly when confronted with opportunities for dishonest gain? Research on the interplay between controlled and automatic processes in decision making suggests 2 hypotheses: According to the “Will” hypothesis, honesty results from the active resistance of temptation, comparable to the controlled cognitive processes that enable the delay of reward. According to the “Grace” hypothesis, honesty results from the absence of temptation, consistent with research emphasizing the determination of behavior by the presence or absence of automatic processes. To test these hypotheses, we examined neural activity in individuals confronted with opportunities for dishonest gain. Subjects undergoing functional magnetic resonance imaging (fMRI) gained money by accurately predicting the outcomes of computerized coin-flips. In some trials, subjects recorded their predictions in advance. In other trials, subjects were rewarded based on self-reported accuracy, allowing them to gain money dishonestly by lying about the accuracy of their predictions. Many subjects behaved dishonestly, as indicated by improbable levels of “accuracy.” Our findings support the Grace hypothesis. Individuals who behaved honestly exhibited no additional control-related activity (or other kind of activity) when choosing to behave honestly, as compared with a control condition in which there was no opportunity for dishonest gain. In contrast, individuals who behaved dishonestly exhibited increased activity in control-related regions of prefrontal cortex, both when choosing to behave dishonestly and on occasions when they refrained from dishonesty. Levels of activity in these regions correlated with the frequency of dishonesty in individuals. PMID:19622733

Stereotypes Possess Heterogeneous Directionality: A Theoretical and Empirical Exploration of Stereotype Structure and Content

PubMed Central

Cox, William T. L.; Devine, Patricia G.

2015-01-01

We advance a theory-driven approach to stereotype structure, informed by connectionist theories of cognition. Whereas traditional models define or tacitly assume that stereotypes possess inherently Group → Attribute activation directionality (e.g., Black activates criminal), our model predicts heterogeneous stereotype directionality. Alongside the classically studied Group → Attribute stereotypes, some stereotypes should be bidirectional (i.e., Group ⇄ Attribute) and others should have Attribute → Group unidirectionality (e.g., fashionable activates gay). We tested this prediction in several large-scale studies with human participants (NCombined = 4,817), assessing stereotypic inferences among various groups and attributes. Supporting predictions, we found heterogeneous directionality both among the stereotype links related to a given social group and also between the links of different social groups. These efforts yield rich datasets that map the networks of stereotype links related to several social groups. We make these datasets publicly available, enabling other researchers to explore a number of questions related to stereotypes and stereotyping. Stereotype directionality is an understudied feature of stereotypes and stereotyping with widespread implications for the development, measurement, maintenance, expression, and change of stereotypes, stereotyping, prejudice, and discrimination. PMID:25811181

Stereotypes possess heterogeneous directionality: a theoretical and empirical exploration of stereotype structure and content.

PubMed

Cox, William T L; Devine, Patricia G

2015-01-01

We advance a theory-driven approach to stereotype structure, informed by connectionist theories of cognition. Whereas traditional models define or tacitly assume that stereotypes possess inherently Group → Attribute activation directionality (e.g., Black activates criminal), our model predicts heterogeneous stereotype directionality. Alongside the classically studied Group → Attribute stereotypes, some stereotypes should be bidirectional (i.e., Group ⇄ Attribute) and others should have Attribute → Group unidirectionality (e.g., fashionable activates gay). We tested this prediction in several large-scale studies with human participants (NCombined = 4,817), assessing stereotypic inferences among various groups and attributes. Supporting predictions, we found heterogeneous directionality both among the stereotype links related to a given social group and also between the links of different social groups. These efforts yield rich datasets that map the networks of stereotype links related to several social groups. We make these datasets publicly available, enabling other researchers to explore a number of questions related to stereotypes and stereotyping. Stereotype directionality is an understudied feature of stereotypes and stereotyping with widespread implications for the development, measurement, maintenance, expression, and change of stereotypes, stereotyping, prejudice, and discrimination.

Advancing Drought Understanding, Monitoring and Prediction

NASA Technical Reports Server (NTRS)

Mariotti, Annarita; Schubert, Siegfried D.; Mo, Kingtse; Peters-Lidard, Christa; Wood, Andy; Pulwarty, Roger; Huang, Jin; Barrie, Dan

2013-01-01

Having the capacity to monitor droughts in near-real time and providing accurate drought prediction from weeks to seasons in advance can greatly reduce the severity of social and economic damage caused by drought, a leading natural hazard for North America. The congressional mandate to establish the National Integrated Drought Information System (NIDIS; Public Law 109-430) in 2006 was a major impulse to develop, integrate, and provide drought information to meet the challenges posed by this hazard. Significant progress has been made on many fronts. On the research front, efforts by the broad scientific community have resulted in improved understanding of North American droughts and improved monitoring and forecasting tools. We now have a better understanding of the droughts of the twentieth century including the 1930s "Dust Bowl"; we have developed a broader array of tools and datasets that enhance the official North American Drought Monitor based on different methodologies such as state-of-the-art land surface modeling (e.g., the North American Land Data Assimilation System) and remote sensing (e.g., the evaporative stress index) to better characterize the occurrence and severity of drought in its multiple manifestations. In addition, we have new tools for drought prediction [including the new National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2, for operational prediction and an experimental National Multimodel Ensemble] and have explored diverse methodologies including ensemble hydrologic prediction approaches. Broad NIDIS-inspired progress is influencing the development of a Global Drought Information System (GDIS) under the auspices of the World Climate Research Program. Despite these advances, current drought monitoring and forecasting capabilities still fall short of users' needs, especially the need for skillful and reliable drought forecasts at regional and local scales. To tackle this outstanding challenging problem, focused and coordinated research efforts are needed, drawing from excellence across the broad drought research community. To meet this challenge, National Oceanic and Atmospheric Administration (NOAA)'s Drought Task Force was established in October 2011 with the ambitious goal of achieving significant new advances in the ability to understand, monitor, and predict drought over North America. The Task Force (duration of October 2011-September 2014) is an initiative of NOAA's Climate Program Office Modeling, Analysis, Predictions, and Projections (MAPP) program in partnership with NIDIS. It brings together over 30 leading MAPP-funded drought scientists from multiple academic and federal institutions [involves scientists from NOAA's research laboratories and centers, the National Aeronautics and Space Administration (NASA), U.S. Department of Agriculture, National Center for Atmospheric Research (NCAR), and many universities] in a concerted research effort that builds on individual MAPP research projects. These projects span the wide spectrum of drought research needed to make fundamental advances, from those aimed at the basic understanding of drought mechanisms to those aimed at testing new drought monitoring and prediction tools for operational and service purposes (as part of NCEP's Climate Test Bed). The Drought Task Force provides focus and coordination to MAPP drought research activities and also facilitates synergies with other national and international drought research efforts, including those by the GDIS.

Prevalence and features of advanced asbestosis (ILO profusion scores above 2/2). International Labour Office.

PubMed

Kilburn, K H

2000-01-01

In this study, the author addressed the following question: Do workers with advanced asbestosis have a restrictive pulmonary physiology, and, alternately, do those who have restrictive physiological tests have advanced asbestosis? One group was identified by obvious radiographic measurements, and the other group was defined via physiologic measurements. Total lung capacity, vital capacity, and flows were measured in 12,856 men exposed to asbestos, of whom 3,445 had radiographic signs of asbestosis, as defined by the International Labour Office criteria. Radiographically advanced asbestosis-International Labour Office criteria profusion greater than 2/2 was present in 85 (2.5%) of men. An additional 52 men had physiologically restrictive disease. The author, who compared pulmonary flows and volumes of these two groups, used mean percentage predicted, adjusted for height, age, and duration of cigarette smoking. Men with radiographically advanced asbestosis had normal total lung capacity (i.e., 105.5% predicted), reduced forced vital capacities (i.e., 82.7% predicted), air trapping (i.e., residual volume/total lung capacity increased to 54.4%), and reduced flows (i.e., forced expiratory flow [FEF25-75] = 60.6% predicted, forced expiratory volume in 1 s = 78.0% predicted, and forced expiratory volume in 1 s/forced vital capacity = 65.5%). In contrast, men selected from the same exposed population for restrictive disease (i.e., reduced total lung capacity [72.6% predicted] and forced vital capacity [61.5% predicted]) also had airflow obstruction (i.e., forced expiratory volume in 1 s/forced vital capacity of 74.5% predicted) and air trapping (i.e., residual volume/total lung capacity of 46.7%). Only half of these men had asbestosis--and it was of minimal severity. In summary, advanced asbestosis was characterized by airway obstruction and air trapping, both of which reduced vital capacity but not total lung capacity; therefore, it was not a restrictive disease. In contrast, restrictive disease was rare and was associated with minimal asbestosis.

NREL Projects Awarded More Than $3 Million to Advance Novel Solar

Science.gov Websites

in Grid Operations," evaluating a research solution to better integrate solar power generation funding program, which advances state-of-the-art techniques for predicting solar power generation to Office to advance predictive modeling of solar power as part of its Solar Forecasting 2 funding program

Echocardiography and risk prediction in advanced heart failure: incremental value over clinical markers.

PubMed

Agha, Syed A; Kalogeropoulos, Andreas P; Shih, Jeffrey; Georgiopoulou, Vasiliki V; Giamouzis, Grigorios; Anarado, Perry; Mangalat, Deepa; Hussain, Imad; Book, Wendy; Laskar, Sonjoy; Smith, Andrew L; Martin, Randolph; Butler, Javed

2009-09-01

Incremental value of echocardiography over clinical parameters for outcome prediction in advanced heart failure (HF) is not well established. We evaluated 223 patients with advanced HF receiving optimal therapy (91.9% angiotensin-converting enzyme inhibitor/angiotensin receptor blocker, 92.8% beta-blockers, 71.8% biventricular pacemaker, and/or defibrillator use). The Seattle Heart Failure Model (SHFM) was used as the reference clinical risk prediction scheme. The incremental value of echocardiographic parameters for event prediction (death or urgent heart transplantation) was measured by the improvement in fit and discrimination achieved by addition of standard echocardiographic parameters to the SHFM. After a median follow-up of 2.4 years, there were 38 (17.0%) events (35 deaths; 3 urgent transplants). The SHFM had likelihood ratio (LR) chi(2) 32.0 and C statistic 0.756 for event prediction. Left ventricular end-systolic volume, stroke volume, and severe tricuspid regurgitation were independent echocardiographic predictors of events. The addition of these parameters to SHFM improved LR chi(2) to 72.0 and C statistic to 0.866 (P < .001 and P=.019, respectively). Reclassifying the SHFM-predicted risk with use of the echocardiography-added model resulted in improved prognostic separation. Addition of standard echocardiographic variables to the SHFM results in significant improvement in risk prediction for patients with advanced HF.

Experimental Detection of the Intrinsic Difference in Raman Optical Activity of a Photoreceptor Protein under Preresonance and Resonance Conditions.

PubMed

Haraguchi, Shojiro; Hara, Miwa; Shingae, Takahito; Kumauchi, Masato; Hoff, Wouter D; Unno, Masashi

2015-09-21

Raman optical activity (ROA) is an advanced technique capable of detecting structural deformations of light-absorbing molecules embedded in chromophoric proteins. Resonance Raman (RR) spectroscopy is widely used to enhance the band intensities. However, theoretical work has predicted that under resonance conditions the ROA spectrum resembles the shape of the RR spectrum. Herein, we use photoactive yellow protein (PYP) to measure the first experimental data on the effect of changing the excitation wavelength on the ROA spectra of a protein. We observe a close similarity between the shape of the RR spectrum and the resonance ROA spectrum of PYP. Furthermore, we experimentally verify the theoretical prediction concerning the ratio of the amplitudes of the ROA and Raman spectra. Our data demonstrate that selecting an appropriate excitation wavelength is a key factor for extracting structural information on a protein active site using ROA spectroscopy. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Quantum mechanical design of enzyme active sites.

PubMed

Zhang, Xiyun; DeChancie, Jason; Gunaydin, Hakan; Chowdry, Arnab B; Clemente, Fernando R; Smith, Adam J T; Handel, T M; Houk, K N

2008-02-01

The design of active sites has been carried out using quantum mechanical calculations to predict the rate-determining transition state of a desired reaction in presence of the optimal arrangement of catalytic functional groups (theozyme). Eleven versatile reaction targets were chosen, including hydrolysis, dehydration, isomerization, aldol, and Diels-Alder reactions. For each of the targets, the predicted mechanism and the rate-determining transition state (TS) of the uncatalyzed reaction in water is presented. For the rate-determining TS, a catalytic site was designed using naturalistic catalytic units followed by an estimation of the rate acceleration provided by a reoptimization of the catalytic site. Finally, the geometries of the sites were compared to the X-ray structures of related natural enzymes. Recent advances in computational algorithms and power, coupled with successes in computational protein design, have provided a powerful context for undertaking such an endeavor. We propose that theozymes are excellent candidates to serve as the active site models for design processes.

The Complexity of Solar and Geomagnetic Indices

NASA Astrophysics Data System (ADS)

Pesnell, W. Dean

2017-08-01

How far in advance can the sunspot number be predicted with any degree of confidence? Solar cycle predictions are needed to plan long-term space missions. Fleets of satellites circle the Earth collecting science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Statistical and timeseries analyses of the sunspot number are often used to predict solar activity. These methods have not been completely successful as the solar dynamo changes over time and one cycle's sunspots are not a faithful predictor of the next cycle's activity. In some ways, using these techniques is similar to asking whether the stock market can be predicted. It has been shown that the Dow Jones Industrial Average (DJIA) can be more accurately predicted during periods when it obeys certain statistical properties than at other times. The Hurst exponent is one such way to partition the data. Another measure of the complexity of a timeseries is the fractal dimension. We can use these measures of complexity to compare the sunspot number with other solar and geomagnetic indices. Our concentration is on how trends are removed by the various techniques, either internally or externally. Comparisons of the statistical properties of the various solar indices may guide us in understanding how the dynamo manifests in the various indices and the Sun.

Community-based participatory research to decrease smoking prevalence in a high-risk young adult population: an evaluation of the Students Against Nicotine and Tobacco Addiction (SANTA) project.

PubMed

Mendenhall, Tai J; Harper, Peter G; Henn, Lisa; Rudser, Kyle D; Schoeller, Bill P

2014-03-01

Students Against Nicotine and Tobacco Addiction is a community-based participatory research project that engages local medical and mental health providers in partnership with students, teachers, and administrators at the Minnesota-based Job Corps. This intervention contains multiple and synchronous elements designed to allay the stress that students attribute to smoking, including physical activities, nonphysical activities, purposeful modifications to the campus's environment and rules/policies, and on-site smoking cessation education and peer support. The intent of the present investigation was to evaluate (a) the types of stress most predictive of smoking behavior and/or nicotine dependence, (b) which activities students are participating in, and (c) which activities are most predictive of behavior change (or readiness to change). Quantitative data were collected through 5 campus-wide surveys. Response rates for each survey exceeded 85%. Stressors most commonly cited included struggles to find a job, financial problems, family conflict, lack of privacy or freedom, missing family or being homesick, dealing with Job Corps rules, and other-unspecified. The most popular activities in which students took part were physically active ones. However, activities most predictive of beneficent change were nonphysical. Approximately one third of respondents were nicotine dependent at baseline. Nearly half intended to quit within 1 month and 74% intended to quit within 6 months. Interventions perceived as most helpful toward reducing smoking were nonphysical in nature. Future efforts with this and comparable populations should engage youth in advancing such activities within a broader range of activity choices, alongside conventional education and support.

2-D Circulation Control Airfoil Benchmark Experiments Intended for CFD Code Validation

NASA Technical Reports Server (NTRS)

Englar, Robert J.; Jones, Gregory S.; Allan, Brian G.; Lin, Johb C.

2009-01-01

A current NASA Research Announcement (NRA) project being conducted by Georgia Tech Research Institute (GTRI) personnel and NASA collaborators includes the development of Circulation Control (CC) blown airfoils to improve subsonic aircraft high-lift and cruise performance. The emphasis of this program is the development of CC active flow control concepts for both high-lift augmentation, drag control, and cruise efficiency. A collaboration in this project includes work by NASA research engineers, whereas CFD validation and flow physics experimental research are part of NASA s systematic approach to developing design and optimization tools for CC applications to fixed-wing aircraft. The design space for CESTOL type aircraft is focusing on geometries that depend on advanced flow control technologies that include Circulation Control aerodynamics. The ability to consistently predict advanced aircraft performance requires improvements in design tools to include these advanced concepts. Validation of these tools will be based on experimental methods applied to complex flows that go beyond conventional aircraft modeling techniques. This paper focuses on recent/ongoing benchmark high-lift experiments and CFD efforts intended to provide 2-D CFD validation data sets related to NASA s Cruise Efficient Short Take Off and Landing (CESTOL) study. Both the experimental data and related CFD predictions are discussed.

Fan Noise Prediction: Status and Needs

NASA Technical Reports Server (NTRS)

Huff, Dennis L.

1997-01-01

The prediction of fan noise is an important part to the prediction of overall turbofan engine noise. Advances in computers and better understanding of the flow physics have allowed researchers to compute sound generation from first principles and rely less on empirical correlations. While progress has been made, there are still many aspects of the problem that need to be explored. This paper presents some recent advances in fan noise prediction and suggests areas that still need further development. Fan noise predictions that support the recommendations are taken from existing publications.

A data mining approach to predict in situ chlorinated ethene detoxification potential

NASA Astrophysics Data System (ADS)

Lee, J.; Im, J.; Kim, U.; Loeffler, F. E.

2015-12-01

Despite major advances in physicochemical remediation technologies, in situ biostimulation and bioaugmentation treatment aimed at stimulating Dehalococcoides mccartyi (Dhc) reductive dechlorination activity remains a cornerstone approach to remedy sites impacted with chlorinated ethenes. In practice, selecting the best remedial strategy is challenging due to uncertainties associated with the microbiology (e.g., presence and activity of Dhc) and geochemical factors influencing Dhc activity. Extensive groundwater datasets collected over decades of monitoring exist, but have not been systematically analyzed. In the present study, geochemical and microbial data sets collected from 35 wells at 5 contaminated sites were used to develop a predictive empirical model using a machine learning algorithm (i) to rank the relative importance of parameters that affect in situ reductive dechlorination potential, and (ii) to provide recommendations for selecting the optimal remediation strategy at a specific site. Classification and regression tree (CART) analysis was applied, and a representative classification tree model was developed that allowed short-term prediction of dechlorination potential. Indirect indicators for low dissolved oxygen (e.g., low NO3-and NO2-, high Fe2+ and CH4) were the most influential factors for predicting dechlorination potential, followed by total organic carbon content (TOC) and Dhc cell abundance. These findings indicate that machine learning-based data mining techniques applied to groundwater monitoring data can lead to the development of predictive groundwater remediation models. A major need for improving the predictive capabilities of the data mining approach is a curated, up-to-date and comprehensive collection of groundwater monitoring data.

Active Control Technology at NASA Langley Research Center

NASA Technical Reports Server (NTRS)

Antcliff, Richard R.; McGowan, Anna-Marie R.

2000-01-01

NASA Langley has a long history of attacking important technical opportunities from a broad base of supporting disciplines. The research and development at Langley in this subject area range from the test tube to the test flight. The information covered here will range from the development of innovative new materials, sensors and actuators, to the incorporation of smart sensors and actuators in practical devices, to the optimization of the location of these devices, to, finally, a wide variety of applications of these devices utilizing Langley's facilities and expertise. Advanced materials are being developed for sensors and actuators, as well as polymers for integrating smart devices into composite structures. Contributions reside in three key areas: computational materials; advanced piezoelectric materials; and integrated composite structures. The computational materials effort is focused on developing predictive tools for the efficient design of new materials with the appropriate combination of properties for next generation smart airframe systems. Research in the area of advanced piezoelectrics includes optimizing the efficiency, force output, use temperature, and energy transfer between the structure and device for both ceramic and polymeric materials. For structural health monitoring, advanced non-destructive techniques including fiber optics are being developed for detection of delaminations, cracks and environmental deterioration in aircraft structures. The computational materials effort is focused on developing predictive tools for the efficient design of new materials with the appropriate combination of properties for next generation smart airframe system. Innovative fabrication techniques processing structural composites with sensor and actuator integration are being developed.

Active optimal control strategies for increasing the efficiency of photovoltaic cells

NASA Astrophysics Data System (ADS)

Aljoaba, Sharif Zidan Ahmad

Energy consumption has increased drastically during the last century. Currently, the worldwide energy consumption is about 17.4 TW and is predicted to reach 25 TW by 2035. Solar energy has emerged as one of the potential renewable energy sources. Since its first physical recognition in 1887 by Adams and Day till nowadays, research in solar energy is continuously developing. This has lead to many achievements and milestones that introduced it as one of the most reliable and sustainable energy sources. Recently, the International Energy Agency declared that solar energy is predicted to be one of the major electricity production energy sources by 2035. Enhancing the efficiency and lifecycle of photovoltaic (PV) modules leads to significant cost reduction. Reducing the temperature of the PV module improves its efficiency and enhances its lifecycle. To better understand the PV module performance, it is important to study the interaction between the output power and the temperature. A model that is capable of predicting the PV module temperature and its effects on the output power considering the individual contribution of the solar spectrum wavelengths significantly advances the PV module edsigns toward higher efficiency. In this work, a thermoelectrical model is developed to predict the effects of the solar spectrum wavelengths on the PV module performance. The model is characterized and validated under real meteorological conditions where experimental temperature and output power of the PV module measurements are shown to agree with the predicted results. The model is used to validate the concept of active optical filtering. Since this model is wavelength-based, it is used to design an active optical filter for PV applications. Applying this filter to the PV module is expected to increase the output power of the module by filtering the spectrum wavelengths. The active filter performance is optimized, where different cutoff wavelengths are used to maximize the module output power. It is predicted that if the optimized active optical filter is applied to the PV module, the module efficiency is predicted to increase by about 1%. Different technologies are considered for physical implementation of the active optical filter.

The Effect of Non-Harmonic Active Twist Actuation on BVI Noise

NASA Technical Reports Server (NTRS)

Fogarty, David E.; Wilbur, Matthew L.; Sekula, Martin K.

2011-01-01

The results of a computational study examining the effects of non-harmonic active-twist control on blade-vortex interaction (BVI) noise for the Apache Active Twist Rotor are presented. Rotor aeroelastic behavior was modeled using the Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics code and the rotor noise was predicted using the acoustics code PSU-WOPWOP. The application of non-harmonic active-twist inputs to the main rotor blade system comprised three parameters: azimuthal location to start actuation, azimuthal duration of actuation, and magnitude of actuation. The acoustic analysis was conducted for a single low-speed flight condition of advance ratio mu=0.14 and shaft angle-of-attack, a(sub s)=+6deg. BVI noise levels were predicted on a flat plane of observers located 1.1 rotor diameters beneath the rotor. The results indicate significant reductions of up to 10dB in BVI noise using a starting azimuthal location for actuation of 90?, an azimuthal duration of actuation of 90deg, and an actuation magnitude of +1.5 ft-lb.

DOE Office of Scientific and Technical Information (OSTI.GOV)

J. Carmack; L. Braase; F. Goldner

The mission of the Advanced Fuels Campaign (AFC) is to perform Research, Development, and Demonstration (RD&D) activities for advanced fuel forms (including cladding) to enhance the performance and safety of the nation’s current and future reactors, enhance proliferation resistance of nuclear fuel, effectively utilize nuclear energy resources, and address the longer-term waste management challenges. This includes development of a state of the art Research and Development (R&D) infrastructure to support the use of a “goal oriented science based approach.” AFC uses a “goal oriented, science based approach” aimed at a fundamental understanding of fuel and cladding fabrication methods and performancemore » under irradiation, enabling the pursuit of multiple fuel forms for future fuel cycle options. This approach includes fundamental experiments, theory, and advanced modeling and simulation. One of the most challenging aspects of AFC is the management, integration, and coordination of major R&D activities across multiple organizations. AFC interfaces and collaborates with Fuel Cycle Technologies (FCT) campaigns, universities, industry, various DOE programs and laboratories, federal agencies (e.g., Nuclear Regulatory Commission [NRC]), and international organizations. Key challenges are the development of fuel technologies to enable major increases in fuel performance (safety, reliability, power and burnup) beyond current technologies, and development of characterization methods and predictive fuel performance models to enable more efficient development and licensing of advanced fuels. Challenged with the research and development of fuels for two different reactor technology platforms, AFC targeted transmutation fuel development and focused ceramic fuel development for Advanced LWR Fuels.« less

Propulsion Research at the Propulsion Research Center of the NASA Marshall Space Flight Center

NASA Technical Reports Server (NTRS)

Blevins, John; Rodgers, Stephen

2003-01-01

The Propulsion Research Center of the NASA Marshall Space Flight Center is engaged in research activities aimed at providing the bases for fundamental advancement of a range of space propulsion technologies. There are four broad research themes. Advanced chemical propulsion studies focus on the detailed chemistry and transport processes for high-pressure combustion, and on the understanding and control of combustion stability. New high-energy propellant research ranges from theoretical prediction of new propellant properties through experimental characterization propellant performance, material interactions, aging properties, and ignition behavior. Another research area involves advanced nuclear electric propulsion with new robust and lightweight materials and with designs for advanced fuels. Nuclear electric propulsion systems are characterized using simulated nuclear systems, where the non-nuclear power source has the form and power input of a nuclear reactor. This permits detailed testing of nuclear propulsion systems in a non-nuclear environment. In-space propulsion research is focused primarily on high power plasma thruster work. New methods for achieving higher thrust in these devices are being studied theoretically and experimentally. Solar thermal propulsion research is also underway for in-space applications. The fourth of these research areas is advanced energetics. Specific research here includes the containment of ion clouds for extended periods. This is aimed at proving the concept of antimatter trapping and storage for use ultimately in propulsion applications. Another activity in this involves research into lightweight magnetic technology for space propulsion applications.

Observational Constraints on Cloud Feedbacks: The Role of Active Satellite Sensors

NASA Astrophysics Data System (ADS)

Winker, David; Chepfer, Helene; Noel, Vincent; Cai, Xia

2017-11-01

Cloud profiling from active lidar and radar in the A-train satellite constellation has significantly advanced our understanding of clouds and their role in the climate system. Nevertheless, the response of clouds to a warming climate remains one of the largest uncertainties in predicting climate change and for the development of adaptions to change. Both observation of long-term changes and observational constraints on the processes responsible for those changes are necessary. We review recent progress in our understanding of the cloud feedback problem. Capabilities and advantages of active sensors for observing clouds are discussed, along with the importance of active sensors for deriving constraints on cloud feedbacks as an essential component of a global climate observing system.

Active Piezoelectric Structures for Tip Clearance Management Assessed

NASA Technical Reports Server (NTRS)

1995-01-01

Managing blade tip clearance in turbomachinery stages is critical to developing advanced subsonic propulsion systems. Active casing structures with embedded piezoelectric actuators appear to be a promising solution. They can control static and dynamic tip clearance, compensate for uneven deflections, and accomplish electromechanical coupling at the material level. In addition, they have a compact design. To assess the feasibility of this concept and assist the development of these novel structures, the NASA Lewis Research Center developed in-house computational capabilities for composite structures with piezoelectric actuators and sensors, and subsequently used them to simulate candidate active casing structures. The simulations indicated the potential of active casings to modify the blade tip clearance enough to improve stage efficiency. They also provided valuable design information, such as preliminary actuator configurations (number and location) and the corresponding voltage patterns required to compensate for uneven casing deformations. An active ovalization of a casing with four discrete piezoceramic actuators attached on the outer surface is shown. The center figure shows the predicted radial displacements along the hoop direction that are induced when electrostatic voltage is applied at the piezoceramic actuators. This work, which has demonstrated the capabilities of in-house computational models to analyze and design active casing structures, is expected to contribute toward the development of advanced subsonic engines.

Applied Meteorology Unit (AMU) Quarterly Report Fourth Quarter FY-04

NASA Technical Reports Server (NTRS)

Bauman, William; Wheeler, Mark; Lambert, Winifred; Case, Jonathan; Short, David

2004-01-01

This report summarizes the Applied Meteorology Unit (A MU) activities for the fourth quarter of Fiscal Year 2004 (July -Sept 2004). Tasks covered are: (1) Objective Lightning Probability Forecast: Phase I, (2) Severe Weather Forecast Decision Aid, (3) Hail Index, (4) Shuttle Ascent Camera Cloud Obstruction Forecast, (5) Advanced Regional Prediction System (ARPS) Optimization and Training Extension and (5) User Control Interface for ARPS Data Analysis System (ADAS) Data Ingest.

Less-structured time in children's daily lives predicts self-directed executive functioning.

PubMed

Barker, Jane E; Semenov, Andrei D; Michaelson, Laura; Provan, Lindsay S; Snyder, Hannah R; Munakata, Yuko

2014-01-01

Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6-7 year-old children's daily, annual, and typical schedules. We categorized children's activities as "structured" or "less-structured" based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up.

Less-structured time in children's daily lives predicts self-directed executive functioning

PubMed Central

Barker, Jane E.; Semenov, Andrei D.; Michaelson, Laura; Provan, Lindsay S.; Snyder, Hannah R.; Munakata, Yuko

2014-01-01

Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6–7 year-old children's daily, annual, and typical schedules. We categorized children's activities as “structured” or “less-structured” based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up. PMID:25071617

Is past academic productivity predictive of radiology resident academic productivity?

PubMed

Patterson, Stephanie K; Fitzgerald, James T; Boyse, Tedric D; Cohan, Richard H

2002-02-01

The authors performed this study to determine whether academic productivity in college and medical school is predictive of the number of publications produced during radiology residency. The authors reviewed the records of 73 radiology residents who completed their residency from 1990 to 2000. Academic productivity during college, medical school, and radiology residency, other postgraduate degrees, and past careers other than radiology were tabulated. The personal essay attached to the residency application was reviewed for any stated academic interest. Residents were classified as being either previously productive or previously unproductive. Publication rates during residency and immediately after residency were compared for the two groups. For the productive residents, a correlation analysis was used to examine the relationship between past frequency of publication and type of previous activity. Least-squares regression analysis was used to investigate the relationship between preresidency academic productivity, advanced degrees, stated interest in academics, and other careers and radiology residency publications. There was no statistically significant difference in the number of articles published by those residents who were active and those who were not active before residency (P = .21). Only authorship of papers as an undergraduate was weakly predictive of residency publication. These selected measures of academic productivity as an undergraduate and during medical school are not helpful for predicting publication during residency. There was no difference in publication potential between those residents who were academically productive in the past and those who were not.

Guiding Young Children's Digital Media Use: SES-Differences in Mediation Concerns and Competence.

PubMed

Nikken, Peter; Opree, Suzanna J

2018-01-01

Previous research about parents' mediation of their young children's (digital) media use has predominantly focused on the different types, determinants, and effectiveness of parental mediation strategies. Although research on parents' perceived mediation concerns and competences is scarce, it is known that, compared to mothers and high-educated parents, fathers and low-educated parents experience greater insecurity (i.e., higher concern and lower competence) when applying media mediation. Based on Bourdieu's theory of social capital it may be expected that-in addition to educational level-marital status and family income predict parents' perceived mediation concerns and competences: Family demographics may predict parents' media proficiency and adoption of new media technologies and these media ecological factors may, in turn, affect perceived concerns and competences. To test this assumption, survey data were collected among 1029 parents of children between the ages of 1 to 9 years. We found that parents' basic media proficiency was lower in low income, low educated, and single-parent families, whereas parents' advanced media proficiency was only lower in low educated and single-parent families. As expected, parents' ease of active co-use was positively associated with parents' basic proficiency, ease of restrictive mediation by basic and advanced proficiency, and ease of imposing technical restrictions by advanced media proficiency. Parents' perceived mediation concerns were, however, unrelated to parents' media proficiency. Also, as expected, low educated parents were less inclined to adopt new media technologies. Adoption of new media was negatively related to perceived mediation concerns, yet did not predict parents' perceived competence.

The ecology of patient and caregiver participation in consultations involving advanced cancer.

PubMed

Freytag, Jennifer; Street, Richard L; Xing, Guibo; Duberstein, Paul R; Fiscella, Kevin; Tancredi, Daniel J; Fenton, Joshua J; Kravitz, Richard L; Epstein, Ronald M

2018-06-01

To identify predictors of participation of patients with advanced cancer in clinical encounters with oncologists and to assess the impact of patient and caregiver participation on perceptions of physician support. This is a secondary data analysis from the Values and Options in Cancer Care study, a cluster randomized clinical trial of a patient-centered communication intervention. Patients and caregivers completed pre-visit and post-visit health and communication measures. Audio recorded patient-caregiver (when present)-physician encounters were coded for active patient/caregiver participation behaviors (eg, question asking, expressing concern) and for physicians' facilitative communication (eg, partnership-building, support). Mixed linear regression models were used to identify patient, physician, and situational factors predicting patient and patient plus caregiver communication behaviors and post-visit outcomes. Physician partnership building predicted greater expressions of concern and more assertive responses from patients and patient-caregiver pairs. Patients' perceptions of greater connectedness with their physician predicted fewer patient expressions of concern. Patient perceptions of physician respect for their autonomy were lower among patients accompanied by caregivers. Caregiver perceptions of physician respect for patient autonomy decreased with increasing patient age and varied by site. In advanced cancer care, patient and caregiver communication is affected by ecological factors within their consultations. Physicians can support greater patient participation in clinical encounters through facilitative communication such as partnership-building and supportive talk. The presence of a caregiver complicates this environment, but partnership building techniques may help promote patient and caregiver participation during these visits. Copyright © 2018 John Wiley & Sons, Ltd.

Viewing Marine Bacteria, Their Activity and Response to Environmental Drivers from Orbit

PubMed Central

Grimes, D. Jay; Ford, Tim E.; Colwell, Rita R.; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G.

2014-01-01

Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions. PMID:24477922

Viewing marine bacteria, their activity and response to environmental drivers from orbit: satellite remote sensing of bacteria.

PubMed

Grimes, D Jay; Ford, Tim E; Colwell, Rita R; Baker-Austin, Craig; Martinez-Urtaza, Jaime; Subramaniam, Ajit; Capone, Douglas G

2014-04-01

Satellite-based remote sensing of marine microorganisms has become a useful tool in predicting human health risks associated with these microscopic targets. Early applications were focused on harmful algal blooms, but more recently methods have been developed to interrogate the ocean for bacteria. As satellite-based sensors have become more sophisticated and our ability to interpret information derived from these sensors has advanced, we have progressed from merely making fascinating pictures from space to developing process models with predictive capability. Our understanding of the role of marine microorganisms in primary production and global elemental cycles has been vastly improved as has our ability to use the combination of remote sensing data and models to provide early warning systems for disease outbreaks. This manuscript will discuss current approaches to monitoring cyanobacteria and vibrios, their activity and response to environmental drivers, and will also suggest future directions.

Information giving and decision-making in patients with advanced cancer: a systematic review.

PubMed

Gaston, Christine M; Mitchell, Geoffrey

2005-11-01

Patients with advanced, non-curable cancer face difficult decisions on further treatment, where a small increase in survival time must be balanced against the toxicity of the treatment. If patients want to be involved in these decisions, in keeping with current notions of autonomy and empowerment, they also require to be adequately informed both on the treatments proposed and on their own disease status and prognosis. A systematic review was performed on decision-making and information provision in patients with advanced cancer. Studies of interventions to improve information giving and encourage participation in decision-making were reviewed, including both randomised controlled trials and uncontrolled studies. Almost all patients expressed a desire for full information, but only about two-thirds wished to participate actively in decision-making. Higher educational level, younger age and female sex were predictive of a desire to participate in decision-making. Active decision-making was more common in patients with certain cancers (e.g. breast) than others (e.g. prostate). A number of simple interventions including question prompt sheets, audio-taping of consultations and patient decision aids have been shown to facilitate such involvement.

25 Years of DECOVALEX - Research Advances and Lessons Learned from an International Model Comparison Initiative

NASA Astrophysics Data System (ADS)

Birkholzer, J. T.

2017-12-01

This presentation provides an overview of an international research and model comparison collaboration (DECOVALEX) for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. Prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel, and is also relevant for a range of other sub-surface engineering activities. DECOVALEX research activities have been supported by a large number of radioactive-waste-management organizations and regulatory authorities. Research teams from more than a dozen international partner organizations have participated in the comparative modeling evaluation of complex field and laboratory experiments in the UK, Switzerland, Japan, France and Sweden. Together, these tasks (1) have addressed a wide range of relevant issues related to engineered and natural system behavior in argillaceous, crystalline and other host rocks, (2) have yielded in-depth knowledge of coupled THM and THMC processes associated with nuclear waste repositories and wider geo-engineering applications, and (3) have advanced the capability, as well as demonstrated the suitability, of numerical simulation models for quantitative analysis.

The impact of real-time and predictive traffic information on travelers' behavior on the I-4 corridor. Final report.

DOT National Transportation Integrated Search

2003-07-01

Real time and predicted traffic information plays a key role in the successful implementation of advanced traveler information systems (ATIS) and advance traffic management systems (ATMS). Traffic information is essentially valuable to both transport...

Advances in Fatigue and Fracture Mechanics Analyses for Aircraft Structures

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

1999-01-01

This paper reviews some of the advances that have been made in stress analyses of cracked aircraft components, in the understanding of the fatigue and fatigue-crack growth process, and in the prediction of residual strength of complex aircraft structures with widespread fatigue damage. Finite-element analyses of cracked structures are now used to determine accurate stress-intensity factors for cracks at structural details. Observations of small-crack behavior at open and rivet-loaded holes and the development of small-crack theory has lead to the prediction of stress-life behavior for components with stress concentrations under aircraft spectrum loading. Fatigue-crack growth under simulated aircraft spectra can now be predicted with the crack-closure concept. Residual strength of cracked panels with severe out-of-plane deformations (buckling) in the presence of stiffeners and multiple-site damage can be predicted with advanced elastic-plastic finite-element analyses and the critical crack-tip-opening angle (CTOA) fracture criterion. These advances are helping to assure continued safety of aircraft structures.

Advances in Fatigue and Fracture Mechanics Analyses for Metallic Aircraft Structures

NASA Technical Reports Server (NTRS)

Newman, J. C., Jr.

2000-01-01

This paper reviews some of the advances that have been made in stress analyses of cracked aircraft components, in the understanding of the fatigue and fatigue-crack growth process, and in the prediction of residual strength of complex aircraft structures with widespread fatigue damage. Finite-element analyses of cracked metallic structures are now used to determine accurate stress-intensity factors for cracks at structural details. Observations of small-crack behavior at open and rivet-loaded holes and the development of small-crack theory has lead to the prediction of stress-life behavior for components with stress concentrations under aircraft spectrum loading. Fatigue-crack growth under simulated aircraft spectra can now be predicted with the crack-closure concept. Residual strength of cracked panels with severe out-of-plane deformations (buckling) in the presence of stiffeners and multiple-site damage can be predicted with advanced elastic-plastic finite-element analyses and the critical crack-tip-opening angle (CTOA) fracture criterion. These advances are helping to assure continued safety of aircraft structures.

Advances in In Vitro and In Silico Tools for Toxicokinetic Dose ...

EPA Pesticide Factsheets

Recent advances in vitro assays, in silico tools, and systems biology approaches provide opportunities for refined mechanistic understanding for chemical safety assessment that will ultimately lead to reduced reliance on animal-based methods. With the U.S. commercial chemical landscape encompassing thousands of chemicals with limited data, safety assessment strategies that reliably predict in vivo systemic exposures and subsequent in vivo effects efficiently are a priority. Quantitative in vitro-in vivo extrapolation (QIVIVE) is a methodology that facilitates the explicit and quantitative application of in vitro experimental data and in silico modeling to predict in vivo system behaviors and can be applied to predict chemical toxicokinetics, toxicodynamics and also population variability. Tiered strategies that incorporate sufficient information to reliably inform the relevant decision context will facilitate acceptance of these alternative data streams for safety assessments. This abstract does not necessarily reflect U.S. EPA policy. This talk will provide an update to an international audience on the state of science being conducted within the EPA’s Office of Research and Development to develop and refine approaches that estimate internal chemical concentrations following a given exposure, known as toxicokinetics. Toxicokinetic approaches hold great potential in their ability to link in vitro activities or toxicities identified during high-throughput screen

Advancing coastal ocean modelling, analysis, and prediction for the US Integrated Ocean Observing System

USGS Publications Warehouse

Wilkin, John L.; Rosenfeld, Leslie; Allen, Arthur; Baltes, Rebecca; Baptista, Antonio; He, Ruoying; Hogan, Patrick; Kurapov, Alexander; Mehra, Avichal; Quintrell, Josie; Schwab, David; Signell, Richard; Smith, Jane

2017-01-01

This paper outlines strategies that would advance coastal ocean modelling, analysis and prediction as a complement to the observing and data management activities of the coastal components of the US Integrated Ocean Observing System (IOOS®) and the Global Ocean Observing System (GOOS). The views presented are the consensus of a group of US-based researchers with a cross-section of coastal oceanography and ocean modelling expertise and community representation drawn from Regional and US Federal partners in IOOS. Priorities for research and development are suggested that would enhance the value of IOOS observations through model-based synthesis, deliver better model-based information products, and assist the design, evaluation, and operation of the observing system itself. The proposed priorities are: model coupling, data assimilation, nearshore processes, cyberinfrastructure and model skill assessment, modelling for observing system design, evaluation and operation, ensemble prediction, and fast predictors. Approaches are suggested to accomplish substantial progress in a 3–8-year timeframe. In addition, the group proposes steps to promote collaboration between research and operations groups in Regional Associations, US Federal Agencies, and the international ocean research community in general that would foster coordination on scientific and technical issues, and strengthen federal–academic partnerships benefiting IOOS stakeholders and end users.

Angiotensin converting enzyme 2 activity and human atrial fibrillation: increased plasma angiotensin converting enzyme 2 activity is associated with atrial fibrillation and more advanced left atrial structural remodelling.

PubMed

Walters, Tomos E; Kalman, Jonathan M; Patel, Sheila K; Mearns, Megan; Velkoska, Elena; Burrell, Louise M

2017-08-01

Angiotensin converting enzyme 2 (ACE2) is an integral membrane protein whose main action is to degrade angiotensin II. Plasma ACE2 activity is increased in various cardiovascular diseases. We aimed to determine the relationship between plasma ACE2 activity and human atrial fibrillation (AF), and in particular its relationship to left atrial (LA) structural remodelling. One hundred and three participants from a tertiary arrhythmia centre, including 58 with paroxysmal AF (PAF), 20 with persistent AF (PersAF), and 25 controls, underwent clinical evaluation, echocardiographic analysis, and measurement of plasma ACE2 activity. A subgroup of 20 participants underwent invasive LA electroanatomic mapping. Plasma ACE2 activity levels were increased in AF [control 13.3 (9.5-22.3) pmol/min/mL; PAF 16.9 (9.7-27.3) pmol/min/mL; PersAF 22.8 (13.7-33.4) pmol/min/mL, P = 0.006]. Elevated plasma ACE2 was associated with older age, male gender, hypertension and vascular disease, elevated left ventricular (LV) mass, impaired LV diastolic function and advanced atrial disease (P < 0.05 for all). Independent predictors of elevated plasma ACE2 activity were AF (P = 0.04) and vascular disease (P < 0.01). There was a significant relationship between elevated ACE2 activity and low mean LA bipolar voltage (adjusted R2 = 0.22, P = 0.03), a high proportion of complex fractionated electrograms (R2 = 0.32, P = 0.009) and a long LA activation time (R2 = 0.20, P = 0.04). Plasma ACE2 activity is elevated in human AF. Both AF and vascular disease predict elevated plasma ACE2 activity, and elevated plasma ACE2 is significantly associated with more advanced LA structural remodelling. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2016. For permissions please email: journals.permissions@oup.com.

Decoding a wide range of hand configurations from macaque motor, premotor, and parietal cortices.

PubMed

Schaffelhofer, Stefan; Agudelo-Toro, Andres; Scherberger, Hansjörg

2015-01-21

Despite recent advances in decoding cortical activity for motor control, the development of hand prosthetics remains a major challenge. To reduce the complexity of such applications, higher cortical areas that also represent motor plans rather than just the individual movements might be advantageous. We investigated the decoding of many grip types using spiking activity from the anterior intraparietal (AIP), ventral premotor (F5), and primary motor (M1) cortices. Two rhesus monkeys were trained to grasp 50 objects in a delayed task while hand kinematics and spiking activity from six implanted electrode arrays (total of 192 electrodes) were recorded. Offline, we determined 20 grip types from the kinematic data and decoded these hand configurations and the grasped objects with a simple Bayesian classifier. When decoding from AIP, F5, and M1 combined, the mean accuracy was 50% (using planning activity) and 62% (during motor execution) for predicting the 50 objects (chance level, 2%) and substantially larger when predicting the 20 grip types (planning, 74%; execution, 86%; chance level, 5%). When decoding from individual arrays, objects and grip types could be predicted well during movement planning from AIP (medial array) and F5 (lateral array), whereas M1 predictions were poor. In contrast, predictions during movement execution were best from M1, whereas F5 performed only slightly worse. These results demonstrate for the first time that a large number of grip types can be decoded from higher cortical areas during movement preparation and execution, which could be relevant for future neuroprosthetic devices that decode motor plans. Copyright © 2015 the authors 0270-6474/15/351068-14$15.00/0.

The development of an acute care case manager orientation.

PubMed

Strzelecki, S; Brobst, R

1997-01-01

The authors describe the development of an inpatient acute care case manager orientation in a community hospital. Benner's application of the Dreyfus model of skill acquisition provides the basis for the orientation program. The candidates for the case manager position were expert clinicians. Because of the role change it was projected that they would function as advanced beginners. It was also predicted that, as the case managers progressed within the role, the educational process would need to be adapted to facilitate progression of skills to the proficient level. Feedback from participants reinforced that the model supported the case manager in the role transition. In addition, the model provided a predictive framework for ongoing educational activities.

Epistemology, Ethics, and Progress in Precision Medicine.

PubMed

Hey, Spencer Phillips; Barsanti-Innes, Brianna

2016-01-01

The emerging paradigm of precision medicine strives to leverage the tools of molecular biology to prospectively tailor treatments to the individual patient. Fundamental to the success of this movement is the discovery and validation of "predictive biomarkers," which are properties of a patient's biological specimens that can be assayed in advance of therapy to inform the treatment decision. Unfortunately, research into biomarkers and diagnostics for precision medicine has fallen well short of expectations. In this essay, we examine the portfolio of research activities into the excision repair cross complement group 1 (ERCC1) gene as a predictive biomarker for precision lung cancer therapy as a case study in elucidating the epistemological and ethical obstacles to developing new precision medicines.

Discovering Anti-platelet Drug Combinations with an Integrated Model of Activator-Inhibitor Relationships, Activator-Activator Synergies and Inhibitor-Inhibitor Synergies

PubMed Central

Lombardi, Federica; Golla, Kalyan; Fitzpatrick, Darren J.; Casey, Fergal P.; Moran, Niamh; Shields, Denis C.

2015-01-01

Identifying effective therapeutic drug combinations that modulate complex signaling pathways in platelets is central to the advancement of effective anti-thrombotic therapies. However, there is no systems model of the platelet that predicts responses to different inhibitor combinations. We developed an approach which goes beyond current inhibitor-inhibitor combination screening to efficiently consider other signaling aspects that may give insights into the behaviour of the platelet as a system. We investigated combinations of platelet inhibitors and activators. We evaluated three distinct strands of information, namely: activator-inhibitor combination screens (testing a panel of inhibitors against a panel of activators); inhibitor-inhibitor synergy screens; and activator-activator synergy screens. We demonstrated how these analyses may be efficiently performed, both experimentally and computationally, to identify particular combinations of most interest. Robust tests of activator-activator synergy and of inhibitor-inhibitor synergy required combinations to show significant excesses over the double doses of each component. Modeling identified multiple effects of an inhibitor of the P2Y12 ADP receptor, and complementarity between inhibitor-inhibitor synergy effects and activator-inhibitor combination effects. This approach accelerates the mapping of combination effects of compounds to develop combinations that may be therapeutically beneficial. We integrated the three information sources into a unified model that predicted the benefits of a triple drug combination targeting ADP, thromboxane and thrombin signaling. PMID:25875950

Joint Center for Satellite Data Assimilation Overview and Research Activities

NASA Astrophysics Data System (ADS)

Auligne, T.

2017-12-01

In 2001 NOAA/NESDIS, NOAA/NWS, NOAA/OAR, and NASA, subsequently joined by the US Navy and Air Force, came together to form the Joint Center for Satellite Data Assimilation (JCSDA) for the common purpose of accelerating the use of satellite data in environmental numerical prediction modeling by developing, using, and anticipating advances in numerical modeling, satellite-based remote sensing, and data assimilation methods. The primary focus was to bring these advances together to improve operational numerical model-based forecasting, under the premise that these partners have common technical and logistical challenges assimilating satellite observations into their modeling enterprises that could be better addressed through cooperative action and/or common solutions. Over the last 15 years, the JCSDA has made and continues to make major contributions to operational assimilation of satellite data. The JCSDA is a multi-agency U.S. government-owned-and-operated organization that was conceived as a venue for the several agencies NOAA, NASA, USAF and USN to collaborate on advancing the development and operational use of satellite observations into numerical model-based environmental analysis and forecasting. The primary mission of the JCSDA is to "accelerate and improve the quantitative use of research and operational satellite data in weather, ocean, climate and environmental analysis and prediction systems." This mission is fulfilled through directed research targeting the following key science objectives: Improved radiative transfer modeling; new instrument assimilation; assimilation of humidity, clouds, and precipitation observations; assimilation of land surface observations; assimilation of ocean surface observations; atmospheric composition; and chemistry and aerosols. The goal of this presentation is to briefly introduce the JCSDA's mission and vision, and to describe recent research activities across various JCSDA partners.

Effectiveness of link prediction for face-to-face behavioral networks.

PubMed

Tsugawa, Sho; Ohsaki, Hiroyuki

2013-01-01

Research on link prediction for social networks has been actively pursued. In link prediction for a given social network obtained from time-windowed observation, new link formation in the network is predicted from the topology of the obtained network. In contrast, recent advances in sensing technology have made it possible to obtain face-to-face behavioral networks, which are social networks representing face-to-face interactions among people. However, the effectiveness of link prediction techniques for face-to-face behavioral networks has not yet been explored in depth. To clarify this point, here we investigate the accuracy of conventional link prediction techniques for networks obtained from the history of face-to-face interactions among participants at an academic conference. Our findings were (1) that conventional link prediction techniques predict new link formation with a precision of 0.30-0.45 and a recall of 0.10-0.20, (2) that prolonged observation of social networks often degrades the prediction accuracy, (3) that the proposed decaying weight method leads to higher prediction accuracy than can be achieved by observing all records of communication and simply using them unmodified, and (4) that the prediction accuracy for face-to-face behavioral networks is relatively high compared to that for non-social networks, but not as high as for other types of social networks.

Predicting Career Advancement with Structural Equation Modelling

ERIC Educational Resources Information Center

Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

2012-01-01

Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

Recent advances in understanding Antarctic subglacial lakes and hydrology.

PubMed

Siegert, Martin J; Ross, Neil; Le Brocq, Anne M

2016-01-28

It is now well documented that over 400 subglacial lakes exist across the bed of the Antarctic Ice Sheet. They comprise a variety of sizes and volumes (from the approx. 250 km long Lake Vostok to bodies of water less than 1 km in length), relate to a number of discrete topographic settings (from those contained within valleys to lakes that reside in broad flat terrain) and exhibit a range of dynamic behaviours (from 'active' lakes that periodically outburst some or all of their water to those isolated hydrologically for millions of years). Here we critique recent advances in our understanding of subglacial lakes, in particular since the last inventory in 2012. We show that within 3 years our knowledge of the hydrological processes at the ice-sheet base has advanced considerably. We describe evidence for further 'active' subglacial lakes, based on satellite observation of ice-surface changes, and discuss why detection of many 'active' lakes is not resolved in traditional radio-echo sounding methods. We go on to review evidence for large-scale subglacial water flow in Antarctica, including the discovery of ancient channels developed by former hydrological processes. We end by predicting areas where future discoveries may be possible, including the detection, measurement and significance of groundwater (i.e. water held beneath the ice-bed interface). © 2015 The Authors.

Prospective study of the evolution of blood lymphoid immune parameters during dacarbazine chemotherapy in metastatic and locally advanced melanoma patients.

PubMed

Mignot, Grégoire; Hervieu, Alice; Vabres, Pierre; Dalac, Sophie; Jeudy, Geraldine; Bel, Blandine; Apetoh, Lionel; Ghiringhelli, François

2014-01-01

The importance of immune responses in the control of melanoma growth is well known. However, the implication of these antitumor immune responses in the efficacy of dacarbazine, a cytotoxic drug classically used in the treatment of melanoma, remains poorly understood in humans. In this prospective observational study, we performed an immunomonitoring of eleven metastatic or locally advanced patients treated with dacarbazine as a first line of treatment. We assessed by flow cytometry lymphoid populations and their activation state; we also isolated NK cells to perform in vitro cytotoxicity tests. We found that chemotherapy induces lymphopenia and that a significantly higher numbers of naïve CD4+ T cells and lower proportion of Treg before chemotherapy are associated with disease control after dacarbazine treatment. Interestingly, NK cell cytotoxicity against dacarbazine-pretreated melanoma cells is only observed in NK cells from patients who achieved disease control. Together, our data pinpoint that some immune factors could help to predict the response of melanoma patients to dacarbazine. Future larger scale studies are warranted to test their validity as prediction markers.

Machine learning for epigenetics and future medical applications

PubMed Central

Holder, Lawrence B.; Haque, M. Muksitul; Skinner, Michael K.

2017-01-01

ABSTRACT Understanding epigenetic processes holds immense promise for medical applications. Advances in Machine Learning (ML) are critical to realize this promise. Previous studies used epigenetic data sets associated with the germline transmission of epigenetic transgenerational inheritance of disease and novel ML approaches to predict genome-wide locations of critical epimutations. A combination of Active Learning (ACL) and Imbalanced Class Learning (ICL) was used to address past problems with ML to develop a more efficient feature selection process and address the imbalance problem in all genomic data sets. The power of this novel ML approach and our ability to predict epigenetic phenomena and associated disease is suggested. The current approach requires extensive computation of features over the genome. A promising new approach is to introduce Deep Learning (DL) for the generation and simultaneous computation of novel genomic features tuned to the classification task. This approach can be used with any genomic or biological data set applied to medicine. The application of molecular epigenetic data in advanced machine learning analysis to medicine is the focus of this review. PMID:28524769

Variability, trends, and predictability of seasonal sea ice retreat and advance in the Chukchi Sea

NASA Astrophysics Data System (ADS)

Serreze, Mark C.; Crawford, Alex D.; Stroeve, Julienne C.; Barrett, Andrew P.; Woodgate, Rebecca A.

2016-10-01

As assessed over the period 1979-2014, the date that sea ice retreats to the shelf break (150 m contour) of the Chukchi Sea has a linear trend of -0.7 days per year. The date of seasonal ice advance back to the shelf break has a steeper trend of about +1.5 days per year, together yielding an increase in the open water period of 80 days. Based on detrended time series, we ask how interannual variability in advance and retreat dates relate to various forcing parameters including radiation fluxes, temperature and wind (from numerical reanalyses), and the oceanic heat inflow through the Bering Strait (from in situ moorings). Of all variables considered, the retreat date is most strongly correlated (r ˜ 0.8) with the April through June Bering Strait heat inflow. After testing a suite of statistical linear models using several potential predictors, the best model for predicting the date of retreat includes only the April through June Bering Strait heat inflow, which explains 68% of retreat date variance. The best model predicting the ice advance date includes the July through September inflow and the date of retreat, explaining 67% of advance date variance. We address these relationships by discussing heat balances within the Chukchi Sea, and the hypothesis of oceanic heat transport triggering ocean heat uptake and ice-albedo feedback. Developing an operational prediction scheme for seasonal retreat and advance would require timely acquisition of Bering Strait heat inflow data. Predictability will likely always be limited by the chaotic nature of atmospheric circulation patterns.

The costs and benefits of temporal predictability: impaired inhibition of prepotent responses accompanies increased activation of task-relevant responses.

PubMed

Korolczuk, Inga; Burle, Boris; Coull, Jennifer T

2018-06-20

While the benefit of temporal predictability on sensorimotor processing is well established, it is still unknown whether this is due to efficient execution of an appropriate response and/or inhibition of an inappropriate one. To answer this question, we examined the effects of temporal predictability in tasks that required selective (Simon task) or global (Stop-signal task) inhibitory control of prepotent responses. We manipulated temporal expectation by presenting cues that either predicted (temporal cues) or not (neutral cues) when the target would appear. In the Simon task, performance was better when target location (left/right) was compatible with the hand of response and performance was improved further still if targets were temporally cued. However, Conditional Accuracy Functions revealed that temporal predictability selectively increased the number of fast, impulsive errors. Temporal cueing had no effect on selective response inhibition, as measured by the dynamics of the interference effect (delta plots) in the Simon task. By contrast, in the Stop-signal task, Stop-signal reaction time, a covert measure of a more global form of response inhibition, was significantly longer in temporally predictive trials. Therefore, when the time of target onset could be predicted in advance, it was harder to stop the impulse to respond to the target. Collectively, our results indicate that temporal cueing compounded the interfering effects of a prepotent response on task performance. We suggest that although temporal predictability enhances activation of task-relevant responses, it impairs inhibition of prepotent responses. Copyright © 2018 Elsevier B.V. All rights reserved.

Dynamic-compliance and viscosity of PET and PEN

NASA Astrophysics Data System (ADS)

Weick, Brian L.

2016-05-01

Complex dynamic-compliance and in-phase dynamic-viscosity data are presented and analyzed for PET and PEN advanced polyester substrates used for magnetic tapes. Frequency-temperature superposition is used to predict long-term behavior. Temperature and frequency ranges for the primary glass transition and secondary transitions are discussed and compared for PET and PEN. Shift factors from frequency-temperature superposition are used to determine activation energies for the transitions, and WLF parameters are determined for the polyester substrates.

Advanced planning activity. [for interplanetary flight and space exploration

NASA Technical Reports Server (NTRS)

1974-01-01

Selected mission concepts for interplanetary exploration through 1985 were examined, including: (1) Jupiter orbiter performance characteristics; (2) solar electric propulsion missions to Mercury, Venus, Neptune, and Uranus; (3) space shuttle planetary missions; (4) Pioneer entry probes to Saturn and Uranus; (5) rendezvous with Comet Kohoutek and Comet Encke; (6) space tug capabilities; and (7) a Pioneer mission to Mars in 1979. Mission options, limitations, and performance predictions are assessed, along with probable configurational, boost, and propulsion requirements.

A Catalytic, Brønsted Base Strategy for Intermolecular Allylic C—H Amination

PubMed Central

Reed, Sean A.; Mazzotti, Anthony R.; White, M. Christina

2009-01-01

A Brønsted base activation mode for oxidative, Pd(II)/sulfoxide catalyzed, intermolecular C—H allylic amination is reported. N,N-diisopropylethylamine was found to promote amination of unactivated terminal olefins, forming the corresponding linear allylic amine products with high levels of stereo-, regio-, and chemoselectivity. The predictable and high selectivity of this C—H oxidation method enables late-stage incorporation of nitrogen into advanced synthetic intermediates and natural products. PMID:19645492

Dynamic-compliance and viscosity of PET and PEN

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weick, Brian L.

Complex dynamic-compliance and in-phase dynamic-viscosity data are presented and analyzed for PET and PEN advanced polyester substrates used for magnetic tapes. Frequency-temperature superposition is used to predict long-term behavior. Temperature and frequency ranges for the primary glass transition and secondary transitions are discussed and compared for PET and PEN. Shift factors from frequency-temperature superposition are used to determine activation energies for the transitions, and WLF parameters are determined for the polyester substrates.

The development and validation of the AMPREDICT model for predicting mobility outcome after dysvascular lower extremity amputation.

PubMed

Czerniecki, Joseph M; Turner, Aaron P; Williams, Rhonda M; Thompson, Mary Lou; Landry, Greg; Hakimi, Kevin; Speckman, Rebecca; Norvell, Daniel C

2017-01-01

The objective of this study was the development of AMPREDICT-Mobility, a tool to predict the probability of independence in either basic or advanced (iBASIC or iADVANCED) mobility 1 year after dysvascular major lower extremity amputation. Two prospective cohort studies during consecutive 4-year periods (2005-2009 and 2010-2014) were conducted at seven medical centers. Multiple demographic and biopsychosocial predictors were collected in the periamputation period among individuals undergoing their first major amputation because of complications of peripheral arterial disease or diabetes. The primary outcomes were iBASIC and iADVANCED mobility, as measured by the Locomotor Capabilities Index. Combined data from both studies were used for model development and internal validation. Backwards stepwise logistic regression was used to develop the final prediction models. The discrimination and calibration of each model were assessed. Internal validity of each model was assessed with bootstrap sampling. Twelve-month follow-up was reached by 157 of 200 (79%) participants. Among these, 54 (34%) did not achieve iBASIC mobility, 103 (66%) achieved at least iBASIC mobility, and 51 (32%) also achieved iADVANCED mobility. Predictive factors associated with reduced odds of achieving iBASIC mobility were increasing age, chronic obstructive pulmonary disease, dialysis, diabetes, prior history of treatment for depression or anxiety, and very poor to fair self-rated health. Those who were white, were married, and had at least a high-school degree had a higher probability of achieving iBASIC mobility. The odds of achieving iBASIC mobility increased with increasing body mass index up to 30 kg/m 2 and decreased with increasing body mass index thereafter. The prediction model of iADVANCED mobility included the same predictors with the exception of diabetes, chronic obstructive pulmonary disease, and education level. Both models showed strong discrimination with C statistics of 0.85 and 0.82, respectively. The mean difference in predicted probabilities for those who did and did not achieve iBASIC and iADVANCED mobility was 33% and 29%, respectively. Tests for calibration and observed vs predicted plots suggested good fit for both models; however, the precision of the estimates of the predicted probabilities was modest. Internal validation through bootstrapping demonstrated some overoptimism of the original model development, with the optimism-adjusted C statistic for iBASIC and iADVANCED mobility being 0.74 and 0.71, respectively, and the discrimination slope 19% and 16%, respectively. AMPREDICT-Mobility is a user-friendly prediction tool that can inform the patient undergoing a dysvascular amputation and the patient's provider about the probability of independence in either basic or advanced mobility at each major lower extremity amputation level. Copyright © 2016 Society for Vascular Surgery. All rights reserved.

DNA Methyltransferase Activity Assays: Advances and Challenges

PubMed Central

Poh, Wan Jun; Wee, Cayden Pang Pee; Gao, Zhiqiang

2016-01-01

DNA methyltransferases (MTases), a family of enzymes that catalyse the methylation of DNA, have a profound effect on gene regulation. A large body of evidence has indicated that DNA MTase is potentially a predictive biomarker closely associated with genetic disorders and genetic diseases like cancer. Given the attention bestowed onto DNA MTases in molecular biology and medicine, highly sensitive detection of DNA MTase activity is essential in determining gene regulation, epigenetic modification, clinical diagnosis and therapeutics. Conventional techniques such as isotope labelling are effective, but they often require laborious sample preparation, isotope labelling, sophisticated equipment and large amounts of DNA, rendering them unsuitable for uses at point-of-care. Simple, portable, highly sensitive and low-cost assays are urgently needed for DNA MTase activity screening. In most recent technological advances, many alternative DNA MTase activity assays such as fluorescent, electrochemical, colorimetric and chemiluminescent assays have been proposed. In addition, many of them are coupled with nanomaterials and/or enzymes to significantly enhance their sensitivity. Herein we review the progress in the development of DNA MTase activity assays with an emphasis on assay mechanism and performance with some discussion on challenges and perspectives. It is hoped that this article will provide a broad coverage of DNA MTase activity assays and their latest developments and open new perspectives toward the development of DNA MTase activity assays with much improved performance for uses in molecular biology and clinical practice. PMID:26909112

Do plasma concentrations of apelin predict prognosis in patients with advanced heart failure?

PubMed

Dalzell, Jonathan R; Jackson, Colette E; Chong, Kwok S; McDonagh, Theresa A; Gardner, Roy S

2014-01-01

Apelin is an endogenous vasodilator and inotrope, plasma concentrations of which are reduced in advanced heart failure (HF). We determined the prognostic significance of plasma concentrations of apelin in advanced HF. Plasma concentrations of apelin were measured in 182 patients with advanced HF secondary to left ventricular systolic dysfunction. The predictive value of apelin for the primary end point of all-cause mortality was assessed over a median follow-up period of 544 (IQR: 196-923) days. In total, 30 patients (17%) reached the primary end point. Of those patients with a plasma apelin concentration above the median, 14 (16%) reached the primary end point compared with 16 (17%) of those with plasma apelin levels below the median (p = NS). NT-proBNP was the most powerful prognostic marker in this population (log rank statistic: 10.37; p = 0.001). Plasma apelin concentrations do not predict medium to long-term prognosis in patients with advanced HF secondary to left ventricular systolic dysfunction.

Advanced Earth-to-orbit propulsion technology program overview: Impact of civil space technology initiative

NASA Technical Reports Server (NTRS)

Stephenson, Frank W., Jr.

1988-01-01

The NASA Earth-to-Orbit (ETO) Propulsion Technology Program is dedicated to advancing rocket engine technologies for the development of fully reusable engine systems that will enable space transportation systems to achieve low cost, routine access to space. The program addresses technology advancements in the areas of engine life extension/prediction, performance enhancements, reduced ground operations costs, and in-flight fault tolerant engine operations. The primary objective is to acquire increased knowledge and understanding of rocket engine chemical and physical processes in order to evolve more realistic analytical simulations of engine internal environments, to derive more accurate predictions of steady and unsteady loads, and using improved structural analyses, to more accurately predict component life and performance, and finally to identify and verify more durable advanced design concepts. In addition, efforts were focused on engine diagnostic needs and advances that would allow integrated health monitoring systems to be developed for enhanced maintainability, automated servicing, inspection, and checkout, and ultimately, in-flight fault tolerant engine operations.

Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics

PubMed Central

Scott, Gregory; Fagerholm, Erik D.; Mutoh, Hiroki; Leech, Robert; Sharp, David J.; Shew, Woodrow L.

2014-01-01

Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain. PMID:25505314

Enzymology under global change: organic nitrogen turnover in alpine and sub-Arctic soils.

PubMed

Weedon, James T; Aerts, Rien; Kowalchuk, George A; van Bodegom, Peter M

2011-01-01

Understanding global change impacts on the globally important carbon storage in alpine, Arctic and sub-Arctic soils requires knowledge of the mechanisms underlying the balance between plant primary productivity and decomposition. Given that nitrogen availability limits both processes, understanding the response of the soil nitrogen cycle to shifts in temperature and other global change factors is crucial for predicting the fate of cold biome carbon stores. Measurements of soil enzyme activities at different positions of the nitrogen cycling network are an important tool for this purpose. We review a selection of studies that provide data on potential enzyme activities across natural, seasonal and experimental gradients in cold biomes. Responses of enzyme activities to increased nitrogen availability and temperature are diverse and seasonal dynamics are often larger than differences due to experimental treatments, suggesting that enzyme expression is regulated by a combination of interacting factors reflecting both nutrient supply and demand. The extrapolation from potential enzyme activities to prediction of elemental nitrogen fluxes under field conditions remains challenging. Progress in molecular '-omics' approaches may eventually facilitate deeper understanding of the links between soil microbial community structure and biogeochemical fluxes. In the meantime, accounting for effects of the soil spatial structure and in situ variations in pH and temperature, better mapping of the network of enzymatic processes and the identification of rate-limiting steps under different conditions should advance our ability to predict nitrogen fluxes.

Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data.

PubMed

Lee, Kyung Sang; Lee, Hyewon; Myung, Woojae; Song, Gil-Young; Lee, Kihwang; Kim, Ho; Carroll, Bernard J; Kim, Doh Kwan

2018-04-01

Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events.

Recent advances in hypersonic technology

NASA Technical Reports Server (NTRS)

Dwoyer, Douglas L.

1990-01-01

This paper will focus on recent advances in hypersonic aerodynamic prediction techniques. Current capabilities of existing numerical methods for predicting high Mach number flows will be discussed and shortcomings will be identified. Physical models available for inclusion into modern codes for predicting the effects of transition and turbulence will also be outlined and their limitations identified. Chemical reaction models appropriate to high-speed flows will be addressed, and the impact of their inclusion in computational fluid dynamics codes will be discussed. Finally, the problem of validating predictive techniques for high Mach number flows will be addressed.

An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment.

PubMed

Huang, Chien-Feng; Li, Hsu-Chih

2017-01-01

The advancement of information technology in financial applications nowadays have led to fast market-driven events that prompt flash decision-making and actions issued by computer algorithms. As a result, today's markets experience intense activity in the highly dynamic environment where trading systems respond to others at a much faster pace than before. This new breed of technology involves the implementation of high-speed trading strategies which generate significant portion of activity in the financial markets and present researchers with a wealth of information not available in traditional low-speed trading environments. In this study, we aim at developing feasible computational intelligence methodologies, particularly genetic algorithms (GA), to shed light on high-speed trading research using price data of stocks on the microscopic level. Our empirical results show that the proposed GA-based system is able to improve the accuracy of the prediction significantly for price movement, and we expect this GA-based methodology to advance the current state of research for high-speed trading and other relevant financial applications.

Research Area 3 - Mathematical Sciences: Multiscale Modeling of the Mechanics of Advanced Energetic Materials Relevant to Detonation Prediction

DTIC Science & Technology

2015-08-24

new energetic materials with enhanced energy release rates and reduced sensitivity to unintentional detonation . The following results have been...Mechanics of Advanced Energetic Materials Relevant to Detonation Prediction The views, opinions and/or findings contained in this report are those of the...modeling, molecular simulations, detonation prediction REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 10. SPONSOR/MONITOR’S

Evaluation of a fecal immunochemistry test prior to colonoscopy for outpatients with various indications.

PubMed

Szilagyi, Andrew; Xue, Xiaoqing

2017-01-01

Stool tests can predict advanced neoplasms prior to colonoscopy. Results of immunochemical stool tests to predict findings at colonoscopy for various indications are less often reported. We compared pre-colonoscopy stool tests with findings in patients undergoing colonoscopy for different indications. Charts of patients undergoing elective or semi-urgent colonoscopy were reviewed. Comparison of adenoma detection rates and pathological findings was made between prescreened and non-prescreened, and between stool-positive and stool-negative cases. Demographics, quality of colonoscopy, and pathological findings were recorded. Odds ratios (ORs) and 95% confidence intervals (CIs) were assessed. Statistical significance was accepted at p ≤0.05. Charts of 325 patients were reviewed. Among them, stool tests were done on 144 patients: 114 were negative and 30 were positive. Findings were similar in the pretest and non-pretest groups. Detection of advanced adenomas per patient was higher in the stool-positive group compared to the stool-negative group (23.4% vs 3.5%, p =0.0016, OR =7.6 [95% CI: 2-29.3]). Five advanced adenomas (without high-grade dysplasia or adenocarcinoma) and several cases of multiple adenomas were missed in the negative group. Sensitivity and specificity for advanced polyps was 63.6% and 82.7%, respectively. The negative predictive value was 96.5%. Male gender was independently predictive of any adenoma. The stool immunochemical test best predicted advanced neoplasms and had a high negative predictive value in this small cohort. Whether this test can be applied to determine the need for colonoscopy in groups other than average risk would require more studies.

A new model for force generation by skeletal muscle, incorporating work-dependent deactivation

PubMed Central

Williams, Thelma L.

2010-01-01

A model is developed to predict the force generated by active skeletal muscle when subjected to imposed patterns of lengthening and shortening, such as those that occur during normal movements. The model is based on data from isolated lamprey muscle and can predict the forces developed during swimming. The model consists of a set of ordinary differential equations, which are solved numerically. The model's first part is a simplified description of the kinetics of Ca2+ release from sarcoplasmic reticulum and binding to muscle protein filaments, in response to neural activation. The second part is based on A. V. Hill's mechanical model of muscle, consisting of elastic and contractile elements in series, the latter obeying known physiological properties. The parameters of the model are determined by fitting the appropriate mathematical solutions to data recorded from isolated lamprey muscle activated under conditions of constant length or rate of change of length. The model is then used to predict the forces developed under conditions of applied sinusoidal length changes, and the results compared with corresponding data. The most significant advance of this model is the incorporation of work-dependent deactivation, whereby a muscle that has been shortening under load generates less force after the shortening ceases than otherwise expected. In addition, the stiffness in this model is not constant but increases with increasing activation. The model yields a closer prediction to data than has been obtained before, and can thus prove an important component of investigations of the neural—mechanical—environmental interactions that occur during natural movements. PMID:20118315

Training Signaling Pathway Maps to Biochemical Data with Constrained Fuzzy Logic: Quantitative Analysis of Liver Cell Responses to Inflammatory Stimuli

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Clarke, David C.; Sorger, Peter K.; Lauffenburger, Douglas A.

2011-01-01

Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone. PMID:21408212

Strategic need for a multi-purpose thermal hydraulic loop for support of advanced reactor technologies

DOE Office of Scientific and Technical Information (OSTI.GOV)

O'Brien, James E.; Sabharwall, Piyush; Yoon, Su -Jong

2014-09-01

This report presents a conceptual design for a new high-temperature multi fluid, multi loop test facility for the INL to support thermal hydraulic, materials, and thermal energy storage research for nuclear and nuclear-hybrid applications. In its initial configuration, the facility will include a high-temperature helium loop, a liquid salt loop, and a hot water/steam loop. The three loops will be thermally coupled through an intermediate heat exchanger (IHX) and a secondary heat exchanger (SHX). Research topics to be addressed with this facility include the characterization and performance evaluation of candidate compact heat exchangers such as printed circuit heat exchangers (PCHEs)more » at prototypical operating conditions, flow and heat transfer issues related to core thermal hydraulics in advanced helium-cooled and salt-cooled reactors, and evaluation of corrosion behavior of new cladding materials and accident-tolerant fuels for LWRs at prototypical conditions. Based on its relevance to advanced reactor systems, the new facility has been named the Advanced Reactor Technology Integral System Test (ARTIST) facility. Research performed in this facility will advance the state of the art and technology readiness level of high temperature intermediate heat exchangers (IHXs) for nuclear applications while establishing the INL as a center of excellence for the development and certification of this technology. The thermal energy storage capability will support research and demonstration activities related to process heat delivery for a variety of hybrid energy systems and grid stabilization strategies. Experimental results obtained from this research will assist in development of reliable predictive models for thermal hydraulic design and safety codes over the range of expected advanced reactor operating conditions. Proposed/existing IHX heat transfer and friction correlations and criteria will be assessed with information on materials compatibility and instrumentation needs. The experimental database will guide development of appropriate predictive methods and be available for code verification and validation (V&V) related to these systems.« less

Clinical application of a systems model of apoptosis execution for the prediction of colorectal cancer therapy responses and personalisation of therapy.

PubMed

Hector, Suzanne; Rehm, Markus; Schmid, Jasmin; Kehoe, Joan; McCawley, Niamh; Dicker, Patrick; Murray, Frank; McNamara, Deborah; Kay, Elaine W; Concannon, Caoimhin G; Huber, Heinrich J; Prehn, Jochen H M

2012-05-01

Key to the clinical management of colorectal cancer is identifying tools which aid in assessing patient prognosis and determining more effective and personalised treatment strategies. We evaluated whether an experimental systems biology strategy which analyses the susceptibility of cancer cells to undergo caspase activation can be exploited to predict patient responses to 5-fluorouracil-based chemotherapy and to case-specifically identify potential alternative targeted treatments to reactivate apoptosis. We quantified five essential apoptosis-regulating proteins (Pro-Caspases 3 and 9, APAF-1, SMAC and XIAP) in samples of Stage II (n = 13) and III (n=17) tumour and normal colonic (n = 8) tissue using absolute quantitative immunoblotting and employed systems simulations of apoptosis signalling to predict the susceptibility of tumour cells to execute apoptosis. Additional systems analyses assessed the efficacy of novel apoptosis-inducing therapeutics such as XIAP antagonists, proteasome inhibitors and Pro-Caspase-3-activating compounds in restoring apoptosis execution in apoptosis-incompetent tumours. Comparisons of caspase activity profiles demonstrated that the likelihood of colorectal tumours to undergo apoptosis decreases with advancing disease stage. Systems-level analysis correctly predicted positive or negative outcome in 85% (p=0.004) of colorectal cancer patients receiving 5-fluorouracil based chemotherapy and significantly outperformed common uni- and multi-variate statistical approaches. Modelling of individual patient responses to novel apoptosis-inducing therapeutics revealed markedly different inter-individual responses. Our study represents the first proof-of-concept example demonstrating the significant clinical potential of systems biology-based approaches for predicting patient outcome and responsiveness to novel targeted treatment paradigms.

The Hydrologic Ensemble Prediction Experiment (HEPEX)

NASA Astrophysics Data System (ADS)

Wood, Andy; Wetterhall, Fredrik; Ramos, Maria-Helena

2015-04-01

The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF), and co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). The HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support. HEPEX pursues this goal through research efforts and practical implementations involving six core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. HEPEX has grown through meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. In the last decade, HEPEX has organized over a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Through these interactions and an active online blog (www.hepex.org), HEPEX has built a strong and active community of nearly 400 researchers & practitioners around the world. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

Calibrating a novel multi-sensor physical activity measurement system.

PubMed

John, D; Liu, S; Sasaki, J E; Howe, C A; Staudenmayer, J; Gao, R X; Freedson, P S

2011-09-01

Advancing the field of physical activity (PA) monitoring requires the development of innovative multi-sensor measurement systems that are feasible in the free-living environment. The use of novel analytical techniques to combine and process these multiple sensor signals is equally important. This paper describes a novel multi-sensor 'integrated PA measurement system' (IMS), the lab-based methodology used to calibrate the IMS, techniques used to predict multiple variables from the sensor signals, and proposes design changes to improve the feasibility of deploying the IMS in the free-living environment. The IMS consists of hip and wrist acceleration sensors, two piezoelectric respiration sensors on the torso, and an ultraviolet radiation sensor to obtain contextual information (indoors versus outdoors) of PA. During lab-based calibration of the IMS, data were collected on participants performing a PA routine consisting of seven different ambulatory and free-living activities while wearing a portable metabolic unit (criterion measure) and the IMS. Data analyses on the first 50 adult participants are presented. These analyses were used to determine if the IMS can be used to predict the variables of interest. Finally, physical modifications for the IMS that could enhance the feasibility of free-living use are proposed and refinement of the prediction techniques is discussed.

Synthetic cannabinoids: In silico prediction of the cannabinoid receptor 1 affinity by a quantitative structure-activity relationship model.

PubMed

Paulke, Alexander; Proschak, Ewgenij; Sommer, Kai; Achenbach, Janosch; Wunder, Cora; Toennes, Stefan W

2016-03-14

The number of new synthetic psychoactive compounds increase steadily. Among the group of these psychoactive compounds, the synthetic cannabinoids (SCBs) are most popular and serve as a substitute of herbal cannabis. More than 600 of these substances already exist. For some SCBs the in vitro cannabinoid receptor 1 (CB1) affinity is known, but for the majority it is unknown. A quantitative structure-activity relationship (QSAR) model was developed, which allows the determination of the SCBs affinity to CB1 (expressed as binding constant (Ki)) without reference substances. The chemically advance template search descriptor was used for vector representation of the compound structures. The similarity between two molecules was calculated using the Feature-Pair Distribution Similarity. The Ki values were calculated using the Inverse Distance Weighting method. The prediction model was validated using a cross validation procedure. The predicted Ki values of some new SCBs were in a range between 20 (considerably higher affinity to CB1 than THC) to 468 (considerably lower affinity to CB1 than THC). The present QSAR model can serve as a simple, fast and cheap tool to get a first hint of the biological activity of new synthetic cannabinoids or of other new psychoactive compounds. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

AE Geomagnetic Index Predictability for High Speed Solar Wind Streams: A Wavelet Decomposition Technique

NASA Technical Reports Server (NTRS)

Guarnieri, Fernando L.; Tsurutani, Bruce T.; Hajra, Rajkumar; Echer, Ezequiel; Gonzalez, Walter D.; Mannucci, Anthony J.

2014-01-01

High speed solar wind streams cause geomagnetic activity at Earth. In this study we have applied a wavelet interactive filtering and reconstruction technique on the solar wind magnetic field components and AE index series to allowed us to investigate the relationship between the two. The IMF Bz component was found as the most significant solar wind parameter responsible by the control of the AE activity. Assuming magnetic reconnection associated to southward directed Bz is the main mechanism transferring energy into the magnetosphere, we adjust parameters to forecast the AE index. The adjusted routine is able to forecast AE, based only on the Bz measured at the L1 Lagrangian point. This gives a prediction approximately 30-70 minutes in advance of the actual geomagnetic activity. The correlation coefficient between the observed AE data and the forecasted series reached values higher than 0.90. In some cases the forecast reproduced particularities observed in the signal very well.The high correlation values observed and the high efficacy of the forecasting can be taken as a confirmation that reconnection is the main physical mechanism responsible for the energy transfer during HILDCAAs. The study also shows that the IMF Bz component low frequencies are most important for AE prediction.

Advanced Fault Diagnosis Methods in Molecular Networks

PubMed Central

Habibi, Iman; Emamian, Effat S.; Abdi, Ali

2014-01-01

Analysis of the failure of cell signaling networks is an important topic in systems biology and has applications in target discovery and drug development. In this paper, some advanced methods for fault diagnosis in signaling networks are developed and then applied to a caspase network and an SHP2 network. The goal is to understand how, and to what extent, the dysfunction of molecules in a network contributes to the failure of the entire network. Network dysfunction (failure) is defined as failure to produce the expected outputs in response to the input signals. Vulnerability level of a molecule is defined as the probability of the network failure, when the molecule is dysfunctional. In this study, a method to calculate the vulnerability level of single molecules for different combinations of input signals is developed. Furthermore, a more complex yet biologically meaningful method for calculating the multi-fault vulnerability levels is suggested, in which two or more molecules are simultaneously dysfunctional. Finally, a method is developed for fault diagnosis of networks based on a ternary logic model, which considers three activity levels for a molecule instead of the previously published binary logic model, and provides equations for the vulnerabilities of molecules in a ternary framework. Multi-fault analysis shows that the pairs of molecules with high vulnerability typically include a highly vulnerable molecule identified by the single fault analysis. The ternary fault analysis for the caspase network shows that predictions obtained using the more complex ternary model are about the same as the predictions of the simpler binary approach. This study suggests that by increasing the number of activity levels the complexity of the model grows; however, the predictive power of the ternary model does not appear to be increased proportionally. PMID:25290670

Impact of domain knowledge on blinded predictions of binding energies by alchemical free energy calculations

NASA Astrophysics Data System (ADS)

Mey, Antonia S. J. S.; Jiménez, Jordi Juárez; Michel, Julien

2018-01-01

The Drug Design Data Resource (D3R) consortium organises blinded challenges to address the latest advances in computational methods for ligand pose prediction, affinity ranking, and free energy calculations. Within the context of the second D3R Grand Challenge several blinded binding free energies predictions were made for two congeneric series of Farsenoid X Receptor (FXR) inhibitors with a semi-automated alchemical free energy calculation workflow featuring FESetup and SOMD software tools. Reasonable performance was observed in retrospective analyses of literature datasets. Nevertheless, blinded predictions on the full D3R datasets were poor due to difficulties encountered with the ranking of compounds that vary in their net-charge. Performance increased for predictions that were restricted to subsets of compounds carrying the same net-charge. Disclosure of X-ray crystallography derived binding modes maintained or improved the correlation with experiment in a subsequent rounds of predictions. The best performing protocols on D3R set1 and set2 were comparable or superior to predictions made on the basis of analysis of literature structure activity relationships (SAR)s only, and comparable or slightly inferior, to the best submissions from other groups.

Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.

PubMed

Weidlich, Iwona E; Pevzner, Yuri; Miller, Benjamin T; Filippov, Igor V; Woodcock, H Lee; Brooks, Bernard R

2015-01-05

Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a web-based tool for structure activity relationship and quantitative structure activity relationship modeling to add to the services provided by CHARMMing (www.charmming.org). This new module implements some of the most recent advances in modern machine learning algorithms-Random Forest, Support Vector Machine, Stochastic Gradient Descent, Gradient Tree Boosting, so forth. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity. © 2014 Wiley Periodicals, Inc.

Pharmacogenetics-based area-under-curve model can predict efficacy and adverse events from axitinib in individual patients with advanced renal cell carcinoma.

PubMed

Yamamoto, Yoshiaki; Tsunedomi, Ryouichi; Fujita, Yusuke; Otori, Toru; Ohba, Mitsuyoshi; Kawai, Yoshihisa; Hirata, Hiroshi; Matsumoto, Hiroaki; Haginaka, Jun; Suzuki, Shigeo; Dahiya, Rajvir; Hamamoto, Yoshihiko; Matsuyama, Kenji; Hazama, Shoichi; Nagano, Hiroaki; Matsuyama, Hideyasu

2018-03-30

We investigated the relationship between axitinib pharmacogenetics and clinical efficacy/adverse events in advanced renal cell carcinoma (RCC) and established a model to predict clinical efficacy and adverse events using pharmacokinetic and gene polymorphisms related to drug metabolism and efflux in a phase II trial. We prospectively evaluated the area under the plasma concentration-time curve (AUC) of axitinib, objective response rate, and adverse events in 44 consecutive advanced RCC patients treated with axitinib. To establish a model for predicting clinical efficacy and adverse events, polymorphisms in genes including ABC transporters ( ABCB1 and ABCG2 ), UGT1A , and OR2B11 were analyzed by whole-exome sequencing, Sanger sequencing, and DNA microarray. To validate this prediction model, calculated AUC by 6 gene polymorphisms was compared with actual AUC in 16 additional consecutive patients prospectively. Actual AUC significantly correlated with the objective response rate ( P = 0.0002) and adverse events (hand-foot syndrome, P = 0.0055; and hypothyroidism, P = 0.0381). Calculated AUC significantly correlated with actual AUC ( P < 0.0001), and correctly predicted objective response rate ( P = 0.0044) as well as adverse events ( P = 0.0191 and 0.0082, respectively). In the validation study, calculated AUC prior to axitinib treatment precisely predicted actual AUC after axitinib treatment ( P = 0.0066). Our pharmacogenetics-based AUC prediction model may determine the optimal initial dose of axitinib, and thus facilitate better treatment of patients with advanced RCC.

Pharmacogenetics-based area-under-curve model can predict efficacy and adverse events from axitinib in individual patients with advanced renal cell carcinoma

PubMed Central

Yamamoto, Yoshiaki; Tsunedomi, Ryouichi; Fujita, Yusuke; Otori, Toru; Ohba, Mitsuyoshi; Kawai, Yoshihisa; Hirata, Hiroshi; Matsumoto, Hiroaki; Haginaka, Jun; Suzuki, Shigeo; Dahiya, Rajvir; Hamamoto, Yoshihiko; Matsuyama, Kenji; Hazama, Shoichi; Nagano, Hiroaki; Matsuyama, Hideyasu

2018-01-01

We investigated the relationship between axitinib pharmacogenetics and clinical efficacy/adverse events in advanced renal cell carcinoma (RCC) and established a model to predict clinical efficacy and adverse events using pharmacokinetic and gene polymorphisms related to drug metabolism and efflux in a phase II trial. We prospectively evaluated the area under the plasma concentration–time curve (AUC) of axitinib, objective response rate, and adverse events in 44 consecutive advanced RCC patients treated with axitinib. To establish a model for predicting clinical efficacy and adverse events, polymorphisms in genes including ABC transporters (ABCB1 and ABCG2), UGT1A, and OR2B11 were analyzed by whole-exome sequencing, Sanger sequencing, and DNA microarray. To validate this prediction model, calculated AUC by 6 gene polymorphisms was compared with actual AUC in 16 additional consecutive patients prospectively. Actual AUC significantly correlated with the objective response rate (P = 0.0002) and adverse events (hand-foot syndrome, P = 0.0055; and hypothyroidism, P = 0.0381). Calculated AUC significantly correlated with actual AUC (P < 0.0001), and correctly predicted objective response rate (P = 0.0044) as well as adverse events (P = 0.0191 and 0.0082, respectively). In the validation study, calculated AUC prior to axitinib treatment precisely predicted actual AUC after axitinib treatment (P = 0.0066). Our pharmacogenetics-based AUC prediction model may determine the optimal initial dose of axitinib, and thus facilitate better treatment of patients with advanced RCC. PMID:29682213

Development of Kinetic Mechanisms for Next-Generation Fuels and CFD Simulation of Advanced Combustion Engines

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pitz, William J.; McNenly, Matt J.; Whitesides, Russell

Predictive chemical kinetic models are needed to represent next-generation fuel components and their mixtures with conventional gasoline and diesel fuels. These kinetic models will allow the prediction of the effect of alternative fuel blends in CFD simulations of advanced spark-ignition and compression-ignition engines. Enabled by kinetic models, CFD simulations can be used to optimize fuel formulations for advanced combustion engines so that maximum engine efficiency, fossil fuel displacement goals, and low pollutant emission goals can be achieved.

Have We Entered a 21st Century Prolonged Minimum of Solar Activity? Updated Implications of a 1987 Prediction

NASA Astrophysics Data System (ADS)

Shirley, James H.

2009-05-01

Fairbridge and Shirley (1987) predicted that a new prolonged minimum of solar activity would be underway by the year 2013 (Solar Physics 110, 191). While it is much too early to tell if this prediction will be fully realized, recent observations document a striking reduction in the Sun's general level of activity. While other forecasts of reduced future activity levels on decadal time scales have appeared, the Fairbridge-Shirley (FS) prediction is unique in pinpointing the current epoch. We are unaware of any forecast method that shows a better correspondence with the actual behavior of the Sun to this point. The FS prediction was based on the present-day recurrence of two physical indicators that were correlated in time with the occurrence of the Wolf, Sporer, and Maunder Minima. The amplitude of the inertial revolution of the axis of symmetry of the Sun's orbital motion about the solar system barycenter, and the direction in space of that axis, each bear a relationship to the occurrence of the prolonged minima of the historic record. The FS prediction appeared before the importance of solar meridional flows was generally appreciated, and before the existence and role of the tachocline was suspected. We will update and restate some of the physical implications of the FS results, along with those of some more recent investigations, particularly with reference to orbit-spin coupling hypotheses (Shirley, 2006: M.N.R.A.S. 368, 280). New investigations combining and integrating modern dynamo models with physical solutions describing key aspects of the variability of the solar motion may lead to significant advances in our ability to forecast future changes in the Sun. Acknowledgement: This work was supported by the resources of the author. No part of this work was performed at the Jet Propulsion Laboratory under a contract from NASA.

Intentional preparation of auditory attention-switches: Explicit cueing and sequential switch-predictability.

PubMed

Seibold, Julia C; Nolden, Sophie; Oberem, Josefa; Fels, Janina; Koch, Iring

2018-06-01

In an auditory attention-switching paradigm, participants heard two simultaneously spoken number-words, each presented to one ear, and decided whether the target number was smaller or larger than 5 by pressing a left or right key. An instructional cue in each trial indicated which feature had to be used to identify the target number (e.g., female voice). Auditory attention-switch costs were found when this feature changed compared to when it repeated in two consecutive trials. Earlier studies employing this paradigm showed mixed results when they examined whether such cued auditory attention-switches can be prepared actively during the cue-stimulus interval. This study systematically assessed which preconditions are necessary for the advance preparation of auditory attention-switches. Three experiments were conducted that controlled for cue-repetition benefits, modality switches between cue and stimuli, as well as for predictability of the switch-sequence. Only in the third experiment, in which predictability for an attention-switch was maximal due to a pre-instructed switch-sequence and predictable stimulus onsets, active switch-specific preparation was found. These results suggest that the cognitive system can prepare auditory attention-switches, and this preparation seems to be triggered primarily by the memorised switching-sequence and valid expectations about the time of target onset.

Urinary biomarkers predict advanced acute kidney injury after cardiovascular surgery.

PubMed

Wang, Jian-Jhong; Chi, Nai-Hsin; Huang, Tao-Min; Connolly, Rory; Chen, Liang Wen; Chueh, Shih-Chieh Jeff; Kan, Wei-Chih; Lai, Chih-Cheng; Wu, Vin-Cent; Fang, Ji-Tseng; Chu, Tzong-Shinn; Wu, Kwan-Dun

2018-04-26

Acute kidney injury (AKI) after cardiovascular surgery is a serious complication. Little is known about the ability of novel biomarkers in combination with clinical risk scores for prediction of advanced AKI. In this prospectively conducted multicenter study, urine samples were collected from 149 adults at 0, 3, 6, 12 and 24 h after cardiovascular surgery. We measured urinary hemojuvelin (uHJV), kidney injury molecule-1 (uKIM-1), neutrophil gelatinase-associated lipocalin (uNGAL), α-glutathione S-transferase (uα-GST) and π-glutathione S-transferase (uπ-GST). The primary outcome was advanced AKI, under the definition of Kidney Disease: Improving Global Outcomes (KDIGO) stage 2, 3 and composite outcomes were KDIGO stage 2, 3 or 90-day mortality after hospital discharge. Patients with advanced AKI had significantly higher levels of uHJV and uKIM-1 at 3, 6 and 12 h after surgery. When normalized by urinary creatinine level, uKIM-1 in combination with uHJV at 3 h post-surgery had a high predictive ability for advanced AKI and composite outcome (AUC = 0.898 and 0.905, respectively). The combination of this biomarker panel (normalized uKIM-1, uHJV at 3 h post-operation) and Liano's score was superior in predicting advanced AKI (AUC = 0.931, category-free net reclassification improvement of 1.149, and p <  0.001). When added to Liano's score, normalized uHJV and uKIM-1 levels at 3 h after cardiovascular surgery enhanced the identification of patients at higher risk of progression to advanced AKI and composite outcomes.

Response of Douglas-fir advance regeneration to overstory removal

Treesearch

J. Chris Maranto; Dennis E. Ferguson; David L. Adams

2008-01-01

A statistical model is presented that predicts periodic height growth for released Pseudotsuga menziesii var. glauca [Beissn.] Franco advance regeneration in central Idaho. Individual tree and site variables were used to construct a model that predicts 5-year height growth for years 6 through 10 after release. Habitat type and height growth prior to...

APPLICATION OF ADVANCED IN VITRO TECHNIQUES TO MEASURE, UNDERSTAND AND PREDICT THE KINETICS AND MECHANISMS OF XENOBIOTIC METABOLISM

EPA Science Inventory

We have developed a research program in metabolism that involves numerous collaborators across EPA as well as other federal and academic labs. A primary goal is to develop and apply advanced in vitro techniques to measure, understand and predict the kinetics and mechanisms of xen...

Materials and structural aspects of advanced gas-turbine helicopter engines

NASA Technical Reports Server (NTRS)

Freche, J. C.; Acurio, J.

1979-01-01

Advances in materials, coatings, turbine cooling technology, structural and design concepts, and component-life prediction of helicopter gas-turbine-engine components are presented. Stationary parts including the inlet particle separator, the front frame, rotor tip seals, vanes and combustors and rotating components - compressor blades, disks, and turbine blades - are discussed. Advanced composite materials are considered for the front frame and compressor blades, prealloyed powder superalloys will increase strength and reduce costs of disks, the oxide dispersion strengthened alloys will have 100C higher use temperature in combustors and vanes than conventional superalloys, ceramics will provide the highest use temperature of 1400C for stator vanes and 1370C for turbine blades, and directionally solidified eutectics will afford up to 50C temperature advantage at turbine blade operating conditions. Coatings for surface protection at higher surface temperatures and design trends in turbine cooling technology are discussed. New analytical methods of life prediction such as strain gage partitioning for high temperature prediction, fatigue life, computerized prediction of oxidation resistance, and advanced techniques for estimating coating life are described.

The predictive value of MRI in detecting thyroid gland invasion in patients with advanced laryngeal or hypopharyngeal carcinoma.

PubMed

Lin, Peiliang; Huang, Xiaoming; Zheng, Chushan; Cai, Qian; Guan, Zhong; Liang, Faya; Zheng, Yiqing

2017-01-01

The aim of this study was to evaluate the predictive value of magnetic resonance imaging (MRI) in detecting thyroid gland invasion (TGI) in patients with advanced laryngeal or hypopharyngeal carcinoma. In a retrospective chart review, 41 patients with advanced laryngeal or hypopharyngeal carcinoma underwent MRI scan before total laryngectomy and ipsilateral or bilateral thyroidectomy during the past 5 years. The MRI findings were compared with the postoperative pathological results. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Among the 41 patients, 3 had thyroid gland invasion in postoperative pathological results. MRI correctly predicted the absence of TGI in 37 of 38 patients and TGI in all 3 patients. The sensitivity, specificity, PPV, and NPV of MRI were 100.0, 97.4, 75.0, and 100 %, respectively, with the diagnostic accuracy of 97.6 %. In consideration of the high negative predictive value of MRI, it may help surgeons selectively preserve thyroid gland in total laryngectomy and reduce the incidence of hypothyroidism and hypoparathyroidism postoperatively.

The role of different sampling methods in improving biological activity prediction using deep belief network.

PubMed

Ghasemi, Fahimeh; Fassihi, Afshin; Pérez-Sánchez, Horacio; Mehri Dehnavi, Alireza

2017-02-05

Thousands of molecules and descriptors are available for a medicinal chemist thanks to the technological advancements in different branches of chemistry. This fact as well as the correlation between them has raised new problems in quantitative structure activity relationship studies. Proper parameter initialization in statistical modeling has merged as another challenge in recent years. Random selection of parameters leads to poor performance of deep neural network (DNN). In this research, deep belief network (DBN) was applied to initialize DNNs. DBN is composed of some stacks of restricted Boltzmann machine, an energy-based method that requires computing log likelihood gradient for all samples. Three different sampling approaches were suggested to solve this gradient. In this respect, the impact of DBN was applied based on the different sampling approaches mentioned above to initialize the DNN architecture in predicting biological activity of all fifteen Kaggle targets that contain more than 70k molecules. The same as other fields of processing research, the outputs of these models demonstrated significant superiority to that of DNN with random parameters. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Rotor Performance at High Advance Ratio: Theory versus Test

NASA Technical Reports Server (NTRS)

Harris, Franklin D.

2008-01-01

Five analytical tools have been used to study rotor performance at high advance ratio. One is representative of autogyro rotor theory in 1934 and four are representative of helicopter rotor theory in 2008. The five theories are measured against three sets of well documented, full-scale, isolated rotor performance experiments. The major finding of this study is that the decades spent by many rotorcraft theoreticians to improve prediction of basic rotor aerodynamic performance has paid off. This payoff, illustrated by comparing the CAMRAD II comprehensive code and Wheatley & Bailey theory to H-34 test data, shows that rational rotor lift to drag ratios are now predictable. The 1934 theory predicted L/D ratios as high as 15. CAMRAD II predictions compared well with H-34 test data having L/D ratios more on the order of 7 to 9. However, the detailed examination of the selected codes compared to H-34 test data indicates that not one of the codes can predict to engineering accuracy above an advance ratio of 0.62 the control positions and shaft angle of attack required for a given lift. There is no full-scale rotor performance data available for advance ratios above 1.0 and extrapolation of currently available data to advance ratios on the order of 2.0 is unreasonable despite the needs of future rotorcraft. Therefore, it is recommended that an overly strong full-scale rotor blade set be obtained and tested in a suitable wind tunnel to at least an advance ratio of 2.5. A tail rotor from a Sikorsky CH-53 or other large single rotor helicopter should be adequate for this exploratory experiment.

Dissociation between Neural Signatures of Stimulus and Choice in Population Activity of Human V1 during Perceptual Decision-Making

PubMed Central

Choe, Kyoung Whan; Blake, Randolph

2014-01-01

Primary visual cortex (V1) forms the initial cortical representation of objects and events in our visual environment, and it distributes information about that representation to higher cortical areas within the visual hierarchy. Decades of work have established tight linkages between neural activity occurring in V1 and features comprising the retinal image, but it remains debatable how that activity relates to perceptual decisions. An actively debated question is the extent to which V1 responses determine, on a trial-by-trial basis, perceptual choices made by observers. By inspecting the population activity of V1 from human observers engaged in a difficult visual discrimination task, we tested one essential prediction of the deterministic view: choice-related activity, if it exists in V1, and stimulus-related activity should occur in the same neural ensemble of neurons at the same time. Our findings do not support this prediction: while cortical activity signifying the variability in choice behavior was indeed found in V1, that activity was dissociated from activity representing stimulus differences relevant to the task, being advanced in time and carried by a different neural ensemble. The spatiotemporal dynamics of population responses suggest that short-term priors, perhaps formed in higher cortical areas involved in perceptual inference, act to modulate V1 activity prior to stimulus onset without modifying subsequent activity that actually represents stimulus features within V1. PMID:24523561

Particle Swarm Optimization for Programming Deep Brain Stimulation Arrays

PubMed Central

Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

2017-01-01

Objective Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main Results The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (≤9.2%) and ROA (≤1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n=3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of <1% between approaches. Significance The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts. PMID:28068291

Particle swarm optimization for programming deep brain stimulation arrays

NASA Astrophysics Data System (ADS)

Peña, Edgar; Zhang, Simeng; Deyo, Steve; Xiao, YiZi; Johnson, Matthew D.

2017-02-01

Objective. Deep brain stimulation (DBS) therapy relies on both precise neurosurgical targeting and systematic optimization of stimulation settings to achieve beneficial clinical outcomes. One recent advance to improve targeting is the development of DBS arrays (DBSAs) with electrodes segmented both along and around the DBS lead. However, increasing the number of independent electrodes creates the logistical challenge of optimizing stimulation parameters efficiently. Approach. Solving such complex problems with multiple solutions and objectives is well known to occur in biology, in which complex collective behaviors emerge out of swarms of individual organisms engaged in learning through social interactions. Here, we developed a particle swarm optimization (PSO) algorithm to program DBSAs using a swarm of individual particles representing electrode configurations and stimulation amplitudes. Using a finite element model of motor thalamic DBS, we demonstrate how the PSO algorithm can efficiently optimize a multi-objective function that maximizes predictions of axonal activation in regions of interest (ROI, cerebellar-receiving area of motor thalamus), minimizes predictions of axonal activation in regions of avoidance (ROA, somatosensory thalamus), and minimizes power consumption. Main results. The algorithm solved the multi-objective problem by producing a Pareto front. ROI and ROA activation predictions were consistent across swarms (<1% median discrepancy in axon activation). The algorithm was able to accommodate for (1) lead displacement (1 mm) with relatively small ROI (⩽9.2%) and ROA (⩽1%) activation changes, irrespective of shift direction; (2) reduction in maximum per-electrode current (by 50% and 80%) with ROI activation decreasing by 5.6% and 16%, respectively; and (3) disabling electrodes (n  =  3 and 12) with ROI activation reduction by 1.8% and 14%, respectively. Additionally, comparison between PSO predictions and multi-compartment axon model simulations showed discrepancies of  <1% between approaches. Significance. The PSO algorithm provides a computationally efficient way to program DBS systems especially those with higher electrode counts.

Does exercise motivation predict engagement in objectively assessed bouts of moderate-intensity exercise? A self-determination theory perspective.

PubMed

Standage, Martyn; Sebire, Simon J; Loney, Tom

2008-08-01

This study examined the utility of motivation as advanced by self-determination theory (Deci & Ryan, 2000) in predicting objectively assessed bouts of moderate intensity exercise behavior. Participants provided data pertaining to their exercise motivation. One week later, participants wore a combined accelerometer and heart rate monitor (Actiheart; Cambridge Neurotechnology Ltd) and 24-hr energy expenditure was estimated for 7 days. After controlling for gender and a combined marker of BMI and waist circumference, results showed autonomous motivation to positively predict moderate-intensity exercise bouts of >or=10 min, or=20 min, and an accumulation needed to meet public health recommendations for moderate intensity activity (i.e., ACSM/AHA guidelines). The present findings add bouts of objectively assessed exercise behavior to the growing body of literature that documents the adaptive consequences of engaging in exercise for autonomous reasons. Implications for practice and future work are discussed.

A Thermodynamically Consistent Damage Model for Advanced Composites

NASA Technical Reports Server (NTRS)

Maimi, Pere; Camanho, Pedro P.; Mayugo, Joan-Andreu; Davila, Carlos G.

2006-01-01

A continuum damage model for the prediction of damage onset and structural collapse of structures manufactured in fiber-reinforced plastic laminates is proposed. The principal damage mechanisms occurring in the longitudinal and transverse directions of a ply are represented by a damage tensor that is fixed in space. Crack closure under load reversal effects are taken into account using damage variables established as a function of the sign of the components of the stress tensor. Damage activation functions based on the LaRC04 failure criteria are used to predict the different damage mechanisms occurring at the ply level. The constitutive damage model is implemented in a finite element code. The objectivity of the numerical model is assured by regularizing the dissipated energy at a material point using Bazant's Crack Band Model. To verify the accuracy of the approach, analyses of coupon specimens were performed, and the numerical predictions were compared with experimental data.

Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts.

PubMed

Bokhorst, Stef; Pedersen, Stine Højlund; Brucker, Ludovic; Anisimov, Oleg; Bjerke, Jarle W; Brown, Ross D; Ehrich, Dorothee; Essery, Richard L H; Heilig, Achim; Ingvander, Susanne; Johansson, Cecilia; Johansson, Margareta; Jónsdóttir, Ingibjörg Svala; Inga, Niila; Luojus, Kari; Macelloni, Giovanni; Mariash, Heather; McLennan, Donald; Rosqvist, Gunhild Ninis; Sato, Atsushi; Savela, Hannele; Schneebeli, Martin; Sokolov, Aleksandr; Sokratov, Sergey A; Terzago, Silvia; Vikhamar-Schuler, Dagrun; Williamson, Scott; Qiu, Yubao; Callaghan, Terry V

2016-09-01

Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region.

Changing Arctic Snow Cover: A Review of Recent Developments and Assessment of Future Needs for Observations, Modelling, and Impacts

NASA Technical Reports Server (NTRS)

Bokhorst, Stef; Pedersen, Stine Hojlund; Brucker, Ludovic; Anisimov, Oleg; Bjerke, Jarle W.; Brown, Ross D.; Ehrich, Dorothee; Essery, Richard L. H.; Heilig, Achim; Ingvander, Susanne;

Electromigration model for the prediction of lifetime based on the failure unit statistics in aluminum metallization

NASA Astrophysics Data System (ADS)

Park, Jong Ho; Ahn, Byung Tae

2003-01-01

A failure model for electromigration based on the "failure unit model" was presented for the prediction of lifetime in metal lines.The failure unit model, which consists of failure units in parallel and series, can predict both the median time to failure (MTTF) and the deviation in the time to failure (DTTF) in Al metal lines. The model can describe them only qualitatively. In our model, both the probability function of the failure unit in single grain segments and polygrain segments are considered instead of in polygrain segments alone. Based on our model, we calculated MTTF, DTTF, and activation energy for different median grain sizes, grain size distributions, linewidths, line lengths, current densities, and temperatures. Comparisons between our results and published experimental data showed good agreements and our model could explain the previously unexplained phenomena. Our advanced failure unit model might be further applied to other electromigration characteristics of metal lines.

Applied Meteorology Unit (AMU) Quarterly Report. First Quarter FY-05

NASA Technical Reports Server (NTRS)

Bauman, William; Wheeler, Mark; Lambert, Winifred; Case, Jonathan; Short, David

2005-01-01

This report summarizes the Applied Meteorology Unit (AMU) activities for the first quarter of Fiscal Year 2005 (October - December 2005). Tasks reviewed include: (1) Objective Lightning Probability Forecast: Phase I, (2) Severe Weather Forecast Decision Aid, (3) Hail Index, (4) Stable Low Cloud Evaluation, (5) Shuttle Ascent Camera Cloud Obstruction Forecast, (6) Range Standardization and Automation (RSA) and Legacy Wind Sensor Evaluation, (7) Advanced Regional Prediction System (ARPS) Optimization and Training Extension, and (8) User Control Interface for ARPS Data Analysis System (ADAS) Data Ingest

Data-driven predictions in the science of science.

PubMed

Clauset, Aaron; Larremore, Daniel B; Sinatra, Roberta

2017-02-03

The desire to predict discoveries-to have some idea, in advance, of what will be discovered, by whom, when, and where-pervades nearly all aspects of modern science, from individual scientists to publishers, from funding agencies to hiring committees. In this Essay, we survey the emerging and interdisciplinary field of the "science of science" and what it teaches us about the predictability of scientific discovery. We then discuss future opportunities for improving predictions derived from the science of science and its potential impact, positive and negative, on the scientific community. Copyright © 2017, American Association for the Advancement of Science.

The quiet revolution of numerical weather prediction.

PubMed

Bauer, Peter; Thorpe, Alan; Brunet, Gilbert

2015-09-03

Advances in numerical weather prediction represent a quiet revolution because they have resulted from a steady accumulation of scientific knowledge and technological advances over many years that, with only a few exceptions, have not been associated with the aura of fundamental physics breakthroughs. Nonetheless, the impact of numerical weather prediction is among the greatest of any area of physical science. As a computational problem, global weather prediction is comparable to the simulation of the human brain and of the evolution of the early Universe, and it is performed every day at major operational centres across the world.

CEAS/AIAA/ICASE/NASA Langley International Forum on Aeroelasticity and Structural Dynamics 1999. Pt. 2

NASA Technical Reports Server (NTRS)

Whitlow, Jr., Woodrow (Editor); Todd, Emily N. (Editor)

1999-01-01

The proceedings of a workshop sponsored by the Confederation of European Aerospace Societies (CEAS), the American Institute of Aeronautics and Astronautics (AIAA), the National Aeronautics and Space Administration (NASA), Washington, D.C., and the Institute for Computer Applications in Science and Engineering (ICASE), Hampton, Virginia, and held in Williamsburg, Virginia June 22-25, 1999 represent a collection of the latest advances in aeroelasticity and structural dynamics from the world community. Research in the areas of unsteady aerodynamics and aeroelasticity, structural modeling and optimization, active control and adaptive structures, landing dynamics, certification and qualification, and validation testing are highlighted in the collection of papers. The wide range of results will lead to advances in the prediction and control of the structural response of aircraft and spacecraft.

The dawn of a revolution in personalized lung cancer prevention.

PubMed

Khuri, Fadlo R

2011-07-01

Lung cancer prevention and early detection, which have fallen on hard times for more than the past 20 years, seem to have turned a corner toward better times ahead. Exciting new results of randomized controlled trials that targeted the arachidonic acid pathway, including a celecoxib trial reported by Mao and colleagues in this issue of the journal (beginning on page 984) and a trial of the prostacyclin analog iloprost, complement recently reported 20%-30% lung cancer mortality reductions, either with aspirin in targeting the arachidonic acid pathway or with computed tomography screening. The new results show encouraging activity personalized to former smokers and/or people expressing predictive biomarkers. These trials and technological advances in molecular profiling and imaging herald substantial clinical advances on the horizon of this field.

Math at home adds up to achievement in school.

PubMed

Berkowitz, Talia; Schaeffer, Marjorie W; Maloney, Erin A; Peterson, Lori; Gregor, Courtney; Levine, Susan C; Beilock, Sian L

2015-10-09

With a randomized field experiment of 587 first-graders, we tested an educational intervention designed to promote interactions between children and parents relating to math. We predicted that increasing math activities at home would increase children's math achievement at school. We tested this prediction by having children engage in math story time with their parents. The intervention, short numerical story problems delivered through an iPad app, significantly increased children's math achievement across the school year compared to a reading (control) group, especially for children whose parents are habitually anxious about math. Brief, high-quality parent-child interactions about math at home help break the intergenerational cycle of low math achievement. Copyright © 2015, American Association for the Advancement of Science.

New technologies in predicting, preventing and controlling emerging infectious diseases.

PubMed

Christaki, Eirini

2015-01-01

Surveillance of emerging infectious diseases is vital for the early identification of public health threats. Emergence of novel infections is linked to human factors such as population density, travel and trade and ecological factors like climate change and agricultural practices. A wealth of new technologies is becoming increasingly available for the rapid molecular identification of pathogens but also for the more accurate monitoring of infectious disease activity. Web-based surveillance tools and epidemic intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely outbreak detection. In this review, we present new methods for regional and global infectious disease surveillance and advances in epidemic modeling aimed to predict and prevent future infectious diseases threats.

New technologies in predicting, preventing and controlling emerging infectious diseases

PubMed Central

Christaki, Eirini

2015-01-01

Surveillance of emerging infectious diseases is vital for the early identification of public health threats. Emergence of novel infections is linked to human factors such as population density, travel and trade and ecological factors like climate change and agricultural practices. A wealth of new technologies is becoming increasingly available for the rapid molecular identification of pathogens but also for the more accurate monitoring of infectious disease activity. Web-based surveillance tools and epidemic intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely outbreak detection. In this review, we present new methods for regional and global infectious disease surveillance and advances in epidemic modeling aimed to predict and prevent future infectious diseases threats. PMID:26068569

Iron-Targeting Antitumor Activity of Gallium Compounds and Novel Insights Into Triapine®-Metal Complexes

PubMed Central

Antholine, William E.

2013-01-01

Abstract Significance: Despite advances made in the treatment of cancer, a significant number of patients succumb to this disease every year. Hence, there is a great need to develop new anticancer agents. Recent Advances: Emerging data show that malignant cells have a greater requirement for iron than normal cells do and that proteins involved in iron import, export, and storage may be altered in cancer cells. Therefore, strategies to perturb these iron-dependent steps in malignant cells hold promise for the treatment of cancer. Recent studies show that gallium compounds and metal-thiosemicarbazone complexes inhibit tumor cell growth by targeting iron homeostasis, including iron-dependent ribonucleotide reductase. Chemical similarities of gallium(III) with iron(III) enable the former to mimic the latter and interpose itself in critical iron-dependent steps in cellular proliferation. Newer gallium compounds have emerged with additional mechanisms of action. In clinical trials, the first-generation-compound gallium nitrate has exhibited activity against bladder cancer and non-Hodgkin's lymphoma, while the thiosemicarbazone Triapine® has demonstrated activity against other tumors. Critical Issues: Novel gallium compounds with greater cytotoxicity and a broader spectrum of antineoplastic activity than gallium nitrate should continue to be developed. Future Directions: The antineoplastic activity and toxicity of the existing novel gallium compounds and thiosemicarbazone-metal complexes should be tested in animal tumor models and advanced to Phase I and II clinical trials. Future research should identify biologic markers that predict tumor sensitivity to gallium compounds. This will help direct gallium-based therapy to cancer patients who are most likely to benefit from it. Antioxid. Redox Signal. 00, 000–000. PMID:22900955

PREDICT: a diagnostic accuracy study of a tool for predicting mortality within one year: who should have an advance healthcare directive?

PubMed

Richardson, Philip; Greenslade, Jaimi; Shanmugathasan, Sulochana; Doucet, Katherine; Widdicombe, Neil; Chu, Kevin; Brown, Anthony

2015-01-01

CARING is a screening tool developed to identify patients who have a high likelihood of death in 1 year. This study sought to validate a modified CARING tool (termed PREDICT) using a population of patients presenting to the Emergency Department. In total, 1000 patients aged over 55 years who were admitted to hospital via the Emergency Department between January and June 2009 were eligible for inclusion in this study. Data on the six prognostic indicators comprising PREDICT were obtained retrospectively from patient records. One-year mortality data were obtained from the State Death Registry. Weights were applied to each PREDICT criterion, and its final score ranged from 0 to 44. Receiver operator characteristic analyses and diagnostic accuracy statistics were used to assess the accuracy of PREDICT in identifying 1-year mortality. The sample comprised 976 patients with a median (interquartile range) age of 71 years (62-81 years) and a 1-year mortality of 23.4%. In total, 50% had ≥1 PREDICT criteria with a 1-year mortality of 40.4%. Receiver operator characteristic analysis gave an area under the curve of 0.86 (95% confidence interval: 0.83-0.89). Using a cut-off of 13 points, PREDICT had a 95.3% (95% confidence interval: 93.6-96.6) specificity and 53.9% (95% confidence interval: 47.5-60.3) sensitivity for predicting 1-year mortality. PREDICT was simpler than the CARING criteria and identified 158 patients per 1000 admitted who could benefit from advance care planning. PREDICT was successfully applied to the Australian healthcare system with findings similar to the original CARING study conducted in the United States. This tool could improve end-of-life care by identifying who should have advance care planning or an advance healthcare directive. © The Author(s) 2014.

Research on chemical vapor deposition processes for advanced ceramic coatings

NASA Technical Reports Server (NTRS)

Rosner, Daniel E.

1993-01-01

Our interdisciplinary background and fundamentally-oriented studies of the laws governing multi-component chemical vapor deposition (VD), particle deposition (PD), and their interactions, put the Yale University HTCRE Laboratory in a unique position to significantly advance the 'state-of-the-art' of chemical vapor deposition (CVD) R&D. With NASA-Lewis RC financial support, we initiated a program in March of 1988 that has led to the advances described in this report (Section 2) in predicting chemical vapor transport in high temperature systems relevant to the fabrication of refractory ceramic coatings for turbine engine components. This Final Report covers our principal results and activities for the total NASA grant of $190,000. over the 4.67 year period: 1 March 1988-1 November 1992. Since our methods and the technical details are contained in the publications listed (9 Abstracts are given as Appendices) our emphasis here is on broad conclusions/implications and administrative data, including personnel, talks, interactions with industry, and some known applications of our work.

Toward large space systems. [Space Construction Base development from shuttles

NASA Technical Reports Server (NTRS)

Daros, C. J.; Freitag, R. F.; Kline, R. L.

1977-01-01

The design of the Space Transportation System, consisting of the Space Shuttle, Spacelab, and upper stages, provides experience for the development of more advanced space systems. The next stage will involve space stations in low earth orbit with limited self-sufficiency, characterized by closed ecological environments, space-generated power, and perhaps the first use of space materials. The third phase would include manned geosynchronous space-station activity and a return to lunar operations. Easier access to space will encourage the use of more complex, maintenance-requiring satellites than those currently used. More advanced space systems could perform a wide range of public services such as electronic mail, personal and police communication, disaster control, earthquake detection/prediction, water availability indication, vehicle speed control, and burglar alarm/intrusion detection. Certain products, including integrated-circuit chips and some enzymes, can be processed to a higher degree of purity in space and might eventually be manufactured there. Hardware including dishes, booms, and planar surfaces necessary for advanced space systems and their development are discussed.

Analysis of clinically important factors on the performance of advanced hydraulic, microprocessor-controlled exo-prosthetic knee joints based on 899 trial fittings

PubMed Central

Hahn, Andreas; Lang, Michael; Stuckart, Claudia

2016-01-01

Abstract The objective of this work is to evaluate whether clinically important factors may predict an individual's capability to utilize the functional benefits provided by an advanced hydraulic, microprocessor-controlled exo-prosthetic knee component. This retrospective cross-sectional cohort analysis investigated the data of above knee amputees captured during routine trial fittings. Prosthetists rated the performance indicators showing the functional benefits of the advanced maneuvering capabilities of the device. Subjects were asked to rate their perception. Simple and multiple linear and logistic regression was applied. Data from 899 subjects with demographics typical for the population were evaluated. Ability to vary gait speed, perform toileting, and ascend stairs were identified as the most sensitive performance predictors. Prior C-Leg users showed benefits during advanced maneuvering. Variables showed plausible and meaningful effects, however, could not claim predictive power. Mobility grade showed the largest effect but also failed to be predictive. Clinical parameters such as etiology, age, mobility grade, and others analyzed here do not suffice to predict individual potential. Daily walking distance may pose a threshold value and be part of a predictive instrument. Decisions based solely on single parameters such as mobility grade rating or walking distance seem to be questionable. PMID:27828871

Analysis of clinically important factors on the performance of advanced hydraulic, microprocessor-controlled exo-prosthetic knee joints based on 899 trial fittings.

PubMed

Hahn, Andreas; Lang, Michael; Stuckart, Claudia

2016-11-01

The objective of this work is to evaluate whether clinically important factors may predict an individual's capability to utilize the functional benefits provided by an advanced hydraulic, microprocessor-controlled exo-prosthetic knee component.This retrospective cross-sectional cohort analysis investigated the data of above knee amputees captured during routine trial fittings. Prosthetists rated the performance indicators showing the functional benefits of the advanced maneuvering capabilities of the device. Subjects were asked to rate their perception. Simple and multiple linear and logistic regression was applied.Data from 899 subjects with demographics typical for the population were evaluated. Ability to vary gait speed, perform toileting, and ascend stairs were identified as the most sensitive performance predictors. Prior C-Leg users showed benefits during advanced maneuvering. Variables showed plausible and meaningful effects, however, could not claim predictive power. Mobility grade showed the largest effect but also failed to be predictive.Clinical parameters such as etiology, age, mobility grade, and others analyzed here do not suffice to predict individual potential. Daily walking distance may pose a threshold value and be part of a predictive instrument. Decisions based solely on single parameters such as mobility grade rating or walking distance seem to be questionable.

Progress of Aircraft System Noise Assessment with Uncertainty Quantification for the Environmentally Responsible Aviation Project

NASA Technical Reports Server (NTRS)

Thomas, Russell H.; Burley, Casey L.; Guo, Yueping

2016-01-01

Aircraft system noise predictions have been performed for NASA modeled hybrid wing body aircraft advanced concepts with 2025 entry-into-service technology assumptions. The system noise predictions developed over a period from 2009 to 2016 as a result of improved modeling of the aircraft concepts, design changes, technology development, flight path modeling, and the use of extensive integrated system level experimental data. In addition, the system noise prediction models and process have been improved in many ways. An additional process is developed here for quantifying the uncertainty with a 95% confidence level. This uncertainty applies only to the aircraft system noise prediction process. For three points in time during this period, the vehicle designs, technologies, and noise prediction process are documented. For each of the three predictions, and with the information available at each of those points in time, the uncertainty is quantified using the direct Monte Carlo method with 10,000 simulations. For the prediction of cumulative noise of an advanced aircraft at the conceptual level of design, the total uncertainty band has been reduced from 12.2 to 9.6 EPNL dB. A value of 3.6 EPNL dB is proposed as the lower limit of uncertainty possible for the cumulative system noise prediction of an advanced aircraft concept.

Advanced Daily Prediction Model for National Suicide Numbers with Social Media Data

PubMed Central

Lee, Kyung Sang; Lee, Hyewon; Myung, Woojae; Song, Gil-Young; Lee, Kihwang; Kim, Ho; Carroll, Bernard J.; Kim, Doh Kwan

2018-01-01

Objective Suicide is a significant public health concern worldwide. Social media data have a potential role in identifying high suicide risk individuals and also in predicting suicide rate at the population level. In this study, we report an advanced daily suicide prediction model using social media data combined with economic/meteorological variables along with observed suicide data lagged by 1 week. Methods The social media data were drawn from weblog posts. We examined a total of 10,035 social media keywords for suicide prediction. We made predictions of national suicide numbers 7 days in advance daily for 2 years, based on a daily moving 5-year prediction modeling period. Results Our model predicted the likely range of daily national suicide numbers with 82.9% accuracy. Among the social media variables, words denoting economic issues and mood status showed high predictive strength. Observed number of suicides one week previously, recent celebrity suicide, and day of week followed by stock index, consumer price index, and sunlight duration 7 days before the target date were notable predictors along with the social media variables. Conclusion These results strengthen the case for social media data to supplement classical social/economic/climatic data in forecasting national suicide events. PMID:29614852

Modified CLIP with objective liver reserve assessment retains prognosis prediction for patients with advanced hepatocellular carcinoma.

PubMed

Shao, Yu-Yun; Liu, Tsung-Hao; Lee, Ying-Hui; Hsu, Chih-Hung; Cheng, Ann-Lii

2016-07-01

The Cancer of the Liver Italian Program (CLIP) score is a commonly used staging system for hepatocellular carcinoma (HCC) helpful with predicting prognosis of advanced HCC. CLIP uses the Child-Turcotte-Pugh (CTP) score to evaluate liver reserve. A new scoring system, the albumin-bilirubin (ALBI) grade, has been proposed as they objectively evaluate liver reserve. We examined whether the modification of CLIP with ALBI retained its prognosis prediction for patients with advanced HCC. We included patients who received first-line antiangiogenic therapy for advanced HCC. Liver reserve was assessed using CTP and ALBI scores, which were then incorporated into CLIP and ALBI-CLIP, respectively. To assess their efficacies of prognostic prediction, the Cox's proportional hazard model and concordance indexes were used. A total of 142 patients were included; 137 of them were classified CTP A and 5 patients CTP B. Patients could be divided into four or five groups with different prognosis according to CLIP and ALBI-CLIP, respectively. Higher R(2) (0.249 vs 0.216) and lower Akaike information criterion (995.0 vs 1001.1) were observed for ALBI-CLIP than for CLIP in the Cox's model predicting overall survival. ALBI-CLIP remained an independent predictor for overall survival when CLIP and ALBI-CLIP were simultaneously incorporated in Cox's models allowing variable selection with adjustment for hepatitis etiology, treatment, and performance status. The concordance index was also higher for ALBI-CLIP than for CLIP (0.724 vs 0.703). Modification of CLIP scoring with ALBI, which objectively assesses liver reserve, retains and might have improved prognosis prediction for advanced HCC. © 2016 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Cognitive predictors of skilled performance with an advanced upper limb multifunction prosthesis: a preliminary analysis.

PubMed

Hancock, Laura; Correia, Stephen; Ahern, David; Barredo, Jennifer; Resnik, Linda

2017-07-01

Purpose The objectives were to 1) identify major cognitive domains involved in learning to use the DEKA Arm; 2) specify cognitive domain-specific skills associated with basic versus advanced users; and 3) examine whether baseline memory and executive function predicted learning. Method Sample included 35 persons with upper limb amputation. Subjects were administered a brief neuropsychological test battery prior to start of DEKA Arm training, as well as physical performance measures at the onset of, and following training. Multiple regression models controlling for age and including neuropsychological tests were developed to predict physical performance scores. Prosthetic performance scores were divided into quartiles and independent samples t-tests compared neuropsychological test scores of advanced scorers and basic scorers. Baseline neuropsychological test scores were used to predict change in scores on physical performance measures across time. Results Cognitive domains of attention and processing speed were statistically significantly related to proficiency of DEKA Arm use and predicted level of proficiency. Conclusions Results support use of neuropsychological tests to predict learning and use of a multifunctional prosthesis. Assessment of cognitive status at the outset of training may help set expectations for the duration and outcomes of treatment. Implications for Rehabilitation Cognitive domains of attention and processing speed were significantly related to level of proficiencyof an advanced multifunctional prosthesis (the DEKA Arm) after training. Results provide initial support for the use of neuropsychological tests to predict advanced learningand use of a multifunctional prosthesis in upper-limb amputees. Results suggest that assessment of patients' cognitive status at the outset of upper limb prosthetictraining may, in the future, help patients, their families and therapists set expectations for theduration and intensity of training and may help set reasonable proficiency goals.

Effectiveness of Link Prediction for Face-to-Face Behavioral Networks

PubMed Central

Tsugawa, Sho; Ohsaki, Hiroyuki

2013-01-01

Research on link prediction for social networks has been actively pursued. In link prediction for a given social network obtained from time-windowed observation, new link formation in the network is predicted from the topology of the obtained network. In contrast, recent advances in sensing technology have made it possible to obtain face-to-face behavioral networks, which are social networks representing face-to-face interactions among people. However, the effectiveness of link prediction techniques for face-to-face behavioral networks has not yet been explored in depth. To clarify this point, here we investigate the accuracy of conventional link prediction techniques for networks obtained from the history of face-to-face interactions among participants at an academic conference. Our findings were (1) that conventional link prediction techniques predict new link formation with a precision of 0.30–0.45 and a recall of 0.10–0.20, (2) that prolonged observation of social networks often degrades the prediction accuracy, (3) that the proposed decaying weight method leads to higher prediction accuracy than can be achieved by observing all records of communication and simply using them unmodified, and (4) that the prediction accuracy for face-to-face behavioral networks is relatively high compared to that for non-social networks, but not as high as for other types of social networks. PMID:24339956

Conflict Probability Estimation for Free Flight

DOT National Transportation Integrated Search

1996-01-01

The safety and efficiency of free flight will benefit from automated conflict : prediction and resolution advisories. Conflict prediction is based on : trajectory prediction and is less certain the farther in advance the prediction, : however. An est...

Advancement of proprotor technology. Task 2: Wind-tunnel test results

NASA Technical Reports Server (NTRS)

1971-01-01

An advanced-design 25-foot-diameter flightworthy proprotor was tested in the NASA-Ames Large-Scale Wind Tunnel. These tests, have verified and confirmed the theory and design solutions developed as part of the Army Composite Aircraft Program. This report presents the test results and compares them with theoretical predictions. During performance tests, the results met or exceeded predictions. Hover thrust 15 percent greater than the predicted maximum was measured. In airplane mode, propulsive efficiencies (some of which exceeded 90 percent) agreed with theory.

Taking Poseidon's Measure from Space: Advances in our Understanding of the Ocean

NASA Astrophysics Data System (ADS)

Avery, S. K.

2017-12-01

In many ways the ocean defines our planet and makes it livable. It provides marine resources and ecosystem services that are critical to a sustainable society. Today we understand that there is a growing need to predict, manage, and adapt to changes on our planet - changes that occur not only in the atmosphere but also in the ocean. Over the last 40 years remarkable advances in measuring key ocean quantities have been made - through the development of new satellite technologies and successful missions as well as through in-situ observing systems enabled by advances in robotics, communications, navigation, and sensors. Ocean science (and atmospheric science) is a science of numbers, imaging, and numerical models. Predictability of the ocean is tied to the scale of variability in space and time. Satellite observations have spectacularly showed us the incredible structure and variability of the ocean. It has been the combination of satellites and in-situ sensors that have allowed us to advance understanding and prediction. This presentation will highlight some of the key scientific advances that have been enabled by satellites.

Advanced propeller noise prediction in the time domain

NASA Technical Reports Server (NTRS)

Farassat, F.; Dunn, M. H.; Spence, P. L.

1992-01-01

The time domain code ASSPIN gives acousticians a powerful technique of advanced propeller noise prediction. Except for nonlinear effects, the code uses exact solutions of the Ffowcs Williams-Hawkings equation with exact blade geometry and kinematics. By including nonaxial inflow, periodic loading noise, and adaptive time steps to accelerate computer execution, the development of this code becomes complete.

Data Mining and Predictive Modeling in Institutional Advancement: How Ten Schools Found Success. Technical Report

ERIC Educational Resources Information Center

Luperchio, Dan

2009-01-01

This technical report, produced in partnership by the Council for Advancement and Support of Education (CASE) and SPSS Inc., explores the promise of data mining alumni records at educational institutions. Working with individual alumni records from The Johns Hopkins Zanvyl Krieger School of Arts and Sciences, a predictive regression model is…

A risk score for the prediction of advanced age-related macular degeneration: Development and validation in 2 prospective cohorts

USDA-ARS?s Scientific Manuscript database

We aimed to develop an eye specific model which used readily available information to predict risk for advanced age-related macular degeneration (AMD). We used the Age-Related Eye Disease Study (AREDS) as our training dataset, which consisted of the 4,507 participants (contributing 1,185 affected v...

Potential biomarker panels in overall breast cancer management: advancements by multilevel diagnostics.

PubMed

Girotra, Shantanu; Yeghiazaryan, Kristina; Golubnitschaja, Olga

2016-09-01

Breast cancer (BC) prevalence has reached an epidemic scale with half a million deaths annually. Current deficits in BC management include predictive and preventive approaches, optimized screening programs, individualized patient profiling, highly sensitive detection technologies for more precise diagnostics and therapy monitoring, individualized prediction and effective treatment of BC metastatic disease. To advance BC management, paradigm shift from delayed to predictive, preventive and personalized medical services is essential. Corresponding step forwards requires innovative multilevel diagnostics procuring specific panels of validated biomarkers. Here, we discuss current instrumental advancements including genomics, proteomics, epigenetics, miRNA, metabolomics, circulating tumor cells and cancer stem cells with a focus on biomarker discovery and multilevel diagnostic panels. A list of the recommended biomarker candidates is provided.

A prospective study of endothelial activation biomarkers, including plasma angiopoietin-1 and angiopoietin-2, in Kenyan women initiating antiretroviral therapy.

PubMed

Graham, Susan M; Rajwans, Nimerta; Tapia, Kenneth A; Jaoko, Walter; Estambale, Benson B A; McClelland, R Scott; Overbaugh, Julie; Liles, W Conrad

2013-06-04

HIV-1-related inflammation is associated with increased levels of biomarkers of vascular adhesion and endothelial activation, and may increase production of the inflammatory protein angiopoietin-2 (ANG-2), an adverse prognostic biomarker in severe systemic infection. We hypothesized that antiretroviral therapy (ART) initiation would decrease endothelial activation, reducing plasma levels of ANG-2. Antiretroviral-naïve Kenyan women with advanced HIV infection were followed prospectively. Endothelial activation biomarkers including soluble intercellular adhesion molecule-1 (ICAM-1), vascular adhesion molecule-1 (VCAM-1), and E-selectin, and plasma ANG-2 and angiopoietin-1 (ANG-1) were tested in stored plasma samples from 0, 6, and 12 months after ART initiation. We used Wilcoxon matched-pairs signed rank tests to compare endothelial activation biomarkers across time-points, generalized estimating equations to analyze associations with change in log10-transformed biomarkers after ART initiation, and Cox proportional-hazards regression to analyze associations with mortality. The 102 HIV-1-seropositive women studied had advanced infection (median CD4 count, 124 cells/μL). Soluble ICAM-1 and plasma ANG-2 levels decreased at both time-points after ART initiation, with concomitant increases in the beneficial protein ANG-1. Higher ANG-2 levels after ART initiation were associated with higher plasma HIV-1 RNA, oral contraceptive pill use, pregnancy, severe malnutrition, and tuberculosis. Baseline ANG-2 levels were higher among five women who died after ART initiation than among women who did not (median 2.85 ng/mL [inter-quartile range (IQR) 2.47-5.74 ng/mL] versus median 1.32 ng/mL [IQR 0.35-2.18 ng/mL], p = 0.01). Both soluble ICAM-1 and plasma ANG-2 levels predicted mortality after ART initiation. Biomarkers of endothelial activation decreased after ART initiation in women with advanced HIV-1 infection. Changes in plasma ANG-2 were associated with HIV-1 RNA levels over 12 months of follow-up. Soluble ICAM-1 and plasma ANG-2 levels represent potential biomarkers for adverse outcomes in advanced HIV-1 infection.

Advanced Technology Composite Fuselage-Structural Performance

NASA Technical Reports Server (NTRS)

Walker, T. H.; Minguet, P. J.; Flynn, B. W.; Carbery, D. J.; Swanson, G. D.; Ilcewicz, L. B.

1997-01-01

Boeing is studying the technologies associated with the application of composite materials to commercial transport fuselage structure under the NASA-sponsored contracts for Advanced Technology Composite Aircraft Structures (ATCAS) and Materials Development Omnibus Contract (MDOC). This report addresses the program activities related to structural performance of the selected concepts, including both the design development and subsequent detailed evaluation. Design criteria were developed to ensure compliance with regulatory requirements and typical company objectives. Accurate analysis methods were selected and/or developed where practical, and conservative approaches were used where significant approximations were necessary. Design sizing activities supported subsequent development by providing representative design configurations for structural evaluation and by identifying the critical performance issues. Significant program efforts were directed towards assessing structural performance predictive capability. The structural database collected to perform this assessment was intimately linked to the manufacturing scale-up activities to ensure inclusion of manufacturing-induced performance traits. Mechanical tests were conducted to support the development and critical evaluation of analysis methods addressing internal loads, stability, ultimate strength, attachment and splice strength, and damage tolerance. Unresolved aspects of these performance issues were identified as part of the assessments, providing direction for future development.

Pretreatment tables predicting pathologic stage of locally advanced prostate cancer.

PubMed

Joniau, Steven; Spahn, Martin; Briganti, Alberto; Gandaglia, Giorgio; Tombal, Bertrand; Tosco, Lorenzo; Marchioro, Giansilvio; Hsu, Chao-Yu; Walz, Jochen; Kneitz, Burkhard; Bader, Pia; Frohneberg, Detlef; Tizzani, Alessandro; Graefen, Markus; van Cangh, Paul; Karnes, R Jeffrey; Montorsi, Francesco; van Poppel, Hein; Gontero, Paolo

2015-02-01

Pretreatment tables for the prediction of pathologic stage have been published and validated for localized prostate cancer (PCa). No such tables are available for locally advanced (cT3a) PCa. To construct tables predicting pathologic outcome after radical prostatectomy (RP) for patients with cT3a PCa with the aim to help guide treatment decisions in clinical practice. This was a multicenter retrospective cohort study including 759 consecutive patients with cT3a PCa treated with RP between 1987 and 2010. Retropubic RP and pelvic lymphadenectomy. Patients were divided into pretreatment prostate-specific antigen (PSA) and biopsy Gleason score (GS) subgroups. These parameters were used to construct tables predicting pathologic outcome and the presence of positive lymph nodes (LNs) after RP for cT3a PCa using ordinal logistic regression. In the model predicting pathologic outcome, the main effects of biopsy GS and pretreatment PSA were significant. A higher GS and/or higher PSA level was associated with a more unfavorable pathologic outcome. The validation procedure, using a repeated split-sample method, showed good predictive ability. Regression analysis also showed an increasing probability of positive LNs with increasing PSA levels and/or higher GS. Limitations of the study are the retrospective design and the long study period. These novel tables predict pathologic stage after RP for patients with cT3a PCa based on pretreatment PSA level and biopsy GS. They can be used to guide decision making in men with locally advanced PCa. Our study might provide physicians with a useful tool to predict pathologic stage in locally advanced prostate cancer that might help select patients who may need multimodal treatment. Copyright © 2014 European Association of Urology. Published by Elsevier B.V. All rights reserved.

National Centers for Environmental Prediction

Science.gov Websites

advance prediction skills for monsoon variability, improved understanding of Indian Ocean-Atmosphere variability and predictability Coordination on research to improve: understanding of ocean processes in the

Mutagenicity in a Molecule: Identification of Core Structural Features of Mutagenicity Using a Scaffold Analysis

PubMed Central

Hsu, Kuo-Hsiang; Su, Bo-Han; Tu, Yi-Shu; Lin, Olivia A.; Tseng, Yufeng J.

2016-01-01

With advances in the development and application of Ames mutagenicity in silico prediction tools, the International Conference on Harmonisation (ICH) has amended its M7 guideline to reflect the use of such prediction models for the detection of mutagenic activity in early drug safety evaluation processes. Since current Ames mutagenicity prediction tools only focus on functional group alerts or side chain modifications of an analog series, these tools are unable to identify mutagenicity derived from core structures or specific scaffolds of a compound. In this study, a large collection of 6512 compounds are used to perform scaffold tree analysis. By relating different scaffolds on constructed scaffold trees with Ames mutagenicity, four major and one minor novel mutagenic groups of scaffold are identified. The recognized mutagenic groups of scaffold can serve as a guide for medicinal chemists to prevent the development of potentially mutagenic therapeutic agents in early drug design or development phases, by modifying the core structures of mutagenic compounds to form non-mutagenic compounds. In addition, five series of substructures are provided as recommendations, for direct modification of potentially mutagenic scaffolds to decrease associated mutagenic activities. PMID:26863515

Comparison of five in vitro bioassays to measure estrogenic activity in environmental waters.

PubMed

Leusch, Frederic D L; de Jager, Christiaan; Levi, Yves; Lim, Richard; Puijker, Leo; Sacher, Frank; Tremblay, Louis A; Wilson, Vickie S; Chapman, Heather F

2010-05-15

Bioassays are well established in the pharmaceutical industry and single compound analysis, but there is still uncertainty about their usefulness in environmental monitoring. We compared the responses of five bioassays designed to measure estrogenic activity (the yeast estrogen screen, ER-CALUX, MELN, T47D-KBluc, and E-SCREEN assays) and chemical analysis on extracts from four different water sources (groundwater, raw sewage, treated sewage, and river water). All five bioassays displayed similar trends and there was good agreement with analytical chemistry results. The data from the ER-CALUX and E-SCREEN bioassays were robust and predictable, and well-correlated with predictions from chemical analysis. The T47D-KBluc appeared likewise promising, but with a more limited sample size it was less compelling. The YES assay was less sensitive than the other assays by an order of magnitude, which resulted in a larger number of nondetects. The MELN assay was less predictable, although the possibility that this was due to laboratory-specific difficulties cannot be discounted. With standardized bioassay data analysis and consistency of operating protocols, bioanalytical tools are a promising advance in the development of a tiered approach to environmental water quality monitoring.

Maxillary movement in distraction osteogenesis using internal devices in cleft palate patients.

PubMed

Tomita, Daisuke; Omura, Susumu; Ozaki, Shusaku; Shimazaki, Kazuo; Fukuyama, Eiji; Tohnai, Iwai; Torikai, Katsuyuki

2011-03-01

The purpose of this cephalometric study was to compare the actual movement with the planned movement of the maxilla by using internal maxillary distraction in cleft lip and palate patients. Twelve patients, including eight with unilateral and four with bilateral cleft lip and palate, underwent maxillary advancement with internal maxillary distractors. Lateral cephalometric radiographs obtained preoperatively, predistraction, and postdistraction were used for analysis. The movement of the maxilla, angular change of the internal devices and rotation of the mandible were measured at each stage, and the planned vector of advancement predicted from the placement vector of the distractors was compared with the actual vector. Internal maxillary distractors were rotated in a clockwise direction during the distraction period. The angular change of the distractors was 7.7°. The amount of actual advancement at anterior nasal spine with distraction was 6.3 mm, which represented about 70% of the distance of activation of distraction. The actual advanced vector at anterior nasal spine was 9.7° smaller than the planned vector. The mandible underwent a clockwise rotation of 3.5°. In the internal distraction technique, the maxilla was advanced inferiorly to the planned vector and with a slight clockwise rotation. These results are useful for surgical planning when using internal distractors.

Efficient Modeling and Active Learning Discovery of Biological Responses

PubMed Central

Naik, Armaghan W.; Kangas, Joshua D.; Langmead, Christopher J.; Murphy, Robert F.

2013-01-01

High throughput and high content screening involve determination of the effect of many compounds on a given target. As currently practiced, screening for each new target typically makes little use of information from screens of prior targets. Further, choices of compounds to advance to drug development are made without significant screening against off-target effects. The overall drug development process could be made more effective, as well as less expensive and time consuming, if potential effects of all compounds on all possible targets could be considered, yet the cost of such full experimentation would be prohibitive. In this paper, we describe a potential solution: probabilistic models that can be used to predict results for unmeasured combinations, and active learning algorithms for efficiently selecting which experiments to perform in order to build those models and determining when to stop. Using simulated and experimental data, we show that our approaches can produce powerful predictive models without exhaustive experimentation and can learn them much faster than by selecting experiments at random. PMID:24358322

The ORF1 Protein Encoded by LINE-1: Structure and Function During L1 Retrotransposition

PubMed Central

Martin, Sandra L.

2006-01-01

LINE-1, or L1 is an autonomous non-LTR retrotransposon in mammals. Retrotransposition requires the function of the two, L1-encoded polypeptides, ORF1p and ORF2p. Early recognition of regions of homology between the predicted amino acid sequence of ORF2 and known endonuclease and reverse transcriptase enzymes led to testable hypotheses regarding the function of ORF2p in retrotransposition. As predicted, ORF2p has been demonstrated to have both endonuclease and reverse transcriptase activities. In contrast, no homologs of known function have contributed to our understanding of the function of ORF1p during retrotransposition. Nevertheless, significant advances have been made such that we now know that ORF1p is a high affinity RNA binding protein that forms a ribonucleoprotein particle together with L1 RNA. Furthermore, ORF1p is a nucleic acid chaperone and this nucleic acid chaperone activity is required for L1 retrotransposition. PMID:16877816

Activated neuro-oxidative and neuro-nitrosative pathways at the end of term are associated with inflammation and physio-somatic and depression symptoms, while predicting outcome characteristics in mother and baby.

PubMed

Roomruangwong, Chutima; Barbosa, Decio Sabbatini; Matsumoto, Andressa Keiko; Nogueira, André de Souza; Kanchanatawan, Buranee; Sirivichayakul, Sunee; Carvalho, André F; Duleu, Sebastien; Geffard, Michel; Moreira, Estefania Gastaldello; Maes, Michael

2017-12-01

To examine oxidative & nitrosative stress (O&NS) biomarkers at the end of term in relation to perinatal affective symptoms, neuro-immune biomarkers and pregnancy-related outcome variables. We measured plasma advanced oxidation protein products (AOPP), nitric oxide metabolites (NOx), total radical trapping antioxidant parameter (TRAP), -sulfhydryl (-SH), peroxides (LOOH) and paraoxonase (PON)1 activity in pregnant women with and without prenatal depression and non-pregnant controls. Pregnancy is accompanied by significantly increased AOPP and NOx, and lowered TRAP, -SH and LOOH. Increased O&NS and lowered LOOH and -SH levels are associated with prenatal depressive and physio-somatic symptoms (fatigue, pain, dyspepsia, gastro-intestinal symptoms). Increased AOPP and NOx are significantly associated with lowered -SH, TRAP and zinc, and with increased haptoglobin and C-reactive protein levels. Increased O&NS and lowered TRAP and PON 1 activity, at the end of term predict mother (e.g. hyperpigmentation, labor duration, caesarian section, cord length, breast milk flow) and baby (e.g. sleep and feeding problems) outcome characteristics. Pregnancy is accompanied by interrelated signs of O&NS, lowered antioxidant defenses and activated neuro-immune pathways. Increased O&NS at the end of term is associated with perinatal depressive and physio-somatic symptoms and may predict obstetric and behavioral complications in mother and baby. Copyright © 2017 Elsevier B.V. All rights reserved.

Integrating discrete stochastic models and single-cell experiments to infer predictive models of MAPK-induced transcription dynamics

NASA Astrophysics Data System (ADS)

Munsky, Brian

2015-03-01

MAPK signal-activated transcription plays central roles in myriad biological processes including stress adaptation responses and cell fate decisions. Recent single-cell and single-molecule experiments have advanced our ability to quantify the spatial, temporal, and stochastic fluctuations for such signals and their downstream effects on transcription regulation. This talk explores how integrating such experiments with discrete stochastic computational analyses can yield quantitative and predictive understanding of transcription regulation in both space and time. We use single-molecule mRNA fluorescence in situ hybridization (smFISH) experiments to reveal locations and numbers of multiple endogenous mRNA species in 100,000's of individual cells, at different times and under different genetic and environmental perturbations. We use finite state projection methods to precisely and efficiently compute the full joint probability distributions of these mRNA, which capture measured spatial, temporal and correlative fluctuations. By combining these experimental and computational tools with uncertainty quantification, we systematically compare models of varying complexity and select those which give optimally precise and accurate predictions in new situations. We use these tools to explore two MAPK-activated gene regulation pathways. In yeast adaptation to osmotic shock, we analyze Hog1 kinase activation of transcription for three different genes STL1 (osmotic stress), CTT1 (oxidative stress) and HSP12 (heat shock). In human osteosarcoma cells under serum induction, we analyze ERK activation of c-Fos transcription.

Seasonal forecasting of fire over Kalimantan, Indonesia

NASA Astrophysics Data System (ADS)

Spessa, A. C.; Field, R. D.; Pappenberger, F.; Langner, A.; Englhart, S.; Weber, U.; Stockdale, T.; Siegert, F.; Kaiser, J. W.; Moore, J.

2015-03-01

Large-scale fires occur frequently across Indonesia, particularly in the southern region of Kalimantan and eastern Sumatra. They have considerable impacts on carbon emissions, haze production, biodiversity, health, and economic activities. In this study, we demonstrate that severe fire and haze events in Indonesia can generally be predicted months in advance using predictions of seasonal rainfall from the ECMWF System 4 coupled ocean-atmosphere model. Based on analyses of long, up-to-date series observations on burnt area, rainfall, and tree cover, we demonstrate that fire activity is negatively correlated with rainfall and is positively associated with deforestation in Indonesia. There is a contrast between the southern region of Kalimantan (high fire activity, high tree cover loss, and strong non-linear correlation between observed rainfall and fire) and the central region of Kalimantan (low fire activity, low tree cover loss, and weak, non-linear correlation between observed rainfall and fire). The ECMWF seasonal forecast provides skilled forecasts of burnt and fire-affected area with several months lead time explaining at least 70% of the variance between rainfall and burnt and fire-affected area. Results are strongly influenced by El Niño years which show a consistent positive bias. Overall, our findings point to a high potential for using a more physical-based method for predicting fires with several months lead time in the tropics rather than one based on indexes only. We argue that seasonal precipitation forecasts should be central to Indonesia's evolving fire management policy.

Motor Development and Physical Activity: A Longitudinal Discordant Twin-Pair Study.

PubMed

Aaltonen, Sari; Latvala, Antti; Rose, Richard J; Pulkkinen, Lea; Kujala, Urho M; Kaprio, Jaakko; Silventoinen, Karri

2015-10-01

Previous longitudinal research suggests that motor proficiency in early life predicts physical activity in adulthood. Familial effects including genetic and environmental factors could explain the association, but no long-term follow-up studies have taken into account potential confounding by genetic and social family background. The present twin study investigated whether childhood motor skill development is associated with leisure-time physical activity levels in adulthood independent of family background. Altogether, 1550 twin pairs from the FinnTwin12 study and 1752 twin pairs from the FinnTwin16 study were included in the analysis. Childhood motor development was assessed by the parents' report of whether one of the co-twins had been ahead of the other in different indicators of motor skill development in childhood. Leisure-time physical activity (MET·h·d) was self-reported by the twins in young adulthood and adulthood. Statistical analyses included conditional and ordinary linear regression models within twin pairs. Using all activity-discordant twin pairs, the within-pair difference in a sum score of motor development in childhood predicted the within-pair difference in the leisure-time physical activity level in young adulthood (P < 0.001). Within specific motor development indicators, learning to stand unaided earlier in infancy predicted higher leisure-time MET values in young adulthood statistically significantly in both samples (FinnTwin12, P = 0.02; and FinnTwin16, P = 0.001) and also in the pooled data set of the FinnTwin12 and FinnTwin16 studies (P < 0.001). Having been more agile than the co-twin as a child predicted higher leisure-time MET values up to adulthood (P = 0.03). More advanced childhood motor development is associated with higher leisure-time MET values in young adulthood at least partly independent of family background in both men and women.

MOTOR DEVELOPMENT AND PHYSICAL ACTIVITY: A LONGITUDINAL DISCORDANT TWIN-PAIR STUDY

PubMed Central

Aaltonen, Sari; Latvala, Antti; Rose, Richard J.; Pulkkinen, Lea; Kujala, Urho M.; Kaprio, Jaakko; Silventoinen, Karri

2015-01-01

Introduction Previous longitudinal research suggests that motor proficiency in early life predicts physical activity in adulthood. Familial effects including genetic and environmental factors could explain the association, but no long-term follow-up studies have taken into account potential confounding by genetic and social family background. The present twin study investigated whether childhood motor skill development is associated with leisure-time physical activity levels in adulthood independent of family background. Methods Altogether, 1 550 twin pairs from the FinnTwin12 study and 1 752 twin pairs from the FinnTwin16 study were included in the analysis. Childhood motor development was assessed by the parents’ report of whether one of the co-twins had been ahead of the other in different indicators of motor skill development in childhood. Leisure-time physical activity (MET hours/day) was self-reported by the twins in young adulthood and adulthood. Statistical analyses included conditional and ordinary linear regression models within twin pairs. Results Using all activity-discordant twin pairs, the within-pair difference in a sum score of motor development in childhood predicted the within-pair difference in the leisure-time physical activity level in young adulthood (p<0.001). Within specific motor development indicators, learning to stand unaided earlier in infancy predicted higher leisure-time MET values in young adulthood statistically significantly in both samples (FinnTwin12 p=0.02, FinnTwin16 p=0.001) and also in the pooled dataset of the FinnTwin12 and FinnTwin16 studies (p<0.001). Having been more agile than the co-twin as a child predicted higher leisure-time MET values up to adulthood (p=0.03). Conclusions More advanced childhood motor development is associated with higher leisure-time MET values in young adulthood at least partly independent of family background, in both men and women. PMID:26378945

Integrated analysis of particle interactions at hadron colliders Report of research activities in 2010-2015

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nadolsky, Pavel M.

2015-08-31

The report summarizes research activities of the project ”Integrated analysis of particle interactions” at Southern Methodist University, funded by 2010 DOE Early Career Research Award DE-SC0003870. The goal of the project is to provide state-of-the-art predictions in quantum chromodynamics in order to achieve objectives of the LHC program for studies of electroweak symmetry breaking and new physics searches. We published 19 journal papers focusing on in-depth studies of proton structure and integration of advanced calculations from different areas of particle phenomenology: multi-loop calculations, accurate long-distance hadronic functions, and precise numerical programs. Methods for factorization of QCD cross sections were advancedmore » in order to develop new generations of CTEQ parton distribution functions (PDFs), CT10 and CT14. These distributions provide the core theoretical input for multi-loop perturbative calculations by LHC experimental collaborations. A novel ”PDF meta-analysis” technique was invented to streamline applications of PDFs in numerous LHC simulations and to combine PDFs from various groups using multivariate stochastic sampling of PDF parameters. The meta-analysis will help to bring the LHC perturbative calculations to the new level of accuracy, while reducing computational efforts. The work on parton distributions was complemented by development of advanced perturbative techniques to predict observables dependent on several momentum scales, including production of massive quarks and transverse momentum resummation at the next-to-next-to-leading order in QCD.« less

Applying Advanced Analytical Approaches to Characterize the Impact of Specific Clinical Gaps and Profiles on the Management of Rheumatoid Arthritis.

PubMed

Ruiz-Cordell, Karyn D; Joubin, Kathy; Haimowitz, Steven

2016-01-01

The goal of this study was to add a predictive modeling approach to the meta-analysis of continuing medical education curricula to determine whether this technique can be used to better understand clinical decision making. Using the education of rheumatologists on rheumatoid arthritis management as a model, this study demonstrates how the combined methodology has the ability to not only characterize learning gaps but also identify those proficiency areas that have the greatest impact on clinical behavior. The meta-analysis included seven curricula with 25 activities. Learners who identified as rheumatologists were evaluated across multiple learning domains, using a uniform methodology to characterize learning gains and gaps. A performance composite variable (called the treatment individualization and optimization score) was then established as a target upon which predictive analytics were conducted. Significant predictors of the target included items related to the knowledge of rheumatologists and confidence concerning 1) treatment guidelines and 2) tests that measure disease activity. In addition, a striking demographic predictor related to geographic practice setting was also identified. The results demonstrate the power of advanced analytics to identify key predictors that influence clinical behaviors. Furthermore, the ability to provide an expected magnitude of change if these predictors are addressed has the potential to substantially refine educational priorities to those drivers that, if targeted, will most effectively overcome clinical barriers and lead to the greatest success in achieving treatment goals.

Anti-Aß immunotherapy in Alzheimer's disease; relevance of transgenic mouse studies to clinical trials

PubMed Central

Wilcock, Donna M.; Colton, Carol A.

2009-01-01

Therapeutic approaches to the treatment of Alzheimer's disease are focused primarily on the Aß peptide which aggregates to form amyloid deposits in the brain. The amyloid hypothesis states that amyloid is the precipitating factor that results in the other pathologies of Alzheimer's, namely neurofibrillary tangles and neurodegeneration, as well as the clinical dementia. One such therapy that has attracted significant attention is anti-Aß immunotherapy. First described in 1999, immunotherapy uses anti-Aß antibodies to lower brain amyloid levels. Active immunization, in which Aß is combined with an adjuvant to stimulate an immune response producing antibodies and passive immunization, in which antibodies are directly injected, were shown to lower brain amyloid levels and improve cognition in multiple transgenic mouse models. Mechanisms of action were studied in these mice and revealed a complex set of mechanisms that depended on the type of antibody used. When active immunization advanced to clinical trials a subset of patients developed meningoencephalitis; an event not predicted in mouse studies. However, it was suspected that a T-cell response due to the type of adjuvant used was the cause of the meningoencephalitis and studies in mice indicated alternative methods of vaccination. Passive immunization has also advanced to phase III clinical trials on the basis of successful transgenic mouse studies. Reports from the active immunization clinical trial indicated that, indeed, amyloid levels in brain were reduced. While APP transgenic mouse models are useful in studying amyloid pathology these mice do not generate significant tau pathology or neuron loss. Continued development of new mouse models that do generate all of these pathologies will be critical in more accurately testing therapeutics and predicting the clinical outcome of such therapeutics. PMID:19096156

A Serum Protein Profile Predictive of the Resistance to Neoadjuvant Chemotherapy in Advanced Breast Cancers*

PubMed Central

Hyung, Seok-Won; Lee, Min Young; Yu, Jong-Han; Shin, Byunghee; Jung, Hee-Jung; Park, Jong-Moon; Han, Wonshik; Lee, Kyung-Min; Moon, Hyeong-Gon; Zhang, Hui; Aebersold, Ruedi; Hwang, Daehee; Lee, Sang-Won; Yu, Myeong-Hee; Noh, Dong-Young

2011-01-01

Prediction of the responses to neoadjuvant chemotherapy (NACT) can improve the treatment of patients with advanced breast cancer. Genes and proteins predictive of chemoresistance have been extensively studied in breast cancer tissues. However, noninvasive serum biomarkers capable of such prediction have been rarely exploited. Here, we performed profiling of N-glycosylated proteins in serum from fifteen advanced breast cancer patients (ten patients sensitive to and five patients resistant to NACT) to discover serum biomarkers of chemoresistance using a label-free liquid chromatography-tandem MS method. By performing a series of statistical analyses of the proteomic data, we selected thirteen biomarker candidates and tested their differential serum levels by Western blotting in 13 independent samples (eight patients sensitive to and five patients resistant to NACT). Among the candidates, we then selected the final set of six potential serum biomarkers (AHSG, APOB, C3, C9, CP, and ORM1) whose differential expression was confirmed in the independent samples. Finally, we demonstrated that a multivariate classification model using the six proteins could predict responses to NACT and further predict relapse-free survival of patients. In summary, global N-glycoproteome profile in serum revealed a protein pattern predictive of the responses to NACT, which can be further validated in large clinical studies. PMID:21799047

Using timing of ice retreat to predict timing of fall freeze-up in the Arctic

NASA Astrophysics Data System (ADS)

Stroeve, Julienne C.; Crawford, Alex D.; Stammerjohn, Sharon

2016-06-01

Reliable forecasts of the timing of sea ice advance are needed in order to reduce risks associated with operating in the Arctic as well as planning of human and environmental emergencies. This study investigates the use of a simple statistical model relating the timing of ice retreat to the timing of ice advance, taking advantage of the inherent predictive power supplied by the seasonal ice-albedo feedback and ocean heat uptake. Results show that using the last retreat date to predict the first advance date is applicable in some regions, such as Baffin Bay and the Laptev and East Siberian seas, where a predictive skill is found even after accounting for the long-term trend in both variables. Elsewhere, in the Arctic, there is some predictive skills depending on the year (e.g., Kara and Beaufort seas), but none in regions such as the Barents and Bering seas or the Sea of Okhotsk. While there is some suggestion that the relationship is strengthening over time, this may reflect that higher correlations are expected during periods when the underlying trend is strong.

A status of the Turbine Technology Team activities

NASA Technical Reports Server (NTRS)

Griffin, Lisa W.

1992-01-01

The recent activities of the Turbine Technology Team of the Consortium for Computational Fluid Dynamics (CFD) Application in Propulsion Technology is presented. The team consists of members from the government, industry, and universities. The goal of this team is to demonstrate the benefits to the turbine design process attainable through the application of CFD. This goal is to be achieved by enhancing and validating turbine design tools for improved loading and flowfield definition and loss prediction, and transferring the advanced technology to the turbine design process. In order to demonstrate the advantages of using CFD early in the design phase, the Space Transportation Main Engine (STME) turbines for the National Launch System (NLS) were chosen on which to focus the team's efforts. The Turbine Team activities run parallel to the STME design work.

Active Rack Isolation System Program and Technical Status

NASA Technical Reports Server (NTRS)

Bushnell, Glenn; Fialho, Ian; Allen, James; Quraishi, Naveed

2000-01-01

The Boeing Active Rack Isolation System (ARIS) is one of the means used to isolate acceleration-sensitive scientific experiments from structurally transmitted disturbances aboard the International Space Station. The presentation provides an overview of ARIS and technical issues associated with the development of the active control system. An overview of ARIS analytical models is presented along with recent isolation performance predictions made using these models. Issues associated with commanding and capturing ARIS data are discussed and possible future options based on the ARIS ISS Characterization Experiment (ICE) Payload On-orbit Processor (POP) are outlined. An overview of the ARIS-ICE experiment scheduled to fly on ISS Flight 6A is presented. The presentation concludes with a discussion of recent- developmental work that includes passive rack damping, umbilical redesigns and advanced multivariable control design methods.

Prospective Study of the Evolution of Blood Lymphoid Immune Parameters during Dacarbazine Chemotherapy in Metastatic and Locally Advanced Melanoma Patients

PubMed Central

Vabres, Pierre; Dalac, Sophie; Jeudy, Geraldine; Bel, Blandine; Apetoh, Lionel; Ghiringhelli, François

2014-01-01

Background The importance of immune responses in the control of melanoma growth is well known. However, the implication of these antitumor immune responses in the efficacy of dacarbazine, a cytotoxic drug classically used in the treatment of melanoma, remains poorly understood in humans. Methods In this prospective observational study, we performed an immunomonitoring of eleven metastatic or locally advanced patients treated with dacarbazine as a first line of treatment. We assessed by flow cytometry lymphoid populations and their activation state; we also isolated NK cells to perform in vitro cytotoxicity tests. Results We found that chemotherapy induces lymphopenia and that a significantly higher numbers of naïve CD4+ T cells and lower proportion of Treg before chemotherapy are associated with disease control after dacarbazine treatment. Interestingly, NK cell cytotoxicity against dacarbazine-pretreated melanoma cells is only observed in NK cells from patients who achieved disease control. Conclusion Together, our data pinpoint that some immune factors could help to predict the response of melanoma patients to dacarbazine. Future larger scale studies are warranted to test their validity as prediction markers. PMID:25170840

Identification of alsterpaullone as a novel small molecule inhibitor to target group 3 medulloblastoma.

PubMed

Faria, Claudia C; Agnihotri, Sameer; Mack, Stephen C; Golbourn, Brian J; Diaz, Roberto J; Olsen, Samantha; Bryant, Melissa; Bebenek, Matthew; Wang, Xin; Bertrand, Kelsey C; Kushida, Michelle; Head, Renee; Clark, Ian; Dirks, Peter; Smith, Christian A; Taylor, Michael D; Rutka, James T

2015-08-28

Advances in the molecular biology of medulloblastoma revealed four genetically and clinically distinct subgroups. Group 3 medulloblastomas are characterized by frequent amplifications of the oncogene MYC, a high incidence of metastasis, and poor prognosis despite aggressive therapy. We investigated several potential small molecule inhibitors to target Group 3 medulloblastomas based on gene expression data using an in silico drug screen. The Connectivity Map (C-MAP) analysis identified piperlongumine as the top candidate drug for non-WNT medulloblastomas and the cyclin-dependent kinase (CDK) inhibitor alsterpaullone as the compound predicted to have specific antitumor activity against Group 3 medulloblastomas. To validate our findings we used these inhibitors against established Group 3 medulloblastoma cell lines. The C-MAP predicted drugs reduced cell proliferation in vitro and increased survival in Group 3 medulloblastoma xenografts. Alsterpaullone had the highest efficacy in Group 3 medulloblastoma cells. Genomic profiling of Group 3 medulloblastoma cells treated with alsterpaullone confirmed inhibition of cell cycle-related genes, and down-regulation of MYC. Our results demonstrate the preclinical efficacy of using a targeted therapy approach for Group 3 medulloblastomas. Specifically, we provide rationale for advancing alsterpaullone as a targeted therapy in Group 3 medulloblastoma.

Bayesian data assimilation provides rapid decision support for vector-borne diseases

PubMed Central

Jewell, Chris P.; Brown, Richard G.

2015-01-01

Predicting the spread of vector-borne diseases in response to incursions requires knowledge of both host and vector demographics in advance of an outbreak. Although host population data are typically available, for novel disease introductions there is a high chance of the pathogen using a vector for which data are unavailable. This presents a barrier to estimating the parameters of dynamical models representing host–vector–pathogen interaction, and hence limits their ability to provide quantitative risk forecasts. The Theileria orientalis (Ikeda) outbreak in New Zealand cattle demonstrates this problem: even though the vector has received extensive laboratory study, a high degree of uncertainty persists over its national demographic distribution. Addressing this, we develop a Bayesian data assimilation approach whereby indirect observations of vector activity inform a seasonal spatio-temporal risk surface within a stochastic epidemic model. We provide quantitative predictions for the future spread of the epidemic, quantifying uncertainty in the model parameters, case infection times and the disease status of undetected infections. Importantly, we demonstrate how our model learns sequentially as the epidemic unfolds and provide evidence for changing epidemic dynamics through time. Our approach therefore provides a significant advance in rapid decision support for novel vector-borne disease outbreaks. PMID:26136225

Using bacterial biomarkers to identify early indicators of cystic fibrosis pulmonary exacerbation onset

PubMed Central

Rogers, Geraint B; Hoffman, Lucas R; Johnson, Matt W; Mayer-Hamblett, Nicole; Schwarze, Jürgen; Carroll, Mary P; Bruce, Kenneth D

2011-01-01

Acute periods of pulmonary exacerbation are the single most important cause of morbidity in cystic fibrosis patients, and may be associated with a loss of lung function. Intervening prior to the onset of a substantially increased inflammatory response may limit the associated damage to the airways. While a number of biomarker assays based on inflammatory markers have been developed, providing useful and important measures of disease during these periods, such factors are typically only elevated once the process of exacerbation has been initiated. Identifying biomarkers that can predict the onset of pulmonary exacerbation at an early stage would provide an opportunity to intervene before the establishment of a substantial immune response, with major implications for the advancement of cystic fibrosis care. The precise triggers of pulmonary exacerbation remain to be determined; however, the majority of models relate to the activity of microbes present in the patient's lower airways of cystic fibrosis. Advances in diagnostic microbiology now allow for the examination of these complex systems at a level likely to identify factors on which biomarker assays can be based. In this article, we discuss key considerations in the design and testing of assays that could predict pulmonary exacerbations. PMID:21405970

Computational methods in the prediction of advanced subsonic and supersonic propeller induced noise: ASSPIN users' manual

NASA Technical Reports Server (NTRS)

Dunn, M. H.; Tarkenton, G. M.

1992-01-01

This document describes the computational aspects of propeller noise prediction in the time domain and the use of high speed propeller noise prediction program ASSPIN (Advanced Subsonic and Supersonic Propeller Induced Noise). These formulations are valid in both the near and far fields. Two formulations are utilized by ASSPIN: (1) one is used for subsonic portions of the propeller blade; and (2) the second is used for transonic and supersonic regions on the blade. Switching between the two formulations is done automatically. ASSPIN incorporates advanced blade geometry and surface pressure modelling, adaptive observer time grid strategies, and contains enhanced numerical algorithms that result in reduced computational time. In addition, the ability to treat the nonaxial inflow case has been included.

Compensatory but not anticipatory adjustments are altered in older adults during lateral postural perturbations.

PubMed

Claudino, Renato; dos Santos, Eloá C C; Santos, Marcio J

2013-08-01

This study investigated anticipatory postural adjustments (APAs) and compensatory postural adjustments (CPAs) and their relationship in older adults during lateral postural perturbations. Unpredictable and predictable postural disturbances were induced by a swinging pendulum that impacted at the shoulder level of two groups of older adults, non-fallers (20) and fallers (20), and in a group of young control subjects (20). The electromyographic (EMG) activity of the postural muscles and the center of pressure (COP) displacement were recorded and quantified within the time intervals typical for APAs and CPAs. Both groups of older adults (non-fallers and fallers) showed higher magnitude of EMG activity in the lateral muscles and increased COP displacement, particularly, during the CPAs time interval when compared to the young group. Older adults, however, were able to change the electrical activity of the muscles during the predictable task by generating APAs with similar magnitudes of those found in young subjects. Compensatory but not anticipatory adjustments are altered in older adults during predictable lateral postural perturbations. These findings provide new data on the role of APAs and CPAs in their relationship in older adults during external lateral perturbations and may advance current rehabilitative management strategies to improve balance control in older individuals. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Linear free energy relationships between aqueous phase hydroxyl radical reaction rate constants and free energy of activation.

PubMed

Minakata, Daisuke; Crittenden, John

2011-04-15

The hydroxyl radical (HO(•)) is a strong oxidant that reacts with electron-rich sites on organic compounds and initiates complex radical chain reactions in aqueous phase advanced oxidation processes (AOPs). Computer based kinetic modeling requires a reaction pathway generator and predictions of associated reaction rate constants. Previously, we reported a reaction pathway generator that can enumerate the most important elementary reactions for aliphatic compounds. For the reaction rate constant predictor, we develop linear free energy relationships (LFERs) between aqueous phase literature-reported HO(•) reaction rate constants and theoretically calculated free energies of activation for H-atom abstraction from a C-H bond and HO(•) addition to alkenes. The theoretical method uses ab initio quantum mechanical calculations, Gaussian 1-3, for gas phase reactions and a solvation method, COSMO-RS theory, to estimate the impact of water. Theoretically calculated free energies of activation are found to be within approximately ±3 kcal/mol of experimental values. Considering errors that arise from quantum mechanical calculations and experiments, this should be within the acceptable errors. The established LFERs are used to predict the HO(•) reaction rate constants within a factor of 5 from the experimental values. This approach may be applied to other reaction mechanisms to establish a library of rate constant predictions for kinetic modeling of AOPs.

The discriminatory capability of existing scores to predict advanced colorectal neoplasia: a prospective colonoscopy study of 5,899 screening participants.

PubMed

Wong, Martin C S; Ching, Jessica Y L; Ng, Simpson; Lam, Thomas Y T; Luk, Arthur K C; Wong, Sunny H; Ng, Siew C; Ng, Simon S M; Wu, Justin C Y; Chan, Francis K L; Sung, Joseph J Y

2016-02-03

We evaluated the performance of seven existing risk scoring systems in predicting advanced colorectal neoplasia in an asymptomatic Chinese cohort. We prospectively recruited 5,899 Chinese subjects aged 50-70 years in a colonoscopy screening programme(2008-2014). Scoring systems under evaluation included two scoring tools from the US; one each from Spain, Germany, and Poland; the Korean Colorectal Screening(KCS) scores; and the modified Asia Pacific Colorectal Screening(APCS) scores. The c-statistics, sensitivity, specificity, positive predictive values(PPVs), and negative predictive values(NPVs) of these systems were evaluated. The resources required were estimated based on the Number Needed to Screen(NNS) and the Number Needed to Refer for colonoscopy(NNR). Advanced neoplasia was detected in 364 (6.2%) subjects. The German system referred the least proportion of subjects (11.2%) for colonoscopy, whilst the KCS scoring system referred the highest (27.4%). The c-statistics of all systems ranged from 0.56-0.65, with sensitivities ranging from 0.04-0.44 and specificities from 0.74-0.99. The modified APCS scoring system had the highest c-statistics (0.65, 95% C.I. 0.58-0.72). The NNS (12-19) and NNR (5-10) were similar among the scoring systems. The existing scoring systems have variable capability to predict advanced neoplasia among asymptomatic Chinese subjects, and further external validation should be performed.

Effects of Predictability of Load Magnitude on the Response of the Flexor Digitorum Superficialis to a Sudden Fingers Extension

PubMed Central

Aimola, Ettore; Valle, Maria Stella; Casabona, Antonino

2014-01-01

Muscle reflexes, evoked by opposing a sudden joint displacement, may be modulated by several factors associated with the features of the mechanical perturbation. We investigated the variations of muscle reflex response in relation to the predictability of load magnitude during a reactive grasping task. Subjects were instructed to flex the fingers 2–5 very quickly after a stretching was exerted by a handle pulled by loads of 750 or 1250 g. Two blocks of trials, one for each load (predictable condition), and one block of trials with a randomized distribution of the loads (unpredictable condition) were performed. Kinematic data were collected by an electrogoniometer attached to the middle phalanx of the digit III while the electromyography of the Flexor Digitorum Superficialis muscle was recorded by surface electrodes. For each trial we measured the kinematics of the finger angular rotation, the latency of muscle response and the level of muscle activation recorded below 50 ms (short-latency reflex), between 50 and 100 ms (long-latency reflex) and between 100 and 140 ms (initial portion of voluntary response) from the movement onset. We found that the latency of the muscle response lengthened from predictable (35.5±1.3 ms for 750 g and 35.5±2.5 ms for 1250 g) to unpredictable condition (43.6±1.3 ms for 750 g and 40.9±2.1 ms for 1250 g) and the level of muscle activation increased with load magnitude. The parallel increasing of muscle activation and load magnitude occurred within the window of the long-latency reflex during the predictable condition, and later, at the earliest portion of the voluntary response, in the unpredictable condition. Therefore, these results indicate that when the amount of an upcoming perturbation is known in advance, the muscle response improves, shortening the latency and modulating the muscle activity in relation to the mechanical demand. PMID:25271638

Studies in geophysics: The Earth's electrical environment

NASA Astrophysics Data System (ADS)

The Earth is electrified. Between the surface and the outer reaches of the atmosphere, there is a global circuit that is maintained by worldwide thunderstorm activity and by upper atmospheric dynamo processes. The highest voltages approach a billion volts and are generated within thunderclouds, where lightning is a visual display of the cloud's electrical nature. The largest currents in the circuit, approaching a million amperes, are associated with the aurora. Because there have been significant advances in understanding many of the component parts of the global electric circuit (lightning, cloud electrification, electrical processes in specific atmospheric regions, and telluric currents), a principal research challenge is to understand how these components interact to shape the global circuit. Increased basic understanding in this field has many potential practical applications, including lightning protection, the design of advanced aircraft and spacecraft, and improvements in weather prediction.

Operational Real-time Forecast of MeV Electrons at Geosynchronous Orbit Based on ACE and GOES-10 Measurements

NASA Astrophysics Data System (ADS)

Li, X.; Temerin, M. A.; Monk, S.; Baker, D. N.; Reeves, G. D.

2002-05-01

The MeV electrons, also known as `killer electrons', have a deleterious impact on satellites through deep dielectric charging and the bodies of astronauts through radiation damage during extravehicular activity. Using a recently developed model based on the standard radial diffusion equation [Li et al., 2001], we show that the intensity of these MeV electrons at geosynchronous orbit can be quantitatively predicted 1-2 days in advance given knowledge of the solar wind. Our current model is operating in real-time, using real-time data from ACE and GOES-10, to make forecast of >2 MeV eletrons at geosynchronous orbit up to 48 hours in advance, the results are available on the web, currently updated every two hours (http://lasp.colorado.edu/~monk/xlf2.html).

Thermal fatigue durability for advanced propulsion materials

NASA Technical Reports Server (NTRS)

Halford, Gary R.

1989-01-01

A review is presented of thermal and thermomechanical fatigue (TMF) crack initiation life prediction and cyclic constitutive modeling efforts sponsored recently by the NASA Lewis Research Center in support of advanced aeronautical propulsion research. A brief description is provided of the more significant material durability models that were created to describe TMF fatigue resistance of both isotropic and anisotropic superalloys, with and without oxidation resistant coatings. The two most significant crack initiation models are the cyclic damage accumulation model and the total strain version of strainrange partitioning. Unified viscoplastic cyclic constitutive models are also described. A troika of industry, university, and government research organizations contributed to the generation of these analytic models. Based upon current capabilities and established requirements, an attempt is made to project which TMF research activities most likely will impact future generation propulsion systems.

Studies in geophysics: The Earth's electrical environment

NASA Technical Reports Server (NTRS)

1986-01-01

The Earth is electrified. Between the surface and the outer reaches of the atmosphere, there is a global circuit that is maintained by worldwide thunderstorm activity and by upper atmospheric dynamo processes. The highest voltages approach a billion volts and are generated within thunderclouds, where lightning is a visual display of the cloud's electrical nature. The largest currents in the circuit, approaching a million amperes, are associated with the aurora. Because there have been significant advances in understanding many of the component parts of the global electric circuit (lightning, cloud electrification, electrical processes in specific atmospheric regions, and telluric currents), a principal research challenge is to understand how these components interact to shape the global circuit. Increased basic understanding in this field has many potential practical applications, including lightning protection, the design of advanced aircraft and spacecraft, and improvements in weather prediction.

The prediction of progression-free and overall survival in women with an advanced stage of epithelial ovarian carcinoma.

PubMed

Gerestein, C G; Eijkemans, M J C; de Jong, D; van der Burg, M E L; Dykgraaf, R H M; Kooi, G S; Baalbergen, A; Burger, C W; Ansink, A C

2009-02-01

Prognosis in women with ovarian cancer mainly depends on International Federation of Gynecology and Obstetrics stage and the ability to perform optimal cytoreductive surgery. Since ovarian cancer has a heterogeneous presentation and clinical course, predicting progression-free survival (PFS) and overall survival (OS) in the individual patient is difficult. The objective of this study was to determine predictors of PFS and OS in women with advanced stage epithelial ovarian cancer (EOC) after primary cytoreductive surgery and first-line platinum-based chemotherapy. Retrospective observational study. Two teaching hospitals and one university hospital in the south-western part of the Netherlands. Women with advanced stage EOC. All women who underwent primary cytoreductive surgery for advanced stage EOC followed by first-line platinum-based chemotherapy between January 1998 and October 2004 were identified. To investigate independent predictors of PFS and OS, a Cox' proportional hazard model was used. Nomograms were generated with the identified predictive parameters. The primary outcome measure was OS and the secondary outcome measures were response and PFS. A total of 118 women entered the study protocol. Median PFS and OS were 15 and 44 months, respectively. Preoperative platelet count (P = 0.007), and residual disease <1 cm (P = 0.004) predicted PFS with a optimism corrected c-statistic of 0.63. Predictive parameters for OS were preoperative haemoglobin serum concentration (P = 0.012), preoperative platelet counts (P = 0.031) and residual disease <1 cm (P = 0.028) with a optimism corrected c-statistic of 0.67. PFS could be predicted by postoperative residual disease and preoperative platelet counts, whereas residual disease, preoperative platelet counts and preoperative haemoglobin serum concentration were predictive for OS. The proposed nomograms need to be externally validated.

A PBPK Model to Predict Disposition of CYP3A-Metabolized Drugs in Pregnant Women: Verification and Discerning the Site of CYP3A Induction.

PubMed

Ke, A B; Nallani, S C; Zhao, P; Rostami-Hodjegan, A; Unadkat, J D

2012-09-26

Besides logistical and ethical concerns, evaluation of safety and efficacy of medications in pregnant women is complicated by marked changes in pharmacokinetics (PK) of drugs. For example, CYP3A activity is induced during the third trimester (T3). We explored whether a previously published physiologically based pharmacokinetic (PBPK) model could quantitatively predict PK profiles of CYP3A-metabolized drugs during T3, and discern the site of CYP3A induction (i.e., liver, intestine, or both). The model accounted for gestational age-dependent changes in maternal physiological function and hepatic CYP3A activity. For model verification, mean plasma area under the curve (AUC), peak plasma concentration (Cmax), and trough plasma concentration (Cmin) of midazolam (MDZ), nifedipine (NIF), and indinavir (IDV) were predicted and compared with published studies. The PBPK model successfully predicted MDZ, NIF, and IDV disposition during T3. A sensitivity analysis suggested that CYP3A induction in T3 is most likely hepatic and not intestinal. Our PBPK model is a useful tool to evaluate different dosing regimens during T3 for drugs cleared primarily via CYP3A metabolism.CPT: Pharmacometrics & Systems Pharmacology (2012) 1, e3; doi:10.1038/psp.2012.2; advance online publication 26 September 2012.

Prediction and Measurement of the Vibration and Acoustic Radiation of Panels Subjected to Acoustic Loading

NASA Technical Reports Server (NTRS)

Turner, Travis L.; Rizzi, Stephen A.

1995-01-01

Interior noise and sonic fatigue are important issues in the development and design of advanced subsonic and supersonic aircraft. Conventional aircraft typically employ passive treatments, such as constrained layer damping and acoustic absorption materials, to reduce the structural response and resulting acoustic levels in the aircraft interior. These techniques require significant addition of mass and only attenuate relatively high frequency noise transmitted through the fuselage. Although structural acoustic coupling is in general very important in the study of aircraft fuselage interior noise, analysis of noise transmission through a panel supported in an infinite rigid baffle (separating two semi-infinite acoustic domains) can be useful in evaluating the effects of active/adaptive materials, complex loading, etc. Recent work has been aimed at developing adaptive and/or active methods of controlling the structural acoustic response of panels to reduce the transmitted noise1. A finite element formulation was recently developed to study the dynamic response of shape memory alloy (SMA) hybrid composite panels (conventional composite panel with embedded SMA fibers) subject to combined acoustic and thermal loads2. Further analysis has been performed to predict the far-field acoustic radiation using the finite element dynamic panel response prediction3. The purpose of the present work is to validate the panel vibration and acoustic radiation prediction methods with baseline experimental results obtained from an isotropic panel, without the effect of SMA.

[The third dimension tomography versus cranial X-ray cephalometry to predict maxilla advance by distraction in hypoplastic maxilla].

PubMed

Rosas-Muñoz, Arturo; Soriano-Padilla, Fernando; Rendón-Macías, Mario Enrique

2010-01-01

the osteogenic distraction is the treatment for the correction of the hypoplastic maxilla secondary to the repair of a cleft lip-palate. Its planning is based on articulated models. Our objective was to describe the accuracy of three-dimensional Cephalometry (CT3D) for projecting jaw displacement. three patients with hypoplastic maxilla. Interventions estimation of the advance required of lateral maxilla through Cephalometry of skull (CLC), CT3D and an articulated model (gold standard). Two months after distraction finalized the advance predicted was compared. the error of the advance projection in each patient was smaller with the CT3D versus CLC (+1, +1 and +1 mm versus -10, -14 and -9mm). Corrections post-distraction were of +25 %, +26 % and +38.4 % on the programmed one. CT3D predicted better the correction (+19 %, +10.8 %, +33.4 % versus CLC: -50 %; -60.8 % and -34.6 %). Chewing alterations were not seen in any patient. the planning of the necessary advance for distraction in patients with hypoplastic maxilla by CT3D can shorten the time of studies and should be consider as next to the projection of articulated model.

Advanced Nacelle Acoustic Lining Concepts Development

NASA Technical Reports Server (NTRS)

Bielak, G.; Gallman, J.; Kunze, R.; Murray, P.; Premo, J.; Kosanchick, M.; Hersh, A.; Celano, J.; Walker, B.; Yu, J.;

Determination of the coronal magnetic field from vector magnetograph data

NASA Technical Reports Server (NTRS)

Mikic, Zoran

1991-01-01

A new algorithm was developed, tested, and applied to determine coronal magnetic fields above solar active regions. The coronal field above NOAA active region AR5747 was successfully estimated on 20 Oct. 1989 from data taken at the Mees Solar Observatory of the Univ. of Hawaii. It was shown that observational data can be used to obtain realistic estimates of coronal magnetic fields. The model has significantly extended the realism with which the coronal magnetic field can be inferred from observations. The understanding of coronal phenomena will be greatly advanced by a reliable technique, such as the one presented, for deducing the detailed spatial structure of the coronal field. The payoff from major current and proposed NASA observational efforts is heavily dependent on the success with which the coronal field can be inferred from vector magnetograms. In particular, the present inability to reliably obtain the coronal field has been a major obstacle to the theoretical advancement of solar flare theory and prediction. The results have shown that the evolutional algorithm can be used to estimate coronal magnetic fields.

An Evolutionary Method for Financial Forecasting in Microscopic High-Speed Trading Environment

PubMed Central

Li, Hsu-Chih

2017-01-01

The advancement of information technology in financial applications nowadays have led to fast market-driven events that prompt flash decision-making and actions issued by computer algorithms. As a result, today's markets experience intense activity in the highly dynamic environment where trading systems respond to others at a much faster pace than before. This new breed of technology involves the implementation of high-speed trading strategies which generate significant portion of activity in the financial markets and present researchers with a wealth of information not available in traditional low-speed trading environments. In this study, we aim at developing feasible computational intelligence methodologies, particularly genetic algorithms (GA), to shed light on high-speed trading research using price data of stocks on the microscopic level. Our empirical results show that the proposed GA-based system is able to improve the accuracy of the prediction significantly for price movement, and we expect this GA-based methodology to advance the current state of research for high-speed trading and other relevant financial applications. PMID:28316618

Integrative sensing and prediction of urban water for sustainable cities (iSPUW)

NASA Astrophysics Data System (ADS)

Seo, D. J.; Fang, N. Z.; Yu, X.; Zink, M.; Gao, J.; Kerkez, B.

2014-12-01

We describe a newly launched project in the Dallas-Fort Worth Metroplex (DFW) area to develop a cyber-physical prototype system that integrates advanced sensing, modeling and prediction of urban water, to support its early adoption by a spectrum of users and stakeholders, and to educate a new generation of future sustainability scientists and engineers. The project utilizes the very high-resolution precipitation and other sensing capabilities uniquely available in DFW as well as crowdsourcing and cloud computing to advance understanding of the urban water cycle and to improve urban sustainability from transient shocks of heavy-to-extreme precipitation under climate change and urbanization. All available water information from observations and models will be fused objectively via advanced data assimilation to produce the best estimate of the state of the uncertain system. Modeling, prediction and decision support tools will be developed in the ensemble framework to increase the information content of the analysis and prediction and to support risk-based decision making.

A survey of advanced battery systems for space applications

NASA Technical Reports Server (NTRS)

Attia, Alan I.

1989-01-01

The results of a survey on advanced secondary battery systems for space applications are presented. Fifty-five battery experts from government, industry and universities participated in the survey by providing their opinions on the use of several battery types for six space missions, and their predictions of likely technological advances that would impact the development of these batteries. The results of the survey predict that only four battery types are likely to exceed a specific energy of 150 Wh/kg and meet the safety and reliability requirements for space applications within the next 15 years.

Seasonal dependence of the predictable low-level circulation patterns over the tropical Indo-Pacific domain

NASA Astrophysics Data System (ADS)

Zhang, Tuantuan; Huang, Bohua; Yang, Song; Laohalertchai, Charoon

2018-06-01

The seasonal dependence of the prediction skill of 850-hPa monthly zonal wind over the tropical Indo-Pacific domain is examined using the ensemble reforecasts for 1983-2010 from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis and Reforecast (CFSRR) project. According to a maximum signal-to-noise empirical orthogonal function analysis, the most predictable patterns of atmospheric low-level circulation are associated with the developing and maturing phases of El Niño-Southern Oscillation (ENSO). The CFSv2 is capable of predicting these ENSO-related patterns up to 9-months in advance for all months, except for May-June when the effect of the spring barrier is strong. The other predictable climate processes associated with the low-level atmospheric circulation are more seasonally dependent. For winter and spring, the second most predictable patterns are associated with the ENSO decaying phase. Within these seasons, the monthly evolution of the predictable patterns is characterized by a southward shift of westerly wind anomalies, generated by the interaction between the annual cycle and the ENSO signals (i.e., the combination-mode). In general, the CFSv2 hindcast well predicts these patterns at least 5 months in advance for spring, while shows much lower skills for winter months. In summer, the second predictable patterns are associated with the western North Pacific (WNP) monsoon (i.e., the WNP anticyclone/cyclone) in short leads while associated with ENSO in longer leads (after 4-month lead). The second predictable patterns in fall are mainly associated with tropical Indian Ocean Dipole, which can be predicted 3 months in advance.

Applied Meteorology Unit (AMU) Quarterly Report - Fourth Quarter FY-09

NASA Technical Reports Server (NTRS)

Bauman, William; Crawford, Winifred; Barrett, Joe; Watson, Leela; Wheeler, Mark

2009-01-01

This report summarizes the Applied Meteorology Unit (AMU) activities for the fourth quarter of Fiscal Year 2009 (July - September 2009). Tasks reports include: (1) Peak Wind Tool for User Launch Commit Criteria (LCC), (2) Objective Lightning Probability Tool. Phase III, (3) Peak Wind Tool for General Forecasting. Phase II, (4) Update and Maintain Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS), (5) Verify MesoNAM Performance (6) develop a Graphical User Interface to update selected parameters for the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLlT)

Selected technology for the gas industry

NASA Technical Reports Server (NTRS)

1975-01-01

A number of papers were presented at a conference concerned with the application of technical topics from aerospace activities for the gas industry. The following subjects were covered: general future of fossil fuels in America, exploration for fossil and nuclear fuels from orbital altitudes, technology for liquefied gas, safety considerations relative to fires, explosions, and detonations, gas turbomachinery technology, fluid properties, fluid flow, and heat transfer, NASA information and documentation systems, instrumentation and measurement, materials and life prediction, reliability and quality assurance, and advanced energy systems (including synthetic fuels, energy storage, solar energy, and wind energy).

A novel 2-step approach combining the NAFLD fibrosis score and liver stiffness measurement for predicting advanced fibrosis.

PubMed

Chan, Wah-Kheong; Nik Mustapha, Nik Raihan; Mahadeva, Sanjiv

2015-10-01

The non-alcoholic fatty liver disease (NAFLD) fibrosis score (NFS) is indeterminate in a proportion of NAFLD patients. Combining the NFS with liver stiffness measurement (LSM) may improve prediction of advanced fibrosis. We aim to evaluate the NFS and LSM in predicting advanced fibrosis in NAFLD patients. The NFS was calculated and LSM obtained for consecutive adult NAFLD patients scheduled for liver biopsy. The accuracy of predicting advanced fibrosis using either modality and in combination were assessed. An algorithm combining the NFS and LSM was developed from a training cohort and subsequently tested in a validation cohort. There were 101 and 46 patients in the training and validation cohort, respectively. In the training cohort, the percentages of misclassifications using the NFS alone, LSM alone, LSM alone (with grey zone), both tests for all patients and a 2-step approach using LSM only for patients with indeterminate and high NFS were 5.0, 28.7, 2.0, 2.0 and 4.0 %, respectively. The percentages of patients requiring liver biopsy were 30.7, 0, 36.6, 36.6 and 18.8 %, respectively. In the validation cohort, the percentages of misclassifications were 8.7, 28.3, 2.2, 2.2 and 8.7 %, respectively. The percentages of patients requiring liver biopsy were 28.3, 0, 41.3, 43.5 and 19.6 %, respectively. The novel 2-step approach further reduced the number of patients requiring a liver biopsy whilst maintaining the accuracy to predict advanced fibrosis. The combination of NFS and LSM for all patients provided no apparent advantage over using either of the tests alone.

Risk Matrix for Prediction of Disease Progression in a Referral Cohort of Patients with Crohn's Disease.

PubMed

Lakatos, Peter L; Sipeki, Nora; Kovacs, Gyorgy; Palyu, Eszter; Norman, Gary L; Shums, Zakera; Golovics, Petra A; Lovasz, Barbara D; Antal-Szalmas, Peter; Papp, Maria

2015-10-01

Early identification of patients with Crohn's disease (CD) at risk of subsequent complications is essential for adapting the treatment strategy. We aimed to develop a prediction model including clinical and serological markers for assessing the probability of developing advanced disease in a prospective referral CD cohort. Two hundred and seventy-one consecutive CD patients (42.4% males, median follow-up 108 months) were included and followed up prospectively. Anti-Saccharomyces cerevisiae antibodies (ASCA IgA/IgG) were determined by enzyme-linked immunosorbent assay. The final analysis was limited to patients with inflammatory disease behaviour at diagnosis. The final definition of advanced disease outcome was having intestinal resection or disease behaviour progression. Antibody (ASCA IgA and/or IgG) status, disease location and need for early azathioprine were included in a 3-, 5- and 7-year prediction matrix. The probability of advanced disease after 5 years varied from 6.2 to 55% depending on the combination of predictors. Similar findings were obtained in Kaplan-Meier analysis; the combination of ASCA, location and early use of azathioprine was associated with the probability of developing advanced disease (p < 0.001, log rank test). Our prediction models identified substantial differences in the probability of developing advanced disease in the early disease course of CD. Markers identified in this referral cohort were different from those previously published in a population-based cohort, suggesting that different prediction models should be used in the referral setting. Copyright © 2015 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Bridging the Gap between Human Judgment and Automated Reasoning in Predictive Analytics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sanfilippo, Antonio P.; Riensche, Roderick M.; Unwin, Stephen D.

2010-06-07

Events occur daily that impact the health, security and sustainable growth of our society. If we are to address the challenges that emerge from these events, anticipatory reasoning has to become an everyday activity. Strong advances have been made in using integrated modeling for analysis and decision making. However, a wider impact of predictive analytics is currently hindered by the lack of systematic methods for integrating predictive inferences from computer models with human judgment. In this paper, we present a predictive analytics approach that supports anticipatory analysis and decision-making through a concerted reasoning effort that interleaves human judgment and automatedmore » inferences. We describe a systematic methodology for integrating modeling algorithms within a serious gaming environment in which role-playing by human agents provides updates to model nodes and the ensuing model outcomes in turn influence the behavior of the human players. The approach ensures a strong functional partnership between human players and computer models while maintaining a high degree of independence and greatly facilitating the connection between model and game structures.« less

JPL's Role in Advancing Earth System Science to Meet the Challenges of Climate and Environmental Change

NASA Technical Reports Server (NTRS)

Evans, Diane

2012-01-01

Objective 2.1.1: Improve understanding of and improve the predictive capability for changes in the ozone layer, climate forcing, and air quality associated with changes in atmospheric composition. Objective 2.1.2: Enable improved predictive capability for weather and extreme weather events. Objective 2.1.3: Quantify, understand, and predict changes in Earth s ecosystems and biogeochemical cycles, including the global carbon cycle, land cover, and biodiversity. Objective 2.1.4: Quantify the key reservoirs and fluxes in the global water cycle and assess water cycle change and water quality. Objective 2.1.5: Improve understanding of the roles of the ocean, atmosphere, land and ice in the climate system and improve predictive capability for its future evolution. Objective 2.1.6: Characterize the dynamics of Earth s surface and interior and form the scientific basis for the assessment and mitigation of natural hazards and response to rare and extreme events. Objective 2.1.7: Enable the broad use of Earth system science observations and results in decision-making activities for societal benefits.

Gene expression profiling reveals activation of the FA/BRCA pathway in advanced squamous cervical cancer with intrinsic resistance and therapy failure.

PubMed

Balacescu, Ovidiu; Balacescu, Loredana; Tudoran, Oana; Todor, Nicolae; Rus, Meda; Buiga, Rares; Susman, Sergiu; Fetica, Bogdan; Pop, Laura; Maja, Laura; Visan, Simona; Ordeanu, Claudia; Berindan-Neagoe, Ioana; Nagy, Viorica

2014-04-08

Advanced squamous cervical cancer, one of the most commonly diagnosed cancers in women, still remains a major problem in oncology due to treatment failure and distant metastasis. Antitumor therapy failure is due to both intrinsic and acquired resistance; intrinsic resistance is often decisive for treatment response. In this study, we investigated the specific pathways and molecules responsible for baseline therapy failure in locally advanced squamous cervical cancer. Twenty-one patients with locally advanced squamous cell carcinoma were enrolled in this study. Primary biopsies harvested prior to therapy were analyzed for whole human gene expression (Agilent) based on the patient's 6 months clinical response. Ingenuity Pathway Analysis was used to investigate the altered molecular function and canonical pathways between the responding and non-responding patients. The microarray results were validated by qRT-PCR and immunohistochemistry. An additional set of 24 formalin-fixed paraffin-embedded cervical cancer samples was used for independent validation of the proteins of interest. A 2859-gene signature was identified to distinguish between responder and non-responder patients. 'DNA Replication, Recombination and Repair' represented one of the most important mechanisms activated in non-responsive cervical tumors, and the 'Role of BRCA1 in DNA Damage Response' was predicted to be the most significantly altered canonical pathway involved in intrinsic resistance (p = 1.86E-04, ratio = 0.262). Immunohistological staining confirmed increased expression of BRCA1, BRIP1, FANCD2 and RAD51 in non-responsive compared with responsive advanced squamous cervical cancer, both in the initial set of 21 cervical cancer samples and the second set of 24 samples. Our findings suggest that FA/BRCA pathway plays an important role in treatment failure in advanced cervical cancer. The assessment of FANCD2, RAD51, BRCA1 and BRIP1 nuclear proteins could provide important information about the patients at risk for treatment failure.

Forecasting Western U.S. Snowpack

NASA Astrophysics Data System (ADS)

Kapnick, S. B.; Yang, X.; Vecchi, G. A.; Delworth, T. L.; Gudgel, R.; Malyshev, S.; Milly, C.; Shevliakova, E.; Underwood, S.; Margulis, S. A.

2017-12-01

Cold season mountain snow accumulation in the western United States plays a critical role in regional hydroclimate and water supply. While climate projections provide estimates of future snowpack loss by the end of the century and weather forecasts provide predictions of weather conditions and hazards out to two weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), particularly beyond 6 months. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate our dynamical system's feasibility of seasonal snowpack predictions and quantify the limits of predictive skill more than 2 seasons in advance for snowpack—snow that accumulates on the ground in the mountains. Our ability to predict snowpack is reliant on both temperature and precipitation prediction skill modulating both the amount of frozen precipitation that falls and how much snow accumulates and stays on the ground throughout the season. We will quantify prediction skill and outline areas necessary for the future advancement of seasonal hydroclimate prediction.

Measured and predicted rotor performance for the SERI advanced wind turbine blades

NASA Astrophysics Data System (ADS)

Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

1992-02-01

Measured and predicted rotor performance for the Solar Energy Research Institute (SERI) advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction.

Collaboratory for the Study of Earthquake Predictability

NASA Astrophysics Data System (ADS)

Schorlemmer, D.; Jordan, T. H.; Zechar, J. D.; Gerstenberger, M. C.; Wiemer, S.; Maechling, P. J.

2006-12-01

Earthquake prediction is one of the most difficult problems in physical science and, owing to its societal implications, one of the most controversial. The study of earthquake predictability has been impeded by the lack of an adequate experimental infrastructure---the capability to conduct scientific prediction experiments under rigorous, controlled conditions and evaluate them using accepted criteria specified in advance. To remedy this deficiency, the Southern California Earthquake Center (SCEC) is working with its international partners, which include the European Union (through the Swiss Seismological Service) and New Zealand (through GNS Science), to develop a virtual, distributed laboratory with a cyberinfrastructure adequate to support a global program of research on earthquake predictability. This Collaboratory for the Study of Earthquake Predictability (CSEP) will extend the testing activities of SCEC's Working Group on Regional Earthquake Likelihood Models, from which we will present first results. CSEP will support rigorous procedures for registering prediction experiments on regional and global scales, community-endorsed standards for assessing probability-based and alarm-based predictions, access to authorized data sets and monitoring products from designated natural laboratories, and software to allow researchers to participate in prediction experiments. CSEP will encourage research on earthquake predictability by supporting an environment for scientific prediction experiments that allows the predictive skill of proposed algorithms to be rigorously compared with standardized reference methods and data sets. It will thereby reduce the controversies surrounding earthquake prediction, and it will allow the results of prediction experiments to be communicated to the scientific community, governmental agencies, and the general public in an appropriate research context.

Serum biomarkers and transient elastography as predictors of advanced liver fibrosis in a United States cohort: the Boston children's hospital experience.

PubMed

Lee, Christine K; Perez-Atayde, Antonio R; Mitchell, Paul D; Raza, Roshan; Afdhal, Nezam H; Jonas, Maureen M

2013-10-01

To evaluate and compare the ability of serum hyaluronic acid (HA) and human cartilage glycoprotein-39 (YKL-40) values, as well as transient elastography (TE) findings, to predict advanced hepatic fibrosis in a cohort from a single pediatric center. Subjects who underwent liver biopsy analysis within 12 months before enrollment were eligible for this prospective study. HA and YKL-40 measurements were obtained within 1 month of TE. A METAVIR score of F3 or F4 was considered to indicate advanced fibrosis. A total of 128 patients (51% males) aged 1.4 months to 27.6 years (22% aged <2 years) were enrolled. Thirty-one subjects had data on only HA and YKL-40 measurements, and 97 subjects had data on both blood tests and TE. For the prediction of advanced fibrosis, the area under the receiver operating characteristic curve (AUC) values were 0.83 for TE, 0.72 for HA, and 0.52 for YKL-40. The AUC of 0.83 for TE was statistically significantly greater than the AUCs for HA (P = .03) and YKL-40 (P < .0001). Optimal cutpoints for predicting F3-F4 fibrosis were 8.6 kPa for TE (P < .0001), 43 ng/mL for HA (P < .0001), and 26.2 ng/mL for YKL-40 (P = .85). The combination of TE and HA was not better than TE alone for predicting advanced fibrosis (P = .15). In this study, which evaluated TE, HA, and YKL-40 to predict liver fibrosis in children in the US, YKL-40 had no predictive value and TE was superior to HA, but the addition of HA did not improve the performance of TE. Our data suggest that TE and HA may be useful noninvasive tools for assessing liver fibrosis in children. Copyright © 2013 Mosby, Inc. All rights reserved.

Prediction of helicopter rotor discrete frequency noise: A computer program incorporating realistic blade motions and advanced acoustic formulation

NASA Technical Reports Server (NTRS)

Brentner, K. S.

1986-01-01

A computer program has been developed at the Langley Research Center to predict the discrete frequency noise of conventional and advanced helicopter rotors. The program, called WOPWOP, uses the most advanced subsonic formulation of Farassat that is less sensitive to errors and is valid for nearly all helicopter rotor geometries and flight conditions. A brief derivation of the acoustic formulation is presented along with a discussion of the numerical implementation of the formulation. The computer program uses realistic helicopter blade motion and aerodynamic loadings, input by the user, for noise calculation in the time domain. A detailed definition of all the input variables, default values, and output data is included. A comparison with experimental data shows good agreement between prediction and experiment; however, accurate aerodynamic loading is needed.

Brain activity associated with illusory correlations in animal phobia

PubMed Central

Wiemer, Julian; Schulz, Stefan M.; Reicherts, Philipp; Glotzbach-Schoon, Evelyn; Andreatta, Marta

2015-01-01

Anxiety disorder patients were repeatedly found to overestimate the association between disorder-relevant stimuli and aversive outcomes despite random contingencies. Such an illusory correlation (IC) might play an important role in the return of fear after extinction learning; yet, little is known about how this cognitive bias emerges in the brain. In a functional magnetic resonance imaging study, 18 female patients with spider phobia and 18 healthy controls were exposed to pictures of spiders, mushrooms and puppies followed randomly by either a painful electrical shock or nothing. In advance, both patients and healthy controls expected more shocks after spider pictures. Importantly, only patients with spider phobia continued to overestimate this association after the experiment. The strength of this IC was predicted by increased outcome aversiveness ratings and primary sensory motor cortex activity in response to the shock after spider pictures. Moreover, increased activation of the left dorsolateral prefrontal cortex (dlPFC) to spider pictures predicted the IC. These results support the theory that phobia-relevant stimuli amplify unpleasantness and sensory motor representations of aversive stimuli, which in turn may promote their overestimation. Hyper-activity in dlPFC possibly reflects a pre-occupation of executive resources with phobia-relevant stimuli, thus complicating the accurate monitoring of objective contingencies and the unlearning of fear. PMID:25411452

Mining of Microbial Genomes for the Novel Sources of Nitrilases.

PubMed

Sharma, Nikhil; Thakur, Neerja; Raj, Tilak; Savitri; Bhalla, Tek Chand

2017-01-01

Next-generation DNA sequencing (NGS) has made it feasible to sequence large number of microbial genomes and advancements in computational biology have opened enormous opportunities to mine genome sequence data for novel genes and enzymes or their sources. In the present communication in silico mining of microbial genomes has been carried out to find novel sources of nitrilases. The sequences selected were analyzed for homology and considered for designing motifs. The manually designed motifs based on amino acid sequences of nitrilases were used to screen 2000 microbial genomes (translated to proteomes). This resulted in identification of one hundred thirty-eight putative/hypothetical sequences which could potentially code for nitrilase activity. In vitro validation of nine predicted sources of nitrilases was done for nitrile/cyanide hydrolyzing activity. Out of nine predicted nitrilases, Gluconacetobacter diazotrophicus , Sphingopyxis alaskensis , Saccharomonospora viridis , and Shimwellia blattae were specific for aliphatic nitriles, whereas nitrilases from Geodermatophilus obscurus , Nocardiopsis dassonvillei , Runella slithyformis , and Streptomyces albus possessed activity for aromatic nitriles. Flavobacterium indicum was specific towards potassium cyanide (KCN) which revealed the presence of nitrilase homolog, that is, cyanide dihydratase with no activity for either aliphatic, aromatic, or aryl nitriles. The present study reports the novel sources of nitrilases and cyanide dihydratase which were not reported hitherto by in silico or in vitro studies.

Seasonal to Decadal Discharge Predictions: Dream, Reality, or Somewhere in Between?

NASA Astrophysics Data System (ADS)

Villarini, G.

2016-12-01

Rivers have always played a central role in human activities including transportation and the provision of freshwater resources for agriculture, industry, and household use. However, too much or too little water in our rivers can have profound societal and economic repercussions, affecting the livelihood of millions of people and resulting in billions of dollars in economic damage. Despite these profound impacts and the critical role that rivers have played in our society, the development of systems enabling skillful predictions of discharge with lead times ranging from several months to several years is still in its infancy. The availability of discharge predictions could have major impacts on a number of sectors and industries, from water resources management to disaster prevention, policy-making and transportation. In this presentation, I will use recent developments from my research group to discuss some of the advances that we have made towards answering the question: Are skillful seasonal to decadal discharge predictions a dream, a reality, or somewhere in between? Results are based on a statistical-dynamical prediction system providing probabilistic seasonal discharge forecasts across the central United States with lead times ranging from a few months to several years.

Nomogram for 30-day morbidity after primary cytoreductive surgery for advanced stage ovarian cancer.

PubMed

Nieuwenhuyzen-de Boer, G M; Gerestein, C G; Eijkemans, M J C; Burger, C W; Kooi, G S

2016-01-01

Extensive surgical procedures to achieve maximal cytoreduction in patients with advanced stage epithelial ovarian cancer (EOC) are inevitably associated with postoperative morbidity and mortality. This study aimed to identify preoperative predictors of 30-day morbidity after primary cytoreductive surgery for advanced stage EOC and to develop a nomogram for individual risk assessment. Patients in The Netherlands who underwent primary cytoreductive surgery for advanced stage EOC between January 2004 and December 2007. All peri- and postoperative complications within 30 days after surgery were registered and classified. To investigate predictors of 30-day morbidity, a Cox proportional hazard model with backward stepwise elimination was utilized. The identified predictors were entered into a nomogram. The main outcome was to identify parameters that predict operative risk. 293 patients entered the study protocol. Optimal cytoreduction was achieved in 136 (46%) patients. Thirty-day morbidity was seen in 99 (34%) patients. Morbidity could be predicted by age (p = 0.033; OR 1.024), preoperative hemoglobin (p = 0.194; OR 0.843), and WHO performance status (p = 0.015; OR 1.821) with a optimism-corrected c-statistic of 0.62. Determinants co-morbidity status, serum CA125 level, platelet count, and presence of ascites were comparable in both groups. Thirty-day morbidity after primary cytoreductive surgery for advanced stage EOC could be predicted by age, hemoglobin, and WHO performance status. The generated nomogram could be valuable for predicting operative risk in the individual patient.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simpson, L.; Britt, J.; Birkmire, R.

ITN Energy Systems, Inc., and Global Solar Energy, Inc., assisted by NREL's PV Manufacturing R&D program, have continued to advance CIGS production technology by developing trajectory-oriented predictive/control models, fault-tolerance control, control platform development, in-situ sensors, and process improvements. Modeling activities included developing physics-based and empirical models for CIGS and sputter-deposition processing, implementing model-based control, and applying predictive models to the construction of new evaporation sources and for control. Model-based control is enabled by implementing reduced or empirical models into a control platform. Reliability improvement activities include implementing preventive maintenance schedules; detecting failed sensors/equipment and reconfiguring to tinue processing; and systematicmore » development of fault prevention and reconfiguration strategies for the full range of CIGS PV production deposition processes. In-situ sensor development activities have resulted in improved control and indicated the potential for enhanced process status monitoring and control of the deposition processes. Substantial process improvements have been made, including significant improvement in CIGS uniformity, thickness control, efficiency, yield, and throughput. In large measure, these gains have been driven by process optimization, which in turn have been enabled by control and reliability improvements due to this PV Manufacturing R&D program.« less

Prefrontal neural correlates of memory for sequences.

PubMed

Averbeck, Bruno B; Lee, Daeyeol

2007-02-28

The sequence of actions appropriate to solve a problem often needs to be discovered by trial and error and recalled in the future when faced with the same problem. Here, we show that when monkeys had to discover and then remember a sequence of decisions across trials, ensembles of prefrontal cortex neurons reflected the sequence of decisions the animal would make throughout the interval between trials. This signal could reflect either an explicit memory process or a sequence-planning process that begins far in advance of the actual sequence execution. This finding extended to error trials such that, when the neural activity during the intertrial interval specified the wrong sequence, the animal also attempted to execute an incorrect sequence. More specifically, we used a decoding analysis to predict the sequence the monkey was planning to execute at the end of the fore-period, just before sequence execution. When this analysis was applied to error trials, we were able to predict where in the sequence the error would occur, up to three movements into the future. This suggests that prefrontal neural activity can retain information about sequences between trials, and that regardless of whether information is remembered correctly or incorrectly, the prefrontal activity veridically reflects the animal's action plan.

Topics in Complexity: Dynamical Patterns in the Cyberworld

NASA Astrophysics Data System (ADS)

Qi, Hong

Quantitative understanding of mechanism in complex systems is a common "difficult" problem across many fields such as physical, biological, social and economic sciences. Investigation on underlying dynamics of complex systems and building individual-based models have recently been fueled by big data resulted from advancing information technology. This thesis investigates complex systems in social science, focusing on civil unrests on streets and relevant activities online. Investigation consists of collecting data of unrests from open digital source, featuring dynamical patterns underlying, making predictions and constructing models. A simple law governing the progress of two-sided confrontations is proposed with data of activities at micro-level. Unraveling the connections between activity of organizing online and outburst of unrests on streets gives rise to a further meso-level pattern of human behavior, through which adversarial groups evolve online and hyper-escalate ahead of real-world uprisings. Based on the patterns found, noticeable improvement of prediction of civil unrests is achieved. Meanwhile, novel model created from combination of mobility dynamics in the cyberworld and a traditional contagion model can better capture the characteristics of modern civil unrests and other contagion-like phenomena than the original one.

[Study on factors influencing survival in patients with advanced gastric carcinoma after resection by Cox's proportional hazard model].

PubMed

Wang, S; Sun, Z; Wang, S

1996-11-01

A prospective follow-up study of 539 advanced gastric carcinoma patients after resection was undertaken between 1 January 1980 and 31 December 1989, with a follow-up rate of 95.36%. A multivariate analysis of possible factors influencing survival of these patients was performed, and their predicting models of survival rates was established by Cox proportional hazard model. The results showed that the major significant prognostic factors influencing survival of these patients were rate and station of lymph node metastases, type of operation, hepatic metastases, size of tumor, age and location of tumor. The most important factor was the rate of lymph node metastases. According to their regression coefficients, the predicting value (PV) of each patient was calculated, then all patients were divided into five risk groups according to PV, their predicting models of survival rates after resection were established in groups. The goodness-fit of estimated predicting models of survival rates were checked by fitting curve and residual plot, and the estimated models tallied with the actual situation. The results suggest that the patients with advanced gastric cancer after resection without lymph node metastases and hepatic metastases had a better prognosis, and their survival probability may be predicted according to the predicting model of survival rates.

Acoustic prediction methods for the NASA generalized advanced propeller analysis system (GAPAS)

NASA Technical Reports Server (NTRS)

Padula, S. L.; Block, P. J. W.

1984-01-01

Classical methods of propeller performance analysis are coupled with state-of-the-art Aircraft Noise Prediction Program (ANOPP:) techniques to yield a versatile design tool, the NASA Generalized Advanced Propeller Analysis System (GAPAS) for the novel quiet and efficient propellers. ANOPP is a collection of modular specialized programs. GAPAS as a whole addresses blade geometry and aerodynamics, rotor performance and loading, and subsonic propeller noise.

The APPLE Trial: Feasibility and Activity of AZD9291 (Osimertinib) Treatment on Positive PLasma T790M in EGFR-mutant NSCLC Patients. EORTC 1613.

PubMed

Remon, Jordi; Menis, Jessica; Hasan, Baktiar; Peric, Aleksandra; De Maio, Eleonora; Novello, Silvia; Reck, Martin; Berghmans, Thierry; Wasag, Bartosz; Besse, Benjamin; Dziadziuszko, Rafal

2017-09-01

The AZD9291 (Osimertinib) Treatment on Positive PLasma T790M in EGFR-mutant NSCLC Patients (APPLE) trial is a randomized, open-label, multicenter, 3-arm, phase II study in advanced, epidermal growth factor receptor (EGFR)-mutant and EGFR tyrosine kinase inhibitor (TKI)-naive non-small-cell lung cancer (NSCLC) patients, to evaluate the best strategy for sequencing gefitinib and osimertinib treatment. Advanced EGFR-mutant NSCLC patients, with World Health Organization performance status 0-2 who are EGFR TKI treatment-naive and eligible to receive first-line treatment with EGFR TKI will be randomized to: In all arms, a plasmatic ctDNA T790M test will be performed by a central laboratory at the Medical University of Gdansk (Poland) but will be applied as a predictive marker for making treatment decisions only in arm B. The primary objective is to evaluate the best strategy for sequencing of treatment with gefitinib and osimertinib in advanced NSCLC patients with common EGFR mutations, and to understand the value of liquid biopsy for the decision-making process. The progression-free survival rate at 18 months is the primary end point of the trial. The activity of osimertinib versus gefitinib to prevent brain metastases will be evaluated. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Modeling Longitudinal Changes in Older Adults’ Memory for Spoken Discourse: Findings from the ACTIVE Cohort

PubMed Central

Payne, Brennan R.; Gross, Alden L.; Parisi, Jeanine M.; Sisco, Shannon M.; Stine-Morrow, Elizabeth A. L.; Marsiske, Michael; Rebok, George W.

2014-01-01

Episodic memory shows substantial declines with advancing age, but research on longitudinal trajectories of spoken discourse memory (SDM) in older adulthood is limited. Using parallel process latent growth curve models, we examined 10 years of longitudinal data from the no-contact control group (N = 698) of the Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) randomized controlled trial in order to test (a) the degree to which SDM declines with advancing age, (b) predictors of these age-related declines, and (c) the within-person relationship between longitudinal changes in SDM and longitudinal changes in fluid reasoning and verbal ability over 10 years, independent of age. Individuals who were younger, White, had more years of formal education, were male, and had better global cognitive function and episodic memory performance at baseline demonstrated greater levels of SDM on average. However, only age at baseline uniquely predicted longitudinal changes in SDM, such that declines accelerated with greater age. Independent of age, within-person decline in reasoning ability over the 10-year study period was substantially correlated with decline in SDM (r = .87). An analogous association with SDM did not hold for verbal ability. The findings suggest that longitudinal declines in fluid cognition are associated with reduced spoken language comprehension. Unlike findings from memory for written prose, preserved verbal ability may not protect against developmental declines in memory for speech. PMID:24304364

Predicted changes in advanced turboprop noise with shaft angle of attack

NASA Technical Reports Server (NTRS)

Padula, S. L.; Block, P. J. W.

1984-01-01

Advanced turboprop blade designs and new propeller installation schemes motivated an effort to include unsteady loading effects in existing propeller noise prediction computer programs. The present work validates the prediction capability while studing the effects of shaft inclination on the radiated sound field. Classical methods of propeller performance analysis supply the time-dependent blade loading needed to calculate noise. Polar plots of the sound pressure level (SPL) of the first four harmonics and overall SPL are indicative of the change in directivity pattern as a function of propeller angle of attack. Noise predictions are compared with newly available wind tunnel data and the accuracy and applicability of the prediction method are discussed. It is concluded that unsteady blade loading caused by inclining the propeller with respect to the flow changes the directionality and the intensity of the radiated noise. These changes are well modeled by the present quasi-steady prediction method.

Analysis and correlation of the test data from an advanced technology rotor system

NASA Technical Reports Server (NTRS)

Jepson, D.; Moffitt, R.; Hilzinger, K.; Bissell, J.

1983-01-01

Comparisons were made of the performance and blade vibratory loads characteristics for an advanced rotor system as predicted by analysis and as measured in a 1/5 scale model wind tunnel test, a full scale model wind tunnel test and flight test. The accuracy with which the various tools available at the various stages in the design/development process (analysis, model test etc.) could predict final characteristics as measured on the aircraft was determined. The accuracy of the analyses in predicting the effects of systematic tip planform variations investigated in the full scale wind tunnel test was evaluated.

Genotype-driven identification of a molecular network predictive of advanced coronary calcium in ClinSeq® and Framingham Heart Study cohorts.

PubMed

Oguz, Cihan; Sen, Shurjo K; Davis, Adam R; Fu, Yi-Ping; O'Donnell, Christopher J; Gibbons, Gary H

2017-10-26

One goal of personalized medicine is leveraging the emerging tools of data science to guide medical decision-making. Achieving this using disparate data sources is most daunting for polygenic traits. To this end, we employed random forests (RFs) and neural networks (NNs) for predictive modeling of coronary artery calcium (CAC), which is an intermediate endo-phenotype of coronary artery disease (CAD). Model inputs were derived from advanced cases in the ClinSeq®; discovery cohort (n=16) and the FHS replication cohort (n=36) from 89 th -99 th CAC score percentile range, and age-matched controls (ClinSeq®; n=16, FHS n=36) with no detectable CAC (all subjects were Caucasian males). These inputs included clinical variables and genotypes of 56 single nucleotide polymorphisms (SNPs) ranked highest in terms of their nominal correlation with the advanced CAC state in the discovery cohort. Predictive performance was assessed by computing the areas under receiver operating characteristic curves (ROC-AUC). RF models trained and tested with clinical variables generated ROC-AUC values of 0.69 and 0.61 in the discovery and replication cohorts, respectively. In contrast, in both cohorts, the set of SNPs derived from the discovery cohort were highly predictive (ROC-AUC ≥0.85) with no significant change in predictive performance upon integration of clinical and genotype variables. Using the 21 SNPs that produced optimal predictive performance in both cohorts, we developed NN models trained with ClinSeq®; data and tested with FHS data and obtained high predictive accuracy (ROC-AUC=0.80-0.85) with several topologies. Several CAD and "vascular aging" related biological processes were enriched in the network of genes constructed from the predictive SNPs. We identified a molecular network predictive of advanced coronary calcium using genotype data from ClinSeq®; and FHS cohorts. Our results illustrate that machine learning tools, which utilize complex interactions between disease predictors intrinsic to the pathogenesis of polygenic disorders, hold promise for deriving predictive disease models and networks.

A LINE-1 Component to Human Aging: Do LINE elements exact a longevity cost for evolutionary advantage?

PubMed Central

Laurent, Georges St.; Hammell, Neil; McCaffrey, Timothy A.

2010-01-01

Advancing age remains the largest risk factor for devastating diseases, such as heart disease, stroke, and cancer. The mechanisms by which advancing age predisposes to disease are now beginning to unfold, due in part, to genetic and environmental manipulations of longevity in lower organisms. Converging lines of evidence suggest that DNA damage may be a final common pathway linking several proposed mechanisms of aging. The present review forwards a theory for an additional aging pathway that involves modes of inherent genetic instability. Long interspersed nuclear elements (LINEs) are endogenous non-LTR retrotransposons that compose about 20% of the human genome. The LINE-1 (L1) gene products, ORF1p and ORF2p, possess mRNA binding, endonuclease, and reverse transcriptase activity that enable retrotransposition. While principally active only during embryogenesis, L1 transcripts are detected in adult somatic cells under certain conditions. The present hypothesis proposes that L1s act as an ‘endogenous clock’, slowly eroding genomic integrity by competing with the organism’s double-strand break repair mechanism. Thus, while L1s are an accepted mechanism of genetic variation fueling evolution, it is proposed that longevity is negatively impacted by somatic L1 activity. The theory predicts testable hypotheses about the relationship between L1 activity, DNA repair, healthy aging, and longevity. PMID:20346965

A New Scoring System to Predict the Risk for High-risk Adenoma and Comparison of Existing Risk Calculators.

PubMed

Murchie, Brent; Tandon, Kanwarpreet; Hakim, Seifeldin; Shah, Kinchit; O'Rourke, Colin; Castro, Fernando J

2017-04-01

Colorectal cancer (CRC) screening guidelines likely over-generalizes CRC risk, 35% of Americans are not up to date with screening, and there is growing incidence of CRC in younger patients. We developed a practical prediction model for high-risk colon adenomas in an average-risk population, including an expanded definition of high-risk polyps (≥3 nonadvanced adenomas), exposing higher than average-risk patients. We also compared results with previously created calculators. Patients aged 40 to 59 years, undergoing first-time average-risk screening or diagnostic colonoscopies were evaluated. Risk calculators for advanced adenomas and high-risk adenomas were created based on age, body mass index, sex, race, and smoking history. Previously established calculators with similar risk factors were selected for comparison of concordance statistic (c-statistic) and external validation. A total of 5063 patients were included. Advanced adenomas, and high-risk adenomas were seen in 5.7% and 7.4% of the patient population, respectively. The c-statistic for our calculator was 0.639 for the prediction of advanced adenomas, and 0.650 for high-risk adenomas. When applied to our population, all previous models had lower c-statistic results although one performed similarly. Our model compares favorably to previously established prediction models. Age and body mass index were used as continuous variables, likely improving the c-statistic. It also reports absolute predictive probabilities of advanced and high-risk polyps, allowing for more individualized risk assessment of CRC.

Demagnetization Tests Performed on a Linear Alternator for a Stirling Power Convertor

NASA Technical Reports Server (NTRS)

Geng, Steven M.; Niedra, Janis M.; Schwarze, Gene E.

2012-01-01

The NASA Glenn Research Center (GRC) is conducting in-house research on rare-earth permanent magnets and linear alternators to assist in developing free-piston Stirling convertors for radioisotope space power systems and for developing advanced linear alternator technology. This research continues at GRC, but, with the exception of Advanced Stirling Radioisotope Generator references, the work presented in this paper was conducted in 2005. A special arc-magnet characterization fixture was designed and built to measure the M-H characteristics of the magnets used in Technology Demonstration Convertors developed under the 110-W Stirling Radioisotope Generator (SRG110) project. This fixture was used to measure these characteristics of the arc magnets and to predict alternator demagnetization temperatures in the SRG110 application. Demagnetization tests using the TDC alternator on the Alternator Test Rig were conducted for two different magnet grades: Sumitomo Neomax 44AH and 42AH. The purpose of these tests was to determine the demagnetization temperatures of the magnets for the alternator under nominal loads. Measurements made during the tests included the linear alternator terminal voltage, current, average power, magnet temperatures, and stator temperatures. The results of these tests were found to be in good agreement with predictions. Alternator demagnetization temperatures in the Advanced Stirling Convertor (ASC-developed under the Advanced Stirling Radioisotope Generator project) were predicted as well because the prediction method had been validated through the SRG110 alternator tests. These predictions led to a specification for maximum temperatures of the ASC pressure vessel.

Predicting survival time in noncurative patients with advanced cancer: a prospective study in China.

PubMed

Cui, Jing; Zhou, Lingjun; Wee, B; Shen, Fengping; Ma, Xiuqiang; Zhao, Jijun

2014-05-01

Accurate prediction of prognosis for cancer patients is important for good clinical decision making in therapeutic and care strategies. The application of prognostic tools and indicators could improve prediction accuracy. This study aimed to develop a new prognostic scale to predict survival time of advanced cancer patients in China. We prospectively collected items that we anticipated might influence survival time of advanced cancer patients. Participants were recruited from 12 hospitals in Shanghai, China. We collected data including demographic information, clinical symptoms and signs, and biochemical test results. Log-rank tests, Cox regression, and linear regression were performed to develop a prognostic scale. Three hundred twenty patients with advanced cancer were recruited. Fourteen prognostic factors were included in the prognostic scale: Karnofsky Performance Scale (KPS) score, pain, ascites, hydrothorax, edema, delirium, cachexia, white blood cell (WBC) count, hemoglobin, sodium, total bilirubin, direct bilirubin, aspartate aminotransferase (AST), and alkaline phosphatase (ALP) values. The score was calculated by summing the partial scores, ranging from 0 to 30. When using the cutoff points of 7-day, 30-day, 90-day, and 180-day survival time, the scores were calculated as 12, 10, 8, and 6, respectively. We propose a new prognostic scale including KPS, pain, ascites, hydrothorax, edema, delirium, cachexia, WBC count, hemoglobin, sodium, total bilirubin, direct bilirubin, AST, and ALP values, which may help guide physicians in predicting the likely survival time of cancer patients more accurately. More studies are needed to validate this scale in the future.

An integrated approach to rotorcraft human factors research

NASA Technical Reports Server (NTRS)

Hart, Sandra G.; Hartzell, E. James; Voorhees, James W.; Bucher, Nancy M.; Shively, R. Jay

1988-01-01

As the potential of civil and military helicopters has increased, more complex and demanding missions in increasingly hostile environments have been required. Users, designers, and manufacturers have an urgent need for information about human behavior and function to create systems that take advantage of human capabilities, without overloading them. Because there is a large gap between what is known about human behavior and the information needed to predict pilot workload and performance in the complex missions projected for pilots of advanced helicopters, Army and NASA scientists are actively engaged in Human Factors Research at Ames. The research ranges from laboratory experiments to computational modeling, simulation evaluation, and inflight testing. Information obtained in highly controlled but simpler environments generates predictions which can be tested in more realistic situations. These results are used, in turn, to refine theoretical models, provide the focus for subsequent research, and ensure operational relevance, while maintaining predictive advantages. The advantages and disadvantages of each type of research are described along with examples of experimental results.

4D Origami by Smart Embroidery.

PubMed

Stoychev, Georgi; Razavi, Mir Jalil; Wang, Xianqiao; Ionov, Leonid

2017-09-01

There exist many methods for processing of materials: extrusion, injection molding, fibers spinning, 3D printing, to name a few. In most cases, materials with a static, fixed shape are produced. However, numerous advanced applications require customized elements with reconfigurable shape. The few available techniques capable of overcoming this problem are expensive and/or time-consuming. Here, the use of one of the most ancient technologies for structuring, embroidering, is proposed to generate sophisticated patterns of active materials, and, in this way, to achieve complex actuation. By combining experiments and computational modeling, the fundamental rules that can predict the folding behavior of sheets with a variety of stitch-patterns are elucidated. It is demonstrated that theoretical mechanics analysis is only suitable to predict the behavior of the simplest experimental setups, whereas computer modeling gives better predictions for more complex cases. Finally, the applicability of the rules by designing basic origami structures and wrinkling substrates with controlled thermal insulation properties is shown. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Advanced Technology Microwave Sounder (ATMS): The First 10 Months On-Orbit

NASA Technical Reports Server (NTRS)

Kim, Edward; Lyu, C-H Joseph; Blackwell, Willaim; Leslie, R. Vince; Baker, Neal; Mo, Tsan; Sun, Ninghai; Bi, Li; Anderson, Kent; Landrum, Mike;

Financing maneuvers. Two opportunities to boost a hospital's working capital.

PubMed

Ferconio, S; Lane, M R

1991-10-01

Two receivables financing approaches, factoring and asset-backed securitization, offer an initial cash flow boost and a predictable source for continual cash flow. In a typical receivables factoring program, a healthcare organization receives advance funding from its receivables and reduces collection and follow-up efforts required of its staff. In exchange, the organization: Sells receivables at a discount between 5 percent and 10 percent off face value; and Pays a factoring fee of up to 20 percent of sold receivables. In a typical asset-backed securitization: Proceeds generated from the sale of A1-rated commercial paper are used to purchase receivables from a hospital; Accounts receivable eligible for sale are advance-funded at a level between 80 and 90 percent, with the unfunded portion remaining an asset of the hospital; The hospital is responsible for collection and follow-up activities; and An asset manager maintains cash collections to retire commercial paper notes and pay administrative costs. A healthcare organization interested in receivables financing should review each option's structure and benefits to assess advance funding provided, costs, a seller's level of control, and program eligibility requirements.

Predictive Models for Carcinogenicity and Mutagenicity ...

EPA Pesticide Factsheets

Mutagenicity and carcinogenicity are endpoints of major environmental and regulatory concern. These endpoints are also important targets for development of alternative methods for screening and prediction due to the large number of chemicals of potential concern and the tremendous cost (in time, money, animals) of rodent carcinogenicity bioassays. Both mutagenicity and carcinogenicity involve complex, cellular processes that are only partially understood. Advances in technologies and generation of new data will permit a much deeper understanding. In silico methods for predicting mutagenicity and rodent carcinogenicity based on chemical structural features, along with current mutagenicity and carcinogenicity data sets, have performed well for local prediction (i.e., within specific chemical classes), but are less successful for global prediction (i.e., for a broad range of chemicals). The predictivity of in silico methods can be improved by improving the quality of the data base and endpoints used for modelling. In particular, in vitro assays for clastogenicity need to be improved to reduce false positives (relative to rodent carcinogenicity) and to detect compounds that do not interact directly with DNA or have epigenetic activities. New assays emerging to complement or replace some of the standard assays include VitotoxTM, GreenScreenGC, and RadarScreen. The needs of industry and regulators to assess thousands of compounds necessitate the development of high-t

Smolting in coastal cutthroat trout Onchorhynchus clarkii clarkii

USGS Publications Warehouse

Zydlewski, Joseph D.; Zydlewski, G.; Kennedy, B.; Gale, W.

2014-01-01

Gill Na+, K+-ATPase activity, condition factor and seawater (SW) challenges were used to assess the development of smolt characteristics in a cohort of hatchery coastal cutthroat trout Oncorhynchus clarkii clarkii from the Cowlitz River in Washington State, U.S.A. Gill Na+, K+-ATPase activity increased slightly in the spring, coinciding with an increase in hypo-osmoregulatory ability. These changes were of lesser magnitude than are observed in other salmonine species. Even at the peak of tolerance, these fish exhibited notable osmotic perturbations in full strength SW. Condition factor in these hatchery fish declined steadily through the spring. Wild captured migrants from four tributaries of the Columbia River had moderately elevated gill Na+, K+-ATPase activity, consistent with smolt development and with greater enzyme activity than autumn captured juveniles from one of the tributaries, Abernathy Creek. Migrant fish also had reduced condition factor. General linear models of 7 years of data from Abernathy Creek suggest that yearly variation, advancing photoperiod (as ordinal date) and fish size (fork length) were significant factors for predicting gill Na+, K+-ATPase activity in these wild fish. Both yearly variation and temperature were significant factors for predicting condition factor. These results suggest that coastal O. c. clarkii exhibit weakly developed characteristics of smolting. These changes are influenced by environmental conditions with great individual variation. The data suggest great physiological plasticity consistent with the variable life-history tactics observed in this species.

Shock-loading response of advanced materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gray, G.T. III

1993-08-01

Advanced materials, such as composites (metal, ceramic, or polymer-matrix), intermetallics, foams (metallic or polymeric-based), laminated materials, and nanostructured materials are receiving increasing attention because their properties can be custom tailored specific applications. The high-rate/impact response of advanced materials is relevant to a broad range of service environments such as the crashworthiness of civilian/military vehicles, foreign-object-damage in aerospace, and light-weight armor. Increased utilization of these material classes under dynamic loading conditions requires an understanding of the relationship between high-rate/shock-wave response as a function of microstructure if we are to develop models to predict material behavior. In this paper the issues relevantmore » to defect generation, storage, and the underlying physical basis needed in predictive models for several advanced materials will be reviewed.« less

Prototype Tool and Focus Group Evaluation for an Advanced Trajectory-Based Operations Concept

NASA Technical Reports Server (NTRS)

Guerreiro, Nelson M.; Jones, Denise R.; Barmore, Bryan E.; Butler, Ricky W.; Hagen, George E.; Maddalon, Jeffrey M.; Ahmad, Nash'at N.

2017-01-01

Trajectory-based operations (TBO) is a key concept in the Next Generation Air Transportation System transformation of the National Airspace System (NAS) that will increase the predictability and stability of traffic flows, support a common operational picture through the use of digital data sharing, facilitate more effective collaborative decision making between airspace users and air navigation service providers, and enable increased levels of integrated automation across the NAS. NASA has been developing trajectory-based systems to improve the efficiency of the NAS during specific phases of flight and is now also exploring Advanced 4-Dimensional Trajectory (4DT) operational concepts that will integrate these technologies and incorporate new technology where needed to create both automation and procedures to support gate-to-gate TBO. A TBO Prototype simulation toolkit has been developed that demonstrates initial functionality of an Advanced 4DT TBO concept. Pilot and controller subject matter experts (SMEs) were brought to the Air Traffic Operations Laboratory at NASA Langley Research Center for discussions on an Advanced 4DT operational concept and were provided an interactive demonstration of the TBO Prototype using four example scenarios. The SMEs provided feedback on potential operational, technological, and procedural opportunities and concerns. This paper describes an Advanced 4DT operational concept, the TBO Prototype, the demonstration scenarios and methods used, and the feedback obtained from the pilot and controller SMEs in this focus group activity.

TransCONFIRM: Identification of a Genetic Signature of Response to Fulvestrant in Advanced Hormone Receptor-Positive Breast Cancer.

PubMed

Jeselsohn, Rinath; Barry, William T; Migliaccio, Ilenia; Biagioni, Chiara; Zhao, Jin; De Tribolet-Hardy, Jonas; Guarducci, Cristina; Bonechi, Martina; Laing, Naomi; Winer, Eric P; Brown, Myles; Leo, Angelo Di; Malorni, Luca

2016-12-01

Fulvestrant is an estrogen receptor (ER) antagonist and an approved treatment for metastatic estrogen receptor-positive (ER + ) breast cancer. With the exception of ER levels, there are no established predictive biomarkers of response to single-agent fulvestrant. We attempted to identify a gene signature of response to fulvestrant in advanced breast cancer. Primary tumor samples from 134 patients enrolled in the phase III CONFIRM study of patients with metastatic ER + breast cancer comparing treatment with either 250 mg or 500 mg fulvestrant were collected for genome-wide transcriptomic analysis. Gene expression profiling was performed using Affymetrix microarrays. An exploratory analysis was performed to identify biologic pathways and new signatures associated with response to fulvestrant. Pathway analysis demonstrated that increased EGF pathway and FOXA1 transcriptional signaling is associated with decreased response to fulvestrant. Using a multivariate Cox model, we identified a novel set of 37 genes with an expression that is independently associated with progression-free survival (PFS). TFAP2C, a known regulator of ER activity, was ranked second in this gene set, and high expression was associated with a decreased response to fulvestrant. The negative predictive value of TFAP2C expression at the protein level was confirmed by IHC. We identified biologic pathways and a novel gene signature in primary ER + breast cancers that predicts for response to treatment in the CONFIRM study. These results suggest potential new therapeutic targets and warrant further validation as predictive biomarkers of fulvestrant treatment in metastatic breast cancer. Clin Cancer Res; 22(23); 5755-64. ©2016 AACR. ©2016 American Association for Cancer Research.

Genome-wide prediction of cis-regulatory regions using supervised deep learning methods.

PubMed

Li, Yifeng; Shi, Wenqiang; Wasserman, Wyeth W

2018-05-31

In the human genome, 98% of DNA sequences are non-protein-coding regions that were previously disregarded as junk DNA. In fact, non-coding regions host a variety of cis-regulatory regions which precisely control the expression of genes. Thus, Identifying active cis-regulatory regions in the human genome is critical for understanding gene regulation and assessing the impact of genetic variation on phenotype. The developments of high-throughput sequencing and machine learning technologies make it possible to predict cis-regulatory regions genome wide. Based on rich data resources such as the Encyclopedia of DNA Elements (ENCODE) and the Functional Annotation of the Mammalian Genome (FANTOM) projects, we introduce DECRES based on supervised deep learning approaches for the identification of enhancer and promoter regions in the human genome. Due to their ability to discover patterns in large and complex data, the introduction of deep learning methods enables a significant advance in our knowledge of the genomic locations of cis-regulatory regions. Using models for well-characterized cell lines, we identify key experimental features that contribute to the predictive performance. Applying DECRES, we delineate locations of 300,000 candidate enhancers genome wide (6.8% of the genome, of which 40,000 are supported by bidirectional transcription data), and 26,000 candidate promoters (0.6% of the genome). The predicted annotations of cis-regulatory regions will provide broad utility for genome interpretation from functional genomics to clinical applications. The DECRES model demonstrates potentials of deep learning technologies when combined with high-throughput sequencing data, and inspires the development of other advanced neural network models for further improvement of genome annotations.

Lingering effects of preceding strong El Niño events on the typhoon activity in early summer: Case study of sub-seasonal and seasonal predictions in 2016

NASA Astrophysics Data System (ADS)

Takaya, Y.; Kubo, Y.; Yamaguchi, M.; Vitart, F.; Hirahara, S.; Maeda, S.

2016-12-01

Strong El Niño events have lingering effects on the seasonal variability in the Indo- western Pacific region in the mature-decay phase of El Niño. Specifically, in the decay phase, a low-level anticyclonic circulation and suppressed convection in the western North Pacific are enforced as a result of a local air-sea feedback in the western North Pacific and remote response to the Indian Ocean warming due to El Niño. The typhoon activity in the western North Pacific is also modulated by the lingering effects in the early typhoon season (boreal spring to early summer) following the strong El Niño events. This study investigates underlying mechanisms and predictability by analyzing the historical analysis data, subseasonal and seasonal reforecast data, and sensitivity experiments with the use of an atmosphere-ocean coupled model for the 2016 typhoon season. In this study, we focus on the remote response of the typhoon activity in the Indo-Pacific region. First, we examined the case of 2016, which exhibited the striking inactive typhoon activity and marked the second latest genesis of the first typhoon of the year since 1977 (Typhoon Nipartak on 3 July 2016). The inactive typhoon activity in the early typhoon season of 2016 is plausibly related to the lingering effects of the preceding strong El Niño in 2015/2016 winter. And the inactive typhoon condition and its related atmosphere-ocean conditions in the western north Pacific were successfully predicted with sub-seasonal prediction systems and JMA seasonal prediction system (JMA/MRI-CPS2) well in advance. A composite analysis using historical analysis data indicates that the typhoon activity tends to be suppressed associated with the Indian Ocean warming in boreal spring to summer following El Niño winters. This is relatively well replicated in reforecasts of JMA/MRI-CPS2. We also carried out sensitivity experiments with JMA/MRI-CPS2, where we strongly nudge sea surface temperature (SST) in the Indian Ocean to climatological SST. The typhoon activity in the western North Pacific is enhanced in the sensitivity experiment, implying that the the Indian Ocean played a role in shaping the inactive typhoon conditions in the 2016 typhoon season. We will further discuss the underlying mechanisms and predictability using the series of experiments.

Nuclease Target Site Selection for Maximizing On-target Activity and Minimizing Off-target Effects in Genome Editing

PubMed Central

Lee, Ciaran M; Cradick, Thomas J; Fine, Eli J; Bao, Gang

2016-01-01

The rapid advancement in targeted genome editing using engineered nucleases such as ZFNs, TALENs, and CRISPR/Cas9 systems has resulted in a suite of powerful methods that allows researchers to target any genomic locus of interest. A complementary set of design tools has been developed to aid researchers with nuclease design, target site selection, and experimental validation. Here, we review the various tools available for target selection in designing engineered nucleases, and for quantifying nuclease activity and specificity, including web-based search tools and experimental methods. We also elucidate challenges in target selection, especially in predicting off-target effects, and discuss future directions in precision genome editing and its applications. PMID:26750397

Blueprint for antimicrobial hit discovery targeting metabolic networks.

PubMed

Shen, Y; Liu, J; Estiu, G; Isin, B; Ahn, Y-Y; Lee, D-S; Barabási, A-L; Kapatral, V; Wiest, O; Oltvai, Z N

2010-01-19

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy.

Comparisons of several aerodynamic methods for application to dynamic loads analyses

NASA Technical Reports Server (NTRS)

Kroll, R. I.; Miller, R. D.

1976-01-01

The results of a study are presented in which the applicability at subsonic speeds of several aerodynamic methods for predicting dynamic gust loads on aircraft, including active control systems, was examined and compared. These aerodynamic methods varied from steady state to an advanced unsteady aerodynamic formulation. Brief descriptions of the structural and aerodynamic representations and of the motion and load equations are presented. Comparisons of numerical results achieved using the various aerodynamic methods are shown in detail. From these results, aerodynamic representations for dynamic gust analyses are identified. It was concluded that several aerodynamic methods are satisfactory for dynamic gust analyses of configurations having either controls fixed or active control systems that primarily affect the low frequency rigid body aircraft response.

Space activities - A review and a look ahead

NASA Technical Reports Server (NTRS)

Durrani, S. H.

1984-01-01

The paper reviews the progress made in manned and unmanned space programs during the last 25 years and names several major accomplishments. The ingredients of success are identified as good engineering, good technology, and good management of a very complex enterprise. An argument is made that the pace of progress will be governed not by technological advances, which can be very rapid, but rather by future institutional arrangements, which are much slower to evolve. It is predicted that the most likely space activities for the next 20 years will be those relating to space commercialization, and several examples are cited. A hope is expressed that policy makers and entrepreneurs will match the spirit of adventure and risk-taking exhibited by engineers in exploring uncharted territory.

Active Control of Inlet Noise on the JT15D Turbofan Engine

NASA Technical Reports Server (NTRS)

Smith, Jerome P.; Hutcheson, Florence V.; Burdisso, Ricardo A.; Fuller, Chris R.

1999-01-01

This report presents the key results obtained by the Vibration and Acoustics Laboratories at Virginia Tech over the year from November 1997 to December 1998 on the Active Noise Control of Turbofan Engines research project funded by NASA Langley Research Center. The concept of implementing active noise control techniques with fuselage-mounted error sensors is investigated both analytically and experimentally. The analytical part of the project involves the continued development of an advanced modeling technique to provide prediction and design guidelines for application of active noise control techniques to large, realistic high bypass engines of the type on which active control methods are expected to be applied. Results from the advanced analytical model are presented that show the effectiveness of the control strategies, and the analytical results presented for fuselage error sensors show good agreement with the experimentally observed results and provide additional insight into the control phenomena. Additional analytical results are presented for active noise control used in conjunction with a wavenumber sensing technique. The experimental work is carried out on a running JT15D turbofan jet engine in a test stand at Virginia Tech. The control strategy used in these tests was the feedforward Filtered-X LMS algorithm. The control inputs were supplied by single and multiple circumferential arrays of acoustic sources equipped with neodymium iron cobalt magnets mounted upstream of the fan. The reference signal was obtained from an inlet mounted eddy current probe. The error signals were obtained from a number of pressure transducers flush-mounted in a simulated fuselage section mounted in the engine test cell. The active control methods are investigated when implemented with the control sources embedded within the acoustically absorptive material on a passively-lined inlet. The experimental results show that the combination of active control techniques with fuselage-mounted error sensors and passive control techniques is an effective means of reducing radiated noise from turbofan engines. Strategic selection of the location of the error transducers is shown to be effective for reducing the radiation towards particular directions in the farfield. An analytical model is used to predict the behavior of the control system and to guide the experimental design configurations, and the analytical results presented show good agreement with the experimentally observed results.

Harvest survivability of oak advanced regeneration

Treesearch

Jeff Stringer

2005-01-01

Natural regeneration of oak requires the occurrence of advance regeneration and/or stems capable of stump sprouting. These stems must be present before harvest and adequate numbers must survive harvest for oaks to successfully regenerate. Regeneration predictions are based on pre-harvest advance regeneration inventories. However, the use of these inventories does not...

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability

EPA Pesticide Factsheets

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

Comparison of Glasgow prognostic score and prognostic index in patients with advanced non-small cell lung cancer.

PubMed

Jiang, Ai-Gui; Chen, Hong-Lin; Lu, Hui-Yu

2015-03-01

Previous studies have shown that Glasgow prognostic score (GPS) and prognostic index (PI) are also powerful prognostic tool for patients with advanced non-small cell lung cancer (NSCLC). The aim of this study was to compare the prognostic value between GPS and PI. We enrolled consecutive patients with advanced NSCLC in this prospective cohort. GPS and PI were calculated before the onset of chemotherapy. The prognosis outcomes included 1-, 3-, and 5-year progression-free survival and overall survival (OS). The performance of two scores in predicting prognosis was analyzed regarding discrimination and calibration. 138 patients were included in the study. The area under the receiver operating characteristic curve for GPS predicting 1-year DFS was 0.62 (95 % confidence interval (CI) 0.56-0.68, P < 0.05), and the area under curve for PI predicting 1-year DFS was 0.57 (95 % CI 0.52-0.63). Delong's test showed that GPS was more accurate than PI in predicting 1-year DFS (P < 0.05). Similar results of discriminatory power were found for predicting 3-year DFS, 1-year OS, and 3-year OS. The predicted 1-year DFS by GPS 0, GPS 1, and GPS 2 were 62.5, 42.1, and 23.1 %, respectively, while actual 1-year DFS by GPS 0, GPS 1, and GPS 2 were 61.1, 43.8, and 27.2 %, respectively. Calibration of the Hosmer and Lemeshow statistic showed good fit of the predicted 1-year DFS to the actual 1-year DFS by GPS (χ(2) = 4.326, P = 0.462), while no fit was found between the predicted 1-year DFS and the actual 1-year DFS by PI (χ(2) = 15.234, P = 0.091). Similar results of calibration power were found for predicting 3-year DFS, 5-year DFS, 1-year OS, 3-year OS, and 5-year OS by GPS and PI. GPS is more accurate than PI in predicting prognosis for patients with advanced NSCLC. GPS can be used as a useful and simple tool for predicting prognosis in patients with NSCLC. However, GPS only can be used for preliminary assessment because of low predicting accuracy.

Influence of the El Niño/Southern Oscillation on tornado and hail frequency in the United States

NASA Astrophysics Data System (ADS)

Allen, John T.; Tippett, Michael K.; Sobel, Adam H.

2015-04-01

The El Niño/Southern Oscillation (ENSO) is characterized by changes in sea surface temperature (SST) and atmospheric convection in the tropical Pacific, and modulates global weather and climate. The phase of ENSO influences United States (US) temperature and precipitation and has long been hypothesized to influence severe thunderstorm occurrence over the US. However, limitations of the severe thunderstorm observational record, combined with large year-to-year variability, have made it difficult to demonstrate an ENSO influence during the peak spring season. Here we use environmental indices that are correlated with tornado and hail activity, and show that ENSO modulates tornado and hail occurrence during the winter and spring by altering the large-scale environment. We show that fewer tornadoes and hail events occur over the central US during El Niño and conversely more occur during La Niña conditions. Moreover, winter ENSO conditions often persist into early spring, and consequently the winter ENSO state can be used to predict changes in tornado and hail frequency during the following spring. Combined with our current ability to predict ENSO several months in advance, our findings provide a basis for long-range seasonal prediction of severe thunderstorm activity.

Recent advances in the in silico modelling of UDP glucuronosyltransferase substrates.

PubMed

Sorich, Michael J; Smith, Paul A; Miners, John O; Mackenzie, Peter I; McKinnon, Ross A

2008-01-01

UDP glucurononosyltransferases (UGT) are a superfamily of enzymes that catalyse the conjugation of a range of structurally diverse drugs, environmental and endogenous chemicals with glucuronic acid. This process plays a significant role in the clearance and detoxification of many chemicals. Over the last decade the regulation and substrate profiles of UGT isoforms have been increasingly characterised. The resulting data has facilitated the prototyping of ligand based in silico models capable of predicting, and gaining insights into, binding affinity and the substrate- and regio- selectivity of glucuronidation by UGT isoforms. Pharmacophore modelling has produced particularly insightful models and quantitative structure-activity relationships based on machine learning algorithms result in accurate predictions. Simple structural chemical descriptors were found to capture much of the chemical information relevant to UGT metabolism. However, quantum chemical properties of molecules and the nucleophilic atoms in the molecule can enhance both the predictivity and chemical intuitiveness of structure-activity models. Chemical diversity analysis of known substrates has shown some bias towards chemicals with aromatic and aliphatic hydroxyl groups. Future progress in in silico development will depend on larger and more diverse high quality metabolic datasets. Furthermore, improved protein structure data on UGTs will enable the application of structural modelling techniques likely leading to greater insight into the binding and reactive processes of UGT catalysed glucuronidation.

Significance of different carbon forms and carbonic anhydrase activity in monitoring and prediction of algal blooms in the urban section of Jialing River, Chongqing, China.

PubMed

Nie, Yudong; Zhang, Zhi; Shen, Qian; Gao, Wenjin; Li, Yingfan

2016-05-18

The Three Gorges Dam is one of the largest hydroelectric power plants worldwide; its reservoir was preliminarily impounded in 2003 and finally impounded to 175 m in 2012. The impoundment caused some environmental problems, such as algal blooms. Carbonic anhydrase (CA) is an important biocatalyst in the carbon utilization by algae and plays an important role in algal blooms. CA has received considerable attention for its role in red tides in oceans, but less investigation has been focused on its role in algal blooms in fresh water. In this study, the seasonal variation of water quality parameters, different carbon forms, carbonic anhydrase activity (CAA), and the algal cell density of four sampling sites in the urban section of the Jialing River were investigated from November 1, 2013 to October 31, 2014. Results indicated that CAA exhibited a positive correlation with dissoluble organic carbon (DOC), pH, and temperature, but a negative correlation with CO2 and dissoluble inorganic carbon (DIC). Algal cell density exhibited a positive correlation with flow velocity (V), pH, particulate organic carbon (POC), and CAA, a negative correlation with CO2, and a negative partial correlation with DIC. The relationship between CAA and algal cell density for the entire year can be described as cells = 23.278CAA - 42.666POC + 139.547pH - 1057.106. The algal bloom prediction model for the key control period can be described as cells = -45.895CAA + 776.103V- 29.523DOC + 14.219PIC + 35.060POC + 19.181 (2 weeks in advance) and cells = 69.200CAA + 203.213V + 4.184CO2 + 38.911DOC + 40.770POC - 189.567 (4 weeks in advance). The findings in this study demonstrate that the carbon utilization by algae is conducted by CA and provide a new method of monitoring algal cell density and predicting algal blooms.

Progress in Earth System Modeling since the ENIAC Calculation

NASA Astrophysics Data System (ADS)

Fung, I.

2009-05-01

The success of the first numerical weather prediction experiment on the ENIAC computer in 1950 was hinged on the expansion of the meteorological observing network, which led to theoretical advances in atmospheric dynamics and subsequently the implementation of the simplified equations on the computer. This paper briefly reviews the progress in Earth System Modeling and climate observations, and suggests a strategy to sustain and expand the observations needed to advance climate science and prediction.

Environment assisted degradation mechanisms in advanced light metals

NASA Technical Reports Server (NTRS)

Gangloff, R. P.; Stoner, G. E.; Swanson, R. E.

1989-01-01

A multifaceted research program on the performance of advanced light metallic alloys in aggressive aerospace environments, and associated environmental failure mechanisms was initiated. The general goal is to characterize alloy behavior quantitatively and to develop predictive mechanisms for environmental failure modes. Successes in this regard will provide the basis for metallurgical optimization of alloy performance, for chemical control of aggressive environments, and for engineering life prediction with damage tolerance and long term reliability.

Development of advanced structural analysis methodologies for predicting widespread fatigue damage in aircraft structures

NASA Technical Reports Server (NTRS)

Harris, Charles E.; Starnes, James H., Jr.; Newman, James C., Jr.

1995-01-01

NASA is developing a 'tool box' that includes a number of advanced structural analysis computer codes which, taken together, represent the comprehensive fracture mechanics capability required to predict the onset of widespread fatigue damage. These structural analysis tools have complementary and specialized capabilities ranging from a finite-element-based stress-analysis code for two- and three-dimensional built-up structures with cracks to a fatigue and fracture analysis code that uses stress-intensity factors and material-property data found in 'look-up' tables or from equations. NASA is conducting critical experiments necessary to verify the predictive capabilities of the codes, and these tests represent a first step in the technology-validation and industry-acceptance processes. NASA has established cooperative programs with aircraft manufacturers to facilitate the comprehensive transfer of this technology by making these advanced structural analysis codes available to industry.

Automatic prediction of solar flares and super geomagnetic storms

NASA Astrophysics Data System (ADS)

Song, Hui

Space weather is the response of our space environment to the constantly changing Sun. As the new technology advances, mankind has become more and more dependent on space system, satellite-based services. A geomagnetic storm, a disturbance in Earth's magnetosphere, may produce many harmful effects on Earth. Solar flares and Coronal Mass Ejections (CMEs) are believed to be the major causes of geomagnetic storms. Thus, establishing a real time forecasting method for them is very important in space weather study. The topics covered in this dissertation are: the relationship between magnetic gradient and magnetic shear of solar active regions; the relationship between solar flare index and magnetic features of solar active regions; based on these relationships a statistical ordinal logistic regression model is developed to predict the probability of solar flare occurrences in the next 24 hours; and finally the relationship between magnetic structures of CME source regions and geomagnetic storms, in particular, the super storms when the D st index decreases below -200 nT is studied and proved to be able to predict those super storms. The results are briefly summarized as follows: (1) There is a significant correlation between magnetic gradient and magnetic shear of active region. Furthermore, compared with magnetic shear, magnetic gradient might be a better proxy to locate where a large flare occurs. It appears to be more accurate in identification of sources of X-class flares than M-class flares; (2) Flare index, defined by weighting the SXR flares, is proved to have positive correlation with three magnetic features of active region; (3) A statistical ordinal logistic regression model is proposed for solar flare prediction. The results are much better than those data published in the NASA/SDAC service, and comparable to the data provided by the NOAA/SEC complicated expert system. To our knowledge, this is the first time that logistic regression model has been applied in solar physics to predict flare occurrences; (4) The magnetic orientation angle [straight theta], determined from a potential field model, is proved to be able to predict the probability of super geomagnetic storms (D= st <=-200nT). The results show that those active regions associated with | [straight theta]| < 90° are more likely to cause a super geomagnetic storm.

The Influence of Big (Clinical) Data and Genomics on Precision Medicine and Drug Development.

PubMed

Denny, Joshua C; Van Driest, Sara L; Wei, Wei-Qi; Roden, Dan M

2018-03-01

Drug development continues to be costly and slow, with medications failing due to lack of efficacy or presence of toxicity. The promise of pharmacogenomic discovery includes tailoring therapeutics based on an individual's genetic makeup, rational drug development, and repurposing medications. Rapid growth of large research cohorts, linked to electronic health record (EHR) data, fuels discovery of new genetic variants predicting drug action, supports Mendelian randomization experiments to show drug efficacy, and suggests new indications for existing medications. New biomedical informatics and machine-learning approaches advance the ability to interpret clinical information, enabling identification of complex phenotypes and subpopulations of patients. We review the recent history of use of "big data" from EHR-based cohorts and biobanks supporting these activities. Future studies using EHR data, other information sources, and new methods will promote a foundation for discovery to more rapidly advance precision medicine. © 2017 American Society for Clinical Pharmacology and Therapeutics.

HEPEX - achievements and challenges!

NASA Astrophysics Data System (ADS)

Pappenberger, Florian; Ramos, Maria-Helena; Thielen, Jutta; Wood, Andy; Wang, Qj; Duan, Qingyun; Collischonn, Walter; Verkade, Jan; Voisin, Nathalie; Wetterhall, Fredrik; Vuillaume, Jean-Francois Emmanuel; Lucatero Villasenor, Diana; Cloke, Hannah L.; Schaake, John; van Andel, Schalk-Jan

2014-05-01

HEPEX is an international initiative bringing together hydrologists, meteorologists, researchers and end-users to develop advanced probabilistic hydrological forecast techniques for improved flood, drought and water management. HEPEX was launched in 2004 as an independent, cooperative international scientific activity. During the first meeting, the overarching goal was defined as: "to develop and test procedures to produce reliable hydrological ensemble forecasts, and to demonstrate their utility in decision making related to the water, environmental and emergency management sectors." The applications of hydrological ensemble predictions span across large spatio-temporal scales, ranging from short-term and localized predictions to global climate change and regional modeling. Within the HEPEX community, information is shared through its blog (www.hepex.org), meetings, testbeds and intercompaison experiments, as well as project reportings. Key questions of HEPEX are: * What adaptations are required for meteorological ensemble systems to be coupled with hydrological ensemble systems? * How should the existing hydrological ensemble prediction systems be modified to account for all sources of uncertainty within a forecast? * What is the best way for the user community to take advantage of ensemble forecasts and to make better decisions based on them? This year HEPEX celebrates its 10th year anniversary and this poster will present a review of the main operational and research achievements and challenges prepared by Hepex contributors on data assimilation, post-processing of hydrologic predictions, forecast verification, communication and use of probabilistic forecasts in decision-making. Additionally, we will present the most recent activities implemented by Hepex and illustrate how everyone can join the community and participate to the development of new approaches in hydrologic ensemble prediction.

Predictive factors for overall quality of life in patients with advanced cancer.

PubMed

Cramarossa, Gemma; Chow, Edward; Zhang, Liying; Bedard, Gillian; Zeng, Liang; Sahgal, Arjun; Vassiliou, Vassilios; Satoh, Takefumi; Foro, Palmira; Ma, Brigette B Y; Chie, Wei-Chu; Chen, Emily; Lam, Henry; Bottomley, Andrew

2013-06-01

This study examined which domains/symptoms from the European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire Core 15 Palliative (QLQ-C15-PAL), an abbreviated version of the health-related EORTC QLQ-C30 questionnaire designed for palliative cancer patients, were predictive of overall quality of life (QOL) in advanced cancer patients. Patients with advanced cancer from six countries completed the QLQ-C15-PAL at consultation and at one follow-up point. Univariate and multivariate regression analyses were conducted to determine the predictive value of the EORTC QLQ-C15-PAL functional/symptom scores for global QOL (question 15). Three hundred forty-nine patients completed the EORTC QLQ-C15-PAL at baseline. In the total patient sample, worse emotional functioning, pain, and appetite loss were the most significant predictive factors for worse QOL. In the subgroup of patients with bone metastases (n = 240), the domains mentioned above were also the most significant predictors, whereas in patients with brain metastases (n = 109), worse physical and emotional functioning most significantly predicted worse QOL. One-month follow-up in 267 patients revealed that the significant predictors changed somewhat over time. For example, in the total patient sample, physical functioning, fatigue, and appetite loss were significant predictors at the follow-up point. A sub-analysis of predictive factors affecting QOL by primary cancer (lung, breast, and prostate) was also conducted for the total patient sample. Deterioration of certain EORTC QLQ-C15-PAL functional/symptom scores significantly contributes to worse overall QOL. Special attention should be directed to managing factors most influential on overall QOL to ensure optimal management of advanced cancer patients.

Advanced Hepatocellular Carcinoma: Which Staging Systems Best Predict Prognosis?

PubMed Central

Huitzil-Melendez, Fidel-David; Capanu, Marinela; O'Reilly, Eileen M.; Duffy, Austin; Gansukh, Bolorsukh; Saltz, Leonard L.; Abou-Alfa, Ghassan K.

2010-01-01

Purpose The purpose of cancer staging systems is to accurately predict patient prognosis. The outcome of advanced hepatocellular carcinoma (HCC) depends on both the cancer stage and the extent of liver dysfunction. Many staging systems that include both aspects have been developed. It remains unknown, however, which of these systems is optimal for predicting patient survival. Patients and Methods Patients with advanced HCC treated over a 5-year period at Memorial Sloan-Kettering Cancer Center were identified from an electronic medical record database. Patients with sufficient data for utilization in all staging systems were included. TNM sixth edition, Okuda, Barcelona Clinic Liver Cancer (BCLC), Cancer of the Liver Italian Program (CLIP), Chinese University Prognostic Index (CUPI), Japan Integrated Staging (JIS), and Groupe d'Etude et de Traitement du Carcinome Hepatocellulaire (GETCH) systems were ranked on the basis of their accuracy at predicting survival by using concordance index (c-index). Other independent prognostic variables were also identified. Results Overall, 187 eligible patients were identified and were staged by using the seven staging systems. CLIP, CUPI, and GETCH were the three top-ranking staging systems. BCLC and TNM sixth edition lacked any meaningful prognostic discrimination. Performance status, AST, abdominal pain, and esophageal varices improved the discriminatory ability of CLIP. Conclusion In our selected patient population, CLIP, CUPI, and GETCH were the most informative staging systems in predicting survival in patients with advanced HCC. Prospective validation is required to determine if they can be accurately used to stratify patients in clinical trials and to direct the appropriate need for systemic therapy versus best supportive care. BCLC and TNM sixth edition were not helpful in predicting survival outcome, and their use is not supported by our data. PMID:20458042

Advanced chronic kidney disease in non-valvular atrial fibrillation: extending the utility of R2CHADS2 to patients with advanced renal failure.

PubMed

Bautista, Josef; Bella, Archie; Chaudhari, Ashok; Pekler, Gerald; Sapra, Katherine J; Carbajal, Roger; Baumstein, Donald

2015-04-01

The R2CHADS2 is a new prediction rule for stroke risk in atrial fibrillation (AF) patients wherein R stands for renal risk. However, it was created from a cohort that excluded patients with advanced renal failure (defined as glomerular filtration rate of <30 mL/min). Our study extends the use of R2CHADS2 to patients with advanced renal failure and aims to compare its predictive power against the currently used CHADS and CHA2DS2VaSc. This retrospective cohort study analyzed the 1-year risk for stroke of the 524 patients with AF at Metropolitan Hospital Center. AUC and C statistics were calculated using three groups: (i) the entire cohort including patients with advanced renal failure, (ii) a cohort excluding patients with advanced renal failure and (iii) all patients with GFR < 30 mL/min only. R2CHADS2, as a predictor for stroke risk, consistently performs better than CHADS2 and CHA2DS2VsC in groups 1 and 2. The C-statistic was highest in R2CHADS compared with CHADS or CHADSVASC in group 1 (0.718 versus 0.605 versus 0.602) and in group 2 (0.724 versus 0.584 versus 0.579). However, there was no statistically significant difference in group 3 (0.631 versus 0.629 versus 0.623). Our study supports the utility of R2CHADS2 as a clinical prediction rule for stroke risk in patients with advanced renal failure.

Advance Noise Control Fan II: Test Rig Fan Risk Management Study

NASA Technical Reports Server (NTRS)

Lucero, John

2013-01-01

Since 1995 the Advanced Noise Control Fan (ANCF) has significantly contributed to the advancement of the understanding of the physics of fan tonal noise generation. The 9'x15' WT has successfully tested multiple high speed fan designs over the last several decades. This advanced several tone noise reduction concepts to higher TRL and the validation of fan tone noise prediction codes.

Wearable activity monitors in oncology trials: Current use of an emerging technology.

PubMed

Gresham, Gillian; Schrack, Jennifer; Gresham, Louise M; Shinde, Arvind M; Hendifar, Andrew E; Tuli, Richard; Rimel, B J; Figlin, Robert; Meinert, Curtis L; Piantadosi, Steven

2018-01-01

Physical activity is an important outcome in oncology trials. Physical activity is commonly assessed using self-reported questionnaires, which are limited by recall and response biases. Recent advancements in wearable technology have provided oncologists with new opportunities to obtain real-time, objective physical activity data. The purpose of this review was to describe current uses of wearable activity monitors in oncology trials. We searched Pubmed, Embase, and the Cochrane Central Register of Controlled Trials for oncology trials involving wearable activity monitors published between 2005 and 2016. We extracted details on study design, types of activity monitors used, and purpose for their use. We summarized activity monitor metrics including step counts, sleep and sedentary time, and time spent in moderate-to-vigorous activity. We identified 41 trials of which 26 (63%) involved cancer survivors (post-treatment) and 15 trials (37%) involved patients with active cancer. Most trials (65%) involved breast cancer patients. Wearable activity monitors were commonly used in exercise (54%) or behavioral (29%) trials. Cancer survivors take between 4660 and 11,000 steps/day and those undergoing treatment take 2885 to 8300steps/day. Wearable activity monitors are increasingly being used to obtain objective measures of physical activity in oncology trials. There is potential for their use to expand to evaluate and predict clinical outcomes such as survival, quality of life, and treatment tolerance in future studies. Currently, there remains a lack of standardization in the types of monitors being used and how their data are being collected, analyzed, and interpreted. Recent advancements in wearable activity monitor technology have provided oncologists with new opportunities to monitor their patients' daily activity in real-world settings. The integration of wearable activity monitors into cancer care will help increase our understanding of the associations between physical activity and the prevention and management of the disease, in addition to other important cancer outcomes. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Marital Conflict Predicts Mother-to-Infant Adrenocortical Transmission.

PubMed

Hibel, Leah C; Mercado, Evelyn

2017-12-21

Employing an experimental design, mother-to-infant transmission of stress was examined. Mothers (N = 117) were randomized to either have a positive or conflictual discussion with their marital partners, after which infants (age = 6 months) participated in a fear and frustration task. Saliva samples were collected to assess maternal cortisol responses to the discussion and infant cortisol responses to the challenge task. Results indicate maternal cortisol reactivity and recovery to the conflict (but not positive) discussion predicted infant cortisol reactivity to the infant challenge. Mothers' positive affect during the discussion buffered, and intrusion during the free-play potentiated, mother-to-infant adrenocortical transmission. These findings advance our understanding of the social and contextual regulation of adrenocortical activity in early childhood. © 2017 The Authors. Child Development © 2017 Society for Research in Child Development, Inc.

Prediction of perceptual defense from experimental stress and susceptibility to stress as indicated by thematic apperception.

PubMed

Tuma, J M

1975-02-01

The present investigation tested the hypothesis advanced by J. Inglis (1961) that perceptual defense and perceptual vigilance result from an interaction between personality differences and degrees of experimental stress. The design, which controlled for questionable procedures used in previous studies, utilized 32 introverts and 32 extraverts, half male and half female, in an experiment with a visual recognition-task. Results indicated that under low-stress conditions introverts and extraverts identified by their response to a thematic apperception task react to threatening stimuli with perceptual defense and perceptual vigilance, respectively. Under high-stress conditions, type of avoidance activity reverses; extraverts react with perceptual defense and introverts with perceptual vigilance. It was suggested that, when both personality and stress variables are controlled, results of the perceptual defense paradigm are predictable and consistent, in support of Inglis' hypothesis.

GEM: Geospace Environment Modeling

NASA Astrophysics Data System (ADS)

Roederer, Juan G.

Shortly after the beginning of the “space age” with the launching of the first man made object into terrestrial orbit, geospace assumed a fundamental role as a technological resource for all countries, advanced and developing alike. Today, satellite systems for communications, weather prediction, navigation, and remote sensing of natural resources are supporting, in an essential way, many facets of societal operations. We must expect that this trend will continue; for instance, in perhaps less than 3 decades, transatmospheric transportation will be routine and satellite systems will sustain human colonies in space.The medium in which Earth-orbiting systems operate is hostile. Far from a perfect vacuum, it is made up of high-temperature gas and corpuscular radiation of varying densities and intensities; these solar-activity controlled variations can reach proportions dangerous to orbital stability, to electronic systems performance, to shuttle and spaceplane reentry, and to the life of humans in orbit. Dramatic examples of solar-activity-induced satellite failures are the unexpected early degradation of the orbit of Skylab due to unusual upper atmosphere heating and the demise of satellite GOES-5, most probably caused by a large injection of energetic electrons from the outer magnetoshere. The need to predict “weather and climate” in geospace is becoming as important as the need to predict weather and climate in the inhospitable regions on Earth into which industrial activity has moved during the last decades, such as the Arctic and some of the arid lands.

General theory for integrated analysis of growth, gene, and protein expression in biofilms.

PubMed

Zhang, Tianyu; Pabst, Breana; Klapper, Isaac; Stewart, Philip S

2013-01-01

A theory for analysis and prediction of spatial and temporal patterns of gene and protein expression within microbial biofilms is derived. The theory integrates phenomena of solute reaction and diffusion, microbial growth, mRNA or protein synthesis, biomass advection, and gene transcript or protein turnover. Case studies illustrate the capacity of the theory to simulate heterogeneous spatial patterns and predict microbial activities in biofilms that are qualitatively different from those of planktonic cells. Specific scenarios analyzed include an inducible GFP or fluorescent protein reporter, a denitrification gene repressed by oxygen, an acid stress response gene, and a quorum sensing circuit. It is shown that the patterns of activity revealed by inducible stable fluorescent proteins or reporter unstable proteins overestimate the region of activity. This is due to advective spreading and finite protein turnover rates. In the cases of a gene induced by either limitation for a metabolic substrate or accumulation of a metabolic product, maximal expression is predicted in an internal stratum of the biofilm. A quorum sensing system that includes an oxygen-responsive negative regulator exhibits behavior that is distinct from any stage of a batch planktonic culture. Though here the analyses have been limited to simultaneous interactions of up to two substrates and two genes, the framework applies to arbitrarily large networks of genes and metabolites. Extension of reaction-diffusion modeling in biofilms to the analysis of individual genes and gene networks is an important advance that dovetails with the growing toolkit of molecular and genetic experimental techniques.

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed Central

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-01-01

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC. PMID:26420960

Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

PubMed

Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

2015-09-28

Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramuhalli, Pradeep; Hirt, Evelyn H.; Dib, Gerges

This project involved the development of enhanced risk monitors (ERMs) for active components in Advanced Reactor (AdvRx) designs by integrating real-time information about equipment condition with risk monitors. Health monitoring techniques in combination with predictive estimates of component failure based on condition and risk monitors can serve to indicate the risk posed by continued operation in the presence of detected degradation. This combination of predictive health monitoring based on equipment condition assessment and risk monitors can also enable optimization of maintenance scheduling with respect to the economics of plant operation. This report summarizes PNNL’s multi-year project on the development andmore » evaluation of an ERM concept for active components while highlighting FY2016 accomplishments. Specifically, this report provides a status summary of the integration and demonstration of the prototypic ERM framework with the plant supervisory control algorithms being developed at Oak Ridge National Laboratory (ORNL), and describes additional case studies conducted to assess sensitivity of the technology to different quantities. Supporting documentation on the software package to be provided to ONRL is incorporated in this report.« less

Development of quantitative structure-activity relationships and its application in rational drug design.

PubMed

Yang, Guang-Fu; Huang, Xiaoqin

2006-01-01

Over forty years have elapsed since Hansch and Fujita published their pioneering work of quantitative structure-activity relationships (QSAR). Following the introduction of Comparative Molecular Field Analysis (CoMFA) by Cramer in 1998, other three-dimensional QSAR methods have been developed. Currently, combination of classical QSAR and other computational techniques at three-dimensional level is of greatest interest and generally used in the process of modern drug discovery and design. During the last several decades, a number of different mythologies incorporating a range of molecular descriptors and different statistical regression ways have been proposed and successfully applied in developing of new drugs, thus QSAR method has been proven to be indispensable in not only the reliable prediction of specific properties of new compounds, but also the help to elucidate the possible molecular mechanism of the receptor-ligand interactions. Here, we review the recent developments in QSAR and their applications in rational drug design, focusing on the reasonable selection of novel molecular descriptors and the construction of predictive QSAR models by the help of advanced computational techniques.

High prevalence and advanced silicosis in active granite workers: a dose-response analysis including FEV1.

PubMed

Rego, Gumersindo; Pichel, Arturo; Quero, Aida; Dubois, Alejandro; Martínez, Cristina; Isidro, Isabel; Gil, Manuel; Cuervo, Víctor; González, Artemio

2008-07-01

To evaluate silica exposure and respiratory disease in granite workers. A cross-sectional study of 440 active granite workers. Seventy-seven (17.5%) have silicosis, complicated in 15 of them; 18 have an obstructive ventilatory defect and 73 had exceeded 3.5 mg/m-year of cumulative silica exposure. Percent predicted FEV1 have a significant negative relation with mg/m(3)-year (P < 0.001) with a trend toward dose-response excluding silicotics and controlling for tobacco. The odds ratio (95% confidence interval) of having a percent predicted FEV1 below 50th percentile is 1.18 (0.66 to 2.11) for nonexposed smokers, 1.47 (0.76 to 2.84) for exposed nonsmokers, and 2.07 (1.12 to 3.85) for exposed smokers, in comparison with the control group. This study suggests that silica induces functional alteration regardless of silicosis and, in all likelihood, synergistically with tobacco. Exposure levels must be controlled better in these workers and those with silicosis must be relocated to risk-free jobs or retired.

Role-play games, experiments, workshops, blog posts: how community activities in HEPEX contribute to advance hydrologic ensemble prediction

NASA Astrophysics Data System (ADS)

Ramos, Maria-Helena; Wetterhall, Fredrik; Wood, Andy; Wang, Qj; Pappenberger, Florian; Verkade, Jan

2017-04-01

Since 2004, HEPEX (Hydrologic Ensemble Prediction Experiment) has been fostering a community of researchers and practitioners around the world. Through the years, it has contributed to establish a more integrative view of hydrological forecasting, where data assimilation, hydro-meteorological modelling chains, post-processing techniques, expert knowledge, and decision support systems are connected to enhance operational systems and water management applications. Here we present the community activities in HEPEX that have contributed to strengthening this unfunded/volunteer effort for more than a decade. It includes the organization of workshops, conference sessions, testbeds and inter-comparison experiments. More recently, HEPEX has also prompted the development of several publicly available role-play games and, since 2013, it has been running a blog portal (www.hepex.org), which is used as an intersection point for members. Through this website, members can continuously share their research, make announcements, report on workshops, projects and meetings, and hear about related research and operational challenges. It also creates a platform for early career scientists to become increasingly involved in hydrological forecasting science and applications.

Insights from advanced analytics at the Veterans Health Administration.

PubMed

Fihn, Stephan D; Francis, Joseph; Clancy, Carolyn; Nielson, Christopher; Nelson, Karin; Rumsfeld, John; Cullen, Theresa; Bates, Jack; Graham, Gail L

2014-07-01

Health care has lagged behind other industries in its use of advanced analytics. The Veterans Health Administration (VHA) has three decades of experience collecting data about the veterans it serves nationwide through locally developed information systems that use a common electronic health record. In 2006 the VHA began to build its Corporate Data Warehouse, a repository for patient-level data aggregated from across the VHA's national health system. This article provides a high-level overview of the VHA's evolution toward "big data," defined as the rapid evolution of applying advanced tools and approaches to large, complex, and rapidly changing data sets. It illustrates how advanced analysis is already supporting the VHA's activities, which range from routine clinical care of individual patients--for example, monitoring medication administration and predicting risk of adverse outcomes--to evaluating a systemwide initiative to bring the principles of the patient-centered medical home to all veterans. The article also shares some of the challenges, concerns, insights, and responses that have emerged along the way, such as the need to smoothly integrate new functions into clinical workflow. While the VHA is unique in many ways, its experience may offer important insights for other health care systems nationwide as they venture into the realm of big data. Project HOPE—The People-to-People Health Foundation, Inc.

Sequential treatment of icotinib after first-line pemetrexed in advanced lung adenocarcinoma with unknown EGFR gene status.

PubMed

Zheng, Yulong; Fang, Weijia; Deng, Jing; Zhao, Peng; Xu, Nong; Zhou, Jianying

2014-07-01

In non-small cell lung cancer (NSCLC), the well-developed epidermal growth factor receptor (EGFR) is an important therapeutic target. EGFR activating gene mutations have been proved strongly predictive of response to EGFR-tyrosine kinase inhibitors (TKI) in NSCLC. However, both in daily clinical practice and clinical trials, patients with unknown EGFR gene status (UN-EGFR-GS) are very common. In this study, we assessed efficacy and tolerability of sequential treatment of first-line pemetrexed followed by icotinib in Chinese advanced lung adenocarcinoma with UN-EGFR-GS. We analyzed 38 patients with advanced lung adenocarcinoma with UN-EGFR-GS treated with first-line pemetrexed-based chemotherapy followed by icotinib as maintenance or second-line therapy. The response rates to pemetrexed and icotinib were 21.1% and 42.1%, respectively. The median overall survival was 27.0 months (95% CI, 19.7-34.2 months). The 12-month overall survival probability was 68.4%. The most common toxicities observed in icotinib phase were rashes, diarrheas, and elevated aminotransferase. Subgroup analysis indicated that the overall survival is correlated with response to icotinib. The sequence of first-line pemetrexed-based chemotherapy followed by icotinib treatment is a promising option for advanced lung adenocarcinoma with UN-EGFR-GS in China.

Cracking the nodule worm code advances knowledge of parasite biology and biotechnology to tackle major diseases of livestock.

PubMed

Tyagi, Rahul; Joachim, Anja; Ruttkowski, Bärbel; Rosa, Bruce A; Martin, John C; Hallsworth-Pepin, Kymberlie; Zhang, Xu; Ozersky, Philip; Wilson, Richard K; Ranganathan, Shoba; Sternberg, Paul W; Gasser, Robin B; Mitreva, Makedonka

2015-11-01

Many infectious diseases caused by eukaryotic pathogens have a devastating, long-term impact on animal health and welfare. Hundreds of millions of animals are affected by parasitic nematodes of the order Strongylida. Unlocking the molecular biology of representatives of this order, and understanding nematode-host interactions, drug resistance and disease using advanced technologies could lead to entirely new ways of controlling the diseases that they cause. Oesophagostomum dentatum (nodule worm; superfamily Strongyloidea) is an economically important strongylid nematode parasite of swine worldwide. The present article reports recent advances made in biology and animal biotechnology through the draft genome and developmental transcriptome of O. dentatum, in order to support biological research of this and related parasitic nematodes as well as the search for new and improved interventions. This first genome of any member of the Strongyloidea is 443 Mb in size and predicted to encode 25,291 protein-coding genes. Here, we review the dynamics of transcription throughout the life cycle of O. dentatum, describe double-stranded RNA interference (RNAi) machinery and infer molecules involved in development and reproduction, and in inducing or modulating immune responses or disease. The secretome predicted for O. dentatum is particularly rich in peptidases linked to interactions with host tissues and/or feeding activity, and a diverse array of molecules likely involved in immune responses. This research progress provides an important resource for future comparative genomic and molecular biological investigations as well as for biotechnological research toward new anthelmintics, vaccines and diagnostic tests. Copyright © 2015 Elsevier Inc. All rights reserved.

Period gene expression in four neurons is sufficient for rhythmic activity of Drosophila melanogaster under dim light conditions.

PubMed

Rieger, Dirk; Wülbeck, Corinna; Rouyer, Francois; Helfrich-Förster, Charlotte

2009-08-01

The clock gene expressing lateral neurons (LN) is crucial for Drosophila 's rhythmic locomotor activity under constant conditions. Among the LN, the PDF expressing small ventral lateral neurons (s-LN(v)) are thought to control the morning activity of the fly (M oscillators) and to drive rhythmic activity under constant darkness. In contrast, a 5th PDF-negative s-LN( v) and the dorsal lateral neurons (LN(d)) appeared to control the fly's evening activity (E oscillators) and to drive rhythmic activity under constant light. Here, the authors restricted period gene expression to 4 LN-the 5th s-LN(v) and 3 LN(d)- that are all thought to belong to the E oscillators and tested them in low light conditions. Interestingly, such flies showed rather normal bimodal activity patterns under light moonlight and constant moonlight conditions, except that the phase of M and E peaks was different. This suggests that these 4 neurons behave as ''M'' and ''E'' cells in these conditions. Indeed, they found by PER and TIM immunohistochemistry that 2 LN(d) advanced their phase upon moonlight as predicted for M oscillators, whereas the 5th s-LN(v) and 1 LN(d) delayed their activity upon moonlight as predicted for E oscillators. Their results suggest that the M or E characteristic of clock neurons is rather flexible. M and E oscillator function may not be restricted to certain anatomically defined groups of clock neurons but instead depends on the environmental conditions.

CADDIS Volume 4. Data Analysis: Advanced Analyses - Controlling for Natural Variability: SSD Plot Diagrams

EPA Pesticide Factsheets

Methods for controlling natural variability, predicting environmental conditions from biological observations method, biological trait data, species sensitivity distributions, propensity scores, Advanced Analyses of Data Analysis references.

The Physics and Chemistry of Marine Aerosols

NASA Astrophysics Data System (ADS)

Russell, Lynn M.

Understanding the physics and chemistry of the marine atmosphere requires both predicting the evolution of its gas and aerosol phases and making observations that reflect the processes in that evolution. This work presents a model of the most fundamental physical and chemical processes important in the marine atmosphere, and discusses the current uncertainties in our theoretical understanding of those processes. Backing up these predictions with observations requires improved instrumentation for field measurements of aerosol. One important advance in this instrumentation is described for accelerating the speed of size distribution measurements. Observations of aerosols in the marine boundary layer during the Atlantic Stratocumulus Transition Experiment (ASTEX) provide an illustration of the impact of cloud processing in marine stratus. More advanced measurements aboard aircraft were enabled by redesigning the design of the system for separating particles by differential mobility and counting them by condensational growth. With this instrumentation, observations made during the Monterey Area Ship Tracks (MAST) Experiment have illustrated the role of aerosol emissions of ships in forming tracks in clouds. High-resolution gas chromatography and mass spectrometry was used with samples extracted by supercritical fluid extraction in order to identify the role of combustion organics in forming ship tracks. The results illustrate the need both for more sophisticated models incorporating organic species in cloud activation and for more extensive boundary layer observations.

Crew workload strategies in advanced cockpits

NASA Technical Reports Server (NTRS)

Hart, Sandra G.

1990-01-01

Many methods of measuring and predicting operator workload have been developed that provide useful information in the design, evaluation, and operation of complex systems and which aid in developing models of human attention and performance. However, the relationships between such measures, imposed task demands, and measures of performance remain complex and even contradictory. It appears that we have ignored an important factor: people do not passively translate task demands into performance. Rather, they actively manage their time, resources, and effort to achieve an acceptable level of performance while maintaining a comfortable level of workload. While such adaptive, creative, and strategic behaviors are the primary reason that human operators remain an essential component of all advanced man-machine systems, they also result in individual differences in the way people respond to the same task demands and inconsistent relationships among measures. Finally, we are able to measure workload and performance, but interpreting such measures remains difficult; it is still not clear how much workload is too much or too little nor the consequences of suboptimal workload on system performance and the mental, physical, and emotional well-being of the human operators. The rationale and philosophy of a program of research developed to address these issues will be reviewed and contrasted to traditional methods of defining, measuring, and predicting human operator workload. Viewgraphs are given.

Bayesian data assimilation provides rapid decision support for vector-borne diseases.

PubMed

Jewell, Chris P; Brown, Richard G

2015-07-06

Predicting the spread of vector-borne diseases in response to incursions requires knowledge of both host and vector demographics in advance of an outbreak. Although host population data are typically available, for novel disease introductions there is a high chance of the pathogen using a vector for which data are unavailable. This presents a barrier to estimating the parameters of dynamical models representing host-vector-pathogen interaction, and hence limits their ability to provide quantitative risk forecasts. The Theileria orientalis (Ikeda) outbreak in New Zealand cattle demonstrates this problem: even though the vector has received extensive laboratory study, a high degree of uncertainty persists over its national demographic distribution. Addressing this, we develop a Bayesian data assimilation approach whereby indirect observations of vector activity inform a seasonal spatio-temporal risk surface within a stochastic epidemic model. We provide quantitative predictions for the future spread of the epidemic, quantifying uncertainty in the model parameters, case infection times and the disease status of undetected infections. Importantly, we demonstrate how our model learns sequentially as the epidemic unfolds and provide evidence for changing epidemic dynamics through time. Our approach therefore provides a significant advance in rapid decision support for novel vector-borne disease outbreaks. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Gas valves, forests and global change: a commentary on Jarvis (1976) ‘The interpretation of the variations in leaf water potential and stomatal conductance found in canopies in the field’

PubMed Central

Beerling, David J.

2015-01-01

Microscopic turgor-operated gas valves on leaf surfaces—stomata—facilitate gas exchange between the plant and the atmosphere, and respond to multiple environmental and endogenous cues. Collectively, stomatal activities affect everything from the productivity of forests, grasslands and crops to biophysical feedbacks between land surface vegetation and climate. In 1976, plant physiologist Paul Jarvis reported an empirical model describing stomatal responses to key environmental and plant conditions that predicted the flux of water vapour from leaves into the surrounding atmosphere. Subsequent theoretical advances, building on this earlier approach, established the current paradigm for capturing the physiological behaviour of stomata that became incorporated into sophisticated models of land carbon cycling. However, these models struggle to accurately predict observed trends in the physiological responses of Northern Hemisphere forests to recent atmospheric CO2 increases, highlighting the need for improved representation of the role of stomata in regulating forest–climate interactions. Bridging this gap between observations and theory as atmospheric CO2 rises and climate change accelerates creates challenging opportunities for the next generation of physiologists to advance planetary ecology and climate science. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society. PMID:25750234

Systematic review of FDG-PET prediction of complete pathological response and survival in rectal cancer.

PubMed

Memon, Sameer; Lynch, A Craig; Akhurst, Timothy; Ngan, Samuel Y; Warrier, Satish K; Michael, Michael; Heriot, Alexander G

2014-10-01

Advances in the management of rectal cancer have resulted in an increased application of multimodal therapy with the aim of tailoring therapy to individual patients. Complete pathological response (pCR) is associated with improved survival and may be potentially managed without radical surgical resection. Over the last decade, there has been increasing interest in the ability of functional imaging to predict complete response to treatment. The aim of this review was to assess the role of (18)F-flurordeoxyglucose positron emission tomography (FDG-PET) in prediction of pCR and prognosis in resectable locally advanced rectal cancer. A search of the MEDLINE and Embase databases was conducted, and a systematic review of the literature investigating positron emission tomography (PET) in the prediction of pCR and survival in rectal cancer was performed. Seventeen series assessing PET prediction of pCR were included in the review. Seven series assessed postchemoradiation SUVmax, which was significantly different between response groups in all six studies that assessed this. Nine series assessed the response index (RI) for SUVmax, which was significantly different between response groups in seven series. Thirteen studies investigated PET response for prediction of survival. Metabolic complete response assessed by SUV2max or visual response and RISUVmax showed strong associations with disease-free survival (DFS) and overall survival (OS). SUV2max and RISUVmax appear to be useful FDG-PET markers for prediction of pCR and these parameters also show strong associations with DFS and OS. FDG-PET may have a role in outcome prediction in patients with advanced rectal cancer.

Using Machine Learning in Adversarial Environments.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Warren Leon Davis

Intrusion/anomaly detection systems are among the first lines of cyber defense. Commonly, they either use signatures or machine learning (ML) to identify threats, but fail to account for sophisticated attackers trying to circumvent them. We propose to embed machine learning within a game theoretic framework that performs adversarial modeling, develops methods for optimizing operational response based on ML, and integrates the resulting optimization codebase into the existing ML infrastructure developed by the Hybrid LDRD. Our approach addresses three key shortcomings of ML in adversarial settings: 1) resulting classifiers are typically deterministic and, therefore, easy to reverse engineer; 2) ML approachesmore » only address the prediction problem, but do not prescribe how one should operationalize predictions, nor account for operational costs and constraints; and 3) ML approaches do not model attackers’ response and can be circumvented by sophisticated adversaries. The principal novelty of our approach is to construct an optimization framework that blends ML, operational considerations, and a model predicting attackers reaction, with the goal of computing optimal moving target defense. One important challenge is to construct a realistic model of an adversary that is tractable, yet realistic. We aim to advance the science of attacker modeling by considering game-theoretic methods, and by engaging experimental subjects with red teaming experience in trying to actively circumvent an intrusion detection system, and learning a predictive model of such circumvention activities. In addition, we will generate metrics to test that a particular model of an adversary is consistent with available data.« less

A mathematical model for predicting the adult height of girls with advanced puberty after spontaneous growth.

PubMed

Lemaire, Pierre; Pierre, Delphine; Bertrand, Jean-Baptiste; Brauner, Raja

2014-07-03

Advanced puberty in girls is defined as the onset of puberty between the ages of 8 yr and 10 yr. The objective was to predict adult height (AH) at initial evaluation and to characterize patients with an actual AH below -2 SD (152 cm) and/or lower than their target height (TH) by > one SD (5.6 cm). Data analysis using multiple linear regression models was performed in 50 girls with advanced puberty who reached their AH after spontaneous puberty. The actual AH (159.0 ± 6.1 cm) was similar to the TH (161.2 ± 4.6 cm) and to the AH predicted at the initial evaluation (160.8 ± 6.0 cm), and the actual AH correlated positively with both (R = 0.76, P = 0.0003; R = 0.71, P = 0.008, respectively).The AH was below 152 cm in 7 girls, of whom 3 were characterized by paternal transmission of the advanced puberty. The AH was lower than the TH by >5.6 cm in 8 girls.The AH (cm) could be calculated at the initial evaluation: 1.8822 age + 3.3510 height (SD) - 0.7465 bone age - 1.7993 pubic hair stage + 2.8409 TH (SD) + 150.32.The formula is available online at http://www.kamick.org/lemaire/med/girls-advpub.html.The calculated AH (159.0 ± 5.7 cm) and the actual AH were highly correlated (R = 0.93). The actual AH was lower than the calculated AH by > 0.5 SD in only one case (4.35 cm). We established a formula that can be used at an initial evaluation to predict the AH, and then to assess the risk of reduced AH as a result of advanced puberty. According to this formula, the actual AH was lower than the calculated AH by more than 2.8 cm (0.5 SD) in only one girl. The AHs of the untreated girls with advanced puberty did not differ from those predicted at the initial evaluation by the Bayley and Pinneau table or from the THs. However, this study provides a useful and ready-to-use formula that can be an additional assessment of girls with advanced puberty.

Predictive Model of Systemic Toxicity (SOT)

EPA Science Inventory

In an effort to ensure chemical safety in light of regulatory advances away from reliance on animal testing, USEPA and L’Oréal have collaborated to develop a quantitative systemic toxicity prediction model. Prediction of human systemic toxicity has proved difficult and remains a ...

Life Prediction of Fretting Fatigue with Advanced Surface Treatments (Preprint)

DTIC Science & Technology

2006-05-01

surfaces and not the fretting pads. The chosen coatings included DLC, Ni-B, Molybdenum, and Nitride. These 4 coatings, their application to the titanium ...Article Preprint 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 4 . TITLE AND SUBTITLE LIFE PREDICTION OF FRETTING FATIGUE WITH ADVANCED SURFACE...TREATMENTS (PREPRINT) 5c. PROGRAM ELEMENT NUMBER N/A 5d. PROJECT NUMBER M02R 5e. TASK NUMBER 30 6 . AUTHOR(S) Patrick J. Golden and Michael

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design

PubMed Central

2017-01-01

Background Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic “big data” from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. Objective The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. Methods An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. Results The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning of a winter influenza season has an exponential growth of infected individuals. For prediction modeling, linear regression was applied on 7-day periods at the time in order to find the peak timing, whereas a derivate of a normal distribution density function was used to find the peak intensity. We found that the integrated detection and prediction method detected the 2008-09 winter influenza season on its starting day (optimal timeliness 0 days), whereas the predicted peak was estimated to occur 7 days ahead of the factual peak and the predicted peak intensity was estimated to be 26% lower than the factual intensity (6.3 compared with 8.5 influenza-diagnosis cases/100,000). Conclusions Our detection and prediction method is one of the first integrated methods specifically designed for local application on influenza data electronically available for surveillance. The performance of the method in a retrospective study indicates that further prospective evaluations of the methods are justified. PMID:28619700

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design.

PubMed

Spreco, Armin; Eriksson, Olle; Dahlström, Örjan; Cowling, Benjamin John; Timpka, Toomas

2017-06-15

Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic "big data" from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used based on the assumption that the beginning of a winter influenza season has an exponential growth of infected individuals. For prediction modeling, linear regression was applied on 7-day periods at the time in order to find the peak timing, whereas a derivate of a normal distribution density function was used to find the peak intensity. We found that the integrated detection and prediction method detected the 2008-09 winter influenza season on its starting day (optimal timeliness 0 days), whereas the predicted peak was estimated to occur 7 days ahead of the factual peak and the predicted peak intensity was estimated to be 26% lower than the factual intensity (6.3 compared with 8.5 influenza-diagnosis cases/100,000). Our detection and prediction method is one of the first integrated methods specifically designed for local application on influenza data electronically available for surveillance. The performance of the method in a retrospective study indicates that further prospective evaluations of the methods are justified. ©Armin Spreco, Olle Eriksson, Örjan Dahlström, Benjamin John Cowling, Toomas Timpka. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 15.06.2017.

Observed and Predicted Risk of Breast Cancer Death in Randomized Trials on Breast Cancer Screening.

PubMed

Autier, Philippe; Boniol, Mathieu; Smans, Michel; Sullivan, Richard; Boyle, Peter

2016-01-01

The role of breast screening in breast cancer mortality declines is debated. Screening impacts cancer mortality through decreasing the number of advanced cancers with poor diagnosis, while cancer treatment works through decreasing the case-fatality rate. Hence, reductions in cancer death rates thanks to screening should directly reflect reductions in advanced cancer rates. We verified whether in breast screening trials, the observed reductions in the risk of breast cancer death could be predicted from reductions of advanced breast cancer rates. The Greater New York Health Insurance Plan trial (HIP) is the only breast screening trial that reported stage-specific cancer fatality for the screening and for the control group separately. The Swedish Two-County trial (TCT)) reported size-specific fatalities for cancer patients in both screening and control groups. We computed predicted numbers of breast cancer deaths, from which we calculated predicted relative risks (RR) and (95% confidence intervals). The Age trial in England performed its own calculations of predicted relative risk. The observed and predicted RR of breast cancer death were 0.72 (0.56-0.94) and 0.98 (0.77-1.24) in the HIP trial, and 0.79 (0.78-1.01) and 0.90 (0.80-1.01) in the Age trial. In the TCT, the observed RR was 0.73 (0.62-0.87), while the predicted RR was 0.89 (0.75-1.05) if overdiagnosis was assumed to be negligible and 0.83 (0.70-0.97) if extra cancers were excluded. In breast screening trials, factors other than screening have contributed to reductions in the risk of breast cancer death most probably by reducing the fatality of advanced cancers in screening groups. These factors were the better management of breast cancer patients and the underreporting of breast cancer as the underlying cause of death. Breast screening trials should publish stage-specific fatalities observed in each group.

Physical Activity in Advanced Age: Physical Activity, Function, and Mortality in Advanced Age: A Longitudinal Follow Up (LiLACS NZ).

PubMed

Mace Firebaugh, Casey; Moyes, Simon; Jatrana, Santosh; Rolleston, Anna; Kerse, Ngaire

2018-01-18

The relationship between physical activity, function, and mortality is not established in advanced age. Physical activity, function, and mortality were followed in a cohort of Māori and non-Māori adults living in advanced age for a period of six years. Generalised Linear regression models were used to analyse the association between physical activity and NEADL while Kaplan-Meier survival analysis, and Cox-proportional hazard models were used to assess the association between the physical activity and mortality. The Hazard Ratio for mortality for those in the least active physical activity quartile was 4.1 for Māori and 1.8 for non- Māori compared to the most active physical activity quartile. There was an inverse relationship between physical activity and mortality, with lower hazard ratios for mortality at all levels of physical activity. Higher levels of physical activity were associated with lower mortality and higher functional status in advanced aged adults.

Predicting pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer: a systematic review.

PubMed

Ryan, J E; Warrier, S K; Lynch, A C; Ramsay, R G; Phillips, W A; Heriot, A G

2016-03-01

Approximately 20% of patients treated with neoadjuvant chemoradiotherapy (nCRT) for locally advanced rectal cancer achieve a pathological complete response (pCR) while the remainder derive the benefit of improved local control and downstaging and a small proportion show a minimal response. The ability to predict which patients will benefit would allow for improved patient stratification directing therapy to those who are likely to achieve a good response, thereby avoiding ineffective treatment in those unlikely to benefit. A systematic review of the English language literature was conducted to identify pathological factors, imaging modalities and molecular factors that predict pCR following chemoradiotherapy. PubMed, MEDLINE and Cochrane Database searches were conducted with the following keywords and MeSH search terms: 'rectal neoplasm', 'response', 'neoadjuvant', 'preoperative chemoradiation', 'tumor response'. After review of title and abstracts, 85 articles addressing the prediction of pCR were selected. Clear methods to predict pCR before chemoradiotherapy have not been defined. Clinical and radiological features of the primary cancer have limited ability to predict response. Molecular profiling holds the greatest potential to predict pCR but adoption of this technology will require greater concordance between cohorts for the biomarkers currently under investigation. At present no robust markers of the prediction of pCR have been identified and the topic remains an area for future research. This review critically evaluates existing literature providing an overview of the methods currently available to predict pCR to nCRT for locally advanced rectal cancer. The review also provides a comprehensive comparison of the accuracy of each modality. Colorectal Disease © 2015 The Association of Coloproctology of Great Britain and Ireland.

The status of perineural invasion predicts the outcomes of postoperative radiotherapy in locally advanced esophageal squamous cell carcinoma.

PubMed

Ning, Zhong-Hua; Zhao, Wei; Li, Xiao-Dong; Chen, Lu-Jun; Xu, Bin; Gu, Wen-Dong; Shao, Ying-Jie; Xu, Yun; Huang, Jin; Pei, Hong-Lei; Jiang, Jing-Ting

2015-01-01

Prognosis of locally advanced esophageal squamous cell carcinoma (ESCC) remains dismal even after curative resection and adjuvant radiotherapy. New biomarkers for predicting prognosis and treatment outcomes are needed for improved treatment stratification of patients with locally advanced ESCC. The prognostic and treatment predictive significance of perineural invasion (PNI) in the locally advanced ESCC remains unclear. This study aimed to examine the effect of PNI on the outcomes of locally advanced ESCC patients after curative resection with or without postoperative radiotherapy (PORT). We retrospectively reviewed 262 consecutive locally advanced ESCC patients who underwent curative resection. Tumors sections were re-evaluated for PNI by an independent pathologist blinded to the patients' outcomes. Overall survival (OS) and disease-free survival (DFS) were determined using the Kaplan-Meier method; univariate log-rank test and multivariate Cox proportional hazard model were used to evaluate the prognostic value of PNI. Finally, 243 patients were analyzed and enrolled into this study, of which 132 received PORT. PNI was identified in 22.2% (54/243) of the pathologic sections. The 5-year DFS was favorable for PNI-negative patients versus PNI-positive patients (21.3% vs. 36.7%, respectively; P = 0.005). The 5-year OS was 40.3% for PNI-negative patients versus 21.7% for PNI-positive patients (P < 0.001). On multivariate analysis, PNI was an independent prognostic factor. In a subset analysis for patients received PORT, PNI was evaluated as a prognostic predictor as well (P < 0.05). In contrast to patients without PORT, PORT couldn't improve the disease recurrence and survival in locally advanced ESCC patients with PNI-positive (P > 0.05). PNI could serve as an independent prognostic factor and prognosticate treatment outcomes in locally advanced ESCC patients. The PNI status should be considered when stratifying high-risk locally advanced ESCC patients for adjuvant radiotherapy. Future prospective study is warranted to confirm our results.

Progress in space weather predictions and applications

NASA Astrophysics Data System (ADS)

Lundstedt, H.

The methods of today's predictions of space weather and effects are so much more advanced and yesterday's statistical methods are now replaced by integrated knowledge-based neuro-computing models and MHD methods. Within the ESA Space Weather Programme Study a real-time forecast service has been developed for space weather and effects. This prototype is now being implemented for specific users. Today's applications are not only so many more but also so much more advanced and user-oriented. A scientist needs real-time predictions of a global index as input for an MHD model calculating the radiation dose for EVAs. A power company system operator needs a prediction of the local value of a geomagnetically induced current. A science tourist needs to know whether or not aurora will occur. Soon we might even be able to predict the tropospheric climate changes and weather caused by the space weather.

Non-Ideality in Solvent Extraction Systems: PNNL FY 2014 Status Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Levitskaia, Tatiana G.; Chatterjee, Sayandev; Pence, Natasha K.

The overall objective of this project is to develop predictive modeling capabilities for advanced fuel cycle separation processes by gaining a fundamental quantitative understanding of non-ideality effects and speciation in relevant aqueous and organic solutions. Aqueous solutions containing actinides and lanthanides encountered during nuclear fuel reprocessing have high ionic strength and do not behave as ideal solutions. Activity coefficients must be calculated to take into account the deviation from ideality and predict their behavior. In FY 2012-2013, a convenient method for determining activity effects in aqueous electrolyte solutions was developed. Our initial experiments demonstrated that water activity and osmotic coefficientsmore » of the electrolyte solutions can be accurately measured by the combination of two techniques, a Water Activity Meter and Vapor Pressure Osmometry (VPO). The water activity measurements have been conducted for binary lanthanide solutions in wide concentration range for all lanthanides (La-Lu with the exception of Pm). The osmotic coefficients and Pitzer parameters for each binary system were obtained by the least squares fitting of the water activity data. However, application of Pitzer model for the quantitative evaluation of the activity effects in the multicomponent mixtures is difficult due to the large number of the required interaction parameters. In FY 2014, the applicability of the Bromley model for the determination of the Ln(NO 3) 3 activity coefficients was evaluated. The new Bromley parameters for the binary Ln(NO 3) 3 electrolytes were obtained based on the available literature and our experimental data. This allowed for the accurate prediction of the Ln(NO 3) 3 activity coefficients for the binary Ln(NO 3) 3 electrolytes. This model was then successfully implemented for the determination of the Ln(NO 3) 3 activity coefficients in the ternary Nd(NO 3) 3/HNO 3/H2O, Eu(NO 3) 3/HNO 3/H 2O, and Eu(NO 3) 3/NaNO 3/H 2O systems. The main achievement of this work is the verified pathway for the estimation of the activity coefficients in the multicomponent aqueous electrolyte systems. The accurate Bromley electrolytes contributions obtained in this work for the entire series of lanthanide(III) nitrates (except Pm) can be applied for predicting activity coefficients and non-ideality effects for multi-component systems containing these species. This work also provides the proof-of-principle of extending the model to more complex multicomponent systems. Moreover, this approach can also be applied to actinide-containing electrolyte systems, for determination of the activity coefficients in concentrated radioactive solutions.« less

Protein-Protein Interface Predictions by Data-Driven Methods: A Review

PubMed Central

Xue, Li C; Dobbs, Drena; Bonvin, Alexandre M.J.J.; Honavar, Vasant

2015-01-01

Reliably pinpointing which specific amino acid residues form the interface(s) between a protein and its binding partner(s) is critical for understanding the structural and physicochemical determinants of protein recognition and binding affinity, and has wide applications in modeling and validating protein interactions predicted by high-throughput methods, in engineering proteins, and in prioritizing drug targets. Here, we review the basic concepts, principles and recent advances in computational approaches to the analysis and prediction of protein-protein interfaces. We point out caveats for objectively evaluating interface predictors, and discuss various applications of data-driven interface predictors for improving energy model-driven protein-protein docking. Finally, we stress the importance of exploiting binding partner information in reliably predicting interfaces and highlight recent advances in this emerging direction. PMID:26460190

A dynamical systems approach to studying midlatitude weather extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide

2017-04-01

Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.

Applied Meteorology Unit (AMU)

NASA Technical Reports Server (NTRS)

Bauman, William; Crawford, Winifred; Barrett, Joe; Watson, Leela; Wheeler, Mark

2010-01-01

This report summarizes the Applied Meteorology Unit (AMU) activities for the first quarter of Fiscal Year 2010 (October - December 2009). A detailed project schedule is included in the Appendix. Included tasks are: (1) Peak Wind Tool for User Launch Commit Criteria (LCC), (2) Objective Lightning Probability Tool, Phase III, (3) Peak Wind Tool for General Forecasting, Phase II, (4) Upgrade Summer Severe Weather Tool in Meteorological Interactive Data Display System (MIDDS), (5) Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) Update and Maintainability, (5) Verify 12-km resolution North American Model (MesoNAM) Performance, and (5) Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) Graphical User Interface.

{gamma}-vibrational states in superheavy nuclei

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun Yang; Institute of Modern Physics, Chinese Academy of Sciences, Lanzhou 730000; Joint Institute for Nuclear Astrophysics, University of Notre Dame, Notre Dame, Indiana 46556

2008-04-15

Recent experimental advances have made it possible to study excited structure in superheavy nuclei. The observed states have often been interpreted as quasiparticle excitations. We show that in superheavy nuclei collective vibrations systematically appear as low-energy excitation modes. By using the microscopic Triaxial Projected Shell Model, we make a detailed prediction on {gamma}-vibrational states and their E2 transition probabilities to the ground state band in fermium and nobelium isotopes where active structure research is going on, and in {sup 270}Ds, the heaviest isotope where decay data have been obtained for the ground-state and for an isomeric state.

Control law parameterization for an aeroelastic wind-tunnel model equipped with an active roll control system and comparison with experiment

NASA Technical Reports Server (NTRS)

Perry, Boyd, III; Dunn, H. J.; Sandford, Maynard C.

1988-01-01

Nominal roll control laws were designed, implemented, and tested on an aeroelastically-scaled free-to-roll wind-tunnel model of an advanced fighter configuration. The tests were performed in the NASA Langley Transonic Dynamics Tunnel. A parametric study of the nominal roll control system was conducted. This parametric study determined possible control system gain variations which yielded identical closed-loop stability (roll mode pole location) and identical roll response but different maximum control-surface deflections. Comparison of analytical predictions with wind-tunnel results was generally very good.

Aeronautics and Space Engineering Board: Aeronautics Assessment Committee

NASA Technical Reports Server (NTRS)

1977-01-01

High temperature engine materials, fatigue and fracture life prediction, composite materials, propulsion noise pollution, propulsion components, full-scale engine research, V/STOL propulsion, advanced engine concepts, and advanced general aviation propulsion research were discussed.

Clocks for the city: circadian differences between forest and city songbirds.

PubMed

Dominoni, D M; Helm, B; Lehmann, M; Dowse, H B; Partecke, J

2013-07-22

To keep pace with progressing urbanization organisms must cope with extensive habitat change. Anthropogenic light and noise have modified differences between day and night, and may thereby interfere with circadian clocks. Urbanized species, such as birds, are known to advance their activity to early morning and night hours. We hypothesized that such modified activity patterns are reflected by properties of the endogenous circadian clock. Using automatic radio-telemetry, we tested this idea by comparing activity patterns of free-living forest and city European blackbirds (Turdus merula). We then recaptured the same individuals and recorded their activity under constant conditions. City birds started their activity earlier and had faster but less robust circadian oscillation of locomotor activity than forest conspecifics. Circadian period length predicted start of activity in the field, and this relationship was mainly explained by fast-paced and early-rising city birds. Although based on only two populations, our findings point to links between city life, chronotype and circadian phenotype in songbirds, and potentially in other organisms that colonize urban habitats, and highlight that urban environments can significantly modify biologically important rhythms in wild organisms.

Fluorescence-based visualization of autophagic activity predicts mouse embryo viability

NASA Astrophysics Data System (ADS)

Tsukamoto, Satoshi; Hara, Taichi; Yamamoto, Atsushi; Kito, Seiji; Minami, Naojiro; Kubota, Toshiro; Sato, Ken; Kokubo, Toshiaki

2014-03-01

Embryo quality is a critical parameter in assisted reproductive technologies. Although embryo quality can be evaluated morphologically, embryo morphology does not correlate perfectly with embryo viability. To improve this, it is important to understand which molecular mechanisms are involved in embryo quality control. Autophagy is an evolutionarily conserved catabolic process in which cytoplasmic materials sequestered by autophagosomes are degraded in lysosomes. We previously demonstrated that autophagy is highly activated after fertilization and is essential for further embryonic development. Here, we developed a simple fluorescence-based method for visualizing autophagic activity in live mouse embryos. Our method is based on imaging of the fluorescence intensity of GFP-LC3, a versatile marker for autophagy, which is microinjected into the embryos. Using this method, we show that embryonic autophagic activity declines with advancing maternal age, probably due to a decline in the activity of lysosomal hydrolases. We also demonstrate that embryonic autophagic activity is associated with the developmental viability of the embryo. Our results suggest that embryonic autophagic activity can be utilized as a novel indicator of embryo quality.

Plasma D-dimer Can Effectively Predict the Prospective Occurrence of Ascites in Advanced Schistosomiasis Japonica Patients.

PubMed

Wu, Xiaoying; Ren, Jianwei; Gao, Zulu; Xu, Yun; Xie, Huiqun; Li, Tingfang; Cheng, Yanhua; Hu, Fei; Liu, Hongyun; Gong, Zhihong; Liang, Jinyi; Shen, Jia; Liu, Zhen; Wu, Feng; Sun, Xi; Niu, Zhongzheng; Ning, An

2017-04-01

China still has more than 30,000 patients of advanced schistosomiasis while new cases being reported consistently. D-dimer is a fibrin degradation product. As ascites being the dominating symptom in advanced schistosomiasis, the present study aimed to explore a prediction model of ascites with D-dimer and other clinical easy-achievable indicators. A case-control study nested in a prospective cohort was conducted in schistosomiasis-endemic area of southern China. A total of 291 patients of advanced schistosomiasis were first investigated in 2013 and further followed in 2014. Information on clinical history, physical examination, and abdominal ultrasonography, including the symptom of ascites was repeatedly collected. Result showed 44 patients having ascites. Most of the patients' ascites were confined in the kidney area with median area of 20 mm 2 . The level of plasma D-dimer and pertinent liver function indicators were measured at the initial investigation in 2013. Compared with those without ascites, cases with ascites had significantly higher levels of D-dimer (0.71±2.44 μg/L vs 0.48±2.12 μg/L, P =0.005), as well ALB (44.5 vs 46.2, g/L) and Type IV collagen (50.04 vs 44.50 μg/L). Receiver operating characteristic curve analyses indicated a moderate predictive value of D-dimer by its own area under curve (AUC) of 0.64 (95% CI: 0.54-0.73) and the cutoff value as 0.81 μg/L. Dichotomized by the cutoff level, D-dimer along with other categorical variables generated a prediction model with AUC of 0.76 (95% CI: 0.68-0.89). Risks of patients with specific characteristics in the prediction model were summarized. Our study suggests that the plasma D-dimer level is a reliable predictor for incident ascites in advanced schistosomiasis japonica patients.

Plasma D-dimer Can Effectively Predict the Prospective Occurrence of Ascites in Advanced Schistosomiasis Japonica Patients

PubMed Central

Wu, Xiaoying; Ren, Jianwei; Gao, Zulu; Xu, Yun; Xie, Huiqun; Li, Tingfang; Cheng, Yanhua; Hu, Fei; Liu, Hongyun; Gong, Zhihong; Liang, Jinyi; Shen, Jia; Liu, Zhen; Wu, Feng; Sun, Xi; Niu, Zhongzheng; Ning, An

2017-01-01

China still has more than 30,000 patients of advanced schistosomiasis while new cases being reported consistently. D-dimer is a fibrin degradation product. As ascites being the dominating symptom in advanced schistosomiasis, the present study aimed to explore a prediction model of ascites with D-dimer and other clinical easy-achievable indicators. A case-control study nested in a prospective cohort was conducted in schistosomiasis-endemic area of southern China. A total of 291 patients of advanced schistosomiasis were first investigated in 2013 and further followed in 2014. Information on clinical history, physical examination, and abdominal ultrasonography, including the symptom of ascites was repeatedly collected. Result showed 44 patients having ascites. Most of the patients’ ascites were confined in the kidney area with median area of 20 mm2. The level of plasma D-dimer and pertinent liver function indicators were measured at the initial investigation in 2013. Compared with those without ascites, cases with ascites had significantly higher levels of D-dimer (0.71±2.44 μg/L vs 0.48±2.12 μg/L, P=0.005), as well ALB (44.5 vs 46.2, g/L) and Type IV collagen (50.04 vs 44.50 μg/L). Receiver operating characteristic curve analyses indicated a moderate predictive value of D-dimer by its own area under curve (AUC) of 0.64 (95% CI: 0.54–0.73) and the cutoff value as 0.81 μg/L. Dichotomized by the cutoff level, D-dimer along with other categorical variables generated a prediction model with AUC of 0.76 (95% CI: 0.68–0.89). Risks of patients with specific characteristics in the prediction model were summarized. Our study suggests that the plasma D-dimer level is a reliable predictor for incident ascites in advanced schistosomiasis japonica patients. PMID:28506039

A Model-based Approach to Controlling the ST-5 Constellation Lights-Out Using the GMSEC Message Bus and Simulink

NASA Technical Reports Server (NTRS)

Witt, Kenneth J.; Stanley, Jason; Shendock, Robert; Mandl, Daniel

2005-01-01

Space Technology 5 (ST-5) is a three-satellite constellation, technology validation mission under the New Millennium Program at NASA to be launched in March 2006. One of the key technologies to be validated is a lights-out, model-based operations approach to be used for one week to control the ST-5 constellation with no manual intervention. The ground architecture features the GSFC Mission Services Evolution Center (GMSEC) middleware, which allows easy plugging in of software components and a standardized messaging protocol over a software bus. A predictive modeling tool built on MatLab's Simulink software package makes use of the GMSEC standard messaging protocol to interface to the Advanced Mission Planning System (AMPS) Scenario Scheduler which controls all activities, resource allocation and real-time re-profiling of constellation resources when non-nominal events occur. The key features of this system, which we refer to as the ST-5 Simulink system, are as follows: Original daily plan is checked to make sure that predicted resources needed are available by comparing the plan against the model. As the plan is run in real-time, the system re-profiles future activities in real-time if planned activities do not occur in the predicted timeframe or fashion. Alert messages are sent out on the GMSEC bus by the system if future predicted problems are detected. This will allow the Scenario Scheduler to correct the situation before the problem happens. The predictive model is evolved automatically over time via telemetry updates thus reducing the cost of implementing and maintaining the models by an order of magnitude from previous efforts at GSFC such as the model-based system built for MAP in the mid-1990's. This paper will describe the key features, lessons learned and implications for future missions once this system is successfully validated on-orbit in 2006.

Physical exam of the adolescent shoulder: tips for evaluating and diagnosing common shoulder disorders in the adolescent athlete.

PubMed

Lazaro, Lionel E; Cordasco, Frank A

2017-02-01

In the young athlete, the shoulder is one of the most frequently injured joints during sports activities. The injuries are either from an acute traumatic event or overuse. Shoulder examination can present some challenges; given the multiple joints involved, the difficulty palpating the underlying structures, and the potential to have both intra- and/or extra-articular problems. Many of the shoulder examination tests can be positive in multiple problems. They usually have high sensitivity but low specificity and therefore low predictive value. The medical history coupled with a detailed physical exam can usually provide the information necessary to obtain an accurate diagnosis. A proficient shoulder examination and the development of an adequate differential diagnosis are important before considering advanced imaging. The shoulder complex relies upon the integrity of multiple structures for normal function. A detailed history is of paramount importance when evaluating young athletes with shoulder problems. A systematic physical examination is extremely important to guiding an accurate diagnosis. The patient's age and activity level are very important when considering the differential diagnosis. Findings obtain through history and physical examination should dictate the decision to obtain advanced imaging of the shoulder.

Recent advances in the characterization of high temperature industrial materials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meadowcroft, D.B.; Tomkings, A.B.

1995-12-31

This paper reviews several techniques under development or recently commercialized which aid the characterization of high temperature plant components when carrying out lifetime predictions. Temperature measurements are frequently limited because of the limited lifetime and cost of thermocouples in aggressive environments and three alternative methods of assessing the ``average effective`` temperature of a component being evaluated by the authors are described steam side oxide thickness (specifically for ferritic superheater tubes), copper gold diffusion couples (``PETIT``), and the measurement of ferrite in duplex steels (``FEROPLUG``). Advances are described which have been made recently in the measurement techniques available for making plantmore » measurements on components to reduce the time needed for significant values of wastage rates to be established. In addition on-line high, temperature corrosion monitors are coming available which allow wastage rates to be assessed over periods of hours or days. These involve electrical resistance or electrochemical techniques. Finally the use of thin layer activation by a radioactive isotope is highlighted which enables the wastage of components to be assessed remotely without direct contact. Whilst available for a long time for laboratory and pilot plant studies, the authors are actively concerned with introducing the technique into operational boiler plant.« less

Characterization of active hair-bundle motility by a mechanical-load clamp

NASA Astrophysics Data System (ADS)

Salvi, Joshua D.; Maoiléidigh, Dáibhid Ó.; Fabella, Brian A.; Tobin, Mélanie; Hudspeth, A. J.

2015-12-01

Active hair-bundle motility endows hair cells with several traits that augment auditory stimuli. The activity of a hair bundle might be controlled by adjusting its mechanical properties. Indeed, the mechanical properties of bundles vary between different organisms and along the tonotopic axis of a single auditory organ. Motivated by these biological differences and a dynamical model of hair-bundle motility, we explore how adjusting the mass, drag, stiffness, and offset force applied to a bundle control its dynamics and response to external perturbations. Utilizing a mechanical-load clamp, we systematically mapped the two-dimensional state diagram of a hair bundle. The clamp system used a real-time processor to tightly control each of the virtual mechanical elements. Increasing the stiffness of a hair bundle advances its operating point from a spontaneously oscillating regime into a quiescent regime. As predicted by a dynamical model of hair-bundle mechanics, this boundary constitutes a Hopf bifurcation.

Test Standard Developed for Determining the Slow Crack Growth of Advanced Ceramics at Ambient Temperature

NASA Technical Reports Server (NTRS)

Choi, Sung R.; Salem, Jonathan A.

1998-01-01

The service life of structural ceramic components is often limited by the process of slow crack growth. Therefore, it is important to develop an appropriate testing methodology for accurately determining the slow crack growth design parameters necessary for component life prediction. In addition, an appropriate test methodology can be used to determine the influences of component processing variables and composition on the slow crack growth and strength behavior of newly developed materials, thus allowing the component process to be tailored and optimized to specific needs. At the NASA Lewis Research Center, work to develop a standard test method to determine the slow crack growth parameters of advanced ceramics was initiated by the authors in early 1994 in the C 28 (Advanced Ceramics) committee of the American Society for Testing and Materials (ASTM). After about 2 years of required balloting, the draft written by the authors was approved and established as a new ASTM test standard: ASTM C 1368-97, Standard Test Method for Determination of Slow Crack Growth Parameters of Advanced Ceramics by Constant Stress-Rate Flexural Testing at Ambient Temperature. Briefly, the test method uses constant stress-rate testing to determine strengths as a function of stress rate at ambient temperature. Strengths are measured in a routine manner at four or more stress rates by applying constant displacement or loading rates. The slow crack growth parameters required for design are then estimated from a relationship between strength and stress rate. This new standard will be published in the Annual Book of ASTM Standards, Vol. 15.01, in 1998. Currently, a companion draft ASTM standard for determination of the slow crack growth parameters of advanced ceramics at elevated temperatures is being prepared by the authors and will be presented to the committee by the middle of 1998. Consequently, Lewis will maintain an active leadership role in advanced ceramics standardization within ASTM. In addition, the authors have been and are involved with several international standardization organizations including the Versailles Project on Advanced Materials and Standards (VAMAS), the International Energy Agency (IEA), and the International Organization for Standardization (ISO). The associated standardization activities involve fracture toughness, strength, elastic modulus, and the machining of advanced ceramics.

A 3D-CFD code for accurate prediction of fluid flows and fluid forces in seals

NASA Technical Reports Server (NTRS)

Athavale, M. M.; Przekwas, A. J.; Hendricks, R. C.

1994-01-01

Current and future turbomachinery requires advanced seal configurations to control leakage, inhibit mixing of incompatible fluids and to control the rotodynamic response. In recognition of a deficiency in the existing predictive methodology for seals, a seven year effort was established in 1990 by NASA's Office of Aeronautics Exploration and Technology, under the Earth-to-Orbit Propulsion program, to develop validated Computational Fluid Dynamics (CFD) concepts, codes and analyses for seals. The effort will provide NASA and the U.S. Aerospace Industry with advanced CFD scientific codes and industrial codes for analyzing and designing turbomachinery seals. An advanced 3D CFD cylindrical seal code has been developed, incorporating state-of-the-art computational methodology for flow analysis in straight, tapered and stepped seals. Relevant computational features of the code include: stationary/rotating coordinates, cylindrical and general Body Fitted Coordinates (BFC) systems, high order differencing schemes, colocated variable arrangement, advanced turbulence models, incompressible/compressible flows, and moving grids. This paper presents the current status of code development, code demonstration for predicting rotordynamic coefficients, numerical parametric study of entrance loss coefficients for generic annular seals, and plans for code extensions to labyrinth, damping, and other seal configurations.

Long Range River Discharge Forecasting Using the Gravity Recovery and Climate Experiment (GRACE) Satellite to Predict Conditions for Endemic Cholera

NASA Astrophysics Data System (ADS)

Jutla, A.; Akanda, A. S.; Colwell, R. R.

2014-12-01

Prediction of conditions of an impending disease outbreak remains a challenge but is achievable if the associated and appropriate large scale hydroclimatic process can be estimated in advance. Outbreaks of diarrheal diseases such as cholera, are related to episodic seasonal variability in river discharge in the regions where water and sanitation infrastructure are inadequate and insufficient. However, forecasting river discharge, few months in advance, remains elusive where cholera outbreaks are frequent, probably due to non-availability of geophysical data as well as transboundary water stresses. Here, we show that satellite derived water storage from Gravity Recovery and Climate Experiment Forecasting (GRACE) sensors can provide reliable estimates on river discharge atleast two months in advance over regional scales. Bayesian regression models predicted flooding and drought conditions, a prerequisite for cholera outbreaks, in Bengal Delta with an overall accuracy of 70% for upto 60 days in advance without using any other ancillary ground based data. Forecasting of river discharge will have significant impacts on planning and designing intervention strategies for potential cholera outbreaks in the coastal regions where the disease remain endemic and often fatal.

Advanced interatrial block predicts new-onset atrial fibrillation and ischemic stroke in patients with heart failure: The "Bayes' Syndrome-HF" study.

PubMed

Escobar-Robledo, Luis Alberto; Bayés-de-Luna, Antoni; Lupón, Josep; Baranchuk, Adrian; Moliner, Pedro; Martínez-Sellés, Manuel; Zamora, Elisabet; de Antonio, Marta; Domingo, Mar; Cediel, Germán; Núñez, Julio; Santiago-Vacas, Evelyn; Bayés-Genís, Antoni

2018-05-18

Advanced interatrial block (IAB) is characterized by a prolonged (≥120 ms) and bimodal P wave in the inferior leads. The association between advanced IAB and atrial fibrillation (AF) is known as "Bayes' Syndrome", and there is scarce information about it in heart failure (HF). We examined the prevalence of IAB and whether advanced IAB could predict new-onset AF and/or stroke in HF patients. The prospective observational "Bayes' Syndrome-HF" study included consecutive outpatients with chronic HF. The primary endpoints were new-onset AF, ischemic stroke, and the composite of both. A secondary endpoint included all-cause death alone or in combination with the primary endpoint. Comprehensive multivariable Cox regression analyses were performed. Among 1050 consecutive patients, 536 (51.0%) were in sinus rhythm, 464 with a measurable P wave are the focus of this study. Two-hundred and sixty patients (56.0%) had normal atrial conduction, 95 (20.5%) partial IAB, and 109 (23.5%) advanced IAB. During a mean follow-up of 4.5 ± 2.1 years, 235 patients experienced all-cause death, new-onset AF, or stroke. In multivariable comprehensive Cox regression analyses, advanced IAB was associated with new-onset AF (HR 2.71 [1.61-4.56], P < 0.001), ischemic stroke (HR 3.02 [1.07-8.53], P = 0.04), and the composite of both (HR 2.42 [1.41-4.15], P < 0.001). In patients with HF advanced IAB predicts new-onset AF and ischemic stroke. Future studies must assess whether anticoagulant treatment in Bayes' Syndrome leads to better outcomes in HF. Copyright © 2017 Elsevier B.V. All rights reserved.

Prognosis in advanced lung cancer--A prospective study examining key clinicopathological factors.

PubMed

Simmons, Claribel P; Koinis, Filippos; Fallon, Marie T; Fearon, Kenneth C; Bowden, Jo; Solheim, Tora S; Gronberg, Bjorn Henning; McMillan, Donald C; Gioulbasanis, Ioannis; Laird, Barry J

2015-06-01

In patients with advanced incurable lung cancer deciding as to the most appropriate treatment (e.g., chemotherapy or supportive care only) is challenging. In such patients the TNM classification system has reached its ceiling therefore other factors are used to assess prognosis and as such, guide treatment. Performance status (PS), weight loss and inflammatory biomarkers (Glasgow Prognostic Score (mGPS)) predict survival in advanced lung cancer however these have not been compared. This study compares key prognostic factors in advanced lung cancer. Patients with newly diagnosed advanced lung cancer were recruited and demographics, weight loss, other prognostic factors (mGPS, PS) were collected. Kaplan-Meier and Cox regression methods were used to compare these prognostic factors. 390 patients with advanced incurable lung cancer were recruited; 341 were male, median age was 66 years (IQR 59-73) and patients had stage IV non-small cell (n=288) (73.8%) or extensive stage small cell lung cancer (n=102) (26.2%). The median survival was 7.8 months. On multivariate analysis only performance status (HR 1.74 CI 1.50-2.02) and mGPS (HR 1.67, CI 1.40-2.00) predicted survival (p<0.001). Survival at 3 months ranged from 99% (ECOG 0-1) to 74% (ECOG 2) and using mGPS, from 99% (mGPS0) to 71% (mGPS2). In combination, survival ranged from 99% (mGPS 0, ECOG 0-1) to 33% (mGPS2, ECOG 3). Performance status and the mGPS are superior prognostic factors in advanced lung cancer. In combination, these improved survival prediction compared with either alone. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Brain activity associated with illusory correlations in animal phobia.

PubMed

Wiemer, Julian; Schulz, Stefan M; Reicherts, Philipp; Glotzbach-Schoon, Evelyn; Andreatta, Marta; Pauli, Paul

2015-07-01

Anxiety disorder patients were repeatedly found to overestimate the association between disorder-relevant stimuli and aversive outcomes despite random contingencies. Such an illusory correlation (IC) might play an important role in the return of fear after extinction learning; yet, little is known about how this cognitive bias emerges in the brain. In a functional magnetic resonance imaging study, 18 female patients with spider phobia and 18 healthy controls were exposed to pictures of spiders, mushrooms and puppies followed randomly by either a painful electrical shock or nothing. In advance, both patients and healthy controls expected more shocks after spider pictures. Importantly, only patients with spider phobia continued to overestimate this association after the experiment. The strength of this IC was predicted by increased outcome aversiveness ratings and primary sensory motor cortex activity in response to the shock after spider pictures. Moreover, increased activation of the left dorsolateral prefrontal cortex (dlPFC) to spider pictures predicted the IC. These results support the theory that phobia-relevant stimuli amplify unpleasantness and sensory motor representations of aversive stimuli, which in turn may promote their overestimation. Hyper-activity in dlPFC possibly reflects a pre-occupation of executive resources with phobia-relevant stimuli, thus complicating the accurate monitoring of objective contingencies and the unlearning of fear. © The Author (2014). Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

An active balance board system with real-time control of stiffness and time-delay to assess mechanisms of postural stability.

PubMed

Cruise, Denise R; Chagdes, James R; Liddy, Joshua J; Rietdyk, Shirley; Haddad, Jeffrey M; Zelaznik, Howard N; Raman, Arvind

2017-07-26

Increased time-delay in the neuromuscular system caused by neurological disorders, concussions, or advancing age is an important factor contributing to balance loss (Chagdes et al., 2013, 2016a,b). We present the design and fabrication of an active balance board system that allows for a systematic study of stiffness and time-delay induced instabilities in standing posture. Although current commercial balance boards allow for variable stiffness, they do not allow for manipulation of time-delay. Having two controllable parameters can more accurately determine the cause of balance deficiencies, and allows us to induce instabilities even in healthy populations. An inverted pendulum model of human posture on such an active balance board predicts that reduced board rotational stiffness destabilizes upright posture through board tipping, and limit cycle oscillations about the upright position emerge as feedback time-delay is increased. We validate these two mechanisms of instability on the designed balance board, showing that rotational stiffness and board time-delay induced the predicted postural instabilities in healthy, young adults. Although current commercial balance boards utilize control of rotational stiffness, real-time control of both stiffness and time-delay on an active balance board is a novel and innovative manipulation to reveal balance deficiencies and potentially improve individualized balance training by targeting multiple dimensions contributing to standing balance. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting Return of Fear Following Exposure Therapy With an Implicit Measure of Attitudes

PubMed Central

Vasey, Michael W.; Harbaugh, Casaundra N.; Buffington, Adam G.; Jones, Christopher R.; Fazio, Russell H.

2012-01-01

We sought to advance understanding of the processes underlying the efficacy of exposure therapy and particularly the phenomenon of return of fear (ROF) following treatment by drawing on a social psychological view of phobias as attitudes. Specifically, a dual process theory of attitude-related behavior predicts that a positive response to exposure therapy may reflect change in either the automatic (the attitude representation itself) or controlled (skills and confidence at coping with the fear) responses to the phobic stimulus, or both. However, if the attitude representation remains negative following treatment, ROF should be more likely. We tested this hypothesis in a clinical sample of individuals with public speaking phobia using a single-session exposure therapy protocol previously shown to be efficacious but also associated with some ROF. Consistent with predictions, a post-treatment implicit measure of attitudes toward public speaking (the Personalized Implicit Association Test [PIAT]) predicted ROF at 1-month follow-up. These results suggest that change in the automatically activated attitude toward the phobic stimulus is an important goal of exposure therapy and that an implicit measure like the PIAT can provide a useful measure of such change by which to gauge the adequacy of exposure treatment and predict its long-term efficacy. PMID:23085186

The Drought Task Force and Research on Understanding, Predicting, and Monitoring Drought

NASA Astrophysics Data System (ADS)

Barrie, D.; Mariotti, A.; Archambault, H. M.; Hoerling, M. P.; Wood, E. F.; Koster, R. D.; Svoboda, M.

2016-12-01

Drought has caused serious social and economic impacts throughout the history of the United States. All Americans are susceptible to the direct and indirect threats drought poses to the Nation. Drought challenges agricultural productivity and reduces the quantity and quality of drinking water supplies upon which communities and industries depend. Drought jeopardizes the integrity of critical infrastructure, causes extensive economic and health impacts, harms ecosystems, and increases energy costs. Ensuring the availability of clean, sufficient, and reliable water resources is a top national and NOAA priority. The Climate Program Office's Modeling, Analysis, Predictions, and Projections (MAPP) program, in partnership with the NOAA-led National Integrated Drought Information System (NIDIS), is focused on improving our understanding of drought causes, evolution, amelioration, and impacts as well as improving our capability to monitor and predict drought. These capabilities and knowledge are critical to providing communities with actionable, reliable information to increase drought preparedness and resilience. This poster will present information on the MAPP-organized Drought Task Force, a consortium of investigators funded by the MAPP program in partnership with NIDIS to advance drought understanding, monitoring, and prediction. Information on Task Force activities, products, and MAPP drought initiatives will be described in the poster, including the Task Force's ongoing focus on the California drought, its predictability, and its causes.

Using remote sensing satellite data and artificial neural network for prediction of potato yield in Bangladesh

NASA Astrophysics Data System (ADS)

Akhand, Kawsar; Nizamuddin, Mohammad; Roytman, Leonid; Kogan, Felix

2016-09-01

Potato is one of the staple foods and cash crops in Bangladesh. It is widely cultivated in all of the districts and ranks second after rice in production. Bangladesh is the fourth largest potato producer in Asia and is among the world's top 15 potato producing countries. The weather condition for potato cultivation is favorable during the sowing, growing and harvesting period. It is a winter crop and is cultivated during the period of November to March. Bangladesh is mainly an agricultural based country with respect to agriculture's contribution to GDP, employment and consumption. Potato is a prominent crop in consideration of production, its internal demand and economic value. Bangladesh has a big economic activities related to potato cultivation and marketing, especially the economic relations among farmers, traders, stockers and cold storage owners. Potato yield prediction before harvest is an important issue for the Government and the stakeholders in managing and controlling the potato market. Advanced very high resolution radiometer (AVHRR) based satellite data product vegetation health indices VCI (vegetation condition index) and TCI (temperature condition index) are used as predictors for early prediction. Artificial neural network (ANN) is used to develop a prediction model. The simulated result from this model is encouraging and the error of prediction is less than 10%.

Preface: Special Topic Section on Advanced Electronic Structure Methods for Solids and Surfaces.

PubMed

Michaelides, Angelos; Martinez, Todd J; Alavi, Ali; Kresse, Georg; Manby, Frederick R

2015-09-14

This Special Topic section on Advanced Electronic Structure Methods for Solids and Surfaces contains a collection of research papers that showcase recent advances in the high accuracy prediction of materials and surface properties. It provides a timely snapshot of a growing field that is of broad importance to chemistry, physics, and materials science.

Inter- and Intralingual Lexical Influences in Advanced Learners' French L3 Oral Production

ERIC Educational Resources Information Center

Lindqvist, Christina

2010-01-01

The present study investigates lexical inter- and intralingual influences in the oral production of 14 very advanced learners of French L3. Lexical deviances are divided into two main categories: formal influence and meaning-based influence. The results show that, as predicted with respect to advanced learners, meaning-based influence is the most…

Space Suit Portable Life Support System Test Bed (PLSS 1.0) Development and Testing

NASA Technical Reports Server (NTRS)

Watts, Carly; Campbell, Colin; Vogel, Matthew; Conger, Bruce

2012-01-01

A multi-year effort has been carried out at NASA-JSC to develop an advanced extra-vehicular activity Portable Life Support System (PLSS) design intended to further the current state of the art by increasing operational flexibility, reducing consumables, and increasing robustness. Previous efforts have focused on modeling and analyzing the advanced PLSS architecture, as well as developing key enabling technologies. Like the current International Space Station Extra-vehicular Mobility Unit PLSS, the advanced PLSS comprises three subsystems required to sustain the crew during extra-vehicular activity including the Thermal, Ventilation, and Oxygen Subsystems. This multi-year effort has culminated in the construction and operation of PLSS 1.0, a test bed that simulates full functionality of the advanced PLSS design. PLSS 1.0 integrates commercial off the shelf hardware with prototype technology development components, including the primary and secondary oxygen regulators, Ventilation Subsystem fan, Rapid Cycle Amine swingbed carbon dioxide and water vapor removal device, and Spacesuit Water Membrane Evaporator heat rejection device. The overall PLSS 1.0 test objective was to demonstrate the capability of the Advanced PLSS to provide key life support functions including suit pressure regulation, carbon dioxide and water vapor removal, thermal control and contingency purge operations. Supplying oxygen was not one of the specific life support functions because the PLSS 1.0 test was not oxygen rated. Nitrogen was used for the working gas. Additional test objectives were to confirm PLSS technology development components performance within an integrated test bed, identify unexpected system level interactions, and map the PLSS 1.0 performance with respect to key variables such as crewmember metabolic rate and suit pressure. Successful PLSS 1.0 testing completed 168 test points over 44 days of testing and produced a large database of test results that characterize system level and component performance. With the exception of several minor anomalies, the PLSS 1.0 test rig performed as expected; furthermore, many system responses trended in accordance with pre-test predictions.

Predicted Role of NAD Utilization in the Control of Circadian Rhythms during DNA Damage Response

PubMed Central

Luna, Augustin; McFadden, Geoffrey B.; Aladjem, Mirit I.; Kohn, Kurt W.

2015-01-01

The circadian clock is a set of regulatory steps that oscillate with a period of approximately 24 hours influencing many biological processes. These oscillations are robust to external stresses, and in the case of genotoxic stress (i.e. DNA damage), the circadian clock responds through phase shifting with primarily phase advancements. The effect of DNA damage on the circadian clock and the mechanism through which this effect operates remains to be thoroughly investigated. Here we build an in silico model to examine damage-induced circadian phase shifts by investigating a possible mechanism linking circadian rhythms to metabolism. The proposed model involves two DNA damage response proteins, SIRT1 and PARP1, that are each consumers of nicotinamide adenine dinucleotide (NAD), a metabolite involved in oxidation-reduction reactions and in ATP synthesis. This model builds on two key findings: 1) that SIRT1 (a protein deacetylase) is involved in both the positive (i.e. transcriptional activation) and negative (i.e. transcriptional repression) arms of the circadian regulation and 2) that PARP1 is a major consumer of NAD during the DNA damage response. In our simulations, we observe that increased PARP1 activity may be able to trigger SIRT1-induced circadian phase advancements by decreasing SIRT1 activity through competition for NAD supplies. We show how this competitive inhibition may operate through protein acetylation in conjunction with phosphorylation, consistent with reported observations. These findings suggest a possible mechanism through which multiple perturbations, each dominant during different points of the circadian cycle, may result in the phase advancement of the circadian clock seen during DNA damage. PMID:26020938

Effects of square-wave and simulated natural light-dark cycles on hamster circadian rhythms

NASA Technical Reports Server (NTRS)

Tang, I. H.; Murakami, D. M.; Fuller, C. A.

1999-01-01

Circadian rhythms of activity (Act) and body temperature (Tb) were recorded from male Syrian hamsters under square-wave (LDSq) and simulated natural (LDSN, with dawn and dusk transitions) light-dark cycles. Light intensity and data sampling were under the synchronized control of a laboratory computer. Changes in reactive and predictive onsets and offsets for the circadian rhythms of Act and Tb were examined in both lighting conditions. The reactive Act onset occurred 1.1 h earlier (P < 0.01) in LDSN than in LDSq and had a longer alpha-period (1.7 h; P < 0.05). The reactive Tb onset was 0.7 h earlier (P < 0.01) in LDSN. In LDSN, the predictive Act onset advanced by 0.3 h (P < 0.05), whereas the Tb predictive onset remained the same as in LDSq. The phase angle difference between Act and Tb predictive onsets decreased by 0.9 h (P < 0.05) in LDSN, but the offsets of both measures remained unchanged. In this study, animals exhibited different circadian entrainment characteristics under LDSq and LDSN, suggesting that gradual and abrupt transitions between light and dark may provide different temporal cues.

Prediction of high incidence of dengue in the Philippines.

PubMed

Buczak, Anna L; Baugher, Benjamin; Babin, Steven M; Ramac-Thomas, Liane C; Guven, Erhan; Elbert, Yevgeniy; Koshute, Phillip T; Velasco, John Mark S; Roque, Vito G; Tayag, Enrique A; Yoon, In-Kyu; Lewis, Sheri H

2014-04-01

Accurate prediction of dengue incidence levels weeks in advance of an outbreak may reduce the morbidity and mortality associated with this neglected disease. Therefore, models were developed to predict high and low dengue incidence in order to provide timely forewarnings in the Philippines. Model inputs were chosen based on studies indicating variables that may impact dengue incidence. The method first uses Fuzzy Association Rule Mining techniques to extract association rules from these historical epidemiological, environmental, and socio-economic data, as well as climate data indicating future weather patterns. Selection criteria were used to choose a subset of these rules for a classifier, thereby generating a Prediction Model. The models predicted high or low incidence of dengue in a Philippines province four weeks in advance. The threshold between high and low was determined relative to historical incidence data. Model accuracy is described by Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity, and Specificity computed on test data not previously used to develop the model. Selecting a model using the F0.5 measure, which gives PPV more importance than Sensitivity, gave these results: PPV = 0.780, NPV = 0.938, Sensitivity = 0.547, Specificity = 0.978. Using the F3 measure, which gives Sensitivity more importance than PPV, the selected model had PPV = 0.778, NPV = 0.948, Sensitivity = 0.627, Specificity = 0.974. The decision as to which model has greater utility depends on how the predictions will be used in a particular situation. This method builds prediction models for future dengue incidence in the Philippines and is capable of being modified for use in different situations; for diseases other than dengue; and for regions beyond the Philippines. The Philippines dengue prediction models predicted high or low incidence of dengue four weeks in advance of an outbreak with high accuracy, as measured by PPV, NPV, Sensitivity, and Specificity.

Prediction of High Incidence of Dengue in the Philippines

PubMed Central

Buczak, Anna L.; Baugher, Benjamin; Babin, Steven M.; Ramac-Thomas, Liane C.; Guven, Erhan; Elbert, Yevgeniy; Koshute, Phillip T.; Velasco, John Mark S.; Roque, Vito G.; Tayag, Enrique A.; Yoon, In-Kyu; Lewis, Sheri H.

2014-01-01

Background Accurate prediction of dengue incidence levels weeks in advance of an outbreak may reduce the morbidity and mortality associated with this neglected disease. Therefore, models were developed to predict high and low dengue incidence in order to provide timely forewarnings in the Philippines. Methods Model inputs were chosen based on studies indicating variables that may impact dengue incidence. The method first uses Fuzzy Association Rule Mining techniques to extract association rules from these historical epidemiological, environmental, and socio-economic data, as well as climate data indicating future weather patterns. Selection criteria were used to choose a subset of these rules for a classifier, thereby generating a Prediction Model. The models predicted high or low incidence of dengue in a Philippines province four weeks in advance. The threshold between high and low was determined relative to historical incidence data. Principal Findings Model accuracy is described by Positive Predictive Value (PPV), Negative Predictive Value (NPV), Sensitivity, and Specificity computed on test data not previously used to develop the model. Selecting a model using the F0.5 measure, which gives PPV more importance than Sensitivity, gave these results: PPV = 0.780, NPV = 0.938, Sensitivity = 0.547, Specificity = 0.978. Using the F3 measure, which gives Sensitivity more importance than PPV, the selected model had PPV = 0.778, NPV = 0.948, Sensitivity = 0.627, Specificity = 0.974. The decision as to which model has greater utility depends on how the predictions will be used in a particular situation. Conclusions This method builds prediction models for future dengue incidence in the Philippines and is capable of being modified for use in different situations; for diseases other than dengue; and for regions beyond the Philippines. The Philippines dengue prediction models predicted high or low incidence of dengue four weeks in advance of an outbreak with high accuracy, as measured by PPV, NPV, Sensitivity, and Specificity. PMID:24722434

Technologies for Turbofan Noise Reduction

NASA Technical Reports Server (NTRS)

Huff, Dennis

2005-01-01

An overview presentation of NASA's engine noise research since 1992 is given for subsonic commercial aircraft applications. Highlights are included from the Advanced Subsonic Technology (AST) Noise Reduction Program and the Quiet Aircraft Technology (QAT) project with emphasis on engine source noise reduction. Noise reduction goals for 10 EPNdB by 207 and 20 EPNdB by 2022 are reviewed. Fan and jet noise technologies are highlighted from the AST program including higher bypass ratio propulsion, scarf inlets, forward-swept fans, swept/leaned stators, chevron nozzles, noise prediction methods, and active noise control for fans. Source diagnostic tests for fans and jets that have been completed over the past few years are presented showing how new flow measurement methods such as Particle Image Velocimetry (PIV) have played a key role in understanding turbulence, the noise generation process, and how to improve noise prediction methods. Tests focused on source decomposition have helped identify which engine components need further noise reduction. The role of Computational AeroAcoustics (CAA) for fan noise prediction is presented. Advanced noise reduction methods such as Hershel-Quincke tubes and trailing edge blowing for fan noise that are currently being pursued n the QAT program are also presented. Highlights are shown form engine validation and flight demonstrations that were done in the late 1990's with Pratt & Whitney on their PW4098 engine and Honeywell on their TFE-731-60 engine. Finally, future propulsion configurations currently being studied that show promise towards meeting NASA's long term goal of 20 dB noise reduction are shown including a Dual Fan Engine concept on a Blended Wing Body aircraft.

American Gastroenterological Association guidelines are inaccurate in detecting pancreatic cysts with advanced neoplasia: a clinicopathologic study of 225 patients with supporting molecular data.

PubMed

Singhi, Aatur D; Zeh, Herbert J; Brand, Randall E; Nikiforova, Marina N; Chennat, Jennifer S; Fasanella, Kenneth E; Khalid, Asif; Papachristou, Georgios I; Slivka, Adam; Hogg, Melissa; Lee, Kenneth K; Tsung, Allan; Zureikat, Amer H; McGrath, Kevin

2016-06-01

The American Gastroenterological Association (AGA) recently reported evidence-based guidelines for the management of asymptomatic neoplastic pancreatic cysts. These guidelines advocate a higher threshold for surgical resection than prior guidelines and imaging surveillance for a considerable number of patients with pancreatic cysts. The aims of this study were to assess the accuracy of the AGA guidelines in detecting advanced neoplasia and present an alternative approach to pancreatic cysts. The study population consisted of 225 patients who underwent EUS-guided FNA for pancreatic cysts between January 2014 and May 2015. For each patient, clinical findings, EUS features, cytopathology results, carcinoembryonic antigen analysis, and molecular testing of pancreatic cyst fluid were reviewed. Molecular testing included the assessment of hotspot mutations and deletions for KRAS, GNAS, VHL, TP53, PIK3CA, and PTEN. Diagnostic pathology results were available for 41 patients (18%), with 13 (6%) harboring advanced neoplasia. Among these cases, the AGA guidelines identified advanced neoplasia with 62% sensitivity, 79% specificity, 57% positive predictive value, and 82% negative predictive value. Moreover, the AGA guidelines missed 45% of intraductal papillary mucinous neoplasms with adenocarcinoma or high-grade dysplasia. For cases without confirmatory pathology, 27 of 184 patients (15%) with serous cystadenomas (SCAs) based on EUS findings and/or VHL alterations would continue magnetic resonance imaging (MRI) surveillance. In comparison, a novel algorithmic pathway using molecular testing of pancreatic cyst fluid detected advanced neoplasias with 100% sensitivity, 90% specificity, 79% positive predictive value, and 100% negative predictive value. The AGA guidelines were inaccurate in detecting pancreatic cysts with advanced neoplasia. Furthermore, because the AGA guidelines manage all neoplastic cysts similarly, patients with SCAs will continue to undergo unnecessary MRI surveillance. The results of an alternative approach with integrative molecular testing are encouraging but require further validation. Copyright © 2016 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

A method to predict different mechanisms for blood-brain barrier permeability of CNS activity compounds in Chinese herbs using support vector machine.

PubMed

Jiang, Ludi; Chen, Jiahua; He, Yusu; Zhang, Yanling; Li, Gongyu

2016-02-01

The blood-brain barrier (BBB), a highly selective barrier between central nervous system (CNS) and the blood stream, restricts and regulates the penetration of compounds from the blood into the brain. Drugs that affect the CNS interact with the BBB prior to their target site, so the prediction research on BBB permeability is a fundamental and significant research direction in neuropharmacology. In this study, we combed through the available data and then with the help of support vector machine (SVM), we established an experiment process for discovering potential CNS compounds and investigating the mechanisms of BBB permeability of them to advance the research in this field four types of prediction models, referring to CNS activity, BBB permeability, passive diffusion and efflux transport, were obtained in the experiment process. The first two models were used to discover compounds which may have CNS activity and also cross the BBB at the same time; the latter two were used to elucidate the mechanism of BBB permeability of those compounds. Three optimization parameter methods, Grid Search, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), were used to optimize the SVM models. Then, four optimal models were selected with excellent evaluation indexes (the accuracy, sensitivity and specificity of each model were all above 85%). Furthermore, discrimination models were utilized to study the BBB properties of the known CNS activity compounds in Chinese herbs and this may guide the CNS drug development. With the relatively systematic and quick approach, the application rationality of traditional Chinese medicines for treating nervous system disease in the clinical practice will be improved.

Immune checkpoint inhibitors in urothelial cancer: recent updates and future outlook.

PubMed

Gopalakrishnan, Dharmesh; Koshkin, Vadim S; Ornstein, Moshe C; Papatsoris, Athanasios; Grivas, Petros

2018-01-01

Bladder cancer is the sixth most common cancer in the US and most tumors have urothelial (transitional cell) histology. Platinum-based chemotherapy has long been the standard of care in advanced disease, but long-term outcomes have largely remained poor. Since the peak incidence of bladder cancer is in the eighth decade of life and beyond, medical comorbidities may often limit the use of chemotherapy. Immune checkpoint inhibitors with their favorable toxicity profiles and notable antitumor activity have ushered in a new era in the treatment of advanced urothelial cancer (UC) with five agents targeting the PD-1/PD-L1 pathway being recently approved by the US Food and Drug administration. A plethora of clinical trials are ongoing in diverse disease settings, employing agents targeting PD-1/PD-L1 and related immune checkpoint pathways. While reactivating anti-tumor immunity, these agents may lead to a unique constellation of immune-related adverse events, which may warrant discontinuation of therapy and potential use of immunosuppression. Novel combinations with various treatment modalities and optimal sequencing of active therapies are being investigated in prospective clinical trials and retrospective registries. At the era of precision molecular medicine, and since patients do not respond uniformly to these agents, there is a growing need for identification and validation of biomarkers that can accurately predict treatment response and assist in patient selection. This review discusses current updates and future directions of immunotherapy in advanced UC.

Implementation and testing of the travel time prediction system (TIPS) : final report, May 2001.

DOT National Transportation Integrated Search

2001-05-01

The Travel Time Prediction System (TIPS) is a portable automated system for predicting and displaying travel time for motorists in advance of and through freeway construction work zones, on a real-time basis. It collects real-time traffic flow data u...

Implementation and testing of the travel time prediction system (TIPS) : executive summary, May 2001.

DOT National Transportation Integrated Search

2001-05-01

The Travel Time Prediction System (TIPS) is a portable automated system for predicting and displaying travel time for motorists in advance of and through freeway construction work zones, on a real-time basis. It collects real-time traffic flow data u...

Chronic Lowering of Blood Pressure by Carotid Baroreflex Activation: Mechanisms and Potential for Hypertension Therapy

PubMed Central

Lohmeier, Thomas E.; Iliescu, Radu

2011-01-01

Recent technical advances have renewed interest in device-based therapy for the treatment of drug-resistant hypertension. Findings from recent clinical trials regarding the efficacy of electrical stimulation of the carotid sinus for the treatment of resistant hypertension are reviewed here. The main goal of this article, however, is to summarize the preclinical studies that have provided insight into the mechanisms that account for the chronic blood pressure lowering effects of carotid baroreflex activation. Some of the mechanisms identified were predictable and confirmed by experimentation. Others have been surprising and controversial and resolution will require further investigation. Although feasibility studies have been promising, firm conclusions regarding the value of this device-based therapy for the treatment of resistant hypertension awaits the results of current multicenter trials. PMID:21357283

Blueprint for antimicrobial hit discovery targeting metabolic networks

PubMed Central

Shen, Y.; Liu, J.; Estiu, G.; Isin, B.; Ahn, Y-Y.; Lee, D-S.; Barabási, A-L.; Kapatral, V.; Wiest, O.; Oltvai, Z. N.

2010-01-01

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy. PMID:20080587

Risk of 12-month mortality among hospital inpatients using the surprise question and SPICT criteria: a prospective study.

PubMed

Mudge, Alison M; Douglas, Carol; Sansome, Xanthe; Tresillian, Michael; Murray, Stephen; Finnigan, Simon; Blaber, Cheryl Ruth

2018-06-01

People with serious life-limiting disease benefit from advance care planning, but require active identification. This study applied the Gold Standards Framework Proactive Identification Guidance (GSF-PIG) to a general hospital population to describe high-risk patients and explore prognostic performance for 12-month mortality. Prospective cohort study conducted in a metropolitan teaching hospital in Australia. Hospital inpatients on a single day aged 18 years and older were eligible, excluding maternity and neonatal, mental health and day treatment patients. Data sources included medical record and structured questions for medical and nursing staff. High-risk was predefined as positive response to the surprise question (SQ) plus two or more SPICT indicators of general deterioration. Descriptive variables included demographics, frailty and functional measures, treating team, advance care planning documentation and hospital utilisation. Primary outcome for prognostic performance was 12-month mortality. We identified 540 eligible inpatients on the study day and 513 had complete data (mean age 60, 54% male, 30% living alone, 19% elective admissions). Of these, 191 (37%) were high-risk; they were older, frailer, more dependent and had been in hospital longer than low-risk participants. Within 12 months, 92 participants (18%) died (72/191(38%) high-risk versus 20/322(6%) low-risk, P<0.001), providing sensitivity 78%, specificity 72%, positive predictive value 38% and negative predictive value 94%. SQ alone provided higher sensitivity, adding advanced disease indicators improved specificity. The GSF-PIG approach identified a large minority of hospital inpatients who might benefit from advance care planning. Future studies are needed to investigate the feasibility, cost and impact of screening in hospitals. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

The Research-to-Operations-to-Research Cycle at NOAA's Space Weather Prediction Center

NASA Astrophysics Data System (ADS)

Singer, H. J.

2017-12-01

The provision of actionable space weather products and services by NOAA's Space Weather Prediction Center relies on observations, models and scientific understanding of our dynamic space environment. It also depends on a deep understanding of the systems and capabilities that are vulnerable to space weather, as well as national and international partnerships that bring together resources, skills and applications to support space weather forecasters and customers. While these activities have been evolving over many years, in October 2015, with the release of the National Space Weather Strategy and National Space Weather Action Plan (NSWAP) by National Science and Technology Council in the Executive Office of the President, there is a new coordinated focus on ensuring the Nation is prepared to respond to and recover from severe space weather storms. One activity highlighted in the NSWAP is the Operations to Research (O2R) and Research to Operations (R2O) process. In this presentation we will focus on current R2O and O2R activities that advance our ability to serve those affected by space weather and give a vision for future programs. We will also provide examples of recent research results that lead to improved operational capabilities, lessons learned in the transition of research to operations, and challenges for both the science and operations communities.

Questioning the Faith - Models and Prediction in Stream Restoration (Invited)

NASA Astrophysics Data System (ADS)

Wilcock, P.

2013-12-01

River management and restoration demand prediction at and beyond our present ability. Management questions, framed appropriately, can motivate fundamental advances in science, although the connection between research and application is not always easy, useful, or robust. Why is that? This presentation considers the connection between models and management, a connection that requires critical and creative thought on both sides. Essential challenges for managers include clearly defining project objectives and accommodating uncertainty in any model prediction. Essential challenges for the research community include matching the appropriate model to project duration, space, funding, information, and social constraints and clearly presenting answers that are actually useful to managers. Better models do not lead to better management decisions or better designs if the predictions are not relevant to and accepted by managers. In fact, any prediction may be irrelevant if the need for prediction is not recognized. The predictive target must be developed in an active dialog between managers and modelers. This relationship, like any other, can take time to develop. For example, large segments of stream restoration practice have remained resistant to models and prediction because the foundational tenet - that channels built to a certain template will be able to transport the supplied sediment with the available flow - has no essential physical connection between cause and effect. Stream restoration practice can be steered in a predictive direction in which project objectives are defined as predictable attributes and testable hypotheses. If stream restoration design is defined in terms of the desired performance of the channel (static or dynamic, sediment surplus or deficit), then channel properties that provide these attributes can be predicted and a basis exists for testing approximations, models, and predictions.

Prediction of Indian Summer-Monsoon Onset Variability: A Season in Advance.

PubMed

Pradhan, Maheswar; Rao, A Suryachandra; Srivastava, Ankur; Dakate, Ashish; Salunke, Kiran; Shameera, K S

2017-10-27

Monsoon onset is an inherent transient phenomenon of Indian Summer Monsoon and it was never envisaged that this transience can be predicted at long lead times. Though onset is precipitous, its variability exhibits strong teleconnections with large scale forcing such as ENSO and IOD and hence may be predictable. Despite of the tremendous skill achieved by the state-of-the-art models in predicting such large scale processes, the prediction of monsoon onset variability by the models is still limited to just 2-3 weeks in advance. Using an objective definition of onset in a global coupled ocean-atmosphere model, it is shown that the skillful prediction of onset variability is feasible under seasonal prediction framework. The better representations/simulations of not only the large scale processes but also the synoptic and intraseasonal features during the evolution of monsoon onset are the comprehensions behind skillful simulation of monsoon onset variability. The changes observed in convection, tropospheric circulation and moisture availability prior to and after the onset are evidenced in model simulations, which resulted in high hit rate of early/delay in monsoon onset in the high resolution model.

Wafer hot spot identification through advanced photomask characterization techniques: part 2

NASA Astrophysics Data System (ADS)

Choi, Yohan; Green, Michael; Cho, Young; Ham, Young; Lin, Howard; Lan, Andy; Yang, Richer; Lung, Mike

2017-03-01

Historically, 1D metrics such as Mean to Target (MTT) and CD Uniformity (CDU) have been adequate for mask end users to evaluate and predict the mask impact on the wafer process. However, the wafer lithographer's process margin is shrinking at advanced nodes to a point that classical mask CD metrics are no longer adequate to gauge the mask contribution to wafer process error. For example, wafer CDU error at advanced nodes is impacted by mask factors such as 3-dimensional (3D) effects and mask pattern fidelity on sub-resolution assist features (SRAFs) used in Optical Proximity Correction (OPC) models of ever-increasing complexity. To overcome the limitation of 1D metrics, there are numerous on-going industry efforts to better define wafer-predictive metrics through both standard mask metrology and aerial CD methods. Even with these improvements, the industry continues to struggle to define useful correlative metrics that link the mask to final device performance. In part 1 of this work, we utilized advanced mask pattern characterization techniques to extract potential hot spots on the mask and link them, theoretically, to issues with final wafer performance. In this paper, part 2, we complete the work by verifying these techniques at wafer level. The test vehicle (TV) that was used for hot spot detection on the mask in part 1 will be used to expose wafers. The results will be used to verify the mask-level predictions. Finally, wafer performance with predicted and verified mask/wafer condition will be shown as the result of advanced mask characterization. The goal is to maximize mask end user yield through mask-wafer technology harmonization. This harmonization will provide the necessary feedback to determine optimum design, mask specifications, and mask-making conditions for optimal wafer process margin.

Score of liver ultrasonography predicts treatment-related severe neutropenia and neutropenic fever in induction chemotherapy with docetaxel for locally advanced head and neck cancer patients with normal serum transamines.

PubMed

Wang, Ting-Yao; Chen, Wei-Ming; Yang, Lan-Yan; Chen, Chao-Yu; Chou, Wen-Chi; Chen, Yi-Yang; Chen, Chih-Cheng; Lee, Kuan-Der; Lu, Chang-Hsien

2016-11-01

Induction chemotherapy with docetaxel improved outcome in advanced head and neck squamous cell carcinoma (HNSCC) patients, but docetaxel was not recommended in liver dysfunction patients for treatment toxicities. Severe neutropenic events (SNE) including severe neutropenia (SN) and febrile neutropenia (FN) still developed in these patients with normal serum transaminases. Ultrasonography (US) fibrotic score represented degree of hepatic parenchymal damage and showed good correlation to fibrotic changes histologically. This study aims to evaluate the association of US fibrotic score with docetaxel treatment-related SNE in advanced HNSCC patients with normal serum transaminases. Between 1 January 2011 and 31 December 2013, a total of 47 advanced HNSCC patients treated with induction docetaxel were enrolled. The clinical features were collected to assess predictive factors for SNE. The patients were divided into two groups by the US fibrotic score with a cutoff value of 7. The Mann-Whitney U test and logistic regression method were used for the risk factor analysis. The background, treatment, and response were similar in both groups except for lower lymphocyte and platelet count in patients with higher US score. Twenty-seven patients (51 %) developed grade 3/4 neutropenia, and more SNE developed in patients with US score ≧7. In multivariate analysis, only US score ≥7 was independent predictive factor for developing SN (hazard ratio 7.71, p = 0.043) and FN (hazard ratio 20.95, p = 0.008). US score ≥7 is an independent risk factor for SNE in advanced HNSCC patients treated with induction docetaxel. US score could be used for risk prediction of docetaxel-related SNE.

25 CFR 170.615 - Can a tribe receive advance payments for non-construction activities?

Code of Federal Regulations, 2010 CFR

2010-04-01

... 25 Indians 1 2010-04-01 2010-04-01 false Can a tribe receive advance payments for non-construction... Agreements Under Isdeaa § 170.615 Can a tribe receive advance payments for non-construction activities? Yes. BIA must make advance payments to a tribe for non-construction activities under 25 U.S.C. 450l for...

25 CFR 170.615 - Can a tribe receive advance payments for non-construction activities?

Code of Federal Regulations, 2011 CFR

2011-04-01

... 25 Indians 1 2011-04-01 2011-04-01 false Can a tribe receive advance payments for non-construction... Agreements Under Isdeaa § 170.615 Can a tribe receive advance payments for non-construction activities? Yes. BIA must make advance payments to a tribe for non-construction activities under 25 U.S.C. 450l for...

Development of linear free energy relationships for aqueous phase radical-involved chemical reactions.

PubMed

Minakata, Daisuke; Mezyk, Stephen P; Jones, Jace W; Daws, Brittany R; Crittenden, John C

2014-12-02

Aqueous phase advanced oxidation processes (AOPs) produce hydroxyl radicals (HO•) which can completely oxidize electron rich organic compounds. The proper design and operation of AOPs require that we predict the formation and fate of the byproducts and their associated toxicity. Accordingly, there is a need to develop a first-principles kinetic model that can predict the dominant reaction pathways that potentially produce toxic byproducts. We have published some of our efforts on predicting the elementary reaction pathways and the HO• rate constants. Here we develop linear free energy relationships (LFERs) that predict the rate constants for aqueous phase radical reactions. The LFERs relate experimentally obtained kinetic rate constants to quantum mechanically calculated aqueous phase free energies of activation. The LFERs have been applied to 101 reactions, including (1) HO• addition to 15 aromatic compounds; (2) addition of molecular oxygen to 65 carbon-centered aliphatic and cyclohexadienyl radicals; (3) disproportionation of 10 peroxyl radicals, and (4) unimolecular decay of nine peroxyl radicals. The LFERs correlations predict the rate constants within a factor of 2 from the experimental values for HO• reactions and molecular oxygen addition, and a factor of 5 for peroxyl radical reactions. The LFERs and the elementary reaction pathways will enable us to predict the formation and initial fate of the byproducts in AOPs. Furthermore, our methodology can be applied to other environmental processes in which aqueous phase radical-involved reactions occur.

Type- and Subtype-Specific Influenza Forecast.

PubMed

Kandula, Sasikiran; Yang, Wan; Shaman, Jeffrey

2017-03-01

Prediction of the growth and decline of infectious disease incidence has advanced considerably in recent years. As these forecasts improve, their public health utility should increase, particularly as interventions are developed that make explicit use of forecast information. It is the task of the research community to increase the content and improve the accuracy of these infectious disease predictions. Presently, operational real-time forecasts of total influenza incidence are produced at the municipal and state level in the United States. These forecasts are generated using ensemble simulations depicting local influenza transmission dynamics, which have been optimized prior to forecast with observations of influenza incidence and data assimilation methods. Here, we explore whether forecasts targeted to predict influenza by type and subtype during 2003-2015 in the United States were more or less accurate than forecasts targeted to predict total influenza incidence. We found that forecasts separated by type/subtype generally produced more accurate predictions and, when summed, produced more accurate predictions of total influenza incidence. These findings indicate that monitoring influenza by type and subtype not only provides more detailed observational content but supports more accurate forecasting. More accurate forecasting can help officials better respond to and plan for current and future influenza activity. © The Author 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Advancing decadal-scale climate prediction in the North Atlantic sector.

PubMed

Keenlyside, N S; Latif, M; Jungclaus, J; Kornblueh, L; Roeckner, E

2008-05-01

The climate of the North Atlantic region exhibits fluctuations on decadal timescales that have large societal consequences. Prominent examples include hurricane activity in the Atlantic, and surface-temperature and rainfall variations over North America, Europe and northern Africa. Although these multidecadal variations are potentially predictable if the current state of the ocean is known, the lack of subsurface ocean observations that constrain this state has been a limiting factor for realizing the full skill potential of such predictions. Here we apply a simple approach-that uses only sea surface temperature (SST) observations-to partly overcome this difficulty and perform retrospective decadal predictions with a climate model. Skill is improved significantly relative to predictions made with incomplete knowledge of the ocean state, particularly in the North Atlantic and tropical Pacific oceans. Thus these results point towards the possibility of routine decadal climate predictions. Using this method, and by considering both internal natural climate variations and projected future anthropogenic forcing, we make the following forecast: over the next decade, the current Atlantic meridional overturning circulation will weaken to its long-term mean; moreover, North Atlantic SST and European and North American surface temperatures will cool slightly, whereas tropical Pacific SST will remain almost unchanged. Our results suggest that global surface temperature may not increase over the next decade, as natural climate variations in the North Atlantic and tropical Pacific temporarily offset the projected anthropogenic warming.

A comparison of muscle activation between back squats and belt squats.

PubMed

Evans, Thomas W; McLester, Cherilyn N; Howard, Jonathan H; McLester, John R; Calloway, Jimmy P

2017-06-08

A machine belt squat is a piece of equipment designed to allow the performance of squats while loading weight on the lifter's hips using a belt. The purpose of this investigation was to determine if belt squats differ from back squats in activation of the primary movers, and to determine the predictive capabilities of back squat load, training status, and anthropometric data on belt squat load. Thirty-one participants (16 males and 15 females) completed anthropometric measurements, a demographic questionnaire, a familiarization visit, and two testing visits, completing a 5 repetition maximum test for back squat and belt squat. Surface electromyography was used to measure muscle activation for the left and right vastus medialis (VMO), vastus lateralis (VLO), rectus femoris (RF), and gluteus maximus (GM). Comparison of muscle activation between the two exercises showed significant differences in the left GM (back squat: 0.84 ± 0.45, belt squat: 0.69 ± 0.22, p=0.015) and right GM (back squat: 0.86 ± 0.45, belt squat: 0.71 ± 0.29, p=0.004). Regression analysis computed significant prediction equations for belt squat load for general population, males, females, and advanced lifters. Overall, results indicate that belt squats may significantly differ in GM activation from back squats. Back squat load, as well as other variables, may be effective in accurately estimating appropriate belt squat load. These findings may help to more appropriately program for training with machine belt squats as a back squat alternative.

A neural model of valuation and information virality

PubMed Central

Baek, Elisa C.; O’Donnell, Matthew Brook; Kim, Hyun Suk; Cappella, Joseph N.

2017-01-01

Information sharing is an integral part of human interaction that serves to build social relationships and affects attitudes and behaviors in individuals and large groups. We present a unifying neurocognitive framework of mechanisms underlying information sharing at scale (virality). We argue that expectations regarding self-related and social consequences of sharing (e.g., in the form of potential for self-enhancement or social approval) are integrated into a domain-general value signal that encodes the value of sharing a piece of information. This value signal translates into population-level virality. In two studies (n = 41 and 39 participants), we tested these hypotheses using functional neuroimaging. Neural activity in response to 80 New York Times articles was observed in theory-driven regions of interest associated with value, self, and social cognitions. This activity then was linked to objectively logged population-level data encompassing n = 117,611 internet shares of the articles. In both studies, activity in neural regions associated with self-related and social cognition was indirectly related to population-level sharing through increased neural activation in the brain's value system. Neural activity further predicted population-level outcomes over and above the variance explained by article characteristics and commonly used self-report measures of sharing intentions. This parsimonious framework may help advance theory, improve predictive models, and inform new approaches to effective intervention. More broadly, these data shed light on the core functions of sharing—to express ourselves in positive ways and to strengthen our social bonds. PMID:28242678

Characterizing Forest Change Using Community-Based Monitoring Data and Landsat Time Series

PubMed Central

DeVries, Ben; Pratihast, Arun Kumar; Verbesselt, Jan; Kooistra, Lammert; Herold, Martin

2016-01-01

Increasing awareness of the issue of deforestation and degradation in the tropics has resulted in efforts to monitor forest resources in tropical countries. Advances in satellite-based remote sensing and ground-based technologies have allowed for monitoring of forests with high spatial, temporal and thematic detail. Despite these advances, there is a need to engage communities in monitoring activities and include these stakeholders in national forest monitoring systems. In this study, we analyzed activity data (deforestation and forest degradation) collected by local forest experts over a 3-year period in an Afro-montane forest area in southwestern Ethiopia and corresponding Landsat Time Series (LTS). Local expert data included forest change attributes, geo-location and photo evidence recorded using mobile phones with integrated GPS and photo capabilities. We also assembled LTS using all available data from all spectral bands and a suite of additional indices and temporal metrics based on time series trajectory analysis. We predicted deforestation, degradation or stable forests using random forest models trained with data from local experts and LTS spectral-temporal metrics as model covariates. Resulting models predicted deforestation and degradation with an out of bag (OOB) error estimate of 29% overall, and 26% and 31% for the deforestation and degradation classes, respectively. By dividing the local expert data into training and operational phases corresponding to local monitoring activities, we found that forest change models improved as more local expert data were used. Finally, we produced maps of deforestation and degradation using the most important spectral bands. The results in this study represent some of the first to combine local expert based forest change data and dense LTS, demonstrating the complementary value of both continuous data streams. Our results underpin the utility of both datasets and provide a useful foundation for integrated forest monitoring systems relying on data streams from diverse sources. PMID:27018852

Differential Activity of Nivolumab, Pembrolizumab and MPDL3280A according to the Tumor Expression of Programmed Death-Ligand-1 (PD-L1): Sensitivity Analysis of Trials in Melanoma, Lung and Genitourinary Cancers

PubMed Central

Carbognin, Luisa; Pilotto, Sara; Milella, Michele; Vaccaro, Vanja; Brunelli, Matteo; Caliò, Anna; Cuppone, Federica; Sperduti, Isabella; Giannarelli, Diana; Chilosi, Marco; Bronte, Vincenzo; Scarpa, Aldo

2015-01-01

Background The potential predictive role of programmed death-ligand-1 (PD-L1) expression on tumor cells in the context of solid tumor treated with checkpoint inhibitors targeting the PD-1 pathway represents an issue for clinical research. Methods Overall response rate (ORR) was extracted from phase I-III trials investigating nivolumab, pembrolizumab and MPDL3280A for advanced melanoma, non-small cell lung cancer (NSCLC) and genitourinary cancer, and cumulated by adopting a fixed and random-effect model with 95% confidence interval (CI). Interaction test according to tumor PD-L1 was accomplished. A sensitivity analysis according to adopted drug, tumor type, PD-L1 cut-off and treatment line was performed. Results Twenty trials (1,475 patients) were identified. A significant interaction (p<0.0001) according to tumor PD-L1 expression was found in the overall sample with an ORR of 34.1% (95% CI 27.6-41.3%) in the PD-L1 positive and 19.9% (95% CI 15.4-25.3%) in the PD-L1 negative population. ORR was significantly higher in PD-L1 positive in comparison to PD-L1 negative patients for nivolumab and pembrolizumab, with an absolute difference of 16.4% and 19.5%, respectively. A significant difference in activity of 22.8% and 8.7% according to PD-L1 was found for melanoma and NSCLC, respectively, with no significant difference for genitourinary cancer. Conclusion Overall, the three antibodies provide a significant differential effect in terms of activity according to PD-L1 expression on tumor cells. The predictive value of PD-L1 on tumor cells seems to be more robust for anti-PD-1 antibody (nivolumab and pembrolizumab), and in the context of advanced melanoma and NSCLC. PMID:26086854

Inflation-predictable behavior and co-eruption deformation at Axial Seamount.

PubMed

Nooner, Scott L; Chadwick, William W

2016-12-16

Deformation of the ground surface at active volcanoes provides information about magma movements at depth. Improved seafloor deformation measurements between 2011 and 2015 documented a fourfold increase in magma supply and confirmed that Axial Seamount's eruptive behavior is inflation-predictable, probably triggered by a critical level of magmatic pressure. A 2015 eruption was successfully forecast on the basis of this deformation pattern and marked the first time that deflation and tilt were captured in real time by a new seafloor cabled observatory, revealing the timing, location, and volume of eruption-related magma movements. Improved modeling of the deformation suggests a steeply dipping prolate-spheroid pressure source beneath the eastern caldera that is consistent with the location of the zone of highest melt within the subcaldera magma reservoir determined from multichannel seismic results. Copyright © 2016, American Association for the Advancement of Science.

Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System

PubMed Central

Katz, Graham; Summers, Kristen; Ackermann, Chris; Zavorin, Ilya; Lim, Zunsik; Muthiah, Sathappan; Butler, Patrick; Self, Nathan; Zhao, Liang; Lu, Chang-Tien; Khandpur, Rupinder Paul; Fayed, Youssef; Ramakrishnan, Naren

2014-01-01

Abstract Developed under the Intelligence Advanced Research Project Activity Open Source Indicators program, Early Model Based Event Recognition using Surrogates (EMBERS) is a large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed on Amazon Web Services using an entirely automated deployment process. We describe the architecture of the system, some of the design tradeoffs encountered during development, and specifics of the machine learning models underlying EMBERS. We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years. PMID:25553271

Extinctions. Paleontological baselines for evaluating extinction risk in the modern oceans.

PubMed

Finnegan, Seth; Anderson, Sean C; Harnik, Paul G; Simpson, Carl; Tittensor, Derek P; Byrnes, Jarrett E; Finkel, Zoe V; Lindberg, David R; Liow, Lee Hsiang; Lockwood, Rowan; Lotze, Heike K; McClain, Craig R; McGuire, Jenny L; O'Dea, Aaron; Pandolfi, John M

2015-05-01

Marine taxa are threatened by anthropogenic impacts, but knowledge of their extinction vulnerabilities is limited. The fossil record provides rich information on past extinctions that can help predict biotic responses. We show that over 23 million years, taxonomic membership and geographic range size consistently explain a large proportion of extinction risk variation in six major taxonomic groups. We assess intrinsic risk-extinction risk predicted by paleontologically calibrated models-for modern genera in these groups. Mapping the geographic distribution of these genera identifies coastal biogeographic provinces where fauna with high intrinsic risk are strongly affected by human activity or climate change. Such regions are disproportionately in the tropics, raising the possibility that these ecosystems may be particularly vulnerable to future extinctions. Intrinsic risk provides a prehuman baseline for considering current threats to marine biodiversity. Copyright © 2015, American Association for the Advancement of Science.

Implantable cardiac resynchronization therapy devices to monitor heart failure clinical status.

PubMed

Fung, Jeffrey Wing-Hong; Yu, Cheuk-Man

2007-03-01

Cardiac resynchronization therapy is a standard therapy for selected patients with heart failure. With advances in technology and storage capacity, the device acts as a convenient platform to provide valuable information about heart failure status in these high-risk patients. Unlike other modalities of investigation which may only allow one-off evaluation, heart failure status can be monitored by device diagnostics including heart rate variability, activity status, and intrathoracic impedance in a continuous basis. These parameters do not just provide long-term prognostic information but also may be useful to predict upcoming heart failure exacerbation. Prompt and early intervention may abort decompensation, prevent hospitalization, improve quality of life, and reduce health care cost. Moreover, this information may be applied to titrate the dosage of medication and monitor response to heart failure treatment. This review will focus on the prognostic and predictive values of heart failure status monitoring provided by these devices.

Human affection exchange: VI. Further tests of reproductive probability as a predictor of men's affection with their adult sons.

PubMed

Floyd, Kory; Sargent, Jack E; Di Corcia, Mark

2004-04-01

The authors examined the communication of affection in men's relationships with their fathers. Drawing from Affection Exchange Theory, the authors advanced four predictions: (a) heterosexual men receive more affection from their own fathers than do homosexual or bisexual men, (b) fathers communicate affection to their sons more through supportive activities than through direct verbal statements or nonverbal gestures, (c) affectionate communication between fathers and sons is linearly related to closeness and interpersonal involvement between them, and (d) fathers' awareness of their sons' sexual orientation is associated with the amount of affection that the fathers communicate to them. Participants were 170 adult men who completed questionnaires regarding affectionate communication in their relationships with their fathers. Half of the men were self-identified as exclusively heterosexual, and the other half were self-identified as exclusively homosexual or bisexual. The results supported all predictions substantially.

Bioinformatics and peptidomics approaches to the discovery and analysis of food-derived bioactive peptides.

PubMed

Agyei, Dominic; Tsopmo, Apollinaire; Udenigwe, Chibuike C

2018-06-01

There are emerging advancements in the strategies used for the discovery and development of food-derived bioactive peptides because of their multiple food and health applications. Bioinformatics and peptidomics are two computational and analytical techniques that have the potential to speed up the development of bioactive peptides from bench to market. Structure-activity relationships observed in peptides form the basis for bioinformatics and in silico prediction of bioactive sequences encrypted in food proteins. Peptidomics, on the other hand, relies on "hyphenated" (liquid chromatography-mass spectrometry-based) techniques for the detection, profiling, and quantitation of peptides. Together, bioinformatics and peptidomics approaches provide a low-cost and effective means of predicting, profiling, and screening bioactive protein hydrolysates and peptides from food. This article discuses the basis, strengths, and limitations of bioinformatics and peptidomics approaches currently used for the discovery and analysis of food-derived bioactive peptides.

Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System.

PubMed

Doyle, Andy; Katz, Graham; Summers, Kristen; Ackermann, Chris; Zavorin, Ilya; Lim, Zunsik; Muthiah, Sathappan; Butler, Patrick; Self, Nathan; Zhao, Liang; Lu, Chang-Tien; Khandpur, Rupinder Paul; Fayed, Youssef; Ramakrishnan, Naren

2014-12-01

Developed under the Intelligence Advanced Research Project Activity Open Source Indicators program, Early Model Based Event Recognition using Surrogates (EMBERS) is a large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed on Amazon Web Services using an entirely automated deployment process. We describe the architecture of the system, some of the design tradeoffs encountered during development, and specifics of the machine learning models underlying EMBERS. We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years.

Low Data Drug Discovery with One-Shot Learning.

PubMed

Altae-Tran, Han; Ramsundar, Bharath; Pappu, Aneesh S; Pande, Vijay

2017-04-26

Recent advances in machine learning have made significant contributions to drug discovery. Deep neural networks in particular have been demonstrated to provide significant boosts in predictive power when inferring the properties and activities of small-molecule compounds (Ma, J. et al. J. Chem. Inf. 2015, 55, 263-274). However, the applicability of these techniques has been limited by the requirement for large amounts of training data. In this work, we demonstrate how one-shot learning can be used to significantly lower the amounts of data required to make meaningful predictions in drug discovery applications. We introduce a new architecture, the iterative refinement long short-term memory, that, when combined with graph convolutional neural networks, significantly improves learning of meaningful distance metrics over small-molecules. We open source all models introduced in this work as part of DeepChem, an open-source framework for deep-learning in drug discovery (Ramsundar, B. deepchem.io. https://github.com/deepchem/deepchem, 2016).

NEURAL SUBSTRATES OF CUE-REACTIVITY: ASSOCIATION WITH TREATMENT OUTCOMES AND RELAPSE

PubMed Central

Courtney, Kelly E.; Schacht, Joseph P.; Hutchison, Kent; Roche, Daniel J.O.; Ray, Lara A.

2016-01-01

Given the strong evidence for neurological alterations at the basis of drug dependence, functional magnetic resonance imaging (fMRI) represents an important tool in the clinical neuroscience of addiction. fMRI cue-reactivity paradigms represent an ideal platform to probe the involvement of neurobiological pathways subserving the reward/motivation system in addiction and potentially offer a translational mechanism by which interventions and behavioral predictions can be tested. Thus, this review summarizes the research that has applied fMRI cue-reactivity paradigms to the study of adult substance use disorder treatment responses. Studies utilizing fMRI cue-reactivity paradigms for the prediction of relapse, and as a means to investigate psychosocial and pharmacological treatment effects on cue-elicited brain activation are presented within four primary categories of substances: alcohol, nicotine, cocaine, and opioids. Lastly, suggestions for how to leverage fMRI technology to advance addiction science and treatment development are provided. PMID:26435524

Water quality in the Schuylkill River, Pennsylvania: the potential for long-lead forecasts

NASA Astrophysics Data System (ADS)

Block, P. J.; Peralez, J.

2012-12-01

Prior analysis of pathogen levels in the Schuylkill River has led to a categorical daily forecast of water quality (denoted as red, yellow, or green flag days.) The forecast, available to the public online through the Philadelphia Water Department, is predominantly based on the local precipitation forecast. In this study, we explore the feasibility of extending the forecast to the seasonal scale by associating large-scale climate drivers with local precipitation and water quality parameter levels. This advance information is relevant for recreational activities, ecosystem health, and water treatment (energy, chemicals), as the Schuylkill provides 40% of Philadelphia's water supply. Preliminary results indicate skillful prediction of average summertime water quality parameters and characteristics, including chloride, coliform, turbidity, alkalinity, and others, using season-ahead oceanic and atmospheric variables, predominantly from the North Atlantic. Water quality parameter trends, including historic land use changes along the river, association with climatic variables, and prediction models will be presented.

Iron-targeting antitumor activity of gallium compounds and novel insights into triapine(®)-metal complexes.

PubMed

Chitambar, Christopher R; Antholine, William E

2013-03-10

Despite advances made in the treatment of cancer, a significant number of patients succumb to this disease every year. Hence, there is a great need to develop new anticancer agents. Emerging data show that malignant cells have a greater requirement for iron than normal cells do and that proteins involved in iron import, export, and storage may be altered in cancer cells. Therefore, strategies to perturb these iron-dependent steps in malignant cells hold promise for the treatment of cancer. Recent studies show that gallium compounds and metal-thiosemicarbazone complexes inhibit tumor cell growth by targeting iron homeostasis, including iron-dependent ribonucleotide reductase. Chemical similarities of gallium(III) with iron(III) enable the former to mimic the latter and interpose itself in critical iron-dependent steps in cellular proliferation. Newer gallium compounds have emerged with additional mechanisms of action. In clinical trials, the first-generation-compound gallium nitrate has exhibited activity against bladder cancer and non-Hodgkin's lymphoma, while the thiosemicarbazone Triapine(®) has demonstrated activity against other tumors. Novel gallium compounds with greater cytotoxicity and a broader spectrum of antineoplastic activity than gallium nitrate should continue to be developed. The antineoplastic activity and toxicity of the existing novel gallium compounds and thiosemicarbazone-metal complexes should be tested in animal tumor models and advanced to Phase I and II clinical trials. Future research should identify biologic markers that predict tumor sensitivity to gallium compounds. This will help direct gallium-based therapy to cancer patients who are most likely to benefit from it.

Year of Tropical Convection (YOTC): Status and Research Agenda

NASA Astrophysics Data System (ADS)

Moncrieff, M. W.; Waliser, D. E.

2009-12-01

The realistic representation of tropical convection in global models is a long-standing challenge for numerical weather prediction and an emerging grand challenge for climate prediction in respect to its physical basis. Insufficient knowledge and practical capabilities in this area disadvantage the modeling and prediction of prominent multi-scale phenomena such as the ITCZ, ENSO, monsoons and their active/break periods, the MJO, subtropical stratus decks, near-surface ocean properties, and tropical cyclones. Science elements include the diurnal cycle of precipitation, multi-scale convective organization, the global energy and water cycle, and interaction between the tropics and extra-tropics which interact strongly on timescales of weeks-to-months: the intersection of weather and climate. To address such challenges, the WCRP and WWRP/THORPEX are conducting a joint international research project, the Year of Tropical Convection (YOTC) which is a coordinated observing, modeling and forecasting project. The focus-year and integrated framework is intended to exploit the vast observational datasets, the modern high-resolution modeling frameworks, and theoretical insights. The over-arching objective is to advance the characterization, diagnosis, modeling, parameterization and prediction of multi-scale organized tropical phenomena and their interaction with the global circulation. The “Year” (May 2008 - April 2010) is intended to leverage recent major investments in Earth Science infrastructure and overlapping observational activities, e.g., Asian Monsoon Years (AMY) and the THORPEX Pacific Asian Regional Campaign (T-PARC). The research agenda involves phenomena and scale-interactions that are problematic for prediction models and have important socio-economic implications: MJO and convectively coupled equatorial waves; easterly waves and tropical cyclones; the monsoons including their intraseasonal variability; the diurnal cycle of precipitation; and two-way tropical-extratropical interaction. This presentation will summarize the status of the above.

Improved accuracy of supervised CRM discovery with interpolated Markov models and cross-species comparison

PubMed Central

Kazemian, Majid; Zhu, Qiyun; Halfon, Marc S.; Sinha, Saurabh

2011-01-01

Despite recent advances in experimental approaches for identifying transcriptional cis-regulatory modules (CRMs, ‘enhancers’), direct empirical discovery of CRMs for all genes in all cell types and environmental conditions is likely to remain an elusive goal. Effective methods for computational CRM discovery are thus a critically needed complement to empirical approaches. However, existing computational methods that search for clusters of putative binding sites are ineffective if the relevant TFs and/or their binding specificities are unknown. Here, we provide a significantly improved method for ‘motif-blind’ CRM discovery that does not depend on knowledge or accurate prediction of TF-binding motifs and is effective when limited knowledge of functional CRMs is available to ‘supervise’ the search. We propose a new statistical method, based on ‘Interpolated Markov Models’, for motif-blind, genome-wide CRM discovery. It captures the statistical profile of variable length words in known CRMs of a regulatory network and finds candidate CRMs that match this profile. The method also uses orthologs of the known CRMs from closely related genomes. We perform in silico evaluation of predicted CRMs by assessing whether their neighboring genes are enriched for the expected expression patterns. This assessment uses a novel statistical test that extends the widely used Hypergeometric test of gene set enrichment to account for variability in intergenic lengths. We find that the new CRM prediction method is superior to existing methods. Finally, we experimentally validate 12 new CRM predictions by examining their regulatory activity in vivo in Drosophila; 10 of the tested CRMs were found to be functional, while 6 of the top 7 predictions showed the expected activity patterns. We make our program available as downloadable source code, and as a plugin for a genome browser installed on our servers. PMID:21821659

Unsteady blade-surface pressures on a large-scale advanced propeller: Prediction and data

NASA Technical Reports Server (NTRS)

Nallasamy, M.; Groeneweg, J. F.

1990-01-01

An unsteady 3-D Euler analysis technique is employed to compute the flow field of an advanced propeller operating at an angle of attack. The predicted blade pressure waveforms are compared with wind tunnel data at two Mach numbers, 0.5 and 0.2. The inflow angle is three degrees. For an inflow Mach number of 0.5, the predicted pressure response is in fair agreement with data: the predicted phases of the waveforms are in close agreement with data while the magnitudes are underpredicted. At the low Mach number of 0.2 (takeoff), the numerical solution shows the formation of a leading edge vortex which is in qualitative agreement with measurements. However, the highly nonlinear pressure response measured on the blade suction surface is not captured in the present inviscid analysis.

Comparative decision models for anticipating shortage of food grain production in India

NASA Astrophysics Data System (ADS)

Chattopadhyay, Manojit; Mitra, Subrata Kumar

2018-01-01

This paper attempts to predict food shortages in advance from the analysis of rainfall during the monsoon months along with other inputs used for crop production, such as land used for cereal production, percentage of area covered under irrigation and fertiliser use. We used six binary classification data mining models viz., logistic regression, Multilayer Perceptron, kernel lab-Support Vector Machines, linear discriminant analysis, quadratic discriminant analysis and k-Nearest Neighbors Network, and found that linear discriminant analysis and kernel lab-Support Vector Machines are equally suitable for predicting per capita food shortage with 89.69 % accuracy in overall prediction and 92.06 % accuracy in predicting food shortage ( true negative rate). Advance information of food shortage can help policy makers to take remedial measures in order to prevent devastating consequences arising out of food non-availability.

Earth Observing System/Advanced Microwave Sounding Unit-A (EOS/AMSU-A): Reliability prediction report for module A1 (channels 3 through 15) and module A2 (channels 1 and 2)

NASA Technical Reports Server (NTRS)

Geimer, W.

1995-01-01

This report documents the final reliability prediction performed on the Earth Observing System/Advanced Microwave Sounding Unit-A (EOS/AMSU-A). The A1 Module contains Channels 3 through 15, and is referred to herein as 'EOS/AMSU-A1'. The A2 Module contains Channels 1 and 2, and is referred herein as 'EOS/AMSU-A2'. The 'specified' figures were obtained from Aerojet Reports 8897-1 and 9116-1. The predicted reliability figure for the EOS/AMSU-A1 meets the specified value and provides a Mean Time Between Failures (MTBF) of 74,390 hours. The predicted reliability figure for the EOS/AMSU-A2 meets the specified value and provides a MTBF of 193,110 hours.

A statistical rain attenuation prediction model with application to the advanced communication technology satellite project. 3: A stochastic rain fade control algorithm for satellite link power via non linear Markow filtering theory

NASA Technical Reports Server (NTRS)

Manning, Robert M.

1991-01-01

The dynamic and composite nature of propagation impairments that are incurred on Earth-space communications links at frequencies in and above 30/20 GHz Ka band, i.e., rain attenuation, cloud and/or clear air scintillation, etc., combined with the need to counter such degradations after the small link margins have been exceeded, necessitate the use of dynamic statistical identification and prediction processing of the fading signal in order to optimally estimate and predict the levels of each of the deleterious attenuation components. Such requirements are being met in NASA's Advanced Communications Technology Satellite (ACTS) Project by the implementation of optimal processing schemes derived through the use of the Rain Attenuation Prediction Model and nonlinear Markov filtering theory.

Unsteady blade surface pressures on a large-scale advanced propeller - Prediction and data

NASA Technical Reports Server (NTRS)

Nallasamy, M.; Groeneweg, J. F.

1990-01-01

An unsteady three dimensional Euler analysis technique is employed to compute the flowfield of an advanced propeller operating at an angle of attack. The predicted blade pressure waveforms are compared with wind tunnel data at two Mach numbers, 0.5 and 0.2. The inflow angle is three degrees. For an inflow Mach number of 0.5, the predicted pressure response is in fair agreement with data: the predicted phases of the waveforms are in close agreement with data while the magnitudes are underpredicted. At the low Mach number of 0.2 (take-off) the numerical solution shows the formation of a leading edge vortex which is in qualitative agreement with measurements. However, the highly nonlinear pressure response measured on the blade suction surface is not captured in the present inviscid analysis.

Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

NASA Technical Reports Server (NTRS)

Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

2014-01-01

This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.

Prediction model for prevalence and incidence of advanced age-related macular degeneration based on genetic, demographic, and environmental variables.

PubMed

Seddon, Johanna M; Reynolds, Robyn; Maller, Julian; Fagerness, Jesen A; Daly, Mark J; Rosner, Bernard

2009-05-01

The joint effects of genetic, ocular, and environmental variables were evaluated and predictive models for prevalence and incidence of AMD were assessed. Participants in the multicenter Age-Related Eye Disease Study (AREDS) were included in a prospective evaluation of 1446 individuals, of which 279 progressed to advanced AMD (geographic atrophy or neovascular disease) and 1167 did not progress during 6.3 years of follow-up. For prevalent AMD, 509 advanced cases were compared with 222 controls. Covariates for the incidence analysis included age, sex, education, smoking, body mass index (BMI), baseline AMD grade, and the AREDS vitamin-mineral treatment assignment. DNA specimens were evaluated for six variants in five genes related to AMD. Unconditional logistic regression analyses were performed for prevalent and incident advanced AMD. An algorithm was developed and receiver operating characteristic curves and C statistics were calculated to assess the predictive ability of risk scores to discriminate progressors from nonprogressors. All genetic polymorphisms were independently related to prevalence of advanced AMD, controlling for genetic factors, smoking, BMI, and AREDS treatment. Multivariate odds ratios (ORs) were 3.5 (95% confidence interval [CI], 1.7-7.1) for CFH Y402H; 3.7 (95% CI, 1.6-8.4) for CFH rs1410996; 25.4 (95% CI, 8.6-75.1) for LOC387715 A69S (ARMS2); 0.3 (95% CI, 0.1-0.7) for C2 E318D; 0.3 (95% CI, 0.1-0.5) for CFB; and 3.6 (95% CI, 1.4-9.4) for C3 R102G, comparing the homozygous risk/protective genotypes to the referent genotypes. For incident AMD, all these variants except CFB were significantly related to progression to advanced AMD, after controlling for baseline AMD grade and other factors, with ORs from 1.8 to 4.0 for presence of two risk alleles and 0.4 for the protective allele. An interaction was seen between CFH402H and treatment, after controlling for all genotypes. Smoking was independently related to AMD, with a multiplicative joint effect with genotype on AMD risk. The C statistic for the full model with all variables was 0.831 for progression to advanced AMD. Factors reflective of nature and nurture are independently related to prevalence and incidence of advanced AMD, with excellent predictive power.

Coastal geomorphology through the looking glass

NASA Astrophysics Data System (ADS)

Sherman, Douglas J.; Bauer, Bernard O.

1993-07-01

Coastal geomorphology will gain future prominence as environmentally sound coastal zone management strategies, requiring scientific information, begin to supplant engineered shoreline stabilization schemes for amelioration of coastal hazards. We anticipate substantial change and progress over the next two decades, but we do not predict revolutionary advances in theoretical understanding of coastal geomorphic systems. Paradigm shifts will not occur; knowledge will advance incrementally. We offer predictions for specific coastal systems delineated according to scale. For the surf zone, we predict advances in wave shoaling theory, but not for wave breaking. We also predict greater understanding of turbulent processes, and substantive improvements in surf-zone circulation and radiation stress models. Very few of these improvements are expected to be incorporated in geomorphic models of coastal processes. We do not envision improvements in the theory of sediment transport, although some new and exciting empirical observations are probable. At the beach and nearshore scale, we predict the development of theoretically-based, two- and three-dimensional morphodynamical models that account for non-linear, time-dependent feedback processes using empirically calibrated modules. Most of the geomorphic research effort, however, will be concentrated at the scale of littoral cells. This scale is appropriate for coastal zone management because processes at this scale are manageable using traditional geomorphic techniques. At the largest scale, little advance will occur in our understanding of how coastlines evolve. Any empirical knowledge that is gained will accrue indirectly. Finally, we contend that anthropogenic influences, directly and indirectly, will be powerful forces in steering the future of Coastal Geomorphology. "If you should suddenly feel the need for a lesson in humility, try forecasting the future…" (Kleppner, 1991, p. 10).

Low levels of Caspase-3 predict favourable response to 5FU-based chemotherapy in advanced colorectal cancer: Caspase-3 inhibition as a therapeutic approach.

PubMed

Flanagan, L; Meyer, M; Fay, J; Curry, S; Bacon, O; Duessmann, H; John, K; Boland, K C; McNamara, D A; Kay, E W; Bantel, H; Schulze-Bergkamen, H; Prehn, J H M

2016-02-04

Colorectal cancer (CRC) is one of the most common cancers in the Western world. 5-Fluorouracil (5FU)-based chemotherapy (CT) remains the mainstay treatment of CRC in the advanced setting, and activates executioner caspases in target cells. Executioner caspases are key proteins involved in cell disassembly during apoptosis. Activation of executioner caspases also has a role in tissue regeneration and repopulation by stimulating signal transduction and cell proliferation in neighbouring, non-apoptotic cells as reported recently. Tissue microarrays (TMAs) consisting of tumour tissue from 93 stage II and III colon cancer patients were analysed by immunohistochemistry. Surprisingly, patients with low levels of active Caspase-3 had an increased disease-free survival time. This was particularly pronounced in patients who received 5FU-based adjuvant CT. In line with this observation, lower serum levels of active Caspase-3 were found in patients with metastasised CRC who revealed stable disease or tumour regression compared with those with disease progression. The role of Caspase-3 in treatment responses was explored further in primary human tumour explant cultures from fresh patient tumour tissue. Exposure of explant cultures to 5FU-based CT increased the percentage of cells positive for active Caspase-3 and Terminal Deoxynucleotidyl Transferase dUTP Nick end Labelling (TUNEL), but also the expression of regeneration and proliferation markers β-Catenin and Ki-67, as well as cyclooxygenase-2 (COX-2). Of note, selective inhibition of Caspase-3 with Ac-DNLD-CHO, a selective, reversible inhibitor of Caspase-3, significantly reduced the expression of proliferation markers as well as COX-2. Inhibition of COX-2 with aspirin or celecoxib did not affect Caspase-3 levels but also reduced Ki-67 and β-Catenin levels, suggesting that Caspase-3 acted via COX-2 to stimulate cell proliferation and tissue regeneration. This indicates that low levels of active Caspase-3 may represent a new predictor of CT responsiveness, and inhibition of Caspase-3, or antagonising downstream effectors of Caspase-3 paracrine signalling, such as COX-2 may improve patient outcomes following CT in advanced CRC.

Advanced Electrocardiographic Predictors of Sudden Death in Familial Dysautonomia

NASA Technical Reports Server (NTRS)

Solaimanzadeh, I.; Schlegel, T. T.; Greco, E. C.; DePalma, J. L.; Starc, V.; Marthol, H.; Tutaj, M.; Buechner, S.; Axelrod, F. B.; Hilz, M. J.

2007-01-01

To identify accurate predictors for the risk of sudden death in patients with familial dysautonomia (FD). Ten-minute resting high-fidelity 12-lead ECGs were obtained from 14 FD patients and 14 age/gender-matched healthy subjects. Multiple conventional and advanced ECG parameters were studied for their ability to predict sudden death in FD over a subsequent 4.5-year period, including multiple indices of linear and non-linear heart rate variability (HRV); QT variability; waveform complexity; high frequency QRS; and derived Frank-lead parameters. Four of the 14 FD patients died suddenly during the follow-up period, usually with concomitant pulmonary disorder. The presence of low vagally-mediated HRV was the ECG finding most predictive of sudden death. Concomitant left ventricular hypertrophy and other ECG abnormalities such as increased QTc and JTc intervals, spatial QRS-T angles, T-wave complexity, and QT variability were also present in FD patients, suggesting that structural heart disease is fairly common in FD. Although excessive or unopposed cardiac vagal (relative to sympathetic) activity has been postulated as a contributor to sudden death in FD, the presence of low vagally-mediated HRV was paradoxically the best predictor of sudden death. However, we suggest that low vagally-mediated HRV be construed not as a direct cause of sudden death in FD, but rather as an effect of concurrent pathological processes, especially hypoxia due to pulmonary disorders and sleep apnea, that themselves increase the risk of sudden death in FD and simultaneously diminish HRV. We speculate that adenosine may play a role in sudden death in FD, possibly independently of vagal activity, and that adenosine inhibitors such as theophylline might therefore be useful as prophylaxis in this disorder.

Predicting armed conflict: Time to adjust our expectations?

PubMed

Cederman, Lars-Erik; Weidmann, Nils B

2017-02-03

This Essay provides an introduction to the general challenges of predicting political violence, particularly compared with predicting other types of events (such as earthquakes). What is possible? What is less realistic? We aim to debunk myths about predicting violence, as well as to illustrate the substantial progress in this field. Copyright © 2017, American Association for the Advancement of Science.

Predictive microbiology: Quantitative science delivering quantifiable benefits to the meat industry and other food industries.

PubMed

McMeekin, T A

2007-09-01

Predictive microbiology is considered in the context of the conference theme "chance, innovation and challenge", together with the impact of quantitative approaches on food microbiology, generally. The contents of four prominent texts on predictive microbiology are analysed and the major contributions of two meat microbiologists, Drs. T.A. Roberts and C.O. Gill, to the early development of predictive microbiology are highlighted. These provide a segue into R&D trends in predictive microbiology, including the Refrigeration Index, an example of science-based, outcome-focussed food safety regulation. Rapid advances in technologies and systems for application of predictive models are indicated and measures to judge the impact of predictive microbiology are suggested in terms of research outputs and outcomes. The penultimate section considers the future of predictive microbiology and advances that will become possible when data on population responses are combined with data derived from physiological and molecular studies in a systems biology approach. Whilst the emphasis is on science and technology for food safety management, it is suggested that decreases in foodborne illness will also arise from minimising human error by changing the food safety culture.

Linking Complex Problem Solving and General Mental Ability to Career Advancement: Does a Transversal Skill Reveal Incremental Predictive Validity?

ERIC Educational Resources Information Center

Mainert, Jakob; Kretzschmar, André; Neubert, Jonas C.; Greiff, Samuel

2015-01-01

Transversal skills, such as complex problem solving (CPS) are viewed as central twenty-first-century skills. Recent empirical findings have already supported the importance of CPS for early academic advancement. We wanted to determine whether CPS could also contribute to the understanding of career advancement later in life. Towards this end, we…