early detection prediction: Topics by Science.gov

Sample records for early detection prediction

Robust regression and posterior predictive simulation increase power to detect early bursts of trait evolution.

PubMed

Slater, Graham J; Pennell, Matthew W

2014-05-01

A central prediction of much theory on adaptive radiations is that traits should evolve rapidly during the early stages of a clade's history and subsequently slowdown in rate as niches become saturated--a so-called "Early Burst." Although a common pattern in the fossil record, evidence for early bursts of trait evolution in phylogenetic comparative data has been equivocal at best. We show here that this may not necessarily be due to the absence of this pattern in nature. Rather, commonly used methods to infer its presence perform poorly when when the strength of the burst--the rate at which phenotypic evolution declines--is small, and when some morphological convergence is present within the clade. We present two modifications to existing comparative methods that allow greater power to detect early bursts in simulated datasets. First, we develop posterior predictive simulation approaches and show that they outperform maximum likelihood approaches at identifying early bursts at moderate strength. Second, we use a robust regression procedure that allows for the identification and down-weighting of convergent taxa, leading to moderate increases in method performance. We demonstrate the utility and power of these approach by investigating the evolution of body size in cetaceans. Model fitting using maximum likelihood is equivocal with regards the mode of cetacean body size evolution. However, posterior predictive simulation combined with a robust node height test return low support for Brownian motion or rate shift models, but not the early burst model. While the jury is still out on whether early bursts are actually common in nature, our approach will hopefully facilitate more robust testing of this hypothesis. We advocate the adoption of similar posterior predictive approaches to improve the fit and to assess the adequacy of macroevolutionary models in general.
Multiple Biomarker Panels for Early Detection of Breast Cancer in Peripheral Blood

PubMed Central

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers. PMID:24371830
Multiple biomarker panels for early detection of breast cancer in peripheral blood.

PubMed

Zhang, Fan; Deng, Youping; Drabier, Renee

2013-01-01

Detecting breast cancer at early stages can be challenging. Traditional mammography and tissue microarray that have been studied for early breast cancer detection and prediction have many drawbacks. Therefore, there is a need for more reliable diagnostic tools for early detection of breast cancer due to a number of factors and challenges. In the paper, we presented a five-marker panel approach based on SVM for early detection of breast cancer in peripheral blood and show how to use SVM to model the classification and prediction problem of early detection of breast cancer in peripheral blood. We found that the five-marker panel can improve the prediction performance (area under curve) in the testing data set from 0.5826 to 0.7879. Further pathway analysis showed that the top four five-marker panels are associated with signaling, steroid hormones, metabolism, immune system, and hemostasis, which are consistent with previous findings. Our prediction model can serve as a general model for multibiomarker panel discovery in early detection of other cancers.
Weather-based prediction of Plasmodium falciparum malaria in epidemic-prone regions of Ethiopia II. Weather-based prediction systems perform comparably to early detection systems in identifying times for interventions.

PubMed

Teklehaimanot, Hailay D; Schwartz, Joel; Teklehaimanot, Awash; Lipsitch, Marc

2004-11-19

Timely and accurate information about the onset of malaria epidemics is essential for effective control activities in epidemic-prone regions. Early warning methods that provide earlier alerts (usually by the use of weather variables) may permit control measures to interrupt transmission earlier in the epidemic, perhaps at the expense of some level of accuracy. Expected case numbers were modeled using a Poisson regression with lagged weather factors in a 4th-degree polynomial distributed lag model. For each week, the numbers of malaria cases were predicted using coefficients obtained using all years except that for which the prediction was being made. The effectiveness of alerts generated by the prediction system was compared against that of alerts based on observed cases. The usefulness of the prediction system was evaluated in cold and hot districts. The system predicts the overall pattern of cases well, yet underestimates the height of the largest peaks. Relative to alerts triggered by observed cases, the alerts triggered by the predicted number of cases performed slightly worse, within 5% of the detection system. The prediction-based alerts were able to prevent 10-25% more cases at a given sensitivity in cold districts than in hot ones. The prediction of malaria cases using lagged weather performed well in identifying periods of increased malaria cases. Weather-derived predictions identified epidemics with reasonable accuracy and better timeliness than early detection systems; therefore, the prediction of malarial epidemics using weather is a plausible alternative to early detection systems.
Functionality of empirical model-based predictive analytics for the early detection of hemodynamic instabilty.

PubMed

Summers, Richard L; Pipke, Matt; Wegerich, Stephan; Conkright, Gary; Isom, Kristen C

2014-01-01

Background. Monitoring cardiovascular hemodynamics in the modern clinical setting is a major challenge. Increasing amounts of physiologic data must be analyzed and interpreted in the context of the individual patients pathology and inherent biologic variability. Certain data-driven analytical methods are currently being explored for smart monitoring of data streams from patients as a first tier automated detection system for clinical deterioration. As a prelude to human clinical trials, an empirical multivariate machine learning method called Similarity-Based Modeling (SBM), was tested in an In Silico experiment using data generated with the aid of a detailed computer simulator of human physiology (Quantitative Circulatory Physiology or QCP) which contains complex control systems with realistic integrated feedback loops. Methods. SBM is a kernel-based, multivariate machine learning method that that uses monitored clinical information to generate an empirical model of a patients physiologic state. This platform allows for the use of predictive analytic techniques to identify early changes in a patients condition that are indicative of a state of deterioration or instability. The integrity of the technique was tested through an In Silico experiment using QCP in which the output of computer simulations of a slowly evolving cardiac tamponade resulted in progressive state of cardiovascular decompensation. Simulator outputs for the variables under consideration were generated at a 2-min data rate (0.083Hz) with the tamponade introduced at a point 420 minutes into the simulation sequence. The functionality of the SBM predictive analytics methodology to identify clinical deterioration was compared to the thresholds used by conventional monitoring methods. Results. The SBM modeling method was found to closely track the normal physiologic variation as simulated by QCP. With the slow development of the tamponade, the SBM model are seen to disagree while the
Using the Autism Detection in Early Childhood (ADEC) and Childhood Autism Rating Scales (CARS) to Predict Long Term Outcomes in Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Nah, Yong-Hwee; Young, Robyn L.; Brewer, Neil

2014-01-01

This study evaluated the predictive validity of the Autism Detection in Early Childhood (ADEC; Young, Autism detection in early childhood: ADEC. Australian Council of Educational Research, Camberwell, VIC 2007) and a well-established screening tool, the Childhood Autism Rating Scale (CARS; Schopler et al. The childhood autism rating scale (CARS).…
Signature-forecasting and early outbreak detection system

PubMed Central

Naumova, Elena N.; MacNeill, Ian B.

2008-01-01

SUMMARY Daily disease monitoring via a public health surveillance system provides valuable information on population risks. Efficient statistical tools for early detection of rapid changes in the disease incidence are a must for modern surveillance. The need for statistical tools for early detection of outbreaks that are not based on historical information is apparent. A system is discussed for monitoring cases of infections with a view to early detection of outbreaks and to forecasting the extent of detected outbreaks. We propose a set of adaptive algorithms for early outbreak detection that does not rely on extensive historical recording. We also include knowledge of infection disease epidemiology into forecasts. To demonstrate this system we use data from the largest water-borne outbreak of cryptosporidiosis, which occurred in Milwaukee in 1993. Historical data are smoothed using a loess-type smoother. Upon receipt of a new datum, the smoothing is updated and estimates are made of the first two derivatives of the smooth curve, and these are used for near-term forecasting. Recent data and the near-term forecasts are used to compute a color-coded warning index, which quantify the level of concern. The algorithms for computing the warning index have been designed to balance Type I errors (false prediction of an epidemic) and Type II errors (failure to correctly predict an epidemic). If the warning index signals a sufficiently high probability of an epidemic, then a forecast of the possible size of the outbreak is made. This longer term forecast is made by fitting a ‘signature’ curve to the available data. The effectiveness of the forecast depends upon the extent to which the signature curve captures the shape of outbreaks of the infection under consideration. PMID:18716671
Detecting failure of climate predictions

USGS Publications Warehouse

Runge, Michael C.; Stroeve, Julienne C.; Barrett, Andrew P.; McDonald-Madden, Eve

2016-01-01

The practical consequences of climate change challenge society to formulate responses that are more suited to achieving long-term objectives, even if those responses have to be made in the face of uncertainty1, 2. Such a decision-analytic focus uses the products of climate science as probabilistic predictions about the effects of management policies3. Here we present methods to detect when climate predictions are failing to capture the system dynamics. For a single model, we measure goodness of fit based on the empirical distribution function, and define failure when the distribution of observed values significantly diverges from the modelled distribution. For a set of models, the same statistic can be used to provide relative weights for the individual models, and we define failure when there is no linear weighting of the ensemble models that produces a satisfactory match to the observations. Early detection of failure of a set of predictions is important for improving model predictions and the decisions based on them. We show that these methods would have detected a range shift in northern pintail 20 years before it was actually discovered, and are increasingly giving more weight to those climate models that forecast a September ice-free Arctic by 2055.
Dynamic linear models using the Kalman filter for early detection and early warning of malaria outbreaks

NASA Astrophysics Data System (ADS)

Merkord, C. L.; Liu, Y.; DeVos, M.; Wimberly, M. C.

2015-12-01

Malaria early detection and early warning systems are important tools for public health decision makers in regions where malaria transmission is seasonal and varies from year to year with fluctuations in rainfall and temperature. Here we present a new data-driven dynamic linear model based on the Kalman filter with time-varying coefficients that are used to identify malaria outbreaks as they occur (early detection) and predict the location and timing of future outbreaks (early warning). We fit linear models of malaria incidence with trend and Fourier form seasonal components using three years of weekly malaria case data from 30 districts in the Amhara Region of Ethiopia. We identified past outbreaks by comparing the modeled prediction envelopes with observed case data. Preliminary results demonstrated the potential for improved accuracy and timeliness over commonly-used methods in which thresholds are based on simpler summary statistics of historical data. Other benefits of the dynamic linear modeling approach include robustness to missing data and the ability to fit models with relatively few years of training data. To predict future outbreaks, we started with the early detection model for each district and added a regression component based on satellite-derived environmental predictor variables including precipitation data from the Tropical Rainfall Measuring Mission (TRMM) and land surface temperature (LST) and spectral indices from the Moderate Resolution Imaging Spectroradiometer (MODIS). We included lagged environmental predictors in the regression component of the model, with lags chosen based on cross-correlation of the one-step-ahead forecast errors from the first model. Our results suggest that predictions of future malaria outbreaks can be improved by incorporating lagged environmental predictors.
Recursive SVM biomarker selection for early detection of breast cancer in peripheral blood.

PubMed

Zhang, Fan; Kaufman, Howard L; Deng, Youping; Drabier, Renee

2013-01-01

Breast cancer is worldwide the second most common type of cancer after lung cancer. Traditional mammography and Tissue Microarray has been studied for early cancer detection and cancer prediction. However, there is a need for more reliable diagnostic tools for early detection of breast cancer. This can be a challenge due to a number of factors and logistics. First, obtaining tissue biopsies can be difficult. Second, mammography may not detect small tumors, and is often unsatisfactory for younger women who typically have dense breast tissue. Lastly, breast cancer is not a single homogeneous disease but consists of multiple disease states, each arising from a distinct molecular mechanism and having a distinct clinical progression path which makes the disease difficult to detect and predict in early stages. In the paper, we present a Support Vector Machine based on Recursive Feature Elimination and Cross Validation (SVM-RFE-CV) algorithm for early detection of breast cancer in peripheral blood and show how to use SVM-RFE-CV to model the classification and prediction problem of early detection of breast cancer in peripheral blood.The training set which consists of 32 health and 33 cancer samples and the testing set consisting of 31 health and 34 cancer samples were randomly separated from a dataset of peripheral blood of breast cancer that is downloaded from Gene Express Omnibus. First, we identified the 42 differentially expressed biomarkers between "normal" and "cancer". Then, with the SVM-RFE-CV we extracted 15 biomarkers that yield zero cross validation score. Lastly, we compared the classification and prediction performance of SVM-RFE-CV with that of SVM and SVM Recursive Feature Elimination (SVM-RFE). We found that 1) the SVM-RFE-CV is suitable for analyzing noisy high-throughput microarray data, 2) it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features, and 3) it can improve the prediction performance (Area Under
Predictive algorithms for early detection of retinopathy of prematurity.

PubMed

Piermarocchi, Stefano; Bini, Silvia; Martini, Ferdinando; Berton, Marianna; Lavini, Anna; Gusson, Elena; Marchini, Giorgio; Padovani, Ezio Maria; Macor, Sara; Pignatto, Silvia; Lanzetta, Paolo; Cattarossi, Luigi; Baraldi, Eugenio; Lago, Paola

2017-03-01

To evaluate sensitivity, specificity and the safest cut-offs of three predictive algorithms (WINROP, ROPScore and CHOP ROP) for retinopathy of prematurity (ROP). A retrospective study was conducted in three centres from 2012 to 2014; 445 preterms with gestational age (GA) ≤ 30 weeks and/or birthweight (BW) ≤ 1500 g, and additional unstable cases, were included. No-ROP, mild and type 1 ROP were categorized. The algorithms were analysed for infants with all parameters (GA, BW, weight gain, oxygen therapy, blood transfusion) needed for calculation (399 babies). Retinopathy of prematurity (ROP) was identified in both eyes in 116 patients (26.1%), and 44 (9.9%) had type 1 ROP. Gestational age and BW were significantly lower in ROP group compared with no-ROP subjects (GA: 26.7 ± 2.2 and 30.2 ± 1.9, respectively, p < 0.0001; BW: 839.8 ± 287.0 and 1288.1 ± 321.5 g, respectively, p = 0.0016). Customized alarms of ROPScore and CHOP ROP correctly identified all infants having any ROP or type 1 ROP. WINROP missed 19 cases of ROP, including three type 1 ROP. ROPScore and CHOP ROP provided the best performances with an area under the receiver operating characteristic curve for the detection of severe ROP of 0.93 (95% CI, 0.90-0.96, and 95% CI, 0.89-0.96, respectively), and WINROP obtained 0.83 (95% CI, 0.77-0.87). Median time from alarm to treatment was 11.1, 5.1 and 9.1 weeks, for WINROP, ROPScore and CHOP ROP, respectively. ROPScore and CHOP ROP showed 100% sensitivity to identify sight-threatening ROP. Predictive algorithms are a reliable tool for early identification of infants requiring referral to an ophthalmologist, for reorganizing resources and reducing stressful procedures to preterm babies. © 2016 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.
Health responsibility and workplace health promotion among women: early detection of cancer.

PubMed

Kushnir, T; Rabinowitz, S; Melamed, S; Weisberg, E; Ribak, J

1995-01-01

The importance of health responsibility as one aspect of a health-promoting lifestyle has been emphasized repeatedly. Yet there are only a few empirical studies of its role in preventive behavior. We examined the relationship between health responsibility and early-detection practices for breast and cervical cancer. A group of 253 women employees of a large industrial company participated in a cancer screening program subsidized by the employer. They completed questionnaires assessing health responsibility and reported early-detection practices: frequency of breast self-examination and physician breast examinations, frequency of Pap tests, and time lapsed since last Pap test and breast examinations. Health responsibility was a significant independent predictor of breast examination indicators but not of Pap tests. Education level was an important predictor for Pap tests, and age predicted most early-detection practices. The findings lend some support to the role of health responsibility in initiating breast examinations. Better prediction of early-detection practices could be achieved by adding cognitive and emotional components to the existing responsibility scale and by distinguishing between retrospective and prospective responsibility.
Can we predict failure in couple therapy early enough to enhance outcome?

PubMed

Pepping, Christopher A; Halford, W Kim; Doss, Brian D

2015-02-01

Feedback to therapists based on systematic monitoring of individual therapy progress reliably enhances therapy outcome. An implicit assumption of therapy progress feedback is that clients unlikely to benefit from therapy can be detected early enough in the course of therapy for corrective action to be taken. To explore the possibility of using feedback of therapy progress to enhance couple therapy outcome, the current study tested whether weekly therapy progress could detect off-track clients early in couple therapy. In an effectiveness trial of couple therapy, 136 couples were monitored weekly on relationship satisfaction and an expert derived algorithm was used to attempt to predict eventual therapy outcome. As expected, the algorithm detected a significant proportion of couples who did not benefit from couple therapy at Session 3, but prediction was substantially improved at Session 4 so that eventual outcome was accurately predicted for 70% of couples, with little improvement of prediction thereafter. More sophisticated algorithms might enhance prediction accuracy, and a trial of the effects of therapy progress feedback on couple therapy outcome is needed. Copyright © 2015 Elsevier Ltd. All rights reserved.
Early detection of Alzheimer disease: methods, markers, and misgivings.

PubMed

Green, R C; Clarke, V C; Thompson, N J; Woodard, J L; Letz, R

1997-01-01

There is at present no reliable predictive test for most forms of Alzheimer disease (AD). Although some information about future risk for disease is available in theory through ApoE genotyping, it is of limited accuracy and utility. Once neuroprotective treatments are available for AD, reliable early detection will become a key component of the treatment strategy. We recently conducted a pilot survey eliciting attitudes and beliefs toward an unspecified and hypothetical predictive test for AD. The survey was completed by a convenience sample of 176 individuals, aged 22-77, which was 75% female, 30% African-American, and of which 33% had a family member with AD. The survey revealed that 69% of this sample would elect to obtain predictive testing for AD if the test were 100% accurate. Individuals were more likely to desire predictive testing if they had an a priori belief that they would develop AD (p = 0.0001), had a lower educational level (p = 0.003), were worried that they would develop AD (p = 0.02), had a self-defined history of depression (p = 0.04), and had a family member with AD (p = 0.04). However, the desire for predictive testing was not significantly associated with age, gender, ethnicity, or income. The desire to obtain predictive testing for AD decreased as the assumed accuracy of the hypothetical test decreased. A better short-term strategy for early detection of AD may be computer-based neuropsychological screening of at-risk (older aged) individuals to identify very early cognitive impairment. Individuals identified in this manner could be referred for diagnostic evaluation and early cases of AD could be identified and treated. A new self-administered, touch-screen, computer-based, neuropsychological screening instrument called Neurobehavioral Evaluation System-3 is described, which may facilitate this type of screening.
Psychosis prediction and clinical utility in familial high-risk studies: Selective review, synthesis, and implications for early detection and intervention

PubMed Central

Shah, Jai L.; Tandon, Neeraj; Keshavan, Matcheri S.

2016-01-01

Aim Accurate prediction of which individuals will go on to develop psychosis would assist early intervention and prevention paradigms. We sought to review investigations of prospective psychosis prediction based on markers and variables examined in longitudinal familial high-risk (FHR) studies. Methods We performed literature searches in MedLine, PubMed and PsycINFO for articles assessing performance characteristics of predictive clinical tests in FHR studies of psychosis. Studies were included if they reported one or more predictive variables in subjects at FHR for psychosis. We complemented this search strategy with references drawn from articles, reviews, book chapters and monographs. Results Across generations of familial high-risk projects, predictive studies have investigated behavioral, cognitive, psychometric, clinical, neuroimaging, and other markers. Recent analyses have incorporated multivariate and multi-domain approaches to risk ascertainment, although with still generally modest results. Conclusions While a broad range of risk factors has been identified, no individual marker or combination of markers can at this time enable accurate prospective prediction of emerging psychosis for individuals at FHR. We outline the complex and multi-level nature of psychotic illness, the myriad of factors influencing its development, and methodological hurdles to accurate and reliable prediction. Prospects and challenges for future generations of FHR studies are discussed in the context of early detection and intervention strategies. PMID:23693118
Liquid biopsy for early detection of lung cancer.

PubMed

Hofman, Paul

2017-01-01

The possibility of complete recovery for a lung cancer patient depends on very early diagnosis, as it allows total surgical resection. Screening for this cancer in a high-risk population can be performed using a radiological approach, but this holds a certain number of limitations. Liquid biopsy could become an alternative and complementary screening approach to chest imaging for early diagnosis of lung cancer. Several circulating biomarkers indicative of lung cancer can be investigated in blood, such as circulating tumor cells, circulating free nucleic acids (RNA and DNA) and proteins. However, none of these biomarkers have yet been adopted in routine clinical practice and studies are ongoing to confirm or not the usefulness and practical interest in routine early diagnosis and screening for lung cancers. Several potential circulating biomarkers for the early detection of lung cancer exist. When coupled to thoracic imaging, these biomarkers must give diagnosis of a totally resectable lung cancer and potentially provide new recommendations for surveillance by imagery of high-risk populations without a detectable nodule. Optimization of the specificity and sensitivity of the detection methods as well as standardization of the techniques is essential before considering for daily practice a liquid biopsy as an early diagnostic tool, or possibly as a predictive test, of lung cancer.
Early Detection of Progressive Adolescent Idiopathic Scoliosis: A Severity Index.

PubMed

Skalli, Wafa; Vergari, Claudio; Ebermeyer, Eric; Courtois, Isabelle; Drevelle, Xavier; Kohler, Remi; Abelin-Genevois, Kariman; Dubousset, Jean

2017-06-01

Early detection of progressive adolescent idiopathic scoliosis (AIS) was assessed based on 3D quantification of the deformity. Based on 3D quantitative description of scoliosis curves, the aim is to assess a specific phenotype that could be an early detectable severity index for progressive AIS. Early detection of progressive scoliosis is important for adapted treatment to limit progression. However, progression risk assessment is mainly based on the follow up, waiting for signs of rapid progression that generally occur during the growth peak. Sixty-five mild scoliosis (16 boys, 49 girls, Cobb Angle between 10 and 20°) with a Risser between 0 and 2 were followed from their first examination until a decision was made by the clinician, either considering the spine as stable at the end of growth (26 patients) or planning to brace because of progression (39 patients). Calibrated biplanar x-rays were performed and 3D reconstructions of the spine allowed calculating six local parameters related to main curve deformity. For progressive curve 3D phenotype assessment, data were compared with those previously assessed for 30 severe scoliosis (Cobb Angle > 35°), 17 scoliosis before brace (Cobb Angle > 29°) and 53 spines of nonscoliosis subjects. A predictive discriminant analysis was performed to assess similarity of mild scoliosis curves either to those of scoliosis or nonscoliosis spines, yielding a severity index (S-index). S-index value at first examination was compared with clinical outcome. At the first exam, 53 out of 65 predictions (82%) were in agreement with actual clinical outcome. Approximately, 89% of the curves that were predicted as progressive proved accurate. Although still requiring large scale validation, results are promising for early detection of progressive curves. 2.
Postnatal BMI changes in children with different birthweights: A trial study for detecting early predictive factors for pediatric obesity

PubMed Central

Nakagawa, Yuichi; Nakanishi, Toshiki; Satake, Eiichiro; Matsushita, Rie; Saegusa, Hirokazu; Kubota, Akira; Natsume, Hiromune; Shibata, Yukinobu; Fujisawa, Yasuko

2018-01-01

Abstract. The purpose of this study was to clarify the degree of early postnatal growth by birthweight and detect early predictive factors for pediatric obesity. Body mass index (BMI) and degree of obesity were examined in children in the fourth year of elementary school and second year of junior high school. Their BMI at birth and three years of age were also examined. Based on birthweight, participants were divided into three groups: low (< 2500 g), middle (2500–3500 g), and high (> 3500 g). Furthermore, according to the degree of obesity, they were divided into two groups: obese (20% ≤) and non-obese (20% >). The change of BMI from birth to three years of age (ΔBMI) showed a strong inverse relationship with birthweight and was significantly different among the three birthweight groups (low > middle > high). The ΔBMI and BMI at three years of age were higher in obese than in non-obese children and showed significant positive correlations with the degree of obesity. Early postnatal growth might be determined by birthweight and was higher in obese than in non-obese children. The ΔBMI from birth to three years of age and BMI at age of three years could be predictive factors for pediatric obesity. PMID:29403153
Identification of a Genomic Signature Predicting for Recurrence in Early Stage Ovarian Cancer

DTIC Science & Technology

2015-12-01

early stage ovarian cancer to help researchers worldwide identify biomarkers that can aid early detection and inform novel targets for therapy. This...to detect differentially expressed genes after transformation using Voom. When using the top 5 genes to build the classifier, it predicted...to analyze expression of micro-RNA in these samples. Thus, at the end of the third year of funding we started a parallel analysis of RNAseq, DNA- CNV
Abusive alcohol consumption among adolescents: a predictive model for maximizing early detection and responses.

PubMed

de Freitas Ferreira, M; de Moraes, C L; Braga, J U; Reichenheim, M E; da Veiga, G V

2018-06-01

To present a predictive model of alcohol abuse among adolescents based on prevalence projections in various population subgroups. Cross-sectional study. The sample consisted of 785 adolescents enrolled in the second year of high school in Rio de Janeiro, Brazil. Alcohol consumption was assessed using the Alcohol Use Disorder Identification Test. Socio-economic, demographic, family, individuals, and school-related variables were examined as potential predictors. The logit model was used to estimate the prevalence projections. Model fitting was examined in relation to the observed data set, and in a subset, that was generated from 200 subsamples of individuals via a bootstrap process using general fit estimators, discrimination, and calibration measures. About 25.5% of the adolescents were classified as positive for alcohol abuse. Being male, being 17-19 years old, not living with mothers, presenting symptoms suggestive of binge eating, having used a strategy of weight reduction in the last 3 months, and, especially, being a victim of family violence were important predictors of abusive consumption of alcohol. While the model's prevalence projection in the absence of these features was 8%, it reaches 68% in the presence of all predictors. Knowledge of predictive characteristics of alcohol abuse is essential for screening, early detection of positive cases, and establishing interventions to reduce consumption among adolescents. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Early Detection of Sporadic Pancreatic Cancer

PubMed Central

Chari, Suresh T.; Kelly, Kimberly; Hollingsworth, Michael A.; Thayer, Sarah P.; Ahlquist, David A.; Andersen, Dana K.; Batra, Surinder K.; Brentnall, Teresa A.; Canto, Marcia; Cleeter, Deborah F.; Firpo, Matthew A.; Gambhir, Sanjiv Sam; Go, Vay Liang W.; Hines, O. Joe; Kenner, Barbara J.; Klimstra, David S.; Lerch, Markus M.; Levy, Michael J.; Maitra, Anirban; Mulvihill, Sean J.; Petersen, Gloria M.; Rhim, Andrew D.; Simeone, Diane M.; Srivastava, Sudhir; Tanaka, Masao; Vinik, Aaron I.; Wong, David

2015-01-01

Abstract Pancreatic cancer (PC) is estimated to become the second leading cause of cancer death in the United States by 2020. Early detection is the key to improving survival in PC. Addressing this urgent need, the Kenner Family Research Fund conducted the inaugural Early Detection of Sporadic Pancreatic Cancer Summit Conference in 2014 in conjunction with the 45th Anniversary Meeting of the American Pancreatic Association and Japan Pancreas Society. This seminal convening of international representatives from science, practice, and clinical research was designed to facilitate challenging interdisciplinary conversations to generate innovative ideas leading to the creation of a defined collaborative strategic pathway for the future of the field. An in-depth summary of current efforts in the field, analysis of gaps in specific areas of expertise, and challenges that exist in early detection is presented within distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. In addition, an overview of efforts in familial PC is presented in an addendum to this article. It is clear from the summit deliberations that only strategically designed collaboration among investigators, institutions, and funders will lead to significant progress in early detection of sporadic PC. PMID:25931254
Early Detection Monitoring for Invasive Fish: St. Louis River (SLR) Pilot Study

EPA Science Inventory

Early detection of aquatic invasive species is necessary to develop and implement timely management responses. Predicting species introductions, however, is difficult and resources are typically limited. Therefore, monitoring strategies should be designed to effectively and eff...
Assessing the Clinical Role of Genetic Markers of Early-Onset Prostate Cancer Among High-Risk Men Enrolled in Prostate Cancer Early Detection

PubMed Central

Hughes, Lucinda; Zhu, Fang; Ross, Eric; Gross, Laura; Uzzo, Robert G.; Chen, David Y. T.; Viterbo, Rosalia; Rebbeck, Timothy R.; Giri, Veda N.

2011-01-01

Background Men with familial prostate cancer (PCA) and African American men are at risk for developing PCA at younger ages. Genetic markers predicting early-onset PCA may provide clinically useful information to guide screening strategies for high-risk men. We evaluated clinical information from six polymorphisms associated with early-onset PCA in a longitudinal cohort of high-risk men enrolled in PCA early detection with significant African American participation. Methods Eligibility criteria include ages 35–69 with a family history of PCA or African American race. Participants undergo screening and biopsy per study criteria. Six markers associated with early-onset PCA (rs2171492 (7q32), rs6983561 (8q24), rs10993994 (10q11), rs4430796 (17q12), rs1799950 (17q21), and rs266849 (19q13)) were genotyped. Cox models were used to evaluate time to PCA diagnosis and PSA prediction for PCA by genotype. Harrell’s concordance index was used to evaluate predictive accuracy for PCA by PSA and genetic markers. Results 460 participants with complete data and ≥1 follow-up visit were included. 56% were African American. Among African American men, rs6983561 genotype was significantly associated with earlier time to PCA diagnosis (p=0.005) and influenced prediction for PCA by the PSA (p<0.001). When combined with PSA, rs6983561 improved predictive accuracy for PCA compared to PSA alone among African American men (PSA= 0.57 vs. PSA+rs6983561=0.75, p=0.03). Conclusions Early-onset marker rs6983561 adds potentially useful clinical information for African American men undergoing PCA risk assessment. Further study is warranted to validate these findings. Impact Genetic markers of early-onset PCA have potential to refine and personalize PCA early detection for high-risk men. PMID:22144497
Phospholamban, a predicted candidate for early cardiac problem detection using signal processing techniques.

PubMed

Hejase de Trad, C

2005-01-01

Heart failure has been identified as a serious international problem, in particular for aging groups, posing both an increasing number of patients on waiting lists in countries susceptible with Medicare systems and increasing financial burdens. It may be imperative to develop a marker that can identify such problems at an early stage. It is believed that certain proteins have crucial roles in early detection of cardiovascular disease, the number one killer in United Arab Emirates. This might be accomplished by recognition of unusual features in protein candidates. Phospholamban (PLB) is a 52 amino acid phosphoprotein which regulates the calcium pump of cardiac sarcoplasmic reticulum (SR). During muscle contraction, PLB inhibits the Ca⁺⁺ pump. During muscle relaxation, it can be phosphorylated, removing the inhibition and allowing Ca⁺⁺ to be pumped back into SR. With the calcium pump disrupted, the heart muscle is probably weakened, resulting in congestive heart failure. Interleukin 6 (IL-6) is considered as a better predictor of heart attack in elderly people. It could serve as an early warning sign since its level increases early in the inflammatory process. Also, it has been established that myocyte enhancer factor 2A (MEF2A) plays a vital role in the development of cardiovascular problems like atherosclerosis and restenosis after angioplasty inflammation. In this paper, the resonance recognition method (RRM) has been employed to determine the characteristic frequencies of the above-mentioned proteins. It has been found that phospholamban and IL-6 share the same characteristic frequency, 0.3320 plusmn 0.0002 suggesting their common probable contribution to heart failure. Myocyte enhancer factor 2A does not share the same characteristic frequency. Hence, phospholamban is suggested as a highly probable early marker for cardiac problem detection.
Early detection and rapid response

USGS Publications Warehouse

Westbrooks, Randy G.; Eplee, Robert E.; Simberloff, Daniel; Rejmánek, Marcel

2011-01-01

Prevention is the first line of defense against introduced invasive species - it is always preferable to prevent the introduction of new invaders into a region or country. However, it is not always possible to detect all alien hitchhikers imported in cargo, or to predict with any degree of certainty which introduced species will become invasive over time. Fortunately, the majority of introduced plants and animals don't become invasive. But, according to scientists at Cornell University, costs and losses due to species that do become invasive are now estimated to be over $137 billion/year in the United States. Early detection and rapid response (EDRR) is the second line of defense against introduced invasive species - EDRR is the preferred management strategy for preventing the establishment and spread of invasive species. Over the past 50 years, there has been a gradual shift away from large and medium scale federal/state single-agency-led weed eradication programs in the United States, to smaller interagency-led projects involving impacted and potential stakeholders. The importance of volunteer weed spotters in detecting and reporting suspected new invasive species has also been recognized in recent years.
New technology for early detection of health threats

NASA Astrophysics Data System (ADS)

Southern, Šárka O.; Lilienthal, Gerald W.

2008-04-01

Governmental agencies charged with protecting the health of the population and agriculture have several main strategic objectives including the detection of harmful agents, the identification of vulnerable biological targets, the prediction of health outcomes and the development of countermeasures. New technologies are urgently needed in several critical areas of bio-chemical defense: economical and minimally invasive biosensors for field use in humans and other species important for agriculture and infrastructure, universal analytical platforms for broad-based, early warnings of threats and technologies guiding the development of countermeasures. A new technology called Stress Response Profiling (SRP) was recently developed by the Gaia Medical Institute. SRP provides a universal analytical platform for monitoring health status based on measurements of physiological stress. The platform is implemented through handheld devices that can be used for noninvasive detection of early-stage health problems. This paper summarizes SRP features, advantages and potential benefits for critical areas of homeland defense.
A Novel Way to Measure and Predict Development: A Heuristic Approach to Facilitate the Early Detection of Neurodevelopmental Disorders.

PubMed

Marschik, Peter B; Pokorny, Florian B; Peharz, Robert; Zhang, Dajie; O'Muircheartaigh, Jonathan; Roeyers, Herbert; Bölte, Sven; Spittle, Alicia J; Urlesberger, Berndt; Schuller, Björn; Poustka, Luise; Ozonoff, Sally; Pernkopf, Franz; Pock, Thomas; Tammimies, Kristiina; Enzinger, Christian; Krieber, Magdalena; Tomantschger, Iris; Bartl-Pokorny, Katrin D; Sigafoos, Jeff; Roche, Laura; Esposito, Gianluca; Gugatschka, Markus; Nielsen-Saines, Karin; Einspieler, Christa; Kaufmann, Walter E

2017-05-01

Substantial research exists focusing on the various aspects and domains of early human development. However, there is a clear blind spot in early postnatal development when dealing with neurodevelopmental disorders, especially those that manifest themselves clinically only in late infancy or even in childhood. This early developmental period may represent an important timeframe to study these disorders but has historically received far less research attention. We believe that only a comprehensive interdisciplinary approach will enable us to detect and delineate specific parameters for specific neurodevelopmental disorders at a very early age to improve early detection/diagnosis, enable prospective studies and eventually facilitate randomised trials of early intervention. In this article, we propose a dynamic framework for characterising neurofunctional biomarkers associated with specific disorders in the development of infants and children. We have named this automated detection 'Fingerprint Model', suggesting one possible approach to accurately and early identify neurodevelopmental disorders.
Early Detection | Division of Cancer Prevention

Cancer.gov

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A combination of circulating miRNAs for the early detection of ovarian cancer

PubMed Central

Yokoi, Akira; Yoshioka, Yusuke; Hirakawa, Akihiro; Yamamoto, Yusuke; Ishikawa, Mitsuya; Ikeda, Shun-ichi; Kato, Tomoyasu; Niimi, Kaoru; Kajiyama, Hiroaki; Kikkawa, Fumitaka; Ochiya, Takahiro

2017-01-01

Ovarian cancer is the leading cause of gynecologic cancer mortality, due to the difficulty of early detection. Current screening methods lack sufficient accuracy, and it is still challenging to propose a new early detection method that improves patient outcomes with less-invasiveness. Although many studies have suggested the utility of circulating microRNAs in cancer detection, their potential for early detection remains elusive. Here, we develop novel predictive models using a combination of 8 circulating serum miRNAs. This method was able to successfully distinguish ovarian cancer patients from healthy controls (area under the curve, 0.97; sensitivity, 0.92; and specificity, 0.91) and early-stage ovarian cancer from patients with benign tumors (0.91, 0.86 and 0.83, respectively). This method also enables subtype classification in 4 types of epithelial ovarian cancer. Furthermore, it is found that most of the 8 miRNAs were packaged in extracellular vesicles, including exosomes, derived from ovarian cancer cells, and they were circulating in murine blood stream. The circulating miRNAs described in this study may serve as biomarkers for ovarian cancer patients. Early detection and subtype determination prior to surgery are crucial for clinicians to design an effective treatment strategy for each patient, as is the goal of precision medicine. PMID:29163790
[Diagnostic performance of surface electrocardiogram in early detection of chagasic cardiomyopathy].

PubMed

Bochard-Villanueva, Bruno; Estornell-Erill, Jordi; Fabregat-Andrés, Óscar; García-González, Pilar; Morell-Cabedo, Salvador; Ridocci-Soriano, Francisco

2015-03-15

Contrast-enhanced cardiac magnetic resonance imaging (CMR) allows early detection of myocardial involvement by Trypanosoma cruzi infection. The aim of our study was to assess the diagnostic performance of the surface electrocardiogram (ECG) in the early detection of Chagas' cardiomyopathy (CCM) compared with CMR. We included 43 asymptomatic patients (30 women, 42 ± 9.8 years), diagnosed of Chagas disease. The sample was divided into 2 groups according to the presence (n=17) or absence (n=26) of electrocardiographic abnormalities. All patients underwent CMR and late gadolinium enhancement (LGE) was used as a marker of early myocardial involvement. Six (14%) patients had a LGE significantly higher in the group who had electrocardiographic abnormalities (29 vs. 4%, P<.05). With CMR as the method of reference, the ECG had a sensitivity of 83% and a negative predictive value of 96% to detect CCM. ECG is a useful, inexpensive and globally available tool for the screening of CCM in asymptomatic patients but with proven myocardial involvement in CMR. Copyright © 2013 Elsevier España, S.L.U. All rights reserved.
Early Detection of Sporadic Pancreatic Cancer

PubMed Central

Kenner, Barbara J.; Chari, Suresh T.; Cleeter, Deborah F.; Go, Vay Liang W.

2015-01-01

Abstract Innovation leading to significant advances in research and subsequent translation to clinical practice is urgently necessary in early detection of sporadic pancreatic cancer. Addressing this need, the Early Detection of Sporadic Pancreatic Cancer Summit Conference was conducted by Kenner Family Research Fund in conjunction with the 2014 American Pancreatic Association and Japan Pancreas Society Meeting. International interdisciplinary scientific representatives engaged in strategic facilitated conversations based on distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. Ideas generated from the summit have led to the development of a Strategic Map for Innovation built upon 3 components: formation of an international collaborative effort, design of an actionable strategic plan, and implementation of operational standards, research priorities, and first-phase initiatives. Through invested and committed efforts of leading researchers and institutions, philanthropic partners, government agencies, and supportive business entities, this endeavor will change the future of the field and consequently the survival rate of those diagnosed with pancreatic cancer. PMID:25938853
Sentinel lymph node detection in patients with early cervical cancer.

PubMed

Acharya, B C; Jihong, L

2009-01-01

Lymph node status is the most important independent prognostic factor in early stage cervical cancer. Intraoperative lymphatic mapping and sentinel lymph node detection have been increasingly evaluated in the treatment of a variety of solid tumors, particularly breast cancer and cutaneous melanoma. This study evaluated the feasibility of these procedures in patients undergoing radical hysterectomy with pelvic lymphadenectomy for early cervical cancer. A total of 30 patients with histologically diagnosed FIGO stage IA to IIA cervical cancer were enrolled to this study. They were scheduled to undergo radical abdominal hysterectomy and pelvic lymphadenectomy after injecting patent blue dye in cervix. A total of 60 SLNs (mean 2.5) were detected in 24 patients with detection rate of 80%. Bilateral SLNs were detected in 70.1% of cases. SLNs were identified in obturator and external iliac areas in 50% and 31.7%, respectively; no SLNs were discovered in the common iliac region. Seven patients (23.3%) had lymph node metastases; one of these had false negative SLN.The false negative rate and negative predictive value were 14.3% and 94.4%, respectively. SLN detection procedure with blue dye technique is a feasible procedure in cervical cancer. Patent blue dye is cheap, safe and effective tracer to detect sentinel node in carcinoma of cervix.
Life expectancy and the value of early detection.

PubMed

Howard, David H

2005-09-01

This paper presents a model of the benefits and costs of early detection of asymptomatic disease as they vary by age. The benefits of early detection tend toward zero as the risk of death from competing causes increases. Costs per detected case also decline with age, assuming that disease incidence rises with age, but are always strictly positive. On balance, there is always an age limit beyond which the costs associated with early detection outweigh the benefits. Application of the model to prostate cancer screening suggests that early detection above age 70 or so is not cost-effective.
Early detection: the impact of genomics.

PubMed

van Lanschot, M C J; Bosch, L J W; de Wit, M; Carvalho, B; Meijer, G A

2017-08-01

The field of genomics has shifted our view on disease development by providing insights in the molecular and functional processes encoded in the genome. In the case of cancer, many alterations in the DNA accumulate that enable tumor growth or even metastatic dissemination. Identification of molecular signatures that define different stages of progression towards cancer can enable early tumor detection. In this review, the impact of genomics will be addressed using early detection of colorectal cancer (CRC) as an example. Increased understanding of the adenoma-to-carcinoma progression has led to the discovery of several diagnostic biomarkers. This combined with technical advancements, has facilitated the development of molecular tests for non-invasive early CRC detection in stool and blood samples. Even though several tests have already made it to clinical practice, sensitivity and specificity for the detection of precancerous lesions still need improvement. Besides the diagnostic qualities, also the accuracy of the intermediate endpoint is an important issue on how the effectiveness of a novel test is perceived. Here, progression biomarkers may provide a more precise measure than the currently used morphologically based features. Similar developments in biomarker use for early detection have taken place in other cancer types.
Resting Heart Rate Predicts Depression and Cognition Early after Ischemic Stroke: A Pilot Study.

PubMed

Tessier, Arnaud; Sibon, Igor; Poli, Mathilde; Audiffren, Michel; Allard, Michèle; Pfeuty, Micha

2017-10-01

Early detection of poststroke depression (PSD) and cognitive impairment (PSCI) remains challenging. It is well documented that the function of autonomic nervous system is associated with depression and cognition. However, their relationship has never been investigated in the early poststroke phase. This pilot study aimed at determining whether resting heart rate (HR) parameters measured in early poststroke phase (1) are associated with early-phase measures of depression and cognition and (2) could be used as new tools for early objective prediction of PSD or PSCI, which could be applicable to patients unable to answer usual questionnaires. Fifty-four patients with first-ever ischemic stroke, without cardiac arrhythmia, were assessed for resting HR and heart rate variability (HRV) within the first week after stroke and for depression and cognition during the first week and at 3 months after stroke. Multiple regression analyses controlled for age, gender, and stroke severity revealed that higher HR, lower HRV, and higher sympathovagal balance (low-frequency/high-frequency ratio of HRV) were associated with higher severity of depressive symptoms within the first week after stroke. Furthermore, higher sympathovagal balance in early phase predicted higher severity of depressive symptoms at the 3-month follow-up, whereas higher HR and lower HRV in early phase predicted lower global cognitive functioning at the 3-month follow-up. Resting HR measurements obtained in early poststroke phase could serve as an objective tool, applicable to patients unable to complete questionnaires, to help in the early prediction of PSD and PSCI. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.
Prediction and early detection of delirium in the intensive care unit by using heart rate variability and machine learning.

PubMed

Oh, Jooyoung; Cho, Dongrae; Park, Jaesub; Na, Se Hee; Kim, Jongin; Heo, Jaeseok; Shin, Cheung Soo; Kim, Jae-Jin; Park, Jin Young; Lee, Boreom

2018-03-27

Delirium is an important syndrome found in patients in the intensive care unit (ICU), however, it is usually under-recognized during treatment. This study was performed to investigate whether delirious patients can be successfully distinguished from non-delirious patients by using heart rate variability (HRV) and machine learning. Electrocardiography data of 140 patients was acquired during daily ICU care, and HRV data were analyzed. Delirium, including its type, severity, and etiologies, was evaluated daily by trained psychiatrists. HRV data and various machine learning algorithms including linear support vector machine (SVM), SVM with radial basis function (RBF) kernels, linear extreme learning machine (ELM), ELM with RBF kernels, linear discriminant analysis, and quadratic discriminant analysis were utilized to distinguish delirium patients from non-delirium patients. HRV data of 4797 ECGs were included, and 39 patients had delirium at least once during their ICU stay. The maximum classification accuracy was acquired using SVM with RBF kernels. Our prediction method based on HRV with machine learning was comparable to previous delirium prediction models using massive amounts of clinical information. Our results show that autonomic alterations could be a significant feature of patients with delirium in the ICU, suggesting the potential for the automatic prediction and early detection of delirium based on HRV with machine learning.
Prediction (early recognition) of emerging flu strain clusters

NASA Astrophysics Data System (ADS)

Li, X.; Phillips, J. C.

2017-08-01

Early detection of incipient dominant influenza strains is one of the key steps in the design and manufacture of an effective annual influenza vaccine. Here we report the most current results for pandemic H3N2 flu vaccine design. A 2006 model of dimensional reduction (compaction) of viral mutational complexity derives two-dimensional Cartesian mutational maps (2DMM) that exhibit an emergent dominant strain as a small and distinct cluster of as few as 10 strains. We show that recent extensions of this model can detect incipient strains one year or more in advance of their dominance in the human population. Our structural interpretation of our unexpectedly rich 2DMM involves sialic acid, and is based on nearly 6000 strains in a series of recent 3-year time windows. Vaccine effectiveness is predicted best by analyzing dominant mutational epitopes.
Early detection of sporadic pancreatic cancer: summative review.

PubMed

Chari, Suresh T; Kelly, Kimberly; Hollingsworth, Michael A; Thayer, Sarah P; Ahlquist, David A; Andersen, Dana K; Batra, Surinder K; Brentnall, Teresa A; Canto, Marcia; Cleeter, Deborah F; Firpo, Matthew A; Gambhir, Sanjiv Sam; Go, Vay Liang W; Hines, O Joe; Kenner, Barbara J; Klimstra, David S; Lerch, Markus M; Levy, Michael J; Maitra, Anirban; Mulvihill, Sean J; Petersen, Gloria M; Rhim, Andrew D; Simeone, Diane M; Srivastava, Sudhir; Tanaka, Masao; Vinik, Aaron I; Wong, David

2015-07-01

Pancreatic cancer (PC) is estimated to become the second leading cause of cancer death in the United States by 2020. Early detection is the key to improving survival in PC. Addressing this urgent need, the Kenner Family Research Fund conducted the inaugural Early Detection of Sporadic Pancreatic Cancer Summit Conference in 2014 in conjunction with the 45th Anniversary Meeting of the American Pancreatic Association and Japan Pancreas Society. This seminal convening of international representatives from science, practice, and clinical research was designed to facilitate challenging interdisciplinary conversations to generate innovative ideas leading to the creation of a defined collaborative strategic pathway for the future of the field. An in-depth summary of current efforts in the field, analysis of gaps in specific areas of expertise, and challenges that exist in early detection is presented within distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. In addition, an overview of efforts in familial PC is presented in an addendum to this article. It is clear from the summit deliberations that only strategically designed collaboration among investigators, institutions, and funders will lead to significant progress in early detection of sporadic PC.
Gastrointestinal Cancers: Screening and Early Detection.

PubMed

Griffin-Sobel, Joyce P

2017-05-01

To present an overview of current practices in the screening and early detection of gastrointestinal cancers. Literature reviews. Screening for gastrointestinal cancers is less than desirable, particularly in underserved populations. There are inadequate methods of screening for early detection of esophageal and gastric cancers. Education of patients is needed to reinforce the importance of screening for gastrointestinal cancers. Copyright © 2017 Elsevier Inc. All rights reserved.
Prelude and Fugue, predicting local protein structure, early folding regions and structural weaknesses.

PubMed

Kwasigroch, Jean Marc; Rooman, Marianne

2006-07-15

Prelude&Fugue are bioinformatics tools aiming at predicting the local 3D structure of a protein from its amino acid sequence in terms of seven backbone torsion angle domains, using database-derived potentials. Prelude(&Fugue) computes all lowest free energy conformations of a protein or protein region, ranked by increasing energy, and possibly satisfying some interresidue distance constraints specified by the user. (Prelude&)Fugue detects sequence regions whose predicted structure is significantly preferred relative to other conformations in the absence of tertiary interactions. These programs can be used for predicting secondary structure, tertiary structure of short peptides, flickering early folding sequences and peptides that adopt a preferred conformation in solution. They can also be used for detecting structural weaknesses, i.e. sequence regions that are not optimal with respect to the tertiary fold. http://babylone.ulb.ac.be/Prelude_and_Fugue.

Early warning signals detect critical impacts of experimental warming.

PubMed

Jarvis, Lauren; McCann, Kevin; Tunney, Tyler; Gellner, Gabriel; Fryxell, John M

2016-09-01

Earth's surface temperatures are projected to increase by ~1-4°C over the next century, threatening the future of global biodiversity and ecosystem stability. While this has fueled major progress in the field of physiological trait responses to warming, it is currently unclear whether routine population monitoring data can be used to predict temperature-induced population collapse. Here, we integrate trait performance theory with that of critical tipping points to test whether early warning signals can be reliably used to anticipate thermally induced extinction events. We find that a model parameterized by experimental growth rates exhibits critical slowing down in the vicinity of an experimentally tested critical threshold, suggesting that dynamical early warning signals may be useful in detecting the potentially precipitous onset of population collapse due to global climate change.
Early literacy and early numeracy: the value of including early literacy skills in the prediction of numeracy development.

PubMed

Purpura, David J; Hume, Laura E; Sims, Darcey M; Lonigan, Christopher J

2011-12-01

The purpose of this study was to examine whether early literacy skills uniquely predict early numeracy skills development. During the first year of the study, 69 3- to 5-year-old preschoolers were assessed on the Preschool Early Numeracy Skills (PENS) test and the Test of Preschool Early Literacy Skills (TOPEL). Participants were assessed again a year later on the PENS test and on the Applied Problems and Calculation subtests of the Woodcock-Johnson III Tests of Achievement. Three mixed effect regressions were conducted using Time 2 PENS, Applied Problems, and Calculation as the dependent variables. Print Knowledge and Vocabulary accounted for unique variance in the prediction of Time 2 numeracy scores. Phonological Awareness did not uniquely predict any of the mathematics domains. The findings of this study identify an important link between early literacy and early numeracy development. Copyright © 2011 Elsevier Inc. All rights reserved.
Can early host responses to mycobacterial infection predict eventual disease outcomes?

PubMed

de Silva, Kumudika; Begg, Douglas J; Plain, Karren M; Purdie, Auriol C; Kawaji, Satoko; Dhand, Navneet K; Whittington, Richard J

2013-11-01

Diagnostic tests used for Johne's disease in sheep either have poor sensitivity and specificity or only detect disease in later stages of infection. Predicting which of the infected sheep are likely to become infectious later in life is currently not feasible and continues to be a major hindrance in disease control. We conducted this longitudinal study to investigate if a suite of diagnostic tests conducted in Mycobacterium avium subspecies paratuberculosis (MAP) exposed lambs at 4 months post infection can accurately predict their clinical status at 12 months post infection. We tracked cellular and humoral responses and quantity of MAP shedding for up to 12 months post challenge in 20 controls and 37 exposed sheep. Infection was defined at necropsy by tissue culture and disease spectrum by lesion type. Data were analysed using univariable and multivariable logistic regression models and a subset of variables from the earliest period post inoculation (4 months) was selected for predicting disease outcomes later on (12 months). Sensitivity and specificity of tests and their combinations in series and parallel were determined. Early elevation in faecal MAP DNA quantity and a lower interferon gamma (IFNγ) response were significantly associated with sheep becoming infectious as well as progressing to severe disease. Conversely, early low faecal MAP DNA and higher interleukin-10 responses were significantly associated with an exposed animal developing protective immunity. Combination of early elevated faecal MAP DNA or lower IFNγ response had the highest sensitivity (75%) and specificity (81%) for identifying sheep that would become infectious. Collectively, these results highlight the potential for combined test interpretation to aid in the early prediction of sheep susceptibility to MAP infection. Copyright © 2013 Elsevier B.V. All rights reserved.
Determinants of Cancer Early Detection Behaviors:Application of Protection Motivation Theory.

PubMed

Rahaei, Zohreh; Ghofranipour, Fazlollah; Morowatisharifabad, Mohammad Ali; Mohammadi, Eesa

2015-01-01

Cancer is account for 13% of all deaths around the world and is the third cause of mortality in Iran. More than one third of these cases are pre-ventable and about 33% are curable with early detection. The aim of this study was to determine the predictors of cancer early detection (CED) behaviors applying Protection Motivation Theory (PMT). In this cross-sectional study, cluster sampling method was employed to recruit 260 individuals of above 20 years old in Yazd, Iran and a researcher designed questionnaire was completed through interviews for each of the respondents. PMT theoretical variables and CED behaviors were the basis of data collection procedure. Participants acquired 64.47% of the protection motivation, 30.97% of the passive and 45.64% of the active behaviors‟ possible scores. Theory constructs predicted 19.8%, 15.6% and 9.6% of the variations for protection motivation, passive and active behavior respectively. Protection motivation was responsible for 3.6% of passive and 8% of active behaviors‟ variations. Considering the scarceness of CED behaviors and the applicability of PMT in predicting these behaviors, utilization of the PMT‟s constructs in any interventional programs to accelerate CED behaviors could be an alternate methodological choice in the cancer control initiatives.
A Mass Spectrometric Analysis Method Based on PPCA and SVM for Early Detection of Ovarian Cancer.

PubMed

Wu, Jiang; Ji, Yanju; Zhao, Ling; Ji, Mengying; Ye, Zhuang; Li, Suyi

2016-01-01

Background. Surfaced-enhanced laser desorption-ionization-time of flight mass spectrometry (SELDI-TOF-MS) technology plays an important role in the early diagnosis of ovarian cancer. However, the raw MS data is highly dimensional and redundant. Therefore, it is necessary to study rapid and accurate detection methods from the massive MS data. Methods. The clinical data set used in the experiments for early cancer detection consisted of 216 SELDI-TOF-MS samples. An MS analysis method based on probabilistic principal components analysis (PPCA) and support vector machine (SVM) was proposed and applied to the ovarian cancer early classification in the data set. Additionally, by the same data set, we also established a traditional PCA-SVM model. Finally we compared the two models in detection accuracy, specificity, and sensitivity. Results. Using independent training and testing experiments 10 times to evaluate the ovarian cancer detection models, the average prediction accuracy, sensitivity, and specificity of the PCA-SVM model were 83.34%, 82.70%, and 83.88%, respectively. In contrast, those of the PPCA-SVM model were 90.80%, 92.98%, and 88.97%, respectively. Conclusions. The PPCA-SVM model had better detection performance. And the model combined with the SELDI-TOF-MS technology had a prospect in early clinical detection and diagnosis of ovarian cancer.
Early Forest Fire Detection Using Radio-Acoustic Sounding System

PubMed Central

Sahin, Yasar Guneri; Ince, Turker

2009-01-01

Automated early fire detection systems have recently received a significant amount of attention due to their importance in protecting the global environment. Some emergent technologies such as ground-based, satellite-based remote sensing and distributed sensor networks systems have been used to detect forest fires in the early stages. In this study, a radio-acoustic sounding system with fine space and time resolution capabilities for continuous monitoring and early detection of forest fires is proposed. Simulations show that remote thermal mapping of a particular forest region by the proposed system could be a potential solution to the problem of early detection of forest fires. PMID:22573967
Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG.

PubMed

Shafi, Mouhsin M; Westover, M Brandon; Cole, Andrew J; Kilbride, Ronan D; Hoch, Daniel B; Cash, Sydney S

2012-10-23

To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients. We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG. Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p < 0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording. In patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary.
Absence of early epileptiform abnormalities predicts lack of seizures on continuous EEG

PubMed Central

Westover, M. Brandon; Cole, Andrew J.; Kilbride, Ronan D.; Hoch, Daniel B.; Cash, Sydney S.

2012-01-01

Objective: To determine whether the absence of early epileptiform abnormalities predicts absence of later seizures on continuous EEG monitoring of hospitalized patients. Methods: We retrospectively reviewed 242 consecutive patients without a prior generalized convulsive seizure or active epilepsy who underwent continuous EEG monitoring lasting at least 18 hours for detection of nonconvulsive seizures or evaluation of unexplained altered mental status. The findings on the initial 30-minute screening EEG, subsequent continuous EEG recordings, and baseline clinical data were analyzed. We identified early EEG findings associated with absence of seizures on subsequent continuous EEG. Results: Seizures were detected in 70 (29%) patients. A total of 52 patients had their first seizure in the initial 30 minutes of continuous EEG monitoring. Of the remaining 190 patients, 63 had epileptiform discharges on their initial EEG, 24 had triphasic waves, while 103 had no epileptiform abnormalities. Seizures were later detected in 22% (n = 14) of studies with epileptiform discharges on their initial EEG, vs 3% (n = 3) of the studies without epileptiform abnormalities on initial EEG (p < 0.001). In the 3 patients without epileptiform abnormalities on initial EEG but with subsequent seizures, the first epileptiform discharge or electrographic seizure occurred within the first 4 hours of recording. Conclusions: In patients without epileptiform abnormalities during the first 4 hours of recording, no seizures were subsequently detected. Therefore, EEG features early in the recording may indicate a low risk for seizures, and help determine whether extended monitoring is necessary. PMID:23054233
CFD modelling of sampling locations for early detection of spontaneous combustion in long-wall gob areas.

PubMed

Yuan, Liming; Smith, Alex C

In this study, computational fluid dynamics (CFD) modeling was conducted to optimize gas sampling locations for the early detection of spontaneous heating in longwall gob areas. Initial simulations were carried out to predict carbon monoxide (CO) concentrations at various regulators in the gob using a bleeder ventilation system. Measured CO concentration values at these regulators were then used to calibrate the CFD model. The calibrated CFD model was used to simulate CO concentrations at eight sampling locations in the gob using a bleederless ventilation system to determine the optimal sampling locations for early detection of spontaneous combustion.
Early detection and intervention for attention-deficit/hyperactivity disorder.

PubMed

Sonuga-Barke, Edmund J S; Koerting, Johanna; Smith, Elizabeth; McCann, Donna C; Thompson, Margaret

2011-04-01

Attention-deficit/hyperactivity disorder (ADHD) is a high-cost/high-burden disorder. Early detection and intervention may prevent or ameliorate the development of the disorder and reduce its long-term impact. In this article, we set out a rationale for an early detection and intervention program. First, we highlight the costs of the condition and second, we discuss the limitations of the current treatments. We then outline the potential value of an early detection and intervention program. We review evidence on predictors of poor outcomes for early ADHD signs and discuss how these might allow us to target early intervention more cost-effectively. We then examine potential barriers to engagement with at-risk samples. This leads to a discussion of possible intervention approaches and how these could be improved. Finally, we describe the Program for Early Detection and Intervention for ADHD (PEDIA), a 5-year program of research supported by the UK National Institute for Health Research and conducted at the University of Southampton (Southampton, UK), which aims to develop and evaluate a strategy for early intervention.
Solar g-modes? Comparison of detected asymptotic g-mode frequencies with solar model predictions

NASA Astrophysics Data System (ADS)

Wood, Suzannah Rebecca; Guzik, Joyce Ann; Mussack, Katie; Bradley, Paul A.

2018-06-01

After many years of searching for solar gravity modes, Fossat et al. (2017) reported detection of the nearly equally spaced high-order g-modes periods using a 15-year time series of GOLF data from the SOHO spacecraft. Here we report progress towards and challenges associated with calculating and comparing g-mode period predictions for several previously published standard solar models using various abundance mixtures and opacities, as well as the predictions for some non-standard models incorporating early mass loss, and compare with the periods reported by Fossat et al (2017). Additionally, we have a side-by-side comparison of results of different stellar pulsation codes for calculating g-mode predictions. These comparisons will allow for testing of nonstandard physics input that affect the core, including an early more massive Sun and dynamic electron screening.
Deep Recurrent Neural Networks for seizure detection and early seizure detection systems

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

Talathi, S. S.

Epilepsy is common neurological diseases, affecting about 0.6-0.8 % of world population. Epileptic patients suffer from chronic unprovoked seizures, which can result in broad spectrum of debilitating medical and social consequences. Since seizures, in general, occur infrequently and are unpredictable, automated seizure detection systems are recommended to screen for seizures during long-term electroencephalogram (EEG) recordings. In addition, systems for early seizure detection can lead to the development of new types of intervention systems that are designed to control or shorten the duration of seizure events. In this article, we investigate the utility of recurrent neural networks (RNNs) in designing seizuremore » detection and early seizure detection systems. We propose a deep learning framework via the use of Gated Recurrent Unit (GRU) RNNs for seizure detection. We use publicly available data in order to evaluate our method and demonstrate very promising evaluation results with overall accuracy close to 100 %. We also systematically investigate the application of our method for early seizure warning systems. Our method can detect about 98% of seizure events within the first 5 seconds of the overall epileptic seizure duration.« less
Serum microRNA expression patterns that predict early treatment failure in prostate cancer patients.

PubMed

Singh, Prashant K; Preus, Leah; Hu, Qiang; Yan, Li; Long, Mark D; Morrison, Carl D; Nesline, Mary; Johnson, Candace S; Koochekpour, Shahriar; Kohli, Manish; Liu, Song; Trump, Donald L; Sucheston-Campbell, Lara E; Campbell, Moray J

2014-02-15

We aimed to identify microRNA (miRNA) expression patterns in the serum of prostate cancer (CaP) patients that predict the risk of early treatment failure following radical prostatectomy (RP). Microarray and Q-RT-PCR analyses identified 43 miRNAs as differentiating disease stages within 14 prostate cell lines and reflectedpublically available patient data. 34 of these miRNA were detectable in the serum of CaP patients. Association with time to biochemical progression was examined in a cohort of CaP patients following RP. A greater than two-fold increase in hazard of biochemical progression associated with altered expression of miR-103, miR-125b and miR-222 (p<.0008) in the serum of CaP patients. Prediction models based on penalized regression analyses showed that the levels of the miRNAs and PSA together were better at detecting false positives than models without miRNAs, for similar level of sensitivity. Analyses of publically available data revealed significant and reciprocal relationships between changes in CpG methylation and miRNA expression patterns suggesting a role for CpG methylation to regulate miRNA. Exploratory validation supported roles for miR-222 and miR-125b to predict progression risk in CaP. The current study established that expression patterns of serum-detectable miRNAs taken at the time of RP are prognostic for men who are at risk of experiencing subsequent early biochemical progression. These non-invasive approaches could be used to augment treatment decisions.
Early-Life Intelligence Predicts Midlife Biological Age

PubMed Central

Caspi, Avshalom; Belsky, Daniel W.; Harrington, Honalee; Houts, Renate; Israel, Salomon; Levine, Morgan E.; Sugden, Karen; Williams, Benjamin; Poulton, Richie; Moffitt, Terrie E.

2016-01-01

Objectives: Early-life intelligence has been shown to predict multiple causes of death in populations around the world. This finding suggests that intelligence might influence mortality through its effects on a general process of physiological deterioration (i.e., individual variation in “biological age”). We examined whether intelligence could predict measures of aging at midlife before the onset of most age-related disease. Methods: We tested whether intelligence assessed in early childhood, middle childhood, and midlife predicted midlife biological age in members of the Dunedin Study, a population-representative birth cohort. Results: Lower intelligence predicted more advanced biological age at midlife as captured by perceived facial age, a 10-biomarker algorithm based on data from the National Health and Nutrition Examination Survey (NHANES), and Framingham heart age (r = 0.1–0.2). Correlations between intelligence and telomere length were less consistent. The associations between intelligence and biological age were not explained by differences in childhood health or parental socioeconomic status, and intelligence remained a significant predictor of biological age even when intelligence was assessed before Study members began their formal schooling. Discussion: These results suggest that accelerated aging may serve as one of the factors linking low early-life intelligence to increased rates of morbidity and mortality. PMID:26014827
Early adolescent symptoms of social phobia prospectively predict alcohol use.

PubMed

Dahne, Jennifer; Banducci, Anne N; Kurdziel, Gretchen; MacPherson, Laura

2014-11-01

The current study examined whether social phobia (SP) symptoms in early adolescence prospectively predicted alcohol use through middle adolescence in a community sample of youth. Data from an ongoing longitudinal study (N = 277) of mechanisms of HIV-related risk behaviors in youth were used to assess the extent to which SP symptoms in early adolescence (mean [SD] age = 11.00 years [0.81]) would predict alcohol use across five annual assessment waves. Adolescents completed measures of SP symptoms, depressive symptoms, and alcohol use at each wave. Higher SP symptoms at baseline predicted higher average odds of alcohol consumption during subsequent waves but did not significantly predict an increase in the odds of alcohol use as a function of time. Within a lagged model, SP symptoms measured at a prior assessment point (1 year earlier) predicted greater odds of drinking alcohol at the following assessment point. Importantly, alcohol use did not significantly predict SP symptoms over time. These results suggest that early SP symptoms are an important risk factor for increased odds of subsequent alcohol use. The present findings highlight that elevated SP symptoms place adolescents at risk for early alcohol use. Early interventions targeting SP symptoms may be crucial for the prevention of problematic alcohol use in early to mid-adolescence. Implications for prevention and treatment approaches are discussed.
Early detection of Zygosaccharomyces rouxii--spawned spoilage in apple juice by electronic nose combined with chemometrics.

PubMed

Wang, Huxuan; Hu, Zhongqiu; Long, Fangyu; Guo, Chunfeng; Yuan, Yahong; Yue, Tianli

2016-01-18

Spoilage spawned by Zygosaccharomyces rouxii can cause sensory defect in apple juice, which could hardly be perceived in the early stage and therefore would lead to the serious economic loss. Thus, it is essential to detect the contamination in early stage to avoid costly waste of products or recalls. In this work the performance of an electronic nose (e-nose) coupled with chemometric analysis was evaluated for diagnosis of the contamination in apple juice, using test panel evaluation as reference. The feasibility of using e-nose responses to predict the spoilage level of apple juice was also evaluated. Coupled with linear discriminant analysis (LDA), detection of the contamination was achieved after 12h, corresponding to the cell concentration of less than 2.0 log 10 CFU/mL, the level at which the test panelists could not yet identify the contamination, indicating that the signals of e-nose could be utilized as early indicators for the onset of contamination. Loading analysis indicated that sensors 2, 6, 7 and 8 were the most important in the detection of Z. rouxii-contaminated apple juice. Moreover, Z. rouxii counts in unknown samples could be well predicted by the established models using partial least squares (PLS) algorithm with high correlation coefficient (R) of 0.98 (Z. rouxii strain ATCC 2623 and ATCC 8383) and 0.97 (Z. rouxii strain B-WHX-12-53). Based on these results, e-nose appears to be promising for rapid analysis of the odor in apple juice during processing or on the shelf to realize the early detection of potential contamination caused by Z. rouxii strains. Copyright © 2015 Elsevier B.V. All rights reserved.
Estimation for aerial detection effectiveness with cooperation efficiency factors of early-warning aircraft in early-warning detection SoS under BSC framework

NASA Astrophysics Data System (ADS)

Zhu, Feng; Hu, Xiaofeng; He, Xiaoyuan; Guo, Rui; Li, Kaiming; Yang, Lu

2017-11-01

In the military field, the performance evaluation of early-warning aircraft deployment or construction is always an important problem needing to be explored. As an effective approach of enterprise management and performance evaluation, Balanced Score Card (BSC) attracts more and more attentions and is studied more and more widely all over the world. It can also bring feasible ideas and technical approaches for studying the issue of the performance evaluation of the deployment or construction of early-warning aircraft which is the important component in early-warning detection system of systems (SoS). Therefore, the deep explored researches are carried out based on the previously research works. On the basis of the characteristics of space exploration and aerial detection effectiveness of early-warning detection SoS and the cardinal principle of BSC are analyzed simply, and the performance evaluation framework of the deployment or construction of early-warning aircraft is given, under this framework, aimed at the evaluation issue of aerial detection effectiveness of early-warning detection SoS with the cooperation efficiency factors of the early-warning aircraft and other land based radars, the evaluation indexes are further designed and the relative evaluation model is further established, especially the evaluation radar chart being also drawn to obtain the evaluation results from a direct sight angle. Finally, some practical computer simulations are launched to prove the validity and feasibility of the research thinking and technologic approaches which are proposed in the paper.
About the Early Detection Research Group | Division of Cancer Prevention

Cancer.gov

The Early Detection Research Group supports research that seeks to determine the effectiveness, operating characteristics and clinical impact (harms as well as benefits) of cancer early detection technologies and practices, such as imaging and molecular biomarker approaches. The group ran two large-scale early detection trials for which data and biospecimens are available
A comparison between the clinical significance and growth mixture modelling early change methods at predicting negative outcomes.

PubMed

Flood, Nicola; Page, Andrew; Hooke, Geoff

2018-05-03

Routine outcome monitoring benefits treatment by identifying potential no change and deterioration. The present study compared two methods of identifying early change and their ability to predict negative outcomes on self-report symptom and wellbeing measures. 1467 voluntary day patients participated in a 10-day group Cognitive Behaviour Therapy (CBT) program and completed the symptom and wellbeing measures daily. Early change, as defined by (a) the clinical significance method and (b) longitudinal modelling, was compared on each measure. Early change, as defined by the simpler clinical significance method, was superior at predicting negative outcomes than longitudinal modelling. The longitudinal modelling method failed to detect a group of deteriorated patients, and agreement between the early change methods and the final unchanged outcome was higher for the clinical significance method. Therapists could use the clinical significance early change method during treatment to alert them of patients at risk for negative outcomes, which in turn could allow therapists to prevent those negative outcomes from occurring.
Evaluating Fluorscence-Based Metrics for Early Detection of ...

EPA Pesticide Factsheets

Summary: This paper discusses the results of an ongoing Water Research Foundation project on developing a fluorescence sensor system for early detection of distribution system nitrification Summary: This paper discusses the results of an ongoing Water Research Foundation project on developing a fluorescence sensor system for early detection of distribution system nitrification

Sentinel lymph node detection in early cervical cancer with combination 99mTc phytate and patent blue.

PubMed

Niikura, Hitoshi; Okamura, Chikako; Akahira, Junichi; Takano, Tadao; Ito, Kiyoshi; Okamura, Kunihiro; Yaegashi, Nobuo

2004-08-01

The purpose of this study was to examine sentinel lymph node (SLN) detection in patients with early stage cervical cancer using (99m)Tc phytate and patent blue dye and to compare our method with published findings utilizing other radioisotopic tracers. A total of 20 consecutive patients with cervical cancer scheduled for radical hysterectomy and total pelvic lymphadenectomy at our hospital underwent SLN detection study. The day before surgery, lymphoscintigraphy was performed with injection of 99m-technetium ((99m)Tc)-labeled phytate into the uterine cervix. At surgery, patients underwent lymphatic mapping with a gamma-detecting probe and patent blue injected into the same points as the phytate solution. At least one positive node was detected in 18 patients (90%). A total of 46 sentinel nodes were detected (mean, 2.3; range, 1-5). Most sentinel nodes were in one of the following sites: external iliac (21 nodes), obturator (15 nodes), and parametrial (7 nodes). Eleven (24%) sentinel nodes were detected only through radioactivity and two (4%) were detected only with blue dye. The sensitivity, specificity, and negative predictive value for SLN detection were all 100%. Nine published studies involving 295 patients had a summarized detection rate of 85%. Summarized sensitivity, specificity, and negative predictive value were 93%, 100%, and 99%, respectively. Combination of (99m)Tc phytate and patent blue is effective in SLN detection in early stage cervical cancer.
Radiolabeled Exosomes for the Early Detection of Metastases and to Predict Breast Cancer Premetastatic Niche

DTIC Science & Technology

2015-08-31

University REPORT DATE : August 31, 2015 TYPE OF REPORT: Annual, Year 2 PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick...if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE August 31, 2015 2...REPORT TYPE Annual 3. DATES COVERED August 01, 2014 - July 31, 2015 4. TITLE AND SUBTITLE Radiolabeled Exosomes for the Early Detection of
Structural and Functional Evaluations for the Early Detection of Glaucoma.

PubMed

Lucy, Katie A; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection.
Structural and Functional Evaluations for the Early Detection of Glaucoma

PubMed Central

Lucy, Katie A.; Wollstein, Gadi

2016-01-01

The early detection of glaucoma is imperative in order to preserve functional vision. Structural and functional methods are utilized to detect and monitor glaucomatous damage and the vision loss it causes. The relationship between these detection measures is complex and differs between individuals, especially in early glaucoma. Using both measures together is advised in order to ensure the highest probability of glaucoma detection, and new testing methods are continuously developed with the goals of earlier disease detection and improvement of disease monitoring. The purpose of this review is to explore the relationship between structural and functional glaucoma detection and discuss important technological advances for early glaucoma detection. PMID:28603546
Raman spectroscopy detection of platelet for Alzheimer’s disease with predictive probabilities

NASA Astrophysics Data System (ADS)

Wang, L. J.; Du, X. Q.; Du, Z. W.; Yang, Y. Y.; Chen, P.; Tian, Q.; Shang, X. L.; Liu, Z. C.; Yao, X. Q.; Wang, J. Z.; Wang, X. H.; Cheng, Y.; Peng, J.; Shen, A. G.; Hu, J. M.

2014-08-01

Alzheimer’s disease (AD) is a common form of dementia. Early and differential diagnosis of AD has always been an arduous task for the medical expert due to the unapparent early symptoms and the currently imperfect imaging examination methods. Therefore, obtaining reliable markers with clinical diagnostic value in easily assembled samples is worthy and significant. Our previous work with laser Raman spectroscopy (LRS), in which we detected platelet samples of different ages of AD transgenic mice and non-transgenic controls, showed great effect in the diagnosis of AD. In addition, a multilayer perception network (MLP) classification method was adopted to discriminate the spectral data. However, there were disturbances, which were induced by noise from the machines and so on, in the data set; thus the MLP method had to be trained with large-scale data. In this paper, we aim to re-establish the classification models of early and advanced AD and the control group with fewer features, and apply some mechanism of noise reduction to improve the accuracy of models. An adaptive classification method based on the Gaussian process (GP) featured, with predictive probabilities, is proposed, which could tell when a data set is related to some kind of disease. Compared with MLP on the same feature set, GP showed much better performance in the experimental results. What is more, since the spectra of platelets are isolated from AD, GP has good expansibility and can be applied in diagnosis of many other similar diseases, such as Parkinson’s disease (PD). Spectral data of 4 month and 12 month AD platelets, as well as control data, were collected. With predictive probabilities, the proposed GP classification method improved the diagnostic sensitivity to nearly 100%. Samples were also collected from PD platelets as classification and comparison to the 12 month AD. The presented approach and our experiments indicate that utilization of GP with predictive probabilities in
Early Literacy and Early Numeracy: The Value of Including Early Literacy Skills in the Prediction of Numeracy Development

ERIC Educational Resources Information Center

Purpura, David J.; Hume, Laura E.; Sims, Darcey M.; Lonigan, Cristopher J.

2011-01-01

The purpose of this study was to examine whether early literacy skills uniquely predict early numeracy skills development. During the first year of the study, 69 3- to 5-year-old preschoolers were assessed on the Preschool Early Numeracy Skills (PENS) test and the Test of Preschool Early Literacy Skills (TOPEL). Participants were assessed again a…
New non-invasive method for early detection of metabolic syndrome in the working population.

PubMed

Romero-Saldaña, Manuel; Fuentes-Jiménez, Francisco J; Vaquero-Abellán, Manuel; Álvarez-Fernández, Carlos; Molina-Recio, Guillermo; López-Miranda, José

2016-12-01

We propose a new method for the early detection of metabolic syndrome in the working population, which was free of biomarkers (non-invasive) and based on anthropometric variables, and to validate it in a new working population. Prevalence studies and diagnostic test accuracy to determine the anthropometric variables associated with metabolic syndrome, as well as the screening validity of the new method proposed, were carried out between 2013 and 2015 on 636 and 550 workers, respectively. The anthropometric variables analysed were: blood pressure, body mass index, waist circumference, waist-height ratio, body fat percentage and waist-hip ratio. We performed a multivariate logistic regression analysis and obtained receiver operating curves to determine the predictive ability of the variables. The new method for the early detection of metabolic syndrome we present is based on a decision tree using chi-squared automatic interaction detection methodology. The overall prevalence of metabolic syndrome was 14.9%. The area under the curve for waist-height ratio and waist circumference was 0.91 and 0.90, respectively. The anthropometric variables associated with metabolic syndrome in the adjusted model were waist-height ratio, body mass index, blood pressure and body fat percentage. The decision tree was configured from the waist-height ratio (⩾0.55) and hypertension (blood pressure ⩾128/85 mmHg), with a sensitivity of 91.6% and a specificity of 95.7% obtained. The early detection of metabolic syndrome in a healthy population is possible through non-invasive methods, based on anthropometric indicators such as waist-height ratio and blood pressure. This method has a high degree of predictive validity and its use can be recommended in any healthcare context. © The European Society of Cardiology 2016.
Early-Life Intelligence Predicts Midlife Biological Age.

PubMed

Schaefer, Jonathan D; Caspi, Avshalom; Belsky, Daniel W; Harrington, Honalee; Houts, Renate; Israel, Salomon; Levine, Morgan E; Sugden, Karen; Williams, Benjamin; Poulton, Richie; Moffitt, Terrie E

2016-11-01

Early-life intelligence has been shown to predict multiple causes of death in populations around the world. This finding suggests that intelligence might influence mortality through its effects on a general process of physiological deterioration (i.e., individual variation in "biological age"). We examined whether intelligence could predict measures of aging at midlife before the onset of most age-related disease. We tested whether intelligence assessed in early childhood, middle childhood, and midlife predicted midlife biological age in members of the Dunedin Study, a population-representative birth cohort. Lower intelligence predicted more advanced biological age at midlife as captured by perceived facial age, a 10-biomarker algorithm based on data from the National Health and Nutrition Examination Survey (NHANES), and Framingham heart age (r = 0.1-0.2). Correlations between intelligence and telomere length were less consistent. The associations between intelligence and biological age were not explained by differences in childhood health or parental socioeconomic status, and intelligence remained a significant predictor of biological age even when intelligence was assessed before Study members began their formal schooling. These results suggest that accelerated aging may serve as one of the factors linking low early-life intelligence to increased rates of morbidity and mortality. © The Author 2015. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Combined Screening for Early Detection of Pre-Eclampsia

PubMed Central

Park, Hee Jin; Shim, Sung Shin; Cha, Dong Hyun

2015-01-01

Although the precise pathophysiology of pre-eclampsia remains unknown, this condition continues to be a major cause of maternal and fetal mortality. Early prediction of pre-eclampsia would allow for timely initiation of preventive therapy. A combination of biophysical and biochemical markers are superior to other tests for early prediction of the development of pre-eclampsia. Apart from the use of parameters in first-trimester aneuploidy screening, cell-free fetal DNA quantification is emerging as a promising marker for prediction of pre-eclampsia. This article reviews the current research of the most important strategies for prediction of pre-eclampsia, including the use of maternal risk factors, mean maternal arterial pressure, ultrasound parameters, and biomarkers. PMID:26247944
Strategies for early detection of resectable pancreatic cancer

PubMed Central

Okano, Keiichi; Suzuki, Yasuyuki

2014-01-01

Pancreatic cancer is difficult to diagnose at an early stage and generally has a poor prognosis. Surgical resection is the only potentially curative treatment for pancreatic carcinoma. To improve the prognosis of this disease, it is essential to detect tumors at early stages, when they are resectable. The optimal approach to screening for early pancreatic neoplasia has not been established. The International Cancer of the Pancreas Screening Consortium has recently finalized several recommendations regarding the management of patients who are at an increased risk of familial pancreatic cancer. In addition, there have been notable advances in research on serum markers, tissue markers, gene signatures, and genomic targets of pancreatic cancer. To date, however, no biomarkers have been established in the clinical setting. Advancements in imaging modalities touch all aspects of the clinical management of pancreatic diseases, including the early detection of pancreatic masses, their characterization, and evaluations of tumor resectability. This article reviews strategies for screening high-risk groups, biomarkers, and current advances in imaging modalities for the early detection of resectable pancreatic cancer. PMID:25170207
Early detection of emerging forest disease using dispersal estimation and ecological niche modeling.

PubMed

Meentemeyer, Ross K; Anacker, Brian L; Mark, Walter; Rizzo, David M

2008-03-01

Distinguishing the manner in which dispersal limitation and niche requirements control the spread of invasive pathogens is important for prediction and early detection of disease outbreaks. Here, we use niche modeling augmented by dispersal estimation to examine the degree to which local habitat conditions vs. force of infection predict invasion of Phytophthora ramorum, the causal agent of the emerging infectious tree disease sudden oak death. We sampled 890 field plots for the presence of P. ramorum over a three-year period (2003-2005) across a range of host and abiotic conditions with variable proximities to known infections in California, USA. We developed and validated generalized linear models of invasion probability to analyze the relative predictive power of 12 niche variables and a negative exponential dispersal kernel estimated by likelihood profiling. Models were developed incrementally each year (2003, 2003-2004, 2003-2005) to examine annual variability in model parameters and to create realistic scenarios for using models to predict future infections and to guide early-detection sampling. Overall, 78 new infections were observed up to 33.5 km from the nearest known site of infection, with slightly increasing rates of prevalence across time windows (2003, 6.5%; 2003-2004, 7.1%; 2003-2005, 9.6%). The pathogen was not detected in many field plots that contained susceptible host vegetation. The generalized linear modeling indicated that the probability of invasion is limited by both dispersal and niche constraints. Probability of invasion was positively related to precipitation and temperature in the wet season and the presence of the inoculum-producing foliar host Umbellularia californica and decreased exponentially with distance to inoculum sources. Models that incorporated niche and dispersal parameters best predicted the locations of new infections, with accuracies ranging from 0.86 to 0.90, suggesting that the modeling approach can be used to forecast
Inversion Method for Early Detection of ARES-1 Case Breach Failure

NASA Technical Reports Server (NTRS)

Mackey, Ryan M.; Kulikov, Igor K.; Bajwa, Anupa; Berg, Peter; Smelyanskiy, Vadim

2010-01-01

A document describes research into the problem of detecting a case breach formation at an early stage of a rocket flight. An inversion algorithm for case breach allocation is proposed and analyzed. It is shown how the case breach can be allocated at an early stage of its development by using the rocket sensor data and the output data from the control block of the rocket navigation system. The results are simulated with MATLAB/Simulink software. The efficiency of an inversion algorithm for a case breach location is discussed. The research was devoted to the analysis of the ARES-l flight during the first 120 seconds after the launch and early prediction of case breach failure. During this time, the rocket is propelled by its first-stage Solid Rocket Booster (SRB). If a breach appears in SRB case, the gases escaping through it will produce the (side) thrust directed perpendicular to the rocket axis. The side thrust creates torque influencing the rocket attitude. The ARES-l control system will compensate for the side thrust until it reaches some critical value, after which the flight will be uncontrollable. The objective of this work was to obtain the start time of case breach development and its location using the rocket inertial navigation sensors and GNC data. The algorithm was effective for the detection and location of a breach in an SRB field joint at an early stage of its development.
Early detection of non-native fishes using fish larvae

EPA Science Inventory

Our objective was to evaluate the use of fish larvae for early detection of non-native fishes, comparing traditional and molecular taxonomy approaches to investigate potential efficiencies. Fish larvae present an interesting opportunity for non-native fish early detection. First,...
Application of carbon nanoparticles in laparoscopic sentinel lymph node detection in patients with early-stage cervical cancer.

PubMed

Lu, Yan; Wei, Jin-Ying; Yao, De-Sheng; Pan, Zhong-Mian; Yao, Yao

2017-01-01

To investigate the value of carbon nanoparticles in identifying sentinel lymph nodes in early-stage cervical cancer. From January 2014 to January 2016, 40 patients with cervical cancer stage IA2-IIA, based on the International Federation of Gynecology and Obstetrics (FIGO) 2009 criteria, were included in this study. The normal cervix around the tumor was injected with a total of 1 mL of carbon nanoparticles (CNP)at 3 and 9 o'clock. All patients then underwent laparoscopic pelvic lymph node dissection and radical hysterectomy. The black-dyed sentinel lymph nodes were removed for routine pathological examination and immunohistochemical staining. Among the 40 patients, 38 patients had at least one sentinel lymph node (SLN). The detection rate was 95% (38/40). One hundred seventy-three SLNs were detected with an average of 3.9 SLNs per side. 25 positive lymph nodes, which included 21 positive SLNs, were detected in 8 (20%) patients. Sentinel lymph nodes were localized in the obturator (47.97%), internal lilac (13.87%), external lilac (26.59%), parametrial (1.16%), and common iliac (8.67%) regions. The sensitivity of the SLN detection was 100% (5/5), the accuracy was 97.37% (37/38), and the negative predictive value was 100. 0% and the false negative rate was 0%. Sentinel lymph nodes can be used to accurately predict the pathological state of pelvic lymph nodes in early cervical cancer. The detection rates and accuracy of sentinel lymph node were high. Carbon nanoparticles can be used to trace the sentinel lymph node in early cervical cancer.
Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis

PubMed Central

Parra-Amaya, Mayra Elizabeth; Puerta-Yepes, María Eugenia; Lizarralde-Bejarano, Diana Paola; Arboleda-Sánchez, Sair

2016-01-01

Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes. There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places. PMID:28933396
Early Detection for Dengue Using Local Indicator of Spatial Association (LISA) Analysis.

PubMed

Parra-Amaya, Mayra Elizabeth; Puerta-Yepes, María Eugenia; Lizarralde-Bejarano, Diana Paola; Arboleda-Sánchez, Sair

2016-03-29

Dengue is a viral disease caused by a flavivirus that is transmitted by mosquitoes of the genus Aedes . There is currently no specific treatment or commercial vaccine for its control and prevention; therefore, mosquito population control is the only alternative for preventing the occurrence of dengue. For this reason, entomological surveillance is recommended by World Health Organization (WHO) to measure dengue risk in endemic areas; however, several works have shown that the current methodology (aedic indices) is not sufficient for predicting dengue. In this work, we modified indices proposed for epidemic periods. The raw value of the epidemiological wave could be useful for detecting risk in epidemic periods; however, risk can only be detected if analyses incorporate the maximum epidemiological wave. Risk classification was performed according to Local Indicators of Spatial Association (LISA) methodology. The modified indices were analyzed using several hypothetical scenarios to evaluate their sensitivity. We found that modified indices could detect spatial and differential risks in epidemic and endemic years, which makes them a useful tool for the early detection of a dengue outbreak. In conclusion, the modified indices could predict risk at the spatio-temporal level in endemic years and could be incorporated in surveillance activities in endemic places.
On-line early fault detection and diagnosis of municipal solid waste incinerators

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

Zhao Jinsong; Huang Jianchao; Sun Wei

A fault detection and diagnosis framework is proposed in this paper for early fault detection and diagnosis (FDD) of municipal solid waste incinerators (MSWIs) in order to improve the safety and continuity of production. In this framework, principal component analysis (PCA), one of the multivariate statistical technologies, is used for detecting abnormal events, while rule-based reasoning performs the fault diagnosis and consequence prediction, and also generates recommendations for fault mitigation once an abnormal event is detected. A software package, SWIFT, is developed based on the proposed framework, and has been applied in an actual industrial MSWI. The application shows thatmore » automated real-time abnormal situation management (ASM) of the MSWI can be achieved by using SWIFT, resulting in an industrially acceptable low rate of wrong diagnosis, which has resulted in improved process continuity and environmental performance of the MSWI.« less
Strategies for early melanoma detection: approaches to the patient with nevi

PubMed Central

Goodson, Agnessa G.; Grossman, Douglas

2009-01-01

Given its propensity to metastasize, and lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. Although there are no non-invasive techniques for definitive diagnosis of melanoma, and the “gold standard” remains biopsy with histologic examination, a variety of modalities may facilitate early melanoma diagnosis and the detection of new and changing nevi. This article reviews general clinical principles of early melanoma detection, and various modalities that are currently available or on the horizon, providing the clinician with an up-to-date understanding of management strategies for their patients with numerous or atypical nevi. Learning objectives At the conclusion of this learning activity, participants should: 1) understand the clinical importance of early melanoma detection; 2) appreciate the challenges of early melanoma diagnosis and which patients are at highest risk; 3) know general principles of early melanoma detection; 4) be familiar with current and emerging modalities that may facilitate early melanoma diagnosis and the detection of new and changing nevi; 5) know the advantages and limitations of each modality; and 6) be able to practice a combined approach to the patient with numerous or clinically atypical nevi. PMID:19389517
Real-Time Detection of Rupture Development: Earthquake Early Warning Using P Waves From Growing Ruptures

NASA Astrophysics Data System (ADS)

Kodera, Yuki

2018-01-01

Large earthquakes with long rupture durations emit P wave energy throughout the rupture period. Incorporating late-onset P waves into earthquake early warning (EEW) algorithms could contribute to robust predictions of strong ground motion. Here I describe a technique to detect in real time P waves from growing ruptures to improve the timeliness of an EEW algorithm based on seismic wavefield estimation. The proposed P wave detector, which employs a simple polarization analysis, successfully detected P waves from strong motion generation areas of the 2011 Mw 9.0 Tohoku-oki earthquake rupture. An analysis using 23 large (M ≥ 7) events from Japan confirmed that seismic intensity predictions based on the P wave detector significantly increased lead times without appreciably decreasing the prediction accuracy. P waves from growing ruptures, being one of the fastest carriers of information on ongoing rupture development, have the potential to improve the performance of EEW systems.
Value of Different Assays for Detection of Human Cytomegalovirus (HCMV) in Predicting the Development of HCMV Disease in Human Immunodeficiency Virus-Infected Patients

PubMed Central

Blank, Brian S. N.; Meenhorst, Pieter L.; Mulder, Jan Willem; Weverling, Gerrit Jan; Putter, Hein; Pauw, Wouter; van Dijk, Willemien C.; Smits, Paul; Lie-A-Ling, Sonja; Reiss, Peter; Lange, Joep M. A.

2000-01-01

In the present prospective study, five blood tests for detection of human cytomegalovirus (HCMV), nucleic acid sequence-based amplification (NASBA) for detection of early (immediate-early antigen) and late (pp67) mRNA, PCR for detection of HCMV DNA (DNA PCR), culture, and pp65 antigenemia assay, and culture and DNA PCR of urine and throat swab specimens were compared for their abilities to predict the development of disease caused by HCMV (HCMV disease). Of 101 human immunodeficiency virus (HIV)-infected patients with ≤100 CD4+ lymphocytes per mm3, 25 patients developed HCMV disease. The pp65 antigenemia assay (sensitivity, 50%; specificity, 89%) and DNA PCR of blood (sensitivity, 69%; specificity, 75%) were most accurate in predicting the development of HCMV disease within the next 12 months. Both blood culture and late pp67 mRNA NASBA had high specificities (91 and 90%, respectively) but low sensitivities (25 and 13%, respectively). The sensitivities of urine culture, DNA PCR, throat swab specimen culture, DNA PCR, and NASBA of blood for detection of the immediate-early antigen were 73, 87, 53, 67, and 63%, respectively, and the specificities were 58, 46, 76, 60, and 72%, respectively. The positive predictive values of all tests however, were low and did not exceed 50%. In conclusion, virological screening by these qualitative assays for detection of HCMV is of limited value for prediction of the development of HCMV disease in HIV-infected patients. PMID:10655346

Liquid biopsy for lung cancer early detection.

PubMed

Santarpia, Mariacarmela; Liguori, Alessia; D'Aveni, Alessandro; Karachaliou, Niki; Gonzalez-Cao, Maria; Daffinà, Maria Grazia; Lazzari, Chiara; Altavilla, Giuseppe; Rosell, Rafael

2018-04-01

Molecularly targeted therapies and immune checkpoint inhibitors have markedly improved the therapeutic management of advanced lung cancer. However, it still remains the leading cause of cancer-related mortality worldwide, with disease stage at diagnosis representing the main prognostic factor. Detection of lung cancer at an earlier stage of disease, potentially susceptible of curative resection, can be critical to improve patients survival. Low-dose computed tomography (LDCT) screening of high-risk patients has been demonstrated to reduce mortality from lung cancer, but can be also associated with high false-positive rate, thus often resulting in unnecessary interventions for patients. Novel sensitive and specific biomarkers for identification of high-risk subjects and early detection that can be used alternatively and/or complement current routine diagnostic procedures are needed. Liquid biopsy has recently demonstrated its clinical usefulness in advanced NSCLC as a surrogate of tissue biopsy for noninvasive assessment of specific genomic alterations, thereby providing prognostic and predictive information. Different biosources from liquid biopsy, including cell free circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs), have also been widely investigated for their potential role in lung cancer diagnosis. This review will provide an overview on the circulating biomarkers being evaluated for lung cancer detection, mainly focusing on results from most recent studies, the techniques developed to perform their assessment in blood and other biologic fluids and challenges in their clinical applications.
Liquid biopsy for lung cancer early detection

PubMed Central

Liguori, Alessia; D’Aveni, Alessandro; Karachaliou, Niki; Gonzalez-Cao, Maria; Daffinà, Maria Grazia; Lazzari, Chiara; Altavilla, Giuseppe; Rosell, Rafael

2018-01-01

Molecularly targeted therapies and immune checkpoint inhibitors have markedly improved the therapeutic management of advanced lung cancer. However, it still remains the leading cause of cancer-related mortality worldwide, with disease stage at diagnosis representing the main prognostic factor. Detection of lung cancer at an earlier stage of disease, potentially susceptible of curative resection, can be critical to improve patients survival. Low-dose computed tomography (LDCT) screening of high-risk patients has been demonstrated to reduce mortality from lung cancer, but can be also associated with high false-positive rate, thus often resulting in unnecessary interventions for patients. Novel sensitive and specific biomarkers for identification of high-risk subjects and early detection that can be used alternatively and/or complement current routine diagnostic procedures are needed. Liquid biopsy has recently demonstrated its clinical usefulness in advanced NSCLC as a surrogate of tissue biopsy for noninvasive assessment of specific genomic alterations, thereby providing prognostic and predictive information. Different biosources from liquid biopsy, including cell free circulating tumor DNA (ctDNA), circulating tumor cells (CTCs), exosomes and tumor-educated platelets (TEPs), have also been widely investigated for their potential role in lung cancer diagnosis. This review will provide an overview on the circulating biomarkers being evaluated for lung cancer detection, mainly focusing on results from most recent studies, the techniques developed to perform their assessment in blood and other biologic fluids and challenges in their clinical applications. PMID:29780635
Analysis of cardiovascular oscillations: A new approach to the early prediction of pre-eclampsia

NASA Astrophysics Data System (ADS)

Malberg, H.; Bauernschmitt, R.; Voss, A.; Walther, T.; Faber, R.; Stepan, H.; Wessel, N.

2007-03-01

Pre-eclampsia (PE) is a serious disorder with high morbidity and mortality occurring during pregnancy; 3%-5% of all pregnant women are affected. Early prediction is still insufficient in clinical practice. Although most pre-eclamptic patients show pathological uterine perfusion in the second trimester, this parameter has a positive predictive accuracy of only 30%, which makes it unsuitable for early, reliable prediction. The study is based on the hypothesis that alterations in cardiovascular regulatory behavior can be used to predict PE. Ninety-six pregnant women in whom Doppler investigation detected perfusion disorders of the uterine arteries were included in the study. Twenty-four of these pregnant women developed PE after the 30th week of gestation. During pregnancy, additional several noninvasive continuous blood pressure recordings were made over 30 min under resting conditions by means of a finger cuff. The time series extracted of systolic as well as diastolic beat-to-beat pressures and the heart rate were studied by variability and coupling analysis to find predictive factors preceding genesis of the disease. In the period between the 18th and 26th weeks of pregnancy, three special variability and baroreflex parameters were able to predict PE several weeks before clinical manifestation. Discriminant function analysis of these parameters was able to predict PE with a sensitivity and specificity of 87.5% and a positive predictive value of 70%. The combined clinical assessment of uterine perfusion and cardiovascular variability demonstrates the best current prediction several weeks before clinical manifestation of PE.
Red-breasted nuthatches detect early increases in spruce budworm populations

Treesearch

Hewlette S. Crawford; Daniel T. Jennings; Timothy L. Stone

1990-01-01

Early suppression .of increasing spruce budworm populations is essential to prevent epidemics; however, early changes in budworm numbers are difficult to detect. An effective and inexpensive method to detect early increases is needed. Red-breasted nuthatches eat more spruce budworm larvae and pupae as the insect increases in number. We estimated the number of large...
Sweet-spot training for early esophageal cancer detection

NASA Astrophysics Data System (ADS)

van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Over the past decade, the imaging tools for endoscopists have improved drastically. This has enabled physicians to visually inspect the intestinal tissue for early signs of malignant lesions. Besides this, recent studies show the feasibility of supportive image analysis for endoscopists, but the analysis problem is typically approached as a segmentation task where binary ground truth is employed. In this study, we show that the detection of early cancerous tissue in the gastrointestinal tract cannot be approached as a binary segmentation problem and it is crucial and clinically relevant to involve multiple experts for annotating early lesions. By employing the so-called sweet spot for training purposes as a metric, a much better detection performance can be achieved. Furthermore, a multi-expert-based ground truth, i.e. a golden standard, enables an improved validation of the resulting delineations. For this purpose, besides the sweet spot we also propose another novel metric, the Jaccard Golden Standard (JIGS) that can handle multiple ground-truth annotations. Our experiments involving these new metrics and based on the golden standard show that the performance of a detection algorithm of early neoplastic lesions in Barrett's esophagus can be increased significantly, demonstrating a 10 percent point increase in the resulting F1 detection score.
Detection of early warning signals of forest mortality in California

NASA Astrophysics Data System (ADS)

Liu, Y.; Kumar, M.; Katul, G. G.; Porporato, A. M.

2017-12-01

Massive forest mortality was observed in California during the most recent drought. Owing to complex interactions of physiological mechanisms under stress, prediction of climate-induced forest mortality using dynamic global vegetation models remains fraught with uncertainty. Given that forest ecosystems approaching mortality tend to exhibit reduction in resilience, we evaluate the time-varying resilience from time series of satellite images to detect early warning signals (EWSs) of mortality. Four metrics of EWSs are used: (1) low greenness, (2) high empirical autocorrelation of greenness, (3) high autocorrelation inferred using a Bayesian dynamic linear model considering the influence of seasonality and climate conditions, and (4) low recovery rate inferred from the drift term in the Langevin equation describing stochastic dynamics. Spatial accuracy and lead-time of these EWSs are evaluated by comparing the EWSs against observed mortality from aerial surveys conducted by the US Forest Service. Our results show that most forested areas in California that underwent mortality exhibit a EWS with a lead time of three months to two years ahead of observed mortality. Notably, EWS is also detected in some areas without mortality, suggesting reduced resilience during drought. Furthermore, the influence of the previous drought (2007-2009) may have propagated into the recent drought (2012-2016) through reduced resilience, hence contributing to the massive forest mortality observed recently. Methodologies developed in this study for detection of EWS will improve the near-term predictability of forest mortality, thus providing crucial information for forest and water resource management.
Early Adolescent Affect Predicts Later Life Outcomes.

PubMed

Kansky, Jessica; Allen, Joseph P; Diener, Ed

2016-07-01

Subjective well-being as a predictor for later behavior and health has highlighted its relationship to health, work performance, and social relationships. However, the majority of such studies neglect the developmental nature of well-being in contributing to important changes across the transition to adulthood. To examine the potential role of subjective well-being as a long-term predictor of critical life outcomes, we examined indicators of positive and negative affect at age 14 as predictors of relationship, adjustment, self-worth, and career outcomes a decade later at ages 23 to 25, controlling for family income and gender. We utilised multi-informant methods including reports from the target participant, close friends, and romantic partners in a demographically diverse community sample of 184 participants. Early adolescent positive affect predicted fewer relationship problems (less self-reported and partner-reported conflict, and greater friendship attachment as rated by close peers) and healthy adjustment to adulthood (lower levels of depression, anxiety, and loneliness). It also predicted positive work functioning (higher levels of career satisfaction and job competence) and increased self-worth. Negative affect did not significantly predict any of these important life outcomes. In addition to predicting desirable mean levels of later outcomes, early positive affect predicted beneficial changes across time in many outcomes. The findings extend early research on the beneficial outcomes of subjective well-being by having an earlier assessment of well-being, including informant reports in measuring a large variety of outcome variables, and by extending the findings to a lower socioeconomic group of a diverse and younger sample. The results highlight the importance of considering positive affect as an important component of subjective well-being distinct from negative affect. © 2016 The International Association of Applied Psychology.
Early Adolescent Affect Predicts Later Life Outcomes

PubMed Central

Kansky, Jessica; Allen, Joseph P.; Diener, Ed

2016-01-01

Background Subjective well-being as a predictor for later behavior and health has highlighted its relationship to health, work performance, and social relationships. However, the majority of such studies neglect the developmental nature of well-being in contributing to important changes across the transition to adulthood. Methods To examine the potential role of subjective well-being as a long-term predictor of critical life outcomes, we examined indicators of positive and negative affect at age 14 as a predictor of relationship, adjustment, self worth, and career outcomes a decade later at ages 23 to 25, controlling for family income and gender. We utilized multi-informant methods including reports from the target participant, close friends, and romantic partners in a demographically diverse community sample of 184 participants. Results Early adolescent positive affect predicted less relationship problems (less self-reported and partner-reported conflict, greater friendship attachment as rated by close peers), healthy adjustment to adulthood (lower levels of depression, anxiety, and loneliness). It also predicted positive work functioning (higher levels of career satisfaction and job competence) and increased self-worth. Negative affect did not significantly predict any of these important life outcomes. In addition to predicting desirable mean levels of later outcomes, early positive affect predicted beneficial changes across time in many outcomes. Conclusions The findings extend early research on the beneficial outcomes of subjective well-being by having an earlier assessment of well-being, including informant reports in measuring a large variety of outcome variables, and by extending the findings to a lower socioeconomic group of a diverse and younger sample. The results highlight the importance of considering positive affect as an important component of subjective well-being distinct from negative affect. PMID:27075545
Kidney Disease: Early Detection and Treatment

MedlinePlus

... Bar Home Current Issue Past Issues Special Section Kidney Disease: Early Detection and Treatment Past Issues / Winter ... called a "urine albumin-to-creatinine ratio." Treating Kidney Disease Kidney disease is usually a progressive disease, ...
UArizona at the CLEF eRisk 2017 Pilot Task: Linear and Recurrent Models for Early Depression Detection

PubMed Central

Sadeque, Farig; Xu, Dongfang; Bethard, Steven

2017-01-01

The 2017 CLEF eRisk pilot task focuses on automatically detecting depression as early as possible from a users’ posts to Reddit. In this paper we present the techniques employed for the University of Arizona team’s participation in this early risk detection shared task. We leveraged external information beyond the small training set, including a preexisting depression lexicon and concepts from the Unified Medical Language System as features. For prediction, we used both sequential (recurrent neural network) and non-sequential (support vector machine) models. Our models perform decently on the test data, and the recurrent neural models perform better than the non-sequential support vector machines while using the same feature sets. PMID:29075167
Early detection of ovarian cancer by serum marker and targeted ultrasound imaging | Division of Cancer Prevention

Cancer.gov

We propose to test the validity and specificity of our targeted ultrasound imaging probes in detecting early stage ovarian cancer (OVCA) by transvaginal ultrasound imaging (TVUS). We then test the predictive validity of these probes in a longitudinal study using the laying hen – the only widely available animal model of spontaneous OVCA. OVCA is a fatal gynecological
Early bronchiectasis in cystic fibrosis detected by surveillance CT.

PubMed

Pillarisetti, Naveen; Linnane, Barry; Ranganathan, Sarath

2010-08-01

There is emerging evidence that cystic fibrosis lung disease begins early in infancy. Newborn screening allows early detection and surveillance of pulmonary disease and the possibility of early intervention in this life-shortening condition. We report two children with cystic fibrosis who underwent a comprehensive assessment from diagnosis that included measurement of lung function, limited-slice high-resolution CT and BAL performed annually. Early aggressive surveillance enabled significant lung disease and bronchiectasis to be detected during the first few years of life and led to a change in management, highlighting a clinical role for CT scanning during the preschool years in children with cystic fibrosis.
Do child's psychosocial functioning, and parent and family characteristics predict early alcohol use? The TRAILS Study.

PubMed

Visser, Leenke; de Winter, Andrea F; Vollebergh, Wilma A M; Verhulst, Frank C; Reijneveld, Sijmen A

2015-02-01

Given the negative consequences of early alcohol use for health and social functioning, it is essential to detect children at risk of early drinking. The aim of this study is to determine predictors of early alcohol use that can easily be detected in Preventive Child Healthcare (PCH). We obtained data from the first two waves on 1261 Dutch adolescents who participated in TRAILS (TRacking Adolescents' Individual Lives Survey) at ages 10-14 years and from the PCH records regarding ages 4-10 years. Early adolescence alcohol use (age 10-14 years) was defined as alcohol use at least once at ages 10-12 years (wave 1) and at least once in the previous 4 weeks at ages 12-14 years (wave 2). Predictors of early alcohol use concerned parent and teacher reports at wave 1 and PCH registrations, regarding the child's psychosocial functioning, and parental and socio-demographic characteristics. A total of 17.2% of the adolescents reported early alcohol use. Predictors of early alcohol use were teacher-reported aggressive behaviour [odds ratios (OR); 95% confidence interval (CI): 1.86; 1.11-3.11], being a boy (OR 1.80, 95%-CI 1.31-2.56), being a non-immigrant (OR 2.31, 95%CI 1.05-5.09), and low and middle educational level of the father (OR 1.71, 95%CI 1.12-2.62 and OR 1.77, 95%CI 1.16-2.70, respectively), mutually adjusted. A limited set of factors was predictive for early alcohol use. Use of this set may improve the detection of early adolescence alcohol use in PCH. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
Objects predict fixations better than early saliency.

PubMed

Einhäuser, Wolfgang; Spain, Merrielle; Perona, Pietro

2008-11-20

Humans move their eyes while looking at scenes and pictures. Eye movements correlate with shifts in attention and are thought to be a consequence of optimal resource allocation for high-level tasks such as visual recognition. Models of attention, such as "saliency maps," are often built on the assumption that "early" features (color, contrast, orientation, motion, and so forth) drive attention directly. We explore an alternative hypothesis: Observers attend to "interesting" objects. To test this hypothesis, we measure the eye position of human observers while they inspect photographs of common natural scenes. Our observers perform different tasks: artistic evaluation, analysis of content, and search. Immediately after each presentation, our observers are asked to name objects they saw. Weighted with recall frequency, these objects predict fixations in individual images better than early saliency, irrespective of task. Also, saliency combined with object positions predicts which objects are frequently named. This suggests that early saliency has only an indirect effect on attention, acting through recognized objects. Consequently, rather than treating attention as mere preprocessing step for object recognition, models of both need to be integrated.
Cumulative early life adversity predicts longevity in wild baboons

PubMed Central

Tung, Jenny; Archie, Elizabeth A.; Altmann, Jeanne; Alberts, Susan C.

2016-01-01

In humans and other animals, harsh circumstances in early life predict morbidity and mortality in adulthood. Multiple adverse conditions are thought to be especially toxic, but this hypothesis has rarely been tested in a prospective, longitudinal framework, especially in long-lived mammals. Here we use prospective data on 196 wild female baboons to show that cumulative early adversity predicts natural adult lifespan. Females who experience ≥3 sources of early adversity die a median of 10 years earlier than females who experience ≤1 adverse circumstances (median lifespan is 18.5 years). Females who experience the most adversity are also socially isolated in adulthood, suggesting that social processes partially explain the link between early adversity and adult survival. Our results provide powerful evidence for the developmental origins of health and disease and indicate that close ties between early adversity and survival arise even in the absence of health habit and health care-related explanations. PMID:27091302
Implementation of predictive data mining techniques for identifying risk factors of early AVF failure in hemodialysis patients.

PubMed

Rezapour, Mohammad; Khavanin Zadeh, Morteza; Sepehri, Mohammad Mehdi

2013-01-01

Arteriovenous fistula (AVF) is an important vascular access for hemodialysis (HD) treatment but has 20-60% rate of early failure. Detecting association between patient's parameters and early AVF failure is important for reducing its prevalence and relevant costs. Also predicting incidence of this complication in new patients is a beneficial controlling procedure. Patient safety and preservation of early AVF failure is the ultimate goal. Our research society is Hasheminejad Kidney Center (HKC) of Tehran, which is one of Iran's largest renal hospitals. We analyzed data of 193 HD patients using supervised techniques of data mining approach. There were 137 male (70.98%) and 56 female (29.02%) patients introduced into this study. The average of age for all the patients was 53.87 ± 17.47 years. Twenty eight patients had smoked and the number of diabetic patients and nondiabetics was 87 and 106, respectively. A significant relationship was found between "diabetes mellitus," "smoking," and "hypertension" with early AVF failure in this study. We have found that these mentioned risk factors have important roles in outcome of vascular surgery, versus other parameters such as "age." Then we predicted this complication in future AVF surgeries and evaluated our designed prediction methods with accuracy rates of 61.66%-75.13%.
Touchscreen typing-pattern analysis for detecting fine motor skills decline in early-stage Parkinson's disease.

PubMed

Iakovakis, Dimitrios; Hadjidimitriou, Stelios; Charisis, Vasileios; Bostantzopoulou, Sevasti; Katsarou, Zoe; Hadjileontiadis, Leontios J

2018-05-16

Parkinson's disease (PD) is a degenerative movement disorder causing progressive disability that severely affects patients' quality of life. While early treatment can produce significant benefits for patients, the mildness of many early signs combined with the lack of accessible high-frequency monitoring tools may delay clinical diagnosis. To meet this need, user interaction data from consumer technologies have recently been exploited towards unsupervised screening for PD symptoms in daily life. Similarly, this work proposes a method for detecting fine motor skills decline in early PD patients via analysis of patterns emerging from finger interaction with touchscreen smartphones during natural typing. Our approach relies on low-/higher-order statistical features of keystrokes timing and pressure variables, computed from short typing sessions. Features are fed into a two-stage multi-model classification pipeline that reaches a decision on the subject's status (PD patient/control) by gradually fusing prediction probabilities obtained for individual typing sessions and keystroke variables. This method achieved an AUC = 0.92 and 0.82/0.81 sensitivity/specificity (matched groups of 18 early PD patients/15 controls) with discriminant features plausibly correlating with clinical scores of relevant PD motor symptoms. These findings suggest an improvement over similar approaches, thereby constituting a further step towards unobtrusive early PD detection from routine activities.
Early prediction of extreme stratospheric polar vortex states based on causal precursors

NASA Astrophysics Data System (ADS)

Kretschmer, Marlene; Runge, Jakob; Coumou, Dim

2017-08-01

Variability in the stratospheric polar vortex (SPV) can influence the tropospheric circulation and thereby winter weather. Early predictions of extreme SPV states are thus important to improve forecasts of winter weather including cold spells. However, dynamical models are usually restricted in lead time because they poorly capture low-frequency processes. Empirical models often suffer from overfitting problems as the relevant physical processes and time lags are often not well understood. Here we introduce a novel empirical prediction method by uniting a response-guided community detection scheme with a causal discovery algorithm. This way, we objectively identify causal precursors of the SPV at subseasonal lead times and find them to be in good agreement with known physical drivers. A linear regression prediction model based on the causal precursors can explain most SPV variability (r2 = 0.58), and our scheme correctly predicts 58% (46%) of extremely weak SPV states for lead times of 1-15 (16-30) days with false-alarm rates of only approximately 5%. Our method can be applied to any variable relevant for (sub)seasonal weather forecasts and could thus help improving long-lead predictions.
Community detection in complex networks using link prediction

NASA Astrophysics Data System (ADS)

Cheng, Hui-Min; Ning, Yi-Zi; Yin, Zhao; Yan, Chao; Liu, Xin; Zhang, Zhong-Yuan

2018-01-01

Community detection and link prediction are both of great significance in network analysis, which provide very valuable insights into topological structures of the network from different perspectives. In this paper, we propose a novel community detection algorithm with inclusion of link prediction, motivated by the question whether link prediction can be devoted to improving the accuracy of community partition. For link prediction, we propose two novel indices to compute the similarity between each pair of nodes, one of which aims to add missing links, and the other tries to remove spurious edges. Extensive experiments are conducted on benchmark data sets, and the results of our proposed algorithm are compared with two classes of baselines. In conclusion, our proposed algorithm is competitive, revealing that link prediction does improve the precision of community detection.
A review of influenza detection and prediction through social networking sites.

PubMed

Alessa, Ali; Faezipour, Miad

2018-02-01

Early prediction of seasonal epidemics such as influenza may reduce their impact in daily lives. Nowadays, the web can be used for surveillance of diseases. Search engines and social networking sites can be used to track trends of different diseases seven to ten days faster than government agencies such as Center of Disease Control and Prevention (CDC). CDC uses the Illness-Like Influenza Surveillance Network (ILINet), which is a program used to monitor Influenza-Like Illness (ILI) sent by thousands of health care providers in order to detect influenza outbreaks. It is a reliable tool, however, it is slow and expensive. For that reason, many studies aim to develop methods that do real time analysis to track ILI using social networking sites. Social media data such as Twitter can be used to predict the spread of flu in the population and can help in getting early warnings. Today, social networking sites (SNS) are used widely by many people to share thoughts and even health status. Therefore, SNS provides an efficient resource for disease surveillance and a good way to communicate to prevent disease outbreaks. The goal of this study is to review existing alternative solutions that track flu outbreak in real time using social networking sites and web blogs. Many studies have shown that social networking sites can be used to conduct real time analysis for better predictions.

When should we expect early bursts of trait evolution in comparative data? Predictions from an evolutionary food web model.

PubMed

Ingram, T; Harmon, L J; Shurin, J B

2012-09-01

Conceptual models of adaptive radiation predict that competitive interactions among species will result in an early burst of speciation and trait evolution followed by a slowdown in diversification rates. Empirical studies often show early accumulation of lineages in phylogenetic trees, but usually fail to detect early bursts of phenotypic evolution. We use an evolutionary simulation model to assemble food webs through adaptive radiation, and examine patterns in the resulting phylogenetic trees and species' traits (body size and trophic position). We find that when foraging trade-offs result in food webs where all species occupy integer trophic levels, lineage diversity and trait disparity are concentrated early in the tree, consistent with the early burst model. In contrast, in food webs in which many omnivorous species feed at multiple trophic levels, high levels of turnover of species' identities and traits tend to eliminate the early burst signal. These results suggest testable predictions about how the niche structure of ecological communities may be reflected by macroevolutionary patterns. © 2012 The Authors. Journal of Evolutionary Biology © 2012 European Society For Evolutionary Biology.
Automated System for Early Breast Cancer Detection in Mammograms

NASA Technical Reports Server (NTRS)

Bankman, Isaac N.; Kim, Dong W.; Christens-Barry, William A.; Weinberg, Irving N.; Gatewood, Olga B.; Brody, William R.

1993-01-01

The increasing demand on mammographic screening for early breast cancer detection, and the subtlety of early breast cancer signs on mammograms, suggest an automated image processing system that can serve as a diagnostic aid in radiology clinics. We present a fully automated algorithm for detecting clusters of microcalcifications that are the most common signs of early, potentially curable breast cancer. By using the contour map of the mammogram, the algorithm circumvents some of the difficulties encountered with standard image processing methods. The clinical implementation of an automated instrument based on this algorithm is also discussed.
Missed, Misused, or Mismanaged: Improving Early Detection Systems to Optimize Child Outcomes

ERIC Educational Resources Information Center

Macy, Marisa; Marks, Kevin; Towle, Alexander

2014-01-01

Early detection efforts have been shown to vary greatly in practice, and there is a general lack of systematic accountability built into monitoring early detection effort impact. This article reviews current early detection practices and the drawbacks of these practices, with particular attention given to prevalent issues of mismeasurement,…
EEG Analytics for Early Detection of Autism Spectrum Disorder: A data-driven approach.

PubMed

Bosl, William J; Tager-Flusberg, Helen; Nelson, Charles A

2018-05-01

Autism spectrum disorder (ASD) is a complex and heterogeneous disorder, diagnosed on the basis of behavioral symptoms during the second year of life or later. Finding scalable biomarkers for early detection is challenging because of the variability in presentation of the disorder and the need for simple measurements that could be implemented routinely during well-baby checkups. EEG is a relatively easy-to-use, low cost brain measurement tool that is being increasingly explored as a potential clinical tool for monitoring atypical brain development. EEG measurements were collected from 99 infants with an older sibling diagnosed with ASD, and 89 low risk controls, beginning at 3 months of age and continuing until 36 months of age. Nonlinear features were computed from EEG signals and used as input to statistical learning methods. Prediction of the clinical diagnostic outcome of ASD or not ASD was highly accurate when using EEG measurements from as early as 3 months of age. Specificity, sensitivity and PPV were high, exceeding 95% at some ages. Prediction of ADOS calibrated severity scores for all infants in the study using only EEG data taken as early as 3 months of age was strongly correlated with the actual measured scores. This suggests that useful digital biomarkers might be extracted from EEG measurements.
Effort and Potential Efficiencies for Aquatic Non-native Species Early Detection

EPA Science Inventory

This manuscript is based on the early aquatic non-native species detection research in the Duluth-Superior harbor. The problem of early detection is essentially that of a "needle in a haystack" - to detect a newly arrived and presumably rare non-native species with a high probabi...
Advances in pancreatic cancer research: moving towards early detection.

PubMed

He, Xiang-Yi; Yuan, Yao-Zong

2014-08-28

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal forms of cancer. Substantial progress has been made in the understanding of the biology of pancreatic cancer, and advances in patient management have been significant. However, most patients (nearly 80%) who present with locally advanced or metastatic disease have an extremely poor prognosis. Survival is better for those with malignant disease localized to the pancreas, because surgical resection at present offers the only chance of cure. Therefore, the early detection of pancreatic cancer may benefit patients with PDAC. However, its low rate of incidence and the limitations of current screening strategies make early detection difficult. Recent advances in the understanding of the pathogenesis of PDAC suggest that it is possible to detect PDAC in early stages and even identify precursor lesions. The presence of new-onset diabetes mellitus in the early phase of pancreatic cancer may provide clues for its early diagnosis. Advances in the identification of novel circulating biomarkers including serological signatures, autoantibodies, epigenetic markers, circulating tumor cells and microRNAs suggest that they can be used as potential tools for the screening of precursors and early stage PDAC in the future. However, proper screening strategies based on effective screening methodologies need to be tested for clinical application.
Meal frequencies in early adolescence predict meal frequencies in late adolescence and early adulthood.

PubMed

Pedersen, Trine Pagh; Holstein, Bjørn E; Flachs, Esben Meulengracht; Rasmussen, Mette

2013-05-04

Health and risk behaviours tend to be maintained from adolescence into adulthood. There is little knowledge on whether meal frequencies in adolescence are maintained into adulthood. We investigated whether breakfast, lunch and evening meal frequencies in early adolescence predicted meal frequencies in late adolescence and in early adulthood. Further, the modifying effect of gender and adolescent family structure were investigated. National representative sample of 15-year-olds in Denmark with 4 and 12 year follow-up studies with measurement of breakfast, lunch and evening meal frequencies. A total of 561 persons completed questionnaires at age 15 years (baseline 1990, n=847, response rate 84.6%), age 19 years (n=729, response rate 73.2%) and age 27 years (n=614, response rate 61.6%). Low meal frequencies at age 15 years was a significant predictor for having low meal frequencies at age 19 years (odds ratio (OR, 95% CI)) varying between 2.11, 1.33-3.34 and 7.48, 3.64-15.41). Also, low meal frequencies at age 19 years predicted low meal frequencies at age 27 years (OR varying between 2.26, 1.30-3.91 and 4.38, 2.36-8.13). Significant predictions over the full study period were seen for low breakfast frequency and low lunch frequency (OR varying between 1.78, 1.13-2.81 and 2.58, 1.31-5.07). Analyses stratified by gender showed the same patterns (OR varying between 1.88, 1.13-3.14 and 8.30, 2.85-24.16). However, the observed predictions were not statistical significant among men between age 15 and 27 years. Analyses stratified by adolescent family structure revealed different lunch predictions in strata. Having low meal frequencies in early adolescence predicted low meal frequencies in late adolescence and early adulthood. We propose that promotion of regular meals become a prioritised issue within health education.
Early detection of psychosis - establishing a service for persons at risk.

PubMed

Schultze-Lutter, Frauke; Ruhrmann, Stephan; Klosterkötter, Joachim

2009-01-01

The establishment phase of an early detection centre for prodromal psychosis is introduced and characterised, along with its detaining and promoting factors within a universal multi-payer health care system. Across the first six years (1998-2003), users' characteristics are compared between different diagnostic groups and to the local population statistics; and, for an exemplary 12-months period (3-1-2002 to 2-28-2003), the characteristics of telephone contacts with the service are studied. Rising steadily in number across the first three years, 872 persons, predominantly of German citizenship and higher education, consulted the service until 2003, 326 with first-episode psychosis and 144 not fulfilling criteria for a current or beginning psychosis. Of the 402 putatively prodromal patients, 94% reported predictive basic symptoms, 68.9% attenuated and 20.6% transient psychotic symptoms. Most contacts by persons meeting any prodromal criterion were initiated by mental health professionals (psychiatrists or psychologists) and counselling services. Supported by public awareness campaigns, an early detection service is well received by its users and private practitioners as reflected by the large proportion of referrals from the latter. However, persons of non-German background as well as of lower education were underrepresented indicating that these sub-groups should be approached by tailored programmes.
Preventive child health care findings on early childhood predict peer-group social status in early adolescence.

PubMed

Jaspers, Merlijne; de Winter, Andrea F; Veenstra, René; Ormel, Johan; Verhulst, Frank C; Reijneveld, Sijmen A

2012-12-01

A disputed social status among peers puts children and adolescents at risk for developing a wide range of problems, such as being bullied. However, there is a lack of knowledge about which early predictors could be used to identify (young) adolescents at risk for a disputed social status. The aim of this study was to assess whether preventive child health care (PCH) findings on early childhood predict neglected and rejected status in early adolescence in a large longitudinal community-based sample. Data came from 898 participants who participated in TRAILS, a longitudinal study. Information on early childhood factors was extracted from the charts of routine PCH visits registered between infancy and age of 4 years. To assess social status, peer nominations were used at age of 10-12 years. Multinomial logistic regression showed that children who had a low birth weight, motor problems, and sleep problems; children of parents with a low educational level (odds ratios [ORs] between 1.71 and 2.90); and those with fewer attention hyperactivity problems (ORs = .43) were more likely to have a neglected status in early adolescence. Boys, children of parents with a low educational level, and children with early externalizing problems were more likely to have a rejected status in early adolescence (ORs between 1.69 and 2.56). PCH findings on early childhood-on motor and social development-are predictive of a neglected and a rejected status in early adolescence. PCH is a good setting to monitor risk factors that predict the social status of young adolescents. Copyright © 2012 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
Method and system for early detection of incipient faults in electric motors

DOEpatents

Parlos, Alexander G; Kim, Kyusung

2003-07-08

A method and system for early detection of incipient faults in an electric motor are disclosed. First, current and voltage values for one or more phases of the electric motor are measured during motor operations. A set of current predictions is then determined via a neural network-based current predictor based on the measured voltage values and an estimate of motor speed values of the electric motor. Next, a set of residuals is generated by combining the set of current predictions with the measured current values. A set of fault indicators is subsequently computed from the set of residuals and the measured current values. Finally, a determination is made as to whether or not there is an incipient electrical, mechanical, and/or electromechanical fault occurring based on the comparison result of the set of fault indicators and a set of predetermined baseline values.
Early Detection and Intervention of ASD: A European Overview

PubMed Central

Narzisi, Antonio; García-Primo, Patricia; Kawa, Rafal

2017-01-01

Over the last several years there has been an increasing focus on early detection of Autism Spectrum Disorder (ASD), not only from the scientific field but also from professional associations and public health systems all across Europe. Not surprisingly, in order to offer better services and quality of life for both children with ASD and their families, different screening procedures and tools have been developed for early assessment and intervention. However, current evidence is needed for healthcare providers and policy makers to be able to implement specific measures and increase autism awareness in European communities. The general aim of this review is to address the latest and most relevant issues related to early detection and treatments. The specific objectives are (1) analyse the impact, describing advantages and drawbacks, of screening procedures based on standardized tests, surveillance programmes, or other observational measures; and (2) provide a European framework of early intervention programmes and practices and what has been learnt from implementing them in public or private settings. This analysis is then discussed and best practices are suggested to help professionals, health systems and policy makers to improve their local procedures or to develop new proposals for early detection and intervention programmes. PMID:29194420
Early detection of invasive plants: principles and practices

USGS Publications Warehouse

Welch, Bradley A.; Geissler, Paul H.; Latham, Penelope

2014-01-01

Invasive plants infest an estimated 2.6 million acres of the 83 million acres managed by the National Park Service (NPS) in the United States. The consequences of these invasions present a significant challenge for the NPS to manage the agency’s natural resources “unimpaired for the enjoyment of future generations.” More NPS lands are infested daily despite diligent efforts to curtail the problem. Impacts from invasive species have been realized in most parks, resulting in an expressed need to control existing infestations and restore affected ecosystems. There is a growing urgency in the NPS and other resource management organizations to be proactive. The NPS I&M Program, in collaboration with the U.S. Geological Survey (USGS) Status and Trends Program, compiled this document to provide guidance and insight to parks and other natural areas engaged in developing early-detection monitoring protocols for invasive plants. While several rapid response frameworks exist, there is no consistent or comprehensive guidance informing the active detection of nonnative plants early in the invasion process. Early-detection was selected as a primary focus for invasive-species monitoring because, along with rapid response, it is a key strategy for successful management of invasive species. Eradication efforts are most successful on small infestations (that is less than 1 hectare) and become less successful as infestation size increases, to the point that eradication is unlikely for large (that is greater than 1,000 hectares) populations of invasive plants. This document provides guidance for natural resource managers wishing to detect invasive plants early through an active, directed monitoring program. It has a Quick-Start Guide to direct readers to specific chapters and text relevant to their needs. Decision trees and flow charts assist the reader in deciding what methods to choose and when to use them. This document is written in a modular format to accommodate use of
[Research on early fire detection with CO-CO2 FTIR-spectroscopy].

PubMed

Du, Jian-hua; Zhang, Ren-cheng; Huang, Xiang-ying; Gong, Xue; Zhang, Xiao-hua

2007-05-01

A new fire detection method is put forward based on the theory of FTIR spectroscopy through analyzing all kinds of detection methods, in which CO and CO2 are chosen as early fire detection objects, and an early fire experiment system has been set up. The concentration characters of CO and CO2 were obtained through early fire experiments including real alarm sources and nuisance alarm sources. In real alarm sources there are abundant CO and CO2 which change regularly. In nuisance alarm sources there is almost no CO. So it's feasible to reduce the false alarms and increase the sensitivity of early fire detectors through analyzing the concentration characters of CO and CO2.
A concept for early cancer detection and therapy

NASA Astrophysics Data System (ADS)

Waynant, Ronald W.; Ilev, Ilko K.; Mitra, Kunal

2003-06-01

Early detection and treatment of breast cancer is least costly in terms of dollars, morbidity and mortality. With new early detection x-ray technology, tumors can be found, diagnosed and treated at a much smaller size than is currently possible. This paper proposes the development of a high resolution, high quality imaging system. It is a laser-driven x-ray system with time-gated detection that removes scattering noise in the image and produces resolution on the order of 10 μm. This higher resolution and higher image quality will enable the detection of one or two millimeter tumors hopefully detecting them before metastasis. We also propose that tumor detection should be followed by an immediate needle-directed, optical fiber biopsy to instantly determine if cancer is present and, if present, the tumor should immediately be given a lethal treatment of laser or x-radiation through the same needle using fiber optics or hollow waveguides. This technology will help prevent multiple interventions resulting in both the lowest overall cost and a more efficacious therapy. The approach can be stopped at the first negative (benign) indication and will help forestall repeated examination as well as reduce patient anxiety.
Early Detection of Lung Cancer Using Nano-Nose - A Review

PubMed Central

Fernandes, M. P.; Venkatesh, S; Sudarshan, B. G

2015-01-01

Lung cancer is one of the malignancies causing deaths worldwide. The yet to be developed non-invasive diagnostic techniques, are a challenge for early detection of cancer before it progresses to its later stages. The currently available diagnostic methods are expensive or invasive, and are not fit for general screening purposes. Early identification not only helps in detecting primary cancer, but also in treating its secondaries; which creates a need for easily applicable tests to screen individuals at risk. A detailed review of the various screening methods, including the latest trend of breath analysis using gold nanoparticles, to identify cancer at its early stage, are studied here. The VOC based breath biomarkers are used to analyze the exhaled breath of the patients. These biomarkers are utilized by Chemiresistors coated with gold nanoparticles, which are found to be the most suited technique for early detection of lung cancer. This technique is highly accurate and is relatively easy to operate and was tested on smokers and non-smokers. This review also gives as an outline of the fabrication and working of the device Na-Nose. The Chemiresistors coated with Gold nanoparticles, show a great potential in being an non-invasive and cost-effective diagnostic technique for early detection of lung cancer. PMID:26628933
Early Detection of Lung Cancer Using Nano-Nose - A Review.

PubMed

Fernandes, M P; Venkatesh, S; Sudarshan, B G

2015-01-01

Lung cancer is one of the malignancies causing deaths worldwide. The yet to be developed non-invasive diagnostic techniques, are a challenge for early detection of cancer before it progresses to its later stages. The currently available diagnostic methods are expensive or invasive, and are not fit for general screening purposes. Early identification not only helps in detecting primary cancer, but also in treating its secondaries; which creates a need for easily applicable tests to screen individuals at risk. A detailed review of the various screening methods, including the latest trend of breath analysis using gold nanoparticles, to identify cancer at its early stage, are studied here. The VOC based breath biomarkers are used to analyze the exhaled breath of the patients. These biomarkers are utilized by Chemiresistors coated with gold nanoparticles, which are found to be the most suited technique for early detection of lung cancer. This technique is highly accurate and is relatively easy to operate and was tested on smokers and non-smokers. This review also gives as an outline of the fabrication and working of the device Na-Nose. The Chemiresistors coated with Gold nanoparticles, show a great potential in being an non-invasive and cost-effective diagnostic technique for early detection of lung cancer.
Validation of the Argentine version of the Memory Binding Test (MBT) for Early Detection of Mild Cognitive Impairment

PubMed Central

Roman, Fabian; Iturry, Mónica; Rojas, Galeno; Barceló, Ernesto; Buschke, Herman; Allegri, Ricardo F.

2016-01-01

ABSTRACT Background: "Forgetfulness" is frequent in normal aging and characteristic of the early stages of dementia syndromes. The episodic memory test is central for detecting amnestic mild cognitive impairment (MCI). The Memory Binding Test (MBT) is a simple, easy and brief memory test to detect the early stage of episodic memory impairment. Objective: To validate the Argentine version of the MBT in a Latin American population and to estimate the diagnostic accuracy as a tool for early detection of MCI. Methods: 88 subjects (46 healthy controls and 42 patients with amnestic MCI) matched for age and educational level were evaluated by an extensive neuropsychological battery and the memory binding test. Results: A significantly better performance was detected in the control group; all MBT scales were predictive of MCI diagnosis (p<.01). The MBT showed high sensitivity (69%) and high specificity (88%), with a PPV of 93% and a NPV of 55% for associative paired recall. A statistically significant difference (c2=14,164, p<.001) was obtained when comparing the area under the curve (AUC) of the MBT (0.88) and the MMSE (0.70). Conclusion: The Argentine version of the MBT correlated significantly with the MMSE and the memory battery and is a useful tool in the detection of MCI. The operating characteristics of the MBT are well suited, surpassing other tests commonly used for detecting MCI. PMID:29213458
Development of predictive weather scenarios for early prediction of rice yield in South Korea

NASA Astrophysics Data System (ADS)

Shin, Y.; Cho, J.; Jung, I.

2017-12-01

International grain prices are becoming unstable due to frequent occurrence of abnormal weather phenomena caused by climate change. Early prediction of grain yield using weather forecast data is important for stabilization of international grain prices. The APEC Climate Center (APCC) is providing seasonal forecast data based on monthly climate prediction models for global seasonal forecasting services. The 3-month and 6-month seasonal forecast data using the multi-model ensemble (MME) technique are provided in their own website, ADSS (APCC Data Service System, http://adss.apcc21.org/). The spatial resolution of seasonal forecast data for each individual model is 2.5°×2.5°(about 250km) and the time scale is created as monthly. In this study, we developed customized weather forecast scenarios that are combined seasonal forecast data and observational data apply to early rice yield prediction model. Statistical downscale method was applied to produce meteorological input data of crop model because field scale crop model (ORYZA2000) requires daily weather data. In order to determine whether the forecasting data is suitable for the crop model, we produced spatio-temporal downscaled weather scenarios and evaluated the predictability by comparison with observed weather data at 57 ASOS stations in South Korea. The customized weather forecast scenarios can be applied to various application fields not only early rice yield prediction. Acknowledgement This work was carried out with the support of "Cooperative Research Program for Agriculture Science and Technology Development (Project No: PJ012855022017)" Rural Development Administration, Republic of Korea.
A simplified clinical risk score predicts the need for early endoscopy in non-variceal upper gastrointestinal bleeding.

PubMed

Tammaro, Leonardo; Buda, Andrea; Di Paolo, Maria Carla; Zullo, Angelo; Hassan, Cesare; Riccio, Elisabetta; Vassallo, Roberto; Caserta, Luigi; Anderloni, Andrea; Natali, Alessandro

2014-09-01

Pre-endoscopic triage of patients who require an early upper endoscopy can improve management of patients with non-variceal upper gastrointestinal bleeding. To validate a new simplified clinical score (T-score) to assess the need of an early upper endoscopy in non variceal bleeding patients. Secondary outcomes were re-bleeding rate, 30-day bleeding-related mortality. In this prospective, multicentre study patients with bleeding who underwent upper endoscopy were enrolled. The accuracy for high risk endoscopic stigmata of the T-score was compared with that of the Glasgow Blatchford risk score. Overall, 602 patients underwent early upper endoscopy, and 472 presented with non-variceal bleeding. High risk endoscopic stigmata were detected in 145 (30.7%) cases. T-score sensitivity and specificity for high risk endoscopic stigmata and bleeding-related mortality was 96% and 30%, and 80% and 71%, respectively. No statistically difference in predicting high risk endoscopic stigmata between T-score and Glasgow Blatchford risk score was observed (ROC curve: 0.72 vs. 0.69, p=0.11). The two scores were also similar in predicting re-bleeding (ROC curve: 0.64 vs. 0.63, p=0.4) and 30-day bleeding-related mortality (ROC curve: 0.78 vs. 0.76, p=0.3). The T-score appeared to predict high risk endoscopic stigmata, re-bleeding and mortality with similar accuracy to Glasgow Blatchford risk score. Such a score may be helpful for the prediction of high-risk patients who need a very early therapeutic endoscopy. Copyright © 2014 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
A Cell-Based Approach to Early Pancreatic Cancer Detection

DTIC Science & Technology

2016-10-01

Award Number: W81XWH-15-1-0457 TITLE: A Cell -Based Approach to Early Pancreatic Cancer Detection PRINCIPAL INVESTIGATOR: Dr. Ben Stanger...SUBTITLE 5a. CONTRACT NUMBER A Cell -Based Approach to Early Pancreatic Cancer Detection 5b. GRANT NUMBER W81XWH-15-1-0457 5c. PROGRAM ELEMENT NUMBER 6...tumor cells from mouse blood by depleting the sample of white blood cells (WBCs). Furthermore, the RNA profile of these cells can be assessed by

Technology for Early Detection of Depression and Anxiety in Older People.

PubMed

Andrews, Jacob A; Astell, Arlene J; Brown, Laura J E; Harrison, Robert F; Hawley, Mark S

2017-01-01

Under-diagnosis of depression and anxiety is common in older adults. This project took a mixed methods approach to explore the application of machine learning and technology for early detection of these conditions. Mood measures collected with digital technologies were used to predict depression and anxiety status according to the Geriatric Depression Scale (GDS) and the Hospital Anxiety and Depression Scale (HADS). Interactive group activities and interviews were used to explore views of older adults and healthcare professionals on this approach respectively. The results show good potential for using a machine learning approach with mood data to predict later depression, though prospective results are preliminary. Qualitative findings highlight motivators and barriers to use of mental health technologies, as well as usability issues. If consideration is given to these issues, this approach could allow alerts to be provided to healthcare staff to draw attention to service users who may go on to experience depression.
[Circulating miR-152 helps early prediction of postoperative biochemical recurrence of prostate cancer].

PubMed

Chen, Jun-Feng; Liao, Yu-Feng; Ma, Jian-Bo; Mao, Qi-Feng; Jia, Guang-Cheng; Dong, Xue-Jun

2017-07-01

To investigate the value of circulating miR-152 in the early prediction of postoperative biochemical recurrence of prostate cancer. Sixty-six cases of prostate cancer were included in this study, 35 with and 31 without biochemical recurrence within two years postoperatively, and another 31 healthy individuals were enrolled as normal controls. The relative expression levels of circulating miR-152 in the serum of the subjects were detected by qRT-PCR, its value in the early diagnosis of postoperative biochemical recurrence of prostate cancer was assessed by ROC curve analysis, and the correlation of its expression level with the clinicopathological parameters of the patients were analyzed. The expression of circulating miR-152 was significantly lower in the serum of the prostate cancer patients than in the normal controls (t = －5.212, P = 0.001), and so was it in the patients with than in those without postoperative biochemical recurrence (t = －5.727, P = 0.001). The ROC curve for the value of miR-152 in the early prediction of postoperative biochemical recurrence of prostate cancer showed the area under the curve (AUC) to be 0.906 (95% CI: 0.809－0.964), with a sensitivity of 91.4% and a specificity of 80.6%. The expression level of miR-152 was correlated with the Gleason score, clinical stage of prostate cancer, biochemical recurrence, and bone metastasis (P <0.05), decreasing with increased Gleason scores and elevated clinical stage of the malignancy. No correlation, however, was found between the miR-152 expression and the patients' age or preoperative PSA level (P >0.05). The expression level of circulating miR-152 is significantly reduced in prostate cancer patients with biochemical recurrence after prostatectomy and could be a biomarker in the early prediction of postoperative biochemical recurrence of the malignancy.
Predicted Errors In Children's Early Sentence Comprehension

PubMed Central

Gertner, Yael; Fisher, Cynthia

2012-01-01

Children use syntax to interpret sentences and learn verbs; this is syntactic bootstrapping. The structure-mapping account of early syntactic bootstrapping proposes that a partial representation of sentence structure, the set of nouns occurring with the verb, guides initial interpretation and provides an abstract format for new learning. This account predicts early successes, but also telltale errors: Toddlers should be unable to tell transitive sentences from other sentences containing two nouns. In testing this prediction, we capitalized on evidence that 21-month-olds use what they have learned about noun order in English sentences to understand new transitive verbs. In two experiments, 21-month-olds applied this noun-order knowledge to two-noun intransitive sentences, mistakenly assigning different interpretations to “The boy and the girl are gorping!” and “The girl and the boy are gorping!”. This suggests that toddlers exploit partial representations of sentence structure to guide sentence interpretation; these sparse representations are useful, but error-prone. PMID:22525312
Glycoprotein Biomarkers for the Early Detection of Aggressive Prostate Cancer — EDRN Public Portal

Cancer.gov

The Early Detection Research Network of the NCI is charged with the discovery, development and validation of biomarkers for early detection and prognosis related to neoplastic disease. Our laboratory is an NCI EDRN (U01CA152813) working on "Glycoprotein biomarkers for the early detection of aggressive prostate cancer". This EDRN administratiVE! supplement is a collaboration with Robert Veltri on his project to identify men with very low risk (indolent) prostate cancer (CaP) at the diagnostic biopsy at selection for active surveillance (AS). We will assess biopsy tissue using quantitative nuclear histomorphometric measurements and molecular biomarkers to predict an unexpected catastrophic CaP in such men with indolent CaP. At Johns Hopkins Hospital w1e use the Epstein criteria that includes; PSA density (PSAD) <0.15 ng/mVcm3, Gleason score SS, S2 cons involved with cancer, and ::;;SO% of any core involved with cancer to select AS. Our approach will study 140 AS men (70 with a expected outcome and 70 with a disastrous outcome) using nuclear histomorphometry and pre-qualified biomarkers quantified by digital microscopy. Previously, our laboratory combined measurements of DNA content and (-2)pPSA in the serum and (-5,-?)pPSA in biopsy tissue to identify 7/10 men that would fail surveillance based on the primary diagnostic biopsy. We now will devHiop a clinical, morphological and biomarker 'signature' for identifying severe aggressive disease from a AS diagnostic biopsy. Our approach will combine nuclear morphometry measured by digital microscopy with a unique biopsy tissue biomarker profile (DNA content, Ki67, Her2neu, CACND1 and periostin). Fcr the molecular targets we will use a multiplex tissue blot (MTB) immunohistochemistry method. The Aims o'f our work include 1) to utilize retrospective archival biopsy material from 70 AS cases where the outcome was unexpected and disastrous and collect an equal number of AS cases (n=140) and perform assays for morphology
Dual-mode microwave system to enhance early detection of cancer

NASA Technical Reports Server (NTRS)

Carr, K. L.; El-Mahdi, A. M.; Shaeffer, J.

1981-01-01

A dual-mode microwave system has been developed that will permit early detection of cancer. The system combines the use of the passive microwave radiometer with an active transmitter. The active transmitter will provide localized heating to enhance early detection by taking advantage of the differential heating (i.e., tumor temperature with respect to surrounding tissue) associated with the thermal characteristics of tumors.
Support Vector Feature Selection for Early Detection of Anastomosis Leakage From Bag-of-Words in Electronic Health Records.

PubMed

Soguero-Ruiz, Cristina; Hindberg, Kristian; Rojo-Alvarez, Jose Luis; Skrovseth, Stein Olav; Godtliebsen, Fred; Mortensen, Kim; Revhaug, Arthur; Lindsetmo, Rolv-Ole; Augestad, Knut Magne; Jenssen, Robert

2016-09-01

The free text in electronic health records (EHRs) conveys a huge amount of clinical information about health state and patient history. Despite a rapidly growing literature on the use of machine learning techniques for extracting this information, little effort has been invested toward feature selection and the features' corresponding medical interpretation. In this study, we focus on the task of early detection of anastomosis leakage (AL), a severe complication after elective surgery for colorectal cancer (CRC) surgery, using free text extracted from EHRs. We use a bag-of-words model to investigate the potential for feature selection strategies. The purpose is earlier detection of AL and prediction of AL with data generated in the EHR before the actual complication occur. Due to the high dimensionality of the data, we derive feature selection strategies using the robust support vector machine linear maximum margin classifier, by investigating: 1) a simple statistical criterion (leave-one-out-based test); 2) an intensive-computation statistical criterion (Bootstrap resampling); and 3) an advanced statistical criterion (kernel entropy). Results reveal a discriminatory power for early detection of complications after CRC (sensitivity 100%; specificity 72%). These results can be used to develop prediction models, based on EHR data, that can support surgeons and patients in the preoperative decision making phase.
Early detection and monitoring of Malaria

NASA Astrophysics Data System (ADS)

Rahman, Md Z.; Roytman, Leonid; Kadik, Abdelhamid; Miller, Howard; Rosy, Dilara A.

2015-05-01

Global Earth Observation Systems of Systems (GEOSS) are bringing vital societal benefits to people around the globe. In this research article, we engage undergraduate students in the exciting area of space exploration to improve the health of millions of people globally. The goal of the proposed research is to place students in a learning environment where they will develop their problem solving skills in the context of a world crisis (e.g., malaria). Malaria remains one of the greatest threats to public health, particularly in developing countries. The World Health Organization has estimated that over one million die of Malaria each year, with more than 80% of these found in Sub-Saharan Africa. The mosquitoes transmit malaria. They breed in the areas of shallow surface water that are suitable to the mosquito and parasite development. These environmental factors can be detected with satellite imagery, which provide high spatial and temporal coverage of the earth's surface. We investigate on moisture, thermal and vegetation stress indicators developed from NOAA operational environmental satellite data. Using these indicators and collected epidemiological data, it is possible to produce a forecast system that can predict the risk of malaria for a particular geographical area with up to four months lead time. This valuable lead time information provides an opportunity for decision makers to deploy the necessary preventive measures (spraying, treated net distribution, storing medications and etc) in threatened areas with maximum effectiveness. The main objective of the proposed research is to study the effect of ecology on human health and application of NOAA satellite data for early detection of malaria.
Europa's small impactor flux and seismic detection predictions

NASA Astrophysics Data System (ADS)

Tsuji, Daisuke; Teanby, Nicholas A.

2016-10-01

Europa is an attractive target for future lander missions due to its dynamic surface and potentially habitable sub-surface environment. Seismology has the potential to provide powerful new constraints on the internal structure using natural sources such as faults or meteorite impacts. Here we predict how many meteorite impacts are likely to be detected using a single seismic station on Europa to inform future mission planning efforts. To this end, we derive: (1) the current small impactor flux on Europa from Jupiter impact rate observations and models; (2) a crater diameter versus impactor energy scaling relation for icy moons by merging previous experiments and simulations; and (3) scaling relations for seismic signal amplitudes as a function of distance from the impact site for a given crater size, based on analogue explosive data obtained on Earth's ice sheets. Finally, seismic amplitudes are compared to predicted noise levels and seismometer performance to determine detection rates. We predict detection of 0.002-20 small local impacts per year based on P-waves travelling directly through the ice crust. Larger regional and global-scale impact events, detected through mantle-refracted waves, are predicted to be extremely rare (10-8-1 detections per year), so are unlikely to be detected by a short duration mission. Estimated ranges include uncertainties from internal seismic attenuation, impactor flux, and seismic amplitude scaling. Internal attenuation is the most significant unknown and produces extreme uncertainties in the mantle-refracted P-wave amplitudes. Our nominal best-guess attenuation model predicts 0.002-5 local direct P detections and 6 × 10-6-0.2 mantle-refracted detections per year. Given that a plausible Europa landed mission will only last around 30 days, we conclude that impacts should not be relied upon for a seismic exploration of Europa. For future seismic exploration, faulting due to stresses in the rigid outer ice shell is likely to be a
Colorectal Cancer: The Importance of Early Detection

MedlinePlus

... of this page please turn JavaScript on. Feature: Colorectal Cancer The Importance of Early Detection Past Issues / Summer ... Cancer of the colon or rectum is called colorectal cancer. The colon and the rectum are part of ...
Automated detection of dark and bright lesions in retinal images for early detection of diabetic retinopathy.

PubMed

Akram, Usman M; Khan, Shoab A

2012-10-01

There is an ever-increasing interest in the development of automatic medical diagnosis systems due to the advancement in computing technology and also to improve the service by medical community. The knowledge about health and disease is required for reliable and accurate medical diagnosis. Diabetic Retinopathy (DR) is one of the most common causes of blindness and it can be prevented if detected and treated early. DR has different signs and the most distinctive are microaneurysm and haemorrhage which are dark lesions and hard exudates and cotton wool spots which are bright lesions. Location and structure of blood vessels and optic disk play important role in accurate detection and classification of dark and bright lesions for early detection of DR. In this article, we propose a computer aided system for the early detection of DR. The article presents algorithms for retinal image preprocessing, blood vessel enhancement and segmentation and optic disk localization and detection which eventually lead to detection of different DR lesions using proposed hybrid fuzzy classifier. The developed methods are tested on four different publicly available databases. The presented methods are compared with recently published methods and the results show that presented methods outperform all others.
microRNA profiling for early detection of nonmelanoma skin cancer.

PubMed

Balci, S; Ayaz, L; Gorur, A; Yildirim Yaroglu, H; Akbayir, S; Dogruer Unal, N; Bulut, B; Tursen, U; Tamer, L

2016-06-01

microRNAs (miRNAs) are single-stranded, noncoding RNA molecules. Given the vast regulatory potential of miRNAs and their often tissue-specific and disease-specific expression patterns, miRNAs are being assessed as possible biomarkers to aid diagnosis and prediction of different types and stages of cancers, including skin cancer. Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the most common forms of nonmelanoma skin cancer (NMSC). BCC originates from the basal layer of the epidermis, while SCC arises from epidermal keratinocytes or from the dermal appendages. Although NMSCs are currently the most common types of malignancies, both BCC and SCC have a better than 95% cure rate if detected early. To identify plasma miRNAs suitable for early detection of NMSC. Expression profiles of 741 miRNAs were evaluated using high-throughput real-time quantitative PCR from plasma samples in 42 patients with NMSC and 282 healthy controls (HCs). Our results demonstrated that in patients with NMSC, compared with HCs, expression levels of miR-30e-3p, miR-145-5p, miR-186-5p and miR-875-5p were significantly (P < 0.05) upregulated, while those of miR-19a-3p, miR-25-3p, miR-30a-5p, miR-451 and miR-576-3p were significantly downregulated. Our study suggests that the miRNAs with significant changes in expression (miR-19a-3p, miR-25-3p, miR-30a-5p, miR-145-5p and miR-186-5p) could serve as novel noninvasive biomarkers for detection of NMSC. © 2015 British Association of Dermatologists.
Fluorescence-based endoscopic imaging of Thomsen-Friedenreich antigen to improve early detection of colorectal cancer.

PubMed

Sakuma, Shinji; Yu, James Y H; Quang, Timothy; Hiwatari, Ken-Ichiro; Kumagai, Hironori; Kao, Stephanie; Holt, Alex; Erskind, Jalysa; McClure, Richard; Siuta, Michael; Kitamura, Tokio; Tobita, Etsuo; Koike, Seiji; Wilson, Kevin; Richards-Kortum, Rebecca; Liu, Eric; Washington, Kay; Omary, Reed; Gore, John C; Pham, Wellington

2015-03-01

Thomsen-Friedenreich (TF) antigen belongs to the mucin-type tumor-associated carbohydrate antigen. Notably, TF antigen is overexpressed in colorectal cancer (CRC) but is rarely expressed in normal colonic tissue. Increased TF antigen expression is associated with tumor invasion and metastasis. In this study, we sought to validate a novel nanobeacon for imaging TF-associated CRC in a preclinical animal model. We developed and characterized the nanobeacon for use with fluorescence colonoscopy. In vivo imaging was performed on an orthotopic rat model of CRC. Both white light and fluorescence colonoscopy methods were utilized to establish the ratio-imaging index for the probe. The nanobeacon exhibited specificity for TF-associated cancer. Fluorescence colonoscopy using the probe can detect lesions at the stage which is not readily confirmed by conventional visualization methods. Further, the probe can report the dynamic change of TF expression as tumor regresses during chemotherapy. Data from this study suggests that fluorescence colonoscopy can improve early CRC detection. Supplemented by the established ratio-imaging index, the probe can be used not only for early detection, but also for reporting tumor response during chemotherapy. Furthermore, since the data obtained through in vivo imaging confirmed that the probe was not absorbed by the colonic mucosa, no registered toxicity is associated with this nanobeacon. Taken together, these data demonstrate the potential of this novel probe for imaging TF antigen as a biomarker for the early detection and prediction of the progression of CRC at the molecular level. © 2014 UICC.
Malignant external otitis: early scintigraphic detection

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

Strashun, A.M.; Nejatheim, M.; Goldsmith, S.J.

1984-02-01

Pseudomonas otitis externa in elderly diabetics may extend aggressively to adjacent bone, cranial nerves, meninges, and vessels, leading to a clinical diagnosis of ''malignant'' external otitis. Early diagnosis is necessary for successful treatment. This study compares the findings of initial radiographs, thin-section tomography of temporal bone, CT scans of head and neck, technetium-99m methylene diphosphonate (MDP) and gallium-67 citrate scintigraphy, and single-photon emission computed tomography (SPECT) for detection of temporal bone osteomylitis in ten patients fulfilling the clinical diagnostic criteria of malignant external otitis. Skull radiographs were negative in all of the eight patients studied. Thin-section tomography was positive inmore » one of the seven patients studied using this modality. CT scanning suggested osteomyelitis in three of nine patients. Both Tc-99m and Ga-67 citrate scintigraphy were positive in 10 of 10 patients. These results suggest that technetium and gallium scintigraphy are more sensitive than radiographs and CT scans for early detection of malignant external otitis.« less
Integrating alternative splicing detection into gene prediction.

PubMed

Foissac, Sylvain; Schiex, Thomas

2005-02-10

Alternative splicing (AS) is now considered as a major actor in transcriptome/proteome diversity and it cannot be neglected in the annotation process of a new genome. Despite considerable progresses in term of accuracy in computational gene prediction, the ability to reliably predict AS variants when there is local experimental evidence of it remains an open challenge for gene finders. We have used a new integrative approach that allows to incorporate AS detection into ab initio gene prediction. This method relies on the analysis of genomically aligned transcript sequences (ESTs and/or cDNAs), and has been implemented in the dynamic programming algorithm of the graph-based gene finder EuGENE. Given a genomic sequence and a set of aligned transcripts, this new version identifies the set of transcripts carrying evidence of alternative splicing events, and provides, in addition to the classical optimal gene prediction, alternative optimal predictions (among those which are consistent with the AS events detected). This allows for multiple annotations of a single gene in a way such that each predicted variant is supported by a transcript evidence (but not necessarily with a full-length coverage). This automatic combination of experimental data analysis and ab initio gene finding offers an ideal integration of alternatively spliced gene prediction inside a single annotation pipeline.
Anomaly Detection in Host Signaling Pathways for the Early Prognosis of Acute Infection.

PubMed

Wang, Kun; Langevin, Stanley; O'Hern, Corey S; Shattuck, Mark D; Ogle, Serenity; Forero, Adriana; Morrison, Juliet; Slayden, Richard; Katze, Michael G; Kirby, Michael

2016-01-01

Clinical diagnosis of acute infectious diseases during the early stages of infection is critical to administering the appropriate treatment to improve the disease outcome. We present a data driven analysis of the human cellular response to respiratory viruses including influenza, respiratory syncytia virus, and human rhinovirus, and compared this with the response to the bacterial endotoxin, Lipopolysaccharides (LPS). Using an anomaly detection framework we identified pathways that clearly distinguish between asymptomatic and symptomatic patients infected with the four different respiratory viruses and that accurately diagnosed patients exposed to a bacterial infection. Connectivity pathway analysis comparing the viral and bacterial diagnostic signatures identified host cellular pathways that were unique to patients exposed to LPS endotoxin indicating this type of analysis could be used to identify host biomarkers that can differentiate clinical etiologies of acute infection. We applied the Multivariate State Estimation Technique (MSET) on two human influenza (H1N1 and H3N2) gene expression data sets to define host networks perturbed in the asymptomatic phase of infection. Our analysis identified pathways in the respiratory virus diagnostic signature as prognostic biomarkers that triggered prior to clinical presentation of acute symptoms. These early warning pathways correctly predicted that almost half of the subjects would become symptomatic in less than forty hours post-infection and that three of the 18 subjects would become symptomatic after only 8 hours. These results provide a proof-of-concept for utility of anomaly detection algorithms to classify host pathway signatures that can identify presymptomatic signatures of acute diseases and differentiate between etiologies of infection. On a global scale, acute respiratory infections cause a significant proportion of human co-morbidities and account for 4.25 million deaths annually. The development of clinical
Anomaly Detection in Host Signaling Pathways for the Early Prognosis of Acute Infection

PubMed Central

O’Hern, Corey S.; Shattuck, Mark D.; Ogle, Serenity; Forero, Adriana; Morrison, Juliet; Slayden, Richard; Katze, Michael G.

2016-01-01

Clinical diagnosis of acute infectious diseases during the early stages of infection is critical to administering the appropriate treatment to improve the disease outcome. We present a data driven analysis of the human cellular response to respiratory viruses including influenza, respiratory syncytia virus, and human rhinovirus, and compared this with the response to the bacterial endotoxin, Lipopolysaccharides (LPS). Using an anomaly detection framework we identified pathways that clearly distinguish between asymptomatic and symptomatic patients infected with the four different respiratory viruses and that accurately diagnosed patients exposed to a bacterial infection. Connectivity pathway analysis comparing the viral and bacterial diagnostic signatures identified host cellular pathways that were unique to patients exposed to LPS endotoxin indicating this type of analysis could be used to identify host biomarkers that can differentiate clinical etiologies of acute infection. We applied the Multivariate State Estimation Technique (MSET) on two human influenza (H1N1 and H3N2) gene expression data sets to define host networks perturbed in the asymptomatic phase of infection. Our analysis identified pathways in the respiratory virus diagnostic signature as prognostic biomarkers that triggered prior to clinical presentation of acute symptoms. These early warning pathways correctly predicted that almost half of the subjects would become symptomatic in less than forty hours post-infection and that three of the 18 subjects would become symptomatic after only 8 hours. These results provide a proof-of-concept for utility of anomaly detection algorithms to classify host pathway signatures that can identify presymptomatic signatures of acute diseases and differentiate between etiologies of infection. On a global scale, acute respiratory infections cause a significant proportion of human co-morbidities and account for 4.25 million deaths annually. The development of clinical
Predicting Readmission at Early Hospitalization Using Electronic Clinical Data: An Early Readmission Risk Score.

PubMed

Tabak, Ying P; Sun, Xiaowu; Nunez, Carlos M; Gupta, Vikas; Johannes, Richard S

2017-03-01

Identifying patients at high risk for readmission early during hospitalization may aid efforts in reducing readmissions. We sought to develop an early readmission risk predictive model using automated clinical data available at hospital admission. We developed an early readmission risk model using a derivation cohort and validated the model with a validation cohort. We used a published Acute Laboratory Risk of Mortality Score as an aggregated measure of clinical severity at admission and the number of hospital discharges in the previous 90 days as a measure of disease progression. We then evaluated the administrative data-enhanced model by adding principal and secondary diagnoses and other variables. We examined the c-statistic change when additional variables were added to the model. There were 1,195,640 adult discharges from 70 hospitals with 39.8% male and the median age of 63 years (first and third quartile: 43, 78). The 30-day readmission rate was 11.9% (n=142,211). The early readmission model yielded a graded relationship of readmission and the Acute Laboratory Risk of Mortality Score and the number of previous discharges within 90 days. The model c-statistic was 0.697 with good calibration. When administrative variables were added to the model, the c-statistic increased to 0.722. Automated clinical data can generate a readmission risk score early at hospitalization with fair discrimination. It may have applied value to aid early care transition. Adding administrative data increases predictive accuracy. The administrative data-enhanced model may be used for hospital comparison and outcome research.
Using Renyi entropy to detect early cardiac autonomic neuropathy.

PubMed

Cornforth, David J; Tarvainen, Mika P; Jelinek, Herbert F

2013-01-01

Cardiac Autonomic Neuropathy (CAN) is a disease that involves nerve damage leading to abnormal control of heart rate. CAN affects the correct operation of the heart and in turn leads to associated arrhythmias and heart attack. An open question is to what extent this condition is detectable by the measurement of Heart Rate Variability (HRV). An even more desirable option is to detect CAN in its early, preclinical stage, to improve treatment and outcomes. In previous work we have shown a difference in the Renyi spectrum between participants identified with well-defined CAN and controls. In this work we applied the multi-scale Renyi entropy for identification of early CAN in diabetes patients. Results suggest that Renyi entropy derived from a 20 minute, Lead-II ECG recording, forms a useful contribution to the detection of CAN even in the early stages of the disease. The positive α parameters (1 ≤ α ≤ 5) associated with the Renyi distribution indicated a significant difference (p < 0.00004) between controls and early CAN as well as definite CAN. This is a significant achievement given the simple nature of the information collected, and raises prospects of a simple screening test and improved outcomes of patients.
DNA Copy Number Signature to Predict Recurrence in Early Stage Ovarian Cancer

DTIC Science & Technology

2016-08-01

AWARD NUMBER: W81XWH-14-1-0194 TITLE: DNA Copy Number Signature to Predict Recurrence in Early-Stage Ovarian Cancer PRINCIPAL INVESTIGATOR...SUBTITLE 5a. CONTRACT NUMBER DNA Copy Number Signature to Predict Recurrence in Early-Stage Ovarian Cancer 5b. GRANT NUMBER W81XWH-14-1-0194 5c. PROGRAM...determine the copy number gain and loss for early stage high grade ovarian cancers through IlluminaHumanOmniExpress-FFPE BeadChip system • Subtask 1 DNA
Methylation analysis of plasma cell-free DNA for breast cancer early detection using bisulfite next-generation sequencing.

PubMed

Li, Zibo; Guo, Xinwu; Tang, Lili; Peng, Limin; Chen, Ming; Luo, Xipeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Xia, Kun; Wang, Jun

2016-10-01

Circulating cell-free DNA (cfDNA) has been considered as a potential biomarker for non-invasive cancer detection. To evaluate the methylation levels of six candidate genes (EGFR, GREM1, PDGFRB, PPM1E, SOX17, and WRN) in plasma cfDNA as biomarkers for breast cancer early detection, quantitative analysis of the promoter methylation of these genes from 86 breast cancer patients and 67 healthy controls was performed by using microfluidic-PCR-based target enrichment and next-generation bisulfite sequencing technology. The predictive performance of different logistic models based on methylation status of candidate genes was investigated by means of the area under the ROC curve (AUC) and odds ratio (OR) analysis. Results revealed that EGFR, PPM1E, and 8 gene-specific CpG sites showed significantly hypermethylation in cancer patients' plasma and significantly associated with breast cancer (OR ranging from 2.51 to 9.88). The AUC values for these biomarkers were ranging from 0.66 to 0.75. Combinations of multiple hypermethylated genes or CpG sites substantially improved the predictive performance for breast cancer detection. Our study demonstrated the feasibility of quantitative measurement of candidate gene methylation in cfDNA by using microfluidic-PCR-based target enrichment and bisulfite next-generation sequencing, which is worthy of further validation and potentially benefits a broad range of applications in clinical oncology practice. Quantitative analysis of methylation pattern of plasma cfDNA by next-generation sequencing might be a valuable non-invasive tool for early detection of breast cancer.

Detection of early seizures by diffuse optical tomography

NASA Astrophysics Data System (ADS)

Zhang, Tao; Hajihashemi, M. Reza; Zhou, Junli; Carney, Paul R.; Jiang, Huabei

2015-03-01

In epilepsy it has been challenging to detect early changes in brain activity that occurs prior to seizure onset and to map their origin and evolution for possible intervention. Besides, preclinical seizure experiments need to be conducted in awake animals with images reconstructed and displayed in real-time. We demonstrate using a rat model of generalized epilepsy that diffuse optical tomography (DOT) provides a unique functional neuroimaging modality for noninvasively and continuously tracking brain activities with high spatiotemporal resolution. We developed methods to conduct seizure experiments in fully awake rats using a subject-specific helmet and a restraining mechanism. For the first time, we detected early hemodynamic responses with heterogeneous patterns several minutes preceding the electroencephalographic seizure onset, supporting the presence of a "pre-seizure" state both in anesthetized and awake rats. Using a novel time-series analysis of scattering images, we show that the analysis of scattered diffuse light is a sensitive and reliable modality for detecting changes in neural activity associated with generalized seizure. We found widespread hemodynamic changes evolving from local regions of the bilateral cortex and thalamus to the entire brain, indicating that the onset of generalized seizures may originate locally rather than diffusely. Together, these findings suggest DOT represents a powerful tool for mapping early seizure onset and propagation pathways.
Phylogeny and species traits predict bird detectability

USGS Publications Warehouse

Solymos, Peter; Matsuoka, Steven M.; Stralberg, Diana; Barker, Nicole K. S.; Bayne, Erin M.

2018-01-01

Avian acoustic communication has resulted from evolutionary pressures and ecological constraints. We therefore expect that auditory detectability in birds might be predictable by species traits and phylogenetic relatedness. We evaluated the relationship between phylogeny, species traits, and field‐based estimates of the two processes that determine species detectability (singing rate and detection distance) for 141 bird species breeding in boreal North America. We used phylogenetic mixed models and cross‐validation to compare the relative merits of using trait data only, phylogeny only, or the combination of both to predict detectability. We found a strong phylogenetic signal in both singing rates and detection distances; however the strength of phylogenetic effects was less than expected under Brownian motion evolution. The evolution of behavioural traits that determine singing rates was found to be more labile, leaving more room for species to evolve independently, whereas detection distance was mostly determined by anatomy (i.e. body size) and thus the laws of physics. Our findings can help in disentangling how complex ecological and evolutionary mechanisms have shaped different aspects of detectability in boreal birds. Such information can greatly inform single‐ and multi‐species models but more work is required to better understand how to best correct possible biases in phylogenetic diversity and other community metrics.
Early detection of pancreatic cancer

PubMed Central

Ahuja, Nita

2015-01-01

Pancreatic adenocarcinoma is a low-incident but highly mortal disease. It accounts for only 3% of estimated new cancer cases each year but is currently the fourth common cause of cancer mortality. By 2030, it is expected to be the 2nd leading cause of cancer death. There is a clear need to diagnose and classify pancreatic cancer at earlier stages in order to give patients the best chance at a definitive cure through surgery. Three precursor lesions that distinctly lead to pancreatic adenocarcinoma have been identified, and we have increasing understanding the non-genetic and genetic risk factors for the disease. With increased understanding about the risk factors, the familial patters, and associated accumulation of genetic mutations involved in pancreatic cancer, we know that there are mutations that occur early in the development of pancreatic cancer and that improved genetic risk-based strategies in screening for pancreatic cancer may be possible and successful at saving or prolonging lives. The remaining challenge is that current standards for diagnosing pancreatic cancer remain too invasive and too costly for widespread screening for pancreatic cancer. Furthermore, the promises of noninvasive methods of detection such as blood, saliva, and stool remain underdeveloped or lack robust testing. However, significant progress has been made, and we are drawing closer to a strategy for the screening and early detection of pancreatic cancer. PMID:26361402
Predictive Trip Detection for Nuclear Power Plants

NASA Astrophysics Data System (ADS)

Rankin, Drew J.; Jiang, Jin

2016-08-01

This paper investigates the use of a Kalman filter (KF) to predict, within the shutdown system (SDS) of a nuclear power plant (NPP), whether safety parameter measurements have reached a trip set-point. In addition, least squares (LS) estimation compensates for prediction error due to system-model mismatch. The motivation behind predictive shutdown is to reduce the amount of time between the occurrence of a fault or failure and the time of trip detection, referred to as time-to-trip. These reductions in time-to-trip can ultimately lead to increases in safety and productivity margins. The proposed predictive SDS differs from conventional SDSs in that it compares point-predictions of the measurements, rather than sensor measurements, against trip set-points. The predictive SDS is validated through simulation and experiments for the steam generator water level safety parameter. Performance of the proposed predictive SDS is compared against benchmark conventional SDS with respect to time-to-trip. In addition, this paper analyzes: prediction uncertainty, as well as; the conditions under which it is possible to achieve reduced time-to-trip. Simulation results demonstrate that on average the predictive SDS reduces time-to-trip by an amount of time equal to the length of the prediction horizon and that the distribution of times-to-trip is approximately Gaussian. Experimental results reveal that a reduced time-to-trip can be achieved in a real-world system with unknown system-model mismatch and that the predictive SDS can be implemented with a scan time of under 100ms. Thus, this paper is a proof of concept for KF/LS-based predictive trip detection.
Nanotechnology-Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer

DTIC Science & Technology

2017-08-01

AWARD NUMBER: W81XWH-15-1-0157 TITLE: Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer PRINCIPAL...TITLE AND SUBTITLE Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer 5a. CONTRACT NUMBER 5b. GRANT NUMBER...identify novel differentially expressed miRNAs in the body fluids (blood, urine, etc.) for an early detection of PCa. Advances in nanotechnology and
Interactive-predictive detection of handwritten text blocks

NASA Astrophysics Data System (ADS)

Ramos Terrades, O.; Serrano, N.; Gordó, A.; Valveny, E.; Juan, A.

2010-01-01

A method for text block detection is introduced for old handwritten documents. The proposed method takes advantage of sequential book structure, taking into account layout information from pages previously transcribed. This glance at the past is used to predict the position of text blocks in the current page with the help of conventional layout analysis methods. The method is integrated into the GIDOC prototype: a first attempt to provide integrated support for interactive-predictive page layout analysis, text line detection and handwritten text transcription. Results are given in a transcription task on a 764-page Spanish manuscript from 1891.
Early Detection of Diabetic Retinopathy.

PubMed

Safi, Hamid; Safi, Sare; Hafezi-Moghadam, Ali; Ahmadieh, Hamid

2018-04-18

Diabetic retinopathy (DR) is a primary cause of visual impairment worldwide. Diabetes mellitus may be associated with ophthalmoscopically nonvisible neurovascular damage that progresses before the first clinical signs of DR appear. Reduction of the inner neuroretinal layer thickness on macular optical coherence tomography (OCT), reduced contrast sensitivity primarily at low spatial frequencies, abnormal results in color vision and microperimetry tests, and a prolonged implicit time recorded by multifocal electroretinography have been proposed for detection of early functional and nonvisible structural neuroretinal changes. Vascular abnormalities such as changes in the retinal vessels caliber, architectural indices, and blood flow have been investigated to evaluate the early stages of DR. The results of OCT angiography, retinal vessel oxygen saturation patterns, and elevated levels of circulating blood markers and cytokines have been suggested as early signs of DR. Light-based molecular imaging in rodents has been developed to demonstrate changes in protein expressions in the retinal microvessels as diagnostic biomarkers. Future clinical studies will examine the safety and efficacy of this approach in humans. We summarize all studies related to subclinical DR biomarkers. Copyright © 2018 Elsevier Inc. All rights reserved.
Early Oscillation Detection for DC/DC Converter Fault Diagnosis

NASA Technical Reports Server (NTRS)

Wang, Bright L.

2011-01-01

The electrical power system of a spacecraft plays a very critical role for space mission success. Such a modern power system may contain numerous hybrid DC/DC converters both inside the power system electronics (PSE) units and onboard most of the flight electronics modules. One of the faulty conditions for DC/DC converter that poses serious threats to mission safety is the random occurrence of oscillation related to inherent instability characteristics of the DC/DC converters and design deficiency of the power systems. To ensure the highest reliability of the power system, oscillations in any form shall be promptly detected during part level testing, system integration tests, flight health monitoring, and on-board fault diagnosis. The popular gain/phase margin analysis method is capable of predicting stability levels of DC/DC converters, but it is limited only to verification of designs and to part-level testing on some of the models. This method has to inject noise signals into the control loop circuitry as required, thus, interrupts the DC/DC converter's normal operation and increases risks of degrading and damaging the flight unit. A novel technique to detect oscillations at early stage for flight hybrid DC/DC converters was developed.
Kick Detection at the Bit: Early Detection via Low Cost Monitoring

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

Tost, Brian; Rose, Kelly; Aminzadeh, Fred

2016-06-07

Formation fluid influxes (i.e. kicks) pose persistent challenges and operational costs during drilling operations. Implications of kicks range in scale but cumulatively result in substantial costs that affect drilling safety, environment, schedule, and infrastructure. Early kick detection presents a low-cost, easily adopted solution for avoiding well control challenges associated with kicks near the bit. Borehole geophysical tools used during the drilling process as part of the logging-while-drilling (LWD) and measurement-while-drilling (MWD) provide the advantage of offering real-time downhole data. LWD/MWD collect data on both the annulus and borehole wall. The annular data are normally treated as background, and are filteredmore » out to isolate the formation measurements. Because kicks will change the local physical properties of annular fluids, bottom-hole measurements are among the first indicators that a formation fluid has invaded the wellbore. This report describes and validates a technique for using the annular portion of LWD/MWD data to facilitate early kick detection using first order principles. The detection technique leverages data from standard and cost-effective technologies that are typically implemented during well drilling, such as MWD/LWD data in combination with mud-pulse telemetry for data transmission.« less
Early Migration Predicts Aseptic Loosening of Cementless Femoral Stems: A Long-term Study.

PubMed

Streit, Marcus R; Haeussler, Daniel; Bruckner, Thomas; Proctor, Tanja; Innmann, Moritz M; Merle, Christian; Gotterbarm, Tobias; Weiss, Stefan

2016-07-01

observers. Patients with a diagnosis of prosthetic joint infection were excluded. Receiver operating characteristic (ROC) curve analysis was used to evaluate diagnostic performance of axial stem migration 1, 2, 3, and 4 years postoperatively as a predictor of aseptic loosening. Survivorship of hips with high (≥ 2.7 mm) and low (< 2.7 mm) migration was compared using a competing-events analysis. Femoral components that had aseptic loosening develop showed greater mean distal migration at 24 months postoperatively than did components that remained well fixed throughout the surveillance period (4.2 mm ± 3.1 mm vs 0.8 mm ± 0.9 mm; mean difference, 3.4 mm, 95% CI, 2.5-4.4; p ≤ 0.001). Distal migration at 24 months postoperatively was a strong risk factor for aseptic loosening (hazard ratio, 1.98; 95% CI, 1.51-2.57; p < 0.001). The associated overall diagnostic performance of 2-year distal migration for predicting aseptic loosening was good (area under the ROC curve, 0.86; 95% CI, 0.72-1.00; p < 0.001). Sensitivity of early migration measurement was high for the prediction of aseptic loosening during the first decade after surgery but decreased markedly thereafter. Stems with large amounts of early migration (≥ 2.7 mm) had lower 18-year survivorship than did stems with little early migration (29% [95% CI, 0%-62%] versus 95% [95% CI, 90%-100%] p < 0.001). Early migration, as measured by EBRA-FCA at 2 years postoperatively, has good diagnostic capabilities for detection of uncemented femoral components at risk for aseptic loosening during the first and early second decades after surgery. However, there was no relationship between early migration patterns and aseptic loosening during the late second and third decades. EBRA-FCA can be used as a research tool to evaluate new cementless stems or in clinical practice to evaluate migration patterns in patients with painful femoral components. Level III, diagnostic study.
Simple Mathematical Models Do Not Accurately Predict Early SIV Dynamics

PubMed Central

Noecker, Cecilia; Schaefer, Krista; Zaccheo, Kelly; Yang, Yiding; Day, Judy; Ganusov, Vitaly V.

2015-01-01

Upon infection of a new host, human immunodeficiency virus (HIV) replicates in the mucosal tissues and is generally undetectable in circulation for 1–2 weeks post-infection. Several interventions against HIV including vaccines and antiretroviral prophylaxis target virus replication at this earliest stage of infection. Mathematical models have been used to understand how HIV spreads from mucosal tissues systemically and what impact vaccination and/or antiretroviral prophylaxis has on viral eradication. Because predictions of such models have been rarely compared to experimental data, it remains unclear which processes included in these models are critical for predicting early HIV dynamics. Here we modified the “standard” mathematical model of HIV infection to include two populations of infected cells: cells that are actively producing the virus and cells that are transitioning into virus production mode. We evaluated the effects of several poorly known parameters on infection outcomes in this model and compared model predictions to experimental data on infection of non-human primates with variable doses of simian immunodifficiency virus (SIV). First, we found that the mode of virus production by infected cells (budding vs. bursting) has a minimal impact on the early virus dynamics for a wide range of model parameters, as long as the parameters are constrained to provide the observed rate of SIV load increase in the blood of infected animals. Interestingly and in contrast with previous results, we found that the bursting mode of virus production generally results in a higher probability of viral extinction than the budding mode of virus production. Second, this mathematical model was not able to accurately describe the change in experimentally determined probability of host infection with increasing viral doses. Third and finally, the model was also unable to accurately explain the decline in the time to virus detection with increasing viral dose. These results
The impact of caregivers on the effectiveness of an early community mental health detection and intervention programme in Hong Kong.

PubMed

Pan, Jia-Yan; Ng, Yat-Nam Petrus; Young, Kim-Wan Daniel

2016-12-01

The prevalence rate of mental illness in Chinese communities is high, but Chinese clients tend to underutilize mental health services. Caregivers may play an important role in mental health early detection and intervention, but few studies have investigated their roles in community mental health services. This study compared the effectiveness of an early detection and intervention programme, the Community Mental Health Intervention Project, for two groups in the context of Hong Kong - clients with and without caregivers. A comparison group pre-post-test design was adopted. A total of 170 service users joined this study, including 100 with caregivers and 70 without caregivers. Both groups showed a significant decrease in psychiatric symptoms and increase in community living skills; the group without caregivers indicated a greater reduction in psychiatric symptoms. Different social work intervention components had different predictive effects on these changes. The Community Mental Health Intervention Project is an effective early detection and intervention programme in working with Hong Kong Chinese people who are suspected of having mental health problems, especially for those without caregivers. © 2014 Wiley Publishing Asia Pty Ltd.
Life Detection on the Early Earth

NASA Technical Reports Server (NTRS)

Runnegar, B.

2004-01-01

Finding evidence for first the existence, and then the nature of life on the early Earth or early Mars requires both the recognition of subtle biosignatures and the elimination of false positives. The history of the search for fossils in increasingly older Precambrian strata illustrates these difficulties very clearly, and new observational and theoretical approaches are both needed and being developed. At the microscopic level of investigation, three-dimensional morphological characterization coupled with in situ chemical (isotopic, elemental, structural) analysis is the desirable first step. Geological context is paramount, as has been demonstrated by the controversies over AH84001, the Greenland graphites, and the Apex chert microfossils . At larger scales, the nature of sedimentary bedforms and the structures they display becomes crucial, and here the methods of condensed matter physics prove most useful in discriminating between biological and non-biological constructions. Ultimately, a combination of geochemical, morphological, and contextural evidence may be required for certain life detection on the early Earth or elsewhere.
MicroRNAs as biomarkers for early breast cancer diagnosis, prognosis and therapy prediction.

PubMed

Nassar, Farah J; Nasr, Rihab; Talhouk, Rabih

2017-04-01

Breast cancer is a major health problem that affects one in eight women worldwide. As such, detecting breast cancer at an early stage anticipates better disease outcome and prolonged patient survival. Extensive research has shown that microRNA (miRNA) are dysregulated at all stages of breast cancer. miRNA are a class of small noncoding RNA molecules that can modulate gene expression and are easily accessible and quantifiable. This review highlights miRNA as diagnostic, prognostic and therapy predictive biomarkers for early breast cancer with an emphasis on the latter. It also examines the challenges that lie ahead in their use as biomarkers. Noteworthy, this review addresses miRNAs reported in patients with early breast cancer prior to chemotherapy, radiotherapy, surgical procedures or distant metastasis (unless indicated otherwise). In this context, miRNA that are mentioned in this review were significantly modulated using more than one statistical test and/or validated by at least two studies. A standardized protocol for miRNA assessment is proposed starting from sample collection to data analysis that ensures comparative analysis of data and reproducibility of results. Copyright © 2016 Elsevier Inc. All rights reserved.
Detection of early caries by laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Sasazawa, Shuhei; Kakino, Satoko; Matsuura, Yuji

2015-07-01

To improve sensitivity of dental caries detection by laser-induced breakdown spectroscopy (LIBS) analysis, it is proposed to utilize emission peaks in the ultraviolet. We newly focused on zinc whose emission peaks exist in ultraviolet because zinc exists at high concentration in the outer layer of enamel. It was shown that by using ratios between heights of an emission peak of Zn and that of Ca, the detection sensitivity and stability are largely improved. It was also shown that early caries are differentiated from healthy part by properly setting a threshold in the detected ratios. The proposed caries detection system can be applied to dental laser systems such as ones based on Er:YAG-lasers. When ablating early caries part by laser light, the system notices the dentist that the ablation of caries part is finished. We also show the intensity of emission peaks of zinc decreased with ablation with Er:YAG laser light.
Progress towards an AIS early detection monitoring network for the Great Lakes

EPA Science Inventory

As an invasion prone location, the lower St. Louis River system (SLR) has been a case study for ongoing research to develop the framework for a practical Great Lakes monitoring network for early detection of aquatic invasive species (AIS). Early detection, however, necessitates f...
A Novel Early Pregnancy Risk Prediction Model for Gestational Diabetes Mellitus.

PubMed

Sweeting, Arianne N; Wong, Jencia; Appelblom, Heidi; Ross, Glynis P; Kouru, Heikki; Williams, Paul F; Sairanen, Mikko; Hyett, Jon A

2018-06-13

Accurate early risk prediction for gestational diabetes mellitus (GDM) would target intervention and prevention in women at the highest risk. We evaluated novel biomarker predictors to develop a first-trimester risk prediction model in a large multiethnic cohort. Maternal clinical, aneuploidy and pre-eclampsia screening markers (PAPP-A, free hCGβ, mean arterial pressure, uterine artery pulsatility index) were measured prospectively at 11-13+6 weeks' gestation in 980 women (248 with GDM; 732 controls). Nonfasting glucose, lipids, adiponectin, leptin, lipocalin-2, and plasminogen activator inhibitor-2 were measured on banked serum. The relationship between marker multiples-of-the-median and GDM was examined with multivariate regression. Model predictive performance for early (< 24 weeks' gestation) and overall GDM diagnosis was evaluated by receiver operating characteristic curves. Glucose, triglycerides, leptin, and lipocalin-2 were higher, while adiponectin was lower, in GDM (p < 0.05). Lipocalin-2 performed best in Caucasians, and triglycerides in South Asians with GDM. Family history of diabetes, previous GDM, South/East Asian ethnicity, parity, BMI, PAPP-A, triglycerides, and lipocalin-2 were significant independent GDM predictors (all p < 0.01), achieving an area under the curve of 0.91 (95% confidence interval [CI] 0.89-0.94) overall, and 0.93 (95% CI 0.89-0.96) for early GDM, in a combined multivariate prediction model. A first-trimester risk prediction model, which incorporates novel maternal lipid markers, accurately identifies women at high risk of GDM, including early GDM. © 2018 S. Karger AG, Basel.
Predicting School Performance with the Early Screening Inventory.

ERIC Educational Resources Information Center

Meisels, Samuel J.; And Others

1984-01-01

Proposes criteria for defining and selecting preschool developmental screening instruments and describes the Early Screening Inventory (ESI), a developmental screening instrument designed to satisfy these criteria. Presents results of several studies demonstrating that the ESI predicts school performance with moderate to excellent accuracy through…
Prevention and Early Detection of Prostate Cancer

PubMed Central

Cuzick, Jack; Thorat, Mangesh A.; Andriole, Gerald; Brawley, Otis W.; Brown, Powel H.; Culig, Zoran; Eeles, Rosalind A.; Ford, Leslie G.; Hamdy, Freddie C.; Holmberg, Lars; Ilic, Dragan; Key, Timothy J.; La Vecchia, Carlo; Lilja, Hans; Marberger, Michael; Meyskens, Frank L.; Minasian, Lori M.; Parker, Chris; Parnes, Howard L.; Perner, Sven; Rittenhouse, Harry; Schalken, Jack; Schmid, Hans-Peter; Schmitz-Dräger, Bernd J.; Schröder, Fritz H.; Stenzl, Arnulf; Tombal, Bertrand; Wilt, Timothy J.; Wolk, Alicja

2014-01-01

Prostate cancer is one of the most common cancers in men and the global burden of this disease is rising. Lifestyle modifications like smoking cessation, exercise and weight control offer opportunities to decrease the risk of developing prostate cancer. Early detection of prostate cancer by PSA screening remains controversial; yet, changes in PSA threshold, frequency of screening, and addition of other biomarkers have potential to minimise overdiagnosis associated with PSA screening. Several new biomarkers appear promising in individuals with elevated PSA levels or those diagnosed with prostate cancer, these are likely to guide in separating individuals who can be spared of aggressive treatment from those who need it. Several pharmacological agents like 5α-reductase inhibitors, aspirin etc. have a potential to prevent development of prostate cancer. In this review, we discuss the current evidence and research questions regarding prevention, early detection of prostate cancer and management of men either at high risk of prostate cancer or diagnosed with low-grade prostate cancer. PMID:25281467
Early detection of poor adherers to statins: applying individualized surveillance to pay for performance.

PubMed

Zimolzak, Andrew J; Spettell, Claire M; Fernandes, Joaquim; Fusaro, Vincent A; Palmer, Nathan P; Saria, Suchi; Kohane, Isaac S; Jonikas, Magdalena A; Mandl, Kenneth D

2013-01-01

Medication nonadherence costs $300 billion annually in the US. Medicare Advantage plans have a financial incentive to increase medication adherence among members because the Centers for Medicare and Medicaid Services (CMS) now awards substantive bonus payments to such plans, based in part on population adherence to chronic medications. We sought to build an individualized surveillance model that detects early which beneficiaries will fall below the CMS adherence threshold. This was a retrospective study of over 210,000 beneficiaries initiating statins, in a database of private insurance claims, from 2008-2011. A logistic regression model was constructed to use statin adherence from initiation to day 90 to predict beneficiaries who would not meet the CMS measure of proportion of days covered 0.8 or above, from day 91 to 365. The model controlled for 15 additional characteristics. In a sensitivity analysis, we varied the number of days of adherence data used for prediction. Lower adherence in the first 90 days was the strongest predictor of one-year nonadherence, with an odds ratio of 25.0 (95% confidence interval 23.7-26.5) for poor adherence at one year. The model had an area under the receiver operating characteristic curve of 0.80. Sensitivity analysis revealed that predictions of comparable accuracy could be made only 40 days after statin initiation. When members with 30-day supplies for their first statin fill had predictions made at 40 days, and members with 90-day supplies for their first fill had predictions made at 100 days, poor adherence could be predicted with 86% positive predictive value. To preserve their Medicare Star ratings, plan managers should identify or develop effective programs to improve adherence. An individualized surveillance approach can be used to target members who would most benefit, recognizing the tradeoff between improved model performance over time and the advantage of earlier detection.

Helicopter main-rotor speed effects: A comparison of predicted ranges of detection from the aural detection program ICHIN and the electronic detection program ARCAS

NASA Technical Reports Server (NTRS)

Mueller, Arnold W.; Smith, Charles D.

1991-01-01

NASA LaRC personnel have conducted a strudy of the predicted acoustic detection ranges associated with reduced helicopter main rotor speeds. This was accomplished by providing identical input information to both the aural detection program ICHIN 6, (I Can Hear It Now, version 6) and the electronic acoustic detection program ARCAS (Assessment of Rotorcraft Detection by Acoustics Sensing). In this study, it was concluded that reducing the main rotor speed of the helicopter by 27 percent reduced both the predicted aural and electronic detection ranges by approximately 50 percent. Additionally, ARCAS was observed to function better with narrowband spectral input than with one-third octave band spectral inputs and the predicted electronic range of acoustic detection is greater than the predicted aural detection range.
[Sentinel node detection in early stage of cervical carcinoma using 99mTc-nanocolloid and blue dye].

PubMed

Sevcík, L; Klát, J; Gráf, P; Koliba, P; Curík, R; Kraft, O

2007-04-01

The aim of the study was to analyse the feasibility of intraoperative sentinel lymph nodes (SLN) detection using gamma detection probe and blue dye in patients undergoing radical hysterectomy for treatment of early stage of cervical cancer. Prospective case observational study. In the period from May 2004 to February 2006 77 patients with early stage of cervical cancer who underwent a radical surgery were included into the study. Patients were divided into three groups according to the tumour volume. First group consists of patients FIGO IA2 and FIGO IB1 with tumour diameter less than 2 cm, second group tumours FIGO IB1 with tumour diameter more than 2 cm and third group stadium IB2. SLN was detected by blue dye and Tc99. Preoperative lymphoscintigraphy was done after Tc99 colloid injection, intraoperative detection was performed by visual observation and by hand-held gamma-detection probe. SLN were histologically and immunohistochemically analysed. A total number of 2764 lymph nodes with an average 36 and 202 SLN with an average 2.6 were identified. The SLN detection rate was 94.8% per patient and 85.1% for the side of dissection and depends on the tumor volume. SLN were identified in obturator area in 48%, in external iliac area in 15%, in common iliac and internal iliac both in 9%, in interiliac region in 8%, in praesacral region in 6% and in parametrial area in 5%. Metastatic disease was detected in 31 patients (40.2%), metastatic involvement of SLN only in 12 patients (15.6%). False negative rate was 2.6%, sensitivity and negative predictive value calculated by patient were 923% and 95.7%. Intraoperative lymphatic mapping using combination of technecium-99-labeled nanocolloid and blue dye are feasible, safe and accurate techniques to identified SLN in early stage of cervical cancer.
Mortality in children with early detected congenital central hypothyroidism.

PubMed

Zwaveling-Soonawala, Nitash; Naafs, Jolanda C; Verkerk, Paul H; van Trotsenburg, A S Paul

2018-06-07

Approximately 60-80% of patients with congenital central hypothyroidism (CH-C) have multiple pituitary hormone deficiencies (MPHD), making CH-C a potentially life-threatening disease. Data on mortality in CH-C patients, however, are lacking. To study mortality rate in early detected and treated pediatric CH-C patients in the Netherlands and to investigate whether causes of death were related to pituitary hormone deficiencies. Overall mortality rate, infant mortality rate and under-5 mortality rate were calculated in all children with CH-C detected by neonatal screening between 1-1-1995 and 1-1-2013. Medical charts were reviewed to establish causes of death. 139 children with CH-C were identified, of which 138 could be traced (82 MPHD/56 isolated CHC). Total observation time was 1414 years with a median follow up duration of 10.2 years. The overall mortality rate was 10.9% (15/138). Infant mortality rate (IMR) and under-5 mortality rate were 65.2/1000 (9/138) and 101.4/1000 (14/138), respectively, compared to an IMR of 4.7/1000 and under-5 mortality of 5.4/1000 live born children in the Netherlands during the same time period (p<0.0001). Main causes of death were severe congenital malformations in six patients, asphyxia in two patients, and congenital or early neonatal infection in two patients. Pituitary hormone deficiency was noted as cause of death in only one infant. We report an increased mortality rate in early detected CH-C patients which does not seem to be related to endocrine disease. This suggests that mortality due to pituitary insufficiency is low in an early detected and treated CH-C population.
Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry

PubMed Central

Kawana, Shuichi; Unno, Yumi; Sakai, Takero; Okamoto, Koji; Yamada, Yasuhide; Sudo, Kazuki; Yamaji, Taiki; Saito, Yutaka; Kanemitsu, Yukihide; Okita, Natsuko Tsuda; Saito, Hiroshi; Tsugane, Shoichiro; Azuma, Takeshi; Ojima, Noriyuki; Yoshida, Masaru

2017-01-01

In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N=79), I (N=80), and II (N=123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis. PMID:28179577
Investigations in the possibility of early detection of colorectal cancer by gas chromatography/triple-quadrupole mass spectrometry.

PubMed

Nishiumi, Shin; Kobayashi, Takashi; Kawana, Shuichi; Unno, Yumi; Sakai, Takero; Okamoto, Koji; Yamada, Yasuhide; Sudo, Kazuki; Yamaji, Taiki; Saito, Yutaka; Kanemitsu, Yukihide; Okita, Natsuko Tsuda; Saito, Hiroshi; Tsugane, Shoichiro; Azuma, Takeshi; Ojima, Noriyuki; Yoshida, Masaru

2017-03-07

In developed countries, the number of patients with colorectal cancer has been increasing, and colorectal cancer is one of the most common causes of cancer death. To improve the quality of life of colorectal cancer patients, it is necessary to establish novel screening methods that would allow early detection of colorectal cancer. We performed metabolome analysis of a plasma sample set from 282 stage 0/I/II colorectal cancer patients and 291 healthy volunteers using gas chromatography/triple-quadrupole mass spectrometry in an attempt to identify metabolite biomarkers of stage 0/I/II colorectal cancer. The colorectal cancer patients included patients with stage 0 (N=79), I (N=80), and II (N=123) in whom invasion and metastasis were absent. Our analytical system detected 64 metabolites in the plasma samples, and the levels of 29 metabolites differed significantly (Bonferroni-corrected p=0.000781) between the patients and healthy volunteers. Based on these results, a multiple logistic regression analysis of various metabolite biomarkers was carried out, and a stage 0/I/II colorectal cancer prediction model was established. The area under the curve, sensitivity, and specificity values of this model for detecting stage 0/I/II colorectal cancer were 0.996, 99.3%, and 93.8%, respectively. The model's sensitivity and specificity values for each disease stage were >90%, and surprisingly, its sensitivity for stage 0, specificity for stage 0, and sensitivity for stage II disease were all 100%. Our predictive model can aid early detection of colorectal cancer and has potential as a novel screening test for cases of colorectal cancer that do not involve lymph node or distant metastasis.
All-optical photoacoustic imaging and detection of early-stage dental caries

NASA Astrophysics Data System (ADS)

Sampathkumar, Ashwin; Hughes, David A.; Longbottom, Chris; Kirk, Katherine J.

2015-02-01

Dental caries remain one of the most common oral diseases in the world. Current detection methods, such as dental explorer and X-ray radiography, suffer from poor sensitivity and specificity at the earliest (and reversible) stages of the disease because of the small size (< 100 microns) of early-stage lesions. We have developed a fine-resolution (480 nm), ultra-broadband (1 GHz), all-optical photoacoustic imaging (AOPAI) system to image and detect early stages of tooth decay. This AOPAI system provides a non-contact, non-invasive and non-ionizing means of detecting early-stage dental caries. Ex-vivo teeth exhibiting early-stage, white-spot lesions were imaged using AOPAI. Experimental scans targeted each early-stage lesion and a reference healthy enamel region. Photoacoustic (PA) signals were generated in the tooth using a 532-nm pulsed laser and the light-induced broadband ultrasound signal was detected at the surface of the tooth with an optical path-stabilized Michelson interferometer operating at 532 nm. The measured time-domain signal was spatially resolved and back-projected to form 2D and 3D maps of the lesion using k-wave reconstruction methods. Experimental data collected from areas of healthy and diseased enamel indicate that the lesion generated a larger PA response compared to healthy enamel. The PA-signal amplitude alone was able to detect a lesion on the surface of the tooth. However, time- reversal reconstructions of the PA scans also quantitatively depicted the depth of the lesion. 3D PA reconstruction of the diseased tooth indicated a sub-surface lesion at a depth of 0.6 mm, in addition to the surface lesion. These results suggest that our AOPAI system is well suited for rapid clinical assessment of early-stage dental caries. An overview of the AOPAI system, fine-resolution PA and histology results of diseased and healthy teeth will be presented.
Lack of Early Improvement Predicts Poor Outcome Following Acute Intracerebral Hemorrhage.

PubMed

Yogendrakumar, Vignan; Smith, Eric E; Demchuk, Andrew M; Aviv, Richard I; Rodriguez-Luna, David; Molina, Carlos A; Silva Blas, Yolanda; Dzialowski, Imanuel; Kobayashi, Adam; Boulanger, Jean-Martin; Lum, Cheemun; Gubitz, Gord; Padma, Vasantha; Roy, Jayanta; Kase, Carlos S; Bhatia, Rohit; Ali, Myzoon; Lyden, Patrick; Hill, Michael D; Dowlatshahi, Dar

2018-04-01

There are limited data as to what degree of early neurologic change best relates to outcome in acute intracerebral hemorrhage. We aimed to derive and validate a threshold for early postintracerebral hemorrhage change that best predicts 90-day outcomes. Derivation: retrospective analysis of collated clinical stroke trial data (Virtual International Stroke Trials Archive). retrospective analysis of a prospective multicenter cohort study (Prediction of haematoma growth and outcome in patients with intracerebral haemorrhage using the CT-angiography spot sign [PREDICT]). Neurocritical and ICUs. Patients with acute intracerebral hemorrhage presenting less than 6 hours. Derivation: 552 patients; validation: 275 patients. None. We generated a receiver operating characteristic curve for the association between 24-hour National Institutes of Health Stroke Scale change and clinical outcome. The primary outcome was a modified Rankin Scale score of 4-6 at 90 days; secondary outcomes were other modified Rankin Scale score ranges (modified Rankin Scale, 2-6, 3-6, 5-6, 6). We employed Youden's J Index to select optimal cut points and calculated sensitivity, specificity, and predictive values. We determined independent predictors via multivariable logistic regression. The derived definitions were validated in the PREDICT cohort. Twenty-four-hour National Institutes of Health Stroke Scale change was strongly associated with 90-day outcome with an area under the receiver operating characteristic curve of 0.75. Youden's method showed an optimum cut point at -0.5, corresponding to National Institutes of Health Stroke Scale change of greater than or equal to 0 (a lack of clinical improvement), which was seen in 46%. Early neurologic change accurately predicted poor outcome when defined as greater than or equal to 0 (sensitivity, 65%; specificity, 73%; positive predictive value, 70%; adjusted odds ratio, 5.05 [CI, 3.25-7.85]) or greater than or equal to 4 (sensitivity, 19%; specificity
Beauty, charm, and F{sub L} at HERA: New data vs. Early predictions

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

Nikolaev, N. N.; Zoller, V. R., E-mail: zoller@itep.r

One of the well-known effects of the asymptotic freedom is splitting of the leading-log BFKL pomeron into a series of isolated poles in complex angular momentum plane. Following our earlier works we explore the phenomenological consequences of the emerging BFKL-Regge factorized expansion for the small-x charm (F{sub 2}{sup c}) and beauty (F{sub 2}{sup b}) structure functions of the proton. As we found earlier, the colordipole approach to the BFKL dynamics predicts uniquely decoupling of subleading hard BFKL exchanges from F{sub 2}{sup c} at moderately large Q{sup 2}. We predicted precocious BFKL asymptotics of F{sub 2}{sup c} (x,Q{sup 2}) with interceptmore » of the rightmost BFKL pole {alpha}{sub P}(0) - 1 = {Delta}{sub P} {approx} 0.4. High-energy open beauty photo- and electroproduction probes the vacuum exchange at much smaller distances and detects significant corrections to the BFKL asymptotics coming from the subleading vacuum poles. In view of the accumulation of the experimental data on small -xF{sub 2}{sup c} and F{sub 2}{sup b} we extended our early predictions to the kinematical domain covered by new HERA measurements. Our structure functions obtained in 1999 agree well with the determination of both F{sub 2}{sup c} and F{sub 2}{sup b} by the H1 published in 2006 but contradict very recent (2008, preliminary)H1 results on F{sub 2}{sup b}. We present also comparison of our early predictions for the longitudinal structure function F{sub L} with recent H1 data (2008) taken at very low Bjorken x. We comment on the electromagnetic corrections to the Okun-Pomeranchuk theorem.« less
Potential Landslide Early Detection Near Wenchuan by a Qualitatively Multi-Baseline Dinsar Method

NASA Astrophysics Data System (ADS)

Dai, K.; Chen, G.; Xu, Q.; Li, Z.; Qu, T.; Hu, L.; Lu, H.

2018-04-01

Early detection of landslides is important for disaster prevention, which was still very hard work with traditional surveying methods. Interferometric Synthetic Aperture Radar (InSAR) technology provided us the ability to monitor displacements along the slope with wide coverage and high accuracy. In this paper, we proposed a qualitatively multi-baseline DInSAR method to early detect and map the potential landslides. Two sections of China National Highway 317 and 213 were selected as study area. With this method 10 potential landslide areas were early detected and mapped in a quick and effective way. One of them (i.e. Shidaguan landslide) collapsed on August 2017, which was coincident with our results, suggesting that this method could become an effective way to acquire the landslide early detection map to assist the future disaster prevention work.
Wheat: Its water use, production and disease detection and prediction. [Kansas

NASA Technical Reports Server (NTRS)

Kanemasu, E. T. (Principal Investigator); Lenhert, D.; Niblett, C.; Manges, H.; Eversmeyer, M. G.

1974-01-01

The author has identified the following significant results. Discussed in this report are: (1) the effects of wheat disease on water use and yield; and (2) the use of ERTS-1 imagery in the evaluation of wheat growth and in the detection of disease severity. Leaf area index was linearly correlated with ratios MSS4:MSS5 and MSS5:MSS6. In an area of severe wheat streak mosaic virus infected fields, correlations of ERTS-1 digital counts with wheat yields and disease severity levels were significant at the 5% level for MSS bands 4 and 5 and band ratios 4/6 and 4/7. Data collection platforms were used to gather meteorological data for the early prediction of rust severity and economic loss.
Early Detection of Child Abuse

PubMed Central

Shearman, J.K.

1987-01-01

Child abuse, neglect and deprivation are more common than was previously thought. Family physicians are in a unique position to help abusers and abused because of their knowledge of patients from the cradle to the grave. They should use this knowledge to observe clues about parenting potential and should make a thorough family history a routine part of history taking in potential parents. They should also observe patients carefully during pregnancy and early childhood to detect parenting problems and to try to prevent all types of abuse, physical, mental and sexual. PMID:21267341
Early Numeracy Indicators: Examining Predictive Utility Across Years and States

ERIC Educational Resources Information Center

Conoyer, Sarah J.; Foegen, Anne; Lembke, Erica S.

2016-01-01

Two studies using similar methods in two states investigated the long-term predictive utility of two single-skill early numeracy Curriculum Based Measures (CBMs) and the degree to which they can adequately predict high-stakes test scores. Data were drawn from kindergarten and first-grade students. State standardized assessment data from the…
Early detection monitoring of Phytophthora ramorum in high-risk forests of California

Treesearch

Ross Meentemeyer; Elizabeth Lotz; David M. Rizzo; Kelly Buja; Walter Mark

2006-01-01

Early detection monitoring is essential for successful control of invasive organisms. Detection of invasions at an early stage of establishment when a population is small and isolated makes eradication more feasible and less costly. Sudden oak death, caused by the recently described pathogen Phytophthora ramorum, is an emerging forest disease that...
Predictivity of Early Depressive Symptoms for Post-Stroke Depression.

PubMed

Lewin-Richter, A; Volz, M; Jöbges, M; Werheid, K

2015-08-01

Depression is a frequent complication after stroke. However, little is known about the predictive value of early self-reported depressive symptoms (DS) for later development of post-stroke depression (PSD) 6 months after discharge. Using a prospective longitudinal design, we investigated the prevalence of DS and examined their predictive value for depressive disorders 6 months after stroke while statistically controlling major established PSD risk factors. During inpatient rehabilitation, 96 stroke patients were screened for DS. After 6 months, 71 patients were attainable for a follow-up. DS was assessed using the 15-item Geriatric Depression Scale (GDS-15). At follow-up a telephone interview that included the Structured Clinical Interview for Psychiatric Disorders (SCID), which is based on DSM-IV criteria, and the GDS-15 was conducted. Patients with major depression (MD) at the follow-up were considered to have PSD. Regression analyses were conducted to examine the influence of early DS on PSD after 6 months while controlling for age, premorbid depression, and functional and cognitive impairments. The percentage of patients who scored above the GDS-15 cut-off for clinically relevant DS increased significantly, from 37% to 44%, after 6 months. According to the SCID, 27% of stroke patients fulfilled the criteria for MD, and another 16% fulfilled those for minor depression. Logistic regression showed that DS at baseline significantly predicted PSD at follow-up (odds ratio: 1.43; 95% CI: 1.15-1.8). Self-reported DS during inpatient rehabilitation are predictive for PSD 6 months after discharge. Assessment of early DS contributes to identifying stroke patients at risk for PSD, thereby facilitating prevention and treatment.
Toward a clinically useful method of predicting early breast-feeding attrition.

PubMed

Lewallen, Lynne Porter; Dick, Margaret J; Wall, Yolanda; Zickefoose, Kimberly Taylor; Hannah, Susan Hensley; Flowers, Janet; Powell, Wanda

2006-08-01

The overall purpose of this study was to revise and test an instrument to identify, during the early postpartum period, women at risk for early breast-feeding attrition. This study was completed in two phases: the first phase tested a revision of the Breast-Feeding Attrition Prediction Tool (BAPT); the second, a new instrument, the Breast-Feeding Attitude Scale (BrAS), which was adapted from the BAPT. The two phases of this study involved 415 pregnant and postpartum women. Women answered questions either by phone (pregnant women) or in their hospital rooms after delivery (postpartum women). Data were analyzed using t tests and reliability analysis. The BAPT did not predict early breast-feeding attrition; however, the BrAS did differentiate between the attitudes of breast-feeding women and those of formula-feeding women and had adequate reliability. Women at risk for early breast-feeding attrition should be identified early so nursing interventions can be directed toward preventing early unintended weaning. Although the BrAS did not reliably identify women at risk in this sample, it did highlight important differences between breast-feeding and formula-feeding women that can be used in designing preconceptional or prenatal educational assessments and interventions.
Early Detection of Human Focal Seizures Based on Cortical Multiunit Activity

PubMed Central

Park, Yun S.; Hochberg, Leigh R.; Eskandar, Emad N.; Cash, Sydney S.; Truccolo, Wilson

2014-01-01

Approximately 50 million people in the world suffer from epileptic seizures. Reliable early seizure detection could bring significantly beneficial therapeutic alternatives. In recent decades, most approaches have relied on scalp EEG and intracranial EEG signals, but practical early detection for closed-loop seizure control remains challenging. In this study, we present preliminary analyses of an early detection approach based on intracortical neuronal multiunit activity (MUA) recorded from a 96-microelectrode array (MEA). The approach consists of (1) MUA detection from broadband field potentials recorded at 30 kHz by the MEA; (2) MUA feature extraction; (3) cost-sensitive support vector machine classification of ictal and interictal samples; and (4) Kalman-filtering postprocessing. MUA was here defined as the number of threshold crossing (spike counts) applied to the 300 Hz – 6 kHz bandpass filtered local field potentials in 0.1 sec time windows. MUA features explored in this study included the mean, variance, and Fano-factor, computed across the MEA channels. In addition, we used the leading eigenvalues of MUA spatial and temporal correlation matrices computed in 1-sec moving time windows. We assessed the seizure detection approach on out-of-sample data from one-participant recordings with six seizure events and 4.73-hour interictal data. The proposed MUA-based detection approach yielded a 100% sensitivity (6/6) and no false positives, and a latency of 4.17 ± 2.27 sec (mean ± SD) with respect to ECoG-identified seizure onsets. These preliminary results indicate intracortical MUA may be a useful signal for early detection of human epileptic seizures. PMID:25571313
Circulating microRNA-22-3p Predicts the Malignant Progression of Precancerous Gastric Lesions from Intestinal Metaplasia to Early Adenocarcinoma.

PubMed

Chen, Tsung-Hsing; Chiu, Cheng-Tang; Lee, Chieh; Chu, Yin-Yi; Cheng, Hao-Tsai; Hsu, Jun-Te; Wu, Ren-Chin; Yeh, Ta-Sen; Lin, Kwang-Huei

2018-05-07

Gastric cancer has a poor outcome and identifying useful biomarkers from peripheral blood or tissue could allow its early detection, or potentially precancerous changes, thus improving the curative rates. MicroRNAs (miRNAs) have been shown to offer great potential in cancer diagnosis and prediction. Here, we investigated the role of plasma miRNAs in the natural course of gastric cancer, from intestinal metaplasia to early cancer. The findings were used to understand whether patients at a high risk of malignancy could be given appropriate interventions in the early disease process, such as using endoscopic submucosal dissection to treat gastric dysplasia or early gastric cancer. Participants were divided into healthy control, intestinal metaplasia (IM), and dysplasia/early cancer (pT1a/b) groups. Microarray was used to select potential markers in tissue. Quantitative real-time polymerase chain reaction data showed circulating miRNA-22-3p had significantly different expression in patients with precancerous lesions or gastric adenocarcinoma. The areas under the curve of incomplete IM versus healthy control, low-grade/high-grade dysplasia, early gastric cancer, and GED were 0.8080, 0.8040, 0.8494, and 0.8095, respectively (all P values < 0.05). Circulating miRNA-22-3p could be a potential biomarker for gastric precancerous dysplasia and early cancer detection.
Prediction of early and late preeclampsia by flow-mediated dilation of the brachial artery*

PubMed Central

Brandão, Augusto Henriques Fulgêncio; Evangelista, Aline Aarão; Martins, Raphaela Menin Franco; Leite, Henrique Vítor; Cabral, Antônio Carlos Vieira

2014-01-01

Objective To assess the accuracy in the prediction of both early and late preeclampsia by flow-mediated dilation of the brachial artery (FMD), a biophysical marker for endothelial dysfunction. Materials and Methods A total of 91 patients, considered at high risk for development of preeclampsia were submitted to brachial artery FMD between 24 and 28 weeks of gestation. Results Nineteen out of the selected patients developed preeclampsia, 8 in its early form and 11 in the late form. With a cut-off value of 6.5%, the FMD sensitivity for early preeclampsia prediction was 75.0%, with specificity of 73.3%, positive predictive value (PPV) of 32.4% and negative predictive value (NPV) of 91.9%. For the prediction of late preeclampsia, sensitivity = 83.3%, specificity = 73.2%, PPV = 34.4% and NPV = 96.2% were observed. And for the prediction of all associated forms of preeclampsia, sensitivity = 84.2%, specificity = 73.6%, PPV = 45.7% and NPV = 94.6% were observed. Conclusion FMD of the brachial artery is a test with good accuracy in the prediction of both early and late preeclampsia, which may represent a positive impact on the follow-up of pregnant women at high risk for developing this syndrome. PMID:25741086
Using Peer Injunctive Norms to Predict Early Adolescent Cigarette Smoking Intentions

PubMed Central

Zaleski, Adam C.; Aloise-Young, Patricia A.

2013-01-01

The present study investigated the importance of the perceived injunctive norm to predict early adolescent cigarette smoking intentions. A total of 271 6th graders completed a survey that included perceived prevalence of friend smoking (descriptive norm), perceptions of friends’ disapproval of smoking (injunctive norm), and future smoking intentions. Participants also listed their five best friends, in which the actual injunctive norm was calculated. Results showed that smoking intentions were significantly correlated with the perceived injunctive norm but not with the actual injunctive norm. Secondly, the perceived injunctive norm predicted an additional 3.4% of variance in smoking intentions above and beyond the perceived descriptive norm. These results demonstrate the importance of the perceived injunctive norm in predicting early adolescent smoking intentions. PMID:24078745
Analysis, prediction, and case studies of early-age cracking in bridge decks

NASA Astrophysics Data System (ADS)

ElSafty, Adel; Graeff, Matthew K.; El-Gharib, Georges; Abdel-Mohti, Ahmed; Mike Jackson, N.

2016-06-01

Early-age cracking can adversely affect strength, serviceability, and durability of concrete bridge decks. Early age is defined as the period after final setting, during which concrete properties change rapidly. Many factors can cause early-age bridge deck cracking including temperature change, hydration, plastic shrinkage, autogenous shrinkage, and drying shrinkage. The cracking may also increase the effect of freeze and thaw cycles and may lead to corrosion of reinforcement. This research paper presents an analysis of causes and factors affecting early-age cracking. It also provides a tool developed to predict the likelihood and initiation of early-age cracking of concrete bridge decks. Understanding the concrete properties is essential so that the developed tool can accurately model the mechanisms contributing to the cracking of concrete bridge decks. The user interface of the implemented computer Excel program enables the user to input the properties of the concrete being monitored. The research study and the developed spreadsheet were used to comprehensively investigate the issue of concrete deck cracking. The spreadsheet is designed to be a user-friendly calculation tool for concrete mixture proportioning, temperature prediction, thermal analysis, and tensile cracking prediction. The study also provides review and makes recommendations on the deck cracking based mainly on the Florida Department of Transportation specifications and Structures Design Guidelines, and Bridge Design Manuals of other states. The results were also compared with that of other commercially available software programs that predict early-age cracking in concrete slabs, concrete pavement, and reinforced concrete bridge decks. The outcome of this study can identify a set of recommendations to limit the deck cracking problem and maintain a longer service life of bridges.

Mathematical models for the early detection and treatment of colorectal cancer.

PubMed

Harper, P R; Jones, S K

2005-05-01

Colorectal cancer is a major cause of death for men and women in the Western world. When the cancer is detected through an awareness of the symptoms by a patient, typically it is at an advanced stage. It is possible to detect cancer at an early stage through screening and the marked differences in survival for early and late stages provide the incentive for the primary prevention or early detection of colorectal cancer. This paper considers mathematical models for colorectal cancer screening together with models for the treatment of patients. Illustrative results demonstrate that detailed attention to the processes involved in diseases, interventions and treatment enable us to combine data and expert knowledge from various sources. Thus a detailed operational model is a very useful tool in helping to make decisions about screening at national and local levels.
Innovative design for early detection of invasive species

EPA Science Inventory

Non-native aquatic species impose significant ecological impacts and rising financial costs in marine and freshwater ecosystems worldwide. Early detection of invasive species, as they enter a vulnerable ecosystem, is critical to successful containment and eradication. ORD, at t...
Early esophageal cancer detection using RF classifiers

NASA Astrophysics Data System (ADS)

Janse, Markus H. A.; van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Esophageal cancer is one of the fastest rising forms of cancer in the Western world. Using High-Definition (HD) endoscopy, gastroenterology experts can identify esophageal cancer at an early stage. Recent research shows that early cancer can be found using a state-of-the-art computer-aided detection (CADe) system based on analyzing static HD endoscopic images. Our research aims at extending this system by applying Random Forest (RF) classification, which introduces a confidence measure for detected cancer regions. To visualize this data, we propose a novel automated annotation system, employing the unique characteristics of the previous confidence measure. This approach allows reliable modeling of multi-expert knowledge and provides essential data for real-time video processing, to enable future use of the system in a clinical setting. The performance of the CADe system is evaluated on a 39-patient dataset, containing 100 images annotated by 5 expert gastroenterologists. The proposed system reaches a precision of 75% and recall of 90%, thereby improving the state-of-the-art results by 11 and 6 percentage points, respectively.
Early optical detection of cerebral edema in vivo.

PubMed

Gill, Amandip S; Rajneesh, Kiran F; Owen, Christopher M; Yeh, James; Hsu, Mike; Binder, Devin K

2011-02-01

Cerebral edema is a significant cause of morbidity and mortality in diverse disease states. Currently, the means to detect progressive cerebral edema in vivo includes the use of intracranial pressure (ICP) monitors and/or serial radiological studies. However, ICP measurements exhibit a high degree of variability, and ICP monitors detect edema only after it becomes sufficient to significantly raise ICP. The authors report the development of 2 distinct minimally invasive fiberoptic near-infrared (NIR) techniques able to directly detect early cerebral edema. Cytotoxic brain edema was induced in adult CD1 mice via water intoxication by intraperitoneal water administration (30% body weight intraperitoneally). An implantable dual-fiberoptic probe was stereotactically placed into the cerebral cortex and connected to optical source and detector hardware. Optical sources consisted of either broadband halogen illumination or a single-wavelength NIR laser diode, and the detector was a sensitive NIR spectrometer or optical power meter. In one subset of animals, a left-sided craniectomy was performed to obtain cortical biopsies for water-content determination to verify cerebral edema. In another subset of animals, an ICP transducer was placed on the contralateral cortex, which was synchronized to a computer and time stamped. Using either broadband illumination with NIR spectroscopy or single-wavelength laser diode illumination with optical power meter detection, the authors detected a reduction in NIR optical reflectance during early cerebral edema. The time intervals between water injection (Time Point 0), optical trigger (defined as a 2-SD change in optical reflectance from baseline), and defined threshold ICP values of 10, 15 and 20 mm Hg were calculated. Reduction in NIR reflectance occurred significantly earlier than any of the ICP thresholds (p < 0.001). Saline-injected control mice exhibited a steady baseline optical signal. There was a significant correlation between
[Autism, neurodevelopment and early detection].

PubMed

Martos-Pérez, J

2006-02-13

Autistic disorder is briefly explained and defined in the light of recent research. From the perspective offered by ontogenesis and the acquisitions that take place during normal development, we present an updated vision of the genesis of autistic disorder and also review the most significant data provided by the different studies that have been conducted on the subject. Detection of the disorder is clearly a difficult task before the age of one year and, in any case, the earliest symptoms are clearly linked to the social and communicative interaction that characteristically takes place at the end of the infant's first year of life. Early detection of the disorder is made possible precisely because of alterations in social and communicative development and, in general, the appearance of psychological functions that play a significant role in the process of humanisation. The article concludes by pointing out the need for further studies that focus on the possible alteration of earlier socio-emotional and affective manifestations.
Technique for Early Reliability Prediction of Software Components Using Behaviour Models

PubMed Central

Ali, Awad; N. A. Jawawi, Dayang; Adham Isa, Mohd; Imran Babar, Muhammad

2016-01-01

Behaviour models are the most commonly used input for predicting the reliability of a software system at the early design stage. A component behaviour model reveals the structure and behaviour of the component during the execution of system-level functionalities. There are various challenges related to component reliability prediction at the early design stage based on behaviour models. For example, most of the current reliability techniques do not provide fine-grained sequential behaviour models of individual components and fail to consider the loop entry and exit points in the reliability computation. Moreover, some of the current techniques do not tackle the problem of operational data unavailability and the lack of analysis results that can be valuable for software architects at the early design stage. This paper proposes a reliability prediction technique that, pragmatically, synthesizes system behaviour in the form of a state machine, given a set of scenarios and corresponding constraints as input. The state machine is utilized as a base for generating the component-relevant operational data. The state machine is also used as a source for identifying the nodes and edges of a component probabilistic dependency graph (CPDG). Based on the CPDG, a stack-based algorithm is used to compute the reliability. The proposed technique is evaluated by a comparison with existing techniques and the application of sensitivity analysis to a robotic wheelchair system as a case study. The results indicate that the proposed technique is more relevant at the early design stage compared to existing works, and can provide a more realistic and meaningful prediction. PMID:27668748
Factors Influencing Early Detection of Oral Cancer by Primary Health-Care Professionals.

PubMed

Hassona, Y; Scully, C; Shahin, A; Maayta, W; Sawair, F

2016-06-01

The purposes of this study are to determine early detection practices performed by primary healthcare professionals, to compare medical and dental sub-groups, and to identify factors that influence the ability of medical and dental practitioners to recognize precancerous changes and clinical signs of oral cancer. A 28-item survey instrument was used to interview a total of 330 Jordanian primary health-care professionals (165 dental and 165 medical). An oral cancer knowledge scale (0 to 31) was generated from correct responses on oral cancer general knowledge. An early detection practice scale (0 to 24) was generated from the reported usage and frequency of procedures in oral cancer examination. Also, a diagnostic ability scale (0 to 100) was generated from correct selections of suspicious oral lesions. Only 17.8 % of the participants reported that they routinely performed oral cancer screening in practices. Their oral cancer knowledge scores ranged from 3 to 31 with a mean of 15.6. The early detection practice scores ranged from 2 to 21 with a mean of 11.6. A significant positive correlation was found between knowledge scores and early detection practice scores (r = 0.22; p < 0.001). The diagnostic ability scores ranged from 11.5 to 96 with a mean of 43.6. The diagnostic ability score was significantly correlated with knowledge scores (r = 0.39; p < 0.001), but not with early detection practice scores (r = 0.01; p = 0.92). Few significant differences were found between medical and dental primary care professionals. Continuous education courses on early diagnosis of oral cancer and oral mucosal lesions are needed for primary health-care professionals.
Early detection of sporadic pancreatic cancer: strategic map for innovation--a white paper.

PubMed

Kenner, Barbara J; Chari, Suresh T; Cleeter, Deborah F; Go, Vay Liang W

2015-07-01

Innovation leading to significant advances in research and subsequent translation to clinical practice is urgently necessary in early detection of sporadic pancreatic cancer. Addressing this need, the Early Detection of Sporadic Pancreatic Cancer Summit Conference was conducted by Kenner Family Research Fund in conjunction with the 2014 American Pancreatic Association and Japan Pancreas Society Meeting. International interdisciplinary scientific representatives engaged in strategic facilitated conversations based on distinct areas of inquiry: Case for Early Detection: Definitions, Detection, Survival, and Challenges; Biomarkers for Early Detection; Imaging; and Collaborative Studies. Ideas generated from the summit have led to the development of a Strategic Map for Innovation built upon 3 components: formation of an international collaborative effort, design of an actionable strategic plan, and implementation of operational standards, research priorities, and first-phase initiatives. Through invested and committed efforts of leading researchers and institutions, philanthropic partners, government agencies, and supportive business entities, this endeavor will change the future of the field and consequently the survival rate of those diagnosed with pancreatic cancer.
Early Detection of Physical Activity for People With Type 1 Diabetes Mellitus.

PubMed

Dasanayake, Isuru S; Bevier, Wendy C; Castorino, Kristin; Pinsker, Jordan E; Seborg, Dale E; Doyle, Francis J; Dassau, Eyal

2015-06-30

Early detection of exercise in individuals with type 1 diabetes mellitus (T1DM) may allow changes in therapy to prevent hypoglycemia. Currently there is limited experience with automated methods that detect the onset and end of exercise in this population. We sought to develop a novel method to quickly and reliably detect the onset and end of exercise in these individuals before significant changes in blood glucose (BG) occur. Sixteen adults with T1DM were studied as outpatients using a diary, accelerometer, heart rate monitor, and continuous glucose monitor for 2 days. These data were used to develop a principal component analysis based exercise detection method. Subjects also performed 60 and 30 minute exercise sessions at 30% and 50% predicted heart rate reserve (HRR), respectively. The detection method was applied to the exercise sessions to determine how quickly the detection of start and end of exercise occurred relative to change in BG. Mild 30% HRR and moderate 50% HRR exercise onset was identified in 6 ± 3 and 5 ± 2 (mean ± SD) minutes, while completion was detected in 3 ± 8 and 6 ± 5 minutes, respectively. BG change from start of exercise to detection time was 1 ± 6 and -1 ± 3 mg/dL, and, from the end of exercise to detection time was 6 ± 4 and -17 ± 13 mg/dL, respectively, for the 2 exercise sessions. False positive and negative ratios were 4 ± 2% and 21 ± 22%. The novel method for exercise detection identified the onset and end of exercise in approximately 5 minutes, with an average BG change of only -6 mg/dL. © 2015 Diabetes Technology Society.
Comparison of the Walz Nomogram and Presence of Secondary Circulating Prostate Cells for Predicting Early Biochemical Failure after Radical Prostatectomy for Prostate Cancer in Chilean Men.

PubMed

Murray, Nigel P; Reyes, Eduardo; Orellana, Nelson; Fuentealba, Cynthia; Jacob, Omar

2015-01-01

To determine the utility of secondary circulating prostate cells for predicting early biochemical failure after radical prostatectomy for prostate cancer and compare the results with the Walz nomagram. A single centre, prospective study of men with prostate cancer treated with radical prostatectomy between 2004 and 2014 was conducted, with registration of clinical-pathological details, total serum PSA pre-surgery, Gleason score, extracapsular extension, positive surgical margins, infiltration of lymph nodes, seminal vesicles and pathological stage. Secondary circulating prostate cells were obtained using differential gel centrifugation and assessed using standard immunocytochemistry with anti-PSA. Biochemical failure was defined as a PSA >0.2ng/ml, predictive values werecalculated using the Walz nomagram and CPC detection. A total of 326 men participated, with a median follow up of 5 years; 64 had biochemical failure within two years. Extracapsular extension, positive surgical margins, pathological stage, Gleason score ≥ 8, infiltration of seminal vesicles and lymph nodes were all associated with higher risk of biochemical failure. The discriminative value for the nomogram and circulating prostate cells was high (AUC >0.80), predictive values were higher for circulating prostate cell detection, with a negative predictive value of 99%, sensitivity of 96% and specificity of 75%. The nomagram had good predictive power to identify men with a high risk of biochemical failure within two years. The presence of circulating prostate cells had the same predictive power, with a higher sensitivity and negative predictive value. The presence of secondary circulating prostate cells identifies a group of men with a high risk of early biochemical failure. Those negative for secondary CPCs have a very low risk of early biochemical failure.
Predicting early positive change in multisystemic therapy with youth exhibiting antisocial behaviors.

PubMed

Tiernan, Kristine; Foster, Sharon L; Cunningham, Phillippe B; Brennan, Patricia; Whitmore, Elizabeth

2015-03-01

This study examined individual and family characteristics that predicted early positive change in the context of Multisystemic Therapy (MST). Families (n = 185; 65% male; average youth age 15 years) receiving MST in community settings completed assessments at the outset of treatment and 6-12 weeks into treatment. Early positive changes in youth antisocial behavior were assessed using the caregiver report on the Child Behavior Checklist Externalizing Behaviors subscale and youth report on the Self-Report Delinquency Scale. Overall, families showed significant positive changes by 6-12 weeks into treatment; these early changes were maintained into midtreatment 6-12 weeks later. Families who exhibited clinically significant gains early in treatment were more likely to terminate treatment successfully compared with those who did not show these gains. Low youth internalizing behaviors and absence of youth drug use predicted early positive changes in MST. High levels of parental monitoring and low levels of affiliation with deviant peers (mechanisms known to be associated with MST success) were also associated with early positive change. (PsycINFO Database Record (c) 2015 APA, all rights reserved).
Predictive modeling of neuroanatomic structures for brain atrophy detection

NASA Astrophysics Data System (ADS)

Hu, Xintao; Guo, Lei; Nie, Jingxin; Li, Kaiming; Liu, Tianming

2010-03-01

In this paper, we present an approach of predictive modeling of neuroanatomic structures for the detection of brain atrophy based on cross-sectional MRI image. The underlying premise of applying predictive modeling for atrophy detection is that brain atrophy is defined as significant deviation of part of the anatomy from what the remaining normal anatomy predicts for that part. The steps of predictive modeling are as follows. The central cortical surface under consideration is reconstructed from brain tissue map and Regions of Interests (ROI) on it are predicted from other reliable anatomies. The vertex pair-wise distance between the predicted vertex and the true one within the abnormal region is expected to be larger than that of the vertex in normal brain region. Change of white matter/gray matter ratio within a spherical region is used to identify the direction of vertex displacement. In this way, the severity of brain atrophy can be defined quantitatively by the displacements of those vertices. The proposed predictive modeling method has been evaluated by using both simulated atrophies and MRI images of Alzheimer's disease.
A new early cognitive screening measure to detect cognitive side-effects of electroconvulsive therapy?

PubMed

Martin, Donel M; Katalinic, Natalie; Ingram, Anna; Schweitzer, Isaac; Smith, Deidre J; Hadzi-Pavlovic, Dusan; Loo, Colleen K

2013-12-01

Cognitive side-effects from electroconvulsive therapy (ECT) can be distressing for patients and early detection may have an important role in guiding treatment decisions over the ECT course. This prospective study examined the utility of an early cognitive screening battery for predicting cognitive side-effects which develop later in the ECT course. The screening battery, together with the Mini Mental Status Examination (MMSE), was administered to 123 patients at baseline and after 3 ECT treatments. A more detailed cognitive battery was administered at baseline, after six treatments (post ECT 6) and after the last ECT treatment (post treatment) to assess cognitive side-effects across several domains: global cognition, anterograde memory, executive function, speed and concentration, and retrograde memory. Multivariate analyses examined the predictive utility of change on items from the screening battery for later cognitive changes at post ECT 6 and post treatment. Results showed that changes on a combination of items from the screening battery were predictive of later cognitive changes at post treatment, particularly for anterograde memory (p < 0.01), after controlling for patient and treatment factors. Change on the MMSE predicted cognitive changes at post ECT 6 but not at post treatment. A scoring method for the new screening battery was tested for discriminative ability in a sub-sample of patients. This study provides preliminary evidence that a simple and easy-to-administer measure may potentially be used to help guide clinical treatment decisions to optimise efficacy and cognitive outcomes. Further development of this measure and validation in a more representative ECT clinical population is required. Copyright © 2013 Elsevier Ltd. All rights reserved.
[CODEPEH 2014 recommendations for the early detection of delayed hearing loss].

PubMed

Núñez-Batalla, Faustino; Jáudenes-Casaubón, Carmen; Sequí-Canet, José Miguel; Vivanco-Allende, Ana; Zubicaray-Ugarteche, José

2016-10-01

The latest scientific literature considers early diagnosis of deafness as key element to define the educational prognosis and inclusion of the deaf child, as advantage can be taken in the critical period of development (0-4 years). Highly significant differences exist between those deaf persons who have been stimulated early and those who have received late or inappropriate intervention. Early identification of late-onset disorders requires special attention and knowledge of all childcare professionals. Programs and additional actions beyond neonatal screening should be designed and planned in order to ensure that every child with a significant hearing loss is detected early. For this purpose, the Committee for the Early Detection of Deafness (CODEPEH) would like to highlight the need for continuous monitoring on the hearing health of children. And, for this reason, CODEPEH drafts the recommendations included in the present document. Copyright © 2015 Asociación Española de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.
Copeptin helps in the early detection of patients with acute myocardial infarction: primary results of the CHOPIN trial (Copeptin Helps in the early detection Of Patients with acute myocardial INfarction).

PubMed

Maisel, Alan; Mueller, Christian; Neath, Sean-Xavier; Christenson, Robert H; Morgenthaler, Nils G; McCord, James; Nowak, Richard M; Vilke, Gary; Daniels, Lori B; Hollander, Judd E; Apple, Fred S; Cannon, Chad; Nagurney, John T; Schreiber, Donald; deFilippi, Christopher; Hogan, Christopher; Diercks, Deborah B; Stein, John C; Headden, Gary; Limkakeng, Alexander T; Anand, Inder; Wu, Alan H B; Papassotiriou, Jana; Hartmann, Oliver; Ebmeyer, Stefan; Clopton, Paul; Jaffe, Allan S; Peacock, W Frank

2013-07-09

The goal of this study was to demonstrate that copeptin levels <14 pmol/L allow ruling out acute myocardial infarction (AMI) when used in combination with cardiac troponin I (cTnI) <99 th percentile and a nondiagnostic electrocardiogram at the time of presentation to the emergency department (ED). Copeptin is secreted from the pituitary early in the course of AMI. This was a 16-site study in 1,967 patients with chest pain presenting to an ED within 6 hours of pain onset. Baseline demographic characteristics and clinical data were collected prospectively. Copeptin levels and a contemporary sensitive cTnI (99 th percentile 40 ng/l; 10% coefficient of variation 0.03 μg/l) were measured in a core laboratory. Patients were followed up for 180 days. The primary outcome was diagnosis of AMI. Final diagnoses were adjudicated by 2 independent cardiologists blinded to copeptin results. AMI was the final diagnosis in 156 patients (7.9%). A negative copeptin and cTnI at baseline ruled out AMI for 58% of patients, with a negative predictive value of 99.2% (95% confidence interval: 98.5 to 99.6). AMIs not detected by the initial cTnI alone were picked up with copeptin >14 pmol/l in 23 (72%) of 32 patients. Non-ST-segment elevation myocardial infarctions undetected by cTnI at 0 h were detected with copeptin >14 pmol/l in 10 (53%) of 19 patients. Projected average time-to-decision could be reduced by 43% (from 3.0 h to 1.8 h) by the early rule out of 58% of patients. Both abnormal copeptin and cTnI were predictors of death at 180 days (p < 0.0001 for both; c index 0.784 and 0.800, respectively). Both were independent of age and each other and provided additional predictive value (all p < 0.0001). Adding copeptin to cTnI allowed safe rule out of AMI with a negative predictive value >99% in patients presenting with suspected acute coronary syndromes. This combination has the potential to rule out AMI in 58% of patients without serial blood draws. Copyright © 2013 American College
Image Discrimination Models Predict Object Detection in Natural Backgrounds

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Rohaly, A. M.; Watson, Andrew B.; Null, Cynthia H. (Technical Monitor)

1994-01-01

Object detection involves looking for one of a large set of object sub-images in a large set of background images. Image discrimination models only predict the probability that an observer will detect a difference between two images. In a recent study based on only six different images, we found that discrimination models can predict the relative detectability of objects in those images, suggesting that these simpler models may be useful in some object detection applications. Here we replicate this result using a new, larger set of images. Fifteen images of a vehicle in an other-wise natural setting were altered to remove the vehicle and mixed with the original image in a proportion chosen to make the target neither perfectly recognizable nor unrecognizable. The target was also rotated about a vertical axis through its center and mixed with the background. Sixteen observers rated these 30 target images and the 15 background-only images for the presence of a vehicle. The likelihoods of the observer responses were computed from a Thurstone scaling model with the assumption that the detectabilities are proportional to the predictions of an image discrimination model. Three image discrimination models were used: a cortex transform model, a single channel model with a contrast sensitivity function filter, and the Root-Mean-Square (RMS) difference of the digital target and background-only images. As in the previous study, the cortex transform model performed best; the RMS difference predictor was second best; and last, but still a reasonable predictor, was the single channel model. Image discrimination models can predict the relative detectabilities of objects in natural backgrounds.
Early hearing detection and intervention: 2010 CODEPEH recommendation.

PubMed

Trinidad-Ramos, Germán; de Aguilar, Valentín Alzina; Jaudenes-Casaubón, Carmen; Núñez-Batalla, Faustino; Sequí-Canet, José Miguel

2010-01-01

Newborn hearing screening is currently performed routinely in many regional health-care systems in Spain. Despite the remarkable expansion in newborn hearing screening since 2000, its feasibility and the benefits of early identification and intervention, many major challenges still remain. In this article, the Committee for the Early Detection of Hearing Loss (Comisión para la Detección Precoz de la Hipoacusia, CODEPEH) updates the recommendations that are considered important for the future development of early hearing detection and intervention (EDHI) systems in the following points: 1. Screening protocols: Separate protocols are recommended for NICU (Neonatal Intensive Care Units) and well-infant nurseries. 2. Diagnostic audiology evaluation. Professionals with skills and expertise in evaluating newborn and young infants should provide diagnosis, selection and fitting of amplification devices. 3. Medical evaluation. Risk factors for congenital and acquired hearing loss have been combined in a single list rather than grouped by time of onset. A stepwise diagnostic paradigm is diagnostically more efficient and cost-effective than a simultaneous testing approach. 4. Early intervention and surveillance. All individuals providing services to infants with hearing loss should have specialized training and expertise in the development of audition, speech and language. Regular surveillance should be performed on developmental milestones, auditory skills, parental concerns, and middle ear status. 5. Quality control. Data management as part of an integrated system is important to monitor and improve the quality of EDHI services. 2009 Elsevier España, S.L. All rights reserved.
Early detection of fungi damage in citrus using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Blasco, Jose; Ortiz, Coral; Sabater, Maria D.; Molto, Enrique

2000-12-01

Early detection of defects and diseases in fruit helps to correctly classify them and make more adequate decisions about the destination of the product: internal market, export or industry. An early fungi infection detection is especially important because a few infected fruits can disseminate the infection to a whole batch, causing great economic losses and affecting to further exports. Ensure products with excellent quality and absolute absence of fungi infections is particularly important in those batches for long conservation or to be exported. The main objective of this work is to detect the fungi infections before they can be visible. Near Infrared spectroscopy has been employed in this work, because it is a non-destructive technique and can be easily implemented on line due to the high speed and simplicity of the process.
Intraoperative Inducibility of Atrial Fibrillation Does Not Predict Early Postoperative Atrial Fibrillation.

PubMed

Lanters, Eva A H; Teuwen, Christophe P; Yaksh, Ameeta; Kik, Charles; van der Does, Lisette J M E; Mouws, Elisabeth M J P; Knops, Paul; van Groningen, Nicole J; Hokken, Thijmen; Bogers, Ad J J C; de Groot, Natasja M S

2018-03-10

Early postoperative atrial fibrillation (EPoAF) is associated with thromboembolic events, prolonged hospitalization, and development of late PoAF (LPoAF). It is, however, unknown if EPoAF can be predicted by intraoperative AF inducibility. The aims of this study are therefore to explore (1) the value of intraoperative inducibility of AF for development of both EPoAF and LPoAF and (2) the predictive value of de novo EPoAF for recurrence of LPoAF. Patients (N=496, 75% male) undergoing cardiothoracic surgery for coronary and/or valvular heart disease were included. AF induction was attempted by atrial pacing, before extracorporeal circulation. All patients were on continuous rhythm monitoring until discharge to detect EPoAF. During a follow-up period of 2 years, LPoAF was detected by ECGs and Holter recordings. Sustained AF was inducible in 56% of patients. There was no difference in patients with or without AF before surgery ( P =0.159), or between different types of surgery ( P =0.687). In patients without a history of AF, incidence of EPoAF and LPoAF was 37% and 2%, respectively. EPoAF recurred in 58% patients with preoperative AF, 53% developed LPoAF. There were no correlations between intraoperative inducibility and EPoAF or LPoAF ( P >0.05). EPoAF was not correlated with LPoAF in patients without a history of AF ( P =0.116), in contrast to patients with AF before surgery ( P <0.001). Intraoperative AF inducibility does not predict development of either EPoAF or LPoAF. In patients with AF before surgery, EPoAF is correlated with LPoAF recurrences. This correlation is absent in patients without AF before surgery. © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.
A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

NASA Technical Reports Server (NTRS)

Crichton, Daniel; Srivastava, Sudhir; Johnsey, Donald

2003-01-01

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

Early indices of deviance detection in humans and animal models.

PubMed

Grimm, Sabine; Escera, Carles; Nelken, Israel

2016-04-01

Detecting unexpected stimuli in the environment is a critical function of the auditory system. Responses to unexpected "deviant" sounds are enhanced compared to responses to expected stimuli. At the human scalp, deviance detection is reflected in the mismatch negativity (MMN) and in an enhancement of the middle-latency response (MLR). Single neurons often respond more strongly to a stimulus when rare than when common, a phenomenon termed stimulus-specific adaptation (SSA). Here we compare stimulus-specific adaptation with scalp-recorded deviance-related responses. We conclude that early markers of deviance detection in the time range of the MLR could be a direct correlate of cortical SSA. Both occur at an early level of cortical activation, both are robust findings with low-probability stimuli, and both show properties of genuine deviance detection. Their causal relation with the later scalp-recorded MMN is a key question in this field. Copyright © 2015 Elsevier B.V. All rights reserved.
[Early detection of autism in children. Review of literature].

PubMed

Pisula, E

1997-01-01

The difficulties with early detection of autistic disorder in children are discussed. DSM-IV diagnostic criteria are presented. Usefulness of clinical interview and clinical experiment in diagnosing autistic disorder are analyzed.
A decade of aquatic invasive species (AIS) early detection ...

EPA Pesticide Factsheets

As an invasion prone location, the St. Louis River Estuary (SLRE) has been a case study for ongoing research to develop the framework for a practical Great Lakes monitoring network for early detection of aquatic invasive species (AIS). Early detection, however, necessitates finding new invaders before they are common. Here we outline our research (2005 present) approach and findings, including strategies to increase detection efficiency by optimizing specimen collection and identification methods. Initial surveys were designed to over-sample to amass data as the basis for numerical experiments to investigate to the effort required for a given detection probability. Later surveys tested the outcome of implementing these strategies, examined the potential benefits of sampling larval fish instead of adults and explored the prospect of using advanced DNA based methods as an alternative to traditional taxonomy. To date we have identified several previously undetected invertebrate invaders, developed survey design and gear recommendations and have refined the search strategy for systems beyond the SLRE. In addition, because we’ve accumulated such a large body of data we now have the basis to show spatial-temporal trends for native and non-native species in the SLRE. not applicable
Office-based spirometry for early detection of obstructive lung disease.

PubMed

Wallace, Laura D; Troy, Kenneth E

2006-09-01

To review the research-based evidence supporting smoking cessation as the only proven method to reduce chronic obstructive pulmonary disease (COPD) progression and to show that early detection of disease with office-based spirometry can lead to therapeutic intervention before physiologic symptoms arise. Extensive review of national and international scientific literature supplemented with drawings and algorithms. Early detection of COPD with spirometry, along with smoking cessation, and aggressive intervention can alter the insidious course of this highly preventable disease. It is imperative that nurse practitioners utilize this simple and inexpensive procedure to identify COPD in its earliest stages, so treatment can reduce individual and community disease burden, reduce morbidity and mortality, and help reduce healthcare costs. Determination of early airflow obstruction supports smoking cessation education, provides objective data for patient motivation, thereby doubling patient compliance and reducing further disease burden.
Unsupervised domain adaptation for early detection of drought stress in hyperspectral images

NASA Astrophysics Data System (ADS)

Schmitter, P.; Steinrücken, J.; Römer, C.; Ballvora, A.; Léon, J.; Rascher, U.; Plümer, L.

2017-09-01

Hyperspectral images can be used to uncover physiological processes in plants if interpreted properly. Machine Learning methods such as Support Vector Machines (SVM) and Random Forests have been applied to estimate development of biomass and detect and predict plant diseases and drought stress. One basic requirement of machine learning implies, that training and testing is done in the same domain and the same distribution. Different genotypes, environmental conditions, illumination and sensors violate this requirement in most practical circumstances. Here, we present an approach, which enables the detection of physiological processes by transferring the prior knowledge within an existing model into a related target domain, where no label information is available. We propose a two-step transformation of the target features, which enables a direct application of an existing model. The transformation is evaluated by an objective function including additional prior knowledge about classification and physiological processes in plants. We have applied the approach to three sets of hyperspectral images, which were acquired with different plant species in different environments observed with different sensors. It is shown, that a classification model, derived on one of the sets, delivers satisfying classification results on the transformed features of the other data sets. Furthermore, in all cases early non-invasive detection of drought stress was possible.
High-b-value diffusion-weighted MR imaging for pretreatment prediction and early monitoring of tumor response to therapy in mice.

PubMed

Roth, Yiftach; Tichler, Thomas; Kostenich, Genady; Ruiz-Cabello, Jesus; Maier, Stephan E; Cohen, Jack S; Orenstein, Arie; Mardor, Yael

2004-09-01

To evaluate the use of diffusion-weighted magnetic resonance (MR) imaging with standard and high b values for pretreatment prediction and early detection of tumor response to various antineoplastic therapies in an animal model. Mice bearing C26 colon carcinoma tumors were treated with doxorubicin (n = 25) and with aminolevulinic acid-based photodynamic therapy (n = 23). Fourteen mice served as controls. Conventional T2-weighted fast spin-echo and diffusion-weighted MR images were acquired once before therapy and at 6, 24, and 48 hours after treatment. Pretreatment and early (1-2 days) posttreatment water diffusion parameters were calculated and compared with later changes in tumor volumes measured on conventional MR images by using the Pearson correlation test. In chemotherapy-treated tumors, a significant correlation (P <.002, r = 0.6) was observed between diffusion parameters that reflected tumor viability, measured prior to treatment, and changes in tumor volumes after therapy. This correlation implies that tumors with high pretreatment viability will respond better to chemotherapy than more necrotic tumors. In tumors treated with photodynamic therapy, no such correlation was found. Changes observed in water diffusion 1-2 days after treatment significantly correlated with later tumor growth rate for both therapies (P <.002, r = 0.54 for photodynamic therapy; P <.0003, r = 0.61 for chemotherapy). High-b-value diffusion-weighted MR imaging has potential use for the early detection of response to therapy and for predicting treatment outcome prior to initiation of chemotherapy. Copyright RSNA, 2004
Prediction in the service of comprehension: modulated early brain responses to omitted speech segments.

PubMed

Bendixen, Alexandra; Scharinger, Mathias; Strauß, Antje; Obleser, Jonas

2014-04-01

Speech signals are often compromised by disruptions originating from external (e.g., masking noise) or internal (e.g., inaccurate articulation) sources. Speech comprehension thus entails detecting and replacing missing information based on predictive and restorative neural mechanisms. The present study targets predictive mechanisms by investigating the influence of a speech segment's predictability on early, modality-specific electrophysiological responses to this segment's omission. Predictability was manipulated in simple physical terms in a single-word framework (Experiment 1) or in more complex semantic terms in a sentence framework (Experiment 2). In both experiments, final consonants of the German words Lachs ([laks], salmon) or Latz ([lats], bib) were occasionally omitted, resulting in the syllable La ([la], no semantic meaning), while brain responses were measured with multi-channel electroencephalography (EEG). In both experiments, the occasional presentation of the fragment La elicited a larger omission response when the final speech segment had been predictable. The omission response occurred ∼125-165 msec after the expected onset of the final segment and showed characteristics of the omission mismatch negativity (MMN), with generators in auditory cortical areas. Suggestive of a general auditory predictive mechanism at work, this main observation was robust against varying source of predictive information or attentional allocation, differing between the two experiments. Source localization further suggested the omission response enhancement by predictability to emerge from left superior temporal gyrus and left angular gyrus in both experiments, with additional experiment-specific contributions. These results are consistent with the existence of predictive coding mechanisms in the central auditory system, and suggestive of the general predictive properties of the auditory system to support spoken word recognition. Copyright © 2014 Elsevier Ltd. All
Investigations of remote sensing techniques for early detection of Dutch elm disease

NASA Technical Reports Server (NTRS)

Hammerschlag, R. S.; Sopstyle, W. J.

1975-01-01

Several forms of aerial photography were pursued in quest of a technique which could provide early detection of Dutch elm disease. The two most promising techniques tested were multispectral photography with object enhancement and biband ratioing coupled with scanning microdensitometry. For practical purposes the multispectral system has the advantage of providing a readily interpretable image in a relatively short time. Laboratory studies indicated that less emphasis should be placed on the use of a red filter or the near infrared beyond 750 mm for early detection of stress within a single plant species. Color infrared film would be optimal when used for a long term detection of loss of plant vigor which results in a physical change in a plant canopy, but should find minimal practicality for early detection of specific sources of plant stress such as Dutch elm disease. Considerable discretion should be used when interpreting imagery on copy film because of loss of resolution and color definition.
EEG seizure detection and prediction algorithms: a survey

NASA Astrophysics Data System (ADS)

Alotaiby, Turkey N.; Alshebeili, Saleh A.; Alshawi, Tariq; Ahmad, Ishtiaq; Abd El-Samie, Fathi E.

2014-12-01

Epilepsy patients experience challenges in daily life due to precautions they have to take in order to cope with this condition. When a seizure occurs, it might cause injuries or endanger the life of the patients or others, especially when they are using heavy machinery, e.g., deriving cars. Studies of epilepsy often rely on electroencephalogram (EEG) signals in order to analyze the behavior of the brain during seizures. Locating the seizure period in EEG recordings manually is difficult and time consuming; one often needs to skim through tens or even hundreds of hours of EEG recordings. Therefore, automatic detection of such an activity is of great importance. Another potential usage of EEG signal analysis is in the prediction of epileptic activities before they occur, as this will enable the patients (and caregivers) to take appropriate precautions. In this paper, we first present an overview of seizure detection and prediction problem and provide insights on the challenges in this area. Second, we cover some of the state-of-the-art seizure detection and prediction algorithms and provide comparison between these algorithms. Finally, we conclude with future research directions and open problems in this topic.
Point/Counterpoint: early detection of prostate cancer: do the benefits outweigh the consequences?

PubMed

Carroll, Peter R; Vickers, Andrew J

2014-05-01

Few clinical issues have polarized the oncology community as much as screening for prostate cancer, with advocates of prostate-specific antigen (PSA) testing vocal on one side and skeptics just as vocal on the other. At the NCCN 19th Annual Conference, Dr. Peter R. Carroll and Dr. Andrew J. Vickers tackled the controversy surrounding early detection of prostate cancer, focusing attention on the randomized trial results at the heart of the matter; over-detection (the Achilles' heel of screening); and the rationale behind the new, streamlined 2014 NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Prostate Cancer Early Detection, which emphasize selective early detection and treatment and are tightly aligned with the NCCN Guidelines for Prostate Cancer. Copyright © 2014 by the National Comprehensive Cancer Network.
A Bayesian framework for early risk prediction in traumatic brain injury

NASA Astrophysics Data System (ADS)

Chaganti, Shikha; Plassard, Andrew J.; Wilson, Laura; Smith, Miya A.; Patel, Mayur B.; Landman, Bennett A.

2016-03-01

Early detection of risk is critical in determining the course of treatment in traumatic brain injury (TBI). Computed tomography (CT) acquired at admission has shown latent prognostic value in prior studies; however, no robust clinical risk predictions have been achieved based on the imaging data in large-scale TBI analysis. The major challenge lies in the lack of consistent and complete medical records for patients, and an inherent bias associated with the limited number of patients samples with high-risk outcomes in available TBI datasets. Herein, we propose a Bayesian framework with mutual information-based forward feature selection to handle this type of data. Using multi-atlas segmentation, 154 image-based features (capturing intensity, volume and texture) were computed over 22 ROIs in 1791 CT scans. These features were combined with 14 clinical parameters and converted into risk likelihood scores using Bayes modeling. We explore the prediction power of the image features versus the clinical measures for various risk outcomes. The imaging data alone were more predictive of outcomes than the clinical data (including Marshall CT classification) for discharge disposition with an area under the curve of 0.81 vs. 0.67, but less predictive than clinical data for discharge Glasgow Coma Scale (GCS) score with an area under the curve of 0.65 vs. 0.85. However, in both cases, combining imaging and clinical data increased the combined area under the curve with 0.86 for discharge disposition and 0.88 for discharge GCS score. In conclusion, CT data have meaningful prognostic value for TBI patients beyond what is captured in clinical measures and the Marshall CT classification.
Biomarkers for early detection of Alzheimer disease.

PubMed

Barber, Robert C

2010-09-01

The existence of an effective biomarker for early detection of Alzheimer disease would facilitate improved diagnosis and stimulate therapeutic trials. Multidisciplinary clinical diagnosis of Alzheimer disease is time consuming and expensive and relies on experts who are rarely available outside of specialty clinics. Thus, many patients do not receive proper diagnosis until the disease has progressed beyond stages in which treatments are maximally effective. In the clinical trial setting, rapid, cost-effective screening of patients for Alzheimer disease is of paramount importance for the development of new treatments. Neuroimaging of cortical amyloid burden and volumetric changes in the brain and assessment of protein concentrations (eg, β-amyloid 1-42, total tau, phosphorylated tau) in cerebrospinal fluid are diagnostic tools that are not widely available. Known genetic markers do not provide sufficient discriminatory power between different forms of dementia to be useful in isolation. Recent studies using panels of biomarkers for diagnosis of Alzheimer disease or mild cognitive impairment have been promising, though no such studies have been cross-validated in independent samples of subjects. The ideal biomarker enabling early detection of Alzheimer disease has not yet been identified.
Development of a quantitative NS1-capture enzyme-linked immunosorbent assay for early detection of yellow fever virus infection.

PubMed

Ricciardi-Jorge, Taissa; Bordignon, Juliano; Koishi, Andrea; Zanluca, Camila; Mosimann, Ana Luiza; Duarte Dos Santos, Claudia Nunes

2017-11-24

Yellow fever is an arboviral disease that causes thousands of deaths every year in Africa and the Americas. However, few commercial diagnostic kits are available. Non-structural protein 1 (NS1) is an early marker of several flavivirus infections and is widely used to diagnose dengue virus (DENV) infection. Nonetheless, little is known about the dynamics of Yellow fever virus (YFV) NS1 expression and secretion, to encourage its use in diagnosis. To tackle this issue, we developed a quantitative NS1-capture ELISA specific for YFV using a monoclonal antibody and recombinant NS1 protein. This test was used to quantify NS1 in mosquito and human cell line cultures infected with vaccine and wild YFV strains. Our results showed that NS1 was detectable in the culture supernatants of both cell lines; however, a higher concentration was maintained as cell-associated rather than secreted into the extracellular milieu. A panel of 73 human samples was used to demonstrate the suitability of YFV NS1 as a diagnostic tool, resulting in 80% sensitivity, 100% specificity, a 100% positive predictive value and a 95.5% negative predictive value compared with RT-PCR. Overall, the developed NS1-capture ELISA showed potential as a promising assay for the detection of early YF infection.
Is breast compression associated with breast cancer detection and other early performance measures in a population-based breast cancer screening program?

PubMed

Moshina, Nataliia; Sebuødegård, Sofie; Hofvind, Solveig

2017-06-01

We aimed to investigate early performance measures in a population-based breast cancer screening program stratified by compression force and pressure at the time of mammographic screening examination. Early performance measures included recall rate, rates of screen-detected and interval breast cancers, positive predictive value of recall (PPV), sensitivity, specificity, and histopathologic characteristics of screen-detected and interval breast cancers. Information on 261,641 mammographic examinations from 93,444 subsequently screened women was used for analyses. The study period was 2007-2015. Compression force and pressure were categorized using tertiles as low, medium, or high. χ 2 test, t tests, and test for trend were used to examine differences between early performance measures across categories of compression force and pressure. We applied generalized estimating equations to identify the odds ratios (OR) of screen-detected or interval breast cancer associated with compression force and pressure, adjusting for fibroglandular and/or breast volume and age. The recall rate decreased, while PPV and specificity increased with increasing compression force (p for trend <0.05 for all). The recall rate increased, while rate of screen-detected cancer, PPV, sensitivity, and specificity decreased with increasing compression pressure (p for trend <0.05 for all). High compression pressure was associated with higher odds of interval breast cancer compared with low compression pressure (1.89; 95% CI 1.43-2.48). High compression force and low compression pressure were associated with more favorable early performance measures in the screening program.
Early Diagnosis and Prediction of Anticancer Drug-induced Cardiotoxicity: From Cardiac Imaging to "Omics" Technologies.

PubMed

Madonna, Rosalinda

2017-07-01

Heart failure due to antineoplastic therapy remains a major cause of morbidity and mortality in oncological patients. These patients often have no prior manifestation of disease. There is therefore a need for accurate identification of individuals at risk of such events before the appearance of clinical manifestations. The present article aims to provide an overview of cardiac imaging as well as new "-omics" technologies, especially with regard to genomics and proteomics as promising tools for the early detection and prediction of cardiotoxicity and individual responses to antineoplastic drugs. Copyright © 2017 Sociedad Española de Cardiología. Published by Elsevier España, S.L.U. All rights reserved.
Beyond Phonology: Visual Processes Predict Alphanumeric and Nonalphanumeric Rapid Naming in Poor Early Readers

ERIC Educational Resources Information Center

Kruk, Richard S.; Luther Ruban, Cassia

2018-01-01

Visual processes in Grade 1 were examined for their predictive influences in nonalphanumeric and alphanumeric rapid naming (RAN) in 51 poor early and 69 typical readers. In a lagged design, children were followed longitudinally from Grade 1 to Grade 3 over 5 testing occasions. RAN outcomes in early Grade 2 were predicted by speeded and nonspeeded…
Quantification of Forecasting and Change-Point Detection Methods for Predictive Maintenance

DTIC Science & Technology

2015-08-19

industries to manage the service life of equipment, and also to detect precursors to the failure of components found in nuclear power plants, wind turbines ...detection methods for predictive maintenance 5a. CONTRACT NUMBER FA2386-14-1-4096 5b. GRANT NUMBER Grant 14IOA015 AOARD-144096 5c. PROGRAM ELEMENT...sensitive to changes related to abnormality. 15. SUBJECT TERMS predictive maintenance , predictive maintenance , forecasting 16
Potential utility of environmental DNA for early detection of Eurasian watermilfoil (Myriophyllum spicatum)

USGS Publications Warehouse

Newton, Jeremy; Sepulveda, Adam; Sylvester, K; Thum, Ryan

2016-01-01

Considering the harmful and irreversible consequences of many biological invasions, early detection of an invasive species is an important step toward protecting ecosystems (Sepulveda et al. 2012). Early detection increases the probability that suppression or eradication efforts will be successful because invasive populations are small and localized (Vander Zanden et al. 2010). However, most invasive species are not detected early because current tools have low detection probabilities when target species are rare and the sampling effort required to achieve acceptable detection capabilities with current tools is seldom tractable (Jerde et al. 2011). As a result, many invasive species go undetected until they are abundant and suppression efforts become costly. Novel DNA-based surveillance tools have recently revolutionized early detection abilities using environmental DNA (eDNA) present in the water (Darling and Mahon 2011, Bohmann et al. 2014). In brief, eDNA monitoring enables the identification of organisms from DNA present and collected in water samples. Aquatic and semiaquatic organisms release DNA contained in sloughed, damaged, or partially decomposed tissue and waste products into the water and molecular techniques allow this eDNA in the water column to be identified from simple and easy-tocollect water samples (Darling and Mahon 2011). Despite limited understanding of the production, persistence, and spread of DNA in water (Barnes et al. 2014), eDNA monitoring has been applied not only to invasive species (Jerde et al. 2011), but also to species that are rare, endangered, or highly elusive (Spear et al. 2014). However, most eDNA research and monitoring has focused on detection of invertebrates and vertebrates and less attentionhas been given to developing eDNA techniques for detecting aquatic invasive plants. Eurasian watermilfoil (EWM; Myriophyllum spicatum L.) is an invasive species for which improved early detection would be particularly helpful. Advanced
Object Detection in Natural Backgrounds Predicted by Discrimination Performance and Models

NASA Technical Reports Server (NTRS)

Ahumada, A. J., Jr.; Watson, A. B.; Rohaly, A. M.; Null, Cynthia H. (Technical Monitor)

1995-01-01

In object detection, an observer looks for an object class member in a set of backgrounds. In discrimination, an observer tries to distinguish two images. Discrimination models predict the probability that an observer detects a difference between two images. We compare object detection and image discrimination with the same stimuli by: (1) making stimulus pairs of the same background with and without the target object and (2) either giving many consecutive trials with the same background (discrimination) or intermixing the stimuli (object detection). Six images of a vehicle in a natural setting were altered to remove the vehicle and mixed with the original image in various proportions. Detection observers rated the images for vehicle presence. Discrimination observers rated the images for any difference from the background image. Estimated detectabilities of the vehicles were found by maximizing the likelihood of a Thurstone category scaling model. The pattern of estimated detectabilities is similar for discrimination and object detection, and is accurately predicted by a Cortex Transform discrimination model. Predictions of a Contrast- Sensitivity- Function filter model and a Root-Mean-Square difference metric based on the digital image values are less accurate. The discrimination detectabilities averaged about twice those of object detection.
[The early pregnancy factor (EPF) as an early marker of disorders in pregnancy].

PubMed

Straube, W; Römer, T; Zeenni, L; Loh, M

1995-01-01

The early pregnancy factor (EPF) seems to be very helpful in clinical applications such as early detection of pregnancy, differential diagnosis of failure of fertilization or implementation and prognosis of a fertilized ovum. Our purpose was to investigate the diagnostic value of single and serial measurement of EPF, especially in the differential diagnosis of abortion and extrauterine pregnancy. Women with a history of 6-16 weeks amenorrhoea with/without vaginal bleeding were included in the prospective study. The EPF-test system was carried out by means of the rosette inhibition method. EPF proved to be always positive in normal pregnant women and always negative in nonpregnant controls. In case of threatened abortion the prognosis was good, when the EPF values were positive, and poor when they became negative. Patients suffering from spontaneous and missed abortion mostly showed negative EPF-values. This was also true in ectopic pregnancies. The sensitivity and specificity of EPF-test system were 83%. The positive predictive value was observed to be 54% and the negative predictive value 95%. The EPF as an early embryonic signal may be a suitable parameter for the clinical use detecting pregnancy disturbances very early.

Early detection of health and welfare compromises through automated detection of behavioural changes in pigs.

PubMed

Matthews, Stephen G; Miller, Amy L; Clapp, James; Plötz, Thomas; Kyriazakis, Ilias

2016-11-01

Early detection of health and welfare compromises in commercial piggeries is essential for timely intervention to enhance treatment success, reduce impact on welfare, and promote sustainable pig production. Behavioural changes that precede or accompany subclinical and clinical signs may have diagnostic value. Often referred to as sickness behaviour, this encompasses changes in feeding, drinking, and elimination behaviours, social behaviours, and locomotion and posture. Such subtle changes in behaviour are not easy to quantify and require lengthy observation input by staff, which is impractical on a commercial scale. Automated early-warning systems may provide an alternative by objectively measuring behaviour with sensors to automatically monitor and detect behavioural changes. This paper aims to: (1) review the quantifiable changes in behaviours with potential diagnostic value; (2) subsequently identify available sensors for measuring behaviours; and (3) describe the progress towards automating monitoring and detection, which may allow such behavioural changes to be captured, measured, and interpreted and thus lead to automation in commercial, housed piggeries. Multiple sensor modalities are available for automatic measurement and monitoring of behaviour, which require humans to actively identify behavioural changes. This has been demonstrated for the detection of small deviations in diurnal drinking, deviations in feeding behaviour, monitoring coughs and vocalisation, and monitoring thermal comfort, but not social behaviour. However, current progress is in the early stages of developing fully automated detection systems that do not require humans to identify behavioural changes; e.g., through automated alerts sent to mobile phones. Challenges for achieving automation are multifaceted and trade-offs are considered between health, welfare, and costs, between analysis of individuals and groups, and between generic and compromise-specific behaviours. Copyright © 2016
The use of early summer mosquito surveillance to predict late summer West Nile virus activity

USGS Publications Warehouse

Ginsberg, Howard S.; Rochlin, Ilia; Campbell, Scott R.

2010-01-01

Utility of early-season mosquito surveillance to predict West Nile virus activity in late summer was assessed in Suffolk County, NY. Dry ice-baited CDC miniature light traps paired with gravid traps were set weekly. Maximum-likelihood estimates of WNV positivity, minimum infection rates, and % positive pools were generally well correlated. However, positivity in gravid traps was not correlated with positivity in CDC light traps. The best early-season predictors of WNV activity in late summer (estimated using maximum-likelihood estimates of Culex positivity in August and September) were early date of first positive pool, low numbers of mosquitoes in July, and low numbers of mosquito species in July. These results suggest that early-season entomological samples can be used to predict WNV activity later in the summer, when most human cases are acquired. Additional research is needed to establish which surveillance variables are most predictive and to characterize the reliability of the predictions.
How can clinicians detect and treat autism early? Methodological trends of technology use in research

PubMed Central

Bölte, S; Bartl-Pokorny, KD; Jonsson, U; Berggren, S; Zhang, D; Kostrzewa, E; Falck-Ytter, T; Einspieler, C; Pokorny, FB; Jones, EJH; Roeyers, H; Charman, T; Marschik, PB

2018-01-01

We reviewed original research papers that used quantifiable technology to detect early autism spectrum disorder (ASD) and identified 376 studies from 34 countries from 1965-2013. Publications have increased significantly since 2000, with most coming from the USA. Electroencephalogram, magnetic resonance imaging and eye-tracking were the most frequently used technologies. Conclusion The use of quantifiable technology to detect early ASD has increased in recent decades, but has had limited impact on early detection and treatment. Further scientific developments are anticipated and we hope that they will increasingly be used in clinical practice for early ASD screening, diagnosis and intervention. PMID:26479859
An Early Prediction of Sunspot Cycle 25

NASA Astrophysics Data System (ADS)

Nandy, D.; Bhowmik, P.

2017-12-01

The Sun's magnetic activity governs our space environment, creates space weather and impacts our technologies and climate. With increasing reliance on space- and ground-based technologies that are subject to space weather, the need to be able to forecast the future activity of the Sun has assumed increasing importance. However, such long-range, decadal-scale space weather prediction has remained a great challenge as evident in the diverging forecasts for solar cycle 24. Based on recently acquired understanding of the physics of solar cycle predictability, we have devised a scheme to extend the forecasting window of solar cycles. Utilizing this we present an early forecast for sunspot cycle 25 which would be of use for space mission planning, satellite life-time estimates, and assessment of the long-term impacts of space weather on technological assets and planetary atmospheres.
Infrared light sensor applied to early detection of tooth decay

NASA Astrophysics Data System (ADS)

Benjumea, Eberto; Espitia, José; Díaz, Leonardo; Torres, Cesar

2017-08-01

The approach dentistry to dental care is gradually shifting to a model focused on early detection and oral-disease prevention; one of the most important methods of prevention of tooth decay is opportune diagnosis of decay and reconstruction. The present study aimed to introduce a procedure for early diagnosis of tooth decay and to compare result of experiment of this method with other common treatments. In this setup, a laser emitting infrared light is injected in core of one bifurcated fiber-optic and conduced to tooth surface and with the same bifurcated fiber the radiation reflected for the same tooth is collected and them conduced to surface of sensor that measures thermal and light frequencies to detect early signs of decay below a tooth surface, where demineralization is difficult to spot with x-ray technology. This device will can be used to diagnose tooth decay without any chemicals and rays such as high power lasers or X-rays.
E-nose based rapid prediction of early mouldy grain using probabilistic neural networks

PubMed Central

Ying, Xiaoguo; Liu, Wei; Hui, Guohua; Fu, Jun

2015-01-01

In this paper, early mouldy grain rapid prediction method using probabilistic neural network (PNN) and electronic nose (e-nose) was studied. E-nose responses to rice, red bean, and oat samples with different qualities were measured and recorded. E-nose data was analyzed using principal component analysis (PCA), back propagation (BP) network, and PNN, respectively. Results indicated that PCA and BP network could not clearly discriminate grain samples with different mouldy status and showed poor predicting accuracy. PNN showed satisfying discriminating abilities to grain samples with an accuracy of 93.75%. E-nose combined with PNN is effective for early mouldy grain prediction. PMID:25714125
UWB based low-cost and non-invasive practical breast cancer early detection

NASA Astrophysics Data System (ADS)

Vijayasarveswari, V.; Khatun, S.; Fakir, M. M.; Jusoh, M.; Ali, S.

2017-03-01

Breast cancer is one of the main causes of women death worldwide. Breast tumor is an early stage of cancer that locates in cells of a human breast. As there is no remedy, early detection is crucial. Towards this, Ultra-Wideband (UWB) is a prominent candidate. It is a wireless communication technology which can achieve high bandwidth with low power utilization. UWB is suitable to be used for short range communication systems including breast cancer detection since it is secure, non-invasive and human health friendly. This paper presents the low-cost and non-invasive early breast cancer detection strategy using UWB sensor (or antenna). Emphasis is given here to detect breast tumor in 2D and 3D environments. The developed system consisted of hardware and software. Hardware included UWB transceiver and a pair of home-made directional sensor/antenna. The software included feed-forward back propagation Neural Network (NN) module to detect the tumor existence, size and location along with soft interface between software and hardware. Forward scattering technique was used by placing two sensors diagonally opposite sides of a breast phantom. UWB pulses were transmitted from one side of phantom and received from other side, controlled by the software interface in PC environment. Collected received signals were then fed into the NN module for training, testing and validation. The system exhibited detection efficiency on tumor existence, location (x, y, z), and size were approximately 100%, (78.17%, 70.66%, 92.46%), 85.86% respectively. The proposed UWB based early breast cancer detection system could be more practical with low-cost, user friendly and non-harmful features. This project may help users to monitor their breast health regularly at their home.
Predictable Locations Aid Early Object Name Learning

PubMed Central

Benitez, Viridiana L.; Smith, Linda B.

2012-01-01

Expectancy-based localized attention has been shown to promote the formation and retrieval of multisensory memories in adults. Three experiments show that these processes also characterize attention and learning in 16- to 18- month old infants and, moreover, that these processes may play a critical role in supporting early object name learning. The three experiments show that infants learn names for objects when those objects have predictable rather than varied locations, that infants who anticipate the location of named objects better learn those object names, and that infants integrate experiences that are separated in time but share a common location. Taken together, these results suggest that localized attention, cued attention, and spatial indexing are an inter-related set of processes in young children that aid in the early building of coherent object representations. The relevance of the experimental results and spatial attention for everyday word learning are discussed. PMID:22989872
Early Executive Function at Age Two Predicts Emergent Mathematics and Literacy at Age Five

PubMed Central

Mulder, Hanna; Verhagen, Josje; Van der Ven, Sanne H. G.; Slot, Pauline L.; Leseman, Paul P. M.

2017-01-01

Previous work has shown that individual differences in executive function (EF) are predictive of academic skills in preschoolers, kindergartners, and older children. Across studies, EF is a stronger predictor of emergent mathematics than literacy. However, research on EF in children below age three is scarce, and it is currently unknown whether EF, as assessed in toddlerhood, predicts emergent academic skills a few years later. This longitudinal study investigates whether early EF, assessed at two years, predicts (emergent) academic skills, at five years. It examines, furthermore, whether early EF is a significantly stronger predictor of emergent mathematics than of emergent literacy, as has been found in previous work on older children. A sample of 552 children was assessed on various EF and EF-precursor tasks at two years. At age five, these children performed several emergent mathematics and literacy tasks. Structural Equation Modeling was used to investigate the relationships between early EF and academic skills, modeled as latent factors. Results showed that early EF at age two was a significant and relatively strong predictor of both emergent mathematics and literacy at age five, after controlling for receptive vocabulary, parental education, and home language. Predictive relations were significantly stronger for mathematics than literacy, but only when a verbal short-term memory measure was left out as an indicator to the latent early EF construct. These findings show that individual differences in emergent academic skills just prior to entry into the formal education system can be traced back to individual differences in early EF in toddlerhood. In addition, these results highlight the importance of task selection when assessing early EF as a predictor of later outcomes, and call for further studies to elucidate the mechanisms through which individual differences in early EF and precursors to EF come about. PMID:29075209
Early Executive Function at Age Two Predicts Emergent Mathematics and Literacy at Age Five.

PubMed

Mulder, Hanna; Verhagen, Josje; Van der Ven, Sanne H G; Slot, Pauline L; Leseman, Paul P M

2017-01-01

Previous work has shown that individual differences in executive function (EF) are predictive of academic skills in preschoolers, kindergartners, and older children. Across studies, EF is a stronger predictor of emergent mathematics than literacy. However, research on EF in children below age three is scarce, and it is currently unknown whether EF, as assessed in toddlerhood, predicts emergent academic skills a few years later. This longitudinal study investigates whether early EF, assessed at two years, predicts (emergent) academic skills, at five years. It examines, furthermore, whether early EF is a significantly stronger predictor of emergent mathematics than of emergent literacy, as has been found in previous work on older children. A sample of 552 children was assessed on various EF and EF-precursor tasks at two years. At age five, these children performed several emergent mathematics and literacy tasks. Structural Equation Modeling was used to investigate the relationships between early EF and academic skills, modeled as latent factors. Results showed that early EF at age two was a significant and relatively strong predictor of both emergent mathematics and literacy at age five, after controlling for receptive vocabulary, parental education, and home language. Predictive relations were significantly stronger for mathematics than literacy, but only when a verbal short-term memory measure was left out as an indicator to the latent early EF construct. These findings show that individual differences in emergent academic skills just prior to entry into the formal education system can be traced back to individual differences in early EF in toddlerhood. In addition, these results highlight the importance of task selection when assessing early EF as a predictor of later outcomes, and call for further studies to elucidate the mechanisms through which individual differences in early EF and precursors to EF come about.
Towards BirthAlert—A Clinical Device Intended for Early Preterm Birth Detection

PubMed Central

Etemadi, Mozziyar; Chung, Philip; Heller, J. Alex; Liu, Jonathan A.; Rand, Larry; Roy, Shuvo

2015-01-01

Preterm birth causes 1 million infant deaths worldwide every year, making it the leading cause of infant mortality. Existing diagnostic tests such as transvaginal ultrasound or fetal fibronectin either cannot determine if preterm birth will occur in the future or can only predict the occurrence once cervical shortening has begun, at which point it is too late to reverse the accelerated parturition process. Using iterative and rapid prototyping techniques, we have developed an intravaginal proof-of-concept device that measures both cervical bioimpedance and cervical fluorescence to characterize microstructural changes in a pregnant woman's cervix in hopes of detecting preterm birth before macroscopic changes manifest in the tissue. If successful, such an early alert during this “silent phase” of the preterm birth syndrome may open a new window of opportunity for interventions that may reverse and avoid preterm birth altogether. PMID:23893706
[Early detection of breast and cervical cancer among indigenous communities in Morelos, Mexico].

PubMed

Campero, Lourdes; Atienzo, Erika E; Marín, Eréndira; de la Vara-Salazar, Elvia; Pelcastre-Villafuerte, Blanca; González, Guillermo

2014-01-01

To analyze the perception in relation to when and how to perform actions for the early detection of breast and cervical cancer among women and health care providers in communities with a high percentage of indigenous population in Morelos, Mexico. Ten health providers and 58 women users of health services were interviewed which have a first level of attention in five communities. The analysis was developed under the approach of the Grounded Theory. Providers are poorly informed about current regulations and specific clinical indications for the detection of cervical and breast cancer. Few practice health literacy under intercultural sensitization. The users have imprecise or wrong notions of the early detection. The need for training in adherence to norms is evident. It is urgent to assume a culturally relevant approach to enable efficient communication and promote health literacy for early detection of these two cancers.
Early Prediction of Cancer Progression by Depth-Resolved Nanoscale Mapping of Nuclear Architecture from Unstained Tissue Specimens.

PubMed

Uttam, Shikhar; Pham, Hoa V; LaFace, Justin; Leibowitz, Brian; Yu, Jian; Brand, Randall E; Hartman, Douglas J; Liu, Yang

2015-11-15

Early cancer detection currently relies on screening the entire at-risk population, as with colonoscopy and mammography. Therefore, frequent, invasive surveillance of patients at risk for developing cancer carries financial, physical, and emotional burdens because clinicians lack tools to accurately predict which patients will actually progress into malignancy. Here, we present a new method to predict cancer progression risk via nanoscale nuclear architecture mapping (nanoNAM) of unstained tissue sections based on the intrinsic density alteration of nuclear structure rather than the amount of stain uptake. We demonstrate that nanoNAM detects a gradual increase in the density alteration of nuclear architecture during malignant transformation in animal models of colon carcinogenesis and in human patients with ulcerative colitis, even in tissue that appears histologically normal according to pathologists. We evaluated the ability of nanoNAM to predict "future" cancer progression in patients with ulcerative colitis who did and did not develop colon cancer up to 13 years after their initial colonoscopy. NanoNAM of the initial biopsies correctly classified 12 of 15 patients who eventually developed colon cancer and 15 of 18 who did not, with an overall accuracy of 85%. Taken together, our findings demonstrate great potential for nanoNAM in predicting cancer progression risk and suggest that further validation in a multicenter study with larger cohorts may eventually advance this method to become a routine clinical test. ©2015 American Association for Cancer Research.
Sensitivity and specificity of automated detection of early repolarization in standard 12-lead electrocardiography.

PubMed

Kenttä, Tuomas; Porthan, Kimmo; Tikkanen, Jani T; Väänänen, Heikki; Oikarinen, Lasse; Viitasalo, Matti; Karanko, Hannu; Laaksonen, Maarit; Huikuri, Heikki V

2015-07-01

Early repolarization (ER) is defined as an elevation of the QRS-ST junction in at least two inferior or lateral leads of the standard 12-lead electrocardiogram (ECG). Our purpose was to create an algorithm for the automated detection and classification of ER. A total of 6,047 electrocardiograms were manually graded for ER by two experienced readers. The automated detection of ER was based on quantification of the characteristic slurring or notching in ER-positive leads. The ER detection algorithm was tested and its results were compared with manual grading, which served as the reference. Readers graded 183 ECGs (3.0%) as ER positive, of which the algorithm detected 176 recordings, resulting in sensitivity of 96.2%. Of the 5,864 ER-negative recordings, the algorithm classified 5,281 as negative, resulting in 90.1% specificity. Positive and negative predictive values for the algorithm were 23.2% and 99.9%, respectively, and its accuracy was 90.2%. Inferior ER was correctly detected in 84.6% and lateral ER in 98.6% of the cases. As the automatic algorithm has high sensitivity, it could be used as a prescreening tool for ER; only the electrocardiograms graded positive by the algorithm would be reviewed manually. This would reduce the need for manual labor by 90%. © 2014 Wiley Periodicals, Inc.
Contrast-Enhanced Ultrasound and Near-Infrared Spectroscopy of the Neonatal Bowel: Novel, Bedside, Noninvasive, and Radiation-Free Imaging for Early Detection of Necrotizing Enterocolitis.

PubMed

Al-Hamad, Suzanne; Hackam, David J; Goldstein, Seth D; Huisman, Thierry A G M; Darge, Kassa; Hwang, Misun

2018-05-31

Despite extensive research and improvements in the field of neonatal care, the morbidity and mortality associated with necrotizing enterocolitis (NEC) have remained unchanged over the past three decades. Early detection of ischemia and necrotic bowel is vital in improving morbidity and mortality associated with NEC; however, strategies for predicting and preventing NEC are lacking. Contrast-enhanced ultrasound (CEUS) and near-infrared spectroscopy (NIRS) are novel techniques in pediatrics that have been proven as safe modalities. CEUS has benefits over conventional ultrasound (US) by its improved real-time evaluation of the micro- and macrovascularities of normally and abnormally perfused tissue. US has been implemented as a useful adjunct to X-ray for earlier evaluation of NEC. NIRS is another noninvasive technique that has shown promise in improving early detection of NEC. The purpose of this article is to review the current understanding of changes in bowel perfusion in NEC, discuss the accuracy of abdominal US in detecting NEC, and explain how the use of CEUS and NIRS will enhance the precise and early detection of altered/pathological bowel wall perfusion in the initial development and course of NEC. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.
Early detection monitoring for larval dreissenid mussels: How much plankton sampling is enough?

USGS Publications Warehouse

Counihan, Timothy D.; Bollens, Stephen M.

2017-01-01

The development of quagga and zebra mussel (dreissenids) monitoring programs in the Pacific Northwest provides a unique opportunity to evaluate a regional invasive species detection effort early in its development. Recent studies suggest that the ecological and economic costs of a dreissenid infestation in the Pacific Northwest of the USA would be significant. Consequently, efforts are underway to monitor for the presence of dreissenids. However, assessments of whether these efforts provide for early detection are lacking. We use information collected from 2012 to 2014 to characterize the development of larval dreissenid monitoring programs in the states of Idaho, Montana, Oregon, and Washington in the context of introduction and establishment risk. We also estimate the effort needed for high-probability detection of rare planktonic taxa in four Columbia and Snake River reservoirs and assess whether the current level of effort provides for early detection. We found that the effort expended to monitor for dreissenid mussels increased substantially from 2012 to 2014, that efforts were distributed across risk categories ranging from high to very low, and that substantial gaps in our knowledge of both introduction and establishment risk exist. The estimated volume of filtered water required to fully census planktonic taxa or to provide high-probability detection of rare taxa was high for the four reservoirs examined. We conclude that the current level of effort expended does not provide for high-probability detection of larval dreissenids or other planktonic taxa when they are rare in these reservoirs. We discuss options to improve early detection capabilities.
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
Retinopathy predicts progression of fasting plasma glucose: An Early Diabetes Intervention Program (EDIP) Analysis

PubMed Central

Patel, Yash R.; Kirkman, M. Sue; Considine, Robert V; Hannon, Tamara S; Mather, Kieren J

2017-01-01

Background Retinopathy is increasingly recognized in prediabetic populations, and may herald increased risk of metabolic worsening. The Early Diabetes Intervention Program (EDIP) evaluated worsening of glycemia in screen-detected Type 2 diabetes, following participants for up to 5 years. Here we have evaluated whether the presence of retinopathy at the time of detection of diabetes was associated with accelerated progression of glycemia. Methods We prospectively studied 194 participants from EDIP with available baseline retinal photographs. Retinopathy was determined at baseline using 7-field fundus photography and defined as an Early Treatment of Diabetic Retinopathy Study Scale grading score of ≥20. Results At baseline, 12% of participants had classical retinal lesions indicating retinopathy. In univariate Cox proportional hazard analysis, the presence of retinopathy at baseline was associated with a doubled risk of progression of fasting plasma glucose (HR 2.02; 95% CI 1.05–3.89). The retinopathy effect was robust to individual adjustment for age and glucose, the most potent determinants of progression in EDIP. Conclusion Retinopathy was associated with increased risk of progression of fasting plasma glucose among adults with screen-detected, early diabetes. Early detection of retinopathy may help individualize more aggressive therapy to prevent progressive metabolic worsening in early diabetes. PMID:28003103
Early prediction of blonanserin response in Japanese patients with schizophrenia.

PubMed

Kishi, Taro; Matsuda, Yuki; Fujita, Kiyoshi; Iwata, Nakao

2014-01-01

Blonanserin is a second-generation antipsychotic used for the treatment of schizophrenia in Japan and Korea. The present study aimed to examine early prediction of blonanserin in patients with schizophrenia. An 8-week, prospective, single-arm, flexible-dose clinical trial of blonanserin in patients with schizophrenia was conducted under real-world conditions. The inclusion criteria were antipsychotic naïve, and first-episode schizophrenia patients or schizophrenia patients with no consumption of any antipsychotic medication for more than 4 weeks before enrollment in this study. The positive predictive value, negative predictive value, sensitivity, specificity, and predictive power were calculated for the response status at week 4 to predict the subsequent response at week 8. Thirty-seven patients were recruited (56.8% of them had first-episode schizophrenia), and 28 (75.7%) completed the trial. At week 8, blonanserin was associated with a significant improvement in the Positive and Negative Syndrome Scale (PANSS) total score (P<0.0001) and in positive (P<0.0001), negative (P<0.0001), and general subscale scores (P<0.0001). In terms of percentage improvement of PANSS total scores from baseline to week 8, 64.9% of patients showed a ≥20% reduction in the PANSS total score and 48.6% showed a ≥30% reduction. However, 8.1% of patients experienced at least one adverse event. Using the 20% reduction in the PANSS total score at week 4 as a definition of an early response, the negative predictive values for later responses (ie, reductions of ≥30 and ≥40 in the PANSS total scores) were 88.9% and 94.1%, respectively. The specificities were 80.0% and 51.6%, respectively. Our results suggest that the blonanserin response at week 4 could predict the later response at week 8.
Early prediction of blonanserin response in Japanese patients with schizophrenia

PubMed Central

Kishi, Taro; Matsuda, Yuki; Fujita, Kiyoshi; Iwata, Nakao

2014-01-01

Background Blonanserin is a second-generation antipsychotic used for the treatment of schizophrenia in Japan and Korea. The present study aimed to examine early prediction of blonanserin in patients with schizophrenia. Methods An 8-week, prospective, single-arm, flexible-dose clinical trial of blonanserin in patients with schizophrenia was conducted under real-world conditions. The inclusion criteria were antipsychotic naïve, and first-episode schizophrenia patients or schizophrenia patients with no consumption of any antipsychotic medication for more than 4 weeks before enrollment in this study. The positive predictive value, negative predictive value, sensitivity, specificity, and predictive power were calculated for the response status at week 4 to predict the subsequent response at week 8. Results Thirty-seven patients were recruited (56.8% of them had first-episode schizophrenia), and 28 (75.7%) completed the trial. At week 8, blonanserin was associated with a significant improvement in the Positive and Negative Syndrome Scale (PANSS) total score (P<0.0001) and in positive (P<0.0001), negative (P<0.0001), and general subscale scores (P<0.0001). In terms of percentage improvement of PANSS total scores from baseline to week 8, 64.9% of patients showed a ≥20% reduction in the PANSS total score and 48.6% showed a ≥30% reduction. However, 8.1% of patients experienced at least one adverse event. Using the 20% reduction in the PANSS total score at week 4 as a definition of an early response, the negative predictive values for later responses (ie, reductions of ≥30 and ≥40 in the PANSS total scores) were 88.9% and 94.1%, respectively. The specificities were 80.0% and 51.6%, respectively. Conclusion Our results suggest that the blonanserin response at week 4 could predict the later response at week 8. PMID:25285009

Feature Biases in Early Word Learning: Network Distinctiveness Predicts Age of Acquisition

ERIC Educational Resources Information Center

Engelthaler, Tomas; Hills, Thomas T.

2017-01-01

Do properties of a word's features influence the order of its acquisition in early word learning? Combining the principles of mutual exclusivity and shape bias, the present work takes a network analysis approach to understanding how feature distinctiveness predicts the order of early word learning. Distance networks were built from nouns with edge…
Devising a method towards development of early warning tool for detection of malaria outbreak.

PubMed

Verma, Preeti; Sarkar, Soma; Singh, Poonam; Dhiman, Ramesh C

2017-11-01

Uncertainty often arises in differentiating seasonal variation from outbreaks of malaria. The present study was aimed to generalize the theoretical structure of sine curve for detecting an outbreak so that a tool for early warning of malaria may be developed. A 'case/mean-ratio scale' system was devised for labelling the outbreak in respect of two diverse districts of Assam and Rajasthan. A curve-based method of analysis was developed for determining outbreak and using the properties of sine curve. It could be used as an early warning tool for Plasmodium falciparum malaria outbreaks. In the present method of analysis, the critical C max (peak value of sine curve) value of seasonally adjusted curve for P. falciparum malaria outbreak was 2.3 for Karbi Anglong and 2.2 for Jaisalmer districts. On case/mean-ratio scale, the C max value of malaria curve between C max and 3.5, the outbreak could be labelled as minor while >3.5 may be labelled as major. In epidemic years, with mean of case/mean ratio of ≥1.00 and root mean square (RMS) ≥1.504 of case/mean ratio, outbreaks can be predicted 1-2 months in advance. The present study showed that in P. falciparum cases in Karbi Anglong (Assam) and Jaisalmer (Rajasthan) districts, the rise in C max value of curve was always followed by rise in average/RMS or both and hence could be used as an early warning tool. The present method provides better detection of outbreaks than the conventional method of mean plus two standard deviation (mean+2 SD). The identified tools are simple and may be adopted for preparedness of malaria outbreaks.
A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness.

PubMed

Li, Gang; Chung, Wan-Young

2015-08-21

Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness.
Early Detection of Amyloid Plaque in Alzheimer’s Disease via X-ray Phase CT

DTIC Science & Technology

2016-08-01

AWARD NUMBER: W81XWH-12-1-0138 TITLE: Early Detection of Amyloid Plaque in Alzheimer’s Disease via X-ray Phase CT PRINCIPAL INVESTIGATOR...NUMBER W81XWH-12-1-0138 Early Detection of Amyloid Plaque in Alzheimer’s Disease via X-ray Phase CT 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...method for early detection of amyloid plaque in Alzheimer’s disease , with three Specific Aims: #1 Develop and optimize an x-ray PCCT to explore the
Model Development and Trial of Early Detection Manual for the Special Needs Children at Early Age Education Level

ERIC Educational Resources Information Center

Anwar, Zainul; Ingarianti, Tri Muji; Suryaningrum, Cahyaning

2016-01-01

This research was aimed to produce the manual for early detection for ABK at the level of early age education (PAUD = "Pendidikan Anak Usia Dini"). Research was "action research" with stages as proposed by Buunk and Van Vugt. Metodology of research these stages were called as PATH ("Problem-Analysis-Test…
Decoding the future from past experience: learning shapes predictions in early visual cortex.

PubMed

Luft, Caroline D B; Meeson, Alan; Welchman, Andrew E; Kourtzi, Zoe

2015-05-01

Learning the structure of the environment is critical for interpreting the current scene and predicting upcoming events. However, the brain mechanisms that support our ability to translate knowledge about scene statistics to sensory predictions remain largely unknown. Here we provide evidence that learning of temporal regularities shapes representations in early visual cortex that relate to our ability to predict sensory events. We tested the participants' ability to predict the orientation of a test stimulus after exposure to sequences of leftward- or rightward-oriented gratings. Using fMRI decoding, we identified brain patterns related to the observers' visual predictions rather than stimulus-driven activity. Decoding of predicted orientations following structured sequences was enhanced after training, while decoding of cued orientations following exposure to random sequences did not change. These predictive representations appear to be driven by the same large-scale neural populations that encode actual stimulus orientation and to be specific to the learned sequence structure. Thus our findings provide evidence that learning temporal structures supports our ability to predict future events by reactivating selective sensory representations as early as in primary visual cortex. Copyright © 2015 the American Physiological Society.
Systematic review of methods to predict and detect anastomotic leakage in colorectal surgery.

PubMed

Hirst, N A; Tiernan, J P; Millner, P A; Jayne, D G

2014-02-01

Anastomotic leakage is a serious complication of gastrointestinal surgery resulting in increased morbidity and mortality, poor function and predisposing to cancer recurrence. Earlier diagnosis and intervention can minimize systemic complications but is hindered by current diagnostic methods that are non-specific and often uninformative. The purpose of this paper is to review current developments in the field and to identify strategies for early detection and treatment of anastomotic leakage. A systematic literature search was performed using the MEDLINE, Embase, PubMed and Cochrane Library databases. Search terms included 'anastomosis' and 'leak' and 'diagnosis' or 'detection' and 'gastrointestinal' or 'colorectal'. Papers concentrating on the diagnosis of gastrointestinal anastomotic leak were identified and further searches were performed by cross-referencing. Computerized tomography CT scanning and water-soluble contrast studies are the current preferred techniques for diagnosing anastomotic leakage but suffer from variable sensitivity and specificity, have logistical constraints and may delay timely intervention. Intra-operative endoscopy and imaging may offer certain advantages, but the ability to predict anastomotic leakage is unproven. Newer techniques involve measurement of biomarkers for anastomotic leakage and have the potential advantage of providing cheap real-time monitoring for postoperative complications. Current diagnostic tests often fail to diagnose anastomotic leak at an early stage that enables timely intervention and minimizes serious morbidity and mortality. Emerging technologies, based on detection of local biomarkers, have achieved proof of concept status but require further evaluation to determine whether they translate into improved patient outcomes. Further research is needed to address this important, yet relatively unrecognized, area of unmet clinical need. Colorectal Disease © 2013 The Association of Coloproctology of Great Britain
Early social networks predict survival in wild bottlenose dolphins.

PubMed

Stanton, Margaret A; Mann, Janet

2012-01-01

A fundamental question concerning group-living species is what factors influence the evolution of sociality. Although several studies link adult social bonds to fitness, social patterns and relationships are often formed early in life and are also likely to have fitness consequences, particularly in species with lengthy developmental periods, extensive social learning, and early social bond-formation. In a longitudinal study of bottlenose dolphins (Tursiops sp.), calf social network structure, specifically the metric eigenvector centrality, predicted juvenile survival in males. Additionally, male calves that died post-weaning had stronger ties to juvenile males than surviving male calves, suggesting that juvenile males impose fitness costs on their younger counterparts. Our study indicates that selection is acting on social traits early in life and highlights the need to examine the costs and benefits of social bonds during formative life history stages.
Early detection of materials degradation

NASA Astrophysics Data System (ADS)

Meyendorf, Norbert

2017-02-01

Lightweight components for transportation and aerospace applications are designed for an estimated lifecycle, taking expected mechanical and environmental loads into account. The main reason for catastrophic failure of components within the expected lifecycle are material inhomogeneities, like pores and inclusions as origin for fatigue cracks, that have not been detected by NDE. However, material degradation by designed or unexpected loading conditions or environmental impacts can accelerate the crack initiation or growth. Conventional NDE methods are usually able to detect cracks that are formed at the end of the degradation process, but methods for early detection of fatigue, creep, and corrosion are still a matter of research. For conventional materials ultrasonic, electromagnetic, or thermographic methods have been demonstrated as promising. Other approaches are focused to surface damage by using optical methods or characterization of the residual surface stresses that can significantly affect the creation of fatigue cracks. For conventional metallic materials, material models for nucleation and propagation of damage have been successfully applied for several years. Material microstructure/property relations are well established and the effect of loading conditions on the component life can be simulated. For advanced materials, for example carbon matrix composites or ceramic matrix composites, the processes of nucleation and propagation of damage is still not fully understood. For these materials NDE methods can not only be used for the periodic inspections, but can significantly contribute to the material scientific knowledge to understand and model the behavior of composite materials.
Development of an assisting detection system for early infarct diagnosis

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

Sim, K. S.; Nia, M. E.; Ee, C. S.

2015-04-24

In this paper, a detection assisting system for early infarct detection is developed. This new developed method is used to assist the medical practitioners to diagnose infarct from computed tomography images of brain. Using this assisting system, the infarct could be diagnosed at earlier stages. The non-contrast computed tomography (NCCT) brain images are the data set used for this system. Detection module extracts the pixel data from NCCT brain images, and produces the colourized version of images. The proposed method showed great potential in detecting infarct, and helps medical practitioners to make earlier and better diagnoses.
Interactions between empathy and resting heart rate in early adolescence predict violent behavior in late adolescence and early adulthood.

PubMed

Galán, Chardée A; Choe, Daniel Ewon; Forbes, Erika E; Shaw, Daniel S

2017-12-01

Although resting heart rate (RHR) and empathy are independently and negatively associated with violent behavior, relatively little is known about the interplay between these psychophysiological and temperament-related risk factors. Using a sample of 160 low-income, racially diverse men followed prospectively from infancy through early adulthood, this study examined whether RHR and empathy during early adolescence independently and interactively predict violent behavior and related correlates in late adolescence and early adulthood. Controlling for child ethnicity, family income, and child antisocial behavior at age 12, empathy inversely predicted moral disengagement and juvenile petitions for violent crimes, while RHR was unrelated to all measures of violent behavior. Interactive effects were also evident such that among men with lower but not higher levels of RHR, lower empathy predicted increased violent behavior, as indexed by juvenile arrests for violent offenses, peer-reported violent behavior at age 17, self-reported moral disengagement at age 17, and self-reported violent behavior at age 20. Implications for prevention and intervention are considered. Specifically, targeting empathic skills among individuals at risk for violent behavior because of specific psychophysiological profiles may lead to more impactful interventions. © 2017 Association for Child and Adolescent Mental Health.
Multi-disciplinary team for early gastric cancer diagnosis improves the detection rate of early gastric cancer.

PubMed

Di, Lianjun; Wu, Huichao; Zhu, Rong; Li, Youfeng; Wu, Xinglong; Xie, Rui; Li, Hongping; Wang, Haibo; Zhang, Hua; Xiao, Hong; Chen, Hui; Zhen, Hong; Zhao, Kui; Yang, Xuefeng; Xie, Ming; Tuo, Bigung

2017-12-06

Gastric cancer is a frequent malignant tumor worldwide and its early detection is crucial for curing the disease and enhancing patients' survival rate. This study aimed to assess whether the multi-disciplinary team (MDT) can improve the detection rate of early gastric cancer (EGC). The detection rate of EGC at the Digestive Endoscopy Center, Affiliated Hospital, Zunyi Medical College, China between September 2013 and September 2015 was analyzed. MDT for the diagnosis of EGC in the hospital was established in September 2014. The study was divided into 2 time periods: September 1, 2013 to August 31, 2014 (period 1) and September 1, 2014 to September 1, 2015 (period 2). A total of 60,800 patients' gastroscopies were performed during the two years. 61 of these patients (0.1%) were diagnosed as EGC, accounting for 16.44% (61/371) of total patients with gastric cancer. The EGC detection rate before MDT (period 1) was 0.05% (16/29403), accounting for 9.09% (16/176) of total patients with gastric cancer during this period. In comparison, the EGC detection rate during MDT (period 2) was 0.15% (45/31397), accounting for 23% (45/195) of total patients with gastric cancer during this period (P < 0.05). Univariate and multivariate logistic analyses showed that intensive gastroscopy for high risk patients of gastric cancer enhanced the detection rate of EGC in cooperation with Department of Pathology (OR = 10.1, 95% CI 2.39-43.3, P < 0.05). MDT could improve the endoscopic detection rate of EGC.
Nanostructured materials with plasmonic nanobiosensors for early cancer detection: A past and future prospect.

PubMed

Sugumaran, Sathish; Jamlos, Mohd Faizal; Ahmad, Mohd Noor; Bellan, Chandar Shekar; Schreurs, Dominique

2018-02-15

Early cancer detection and treatment is an emerging and fascinating field of plasmonic nanobiosensor research. It paves to enrich a life without affecting living cells leading to a possible survival of the patient. This review describes a past and future prospect of an integrated research field on nanostructured metamaterials, microwave transmission, surface plasmonic resonance, nanoantennas, and their manifested versatile properties with nano-biosensors towards early cancer detection to preserve human health. Interestingly, (i) microwave transmission shows more advantages than other electromagnetic radiation in reacting with biological tissues, (ii) nanostructured metamaterial (Au) with special properties like size and shape can stimulate plasmonic effects, (iii) plasmonic based nanobiosensors are to explore the efficacy for early cancer tumour detection or single molecular detection and (iv) nanoantenna wireless communication by using microwave inverse scattering nanomesh (MISN) technique instead of conventional techniques can be adopted to characterize the microwave scattered signals from the biomarkers. It reveals that the nanostructured material with plasmonic nanobiosensor paves a fascinating platform towards early detection of cancer tumour and is anticipated to be exploited as a magnificent field in the future. Copyright © 2017 Elsevier B.V. All rights reserved.
Early Detection of Pancreatic Cancer: The Role of Industry in the Development of Biomarkers.

PubMed

Kenner, Barbara J; Go, Vay Liang W; Chari, Suresh T; Goldberg, Ann E; Rothschild, Laura J

A diagnosis of pancreatic cancer is devastating owing to its poor prognosis, with a 5-year survival rate of only 9%. Currently, most individuals are diagnosed at a late stage when treatment options are limited. Early detection of pancreatic cancer provides the greatest hope for making substantial improvements in survival. The Kenner Family Research Fund in partnership with the American Pancreatic Association has sponsored a series of fora to stimulate discussion and collaboration on early detection of pancreatic cancer. At the first forum in 2014, "Early Detection of Sporadic Pancreatic Cancer Summit Conference," a strategic plan was set forth by an international group of interdisciplinary scientific representatives and subsequently The Strategic Map for Innovation was generated. The current conference report is the third forum in the series, "Early Detection of Pancreatic Cancer: The Role of Industry in the Development of Biomarkers," which was held in Boston, Massachusetts, on October 27, 2016. This report provides an overview of examples of innovative initiatives by industry and confirms the critical need for collaboration among industry, government, research institutions, and advocacy groups in order to make pancreatic cancer more easily detectable in its earlier stages, when it is more treatable.
Detection and Proportion of Very Early Dental Caries in Independent Living Older Adults

PubMed Central

Holtzman, Jennifer S.; Kohanchi, Daniel; Biren-Fetz, John; Fontana, Margherita; Ramchandani, Manisha; Osann, Kathryn; Hallajian, Lucy; Mansour, Stephanie; Nabelsi, Tasneem; Chung, Na Eun; Wilder-Smith, Petra

2015-01-01

Background and Objectives Dental caries is an important healthcare challenge in adults over 65 years of age. Integration of oral health screening into non-dental primary care practice may improve access to preventive dental care for vulnerable populations such as the elderly. Such integration would require easy, fast, and accurate early caries detection tools. Primary goal of this study was to evaluate the diagnostic performance of optical coherence tomography (OCT) imaging for detecting very early caries in the elderly living in community-based settings. The International Caries Detection and Assessment System (ICDAS) served as gold standard. Secondary goal of this study was to provide baseline prevalence data of very early caries lesions in independent living adults aged 65+ years. Materials and Methods Seventy-two subjects were recruited from three sites in Southern California: a retirement community, a senior health fair, and a convalescent hospital. Clinical examination was performed using the ICDAS visual criteria and this was followed by OCT imaging. The two-dimensional OCT images (B-scan) were analyzed with simple software. Locations with a log of back-scattered light intensity (BSLI) below 2.9 were scored as sound, and areas equaling or exceeding 2.9 BSLI were considered carious. Diagnostic performance of OCT imaging was compared with ICDAS score. Results OCT-based diagnosis demonstrated very good sensitivity (95.1%) and good specificity (85.8%). 54.7% of dentate subjects had at least one tooth with very early coronal caries. Conclusions Early coronal decay is prevalent in the unrestored pits and fissures of coronal surfaces of teeth in independent living adults aged 65+ years. Though OCT imaging coupled with a simple diagnostic algorithm can accurately detect areas of very early caries in community-based settings, existing devices are expensive and not well-suited for use by non-dental health care providers. Simple, inexpensive, fast, and accurate tools
Empirical evaluation demonstrated importance of validating biomarkers for early detection of cancer in screening settings to limit the number of false-positive findings.

PubMed

Chen, Hongda; Knebel, Phillip; Brenner, Hermann

2016-07-01

Search for biomarkers for early detection of cancer is a very active area of research, but most studies are done in clinical rather than screening settings. We aimed to empirically evaluate the role of study setting for early detection marker identification and validation. A panel of 92 candidate cancer protein markers was measured in 35 clinically identified colorectal cancer patients and 35 colorectal cancer patients identified at screening colonoscopy. For each case group, we selected 38 controls without colorectal neoplasms at screening colonoscopy. Single-, two- and three-marker combinations discriminating cases and controls were identified in each setting and subsequently validated in the alternative setting. In all scenarios, a higher number of predictive biomarkers were initially detected in the clinical setting, but a substantially lower proportion of identified biomarkers could subsequently be confirmed in the screening setting. Confirmation rates were 50.0%, 84.5%, and 74.2% for one-, two-, and three-marker algorithms identified in the screening setting and were 42.9%, 18.6%, and 25.7% for algorithms identified in the clinical setting. Validation of early detection markers of cancer in a true screening setting is important to limit the number of false-positive findings. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
Predictive Detection of Tuberculosis using Electronic Nose Technology

NASA Astrophysics Data System (ADS)

Gibson, Tim; Kolk, Arend; Reither, Klaus; Kuipers, Sjoukje; Hallam, Viv; Chandler, Rob; Dutta, Ritaban; Maboko, Leonard; Jung, Jutta; Klatser, Paul

2009-05-01

The adaptation and use of a Bloodhound® ST214 electronic nose to rapidly detect TB in sputum samples has been discussed in the past, with some promising results being obtained in 2007. Some of the specific VOC's associated with Mycobacteria tuberculosis organisms are now being discovered and a paper was published in 2008, but the method of predicting the presence of TB in sputum samples using the VOC biomarkers has yet to be fully optimised. Nevertheless, with emphasis on the sampling techniques and with new data processing techniques to obtain consistent results progress is being made Sensitivity and specificity levels for field detection of TB have been set by WHO at a minimum level of 85% and 95% respectively, and the e-nose technique is working towards these figures. In a series of experiments carried out in Mbeya, Tanzania, Africa, data from a full 5 days of sampling was combined giving a total of 248 sputum samples analysed. From the data obtained we can report results that show specificities and sensitivities in the 70-80% region when actually predicting the presence of TB in unknown sputum samples. The results are a further step forward in the rapid detection of TB in the clinics in developing countries and show continued promise for future development of an optimised instrument for TB prediction.
Negative affective spillover from daily events predicts early response to cognitive therapy for depression.

PubMed

Cohen, Lawrence H; Gunthert, Kathleen C; Butler, Andrew C; Parrish, Brendt P; Wenze, Susan J; Beck, Judith S

2008-12-01

This study evaluated the predictive role of depressed outpatients' (N = 62) affective reactivity to daily stressors in their rates of improvement in cognitive therapy (CT). For 1 week before treatment, patients completed nightly electronic diaries that assessed daily stressors and negative affect (NA). The authors used multilevel modeling to compute each patient's within-day relationship between daily stressors and daily NA (within-day reactivity), as well as the relationship between daily stressors and next-day NA (next-day reactivity; affective spillover). In growth model analyses, the authors evaluated the predictive role of patients' NA reactivity in their early (Sessions 1-4) and late (Sessions 5-12) response to CT. Within-day NA reactivity did not predict early or late response to CT. However, next-day reactivity predicted early response to CT, such that patients who had greater NA spillover in response to negative events had a slower rate of symptom change during the first 4 sessions. Affective spillover did not influence later response to CT. The findings suggest that depressed patients who have difficulty bouncing back the next day from their NA reactions to a relative increase in daily negative events will respond less quickly to the early sessions of CT.
Early Recurrence After Hepatectomy for Colorectal Liver Metastases: What Optimal Definition and What Predictive Factors?

PubMed Central

Imai, Katsunori; Allard, Marc-Antoine; Benitez, Carlos Castro; Vibert, Eric; Sa Cunha, Antonio; Cherqui, Daniel; Castaing, Denis; Bismuth, Henri; Baba, Hideo

2016-01-01

Background. The purpose of this study was to determine the optimal definition and elucidate the predictive factors of early recurrence after surgery for colorectal liver metastases (CRLM). Methods. Among 987 patients who underwent curative surgery for CRLM from 1990 to 2012, 846 with a minimum follow-up period of 24 months were eligible for this study. The minimum p value approach of survival after initial recurrence was used to determine the optimal cutoff for the definition of early recurrence. The predictive factors of early recurrence and prognostic factors of survival were analyzed. Results. For 667 patients (79%) who developed recurrence, the optimal cutoff point of early recurrence was determined to be 8 months after surgery. The impact of early recurrence on survival was demonstrated mainly in patients who received preoperative chemotherapy. Among the 691 patients who received preoperative chemotherapy, recurrence was observed in 562 (81%), and survival in patients with early recurrence was significantly worse than in those with late recurrence (5-year survival 18.5% vs. 53.4%, p < .0001). Multivariate logistic analysis identified age ≤57 years (p = .0022), >1 chemotherapy line (p = .03), disease progression during last-line chemotherapy (p = .024), >3 tumors (p = .0014), and carbohydrate antigen 19-9 >60 U/mL (p = .0003) as independent predictors of early recurrence. Salvage surgery for recurrence significantly improved survival, even in patients with early recurrence. Conclusion. The optimal cutoff point of early recurrence was determined to be 8 months. The preoperative prediction of early recurrence is possible and crucial for designing effective perioperative chemotherapy regimens. Implications for Practice: In this study, the optimal cutoff point of early recurrence was determined to be 8 months after surgery based on the minimum p value approach, and its prognostic impact was demonstrated mainly in patients who received preoperative chemotherapy
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

Genetics and Early Detection in Idiopathic Pulmonary Fibrosis

PubMed Central

Putman, Rachel K.; Rosas, Ivan O.

2014-01-01

Genetic studies hold promise in helping to identify patients with early idiopathic pulmonary fibrosis (IPF). Recent studies using chest computed tomograms (CTs) in smokers and in the general population have demonstrated that imaging abnormalities suggestive of an early stage of pulmonary fibrosis are not uncommon and are associated with respiratory symptoms, physical examination abnormalities, and physiologic decrements expected, but less severe than those noted in patients with IPF. Similarly, recent genetic studies have demonstrated strong and replicable associations between a common promoter polymorphism in the mucin 5B gene (MUC5B) and both IPF and the presence of abnormal imaging findings in the general population. Despite these findings, it is important to note that the definition of early-stage IPF remains unclear, limited data exist to definitively connect abnormal imaging findings to IPF, and genetic studies assessing early-stage pulmonary fibrosis remain in their infancy. In this perspective we provide updated information on interstitial lung abnormalities and their connection to IPF. We summarize information on the genetics of pulmonary fibrosis by focusing on the recent genetic findings of MUC5B. Finally, we discuss the implications of these findings and suggest a roadmap for the use of genetics in the detection of early IPF. PMID:24547893
A Novel Arc Fault Detector for Early Detection of Electrical Fires

PubMed Central

Yang, Kai; Zhang, Rencheng; Yang, Jianhong; Liu, Canhua; Chen, Shouhong; Zhang, Fujiang

2016-01-01

Arc faults can produce very high temperatures and can easily ignite combustible materials; thus, they represent one of the most important causes of electrical fires. The application of arc fault detection, as an emerging early fire detection technology, is required by the National Electrical Code to reduce the occurrence of electrical fires. However, the concealment, randomness and diversity of arc faults make them difficult to detect. To improve the accuracy of arc fault detection, a novel arc fault detector (AFD) is developed in this study. First, an experimental arc fault platform is built to study electrical fires. A high-frequency transducer and a current transducer are used to measure typical load signals of arc faults and normal states. After the common features of these signals are studied, high-frequency energy and current variations are extracted as an input eigenvector for use by an arc fault detection algorithm. Then, the detection algorithm based on a weighted least squares support vector machine is designed and successfully applied in a microprocessor. Finally, an AFD is developed. The test results show that the AFD can detect arc faults in a timely manner and interrupt the circuit power supply before electrical fires can occur. The AFD is not influenced by cross talk or transient processes, and the detection accuracy is very high. Hence, the AFD can be installed in low-voltage circuits to monitor circuit states in real-time to facilitate the early detection of electrical fires. PMID:27070618
Improving early detection initiatives: a qualitative study exploring perspectives of older people and professionals.

PubMed

Lette, Manon; Stoop, Annerieke; Lemmens, Lidwien C; Buist, Yvette; Baan, Caroline A; de Bruin, Simone R

2017-06-23

A wide range of initiatives on early detection and intervention have been developed to proactively identify problems related to health and wellbeing in (frail) older people, with the aim of supporting them to live independently for as long as possible. Nevertheless, it remains unclear what the best way is to design such initiatives and how older people's needs and preferences can be best addressed. This study aimed to address this gap in the literature by exploring: 1) older people's perspectives on health and living environment in relation to living independently at home; 2) older people's needs and preferences in relation to initiating and receiving care and support; and 3) professionals' views on what would be necessary to enable the alignment of early detection initiatives with older people's own needs and preferences. In this qualitative study, we conducted semi-structured interviews with 36 older people and 19 professionals in proactive elderly care. Data were analysed using the framework analysis method. From the interviews with older people important themes in relation to health and living environment emerged, such as maintaining independence, appropriate housing, social relationships, a supporting network and a sense of purpose and autonomy. Older people preferred to remain self-sufficient, and they would rather not ask for help for psychological or social problems. However, the interviews also highlighted that they were not always able or willing to anticipate future needs, which can hinder early detection or early intervention. At the same time, professionals indicated that older people tend to over-estimate their self-reliance and therefore advocated for early detection and intervention, including social and psychological issues. Older people have a broad range of needs in different domains of life. Discrepancies exist between older people and professionals with regard to their views on timing and scope of early detection initiatives. This study aimed
Orthostatic hypotension predicts motor decline in early Parkinson disease.

PubMed

Kotagal, Vikas; Lineback, Christina; Bohnen, Nicolaas I; Albin, Roger L

2016-11-01

Orthostatic hypotension is increasingly reported as a risk factor for development of late-stage disease features in Parkinson disease (PD). Less is known about its significance in individuals with early PD who are often targeted for neuroprotective trials. Using data from the CALM-PD trial (n = 275), we explored whether early orthostatic hypotension predicts a decline in the Unified Parkinson's Disease Rating Scale (UPDRS) II (activities of daily living) or UDPRS III (motor) score after 102 weeks. We also explored risk factors for worsening orthostatic hypotension over a nearly 2-year period. After controlling for age, disease duration, gender, study drug, change in mini-mental status exam score, levodopa equivalent dose, and baseline UPDRS II or III score respectively, the degree of orthostatic hypotension at enrollment associated with a worsening in UPDRS motor score (t = 2.40, p = 0.017) at week 102 but not with UPDRS ADL score (t = 0.83, p = 0.409). Worsening in orthostatic hypotension during the study associated with longer disease duration (t = 2.37, p = 0.019) and lower body mass index (BMI) (t = -2.96, p = 0.003). Baseline orthostatic hypotension is a predictor of UPDRS motor decline in individuals with early PD and should be accounted for in clinical trial design. Low BMI may predict orthostatic hypotension in PD. Copyright © 2016 Elsevier Ltd. All rights reserved.
Catalyzing Novel Approaches to Rapid, Accurate, and Affordable Early Cancer Detection.

PubMed

Dhar, Asif; Meagher, Beth; Ryscavage, Andrew

Inspired by the Cancer Moonshot, a dedicated team of professionals worked with leaders across the cancer ecosystem to look for an opportunity to radically reduce cancer mortality globally by focusing on early cancer detection. After an initial survey of cancer innovation, progress, and pitfalls, the team believed that if new rapid, affordable, and accurate early detection solutions were appropriately brought to market, it would be possible to intervene earlier when cancer is most treatable.An extensive process began, informed by dozens of experts in the cancer ecosystem. The Cancer XPRIZE team designed a prize competition where "the winning team will develop a means to rapidly, accurately, and affordably screen for early cancers where intervention can reduce human suffering."The following outlines the Cancer XPRIZE's experience using a powerful approach-the radical prize design-to catch more cancers in time to make a difference saving lives, dollars, and suffering.
Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.
A Context-Aware EEG Headset System for Early Detection of Driver Drowsiness

PubMed Central

Li, Gang; Chung, Wan-Young

2015-01-01

Driver drowsiness is a major cause of mortality in traffic accidents worldwide. Electroencephalographic (EEG) signal, which reflects the brain activities, is more directly related to drowsiness. Thus, many Brain-Machine-Interface (BMI) systems have been proposed to detect driver drowsiness. However, detecting driver drowsiness at its early stage poses a major practical hurdle when using existing BMI systems. This study proposes a context-aware BMI system aimed to detect driver drowsiness at its early stage by enriching the EEG data with the intensity of head-movements. The proposed system is carefully designed for low-power consumption with on-chip feature extraction and low energy Bluetooth connection. Also, the proposed system is implemented using JAVA programming language as a mobile application for on-line analysis. In total, 266 datasets obtained from six subjects who participated in a one-hour monotonous driving simulation experiment were used to evaluate this system. According to a video-based reference, the proposed system obtained an overall detection accuracy of 82.71% for classifying alert and slightly drowsy events by using EEG data alone and 96.24% by using the hybrid data of head-movement and EEG. These results indicate that the combination of EEG data and head-movement contextual information constitutes a robust solution for the early detection of driver drowsiness. PMID:26308002
The Early Detection of Pancreatic Cancer: What Will it Take to Diagnose and Treat Curable Pancreatic Neoplasia?

PubMed Central

Lennon, Anne Marie; Wolfgang, Christopher L.; Canto, Marcia Irene; Klein, Alison P.; Herman, Joseph M.; Goggins, Michael; Fishman, Elliot K.; Kamel, Ihab; Weiss, Matthew J.; Diaz, Luis A.; Papadopoulos, Nickolas; Kinzler, Kenneth W.; Vogelstein, Bert; Hruban, Ralph H.

2014-01-01

Pancreatic cancer is the deadliest of all solid malignancies. Early detection offers the best hope for a cure, but characteristics of this disease such as the lack of early clinical symptoms, make the early detection difficult. Recent genetic mapping of the molecular evolution of pancreatic cancer suggests that a large window of opportunity exists for the early detection of pancreatic neoplasia, and developments in cancer genetics offer new, potentially highly specific, approaches for screening for curable pancreatic neoplasia. We review the challenges of screening for early pancreatic neoplasia, as well as opportunities presented by incorporating molecular genetics into these efforts. PMID:24924775
A Simulation-Based Study on the Comparison of Statistical and Time Series Forecasting Methods for Early Detection of Infectious Disease Outbreaks.

PubMed

Yang, Eunjoo; Park, Hyun Woo; Choi, Yeon Hwa; Kim, Jusim; Munkhdalai, Lkhagvadorj; Musa, Ibrahim; Ryu, Keun Ho

2018-05-11

Early detection of infectious disease outbreaks is one of the important and significant issues in syndromic surveillance systems. It helps to provide a rapid epidemiological response and reduce morbidity and mortality. In order to upgrade the current system at the Korea Centers for Disease Control and Prevention (KCDC), a comparative study of state-of-the-art techniques is required. We compared four different temporal outbreak detection algorithms: the CUmulative SUM (CUSUM), the Early Aberration Reporting System (EARS), the autoregressive integrated moving average (ARIMA), and the Holt-Winters algorithm. The comparison was performed based on not only 42 different time series generated taking into account trends, seasonality, and randomly occurring outbreaks, but also real-world daily and weekly data related to diarrhea infection. The algorithms were evaluated using different metrics. These were namely, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), F1 score, symmetric mean absolute percent error (sMAPE), root-mean-square error (RMSE), and mean absolute deviation (MAD). Although the comparison results showed better performance for the EARS C3 method with respect to the other algorithms, despite the characteristics of the underlying time series data, Holt⁻Winters showed better performance when the baseline frequency and the dispersion parameter values were both less than 1.5 and 2, respectively.
Early detection of ecosystem regime shifts: a multiple method evaluation for management application.

PubMed

Lindegren, Martin; Dakos, Vasilis; Gröger, Joachim P; Gårdmark, Anna; Kornilovs, Georgs; Otto, Saskia A; Möllmann, Christian

2012-01-01

Critical transitions between alternative stable states have been shown to occur across an array of complex systems. While our ability to identify abrupt regime shifts in natural ecosystems has improved, detection of potential early-warning signals previous to such shifts is still very limited. Using real monitoring data of a key ecosystem component, we here apply multiple early-warning indicators in order to assess their ability to forewarn a major ecosystem regime shift in the Central Baltic Sea. We show that some indicators and methods can result in clear early-warning signals, while other methods may have limited utility in ecosystem-based management as they show no or weak potential for early-warning. We therefore propose a multiple method approach for early detection of ecosystem regime shifts in monitoring data that may be useful in informing timely management actions in the face of ecosystem change.
Early Detection of Ecosystem Regime Shifts: A Multiple Method Evaluation for Management Application

PubMed Central

Lindegren, Martin; Dakos, Vasilis; Gröger, Joachim P.; Gårdmark, Anna; Kornilovs, Georgs; Otto, Saskia A.; Möllmann, Christian

2012-01-01

Critical transitions between alternative stable states have been shown to occur across an array of complex systems. While our ability to identify abrupt regime shifts in natural ecosystems has improved, detection of potential early-warning signals previous to such shifts is still very limited. Using real monitoring data of a key ecosystem component, we here apply multiple early-warning indicators in order to assess their ability to forewarn a major ecosystem regime shift in the Central Baltic Sea. We show that some indicators and methods can result in clear early-warning signals, while other methods may have limited utility in ecosystem-based management as they show no or weak potential for early-warning. We therefore propose a multiple method approach for early detection of ecosystem regime shifts in monitoring data that may be useful in informing timely management actions in the face of ecosystem change. PMID:22808007
Nanotechnology-Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer

DTIC Science & Technology

2016-08-01

1 AD _________________ AWARD NUMBER: W81XWH-15-1-0157 TITLE: Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate...DATES COVERED 15 Jul 2015 - 14 Jul 2016 4. TITLE AND SUBTITLE Nanotechnology -Based Detection of Novel microRNAs for Early Diagnosis of Prostate Cancer...the expression level of deregulated miRNAs in mouse and human PCa tissues as well as serum samples using an advanced nanotechnology -based sensing
Video comparator system for early detection of cutaneous malignant melanoma

NASA Astrophysics Data System (ADS)

Craine, Eric R.; Craine, Brian L.

1992-05-01

The recognized incidence of cutaneous malignant melanoma in the United States is now rising faster than any other cancer, increasing by 83% from 1980 to 1987. Recent revelations that depletion of the earth's ozone layer is accelerating at a more rapid rate than previously believed can only exacerbate current projections for the increased incidence of this deadly disease. Because there is no good treatment for metastatic melanoma even small cancers often prove fatal if not detected early. Melanoma allowed to invade the subcutaneous tissue is associated with a five-year survival rate of only 44%. Ironically, few cancers provide a greater opportunity for early discovery and cure. Cutaneous melanoma is not only located where it is readily observed, but typically undergoes a `radial growth' phase prior to metastasis. During this phase the net growth is superficial and circumferential, gradually increasing the area of the lesion and changing its coloration. Screening measures for the early detection of melanoma must concentrate on two primary tasks: (1) detection of lesion changes indicative of the radial growth stage of malignancy and (2) alerting the patient and physician to the existence of a new or changed lesion on the skin. To accomplish these goals we have experimented with the applicability of a microcomputer based video imaging system which stores an image archive of historical reference images for each patient. With the acquisition of new images of the patient, easily registered with the archival images through a technique we have developed we are able to perform a blink comparison of the image pairs. This technique appears to be far more effective than currently used techniques for detecting changed lesions on a comprehensive basis.
Early functional MRI activation predicts motor outcome after ischemic stroke: a longitudinal, multimodal study.

PubMed

Du, Juan; Yang, Fang; Zhang, Zhiqiang; Hu, Jingze; Xu, Qiang; Hu, Jianping; Zeng, Fanyong; Lu, Guangming; Liu, Xinfeng

2018-05-15

An accurate prediction of long term outcome after stroke is urgently required to provide early individualized neurorehabilitation. This study aimed to examine the added value of early neuroimaging measures and identify the best approaches for predicting motor outcome after stroke. This prospective study involved 34 first-ever ischemic stroke patients (time since stroke: 1-14 days) with upper limb impairment. All patients underwent baseline multimodal assessments that included clinical (age, motor impairment), neurophysiological (motor-evoked potentials, MEP) and neuroimaging (diffusion tensor imaging and motor task-based fMRI) measures, and also underwent reassessment 3 months after stroke. Bivariate analysis and multivariate linear regression models were used to predict the motor scores (Fugl-Meyer assessment, FMA) at 3 months post-stroke. With bivariate analysis, better motor outcome significantly correlated with (1) less initial motor impairment and disability, (2) less corticospinal tract injury, (3) the initial presence of MEPs, (4) stronger baseline motor fMRI activations. In multivariate analysis, incorporating neuroimaging data improved the predictive accuracy relative to only clinical and neurophysiological assessments. Baseline fMRI activation in SMA was an independent predictor of motor outcome after stroke. A multimodal model incorporating fMRI and clinical measures best predicted the motor outcome following stroke. fMRI measures obtained early after stroke provided independent prediction of long-term motor outcome.
Characterization of normality of chaotic systems including prediction and detection of anomalies

NASA Astrophysics Data System (ADS)

Engler, Joseph John

Accurate prediction and control pervades domains such as engineering, physics, chemistry, and biology. Often, it is discovered that the systems under consideration cannot be well represented by linear, periodic nor random data. It has been shown that these systems exhibit deterministic chaos behavior. Deterministic chaos describes systems which are governed by deterministic rules but whose data appear to be random or quasi-periodic distributions. Deterministically chaotic systems characteristically exhibit sensitive dependence upon initial conditions manifested through rapid divergence of states initially close to one another. Due to this characterization, it has been deemed impossible to accurately predict future states of these systems for longer time scales. Fortunately, the deterministic nature of these systems allows for accurate short term predictions, given the dynamics of the system are well understood. This fact has been exploited in the research community and has resulted in various algorithms for short term predictions. Detection of normality in deterministically chaotic systems is critical in understanding the system sufficiently to able to predict future states. Due to the sensitivity to initial conditions, the detection of normal operational states for a deterministically chaotic system can be challenging. The addition of small perturbations to the system, which may result in bifurcation of the normal states, further complicates the problem. The detection of anomalies and prediction of future states of the chaotic system allows for greater understanding of these systems. The goal of this research is to produce methodologies for determining states of normality for deterministically chaotic systems, detection of anomalous behavior, and the more accurate prediction of future states of the system. Additionally, the ability to detect subtle system state changes is discussed. The dissertation addresses these goals by proposing new representational
Role of EEG as Biomarker in the Early Detection and Classification of Dementia

PubMed Central

Al-Qazzaz, Noor Kamal; Ali, Sawal Hamid Bin MD.; Ahmad, Siti Anom; Chellappan, Kalaivani; Islam, Md. Shabiul; Escudero, Javier

2014-01-01

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis. PMID:25093211
Role of EEG as biomarker in the early detection and classification of dementia.

PubMed

Al-Qazzaz, Noor Kamal; Ali, Sawal Hamid Bin Md; Ahmad, Siti Anom; Chellappan, Kalaivani; Islam, Md Shabiul; Escudero, Javier

2014-01-01

The early detection and classification of dementia are important clinical support tasks for medical practitioners in customizing patient treatment programs to better manage the development and progression of these diseases. Efforts are being made to diagnose these neurodegenerative disorders in the early stages. Indeed, early diagnosis helps patients to obtain the maximum treatment benefit before significant mental decline occurs. The use of electroencephalogram as a tool for the detection of changes in brain activities and clinical diagnosis is becoming increasingly popular for its capabilities in quantifying changes in brain degeneration in dementia. This paper reviews the role of electroencephalogram as a biomarker based on signal processing to detect dementia in early stages and classify its severity. The review starts with a discussion of dementia types and cognitive spectrum followed by the presentation of the effective preprocessing denoising to eliminate possible artifacts. It continues with a description of feature extraction by using linear and nonlinear techniques, and it ends with a brief explanation of vast variety of separation techniques to classify EEG signals. This paper also provides an idea from the most popular studies that may help in diagnosing dementia in early stages and classifying through electroencephalogram signal processing and analysis.
FluBreaks: early epidemic detection from Google flu trends.

PubMed

Pervaiz, Fahad; Pervaiz, Mansoor; Abdur Rehman, Nabeel; Saif, Umar

2012-10-04

The Google Flu Trends service was launched in 2008 to track changes in the volume of online search queries related to flu-like symptoms. Over the last few years, the trend data produced by this service has shown a consistent relationship with the actual number of flu reports collected by the US Centers for Disease Control and Prevention (CDC), often identifying increases in flu cases weeks in advance of CDC records. However, contrary to popular belief, Google Flu Trends is not an early epidemic detection system. Instead, it is designed as a baseline indicator of the trend, or changes, in the number of disease cases. To evaluate whether these trends can be used as a basis for an early warning system for epidemics. We present the first detailed algorithmic analysis of how Google Flu Trends can be used as a basis for building a fully automated system for early warning of epidemics in advance of methods used by the CDC. Based on our work, we present a novel early epidemic detection system, called FluBreaks (dritte.org/flubreaks), based on Google Flu Trends data. We compared the accuracy and practicality of three types of algorithms: normal distribution algorithms, Poisson distribution algorithms, and negative binomial distribution algorithms. We explored the relative merits of these methods, and related our findings to changes in Internet penetration and population size for the regions in Google Flu Trends providing data. Across our performance metrics of percentage true-positives (RTP), percentage false-positives (RFP), percentage overlap (OT), and percentage early alarms (EA), Poisson- and negative binomial-based algorithms performed better in all except RFP. Poisson-based algorithms had average values of 99%, 28%, 71%, and 76% for RTP, RFP, OT, and EA, respectively, whereas negative binomial-based algorithms had average values of 97.8%, 17.8%, 60%, and 55% for RTP, RFP, OT, and EA, respectively. Moreover, the EA was also affected by the region's population size
Early hospital mortality prediction of intensive care unit patients using an ensemble learning approach.

PubMed

Awad, Aya; Bader-El-Den, Mohamed; McNicholas, James; Briggs, Jim

2017-12-01

Mortality prediction of hospitalized patients is an important problem. Over the past few decades, several severity scoring systems and machine learning mortality prediction models have been developed for predicting hospital mortality. By contrast, early mortality prediction for intensive care unit patients remains an open challenge. Most research has focused on severity of illness scoring systems or data mining (DM) models designed for risk estimation at least 24 or 48h after ICU admission. This study highlights the main data challenges in early mortality prediction in ICU patients and introduces a new machine learning based framework for Early Mortality Prediction for Intensive Care Unit patients (EMPICU). The proposed method is evaluated on the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database. Mortality prediction models are developed for patients at the age of 16 or above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU). We employ the ensemble learning Random Forest (RF), the predictive Decision Trees (DT), the probabilistic Naive Bayes (NB) and the rule-based Projective Adaptive Resonance Theory (PART) models. The primary outcome was hospital mortality. The explanatory variables included demographic, physiological, vital signs and laboratory test variables. Performance measures were calculated using cross-validated area under the receiver operating characteristic curve (AUROC) to minimize bias. 11,722 patients with single ICU stays are considered. Only patients at the age of 16 years old and above in Medical ICU (MICU), Surgical ICU (SICU) or Cardiac Surgery Recovery Unit (CSRU) are considered in this study. The proposed EMPICU framework outperformed standard scoring systems (SOFA, SAPS-I, APACHE-II, NEWS and qSOFA) in terms of AUROC and time (i.e. at 6h compared to 48h or more after admission). The results show that although there are many values missing in the first few hour of ICU admission
Sampling design for aquatic invasive species early detection in Great Lakes ports

EPA Science Inventory

From 2006-2012, we evaluated a pilot aquatic invasive species (AIS) early detection monitoring program in Lake Superior that was designed to detect newly introduced fishes. We established survey protocols for three major ports (Duluth-Superior, Sault Ste. Marie, Thunder Bay) and ...

[Early detection of cervical cancer in Chile: time for change].

PubMed

Léniz Martelli, Javiera; Van De Wyngard, Vanessa; Lagos, Marcela; Barriga, María Isabel; Puschel Illanes, Klaus; Ferreccio Readi, Catterina

2014-08-01

Mortality rates for cervical cancer (CC) in Chile are higher than those of developed countries and it has an unequal socioeconomic distribution. The recognition of human papilloma virus (HPV) as the causal agent of cervical cancer in the early 80's changed the prevention paradigms. Current goals are to prevent HPV infection by vaccination before the onset of sexual activity and to detect HPV infection in women older than 30 years. This article reviews CC prevention and early detection methods, discusses relevant evidence to support a change in Chile and presents an innovation proposal. A strategy of primary screening based on HPV detection followed by triage of HPV-positive women by colposcopy in primary care or by cytological or molecular reflex testing is proposed. Due to the existence in Chile of a well-organized nationwide CC prevention program, the replacement of a low-sensitivity screening test such as the Papanicolau test with a highly sensitive one such as HPV detection, could quickly improve the effectiveness of the program. The program also has a network of personnel qualified to conduct naked-eye inspections of the cervix, who could easily be trained to perform triage colposcopy. The incorporation of new prevention strategies could reduce the deaths of Chilean women and correct inequities.
Early Oscillation Detection Technique for Hybrid DC/DC Converters

NASA Technical Reports Server (NTRS)

Wang, Bright L.

2011-01-01

Oscillation or instability is a situation that must be avoided for reliable hybrid DC/DC converters. A real-time electronics measurement technique was developed to detect catastrophic oscillations at early stages for hybrid DC/DC converters. It is capable of identifying low-level oscillation and determining the degree of the oscillation at a unique frequency for every individual model of the converters without disturbing their normal operations. This technique is specially developed for space-used hybrid DC/DC converters, but it is also suitable for most of commercial and military switching-mode power supplies. This is a weak-electronic-signal detection technique to detect hybrid DC/DC converter oscillation presented as a specific noise signal at power input pins. It is based on principles of feedback control loop oscillation and RF signal modulations, and is realized by using signal power spectral analysis. On the power spectrum, a channel power amplitude at characteristic frequency (CPcf) and a channel power amplitude at switching frequency (CPsw) are chosen as oscillation level indicators. If the converter is stable, the CPcf is a very small pulse and the CPsw is a larger, clear, single pulse. At early stage of oscillation, the CPcf increases to a certain level and the CPsw shows a small pair of sideband pulses around it. If the converter oscillates, the CPcf reaches to a higher level and the CPsw shows more high-level sideband pulses. A comprehensive stability index (CSI) is adopted as a quantitative measure to accurately assign a degree of stability to a specific DC/DC converter. The CSI is a ratio of normal and abnormal power spectral density, and can be calculated using specified and measured CPcf and CPsw data. The novel and unique feature of this technique is the use of power channel amplitudes at characteristic frequency and switching frequency to evaluate stability and identify oscillations at an early stage without interfering with a DC/DC converter s
Early Hearing Detection and Intervention in Developing Countries: Current Status and Prospects

ERIC Educational Resources Information Center

Olusanya, Bolajoko O.

2006-01-01

Infant hearing screening is emerging rapidly as a silent global revolution for the early detection of children with congenital or early onset hearing loss to ensure timely enrollment in family-oriented intervention programs for the development of spoken language. This article examines the overriding and interrelated scientific, ethical and…
Early detection of tooth wear by en-face optical coherence tomography

NASA Astrophysics Data System (ADS)

Mărcăuteanu, Corina; Negrutiu, Meda; Sinescu, Cosmin; Demjan, Eniko; Hughes, Mike; Bradu, Adrian; Dobre, George; Podoleanu, Adrian G.

2009-02-01

Excessive dental wear (pathological attrition and/or abfractions) is a frequent complication in bruxing patients. The parafunction causes heavy occlusal loads. The aim of this study is the early detection and monitoring of occlusal overload in bruxing patients. En-face optical coherence tomography was used for investigating and imaging of several extracted tooth, with a normal morphology, derived from patients with active bruxism and from subjects without parafunction. We found a characteristic pattern of enamel cracks in patients with first degree bruxism and with a normal tooth morphology. We conclude that the en-face optical coherence tomography is a promising non-invasive alternative technique for the early detection of occlusal overload, before it becomes clinically evident as tooth wear.
Oral cancer. Practical prevention and early detection for the dental team.

PubMed

Kerr, A Ross; Cruz, Gustavo D

2002-01-01

Approximately 2,000 patients a year are diagnosed with oral cancer in New York State. In an effort to control this deadly disease, Governor George Pataki has taken a leadership role in the United States by mandating and funding training for dentists in the prevention and early detection of oral cancer. The purpose of this article is to highlight the epidemiology of oral cancer, to show how the dental profession can contribute to the health of the citizens of New York State, and to provide practical guidelines for both tobacco cessation intervention and utilization of existing technology for the early detection of oral cancer and precancerous conditions in the general dental practice setting.
Oral precancerous lesions: Problems of early detection and oral cancer prevention

NASA Astrophysics Data System (ADS)

Gileva, Olga S.; Libik, Tatiana V.; Danilov, Konstantin V.

2016-08-01

The study presents the results of the research in the structure, local and systemic risk factors, peculiarities of the clinical manifestation, and quality of primary diagnosis of precancerous oral mucosa lesions (OMLs). In the study a wide range of OMLs and high (25.4%) proportion of oral precancerous lesions (OPLs) in their structure was indicated. The high percentage of different diagnostic errors and the lack of oncological awareness of dental practitioners, as well as the sharp necessity of inclusion of precancer/cancer early detection techniques into their daily practice were noted. The effectiveness of chemilumenescence system of early OPLs and oral cancer detection was demonstrated, the prospects of infrared thermography as a diagnostic tool were also discussed.
Plasma NGAL predicts early acute kidney injury no earlier than s-creatinine or cystatin C in severely burned patients.

PubMed

Rakkolainen, Ilmari; Vuola, Jyrki

2016-03-01

Neutrophil gelatinase-associated lipocalin (NGAL) is a novel biomarker used in acute kidney injury (AKI) diagnostics. Studies on burn patients have highlighted it as a promising biomarker for early detection of AKI. This study was designed to discover whether plasma NGAL is as a biomarker superior to serum creatinine and cystatin C in detecting AKI in severely burned patients. Nineteen subjects were enrolled from March 2013 to September 2014 in the Helsinki Burn Centre. Serum creatinine, cystatin C, and plasma NGAL were collected from the patients at admission and every 12h during the first 48h and thereafter daily until seven days following admission. AKI was defined by acute kidney injury network criteria. Nine (47%) developed AKI during their intensive care unit stay and two (11%) underwent renal replacement therapy. All biomarkers were significantly higher in the AKI group but serum creatinine- and cystatin C values reacted more rapidly to changes in kidney function than did plasma NGAL. Plasma NGAL tended to rise on average 72h±29h (95% CI) later in patients with early AKI than did serum creatinine. Area-under-the-curve values calculated for each biomarker were 0.92 for serum creatinine, 0.87 for cystatin C, and 0.62 for plasma NGAL predicting AKI by the receiver-operating-characteristic method. This study demonstrated serum creatinine and cystatin C as faster and more reliable biomarkers than plasma NGAL in detecting early AKI within one week of injury in patients with severe burns. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.
Interagency partnering for weed prevention--progress on development of a National Early Detection and Rapid Response System for Invasive Plants in the United States

USGS Publications Warehouse

Westbrooks, R.; Westbrooks, R.

2011-01-01

Over the past 50 years, experience has shown that interagency groups provide an effective forum for addressing various invasive species issues and challenges on multiple land units. However, more importantly, they can also provide a coordinated framework for early detection, reporting, identification and vouchering, rapid assessment, and rapid response to new and emerging invasive plants in the United States. Interagency collaboration maximizes the use of available expertise, resources, and authority for promoting early detection and rapid response (EDRR) as the preferred management option for addressing new and emerging invasive plants. Currently, an interagency effort is underway to develop a National EDRR System for Invasive Plants in the United States. The proposed system will include structural and informational elements. Structural elements of the system include a network of interagency partner groups to facilitate early detection and rapid response to new invasive plants, including the Federal Interagency Committee for the Management of Noxious and Exotic Weeds (FICMNEW), State Invasive Species Councils, State Early Detection and Rapid Response Coordinating Committees, State Volunteer Detection and Reporting Networks, Invasive Plant Task Forces, and Cooperative Weed Management Areas. Informational elements and products being developed include Regional Invasive Plant Atlases, and EDRR Guidelines for EDRR Volunteer Network Training, Rapid Assessment and Rapid Response, and Criteria for Selection of EDRR Species. System science and technical support elements which are provided by cooperating state and federal scientists, include EDRR guidelines, training curriculum for EDRR volunteers and agency field personnel, plant identification and vouchering, rapid assessments, as well as predictive modeling and ecological range studies for invasive plant species.
Clinical evaluation of C-reactive protein and procalcitonin for the early detection of postoperative complications after laparoscopic sleeve gastrectomy.

PubMed

Frask, Agata; Orłowski, Michał; Dowgiałło-Wnukiewicz, Natalia; Lech, Paweł; Gajewski, Krzysztof; Michalik, Maciej

2017-06-01

Among the most common early complications after bariatric surgery are anastomosis leak and bleeding. In order to react quickly and perform accurate treatment before the clinical signs appear, early predictors should be found. In the study C-reactive protein (CRP) and procalcitonin (PCT) levels were investigated. Characterized by a relatively short half-life, they can predict surgical complications. To develop and implement certain standards for early detection of complications. The study involved 319 adults who underwent laparoscopic sleeve gastrectomy (LSG) as a surgical intervention for morbid obesity at the Department of General Surgery of Ceynowa Hospital in Wejherowo. Every patient had CRP and PCT levels measured before the surgery and on the 1 st and 2 nd postoperative day (POD). Early postoperative complications occurred in 19 (5.96%) patients. Septic and non-septic complications occurred in 3 and 16 patients respectively. Among the patients with septic postoperative complications CRP level increased significantly on the 2 nd POD compared to the remainder (p = 0.0221). Among the patients with non-septic postoperative complications CRP level increased significantly on the 1 st and 2 nd POD compared to the remainder. Among the patients with septic and non-septic postoperative complications PCT level increased significantly on the 2 nd POD compared to the remainder. The CRP and PCT level are supposed to be relevant diagnostic markers to predict non-septic and septic complications after LSG.
Clinical evaluation of C-reactive protein and procalcitonin for the early detection of postoperative complications after laparoscopic sleeve gastrectomy

PubMed Central

Frask, Agata; Orłowski, Michał; Lech, Paweł; Gajewski, Krzysztof; Michalik, Maciej

2017-01-01

Introduction Among the most common early complications after bariatric surgery are anastomosis leak and bleeding. In order to react quickly and perform accurate treatment before the clinical signs appear, early predictors should be found. In the study C-reactive protein (CRP) and procalcitonin (PCT) levels were investigated. Characterized by a relatively short half-life, they can predict surgical complications. Aim To develop and implement certain standards for early detection of complications. Material and methods The study involved 319 adults who underwent laparoscopic sleeve gastrectomy (LSG) as a surgical intervention for morbid obesity at the Department of General Surgery of Ceynowa Hospital in Wejherowo. Every patient had CRP and PCT levels measured before the surgery and on the 1st and 2nd postoperative day (POD). Results Early postoperative complications occurred in 19 (5.96%) patients. Septic and non-septic complications occurred in 3 and 16 patients respectively. Among the patients with septic postoperative complications CRP level increased significantly on the 2nd POD compared to the remainder (p = 0.0221). Among the patients with non-septic postoperative complications CRP level increased significantly on the 1st and 2nd POD compared to the remainder. Among the patients with septic and non-septic postoperative complications PCT level increased significantly on the 2nd POD compared to the remainder. Conclusions The CRP and PCT level are supposed to be relevant diagnostic markers to predict non-septic and septic complications after LSG. PMID:28694902
Identification of genetic variants predictive of early onset pancreatic cancer through a population science analysis of functional genomic datasets

PubMed Central

Chen, Jinyun; Wu, Xifeng; Huang, Yujing; Chen, Wei; Brand, Randall E.; Killary, Ann M.; Sen, Subrata; Frazier, Marsha L.

2016-01-01

Biomarkers are critically needed for the early detection of pancreatic cancer (PC) are urgently needed. Our purpose was to identify a panel of genetic variants that, combined, can predict increased risk for early-onset PC and thereby identify individuals who should begin screening at an early age. Previously, we identified genes using a functional genomic approach that were aberrantly expressed in early pathways to PC tumorigenesis. We now report the discovery of single nucleotide polymorphisms (SNPs) in these genes associated with early age at diagnosis of PC using a two-phase study design. In silico and bioinformatics tools were used to examine functional relevance of the identified SNPs. Eight SNPs were consistently associated with age at diagnosis in the discovery phase, validation phase and pooled analysis. Further analysis of the joint effects of these 8 SNPs showed that, compared to participants carrying none of these unfavorable genotypes (median age at PC diagnosis 70 years), those carrying 1–2, 3–4, or 5 or more unfavorable genotypes had median ages at diagnosis of 64, 63, and 62 years, respectively (P = 3.0E–04). A gene-dosage effect was observed, with age at diagnosis inversely related to number of unfavorable genotypes (Ptrend = 1.0E–04). Using bioinformatics tools, we found that all of the 8 SNPs were predicted to play functional roles in the disruption of transcription factor and/or enhancer binding sites and most of them were expression quantitative trait loci (eQTL) of the target genes. The panel of genetic markers identified may serve as susceptibility markers for earlier PC diagnosis. PMID:27486767
A Simple System for the Early Detection of Breast Cancer

DTIC Science & Technology

2016-07-01

AWARD NUMBER: W81XWH-14-1-0231 TITLE: A Simple System for Early Detection of Breast Cancer PRINCIPAL INVESTIGATOR: Stephen Johnston CONTRACTING...ADDRESS. 1. REPORT DATE July 2016 2. REPORT TYPE Annual 3. DATES COVERED 1Jul2015 - 30Jun2016 4. TITLE AND SUBTITLE A Simple System for the Early...Form 298 (Rev. 8-98) Prescribed by ANSI Std. Z39.18 W81XWH-14-1-0231 Abstract: We invented the immunosignature technology (IMS) as a simple , universal
The Early Detection of the Emerald Ash Borer (EAB) Using Advanced Geospacial Technologies

NASA Astrophysics Data System (ADS)

Hu, B.; Li, J.; Wang, J.; Hall, B.

2014-11-01

The objectives of this study were to exploit Light Detection And Ranging (LiDAR) and very high spatial resolution (VHR) data and their synergy with hyperspectral imagery in the early detection of the EAB presence in trees within urban areas and to develop a framework to combine information extracted from multiple data sources. To achieve these, an object-oriented framework was developed to combine information derived from available data sets to characterize ash trees. Within this framework, individual trees were first extracted and then classified into different species based on their spectral information derived from hyperspectral imagery, spatial information from VHR imagery, and for each ash tree its health state and EAB infestation stage were determined based on hyperspectral imagery. The developed framework and methods were demonstrated to be effective according to the results obtained on two study sites in the city of Toronto, Ontario Canada. The individual tree delineation method provided satisfactory results with an overall accuracy of 78 % and 19 % commission and 23 % omission errors when used on the combined very high-spatial resolution imagery and LiDAR data. In terms of the identification of ash trees, given sufficient representative training data, our classification model was able to predict tree species with above 75 % overall accuracy, and mis-classification occurred mainly between ash and maple trees. The hypothesis that a strong correlation exists between general tree stress and EAB infestation was confirmed. Vegetation indices sensitive to leaf chlorophyll content derived from hyperspectral imagery can be used to predict the EAB infestation levels for each ash tree.
Early Detection Research Network (EDRN) | Division of Cancer Prevention

Cancer.gov

http://edrn.nci.nih.gov/EDRN is a collaborative network that maintains comprehensive infrastructure and resources critical to the discovery, development and validation of biomarkers for cancer risk and early detection. The program comprises a public/private sector consortium to accelerate the development of biomarkers that will change medical practice, ensure data
Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy.

PubMed

Ramgopal, Sriram; Thome-Souza, Sigride; Jackson, Michele; Kadish, Navah Ester; Sánchez Fernández, Iván; Klehm, Jacquelyn; Bosl, William; Reinsberger, Claus; Schachter, Steven; Loddenkemper, Tobias

2014-08-01

Nearly one-third of patients with epilepsy continue to have seizures despite optimal medication management. Systems employed to detect seizures may have the potential to improve outcomes in these patients by allowing more tailored therapies and might, additionally, have a role in accident and SUDEP prevention. Automated seizure detection and prediction require algorithms which employ feature computation and subsequent classification. Over the last few decades, methods have been developed to detect seizures utilizing scalp and intracranial EEG, electrocardiography, accelerometry and motion sensors, electrodermal activity, and audio/video captures. To date, it is unclear which combination of detection technologies yields the best results, and approaches may ultimately need to be individualized. This review presents an overview of seizure detection and related prediction methods and discusses their potential uses in closed-loop warning systems in epilepsy. Copyright © 2014. Published by Elsevier Inc.
Early, Accurate Diagnosis and Early Intervention in Cerebral Palsy: Advances in Diagnosis and Treatment.

PubMed

Novak, Iona; Morgan, Cathy; Adde, Lars; Blackman, James; Boyd, Roslyn N; Brunstrom-Hernandez, Janice; Cioni, Giovanni; Damiano, Diane; Darrah, Johanna; Eliasson, Ann-Christin; de Vries, Linda S; Einspieler, Christa; Fahey, Michael; Fehlings, Darcy; Ferriero, Donna M; Fetters, Linda; Fiori, Simona; Forssberg, Hans; Gordon, Andrew M; Greaves, Susan; Guzzetta, Andrea; Hadders-Algra, Mijna; Harbourne, Regina; Kakooza-Mwesige, Angelina; Karlsson, Petra; Krumlinde-Sundholm, Lena; Latal, Beatrice; Loughran-Fowlds, Alison; Maitre, Nathalie; McIntyre, Sarah; Noritz, Garey; Pennington, Lindsay; Romeo, Domenico M; Shepherd, Roberta; Spittle, Alicia J; Thornton, Marelle; Valentine, Jane; Walker, Karen; White, Robert; Badawi, Nadia

2017-09-01

Cerebral palsy describes the most common physical disability in childhood and occurs in 1 in 500 live births. Historically, the diagnosis has been made between age 12 and 24 months but now can be made before 6 months' corrected age. To systematically review best available evidence for early, accurate diagnosis of cerebral palsy and to summarize best available evidence about cerebral palsy-specific early intervention that should follow early diagnosis to optimize neuroplasticity and function. This study systematically searched the literature about early diagnosis of cerebral palsy in MEDLINE (1956-2016), EMBASE (1980-2016), CINAHL (1983-2016), and the Cochrane Library (1988-2016) and by hand searching. Search terms included cerebral palsy, diagnosis, detection, prediction, identification, predictive validity, accuracy, sensitivity, and specificity. The study included systematic reviews with or without meta-analyses, criteria of diagnostic accuracy, and evidence-based clinical guidelines. Findings are reported according to the PRISMA statement, and recommendations are reported according to the Appraisal of Guidelines, Research and Evaluation (AGREE) II instrument. Six systematic reviews and 2 evidence-based clinical guidelines met inclusion criteria. All included articles had high methodological Quality Assessment of Diagnostic Accuracy Studies (QUADAS) ratings. In infants, clinical signs and symptoms of cerebral palsy emerge and evolve before age 2 years; therefore, a combination of standardized tools should be used to predict risk in conjunction with clinical history. Before 5 months' corrected age, the most predictive tools for detecting risk are term-age magnetic resonance imaging (86%-89% sensitivity), the Prechtl Qualitative Assessment of General Movements (98% sensitivity), and the Hammersmith Infant Neurological Examination (90% sensitivity). After 5 months' corrected age, the most predictive tools for detecting risk are magnetic resonance imaging (86
Early detection of emerald ash borer infestation using multisourced data: a case study in the town of Oakville, Ontario, Canada

NASA Astrophysics Data System (ADS)

Zhang, Kongwen; Hu, Baoxin; Robinson, Justin

2014-01-01

The emerald ash borer (EAB) poses a significant economic and environmental threat to ash trees in southern Ontario, Canada, and the northern states of the USA. It is critical that effective technologies are urgently developed to detect, monitor, and control the spread of EAB. This paper presents a methodology using multisourced data to predict potential infestations of EAB in the town of Oakville, Ontario, Canada. The information combined in this study includes remotely sensed data, such as high spatial resolution aerial imagery, commercial ground and airborne hyperspectral data, and Google Earth imagery, in addition to nonremotely sensed data, such as archived paper maps and documents. This wide range of data provides extensive information that can be used for early detection of EAB, yet their effective employment and use remain a significant challenge. A prediction function was developed to estimate the EAB infestation states of individual ash trees using three major attributes: leaf chlorophyll content, tree crown spatial pattern, and prior knowledge. Comparison between these predicted values and a ground-based survey demonstrated an overall accuracy of 62.5%, with 22.5% omission and 18.5% commission errors.
Predicting sexual coercion in early adulthood: The transaction among maltreatment, gang affiliation, and adolescent socialization of coercive relationship norms.

PubMed

Ha, Thao; Kim, Hanjoe; Christopher, Caroline; Caruthers, Allison; Dishion, Thomas J

2016-08-01

This study tested a transactional hypothesis predicting early adult sexual coercion from family maltreatment, early adolescent gang affiliation, and socialization of adolescent friendships that support coercive relationship norms. The longitudinal study of a community sample of 998 11-year-olds was intensively assessed in early and middle adolescence and followed to 23-24 years of age. At age 16-17 youth were videotaped with a friend, and their interactions were coded for coercive relationship talk. Structural equation modeling revealed that maltreatment predicted gang affiliation during early adolescence. Both maltreatment and gang affiliation strongly predicted adolescent sexual promiscuity and coercive relationship norms with friends at age 16-17 years. Adolescent sexual promiscuity, however, did not predict sexual coercion in early adulthood. In contrast, higher levels of observed coercive relationship talk with a friend predicted sexual coercion in early adulthood for both males and females. These findings suggest that peers have a socialization function in the development of norms prognostic of sexual coercion, and the need to consider peers in the promotion of healthy relationships.
Defining and Predicting Patterns of Early Response in a Web-Based Intervention for Depression

PubMed Central

Arndt, Alice; Rubel, Julian; Berger, Thomas; Schröder, Johanna; Späth, Christina; Meyer, Björn; Greiner, Wolfgang; Gräfe, Viola; Hautzinger, Martin; Fuhr, Kristina; Rose, Matthias; Nolte, Sandra; Löwe, Bernd; Hohagen, Fritz; Klein, Jan Philipp; Moritz, Steffen

2017-01-01

Background Web-based interventions for individuals with depressive disorders have been a recent focus of research and may be an effective adjunct to face-to-face psychotherapy or pharmacological treatment. Objective The aim of our study was to examine the early change patterns in Web-based interventions to identify differential effects. Methods We applied piecewise growth mixture modeling (PGMM) to identify different latent classes of early change in individuals with mild-to-moderate depression (n=409) who underwent a CBT-based web intervention for depression. Results Overall, three latent classes were identified (N=409): Two early response classes (n=158, n=185) and one early deterioration class (n=66). Latent classes differed in terms of outcome (P<.001) and adherence (P=.03) in regard to the number of modules (number of modules with a duration of at least 10 minutes) and the number of assessments (P<.001), but not in regard to the overall amount of time using the system. Class membership significantly improved outcome prediction by 24.8% over patient intake characteristics (P<.001) and significantly added to the prediction of adherence (P=.04). Conclusions These findings suggest that in Web-based interventions outcome and adherence can be predicted by patterns of early change, which can inform treatment decisions and potentially help optimize the allocation of scarce clinical resources. PMID:28600278
Early Prediction of Reading Comprehension within the Simple View Framework

ERIC Educational Resources Information Center

Catts, Hugh W.; Herrera, Sarah; Nielsen, Diane Corcoran; Bridges, Mindy Sittner

2015-01-01

The simple view of reading proposes that reading comprehension is the product of word reading and language comprehension. In this study, we used the simple view framework to examine the early prediction of reading comprehension abilities. Using multiple measures for all constructs, we assessed word reading precursors (i.e., letter knowledge,…

EARLY DETECTION MONITORING OF INVASIVE SPECIES IN GREAT LAKES HARBORS

EPA Science Inventory

The Great Ships Initiative (GSI) has asked for a presentation on designing harbor monitoring. Our research/development project on early detection provides some examples and lessons for GSI to consider in evaluating effectiveness of ballast water treatments; the presentation allo...
Object detection in natural backgrounds predicted by discrimination performance and models

NASA Technical Reports Server (NTRS)

Rohaly, A. M.; Ahumada, A. J. Jr; Watson, A. B.

1997-01-01

Many models of visual performance predict image discriminability, the visibility of the difference between a pair of images. We compared the ability of three image discrimination models to predict the detectability of objects embedded in natural backgrounds. The three models were: a multiple channel Cortex transform model with within-channel masking; a single channel contrast sensitivity filter model; and a digital image difference metric. Each model used a Minkowski distance metric (generalized vector magnitude) to summate absolute differences between the background and object plus background images. For each model, this summation was implemented with three different exponents: 2, 4 and infinity. In addition, each combination of model and summation exponent was implemented with and without a simple contrast gain factor. The model outputs were compared to measures of object detectability obtained from 19 observers. Among the models without the contrast gain factor, the multiple channel model with a summation exponent of 4 performed best, predicting the pattern of observer d's with an RMS error of 2.3 dB. The contrast gain factor improved the predictions of all three models for all three exponents. With the factor, the best exponent was 4 for all three models, and their prediction errors were near 1 dB. These results demonstrate that image discrimination models can predict the relative detectability of objects in natural scenes.
Early detection surveillance for an emerging plant pathogen: a rule of thumb to predict prevalence at first discovery

PubMed Central

Parnell, S.; Gottwald, T. R.; Cunniffe, N. J.; Alonso Chavez, V.; van den Bosch, F.

2015-01-01

Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally. PMID:26336177
Predicting and Detecting Emerging Cyberattack Patterns Using StreamWorks

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

Chin, George; Choudhury, Sutanay; Feo, John T.

2014-06-30

The number and sophistication of cyberattacks on industries and governments have dramatically grown in recent years. To counter this movement, new advanced tools and techniques are needed to detect cyberattacks in their early stages such that defensive actions may be taken to avert or mitigate potential damage. From a cybersecurity analysis perspective, detecting cyberattacks may be cast as a problem of identifying patterns in computer network traffic. Logically and intuitively, these patterns may take on the form of a directed graph that conveys how an attack or intrusion propagates through the computers of a network. Such cyberattack graphs could providemore » cybersecurity analysts with powerful conceptual representations that are natural to express and analyze. We have been researching and developing graph-centric approaches and algorithms for dynamic cyberattack detection. The advanced dynamic graph algorithms we are developing will be packaged into a streaming network analysis framework known as StreamWorks. With StreamWorks, a scientist or analyst may detect and identify precursor events and patterns as they emerge in complex networks. This analysis framework is intended to be used in a dynamic environment where network data is streamed in and is appended to a large-scale dynamic graph. Specific graphical query patterns are decomposed and collected into a graph query library. The individual decomposed subpatterns in the library are continuously and efficiently matched against the dynamic graph as it evolves to identify and detect early, partial subgraph patterns. The scalable emerging subgraph pattern algorithms will match on both structural and semantic network properties.« less
Results of an early hearing detection program.

PubMed

Borkoski Barreiro, Silvia A; Falcón González, Juan C; Bueno Yanes, Jorge; Pérez Bermúdez, José L; López Cano, Zoraida; Ramos Macías, Ángel

2013-01-01

Neonatal hearing loss is a public health problem that meets the requirements for submission to universal screening. Our objective was to analyse the results of the early hearing detection and intervention program implemented at our centre between January 2007 and December 2010. We studied 26,717 newborns during the period mentioned, using transient otoacoustic emissions (TOAEs) for the screening. The diagnostic phase was carried out at the hearing loss department. In our area, there were 27,935 births between January 2007 and December 2010. The screening was performed on 26,717 children. Of these, 24,173 had positive TOAEs, 1,040 had no TOAEs and 1,504 presented TOAEs in 1 ear with absence of TOAEs in the contralateral ear. Risk factors associated with hearing loss were found in 4,674 infants. In a second phase of the program, TOAEs were given to 5,156 children, of whom 4,626 had positive otoacoustic emissions in both ears, 323 had no TOAEs in 1 ear and 207 failed this second phase. Of all children studied, 3.8% were referred to auditory brainstem response (ABR) testing and 26 children entered the cochlear implant program. The program reached coverage of 95.64%. The early hearing detection and intervention program at our hospital is suitable for our environment, reaching 95.64% of coverage. We consider the relationship between effectiveness and efficiency to be positive. Copyright © 2012 Elsevier España, S.L. All rights reserved.
Early Detection of Infection in Pigs through an Online Monitoring System.

PubMed

Martínez-Avilés, M; Fernández-Carrión, E; López García-Baones, J M; Sánchez-Vizcaíno, J M

2017-04-01

Late detection of emergency diseases causes significant economic losses for pig producers and governments. As the first signs of animal infection are usually fever and reduced motion that lead to reduced consumption of water and feed, we developed a novel smart system to monitor body temperature and motion in real time, facilitating the early detection of infectious diseases. In this study, carried out within the framework of the European Union research project Rapidia Field, we tested the smart system on 10 pigs experimentally infected with two doses of an attenuated strain of African swine fever. Biosensors and an accelerometer embedded in an eartag captured data before and after infection, and video cameras were used to monitor the animals 24 h per day. The results showed that in 8 of 9 cases, the monitoring system detected infection onset as an increase in body temperature and decrease in movement before or simultaneously with fever detection based on rectal temperature measurement, observation of clinical signs, the decrease in water consumption or positive qPCR detection of virus. In addition, this decrease in movement was reliably detected using automatic analysis of video images therefore providing an inexpensive alternative to direct motion measurement. The system can be set up to alert staff when high fever, reduced motion or both are detected in one or more animals. This system may be useful for monitoring sentinel herds in real time, considerably reducing the financial and logistical costs of periodic sampling and increasing the chances of early detection of infection. © 2015 Blackwell Verlag GmbH.
Which behavioral, emotional and school problems in middle-childhood predict early sexual behavior?

PubMed

Parkes, Alison; Waylen, Andrea; Sayal, Kapil; Heron, Jon; Henderson, Marion; Wight, Daniel; Macleod, John

2014-04-01

Mental health and school adjustment problems are thought to distinguish early sexual behavior from normative timing (16-18 years), but little is known about how early sexual behavior originates from these problems in middle-childhood. Existing studies do not allow for co-occurring problems, differences in onset and persistence, and there is no information on middle-childhood school adjustment in relationship to early sexual activity. This study examined associations between several middle-childhood problems and early sexual behavior, using a subsample (N = 4,739, 53 % female, 98 % white, mean age 15 years 6 months) from a birth cohort study, the Avon Longitudinal Study of Parents and Children. Adolescents provided information at age 15 on early sexual behavior (oral sex and/or intercourse) and sexual risk-taking, and at age 13 on prior risk involvement (sexual behavior, antisocial behavior and substance use). Information on hyperactivity/inattention, conduct problems, depressive symptoms, peer relationship problems, school dislike and school performance was collected in middle-childhood at Time 1 (6-8 years) and Time 2 (10-11 years). In agreement with previous research, conduct problems predicted early sexual behavior, although this was found only for persistent early problems. In addition, Time 2 school dislike predicted early sexual behavior, while peer relationship problems were protective. Persistent early school dislike further characterized higher-risk groups (early sexual behavior preceded by age 13 risk, or accompanied by higher sexual risk-taking). The study establishes middle-childhood school dislike as a novel risk factor for early sexual behavior and higher-risk groups, and the importance of persistent conduct problems. Implications for the identification of children at risk and targeted intervention are discussed, as well as suggestions for further research.
Method for early detection of infectious mononucleosis

DOEpatents

Willard, K.E.

1982-08-10

Early detection of infectious mononucleosis is carried out using a sample of human blood by isolating and identifying the presence of Inmono proteins in the sample from a two-dimensional protein map with the proteins being characterized by having isoelectric banding as measured in urea of about -16 to -17 with respect to certain isoelectric point standards and molecular mass of about 70 to 75 K daltons as measured in the presence of sodium dodecylsulfate containing polyacrylamide gels, the presence of the Inmono proteins being correlated with the existence of infectious mononucleosis.
Strategies for Early Outbreak Detection of Malaria in the Amhara Region of Ethiopia

NASA Astrophysics Data System (ADS)

Nekorchuk, D.; Gebrehiwot, T.; Mihretie, A.; Awoke, W.; Wimberly, M. C.

2017-12-01

Traditional epidemiological approaches to early detection of disease outbreaks are based on relatively straightforward thresholds (e.g. 75th percentile, standard deviations) estimated from historical case data. For diseases with strong seasonality, these can be modified to create separate thresholds for each seasonal time step. However, for disease processes that are non-stationary, more sophisticated techniques are needed to more accurately estimate outbreak threshold values. Early detection for geohealth-related diseases that also have environmental drivers, such as vector-borne diseases, may also benefit from the integration of time-lagged environmental data and disease ecology models into the threshold calculations. The Epidemic Prognosis Incorporating Disease and Environmental Monitoring for Integrated Assessment (EPIDEMIA) project has been integrating malaria case surveillance with remotely-sensed environmental data for early detection, warning, and forecasting of malaria epidemics in the Amhara region of Ethiopia, and has five years of weekly time series data from 47 woredas (districts). Efforts to reduce the burden of malaria in Ethiopia has been met with some notable success in the past two decades with major reduction in cases and deaths. However, malaria remains a significant public health threat as 60% of the population live in malarious areas, and due to the seasonal and unstable transmission patterns with cyclic outbreaks, protective immunity is generally low which could cause high morbidity and mortality during the epidemics. This study compared several approaches for defining outbreak thresholds and for identifying a potential outbreak based on deviations from these thresholds. We found that model-based approaches that accounted for climate-driven seasonality in malaria transmission were most effective, and that incorporating a trend component improved outbreak detection in areas with active malaria elimination efforts. An advantage of these early
First step toward translation of thermophotonic lock-in imaging to dentistry as an early caries detection technology

NASA Astrophysics Data System (ADS)

Ojaghi, Ashkan; Parkhimchyk, Artur; Tabatabaei, Nima

2016-09-01

Early detection of the most prevalent oral disease worldwide, i.e., dental caries, still remains as one of the major challenges in dentistry. The current dental standard of care relies on caries detection methods, such as visual inspection and x-ray radiography, which lack the sufficient specificity and sensitivity to detect caries at early stages of formation when they can be healed. We report on the feasibility of early caries detection in a clinically and commercially viable thermophotonic imaging system. The system incorporates intensity-modulated laser light along with a low-cost long-wavelength infrared (LWIR; 8 to 14 μm) camera, providing diagnostic contrast based on the enhanced light absorption of early caries. The LWIR camera is highly suitable for integration into clinical platforms because of its low weight and cost. In addition, through theoretical modeling, we show that LWIR detection enhances the diagnostic contrast due to the minimal LWIR transmittance of enamel and suppression of the masking effect of the direct thermal Planck emission. Diagnostic performance of the system and its detection threshold are experimentally evaluated by monitoring the inception and progression of artificially induced occlusal and smooth surface caries. The results are suggestive of the suitability of the developed LWIR system for detecting early dental caries.
Recent advances in targeted endoscopic imaging: Early detection of gastrointestinal neoplasms

PubMed Central

Kwon, Yong-Soo; Cho, Young-Seok; Yoon, Tae-Jong; Kim, Ho-Shik; Choi, Myung-Gyu

2012-01-01

Molecular imaging has emerged as a new discipline in gastrointestinal endoscopy. This technology encompasses modalities that can visualize disease-specific morphological or functional tissue changes based on the molecular signature of individual cells. Molecular imaging has several advantages including minimal damage to tissues, repetitive visualization, and utility for conducting quantitative analyses. Advancements in basic science coupled with endoscopy have made early detection of gastrointestinal cancer possible. Molecular imaging during gastrointestinal endoscopy requires the development of safe biomarkers and exogenous probes to detect molecular changes in cells with high specificity anda high signal-to-background ratio. Additionally, a high-resolution endoscope with an accurate wide-field viewing capability must be developed. Targeted endoscopic imaging is expected to improve early diagnosis and individual therapy of gastrointestinal cancer. PMID:22442742
Early Breast Cancer Detection by Ultrawide Band Imaging with Dispersion Consideration

NASA Astrophysics Data System (ADS)

Xiao, Xia; Kikkawa, Takamaro

2008-04-01

Ultrawide band (UWB) microwave imaging is a promising method for early-stage breast cancer detection based on the large contrast of electric parameters between the tumor and the normal breast tissue. The tumor can be detected by analyzing the reflection and scattering behavior of the UWB microwave propagating in the breast. In this study, the tumor location is determined by comparing the waveforms resulted from the tumor-containing and tumor-free breasts. The frequency dispersive characteristics of the fatty breast tissue, skin and tumor are considered in the study to approach the actual electrical properties of the breast. The correct location and size are visualized for an early-stage tumor embedded in the breast using the principle of a confocal microwave imaging technique.
Advancing Early Detection of Autism Spectrum Disorder by Applying an Integrated Two-Stage Screening Approach

ERIC Educational Resources Information Center

Oosterling, Iris J.; Wensing, Michel; Swinkels, Sophie H.; van der Gaag, Rutger Jan; Visser, Janne C.; Woudenberg, Tim; Minderaa, Ruud; Steenhuis, Mark-Peter; Buitelaar, Jan K.

2010-01-01

Background: Few field trials exist on the impact of implementing guidelines for the early detection of autism spectrum disorders (ASD). The aims of the present study were to develop and evaluate a clinically relevant integrated early detection programme based on the two-stage screening approach of Filipek et al. (1999), and to expand the evidence…
Detecting COPD exacerbations early using daily telemonitoring of symptoms and k-means clustering: a pilot study.

PubMed

Sanchez-Morillo, Daniel; Fernandez-Granero, Miguel Angel; Jiménez, Antonio León

2015-05-01

COPD places an enormous burden on the healthcare systems and causes diminished health-related quality of life. The highest proportion of human and economic cost is associated with admissions for acute exacerbation of respiratory symptoms (AECOPD). Since prompt detection and treatment of exacerbations may improve outcomes, early detection of AECOPD is a critical issue. This pilot study was aimed to determine whether a mobile health system could enable early detection of AECOPD on a day-to-day basis. A novel electronic questionnaire for the early detection of COPD exacerbations was evaluated during a 6-months field trial in a group of 16 patients. Pattern recognition techniques were applied. A k-means clustering algorithm was trained and validated, and its accuracy in detecting AECOPD was assessed. Sensitivity and specificity were 74.6 and 89.7 %, respectively, and area under the receiver operating characteristic curve was 0.84. 31 out of 33 AECOPD were early identified with an average of 4.5 ± 2.1 days prior to the onset of the exacerbation that was considered the day of medical attendance. Based on the findings of this preliminary pilot study, the proposed electronic questionnaire and the applied methodology could help to early detect COPD exacerbations on a day-to-day basis and therefore could provide support to patients and physicians.
Cognitive and Social Processes Predicting Partner Psychological Adaptation to Early Stage Breast Cancer

PubMed Central

Manne, Sharon; Ostroff, Jamie; Fox, Kevin; Grana, Generosa; Winkel, Gary

2009-01-01

Introduction The diagnosis and subsequent treatment for early stage breast cancer is stressful for partners. Little is known about the role of cognitive and social processes predicting the longitudinal course of partners’ psychosocial adaptation. This study evaluated the role of cognitive and social processing in partner psychological adaptation to early stage breast cancer, evaluating both main and moderator effect models. Moderating effects for meaning-making, acceptance, and positive reappraisal on the predictive association of searching for meaning, emotional processing, and emotional expression on partner psychological distress were examined. Materials and Methods Partners of women diagnosed with early stage breast cancer were evaluated shortly after the ill partner’s diagnosis (n= 253), nine (n = 167), and 18 months (n = 149) later. Partners completed measures of emotional expression, emotional processing, acceptance, meaning-making, and general and cancer-specific distress at all time points. Results Lower satisfaction with partner support predicted greater global distress, and greater use of positive reappraisal was associated with greater distress. The predicted moderator effects for found meaning on the associations between the search for meaning and cancer-specific distress were found and similar moderating effects for positive reappraisal on the associations between emotional expression and global distress and for acceptance on the association between emotional processing and cancer-specific distress were found. Conclusions Results indicate several cognitive-social processes directly predict partner distress. However, moderator effect models in which the effects of partners’ processing depends upon whether these efforts result changes in perceptions of the cancer experience may add to the understanding of partners’ adaptation to cancer. PMID:18435865
Cognitive and social processes predicting partner psychological adaptation to early stage breast cancer.

PubMed

Manne, Sharon; Ostroff, Jamie; Fox, Kevin; Grana, Generosa; Winkel, Gary

2009-02-01

The diagnosis and subsequent treatment for early stage breast cancer is stressful for partners. Little is known about the role of cognitive and social processes predicting the longitudinal course of partners' psychosocial adaptation. This study evaluated the role of cognitive and social processing in partner psychological adaptation to early stage breast cancer, evaluating both main and moderator effect models. Moderating effects for meaning making, acceptance, and positive reappraisal on the predictive association of searching for meaning, emotional processing, and emotional expression on partner psychological distress were examined. Partners of women diagnosed with early stage breast cancer were evaluated shortly after the ill partner's diagnosis (N=253), 9 (N=167), and 18 months (N=149) later. Partners completed measures of emotional expression, emotional processing, acceptance, meaning making, and general and cancer-specific distress at all time points. Lower satisfaction with partner support predicted greater global distress, and greater use of positive reappraisal was associated with greater distress. The predicted moderator effects for found meaning on the associations between the search for meaning and cancer-specific distress were found and similar moderating effects for positive reappraisal on the associations between emotional expression and global distress and for acceptance on the association between emotional processing and cancer-specific distress were found. Results indicate several cognitive-social processes directly predict partner distress. However, moderator effect models in which the effects of partners' processing depends upon whether these efforts result in changes in perceptions of the cancer experience may add to the understanding of partners' adaptation to cancer.
Early detection of epilepsy seizures based on a weightless neural network.

PubMed

de Aguiar, Kleber; Franca, Felipe M G; Barbosa, Valmir C; Teixeira, Cesar A D

2015-08-01

This work introduces a new methodology for the early detection of epileptic seizure based on the WiSARD weightless neural network model and a new approach in terms of preprocessing the electroencephalogram (EEG) data. WiSARD has, among other advantages, the capacity of perform the training phase in a very fast way. This speed in training is due to the fact that WiSARD's neurons work like Random Access Memories (RAM) addressed by input patterns. Promising results were obtained in the anticipation of seizure onsets in four representative patients from the European Database on Epilepsy (EPILEPSIAE). The proposed seizure early detection WNN architecture was explored by varying the detection anticipation (δ) in the 2 to 30 seconds interval, and by adopting 2 and 3 seconds as the width of the Sliding Observation Window (SOW) input. While in the most challenging patient (A) one obtained accuracies from 99.57% (δ=2s; SOW=3s) to 72.56% (δ=30s; SOW=2s), patient D seizures could be detected in the 99.77% (δ=2s; SOW=2s) to 99.93% (δ=30s; SOW=3s) accuracy interval.
How Homes Influence Schools: Early Parenting Predicts African American Children's Classroom Social-Emotional Functioning

ERIC Educational Resources Information Center

Baker, Claire E.; Rimm-Kaufman, Sara E.

2014-01-01

Data from the Early Childhood Longitudinal Study, Kindergarten Cohort were used to examine the extent to which early parenting predicted African American children's kindergarten social-emotional functioning. Teachers rated children's classroom social-emotional functioning in four areas (i.e., approaches to learning, self-control, interpersonal…
[Usefulness of upper gastrointestinal series to detect leaks in the early postoperative period of bariatric surgery].

PubMed

Medina, Francisco J; Miranda-Merchak, Andrés; Martínez, Alonso; Sánchez, Felipe; Bravo, Sebastián; Contreras, Juan Eduardo; Alliende, Isabel; Canals, Andrea

2016-04-01

Postoperative leaks are the most undesirable complication of bariatric surgery and upper gastrointestinal (GI) series are routinely ordered to rule them out. Despite the published literature recommending against its routine use, it is still being customarily used in Chile. To examine the usefulness of routine upper GI series using water-soluble iodinated contrast media for the detection of early postoperative leaks in patients undergoing bariatric surgery. A cohort of 328 patients subjected to bariatric surgery was followed from October 2012 to October 2013. Most of them underwent sleeve gastrectomy. Upper GI series on the first postoperative day were ordered to 308 (94%) patients. Postoperative leaks were observed in two patients, with an incidence of 0.6%. The sensitivity for upper GI series detection of leak was 0% and the negative predictive value was 99%. Routine upper GI series after bariatric surgery is not useful for the diagnosis of postoperative leak, given the low incidence of this complication and the low sensitivity of the technique.
Flow Test to Predict Early Hypotony and Hypertensive Phase After Ahmed Glaucoma Valve (AGV) Surgical Implantation.

PubMed

Cheng, Jason; Beltran-Agullo, Laura; Buys, Yvonne M; Moss, Edward B; Gonzalez, Johanna; Trope, Graham E

2016-06-01

To assess the validity of a preimplantation flow test to predict early hypotony [intraocular pressure (IOP)≤5 mm Hg on 2 consecutive visits and hypertensive phase (HP) (IOP>21 mm Hg) after Ahmed Glaucoma Valve (AGV) implantation. Prospective interventional study on patients receiving an AGV. A preimplantation flow test using a gravity-driven reservoir and an open manometer was performed on all AGVs. Opening pressure (OP) and closing pressure (CP) were defined as the pressure at which fluid was seen to flow or stop flowing through the AGV, respectively. OP and CP were measured twice per AGV. Patients were followed for 12 weeks. In total, 20 eyes from 19 patients were enrolled. At 12 weeks the mean IOP decreased from 29.2±9.1 to 16.8±5.2 mm Hg (P<0.01). The mean AGV OP was 17.5±5.4 mm Hg and the mean CP was 6.7±2.3 mm Hg. Early (within 2 wk postoperative) HP occurred in 37% and hypotony in 16% of cases. An 18 mm Hg cutoff for the OP gave a sensitivity of 0.71, specificity of 0.83, positive predictive value of 0.71, and negative predictive value of 0.83 for predicting an early HP. A 7 mm Hg cutoff for the CP yielded a sensitivity of 1.0, specificity of 0.38, positive predictive value of 0.23, and negative predictive value of 1.0 for predicting hypotony. Preoperative OP and CP may predict early hypotony or HP and may be used as a guide as to which AGV valves to discard before implantation surgery.

DCP's Early Detection Research Guides Future Science | Division of Cancer Prevention

Cancer.gov

Early detection research funded by the NCI's Division of Cancer Prevention has positively steered both public health and clinical outcomes, and set the stage for findings in the next generation of research. |
IL-10 combined with procalcitonin improves early prediction of complications of febrile neutropenia in hematological patients.

PubMed

Vänskä, Matti; Koivula, Irma; Jantunen, Esa; Hämäläinen, Sari; Purhonen, Anna-Kaisa; Pulkki, Kari; Juutilainen, Auni

2012-12-01

Early diagnosis of complicated course in febrile neutropenia is cumbersome due to the non-specificity of clinical and laboratory signs of severe infection. This prospective study included 100 adult hematological patients with febrile neutropenia after intensive chemotherapy at the onset of fever (d0) and for 3 days (d1-d3) thereafter. The study aim was to find early predictors for complicated course of febrile neutropenia, defined as bacteremia or septic shock. Interleukin 6 (IL-6), interleukin 10 (IL-10), procalcitonin (PCT) and C-reactive protein (CRP) all predicted complicated course of febrile neutropenia on d0, but only PCT was predictive throughout the study period. For IL-10 on d0-1 with cut-off 37 ng/L, sensitivity was 0.71, specificity 0.82, positive predictive value 0.52 and negative predictive value 0.92. For PCT on d0-1 with cut-off 0.13 μg/L, the respective measures were 0.95, 0.53, 0.36, and 0.98. For the combination of IL-10 and PCT on d0-1 with the same cut-offs, specificity improved to 0.85 and positive predictive value to 0.56. In conclusion, the present study confirms the high negative predictive value of PCT and provides new evidence for IL-10 as an early predictor for complicated course of febrile neutropenia in hematological patients. Combining IL-10 with PCT improves the early prediction for complicated course of febrile neutropenia. Copyright © 2012 Elsevier Ltd. All rights reserved.
Understanding Perceived Benefit of Early Cancer Detection: Community-Partnered Research with African American Women in South Los Angeles.

PubMed

Bazargan, Mohsen; Lucas-Wright, Anna; Jones, Loretta; Vargas, Roberto; Vadgama, Jaydutt V; Evers-Manly, Shirley; Maxwell, Annette E

2015-09-01

African American women have lower 5-year cancer survival rates than non-Latino White women. Differences in perceived benefits of early cancer detection among racial/ethnic groups may affect cancer-screening behaviors. This study assessed correlates of perceived benefits of early breast, cervical and colorectal cancer detection among 513 African American women. Using a community-partnered participatory research approach, we conducted a survey on cancer screening, risk behaviors, and related knowledge and attitudes among African American parishioners at 11 churches in South Los Angeles, a neighborhood that experiences one of the highest cancer mortality rates in California. African American women who participated in this study were more likely to believe that chances for survival are very good or good after early detection of breast cancer (74%) than after early detection of colorectal (51%) and cervical cancer (52%). Multivariate analyses show that perceived benefit of early cancer detection is associated with higher cancer knowledge and having discussed one's cancer risk with a doctor. Given that 5-year survival rates for early stage breast, cervical, and colorectal cancer range from 84% to 93%, our data suggest that a substantial proportion of African American women in South Los Angeles are not aware of the benefits of early detection, particularly of colorectal and cervical cancers. Programs that increase cancer knowledge and encourage a discussion of individual's cancer risk with a doctor may be able to increase perceived benefit of early detection, a construct that has been shown to be associated with cancer screening in some studies.
Use of reflectance spectroscopy for early detection of calcium deficiency in plants

NASA Astrophysics Data System (ADS)

Li, Bingqing; Wah, Liew Oi; Asundi, Anand K.

2005-04-01

This article investigates calcium deficiency symptoms of the plants grown under hydroponics conditions. Leaf reflectance data were collected from plants, and then transformed to L*, a*, b* values, which provide color information of the leaves. After comparing the color information of deficient plants to control plants, a set of deficiency criterion was established for early detection of calcium deficiency in the plants. Calcium deficiency could be detected as early as two days from the onset of stress in mature plants when optical data were collected from terminal young leaves. Young plants subjected to calcium stress for 9 days could not be distinguished from nutrient sufficient plants.
Predictive values of BI-RADS(®) magnetic resonance imaging (MRI) in the detection of breast ductal carcinoma in situ (DCIS).

PubMed

Badan, Gustavo Machado; Piato, Sebastião; Roveda, Décio; de Faria Castro Fleury, Eduardo

2016-10-01

The purpose of this study was to evaluate BI-RADS indicators in the detection of DCIS by MRI. Prospective observational study that started in 2014 and lasted 24 months. A total of 110 consecutive patients were evaluated, who presented with suspicious or highly suspicious microcalcifications on screening mammography (BI-RADS categories 4 and 5) and underwent stereotactic-guided breast biopsy, having had an MRI scan performed prior to biopsy. Altogether, 38 cases were characterized as positive for malignancy, of which 25 were DCIS and 13 were invasive ductal carcinoma cases. MRI had a sensitivity of 96%; specificity of 75.67%; positive predictive value (PPV) for DCIS detection of 57.14%; negative predictive value (NPV) in the detection of DCIS of 98.24%; and an accuracy of 80.80%. BI-RADS as a tool for the detection of DCIS by MRI is a powerful instrument whose sensitivity was higher when compared to that observed for mammography in the literature. Likewise, the PPV obtained by MRI was higher than that observed in the present study for mammography, and the high NPV obtained on MRI scans can provide early evidence to discourage breast biopsy in selected cases. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Connective tissue-activating peptide III: a novel blood biomarker for early lung cancer detection.

PubMed

Yee, John; Sadar, Marianne D; Sin, Don D; Kuzyk, Michael; Xing, Li; Kondra, Jennifer; McWilliams, Annette; Man, S F Paul; Lam, Stephen

2009-06-10

There are no reliable blood biomarkers to detect early lung cancer. We used a novel strategy that allows discovery of differentially present proteins against a complex and variable background. Mass spectrometry analyses of paired pulmonary venous-radial arterial blood from 16 lung cancer patients were applied to identify plasma proteins potentially derived from the tumor microenvironment. Two differentially expressed proteins were confirmed in 64 paired venous-arterial blood samples using an immunoassay. Twenty-eight pre- and postsurgical resection peripheral blood samples and two independent, blinded sets of plasma from 149 participants in a lung cancer screening study (49 lung cancers and 100 controls) and 266 participants from the National Heart Lung and Blood Institute Lung Health Study (45 lung cancer and 221 matched controls) determined the accuracy of the two protein markers to detect subclinical lung cancer. Connective tissue-activating peptide III (CTAP III)/ neutrophil activating protein-2 (NAP-2) and haptoglobin were identified to be significantly higher in venous than in arterial blood. CTAP III/NAP-2 levels decreased after tumor resection (P = .01). In two independent population cohorts, CTAP III/NAP-2 was significantly associated with lung cancer and improved the accuracy of a lung cancer risk prediction model that included age, smoking, lung function (FEV(1)), and an interaction term between FEV(1) and CTAP III/NAP-2 (area under the curve, 0.84; 95% CI, 0.77 to 0.91) compared to CAPIII/NAP-2 alone. We identified CTAP III/NAP-2 as a novel biomarker to detect preclinical lung cancer. The study underscores the importance of applying blood biomarkers as part of a multimodal lung cancer risk prediction model instead of as stand-alone tests.
Important first encounter: Service user experience of pathways to care and early detection in first-episode psychosis.

PubMed

Jansen, Jens Einar; Pedersen, Marlene Buch; Hastrup, Lene Halling; Haahr, Ulrik Helt; Simonsen, Erik

2018-04-01

Long duration of untreated psychosis is associated with poor clinical and functional outcomes. However, few systematic attempts have been made to reduce this delay and little is known of service users' experience of early detection efforts. We explored service users' experience of an early detection service and transition to specialized treatment service, including pathway to care, understanding of illness and barriers to adequate assessment and treatment. In-depth interviews were conducted with 10 service users (median age 21, range 18-27, five males and five females) who were diagnosed with a first-episode non-affective psychosis and who were seen by an early detection team (TOP) and currently enrolled in a specialized early intervention service for this disorder (OPUS). Stigma and fear of the 'psychiatric system' were reported as significant barriers to help seeking, while family members were seen as a crucial support. Moreover, the impact of traumatic events on the experience and development of psychosis was highlighted. Finally, participants were relieved by the prospect of receiving help and the early detection team seemed to create a trusting relationship by offering a friendly, 'anti-stigmatized' space, where long-term symptomatology could be disclosed through accurate and validating questioning. Early detection services have two important functions. One is to make accurate assessments and referrals. The other is to instil hope and trust, and to facilitate further treatment by forming an early therapeutic alliance. The findings in this study provide important insights into the way in which early detection efforts and pathways to care are experienced by service users, with direct implications for improving psychiatric services. © 2015 Wiley Publishing Asia Pty Ltd.
Predicting early cognitive decline in newly-diagnosed Parkinson's patients: A practical model.

PubMed

Hogue, Olivia; Fernandez, Hubert H; Floden, Darlene P

2018-06-19

To create a multivariable model to predict early cognitive decline among de novo patients with Parkinson's disease, using brief, inexpensive assessments that are easily incorporated into clinical flow. Data for 351 drug-naïve patients diagnosed with idiopathic Parkinson's disease were obtained from the Parkinson's Progression Markers Initiative. Baseline demographic, disease history, motor, and non-motor features were considered as candidate predictors. Best subsets selection was used to determine the multivariable baseline symptom profile that most accurately predicted individual cognitive decline within three years. Eleven per cent of the sample experienced cognitive decline. The final logistic regression model predicting decline included five baseline variables: verbal memory retention, right-sided bradykinesia, years of education, subjective report of cognitive impairment, and REM behavior disorder. Model discrimination was good (optimism-adjusted concordance index = .749). The associated nomogram provides a tool to determine individual patient risk of meaningful cognitive change in the early stages of the disease. Through the consideration of easily-implemented or routinely-gathered assessments, we have identified a multidimensional baseline profile and created a convenient, inexpensive tool to predict cognitive decline in the earliest stages of Parkinson's disease. The use of this tool would generate prediction at the individual level, allowing clinicians to tailor medical management for each patient and identify at-risk patients for clinical trials aimed at disease modifying therapies. Copyright © 2018. Published by Elsevier Ltd.
Staphylococcus aureus carriage at admission predicts early-onset pneumonia after burn trauma.

PubMed

Fournier, A; Voirol, P; Krähenbühl, M; Bonnemain, C-L; Fournier, C; Dupuis-Lozeron, E; Pantet, O; Pagani, J-L; Revelly, J-P; Sadeghipour, F; Eggimann, P; Que, Y-A

2017-03-01

Early-onset pneumonia (EOP) is frequent after burn trauma, increasing morbidity in the critical resuscitation phase, which may preclude early aggressive management of burn wounds. Currently, however, preemptive treatment is not recommended. The aim of this study was to identify predictive factors for EOP that may justify early empirical antibiotic treatment. Data for all burn patients requiring ≥4 h mechanical ventilation (MV) who were admitted between January 2001 and October 2012 were extracted from the hospital's computerized information system. We reviewed EOP episodes (≤7 days) among patients who underwent endotracheal aspiration (ETA) within 5 days after admission. Univariate and multivariate analyses were performed to identify independent factors associated with EOP. Logistic regression was used to identify factors predicting EOP development. During the study period, 396 burn patients were admitted. ETA was performed within 5 days in 204/290 patients receiving ≥4 h MV. One hundred and eight patients developed EOP; 47 cases were caused by Staphylococcus aureus, 37 by Haemophilus influenzae, and 23 by Streptococcus pneumoniae. Among the 33 patients showing S. aureus positivity on ETA samples, 16 (48.5 %) developed S. aureus EOP. Among the 156 S. aureus non-carriers, 16 (10.2 %) developed EOP. Staphylococcus aureus carriage independently predicted EOP (p < 0.0001). We identified S. aureus carriage as an independent and strong predictor of EOP. As rapid point-of-care testing for S. aureus is readily available, we recommend testing of all patients at admission for burn trauma and the consideration of early preemptive treatment in all positive patients. Further studies are needed to evaluate this new strategy.
Predicting Early Maladaptive Schemas Using Baumrind's Parenting Styles.

PubMed

Esmali Kooraneh, Ahmad; Amirsardari, Leili

2015-06-01

Families play an essential role in maintaining children's mental, social, and physical health. The family provides the first and the most important social context for human development. The present study aimed to predict early maladaptive schemas using Baumrind's parenting styles (root development). A total of 357 undergraduate students of Islamic Azad University, Urmia Branch, Iran, were selected through random cluster sampling during 2013 and 2014. The students were assessed using the Schema Questionnaire-Short Form (SQ-SF) and the Baumrind's parenting styles inventories. The result of regression analysis showed that Baumrind's parenting styles are significant predictors of early maladaptive schemas (P < 0.001). The authoritative parenting style has some features such as showing high levels of warmth or encouraging kids to express their own possibly divergent opinions. The authoritarian parenting style, however, possesses traits such as heartlessness, impassiveness, strictness, and lack of attention to the children's developmental needs, which is not acceptable.
Sampling design for early detection of aquatic invasive species in Great Lakes ports

EPA Science Inventory

We evaluated a pilot adaptive monitoring program for aquatic invasive species (AIS) early detection in Lake Superior. The monitoring program is designed to detect newly-introduced fishes, and encompasses the lake’s three major ports (Duluth-Superior, Sault Ste. Marie, Thund...
Can overt diabetes mellitus be predicted by an early A1C value in gestational diabetics?

PubMed

Granada, Catalina; Forbes, Joanna; Sangi-Haghpeykar, Haleh; Davidson, Christina

2014-01-01

To test the hypothesis that a hemoglobin A1C value (A1C) in early pregnancy is predictive of overt diabetes mellitus (DM) postpartum in women with gestational diabetes (GDM). In this case-control analysis of women with an early pregnancy diagnosis of GDM, we estimated the association between an early pregnancy A1C and subsequent diagnosis of DM. Women with a normal postpartum diabetic screen (controls) were compared against those with confirmed postpartum DM (cases). Ability of A1C levels to predict DM was examined via logistic regression analysis and corresponding receiver operating characteristic values. During the 10-year study period 166 women met the inclusion criteria: 140 (84%) had normal postpartum testing (controls), and 26 (16%) were diagnosed with DM (cases). The mean A1C value was significantly higher among cases than controls (6.7 vs. 5.6, p < 0.0001, SD 1.3-5). Cases had A1Cs ranging from 5.5- 11.7%, while controls had A1Cs ranging from 4.3-7.8%. The best discriminatory cut point for postpartum DM was an A1C > 5.9% (sensitivity 81%, specificity 83%, positive predictive value 47%, negative predictive value Our findings suggest that an elevated early pregnancy A1C may be predictive of overt DM. Larger studies are needed to further validate this association.
Maternal Psychopathology and Early Child Temperament Predict Young Children's Salivary Cortisol 3 Years Later

ERIC Educational Resources Information Center

Dougherty, Lea R.; Smith, Victoria C.; Olino, Thomas M.; Dyson, Margaret W.; Bufferd, Sara J.; Rose, Suzanne A.; Klein, Daniel N.

2013-01-01

Neuroendocrine dysfunction is hypothesized to be an early emerging vulnerability marker for depression. We tested whether the main and interactive effects of maternal psychopathology and early child temperamental vulnerability for depression assessed at age three predicted offspring's basal cortisol function at age 6 years. 228 (122 males)…
Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations from the CDC Working Group.

PubMed

Buehler, James W; Hopkins, Richard S; Overhage, J Marc; Sosin, Daniel M; Tong, Van

2004-05-07

The threat of terrorism and high-profile disease outbreaks has drawn attention to public health surveillance systems for early detection of outbreaks. State and local health departments are enhancing existing surveillance systems and developing new systems to better detect outbreaks through public health surveillance. However, information is limited about the usefulness of surveillance systems for outbreak detection or the best ways to support this function. This report supplements previous guidelines for evaluating public health surveillance systems. Use of this framework is intended to improve decision-making regarding the implementation of surveillance for outbreak detection. Use of a standardized evaluation methodology, including description of system design and operation, also will enhance the exchange of information regarding methods to improve early detection of outbreaks. The framework directs particular attention to the measurement of timeliness and validity for outbreak detection. The evaluation framework is designed to support assessment and description of all surveillance approaches to early detection, whether through traditional disease reporting, specialized analytic routines for aberration detection, or surveillance using early indicators of disease outbreaks, such as syndromic surveillance.
Early detection surveillance for an emerging plant pathogen: a rule of thumb to predict prevalence at first discovery.

PubMed

Parnell, S; Gottwald, T R; Cunniffe, N J; Alonso Chavez, V; van den Bosch, F

2015-09-07

Emerging plant pathogens are a significant problem for conservation and food security. Surveillance is often instigated in an attempt to detect an invading epidemic before it gets out of control. Yet in practice many epidemics are not discovered until already at a high prevalence, partly due to a lack of quantitative understanding of how surveillance effort and the dynamics of an invading epidemic relate. We test a simple rule of thumb to determine, for a surveillance programme taking a fixed number of samples at regular intervals, the distribution of the prevalence an epidemic will have reached on first discovery (discovery-prevalence) and its expectation E(q*). We show that E(q*) = r/(N/Δ), i.e. simply the rate of epidemic growth divided by the rate of sampling; where r is the epidemic growth rate, N is the sample size and Δ is the time between sampling rounds. We demonstrate the robustness of this rule of thumb using spatio-temporal epidemic models as well as data from real epidemics. Our work supports the view that, for the purposes of early detection surveillance, simple models can provide useful insights in apparently complex systems. The insight can inform decisions on surveillance resource allocation in plant health and has potential applicability to invasive species generally. © 2015 The Author(s).
Early detection of crop injury from herbicide glyphosate by leaf biochemical parameter inversion

USDA-ARS?s Scientific Manuscript database

Early detection of crop injury from glyphosate is of significant importance in crop management. In this paper, we attempt to detect glyphosate-induced crop injury by PROSPECT (leaf optical PROperty SPECTra model) inversion through leaf hyperspectral reflectance measurements for non-Glyphosate-Resist...
Predictive information processing is a fundamental learning mechanism present in early development: evidence from infants.

PubMed

Trainor, Laurel J

2012-02-01

Evidence is presented that predictive coding is fundamental to brain function and present in early infancy. Indeed, mismatch responses to unexpected auditory stimuli are among the earliest robust cortical event-related potential responses, and have been measured in young infants in response to many types of deviation, including in pitch, timing, and melodic pattern. Furthermore, mismatch responses change quickly with specific experience, suggesting that predictive coding reflects a powerful, early-developing learning mechanism. Copyright © 2011 Elsevier B.V. All rights reserved.
Developing a discrete choice experiment in Malawi: eliciting preferences for breast cancer early detection services.

PubMed

Kohler, Racquel E; Lee, Clara N; Gopal, Satish; Reeve, Bryce B; Weiner, Bryan J; Wheeler, Stephanie B

2015-01-01

In Malawi, routine breast cancer screening is not available and little is known about women's preferences regarding early detection services. Discrete choice experiments are increasingly used to reveal preferences about new health services; however, selecting appropriate attributes that describe a new health service is imperative to ensure validity of the choice experiment. To identify important factors that are relevant to Malawian women's preferences for breast cancer detection services and to select attributes and levels for a discrete choice experiment in a setting where both breast cancer early detection and choice experiments are rare. We reviewed the literature to establish an initial list of potential attributes and levels for a discrete choice experiment and conducted qualitative interviews with health workers and community women to explore relevant local factors affecting decisions to use cancer detection services. We tested the design through cognitive interviews and refined the levels, descriptions, and designs. Themes that emerged from interviews provided critical information about breast cancer detection services, specifically, that breast cancer interventions should be integrated into other health services because asymptomatic screening may not be practical as an individual service. Based on participants' responses, the final attributes of the choice experiment included travel time, health encounter, health worker type and sex, and breast cancer early detection strategy. Cognitive testing confirmed the acceptability of the final attributes, comprehension of choice tasks, and women's abilities to make trade-offs. Applying a discrete choice experiment for breast cancer early detection was feasible with appropriate tailoring for a low-income, low-literacy African setting.
Comparison of Swirl Sign and Black Hole Sign in Predicting Early Hematoma Growth in Patients with Spontaneous Intracerebral Hemorrhage.

PubMed

Xiong, Xin; Li, Qi; Yang, Wen-Song; Wei, Xiao; Hu, Xi; Wang, Xing-Chen; Zhu, Dan; Li, Rui; Cao, Du; Xie, Peng

2018-01-29

BACKGROUND Early hematoma growth is associated with poor outcome in patients with spontaneous intracerebral hemorrhage (ICH). The swirl sign (SS) and the black hole sign (BHS) are imaging markers in ICH patients. The aim of this study was to compare the predictive value of these 2 signs for early hematoma growth. MATERIAL AND METHODS ICH patients were screened for the appearance of the 2 signs within 6 h after onset of symptoms. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the 2 signs in predicting early hematoma growth were assessed. The accuracy of the 2 signs in predicting early hematoma growth was analyzed by receiver-operator analysis. RESULTS A total of 200 patients were enrolled in this study. BHS was found in 30 (15%) patients, and SS was found in 70 (35%) patients. Of the 71 patients with early hematoma growth, BHS was found on initial computed tomography scans in 24 (33.8%) and SS in 33 (46.5%). The sensitivity, specificity, PPV, and NPV of BHS for predicting early hematoma growth were 33.8%, 95.3%, 80.0%, and 72.0%, respectively. The sensitivity, specificity, PPV, and NPV of SS were 46.5%, 71.3%, 47.0%, and 71.0%, respectively. The area under the curve was 0.646 for BHS and 0.589 for SS (P=0.08). Multivariate logistic regression showed that presence of BHS is an independent predictor of early hematoma growth. CONCLUSIONS The Black hole sign seems to be good predictor for hematoma growth. The presence of swirl sign on admission CT does not independently predict hematoma growth in patients with ICH.
Distributed fiber optic sensor-enhanced detection and prediction of shrinkage-induced delamination of ultra-high-performance concrete overlay

NASA Astrophysics Data System (ADS)

Bao, Yi; Valipour, Mahdi; Meng, Weina; Khayat, Kamal H.; Chen, Genda

2017-08-01

This study develops a delamination detection system for smart ultra-high-performance concrete (UHPC) overlays using a fully distributed fiber optic sensor. Three 450 mm (length) × 200 mm (width) × 25 mm (thickness) UHPC overlays were cast over an existing 200 mm thick concrete substrate. The initiation and propagation of delamination due to early-age shrinkage of the UHPC overlay were detected as sudden increases and their extension in spatial distribution of shrinkage-induced strains measured from the sensor based on pulse pre-pump Brillouin optical time domain analysis. The distributed sensor is demonstrated effective in detecting delamination openings from microns to hundreds of microns. A three-dimensional finite element model with experimental material properties is proposed to understand the complete delamination process measured from the distributed sensor. The model is validated using the distributed sensor data. The finite element model with cohesive elements for the overlay-substrate interface can predict the complete delamination process.

Environmental DNA as a new method for early detection of New Zealand mudsnails (Potamopyrgus antipodarum)

USGS Publications Warehouse

Goldberg, Caren S.; Sepulveda, Adam; Ray, Andrew; Baumgardt, Jeremy A.; Waits, Lisette P.

2013-01-01

Early detection of aquatic invasive species is a critical task for management of aquatic ecosystems. This task is hindered by the difficulty and cost of surveying aquatic systems thoroughly. The New Zealand mudsnail (Potamopyrgus antipodarum) is a small, invasive parthenogenic mollusk that can reach very high population densities and severely affects ecosystem functioning. To assist in the early detection of this invasive species, we developed and validated a highly sensitive environmental deoxyribonucleic acid (eDNA) assay. We used a dose–response laboratory experiment to investigate the relationship between New Zealand mudsnail density and eDNA detected through time. We documented that as few as 1 individual in 1.5 L of water for 2 d could be detected with this method, and that eDNA from this species may remain detectable for 21 to 44 d after mudsnail removal. We used the eDNA method to confirm the presence of New Zealand mudsnail eDNA at densities as low as 11 to 144 snails/m2 in a eutrophic 5th-order river. Combined, these results demonstrate the high potential for eDNA surveys to assist with early detection of a widely distributed invasive aquatic invertebrate.
Exploring Early Detection Methods: Using the Intraductal Approach to Predict Breast Cancer

DTIC Science & Technology

2005-06-01

Evidence of intraductal and atypical hyperplasia in from mutations. Prehn (1994) wrote that mutations may have epithelial cells may allow for prediction and...Cler, L., Shivapurkar, N., Milchgrub, S., Peters, G.N., Leitch, Prehn , R.T. (1994). Cancers beget mutations versus mutations beget cancers. A.M., et
Prediction Metrics for Chemical Detection in Long-Wave Infrared Hyperspectral Imagery

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

Chilton, Marie C.; Walsh, Stephen J.; Daly, Don S.

2009-01-29

A natural or anthropogenic process often generates a signature gas plume whose chemical constituents may be identified using hyperspectral imagery. A hyperspectral image is a pixel-indexed set of spectra where each spectrum reflects the chemical constituents of the plume, the atmosphere, the bounding background surface, and instrument noise. This study explored the relationship between gas absorbance and background emissivity across the long-wave infrared (LWIR) spectrum and how they affect relative gas detection sensitivity. The physics-based model for the observed radiance shows that high gas absorbance coupled with low background emissivity at a single wavenumber results in a stronger recorded radiance.more » Two sensitivity measures were developed to predict relative probability of detection using chemical absorbance and background emissivity: one focused on a single wavenumber while another accounted for the entire spectrum. The predictive abilities of these measures were compared to synthetic image analysis. This study simulated images with 499 distinct gases at each of 6 concentrations over 6 different background surfaces with the atmosphere and level of instrument noise held constant. The Whitened Matched Filter was used to define gas detection from an image spectrum. The estimate of a chemical’s probability of detection at a given concentration over a specific background was the proportion of detections in 500 trials. Of the 499 chemicals used in the images, 276 had estimated probabilities of detection below 0.2 across all backgrounds and concentrations; these chemicals were removed from the study. For 92.8 percent of the remaining chemicals, the single channel measure correctly predicted the background over which the chemical had the largest relative probability of detection. Further, the measure which accounted for information across all wavenumbers predicted the background over which the chemical had the largest relative probability of detection for
Identification and Prediction of Drinking Trajectories in Early and Mid-Adolescence

ERIC Educational Resources Information Center

Van Der Vorst, Haske; Vermulst, Ad A.; Meeus, Wim H. J.; Dekovic, Maja; Engels, Rutger C. M. E.

2009-01-01

The aim of this study was to identify subgroups of early and mid-adolescents with different drinking trajectories. In addition, we examined whether gender, parental, and peer factors predicted adolescents' membership of these drinking trajectories. We used longitudinal data of 428 families (fathers, mothers, mid-adolescents, and their younger…
Methods for Detecting Early Warnings of Critical Transitions in Time Series Illustrated Using Simulated Ecological Data

PubMed Central

Dakos, Vasilis; Carpenter, Stephen R.; Brock, William A.; Ellison, Aaron M.; Guttal, Vishwesha; Ives, Anthony R.; Kéfi, Sonia; Livina, Valerie; Seekell, David A.; van Nes, Egbert H.; Scheffer, Marten

2012-01-01

Many dynamical systems, including lakes, organisms, ocean circulation patterns, or financial markets, are now thought to have tipping points where critical transitions to a contrasting state can happen. Because critical transitions can occur unexpectedly and are difficult to manage, there is a need for methods that can be used to identify when a critical transition is approaching. Recent theory shows that we can identify the proximity of a system to a critical transition using a variety of so-called ‘early warning signals’, and successful empirical examples suggest a potential for practical applicability. However, while the range of proposed methods for predicting critical transitions is rapidly expanding, opinions on their practical use differ widely, and there is no comparative study that tests the limitations of the different methods to identify approaching critical transitions using time-series data. Here, we summarize a range of currently available early warning methods and apply them to two simulated time series that are typical of systems undergoing a critical transition. In addition to a methodological guide, our work offers a practical toolbox that may be used in a wide range of fields to help detect early warning signals of critical transitions in time series data. PMID:22815897
Development of Mechanochemically Active Polymers for Early Damage Detection

NASA Astrophysics Data System (ADS)

Zou, Jin

Identification of early damage in polymer composite materials is of significant importance so that preventative measures can be taken before the materials reach catastrophic failure. Scientists have been developing damage detection technologies over many years and recently, mechanophore-based polymers, in which mechanical energy is translated to activate a chemical transformation, have received increasing attention. More specifically, the damage can be made detectable by mechanochromic polymers, which provide a visible color change upon the scission of covalent bonds under stress. This dissertation focuses on the study of a novel self-sensing framework for identifying early and in-situ damage by employing unique stress-sensing mechanophores. Two types of mechanophores, cyclobutane and cyclooctane, were utilized, and the former formed from cinnamoyl moeities and the latter formed from anthracene upon photodimerization. The effects on the thermal and mechanical properties with the addition of the cyclobutane-based polymers into epoxy matrices were investigated. The emergence of cracks was detected by fluorescent signals at a strain level right after the yield point of the polymer blends, and the fluorescence intensified with the accumulation of strain. Similar to the mechanism of fluorescence emission from the cleavage of cyclobutane, the cyclooctane moiety generated fluorescent emission with a higher quantum yield upon cleavage. The experimental results also demonstrated the success of employing the cyclooctane type mechanophore as a potential force sensor, as the fluorescence intensification was correlated with the strain increase.
Robust Kalman filter design for predictive wind shear detection

NASA Technical Reports Server (NTRS)

Stratton, Alexander D.; Stengel, Robert F.

1991-01-01

Severe, low-altitude wind shear is a threat to aviation safety. Airborne sensors under development measure the radial component of wind along a line directly in front of an aircraft. In this paper, optimal estimation theory is used to define a detection algorithm to warn of hazardous wind shear from these sensors. To achieve robustness, a wind shear detection algorithm must distinguish threatening wind shear from less hazardous gustiness, despite variations in wind shear structure. This paper presents statistical analysis methods to refine wind shear detection algorithm robustness. Computational methods predict the ability to warn of severe wind shear and avoid false warning. Comparative capability of the detection algorithm as a function of its design parameters is determined, identifying designs that provide robust detection of severe wind shear.
The Effect of Early Visual Deprivation on the Development of Face Detection

ERIC Educational Resources Information Center

Mondloch, Catherine J.; Segalowitz, Sidney J.; Lewis, Terri L.; Dywan, Jane; Le Grand, Richard; Maurer, Daphne

2013-01-01

The expertise of adults in face perception is facilitated by their ability to rapidly detect that a stimulus is a face. In two experiments, we examined the role of early visual input in the development of face detection by testing patients who had been treated as infants for bilateral congenital cataract. Experiment 1 indicated that, at age 9 to…
Amplification of human papillomavirus early genes for detection of nine genotypes in Venezuelan women.

PubMed

Michelli, Elvia; Téllez, Luis; Mendoza, José-Andrés; Noguera, María-Eugenia; Milano, Melisse; Vera, Reauben; Callejas, Diana

2013-12-01

Genotyping of human papillomavirus (HPV) by molecular methods may enhance assessment information for screening and following of cervical infection. In this study, cervical samples were obtained from 250 women, along with colposcopic and cytological evaluations. A Nested-PCR-Multiplex assay was used for HPV detection and genotyping for HPV E6/E7 early regions. Infection with HPV was detected in 26.0% of the samples, with 98.46% positive for at least one genotype. High-risk HPVs were identified in 98.44%. HPV18 infection was detected in 76.92% of samples and HPV16 in 36.92%, whether as individual or as multiple infections. These infections were seen more frequently in women under 35 years of age (64.7%). The Pap-smear examination showed that 16.92% (11/65) of the samples had cervical changes suggesting HPV infection, whereas the colposcopic evaluation was suggestive of HPV infection in 47.69% (31/65) of DNA-HPV positive samples. There was a high frequency of high-risk HPV genotypes, particularly HPV18, alone or in multiple-type infections. Colposcopy findings showed to have a high predictive value for the diagnosis of HPV infection. The results reflect that over 50% of HPV-positive patients had a normal colposcopy and/or cytology, highlighting the importance of including HPV testing along with genotype identification in routine gynecological evaluations.
Barriers for Early Detection of Cancer Amongst Urban Indian Women: A Cross Sectional Study

PubMed Central

Kadam, Yugantara R.; Quraishi, Sanjay R.; Dhoble, Randheer V.; Sawant, Minaxi R.; Gore, Alka D.

2016-01-01

Background: Cancer is a leading cause of death globally. Every year, millions of cancer patients could be saved from premature death and and suffering if they had timely access to early detection and treatment. There are two main components of early detection: early diagnosis and screening. In India, cancers of cervix, breast, mouth/oropharynx are the most frequent cancers in women. These cancers are amenable to early detection. More than two third of the cancer patients are already in an advanced and incurable stage at the time of diagnosis. Objectives: This study was designed with the aim to know the reasons for non availment of cancer screening procedures and early diagnostic facilities. Materials and Methods: This cross-sectional study was planned in Sangli, Miraj and Kupwad Corporation area during October 2013 - March 2014 by a pretested questionnaire. Women of 25 years and above were study subjects selected randomly from a cluster sample of ward with estimated sample size of 559 women. Statistical analysis was done with the help of IBM SPSS 22. Results: Nearly 74% of women said that cancer is curable. For awareness about signs and symptoms, risk factors and screening test 82.3% women scored less than 50% of total score. Only 17.7% women had awareness score more than 50%. But their attitude score was > 50% in 85.2% of women. For practice score, 24.4% women scored > 50%. Significant association was found between awareness, attitude and practice scores and education, occupation and history of cancer in family, friends and neighborhood of respondents. Conclusions: Low awareness is the main barrier for undergoing cancer screening and early detection. There is a need of effective health education programme. PMID:27366310
Hypoglycemia Early Alarm Systems Based on Recursive Autoregressive Partial Least Squares Models

PubMed Central

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Background Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. Methods A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Results Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. Conclusions The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. PMID:23439179
Hypoglycemia early alarm systems based on recursive autoregressive partial least squares models.

PubMed

Bayrak, Elif Seyma; Turksoy, Kamuran; Cinar, Ali; Quinn, Lauretta; Littlejohn, Elizabeth; Rollins, Derrick

2013-01-01

Hypoglycemia caused by intensive insulin therapy is a major challenge for artificial pancreas systems. Early detection and prevention of potential hypoglycemia are essential for the acceptance of fully automated artificial pancreas systems. Many of the proposed alarm systems are based on interpretation of recent values or trends in glucose values. In the present study, subject-specific linear models are introduced to capture glucose variations and predict future blood glucose concentrations. These models can be used in early alarm systems of potential hypoglycemia. A recursive autoregressive partial least squares (RARPLS) algorithm is used to model the continuous glucose monitoring sensor data and predict future glucose concentrations for use in hypoglycemia alarm systems. The partial least squares models constructed are updated recursively at each sampling step with a moving window. An early hypoglycemia alarm algorithm using these models is proposed and evaluated. Glucose prediction models based on real-time filtered data has a root mean squared error of 7.79 and a sum of squares of glucose prediction error of 7.35% for six-step-ahead (30 min) glucose predictions. The early alarm systems based on RARPLS shows good performance. A sensitivity of 86% and a false alarm rate of 0.42 false positive/day are obtained for the early alarm system based on six-step-ahead predicted glucose values with an average early detection time of 25.25 min. The RARPLS models developed provide satisfactory glucose prediction with relatively smaller error than other proposed algorithms and are good candidates to forecast and warn about potential hypoglycemia unless preventive action is taken far in advance. © 2012 Diabetes Technology Society.
Set-membership fault detection under noisy environment with application to the detection of abnormal aircraft control surface positions

NASA Astrophysics Data System (ADS)

El Houda Thabet, Rihab; Combastel, Christophe; Raïssi, Tarek; Zolghadri, Ali

2015-09-01

The paper develops a set membership detection methodology which is applied to the detection of abnormal positions of aircraft control surfaces. Robust and early detection of such abnormal positions is an important issue for early system reconfiguration and overall optimisation of aircraft design. In order to improve fault sensitivity while ensuring a high level of robustness, the method combines a data-driven characterisation of noise and a model-driven approach based on interval prediction. The efficiency of the proposed methodology is illustrated through simulation results obtained based on data recorded in several flight scenarios of a highly representative aircraft benchmark.
Infarct Volume Prediction by Early Magnetic Resonance Imaging in a Murine Stroke Model Depends on Ischemia Duration and Time of Imaging.

PubMed

Leithner, Christoph; Füchtemeier, Martina; Jorks, Devi; Mueller, Susanne; Dirnagl, Ulrich; Royl, Georg

2015-11-01

Despite standardization of experimental stroke models, final infarct sizes after middle cerebral artery occlusion (MCAO) vary considerably. This introduces uncertainties in the evaluation of drug effects on stroke. Magnetic resonance imaging may detect variability of surgically induced ischemia before treatment and thus improve treatment effect evaluation. MCAO of 45 and 90 minutes induced brain infarcts in 83 mice. During, and 3 and 6 hours after MCAO, we performed multiparametric magnetic resonance imaging. We evaluated time courses of cerebral blood flow, apparent diffusion coefficient (ADC), T1, T2, accuracy of infarct prediction strategies, and impact on statistical evaluation of experimental stroke studies. ADC decreased during MCAO but recovered completely on reperfusion after 45 and partially after 90-minute MCAO, followed by a secondary decline. ADC lesion volumes during MCAO or at 6 hours after MCAO largely determined final infarct volumes for 90 but not for 45 minutes MCAO. The majority of chance findings of final infarct volume differences in random group allocations of animals were associated with significant differences in early ADC lesion volumes for 90, but not for 45-minute MCAO. The prediction accuracy of early magnetic resonance imaging for infarct volumes depends on timing of magnetic resonance imaging and MCAO duration. Variability of the posterior communicating artery in C57Bl6 mice contributes to differences in prediction accuracy between short and long MCAO. Early ADC imaging may be used to reduce errors in the interpretation of post MCAO treatment effects on stroke volumes. © 2015 American Heart Association, Inc.
Efficacy of first-trimester ultrasound parameters for prediction of early spontaneous abortion.

PubMed

Datta, Mamta Rath; Raut, Ankush

2017-09-01

To assess first-trimester ultrasound measurements for the prediction of early spontaneous abortion. In a prospective observational study in Jamshedpur, India, women with singleton pregnancies of 42-76 days were enrolled between November 2014 and April 2016. Inclusion criteria were spontaneous conception, embryonic cardiac activity, and regular menstrual cycle. Fetal crown-to-rump length (CRL), gestational sac diameter (GSD), yolk sac diameter (YSD), and fetal heart rate (FHR) were measured by transvaginal ultrasonography. Ultrasonography was repeated at 12 weeks and beyond to determine pregnancy continuation. Among 800 women, 140 (17.5%) experienced early spontaneous abortion. CRL, GSD, and FHR values below the 5th percentile (odds ratio [OR] 26.48, 26.94, and 100.63, respectively), and YSD above the 95th percentile (OR 1.04) were predictors of early abortion. Normal YSD did not reduce the risk of abortion if the other three parameters were below the 5th percentile (OR 34.27). For every 10-bpm decrease in FHR below 130, there was 26.7% increased risk of abortion. GSD-CRL difference of less than 5 mm was associated with a higher likelihood of abortion (OR 4.88). First-trimester ultrasound measurements are predictors of early abortion. Risk assessment tables based on combinations of abnormal measures might improve prediction rates. © 2017 International Federation of Gynecology and Obstetrics.
OS087. Maternal characteristics, mean arterial pressure and PLGF in early prediction of preeclampsia.

PubMed

Kuc, S; Koster, M P; Franx, A; Schielen, P C; Visser, G H

2012-07-01

In a previous study, we described the predictive value of first-trimester pregnancy-associated plasma protein-A (PAPP-A), free beta-subunit of human chorionic gonadotrophin (fb-hCG), Placental Growth Factor (PlGF) and A Desintegrin And Metalloproteinase 12 (ADAM12) for early onset preeclampsia (delivery <34 weeks) [1]. The objective of the current study was to obtain the predictive value of these serum makers, for both early onset PE (EOPE) and late onset PE (LOPE), combined with maternal characteristics and first-trimester maternal mean arterial blood pressure (MAP). This was a nested case-control study, using stored first-trimester maternal serum from 167 women who subsequently developed PE, and 500 uncomplicated singleton pregnancies which resulted in a live birth =>37 weeks. Maternal characteristics (i.e. medical records, parity, weight, length) MAP and pregnancy outcome (i.e. gestational age at delivery, birthweight, fetal sex) were collected for each individual and used to calculate prior risks for PE in a multiple logistic regression model. MAP values and marker levels of PAPP-A, fb-hCG, PlGF and ADAM12 were expressed as multiples of the gestation-specific normal median (MoMs). Subsequently, MoMs were log-transformed and compared between PE and controls using Student's t-tests. Posterior risks were calculated using different combinations of variables;(1) maternal characteristics, serum markers, and MAP separately (2) maternal characteristics combined with serum markers or MAP (3) maternal characteristics combined with serum markers and MAP. The model-predicted detection rates (DR) for fixed 10% false-positive rates were obtained for EOPE and LOPE with or without intra-uterine growth restriction (IUGR,birth weight <10th centile). The maternal characteristics: maternal age, weight, length, smoking status and nulliparity were discriminative between PE and control groups and therefore incorporated in the multiple logistic regression model. MoM MAP was
Early Detection of Human Epileptic Seizures Based on Intracortical Local Field Potentials

PubMed Central

Park, Yun S.; Hochberg, Leigh R.; Eskandar, Emad N.; Cash, Sydney S.; Truccolo, Wilson

2014-01-01

The unpredictability of re-occurring seizures dramatically impacts the quality of life and autonomy of people with epilepsy. Reliable early seizure detection could open new therapeutic possibilities and thus substantially improve quality of life and autonomy. Though many seizure detection studies have shown the potential of scalp electroencephalogram (EEG) and intracranial EEG (iEEG) signals, reliable early detection of human seizures remains elusive in practice. Here, we examined the use of intracortical local field potentials (LFPs) recorded from 4×4-mm2 96-microelectrode arrays (MEA) for early detection of human epileptic seizures. We adopted a framework consisting of (1) sampling of intracortical LFPs; (2) denoising of LFPs with the Kalman filter; (3) spectral power estimation in specific frequency bands using 1-sec moving time windows; (4) extraction of statistical features, such as the mean, variance, and Fano factor (calculated across channels) of the power in each frequency band; and (5) cost-sensitive support vector machine (SVM) classification of ictal and interictal samples. We tested the framework in one-participant dataset, including 4 seizures and corresponding interictal recordings preceding each seizure. The participant was a 52-year-old woman suffering from complex partial seizures. LFPs were recorded from an MEA implanted in the participant’s left middle temporal gyrus. In this participant, spectral power in 0.3–10 Hz, 20–55 Hz, and 125–250 Hz changed significantly between ictal and interictal epochs. The examined seizure detection framework provided an event-wise sensitivity of 100% (4/4) and only one 20-sec-long false positive event in interictal recordings (likely an undetected subclinical event under further visual inspection), and a detection latency of 4.35 ± 2.21 sec (mean ± std) with respect to iEEG-identified seizure onsets. These preliminary results indicate that intracortical MEA recordings may provide key signals to quickly
A prediction model for early death in non-small cell lung cancer patients following curative-intent chemoradiotherapy.

PubMed

Jochems, Arthur; El-Naqa, Issam; Kessler, Marc; Mayo, Charles S; Jolly, Shruti; Matuszak, Martha; Faivre-Finn, Corinne; Price, Gareth; Holloway, Lois; Vinod, Shalini; Field, Matthew; Barakat, Mohamed Samir; Thwaites, David; de Ruysscher, Dirk; Dekker, Andre; Lambin, Philippe

2018-02-01

Early death after a treatment can be seen as a therapeutic failure. Accurate prediction of patients at risk for early mortality is crucial to avoid unnecessary harm and reducing costs. The goal of our work is two-fold: first, to evaluate the performance of a previously published model for early death in our cohorts. Second, to develop a prognostic model for early death prediction following radiotherapy. Patients with NSCLC treated with chemoradiotherapy or radiotherapy alone were included in this study. Four different cohorts from different countries were available for this work (N = 1540). The previous model used age, gender, performance status, tumor stage, income deprivation, no previous treatment given (yes/no) and body mass index to make predictions. A random forest model was developed by learning on the Maastro cohort (N = 698). The new model used performance status, age, gender, T and N stage, total tumor volume (cc), total tumor dose (Gy) and chemotherapy timing (none, sequential, concurrent) to make predictions. Death within 4 months of receiving the first radiotherapy fraction was used as the outcome. Early death rates ranged from 6 to 11% within the four cohorts. The previous model performed with AUC values ranging from 0.54 to 0.64 on the validation cohorts. Our newly developed model had improved AUC values ranging from 0.62 to 0.71 on the validation cohorts. Using advanced machine learning methods and informative variables, prognostic models for early mortality can be developed. Development of accurate prognostic tools for early mortality is important to inform patients about treatment options and optimize care.
[Prediction of psychosis by stepwise multilevel assessment--the Basel FePsy (Early Recognition of Psychosis)-Project].

PubMed

Riecher-Rössler, A; Aston, J; Borgwardt, S; Bugra, H; Fuhr, P; Gschwandtner, U; Koutsouleris, N; Pflueger, M; Tamagni, C; Radü, E-W; Rapp, C; Smieskova, R; Studerus, E; Walter, A; Zimmermann, R

2013-05-01

We have conducted various studies in Basel with the aim of improving the methods for the early detection of psychosis (Früherkennung von Psychosen, FePsy). From 1.3.2000 to 29.2.2004 234 individuals were screened using the Basel Screening Instrument for Psychosis (BSIP). 106 patients were identified as at risk for psychosis; out of these 53 remained in follow-up for up to 7 years (mean 5.4 years). The assessments were done with a specifically developed instrument for history taking, various scales for the psychopathology, assessments of neuropsychology and fine motor functioning, clinical and quantitative EEG, MRI of the brain, laboratory etc. Based on the BSIP alone, a relatively reliable prediction was possible: 21 (39.6%) of the individuals identified as at risk developed psychosis within the follow-up time. Post-hoc prediction could be improved to 81% by weighting psychopathology and including neuropsychology. Including the other domains obviously allows further improvements of prediction. The risk for psychosis should be assessed in a stepwise procedure. In a first step, a clinically oriented screening should be conducted. If an at-risk status is found, further assessments in various domains should be done in a specialised centre. © Georg Thieme Verlag KG Stuttgart · New York.
Simple predictive model for Early Childhood Caries of Chilean children.

PubMed

Fierro Monti, Claudia; Pérez Flores, M; Brunotto, M

2014-01-01

Early Childhood Caries (ECC), in both industrialized and developing countries, is the most prevalent chronic disease in childhood and it is still a health public problem, affecting mainly populations considered as vulnerable, despite being preventable. The purpose of this study was to obtain a simple predictive model based on risk factors for improving public health strategies for ECC prevention for 3-5 year-old children. Clinical, environmental and psycho-socio-cultural data of children (n=250) aged 3-5 years, of both genders, from the Health Centers, were recorded in a Clinical History and Behavioral Survey. 24% of children presented behavioral problems (bizarre behavior was the main feature observed as behavioral problems). The variables associated to dmf ?4 were: bad children temperament (OR=2.43 [1.34, 4.40]) and home stress (OR=3.14 [1.54, 6.41]). It was observed that the model for male gender has higher accuracy for ECC (AUC= 78%, p-value=0.000) than others. Based on the results, we proposed a model where oral hygiene, sugar intake, male gender, and difficult temperament are main factors for predicting ECC. This model could be a promising tool for cost-effective early childhood caries control.

Cognitive ability in young adulthood predicts risk of early-onset dementia in Finnish men.

PubMed

Rantalainen, Ville; Lahti, Jari; Henriksson, Markus; Kajantie, Eero; Eriksson, Johan G; Räikkönen, Katri

2018-06-06

To test if the Finnish Defence Forces Basic Intellectual Ability Test scores at 20.1 years predicted risk of organic dementia or Alzheimer disease (AD). Dementia was defined as inpatient or outpatient diagnosis of organic dementia or AD risk derived from Hospital Discharge or Causes of Death Registers in 2,785 men from the Helsinki Birth Cohort Study, divided based on age at first diagnosis into early onset (<65 years) or late onset (≥65 years). The Finnish Defence Forces Basic Intellectual Ability Test comprises verbal, arithmetic, and visuospatial subtests and a total score (scores transformed into a mean of 100 and SD of 15). We used Cox proportional hazard models and adjusted for age at testing, childhood socioeconomic status, mother's age at delivery, parity, participant's birthweight, education, and stroke or coronary heart disease diagnosis. Lower cognitive ability total and verbal ability (hazard ratio [HR] per 1 SD disadvantage >1.69, 95% confidence interval [CI] 1.01-2.63) scores predicted higher early-onset any dementia risk across the statistical models; arithmetic and visuospatial ability scores were similarly associated with early-onset any dementia risk, but these associations weakened after covariate adjustments (HR per 1 SD disadvantage >1.57, 95% CI 0.96-2.57). All associations were rendered nonsignificant when we adjusted for participant's education. Cognitive ability did not predict late-onset dementia risk. These findings reinforce previous suggestions that lower cognitive ability in early life is a risk factor for early-onset dementia. © 2018 American Academy of Neurology.
Profiling persistent tubercule bacilli from patient sputa during therapy predicts early drug efficacy.

PubMed

Honeyborne, Isobella; McHugh, Timothy D; Kuittinen, Iitu; Cichonska, Anna; Evangelopoulos, Dimitrios; Ronacher, Katharina; van Helden, Paul D; Gillespie, Stephen H; Fernandez-Reyes, Delmiro; Walzl, Gerhard; Rousu, Juho; Butcher, Philip D; Waddell, Simon J

2016-04-07

New treatment options are needed to maintain and improve therapy for tuberculosis, which caused the death of 1.5 million people in 2013 despite potential for an 86 % treatment success rate. A greater understanding of Mycobacterium tuberculosis (M.tb) bacilli that persist through drug therapy will aid drug development programs. Predictive biomarkers for treatment efficacy are also a research priority. Genome-wide transcriptional profiling was used to map the mRNA signatures of M.tb from the sputa of 15 patients before and 3, 7 and 14 days after the start of standard regimen drug treatment. The mRNA profiles of bacilli through the first 2 weeks of therapy reflected drug activity at 3 days with transcriptional signatures at days 7 and 14 consistent with reduced M.tb metabolic activity similar to the profile of pre-chemotherapy bacilli. These results suggest that a pre-existing drug-tolerant M.tb population dominates sputum before and after early drug treatment, and that the mRNA signature at day 3 marks the killing of a drug-sensitive sub-population of bacilli. Modelling patient indices of disease severity with bacterial gene expression patterns demonstrated that both microbiological and clinical parameters were reflected in the divergent M.tb responses and provided evidence that factors such as bacterial load and disease pathology influence the host-pathogen interplay and the phenotypic state of bacilli. Transcriptional signatures were also defined that predicted measures of early treatment success (rate of decline in bacterial load over 3 days, TB test positivity at 2 months, and bacterial load at 2 months). This study defines the transcriptional signature of M.tb bacilli that have been expectorated in sputum after two weeks of drug therapy, characterizing the phenotypic state of bacilli that persist through treatment. We demonstrate that variability in clinical manifestations of disease are detectable in bacterial sputa signatures, and that the changing M.tb m
Smoke regions extraction based on two steps segmentation and motion detection in early fire

NASA Astrophysics Data System (ADS)

Jian, Wenlin; Wu, Kaizhi; Yu, Zirong; Chen, Lijuan

2018-03-01

Aiming at the early problems of video-based smoke detection in fire video, this paper proposes a method to extract smoke suspected regions by combining two steps segmentation and motion characteristics. Early smoldering smoke can be seen as gray or gray-white regions. In the first stage, regions of interests (ROIs) with smoke are obtained by using two step segmentation methods. Then, suspected smoke regions are detected by combining the two step segmentation and motion detection. Finally, morphological processing is used for smoke regions extracting. The Otsu algorithm is used as segmentation method and the ViBe algorithm is used to detect the motion of smoke. The proposed method was tested on 6 test videos with smoke. The experimental results show the effectiveness of our proposed method over visual observation.
The roles of birth inputs and outputs in predicting health, behaviour and test scores in early childhood.

PubMed

Li, Kai; Poirier, Dale J

2003-11-30

The goal of this study is to address directly the predictive value of birth inputs and outputs, particularly birth weight, for measures of early childhood development in a simultaneous equations modelling framework. Strikingly, birth outputs have virtually no structural/causal effects on early childhood developmental outcomes, and only maternal smoking and drinking during pregnancy have some effects on child height. Not surprisingly, family child-rearing environment has sizeable negative and positive effects on a behavioural problems index and a mathematics/reading test score, respectively, and a mildly surprising negative effect on child height. Despite little evidence of a structural/causal effect of birth weight on early childhood developmental outcomes, our results demonstrate that birth weight nonetheless has strong predictive effects on early childhood outcomes. Furthermore, these effects are largely invariant to whether family child-rearing environment is taken into account. Family child-rearing environment has both structural and predictive effects on early childhood outcomes, but they are largely orthogonal and in addition to the effects of birth weight. Copyright 2003 John Wiley & Sons, Ltd.
A decade of aquatic invasive species (AIS) early detection method development in the St. Louis River estuary

EPA Science Inventory

As an invasion prone location, the St. Louis River Estuary (SLRE) has been a case study for ongoing research to develop the framework for a practical Great Lakes monitoring network for early detection of aquatic invasive species (AIS). Early detection, however, necessitates findi...
Identification and prediction of drinking trajectories in early and mid-adolescence.

PubMed

Van Der Vorst, Haske; Vermulst, Ad A; Meeus, Wim H J; Deković, Maja; Engels, Rutger C M E

2009-05-01

The aim of this study was to identify subgroups of early and mid-adolescents with different drinking trajectories. In addition, we examined whether gender, parental, and peer factors predicted adolescents' membership of these drinking trajectories. We used longitudinal data of 428 families (fathers, mothers, mid-adolescents, and their younger siblings). Latent Class Growth Analyses were performed to identify drinking trajectories. Four drinking trajectories emerged for early adolescents: abstainers, light drinkers, increasers, and heavy drinkers. For mid-adolescents, we identified a fifth group (stable drinkers) in addition to the four trajectories identified for early adolescents. Our results showed that being a boy, having a best friend or father who drinks heavily, and having parents who are permissive toward adolescents' alcohol creates increased risk for both siblings to attend the more heavy drinking trajectories.
Preface to the Focus Issue: chaos detection methods and predictability.

PubMed

Gottwald, Georg A; Skokos, Charalampos

2014-06-01

This Focus Issue presents a collection of papers originating from the workshop Methods of Chaos Detection and Predictability: Theory and Applications held at the Max Planck Institute for the Physics of Complex Systems in Dresden, June 17-21, 2013. The main aim of this interdisciplinary workshop was to review comprehensively the theory and numerical implementation of the existing methods of chaos detection and predictability, as well as to report recent applications of these techniques to different scientific fields. The collection of twelve papers in this Focus Issue represents the wide range of applications, spanning mathematics, physics, astronomy, particle accelerator physics, meteorology and medical research. This Preface surveys the papers of this Issue.
Validation of Biomarkers for the Early Detection of Colorectal Adenocarcinoma (GLNE 010) — EDRN Public Portal

Cancer.gov

We propose a Phase 2 (large cross-sectional) PRoBE-compliant validation trial of stool-based and serum-based tests for the detection of colorectal neoplasia (1). The trial is powered to detect early stage colorectal adenocarcinoma or high grade dysplasia. This is the most stringent, conservative approach to the early diagnosis of colonic neoplasia and addresses the most important endpoint of identifying individuals with curable, early stage cancer and those with very high risk non-invasive neoplasia (high grade dysplasia).
The predictive factors for lymph node metastasis in early gastric cancer: A clinical study.

PubMed

Wang, Yinzhong

2015-01-01

To detect the clinicopathological factors associated with lymph node metastases in early gastric cancer. We retrospectively evaluated the distribution of metastatic nodes in 198 patients with early gastric cancer treated in our hospital between May 2008 and January 2015, the clinicopathological factors including age, gender, tumor location, tumor size, macroscopic type, depth of invasion, histological type and venous invasion were studied, and the relationship between various parameters and lymph node metastases was analyzed. In this study, one hundred and ninety-eight patients with early gastric cancer were included, and lymph node metastasis was detected in 28 patients. Univariate analysis revealed a close relationship between tumor size, depth of invasion, histological type, venous invasion, local ulceration and lymph node metastases. Multivariate analysis revealed that the five factors were independent risk factors for lymph node metastases. The clinicopathological parameters including tumor size, depth of invasion, local ulceration, histological type and venous invasion are closely correlated with lymph node metastases, should be paid high attention in early gastric cancer patients.
[Validation of three screening tests used for early detection of cervical cancer].

PubMed

Rodriguez-Reyes, Esperanza Rosalba; Cerda-Flores, Ricardo M; Quiñones-Pérez, Juan M; Cortés-Gutiérrez, Elva I

2008-01-01

to evaluate the validity (sensitivity, specificity, and accuracy) of three screening methods used in the early detection of the cervical carcinoma versus the histopathology diagnosis. a selected sample of 107 women attended in the Opportune Detection of Cervicouterine Cancer Program in the Hospital de Zona 46, Instituto Mexicano del Seguro Social in Durango, during the 2003 was included. The application of Papa-nicolaou, acetic acid test, and molecular detection of human papillomavirus, and histopatholgy diagnosis were performed in all the patients at the time of the gynecological exam. The detection and tipification of the human papillomavirus was performed by polymerase chain reaction (PCR) and analysis of polymorphisms of length of restriction fragments (RFLP). Histopathology diagnosis was considered the gold standard. The evaluation of the validity was carried out by the Bayesian method for diagnosis test. the positive cases for acetic acid test, Papanicolaou, and PCR were 47, 22, and 19. The accuracy values were 0.70, 0.80 and 0.99, respectively. since the molecular method showed a greater validity in the early detection of the cervical carcinoma we considered of vital importance its implementation in suitable programs of Opportune Detection of Cervicouterino Cancer Program in Mexico. However, in order to validate this conclusion, cross-sectional studies in different region of country must be carried out.
The family environment predicts long-term academic achievement and classroom behavior following traumatic brain injury in early childhood.

PubMed

Durber, Chelsea M; Yeates, Keith Owen; Taylor, H Gerry; Walz, Nicolay Chertkoff; Stancin, Terry; Wade, Shari L

2017-07-01

This study examined how the family environment predicts long-term academic and behavioral functioning in school following traumatic brain injury (TBI) in early childhood. Using a concurrent cohort, prospective design, 15 children with severe TBI, 39 with moderate TBI, and 70 with orthopedic injury (OI) who were injured when they were 3-7 years of age were compared on tests of academic achievement and parent and teacher ratings of school performance and behavior on average 6.83 years postinjury. Soon after injury and at the longer term follow-up, families completed measures of parental psychological distress, family functioning, and quality of the home environment. Hierarchical linear regression analyses examined group differences in academic outcomes and their associations with measures of the early and later family environment. The severe TBI group, but not the moderate TBI group, performed worse than did the OI group on all achievement tests, parent ratings of academic performance, and teacher ratings of internalizing problems. Higher quality early and late home environments predicted stronger academic skills and better classroom behavior for children with both TBI and OI. The early family environment more consistently predicted academic achievement, whereas the later family environment more consistently predicted classroom functioning. The quality of the home environment predicted academic outcomes more strongly than did parental psychological distress or family functioning. TBI in early childhood has long-term consequences for academic achievement and school performance and behavior. Higher quality early and later home environments predict better school outcomes for both children with TBI and children with OI. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Surface engineered biosensors for the early detection of cancer

NASA Astrophysics Data System (ADS)

Islam, Muhymin

Cancer commences in the building block of human body which is cells and in most of the cases remains silent at early stage. Diseases are only expressed at molecular and cellular level at primary stages. Recognition of diseases at this micro and nano level might reduce the mortality rate of cancer significantly. This research work aimed to introduce novel electronic biosensors for for identification of cancer at cellular level. The dissertation study focuses on 1) Label-Free Isolation of Metastatic Tumor Cells Using Filter Based Microfluidic device; 2) Nanotextured Polymer Substrates for Enhanced Cancer Cell Isolation and Cell Growth; 3) Nanotextured Microfluidic Channel for Electrical Profiling and Detection of Tumor Cells from Blood; and 4) Single Biochip for the Detection of Tumor Cells by Electrical Profile and Surface Immobilized Aptamer. Standard silicon processing techniques were followed to fabricate all of the biosensors. Nantoextruing and surface functionalizon were also incorporated to elevate the efficiency of the devices. The first approach aimed to detect cancer cells from blood based on their mechanophysical properties. Cancer cells are larger than blood cells but highly elastic in nature. These cells can squeeze through small microchannels much smaller than their size. The cross sectional area of the microchannels was optimized to isolate tumor cells from blood. Nanotextured polymer substrates, a platform inspired from the natural basement membrane was used to enhance the isolation and growth of tumor cells. Micro reactive ion etching was performed to have better control on features of nantoxtured surfaces and did not require any template. Next, electrical measurement of ionic current was performed across single microchannel to detect tumor cells from blood. Later, nanotexturing enhanced the efficiency of the device by selectively altering the translocation profile of cancer cells. Eventually aptamer functionalized nanotextured polymer surface was
Predictive Coding Accelerates Word Recognition and Learning in the Early Stages of Language Development

ERIC Educational Resources Information Center

Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna

2017-01-01

The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard…
Methylation Markers for Early Detection and Differentiation of Follicular Thyroid Cancer Subtypes

PubMed Central

Stephen, Josena K.; Chen, Kang Mei; Merritt, Jason; Chitale, Dhananjay; Divine, George; Worsham, Maria J.

2016-01-01

Thyroid cancer has the fastest rising incidence rates and is the fifth most common cancer in women. There are four main types of which the papillary and follicular types together account for >90%, followed by medullary cancers (3%−5%) and anaplastic carcinomas (<3%). For individuals who present with early stage disease of papillary and follicular cancers, there are no accurate markers to predict whether they will develop metastatic or recurrent disease. Our immediate goal is to molecularly differentiate follicular cancer subtypes for enhanced classification. Promoter methylation status of genes with reported associations in thyroid cancer (CASP8, CDKN2A, DAPK1, ESR1, NIS, RASSF1 and TIMP3) were examined in a cohort of follicular thyroid cancers comprising of 26 Hurthle and 27 Classic subtypes utilizing quantitative methylation-specific PCR. RASSF1 was differentially methylated in Classic tumor tissue compared to Hurthle (p<0.001). Methylation of RASSF1 pointed to racial group differences between African Americans and Caucasian Americans (p=0.05). Extra thyroidal extension was found to be associated with DAPK1 (p=0.014) and ESR1 (p=0.036) methylation. Late stage disease was associated with older age (p<0.001) and methylation of DAPK1 (p=0.034) and ESR1 (p=0.035). The methylation status of RASSF1, DAPK1 and ESR1 suggests the utility of methylation markers to molecularly differentiate thyroid cancer subtypes for enhanced classification and early detection of thyroid cancer. PMID:27158284
Multifocal visual evoked potentials for early glaucoma detection.

PubMed

Weizer, Jennifer S; Musch, David C; Niziol, Leslie M; Khan, Naheed W

2012-07-01

To compare multifocal visual evoked potentials (mfVEP) with other detection methods in early open-angle glaucoma. Ten patients with suspected glaucoma and 5 with early open-angle glaucoma underwent mfVEP, standard automated perimetry (SAP), short-wave automated perimetry, frequency-doubling technology perimetry, and nerve fiber layer optical coherence tomography. Nineteen healthy control subjects underwent mfVEP and SAP for comparison. Comparisons between groups involving continuous variables were made using independent t tests; for categorical variables, Fisher's exact test was used. Monocular mfVEP cluster defects were associated with an increased SAP pattern standard deviation (P = .0195). Visual fields that showed interocular mfVEP cluster defects were more likely to also show superior quadrant nerve fiber layer thinning by OCT (P = .0152). Multifocal visual evoked potential cluster defects are associated with a functional and an anatomic measure that both relate to glaucomatous optic neuropathy. Copyright 2012, SLACK Incorporated.
Why Ambiguity Detection Is a Predictor of Early Reading Skill

ERIC Educational Resources Information Center

Wankoff, Lorain Szabo; Cairns, Helen Smith

2009-01-01

This study was designed to determine the contributions of metalinguistic skill and psycholinguistic processing ability to children's ability to detect the ambiguity of sentences and the relationship among all three factors to early reading ability. A total of 20 first graders and 20 second graders were given tasks testing the following abilities:…
Use of digital PCR to improve early detection of CLas infection

USDA-ARS?s Scientific Manuscript database

Huanglongbing is a devastating disease of citrus caused by the bacterium Candidatus Liberibacter asiaticus. Huanglongbing has devastated the Florida citrus industry and is threatening citrus in Texas and California. Detection of Candidatus Liberibacter asiaticus infections as early as possible is ...
RED Alert – Early warning or detection of global re-emerging infectious disease (RED)

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

Deshpande, Alina

This is the PDF of a presentation for a webinar given by Los Alamos National Laboratory (LANL) on the early warning or detection of global re-emerging infectious disease (RED). First, there is an overview of LANL biosurveillance tools. Then, information is given about RED Alert. Next, a demonstration is given of a component prototype. RED Alert is an analysis tool that can provide early warning or detection of the re-emergence of an infectious disease at the global level, but through a local lens.
Effective Partnering of State Agencies to Achieve Early Hearing Detection and Intervention Benchmarks

ERIC Educational Resources Information Center

Corwin, Joanne

2011-01-01

Relative to Early Hearing Detection and Intervention (EHDI), New Mexico struggles with multiple points of referral into early intervention in the same way most states do. Referrals are not systematized through a single point of entry. The Step*Hi (statewide Parent-Infant) Program of the New Mexico School for the Deaf (NMSD) receives referrals from…
Prediction of acute renal allograft rejection in early post-transplantation period by soluble CD30.

PubMed

Dong, Wang; Shunliang, Yang; Weizhen, Wu; Qinghua, Wang; Zhangxin, Zeng; Jianming, Tan; He, Wang

2006-06-01

To evaluate the feasibility of serum sCD30 for prediction of acute graft rejection, we analyzed clinical data of 231 patients, whose serum levels of sCD30 were detected by ELISA before and after transplantation. They were divided into three groups: acute rejection group (AR, n = 49), uncomplicated course group (UC, n = 171) and delayed graft function group (DGF, n = 11). Preoperative sCD30 levels of three groups were 183 +/- 74, 177 +/- 82 and 168 +/- 53 U/ml, respectively (P = 0.82). Significant decrease of sCD30 was detected in three groups on day 5 and 10 post-transplantation respectively (52 +/- 30 and 9 +/- 5 U/ml respectively, P < 0.001). Compared with Group UC and DGF, patients of Group AR had higher sCD30 values on day 5 post-transplantation (92 +/- 27 U/ml vs. 41 +/- 20 U/ml and 48 +/- 18 U/ml, P < 0.001). However, sCD30 levels on day 10 post-transplantation were virtually similar in patients of three groups (P = 0.43). Receiver operating characteristic (ROC) curve demonstrated that sCD30 level on day 5 post-transplantation could differentiate patients who subsequently suffered acute allograft rejection from others (area under ROC curve 0.95). According to ROC curve, 65 U/ml may be the optimal operational cut-off level to predict impending graft rejection (specificity 91.8%, sensitivity 87.1%). Measurement of soluble CD30 on day 5 post-transplantation might offer a noninvasive means to recognize patients at risk of impending acute graft rejection during early post-transplantation period.

Early Prediction of Student Dropout and Performance in MOOCSs Using Higher Granularity Temporal Information

ERIC Educational Resources Information Center

Ye, Cheng; Biswas, Gautam

2014-01-01

Our project is motivated by the early dropout and low completion rate problem in MOOCs. We have extended traditional features for MOOC analysis with richer and higher granularity information to make more accurate predictions of dropout and performance. The results show that finer-grained temporal information increases the predictive power in the…
Early Detection and Mass Screening For Cancer

PubMed Central

Miller, A. B.

1972-01-01

The author reviews the evidence for the efficacy of early detection and mass screening programs in reducing morbidity and mortality from cancer. In cancer of the cervix, although screening reduces morbidity, we still do not have evidence for reduction in mortality. In cancer of the breast, one study suggests a reduction in mortality in the 50-59 year age group following screening by clinical examination and mammography. In other sites, especially lung, there is no evidence at present to support the adoption of mass screening programs. It is important that such programs should be carefully evaluated in the population, preferably in controlled studies. PMID:20468806
Early-onset Conduct Problems: Predictions from daring temperament and risk taking behavior.

PubMed

Bai, Sunhye; Lee, Steve S

2017-12-01

Given its considerable public health significance, identifying predictors of early expressions of conduct problems is a priority. We examined the predictive validity of daring, a key dimension of temperament, and the Balloon Analog Risk Task (BART), a laboratory-based measure of risk taking behavior, with respect to two-year change in parent, teacher-, and youth self-reported oppositional defiant disorder (ODD), conduct disorder (CD), and antisocial behavior. At baseline, 150 ethnically diverse 6- to 10-year old (M=7.8, SD=1.1; 69.3% male) youth with ( n =82) and without ( n =68) DSM-IV ADHD completed the BART whereas parents rated youth temperament (i.e., daring); parents and teachers also independently rated youth ODD and CD symptoms. Approximately 2 years later, multi-informant ratings of youth ODD, CD, and antisocial behavior were gathered from rating scales and interviews. Whereas risk taking on the BART was unrelated to conduct problems, individual differences in daring prospectively predicted multi-informant rated conduct problems, independent of baseline risk taking, conduct problems, and ADHD diagnostic status. Early differences in the propensity to show positive socio-emotional responses to risky or novel experiences uniquely predicted escalating conduct problems in childhood, even with control of other potent clinical correlates. We consider the role of temperament in the origins and development of significant conduct problems from childhood to adolescence, including possible explanatory mechanisms underlying these predictions.
A situational analysis of breast cancer early detection services in Trinidad and Tobago.

PubMed

Badal, Kimberly; Rampersad, Fidel; Warner, Wayne A; Toriola, Adetunji T; Mohammed, Hamish; Scheffel, Harold-Alexis; Ali, Rehanna; Moosoodeen, Murrie; Konduru, Siva; Russel, Adaila; Haraksingh, Rajini

2018-01-01

A situational analysis of breast cancer (BC) early detection services was carried out to investigate whether Trinidad and Tobago (T&T) has the framework for successful organized national screening. An online survey was designed to assess the availability, accessibility, quality control and assurance (QC&A), and monitoring and evaluation (M&E) mechanisms for public and private BC early detection. A focus group with local radiologists (n = 3) was held to identify unaddressed challenges and make recommendations for improvement. Major public hospitals offer free detection services with wait times of 1-6 months for an appointment. Private institutions offer mammograms for TTD$240 (USD$37) at minimum with same day service. Both sectors report a lack of trained staff. Using 1.2 mammograms per 10,000 women ≥40 years as sufficient, the public sector's rate of 0.19 mammograms per 10,000 women ≥40 years for screening and diagnosis is inadequate. Program M&E mechanisms, QC&A guidelines for machinery use, delays in receipt of pathology reports, and unreliable drug access are further unaddressed challenges. T&T must first strengthen its human and physical resources, implement M&E and QC&A measures, strengthen cancer care, and address other impediments to BC early detection before investing in nationally organized BC screening.
Lactate clearance cut off for early mortality prediction in adult sepsis and septic shock patients

NASA Astrophysics Data System (ADS)

Sinto, R.; Widodo, D.; Pohan, H. T.

2018-03-01

Previous lactate clearance cut off for early mortality prediction in sepsis and septic shock patient was determined by consensus from small sample size-study. We investigated the best lactate clearance cut off and its ability to predict early mortality in sepsis and septic shock patients. This cohort study was conducted in Intensive Care Unit of CiptoMangunkusumo Hospital in 2013. Patients’ lactate clearance and eight other resuscitationendpoints were recorded, and theoutcome was observed during the first 120 hours. The clearance cut off was determined using receiver operating characteristic (ROC) analysis, and its ability was investigated with Cox’s proportional hazard regression analysis using other resuscitation endpoints as confounders. Total of 268 subjects was included, of whom 70 (26.11%) subjects died within the first 120 hours. The area under ROC of lactate clearance to predict early mortality was 0.78 (95% % confidence interval [CI] 0.71-0.84) with best cut off was <7.5% (sensitivity and specificity 88.99% and 81.4% respectively). Compared with group achieving lactate clearance target, group not achieving lactate clearance target had to increase early mortality risk (adjusted hazard ratio 13.42; 95%CI 7.19-25.07). In conclusion, the best lactate clearance cut off as anearly mortality predictor in sepsis and septic shock patients is 7.5%.
Lung Cancer Workshop XI: Tobacco-Induced Disease: Advances in Policy, Early Detection and Management.

PubMed

Mulshine, James L; Avila, Rick; Yankelevitz, David; Baer, Thomas M; Estépar, Raul San Jose; Ambrose, Laurie Fenton; Aldigé, Carolyn R

2015-05-01

The Prevent Cancer Foundation Lung Cancer Workshop XI: Tobacco-Induced Disease: Advances in Policy, Early Detection and Management was held in New York, NY on May 16 and 17, 2014. The two goals of the Workshop were to define strategies to drive innovation in precompetitive quantitative research on the use of imaging to assess new therapies for management of early lung cancer and to discuss a process to implement a national program to provide high quality computed tomography imaging for lung cancer and other tobacco-induced disease. With the central importance of computed tomography imaging for both early detection and volumetric lung cancer assessment, strategic issues around the development of imaging and ensuring its quality are critical to ensure continued progress against this most lethal cancer.
2014 CODEPEH recommendations: Early detection of late onset deafness, audiological diagnosis, hearing aid fitting and early intervention.

PubMed

Núñez-Batalla, Faustino; Jáudenes-Casaubón, Carmen; Sequí-Canet, Jose Miguel; Vivanco-Allende, Ana; Zubicaray-Ugarteche, Jose

2016-01-01

The latest scientific literature considers early diagnosis of deafness as the key element to define the educational and inclusive prognosis of the deaf child, because it allows taking advantage of the critical period of development (0-4 years). Highly significant differences exist between deaf people who have been stimulated early and those who have received late or improper intervention. Early identification of late-onset disorders requires special attention and knowledge on the part of every childcare professional. Programs and additional actions beyond neonatal screening should be designed and planed to ensure that every child with a significant hearing loss is detected early. For this purpose, the CODEPEH would like to highlight the need for continuous monitoring of children's auditory health. Consequently, CODEPEH has drafted the recommendations included in the present document. Copyright © 2015 Elsevier España, S.L.U. and Sociedad Española de Otorrinolaringología y Patología Cérvico-Facial. All rights reserved.
The role of imaging in early hip OA.

PubMed

Siebelt, M; Agricola, R; Weinans, H; Kim, Y J

2014-10-01

Hip osteoarthritis (OA) is characterized by cartilage degradation, subchondral bone sclerosis and osteophyte formation. Nowadays, OA is thought to develop via different etiologies that all lead to a similar form of end stage joint degradation. One of these subtypes is related to an abnormal shaped hip joint, like acetabular dysplasia and a cam deformity. These bony abnormalities are highly predictive for development of hip OA, but they are likely to already be present from childhood. This suggests that these deformations induce OA changes in the hip, well before extensive hip degradation becomes present three to four decades later. Accurate detection and successful characterization of these early OA events might lead to better treatment options for hip OA besides nowadays available invasive joint replacement surgery. However, current diagnostic imaging techniques like radiographs or plain magnetic resonance imaging (MRI), are not sensitive enough to detect these subtle early OA changes. Nor are they able to disentangle intertwined and overlapping cascades from different OA subtypes, and neither can they predict OA progression. New and more sensitive imaging techniques might enable us to detect first OA changes on a cellular level, providing us with new opportunities for early intervention. In this respect, shape analysis using radiography, MRI, computed tomography (CT), single photon emission computed tomography (SPECT)/CT, and positron emission tomography (PET) might prove promising techniques and be more suited to detect early pathological changes in the hip joint. A broad application of these techniques might give us more understanding what can be considered physiological adaptation of the hip, or when early OA really starts. With a more clear definition of early OA, more homogenous patient populations can be selected and help with the development of new disease modifying OA interventions. Copyright © 2014 Osteoarthritis Research Society International
Contingency Table Browser - prediction of early stage protein structure.

PubMed

Kalinowska, Barbara; Krzykalski, Artur; Roterman, Irena

2015-01-01

The Early Stage (ES) intermediate represents the starting structure in protein folding simulations based on the Fuzzy Oil Drop (FOD) model. The accuracy of FOD predictions is greatly dependent on the accuracy of the chosen intermediate. A suitable intermediate can be constructed using the sequence-structure relationship information contained in the so-called contingency table - this table expresses the likelihood of encountering various structural motifs for each tetrapeptide fragment in the amino acid sequence. The limited accuracy with which such structures could previously be predicted provided the motivation for a more indepth study of the contingency table itself. The Contingency Table Browser is a tool which can visualize, search and analyze the table. Our work presents possible applications of Contingency Table Browser, among them - analysis of specific protein sequences from the point of view of their structural ambiguity.
Early prediction of intensive care unit-acquired weakness using easily available parameters: a prospective observational study.

PubMed

Wieske, Luuk; Witteveen, Esther; Verhamme, Camiel; Dettling-Ihnenfeldt, Daniela S; van der Schaaf, Marike; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

2014-01-01

An early diagnosis of Intensive Care Unit-acquired weakness (ICU-AW) using muscle strength assessment is not possible in most critically ill patients. We hypothesized that development of ICU-AW can be predicted reliably two days after ICU admission, using patient characteristics, early available clinical parameters, laboratory results and use of medication as parameters. Newly admitted ICU patients mechanically ventilated ≥2 days were included in this prospective observational cohort study. Manual muscle strength was measured according to the Medical Research Council (MRC) scale, when patients were awake and attentive. ICU-AW was defined as an average MRC score <4. A prediction model was developed by selecting predictors from an a-priori defined set of candidate predictors, based on known risk factors. Discriminative performance of the prediction model was evaluated, validated internally and compared to the APACHE IV and SOFA score. Of 212 included patients, 103 developed ICU-AW. Highest lactate levels, treatment with any aminoglycoside in the first two days after admission and age were selected as predictors. The area under the receiver operating characteristic curve of the prediction model was 0.71 after internal validation. The new prediction model improved discrimination compared to the APACHE IV and the SOFA score. The new early prediction model for ICU-AW using a set of 3 easily available parameters has fair discriminative performance. This model needs external validation.
The AFHSC-Division of GEIS Operations Predictive Surveillance Program: a multidisciplinary approach for the early detection and response to disease outbreaks

PubMed Central

2011-01-01

The Armed Forces Health Surveillance Center, Division of Global Emerging Infections Surveillance and Response System Operations (AFHSC-GEIS) initiated a coordinated, multidisciplinary program to link data sets and information derived from eco-climatic remote sensing activities, ecologic niche modeling, arthropod vector, animal disease-host/reservoir, and human disease surveillance for febrile illnesses, into a predictive surveillance program that generates advisories and alerts on emerging infectious disease outbreaks. The program’s ultimate goal is pro-active public health practice through pre-event preparedness, prevention and control, and response decision-making and prioritization. This multidisciplinary program is rooted in over 10 years experience in predictive surveillance for Rift Valley fever outbreaks in Eastern Africa. The AFHSC-GEIS Rift Valley fever project is based on the identification and use of disease-emergence critical detection points as reliable signals for increased outbreak risk. The AFHSC-GEIS predictive surveillance program has formalized the Rift Valley fever project into a structured template for extending predictive surveillance capability to other Department of Defense (DoD)-priority vector- and water-borne, and zoonotic diseases and geographic areas. These include leishmaniasis, malaria, and Crimea-Congo and other viral hemorrhagic fevers in Central Asia and Africa, dengue fever in Asia and the Americas, Japanese encephalitis (JE) and chikungunya fever in Asia, and rickettsial and other tick-borne infections in the U.S., Africa and Asia. PMID:21388561
FRONTIER FIELDS: HIGH-REDSHIFT PREDICTIONS AND EARLY RESULTS

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

Coe, Dan; Bradley, Larry; Zitrin, Adi, E-mail: DCoe@STScI.edu

2015-02-20

The Frontier Fields program is obtaining deep Hubble and Spitzer Space Telescope images of new ''blank'' fields and nearby fields gravitationally lensed by massive galaxy clusters. The Hubble images of the lensed fields are revealing nJy sources (AB mag > 31), the faintest galaxies yet observed. The full program will transform our understanding of galaxy evolution in the first 600 million years (z > 9). Previous programs have yielded a dozen or so z > 9 candidates, including perhaps fewer than expected in the Ultra Deep Field and more than expected in shallower Hubble images. In this paper, we present high-redshift (z >more » 6) number count predictions for the Frontier Fields and candidates in three of the first Hubble images. We show the full Frontier Fields program may yield up to ∼70 z > 9 candidates (∼6 per field). We base this estimate on an extrapolation of luminosity functions observed between 4 < z < 8 and gravitational lensing models submitted by the community. However, in the first two deep infrared Hubble images obtained to date, we find z ∼ 8 candidates but no strong candidates at z > 9. We defer quantitative analysis of the z > 9 deficit (including detection completeness estimates) to future work including additional data. At these redshifts, cosmic variance (field-to-field variation) is expected to be significant (greater than ±50%) and include clustering of early galaxies formed in overdensities. The full Frontier Fields program will significantly mitigate this uncertainty by observing six independent sightlines each with a lensing cluster and nearby blank field.« less
Predicting Early Spelling: The Contribution of Children's Early Literacy, Private Speech during Spelling, Behavioral Regulation, and Parental Spelling Support

ERIC Educational Resources Information Center

Aram, Dorit; Abiri, Shimrit; Elad, Lili

2014-01-01

The present study aimed to extend understanding of preschoolers' early spelling using the Vygotskian ("Mind in society: the development of higher psychological processes," Cambridge, Harvard University Press, 1978) paradigm of child development. We assessed the contribution of maternal spelling support in predicting children's word…
Hepatocellular Carcinoma Screening Associated with Early Tumor Detection and Improved Survival Among Patients with Cirrhosis in the US.

PubMed

Singal, Amit G; Mittal, Sahil; Yerokun, Olutola A; Ahn, Chul; Marrero, Jorge A; Yopp, Adam C; Parikh, Neehar D; Scaglione, Steve J

2017-09-01

Professional societies recommend hepatocellular carcinoma screening in patients with cirrhosis, but high-quality data evaluating its effectiveness to improve early tumor detection and survival in "real world" clinical practice are needed. We aim to characterize the association between hepatocellular carcinoma screening and early tumor detection, curative treatment, and overall survival among patients with cirrhosis. We performed a retrospective cohort study of patients diagnosed with hepatocellular carcinoma between June 2012 and May 2013 at 4 health systems in the US. Patients were categorized in the screening group if hepatocellular carcinoma was detected by imaging performed for screening purposes. Generalized linear models and multivariate Cox regression with frailty adjustment were used to compare early detection, curative treatment, and survival between screen-detected and non-screen-detected patients. Among 374 hepatocellular carcinoma patients, 42% (n = 157) were detected by screening. Screen-detected patients had a significantly higher proportion of early tumors (Barcelona Clinic Liver Cancer stage A 63.1% vs 36.4%, P <.001) and were more likely to undergo curative treatment (31% vs 13%, P = .02). Hepatocellular carcinoma screening was significantly associated with improved survival in multivariate analysis (hazards ratio 0.41; 95% confidence interval, 0.26-0.65) after adjusting for patient demographics, Child-Pugh class, and performance status. Median survival of screen-detected patients was 14.6 months, compared with 6.0 months for non-screen-detected patients, with the difference remaining significant after adjusting for lead-time bias (hazards ratio 0.59, 95% confidence interval, 0.37-0.93). Hepatocellular carcinoma screening is associated with increased early tumor detection and improved survival; however, a minority of hepatocellular carcinoma patients are detected by screening. Interventions to increase screening use in patients with cirrhosis may
Assessment of a lecture on cancer prevention and the early detection of cancer.

PubMed

Banner, William P; Booroojian, Stefani; Hernandez, Lori; Lopez, Brad; Pinzon-Perez, Helda

2002-01-01

Cancer prevention and the early detection can affect morbidity and mortality. Through educational programs, recommendations for beneficial lifestyle changes and cancer screening may be introduced to the public. The purpose of this study was to determine whether a videotaped lecture concerning cancer prevention and early detection is of educational value. College students in a health science class participated in the study. The students' comprehension of the subject matter was assessed immediately before and a week after they viewed the lecture. The students' scores on the second test were significantly better as measured by a paired-difference experiment. This videotaped lecture has merit as an educational program.
Glypican1 identifies cancer exosomes and facilitates early detection of cancer

PubMed Central

Melo, Sonia A.; Luecke, Linda B.; Kahlert, Christoph; Fernandez, Agustin F.; Gammon, Seth T.; Kaye, Judith; LeBleu, Valerie S.; Mittendorf, Elizabeth A.; Weitz, Juergen; Rahbari, Nuh; Reissfelder, Christoph; Pilarsky, Christian; Fraga, Mario F.; Piwnica-Worms, David; Kalluri, Raghu

2016-01-01

Summary Exosomes are lipid bilayer-enclosed extracellular vesicles (EVs) that contain proteins and nucleic acids. They are secreted by all cells and circulate in the blood. Specific detection and isolation of cancer cell-derived exosomes in circulation is currently lacking. Using mass spectrometry analyses, we identified a cell surface proteoglycan, glypican-1 (GPC1), specifically enriched on cancer cell-derived exosomes. GPC1+ circulating exosomes (crExos) were monitored and isolated using flow cytometry from the serum of cancer patients and mice with cancer. GPC1+ crExos were detected in the serum of patients with pancreas cancer with absolute specificity and sensitivity, distinguishing healthy subjects and patients with a benign pancreas disease from patients with early and late stage pancreas cancer. Levels of GPC1+ crExos correlate with tumor burden and survival in patients pre- and post-surgical tumor resection. GPC1+ crExos from patients and from mice with spontaneous pancreas tumors driven by oncogenic KRAS contained RNA with specific KRAS mutation, and it emerges as a reliable biomarker for the detection of PanIN lesions despite negative signal by MRI in mice. GPC1+ crExos may serve as a potential non-invasive diagnostic and screening tool to detect early stages of pancreas cancer to facilitate possible curative surgical therapy. PMID:26106858
Why do early mathematics skills predict later reading? The role of mathematical language.

PubMed

Purpura, David J; Logan, Jessica A R; Hassinger-Das, Brenna; Napoli, Amy R

2017-09-01

A growing body of evidence indicates that the development of mathematics and literacy skills is highly related. The importance of literacy skills-specifically language-for mathematics development has been well rationalized. However, despite several prominent studies indicating that mathematics skills are highly predictive of literacy development, the reason for this relation is not well understood. The purpose of this study was to identify how and why early mathematics is predictive of early literacy development. Participants included 125 preschool children 3-5 years old (M = 4 years 3 months). Participants were assessed on mathematics, literacy, and cognitive measures in both the fall and spring of their preschool year. Mediation analyses indicated that the relation between early mathematics and literacy skills is mediated by children's mathematical language skills. These findings suggest that, in prior research identifying mathematical performance as a significant predictor of later literacy skills, mathematical performance may have acted only as a proxy measure for more complex language skills such as those assessed on a mathematical language measure. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Early Prediction of Intensive Care Unit-Acquired Weakness: A Multicenter External Validation Study.

PubMed

Witteveen, Esther; Wieske, Luuk; Sommers, Juultje; Spijkstra, Jan-Jaap; de Waard, Monique C; Endeman, Henrik; Rijkenberg, Saskia; de Ruijter, Wouter; Sleeswijk, Mengalvio; Verhamme, Camiel; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

2018-01-01

An early diagnosis of intensive care unit-acquired weakness (ICU-AW) is often not possible due to impaired consciousness. To avoid a diagnostic delay, we previously developed a prediction model, based on single-center data from 212 patients (development cohort), to predict ICU-AW at 2 days after ICU admission. The objective of this study was to investigate the external validity of the original prediction model in a new, multicenter cohort and, if necessary, to update the model. Newly admitted ICU patients who were mechanically ventilated at 48 hours after ICU admission were included. Predictors were prospectively recorded, and the outcome ICU-AW was defined by an average Medical Research Council score <4. In the validation cohort, consisting of 349 patients, we analyzed performance of the original prediction model by assessment of calibration and discrimination. Additionally, we updated the model in this validation cohort. Finally, we evaluated a new prediction model based on all patients of the development and validation cohort. Of 349 analyzed patients in the validation cohort, 190 (54%) developed ICU-AW. Both model calibration and discrimination of the original model were poor in the validation cohort. The area under the receiver operating characteristics curve (AUC-ROC) was 0.60 (95% confidence interval [CI]: 0.54-0.66). Model updating methods improved calibration but not discrimination. The new prediction model, based on all patients of the development and validation cohort (total of 536 patients) had a fair discrimination, AUC-ROC: 0.70 (95% CI: 0.66-0.75). The previously developed prediction model for ICU-AW showed poor performance in a new independent multicenter validation cohort. Model updating methods improved calibration but not discrimination. The newly derived prediction model showed fair discrimination. This indicates that early prediction of ICU-AW is still challenging and needs further attention.
Early Detection of Chronic Obstructive Pulmonary Disease in Primary Care.

PubMed

Kobayashi, Seiichi; Hanagama, Masakazu; Yanai, Masaru

2017-12-01

Objective To evaluate the effectiveness of an early detection program for chronic obstructive pulmonary disease (COPD) in a primary care setting in Japan. Methods Participants of ≥40 years of age who regularly visited a general practitioner's clinic due to chronic disease were asked to complete a COPD screening questionnaire (COPD Population Screener; COPD-PS) and undergo simplified spirometry using a handheld spirometric device. Patients who showed possible COPD were referred to a respiratory specialist and underwent a detailed examination that included spirometry and chest radiography. Results A total of 111 patients with possible COPD were referred for close examination. Among these patients, 27 patients were newly diagnosed with COPD. The patients with COPD were older, had lower BMI values, and had a longer smoking history in comparison to non-COPD patients. COPD patients also had more comorbid conditions. A diagnosis of COPD was significantly associated with a high COPD-PS score (p<0.001) and the detection of possible airflow limitation evaluated by the handheld spirometric device (p<0.01). An ROC curve analysis demonstrated that 5 points was the best COPD-PS cut-off value for the diagnosis of COPD. The combination of both tools showed 40.7% of sensitivity and 96.4% of specificity. Conclusion The use of the COPD-PS plus a handheld spirometric device could facilitate the early detection of undiagnosed COPD in primary care.
A Review of Non-Invasive Techniques to Detect and Predict Localised Muscle Fatigue

PubMed Central

Al-Mulla, Mohamed R.; Sepulveda, Francisco; Colley, Martin

2011-01-01

Muscle fatigue is an established area of research and various types of muscle fatigue have been investigated in order to fully understand the condition. This paper gives an overview of the various non-invasive techniques available for use in automated fatigue detection, such as mechanomyography, electromyography, near-infrared spectroscopy and ultrasound for both isometric and non-isometric contractions. Various signal analysis methods are compared by illustrating their applicability in real-time settings. This paper will be of interest to researchers who wish to select the most appropriate methodology for research on muscle fatigue detection or prediction, or for the development of devices that can be used in, e.g., sports scenarios to improve performance or prevent injury. To date, research on localised muscle fatigue focuses mainly on the clinical side. There is very little research carried out on the implementation of detecting/predicting fatigue using an autonomous system, although recent research on automating the process of localised muscle fatigue detection/prediction shows promising results. PMID:22163810

Donor information based prediction of early allograft dysfunction and outcome in liver transplantation.

PubMed

Hoyer, Dieter P; Paul, Andreas; Gallinat, Anja; Molmenti, Ernesto P; Reinhardt, Renate; Minor, Thomas; Saner, Fuat H; Canbay, Ali; Treckmann, Jürgen W; Sotiropoulos, Georgios C; Mathé, Zoltan

2015-01-01

Poor initial graft function was recently newly defined as early allograft dysfunction (EAD) [Olthoff KM, Kulik L, Samstein B, et al. Validation of a current definition of early allograft dysfunction in liver transplant recipients and analysis of risk factors. Liver Transpl 2010; 16: 943]. Aim of this analysis was to evaluate predictive donor information for development of EAD. Six hundred and seventy-eight consecutive adult patients (mean age 51.6 years; 60.3% men) who received a primary liver transplantation (LT) (09/2003-12/2011) were included. Standard donor data were correlated with EAD and outcome by univariable/multivariable logistic regression and Cox proportional hazards to identify prognostic donor factors after adjustment for recipient confounders. Estimates of relevant factors were utilized for construction of a new continuous risk index to develop EAD. 38.7% patients developed EAD. 30-day survival of grafts with and without EAD was 59.8% and 89.7% (P < 0.0001). 30-day survival of patients with and without EAD was 68.5% and 93.1% (P < 0.0001) respectively. Donor body mass index (P = 0.0112), gGT (P = 0.0471), macrosteatosis (P = 0.0006) and cold ischaemia time (CIT) (P = 0.0031) were predictors of EAD. Internal cross validation showed a high predictive value (c-index = 0.622). Early allograft dysfunction correlates with early results of LT and can be predicted by donor data only. The newly introduced risk index potentially optimizes individual decisions to accept/decline high risk organs. Outcome of these organs might be improved by shortening CIT. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
An intelligent detecting system for permeability prediction of MBR.

PubMed

Han, Honggui; Zhang, Shuo; Qiao, Junfei; Wang, Xiaoshuang

2018-01-01

The membrane bioreactor (MBR) has been widely used to purify wastewater in wastewater treatment plants. However, a critical difficulty of the MBR is membrane fouling. To reduce membrane fouling, in this work, an intelligent detecting system is developed to evaluate the performance of MBR by predicting the membrane permeability. This intelligent detecting system consists of two main parts. First, a soft computing method, based on the partial least squares method and the recurrent fuzzy neural network, is designed to find the nonlinear relations between the membrane permeability and the other variables. Second, a complete new platform connecting the sensors and the software is built, in order to enable the intelligent detecting system to handle complex algorithms. Finally, the simulation and experimental results demonstrate the reliability and effectiveness of the proposed intelligent detecting system, underlying the potential of this system for the online membrane permeability for detecting membrane fouling of MBR.
Progress towards early detection services for infants with hearing loss in developing countries

PubMed Central

Olusanya, Bolajoko O; Swanepoel, De Wet; Chapchap, Mônica J; Castillo, Salvador; Habib, Hamed; Mukari, Siti Z; Martinez, Norberto V; Lin, Hung-Ching; McPherson, Bradley

2007-01-01

Background Early detection of infants with permanent hearing loss through infant hearing screening is recognised and routinely offered as a vital component of early childhood care in developed countries. This article investigates the initiatives and progress towards early detection of infants with hearing loss in developing countries against the backdrop of the dearth of epidemiological data from this region. Methods A cross-sectional, descriptive study based on responses to a structured questionnaire eliciting information on the nature and scope of early hearing detection services; strategies for financing services; parental and professional attitudes towards screening; and the performance of screening programmes. Responses were complemented with relevant data from the internet and PubMed/Medline. Results Pilot projects using objective screening tests are on-going in a growing number of countries. Screening services are provided at public/private hospitals and/or community health centres and at no charge only in a few countries. Attitudes amongst parents and health care workers are typically positive towards such programmes. Screening efficiency, as measured by referral rate at discharge, was generally found to be lower than desired but several programmes achieved other international benchmarks. Coverage is generally above 90% but poor follow-up rates remain a challenge in some countries. The mean age of diagnosis is usually less than six months, even for community-based programmes. Conclusion Lack of adequate resources by many governments may limit rapid nationwide introduction of services for early hearing detection and intervention, but may not deter such services altogether. Parents may be required to pay for services in some settings in line with the existing practice where healthcare services are predominantly financed by out-of-pocket spending rather than public funding. However, governments and their international development partners need to complement
Early and simple detection of diastolic dysfunction during weaning from mechanical ventilation

PubMed Central

2012-01-01

Weaning from mechanical ventilation imposes additional work on the cardiovascular system and can provoke or unmask left ventricular diastolic dysfunction with consecutive pulmonary edema or systolic dysfunction with inadequate increase of cardiac output and unsuccessful weaning. Echocardiography, which is increasingly used for hemodynamic assessment of critically ill patients, allows differentiation between systolic and diastolic failure. For various reasons, transthoracic echocardiographic assessment was limited to patients with good echo visibility and to those with sinus rhythm without excessive tachycardia. In these patients, often selected after unsuccessful weaning, echocardiographic findings were predictive for weaning failure of cardiac origin. In some studies, patients with various degrees of systolic dysfunction were included, making evaluation of the diastolic dysfunction to the weaning failure even more difficult. The recent study by Moschietto and coworkers included unselected patients and used very simple diastolic variables for assessment of diastolic function. They also included patients with atrial fibrillation and repeated echocardiographic examination only 10 minutes after starting a spontaneous breathing trial. The main finding was that weaning failure was not associated with systolic dysfunction but with diastolic dysfunction. By measuring simple and robust parameters for detection of diastolic dysfunction, the study was able to predict weaning failure in patients with sinus rhythm and atrial fibrillation as early as 10 minutes after beginning a spontaneous breathing trial. Further studies are necessary to determine whether appropriate treatment tailored according to the echocardiographic findings will result in successful weaning. PMID:22770365
Early and simple detection of diastolic dysfunction during weaning from mechanical ventilation.

PubMed

Voga, Gorazd

2012-07-06

Weaning from mechanical ventilation imposes additional work on the cardiovascular system and can provoke or unmask left ventricular diastolic dysfunction with consecutive pulmonary edema or systolic dysfunction with inadequate increase of cardiac output and unsuccessful weaning. Echocardiography, which is increasingly used for hemodynamic assessment of critically ill patients, allows differentiation between systolic and diastolic failure. For various reasons, transthoracic echocardiographic assessment was limited to patients with good echo visibility and to those with sinus rhythm without excessive tachycardia. In these patients, often selected after unsuccessful weaning, echocardiographic findings were predictive for weaning failure of cardiac origin. In some studies, patients with various degrees of systolic dysfunction were included, making evaluation of the diastolic dysfunction to the weaning failure even more difficult. The recent study by Moschietto and coworkers included unselected patients and used very simple diastolic variables for assessment of diastolic function. They also included patients with atrial fibrillation and repeated echocardiographic examination only 10 minutes after starting a spontaneous breathing trial. The main finding was that weaning failure was not associated with systolic dysfunction but with diastolic dysfunction. By measuring simple and robust parameters for detection of diastolic dysfunction, the study was able to predict weaning failure in patients with sinus rhythm and atrial fibrillation as early as 10 minutes after beginning a spontaneous breathing trial. Further studies are necessary to determine whether appropriate treatment tailored according to the echocardiographic findings will result in successful weaning.
Early Detection Rapid Response Program Targets New Noxious Weed Species in Washington State

ERIC Educational Resources Information Center

Andreas, Jennifer E.; Halpern, Alison D.; DesCamp, Wendy C.; Miller, Timothy W.

2015-01-01

Early detection, rapid response is a critical component of invasive plant management. It can be challenging, however, to detect new invaders before they become established if landowners cannot identify species of concern. In order to increase awareness, eye-catching postcards were developed in Washington State as part of a noxious weed educational…
Phonological Representations and Early Literacy in Chinese

ERIC Educational Resources Information Center

Kidd, Joanna C.; Shum, Kathy Kar-Man; Ho, Connie Suk-Han; Au, Terry Kit-fong

2015-01-01

Phonological processing skills predict early reading development, but what underlies developing phonological processing skills? Phonological representations of 140 native Cantonese-speaking Chinese children (age 4-10) were assessed with speech gating, mispronunciation detection, and nonword repetition tasks; their nonverbal IQ, reading, and…
Predictive Validity of Early Literacy Measures for Korean English Language Learners in the United States

ERIC Educational Resources Information Center

Han, Jeanie Nam; Vanderwood, Michael L.; Lee, Catherine Y.

2015-01-01

This study examined the predictive validity of early literacy measures with first-grade Korean English language learners (ELLs) in the United States at varying levels of English proficiency. Participants were screened using Dynamic Indicators of Basic Early Literacy Skills (DIBELS) Phoneme Segmentation Fluency (PSF), DIBELS Nonsense Word Fluency…
Cognitive flexibility predicts early reading skills

PubMed Central

Colé, Pascale; Duncan, Lynne G.; Blaye, Agnès

2014-01-01

An important aspect of learning to read is efficiency in accessing different kinds of linguistic information (orthographic, phonological, and semantic) about written words. The present study investigates whether, in addition to the integrity of such linguistic skills, early progress in reading may require a degree of cognitive flexibility in order to manage the coordination of this information effectively. Our study will look for evidence of a link between flexibility and both word reading and passage reading comprehension, and examine whether any such link involves domain-general or reading-specific flexibility. As the only previous support for a predictive relationship between flexibility and early reading comes from studies of reading comprehension in the opaque English orthography, another possibility is that this relationship may be largely orthography-dependent, only coming into play when mappings between representations are complex and polyvalent. To investigate these questions, 60 second-graders learning to read the more transparent French orthography were presented with two multiple classification tasks involving reading-specific cognitive flexibility (based on words) and non-specific flexibility (based on pictures). Reading skills were assessed by word reading, pseudo-word decoding, and passage reading comprehension measures. Flexibility was found to contribute significant unique variance to passage reading comprehension even in the less opaque French orthography. More interestingly, the data also show that flexibility is critical in accounting for one of the core components of reading comprehension, namely, the reading of words in isolation. Finally, the results constrain the debate over whether flexibility has to be reading-specific to be critically involved in reading. PMID:24966842
Influenza detection and prediction algorithms: comparative accuracy trial in Östergötland county, Sweden, 2008-2012.

PubMed

Spreco, A; Eriksson, O; Dahlström, Ö; Timpka, T

2017-07-01

Methods for the detection of influenza epidemics and prediction of their progress have seldom been comparatively evaluated using prospective designs. This study aimed to perform a prospective comparative trial of algorithms for the detection and prediction of increased local influenza activity. Data on clinical influenza diagnoses recorded by physicians and syndromic data from a telenursing service were used. Five detection and three prediction algorithms previously evaluated in public health settings were calibrated and then evaluated over 3 years. When applied on diagnostic data, only detection using the Serfling regression method and prediction using the non-adaptive log-linear regression method showed acceptable performances during winter influenza seasons. For the syndromic data, none of the detection algorithms displayed a satisfactory performance, while non-adaptive log-linear regression was the best performing prediction method. We conclude that evidence was found for that available algorithms for influenza detection and prediction display satisfactory performance when applied on local diagnostic data during winter influenza seasons. When applied on local syndromic data, the evaluated algorithms did not display consistent performance. Further evaluations and research on combination of methods of these types in public health information infrastructures for 'nowcasting' (integrated detection and prediction) of influenza activity are warranted.
DESI-Detection of early-season invasives (software-installation manual and user's guide version 1.0)

USGS Publications Warehouse

Kokaly, Raymond F.

2011-01-01

This report describes a software system for detecting early-season invasive plant species, such as cheatgrass. The report includes instructions for installing the software and serves as a user's guide in processing Landsat satellite remote sensing data to map the distributions of cheatgrass and other early-season invasive plants. The software was developed for application to the semi-arid regions of southern Utah; however, the detection parameters can be altered by the user for application to other areas.
Sensor data monitoring and decision level fusion scheme for early fire detection

NASA Astrophysics Data System (ADS)

Rizogiannis, Constantinos; Thanos, Konstantinos Georgios; Astyakopoulos, Alkiviadis; Kyriazanos, Dimitris M.; Thomopoulos, Stelios C. A.

2017-05-01

The aim of this paper is to present the sensor monitoring and decision level fusion scheme for early fire detection which has been developed in the context of the AF3 Advanced Forest Fire Fighting European FP7 research project, adopted specifically in the OCULUS-Fire control and command system and tested during a firefighting field test in Greece with prescribed real fire, generating early-warning detection alerts and notifications. For this purpose and in order to improve the reliability of the fire detection system, a two-level fusion scheme is developed exploiting a variety of observation solutions from air e.g. UAV infrared cameras, ground e.g. meteorological and atmospheric sensors and ancillary sources e.g. public information channels, citizens smartphone applications and social media. In the first level, a change point detection technique is applied to detect changes in the mean value of each measured parameter by the ground sensors such as temperature, humidity and CO2 and then the Rate-of-Rise of each changed parameter is calculated. In the second level the fire event Basic Probability Assignment (BPA) function is determined for each ground sensor using Fuzzy-logic theory and then the corresponding mass values are combined in a decision level fusion process using Evidential Reasoning theory to estimate the final fire event probability.
Early Detection of Breast Cancer Using Autoantibody Markers — EDRN Public Portal

Cancer.gov

To identify large numbers of antigens that can be used to recognize the presence of cancer by detecting antibodies to tumor proteins in the serum of the test subjects. Our technology will provide an early detection test for breast cancer in asymptomatic women. We will use bioinformatics techniques to analyze these protein microarray-immunoassays to discriminate between cancer patients and healthy subjects so as to detect disease prior to standard diagnoses as well as discriminate patients with benign conditions or other cancers that might be a false positive in less specific assays.
Frequency Effects or Context Effects in Second Language Word Learning: What Predicts Early Lexical Production?

ERIC Educational Resources Information Center

Crossley, Scott A.; Subtirelu, Nicholas; Salsbury, Tom

2013-01-01

This study examines frequency, contextual diversity, and contextual distinctiveness effects in predicting produced versus not-produced frequent nouns and verbs by early second language (L2) learners of English. The study analyzes whether word frequency is the strongest predictor of early L2 word production independent of contextual diversity and…
77 FR 60703 - Breast and Cervical Cancer Early Detection and Control Advisory Committee: Notice of Charter Renewal

Federal Register 2010, 2011, 2012, 2013, 2014

2012-10-04

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Breast and Cervical Cancer Early Detection and Control Advisory Committee: Notice of Charter Renewal This gives notice under the Federal Advisory Committee Act (Pub. L. 92-463) of October 6, 1972, that the Breast and Cervical Cancer Early Detection and Control...
Predicting Early Maladaptive Schemas Using Baumrind’s Parenting Styles

PubMed Central

Esmali Kooraneh, Ahmad; Amirsardari, Leili

2015-01-01

Background: Families play an essential role in maintaining children’s mental, social, and physical health. The family provides the first and the most important social context for human development. Objectives: The present study aimed to predict early maladaptive schemas using Baumrind’s parenting styles (root development). Patients and Methods: A total of 357 undergraduate students of Islamic Azad University, Urmia Branch, Iran, were selected through random cluster sampling during 2013 and 2014. The students were assessed using the Schema Questionnaire-Short Form (SQ-SF) and the Baumrind’s parenting styles inventories. Results: The result of regression analysis showed that Baumrind’s parenting styles are significant predictors of early maladaptive schemas (P < 0.001). Conclusions: The authoritative parenting style has some features such as showing high levels of warmth or encouraging kids to express their own possibly divergent opinions. The authoritarian parenting style, however, possesses traits such as heartlessness, impassiveness, strictness, and lack of attention to the children’s developmental needs, which is not acceptable. PMID:26288648
Early Detection Monitoring Approaches for Exotic Aquatic Species in Great Lakes Harbors and Embayments

EPA Science Inventory

Aquatic invasive species pose a significant ecological and economic threat in the Great Lakes basin. Early detection of invaders is desirable so as to allow for a timely management response, raising the question of how to accomplish this detection in a consistent, cost-effective...
Vasoactive agents for the prediction of early- and late-onset preeclampsia in a high-risk cohort

PubMed Central

2013-01-01

Background To evaluate the soluble fms-like tyrosine kinase-1 (sFlt-1), placental growth factor (PlGF), and sFlt-1/PlGF ratio for the prediction of early- and late-onset preeclampsia in a high-risk cohort. Methods We studied serial serum samples collected prospectively at 12 + 0 - 14 + 0, 18 + 0 - 20 + 0, and 26 + 0 - 28 + 0 weeks + days of gestation in 6 women who developed early-onset preeclampsia (before 34 weeks of gestation) and in 21 women who developed late-onset preeclampsia (after 34 weeks of gestation) with automated ElecSys 2010 immunoanalyzer (Roche Diagnostics, Germany). Twenty-six high-risk women and 53 women without risk factors with normal pregnancies served as controls. Results Serum PlGF concentrations were lower at 18 + 0 to 20 + 0, and 26 + 0 to 28 + 0 weeks of gestation in women who developed early-onset preeclampsia compared to women who developed late-onset preeclampsia and to controls (p < 0.05 for all comparisons). At 18 + 0 to 20 + 0 weeks of gestation area under the receiver-operating characteristic curve (AUC) for serum PlGF was 99.8% (p = 0.0007, 95% CI 99.0-100.0). At 26 + 0 to 28 + 0 weeks of gestation serum sFlt-1/PlGF ratio explicitly detects those women who developed early-onset preeclampsia (AUC 100.0%, p = 0.0007, 95% CI 100–100). Amongst women with late-onset preeclampsia, those who developed severe form of the disease (N = 8) had significantly higher serum sFlt-1 concentrations at all three timepoints (p = 0.004, p = 0.006, and p = 0.003, respectively) compared to women with non-severe form (N = 13). Conclusions Low serum PlGF concentration predicts early-onset preeclampsia from the second trimester and elevated serum sFlt-1/PlGF ratio from 26 to 28 weeks of gestation. Elevated serum sFlt-1 concentration in the first trimester in women who later develop late-onset, severe preeclampsia may suggest different etiology compared to the late
Predictive coding accelerates word recognition and learning in the early stages of language development.

PubMed

Ylinen, Sari; Bosseler, Alexis; Junttila, Katja; Huotilainen, Minna

2017-11-01

The ability to predict future events in the environment and learn from them is a fundamental component of adaptive behavior across species. Here we propose that inferring predictions facilitates speech processing and word learning in the early stages of language development. Twelve- and 24-month olds' electrophysiological brain responses to heard syllables are faster and more robust when the preceding word context predicts the ending of a familiar word. For unfamiliar, novel word forms, however, word-expectancy violation generates a prediction error response, the strength of which significantly correlates with children's vocabulary scores at 12 months. These results suggest that predictive coding may accelerate word recognition and support early learning of novel words, including not only the learning of heard word forms but also their mapping to meanings. Prediction error may mediate learning via attention, since infants' attention allocation to the entire learning situation in natural environments could account for the link between prediction error and the understanding of word meanings. On the whole, the present results on predictive coding support the view that principles of brain function reported across domains in humans and non-human animals apply to language and its development in the infant brain. A video abstract of this article can be viewed at: http://hy.fi/unitube/video/e1cbb495-41d8-462e-8660-0864a1abd02c. [Correction added on 27 January 2017, after first online publication: The video abstract link was added.]. © 2016 John Wiley & Sons Ltd.
How learning analytics can early predict under-achieving students in a blended medical education course.

PubMed

Saqr, Mohammed; Fors, Uno; Tedre, Matti

2017-07-01

Learning analytics (LA) is an emerging discipline that aims at analyzing students' online data in order to improve the learning process and optimize learning environments. It has yet un-explored potential in the field of medical education, which can be particularly helpful in the early prediction and identification of under-achieving students. The aim of this study was to identify quantitative markers collected from students' online activities that may correlate with students' final performance and to investigate the possibility of predicting the potential risk of a student failing or dropping out of a course. This study included 133 students enrolled in a blended medical course where they were free to use the learning management system at their will. We extracted their online activity data using database queries and Moodle plugins. Data included logins, views, forums, time, formative assessment, and communications at different points of time. Five engagement indicators were also calculated which would reflect self-regulation and engagement. Students who scored below 5% over the passing mark were considered to be potentially at risk of under-achieving. At the end of the course, we were able to predict the final grade with 63.5% accuracy, and identify 53.9% of at-risk students. Using a binary logistic model improved prediction to 80.8%. Using data recorded until the mid-course, prediction accuracy was 42.3%. The most important predictors were factors reflecting engagement of the students and the consistency of using the online resources. The analysis of students' online activities in a blended medical education course by means of LA techniques can help early predict underachieving students, and can be used as an early warning sign for timely intervention.

Early Attempts to Detect the Neutrino at the Cavendish Laboratory

NASA Astrophysics Data System (ADS)

Navarro, Jaume

2006-03-01

In the 1920s and early 1930s the Cavendish Laboratory in Cambridge was preeminent in experimental research on radioactivity and nuclear physics, with theoretical physics playing a subsidiary role in guiding, but not determining the course of experimental research. Soon after Wolfgang Pauli (1900 1958) proposed his neutrino hypothesis in 1930 to preserve conservation of energy and momentum in beta decay, experiments the first of their kind were carried out in the Cavendish Laboratory to detect Pauli’s elusive particle, but they were abandoned in 1936. I trace these early attempts and suggest reasons for their abandonment, which may contribute to an understanding of the complex way in which theoretical entities are accepted by physicists.
Gait Rather Than Cognition Predicts Decline in Specific Cognitive Domains in Early Parkinson's Disease.

PubMed

Morris, Rosie; Lord, Sue; Lawson, Rachael A; Coleman, Shirley; Galna, Brook; Duncan, Gordon W; Khoo, Tien K; Yarnall, Alison J; Burn, David J; Rochester, Lynn

2017-11-09

Dementia is significant in Parkinson's disease (PD) with personal and socioeconomic impact. Early identification of risk is of upmost importance to optimize management. Gait precedes and predicts cognitive decline and dementia in older adults. We aimed to evaluate gait characteristics as predictors of cognitive decline in newly diagnosed PD. One hundred and nineteen participants recruited at diagnosis were assessed at baseline, 18 and 36 months. Baseline gait was characterized by variables that mapped to five domains: pace, rhythm, variability, asymmetry, and postural control. Cognitive assessment included attention, fluctuating attention, executive function, visual memory, and visuospatial function. Mixed-effects models tested independent gait predictors of cognitive decline. Gait characteristics of pace, variability, and postural control predicted decline in fluctuating attention and visual memory, whereas baseline neuropsychological assessment performance did not predict decline. This provides novel evidence for gait as a clinical biomarker for PD cognitive decline in early disease. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America.
Detection and mapping of delays in early cortical folding derived from in utero MRI

NASA Astrophysics Data System (ADS)

Habas, Piotr A.; Rajagopalan, Vidya; Scott, Julia A.; Kim, Kio; Roosta, Ahmad; Rousseau, Francois; Barkovich, A. James; Glenn, Orit A.; Studholme, Colin

2011-03-01

Understanding human brain development in utero and detecting cortical abnormalities related to specific clinical conditions is an important area of research. In this paper, we describe and evaluate methodology for detection and mapping of delays in early cortical folding from population-based studies of fetal brain anatomies imaged in utero. We use a general linear modeling framework to describe spatiotemporal changes in curvature of the developing brain and explore the ability to detect and localize delays in cortical folding in the presence of uncertainty in estimation of the fetal age. We apply permutation testing to examine which regions of the brain surface provide the most statistical power to detect a given folding delay at a given developmental stage. The presented methodology is evaluated using MR scans of fetuses with normal brain development and gestational ages ranging from 20.57 to 27.86 weeks. This period is critical in early cortical folding and the formation of the primary and secondary sulci. Finally, we demonstrate a clinical application of the framework for detection and localization of folding delays in fetuses with isolated mild ventriculomegaly.
Magnetic Resonance Imaging to Detect Early Molecular and Cellular Changes in Alzheimer's Disease.

PubMed

Knight, Michael J; McCann, Bryony; Kauppinen, Risto A; Coulthard, Elizabeth J

2016-01-01

Recent pharmaceutical trials have demonstrated that slowing or reversing pathology in Alzheimer's disease is likely to be possible only in the earliest stages of disease, perhaps even before significant symptoms develop. Pathology in Alzheimer's disease accumulates for well over a decade before symptoms are detected giving a large potential window of opportunity for intervention. It is therefore important that imaging techniques detect subtle changes in brain tissue before significant macroscopic brain atrophy. Current diagnostic techniques often do not permit early diagnosis or are too expensive for routine clinical use. Magnetic Resonance Imaging (MRI) is the most versatile, affordable, and powerful imaging modality currently available, being able to deliver detailed analyses of anatomy, tissue volumes, and tissue state. In this mini-review, we consider how MRI might detect patients at risk of future dementia in the early stages of pathological change when symptoms are mild. We consider the contributions made by the various modalities of MRI (structural, diffusion, perfusion, relaxometry) in identifying not just atrophy (a late-stage AD symptom) but more subtle changes reflective of early dementia pathology. The sensitivity of MRI not just to gross anatomy but to the underlying "health" at the cellular (and even molecular) scales, makes it very well suited to this task.
Identification and validation of FGFR2 peptide for detection of early Barrett's neoplasia

PubMed Central

Zhou, Juan; He, Lei; Pang, Zhijun; Appelman, Henry D.; Kuick, Rork; Beer, David G.; Li, Meng; Wang, Thomas D.

2017-01-01

The incidence of esophageal adenocarcinoma (EAC) is rising rapidly, and early detection within the precursor state of Barrett's esophagus (BE) is challenged by flat premalignant lesions that are difficult detect with conventional endoscopic surveillance. Overexpression of cell surface fibroblast growth factor receptor 2 (FGFR2) is an early event in progression of BE to EAC, and is a promising imaging target. We used phage display to identify the peptide SRRPASFRTARE that binds specifically to the extracellular domain of FGFR2. We labeled this peptide with a near-infrared fluorophore Cy5.5, and validated the specific binding to FGFR2 overexpressed in cells in vitro. We found high affinity kd = 68 nM and rapid binding k = 0.16 min−1 (6.2 min). In human esophageal specimens, we found significantly greater peptide binding to high-grade dysplasia (HGD) versus either BE or normal squamous epithelium, and good correlation with anti-FGFR2 antibody. We also observed significantly greater peptide binding to excised specimens of esophageal squamous cell carcinoma and gastric cancer compared to normal mucosa. These results demonstrate potential for this FGFR2 peptide to be used as a clinical imaging agent to guide tissue biopsy and improve methods for early detection of EAC and potentially other epithelial-derived cancers. PMID:29152066
Non-supervised method for early forest fire detection and rapid mapping

NASA Astrophysics Data System (ADS)

Artés, Tomás; Boca, Roberto; Liberta, Giorgio; San-Miguel, Jesús

2017-09-01

Natural hazards are a challenge for the society. Scientific community efforts have been severely increased assessing tasks about prevention and damage mitigation. The most important points to minimize natural hazard damages are monitoring and prevention. This work focuses particularly on forest fires. This phenomenon depends on small-scale factors and fire behavior is strongly related to the local weather. Forest fire spread forecast is a complex task because of the scale of the phenomena, the input data uncertainty and time constraints in forest fire monitoring. Forest fire simulators have been improved, including some calibration techniques avoiding data uncertainty and taking into account complex factors as the atmosphere. Such techniques increase dramatically the computational cost in a context where the available time to provide a forecast is a hard constraint. Furthermore, an early mapping of the fire becomes crucial to assess it. In this work, a non-supervised method for forest fire early detection and mapping is proposed. As main sources, the method uses daily thermal anomalies from MODIS and VIIRS combined with land cover map to identify and monitor forest fires with very few resources. This method relies on a clustering technique (DBSCAN algorithm) and on filtering thermal anomalies to detect the forest fires. In addition, a concave hull (alpha shape algorithm) is applied to obtain rapid mapping of the fire area (very coarse accuracy mapping). Therefore, the method leads to a potential use for high-resolution forest fire rapid mapping based on satellite imagery using the extent of each early fire detection. It shows the way to an automatic rapid mapping of the fire at high resolution processing as few data as possible.
Novel Multistatic Adaptive Microwave Imaging Methods for Early Breast Cancer Detection

NASA Astrophysics Data System (ADS)

Xie, Yao; Guo, Bin; Li, Jian; Stoica, Petre

2006-12-01

Multistatic adaptive microwave imaging (MAMI) methods are presented and compared for early breast cancer detection. Due to the significant contrast between the dielectric properties of normal and malignant breast tissues, developing microwave imaging techniques for early breast cancer detection has attracted much interest lately. MAMI is one of the microwave imaging modalities and employs multiple antennas that take turns to transmit ultra-wideband (UWB) pulses while all antennas are used to receive the reflected signals. MAMI can be considered as a special case of the multi-input multi-output (MIMO) radar with the multiple transmitted waveforms being either UWB pulses or zeros. Since the UWB pulses transmitted by different antennas are displaced in time, the multiple transmitted waveforms are orthogonal to each other. The challenge to microwave imaging is to improve resolution and suppress strong interferences caused by the breast skin, nipple, and so forth. The MAMI methods we investigate herein utilize the data-adaptive robust Capon beamformer (RCB) to achieve high resolution and interference suppression. We will demonstrate the effectiveness of our proposed methods for breast cancer detection via numerical examples with data simulated using the finite-difference time-domain method based on a 3D realistic breast model.
[Chickenpox case estimation in acyclovir pharmacy survey and early bioterrorism detection].

PubMed

Sugawara, Tamie; Ohkusa, Yasushi; Kawanohara, Hirokazu; Taniguchi, Kiyosu; Okabe, Nobuhiko

2011-11-01

Early potential health hazards and bioterrorism threats require early detection. Smallpox cases caused by terrorist could, for example, be treated by prescribing acyclovir to those having fever and vesicle exanthema diagnosed as chicken pox. We have constructed real-time pharmacy surveillance scenarios using information technology (IT) to monitor acyclovir prescription. We collected the number of acyclovir prescriptions from 5138 pharmacies using the Application Server Provider System (ASP) to estimate the number of cases. We then compared the number of those given acyclovir under 15 years old from pharmacy surveillance and sentinel surveillance for chickenpox under the Infection Disease Control Law. The estimated number of under 15 years old prescribed acyclovir in pharmacy surveillance resembled sentinel surveillance results and showed a similar seasonal chickenpox pattern. The correlation coefficient was 0.8575. The estimated numbers of adults, older than 15 but under 65 years old, and elderly, older than 65, prescribed acyclovir showed no clear seasonal pattern. Pharmacy surveillance for acyclovir identified the baseline and can be used to detect unusual chickenpox outbreak. Bioterrorism attack could potentially be detected using smallpox virus when acyclovir prescription for adults suddenly increases without outbreaks in children or the elderly. This acyclovir prescription monitoring such as an application is, to our knowledge, the first of its kind anywhre.
Sensitivity and accuracy of high-throughput metabarcoding methods for early detection of invasive fish species

EPA Science Inventory

For early detection biomonitoring of aquatic invasive species, sensitivity to rare individuals and accurate, high-resolution taxonomic classification are critical to minimize detection errors. Given the great expense and effort associated with morphological identification of many...
Barriers to early detection of cervical-uterine cancer in Mexico.

PubMed

Lazcano-Ponce, E C; Castro, R; Allen, B; Nájera, P; Alonso de Ruíz, P A; Hernández-Avila, M

1999-04-01

In Mexico, a woman dies of cervical-uterine cancer every 2 hours, indicating a low impact by the national program for early detection of this cancer, principally because of problems related to quality and coverage. Through a qualitative study, we identified the principal barriers to use of the detection program from the point of view of actual and potential program users. Four focus groups were organized in standard conditions in Mexico City (urban, developed) and in the southern state of Oaxaca (rural, economically disadvantaged area). Participants were either women with at least one previous Papanicolaou (Pap) test or women who had never had the test. Barriers to Pap test use included (1) lack of knowledge about cervical-uterine cancer etiology, (2) not knowing that the Pap test exists, (3) the conception that cancer is an inevitably fatal disease, (4) problems in doctor/medical institution-patient relationships, (5) giving priority to unmet needs related to extreme poverty, (6) opposition by the male sexual partner, (7) rejection of the pelvic examination, (8) long waits for sample collection and receiving results, and (9) perceived high costs for care. To increase coverage of the early detection program for cervical-uterine cancer in Mexico, the needs, perceptions, and beliefs of women and their partners must be taken into account when developing policy and planning, given the role these factors play in the decision-making process that leads to their participation or nonparticipation in this program.
Early detection of acute kidney injury after pediatric cardiac surgery

PubMed Central

Jefferies, John Lynn; Devarajan, Prasad

2016-01-01

Acute kidney injury (AKI) is increasingly recognized as a common problem in children undergoing cardiac surgery, with well documented increases in morbidity and mortality in both the short and the long term. Traditional approaches to the identification of AKI such as changes in serum creatinine have revealed a large incidence in this population with significant negative impact on clinical outcomes. However, the traditional diagnostic approaches to AKI diagnosis have inherent limitations that may lead to under-diagnosis of this pathologic process. There is a dearth of randomized controlled trials for the prevention and treatment of AKI associated with cardiac surgery, at least in part due to the paucity of early predictive biomarkers. Novel non-invasive biomarkers have ushered in a new era that allows for earlier detection of AKI. With these new diagnostic tools, a more consistent approach can be employed across centers that may facilitate a more accurate representation of the actual prevalence of AKI and more importantly, clinical investigation that may minimize the occurrence of AKI following pediatric cardiac surgery. A thoughtful management approach is necessary to mitigate the effects of AKI after cardiac surgery, which is best accomplished in close collaboration with pediatric nephrologists. Long-term surveillance for improvement in kidney function and potential development of chronic kidney disease should also be a part of the comprehensive management strategy. PMID:27429538
Predicting Academic Achievement and Attainment: The Contribution of Early Academic Skills, Attention Difficulties, and Social Competence

ERIC Educational Resources Information Center

Rabiner, David L.; Godwin, Jennifer; Dodge, Kenneth A.

2016-01-01

Research predicting academic achievement from early academic, attention, and socioemotional skills has largely focused on elementary school outcomes and rarely included peer assessments of social competence. We examined associations between these early child characteristics and academic outcomes into young adulthood using the Fast Track normative…
A global hydrographic array for early detection of floods and droughts

NASA Astrophysics Data System (ADS)

Brakenridge, G.; Nghiem, S.; Caquard, S.

An array of over 700 20 km-long river gaging reaches, distributed world-wide, is imaged by the SeaWinds radar scatterometer aboard QuikSCAT every 2.5 days. Strongly negative HH/VV polarity ratios indicate large amounts of surface water. We set individual reach thresholds so that the transition from bankfull to overbank river flow can be identified according to changes in this ratio. Similarly, the wide-swath MODIS optical sensors provide frequent repeat coverage of the reaches at much higher spatial resolution (250 m). In this case, several reach water surface area thresholds can be identified: low flow or drought conditions, normal in-channel flow, overbank flow, and extreme flood conditions. Sustained data collection for the reaches by both sensors allows the radar response to changing surface water to be defined, and allows evaluation of the sensitivity of the MODIS data to river discharge changes. New approaches, such as ``unmixing'' analysis of mixed water/land MODIS pixels can extend detection limits to smaller rivers and streams. It is now possible for wide-area, frequent revisit terrestrial remote sensing to provide human society with early warning of both floods and droughts and by direct observation of the runoff component of the Earth's hydrologic cycle. Examples of both radar and optical approaches towards this end are at the web sites below: http://www.dartmouth.edu/˜ floods/Modisrapidresponse.html http://www.dartmouth.edu/˜ floods/sensorweb/SensorWebindex.html http://www.dartmouth.edu/˜ floods/Quikscat/Regional2/CurrentTisza.jpg} In particular, early flood detection results are obtained over an extensive region in eastern Europe including the Tisza River basin, Romania, Hungary, and adjacent nations. Flood detection maps are updated weekly at the web site. The combination of QuikSCAT and MODIS takes advantage of the large-area coverage of these sensors together with the high temporal resolution of QuikSCAT and the high spatial resolution of MODIS
Future Directions for the Early Detection of Colorectal Cancer Recurrence

PubMed Central

Walker, Avery S.; Johnson, Eric K.; Maykel, Justin A.; Stojadinovic, Alex; Nissan, Aviram; Brucher, Bjorn; Champagne, Bradley J.; Steele, Scott R.

2014-01-01

Surgical resection remains a mainstay of treatment and is highly effective for localized colorectal cancer. However, ~30-40% of patients develop recurrence following surgery and 40-50% of recurrences are apparent within the first few years after initial surgical resection. Several variables factor into the ultimate outcome of these patients, including the extent of disease, tumor biology, and patient co-morbidities. Additionally, the time from initial treatment to the development of recurrence is strongly associated with overall survival, particularly in patients who recur within one year of their surgical resection. Current post-resection surveillance strategies involve physical examination, laboratory, endoscopic and imaging studies utilizing various high and low-intensity protocols. Ultimately, the goal is to detect recurrence as early as possible, and ideally in the asymptomatic localized phase, to allow initiation of treatment that may still result in cure. While current strategies have been effective, several efforts are evolving to improve our ability to identify recurrent disease at its earliest phase. Our aim with this article is to briefly review the options available and, more importantly, examine emerging and future options to assist in the early detection of colon and rectal cancer recurrence. PMID:24790655
Predicting Early School Achievement with the EDI: A Longitudinal Population-Based Study

ERIC Educational Resources Information Center

Forget-Dubois, Nadine; Lemelin, Jean-Pascal; Boivin, Michel; Dionne, Ginette; Seguin, Jean R.; Vitaro, Frank; Tremblay, Richard E.

2007-01-01

School readiness tests are significant predictors of early school achievement. Measuring school readiness on a large scale would be necessary for the implementation of intervention programs at the community level. However, assessment of school readiness is costly and time consuming. This study assesses the predictive value of a school readiness…
Early Family System Types Predict Children's Emotional Attention Biases at School Age

ERIC Educational Resources Information Center

Lindblom, Jallu; Peltola, Mikko J.; Vänskä, Mervi; Hietanen, Jari K.; Laakso, Anu; Tiitinen, Aila; Tulppala, Maija; Punamäki, Raija-Leena

2017-01-01

The family environment shapes children's social information processing and emotion regulation. Yet, the long-term effects of early family systems have rarely been studied. This study investigated how family system types predict children's attentional biases toward facial expressions at the age of 10 years. The participants were 79 children from…
Dielectric Spectroscopic Detection of Early Failures in 3-D Integrated Circuits.

PubMed

Obeng, Yaw; Okoro, C A; Ahn, Jung-Joon; You, Lin; Kopanski, Joseph J

The commercial introduction of three dimensional integrated circuits (3D-ICs) has been hindered by reliability challenges, such as stress related failures, resistivity changes, and unexplained early failures. In this paper, we discuss a new RF-based metrology, based on dielectric spectroscopy, for detecting and characterizing electrically active defects in fully integrated 3D devices. These defects are traceable to the chemistry of the insolation dielectrics used in the through silicon via (TSV) construction. We show that these defects may be responsible for some of the unexplained early reliability failures observed in TSV enabled 3D devices.
Detection of early primary colorectal cancer with upconversion luminescent NP-based molecular probes

NASA Astrophysics Data System (ADS)

Liu, Chunyan; Qi, Yifei; Qiao, Ruirui; Hou, Yi; Chan, Kaying; Li, Ziqian; Huang, Jiayi; Jing, Lihong; Du, Jun; Gao, Mingyuan

2016-06-01

Early detection and diagnosis of cancers is extremely beneficial for improving the survival rate of cancer patients and molecular imaging techniques are believed to be relevant for offering clinical solutions. Towards early cancer detection, we developed a primary animal colorectal cancer model and constructed a tumor-specific imaging probe by using biocompatible NaGdF4:Yb,Er@NaGdF4 upconversion luminescent NPs for establishing a sensitive early tumor imaging method. The primary animal tumor model, which can better mimic the human colorectal cancer, was built upon continual administration of 1,2-dimethylhydrazine in Kunming mice and the tumor development was carefully monitored through histopathological and immunohistochemical analyses to reveal the pathophysiological processes and molecular features of the cancer microenvironment. The upconversion imaging probe was constructed through covalent coupling of PEGylated core-shell NPs with folic acid whose receptor is highly expressed in the primary tumors. Upon 980 nm laser excitation, the primary colorectal tumors in the complex abdominal environment were sensitively imaged owing to the ultralow background of the upconversion luminescence and the high tumor-targeting specificity of the nanoprobe. We believe that the current studies provide a highly effective and potential approach for early colorectal cancer diagnosis and tumor surgical navigation.Early detection and diagnosis of cancers is extremely beneficial for improving the survival rate of cancer patients and molecular imaging techniques are believed to be relevant for offering clinical solutions. Towards early cancer detection, we developed a primary animal colorectal cancer model and constructed a tumor-specific imaging probe by using biocompatible NaGdF4:Yb,Er@NaGdF4 upconversion luminescent NPs for establishing a sensitive early tumor imaging method. The primary animal tumor model, which can better mimic the human colorectal cancer, was built upon continual
Predicting distant failure in early stage NSCLC treated with SBRT using clinical parameters.

PubMed

Zhou, Zhiguo; Folkert, Michael; Cannon, Nathan; Iyengar, Puneeth; Westover, Kenneth; Zhang, Yuanyuan; Choy, Hak; Timmerman, Robert; Yan, Jingsheng; Xie, Xian-J; Jiang, Steve; Wang, Jing

2016-06-01

The aim of this study is to predict early distant failure in early stage non-small cell lung cancer (NSCLC) treated with stereotactic body radiation therapy (SBRT) using clinical parameters by machine learning algorithms. The dataset used in this work includes 81 early stage NSCLC patients with at least 6months of follow-up who underwent SBRT between 2006 and 2012 at a single institution. The clinical parameters (n=18) for each patient include demographic parameters, tumor characteristics, treatment fraction schemes, and pretreatment medications. Three predictive models were constructed based on different machine learning algorithms: (1) artificial neural network (ANN), (2) logistic regression (LR) and (3) support vector machine (SVM). Furthermore, to select an optimal clinical parameter set for the model construction, three strategies were adopted: (1) clonal selection algorithm (CSA) based selection strategy; (2) sequential forward selection (SFS) method; and (3) statistical analysis (SA) based strategy. 5-cross-validation is used to validate the performance of each predictive model. The accuracy was assessed by area under the receiver operating characteristic (ROC) curve (AUC), sensitivity and specificity of the system was also evaluated. The AUCs for ANN, LR and SVM were 0.75, 0.73, and 0.80, respectively. The sensitivity values for ANN, LR and SVM were 71.2%, 72.9% and 83.1%, while the specificity values for ANN, LR and SVM were 59.1%, 63.6% and 63.6%, respectively. Meanwhile, the CSA based strategy outperformed SFS and SA in terms of AUC, sensitivity and specificity. Based on clinical parameters, the SVM with the CSA optimal parameter set selection strategy achieves better performance than other strategies for predicting distant failure in lung SBRT patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Clinical Phenotype Predicts Early Staged Bilateral Deep Brain Stimulation in Parkinson’s Disease

PubMed Central

Sung, Victor W.; Watts, Ray L.; Schrandt, Christian J.; Guthrie, Stephanie; Wang, Deli; Amara, Amy W.; Guthrie, Barton L.; Walker, Harrison C.

2014-01-01

Object While many centers place bilateral DBS systems simultaneously, unilateral STN DBS followed by a staged contralateral procedure has emerged as a treatment option for many patients. However little is known about whether the preoperative phenotype predicts when staged placement of a DBS electrode in the opposite subthalamic nucleus will be required. We aimed to determine whether preoperative clinical phenotype predicts early staged placement of a second subthalamic deep brain stimulation (DBS) electrode in patients who undergo unilateral subthalamic DBS for Parkinson's disease (PD). Methods Eighty-two consecutive patients with advanced PD underwent unilateral subthalamic DBS contralateral to the most affected hemibody and had at least 2 years of follow-up. Multivariate logistic regression determined preoperative characteristics that predicted staged placement of a second electrode in the opposite subthalamic nucleus. Preoperative measurements included aspects of the Unified Parkinson Disease Rating Scale (UPDRS), motor asymmetry index, and body weight. Results At 2 years follow-up, 28 of the 82 patients (34%) had undergone staged placement of a contralateral electrode while the remainder chose to continue with unilateral stimulation. Statistically significant improvements in UPDRS total and part 3 scores were retained at the end of the 2 year follow-up period in both subsets of patients. Multivariate logistic regression showed that the most important predictors for early staged placement of a second subthalamic stimulator were low asymmetry index (odds ratio 13.4; 95% confidence interval 2.8, 64.9), high tremor subscore (OR 7.2; CI 1.5, 35.0), and low body weight (OR 5.5; CI 1.4, 22.3). Conclusions This single center study provides evidence that elements of the preoperative PD phenotype predict whether patients will require early staged bilateral subthalamic DBS. These data may aid in the management of patients with advanced PD who undergo subthalamic DBS. PMID

Detection of oral early cancerous lesion by using polarization-sensitive optical coherence tomography: mice model

NASA Astrophysics Data System (ADS)

Lee, Hong-Yi; Chen, Ping-Hsien; Lee, Tzu-Han; Chang, Kuo-Wei; Kuo, Wen-Chuan

2018-02-01

Oral cancer is the 11th most common cancer worldwide, especially in a male adult. The median age of death in oral cancer was 55 years, 10-20 years earlier than other cancers. Presently, oral cancer is often found in late stage, because the lesion is often flat in early stage and is difficult to diagnose under traditional white light imaging. The only definitive method for determining cancer is an invasive biopsy and then using histology examination. How to detect precancerous lesions or early malignant lesions is an important issue for improving prognosis of oral cancer. Optical coherence tomography (OCT) is a new optical tool for diagnosing early malignant lesions in the skin or gastrointestinal tract recently. Here we report a new method for detecting precancerous or early malignant oral lesions by using swept source polarization-sensitive optical coherence tomography (PS-OCT) with center-wavelength 1310 nm, bandwidth 110 nm and 100 kHz swept rate. We used all single-mode fiber design to detect the change of birefringence information in the epithelium structure. This system has an advantage that enables measurement of backscattered intensity and birefringence simultaneously with only one A-scan per transverse location. In preliminary result, we computed the slope of the every A-scan signal in tissue part using a linear-curve fitting in backscattered intensity and birefringence on the enface. In this research, we used an oral cancer mice model for observing the change of structure and birefringence properties in different stages of oral cancer mice. We presented the parametric enface imaging that can detect the early oral malignant lesions.
Method for early detection of cooling-loss events

DOEpatents

Bermudez, Sergio A.; Hamann, Hendrik; Marianno, Fernando J.

2015-06-30

A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.
Method for early detection of cooling-loss events

DOEpatents

Bermudez, Sergio A.; Hamann, Hendrik F.; Marianno, Fernando J.

2015-12-22

A method of detecting cooling-loss event early is provided. The method includes defining a relative humidity limit and change threshold for a given space, measuring relative humidity in the given space, determining, with a processing unit, whether the measured relative humidity is within the defined relative humidity limit, generating a warning in an event the measured relative humidity is outside the defined relative humidity limit and determining whether a change in the measured relative humidity is less than the defined change threshold for the given space and generating an alarm in an event the change is greater than the defined change threshold.
Early detection of Trichinella spiralis DNA in the feces of experimentally infected mice by using PCR.

PubMed

Liu, Xiao Lin; Ren, Hua Nan; Shi, Ya Li; Hu, Chen Xi; Song, Yan Yan; Duan, Jiang Yang; Zhang, Hui Ping; Du, Xin Rui; Liu, Ruo Dan; Jiang, Peng; Wang, Zhong Quan; Cui, Jing

2017-02-01

The aim of this study was to detect Trichinella spiralis DNA in mouse feces during the early stages of infection using PCR. The target gene fragment, a 1.6kb repetitive sequence of T. spiralis genome, was amplified by PCR from feces of mice infected with 100 or 300 larvae at 3-24h post infection (hpi) and 2-28dpi. The sensitivity of PCR was 0.016 larvae in feces. The primers used were highly specific for T. spiralis. No cross-reactivity was observed with the DNA of other intestinal helminths. T. spiralis DNA was detected in 100% (12/12) of feces of mice infected with 100 or 300 larvae as early as 3hpi, with the peak detection lasting to 12-24hpi, and then fluctuating before declining gradually. By 28dpi, the detection rate of T. spiralis DNA in feces of the two groups of infected mice decreased to 8.33% and 25%, respectively. PCR detection of T. spiralis DNA in feces is simple and specific; it might be useful for the early diagnosis of Trichinella infection. Copyright © 2016 Elsevier B.V. All rights reserved.
New Predictive Model at 11+0 to 13+6 Gestational Weeks for Early-Onset Preeclampsia With Fetal Growth Restriction.

PubMed

Chang, Ying; Chen, Xu; Cui, Hong-Yan; Li, Xing; Xu, Ya-Ling

2017-05-01

The aim of the present study was to determine a predictive model for early-onset preeclampsia with fetal growth restriction (FGR) to be used at 11 +0 to 13 +6 gestational weeks, by combining the maternal serum level of pregnancy-associated plasma protein-A (PAPP-A), placental growth factor (PLGF), placental protein 13 (PP13), soluble endoglin (sEng), mean arterial pressure (MAP), and uterine artery Doppler. This was a retrospective cohort study of 4453 pregnant women. Uterine artery Doppler examination was conducted in the first trimester. Maternal serum PAPP-A, PLGF, PP13, and sEng were measured. Mean arterial pressure was obtained. Women were classified as with/without early-onset preeclampsia, and women with preeclampsia were classified as with/without FGR. Receiver operating characteristic analysis was performed to determine the value of the model. There were 30 and 32 pregnant women with early-onset preeclampsia with and without FGR. The diagnosis rate of early-onset preeclampsia with FGR was 67.4% using the predictive model when the false positive rate was set at 5% and 73.2% when the false positive rate was 10%. The predictive model (MAP, uterine artery Doppler measurements, and serum biomarkers) had some predictive value for the early diagnosis (11 +0 to 13 +6 gestational weeks) of early-onset preeclampsia with FGR.
Detection and Evaluation of Early Breast Cancer via Magnetic Resonance Imaging: Studies of Mouse Models and Clinical Implementation

DTIC Science & Technology

2008-03-01

CONTRACT NUMBER Detection and Evaluation of Early Breast Cancer via Magnetic Resonance Imaging: Studies of Mouse Models and Clinical Implementation...research proposed here can directly lead to clinical improvements in both early breast cancer detection, as well as effective breast cancer therapy. To date... cancer is a major prognostic factor in the management of the disease. In particular, detecting breast cancer in its pre-invasive form as ductal carcinoma
Early detection of response to radiation therapy in patients with brain malignancies using conventional and high b-value diffusion-weighted magnetic resonance imaging.

PubMed

Mardor, Yael; Pfeffer, Raphael; Spiegelmann, Roberto; Roth, Yiftach; Maier, Stephan E; Nissim, Ouzi; Berger, Raanan; Glicksman, Ami; Baram, Jacob; Orenstein, Arie; Cohen, Jack S; Tichler, Thomas

2003-03-15

To study the feasibility of using diffusion-weighted magnetic resonance imaging (DWMRI), which is sensitive to the diffusion of water molecules in tissues, for detection of early tumor response to radiation therapy; and to evaluate the additional information obtained from high DWMRI, which is more sensitive to low-mobility water molecules (such as intracellular or bound water), in increasing the sensitivity to response. Standard MRI and DWMRI were acquired before and at regular intervals after initiating radiation therapy for 10 malignant brain lesions in eight patients. One week posttherapy, three of six responding lesions showed an increase in the conventional DWMRI parameters. Another three responding lesions showed no change. Four nonresponding lesions showed a decrease or no change. The early change in the diffusion parameters was enhanced by using high DWMRI. When high DWMRI was used, all responding lesions showed increase in the diffusion parameter and all nonresponding lesions showed no change or decrease. Response was determined by standard MRI 7 weeks posttherapy. The changes in the diffusion parameters measured 1 week after initiating treatment were correlated with later tumor response or no response (P <.006). This correlation was increased to P <.0006 when high DWMRI was used. The significant correlation between changes in diffusion parameters 1 week after initiating treatment and later tumor response or no response suggests the feasibility of using DWMRI for early, noninvasive prediction of tumor response. The ability to predict response may enable early termination of treatment in nonresponding patients, prevent additional toxicity, and allow for early changes in treatment.
Parafoveal Target Detectability Reversal Predicted by Local Luminance and Contrast Gain Control

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.; Beard, Bettina L.; Null, Cynthia H. (Technical Monitor)

1996-01-01

This project is part of a program to develop image discrimination models for the prediction of the detectability of objects in a range of backgrounds. We wanted to see if the models could predict parafoveal object detection as well as they predict detection in foveal vision. We also wanted to make our simplified models more general by local computation of luminance and contrast gain control. A signal image (0.78 x 0.17 deg) was made by subtracting a simulated airport runway scene background image (2.7 deg square) from the same scene containing an obstructing aircraft. Signal visibility contrast thresholds were measured in a fully crossed factorial design with three factors: eccentricity (0 deg or 4 deg), background (uniform or runway scene background), and fixed-pattern white noise contrast (0%, 5%, or 10%). Three experienced observers responded to three repetitions of 60 2IFC trials in each condition and thresholds were estimated by maximum likelihood probit analysis. In the fovea the average detection contrast threshold was 4 dB lower for the runway background than for the uniform background, but in the parafovea, the average threshold was 6 dB higher for the runway background than for the uniform background. This interaction was similar across the different noise levels and for all three observers. A likely reason for the runway background giving a lower threshold in the fovea is the low luminance near the signal in that scene. In our model, the local luminance computation is controlled by a spatial spread parameter. When this parameter and a corresponding parameter for the spatial spread of contrast gain were increased for the parafoveal predictions, the model predicts the interaction of background with eccentricity.
Early starting, aggressive, and/or callous-unemotional? Examining the overlap and predictive utility of antisocial behavior subtypes

PubMed Central

Hyde, Luke W.; Burt, S. Alexandra; Shaw, Daniel S.; Donnellan, M. Brent; Forbes, Erika E.

2015-01-01

Antisocial behavior (AB) in adolescence predicts problematic outcomes in adulthood. However, researchers have noted marked heterogeneity within the broad group of youth engaging in these destructive behaviors and have attempted to identify those with distinct etiologies and different trajectories of symptoms. In the present study, we evaluate three prominent AB subtyping approaches: age of onset, presence of callous-unemotional (CU) traits, and aggressive versus rule breaking symptoms. We examined the overlap of these subtypes and their predictive validity in a diverse sample of 268 low-income young men followed prospectively from adolescence into emerging adulthood. We found that those with early starting AB were uniquely high on aggressive symptoms but not on CU traits. Early starting AB and both aggression and rule breaking measured during adolescence predicted most subsequent psychiatric and AB outcomes in early adulthood in univariate models, whereas CU traits were only predictive of adolescent arrests, later substance dependence diagnosis, and later CU traits. Finally, after accounting for shared variance among predictor variables, we found that aggressive symptoms explained the most unique variance in predicting several later outcomes (e.g., antisocial personality disorder) over and above other subtyping approaches. Results are discussed in relation to of the utility of existing subtyping approaches to AB, noting that aggression and age of onset, but not CU traits, appear to be the best at predicting later negative outcome. PMID:25603360
76 FR 55915 - Request for Nominations of Candidates to Serve on the Breast and Cervical Cancer Early Detection...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-09

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention Request for Nominations of Candidates to Serve on the Breast and Cervical Cancer Early Detection and Control Advisory... Secretary for Health, and the CDC on the early detection and control of breast and cervical cancer. The role...
Phase II Validation of a New Panel of Biomarkers for Early Detection of Ovarian Cancer — EDRN Public Portal

Cancer.gov

While all cancer patients could potentially benefit from earlier detection and prevention, the development of new screening technologies and chemoprevention for epithelial ovarian cancer (EOC) is unique in this regard. EOC is characterized by few early symptoms, presentation at an advanced stage, and poor survival. Presently there is no commercially available test that is diagnostic for either early or advanced stage epithelial ovarian cancer. The most commonly used marker, CA125, identifies a group of cell surface glycoproteins, which have uncertain biological behavior and very limited clinical utility for the detection of early stage disease. In recent years, several approaches have been used in order to develop a test for early detection, including the analysis of serum samples by SELDI-TOF and MALDI-TOF to find proteins or protein fragments of unknown identity that detect the presence/absence of cancer. Unfortunately, at the present time, none of these techniques have been shown to be adequate. Therefore, the development of a test that can detect early stages of the disease could dramatically improve treatment success and long-term survival. We have developed a new blood test based on a different approach: 1) we used known proteins related to cancer biology, 2) we characterized these proteins with several different screening steps using samples obtained from both healthy and cancer patient populations, and 3) validated the results with different techniques. Using split point analysis with four markers, 96 out of 100 EOC patients (96%) were correctly diagnosed with ovarian cancer (including 23 of 24 patients with Stage I/II EOC). In the healthy group, 6 out of 106 individuals were diagnosed incorrectly (5.6%). Working in collaboration with the Early Detection Network (EDRN/NCI/NIH), we performed Phase I discovery study confirming the potential application of this test for early detection of ovarian cancer (Preliminary results). The main objective of this pr
Sentinel lymph node detection in early stage cervical cancer: a prospective study comparing preoperative lymphoscintigraphy, intraoperative gamma probe, and blue dye.

PubMed

Kara, P Pelin; Ayhan, Ali; Caner, Biray; Gültekin, Murat; Ugur, Omer; Bozkurt, M Fani; Usubutun, Alp

2008-07-01

The objective of this prospective study was to determine the feasibility of sentinel lymph node (SLN) detection in patients with cervical cancer using lymphoscintigraphy (LS), gamma probe, and blue dye. A total of 32 patients with early stage cervical cancer (FIGO IA2-IIA) who were treated with total abdominal hysterectomy and bilateral pelvic and paraortic lymphadenectomy underwent SLN biopsy. LS was performed on all the patients following the injection of 74 MBq technetium-99m-nanocolloid pericervically. The first appearing persistent focal accumulation on either dynamic or static images of LS was considered to be an SLN. Blue dye was injected just prior to surgical incision in 16 patients (50%) at the same locations as the radioactive isotope injection. During the operation, blue-stained node(s) were excised as SLNs. For gamma probe, a lymph node was accepted as an SLN, if its ex vivo radioactive counts were at least 10-fold above background radioactivity. SLNs, which were negative by routine hematoxylin and eosin (H&E) examination, were histopathologically reevaluated for the presence of micrometastases by step sectioning and immunohistochemical staining with pancytokeratin. At least one SLN was identified for each patient by gamma probe. Intraoperative gamma probe was the most sensitive method with a technical success rate of SLN detection of 100% (32/32), followed by LS 87.5% (28/32) and blue dye 68.8% (11/16), respectively. The average number of SLNs per patient detected by gamma probe was 2.09 (range 1-5). The localizations of the SLNs were external iliac 47.8%, obturatory 32.8%, common iliac 9%, paraaortic 4.4%, and paracervical 6%. Micrometastases, not detected by routine H&E were found by immunohistochemistry in one patient. On the basis of the histopathological analysis, the negative predictive value for predicting metastases was 100%, and there were no false-negative results. Preoperative LS with radiocolloids, intraoperative lymphatic mapping with
Improvement of the predicted aural detection code ICHIN (I Can Hear It Now)

NASA Technical Reports Server (NTRS)

Mueller, Arnold W.; Smith, Charles D.; Lemasurier, Phillip

1993-01-01

Acoustic tests were conducted to study the far-field sound pressure levels and aural detection ranges associated with a Sikorsky S-76A helicopter in straight and level flight at various advancing blade tip Mach numbers. The flight altitude was nominally 150 meters above ground level. This paper compares the normalized predicted aural detection distances, based on the measured far-field sound pressure levels, to the normalized measured aural detection distances obtained from sound jury response measurements obtained during the same test. Both unmodified and modified versions of the prediction code ICHIN-6 (I Can Hear It Now) were used to produce the results for this study.
Prediction of adolescent and adult adiposity outcomes from early life anthropometrics.

PubMed

Graversen, Lise; Sørensen, Thorkild I A; Gerds, Thomas A; Petersen, Liselotte; Sovio, Ulla; Kaakinen, Marika; Sandbaek, Annelli; Laitinen, Jaana; Taanila, Anja; Pouta, Anneli; Järvelin, Marjo-Riitta; Obel, Carsten

2015-01-01

Maternal body mass index (BMI), birth weight, and preschool BMI may help identify children at high risk of overweight as they are (1) similarly linked to adolescent overweight at different stages of the obesity epidemic, (2) linked to adult obesity and metabolic alterations, and (3) easily obtainable in health examinations in young children. The aim was to develop early childhood prediction models of adolescent overweight, adult overweight, and adult obesity. Prediction models at various ages in the Northern Finland Birth Cohort born in 1966 (NFBC1966) were developed. Internal validation was tested using a bootstrap design, and external validation was tested for the model predicting adolescent overweight using the Northern Finland Birth Cohort born in 1986 (NFBC1986). A prediction model developed in the NFBC1966 to predict adolescent overweight, applied to the NFBC1986, and aimed at labelling 10% as "at risk" on the basis of anthropometric information collected until 5 years of age showed that half of those at risk in fact did become overweight. This group constituted one-third of all who became overweight. Our prediction model identified a subgroup of children at very high risk of becoming overweight, which may be valuable in public health settings dealing with obesity prevention. © 2014 The Obesity Society.
Aquatic invasive species early detection in the Great Lakes: Lessons concerning strategy

EPA Science Inventory

Great Lakes coastal systems are vulnerable to introduction of a wide variety of non-indigenous species (NIS), and the desire to effectively respond to future invaders is prompting efforts towards establishing a broad early-detection network. Such a network requires statistically...
Thermo-mechanical simulations of early-age concrete cracking with durability predictions

NASA Astrophysics Data System (ADS)

Havlásek, Petr; Šmilauer, Vít; Hájková, Karolina; Baquerizo, Luis

2017-09-01

Concrete performance is strongly affected by mix design, thermal boundary conditions, its evolving mechanical properties, and internal/external restraints with consequences to possible cracking with impaired durability. Thermo-mechanical simulations are able to capture those relevant phenomena and boundary conditions for predicting temperature, strains, stresses or cracking in reinforced concrete structures. In this paper, we propose a weakly coupled thermo-mechanical model for early age concrete with an affinity-based hydration model for thermal part, taking into account concrete mix design, cement type and thermal boundary conditions. The mechanical part uses B3/B4 model for concrete creep and shrinkage with isotropic damage model for cracking, able to predict a crack width. All models have been implemented in an open-source OOFEM software package. Validations of thermo-mechanical simulations will be presented on several massive concrete structures, showing excellent temperature predictions. Likewise, strain validation demonstrates good predictions on a restrained reinforced concrete wall and concrete beam. Durability predictions stem from induction time of reinforcement corrosion, caused by carbonation and/or chloride ingress influenced by crack width. Reinforcement corrosion in concrete struts of a bridge will serve for validation.
Novel Use of Flu Surveillance Data: Evaluating Potential of Sentinel Populations for Early Detection of Influenza Outbreaks.

PubMed

Daughton, Ashlynn R; Velappan, Nileena; Abeyta, Esteban; Priedhorsky, Reid; Deshpande, Alina

2016-01-01

Influenza causes significant morbidity and mortality each year, with 2-8% of weekly outpatient visits around the United States for influenza-like-illness (ILI) during the peak of the season. Effective use of existing flu surveillance data allows officials to understand and predict current flu outbreaks and can contribute to reductions in influenza morbidity and mortality. Previous work used the 2009-2010 influenza season to investigate the possibility of using existing military and civilian surveillance systems to improve early detection of flu outbreaks. Results suggested that civilian surveillance could help predict outbreak trajectory in local military installations. To further test that hypothesis, we compare pairs of civilian and military outbreaks in seven locations between 2000 and 2013. We find no predictive relationship between outbreak peaks or time series of paired outbreaks. This larger study does not find evidence to support the hypothesis that civilian data can be used as sentinel surveillance for military installations. We additionally investigate the effect of modifying the ILI case definition between the standard Department of Defense definition, a more specific definition proposed in literature, and confirmed Influenza A. We find that case definition heavily impacts results. This study thus highlights the importance of careful selection of case definition, and appropriate consideration of case definition in the interpretation of results.
Predicting Adult Criminal Behavior from Juvenile Delinquency: Ex-Ante vs. Ex-Post Benefits of Early Intervention

PubMed Central

White, Barry A. B.; Temple, Judy A.; Reynolds, Arthur J.

2016-01-01

Recent analyses of the long-term societal benefits from early intervention (prenatal care, home visitation, and high quality preschool) for at-risk children commonly include significant savings to society in the form of reduced juvenile delinquency and adult criminal behavior. However, a nontrivial proportion of the reported benefits of several early intervention programs are based on forecasts of criminal behavior throughout adulthood conditional on intervention effects on delinquency in adolescence. Data from the Chicago Longitudinal Study (CLS), an investigation of the life course of 1,539 children from low-income families born in 1979–1980, are used to investigate the bias resulting from predicting the effect of early intervention on adult criminal behavior from the effect on delinquency in adolescence. The investigation concludes that the general method used to predict adult criminal behavior results in a conservative estimate of the reduction in the cost of adult criminal behavior attributed to early intervention. PMID:27867324
Predicting Adult Criminal Behavior from Juvenile Delinquency: Ex-Ante vs. Ex-Post Benefits of Early Intervention.

PubMed

White, Barry A B; Temple, Judy A; Reynolds, Arthur J

2010-12-01

Recent analyses of the long-term societal benefits from early intervention (prenatal care, home visitation, and high quality preschool) for at-risk children commonly include significant savings to society in the form of reduced juvenile delinquency and adult criminal behavior. However, a nontrivial proportion of the reported benefits of several early intervention programs are based on forecasts of criminal behavior throughout adulthood conditional on intervention effects on delinquency in adolescence. Data from the Chicago Longitudinal Study (CLS), an investigation of the life course of 1,539 children from low-income families born in 1979-1980, are used to investigate the bias resulting from predicting the effect of early intervention on adult criminal behavior from the effect on delinquency in adolescence. The investigation concludes that the general method used to predict adult criminal behavior results in a conservative estimate of the reduction in the cost of adult criminal behavior attributed to early intervention.
University Students' Early Maladaptive Schemas' Prediction of Their Mindfulness Levels

ERIC Educational Resources Information Center

Yalcin, S.Barbaros; Kavakli, Mehmet; Kesici, Sahin; Ak, Mehmet

2017-01-01

Purpose: The aim of this study is to determine whether university students' early maladaptive schemas predict their mindfulness levels or not. Methods: The study was carried out in the relational screening model. The study group consisted of 293 university students; 237 (80,9%) females and 56 (19,1%) males. "Mindful Attention Awareness Scale…

Blueprint of quartz crystal microbalance biosensor for early detection of breast cancer through salivary autoantibodies against ATP6AP1.

PubMed

Arif, Sania; Qudsia, Syeda; Urooj, Samina; Chaudry, Nazia; Arshad, Aneeqa; Andleeb, Saadia

2015-03-15

Breast cancer represents a significant health problem because of its high prevalence. Tests like mammography, which are used abundantly for the detection of breast cancer, suffer from serious limitations. Mammography correctly detects malignancy about 80-90% of the times, failing in places when (1) the tumor is small at early stage, (2) breast tissue is dense or (3) in women of less than 40 years. Serum-based detection of biomarkers involves risk of disease transfer, along with other concerns. These techniques compromise in the early detection of breast cancer. Early detection of breast cancer is a crucial factor to enhance the survival rate of patient. Development of regular screening tests for early diagnosis of breast cancer is a challenge. This review highlights the design of a handy and household biosensor device aimed for self-screening and early diagnosis of breast cancer. The design makes use of salivary autoantibodies for specificity to develop a noninvasive procedure, breast cancer specific biomarkers for precision for the development of device, and biosensor technology for sensitivity to screen the early cases of breast cancer more efficiently. Copyright © 2014 Elsevier B.V. All rights reserved.
Breast cancer early detection via tracking of skin back-scattered secondary speckle patterns

NASA Astrophysics Data System (ADS)

Bennett, Aviya; Sirkis, Talia; Beiderman, Yevgeny; Agdarov, Sergey; Beiderman, Yafim; Zalevsky, Zeev

2018-02-01

Breast cancer has become a major cause of death among women. The lifetime risk of a woman developing this disease has been established as one in eight. The most useful way to reduce breast cancer death is to treat the disease as early as possible. The existing methods of early diagnostics of breast cancer are mainly based on screening mammography or Magnetic Resonance Imaging (MRI) periodically conducted at medical facilities. In this paper the authors proposing a new approach for simple breast cancer detection. It is based on skin stimulation by sound waves, illuminating it by laser beam and tracking the reflected secondary speckle patterns. As first approach, plastic balls of different sizes were placed under the skin of chicken breast and detected by the proposed method.
Predicting stillbirth in a low resource setting.

PubMed

Kayode, Gbenga A; Grobbee, Diederick E; Amoakoh-Coleman, Mary; Adeleke, Ibrahim Taiwo; Ansah, Evelyn; de Groot, Joris A H; Klipstein-Grobusch, Kerstin

2016-09-20

Stillbirth is a major contributor to perinatal mortality and it is particularly common in low- and middle-income countries, where annually about three million stillbirths occur in the third trimester. This study aims to develop a prediction model for early detection of pregnancies at high risk of stillbirth. This retrospective cohort study examined 6,573 pregnant women who delivered at Federal Medical Centre Bida, a tertiary level of healthcare in Nigeria from January 2010 to December 2013. Descriptive statistics were performed and missing data imputed. Multivariable logistic regression was applied to examine the associations between selected candidate predictors and stillbirth. Discrimination and calibration were used to assess the model's performance. The prediction model was validated internally and over-optimism was corrected. We developed a prediction model for stillbirth that comprised maternal comorbidity, place of residence, maternal occupation, parity, bleeding in pregnancy, and fetal presentation. As a secondary analysis, we extended the model by including fetal growth rate as a predictor, to examine how beneficial ultrasound parameters would be for the predictive performance of the model. After internal validation, both calibration and discriminative performance of both the basic and extended model were excellent (i.e. C-statistic basic model = 0.80 (95 % CI 0.78-0.83) and extended model = 0.82 (95 % CI 0.80-0.83)). We developed a simple but informative prediction model for early detection of pregnancies with a high risk of stillbirth for early intervention in a low resource setting. Future research should focus on external validation of the performance of this promising model.
Does early childhood callous-unemotional behavior uniquely predict behavior problems or callous-unemotional behavior in late childhood?

PubMed Central

Waller, Rebecca; Dishion, Thomas J.; Shaw, Daniel S.; Gardner, Frances; Wilson, Melvin N.; Hyde, Luke W.

2016-01-01

Callous unemotional (CU) behavior has been linked to behavior problems in children and adolescents. However, few studies have examined whether CU behavior in early childhood predicts behavior problems or CU behavior in late childhood. This study examined whether indicators of CU behavior at ages 2–4 predicted aggression, rule-breaking, and CU behavior across informants at age 9.5. To test the unique predictive and convergent validity of CU behavior in early childhood, we accounted for stability in behavior problems and method effects to rule out the possibility that rater biases inflated the magnitude of any associations found. Cross-informant data were collected from a multi-ethnic, high-risk sample (N = 731; female = 49%) at ages 2–4 and again at age 9.5. From age 3, CU behavior uniquely predicted aggression and rule-breaking across informants. There were also unique associations between CU behavior assessed at ages 3 and 4 and CU behavior assessed at age 9.5. Findings demonstrate that early-childhood indicators of CU behavior account for unique variance in later childhood behavior problems and CU behavior, taking into account stability in behavior problems over time and method effects. Convergence with a traditional measure of CU behavior in late childhood provides support for the construct validity of a brief early childhood measure of CU behavior. PMID:27598253
Early fibrinogen degradation coagulopathy: a predictive factor of parenchymal hematomas in cerebral rt-PA thrombolysis.

PubMed

Sun, Xuhong; Berthiller, Julien; Trouillas, Paul; Derex, Laurent; Diallo, Laho; Hanss, Michel

2015-04-15

The purpose of this study was to systematically determine the correlations between the post-thrombolytic changes of hemostasis parameters and the occurrence of early intracerebral hemorrhage (ICH). In 72 consecutive patients with cerebral infarcts treated with rt-PA, plasma levels of fibrinogen, plasminogen, alpha2-antiplasmin, factor XIII, fibrin(ogen) degradation products (FDPs) and d-Dimers were measured at baseline, 2 and 24h after thrombolysis. Correlations were studied between the hemostasis events and early (less than 24h) hemorrhagic infarcts (HIs) or parenchymatous hematomas (PH). Of 72 patients, 6 patients (8.3%) had early PHs, 11 (15.3%) had early HIs, and 55 (76.4%) had no bleeding. Early HIs were not linked to any hemostasis parameter at any time. Univariate comparison of patients having early PHs with non-bleeding patients showed hemostasis abnormalities at 2h: high FDP (p=0.01), high Log FDP (p=0.01), low fibrinogen (p=0.01), and low Log fibrinogen (p=0.01). Logistic regression adjusted for age, NIHSS and diabetes confirmed these 2hour predictors: Log FDP (OR: 7.50; CI: 1.26 to 44.61, p=0.03), and Log fibrinogen (OR: 19.32; CI: 1.81 to 205.98, p=0.01). The decrease in fibrinogen less than 2g/L multiplies the odds of early PH by a factor 12.82. An early fibrinogen degradation coagulopathy involving an increase of FDP and a massive consumption of circulating fibrinogen is predictive of early parenchymal hematomas, indicating the occurrence of a particularly intense lysis of circulating fibrinogen. These results, if confirmed by future studies, suggest that early assays of fibrinogen and FDP may be useful in predicting the risk of post-thrombolytic intracerebral hematoma. Copyright © 2015 Elsevier B.V. All rights reserved.
Health economics evaluation of a gastric cancer early detection and treatment program in China.

PubMed

Li, Dan; Yuan, Yuan; Sun, Li-Ping; Fang, Xue; Zhou, Bao-Sen

2014-01-01

To use health economics methodology to assess the screening program on gastric cancer in Zhuanghe, China, so as to provide the basis for health decision on expanding the program of early detection and treatment. The expense of an early detection and treatment program for gastric cancer in patients found by screening, and also costs of traditional treatment in a hospital of Zhuanghe were assessed. Three major techniques of medical economics, namely cost-effective analysis (CEA), cost-benefit analysis (CBA) and cost-utility analysis (CUA), were used to assess the screening program. RESULTS from CEA showed that investing every 25, 235 Yuan on screening program in Zhuanghe area, one gastric cancer patient could be saved. Data from CUA showed that it was cost 1, 370 Yuan per QALY saved. RESULTS from CBA showed that: the total cost was 1,945,206 Yuan with a benefit as 8,669,709 Yuan and an CBR of 4.46. The early detection and treatment program of gastric cancer appears economic and society-beneficial. We suggest that it should be carry out in more high risk areas for gastric cancer.
Early Detection and Screening for Breast Cancer.

PubMed

Coleman, Cathy

2017-05-01

To review the history, current status, and future trends related to breast cancer screening. Peer-reviewed articles, web sites, and textbooks. Breast cancer remains a complex, heterogeneous disease. Serial screening with mammography is the most effective method to detect early stage disease and decrease mortality. Although politics and economics may inhibit organized mammography screening programs in many countries, the judicious use of proficient clinical and self-breast examination can also identify small tumors leading to reduced morbidity. Oncology nurses have exciting opportunities to lead, facilitate, and advocate for delivery of high-quality screening services targeting individuals and communities. A practical approach is needed to translate the complexities and controversies surrounding breast cancer screening into improved care outcomes. Copyright © 2017 Elsevier Inc. All rights reserved.
Effects of historical and predictive information on ability of transport pilot to predict an alert

NASA Technical Reports Server (NTRS)

Trujillo, Anna C.

1994-01-01

In the aviation community, the early detection of the development of a possible subsystem problem during a flight is potentially useful for increasing the safety of the flight. Commercial airlines are currently using twin-engine aircraft for extended transport operations over water, and the early detection of a possible problem might increase the flight crew's options for safely landing the aircraft. One method for decreasing the severity of a developing problem is to predict the behavior of the problem so that appropriate corrective actions can be taken. To investigate the pilots' ability to predict long-term events, a computer workstation experiment was conducted in which 18 airline pilots predicted the alert time (the time to an alert) using 3 different dial displays and 3 different parameter behavior complexity levels. The three dial displays were as follows: standard (resembling current aircraft round dial presentations); history (indicating the current value plus the value of the parameter 5 sec in the past); and predictive (indicating the current value plus the value of the parameter 5 sec into the future). The time profiles describing the behavior of the parameter consisted of constant rate-of-change profiles, decelerating profiles, and accelerating-then-decelerating profiles. Although the pilots indicated that they preferred the near term predictive dial, the objective data did not support its use. The objective data did show that the time profiles had the most significant effect on performance in estimating the time to an alert.
Predictive Value of Early Skin Rash in Cetuximab-Based Therapy of Advanced Biliary Tract Cancer.

PubMed

Rubovszky, Gábor; Budai, Barna; Ganofszky, Erna; Horváth, Zsolt; Juhos, Éva; Madaras, Balázs; Nagy, Tünde; Szabó, Eszter; Pintér, Tamás; Tóth, Erika; Nagy, Péter; Láng, István; Hitre, Erika

2018-04-01

Randomized trials in advanced biliary tract cancer (BTC) did not show benefit of cetuximab addition over chemotherapy. This is probably due to the lack of predictive biomarkers. The aim of this study was to explore possible predictive factors. Between 2009 and 2014, 57 patients were treated in 3-week cycles with cetuximab (250 mg/m 2 /week, loading dose: 400 mg/m 2 ), gemcitabine (1000 mg/m 2 on day 1 and 8), and capecitabine (1300 mg/m 2 /day on days 1-14). The objective response rate (ORR), progression-free (PFS) and overall survival (OS) and the adverse events (AEs) were evaluated. An exploratory analysis was performed to find possible predictive factors on clinicopathological characteristics, routine laboratory parameters and early AEs, which occurred within 2 months from the beginning of treatment. The ORR was 21%. The median PFS and OS were 34 (95% CI: 24-40) and 54 (43-67) weeks, respectively. The most frequent AEs were skin toxicities. In univariate analysis performance status, previous stent implantation, thrombocyte count at the start of therapy, early neutropenia and skin rash statistically significantly influenced the ORR, PFS and/or OS. In multivariate Cox regression analysis only normal thrombocyte count at treatment start and early acneiform rash were independent markers of longer survival. In patients showing early skin rash compared to the others the median PFS was 39 vs. 13 weeks and the median OS was 67 vs. 26 weeks, respectively. It is suggested that early skin rash can be used as a biomarker to select patients who would benefit from the treatment with cetuximab plus chemotherapy.
HYPERGLYCOSYLATED HUMAN CHORIONIC GONADOTROPIN AS AN EARLY PREDICTOR OF PREGNANCY OUTCOMES AFTER IN VITRO FERTILIZATION

PubMed Central

Chuan, Sandy; Homer, Michael; Pandian, Raj; Conway, Deirdre; Garzo, Gabriel; Yeo, Lisa; Su, H. Irene

2014-01-01

Objective To determine if hyperglycosylated hCG (hhCG), produced by invasive trophoblasts, measured as early as 9 days after egg retrieval can predict ongoing pregnancies (OP) after in vitro fertilization and fresh embryo transfer (IVF-ET). Design Cohort Setting Academic ART center Patients Consecutive patients undergoing IVF-ET Interventions Serum hhCG and hCG levels measured 9 (D9) and 16 (D16) days after egg retrieval Outcome Ongoing pregnancy (OP) beyond 9 weeks of gestation Results OP (62 of 112 participants) was associated with higher D9 levels of hhCG and hCG However, hhCG was detectable in all D9 OP samples, while hCG was detectable in only 22%. D9 hhCG levels >110 pg/mL was 96% specific for OP, yielding a positive predictive value of 95%. Compared to D9 hCG levels, hhCG was more sensitive and had a larger area under the curve (0.87 vs. 0.67). Diagnostic test characteristics were similar between D16 hhCG and hCG levels. Conclusions In patients undergoing assisted reproduction, a test to detect pregnancy early and predict outcomes is highly desirable. HhCG is detectable in serum 9 days after egg retrieval IVF-ET cycles. At this early assessment, hhCG is superior to traditional hCG and highly predictive of ongoing pregnancies. PMID:24355054
Early detection of protozoan grazers in algal biofuel cultures.

PubMed

Day, John G; Thomas, Naomi J; Achilles-Day, Undine E M; Leakey, Raymond J G

2012-06-01

Future micro-algal biofuels will most likely be derived from open-pond production systems. These are by definition open to "invasion" by grazers, which could devastate micro-algal mass-cultures. There is an urgent requirement for methodologies capable of early detection and control of grazers in dense algal cultures. In this study a model system employing the marine alga Nannochloropsis oculata was challenged by grazers including ciliates, amoebae and a heterotrophic dinoflagellate. A FlowCAM flow-cytometer was used to detect all grazers investigated (size range <20->80 μm in length) in the presence of algae. Detection limits were <10 cells ml(-1) for both "large" and "small" model grazers, Euplotes vannus (80 × 45 μm) and an unidentified holotrichous ciliate (~18 × 8 μm) respectively. Furthermore, the system can distinguish the presence of ciliates in N. oculata cultures with biotechnologically relevant cell densities; i.e. >1.4 × 10(8) cells ml(-1) (>0.5 g l(-1) dry wt.). Copyright © 2012 Elsevier Ltd. All rights reserved.
Interactions between callous unemotional behaviors and executive function in early childhood predict later socioemotional functioning

PubMed Central

Waller, Rebecca; Hyde, Luke W.; Baskin-Sommers, Arielle; Olson, Sheryl L.

2018-01-01

Callous unemotional (CU) behaviors are linked to aggression, behavior problems, and difficulties in peer relationships in children and adolescents. However, few studies have examined whether early childhood CU behaviors predict aggression or peer-rejection during late-childhood or potential moderation of this relationship by executive function. The current study examined whether the interaction of CU behaviors and executive function in early childhood predicted different forms of aggression in late-childhood, including proactive, reactive, and relational aggression, as well as how much children were liked by their peers. Data from cross-informant reports and multiple observational tasks were collected from a high-risk sample (N=240; female=118) at ages 3 and 10 years old. Parent reports of CU behaviors at age 3 predicted teacher reports of reactive, proactive, and relational aggression, as well as lower peer-liking at age 10. Moderation analysis showed that specifically at high levels of CU behaviors and low levels of observed executive function, children were reported by teachers as showing greater reactive and proactive aggression, and were less-liked by peers. Findings demonstrate that early childhood CU behaviors and executive function have unique main and interactive effects on both later aggression and lower peer-liking even when taking into account stability in behavior problems over time. By elucidating how CU behaviors and deficits in executive function potentiate each other during early childhood, we can better characterize the emergence of severe and persistent behavior and interpersonal difficulties across development. PMID:27418255
Early prediction of eruption site using lightning location data: Estimates of accuracy during past eruptions

NASA Astrophysics Data System (ADS)

Nína Petersen, Guðrún; Arason, Þórður; Bjornsson, Halldór

2013-04-01

Eruption of subglacial volcanoes may lead to catastrophic floods and therefore early determination of the exact eruption site may be critical to civil protection evacuation plans. Poor visibility due to weather or darkness often inhibit positive identification of exact eruption location for many hours. However, because of the proximity and abundance of water in powerful subglacial volcanic eruptions, they are probably always accompanied by early lightning activity in the volcanic column. Lightning location systems, designed for weather thunderstorm monitoring, based on remote detection of electromagnetic waves from lightning, can provide valuable real-time information on location of eruption site. Important aspect of such remote detection is its independence of weather, apart from thunderstorms close to the volcano. Individual lightning strikes can be 5-10 km in length and are sometimes tilted and to the side of the volcanic column. This adds to the lightning location uncertainty, which is often a few km. Furthermore, the volcanic column may be swayed by the local wind to one side. Therefore, location of a single lightning can be misleading but by calculating average location of many lightning strikes and applying wind correction a more accurate eruption site location can be obtained. In an effort to assess the expected accuracy, the average lightning locations during the past five volcanic eruptions in Iceland (1998-2011) were compared to the exact site of the eruption vent. Simultaneous weather thunderstorms might have complicated this analysis, but there were no signs of ordinary thunderstorms in Iceland during these eruptions. To identify a suitable wind correction, the vector wind at the 500 hPa pressure level (5-6 km altitude) was compared to mean lightning locations during the eruptions. The essential elements of a system, which predicts the eruption site during the first hour(s) of an eruption, will be described.
Parents' detection of early signs in their children having an autistic spectrum disorder.

PubMed

Sivberg, Bengt

2003-12-01

The study aimed to describe parents' views of their early perception and detection that something was wrong with their child and to give a comprehensive description of early signs to help primary health care nurses to focus on relevant symptoms. Participants were 66 parents from a total of 37 families, a population-based sample from a Swedish county. Interview data were analyzed by manifest content analysis. The results indicated a few critical periods: around the birth, early speech development, and school start. The diagnosis of autistic spectrum disorders was delayed. The parents' reports were congruent with earlier observation studies.
Does Violence in Adolescence Differentially Predict Offending Patterns in Early Adulthood?

PubMed

Cardwell, Stephanie M; Piquero, Alex R

2018-05-01

Previous research is mixed on whether the commission of a violent offense in adolescence is predictive of criminal career characteristics. In the current study, we addressed the following: (a) What factors predict the commission of serious violence in mid-adolescence? and (b) Does involvement in serious violence in mid-adolescence lead to more chronic and/or more heterogeneous patterns of offending in early adulthood? Data were obtained from the Pathways to Desistance Study, a longitudinal study of serious adolescent offenders in Philadelphia, Pennsylvania, and Phoenix, Arizona. Prior arrests, violence exposure, and gang involvement distinguished adolescents who engaged in violence at baseline. A violent offense at baseline was not predictive of a higher frequency of rearrests but was associated with membership in the low offending trajectory. In conclusion, violent offending in adolescence might be a poor predictor of chronic and heterogeneous patterns of offending throughout the life course.
Saliency predicts change detection in pictures of natural scenes.

PubMed

Wright, Michael J

2005-01-01

It has been proposed that the visual system encodes the salience of objects in the visual field in an explicit two-dimensional map that guides visual selective attention. Experiments were conducted to determine whether salience measurements applied to regions of pictures of outdoor scenes could predict the detection of changes in those regions. To obtain a quantitative measure of change detection, observers located changes in pairs of colour pictures presented across an interstimulus interval (ISI). Salience measurements were then obtained from different observers for image change regions using three independent methods, and all were positively correlated with change detection. Factor analysis extracted a single saliency factor that accounted for 62% of the variance contained in the four measures. Finally, estimates of the magnitude of the image change in each picture pair were obtained, using nine separate visual filters representing low-level vision features (luminance, colour, spatial frequency, orientation, edge density). None of the feature outputs was significantly associated with change detection or saliency. On the other hand it was shown that high-level (structural) properties of the changed region were related to saliency and to change detection: objects were more salient than shadows and more detectable when changed.
Early Oscillation Detection for Hybrid DC/DC Converter Fault Diagnosis

NASA Technical Reports Server (NTRS)

Wang, Bright L.

2011-01-01

This paper describes a novel fault detection technique for hybrid DC/DC converter oscillation diagnosis. The technique is based on principles of feedback control loop oscillation and RF signal modulations, and Is realized by using signal spectral analysis. Real-circuit simulation and analytical study reveal critical factors of the oscillation and indicate significant correlations between the spectral analysis method and the gain/phase margin method. A stability diagnosis index (SDI) is developed as a quantitative measure to accurately assign a degree of stability to the DC/DC converter. This technique Is capable of detecting oscillation at an early stage without interfering with DC/DC converter's normal operation and without limitations of probing to the converter.
Prospective assessment of early fetal loss using an immunoenzymometric screening assay for detection of urinary human chorionic gonadotropin.

PubMed

Taylor, C A; Overstreet, J W; Samuels, S J; Boyers, S P; Canfield, R E; O'Connor, J F; Hanson, F W; Lasley, B L

1992-06-01

To develop an economical, nonradiometric immunoenzymometric assay (IEMA) for the detection of urinary human chorionic gonadotropin (hCG) in studies of early fetal loss. To be effective, the IEMA must have a sensitivity equal to the standard immunoradiometric assay (IRMA) and sufficient specificity to eliminate the need for screening most nonconceptive cycles with the expensive and labor-intensive IRMA. Two different assays were used to measure hCG in daily early morning urine samples from potential conceptive cycles. Women undergoing donor artificial insemination (AI) were evaluated in a prospective study. Ninety-two women volunteers were selected on the basis of apparent normal reproductive health. Artificial insemination with nonfrozen donor semen was performed by cervical cup twice each menstrual cycle at 48-hour intervals, and daily urine samples were self-collected throughout the menstrual cycle. An IEMA was developed to detect urinary hCG using the same antibodies as in the standard IRMA; a study was designed to determine whether this nonradiometric assay could successfully detect the early fetal loss that was detected by the IRMA. Of 224 menstrual cycles analyzed by both assays, a total of six early fetal losses were detected by the IRMA. When the tentative screening rule was set to allow all six of these losses and 95% of future losses to be detected by the IEMA, an additional 34 false-positive results were detected by the IEMA. The specificity of the IEMA with this rule was calculated to be 84%. An IEMA based on the same antibodies used for the standard IRMA can serve as an efficient screening assay for the detection of early fetal loss. When the IEMA is used in this manner, nearly 80% of screened menstrual cycles can be eliminated without further testing by the IRMA.
Vital Signs: How Early Can Resident Evaluation Predict Acquisition of Competency in Surgical Pathology?

PubMed Central

Ducatman, Barbara S.; Williams, H. James; Hobbs, Gerald; Gyure, Kymberly A.

2009-01-01

Objectives To determine whether a longitudinal, case-based evaluation system can predict acquisition of competency in surgical pathology and how trainees at risk can be identified early. Design Data were collected for trainee performance on surgical pathology cases (how well their diagnosis agreed with the faculty diagnosis) and compared with training outcomes. Negative training outcomes included failure to complete the residency, failure to pass the anatomic pathology component of the American Board of Pathology examination, and/or failure to obtain or hold a position immediately following training. Findings Thirty-three trainees recorded diagnoses for 54 326 surgical pathology cases, with outcome data available for 15 residents. Mean case-based performance was significantly higher for those with positive outcomes, and outcome status could be predicted as early as postgraduate year-1 (P = .0001). Performance on the first postgraduate year-1 rotation was significantly associated with the outcome (P = .02). Although trainees with unsuccessful outcomes improved their performance more rapidly, they started below residents with successful outcomes and did not make up the difference during training. There was no significant difference in Step 1 or 2 United States Medical Licensing Examination (USMLE) scores when compared with performance or final outcomes (P = .43 and P = .68, respectively) and the resident in-service examination (RISE) had limited predictive ability. Discussion Differences between successful- and unsuccessful-outcome residents were most evident in early residency, ideal for designing interventions or counseling residents to consider another specialty. Conclusion Our longitudinal case-based system successfully identified trainees at risk for failure to acquire critical competencies for surgical pathology early in the program. PMID:21975705
NCI Awards 18 Grants to Continue the Early Detection Research Network (EDRN) Biomarkers Effort | Division of Cancer Prevention

Cancer.gov

The NCI has awarded 18 grants to continue the Early Detection Research Network (EDRN), a national infrastructure that supports the integrated development, validation, and clinical application of biomarkers for the early detection of cancer. The awards fund 7 Biomarker Developmental Laboratories, 8 Clinical Validation Centers, 2 Biomarker Reference Laboratories, and a Data

Method for predicting peptide detection in mass spectrometry

DOEpatents

Kangas, Lars [West Richland, WA; Smith, Richard D [Richland, WA; Petritis, Konstantinos [Richland, WA

2010-07-13

A method of predicting whether a peptide present in a biological sample will be detected by analysis with a mass spectrometer. The method uses at least one mass spectrometer to perform repeated analysis of a sample containing peptides from proteins with known amino acids. The method then generates a data set of peptides identified as contained within the sample by the repeated analysis. The method then calculates the probability that a specific peptide in the data set was detected in the repeated analysis. The method then creates a plurality of vectors, where each vector has a plurality of dimensions, and each dimension represents a property of one or more of the amino acids present in each peptide and adjacent peptides in the data set. Using these vectors, the method then generates an algorithm from the plurality of vectors and the calculated probabilities that specific peptides in the data set were detected in the repeated analysis. The algorithm is thus capable of calculating the probability that a hypothetical peptide represented as a vector will be detected by a mass spectrometry based proteomic platform, given that the peptide is present in a sample introduced into a mass spectrometer.
Future Directions for the Early Detection of Recurrent Breast Cancer

PubMed Central

Schneble, Erika J.; Graham, Lindsey J.; Shupe, Matthew P.; Flynt, Frederick L.; Banks, Kevin P.; Kirkpatrick, Aaron D.; Nissan, Aviram; Henry, Leonard; Stojadinovic, Alexander; Shumway, Nathan M.; Avital, Itzhak; Peoples, George E.; Setlik, Robert F.

2014-01-01

The main goal of follow-up care after breast cancer treatment is the early detection of disease recurrence. In this review, we emphasize the multidisciplinary approach to this continuity of care from surgery, medical oncology, and radiology. Challenges within each setting are briefly addressed as a means of discussion for the future directions of an effective and efficient surveillance plan of post-treatment breast cancer care. PMID:24790657
Early atmospheric detection of carbon dioxide from carbon capture and storage sites

PubMed Central

Pak, Nasrin Mostafavi; Rempillo, Ofelia; Norman, Ann-Lise; Layzell, David B.

2016-01-01

ABSTRACT The early atmospheric detection of carbon dioxide (CO2) leaks from carbon capture and storage (CCS) sites is important both to inform remediation efforts and to build and maintain public support for CCS in mitigating greenhouse gas emissions. A gas analysis system was developed to assess the origin of plumes of air enriched in CO2, as to whether CO2 is from a CCS site or from the oxidation of carbon compounds. The system measured CO2 and O2 concentrations for different plume samples relative to background air and calculated the gas differential concentration ratio (GDCR = −ΔO2/ΔCO2). The experimental results were in good agreement with theoretical calculations that placed GDCR values for a CO2 leak at 0.21, compared with GDCR values of 1–1.8 for the combustion of carbon compounds. Although some combustion plume samples deviated in GDCR from theoretical, the very low GDCR values associated with plumes from CO2 leaks provided confidence that this technology holds promise in providing a tool for the early detection of CO2 leaks from CCS sites. Implications: This work contributes to the development of a cost-effective technology for the early detection of leaks from sites where CO2 has been injected into the subsurface to enhance oil recovery or to permanently store the gas as a strategy for mitigating climate change. Such technology will be important in building public confidence regarding the safety and security of carbon capture and storage sites. PMID:27111469
Early atmospheric detection of carbon dioxide from carbon capture and storage sites.

PubMed

Pak, Nasrin Mostafavi; Rempillo, Ofelia; Norman, Ann-Lise; Layzell, David B

2016-08-01

The early atmospheric detection of carbon dioxide (CO2) leaks from carbon capture and storage (CCS) sites is important both to inform remediation efforts and to build and maintain public support for CCS in mitigating greenhouse gas emissions. A gas analysis system was developed to assess the origin of plumes of air enriched in CO2, as to whether CO2 is from a CCS site or from the oxidation of carbon compounds. The system measured CO2 and O2 concentrations for different plume samples relative to background air and calculated the gas differential concentration ratio (GDCR = -ΔO2/ΔCO2). The experimental results were in good agreement with theoretical calculations that placed GDCR values for a CO2 leak at 0.21, compared with GDCR values of 1-1.8 for the combustion of carbon compounds. Although some combustion plume samples deviated in GDCR from theoretical, the very low GDCR values associated with plumes from CO2 leaks provided confidence that this technology holds promise in providing a tool for the early detection of CO2 leaks from CCS sites. This work contributes to the development of a cost-effective technology for the early detection of leaks from sites where CO2 has been injected into the subsurface to enhance oil recovery or to permanently store the gas as a strategy for mitigating climate change. Such technology will be important in building public confidence regarding the safety and security of carbon capture and storage sites.
Raman spectroscopy and Raman imaging for early detection of cancer

NASA Astrophysics Data System (ADS)

Joshi, Narahari V.; Ortega, Angel; Estrela, Jose Maria

2004-06-01

Raman spectroscopy is a powerful technique as it provides fundamental information about vibrational modes of a system. Eigenvalues of these modes are very sensitive to the strength of the chemical bonds and perturbations caused by the environment, particularly charge distribution and alterations in the dipole strength of the system. All these parameters are profoundly modified during the tumor formation process nad hence Raman technique could be a unique and also a direct approach for evaluating tumor genesis at early stages. for this pupose the present investigation was carried out. We used cultured wild type and c-ras transformed NIH 3T3 fibroblast. The samples were treated with methyl alcohol solution ina conventional manner and then Raman spectra nad images were obtained by a specially developed confocal Raman microscope. The present results reveal differences between both cell types in the spectral details as well as in the morphology. Raman images are able to detect the exact site where cancer-related changes have taken place. These results clearly indicate the superiority of the present technique over conventional methods such as images obtained by X-rays or Nuclear Magnetic Resonance (NMR). Moreover, unlike other approaches, Raman images detect alterations at the submicron level rather than in the centimeter or millimeter range. Being an optical method it can be applied in vivo as a non-invasive technique potentially useful to early detection of cancer (particularly easy accessible cancers such as those of the skin and the digestive tract). The obtained resulsts suggest the great potential of Raman imaging in premature clinical diagnostic approaches.
Oxygen Uptake Efficiency Plateau Best Predicts Early Death in Heart Failure

PubMed Central

Hansen, James E.; Stringer, William W.

2012-01-01

Background: The responses of oxygen uptake efficiency (ie, oxygen uptake/ventilation = V˙o2/V˙e) and its highest plateau (OUEP) during incremental cardiopulmonary exercise testing (CPET) in patients with chronic left heart failure (HF) have not been previously reported. We planned to test the hypothesis that OUEP during CPET is the best single predictor of early death in HF. Methods: We evaluated OUEP, slope of V˙o2 to log(V˙e) (oxygen uptake efficiency slope), oscillatory breathing, and all usual resting and CPET measurements in 508 patients with low-ejection-fraction (< 35%) HF. Each had further evaluations at other sites, including cardiac catheterization. Outcomes were 6-month all-reason mortality and morbidity (death or > 24 h cardiac hospitalization). Statistical analyses included area under curve of receiver operating characteristics, ORs, univariate and multivariate Cox regression, and Kaplan-Meier plots. Results: OUEP, which requires only moderate exercise, was often reduced in patients with HF. A low % predicted OUEP was the single best predictor of mortality (P < .0001), with an OR of 13.0 (P < .001). When combined with oscillatory breathing, the OR increased to 56.3, superior to all other resting or exercise parameters or combinations of parameters. Other statistical analyses and morbidity analysis confirmed those findings. Conclusions: OUEP is often reduced in patients with HF. Low % predicted OUEP (< 65% predicted) is the single best predictor of early death, better than any other CPET or other cardiovascular measurement. Paired with oscillatory breathing, it is even more powerful. PMID:22030802
The Importance of Distinguishing "Propensity" versus "Ability" to Imitate in ASD Research and Early Detection

ERIC Educational Resources Information Center

Vivanti, Giacomo

2015-01-01

Imitation abnormalities are often documented in young children with Autism Spectrum Disorder (ASD), however the relevance of imitation to early development and early detection of ASD remains unclear. Recent studies that investigated whether imitation at 12 months distinguishes children who will subsequently receive an ASD diagnosis from other…
Personality and attention: Levels of neuroticism and extraversion can predict attentional performance during a change detection task.

PubMed

Hahn, Sowon; Buttaccio, Daniel R; Hahn, Jungwon; Lee, Taehun

2015-01-01

The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the Revised Eysenck Personality Questionnaire (EPQ-R). Multiple regression analyses revealed that higher levels of extraversion predict increased change detection accuracies, while higher levels of neuroticism predict decreased change detection accuracies. In addition, neurotic individuals exhibited decreased sensitivity A' and increased fixation dwell times. Hierarchical regression analyses further revealed that eye movement measures mediate the relationship between neuroticism and change detection accuracies. Based on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the relationship between neuroticism and attention.
Early experiences building a software quality prediction model

NASA Technical Reports Server (NTRS)

Agresti, W. W.; Evanco, W. M.; Smith, M. C.

1990-01-01

Early experiences building a software quality prediction model are discussed. The overall research objective is to establish a capability to project a software system's quality from an analysis of its design. The technical approach is to build multivariate models for estimating reliability and maintainability. Data from 21 Ada subsystems were analyzed to test hypotheses about various design structures leading to failure-prone or unmaintainable systems. Current design variables highlight the interconnectivity and visibility of compilation units. Other model variables provide for the effects of reusability and software changes. Reported results are preliminary because additional project data is being obtained and new hypotheses are being developed and tested. Current multivariate regression models are encouraging, explaining 60 to 80 percent of the variation in error density of the subsystems.
77 FR 71193 - Breast and Cervical Cancer Early Detection Federal Advisory Committee

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-29

... DEPARTMENT OF HEALTH AND HUMAN SERVICES Centers for Disease Control and Prevention (CDC) Breast and Cervical Cancer Early Detection Federal Advisory Committee Correction: This notice was published in the Federal Register on November 5, 2012, Volume 77, Number 214, Page 66469. A teleconference line...
Cardiac fibrosis detected by magnetic resonance imaging on predicting time course diversity of left ventricular reverse remodeling in patients with idiopathic dilated cardiomyopathy.

PubMed

Ikeda, Yuki; Inomata, Takayuki; Fujita, Teppei; Iida, Yuichiro; Nabeta, Takeru; Ishii, Shunsuke; Maekawa, Emi; Yanagisawa, Tomoyoshi; Mizutani, Tomohiro; Naruke, Takashi; Koitabashi, Toshimi; Takeuchi, Ichiro; Ako, Junya

2016-11-01

This study aimed to identify the association between the time course of left ventricular reverse remodeling (LVRR) and late gadolinium enhancement in cardiac magnetic resonance imaging (LGE-cMRI) in patients with idiopathic dilated cardiomyopathy (IDCM). We identified 214 IDCM patients treated by optimal pharmacotherapies. LVRR was defined as ≥10 % increment in LV ejection fraction along with ≥10 % reduction in LV end-diastolic dimension. Findings of LGE-cMRI focusing on presence and extent of LGE were evaluated at baseline. Echocardiographic evaluation for detecting LVRR was performed in all patients for 3 years. The primary endpoint was defined as composite events (CEs) including readmission for heart failure, detection of major ventricular arrhythmia, and all-cause mortality. LVRR was found at <1 year in 59 patients (28 %, early responder), ≥1 year in 56 patients (26 %, late responder), and was absent in 99 patients (46 %, non-responder). Multivariate Cox-proportional hazards analysis revealed that both early responders (P = 0.02) and late responders (P < 0.001) had lower incidence of CEs than non-responders. Among 66 subjects (23 %) with complete cMRI evaluation, LGE was detected more often in late and non- than early responders (65, 83 vs. 23 % P < 0.001, respectively), whereas the LGE area was smaller in both early and late than non-responders (2 ± 3, 4 ± 3 vs. 12 ± 10 %, P < 0.001, respectively). In conclusion, evaluating the presence and the extent of LGE is useful for predicting the clinical differences of LVRR time course and subsequent long-term outcomes.
Early Detection of At-Risk Undergraduate Students through Academic Performance Predictors

ERIC Educational Resources Information Center

Rowtho, Vikash

2017-01-01

Undergraduate student dropout is gradually becoming a global problem and the 39 Small Islands Developing States (SIDS) are no exception to this trend. The purpose of this research was to develop a method that can be used for early detection of students who are at-risk of performing poorly in their undergraduate studies. A sample of 279 students…
Enhancing early detection of exotic pests in agricultural and forest ecosystems using an urban-gradient framework.

PubMed

Colunga-Garcia, Manuel; Magarey, Roger A; Haack, Robert A; Gage, Stuart H; Qi, Jiaquo

2010-03-01

Urban areas are hubs of international transport and therefore are major gateways for exotic pests. Applying an urban gradient to analyze this pathway could provide insight into the ecological processes involved in human-mediated invasions. We defined an urban gradient for agricultural and forest ecosystems in the contiguous United States to (1) assess whether ecosystems nearer more urbanized areas were at greater risk of invasion, and (2) apply this knowledge to enhance early detection of exotic pests. We defined the gradient using the tonnage of imported products in adjacent urban areas and their distance to nearby agricultural or forest land. County-level detection reports for 39 exotic agricultural and forest pests of major economic importance were used to characterize invasions along the gradient. We found that counties with more exotic pests were nearer the urban end of the gradient. Assuming that the exotic species we analyzed represent typical invaders, then early detection efforts directed at 21-26% of U.S. agricultural and forest land would likely be able to detect 70% of invaded counties and 90% of the selected species. Applying an urban-gradient framework to current monitoring strategies should enhance early detection efforts of exotic pests, facilitating optimization in allocating resources to areas at greater risk of future invasions.
Long-term predictive models of risk factors for early chronic kidney disease: a longitudinal study.

PubMed

Wu, Wen-Chih; Hsieh, Po-Chien; Hu, Fu-Kang; Kuan, Jen-Chun; Chu, Chi-Ming; Sun, Chien-An; Yang, Tsan; Su, Sui-Lung; Chou, Yu-Ching

2018-04-13

The high incidence and prevalence of chronic kidney disease (CKD) in Taiwan have produced tremendous burdens on health care resources. The work environment of air force special operations personnel engenders high psychological stress, and the resulting increased blood pressure can lead to glomerular hypertension and accelerated glomerular injury in the long term. The aim of the study was to establish the predictive models to define the predictors of CKD. The results indicated that the prevalence of CKD over 4 consecutive years was 3.8%, 9.4%, 9.0%, and 9.4%. The capability of using occult blood in urine to predict the risk of CKD after 1, 2, and 3 years was statistically significant. The age-adjusted odds ratio (OR) and 95% confidence interval (CI) were 7.94 (95% CI: 2.61-24.14), 12.35 (95% CI: 4.02-37.94) and 4.25 (95% CI: 1.32-13.70), respectively. The predictive power of occult blood in urine for the risk of CKD in each model was statistically significant. Future investigations can explore the feasibility of implementing simple and accurate urine dipsticks for preliminary testing besides annual aircrew physical examinations to facilitate early detection and treatment. This study was a longitudinal study, in which air force special operations personnel who received physical examinations at military hospitals between 2004 and 2010 were selected. CKD was determined based on the definition provided by the US National Kidney Foundation. Overall, 212 participants that could be followed continuously for 4 years were analyzed.
Big data analytics for early detection of breast cancer based on machine learning

NASA Astrophysics Data System (ADS)

Ivanova, Desislava

2017-12-01

This paper presents the concept and the modern advances in personalized medicine that rely on technology and review the existing tools for early detection of breast cancer. The breast cancer types and distribution worldwide is discussed. It is spent time to explain the importance of identifying the normality and to specify the main classes in breast cancer, benign or malignant. The main purpose of the paper is to propose a conceptual model for early detection of breast cancer based on machine learning for processing and analysis of medical big dataand further knowledge discovery for personalized treatment. The proposed conceptual model is realized by using Naive Bayes classifier. The software is written in python programming language and for the experiments the Wisconsin breast cancer database is used. Finally, the experimental results are presented and discussed.
Anteroposterior chest radiograph vs. chest CT scan in early detection of pneumothorax in trauma patients.

PubMed

Omar, Hesham R; Mangar, Devanand; Khetarpal, Suneel; Shapiro, David H; Kolla, Jaya; Rashad, Rania; Helal, Engy; Camporesi, Enrico M

2011-09-27

Pneumothorax is a common complication following blunt chest wall trauma. In these patients, because of the restrictions regarding immobilization of the cervical spine, Anteroposterior (AP) chest radiograph is usually the most feasible initial study which is not as sensitive as the erect chest X-ray or CT chest for detection of a pneumothorax. We will present 3 case reports which serve for better understanding of the entity of occult pneumothorax. The first case is an example of a true occult pneumothorax where an initial AP chest X-ray revealed no evidence of pneumothorax and a CT chest immediately performed revealed evidence of pneumothorax. The second case represents an example of a missed rather than a truly occult pneumothorax where the initial chest radiograph revealed clues suggesting the presence of pneumothorax which were missed by the reading radiologist. The third case emphasizes the fact that "occult pneumothorax is predictable". The presence of subcutaneous emphesema and pulmonary contusion should call for further imaging with CT chest to rule out pneumothorax. Thoracic CT scan is therefore the "gold standard" for early detection of a pneumothorax in trauma patients. This report aims to sensitize readers to the entity of occult pneumothorax and create awareness among intensivists and ER physicians regarding the proper diagnosis and management.
Development of a Metabolic Biosignature for Detection of Early Lyme Disease

PubMed Central

Molins, Claudia R.; Ashton, Laura V.; Wormser, Gary P.; Hess, Ann M.; Delorey, Mark J.; Mahapatra, Sebabrata; Schriefer, Martin E.; Belisle, John T.

2015-01-01

Background. Early Lyme disease patients often present to the clinic prior to developing a detectable antibody response to Borrelia burgdorferi, the etiologic agent. Thus, existing 2-tier serology-based assays yield low sensitivities (29%–40%) for early infection. The lack of an accurate laboratory test for early Lyme disease contributes to misconceptions about diagnosis and treatment, and underscores the need for new diagnostic approaches. Methods. Retrospective serum samples from patients with early Lyme disease, other diseases, and healthy controls were analyzed for small molecule metabolites by liquid chromatography-mass spectrometry (LC-MS). A metabolomics data workflow was applied to select a biosignature for classifying early Lyme disease and non-Lyme disease patients. A statistical model of the biosignature was trained using the patients' LC-MS data, and subsequently applied as an experimental diagnostic tool with LC-MS data from additional patient sera. The accuracy of this method was compared with standard 2-tier serology. Results. Metabolic biosignature development selected 95 molecular features that distinguished early Lyme disease patients from healthy controls. Statistical modeling reduced the biosignature to 44 molecular features, and correctly classified early Lyme disease patients and healthy controls with a sensitivity of 88% (84%–95%), and a specificity of 95% (90%–100%). Importantly, the metabolic biosignature correctly classified 77%–95% of the of serology negative Lyme disease patients. Conclusions. The data provide proof-of-concept that metabolic profiling for early Lyme disease can achieve significantly greater (P < .0001) diagnostic sensitivity than current 2-tier serology, while retaining high specificity. PMID:25761869
Enhancing early bladder cancer detection with fluorescence-guided endoscopic optical coherence tomography

NASA Astrophysics Data System (ADS)

Pan, Y. T.; Xie, T. Q.; Du, C. W.; Bastacky, S.; Meyers, S.; Zeidel, M. L.

2003-12-01

We report an experimental study of the possibility of enhancing early bladder cancer diagnosis with fluorescence-image-guided endoscopic optical coherence tomography (OCT). After the intravesical instillation of a 10% solution of 5-aminolevulinic acid, simultaneous fluorescence imaging (excitation of 380-420 nm, emission of 620-700 nm) and OCT are performed on rat bladders to identify the photochemical and morphological changes associated with uroepithelial tumorigenesis. The preliminary results of our ex vivo study reveal that both fluorescence and OCT can identify early uroepithelial cancers, and OCT can detect precancerous lesions (e.g., hyperplasia) that fluorescence may miss. This suggests that a cystoscope combining 5-aminolevulinic acid fluorescence and OCT imaging has the potential to enhance the efficiency and sensitivity of early bladder cancer diagnosis.
A novel multimodal optical imaging system for early detection of oral cancer

PubMed Central

Malik, Bilal H.; Jabbour, Joey M.; Cheng, Shuna; Cuenca, Rodrigo; Cheng, Yi-Shing Lisa; Wright, John M.; Jo, Javier A.; Maitland, Kristen C.

2015-01-01

Objectives Several imaging techniques have been advocated as clinical adjuncts to improve identification of suspicious oral lesions. However, these have not yet shown superior sensitivity or specificity over conventional oral examination techniques. We developed a multimodal, multi-scale optical imaging system that combines macroscopic biochemical imaging of fluorescence lifetime imaging (FLIM) with subcellular morphologic imaging of reflectance confocal microscopy (RCM) for early detection of oral cancer. We tested our system on excised human oral tissues. Study Design A total of four tissue specimen were imaged. These specimens were diagnosed as one each: clinically normal, oral lichen planus, gingival hyperplasia, and superficially-invasive squamous cell carcinoma (SCC). The optical and fluorescence lifetime properties of each specimen were recorded. Results Both quantitative and qualitative differences between normal, benign and SCC lesions can be resolved with FLIM-RCM imaging. The results demonstrate that an integrated approach based on these two methods can potentially enable rapid screening and evaluation of large areas of oral epithelial tissue. Conclusions Early results from ongoing studies of imaging human oral cavity illustrate the synergistic combination of the two modalities. An adjunct device based on such optical characterization of oral mucosa can potentially be used to detect oral carcinogenesis in early stages. PMID:26725720
Nanoparticle-facilitated functional and molecular imaging for the early detection of cancer

PubMed Central

Sivasubramanian, Maharajan; Hsia, Yu; Lo, Leu-Wei

2014-01-01

Cancer detection in its early stages is imperative for effective cancer treatment and patient survival. In recent years, biomedical imaging techniques, such as magnetic resonance imaging, computed tomography and ultrasound have been greatly developed and have served pivotal roles in clinical cancer management. Molecular imaging (MI) is a non-invasive imaging technique that monitors biological processes at the cellular and sub-cellular levels. To achieve these goals, MI uses targeted imaging agents that can bind targets of interest with high specificity and report on associated abnormalities, a task that cannot be performed by conventional imaging techniques. In this respect, MI holds great promise as a potential therapeutic tool for the early diagnosis of cancer. Nevertheless, the clinical applications of targeted imaging agents are limited due to their inability to overcome biological barriers inside the body. The use of nanoparticles has made it possible to overcome these limitations. Hence, nanoparticles have been the subject of a great deal of recent studies. Therefore, developing nanoparticle-based imaging agents that can target tumors via active or passive targeting mechanisms is desirable. This review focuses on the applications of various functionalized nanoparticle-based imaging agents used in MI for the early detection of cancer. PMID:25988156

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