Waist circumference shows the highest predictive value for metabolic syndrome, and waist-to-hip ratio for its components, in Spanish adolescents.

PubMed

Perona, Javier S; Schmidt-RioValle, Jacqueline; Rueda-Medina, Blanca; Correa-Rodríguez, María; González-Jiménez, Emilio

2017-09-01

Both waist circumference (WC) and waist-to-hip ratio (WHR) have been proposed as predictors of metabolic syndrome (MetS) in adolescents, but no consensus has been reached to date. This study hypothesizes that WC provides a greater predictive value for MetS in Spanish adolescents than WHR. A cross-sectional study was performed on 1001 adolescents (13.2 ± 1.2 years) randomly recruited from schools in southeast Spain. Anthropometric measures were correlated with the components of MetS (triglycerides, glucose, blood pressure, and high-density lipoprotein cholesterol) as well as inflammation markers (interleukin-6 and tumor necrosis factor-alpha , C-reactive protein, and ceruloplasmin). Receiver-operator curves were created to determine the predictive value of these variables for MetS. Boys had higher values of all anthropometric parameters compared with girls, but the prevalence of MetS was significantly higher in girls. WHR was the only parameter that correlated significantly with all biochemical and inflammatory variables in boys. In girls, WHR, body mass index, waist-to-height ratio, WC, and body fat percentage correlated only with plasma insulin levels, systolic and diastolic pressures, and ceruloplasmin. In both groups, all anthropometric measures were able to predict MetS (area under the curve > 0.94). In particular, WC was able to predict MetS with area under the curve = 1.00. However, WHR was able to predict a higher number of components of MetS. WHR was the anthropometric index that showed the highest predictive value for MetS components, whereas WC was the one that best predicted the MetS among the population of adolescents studied. These findings justify the need to incorporate WHR and WC determinations into daily clinical practice to predict the MetS. Copyright © 2017 Elsevier Inc. All rights reserved.

Assessment of CAPRI predictions in rounds 3-5 shows progress in docking procedures.

PubMed

Méndez, Raúl; Leplae, Raphaël; Lensink, Marc F; Wodak, Shoshana J

2005-08-01

The current status of docking procedures for predicting protein-protein interactions starting from their three-dimensional (3D) structure is reassessed by evaluating blind predictions, performed during 2003-2004 as part of Rounds 3-5 of the community-wide experiment on Critical Assessment of PRedicted Interactions (CAPRI). Ten newly determined structures of protein-protein complexes were used as targets for these rounds. They comprised 2 enzyme-inhibitor complexes, 2 antigen-antibody complexes, 2 complexes involved in cellular signaling, 2 homo-oligomers, and a complex between 2 components of the bacterial cellulosome. For most targets, the predictors were given the experimental structures of 1 unbound and 1 bound component, with the latter in a random orientation. For some, the structure of the free component was derived from that of a related protein, requiring the use of homology modeling. In some of the targets, significant differences in conformation were displayed between the bound and unbound components, representing a major challenge for the docking procedures. For 1 target, predictions could not go to completion. In total, 1866 predictions submitted by 30 groups were evaluated. Over one-third of these groups applied completely novel docking algorithms and scoring functions, with several of them specifically addressing the challenge of dealing with side-chain and backbone flexibility. The quality of the predicted interactions was evaluated by comparison to the experimental structures of the targets, made available for the evaluation, using the well-agreed-upon criteria used previously. Twenty-four groups, which for the first time included an automatic Web server, produced predictions ranking from acceptable to highly accurate for all targets, including those where the structures of the bound and unbound forms differed substantially. These results and a brief survey of the methods used by participants of CAPRI Rounds 3-5 suggest that genuine progress in the

47 CFR 76.54 - Significantly viewed signals; method to be followed for special showings.

Code of Federal Regulations, 2012 CFR

2012-10-01

... 47 Telecommunication 4 2012-10-01 2012-10-01 false Significantly viewed signals; method to be followed for special showings. 76.54 Section 76.54 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Carriage of Television...

47 CFR 76.54 - Significantly viewed signals; method to be followed for special showings.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 47 Telecommunication 4 2013-10-01 2013-10-01 false Significantly viewed signals; method to be followed for special showings. 76.54 Section 76.54 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Carriage of Television...

47 CFR 76.54 - Significantly viewed signals; method to be followed for special showings.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 47 Telecommunication 4 2014-10-01 2014-10-01 false Significantly viewed signals; method to be followed for special showings. 76.54 Section 76.54 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Carriage of Television...

47 CFR 76.54 - Significantly viewed signals; method to be followed for special showings.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 4 2011-10-01 2011-10-01 false Significantly viewed signals; method to be followed for special showings. 76.54 Section 76.54 Telecommunication FEDERAL COMMUNICATIONS COMMISSION (CONTINUED) BROADCAST RADIO SERVICES MULTICHANNEL VIDEO AND CABLE TELEVISION SERVICE Carriage of Television...

Predicting the Functional Impact of KCNQ1 Variants of Unknown Significance.

PubMed

Li, Bian; Mendenhall, Jeffrey L; Kroncke, Brett M; Taylor, Keenan C; Huang, Hui; Smith, Derek K; Vanoye, Carlos G; Blume, Jeffrey D; George, Alfred L; Sanders, Charles R; Meiler, Jens

2017-10-01

An emerging standard-of-care for long-QT syndrome uses clinical genetic testing to identify genetic variants of the KCNQ1 potassium channel. However, interpreting results from genetic testing is confounded by the presence of variants of unknown significance for which there is inadequate evidence of pathogenicity. In this study, we curated from the literature a high-quality set of 107 functionally characterized KCNQ1 variants. Based on this data set, we completed a detailed quantitative analysis on the sequence conservation patterns of subdomains of KCNQ1 and the distribution of pathogenic variants therein. We found that conserved subdomains generally are critical for channel function and are enriched with dysfunctional variants. Using this experimentally validated data set, we trained a neural network, designated Q1VarPred, specifically for predicting the functional impact of KCNQ1 variants of unknown significance. The estimated predictive performance of Q1VarPred in terms of Matthew's correlation coefficient and area under the receiver operating characteristic curve were 0.581 and 0.884, respectively, superior to the performance of 8 previous methods tested in parallel. Q1VarPred is publicly available as a web server at http://meilerlab.org/q1varpred. Although a plethora of tools are available for making pathogenicity predictions over a genome-wide scale, previous tools fail to perform in a robust manner when applied to KCNQ1. The contrasting and favorable results for Q1VarPred suggest a promising approach, where a machine-learning algorithm is tailored to a specific protein target and trained with a functionally validated data set to calibrate informatics tools. © 2017 American Heart Association, Inc.

PCOS women show significantly higher homocysteine level, independent to glucose and E2 level

PubMed Central

Eskandari, Zahra; Sadrkhanlou, Rajab-Ali; Nejati, Vahid; Tizro, Gholamreza

2016-01-01

Background: It is reasonable to think that some biochemical characteristics of follicular fluid (FF) surrounding the oocyte may play a critical role in determining the quality of oocyte and the subsequent potential needed to achieve fertilization and embryo development. Objective: This study was carried out to evaluate the levels of FF homocysteine (Hcy) in IVF candidate polycystic ovary syndrome (PCOS) women and any relationships with FF glucose and estradiol (E2) levels. Materials and Methods: In this case control study which was performed in Dr. Tizro Day Care and IVF Center 70 infertile patients were enrolled in two groups: comprising 35 PCOS and 35 non PCOS women. Long protocol was performed for all patients. FF Hcy, glucose and E2 levels were analyzed at the time of oocyte retrieval. Results: It was observed that FF Hcy level was significantly higher in PCOS patients compared with non PCOSs (p<0.01). Observations demonstrated that in PCOS group, the Hcy level increased independent to E2, glucose levels, BMI and age, while the PCOS group showed significantly higher BMI compared with non-PCOS group (p=0.03). However, no significant differences were revealed between groups for FF glucose and E2 levels. Conclusion: Present data showed that although FF glucose and E2 levels were constant in PCOS and non PCOS patients, but the FF Hcy levels in PCOS were significantly increased (p=0.01). PMID:27679823

Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

PubMed

Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin

2016-11-01

Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS  = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.

Bilirubin nomogram for prediction of significant hyperbilirubinemia in north Indian neonates.

PubMed

Pathak, Umesh; Chawla, Deepak; Kaur, Saranjit; Jain, Suksham

2013-04-01

(i) To construct hour-specific serum total bilirubin (STB) nomogram in neonates born at =35 weeks of gestation; (ii)To evaluate efficacy of pre-discharge bilirubin measurement in predicting hyperbilirubinemia needing treatment. Diagnostic test performance in a prospective cohort study. Teaching hospital in Northern India. Healthy neonates with gestation =35 weeks or birth weight =2000 g. Serum total bilirubin was measured in all enrolled neonates at 24 ± 6, 72-96 and 96-144 h of postnatal age and when indicated clinically. Neonates were followed up during hospital stay and after discharge till completion of 7th postnatal day. Key outcome was significant hyperbilirubinemia (SHB) defined as need of phototherapy based on modified American Academy of Pediatrics (AAP) guidelines. In neonates born at 38 or more weeks of gestation middle line and in neonates born at 37 or less completed weeks of gestation, lower line of phototherapy thresholds were used to initiate phototherapy. For construction of nomogram, STB values were clubbed in six-hour epochs (age ± 3 hours) for postnatal age up to 48 h and twelve-hour epochs (age ± 6 hours) for age beyond 48 h. Predictive ability of the nomogram was assessed by calculating sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratio, by plotting receiver-operating characteristics (ROC) curve and calculating c-statistic. 997 neonates (birth weight: 2627 ± 536 g, gestation: 37.8 ± 1.5 weeks) were enrolled, of which 931 completed followup. Among enrolled neonates 344 (34.5%) were low birth weight. Rate of exclusive breastfeeding during hospital stay was more than 80%. Bilirubin nomogram was constructed using 40th, 75th and 95th percentile values of hour-specific bilirubin. Pre-discharge STB of =95th percentile was assigned to be in high-risk zone, between 75th and 94th centile in upper-intermediate risk zone, between 40th and 74th centile in lower-intermediate risk zone and below 40th

Echocardiographic parameters predicting acute hemodynamically significant mitral regurgitation during transfemoral transcatheter aortic valve replacement.

PubMed

Ito, Asahiro; Iwata, Shinichi; Mizutani, Kazuki; Nonin, Shinichi; Nishimura, Shinsuke; Takahashi, Yosuke; Yamada, Tokuhiro; Murakami, Takashi; Shibata, Toshihiko; Yoshiyama, Minoru

2018-03-01

Alteration in mitral valve morphology resulting from retrograde stiff wire entanglement sometimes causes hemodynamically significant acute mitral regurgitation (MR) during transfemoral transcatheter aortic valve replacement (TAVR). Little is known about the echocardiographic parameters related to hemodynamically significant acute MR. This study population consisted of 64 consecutive patients who underwent transfemoral TAVR. We defined hemodynamically significant acute MR as changes in the severity of MR with persistent hypotension (systolic blood pressure < 80-90 mm Hg or mean arterial pressure 30 mm Hg lower than baseline). Hemodynamically significant acute MR occurred in 5 cases (7.8%). Smaller left ventricular end-systolic diameter (LVDs), larger ratios of the coiled section of stiff wire tip to LVDs (wire-width/LVDs), and higher Wilkins score were significantly associated with hemodynamically significant acute MR (P < .05), whereas the parameters of functional MR (annular area, anterior-posterior diameter, tenting area, and coaptation length) were not. Moreover, when patients were divided into 4 groups according to wire-width/LVDs and Wilkins score, the group with the larger wire-width/LVDs and higher Wilkins score improved prediction rates (P < .05). Small left ventricle or wire oversizing and calcific mitral apparatus were predictive of hemodynamically significant acute MR. These findings are important for risk stratification, and careful monitoring using intraoperative transesophageal echocardiography may improve the safety in this population. © 2017, Wiley Periodicals, Inc.

Thyroid Gland Involvement in Carcinoma Larynx and Hypopharynx-Predictive Factors and Prognostic Significance.

PubMed

Iype, Elizabeth Mathew; Jagad, Vijay; Nochikattil, Santhosh Kumar; Varghese, Bipin T; Sebastian, Paul

2016-02-01

Intraoperative management of thyroid gland in laryngeal and hypopharyngeal cancer is controversial. The objectives of this study were to determine the incidence of thyroid gland invasion in patients undergoing surgery for laryngeal or hypopharyngeal carcinoma, to assess predictive factors and to assess the prognosis in patients with and without thyroid gland invasion. One hundred and thirty-three patients who underwent surgery for carcinoma larynx and hypopharynx from 2006 to 2010 were reviewed retrospectively. Surgical specimens were examined to determine the incidence of thyroid gland invasion and predictive factors were analysed. The recurrence rate and the survival in patients with and without thyroid gland invasion were also analysed. Out of the 133 patients with carcinoma larynx and hypopharynx who underwent surgery, histological thyroid gland invasion was observed in 28/133 (21%) patients. Significant relationship was found between histological thyroid gland invasion and preoperative evidence of thyroid cartilage erosion by CT scan and also when gross thyroid gland involvement observed during surgery. There is significant association between thyroid gland invasion when there is upper oesophageal or subglottic involvement. After analysing the retrospective data from our study, we would like to suggest that thyroid gland need not be removed routinely in all laryngectomies, unless there is advanced disease with thyroid cartilage erosion and gross thyroid gland involvement or disease with significant subglottic or oesophageal involvement.

Diagnostic Dilemma for Low Viremia with Significant Fibrosis; Is HBV DNA Threshold Level a Good Indicator for Predicting Liver Damage?

PubMed

Yenilmez, Ercan; Çetinkaya, Rıza Aytaç; Tural, Ersin

2018-05-04

The most important difficulties about management of hepatitis B are still determining the liver damage and the right time to start antiviral therapy. To reveal the role of hepatitis B virus DNA threshold level for prediction of liver fibrosis and inflammation in young-aged hepatitis B e antigen negative chronic hepatitis B patients. Diagnostic accuracy study. A total of 273 hepatitis B e antigen negative young chronic hepatitis B patients with any hepatitis B virus DNA levels between 2008 and 2016, who had liver biopsy after at least 6 months follow up period, enrolled in this retrospective study. We created two groups as case and control, cases with hepatitis B virus DNA levels below 2.000 IU/mL and controls with hepatitis B virus DNA levels over 2.000 IU/mL. Having histological activity index ≥4 or/and fibrosis scores ≥2 were defined as significant histological abnormality. Then, we analyzed the relationship between these groups. We showed that significant fibrosis may occur in one third of young chronic hepatitis B patients with low viremia (30.2%, n=42/139 in cases, %55.2, n=74/134 in controls). Among the 42 cases with low viremia and significant fibrosis, 21.4% had alanine aminotransferase level between 40-59 U/L, 42.8% had alanine aminotransferase level between 60-79 U/L, and 35.7% had alanine aminotransferase level over 80 U/L. There was weak correlation between hepatitis B virus DNA threshold level and fibrosis score (p=0.000, rho=0.253). The optimum serum hepatitis B virus DNA threshold level in our study for predicting significant fibrosis was 1293 IU/mL (p=0.00, AUC: 0.657±0.034). The optimum alanine aminotransferase threshold level for predicting significant histological activity index and fibrosis was 64.5 and 59.5 U/L, respectively. The sensitivity and the specificity of 1293 vs 2000 IU/mL hepatitis B virus DNA threshold with 60 U/L alanine aminotransferase threshold level for predicting F≥2 fibrosis score were similar (sensitivity: 0.43 and 0

Fibrillary glomerulonephritis associated with monoclonal gammopathy of undetermined significance showing lambda-type Bence Jones protein.

PubMed

Nagao, Tomoaki; Okura, Takafumi; Miyoshi, Ken-Ichi; Watanabe, Sanae; Manabe, Seiko; Kurata, Mie; Irita, Jun; Fukuoka, Tomikazu; Higaki, Jitsuo

2005-09-01

A 79-year-old woman was admitted to our hospital because of leg edema due to a nephrotic syndrome. Urinary and serum immunoelectrophoresis showed positive for the lambda type of Bence Jones protein. A bone marrow aspiration test revealed mild plasmacytosis (6.4% of the total cells). These findings confirmed her diagnosis of monoclonal gammopathy of undetermined significance (MGUS). Her renal biopsy specimen revealed mild mesangial cell proliferation and an increase in the mesangial matrix. Immunofluorescence studies showed positive staining for IgG, IgA, C3, and kappa and lambda light chains in the capillary wall and mesangium area. Electron microscopy showed that the electron deposits in the thickened basement membrane were formed by randomly arranged 16- to 18-nm nonbranching fibrils. A Congo red stain for amyloid was negative. These findings corresponded with the diagnosis of fibrillary glomerulonephritis. Therefore, this case showed a rare combination of fibrillary glomerulonephritis and MGUS.

Neurons in cat V1 show significant clustering by degree of tuning

PubMed Central

Ziskind, Avi J.; Emondi, Al A.; Kurgansky, Andrei V.; Rebrik, Sergei P.

2015-01-01

Neighboring neurons in cat primary visual cortex (V1) have similar preferred orientation, direction, and spatial frequency. How diverse is their degree of tuning for these properties? To address this, we used single-tetrode recordings to simultaneously isolate multiple cells at single recording sites and record their responses to flashed and drifting gratings of multiple orientations, spatial frequencies, and, for drifting gratings, directions. Orientation tuning width, spatial frequency tuning width, and direction selectivity index (DSI) all showed significant clustering: pairs of neurons recorded at a single site were significantly more similar in each of these properties than pairs of neurons from different recording sites. The strength of the clustering was generally modest. The percent decrease in the median difference between pairs from the same site, relative to pairs from different sites, was as follows: for different measures of orientation tuning width, 29–35% (drifting gratings) or 15–25% (flashed gratings); for DSI, 24%; and for spatial frequency tuning width measured in octaves, 8% (drifting gratings). The clusterings of all of these measures were much weaker than for preferred orientation (68% decrease) but comparable to that seen for preferred spatial frequency in response to drifting gratings (26%). For the above properties, little difference in clustering was seen between simple and complex cells. In studies of spatial frequency tuning to flashed gratings, strong clustering was seen among simple-cell pairs for tuning width (70% decrease) and preferred frequency (71% decrease), whereas no clustering was seen for simple-complex or complex-complex cell pairs. PMID:25652921

Gamma-glutamyl transpeptidase to cholinesterase and platelet ratio in predicting significant liver fibrosis and cirrhosis of chronic hepatitis B.

PubMed

Liu, Danping; Li, Jian; Lu, Wei; Wang, Yanbing; Zhou, Xinlan; Huang, Dan; Li, Xiufen; Ding, Rongrong; Zhang, Zhanqing

2018-06-12

To evaluate the performance of a new mathematical model gamma- glutamyl transpeptidase to cholinesterase and platelet ratio (GCPR) versus gamma- glutamyl transpeptidase to platelet ratio (GPR) in predicting significant fibrosis and cirrhosis of chronic hepatitis B (CHB). A complete cohort of 2343 patients was divided into early and late cohort depending on the time of liver biopsy. With reference to the Scheuer standard, liver pathological stage ≥S2 and ≥S4 were defined as significant fibrosis and cirrhosis, respectively. ROC curve was used to evaluate the performance of investigated models. In early cohort，the areas under ROC curves (AUROCs) of GCPR in predicting significant fibrosis of HBeAg-positive and HBeAg-negative patients (0.782 and 0.775) were both significantly greater than those of GPR (0.748 and 0.747) (Z＝8.198 and Z＝6.023, both P<0.0001); the AUROCs of GCPR in predicting cirrhosis of HBeAg-positive and HBeAg-negative patients (0.842 and 0.861) were both significantly greater than those of GPR (0.802 and 0.823) (Z＝6.686 and Z＝6.116, both P<0.0001). In early, late and complete cohort, using a single cutoff of GPCR>0.080, the specificities of GCPR in predicting significant fibrosis of HBeAg-positive patients were 83.3%, 88.2% and 85.0%, and of HBeAg-negative patients were 87.6%, 87.4% and 87.6%, respectively; and the sensitivities of GCPR in predicting cirrhosis of HBeAg-positive patients were 81.9%, 88.7% and 84.2%, and of HBeAg-negative patients were 83.1%,82.1% and 82.7%, respectively. GCPR has higher performance than GPR in predicting significant fibrosis and cirrhosis of CHB. Copyright © 2018 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Cross-reactivity of steroid hormone immunoassays: clinical significance and two-dimensional molecular similarity prediction

PubMed Central

2014-01-01

Background Immunoassays are widely used in clinical laboratories for measurement of plasma/serum concentrations of steroid hormones such as cortisol and testosterone. Immunoassays can be performed on a variety of standard clinical chemistry analyzers, thus allowing even small clinical laboratories to do analysis on-site. One limitation of steroid hormone immunoassays is interference caused by compounds with structural similarity to the target steroid of the assay. Interfering molecules include structurally related endogenous compounds and their metabolites as well as drugs such as anabolic steroids and synthetic glucocorticoids. Methods Cross-reactivity of a structurally diverse set of compounds were determined for the Roche Diagnostics Elecsys assays for cortisol, dehydroepiandrosterone (DHEA) sulfate, estradiol, progesterone, and testosterone. These data were compared and contrasted to package insert data and published cross-reactivity studies for other marketed steroid hormone immunoassays. Cross-reactivity was computationally predicted using the technique of two-dimensional molecular similarity. Results The Roche Elecsys Cortisol and Testosterone II assays showed a wider range of cross-reactivity than the DHEA sulfate, Estradiol II, and Progesterone II assays. 6-Methylprednisolone and prednisolone showed high cross-reactivity for the cortisol assay, with high likelihood of clinically significant effect for patients administered these drugs. In addition, 21-deoxycortisol likely produces clinically relevant cross-reactivity for cortisol in patients with 21-hydroxylase deficiency, while 11-deoxycortisol may produce clinically relevant cross-reactivity in 11β-hydroxylase deficiency or following metyrapone challenge. Several anabolic steroids may produce clinically significant false positives on the testosterone assay, although interpretation is limited by sparse pharmacokinetic data for some of these drugs. Norethindrone therapy may impact immunoassay measurement

Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System

PubMed Central

Katz, Graham; Summers, Kristen; Ackermann, Chris; Zavorin, Ilya; Lim, Zunsik; Muthiah, Sathappan; Butler, Patrick; Self, Nathan; Zhao, Liang; Lu, Chang-Tien; Khandpur, Rupinder Paul; Fayed, Youssef; Ramakrishnan, Naren

2014-01-01

Abstract Developed under the Intelligence Advanced Research Project Activity Open Source Indicators program, Early Model Based Event Recognition using Surrogates (EMBERS) is a large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed on Amazon Web Services using an entirely automated deployment process. We describe the architecture of the system, some of the design tradeoffs encountered during development, and specifics of the machine learning models underlying EMBERS. We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years. PMID:25553271

Forecasting Significant Societal Events Using The Embers Streaming Predictive Analytics System.

PubMed

Doyle, Andy; Katz, Graham; Summers, Kristen; Ackermann, Chris; Zavorin, Ilya; Lim, Zunsik; Muthiah, Sathappan; Butler, Patrick; Self, Nathan; Zhao, Liang; Lu, Chang-Tien; Khandpur, Rupinder Paul; Fayed, Youssef; Ramakrishnan, Naren

2014-12-01

Developed under the Intelligence Advanced Research Project Activity Open Source Indicators program, Early Model Based Event Recognition using Surrogates (EMBERS) is a large-scale big data analytics system for forecasting significant societal events, such as civil unrest events on the basis of continuous, automated analysis of large volumes of publicly available data. It has been operational since November 2012 and delivers approximately 50 predictions each day for countries of Latin America. EMBERS is built on a streaming, scalable, loosely coupled, shared-nothing architecture using ZeroMQ as its messaging backbone and JSON as its wire data format. It is deployed on Amazon Web Services using an entirely automated deployment process. We describe the architecture of the system, some of the design tradeoffs encountered during development, and specifics of the machine learning models underlying EMBERS. We also present a detailed prospective evaluation of EMBERS in forecasting significant societal events in the past 2 years.

VAN method of short-term earthquake prediction shows promise

NASA Astrophysics Data System (ADS)

Uyeda, Seiya

Although optimism prevailed in the 1970s, the present consensus on earthquake prediction appears to be quite pessimistic. However, short-term prediction based on geoelectric potential monitoring has stood the test of time in Greece for more than a decade [VarotsosandKulhanek, 1993] Lighthill, 1996]. The method used is called the VAN method.The geoelectric potential changes constantly due to causes such as magnetotelluric effects, lightning, rainfall, leakage from manmade sources, and electrochemical instabilities of electrodes. All of this noise must be eliminated before preseismic signals are identified, if they exist at all. The VAN group apparently accomplished this task for the first time. They installed multiple short (100-200m) dipoles with different lengths in both north-south and east-west directions and long (1-10 km) dipoles in appropriate orientations at their stations (one of their mega-stations, Ioannina, for example, now has 137 dipoles in operation) and found that practically all of the noise could be eliminated by applying a set of criteria to the data.

A link prediction approach to cancer drug sensitivity prediction.

PubMed

Turki, Turki; Wei, Zhi

2017-10-03

Predicting the response to a drug for cancer disease patients based on genomic information is an important problem in modern clinical oncology. This problem occurs in part because many available drug sensitivity prediction algorithms do not consider better quality cancer cell lines and the adoption of new feature representations; both lead to the accurate prediction of drug responses. By predicting accurate drug responses to cancer, oncologists gain a more complete understanding of the effective treatments for each patient, which is a core goal in precision medicine. In this paper, we model cancer drug sensitivity as a link prediction, which is shown to be an effective technique. We evaluate our proposed link prediction algorithms and compare them with an existing drug sensitivity prediction approach based on clinical trial data. The experimental results based on the clinical trial data show the stability of our link prediction algorithms, which yield the highest area under the ROC curve (AUC) and are statistically significant. We propose a link prediction approach to obtain new feature representation. Compared with an existing approach, the results show that incorporating the new feature representation to the link prediction algorithms has significantly improved the performance.

Polygenic scores predict alcohol problems in an independent sample and show moderation by the environment.

PubMed

Salvatore, Jessica E; Aliev, Fazil; Edwards, Alexis C; Evans, David M; Macleod, John; Hickman, Matthew; Lewis, Glyn; Kendler, Kenneth S; Loukola, Anu; Korhonen, Tellervo; Latvala, Antti; Rose, Richard J; Kaprio, Jaakko; Dick, Danielle M

2014-04-10

Alcohol problems represent a classic example of a complex behavioral outcome that is likely influenced by many genes of small effect. A polygenic approach, which examines aggregate measured genetic effects, can have predictive power in cases where individual genes or genetic variants do not. In the current study, we first tested whether polygenic risk for alcohol problems-derived from genome-wide association estimates of an alcohol problems factor score from the age 18 assessment of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4304 individuals of European descent; 57% female)-predicted alcohol problems earlier in development (age 14) in an independent sample (FinnTwin12; n = 1162; 53% female). We then tested whether environmental factors (parental knowledge and peer deviance) moderated polygenic risk to predict alcohol problems in the FinnTwin12 sample. We found evidence for both polygenic association and for additive polygene-environment interaction. Higher polygenic scores predicted a greater number of alcohol problems (range of Pearson partial correlations 0.07-0.08, all p-values ≤ 0.01). Moreover, genetic influences were significantly more pronounced under conditions of low parental knowledge or high peer deviance (unstandardized regression coefficients (b), p-values (p), and percent of variance (R2) accounted for by interaction terms: b = 1.54, p = 0.02, R2 = 0.33%; b = 0.94, p = 0.04, R2 = 0.30%, respectively). Supplementary set-based analyses indicated that the individual top single nucleotide polymorphisms (SNPs) contributing to the polygenic scores were not individually enriched for gene-environment interaction. Although the magnitude of the observed effects are small, this study illustrates the usefulness of polygenic approaches for understanding the pathways by which measured genetic predispositions come together with environmental factors to predict complex behavioral outcomes.

Big data integration shows Australian bush-fire frequency is increasing significantly.

PubMed

Dutta, Ritaban; Das, Aruneema; Aryal, Jagannath

2016-02-01

Increasing Australian bush-fire frequencies over the last decade has indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial, temporal and climatic aspects of bush-fire events and provides contextual information to model various climate data for accurately predicting future bush-fire hot spots. In this study, we develop an ensemble method based on a two-layered machine learning model to establish relationship between fire incidence and climatic data. In a 336 week data trial, we demonstrate that the model provides highly accurate bush-fire incidence hot-spot estimation (91% global accuracy) from the weekly climatic surfaces. Our analysis also indicates that Australian weekly bush-fire frequencies increased by 40% over the last 5 years, particularly during summer months, implicating a serious climatic shift.

Big data integration shows Australian bush-fire frequency is increasing significantly

PubMed Central

Dutta, Ritaban; Das, Aruneema; Aryal, Jagannath

2016-01-01

Increasing Australian bush-fire frequencies over the last decade has indicated a major climatic change in coming future. Understanding such climatic change for Australian bush-fire is limited and there is an urgent need of scientific research, which is capable enough to contribute to Australian society. Frequency of bush-fire carries information on spatial, temporal and climatic aspects of bush-fire events and provides contextual information to model various climate data for accurately predicting future bush-fire hot spots. In this study, we develop an ensemble method based on a two-layered machine learning model to establish relationship between fire incidence and climatic data. In a 336 week data trial, we demonstrate that the model provides highly accurate bush-fire incidence hot-spot estimation (91% global accuracy) from the weekly climatic surfaces. Our analysis also indicates that Australian weekly bush-fire frequencies increased by 40% over the last 5 years, particularly during summer months, implicating a serious climatic shift. PMID:26998312

Structural Modification of (-)-Epigallocatechin Gallate (EGCG) Shows Significant Enhancement in Mitochondrial Biogenesis.

PubMed

Ha, Taewoong; Kim, Mi Kyoung; Park, Kwang-Su; Jung, Woong; Choo, Hyunah; Chong, Youhoon

2018-04-18

(-)-Epigallocatechin-3-gallate (EGCG) is known as a mitochondria-targeted molecule that can prevent mitochondrial deterioration and induce mitochondrial biogenesis by modulating key regulators of mitochondrial metabolism. In this study, we tackled whether derivatization of EGCG could result in enhancement of its effects on mitochondrial biogenesis. EGCG, EGCG peracetate (AcEGCG), and its 4″- O-alkyl substituted congeners prepared by previously reported procedures were biologically evaluated. Interestingly, EGCG and AcEGCG were only marginally effective in inducing mitochondrial biogenesis, while AcEGCG congeners with an alkyl group at the 4″- O position showed significantly increased biological activity compared to their parent compound. Among these series, 3f with a methyl-branched carbonate chain at the 4″- O position of the AcEGCG scaffold showed the most enhancement in inducing mitochondrial biogenesis. Hepa1-6 cells treated with 3f exhibited increases in both mitochondrial mass (1.5 times) and relative mtDNA content to nDNA (1.5 times). As a mitochondrial biogenesis enhancer, 3f also increased expression levels of regulators for mitochondrial function, including PGC-1α (4.0 fold), p-AMPK (2.5 fold), SIRT1 (4.2 fold), ERRα (1.8 fold), NRF-1 (1.6 fold), NRF-2 (1.7 fold), and mtTFA (1.6 folds). Investigation of oxidative phosphorylation by mitochondria in the presence of 3f revealed that 3f increased the NAD + /NADH ratio, the amount of cytochrome c, ATP synthesis, and oxygen consumption in Hepa1-6 cells by 2.2, 1.4, 1.5, and 2.1 fold, respectively. Taken together, these results warrant an extensive structure-activity relationship study for EGCG derivatives to develop novel mitochondrial biogenesis enhancers.

Prediction of functionally significant single nucleotide polymorphisms in PTEN tumor suppressor gene: An in silico approach.

PubMed

Khan, Imran; Ansari, Irfan A; Singh, Pratichi; Dass J, Febin Prabhu

2017-09-01

The phosphatase and tensin homolog (PTEN) gene plays a crucial role in signal transduction by negatively regulating the PI3K signaling pathway. It is the most frequent mutated gene in many human-related cancers. Considering its critical role, a functional analysis of missense mutations of PTEN gene was undertaken in this study. Thirty five nonsynonymous single nucleotide polymorphisms (nsSNPs) within the coding region of the PTEN gene were selected for our in silico investigation, and five nsSNPs (G129E, C124R, D252G, H61D, and R130G) were found to be deleterious based on combinatorial predictions of different computational tools. Moreover, molecular dynamics (MD) simulation was performed to investigate the conformational variation between native and all the five mutant PTEN proteins having predicted deleterious nsSNPs. The results of MD simulation of all mutant models illustrated variation in structural attributes such as root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and total energy; which depicts the structural stability of PTEN protein. Furthermore, mutant PTEN protein structures also showed a significant variation in the solvent accessible surface area and hydrogen bond frequencies from the native PTEN structure. In conclusion, results of this study have established the deleterious effect of the all the five predicted nsSNPs on the PTEN protein structure. Thus, results of the current study can pave a new platform to sort out nsSNPs that can be undertaken for the confirmation of their phenotype and their correlation with diseased status in case of control studies. © 2016 International Union of Biochemistry and Molecular Biology, Inc.

Predicting significant torso trauma.

PubMed

Nirula, Ram; Talmor, Daniel; Brasel, Karen

2005-07-01

Identification of motor vehicle crash (MVC) characteristics associated with thoracoabdominal injury would advance the development of automatic crash notification systems (ACNS) by improving triage and response times. Our objective was to determine the relationships between MVC characteristics and thoracoabdominal trauma to develop a torso injury probability model. Drivers involved in crashes from 1993 to 2001 within the National Automotive Sampling System were reviewed. Relationships between torso injury and MVC characteristics were assessed using multivariate logistic regression. Receiver operating characteristic curves were used to compare the model to current ACNS models. There were a total of 56,466 drivers. Age, ejection, braking, avoidance, velocity, restraints, passenger-side impact, rollover, and vehicle weight and type were associated with injury (p < 0.05). The area under the receiver operating characteristic curve (83.9) was significantly greater than current ACNS models. We have developed a thoracoabdominal injury probability model that may improve patient triage when used with ACNS.

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.

Physiologically-based, predictive analytics using the heart-rate-to-Systolic-Ratio significantly improves the timeliness and accuracy of sepsis prediction compared to SIRS.

PubMed

Danner, Omar K; Hendren, Sandra; Santiago, Ethel; Nye, Brittany; Abraham, Prasad

2017-04-01

Enhancing the efficiency of diagnosis and treatment of severe sepsis by using physiologically-based, predictive analytical strategies has not been fully explored. We hypothesize assessment of heart-rate-to-systolic-ratio significantly increases the timeliness and accuracy of sepsis prediction after emergency department (ED) presentation. We evaluated the records of 53,313 ED patients from a large, urban teaching hospital between January and June 2015. The HR-to-systolic ratio was compared to SIRS criteria for sepsis prediction. There were 884 patients with discharge diagnoses of sepsis, severe sepsis, and/or septic shock. Variations in three presenting variables, heart rate, systolic BP and temperature were determined to be primary early predictors of sepsis with a 74% (654/884) accuracy compared to 34% (304/884) using SIRS criteria (p < 0.0001)in confirmed septic patients. Physiologically-based predictive analytics improved the accuracy and expediency of sepsis identification via detection of variations in HR-to-systolic ratio. This approach may lead to earlier sepsis workup and life-saving interventions. Copyright © 2017 Elsevier Inc. All rights reserved.

Significance of worsening renal function and nuclear cardiology for predicting cardiac death in patients with known or suspected coronary artery disease.

PubMed

Yoda, Shunichi; Nakanishi, Kanae; Tano, Ayako; Hori, Yusuke; Suzuki, Yasuyuki; Matsumoto, Naoya; Hirayama, Atsushi

2015-11-01

Estimated glomerular filtration rates (eGFRs) at baseline are useful to determine the severity of renal function and to predict cardiac events. However, no studies aimed to demonstrate significance of eGFRs measured during follow-up and usefulness of combination with nuclear cardiology for prediction of cardiac death in patients with coronary artery disease (CAD). We retrospectively investigated 1739 patients with known/suspected CAD who underwent myocardial perfusion single photon emission computed tomography (SPECT), who had eGFRs measured at baseline and after one year and who underwent a three-year follow-up. The SPECT images were analyzed with the visual scoring model to estimate summed defect scores. Reduction in eGFRs (ΔeGFR) was defined as the difference between eGFRs measured after one year and at baseline. The endpoint of the follow-up was cardiac deaths within three years after the SPECT, which were identified with medical records or responses to posted questionnaires. Cardiac death was observed in 54 of 1739 patients during the follow-up period (45.6±9.1 months). The multivariate Cox regression analysis showed baseline eGFRs, ΔeGFR, and summed stress scores to be significant independent variables for prediction of cardiac death. The area under receiver operating characteristic curves for detection of cardiac death was 0.677 for the baseline eGFR and 0.802 for the follow-up eGFR. Sensitivity of detection of cardiac death was significantly higher in the follow-up eGFR than in the baseline eGFR (p=0.0002). Combination of the best cut-off values, i.e. 9 for the summed stress scores and 10 for the ΔeGFR, which were suggested by receiver operating characteristic analysis, was useful for risk stratification of cardiac death both in patients with and without chronic kidney disease. Baseline and follow-up eGFRs as well as nuclear variables are useful to predict cardiac death in patients with known/suspected CAD. Copyright © 2015 Japanese College of

24-Hour colonic manometry in pediatric slow transit constipation shows significant reductions in antegrade propagation.

PubMed

King, Sebastian K; Catto-Smith, Anthony G; Stanton, Michael P; Sutcliffe, Jonathan R; Simpson, Dianne; Cook, Ian; Dinning, Phil; Hutson, John M; Southwell, Bridget R

2008-08-01

The physiological basis of slow transit constipation (STC) in children remains poorly understood. We wished to examine pan-colonic motility in a group of children with severe chronic constipation refractory to conservative therapy. We performed 24 h pan-colonic manometry in 18 children (13 boys, 11.6 +/- 0.9 yr, range 6.6-18.7 yr) with scintigraphically proven STC. A water-perfused, balloon tipped, 8-channel, silicone catheter with a 7.5 cm intersidehole distance was introduced through a previously formed appendicostomy. Comparison data were obtained from nasocolonic motility studies in 16 healthy young adult controls and per-appendicostomy motility studies in eight constipated children with anorectal retention and/or normal transit on scintigraphy (non-STC). Antegrade propagating sequences (PS) were significantly less frequent (P < 0.01) in subjects with STC (29 +/- 4 per 24 h) compared to adult (53 +/- 4 per 24 h) and non-STC (70 +/- 14 per 24 h) subjects. High amplitude propagating sequences (HAPS) were of a normal frequency in STC subjects. Retrograde propagating sequences were significantly more frequent (P < 0.05) in non-STC subjects compared to STC and adult subjects. High amplitude retrograde propagating sequences were only identified in the STC and non-STC pediatric groups. The normal increase in motility index associated with waking and ingestion of a meal was absent in STC subjects. Prolonged pancolonic manometry in children with STC showed significant impairment in antegrade propagating motor activity and failure to respond to normal physiological stimuli. Despite this, HAPS occurred with normal frequency. These findings suggest significant clinical differences between STC in children and adults.

Recidivism in female offenders: PCL-R lifestyle factor and VRAG show predictive validity in a German sample.

PubMed

Eisenbarth, Hedwig; Osterheider, Michael; Nedopil, Norbert; Stadtland, Cornelis

2012-01-01

A clear and structured approach to evidence-based and gender-specific risk assessment of violence in female offenders is high on political and mental health agendas. However, most data on the factors involved in risk-assessment instruments are based on data of male offenders. The aim of the present study was to validate the use of the Psychopathy Checklist Revised (PCL-R), the HCR-20 and the Violence Risk Appraisal Guide (VRAG) for the prediction of recidivism in German female offenders. This study is part of the Munich Prognosis Project (MPP). It focuses on a subsample of female delinquents (n = 80) who had been referred for forensic-psychiatric evaluation prior to sentencing. The mean time at risk was 8 years (SD = 5 years; range: 1-18 years). During this time, 31% (n = 25) of the female offenders were reconvicted, 5% (n = 4) for violent and 26% (n = 21) for non-violent re-offenses. The predictive validity of the PCL-R for general recidivism was calculated. Analysis with receiver-operating characteristics revealed that the PCL-R total score, the PCL-R antisocial lifestyle factor, the PCL-R lifestyle factor and the PCL-R impulsive and irresponsible behavioral style factor had a moderate predictive validity for general recidivism (area under the curve, AUC = 0.66, p = 0.02). The VRAG has also demonstrated predictive validity (AUC = 0.72, p = 0.02), whereas the HCR-20 showed no predictive validity. These results appear to provide the first evidence that the PCL-R total score and the antisocial lifestyle factor are predictive for general female recidivism, as has been shown consistently for male recidivists. The implications of these findings for crime prevention, prognosis in women, and future research are discussed. Copyright © 2012 John Wiley & Sons, Ltd.

Naproxcinod shows significant advantages over naproxen in the mdx model of Duchenne Muscular Dystrophy.

PubMed

Miglietta, Daniela; De Palma, Clara; Sciorati, Clara; Vergani, Barbara; Pisa, Viviana; Villa, Antonello; Ongini, Ennio; Clementi, Emilio

2015-08-22

In dystrophin-deficient muscles of Duchenne Muscular Dystrophy (DMD) patients and the mdx mouse model, nitric oxide (NO) signalling is impaired. Previous studies have shown that NO-donating drugs are beneficial in dystrophic mouse models. Recently, a long-term treatment (9 months) of mdx mice with naproxcinod, an NO-donating naproxen, has shown a significant improvement of the dystrophic phenotype with beneficial effects present throughout the disease progression. It remains however to be clearly dissected out which specific effects are due to the NO component compared with the anti-inflammatory activity associated with naproxen. Understanding the contribution of NO vs the anti-inflammatory effect is important, in view of the potential therapeutic perspective, and this is the final aim of this study. Five-week-old mdx mice received either naproxcinod (30 mg/kg) or the equimolar dose of naproxen (20 mg/kg) in the diet for 6 months. Control mdx mice were used as reference. Treatments (or vehicle for control groups) were administered daily in the diet. For the first 3 months the study was performed in sedentary animals, then all mice were subjected to exercise until the sixth month. Skeletal muscle force was assessed by measuring whole body tension in sedentary animals as well as in exercised mice and resistance to fatigue was measured after 3 months of running exercise. At the end of 6 months of treatment, animals were sacrificed for histological analysis and measurement of naproxen levels in blood and skeletal muscle. Naproxcinod significantly ameliorated skeletal muscle force and resistance to fatigue in sedentary as well as in exercised mice, reduced inflammatory infiltrates and fibrosis deposition in both cardiac and diaphragm muscles. Conversely, the equimolar dose of naproxen showed no effects on fibrosis and improved muscle function only in sedentary mice, while the beneficial effects in exercised mice were lost demonstrating a limited and short

Motivationally Significant Stimuli Show Visual Prior Entry: Evidence for Attentional Capture

ERIC Educational Resources Information Center

West, Greg L.; Anderson, Adam A. K.; Pratt, Jay

2009-01-01

Previous studies that have found attentional capture effects for stimuli of motivational significance do not directly measure initial attentional deployment, leaving it unclear to what extent these items produce attentional capture. Visual prior entry, as measured by temporal order judgments (TOJs), rests on the premise that allocated attention…

Weather chains during the 2013/2014 winter and their significance for seasonal prediction

NASA Astrophysics Data System (ADS)

Davies, Huw C.

2015-11-01

Day-to-day weather forecasting has improved substantially over the past few decades. In contrast, progress in seasonal prediction outside the tropics has been meagre and mixed. On seasonal timescales, the constraining influence of the initial atmospheric state is weak, and the internal variability associated with transient weather systems tends to be large compared with the nuanced influence of anomalies in external forcing. Current research and operational activities focus on exploring and exploiting potential links between external anomalies and seasonal-mean climate patterns. Here I examine reanalysed meteorological data sets for the unusual winter 2013/2014, with drought and freezing conditions juxtaposed over North America and severe wet and stormy weather over parts of Europe, to study the role of weather systems and their transient upper-tropospheric flow patterns. I find that the amplitude, recurrence and location of these transient patterns account directly for the corresponding anomalous seasonal-mean patterns. They occurred episodically and sequentially, were linked dynamically, and exhibited some circumpolar connectivity. I conclude that the upper-tropospheric components of transient weather systems are significant for understanding and predicting seasonal weather patterns, whereas the role of external factors is more subtle.

Linking Compositional and Functional Predictions to Decipher the Biogeochemical Significance in DFAA Turnover of Abundant Bacterioplankton Lineages in the North Sea.

PubMed

Wemheuer, Bernd; Wemheuer, Franziska; Meier, Dimitri; Billerbeck, Sara; Giebel, Helge-Ansgar; Simon, Meinhard; Scherber, Christoph; Daniel, Rolf

2017-11-05

Deciphering the ecological traits of abundant marine bacteria is a major challenge in marine microbial ecology. In the current study, we linked compositional and functional predictions to elucidate such traits for abundant bacterioplankton lineages in the North Sea. For this purpose, we investigated entire and active bacterioplankton composition along a transect ranging from the German Bight to the northern North Sea by pyrotag sequencing of bacterial 16S rRNA genes and transcripts. Functional profiles were inferred from 16S rRNA data using Tax4Fun. Bacterioplankton communities were dominated by well-known marine lineages including clusters/genera that are affiliated with the Roseobacter group and the Flavobacteria . Variations in community composition and function were significantly explained by measured environmental and microbial properties. Turnover of dissolved free amino acids (DFAA) showed the strongest correlation to community composition and function. We applied multinomial models, which enabled us to identify bacterial lineages involved in DFAA turnover. For instance, the genus Planktomarina was more abundant at higher DFAA turnover rates, suggesting its vital role in amino acid degradation. Functional predictions further indicated that Planktomarina is involved in leucine and isoleucine degradation. Overall, our results provide novel insights into the biogeochemical significance of abundant bacterioplankton lineages in the North Sea.

Analytic Methods for Predicting Significant Multi-Quanta Effects in Collisional Molecular Energy Transfer

NASA Technical Reports Server (NTRS)

Bieniek, Ronald J.

1996-01-01

Collision-induced transitions can significantly affect molecular vibrational-rotational populations and energy transfer in atmospheres and gaseous systems. This, in turn. can strongly influence convective heat transfer through dissociation and recombination of diatomics. and radiative heat transfer due to strong vibrational coupling. It is necessary to know state-to-state rates to predict engine performance and aerothermodynamic behavior of hypersonic flows, to analyze diagnostic radiative data obtained from experimental test facilities, and to design heat shields and other thermal protective systems. Furthermore, transfer rates between vibrational and translational modes can strongly influence energy flow in various 'disturbed' environments, particularly where the vibrational and translational temperatures are not equilibrated.

Amnesic patients show superior generalization in category learning.

PubMed

O'Connell, Garret; Myers, Catherine E; Hopkins, Ramona O; McLaren, R P; Gluck, Mark A; Wills, Andy J

2016-11-01

Generalization is the application of existing knowledge to novel situations. Questions remain about the precise role of the hippocampus in this facet of learning, but a connectionist model by Gluck and Myers (1993) predicts that generalization should be enhanced following hippocampal damage. In a two-category learning task, a group of amnesic patients (n = 9) learned the training items to a similar level of accuracy as matched controls (n = 9). Both groups then classified new items at various levels of distortion. The amnesic group showed significantly more accurate generalization to high-distortion novel items, a difference also present compared to a larger group of unmatched controls (n = 33). The model prediction of a broadening of generalization gradients in amnesia, at least for items near category boundaries, was supported by the results. Our study shows for the first time that amnesia can sometimes improve generalization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Prediction of HIV-1 sensitivity to broadly neutralizing antibodies shows a trend towards resistance over time.

PubMed

Hake, Anna; Pfeifer, Nico

2017-10-01

Treatment with broadly neutralizing antibodies (bNAbs) has proven effective against HIV-1 infections in humanized mice, non-human primates, and humans. Due to the high mutation rate of HIV-1, resistance testing of the patient's viral strains to the bNAbs is still inevitable. So far, bNAb resistance can only be tested in expensive and time-consuming neutralization experiments. Here, we introduce well-performing computational models that predict the neutralization response of HIV-1 to bNAbs given only the envelope sequence of the virus. Using non-linear support vector machines based on a string kernel, the models learnt even the important binding sites of bNAbs with more complex epitopes, i.e., the CD4 binding site targeting bNAbs, proving thereby the biological relevance of the models. To increase the interpretability of the models, we additionally provide a new kind of motif logo for each query sequence, visualizing those residues of the test sequence that influenced the prediction outcome the most. Moreover, we predicted the neutralization sensitivity of around 34,000 HIV-1 samples from different time points to a broad range of bNAbs, enabling the first analysis of HIV resistance to bNAbs on a global scale. The analysis showed for many of the bNAbs a trend towards antibody resistance over time, which had previously only been discovered for a small non-representative subset of the global HIV-1 population.

Prediction of HIV-1 sensitivity to broadly neutralizing antibodies shows a trend towards resistance over time

PubMed Central

2017-01-01

Treatment with broadly neutralizing antibodies (bNAbs) has proven effective against HIV-1 infections in humanized mice, non-human primates, and humans. Due to the high mutation rate of HIV-1, resistance testing of the patient’s viral strains to the bNAbs is still inevitable. So far, bNAb resistance can only be tested in expensive and time-consuming neutralization experiments. Here, we introduce well-performing computational models that predict the neutralization response of HIV-1 to bNAbs given only the envelope sequence of the virus. Using non-linear support vector machines based on a string kernel, the models learnt even the important binding sites of bNAbs with more complex epitopes, i.e., the CD4 binding site targeting bNAbs, proving thereby the biological relevance of the models. To increase the interpretability of the models, we additionally provide a new kind of motif logo for each query sequence, visualizing those residues of the test sequence that influenced the prediction outcome the most. Moreover, we predicted the neutralization sensitivity of around 34,000 HIV-1 samples from different time points to a broad range of bNAbs, enabling the first analysis of HIV resistance to bNAbs on a global scale. The analysis showed for many of the bNAbs a trend towards antibody resistance over time, which had previously only been discovered for a small non-representative subset of the global HIV-1 population. PMID:29065122

Diagnostic value of thallium-201 myocardial perfusion IQ-SPECT without and with computed tomography-based attenuation correction to predict clinically significant and insignificant fractional flow reserve

PubMed Central

Tanaka, Haruki; Takahashi, Teruyuki; Ohashi, Norihiko; Tanaka, Koichi; Okada, Takenori; Kihara, Yasuki

2017-01-01

Abstract The aim of this study was to clarify the predictive value of fractional flow reserve (FFR) determined by myocardial perfusion imaging (MPI) using thallium (Tl)-201 IQ-SPECT without and with computed tomography-based attenuation correction (CT-AC) for patients with stable coronary artery disease (CAD). We assessed 212 angiographically identified diseased vessels using adenosine-stress Tl-201 MPI-IQ-SPECT/CT in 84 consecutive, prospectively identified patients with stable CAD. We compared the FFR in 136 of the 212 diseased vessels using visual semiquantitative interpretations of corresponding territories on MPI-IQ-SPECT images without and with CT-AC. FFR inversely correlated most accurately with regional summed difference scores (rSDS) in images without and with CT-AC (r = −0.584 and r = −0.568, respectively, both P < .001). Receiver-operating characteristics analyses using rSDS revealed an optimal FFR cut-off of <0.80 without and with CT-AC. Although the diagnostic accuracy of FFR <0.80 did not significantly differ, FFR ≥0.82 was significantly more accurate with, than without CT-AC. Regions with rSDS ≥2 without or with CT-AC predicted FFR <0.80, and those with rSDS ≤1 without and with CT-AC predicted FFR ≥0.81, with 73% and 83% sensitivity, 84% and 67% specificity, and 79% and 75% accuracy, respectively. Although limited by the sample size and the single-center design, these findings showed that the IQ-SPECT system can predict FFR at an optimal cut-off of <0.80, and we propose a novel application of CT-AC to MPI-IQ-SPECT for predicting clinically significant and insignificant FFR even in nonobese patients. PMID:29390486

Neuromusculoskeletal Model Calibration Significantly Affects Predicted Knee Contact Forces for Walking

PubMed Central

Serrancolí, Gil; Kinney, Allison L.; Fregly, Benjamin J.; Font-Llagunes, Josep M.

2016-01-01

Though walking impairments are prevalent in society, clinical treatments are often ineffective at restoring lost function. For this reason, researchers have begun to explore the use of patient-specific computational walking models to develop more effective treatments. However, the accuracy with which models can predict internal body forces in muscles and across joints depends on how well relevant model parameter values can be calibrated for the patient. This study investigated how knowledge of internal knee contact forces affects calibration of neuromusculoskeletal model parameter values and subsequent prediction of internal knee contact and leg muscle forces during walking. Model calibration was performed using a novel two-level optimization procedure applied to six normal walking trials from the Fourth Grand Challenge Competition to Predict In Vivo Knee Loads. The outer-level optimization adjusted time-invariant model parameter values to minimize passive muscle forces, reserve actuator moments, and model parameter value changes with (Approach A) and without (Approach B) tracking of experimental knee contact forces. Using the current guess for model parameter values but no knee contact force information, the inner-level optimization predicted time-varying muscle activations that were close to experimental muscle synergy patterns and consistent with the experimental inverse dynamic loads (both approaches). For all the six gait trials, Approach A predicted knee contact forces with high accuracy for both compartments (average correlation coefficient r = 0.99 and root mean square error (RMSE) = 52.6 N medial; average r = 0.95 and RMSE = 56.6 N lateral). In contrast, Approach B overpredicted contact force magnitude for both compartments (average RMSE = 323 N medial and 348 N lateral) and poorly matched contact force shape for the lateral compartment (average r = 0.90 medial and −0.10 lateral). Approach B had statistically higher

Tropical forecasting - Predictability perspective

NASA Technical Reports Server (NTRS)

Shukla, J.

1989-01-01

Results are presented of classical predictability studies and forecast experiments with observed initial conditions to show the nature of initial error growth and final error equilibration for the tropics and midlatitudes, separately. It is found that the theoretical upper limit of tropical circulation predictability is far less than for midlatitudes. The error growth for a complete general circulation model is compared to a dry version of the same model in which there is no prognostic equation for moisture, and diabatic heat sources are prescribed. It is found that the growth rate of synoptic-scale errors for the dry model is significantly smaller than for the moist model, suggesting that the interactions between dynamics and moist processes are among the important causes of atmospheric flow predictability degradation. Results are then presented of numerical experiments showing that correct specification of the slowly varying boundary condition of SST produces significant improvement in the prediction of time-averaged circulation and rainfall over the tropics.

The Enduring Predictive Significance of Early Maternal Sensitivity: Social and Academic Competence through Age 32 Years

ERIC Educational Resources Information Center

Raby, K. Lee; Roisman, Glenn I.; Fraley, R. Chris; Simpson, Jeffry A.

2015-01-01

This study leveraged data from the Minnesota Longitudinal Study of Risk and Adaptation (N = 243) to investigate the predictive significance of maternal sensitivity during the first 3 years of life for social and academic competence through age 32 years. Structural model comparisons replicated previous findings that early maternal sensitivity…

Spatially resolved flux measurements of NOx from London suggest significantly higher emissions than predicted by inventories.

PubMed

Vaughan, Adam R; Lee, James D; Misztal, Pawel K; Metzger, Stefan; Shaw, Marvin D; Lewis, Alastair C; Purvis, Ruth M; Carslaw, David C; Goldstein, Allen H; Hewitt, C Nicholas; Davison, Brian; Beevers, Sean D; Karl, Thomas G

2016-07-18

To date, direct validation of city-wide emissions inventories for air pollutants has been difficult or impossible. However, recent technological innovations now allow direct measurement of pollutant fluxes from cities, for comparison with emissions inventories, which are themselves commonly used for prediction of current and future air quality and to help guide abatement strategies. Fluxes of NOx were measured using the eddy-covariance technique from an aircraft flying at low altitude over London. The highest fluxes were observed over central London, with lower fluxes measured in suburban areas. A footprint model was used to estimate the spatial area from which the measured emissions occurred. This allowed comparison of the flux measurements to the UK's National Atmospheric Emissions Inventory (NAEI) for NOx, with scaling factors used to account for the actual time of day, day of week and month of year of the measurement. The comparison suggests significant underestimation of NOx emissions in London by the NAEI, mainly due to its under-representation of real world road traffic emissions. A comparison was also carried out with an enhanced version of the inventory using real world driving emission factors and road measurement data taken from the London Atmospheric Emissions Inventory (LAEI). The measurement to inventory agreement was substantially improved using the enhanced version, showing the importance of fully accounting for road traffic, which is the dominant NOx emission source in London. In central London there was still an underestimation by the inventory of 30-40% compared with flux measurements, suggesting significant improvements are still required in the NOx emissions inventory.

The Prognostic Significance of Sentinel Lymph Node Status for Patients with Thick Melanoma.

PubMed

Bello, Danielle M; Han, Gang; Jackson, Laura; Bulloch, Kaleigh; Ariyan, Stephan; Narayan, Deepak; Rothberg, Bonnie Gould; Han, Dale

2016-12-01

Sentinel lymph node biopsy (SLNB) is recommended for patients with intermediate-thickness melanoma, but the use of SLNB for patients with thick melanoma is debated. This report presents a single-institution study investigating factors predictive of sentinel lymph node (SLN) metastasis and outcome for thick-melanoma patients . A retrospective review of a single-institution database from 1997 to 2012 identified 147 patients with thick primary cutaneous melanoma (≥4 mm) who had an SLNB. Clinicopathologic characteristics were correlated with nodal status and outcome. The median age of the patients was 67 years, and 61.9 % of the patients were men. The median tumor thickness was 5.5 mm, and 54 patients (36.7 %) had a positive SLN. Multivariable analysis showed that only tumor thickness significantly predicted SLN metastasis (odds ratio 1.14; 95 % confidence interval (CI) 1.02-1.28; P = 0.02). The overall median follow-up period was 34.6 months. Overall survival (OS) and melanoma-specific survival (MSS) were significantly worse for the positive versus negative-SLN patients. Multivariable analysis showed that age [hazard ratio (HR) 1.04; 95 % CI 1.01-1.07; P = 0.02] and SLN status (HR 2.24; 95 % CI 1.03-4.88; P = 0.04) significantly predicted OS, whereas only SLN status (HR 3.85; 95 % CI 2.13-6.97; P < 0.01) significantly predicted MSS. Tumor thickness predicts SLN status in thick melanomas. Furthermore, SLN status is prognostic for OS and MSS in thick-melanoma patients, with positive-SLN patients having significantly worse OS and MSS. These findings show that SLNB should be recommended for thick-melanoma patients, particularly because detection of SLN metastasis can identify patients for potential systemic therapy and treatment of nodal disease at a microscopic stage.

Whole genome prediction and heritability of childhood asthma phenotypes.

PubMed

McGeachie, Michael J; Clemmer, George L; Croteau-Chonka, Damien C; Castaldi, Peter J; Cho, Michael H; Sordillo, Joanne E; Lasky-Su, Jessica A; Raby, Benjamin A; Tantisira, Kelan G; Weiss, Scott T

2016-12-01

While whole genome prediction (WGP) methods have recently demonstrated successes in the prediction of complex genetic diseases, they have not yet been applied to asthma and related phenotypes. Longitudinal patterns of lung function differ between asthmatics, but these phenotypes have not been assessed for heritability or predictive ability. Herein, we assess the heritability and genetic predictability of asthma-related phenotypes. We applied several WGP methods to a well-phenotyped cohort of 832 children with mild-to-moderate asthma from CAMP. We assessed narrow-sense heritability and predictability for airway hyperresponsiveness, serum immunoglobulin E, blood eosinophil count, pre- and post-bronchodilator forced expiratory volume in 1 sec (FEV 1 ), bronchodilator response, steroid responsiveness, and longitudinal patterns of lung function (normal growth, reduced growth, early decline, and their combinations). Prediction accuracy was evaluated using a training/testing set split of the cohort. We found that longitudinal lung function phenotypes demonstrated significant narrow-sense heritability (reduced growth, 95%; normal growth with early decline, 55%). These same phenotypes also showed significant polygenic prediction (areas under the curve [AUCs] 56% to 62%). Including additional demographic covariates in the models increased prediction 4-8%, with reduced growth increasing from 62% to 66% AUC. We found that prediction with a genomic relatedness matrix was improved by filtering available SNPs based on chromatin evidence, and this result extended across cohorts. Longitudinal reduced lung function growth displayed extremely high heritability. All phenotypes with significant heritability showed significant polygenic prediction. Using SNP-prioritization increased prediction across cohorts. WGP methods show promise in predicting asthma-related heritable traits.

Children's Understanding of Showing Off.

ERIC Educational Resources Information Center

Bennett, Mark; Yeeles, Caroline

1990-01-01

Interviews 46 British children, ages 8 to 11, to test their understanding of showing off. Confirms prediction that younger childrens' understanding of motivation for showing off is based on psychological determinants and that 11-year-olds' understanding focuses on interpersonal determinants. Also discusses children's understanding of emotional…

Why significant variables aren't automatically good predictors.

PubMed

Lo, Adeline; Chernoff, Herman; Zheng, Tian; Lo, Shaw-Hwa

2015-11-10

Thus far, genome-wide association studies (GWAS) have been disappointing in the inability of investigators to use the results of identified, statistically significant variants in complex diseases to make predictions useful for personalized medicine. Why are significant variables not leading to good prediction of outcomes? We point out that this problem is prevalent in simple as well as complex data, in the sciences as well as the social sciences. We offer a brief explanation and some statistical insights on why higher significance cannot automatically imply stronger predictivity and illustrate through simulations and a real breast cancer example. We also demonstrate that highly predictive variables do not necessarily appear as highly significant, thus evading the researcher using significance-based methods. We point out that what makes variables good for prediction versus significance depends on different properties of the underlying distributions. If prediction is the goal, we must lay aside significance as the only selection standard. We suggest that progress in prediction requires efforts toward a new research agenda of searching for a novel criterion to retrieve highly predictive variables rather than highly significant variables. We offer an alternative approach that was not designed for significance, the partition retention method, which was very effective predicting on a long-studied breast cancer data set, by reducing the classification error rate from 30% to 8%.

How useful are ARFI elastography cut-off values proposed by meta-analysis for predicting the significant fibrosis and compensated liver cirrhosis?

PubMed

Bota, Simona; Sporea, Ioan; Sirli, Roxana; Popescu, Alina; Gradinaru-Tascau, Oana

2015-06-01

To evaluate how often do we "miss" chronic hepatitis C patients with at least significant fibrosis (F>/=2) and those with compensated cirrhosis, by using Acoustic Radiation Force Impulse (ARFI) elastography cut-off values proposed by meta-analysis. Our study included 132 patients with chronic hepatitis C, evaluated by means of ARFI and liver biopsy (LB), in the same session. Reliable measurements were defined as: median value of 10 liver stiffness (LS) measurements with a success rate>/=60% and an interquartile range interval<30%. For predicting F>/=2 and F=4 we used the LS cut-offs proposed in the last published meta-analysis: 1.35 m/s and 1.87 m/s, respectively. Reliable LS measurements by means of ARFI were obtained in 117 patients (87.9%). In our study, 58 patients (49.6%) had LS values <1.35 m/s; from these 75.8% had F>/=2 in LB. From the 59 patients (50.4%) with LS values>/=1.35 m/s, only 6.8% had F0 or F1 in LB. Also, in our study, 88 patients (75.3%) had LS values <1.87 m/s; from these only 2.2 % had F4 in LB. From the 29 patients (24.7%) with LS values>/=1.87 m/s, 41.3% had F4 in LB. Both for prediction of at least significant fibrosis and liver cirrhosis, higher aminotransferases levels were associated with wrongly classified patients, in univariate and multivariate analysis. ARFI elastography had a very good positive predictive value (93.2%) for predicting the presence of significant fibrosis and excellent negative predictive value (97.8%) for excluding the presence of compensated liver cirrhosis.

Addendum to the article: Misuse of null hypothesis significance testing: Would estimation of positive and negative predictive values improve certainty of chemical risk assessment?

PubMed

Bundschuh, Mirco; Newman, Michael C; Zubrod, Jochen P; Seitz, Frank; Rosenfeldt, Ricki R; Schulz, Ralf

2015-03-01

We argued recently that the positive predictive value (PPV) and the negative predictive value (NPV) are valuable metrics to include during null hypothesis significance testing: They inform the researcher about the probability of statistically significant and non-significant test outcomes actually being true. Although commonly misunderstood, a reported p value estimates only the probability of obtaining the results or more extreme results if the null hypothesis of no effect was true. Calculations of the more informative PPV and NPV require a priori estimate of the probability (R). The present document discusses challenges of estimating R.

Carotid plaque-thickness and common carotid IMT show additive value in cardiovascular risk prediction and reclassification.

PubMed

Amato, Mauro; Veglia, Fabrizio; de Faire, Ulf; Giral, Philippe; Rauramaa, Rainer; Smit, Andries J; Kurl, Sudhir; Ravani, Alessio; Frigerio, Beatrice; Sansaro, Daniela; Bonomi, Alice; Tedesco, Calogero C; Castelnuovo, Samuela; Mannarino, Elmo; Humphries, Steve E; Hamsten, Anders; Tremoli, Elena; Baldassarre, Damiano

2017-08-01

Carotid plaque size and the mean common carotid intima-media thickness measured in plaque-free areas (PF CC-IMT mean ) have been identified as predictors of vascular events (VEs), but their complementarity in risk prediction and stratification is still unresolved. The aim of this study was to evaluate the independence of carotid plaque thickness and PF CC-IMT mean in cardiovascular risk prediction and risk stratification. The IMPROVE-study is a European cohort (n = 3703), where the thickness of the largest plaque detected in the whole carotid tree was indexed as cIMT max . PF CC-IMT mean was also assessed. Hazard Ratios (HR) comparing the top quartiles of cIMT max and PF CC-IMT mean versus their respective 1-3 quartiles were calculated using Cox regression. After a 36.2-month follow-up, there were 215 VEs (125 coronary, 73 cerebral and 17 peripheral). Both cIMT max and PF CC-IMT mean were mutually independent predictors of combined-VEs, after adjustment for center, age, sex, risk factors and pharmacological treatment [HR (95% CI) = 1.98 (1.47, 2.67) and 1.68 (1.23, 2.29), respectively]. Both variables were independent predictors of cerebrovascular events (ischemic stroke, transient ischemic attack), while only cIMT max was an independent predictor of coronary events (myocardial infarction, sudden cardiac death, angina pectoris, angioplasty, coronary bypass grafting). In reclassification analyses, PF CC-IMT mean significantly adds to a model including both Framingham Risk Factors and cIMT max (Integrated Discrimination Improvement; IDI = 0.009; p = 0.0001) and vice-versa (IDI = 0.02; p < 0.0001). cIMT max and PF CC-IMT mean are independent predictors of VEs, and as such, they should be used as additive rather than alternative variables in models for cardiovascular risk prediction and reclassification. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

The significance of tumor heterogeneity for prediction of DNA ploidy of prostate cancer.

PubMed

Häggarth, Lars; Auer, Gert; Busch, Christer; Norberg, Mona; Häggman, Michael; Egevad, Lars

2005-01-01

In a previous study, we mapped the ploidy heterogeneity of prostate cancer using flow cytometry in 676 tumor samples from 50 radical prostatectomy specimens. Ploidy heterogeneity was common (42% of tumors) and was found in all non-diploid tumors. The volume of non-diploid tumor was estimated and found to predict extra-prostatic extension and seminal vesicle invasion. The aim of this study was to evaluate the impact of tumor heterogeneity on preoperative ploidy assessment. In 50 men at least six core biopsies were taken before prostatectomy. Sections from biopsies with cancer were Feulgen-stained for image cytometry. After exclusion of biopsies with insufficient material, 123 histograms from 48 men (mean 2.6; range 1-7) remained for analysis. In 32 men, biopsies were diploid. In 16 men, at least one biopsy was non-diploid (14 tetraploid, two aneuploid) and 10 of them also had diploid biopsies. In 34 men (71%), the prostatectomy specimens were correctly predicted as being either diploid (48%) or non-diploid (23%). The sensitivity and specificity of biopsies for predicting non-diploid cancer were 55% and 82%, respectively, and the positive and negative predictive values were 69% and 72%, respectively. The ploidy status of tumors with and without ploidy heterogeneity was correctly predicted in 55% and 82% of cases, respectively (p=0.04). Biopsies underestimated ploidy in 9/20 tumors (45%) with heterogeneous ploidy status. Underestimation mainly occurred when one or two cores were analyzed. Preoperative prediction of the ploidy status of prostate cancer is hampered by tumor heterogeneity. Analysis of multiple biopsies is important for correct preoperative ploidy estimation.

Are different cut-off values of liver stiffness assessed by transient elastography according to the etiology of liver cirrhosis for predicting significant esophageal varices?

PubMed

Sporea, Ioan; Raţiu, Iulia; Bota, Simona; Şirli, Roxana; Jurchiş, Ana

2013-06-01

To determine if liver stiffness (LS) measurements by means of Transient Elastography (TE) vary according to the etiology of the underlying liver cirrhosis and to find if there are different TE cut-off values able to predict the presence of significant EV in alcoholic vs. viral etiology of cirrhosis. This retrospective study included patients diagnosed with liver cirrhosis of viral or alcoholic etiology. All patients were evaluated by means of TE (FibroScan) and upper gastrointestinal endoscopy. We performed 10 LS measurements in each patient and a median value expressed in kiloPascals (kPa) was calculated. Only those with a SR >/= 60% and an IQR<30% were considered as reliable MS measurements. According to the presence of EV the patients were divided in two categories: without significant EV and patients with significant EV (at least grade 2). The study included 697 cirrhotic patients with reliable LS measurements. The median LS values assessed by TE were significantly higher in cirrhotic patients with alcoholic etiology as compared with those with viral etiology of liver disease: 41 kPa vs. 21.1 kPa, p<0.0001. In the entire cohort of cirrhotic patients, LS assessed by means of TE for a cut-off value >29.5 kPa, had 77.5% sensitivity and 86.9% specificity for predicting the presence of significant EV (AUROC=0.871). The best LS cut-off value for predicting the presence of significant EV was higher in alcoholic cirrhosis as compared with those with viral etiology of liver cirrhosis: 32.5 kPa (AUROC=0.836) vs. 24.8 kPa (AUROC=0.867). LS cut-off values assessed by TE for predicting significant EV are significantly higher in patients with alcoholic cirrhosis as compared with patients with liver cirrhosis of viral etiology.

Non-Targeted Effects Models Predict Significantly Higher Mars Mission Cancer Risk than Targeted Effects Models

DOE PAGES

Cucinotta, Francis A.; Cacao, Eliedonna

2017-05-12

Cancer risk is an important concern for galactic cosmic ray (GCR) exposures, which consist of a wide-energy range of protons, heavy ions and secondary radiation produced in shielding and tissues. Relative biological effectiveness (RBE) factors for surrogate cancer endpoints in cell culture models and tumor induction in mice vary considerable, including significant variations for different tissues and mouse strains. Many studies suggest non-targeted effects (NTE) occur for low doses of high linear energy transfer (LET) radiation, leading to deviation from the linear dose response model used in radiation protection. Using the mouse Harderian gland tumor experiment, the only extensive data-setmore » for dose response modelling with a variety of particle types (>4), for the first-time a particle track structure model of tumor prevalence is used to investigate the effects of NTEs in predictions of chronic GCR exposure risk. The NTE model led to a predicted risk 2-fold higher compared to a targeted effects model. The scarcity of data with animal models for tissues that dominate human radiation cancer risk, including lung, colon, breast, liver, and stomach, suggest that studies of NTEs in other tissues are urgently needed prior to long-term space missions outside the protection of the Earth’s geomagnetic sphere.« less

Non-Targeted Effects Models Predict Significantly Higher Mars Mission Cancer Risk than Targeted Effects Models

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

Cucinotta, Francis A.; Cacao, Eliedonna

Cancer risk is an important concern for galactic cosmic ray (GCR) exposures, which consist of a wide-energy range of protons, heavy ions and secondary radiation produced in shielding and tissues. Relative biological effectiveness (RBE) factors for surrogate cancer endpoints in cell culture models and tumor induction in mice vary considerable, including significant variations for different tissues and mouse strains. Many studies suggest non-targeted effects (NTE) occur for low doses of high linear energy transfer (LET) radiation, leading to deviation from the linear dose response model used in radiation protection. Using the mouse Harderian gland tumor experiment, the only extensive data-setmore » for dose response modelling with a variety of particle types (>4), for the first-time a particle track structure model of tumor prevalence is used to investigate the effects of NTEs in predictions of chronic GCR exposure risk. The NTE model led to a predicted risk 2-fold higher compared to a targeted effects model. The scarcity of data with animal models for tissues that dominate human radiation cancer risk, including lung, colon, breast, liver, and stomach, suggest that studies of NTEs in other tissues are urgently needed prior to long-term space missions outside the protection of the Earth’s geomagnetic sphere.« less

Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions.

PubMed

Hengl, Tomislav; Heuvelink, Gerard B M; Kempen, Bas; Leenaars, Johan G B; Walsh, Markus G; Shepherd, Keith D; Sila, Andrew; MacMillan, Robert A; Mendes de Jesus, Jorge; Tamene, Lulseged; Tondoh, Jérôme E

2015-01-01

80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008-2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management--organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15-75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological

AST-platelet ratio index, Forns index and FIB-4 in the prediction of significant fibrosis and cirrhosis in patients with chronic hepatitis C.

PubMed

Güzelbulut, Fatih; Çetınkaya, Züleyha Akkan; Sezıklı, Mesut; Yaşar, Bülent; Ozkara, Selvinaz; Övünç, Ayşe Oya Kurdaş

2011-06-01

The aim of this study was to evaluate the diagnostic accuracy of aspartate aminotransferase-platelet ratio index, the Forns index and FIB-4 for the assessment of hepatic fibrosis in chronic hepatitis C patients by comparison with liver biopsy. We retrospectively reviewed our computerized data of chronic hepatitis C patients who admitted to the Gastroenterology Clinic between 2004 and 2008. Treatment-naive chronic hepatitis C patients who had undergone liver biopsy and had laboratory test results allowing the calculation of aspartate aminotransferase-platelet ratio index, the Forns index and FIB-4 were included in this study. The degree of fibrosis was scored according to the METAVIR staging system. Significant fibrosis was defined as F2-4 and cirrhosis as F4. Aspartate aminotransferase-platelet ratio index, the Forns index and FIB-4 were calculated based on the original studies. Tests results were compared between groups F0-1 (no or mild fibrosis) versus F2-4 (significant fibrosis) and F03 (no cirrhosis) versus F4 (cirrhosis). One hundred and fifty patients with chronic hepatitis C were included in this study. The areas under the ROC curves of the Forns index, aspartate aminotransferase-platelet ratio index and FIB-4 to predict significant fibrosis were 0.795, 0.774 and 0.764, respectively. The area under the ROC curves of the Forns index, aspartate aminotransferase-platelet ratio index and FIB-4 to predict cirrhosis were 0.879, 0.839 and 0.874, respectively. The Forns index, aspartate aminotransferase-platelet ratio index and FIB-4 were accurate noninvasive blood tests to predict the presence or absence of significant fibrosis and cirrhosis in half of the chronic hepatitis C patients. The Forns index was slightly better than the aspartate aminotransferase-platelet ratio index and FIB-4 in the prediction of significant fibrosis and cirrhosis.

Early signs that predict later haemodynamically significant patent ductus arteriosus.

PubMed

Engür, Defne; Deveci, Murat; Türkmen, Münevver K

2016-03-01

Our aim was to determine the optimal cut-off values, sensitivity, specificity, and diagnostic power of 12 echocardiographic parameters on the second day of life to predict subsequent ductal patency. We evaluated preterm infants, born at ⩽32 weeks of gestation, starting on their second day of life, and they were evaluated every other day until ductal closure or until there were clinical signs of re-opening. We measured transductal diameter; pulmonary arterial diastolic flow; retrograde aortic diastolic flow; pulsatility index of the left pulmonary artery and descending aorta; left atrium and ventricle/aortic root ratio; left ventricular output; left ventricular flow velocity time integral; mitral early/late diastolic flow; and superior caval vein diameter and flow as well as performed receiver operating curve analysis. Transductal diameter (>1.5 mm); pulmonary arterial diastolic flow (>25.6 cm/second); presence of retrograde aortic diastolic flow; ductal diameter by body weight (>1.07 mm/kg); left pulmonary arterial pulsatility index (⩽0.71); and left ventricle to aortic root ratio (>2.2) displayed high sensitivity and specificity (p0.9). Parameters with moderate sensitivity and specificity were as follows: left atrial to aortic root ratio; left ventricular output; left ventricular flow velocity time integral; and mitral early/late diastolic flow ratio (p0.05) had low diagnostic value. Left pulmonary arterial pulsatility index, left ventricle/aortic root ratio, and ductal diameter by body weight are useful adjuncts offering a broader outlook for predicting ductal patency.

Clinical significance of the neutrophil-lymphocyte ratio as an early predictive marker for adverse outcomes in patients with acute pancreatitis

PubMed Central

Jeon, Tae Joo; Park, Ji Young

2017-01-01

AIM To investigated the prognostic value of the neutrophil-lymphocyte ratio (NLR) in patients with acute pancreatitis and determined an optimal cut-off value for the prediction of adverse outcomes in these patients. METHODS We retrospectively analyzed 490 patients with acute pancreatitis diagnosed between March 2007 and December 2012. NLRs were calculated at admission and 24, 48, and 72 h after admission. Patients were grouped according to acute pancreatitis severity and organ failure occurrence, and a comparative analysis was performed to compare the NLR between groups. RESULTS Among the 490 patients, 70 had severe acute pancreatitis with 31 experiencing organ failure. The severe acute pancreatitis group had a significantly higher NLR than the mild acute pancreatitis group on all 4 d (median, 6.14, 6.71, 5.70, and 4.00 vs 4.74, 4.47, 3.20, and 3.30, respectively, P < 0.05). The organ failure group had a significantly higher NLR than the group without organ failure on all 4 d (median, 7.09, 6.72, 6.27, and 6.24 vs 4.85, 4.49, 3.35, and 2.34, respectively, P < 0.05). The optimal cut-off value for baseline NLR was 4.76 in predicting severity and 4.88 in predicting organ failure in acute pancreatitis. CONCLUSION Elevated baseline NLR correlates with severe acute pancreatitis and organ failure. PMID:28638228

Clinical significance of the neutrophil-lymphocyte ratio as an early predictive marker for adverse outcomes in patients with acute pancreatitis.

PubMed

Jeon, Tae Joo; Park, Ji Young

2017-06-07

To investigated the prognostic value of the neutrophil-lymphocyte ratio (NLR) in patients with acute pancreatitis and determined an optimal cut-off value for the prediction of adverse outcomes in these patients. We retrospectively analyzed 490 patients with acute pancreatitis diagnosed between March 2007 and December 2012. NLRs were calculated at admission and 24, 48, and 72 h after admission. Patients were grouped according to acute pancreatitis severity and organ failure occurrence, and a comparative analysis was performed to compare the NLR between groups. Among the 490 patients, 70 had severe acute pancreatitis with 31 experiencing organ failure. The severe acute pancreatitis group had a significantly higher NLR than the mild acute pancreatitis group on all 4 d (median, 6.14, 6.71, 5.70, and 4.00 vs 4.74, 4.47, 3.20, and 3.30, respectively, P < 0.05). The organ failure group had a significantly higher NLR than the group without organ failure on all 4 d (median, 7.09, 6.72, 6.27, and 6.24 vs 4.85, 4.49, 3.35, and 2.34, respectively, P < 0.05). The optimal cut-off value for baseline NLR was 4.76 in predicting severity and 4.88 in predicting organ failure in acute pancreatitis. Elevated baseline NLR correlates with severe acute pancreatitis and organ failure.

Aircraft Noise Prediction Program (ANOPP) Fan Noise Prediction for Small Engines

NASA Technical Reports Server (NTRS)

Hough, Joe W.; Weir, Donald S.

1996-01-01

The Fan Noise Module of ANOPP is used to predict the broadband noise and pure tones for axial flow compressors or fans. The module, based on the method developed by M. F. Heidmann, uses empirical functions to predict fan noise spectra as a function of frequency and polar directivity. Previous studies have determined the need to modify the module to better correlate measurements of fan noise from engines in the 3000- to 6000-pound thrust class. Additional measurements made by AlliedSignal have confirmed the need to revise the ANOPP fan noise method for smaller engines. This report describes the revisions to the fan noise method which have been verified with measured data from three separate AlliedSignal fan engines. Comparisons of the revised prediction show a significant improvement in overall and spectral noise predictions.

Accurate and dynamic predictive model for better prediction in medicine and healthcare.

PubMed

Alanazi, H O; Abdullah, A H; Qureshi, K N; Ismail, A S

2018-05-01

Information and communication technologies (ICTs) have changed the trend into new integrated operations and methods in all fields of life. The health sector has also adopted new technologies to improve the systems and provide better services to customers. Predictive models in health care are also influenced from new technologies to predict the different disease outcomes. However, still, existing predictive models have suffered from some limitations in terms of predictive outcomes performance. In order to improve predictive model performance, this paper proposed a predictive model by classifying the disease predictions into different categories. To achieve this model performance, this paper uses traumatic brain injury (TBI) datasets. TBI is one of the serious diseases worldwide and needs more attention due to its seriousness and serious impacts on human life. The proposed predictive model improves the predictive performance of TBI. The TBI data set is developed and approved by neurologists to set its features. The experiment results show that the proposed model has achieved significant results including accuracy, sensitivity, and specificity.

Predicting Significant Reductions in Instructional Expenditures by School Districts

ERIC Educational Resources Information Center

Trussel, John M.; Patrick, Patricia A.

2012-01-01

This article uses survival analysis to investigate the symptoms of fiscal distress that can lead to significant reductions in instructional expenditures by independent public school districts in the United States. We hypothesize that the likelihood of significant reductions in instructional expenditures is positively correlated with revenue…

Use of data mining to predict significant factors and benefits of bilateral cochlear implantation.

PubMed

Ramos-Miguel, Angel; Perez-Zaballos, Teresa; Perez, Daniel; Falconb, Juan Carlos; Ramosb, Angel

2015-11-01

Data mining (DM) is a technique used to discover pattern and knowledge from a big amount of data. It uses artificial intelligence, automatic learning, statistics, databases, etc. In this study, DM was successfully used as a predictive tool to assess disyllabic speech test performance in bilateral implanted patients with a success rate above 90%. 60 bilateral sequentially implanted adult patients were included in the study. The DM algorithms developed found correlations between unilateral medical records and Audiological test results and bilateral performance by establishing relevant variables based on two DM techniques: the classifier and the estimation. The nearest neighbor algorithm was implemented in the first case, and the linear regression in the second. The results showed that patients with unilateral disyllabic test results below 70% benefited the most from a bilateral implantation. Finally, it was observed that its benefits decrease as the inter-implant time increases.

An active principle of Nigella sativa L., thymoquinone, showing significant antimicrobial activity against anaerobic bacteria.

PubMed

Randhawa, Mohammad Akram; Alenazy, Awwad Khalaf; Alrowaili, Majed Gorayan; Basha, Jamith

2017-01-01

Thymoquinone (TQ) is the major active principle of Nigella sativa seed (black seed) and is known to control many fungi, bacteria, and some viruses. However, the activity of TQ against anaerobic bacteria is not well demonstrated. Anaerobic bacteria can cause severe infections, including diarrhea, aspiration pneumonia, and brain abscess, particularly in immunodeficient individuals. The present study aimed to investigate the in vitro antimicrobial activity of TQ against some anaerobic pathogens in comparison to metronidazole. Standard, ATCC, strains of four anaerobic bacteria ( Clostridium difficile , Clostridium perfringens , Bacteroides fragilis , and Bacteroides thetaiotaomicron ), were initially isolated on special Brucella agar base (with hemin and vitamin K). Then, minimum inhibitory concentrations (MICs) of TQ and metronidazole were determined against these anaerobes when grown in Brucella agar, using serial agar dilution method according to the recommended guidelines for anaerobic organisms instructed by the Clinical and Laboratory Standards Institute. TQ showed a significant antimicrobial activity against anaerobic bacteria although much weaker than metronidazole. MICs of TQ and metronidazole against various anaerobic human pathogens tested were found to be between 10-160 mg/L and 0.19-6.25 mg/L, respectively. TQ controlled the anaerobic human pathogenic bacteria, which supports the use of N. sativa in the treatment of diarrhea in folk medicine. Further investigations are in need for determination of the synergistic effect of TQ in combination with metronidazole and the activity of derivatives of TQ against anaerobic infections.

Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions

PubMed Central

Hengl, Tomislav; Heuvelink, Gerard B. M.; Kempen, Bas; Leenaars, Johan G. B.; Walsh, Markus G.; Shepherd, Keith D.; Sila, Andrew; MacMillan, Robert A.; Mendes de Jesus, Jorge; Tamene, Lulseged; Tondoh, Jérôme E.

2015-01-01

80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological

Enhancing interacting residue prediction with integrated contact matrix prediction in protein-protein interaction.

PubMed

Du, Tianchuan; Liao, Li; Wu, Cathy H

2016-12-01

Identifying the residues in a protein that are involved in protein-protein interaction and identifying the contact matrix for a pair of interacting proteins are two computational tasks at different levels of an in-depth analysis of protein-protein interaction. Various methods for solving these two problems have been reported in the literature. However, the interacting residue prediction and contact matrix prediction were handled by and large independently in those existing methods, though intuitively good prediction of interacting residues will help with predicting the contact matrix. In this work, we developed a novel protein interacting residue prediction system, contact matrix-interaction profile hidden Markov model (CM-ipHMM), with the integration of contact matrix prediction and the ipHMM interaction residue prediction. We propose to leverage what is learned from the contact matrix prediction and utilize the predicted contact matrix as "feedback" to enhance the interaction residue prediction. The CM-ipHMM model showed significant improvement over the previous method that uses the ipHMM for predicting interaction residues only. It indicates that the downstream contact matrix prediction could help the interaction site prediction.

Accuracy of the prostate health index versus the urinary prostate cancer antigen 3 score to predict overall and significant prostate cancer at initial biopsy.

PubMed

Seisen, Thomas; Rouprêt, Morgan; Brault, Didier; Léon, Priscilla; Cancel-Tassin, Géraldine; Compérat, Eva; Renard-Penna, Raphaële; Mozer, Pierre; Guechot, Jérome; Cussenot, Olivier

2015-01-01

It remains unclear whether the Prostate Health Index (PHI) or the urinary Prostate-Cancer Antigen 3 (PCA-3) score is more accurate at screening for prostate cancer (PCa). The aim of this study was to prospectively compare the accuracy of PHI and PCA-3 scores to predict overall and significant PCa in men undergoing an initial prostate biopsy. Double-blind assessments of PHI and PCA-3 were conducted by referent physicians in 138 patients who subsequently underwent trans-rectal ultrasound-guided prostate biopsy according to a 12-core scheme. Predictive accuracies of PHI and PCA-3 were assessed using AUC and compared according to the DeLong method. Diagnostic performances with usual cut-off values for positivity (i.e., PHI >40 and PCA-3 >35) were calculated, and odds ratios associated with predicting PCa overall and significant PCa as defined by pathological updated Epstein criteria (i.e., Gleason score ≥7, more than three positive cores, or >50% cancer involvement in any core) were estimated using logistic regression. Prevalences of overall and significant PCa were 44.9% and 28.3%, respectively. PCA-3 (AUC = 0.71) was the most accurate predictor of PCa overall, and significantly outperformed PHI (AUC = 0.65; P = 0.03). However, PHI (AUC = 0.80) remained the most accurate predictor when screening exclusively for significant PCa and significantly outperformed PCA-3 (AUC = 0.55; P = 0.03). Furthermore, PCA-3 >35 had the best accuracy, and positive or negative predictive values when screening for PCa overall whereas these diagnostic performances were greater for PHI >40 when exclusively screening for significant PCa. PHI > 40 combined with PCA-3 > 35 was more specific in both cases. In multivariate analyses, PCA-3 >35 (OR = 5.68; 95%CI = [2.21-14.59]; P < 0.001) was significantly correlated with the presence of PCa overall, but PHI >40 (OR = 9.60; 95%CI = [1.72-91.32]; P = 0.001) was the only independent predictor

The prognostic significance of UCA1 for predicting clinical outcome in patients with digestive system malignancies

PubMed Central

Zhu, Zheng-Ming

2017-01-01

Background Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. Results The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52–2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45–2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30–3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. Materials and methods A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Conclusions Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers. PMID:28380443

The prognostic significance of UCA1 for predicting clinical outcome in patients with digestive system malignancies.

PubMed

Liu, Fang-Teng; Dong, Qing; Gao, Hui; Zhu, Zheng-Ming

2017-06-20

Urothelial Carcinoma Associated 1 (UCA1) was an originally identified lncRNA in bladder cancer. Previous studies have reported that UCA1 played a significant role in various types of cancer. This study aimed to clarify the prognostic value of UCA1 in digestive system cancers. The meta-analysis of 15 studies were included, comprising 1441 patients with digestive system cancers. The pooled results of 14 studies indicated that high expression of UCA1 was significantly associated with poorer OS in patients with digestive system cancers (HR: 1.89, 95 % CI: 1.52-2.26). In addition, UCA1 could be as an independent prognostic factor for predicting OS of patients (HR: 1.85, 95 % CI: 1.45-2.25). The pooled results of 3 studies indicated a significant association between UCA1 and DFS in patients with digestive system cancers (HR = 2.50; 95 % CI = 1.30-3.69). Statistical significance was also observed in subgroup meta-analysis. Furthermore, the clinicopathological values of UCA1 were discussed in esophageal cancer, colorectal cancer and pancreatic cancer. A comprehensive retrieval was performed to search studies evaluating the prognostic value of UCA1 in digestive system cancers. Many databases were involved, including PubMed, Web of Science, Embase and Chinese National Knowledge Infrastructure and Wanfang database. Quantitative meta-analysis was performed with standard statistical methods and the prognostic significance of UCA1 in digestive system cancers was qualified. Elevated level of UCA1 indicated the poor clinical outcome for patients with digestive system cancers. It may serve as a new biomarker related to prognosis in digestive system cancers.

Patient-derived glioblastoma cells show significant heterogeneity in treatment responses to the inhibitor-of-apoptosis-protein antagonist birinapant

PubMed Central

Zakaria, Z; Tivnan, A; Flanagan, L; Murray, D W; Salvucci, M; Stringer, B W; Day, B W; Boyd, A W; Kögel, D; Rehm, M; O'Brien, D F; Byrne, A T; Prehn, J H M

2016-01-01

Background: Resistance to temozolomide (TMZ) greatly limits chemotherapeutic effectiveness in glioblastoma (GBM). Here we analysed the ability of the Inhibitor-of-apoptosis-protein (IAP) antagonist birinapant to enhance treatment responses to TMZ in both commercially available and patient-derived GBM cells. Methods: Responses to TMZ and birinapant were analysed in a panel of commercial and patient-derived GBM cell lines using colorimetric viability assays, flow cytometry, morphological analysis and protein expression profiling of pro- and antiapoptotic proteins. Responses in vivo were analysed in an orthotopic xenograft GBM model. Results: Single-agent treatment experiments categorised GBM cells into TMZ-sensitive cells, birinapant-sensitive cells, and cells that were insensitive to either treatment. Combination treatment allowed sensitisation to therapy in only a subset of resistant GBM cells. Cell death analysis identified three principal response patterns: Type A cells that readily activated caspase-8 and cell death in response to TMZ while addition of birinapant further sensitised the cells to TMZ-induced cell death; Type B cells that readily activated caspase-8 and cell death in response to birinapant but did not show further sensitisation with TMZ; and Type C cells that showed no significant cell death or moderately enhanced cell death in the combined treatment paradigm. Furthermore, in vivo, a Type C patient-derived cell line that was TMZ-insensitive in vitro and showed a strong sensitivity to TMZ and TMZ plus birinapant treatments. Conclusions: Our results demonstrate remarkable differences in responses of patient-derived GBM cells to birinapant single and combination treatments, and suggest that therapeutic responses in vivo may be greatly affected by the tumour microenvironment. PMID:26657652

Sub-seasonal prediction of significant wave heights over the Western Pacific and Indian Oceans, part II: The impact of ENSO and MJO

NASA Astrophysics Data System (ADS)

Shukla, Ravi P.; Kinter, James L.; Shin, Chul-Su

2018-03-01

This study evaluates the effect of El Niño and the Southern Oscillation (ENSO) and Madden Julian Oscillation (MJO) events on 14-day mean significant wave height (SWH) at 3 weeks lead time (Wk34) over the Western Pacific and Indian Oceans using the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2). The WAVEWATCH-3 (WW3) model is forced with daily 10m-winds predicted by a modified version of CFSv2 that is initialized with multiple ocean analyses in both January and May for 1979-2008. A significant anomaly correlation of predicted and observed SWH anomalies (SWHA) at Wk34 lead-time is found over portions of the domain, including the central western Pacific, South China Sea (SCS), Bay of Bengal (BOB) and southern Indian Ocean (IO) in January cases, and over BOB, equatorial western Pacific, the Maritime Continent and southern IO in May cases. The model successfully predicts almost all the important features of the observed composite SWHA during El Niño events in January, including negative SWHA in the central IO where westerly wind anomalies act on an easterly mean state, and positive SWHA over the southern Ocean (SO) where westerly wind anomalies act on a westerly mean state. The model successfully predicts the sign and magnitude of SWHA at Wk34 lead-time in May over the BOB and SCS in composites of combined phases-2-3 and phases-6-7 of MJO. The observed leading mode of SWHA in May and the third mode of SWHA in January are influenced by the combined effects of ENSO and MJO. Based on spatial and temporal correlations, the spatial patterns of SWHA in the model at Wk34 in both January and May are in good agreement with the observations over the equatorial western Pacific, equatorial and southern IO, and SO.

Skilful Seasonal Predictions of Summer European Rainfall

NASA Astrophysics Data System (ADS)

Dunstone, Nick; Smith, Doug; Scaife, Adam; Hermanson, Leon; Fereday, David; O'Reilly, Chris; Stirling, Alison; Eade, Rosie; Gordon, Margaret; MacLachlan, Craig; Woollings, Tim; Sheen, Katy; Belcher, Stephen

2018-04-01

Year-to-year variability in Northern European summer rainfall has profound societal and economic impacts; however, current seasonal forecast systems show no significant forecast skill. Here we show that skillful predictions are possible (r 0.5, p < 0.001) using the latest high-resolution Met Office near-term prediction system over 1960-2017. The model predictions capture both low-frequency changes (e.g., wet summers 2007-2012) and some of the large individual events (e.g., dry summer 1976). Skill is linked to predictable North Atlantic sea surface temperature variability changing the supply of water vapor into Northern Europe and so modulating convective rainfall. However, dynamical circulation variability is not well predicted in general—although some interannual skill is found. Due to the weak amplitude of the forced model signal (likely caused by missing or weak model responses), very large ensembles (>80 members) are required for skillful predictions. This work is promising for the development of European summer rainfall climate services.

Integrated genomic and immunophenotypic classification of pancreatic cancer reveals three distinct subtypes with prognostic/predictive significance.

PubMed

Wartenberg, Martin; Cibin, Silvia; Zlobec, Inti; Vassella, Erik; Eppenberger-Castori, Serenella M M; Terracciano, Luigi; Eichmann, Micha; Worni, Mathias; Gloor, Beat; Perren, Aurel; Karamitopoulou, Eva

2018-04-16

Current clinical classification of pancreatic ductal adenocarcinoma (PDAC) is unable to predict prognosis or response to chemo- or immunotherapy and does not take into account the host reaction to PDAC-cells. Our aim is to classify PDAC according to host- and tumor-related factors into clinically/biologically relevant subtypes by integrating molecular and microenvironmental findings. A well-characterized PDAC-cohort (n=110) underwent next-generation sequencing with a hotspot cancer panel, while Next-generation Tissue-Microarrays were immunostained for CD3, CD4, CD8, CD20, PD-L1, p63, hyaluronan-mediated motility receptor (RHAMM) and DNA mismatch-repair proteins. Previous data on FOXP3 were integrated. Immune-cell counts and protein expression were correlated with tumor-derived driver mutations, clinicopathologic features (TNM 8. 2017), survival and epithelial-mesenchymal-transition (EMT)-like tumor budding.  Results: Three PDAC-subtypes were identified: the "immune-escape" (54%), poor in T- and B-cells and enriched in FOXP3+Tregs, with high-grade budding, frequent CDKN2A- , SMAD4- and PIK3CA-mutations and poor outcome; the "immune-rich" (35%), rich in T- and B-cells and poorer in FOXP3+Tregs, with infrequent budding, lower CDKN2A- and PIK3CA-mutation rate and better outcome and a subpopulation with tertiary lymphoid tissue (TLT), mutations in DNA damage response genes (STK11, ATM) and the best outcome; and the "immune-exhausted" (11%) with immunogenic microenvironment and two subpopulations: one with PD-L1-expression and high PIK3CA-mutation rate and a microsatellite-unstable subpopulation with high prevalence of JAK3-mutations. The combination of low budding, low stromal FOXP3-counts, presence of TLTs and absence of CDKN2A-mutations confers significant survival advantage in PDAC-patients. Immune host responses correlate with tumor characteristics leading to morphologically recognizable PDAC-subtypes with prognostic/predictive significance. Copyright ©2018

Additional Value of Transluminal Attenuation Gradient in CT Angiography to Predict Hemodynamic Significance of Coronary Artery Stenosis

PubMed Central

Stuijfzand, Wynand J.; Danad, Ibrahim; Raijmakers, Pieter G.; Marcu, C. Bogdan; Heymans, Martijn W.; van Kuijk, Cornelis C.; van Rossum, Albert C.; Nieman, Koen; Min, James K.; Leipsic, Jonathon; van Royen, Niels; Knaapen, Paul

2015-01-01

OBJECTIVES The current study evaluates the incremental value of transluminal attenuation gradient (TAG), TAG with corrected contrast opacification (CCO), and TAG with exclusion of calcified coronary segments (ExC) over coronary computed tomography angiogram (CTA) alone using fractional flow reserve (FFR) as the gold standard. BACKGROUND TAG is defined as the contrast opacification gradient along the length of a coronary artery on a coronary CTA. Preliminary data suggest that TAG provides additional functional information. Interpretation of TAG is hampered by multiple heartbeat acquisition algorithms and coronary calcifications. Two correction models have been proposed based on either dephasing of contrast delivery by relating coronary density to corresponding descending aortic opacification (TAG-CCO) or excluding calcified coronary segments (TAG-ExC). METHODS Eighty-five patients with intermediate probability of coronary artery disease were prospectively included. All patients underwent step-and-shoot 256-slice coronary CTA. TAG, TAG-CCO, and TAG-ExC analyses were performed followed by invasive coronary angiography in conjunction with FFR measurements of all major coronary branches. RESULTS Thirty-four patients (40%) were diagnosed with hemodynamically-significant coronary artery disease (i.e., FFR ≤0.80). On a per-vessel basis (n = 253), 59 lesions (23%) were graded as hemodynamically significant, and the diagnostic accuracy of coronary CTA (diameter stenosis ≥50%) was 95%, 75%, 98%, and 54% for sensitivity, specificity, negative predictive value, and positive predictive value, respectively. TAG and TAG-ExC did not discriminate between vessels with or without hemodynamically significant lesions (−13.5 ± 17.1 HU [Hounsfield units] × 10 mm−1 vs. −11.6 ± 13.3 HU × 10 mm−1, p = 0.36; and 13.1 ± 15.9 HU × 10 mm−1 vs. −11.4 ± 11.7 HU × 10 mm−1, p = 0.77, respectively). TAG-CCO was lower in vessels with a hemodynamically-significant lesion (−0

Dietary flavonoid aglycones and their glycosides: Which show better biological significance?

PubMed

Xiao, Jianbo

2017-06-13

flavonoids for human health. It is possible that the effects of glycosylation on flavonoid bioactivity in vitro may differ from that seen in vivo. With in vivo (oral) treatment, flavonoid glycosides showed similar or even higher antidiabetes, anti-inflammatory, antidegranulating, antistress, and antiallergic activity than their flavonoid aglycones. Flavonoid glycosides keep higher plasma levels and have a longer mean residence time than those of aglycones. We should pay more attention to in vivo benefits of flavonoid glycosides, especially C-glycosides.

Predictive maps for Juno perijoves and identification of significant features

NASA Astrophysics Data System (ADS)

Rogers, J. H.; Adamoli, G.; Jacquesson, M.; Vedovato, M.; Mettig, H.-J.; Eichstädt, G.; Caplinger, M.; Momary, T. W.; Orton, G. S.; Tabataba-Vakili, F.; Hansen, C. J.

2017-09-01

At each Juno perijove, JunoCam takes hi-res images of selected latitudes along the sub-spacecraft track, as determined by public voting. To inform this target election process, we use the continuous coverage of Jupiter's visible clouds by amateur imaging, and the tracking of features from those images by the JUPOS project, to identify the features which are expected to be visible at the upcoming perijove. We produce a predictive map for each perijove, and subsequently annotate the JunoCam images to locate the known jets and circulation. Up to perijove 5, this collaboration has contributed to hi-res imaging of several long-lived circulations in northern and southern hemispheres, of major new convective outbreaks in the North and South Equatorial Belts, and of the North Temperate Belt maturing after a cyclic outbreak.

Gambling score in earthquake prediction analysis

NASA Astrophysics Data System (ADS)

Molchan, G.; Romashkova, L.

2011-03-01

The number of successes and the space-time alarm rate are commonly used to characterize the strength of an earthquake prediction method and the significance of prediction results. It has been recently suggested to use a new characteristic to evaluate the forecaster's skill, the gambling score (GS), which incorporates the difficulty of guessing each target event by using different weights for different alarms. We expand parametrization of the GS and use the M8 prediction algorithm to illustrate difficulties of the new approach in the analysis of the prediction significance. We show that the level of significance strongly depends (1) on the choice of alarm weights, (2) on the partitioning of the entire alarm volume into component parts and (3) on the accuracy of the spatial rate measure of target events. These tools are at the disposal of the researcher and can affect the significance estimate. Formally, all reasonable GSs discussed here corroborate that the M8 method is non-trivial in the prediction of 8.0 ≤M < 8.5 events because the point estimates of the significance are in the range 0.5-5 per cent. However, the conservative estimate 3.7 per cent based on the number of successes seems preferable owing to two circumstances: (1) it is based on relative values of the spatial rate and hence is more stable and (2) the statistic of successes enables us to construct analytically an upper estimate of the significance taking into account the uncertainty of the spatial rate measure.

Serving Up Activities for TV Cooking Shows.

ERIC Educational Resources Information Center

Katchen, Johanna E.

This paper documents a presentation given on the use of English-language television cooking shows in English-as-a-Second-Language (ESL) and English-as-a-Foreign-Language (EFL) classrooms in Taiwan. Such shows can be ideal for classroom use, since they have a predictable structure consisting of short segments, are of interest to most students,…

1.5-Tesla Multiparametric-Magnetic Resonance Imaging for the detection of clinically significant prostate cancer.

PubMed

Popita, Cristian; Popita, Anca Raluca; Sitar-Taut, Adela; Petrut, Bogdan; Fetica, Bogdan; Coman, Ioan

2017-01-01

Multiparametric-magnetic resonance imaging (mp-MRI) is the main imaging modality used for prostate cancer detection. The aim of this study is to evaluate the diagnostic performance of mp-MRI at 1.5-Tesla (1.5-T) for the detection of clinically significant prostate cancer. In this ethical board approved prospective study, 39 patients with suspected prostate cancer were included. Patients with a history of positive prostate biopsy and patients treated for prostate cancer were excluded. All patients were examined at 1.5-T MRI, before standard transrectal ultrasonography-guided biopsy. The overall sensitivity, specificity, positive predictive value and negative predictive value for mp-MRI were 100%, 73.68%, 80% and 100%, respectively. Our results showed that 1.5 T mp-MRI has a high sensitivity for detection of clinically significant prostate cancer and high negative predictive value in order to rule out significant disease.

Prognostic significance of electrical alternans versus signal averaged electrocardiography in predicting the outcome of electrophysiological testing and arrhythmia-free survival

NASA Technical Reports Server (NTRS)

Armoundas, A. A.; Rosenbaum, D. S.; Ruskin, J. N.; Garan, H.; Cohen, R. J.

1998-01-01

OBJECTIVE: To investigate the accuracy of signal averaged electrocardiography (SAECG) and measurement of microvolt level T wave alternans as predictors of susceptibility to ventricular arrhythmias. DESIGN: Analysis of new data from a previously published prospective investigation. SETTING: Electrophysiology laboratory of a major referral hospital. PATIENTS AND INTERVENTIONS: 43 patients, not on class I or class III antiarrhythmic drug treatment, undergoing invasive electrophysiological testing had SAECG and T wave alternans measurements. The SAECG was considered positive in the presence of one (SAECG-I) or two (SAECG-II) of three standard criteria. T wave alternans was considered positive if the alternans ratio exceeded 3.0. MAIN OUTCOME MEASURES: Inducibility of sustained ventricular tachycardia or fibrillation during electrophysiological testing, and 20 month arrhythmia-free survival. RESULTS: The accuracy of T wave alternans in predicting the outcome of electrophysiological testing was 84% (p < 0.0001). Neither SAECG-I (accuracy 60%; p < 0.29) nor SAECG-II (accuracy 71%; p < 0.10) was a statistically significant predictor of electrophysiological testing. SAECG, T wave alternans, electrophysiological testing, and follow up data were available in 36 patients while not on class I or III antiarrhythmic agents. The accuracy of T wave alternans in predicting the outcome of arrhythmia-free survival was 86% (p < 0.030). Neither SAECG-I (accuracy 65%; p < 0.21) nor SAECG-II (accuracy 71%; p < 0.48) was a statistically significant predictor of arrhythmia-free survival. CONCLUSIONS: T wave alternans was a highly significant predictor of the outcome of electrophysiological testing and arrhythmia-free survival, while SAECG was not a statistically significant predictor. Although these results need to be confirmed in prospective clinical studies, they suggest that T wave alternans may serve as a non-invasive probe for screening high risk populations for malignant ventricular

Prevalence, significance and predictive value of antiphospholipid antibodies in Crohn’s disease

PubMed Central

Sipeki, Nora; Davida, Laszlo; Palyu, Eszter; Altorjay, Istvan; Harsfalvi, Jolan; Antal Szalmas, Peter; Szabo, Zoltan; Veres, Gabor; Shums, Zakera; Norman, Gary L; Lakatos, Peter L; Papp, Maria

2015-01-01

status of the patients. Occurrence of anti-β2-GPI, ACA and anti-PS/PT was not different between the group of patients with active vs inactive disease state according to appropriate clinical, laboratory and endoscopic scores in CD as well as in UC patients. All subtypes of anti-β2-GPI and ACA IgM status were found to be very stable over time, in contrast ACA IgG and even more ACA IgA status showed significant intraindividual changes. Changes in antibody status were more remarkable in CD than UC (ACA IgA: 49.9% vs 23.3% and ACA IgG: 21.2% vs 5.8%). Interestingly, 59.1% and 30.1% of CD patients who received anti-TNF therapy showed significant negative to positive changes in ACA IgA and IgG antibody status respectively. APLA status was not associated with the clinical phenotype at diagnosis or during follow-up, medical therapy, or thrombotic events and it was not associated with the probability of developing complicated disease phenotype or surgery in a Kaplan-Meier analysis. CONCLUSION: The present study demonstrated enhanced formation of APLAs in CD patients. However, presence of different APLAs were not associated with the clinical phenotype or disease course. PMID:26078573

Assessment of Arctic and Antarctic Sea Ice Predictability in CMIP5 Decadal Hindcasts

NASA Technical Reports Server (NTRS)

Yang, Chao-Yuan; Liu, Jiping (Inventor); Hu, Yongyun; Horton, Radley M.; Chen, Liqi; Cheng, Xiao

2016-01-01

This paper examines the ability of coupled global climate models to predict decadal variability of Arctic and Antarctic sea ice. We analyze decadal hindcasts/predictions of 11 Coupled Model Intercomparison Project Phase 5 (CMIP5) models. Decadal hindcasts exhibit a large multimodel spread in the simulated sea ice extent, with some models deviating significantly from the observations as the predicted ice extent quickly drifts away from the initial constraint. The anomaly correlation analysis between the decadal hindcast and observed sea ice suggests that in the Arctic, for most models, the areas showing significant predictive skill become broader associated with increasing lead times. This area expansion is largely because nearly all the models are capable of predicting the observed decreasing Arctic sea ice cover. Sea ice extent in the North Pacific has better predictive skill than that in the North Atlantic (particularly at a lead time of 3-7 years), but there is a reemerging predictive skill in the North Atlantic at a lead time of 6-8 years. In contrast to the Arctic, Antarctic sea ice decadal hindcasts do not show broad predictive skill at any timescales, and there is no obvious improvement linking the areal extent of significant predictive skill to lead time increase. This might be because nearly all the models predict a retreating Antarctic sea ice cover, opposite to the observations. For the Arctic, the predictive skill of the multi-model ensemble mean outperforms most models and the persistence prediction at longer timescales, which is not the case for the Antarctic. Overall, for the Arctic, initialized decadal hindcasts show improved predictive skill compared to uninitialized simulations, although this improvement is not present in the Antarctic.

Detection of Significant Pneumococcal Meningitis Biomarkers by Ego Network.

PubMed

Wang, Qian; Lou, Zhifeng; Zhai, Liansuo; Zhao, Haibin

2017-06-01

To identify significant biomarkers for detection of pneumococcal meningitis based on ego network. Based on the gene expression data of pneumococcal meningitis and global protein-protein interactions (PPIs) data recruited from open access databases, the authors constructed a differential co-expression network (DCN) to identify pneumococcal meningitis biomarkers in a network view. Here EgoNet algorithm was employed to screen the significant ego networks that could accurately distinguish pneumococcal meningitis from healthy controls, by sequentially seeking ego genes, searching candidate ego networks, refinement of candidate ego networks and significance analysis to identify ego networks. Finally, the functional inference of the ego networks was performed to identify significant pathways for pneumococcal meningitis. By differential co-expression analysis, the authors constructed the DCN that covered 1809 genes and 3689 interactions. From the DCN, a total of 90 ego genes were identified. Starting from these ego genes, three significant ego networks (Module 19, Module 70 and Module 71) that could predict clinical outcomes for pneumococcal meningitis were identified by EgoNet algorithm, and the corresponding ego genes were GMNN, MAD2L1 and TPX2, respectively. Pathway analysis showed that these three ego networks were related to CDT1 association with the CDC6:ORC:origin complex, inactivation of APC/C via direct inhibition of the APC/C complex pathway, and DNA strand elongation, respectively. The authors successfully screened three significant ego modules which could accurately predict the clinical outcomes for pneumococcal meningitis and might play important roles in host response to pathogen infection in pneumococcal meningitis.

1.5-Tesla Multiparametric-Magnetic Resonance Imaging for the detection of clinically significant prostate cancer

PubMed Central

POPITA, CRISTIAN; POPITA, ANCA RALUCA; SITAR-TAUT, ADELA; PETRUT, BOGDAN; FETICA, BOGDAN; COMAN, IOAN

2017-01-01

Background and aim Multiparametric-magnetic resonance imaging (mp-MRI) is the main imaging modality used for prostate cancer detection. The aim of this study is to evaluate the diagnostic performance of mp-MRI at 1.5-Tesla (1.5-T) for the detection of clinically significant prostate cancer. Methods In this ethical board approved prospective study, 39 patients with suspected prostate cancer were included. Patients with a history of positive prostate biopsy and patients treated for prostate cancer were excluded. All patients were examined at 1.5-T MRI, before standard transrectal ultrasonography–guided biopsy. Results The overall sensitivity, specificity, positive predictive value and negative predictive value for mp-MRI were 100%, 73.68%, 80% and 100%, respectively. Conclusion Our results showed that 1.5 T mp-MRI has a high sensitivity for detection of clinically significant prostate cancer and high negative predictive value in order to rule out significant disease. PMID:28246496

Predicting flight delay based on multiple linear regression

NASA Astrophysics Data System (ADS)

Ding, Yi

2017-08-01

Delay of flight has been regarded as one of the toughest difficulties in aviation control. How to establish an effective model to handle the delay prediction problem is a significant work. To solve the problem that the flight delay is difficult to predict, this study proposes a method to model the arriving flights and a multiple linear regression algorithm to predict delay, comparing with Naive-Bayes and C4.5 approach. Experiments based on a realistic dataset of domestic airports show that the accuracy of the proposed model approximates 80%, which is further improved than the Naive-Bayes and C4.5 approach approaches. The result testing shows that this method is convenient for calculation, and also can predict the flight delays effectively. It can provide decision basis for airport authorities.

Seismic activity prediction using computational intelligence techniques in northern Pakistan

NASA Astrophysics Data System (ADS)

Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

2017-10-01

Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

Large-scale structure prediction by improved contact predictions and model quality assessment.

PubMed

Michel, Mirco; Menéndez Hurtado, David; Uziela, Karolis; Elofsson, Arne

2017-07-15

Accurate contact predictions can be used for predicting the structure of proteins. Until recently these methods were limited to very big protein families, decreasing their utility. However, recent progress by combining direct coupling analysis with machine learning methods has made it possible to predict accurate contact maps for smaller families. To what extent these predictions can be used to produce accurate models of the families is not known. We present the PconsFold2 pipeline that uses contact predictions from PconsC3, the CONFOLD folding algorithm and model quality estimations to predict the structure of a protein. We show that the model quality estimation significantly increases the number of models that reliably can be identified. Finally, we apply PconsFold2 to 6379 Pfam families of unknown structure and find that PconsFold2 can, with an estimated 90% specificity, predict the structure of up to 558 Pfam families of unknown structure. Out of these, 415 have not been reported before. Datasets as well as models of all the 558 Pfam families are available at http://c3.pcons.net/ . All programs used here are freely available. arne@bioinfo.se. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Spatiotemporal Bayesian networks for malaria prediction.

PubMed

Haddawy, Peter; Hasan, A H M Imrul; Kasantikul, Rangwan; Lawpoolsri, Saranath; Sa-Angchai, Patiwat; Kaewkungwal, Jaranit; Singhasivanon, Pratap

2018-01-01

Targeted intervention and resource allocation are essential for effective malaria control, particularly in remote areas, with predictive models providing important information for decision making. While a diversity of modeling technique have been used to create predictive models of malaria, no work has made use of Bayesian networks. Bayes nets are attractive due to their ability to represent uncertainty, model time lagged and nonlinear relations, and provide explanations. This paper explores the use of Bayesian networks to model malaria, demonstrating the approach by creating village level models with weekly temporal resolution for Tha Song Yang district in northern Thailand. The networks are learned using data on cases and environmental covariates. Three types of networks are explored: networks for numeric prediction, networks for outbreak prediction, and networks that incorporate spatial autocorrelation. Evaluation of the numeric prediction network shows that the Bayes net has prediction accuracy in terms of mean absolute error of about 1.4 cases for 1 week prediction and 1.7 cases for 6 week prediction. The network for outbreak prediction has an ROC AUC above 0.9 for all prediction horizons. Comparison of prediction accuracy of both Bayes nets against several traditional modeling approaches shows the Bayes nets to outperform the other models for longer time horizon prediction of high incidence transmission. To model spread of malaria over space, we elaborate the models with links between the village networks. This results in some very large models which would be far too laborious to build by hand. So we represent the models as collections of probability logic rules and automatically generate the networks. Evaluation of the models shows that the autocorrelation links significantly improve prediction accuracy for some villages in regions of high incidence. We conclude that spatiotemporal Bayesian networks are a highly promising modeling alternative for prediction

True grit and genetics: predicting academic achievement from personality

PubMed Central

Rimfeld, Kaili; Kovas, Yulia; Dale, Philip S.; Plomin, Robert

2015-01-01

Grit -- perseverance and passion for long-term goals -- has been shown to be a significant predictor of academic success, even after controlling for other personality factors. Here, for the first time, we use a UK-representative sample and a genetically sensitive design to unpack the etiology of grit and its prediction of academic achievement in comparison to well-established personality traits. For 4,642 16-year-olds (2,321 twin pairs), we used the Grit-S scale (Perseverance of Effort and Consistency of Interest), along with the Big-5 personality traits, to predict scores on the General Certificate of Secondary Education (GCSE) exams, which are administered UK-wide at the end of compulsory education. Twin analyses of Grit Perseverance yielded a heritability estimate of 37% (20% for Consistency of Interest) and no evidence for shared environmental influence. Personality, primarily Conscientiousness, predicts about 6% of the variance in GCSE scores, but Grit adds little to this prediction. Moreover, multivariate twin analyses showed that roughly two-thirds of the GCSE prediction is mediated genetically. Grit Perseverance of Effort and Big-5 Conscientiousness are to a large extent the same trait both phenotypically (r=0.53) and genetically (genetic correlation = 0. 86). We conclude that the etiology of Grit is highly similar to other personality traits, not only in showing substantial genetic influence but also in showing no influence of shared environmental factors. Personality significantly predicts academic achievement, but Grit adds little phenotypically or genetically to the prediction of academic achievement beyond traditional personality factors, especially Conscientiousness. PMID:26867111

Evoked Emotions Predict Food Choice

PubMed Central

Dalenberg, Jelle R.; Gutjar, Swetlana; ter Horst, Gert J.; de Graaf, Kees; Renken, Remco J.; Jager, Gerry

2014-01-01

In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores. PMID:25521352

Evoked emotions predict food choice.

PubMed

Dalenberg, Jelle R; Gutjar, Swetlana; Ter Horst, Gert J; de Graaf, Kees; Renken, Remco J; Jager, Gerry

2014-01-01

In the current study we show that non-verbal food-evoked emotion scores significantly improve food choice prediction over merely liking scores. Previous research has shown that liking measures correlate with choice. However, liking is no strong predictor for food choice in real life environments. Therefore, the focus within recent studies shifted towards using emotion-profiling methods that successfully can discriminate between products that are equally liked. However, it is unclear how well scores from emotion-profiling methods predict actual food choice and/or consumption. To test this, we proposed to decompose emotion scores into valence and arousal scores using Principal Component Analysis (PCA) and apply Multinomial Logit Models (MLM) to estimate food choice using liking, valence, and arousal as possible predictors. For this analysis, we used an existing data set comprised of liking and food-evoked emotions scores from 123 participants, who rated 7 unlabeled breakfast drinks. Liking scores were measured using a 100-mm visual analogue scale, while food-evoked emotions were measured using 2 existing emotion-profiling methods: a verbal and a non-verbal method (EsSense Profile and PrEmo, respectively). After 7 days, participants were asked to choose 1 breakfast drink from the experiment to consume during breakfast in a simulated restaurant environment. Cross validation showed that we were able to correctly predict individualized food choice (1 out of 7 products) for over 50% of the participants. This number increased to nearly 80% when looking at the top 2 candidates. Model comparisons showed that evoked emotions better predict food choice than perceived liking alone. However, the strongest predictive strength was achieved by the combination of evoked emotions and liking. Furthermore we showed that non-verbal food-evoked emotion scores more accurately predict food choice than verbal food-evoked emotions scores.

Web-based thyroid imaging reporting and data system: Malignancy risk of atypia of undetermined significance or follicular lesion of undetermined significance thyroid nodules calculated by a combination of ultrasonography features and biopsy results.

PubMed

Choi, Young Jun; Baek, Jung Hwan; Shin, Jung Hee; Shim, Woo Hyun; Kim, Seon-Ok; Lee, Won-Hong; Song, Dong Eun; Kim, Tae Yong; Chung, Ki-Wook; Lee, Jeong Hyun

2018-05-13

The purpose of this study was to construct a web-based predictive model using ultrasound characteristics and subcategorized biopsy results for thyroid nodules of atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) to stratify the risk of malignancy. Data included 672 thyroid nodules from 656 patients from a historical cohort. We analyzed ultrasound images of thyroid nodules and biopsy results according to nuclear atypia and architectural atypia. Multivariate logistic regression analysis was performed to predict whether nodules were diagnosed as malignant or benign. The ultrasound features, including spiculated margin, marked hypoechogenicity, calcifications, biopsy results, and cytologic atypia, showed significant differences between groups. A 13-point risk scoring system was developed, and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve of the development and validation sets were 0.837 and 0.830, respectively (http://www.gap.kr/thyroidnodule_b3.php). We devised a web-based predictive model using the combined information of ultrasound characteristics and biopsy results for AUS/FLUS thyroid nodules to stratify the malignant risk. © 2018 Wiley Periodicals, Inc.

Triaging TIA/minor stroke patients using the ABCD2 score does not predict those with significant carotid disease.

PubMed

Walker, J; Isherwood, J; Eveson, D; Naylor, A R

2012-05-01

'Rapid Access' TIA Clinics use the ABCD(2) score to triage patients as it is not possible to see everyone with a suspected TIA <24 h. Those scoring 0-3 are seen within seven days, while patients scoring 4-7 are seen as soon as possible (preferably <24 h). It was hypothesized that patients scoring 4-7 would have a higher yield of significant carotid disease. Prospective study of correlation between Family Doctor (FD) or Emergency Department (ED) ABCD(2) score and specialist consultant Stroke Physician measured ABCD(2) score and prevalence of ≥50% ipsilateral carotid stenosis or occlusion in patients presenting with 'any territory' TIA/minor stroke or 'carotid territory' TIA/minor stroke. Between 1.10.2008 and 31.04.2011, 2452 patients were referred to the Leicester Rapid Access TIA Service. After Stroke Physician review, 1273 (52%) were thought to have suffered a minor stroke/TIA. Of these, both FD/ED referrer and Specialist Stroke Consultant ABCD(2) scores and carotid Duplex ultrasound studies were available for 843 (66%). The yield for identifying a ≥50% stenosis or carotid occlusion was 109/843 (12.9%) in patients with 'any territory' TIA/minor stroke and 101/740 (13.6%) in those with a clinical diagnosis of 'carotid territory' TIA/minor stroke. There was no association between ABCD(2) score and the likelihood of encountering significant carotid disease and analyses of the area under the receiver operating characteristic curve (AUC) for FD/ED referrer and stroke specialist ABCD(2) scores showed no prediction of carotid stenosis (FD/ED: AUC 0.50 (95%CI 0.44-0.55, p = 0.9), Specialist: AUC 0.51 (95%CI 0.45-0.57, p = 0.78). The ABCD(2) score was unable to identify TIA/minor stroke patients with a higher prevalence of clinically important ipsilateral carotid disease. Copyright © 2012 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

KRAS mutations and CDKN2A promoter methylation show an interactive adverse effect on survival and predict recurrence of rectal cancer.

PubMed

Kohonen-Corish, Maija R J; Tseung, Jason; Chan, Charles; Currey, Nicola; Dent, Owen F; Clarke, Stephen; Bokey, Les; Chapuis, Pierre H

2014-06-15

Colonic and rectal cancers differ in their clinicopathologic features and treatment strategies. Molecular markers such as gene methylation, microsatellite instability and KRAS mutations, are becoming increasingly important in guiding treatment decisions in colorectal cancer. However, their association with clinicopathologic variables and utility in the management of rectal cancer is still poorly understood. We analyzed CDKN2A gene methylation, CpG island methylator phenotype (CIMP), microsatellite instability and KRAS/BRAF mutations in a cohort of 381 rectal cancers with extensive clinical follow-up data. BRAF mutations (2%), CIMP-high (4%) and microsatellite instability-high (2%) were rare, whereas KRAS mutations (39%), CDKN2A methylation (20%) and CIMP-low (25%) were more common. Only CDKN2A methylation and KRAS mutations showed an association with poor overall survival but these did not remain significant when analyzed with other clinicopathologic factors. In contrast, this prognostic effect was strengthened by the joint presence of CDKN2A methylation and KRAS mutations, which independently predicted recurrence of cancer and was associated with poor overall and cancer-specific survival. This study has identified a subgroup of more aggressive rectal cancers that may arise through the KRAS-p16 pathway. It has been previously shown that an interaction of p16 deficiency and oncogenic KRAS promotes carcinogenesis in the mouse and is characterized by loss of oncogene-induced senescence. These findings may provide avenues for the discovery of new treatments in rectal cancer. © 2013 UICC.

Evaluating Diagnostic Accuracy of Noninvasive Tests in Assessment of Significant Liver Fibrosis in Chronic Hepatitis C Egyptian Patients.

PubMed

Omran, Dalia; Zayed, Rania A; Nabeel, Mohammed M; Mobarak, Lamiaa; Zakaria, Zeinab; Farid, Azza; Hassany, Mohamed; Saif, Sameh; Mostafa, Muhammad; Saad, Omar Khalid; Yosry, Ayman

2018-05-01

Stage of liver fibrosis is critical for treatment decision and prediction of outcomes in chronic hepatitis C (CHC) patients. We evaluated the diagnostic accuracy of transient elastography (TE)-FibroScan and noninvasive serum markers tests in the assessment of liver fibrosis in CHC patients, in reference to liver biopsy. One-hundred treatment-naive CHC patients were subjected to liver biopsy, TE-FibroScan, and eight serum biomarkers tests; AST/ALT ratio (AAR), AST to platelet ratio index (APRI), age-platelet index (AP index), fibrosis quotient (FibroQ), fibrosis 4 index (FIB-4), cirrhosis discriminant score (CDS), King score, and Goteborg University Cirrhosis Index (GUCI). Receiver operating characteristic curves were constructed to compare the diagnostic accuracy of these noninvasive methods in predicting significant fibrosis in CHC patients. TE-FibroScan predicted significant fibrosis at cutoff value 8.5 kPa with area under the receiver operating characteristic (AUROC) 0.90, sensitivity 83%, specificity 91.5%, positive predictive value (PPV) 91.2%, and negative predictive value (NPV) 84.4%. Serum biomarkers tests showed that AP index and FibroQ had the highest diagnostic accuracy in predicting significant liver fibrosis at cutoff 4.5 and 2.7, AUROC was 0.8 and 0.8 with sensitivity 73.6% and 73.6%, specificity 70.2% and 68.1%, PPV 71.1% and 69.8%, and NPV 72.9% and 72.3%, respectively. Combined AP index and FibroQ had AUROC 0.83 with sensitivity 73.6%, specificity 80.9%, PPV 79.6%, and NPV 75.7% for predicting significant liver fibrosis. APRI, FIB-4, CDS, King score, and GUCI had intermediate accuracy in predicting significant liver fibrosis with AUROC 0.68, 0.78, 0.74, 0.74, and 0.67, respectively, while AAR had low accuracy in predicting significant liver fibrosis. TE-FibroScan is the most accurate noninvasive alternative to liver biopsy. AP index and FibroQ, either as individual tests or combined, have good accuracy in predicting significant liver fibrosis

Significant body point labeling and tracking.

PubMed

Azhar, Faisal; Tjahjadi, Tardi

2014-09-01

In this paper, a method is presented to label and track anatomical landmarks (e.g., head, hand/arm, feet), which are referred to as significant body points (SBPs), using implicit body models. By considering the human body as an inverted pendulum model, ellipse fitting and contour moments are applied to classify it as being in Stand, Sit, or Lie posture. A convex hull of the silhouette contour is used to determine the locations of SBPs. The particle filter or a motion flow-based method is used to predict SBPs in occlusion. Stick figures of various activities are generated by connecting the SBPs. The qualitative and quantitative evaluation show that the proposed method robustly labels and tracks SBPs in various activities of two different (low and high) resolution data sets.

Prevalence and prognostic significance of hyperkalemia in hospitalized patients with cirrhosis.

PubMed

Maiwall, Rakhi; Kumar, Suman; Sharma, Manoj Kumar; Wani, Zeeshan; Ozukum, Mulu; Sarin, Shiv Kumar

2016-05-01

The prevalence and clinical significance of hyponatremia in cirrhotics have been well studied; however, there are limited data on hyperkalemia in cirrhotics. We evaluated the prevalence and prognostic significance of hyperkalemia in hospitalized patients with cirrhosis and developed a prognostic model incorporating potassium for prediction of liver-related death in these patients. The training derivative cohort of patients was used for development of prognostic scores (Group A, n = 1160), which were validated in a large prospective cohort of cirrhotic patients. (Group B, n = 2681) of cirrhosis. Hyperkalemia was seen in 189 (14.1%) and 336 (12%) in Group A and Group B, respectively. Potassium showed a significant association that was direct with creatinine (P < 0.001) and urea (P < 0.001) and inverse with sodium (P < 0.001). Mortality was also significantly higher in patients with hyperkalemia (P = 0.0015, Hazard Ratio (HR) 1.3, 95% confidence interval 1.11-1.57). Combination of all these parameters into a single value predictor, that is, renal dysfunction index predicted mortality better than the individual components. Combining renal dysfunction index with other known prognostic markers (i.e. serum bilirubin, INR, albumin, hepatic encephalopathy, and ascites) in the "K" model predicted both short-term and long-term mortality with an excellent accuracy (Concordance-index 0.78 and 0.80 in training and validation cohorts, respectively). This was also superior to Model for End-stage Liver Disease, Model for End-stage liver disease sodium (MELDNa), and Child-Turcott-Pugh scores. Cirrhotics frequently have impaired potassium homeostasis, which has a prognostic significance. Serum potassium correlates directly with serum creatinine and urea and inversely with serum sodium. The model incorporating serum potassium developed from this study ("K"model) can predict death in advanced cirrhotics with an excellent accuracy. © 2015 Journal of

The cosmopolitan maternal heritage of the Thoroughbred racehorse breed shows a significant contribution from British and Irish native mares.

PubMed

Bower, M A; Campana, M G; Whitten, M; Edwards, C J; Jones, H; Barrett, E; Cassidy, R; Nisbet, R E R; Hill, E W; Howe, C J; Binns, M

2011-04-23

The paternal origins of Thoroughbred racehorses trace back to a handful of Middle Eastern stallions, imported to the British Isles during the seventeenth century. Yet, few details of the foundation mares were recorded, in many cases not even their names (several different maternal lineages trace back to 'A Royal Mare'). This has fuelled intense speculation over their origins. We examined mitochondrial DNA from 1929 horses to determine the origin of Thoroughbred foundation mares. There is no evidence to support exclusive Arab maternal origins as some historical records have suggested, or a significant importation of Oriental mares (the term used in historic records to refer to Middle East and western Asian breeds including Arab, Akhal-Teke, Barb and Caspian). Instead, we show that Thoroughbred foundation mares had a cosmopolitan European heritage with a far greater contribution from British and Irish Native mares than previously recognized.

A grey NGM(1,1, k) self-memory coupling prediction model for energy consumption prediction.

PubMed

Guo, Xiaojun; Liu, Sifeng; Wu, Lifeng; Tang, Lingling

2014-01-01

Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations. Although there are several prediction techniques, selection of the most appropriate technique is of vital importance. As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM(1,1, k) self-memory coupling prediction model is put forward in order to promote the predictive performance. It achieves organic integration of the self-memory principle of dynamic system and grey NGM(1,1, k) model. The traditional grey model's weakness as being sensitive to initial value can be overcome by the self-memory principle. In this study, total energy, coal, and electricity consumption of China is adopted for demonstration by using the proposed coupling prediction technique. The results show the superiority of NGM(1,1, k) self-memory coupling prediction model when compared with the results from the literature. Its excellent prediction performance lies in that the proposed coupling model can take full advantage of the systematic multitime historical data and catch the stochastic fluctuation tendency. This work also makes a significant contribution to the enrichment of grey prediction theory and the extension of its application span.

Four-phonon scattering significantly reduces intrinsic thermal conductivity of solids

NASA Astrophysics Data System (ADS)

Feng, Tianli; Lindsay, Lucas; Ruan, Xiulin

2017-10-01

For decades, the three-phonon scattering process has been considered to govern thermal transport in solids, while the role of higher-order four-phonon scattering has been persistently unclear and so ignored. However, recent quantitative calculations of three-phonon scattering have often shown a significant overestimation of thermal conductivity as compared to experimental values. In this Rapid Communication we show that four-phonon scattering is generally important in solids and can remedy such discrepancies. For silicon and diamond, the predicted thermal conductivity is reduced by 30% at 1000 K after including four-phonon scattering, bringing predictions in excellent agreement with measurements. For the projected ultrahigh-thermal conductivity material, zinc-blende BAs, a competitor of diamond as a heat sink material, four-phonon scattering is found to be strikingly strong as three-phonon processes have an extremely limited phase space for scattering. The four-phonon scattering reduces the predicted thermal conductivity from 2200 to 1400 W/m K at room temperature. The reduction at 1000 K is 60%. We also find that optical phonon scattering rates are largely affected, being important in applications such as phonon bottlenecks in equilibrating electronic excitations. Recognizing that four-phonon scattering is expensive to calculate, in the end we provide some guidelines on how to quickly assess the significance of four-phonon scattering, based on energy surface anharmonicity and the scattering phase space. Our work clears the decades-long fundamental question of the significance of higher-order scattering, and points out ways to improve thermoelectrics, thermal barrier coatings, nuclear materials, and radiative heat transfer.

Predicting Performance in Higher Education Using Proximal Predictors.

PubMed

Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

2016-01-01

We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance.

Predictive significance of the European LeukemiaNet classification of genetic aberrations in patients with acute myeloid leukaemia undergoing allogeneic stem cell transplantation.

PubMed

Hemmati, Philipp G; Vuong, Lam G; Terwey, Theis H; Jehn, Christian F; le Coutre, Philipp; Penack, Olaf; Na, Il-Kang; Dörken, Bernd; Arnold, Renate

2017-02-01

The purpose of this study was to evaluate the predictive capacity of the European LeukemiaNet (ELN) classification of genetic risk in patients with acute myeloid leukaemia (AML) undergoing allogeneic stem cell transplantation (alloSCT). We retrospectively analysed 274 patients transplanted at our centre between 2004 and 2014. The ELN grouping is comparable to the Southwest Oncology Group/Eastern Cooperative Oncology Group (SWOG/ECOG) stratification in predicting the outcome after alloSCT [overall P = 0.0064 for disease-free survival (DFS), overall P = 0.003 for relapse]. Patients with an intermediate-1 profile have a significantly elevated 5-yr relapse incidence as compared to favourable risk patients, that is 40% vs. 15%, [hazard ratio (HR) 2.58, P = 0.048]. An intermediate-1 risk profile is an independent predictor for relapse as determined by multivariate Cox regression analysis (HR 3.05, P = 0.023). In intermediate-1 patients, the presence of an FLT3 internal tandem duplication (FLT3-ITD) is associated with a significantly increased relapse incidence (P = 0.0323), and a lower DFS (P = 0.0465). FLT3-ITD is an independent predictor for overall survival, DFS and relapse incidence in the intermediate-1 subgroup. The ELN stratification of genetic risk predicts the outcome of patients with AML undergoing alloSCT. Patients with an intermediate-1 profile have a high risk for treatment failure due to relapse, which prompts the development of alternative treatment strategies. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance.

PubMed

Kramer, Karen L; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children's growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children's monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children's growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children's growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children's growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance.

Children with autism spectrum disorder show reduced adaptation to number

PubMed Central

Turi, Marco; Burr, David C.; Igliozzi, Roberta; Aagten-Murphy, David; Muratori, Filippo; Pellicano, Elizabeth

2015-01-01

Autism is known to be associated with major perceptual atypicalities. We have recently proposed a general model to account for these atypicalities in Bayesian terms, suggesting that autistic individuals underuse predictive information or priors. We tested this idea by measuring adaptation to numerosity stimuli in children diagnosed with autism spectrum disorder (ASD). After exposure to large numbers of items, stimuli with fewer items appear to be less numerous (and vice versa). We found that children with ASD adapted much less to numerosity than typically developing children, although their precision for numerosity discrimination was similar to that of the typical group. This result reinforces recent findings showing reduced adaptation to facial identity in ASD and goes on to show that reduced adaptation is not unique to faces (social stimuli with special significance in autism), but occurs more generally, for both parietal and temporal functions, probably reflecting inefficiencies in the adaptive interpretation of sensory signals. These results provide strong support for the Bayesian theories of autism. PMID:26056294

Prediction of Protein Configurational Entropy (Popcoen).

PubMed

Goethe, Martin; Gleixner, Jan; Fita, Ignacio; Rubi, J Miguel

2018-03-13

A knowledge-based method for configurational entropy prediction of proteins is presented; this methodology is extremely fast, compared to previous approaches, because it does not involve any type of configurational sampling. Instead, the configurational entropy of a query fold is estimated by evaluating an artificial neural network, which was trained on molecular-dynamics simulations of ∼1000 proteins. The predicted entropy can be incorporated into a large class of protein software based on cost-function minimization/evaluation, in which configurational entropy is currently neglected for performance reasons. Software of this type is used for all major protein tasks such as structure predictions, proteins design, NMR and X-ray refinement, docking, and mutation effect predictions. Integrating the predicted entropy can yield a significant accuracy increase as we show exemplarily for native-state identification with the prominent protein software FoldX. The method has been termed Popcoen for Prediction of Protein Configurational Entropy. An implementation is freely available at http://fmc.ub.edu/popcoen/ .

Significance of blood pressure variability in patients with sepsis.

PubMed

Pandey, Nishant Raj; Bian, Yu-Yao; Shou, Song-Tao

2014-01-01

This study was undertaken to observe the characteristics of blood pressure variability (BPV) and sepsis and to investigate changes in blood pressure and its value on the severity of illness in patients with sepsis. Blood parameters, APACHE II score, and 24-hour ambulatory BP were analyzed in 89 patients with sepsis. In patients with APACHE II score>19, the values of systolic blood pressure (SBPV), diasystolic blood pressure (DBPV), non-dipper percentage, cortisol (COR), lactate (LAC), platelet count (PLT) and glucose (GLU) were significantly higher than in those with APACHE II score ≤19 (P<0.05), whereas the values of procalcitonin (PCT), white blood cell (WBC), creatinine (Cr), PaO2, C-reactive protein (CRP), adrenocorticotropic hormone (ACTH) and tumor necrosis factor α (TNF-α) were not statistically significant (P>0.05). Correlation analysis showed that APACHE II scores correlated significantly with SBPV and DBPV (P<0.01, r=0.732 and P<0.01, r=0.762). SBPV and DBPV were correlated with COR (P=0.018 and r=0.318; P=0.008 and r=0.353 respectively). However, SBPV and DBPV were not correlated with TNF-α, IL-10, and PCT (P>0.05). Logistic regression analysis of SBPV, DBPV, APACHE II score, and LAC was used to predict prognosis in terms of survival and non-survival rates. Receiver operating characteristics curve (ROC) showed that DBPV was a better predictor of survival rate with an AUC value of 0.890. However, AUC of SBPV, APACHE II score, and LAC was 0.746, 0.831 and 0.915, respectively. The values of SBPV, DBPV and non-dipper percentage are higher in patients with sepsis. DBPV and SBPV can be used to predict the survival rate of patients with sepsis.

The predictive power of local properties of financial networks

NASA Astrophysics Data System (ADS)

Caraiani, Petre

2017-01-01

The literature on analyzing the dynamics of financial networks has focused so far on the predictive power of global measures of networks like entropy or index cohesive force. In this paper, I show that the local network properties have similar predictive power. I focus on key network measures like average path length, average degree or cluster coefficient, and also consider the diameter and the s-metric. Using Granger causality tests, I show that some of these measures have statistically significant prediction power with respect to the dynamics of aggregate stock market. Average path length is most robust relative to the frequency of data used or specification (index or growth rate). Most measures are found to have predictive power only for monthly frequency. Further evidences that support this view are provided through a simple regression model.

Incorporating significant amino acid pairs and protein domains to predict RNA splicing-related proteins with functional roles

NASA Astrophysics Data System (ADS)

Hsu, Justin Bo-Kai; Huang, Kai-Yao; Weng, Tzu-Ya; Huang, Chien-Hsun; Lee, Tzong-Yi

2014-01-01

Machinery of pre-mRNA splicing is carried out through the interaction of RNA sequence elements and a variety of RNA splicing-related proteins (SRPs) (e.g. spliceosome and splicing factors). Alternative splicing, which is an important post-transcriptional regulation in eukaryotes, gives rise to multiple mature mRNA isoforms, which encodes proteins with functional diversities. However, the regulation of RNA splicing is not yet fully elucidated, partly because SRPs have not yet been exhaustively identified and the experimental identification is labor-intensive. Therefore, we are motivated to design a new method for identifying SRPs with their functional roles in the regulation of RNA splicing. The experimentally verified SRPs were manually curated from research articles. According to the functional annotation of Splicing Related Gene Database, the collected SRPs were further categorized into four functional groups including small nuclear Ribonucleoprotein, Splicing Factor, Splicing Regulation Factor and Novel Spliceosome Protein. The composition of amino acid pairs indicates that there are remarkable differences among four functional groups of SRPs. Then, support vector machines (SVMs) were utilized to learn the predictive models for identifying SRPs as well as their functional roles. The cross-validation evaluation presents that the SVM models trained with significant amino acid pairs and functional domains could provide a better predictive performance. In addition, the independent testing demonstrates that the proposed method could accurately identify SRPs in mammals/plants as well as effectively distinguish between SRPs and RNA-binding proteins. This investigation provides a practical means to identifying potential SRPs and a perspective for exploring the regulation of RNA splicing.

Incorporating significant amino acid pairs and protein domains to predict RNA splicing-related proteins with functional roles.

PubMed

Hsu, Justin Bo-Kai; Huang, Kai-Yao; Weng, Tzu-Ya; Huang, Chien-Hsun; Lee, Tzong-Yi

2014-01-01

Machinery of pre-mRNA splicing is carried out through the interaction of RNA sequence elements and a variety of RNA splicing-related proteins (SRPs) (e.g. spliceosome and splicing factors). Alternative splicing, which is an important post-transcriptional regulation in eukaryotes, gives rise to multiple mature mRNA isoforms, which encodes proteins with functional diversities. However, the regulation of RNA splicing is not yet fully elucidated, partly because SRPs have not yet been exhaustively identified and the experimental identification is labor-intensive. Therefore, we are motivated to design a new method for identifying SRPs with their functional roles in the regulation of RNA splicing. The experimentally verified SRPs were manually curated from research articles. According to the functional annotation of Splicing Related Gene Database, the collected SRPs were further categorized into four functional groups including small nuclear Ribonucleoprotein, Splicing Factor, Splicing Regulation Factor and Novel Spliceosome Protein. The composition of amino acid pairs indicates that there are remarkable differences among four functional groups of SRPs. Then, support vector machines (SVMs) were utilized to learn the predictive models for identifying SRPs as well as their functional roles. The cross-validation evaluation presents that the SVM models trained with significant amino acid pairs and functional domains could provide a better predictive performance. In addition, the independent testing demonstrates that the proposed method could accurately identify SRPs in mammals/plants as well as effectively distinguish between SRPs and RNA-binding proteins. This investigation provides a practical means to identifying potential SRPs and a perspective for exploring the regulation of RNA splicing.

Clinical Significance of the Prognostic Nutritional Index for Predicting Short- and Long-Term Surgical Outcomes After Gastrectomy: A Retrospective Analysis of 7781 Gastric Cancer Patients.

PubMed

Lee, Jee Youn; Kim, Hyoung-Il; Kim, You-Na; Hong, Jung Hwa; Alshomimi, Saeed; An, Ji Yeong; Cheong, Jae-Ho; Hyung, Woo Jin; Noh, Sung Hoon; Kim, Choong-Bai

2016-05-01

To evaluate the predictive and prognostic significance of the prognostic nutritional index (PNI) in a large cohort of gastric cancer patients who underwent gastrectomy.Assessing a patient's immune and nutritional status, PNI has been reported as a predictive marker for surgical outcomes in various types of cancer.We retrospectively reviewed data from a prospectively maintained database of 7781 gastric cancer patients who underwent gastrectomy from January 2001 to December 2010 at a single center. From this data, we analyzed clinicopathologic characteristics, PNI, and short- and long-term surgical outcomes for each patient. We used the PNI value for the 10th percentile (46.70) of the study cohort as a cut-off for dividing patients into low and high PNI groups.Regarding short-term outcomes, multivariate analysis showed a low PNI (odds ratio [OR] = 1.505, 95% CI = 1.212-1.869, P <0.001), old age, male sex, high body mass index, medical comorbidity, total gastrectomy, and combined resection to be independent predictors of postoperative complications. Among these, only low PNI (OR = 4.279, 95% CI = 1.760-10.404, P = 0.001) and medical comorbidity were independent predictors of postoperative mortality. For long-term outcomes, low PNI was a poor prognostic factor for overall survival, but not recurrence (overall survival: hazard ratio [HR] = 1.383, 95% CI = 1.221-1.568, P < 0.001; recurrence-free survival: HR = 1.142, 95% CI = 0.985-1.325, P = 0.078).PNI can be used to predict patients at increased risk of postoperative morbidity and mortality. Although PNI was an independent prognostic factor for overall survival, the index was not associated with cancer recurrence.

Gene Expression Profiling Predicts the Development of Oral Cancer

PubMed Central

Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

2011-01-01

Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

Predictive control and estimation algorithms for the NASA/JPL 70-meter antennas

NASA Technical Reports Server (NTRS)

Gawronski, W.

1991-01-01

A modified output prediction procedure and a new controller design is presented based on the predictive control law. Also, a new predictive estimator is developed to complement the controller and to enhance system performance. The predictive controller is designed and applied to the tracking control of the Deep Space Network 70 m antennas. Simulation results show significant improvement in tracking performance over the linear quadratic controller and estimator presently in use.

Potential predictability of a Colombian river flow

NASA Astrophysics Data System (ADS)

Córdoba-Machado, Samir; Palomino-Lemus, Reiner; Quishpe-Vásquez, César; García-Valdecasas-Ojeda, Matilde; Raquel Gámiz-Fortis, Sonia; Castro-Díez, Yolanda; Jesús Esteban-Parra, María

2017-04-01

In this study the predictability of an important Colombian river (Cauca) has been analysed based on the use of climatic variables as potential predictors. Cauca River is considered one of the most important rivers of Colombia because its basin supports important productive activities related with the agriculture, such as the production of coffee or sugar. Potential relationships between the Cauca River seasonal streamflow anomalies and different climatic variables such as sea surface temperature (SST), precipitation (Pt), temperature over land (Tm) and soil water (Sw) have been analysed for the period 1949-2009. For this end, moving correlation analysis of 30 years have been carried out for lags from one to four seasons for the global SST, and from one to two seasons for South America Pt, Tm and Sw. Also, the stability of the significant correlations have been also studied, identifying the regions used as potential predictors of streamflow. Finally, in order to establish a prediction scheme based on the previous stable correlations, a Principal Component Analysis (PCA) applied on the potential predictor regions has been carried out in order to obtain a representative time series for each predictor field. Significant and stable correlations between the seasonal streamflow and the tropical Pacific SST (El Niño region) are found for lags from one to four (one-year) season. Additionally, some regions in the Indian and Atlantic Oceans also show significant and stable correlations at different lags, highlighting the importance that exerts the Atlantic SST on the hydrology of Colombia. Also significant and stable correlations are found with the Pt, Tm and Sw for some regions over South America, at lags of one and two seasons. The prediction of Cauca seasonal streamflow based on this scheme shows an acceptable skill and represents a relative improvement compared with the predictability obtained using the teleconnection indices associated with El Niño. Keywords

Predicting the effect of disability on employment status and income.

PubMed

Randolph, Diane Smith

2004-01-01

Research shows that participation in employment contributes to life satisfaction for persons with disabilities [18]. Title I of the Americans with Disabilities Act (ADA) sought to prohibit discrimination against persons with disabilities in the workplace, however, the ADA's effectiveness remains controversial. This research utilizes data from the disability supplement of the 2000 Behavioral Risk Factor Surveillance System to examine the impact of disability status on predicting employment status and income. Confounding variables such as gender, age, educational level, race and marital/parental status are examined regarding their influence on results. Results from analysis utilizing zero-order correlation, linear and logistic regression analysis techniques revealed that disability status has a significant predictive effect on inability to work. Furthermore, results continue to show that despite legislation, the higher the level of disability, the lower the employment status (those employed for wages) and income. Finally, disability status, coupled with being female or decreased educational level, consistently shows significance in predicting lower employment status and income than men or non-minorities with disabilities. Future research opportunities and policy implications are discussed with regard to the results presented.

The no-show patient in the model family practice unit.

PubMed

Dervin, J V; Stone, D L; Beck, C H

1978-12-01

Appointment breaking by patients causes problems for the physician's office. Patients who neither keep nor cancel their appointments are often referred to as "no shows." Twenty variables were identified as potential predictors of no-show behavior. These predictors were applied to 291 Family Practice Center patients during a one-month study in April 1977. A discriminant function and multiple regression procedure were utilized ascertain the predictability of the selected variables. Predictive accuracy of the variables was 67.4 percent compared to the presently utilized constant predictor technique, which is 73 percent accurate. Modification of appointment schedules based upon utilization of the variables studies as predictors of show/no-show behavior does not appear to be an effective strategy in the Family Practice Center of the Community Hospital of Sonoma County, Santa Rosa, due to the high proportion of patients who do, in fact, show. In clinics with lower show rates, the technique may prove to be an effective strategy.

Metabolomic prediction of yield in hybrid rice.

PubMed

Xu, Shizhong; Xu, Yang; Gong, Liang; Zhang, Qifa

2016-10-01

Rice (Oryza sativa) provides a staple food source for more than 50% of the world's population. An increase in yield can significantly contribute to global food security. Hybrid breeding can potentially help to meet this goal because hybrid rice often shows a considerable increase in yield when compared with pure-bred cultivars. We recently developed a marker-guided prediction method for hybrid yield and showed a substantial increase in yield through genomic hybrid breeding. We now have transcriptomic and metabolomic data as potential resources for prediction. Using six prediction methods, including least absolute shrinkage and selection operator (LASSO), best linear unbiased prediction (BLUP), stochastic search variable selection, partial least squares, and support vector machines using the radial basis function and polynomial kernel function, we found that the predictability of hybrid yield can be further increased using these omic data. LASSO and BLUP are the most efficient methods for yield prediction. For high heritability traits, genomic data remain the most efficient predictors. When metabolomic data are used, the predictability of hybrid yield is almost doubled compared with genomic prediction. Of the 21 945 potential hybrids derived from 210 recombinant inbred lines, selection of the top 10 hybrids predicted from metabolites would lead to a ~30% increase in yield. We hypothesize that each metabolite represents a biologically built-in genetic network for yield; thus, using metabolites for prediction is equivalent to using information integrated from these hidden genetic networks for yield prediction. © 2016 The Authors The Plant Journal © 2016 John Wiley & Sons Ltd.

A Grey NGM(1,1, k) Self-Memory Coupling Prediction Model for Energy Consumption Prediction

PubMed Central

Guo, Xiaojun; Liu, Sifeng; Wu, Lifeng; Tang, Lingling

2014-01-01

Energy consumption prediction is an important issue for governments, energy sector investors, and other related corporations. Although there are several prediction techniques, selection of the most appropriate technique is of vital importance. As for the approximate nonhomogeneous exponential data sequence often emerging in the energy system, a novel grey NGM(1,1, k) self-memory coupling prediction model is put forward in order to promote the predictive performance. It achieves organic integration of the self-memory principle of dynamic system and grey NGM(1,1, k) model. The traditional grey model's weakness as being sensitive to initial value can be overcome by the self-memory principle. In this study, total energy, coal, and electricity consumption of China is adopted for demonstration by using the proposed coupling prediction technique. The results show the superiority of NGM(1,1, k) self-memory coupling prediction model when compared with the results from the literature. Its excellent prediction performance lies in that the proposed coupling model can take full advantage of the systematic multitime historical data and catch the stochastic fluctuation tendency. This work also makes a significant contribution to the enrichment of grey prediction theory and the extension of its application span. PMID:25054174

Marker-Based Estimates Reveal Significant Non-additive Effects in Clonally Propagated Cassava (Manihot esculenta): Implications for the Prediction of Total Genetic Value and the Selection of Varieties.

PubMed

Wolfe, Marnin D; Kulakow, Peter; Rabbi, Ismail Y; Jannink, Jean-Luc

2016-08-31

In clonally propagated crops, non-additive genetic effects can be effectively exploited by the identification of superior genetic individuals as varieties. Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop that feeds hundreds of millions. We quantified the amount and nature of non-additive genetic variation for three key traits in a breeding population of cassava from sub-Saharan Africa using additive and non-additive genome-wide marker-based relationship matrices. We then assessed the accuracy of genomic prediction for total (additive plus non-additive) genetic value. We confirmed previous findings based on diallel populations, that non-additive genetic variation is significant for key cassava traits. Specifically, we found that dominance is particularly important for root yield and epistasis contributes strongly to variation in CMD resistance. Further, we showed that total genetic value predicted observed phenotypes more accurately than additive only models for root yield but not for dry matter content, which is mostly additive or for CMD resistance, which has high narrow-sense heritability. We address the implication of these results for cassava breeding and put our work in the context of previous results in cassava, and other plant and animal species. Copyright © 2016 Author et al.

Correlation of clinical predictions and surgical results in maxillary superior repositioning.

PubMed

Tabrizi, Reza; Zamiri, Barbad; Kazemi, Hamidreza

2014-05-01

This is a prospective study to evaluate the accuracy of clinical predictions related to surgical results in subjects who underwent maxillary superior repositioning without anterior-posterior movement. Surgeons' predictions according to clinical (tooth show at rest and at the maximum smile) and cephalometric evaluation were documented for the amount of maxillary superior repositioning. Overcorrection or undercorrection was documented for every subject 1 year after the operations. Receiver operating characteristic curve test was used to find a cutoff point in prediction errors and to determine positive predictive value (PPV) and negative predictive value. Forty subjects (14 males and 26 females) were studied. Results showed a significant difference between changes in the tooth show at rest and at the maximum smile line before and after surgery. Analysis of the data demonstrated no correlation between the predictive data and the surgical results. The incidence of undercorrection (25%) was more common than overcorrection (7.5%). The cutoff point for errors in predictions was 5 mm for tooth show at rest and 15 mm at the maximum smile. When the amount of the presurgical tooth show at rest was more than 5 mm, 50.5% of clinical predictions did not match the clinical results (PPV), and 75% of clinical predictions showed the same results when the tooth show was less than 5 mm (negative predictive value). When the amount of presurgical tooth shown in the maximum smile line was more than 15 mm, 75% of clinical predictions did not match with clinical results (PPV), and 25% of the predictions had the same results because the tooth show at the maximum smile was lower than 15 mm. Clinical predictions according to the tooth show at rest and at the maximum smile have a poor correlation with clinical results in maxillary superior repositioning for vertical maxillary excess. The risk of errors in predictions increased when the amount of superior repositioning of the maxilla increased

Using Conversation Topics for Predicting Therapy Outcomes in Schizophrenia

PubMed Central

Howes, Christine; Purver, Matthew; McCabe, Rose

2013-01-01

Previous research shows that aspects of doctor-patient communication in therapy can predict patient symptoms, satisfaction and future adherence to treatment (a significant problem with conditions such as schizophrenia). However, automatic prediction has so far shown success only when based on low-level lexical features, and it is unclear how well these can generalize to new data, or whether their effectiveness is due to their capturing aspects of style, structure or content. Here, we examine the use of topic as a higher-level measure of content, more likely to generalize and to have more explanatory power. Investigations show that while topics predict some important factors such as patient satisfaction and ratings of therapy quality, they lack the full predictive power of lower-level features. For some factors, unsupervised methods produce models comparable to manual annotation. PMID:23943658

Sibling Competition & Growth Tradeoffs. Biological vs. Statistical Significance

PubMed Central

Kramer, Karen L.; Veile, Amanda; Otárola-Castillo, Erik

2016-01-01

Early childhood growth has many downstream effects on future health and reproduction and is an important measure of offspring quality. While a tradeoff between family size and child growth outcomes is theoretically predicted in high-fertility societies, empirical evidence is mixed. This is often attributed to phenotypic variation in parental condition. However, inconsistent study results may also arise because family size confounds the potentially differential effects that older and younger siblings can have on young children’s growth. Additionally, inconsistent results might reflect that the biological significance associated with different growth trajectories is poorly understood. This paper addresses these concerns by tracking children’s monthly gains in height and weight from weaning to age five in a high fertility Maya community. We predict that: 1) as an aggregate measure family size will not have a major impact on child growth during the post weaning period; 2) competition from young siblings will negatively impact child growth during the post weaning period; 3) however because of their economic value, older siblings will have a negligible effect on young children’s growth. Accounting for parental condition, we use linear mixed models to evaluate the effects that family size, younger and older siblings have on children’s growth. Congruent with our expectations, it is younger siblings who have the most detrimental effect on children’s growth. While we find statistical evidence of a quantity/quality tradeoff effect, the biological significance of these results is negligible in early childhood. Our findings help to resolve why quantity/quality studies have had inconsistent results by showing that sibling competition varies with sibling age composition, not just family size, and that biological significance is distinct from statistical significance. PMID:26938742

Skillful prediction of northern climate provided by the ocean

PubMed Central

Årthun, Marius; Eldevik, Tor; Viste, Ellen; Drange, Helge; Furevik, Tore; Johnson, Helen L.; Keenlyside, Noel S.

2017-01-01

It is commonly understood that a potential for skillful climate prediction resides in the ocean. It nevertheless remains unresolved to what extent variable ocean heat is imprinted on the atmosphere to realize its predictive potential over land. Here we assess from observations whether anomalous heat in the Gulf Stream's northern extension provides predictability of northwestern European and Arctic climate. We show that variations in ocean temperature in the high latitude North Atlantic and Nordic Seas are reflected in the climate of northwestern Europe and in winter Arctic sea ice extent. Statistical regression models show that a significant part of northern climate variability thus can be skillfully predicted up to a decade in advance based on the state of the ocean. Particularly, we predict that Norwegian air temperature will decrease over the coming years, although staying above the long-term (1981–2010) average. Winter Arctic sea ice extent will remain low but with a general increase towards 2020. PMID:28631732

Skillful prediction of northern climate provided by the ocean

NASA Astrophysics Data System (ADS)

Årthun, Marius; Eldevik, Tor; Viste, Ellen; Drange, Helge; Furevik, Tore; Johnson, Helen L.; Keenlyside, Noel S.

2017-06-01

It is commonly understood that a potential for skillful climate prediction resides in the ocean. It nevertheless remains unresolved to what extent variable ocean heat is imprinted on the atmosphere to realize its predictive potential over land. Here we assess from observations whether anomalous heat in the Gulf Stream's northern extension provides predictability of northwestern European and Arctic climate. We show that variations in ocean temperature in the high latitude North Atlantic and Nordic Seas are reflected in the climate of northwestern Europe and in winter Arctic sea ice extent. Statistical regression models show that a significant part of northern climate variability thus can be skillfully predicted up to a decade in advance based on the state of the ocean. Particularly, we predict that Norwegian air temperature will decrease over the coming years, although staying above the long-term (1981-2010) average. Winter Arctic sea ice extent will remain low but with a general increase towards 2020.

Sweat loss prediction using a multi-model approach

NASA Astrophysics Data System (ADS)

Xu, Xiaojiang; Santee, William R.

2011-07-01

A new multi-model approach (MMA) for sweat loss prediction is proposed to improve prediction accuracy. MMA was computed as the average of sweat loss predicted by two existing thermoregulation models: i.e., the rational model SCENARIO and the empirical model Heat Strain Decision Aid (HSDA). Three independent physiological datasets, a total of 44 trials, were used to compare predictions by MMA, SCENARIO, and HSDA. The observed sweat losses were collected under different combinations of uniform ensembles, environmental conditions (15-40°C, RH 25-75%), and exercise intensities (250-600 W). Root mean square deviation (RMSD), residual plots, and paired t tests were used to compare predictions with observations. Overall, MMA reduced RMSD by 30-39% in comparison with either SCENARIO or HSDA, and increased the prediction accuracy to 66% from 34% or 55%. Of the MMA predictions, 70% fell within the range of mean observed value ± SD, while only 43% of SCENARIO and 50% of HSDA predictions fell within the same range. Paired t tests showed that differences between observations and MMA predictions were not significant, but differences between observations and SCENARIO or HSDA predictions were significantly different for two datasets. Thus, MMA predicted sweat loss more accurately than either of the two single models for the three datasets used. Future work will be to evaluate MMA using additional physiological data to expand the scope of populations and conditions.

Protein docking prediction using predicted protein-protein interface.

PubMed

Li, Bin; Kihara, Daisuke

2012-01-10

Many important cellular processes are carried out by protein complexes. To provide physical pictures of interacting proteins, many computational protein-protein prediction methods have been developed in the past. However, it is still difficult to identify the correct docking complex structure within top ranks among alternative conformations. We present a novel protein docking algorithm that utilizes imperfect protein-protein binding interface prediction for guiding protein docking. Since the accuracy of protein binding site prediction varies depending on cases, the challenge is to develop a method which does not deteriorate but improves docking results by using a binding site prediction which may not be 100% accurate. The algorithm, named PI-LZerD (using Predicted Interface with Local 3D Zernike descriptor-based Docking algorithm), is based on a pair wise protein docking prediction algorithm, LZerD, which we have developed earlier. PI-LZerD starts from performing docking prediction using the provided protein-protein binding interface prediction as constraints, which is followed by the second round of docking with updated docking interface information to further improve docking conformation. Benchmark results on bound and unbound cases show that PI-LZerD consistently improves the docking prediction accuracy as compared with docking without using binding site prediction or using the binding site prediction as post-filtering. We have developed PI-LZerD, a pairwise docking algorithm, which uses imperfect protein-protein binding interface prediction to improve docking accuracy. PI-LZerD consistently showed better prediction accuracy over alternative methods in the series of benchmark experiments including docking using actual docking interface site predictions as well as unbound docking cases.

Systematic literature review shows that appetite rating does not predict energy intake.

PubMed

Holt, Guy M; Owen, Lauren J; Till, Sophie; Cheng, Yanying; Grant, Vicky A; Harden, Charlotte J; Corfe, Bernard M

2017-11-02

Ratings of appetite are commonly used to assess appetite modification following an intervention. Subjectively rated appetite is a widely employed proxy measure for energy intake (EI), measurement of which requires greater time and resources. However, the validity of appetite as a reliable predictor of EI has not yet been reviewed systematically. This literature search identified studies that quantified both appetite ratings and EI. Outcomes were predefined as: (1) agreement between self-reported appetite scores and EI; (2) no agreement between self-reported appetitescores and EI. The presence of direct statistical comparison between the endpoints, intervention type and study population were also recorded. 462 papers were included in this review. Appetite scores failed to correspond with EI in 51.3% of the total studies. Only 6% of all studies evaluated here reported a direct statistical comparison between appetite scores and EI. χ 2 analysis demonstrated that any relationship between EI and appetite was independent of study type stratification by age, gender or sample size. The very substantive corpus reviewed allows us to conclude that self-reported appetite ratings of appetite do not reliably predict EI. Caution should be exercised when drawing conclusions based from self-reported appetite scores in relation to prospective EI.

Significance of a Behavioral Economic Index of Reward Value in Predicting Drinking Problem Resolution

ERIC Educational Resources Information Center

Tucker, Jalie A.; Vuchinich, Rudy E.; Black, Bethany C.; Rippens, Paula D.

2006-01-01

This study investigated whether a behavioral economic index of the value of rewards available over different time horizons improved prediction of drinking outcomes beyond established biopsychosocial predictors. Preferences for immediate drinking versus more delayed rewards made possible by saving money were determined from expenditures prior to…

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

PubMed

Zheng, Ce; Kurgan, Lukasz

2008-10-10

beta-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of beta-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based beta-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential beta-turns, while the remaining four amino acids are useful to predict non-beta-turns. Empirical evaluation using three nonredundant datasets shows favorable Q total, Q predicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Q total barrier and achieves Q total = 80.9%, MCC = 0.47, and Q predicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Experiments show that the proposed method constitutes an improvement over the competing prediction

Mid-Treatment Sleep Duration Predicts Clinically Significant Knee Osteoarthritis Pain reduction at 6 months: Effects From a Behavioral Sleep Medicine Clinical Trial.

PubMed

Salwen, Jessica K; Smith, Michael T; Finan, Patrick H

2017-02-01

To determine the relative influence of sleep continuity (sleep efficiency, sleep onset latency, total sleep time [TST], and wake after sleep onset) on clinical pain outcomes within a trial of cognitive behavioral therapy for insomnia (CBT-I) for patients with comorbid knee osteoarthritis and insomnia. Secondary analyses were performed on data from 74 patients with comorbid insomnia and knee osteoarthritis who completed a randomized clinical trial of 8-session multicomponent CBT-I versus an active behavioral desensitization control condition (BD), including a 6-month follow-up assessment. Data used herein include daily diaries of sleep parameters, actigraphy data, and self-report questionnaires administered at specific time points. Patients who reported at least 30% improvement in self-reported pain from baseline to 6-month follow-up were considered responders (N = 31). Pain responders and nonresponders did not differ significantly at baseline across any sleep continuity measures. At mid-treatment, only TST predicted pain response via t tests and logistic regression, whereas other measures of sleep continuity were nonsignificant. Recursive partitioning analyses identified a minimum cut-point of 382 min of TST achieved at mid-treatment in order to best predict pain improvements 6-month posttreatment. Actigraphy results followed the same pattern as daily diary-based results. Clinically significant pain reductions in response to both CBT-I and BD were optimally predicted by achieving approximately 6.5 hr sleep duration by mid-treatment. Thus, tailoring interventions to increase TST early in treatment may be an effective strategy to promote long-term pain reductions. More comprehensive research on components of behavioral sleep medicine treatments that contribute to pain response is warranted. © Sleep Research Society 2016. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Development of Operational Wave-Tide-Storm surges Coupling Prediction System

NASA Astrophysics Data System (ADS)

You, S. H.; Park, S. W.; Kim, J. S.; Kim, K. L.

2009-04-01

uncoupling and coupling cases for each typhoon. When the typhoon Nabi hit at southern coast of Kyushu, predicted significant wave height reached over 10 m. The difference of significant wave height between wave and wave-tide-storm surges model represents large variation at the southwestern coast of Korea with about 0.5 m. Other typhoon cases also show similar results with typhoon Nabi case. For typhoon Shanshan case the difference of significant wave height reached up to 0.3 m. When the typhoon Nari was affected in the southern coast of Korea, predicted significant wave height was about 5m. The typhoon Nari case also shows the difference of significant wave height similar with other typhoon cases. Using the observation from ocean buoy operated by KMA, we compared wave information simulated by wave and wave-storm surges coupling model. The significant wave height simulated by wave-tide-storm surges model shows the tidal modulation features in the western and southern coast of Korea. And the difference of significant wave height between two models reached up to 0.5 m. The coupling effect also can be identified in the wave direction, wave period and wave length. In addition, wave spectrum is also changeable due to coupling effect of wave-tide-storm surges model. The development, testing and application of a coupling module in which wave-tide-storm surges are incorporated within the frame of KMA Ocean prediction system, has been considered as a step forward in respect of ocean forecasting. In addition, advanced wave prediction model will be applicable to the effect of ocean in the weather forecasting system. The main purpose of this study is to show how the coupling module developed and to report on a series of experiments dealing with the sensitivities and real case prediction of coupling wave-tide-storm surges prediction system.

Highly accurate prediction of emotions surrounding the attacks of September 11, 2001 over 1-, 2-, and 7-year prediction intervals.

PubMed

Doré, Bruce P; Meksin, Robert; Mather, Mara; Hirst, William; Ochsner, Kevin N

2016-06-01

In the aftermath of a national tragedy, important decisions are predicated on judgments of the emotional significance of the tragedy in the present and future. Research in affective forecasting has largely focused on ways in which people fail to make accurate predictions about the nature and duration of feelings experienced in the aftermath of an event. Here we ask a related but understudied question: can people forecast how they will feel in the future about a tragic event that has already occurred? We found that people were strikingly accurate when predicting how they would feel about the September 11 attacks over 1-, 2-, and 7-year prediction intervals. Although people slightly under- or overestimated their future feelings at times, they nonetheless showed high accuracy in forecasting (a) the overall intensity of their future negative emotion, and (b) the relative degree of different types of negative emotion (i.e., sadness, fear, or anger). Using a path model, we found that the relationship between forecasted and actual future emotion was partially mediated by current emotion and remembered emotion. These results extend theories of affective forecasting by showing that emotional responses to an event of ongoing national significance can be predicted with high accuracy, and by identifying current and remembered feelings as independent sources of this accuracy. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Highly accurate prediction of emotions surrounding the attacks of September 11, 2001 over 1-, 2-, and 7-year prediction intervals

PubMed Central

Doré, B.P.; Meksin, R.; Mather, M.; Hirst, W.; Ochsner, K.N

2016-01-01

In the aftermath of a national tragedy, important decisions are predicated on judgments of the emotional significance of the tragedy in the present and future. Research in affective forecasting has largely focused on ways in which people fail to make accurate predictions about the nature and duration of feelings experienced in the aftermath of an event. Here we ask a related but understudied question: can people forecast how they will feel in the future about a tragic event that has already occurred? We found that people were strikingly accurate when predicting how they would feel about the September 11 attacks over 1-, 2-, and 7-year prediction intervals. Although people slightly under- or overestimated their future feelings at times, they nonetheless showed high accuracy in forecasting 1) the overall intensity of their future negative emotion, and 2) the relative degree of different types of negative emotion (i.e., sadness, fear, or anger). Using a path model, we found that the relationship between forecasted and actual future emotion was partially mediated by current emotion and remembered emotion. These results extend theories of affective forecasting by showing that emotional responses to an event of ongoing national significance can be predicted with high accuracy, and by identifying current and remembered feelings as independent sources of this accuracy. PMID:27100309

Significance of a diagnosis of atypical squamous cells of undetermined significance for Papanicolaou smears in perimenopausal and postmenopausal women.

PubMed

Keating, J T; Wang, H H

2001-04-25

The current study was conducted to determine the significance of a diagnosis of atypical squamous cells of undetermined significance (ASCUS) in perimenopausal and postmenopausal women. The reports for all Papanicolaou (Pap) smears viewed in the study institution's cytology laboratory over a 6-month period were reviewed. Women were divided into premenopausal (age < or = 45 years), perimenopausal (ages 46-54 years), and postmenopausal (age > or = 55 years) categories. Slide review and 2-year follow-up were obtained for selected cases diagnosed as ASCUS. ASCUS cases among the perimenopausal women were compared with an age-matched control group. The total number of abnormal Pap smears in the premenopausal, perimenopausal, and postmenopausal categories were 770 (6.8%), 104 (4.3%), and 67 (2.9%), with 482, 83, and 41 diagnoses of ASCUS, respectively. The ratio of ASCUS to squamous intraepithelial lesions (SIL) was 2.2 overall and 1.9, 7.5, and 4.1, respectively, for each group (P < 0.001). The positive predictive value for a diagnosis of SIL on subsequent Pap smears or biopsies was 22%, 12.2%, and 29.7%, respectively. Slide review showed that the premenopausal ASCUS cases appeared to have a higher percentage of nuclear-cytoplasmic ratio increase and nuclear membrane irregularities compared with the other categories (P = 0.03 and P = 0.02, respectively) and the perimenopausal group was found to have more ASCUS in metaplastic cells (P = 0.03). In perimenopausal women, slides diagnosed as ASCUS demonstrated more air-drying artifact than the control group (P = 0.004) but had less obvious atrophy (P = 0.01). Despite a decreased abnormality rate with increasing age, the results of the current study show that the perimenopausal and postmenopausal groups appear to have elevated ASCUS-to-SIL ratios. ASCUS appears to have a particularly low positive predictive value for SIL in perimenopausal women, and therefore most likely is overcalled in this age group. This may be attributable

Analysis of a large dataset of mycorrhiza inoculation field trials on potato shows highly significant increases in yield.

PubMed

Hijri, Mohamed

2016-04-01

An increasing human population requires more food production in nutrient-efficient systems in order to simultaneously meet global food needs while reducing the environmental footprint of agriculture. Arbuscular mycorrhizal fungi (AMF) have the potential to enhance crop yield, but their efficiency has yet to be demonstrated in large-scale crop production systems. This study reports an analysis of a dataset consisting of 231 field trials in which the same AMF inoculant (Rhizophagus irregularis DAOM 197198) was applied to potato over a 4-year period in North America and Europe under authentic field conditions. The inoculation was performed using a liquid suspension of AMF spores that was sprayed onto potato seed pieces, yielding a calculated 71 spores per seed piece. Statistical analysis showed a highly significant increase in marketable potato yield (ANOVA, P < 0.0001) for inoculated fields (42.2 tons/ha) compared with non-inoculated controls (38.3 tons/ha), irrespective of trial year. The average yield increase was 3.9 tons/ha, representing 9.5 % of total crop yield. Inoculation was profitable with a 0.67-tons/ha increase in yield, a threshold reached in almost 79 % of all trials. This finding clearly demonstrates the benefits of mycorrhizal-based inoculation on crop yield, using potato as a case study. Further improvements of these beneficial inoculants will help compensate for crop production deficits, both now and in the future.

Seasonal Predictability in a Model Atmosphere.

NASA Astrophysics Data System (ADS)

Lin, Hai

2001-07-01

The predictability of atmospheric mean-seasonal conditions in the absence of externally varying forcing is examined. A perfect-model approach is adopted, in which a global T21 three-level quasigeostrophic atmospheric model is integrated over 21 000 days to obtain a reference atmospheric orbit. The model is driven by a time-independent forcing, so that the only source of time variability is the internal dynamics. The forcing is set to perpetual winter conditions in the Northern Hemisphere (NH) and perpetual summer in the Southern Hemisphere.A significant temporal variability in the NH 90-day mean states is observed. The component of that variability associated with the higher-frequency motions, or climate noise, is estimated using a method developed by Madden. In the polar region, and to a lesser extent in the midlatitudes, the temporal variance of the winter means is significantly greater than the climate noise, suggesting some potential predictability in those regions.Forecast experiments are performed to see whether the presence of variance in the 90-day mean states that is in excess of the climate noise leads to some skill in the prediction of these states. Ensemble forecast experiments with nine members starting from slightly different initial conditions are performed for 200 different 90-day means along the reference atmospheric orbit. The serial correlation between the ensemble means and the reference orbit shows that there is skill in the 90-day mean predictions. The skill is concentrated in those regions of the NH that have the largest variance in excess of the climate noise. An EOF analysis shows that nearly all the predictive skill in the seasonal means is associated with one mode of variability with a strong axisymmetric component.

Making detailed predictions makes (some) predictions worse

NASA Astrophysics Data System (ADS)

Kelly, Theresa F.

In this paper, we investigate whether making detailed predictions about an event makes other predictions worse. Across 19 experiments, 10,895 participants, and 415,960 predictions about 724 professional sports games, we find that people who made detailed predictions about sporting events (e.g., how many hits each baseball team would get) made worse predictions about more general outcomes (e.g., which team would win). We rule out that this effect is caused by inattention or fatigue, thinking too hard, or a differential reliance on holistic information about the teams. Instead, we find that thinking about game-relevant details before predicting winning teams causes people to give less weight to predictive information, presumably because predicting details makes information that is relatively useless for predicting the winning team more readily accessible in memory and therefore incorporated into forecasts. Furthermore, we show that this differential use of information can be used to predict what kinds of games will and will not be susceptible to the negative effect of making detailed predictions.

The Diagnostic Performance of Multiparametric Magnetic Resonance Imaging to Detect Significant Prostate Cancer.

PubMed

Thompson, J E; van Leeuwen, P J; Moses, D; Shnier, R; Brenner, P; Delprado, W; Pulbrook, M; Böhm, M; Haynes, A M; Hayen, A; Stricker, P D

2016-05-01

We assess the accuracy of multiparametric magnetic resonance imaging for significant prostate cancer detection before diagnostic biopsy in men with an abnormal prostate specific antigen/digital rectal examination. A total of 388 men underwent multiparametric magnetic resonance imaging, including T2-weighted, diffusion weighted and dynamic contrast enhanced imaging before biopsy. Two radiologists used PI-RADS to allocate a score of 1 to 5 for suspicion of significant prostate cancer (Gleason 7 with more than 5% grade 4). PI-RADS 3 to 5 was considered positive. Transperineal template guided mapping biopsy of 18 regions (median 30 cores) was performed with additional manually directed cores from magnetic resonance imaging positive regions. The anatomical location, size and grade of individual cancer areas in the biopsy regions (18) as the primary outcome and in prostatectomy specimens (117) as the secondary outcome were correlated to the magnetic resonance imaging positive regions. Of the 388 men who were enrolled in the study 344 were analyzed. Multiparametric magnetic resonance imaging was positive in 77.0% of patients, 62.5% had prostate cancer and 41.6% had significant prostate cancer. The detection of significant prostate cancer by multiparametric magnetic resonance imaging had a sensitivity of 96%, specificity of 36%, negative predictive value of 92% and positive predictive value of 52%. Adding PI-RADS to the multivariate model, including prostate specific antigen, digital rectal examination, prostate volume and age, improved the AUC from 0.776 to 0.879 (p <0.001). Anatomical concordance analysis showed a low mismatch between the magnetic resonance imaging positive regions and biopsy positive regions (4 [2.9%]), and the significant prostate cancer area in the radical prostatectomy specimen (3 [3.3%]). In men with an abnormal prostate specific antigen/digital rectal examination, multiparametric magnetic resonance imaging detected significant prostate cancer

Significance of SYT8 For the Detection, Prediction, and Treatment of Peritoneal Metastasis From Gastric Cancer.

PubMed

Kanda, Mitsuro; Shimizu, Dai; Tanaka, Haruyoshi; Tanaka, Chie; Kobayashi, Daisuke; Hayashi, Masamichi; Iwata, Naoki; Niwa, Yukiko; Yamada, Suguru; Fujii, Tsutomu; Sugimoto, Hiroyuki; Murotani, Kenta; Fujiwara, Michitaka; Kodera, Yasuhiro

2018-03-01

To develop novel diagnostic and therapeutic targets specific for peritoneal metastasis of gastric cancer (GC). Advanced GC frequently recurs because of undetected micrometastases even after curative resection. Peritoneal metastasis has been the most frequent recurrent pattern after gastrectomy and is incurable. We conducted a recurrence pattern-specific transcriptome analysis in an independent cohort of 16 patients with stage III GC who underwent curative gastrectomy and adjuvant S-1 for screening candidate molecules specific for peritoneal metastasis of GC. Next, another 340 patients were allocated to discovery and validation sets (1:2) to evaluate the diagnostic and predictive value of the candidate molecule. The results of quantitative reverse-transcription PCR and immunohistochemical analysis were correlated with clinical characteristics and survival. The effects of siRNA-mediated knockdown on phenotype and fluorouracil sensitivity of GC cells were evaluated in vitro, and the therapeutic effects of siRNAs were evaluated using a mouse xenograft model. Synaptotagmin VIII (SYT8) was identified as a candidate biomarker specific to peritoneal metastasis. In the discovery set, the optimal cut-off of SYT8 expression was established as 0.005. Expression levels of SYT8 mRNA in GC tissues were elevated in the validation set comprising patients with peritoneal recurrence or metastasis. SYT8 levels above the cut-off value were significantly and specifically associated with peritoneal metastasis, and served as an independent prognostic marker for peritoneal recurrence-free survival of patients with stage II/III GC. The survival difference between patients with SYT8 levels above and below the cut-off was associated with patients who received adjuvant chemotherapy. Inhibition of SYT8 expression by GC cells correlated with decreased invasion, migration, and fluorouracil resistance. Intraperitoneal administration of SYT8-siRNA inhibited the growth of peritoneal nodules and

Bankruptcy prediction for credit risk using neural networks: a survey and new results.

PubMed

Atiya, A F

2001-01-01

The prediction of corporate bankruptcies is an important and widely studied topic since it can have significant impact on bank lending decisions and profitability. This work presents two contributions. First we review the topic of bankruptcy prediction, with emphasis on neural-network (NN) models. Second, we develop an NN bankruptcy prediction model. Inspired by one of the traditional credit risk models developed by Merton (1974), we propose novel indicators for the NN system. We show that the use of these indicators in addition to traditional financial ratio indicators provides a significant improvement in the (out-of-sample) prediction accuracy (from 81.46% to 85.5% for a three-year-ahead forecast).

Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments

PubMed Central

Zheng, Ce; Kurgan, Lukasz

2008-01-01

Background β-turn is a secondary protein structure type that plays significant role in protein folding, stability, and molecular recognition. To date, several methods for prediction of β-turns from protein sequences were developed, but they are characterized by relatively poor prediction quality. The novelty of the proposed sequence-based β-turn predictor stems from the usage of a window based information extracted from four predicted three-state secondary structures, which together with a selected set of position specific scoring matrix (PSSM) values serve as an input to the support vector machine (SVM) predictor. Results We show that (1) all four predicted secondary structures are useful; (2) the most useful information extracted from the predicted secondary structure includes the structure of the predicted residue, secondary structure content in a window around the predicted residue, and features that indicate whether the predicted residue is inside a secondary structure segment; (3) the PSSM values of Asn, Asp, Gly, Ile, Leu, Met, Pro, and Val were among the top ranked features, which corroborates with recent studies. The Asn, Asp, Gly, and Pro indicate potential β-turns, while the remaining four amino acids are useful to predict non-β-turns. Empirical evaluation using three nonredundant datasets shows favorable Qtotal, Qpredicted and MCC values when compared with over a dozen of modern competing methods. Our method is the first to break the 80% Qtotal barrier and achieves Qtotal = 80.9%, MCC = 0.47, and Qpredicted higher by over 6% when compared with the second best method. We use feature selection to reduce the dimensionality of the feature vector used as the input for the proposed prediction method. The applied feature set is smaller by 86, 62 and 37% when compared with the second and two third-best (with respect to MCC) competing methods, respectively. Conclusion Experiments show that the proposed method constitutes an improvement over the competing

Using overbooking to manage no-shows in an Italian healthcare center.

PubMed

Parente, Chiara Anna; Salvatore, Domenico; Gallo, Giampiero Maria; Cipollini, Fabrizio

2018-03-15

of a simulation study under different scenarios in terms of number of resources and no-show rates. The same overbooking strategy was also implemented in practice (giving the opportunity to consider it as a quasi-experiment) to reduce the negative impact caused by non attendance in the MR ward. Both the quasi-experiment and the simulation study demonstrated that the strategy improved the center's productivity and reduced idle time of resources, although it increased slightly the patient's waiting time and the staff's overtime. This represents an evidence that overbooking can be suitable to improve the management of healthcare centers without adversely affecting their costs and the quality of cares offered. We shown that a well designed overbooking procedure can improve the management of medical centers, in terms of a significant increase of revenue, while keeping patient's waiting time and overtime under control. This was demonstrated by the results of a quasi-experiment (practical implementation of the strategy in the MR ward) and a simulation study (under different scenarios). Such positive results took advantage from a predictive model of no-show carefully designed around the medical center data.

PconsFold: improved contact predictions improve protein models.

PubMed

Michel, Mirco; Hayat, Sikander; Skwark, Marcin J; Sander, Chris; Marks, Debora S; Elofsson, Arne

2014-09-01

Recently it has been shown that the quality of protein contact prediction from evolutionary information can be improved significantly if direct and indirect information is separated. Given sufficiently large protein families, the contact predictions contain sufficient information to predict the structure of many protein families. However, since the first studies contact prediction methods have improved. Here, we ask how much the final models are improved if improved contact predictions are used. In a small benchmark of 15 proteins, we show that the TM-scores of top-ranked models are improved by on average 33% using PconsFold compared with the original version of EVfold. In a larger benchmark, we find that the quality is improved with 15-30% when using PconsC in comparison with earlier contact prediction methods. Further, using Rosetta instead of CNS does not significantly improve global model accuracy, but the chemistry of models generated with Rosetta is improved. PconsFold is a fully automated pipeline for ab initio protein structure prediction based on evolutionary information. PconsFold is based on PconsC contact prediction and uses the Rosetta folding protocol. Due to its modularity, the contact prediction tool can be easily exchanged. The source code of PconsFold is available on GitHub at https://www.github.com/ElofssonLab/pcons-fold under the MIT license. PconsC is available from http://c.pcons.net/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

RRCRank: a fusion method using rank strategy for residue-residue contact prediction.

PubMed

Jing, Xiaoyang; Dong, Qiwen; Lu, Ruqian

2017-09-02

In structural biology area, protein residue-residue contacts play a crucial role in protein structure prediction. Some researchers have found that the predicted residue-residue contacts could effectively constrain the conformational search space, which is significant for de novo protein structure prediction. In the last few decades, related researchers have developed various methods to predict residue-residue contacts, especially, significant performance has been achieved by using fusion methods in recent years. In this work, a novel fusion method based on rank strategy has been proposed to predict contacts. Unlike the traditional regression or classification strategies, the contact prediction task is regarded as a ranking task. First, two kinds of features are extracted from correlated mutations methods and ensemble machine-learning classifiers, and then the proposed method uses the learning-to-rank algorithm to predict contact probability of each residue pair. First, we perform two benchmark tests for the proposed fusion method (RRCRank) on CASP11 dataset and CASP12 dataset respectively. The test results show that the RRCRank method outperforms other well-developed methods, especially for medium and short range contacts. Second, in order to verify the superiority of ranking strategy, we predict contacts by using the traditional regression and classification strategies based on the same features as ranking strategy. Compared with these two traditional strategies, the proposed ranking strategy shows better performance for three contact types, in particular for long range contacts. Third, the proposed RRCRank has been compared with several state-of-the-art methods in CASP11 and CASP12. The results show that the RRCRank could achieve comparable prediction precisions and is better than three methods in most assessment metrics. The learning-to-rank algorithm is introduced to develop a novel rank-based method for the residue-residue contact prediction of proteins, which

Attributing Predictable Signals at Subseasonal Timescales

NASA Astrophysics Data System (ADS)

Shelly, A.; Norton, W.; Rowlands, D.; Beech-Brandt, J.

2016-12-01

Subseasonal forecasts offer significant economic value in the management of energy infrastructure and through the associated financial markets. Models are now accurate enough to provide, for some occasions, good forecasts in the subseasonal range. However, it is often not clear what the drivers of these subseasonal signals are and if the forecasts could be more accurate with better representation of physical processes. Also what are the limits of predictability in the subseasonal range? To address these questions, we have run the ECMWF monthly forecast system over the 2015/16 winter with a set of 6 week ensemble integrations initialised every week over the period. In these experiments, we have relaxed the band 15N to 15S to reanalysis fields. Hence, we have a set of forecasts where the tropics is constrained to actual events and we can analyse the changes in predictability in middle latitudes - in particular in regions of high energy consumption like North America and Europe. Not surprisingly, the forecast of some periods are significantly improved while others show no improvement. We discuss events/patterns that have extended range predictability and also the tropical forecast errors which prevent the potential predictability in middle latitudes from being realised.

Improved eye- and skin-color prediction based on 8 SNPs.

PubMed

Hart, Katie L; Kimura, Shey L; Mushailov, Vladimir; Budimlija, Zoran M; Prinz, Mechthild; Wurmbach, Elisa

2013-06-01

To improve the 7-plex system to predict eye and skin color by increasing precision and detailed phenotypic descriptions. Analysis of an eighth single nucleotide polymorphism (SNP), rs12896399 (SLC24A4), showed a statistically significant association with human eye color (P=0.007) but a rather poor strength of agreement (κ=0.063). This SNP was added to the 7-plex system (rs12913832 at HERC2, rs1545397 at OCA2, rs16891982 at SLC45A2, rs1426654 at SLC24A5, rs885479 at MC1R, rs6119471 at ASIP, and rs12203592 at IRF4). Further, the instruction guidelines on the interpretation of genotypes were changed to create a new 8-plex system. This was based on the analysis of an 803-sample training set of various populations. The newly developed 8-plex system can predict the eye colors brown, green, and blue, and skin colors light, not dark, and not light. It is superior to the 7-plex system with its additional ability to predict blue eye and light skin color. The 8-plex system was tested on an additional 212 samples, the test set. Analysis showed that the number of positive descriptions for eye colors as being brown, green, or blue increased significantly (P=6.98e-15, z-score: -7.786). The error rate for eye-color prediction was low, at approximately 5%, while the skin color prediction showed no error in the test set (1% in training set). We can conclude that the new 8-plex system for the prediction of eye and skin color substantially enhances its former version.

Sparse Bayesian Learning for Identifying Imaging Biomarkers in AD Prediction

PubMed Central

Shen, Li; Qi, Yuan; Kim, Sungeun; Nho, Kwangsik; Wan, Jing; Risacher, Shannon L.; Saykin, Andrew J.

2010-01-01

We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accurate prediction and identify critical imaging markers relevant to AD at the same time. ARD is one of the most successful Bayesian feature selection methods. PARD is a powerful Bayesian feature selection method, and provides sparse models that is easy to interpret. PARD selects the model with the best estimate of the predictive performance instead of choosing the one with the largest marginal model likelihood. Comparative study with support vector machine (SVM) shows that ARD/PARD in general outperform SVM in terms of prediction accuracy. Additional comparison with surface-based general linear model (GLM) analysis shows that regions with strongest signals are identified by both GLM and ARD/PARD. While GLM P-map returns significant regions all over the cortex, ARD/PARD provide a small number of relevant and meaningful imaging markers with predictive power, including both cortical and subcortical measures. PMID:20879451

Skillful regional prediction of Arctic sea ice on seasonal timescales

NASA Astrophysics Data System (ADS)

Bushuk, Mitchell; Msadek, Rym; Winton, Michael; Vecchi, Gabriel A.; Gudgel, Rich; Rosati, Anthony; Yang, Xiaosong

2017-05-01

Recent Arctic sea ice seasonal prediction efforts and forecast skill assessments have primarily focused on pan-Arctic sea ice extent (SIE). In this work, we move toward stakeholder-relevant spatial scales, investigating the regional forecast skill of Arctic sea ice in a Geophysical Fluid Dynamics Laboratory (GFDL) seasonal prediction system. Using a suite of retrospective initialized forecasts spanning 1981-2015 made with a coupled atmosphere-ocean-sea ice-land model, we show that predictions of detrended regional SIE are skillful at lead times up to 11 months. Regional prediction skill is highly region and target month dependent and generically exceeds the skill of an anomaly persistence forecast. We show for the first time that initializing the ocean subsurface in a seasonal prediction system can yield significant regional skill for winter SIE. Similarly, as suggested by previous work, we find that sea ice thickness initial conditions provide a crucial source of skill for regional summer SIE.

Automatic speech recognition using a predictive echo state network classifier.

PubMed

Skowronski, Mark D; Harris, John G

2007-04-01

We have combined an echo state network (ESN) with a competitive state machine framework to create a classification engine called the predictive ESN classifier. We derive the expressions for training the predictive ESN classifier and show that the model was significantly more noise robust compared to a hidden Markov model in noisy speech classification experiments by 8+/-1 dB signal-to-noise ratio. The simple training algorithm and noise robustness of the predictive ESN classifier make it an attractive classification engine for automatic speech recognition.

Predictability of the European heat and cold waves

NASA Astrophysics Data System (ADS)

Lavaysse, Christophe; Naumann, Gustavo; Alfieri, Lorenzo; Salamon, Peter; Vogt, Jürgen

2018-06-01

Heat and cold waves may have considerable human and economic impacts in Europe. Recent events, like the heat waves observed in France in 2003 and Russia in 2010, illustrated the major consequences to be expected. Reliable Early Warning Systems for extreme temperatures would, therefore, be of high value for decision makers. However, they require a clear definition and robust forecasts of these events. This study analyzes the predictability of heat and cold waves over Europe, defined as at least three consecutive days of {T}_{min} and {T}_{max} above the quantile Q90 (under Q10), using the extended ensemble system of ECMWF. The results show significant predictability for events within a 2-week lead time, but with a strong decrease of the predictability during the first week of forecasts (from 80 to 40% of observed events correctly forecasted). The scores show a higher predictive skill for the cold waves (in winter) than for the heat waves (in summer). The uncertainties and the sensitivities of the predictability are discussed on the basis of tests conducted with different spatial and temporal resolutions. Results demonstrate the negligible effect of the temporal resolution (very few errors due to bad timing of the forecasts), and a better predictability of large-scale events. The onset and the end of the waves are slightly less predictable with an average of about 35% (30%) of observed heat (cold) waves onsets or ends correctly forecasted with a 5-day lead time. Finally, the forecasted intensities show a correlation of about 0.65 with those observed, revealing the challenge to predict this important characteristic.

Development of a Microsimulation Model to Predict Stroke and Long-Term Mortality in Adherent and Nonadherent Medically Managed and Surgically Treated Octogenarians with Asymptomatic Significant Carotid Artery Stenosis.

PubMed

Luebke, Thomas; Brunkwall, Jan

2016-08-01

The primary study objective was to develop a microsimulation model to predict preventable first-ever and recurrent strokes and mortality for a population of medically or surgically managed octogenarians with substantial (>60%) asymptomatic carotid artery stenosis and comparing an adherent with a real-world nonadherent best medical treatment (BMT) regimen subjected to sex. A Monte Carlo microsimulation model was constructed with a 14-year time horizon and with 10,000 patients. Probabilities and values for clinical outcomes were obtained from the current literature. The stratification of the microsimulation estimates by treatment strategy within the female group of octogenarians showed a statistically significant lower stroke rate during follow-up for carotid endarterectomy (CEA) compared with nonadherent BMT (P < 0.0001) as well as compared with adherent BMT (P < 0.0001). In male octogenarians, the CEA strategy was also associated with statistically significant lower stroke rates compared with adherent and nonadherent BMT (P < 0.0001 and P < 0.0001, respectively). For each treatment strategy, female octogenarians had a statistically significant longer overall long-term survival compared with male octogenarians (P < 0.0001, respectively). In terms of stratification by sex, in octogenarian men and women, long-term survival was significantly better for adherent BMT compared with nonadherent BMT, and CEA was associated with a significant better long-term survival compared with nonadherent BMT. In the present microsimulation, in real-world drug adherence, it was likely that a strategy of early endarterectomy was beneficial in octogenarians with significant asymptomatic carotid artery disease compared with BMT alone. Copyright © 2016 Elsevier Inc. All rights reserved.

Prediction of the space adaptation syndrome

NASA Technical Reports Server (NTRS)

Reschke, M. F.; Homick, J. L.; Ryan, P.; Moseley, E. C.

1984-01-01

The univariate and multivariate relationships of provocative measures used to produce motion sickness symptoms were described. Normative subjects were used to develop and cross-validate sets of linear equations that optimally predict motion sickness in parabolic flights. The possibility of reducing the number of measurements required for prediction was assessed. After describing the variables verbally and statistically for 159 subjects, a factor analysis of 27 variables was completed to improve understanding of the relationships between variables and to reduce the number of measures for prediction purposes. The results of this analysis show that none of variables are significantly related to the responses to parabolic flights. A set of variables was selected to predict responses to KC-135 flights. A series of discriminant analyses were completed. Results indicate that low, moderate, or severe susceptibility could be correctly predicted 64 percent and 53 percent of the time on original and cross-validation samples, respectively. Both the factor analysis and the discriminant analysis provided no basis for reducing the number of tests.

A morphometric and histological study of placental malaria shows significant changes to villous architecture in both Plasmodium falciparum and Plasmodium vivax infection

PubMed Central

2014-01-01

Background Malaria in pregnancy remains a major health problem. Placental malaria infection may cause pathophysiological changes in pregnancy and result in morphological changes to placental villi. Quantitative histomorphological image analysis of placental biopsies was performed to compare placental villous architecture between active or treated placental malaria cases and controls. Methods A total of 67 placentas were studied from three clinical groups: control patients who did not have malaria (n = 27), active (n = 14) and treated (n=26) malaria cases, including both Plasmodium falciparum and Plasmodium vivax infections. Image analysis of histological placental sections was performed using ImageJ software to measure the number and size (area) of terminal villi, perimeter measurement per villus and total perimeter per unit area, and number of capillaries per villus (vascularity). Histological features of placental malaria were scored and these results were correlated with malaria status and clinical outcomes. Results Villous size correlated with vascularity (p <0.0001) but was inversely correlated with observed villi per unit area, (p = 0.0001). Significantly greater villous area and vascularity was observed in UK controls. Indices of histological malaria infection were significantly greater in active versus treated malaria cases. Active placental malaria cases showed significantly smaller villous area (p <0.0084), vascularity (p <0.0139) and perimeter (p <0.0006) than treated malaria cases or controls, but significantly more villi per unit area (p <0.0001). Villous size in treated malaria cases was significantly larger than active placental malaria cases (p <0.001) and similar to controls. There was a significant relationship between villous number and anaemia at the time of infection (p <0.0034), but not placental weight, birth weight or gestational age at delivery. No differences were found between histology or villous morphology comparing infections with P

Predictive systems ecology

PubMed Central

Evans, Matthew R.; Bithell, Mike; Cornell, Stephen J.; Dall, Sasha R. X.; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J.; Lewis, Simon L.; Mace, Georgina M.; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K. J.; Petchey, Owen; Smith, Matthew; Travis, Justin M. J.; Benton, Tim G.

2013-01-01

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive. PMID:24089332

Predictive systems ecology.

PubMed

Evans, Matthew R; Bithell, Mike; Cornell, Stephen J; Dall, Sasha R X; Díaz, Sandra; Emmott, Stephen; Ernande, Bruno; Grimm, Volker; Hodgson, David J; Lewis, Simon L; Mace, Georgina M; Morecroft, Michael; Moustakas, Aristides; Murphy, Eugene; Newbold, Tim; Norris, K J; Petchey, Owen; Smith, Matthew; Travis, Justin M J; Benton, Tim G

2013-11-22

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

Prediction of Marital Satisfaction Based on Emotional Intelligence in Postmenopausal Women.

PubMed

Heidari, Mohammad; Shahbazi, Sara; Ghafourifard, Mansour; Ali Sheikhi, Rahim

2017-12-01

This study was coperinducted with the aim of prediction of marital satisfaction based on emotional intelligence for postmenopausal women. This cross-sectional study was the descriptive-correlation and with a sample size of 134 people to predict marital satisfaction based on emotional intelligence for postmenopausal women was conducted in the Borujen city. The subjects were selected by convenience sampling. Data collection tools included an emotional intelligence questionnaire (Bar-on) and Enrich marital satisfaction questionnaire. The results of this study showed a significant positive relationship between marital satisfaction and emotional intelligence ( P < 0.05, r = 0.25). Also, regression analysis showed that emotional intelligence ( β = 0.31) can predict positively and significantly marital satisfaction. Due to the positive relationship between emotional intelligence and marital satisfaction, adequacy of emotional intelligence is improved as important structural in marital satisfaction. So it seems that can with measuring emotional intelligence in reinforced marital satisfaction during menopause, done appropriate action.

Predicting Effects of Psychological Inflexibility/Experiential Avoidance and Stress Coping Strategies for Internet Addiction, Significant Depression, and Suicidality in College Students: A Prospective Study.

PubMed

Chou, Wei-Po; Yen, Cheng-Fang; Liu, Tai-Ling

2018-04-18

The aims of this study were to evaluate the predicting effects of psychological inflexibility/experiential avoidance (PI/EA) and stress coping strategies for Internet addiction, significant depression and suicidality among college students during the follow-up period of one year. A total of 500 college students participated in this study. The level of PI/EA and stress coping strategies were evaluated initially. One year later, 324 participants were invited to complete the Chen Internet Addiction Scale, Beck Depression Inventory-II and the questionnaire for suicidality to evaluate depression symptoms and internet addiction and suicidality. The predicting effects of PI/EA and stress coping strategies were examined by using logistic regression analysis controlling for the effects of gender and age. The results indicated that PI/EA at the initial assessment increased the risk of Internet addiction (OR = 1.087, 95% CI: 1.042–1.135), significant depression (OR = 1.125, 95% CI: 1.081–1.170), and suicidality (OR = 1.099, 95% CI: 1.053–1.147) at the follow-up assessment. Less effective coping at the initial assessment also increased the risk of Internet addiction (OR = 1.074, 95% CI: 1.011–1.140), significant depression (OR = 1.091, 95% CI: 1.037–1.147), and suicidality (OR = 1.074, 95% CI: 1.014–1.138) at the follow-up assessment. Problem focused and emotion-focus coping at the initial assessment was not significantly associated with the risks of Internet addiction, significant depression, and suicidality at the follow-up assessment. College students who have high PI/EA or are accustomed to using less effective stress coping strategies should be the target of prevention programs for IA (internet addiction), depression, and suicidality.

Predicting Effects of Psychological Inflexibility/Experiential Avoidance and Stress Coping Strategies for Internet Addiction, Significant Depression, and Suicidality in College Students: A Prospective Study

PubMed Central

Chou, Wei-Po; Yen, Cheng-Fang; Liu, Tai-Ling

2018-01-01

The aims of this study were to evaluate the predicting effects of psychological inflexibility/experiential avoidance (PI/EA) and stress coping strategies for Internet addiction, significant depression and suicidality among college students during the follow-up period of one year. A total of 500 college students participated in this study. The level of PI/EA and stress coping strategies were evaluated initially. One year later, 324 participants were invited to complete the Chen Internet Addiction Scale, Beck Depression Inventory-II and the questionnaire for suicidality to evaluate depression symptoms and internet addiction and suicidality. The predicting effects of PI/EA and stress coping strategies were examined by using logistic regression analysis controlling for the effects of gender and age. The results indicated that PI/EA at the initial assessment increased the risk of Internet addiction (OR = 1.087, 95% CI: 1.042–1.135), significant depression (OR = 1.125, 95% CI: 1.081–1.170), and suicidality (OR = 1.099, 95% CI: 1.053–1.147) at the follow-up assessment. Less effective coping at the initial assessment also increased the risk of Internet addiction (OR = 1.074, 95% CI: 1.011–1.140), significant depression (OR = 1.091, 95% CI: 1.037–1.147), and suicidality (OR = 1.074, 95% CI: 1.014–1.138) at the follow-up assessment. Problem focused and emotion-focus coping at the initial assessment was not significantly associated with the risks of Internet addiction, significant depression, and suicidality at the follow-up assessment. College students who have high PI/EA or are accustomed to using less effective stress coping strategies should be the target of prevention programs for IA (internet addiction), depression, and suicidality. PMID:29670025

Predictability of Seasonal Rainfall over the Greater Horn of Africa

NASA Astrophysics Data System (ADS)

Ngaina, J. N.

2016-12-01

The El Nino-Southern Oscillation (ENSO) is a primary mode of climate variability in the Greater of Africa (GHA). The expected impacts of climate variability and change on water, agriculture, and food resources in GHA underscore the importance of reliable and accurate seasonal climate predictions. The study evaluated different model selection criteria which included the Coefficient of determination (R2), Akaike's Information Criterion (AIC), Bayesian Information Criterion (BIC), and the Fisher information approximation (FIA). A forecast scheme based on the optimal model was developed to predict the October-November-December (OND) and March-April-May (MAM) rainfall. The predictability of GHA rainfall based on ENSO was quantified based on composite analysis, correlations and contingency tables. A test for field-significance considering the properties of finiteness and interdependence of the spatial grid was applied to avoid correlations by chance. The study identified FIA as the optimal model selection criterion. However, complex model selection criteria (FIA followed by BIC) performed better compared to simple approach (R2 and AIC). Notably, operational seasonal rainfall predictions over the GHA makes of simple model selection procedures e.g. R2. Rainfall is modestly predictable based on ENSO during OND and MAM seasons. El Nino typically leads to wetter conditions during OND and drier conditions during MAM. The correlations of ENSO indices with rainfall are statistically significant for OND and MAM seasons. Analysis based on contingency tables shows higher predictability of OND rainfall with the use of ENSO indices derived from the Pacific and Indian Oceans sea surfaces showing significant improvement during OND season. The predictability based on ENSO for OND rainfall is robust on a decadal scale compared to MAM. An ENSO-based scheme based on an optimal model selection criterion can thus provide skillful rainfall predictions over GHA. This study concludes that the

The gamma-glutamyl transpeptidase to platelet ratio (GPR) predicts significant liver fibrosis and cirrhosis in patients with chronic HBV infection in West Africa.

PubMed

Lemoine, Maud; Shimakawa, Yusuke; Nayagam, Shevanthi; Khalil, Mustapha; Suso, Penda; Lloyd, Jo; Goldin, Robert; Njai, Harr-Freeya; Ndow, Gibril; Taal, Makie; Cooke, Graham; D'Alessandro, Umberto; Vray, Muriel; Mbaye, Papa Saliou; Njie, Ramou; Mallet, Vincent; Thursz, Mark

2016-08-01

Simple and inexpensive non-invasive fibrosis tests are highly needed but have been poorly studied in sub-Saharan Africa. Using liver histology as a gold standard, we developed a novel index using routine laboratory tests to predict significant fibrosis in patients with chronic HBV infection in The Gambia, West Africa. We prospectively assessed the diagnostic accuracy of the novel index, Fibroscan, aspartate transaminase-to-platelet ratio index (APRI), and Fib-4 in Gambian patients with CHB (training set) and also in French and Senegalese CHB cohorts (validation sets). Of 135 consecutive treatment-naïve patients with CHB who had liver biopsy, 39% had significant fibrosis (Metavir fibrosis stage ≥F2) and 15% had cirrhosis (F4). In multivariable analysis, gamma-glutamyl transpeptidase (GGT) and platelet count were independent predictors of significant fibrosis. Consequently, GGT-to-platelet ratio (GPR) was developed. In The Gambia, the area under the receiver operating characteristic curve (AUROC) of the GPR was significantly higher than that of APRI and Fib-4 to predict ≥F2, ≥F3 and F4. In Senegal, the AUROC of GPR was significantly better than Fib-4 and APRI for ≥F2 (0.73, 95% CI 0.59 to 0.86) and better than Fib-4 and Fibroscan for ≥F3 (0.93, 0.87 to 0.99). In France, the AUROC of GPR to diagnose ≥F2 (0.72, 95% CI 0.59 to 0.85) and F4 (0.87, 0.76 to 0.98) was equivalent to that of APRI and Fib-4. The GPR is a more accurate routine laboratory marker than APRI and Fib-4 to stage liver fibrosis in patients with CHB in West Africa. The GPR represents a simple and inexpensive alternative to liver biopsy and Fibroscan in sub-Saharan Africa. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Evolution of EF-hand calcium-modulated proteins. III. Exon sequences confirm most dendrograms based on protein sequences: calmodulin dendrograms show significant lack of parallelism

NASA Technical Reports Server (NTRS)

Nakayama, S.; Kretsinger, R. H.

1993-01-01

In the first report in this series we presented dendrograms based on 152 individual proteins of the EF-hand family. In the second we used sequences from 228 proteins, containing 835 domains, and showed that eight of the 29 subfamilies are congruent and that the EF-hand domains of the remaining 21 subfamilies have diverse evolutionary histories. In this study we have computed dendrograms within and among the EF-hand subfamilies using the encoding DNA sequences. In most instances the dendrograms based on protein and on DNA sequences are very similar. Significant differences between protein and DNA trees for calmodulin remain unexplained. In our fourth report we evaluate the sequences and the distribution of introns within the EF-hand family and conclude that exon shuffling did not play a significant role in its evolution.

Prognostic significance of nuclear pSTAT3 in oral cancer.

PubMed

Macha, Muzafar A; Matta, Ajay; Kaur, Jatinder; Chauhan, S S; Thakar, Alok; Shukla, Nootan K; Gupta, Siddhartha Datta; Ralhan, Ranju

2011-04-01

Aberrant nuclear accumulation of proteins influences tumor development and may predict biologic aggressiveness and disease prognosis. This study determined the prognostic significance of pSTAT3 (phosphorylayed signal transducer and activator of transcription 3) in oral squamous cell carcinomas (OSCCs). Using immunohistochemistry, a significant increase in nuclear accumulation of pSTAT3 was observed in 49 of 90 leukoplakias (54.4%) and 63/94 OSCCs (67%) (p(trend) < .001). Increased pSTAT3 was associated with tumor stage (p = .01), nodal metastasis (p = .0018), and tobacco consumption (p = .004). Kaplan-Meier analysis demonstrated that OSCC with increased nuclear pSTAT3 showed significantly reduced disease-free survival (13 months), compared with the patients with no nuclear pSTAT3 expression (64 months, p = .019). Cox regression analysis revealed nuclear pSTAT3 as the most significant predictor of poor prognosis (p = .024, hazard ratio [HR] = 2.7). Increased nuclear accumulation of pSTAT3 occurs in early premalignant stages and is a marker for poor prognosis of OSCC. Copyright © 2010 Wiley Periodicals, Inc.

Significance of satellite sign and spot sign in predicting hematoma expansion in spontaneous intracerebral hemorrhage.

PubMed

Yu, Zhiyuan; Zheng, Jun; Ali, Hasan; Guo, Rui; Li, Mou; Wang, Xiaoze; Ma, Lu; Li, Hao; You, Chao

2017-11-01

Hematoma expansion is related to poor outcome in spontaneous intracerebral hemorrhage (ICH). Recently, a non-enhanced computed tomography (CT) based finding, termed the 'satellite sign', was reported to be a novel predictor for poor outcome in spontaneous ICH. However, it is still unclear whether the presence of the satellite sign is related to hematoma expansion. Initial computed tomography angiography (CTA) was conducted within 6h after ictus. Satellite sign on non-enhanced CT and spot sign on CTA were detected by two independent reviewers. The sensitivity and specificity of both satellite sign and spot sign were calculated. Receiver-operator analysis was conducted to evaluate their predictive accuracy for hematoma expansion. This study included 153 patients. Satellite sign was detected in 58 (37.91%) patients and spot sign was detected in 38 (24.84%) patients. Among 37 patients with hematoma expansion, 22 (59.46%) had satellite sign and 23 (62.16%) had spot sign. The sensitivity and specificity of satellite sign for prediction of hematoma expansion were 59.46% and 68.97%, respectively. The sensitivity and specificity of spot sign were 62.16% and 87.07%, respectively. The area under the curve (AUC) of satellite sign was 0.642 and the AUC of spot sign was 0.746. (P=0.157) CONCLUSION: Our results suggest that the satellite sign is an independent predictor for hematoma expansion in spontaneous ICH. Although spot sign has the higher predictive accuracy, satellite sign is still an acceptable predictor for hematoma expansion when CTA is unavailable. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting readmission risk with institution-specific prediction models.

PubMed

Yu, Shipeng; Farooq, Faisal; van Esbroeck, Alexander; Fung, Glenn; Anand, Vikram; Krishnapuram, Balaji

2015-10-01

The ability to predict patient readmission risk is extremely valuable for hospitals, especially under the Hospital Readmission Reduction Program of the Center for Medicare and Medicaid Services which went into effect starting October 1, 2012. There is a plethora of work in the literature that deals with developing readmission risk prediction models, but most of them do not have sufficient prediction accuracy to be deployed in a clinical setting, partly because different hospitals may have different characteristics in their patient populations. We propose a generic framework for institution-specific readmission risk prediction, which takes patient data from a single institution and produces a statistical risk prediction model optimized for that particular institution and, optionally, for a specific condition. This provides great flexibility in model building, and is also able to provide institution-specific insights in its readmitted patient population. We have experimented with classification methods such as support vector machines, and prognosis methods such as the Cox regression. We compared our methods with industry-standard methods such as the LACE model, and showed the proposed framework is not only more flexible but also more effective. We applied our framework to patient data from three hospitals, and obtained some initial results for heart failure (HF), acute myocardial infarction (AMI), pneumonia (PN) patients as well as patients with all conditions. On Hospital 2, the LACE model yielded AUC 0.57, 0.56, 0.53 and 0.55 for AMI, HF, PN and All Cause readmission prediction, respectively, while the proposed model yielded 0.66, 0.65, 0.63, 0.74 for the corresponding conditions, all significantly better than the LACE counterpart. The proposed models that leverage all features at discharge time is more accurate than the models that only leverage features at admission time (0.66 vs. 0.61 for AMI, 0.65 vs. 0.61 for HF, 0.63 vs. 0.56 for PN, 0.74 vs. 0.60 for All

Self-Reported Mental Health Predicts Acute Respiratory Infection.

PubMed

Maxwell, Lizzie; Barrett, Bruce; Chase, Joseph; Brown, Roger; Ewers, Tola

2015-06-01

Poor mental health conditions, including stress and depression, have been recognized as a risk factor for the development of acute respiratory infection. Very few studies have considered the role of general mental health in acute respiratory infection occurrence. The aim of this analysis is to determine if overall mental health, as assessed by the mental component of the Short Form 12 Health Survey, predicts incidence, duration, or severity of acute respiratory infection. Data utilized for this analysis came from the National Institute of Health-funded Meditation or Exercise for Preventing Acute Respiratory Infection (MEPARI) and MEPARI-2 randomized controlled trials examining the effects of meditation or exercise on acute respiratory infection among adults aged > 30 years in Madison, Wisconsin. A Kendall tau rank correlation compared the Short Form 12 mental component, completed by participants at baseline, with acute respiratory infection incidence, duration, and area-under-the-curve (global) severity, as assessed by the Wisconsin Upper Respiratory Symptom Survey. Participants were recruited from Madison, Wis, using advertisements in local media. Short Form 12 mental health scores significantly predicted incidence (P = 0.037) of acute respiratory infection, but not duration (P = 0.077) or severity (P = 0.073). The Positive and Negative Affect Schedule (PANAS) negative emotion measure significantly predicted global severity (P = 0.036), but not incidence (P = 0.081) or duration (P = 0.125). Mindful Attention Awareness Scale scores significantly predicted incidence of acute respiratory infection (P = 0.040), but not duration (P = 0.053) or severity (P = 0.70). The PHQ-9, PSS-10, and PANAS positive measures did not show significant predictive associations with any of the acute respiratory infection outcomes. Self-reported overall mental health, as measured by the mental component of Short Form 12, predicts acute respiratory infection incidence.

AIRS associated accomplishments at the JCSDA: First use of full spatial resolution hyperspectral data show significant improvements in global forecasts

NASA Astrophysics Data System (ADS)

Le Marshall, J.; Jung, J.; Lord, S. J.; Derber, J. C.; Treadon, R.; Joiner, J.; Goldberg, M.; Wolf, W.; Liu, H. C.

2005-08-01

The National Aeronautics and Space Administration (NASA), National Oceanic and Atmospheric Administration (NOAA), and Department of Defense (DoD), Joint Center for Satellite Data Assimilation (JCSDA) was established in 2000/2001. The goal of the JCSDA is to accelerate the use of observations from earth-orbiting satellites into operational numerical environmental analysis and prediction systems for the purpose of improving weather and oceanic forecasts, seasonal climate forecasts and the accuracy of climate data sets. As a result, a series of data assimilation experiments were undertaken at the JCSDA as part of the preparations for the operational assimilation of AIRS data by its partner organizations1,2. Here, for the first time full spatial resolution radiance data, available in real-time from the AIRS instrument, were used at the JCSDA in data assimilation studies over the globe utilizing the operational NCEP Global Forecast System (GFS). The radiance data from each channel of the instrument were carefully screened for cloud effects and those radiances which were deemed to be clear of cloud effects were used by the GFS forecast system. The result of these assimilation trials has been a first demonstration of significant improvements in forecast skill over both the Northern and Southern Hemisphere compared to the operational system without AIRS data. The experimental system was designed in a way that rendered it feasible for operational application, and that constraint involved using the subset of AIRS channels chosen for operational distribution and an analysis methodology close to the current analysis practice, with particular consideration given to time limitations. As a result, operational application of these AIRS data was enabled by the recent NCEP operational upgrade. In addition, because of the improved impact resulting from use of this enhanced data set compared to that used operationally to date, provision of a realtime "warmest field" of view data set

Predictive factors for long-term survival in patients with clinically significant portal hypertension following resection of hepatocellular carcinoma.

PubMed

Choi, Gi H; Park, Jun Y; Hwang, Ho K; Kim, Dong H; Kang, Chang M; Choi, Jin S; Park, Young N; Kim, Do Y; Ahn, Sang H; Han, Kwang-Hyub; Chon, Chae Y; Lee, Woo J

2011-04-01

Hepatic resection for hepatocellular carcinoma (HCC) is not currently recommended for patients with clinically significant portal hypertension (PHT); however, recent studies have shown similar post-operative outcomes between patients with and without clinically significant PHT. To clarify the post-operative prognostic relevance of clinically significant PHT in Child-Pugh A cirrhotic patients. A total of 100 Child-Pugh A cirrhotic patients who underwent curative resection of HCC were eligible for this analysis. Patients were divided into two groups: PHT group (n=47) and non-PHT group (n=53). Clinicopathological variables showed no significant differences except for prothrombine time. Liver-related complications were significantly higher in the PHT group (P=0.015), and the 5-year overall survival rate was significantly higher in the non-PHT group (78.7 vs. 37.9%, P<0.001). The proportion of patients who died because of complications of cirrhosis was significantly higher in the PHT group (P=0.001). Multivariate analysis indicated that the presence of clinically significant PHT was the most powerful adverse prognostic factor for overall survival. Multivariate analysis of the 47 patients with clinically significant PHT indicated that gross vascular invasion and non-single nodular type were poor prognostic factors. The 5-year survival rate of patients with single nodular type and without gross vascular invasion (n=17) was 78.4%. In Child-Pugh A cirrhotic patients, the presence of clinically significant PHT was significantly associated with post-operative hepatic decompensation and poor prognosis after resection of HCC. However, in patients with clinically significant PHT, those with single nodular tumours lacking gross vascular invasion may be good surgical candidates. © 2011 John Wiley & Sons A/S.

General overview on structure prediction of twilight-zone proteins.

PubMed

Khor, Bee Yin; Tye, Gee Jun; Lim, Theam Soon; Choong, Yee Siew

2015-09-04

Protein structure prediction from amino acid sequence has been one of the most challenging aspects in computational structural biology despite significant progress in recent years showed by critical assessment of protein structure prediction (CASP) experiments. When experimentally determined structures are unavailable, the predictive structures may serve as starting points to study a protein. If the target protein consists of homologous region, high-resolution (typically <1.5 Å) model can be built via comparative modelling. However, when confronted with low sequence similarity of the target protein (also known as twilight-zone protein, sequence identity with available templates is less than 30%), the protein structure prediction has to be initiated from scratch. Traditionally, twilight-zone proteins can be predicted via threading or ab initio method. Based on the current trend, combination of different methods brings an improved success in the prediction of twilight-zone proteins. In this mini review, the methods, progresses and challenges for the prediction of twilight-zone proteins were discussed.

Progress Toward Improving Jet Noise Predictions in Hot Jets

NASA Technical Reports Server (NTRS)

Khavaran, Abbas; Kenzakowski, Donald C.

2007-01-01

An acoustic analogy methodology for improving noise predictions in hot round jets is presented. Past approaches have often neglected the impact of temperature fluctuations on the predicted sound spectral density, which could be significant for heated jets, and this has yielded noticeable acoustic under-predictions in such cases. The governing acoustic equations adopted here are a set of linearized, inhomogeneous Euler equations. These equations are combined into a single third order linear wave operator when the base flow is considered as a locally parallel mean flow. The remaining second-order fluctuations are regarded as the equivalent sources of sound and are modeled. It is shown that the hot jet effect may be introduced primarily through a fluctuating velocity/enthalpy term. Modeling this additional source requires specialized inputs from a RANS-based flowfield simulation. The information is supplied using an extension to a baseline two equation turbulence model that predicts total enthalpy variance in addition to the standard parameters. Preliminary application of this model to a series of unheated and heated subsonic jets shows significant improvement in the acoustic predictions at the 90 degree observer angle.

A Novel Dynamic Update Framework for Epileptic Seizure Prediction

PubMed Central

Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices. PMID:25050381

A novel dynamic update framework for epileptic seizure prediction.

PubMed

Han, Min; Ge, Sunan; Wang, Minghui; Hong, Xiaojun; Han, Jie

2014-01-01

Epileptic seizure prediction is a difficult problem in clinical applications, and it has the potential to significantly improve the patients' daily lives whose seizures cannot be controlled by either drugs or surgery. However, most current studies of epileptic seizure prediction focus on high sensitivity and low false-positive rate only and lack the flexibility for a variety of epileptic seizures and patients' physical conditions. Therefore, a novel dynamic update framework for epileptic seizure prediction is proposed in this paper. In this framework, two basic sample pools are constructed and updated dynamically. Furthermore, the prediction model can be updated to be the most appropriate one for the prediction of seizures' arrival. Mahalanobis distance is introduced in this part to solve the problem of side information, measuring the distance between two data sets. In addition, a multichannel feature extraction method based on Hilbert-Huang transform and extreme learning machine is utilized to extract the features of a patient's preseizure state against the normal state. At last, a dynamic update epileptic seizure prediction system is built up. Simulations on Freiburg database show that the proposed system has a better performance than the one without update. The research of this paper is significantly helpful for clinical applications, especially for the exploitation of online portable devices.

Clinical significance of lymph node metastasis in gastric cancer

PubMed Central

Deng, Jing-Yu; Liang, Han

2014-01-01

Gastric cancer, one of the most common malignancies in the world, frequently reveals lymph node, peritoneum, and liver metastases. Most of gastric cancer patients present with lymph node metastasis when they were initially diagnosed or underwent surgical resection, which results in poor prognosis. Both the depth of tumor invasion and lymph node involvement are considered as the most important prognostic predictors of gastric cancer. Although extended lymphadenectomy was not considered a survival benefit procedure and was reported to be associated with high mortality and morbidity in two randomized controlled European trials, it showed significant superiority in terms of lower locoregional recurrence and disease related deaths compared to limited lymphadenectomy in a 15-year follow-up study. Almost all clinical investigators have reached a consensus that the predictive efficiency of the number of metastatic lymph nodes is far better than the extent of lymph node metastasis for the prognosis of gastric cancer worldwide, but other nodal metastatic classifications of gastric cancer have been proposed as alternatives to the number of metastatic lymph nodes for improving the predictive efficiency for patient prognosis. It is still controversial over whether the ratio between metastatic and examined lymph nodes is superior to the number of metastatic lymph nodes in prognostic evaluation of gastric cancer. Besides, the negative lymph node count has been increasingly recognized to be an important factor significantly associated with prognosis of gastric cancer. PMID:24744586

Predicting weight status stability and change from fifth grade to eighth grade: the significant role of adolescents' social-emotional well-being.

PubMed

Chang, Yiting; Gable, Sara

2013-04-01

The primary objective of this study was to predict weight status stability and change across the transition to adolescence using parent reports of child and household routines and teacher and child self-reports of social-emotional development. Data were from the Early Childhood Longitudinal Study-Kindergarten Cohort (ECLS-K), a nationally representative sample of children who entered kindergarten during 1998-1999 and were followed through eighth grade. At fifth grade, parents reported on child and household routines and the study child and his/her primary classroom teacher reported on the child's social-emotional functioning. At fifth and eighth grade, children were directly weighed and measured at school. Nine mutually-exclusive weight trajectory groups were created to capture stability or change in weight status from fifth to eighth grade: (1) stable obese (ObeSta); (2) obese to overweight (ObePos1); (3) obese to healthy (ObePos2); (4) stable overweight (OverSta); (5) overweight to healthy (OverPos); (6) overweight to obese (OverNeg); (7) stable healthy (HelSta); (8) healthy to overweight (HelNeg1); and (9) healthy to obese (HelNeg2). Except for breakfast consumption at home, school-provided lunches, nighttime sleep duration, household and child routines did not predict stability or change in weight status. Instead, weight status trajectory across the transition to adolescence was significantly predicted by measures of social-emotional functioning at fifth grade. Assessing children's social-emotional well-being in addition to their lifestyle routines during the transition to adolescence is a noteworthy direction for adolescent obesity prevention and intervention. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Investigation on the Accuracy of Superposition Predictions of Film Cooling Effectiveness

NASA Astrophysics Data System (ADS)

Meng, Tong; Zhu, Hui-ren; Liu, Cun-liang; Wei, Jian-sheng

2018-05-01

Film cooling effectiveness on flat plates with double rows of holes has been studied experimentally and numerically in this paper. This configuration is widely used to simulate the multi-row film cooling on turbine vane. Film cooling effectiveness of double rows of holes and each single row was used to study the accuracy of superposition predictions. Method of stable infrared measurement technique was used to measure the surface temperature on the flat plate. This paper analyzed the factors that affect the film cooling effectiveness including hole shape, hole arrangement, row-to-row spacing and blowing ratio. Numerical simulations were performed to analyze the flow structure and film cooling mechanisms between each film cooling row. Results show that the blowing ratio within the range of 0.5 to 2 has a significant influence on the accuracy of superposition predictions. At low blowing ratios, results obtained by superposition method agree well with the experimental data. While at high blowing ratios, the accuracy of superposition prediction decreases. Another significant factor is hole arrangement. Results obtained by superposition prediction are nearly the same as experimental values of staggered arrangement structures. For in-line configurations, the superposition values of film cooling effectiveness are much higher than experimental data. For different hole shapes, the accuracy of superposition predictions on converging-expanding holes is better than cylinder holes and compound angle holes. For two different hole spacing structures in this paper, predictions show good agreement with the experiment results.

In silico prediction of potential chemical reactions mediated by human enzymes.

PubMed

Yu, Myeong-Sang; Lee, Hyang-Mi; Park, Aaron; Park, Chungoo; Ceong, Hyithaek; Rhee, Ki-Hyeong; Na, Dokyun

2018-06-13

Administered drugs are often converted into an ineffective or activated form by enzymes in our body. Conventional in silico prediction approaches focused on therapeutically important enzymes such as CYP450. However, there are more than thousands of different cellular enzymes that potentially convert administered drug into other forms. We developed an in silico model to predict which of human enzymes including metabolic enzymes as well as CYP450 family can catalyze a given chemical compound. The prediction is based on the chemical and physical similarity between known enzyme substrates and a query chemical compound. Our in silico model was developed using multiple linear regression and the model showed high performance (AUC = 0.896) despite of the large number of enzymes. When evaluated on a test dataset, it also showed significantly high performance (AUC = 0.746). Interestingly, evaluation with literature data showed that our model can be used to predict not only enzymatic reactions but also drug conversion and enzyme inhibition. Our model was able to predict enzymatic reactions of a query molecule with a high accuracy. This may foster to discover new metabolic routes and to accelerate the computational development of drug candidates by enabling the prediction of the potential conversion of administered drugs into active or inactive forms.

Compressed sensing based missing nodes prediction in temporal communication network

NASA Astrophysics Data System (ADS)

Cheng, Guangquan; Ma, Yang; Liu, Zhong; Xie, Fuli

2018-02-01

The reconstruction of complex network topology is of great theoretical and practical significance. Most research so far focuses on the prediction of missing links. There are many mature algorithms for link prediction which have achieved good results, but research on the prediction of missing nodes has just begun. In this paper, we propose an algorithm for missing node prediction in complex networks. We detect the position of missing nodes based on their neighbor nodes under the theory of compressed sensing, and extend the algorithm to the case of multiple missing nodes using spectral clustering. Experiments on real public network datasets and simulated datasets show that our algorithm can detect the locations of hidden nodes effectively with high precision.

Significance of atypical squamous cells of undetermined significance on ThinPrep papanicolaou smears.

PubMed

Eltabbakh, G H; Lipman, J N; Mount, S L; Morgan, A

2000-10-01

The aim of this study was to assess the prevalence and risk factors predictive of dysplasia among women seen in a gynecologic oncology service with the cytologic diagnosis of atypical squamous cells of undetermined significance (ASCUS) on Papanicolaou smears obtained by the ThinPrep method. Patients with ASCUS ThinPrep Papanicolaou smears seen at the Division of Gynecologic Oncology, University of Vermont, between 1997 and 1999 were identified. The cytologic smears were reviewed and subtyped into reactive or suggestive of squamous intraepithelial lesion (SIL). The charts of these patients were reviewed and the following information was abstracted: age, gravidity, parity, menopausal status, use of hormonal replacement therapy, smoking, history of pelvic cancer, history of radiation therapy, history of abnormal Papanicolaou smear and its treatment, history of human papillomavirus (HPV) infection, and follow-up information including results of repeat Papanicolaou smears, colposcopy, and biopsies. The prevalence of dysplasia was calculated. The demographic features of women with ASCUS, reactive, were compared with those with ASCUS, SIL, using a two-sample t test, chi(2), and Fisher's exact test. Risk factors predictive of dysplasia were calculated using the odds ratio and the 95% confidence interval. P < 0.05 was considered significant. One hundred twenty-six patients with ASCUS on ThinPrep Papanicolaou smear were identified; 63 patients had ASCUS, reactive, and 63 patients had ASCUS, SIL. The demographic features of both groups were similar. The overall prevalence of dysplasia was 15.9% and was significantly higher among women with ASCUS, SIL, than among women with ASCUS, reactive (25.4% versus 6.4%, P = 0.003). The type of ASCUS cytology (reactive versus SIL), smoking, and history of HPV were significant risk factors for dysplasia (P = 0.003, 0.037, and 0. 042, respectively). The prevalence of dysplasia among women seen in a gynecologic oncology service with ASCUS

Predicting drug-target interactions using restricted Boltzmann machines.

PubMed

Wang, Yuhao; Zeng, Jianyang

2013-07-01

In silico prediction of drug-target interactions plays an important role toward identifying and developing new uses of existing or abandoned drugs. Network-based approaches have recently become a popular tool for discovering new drug-target interactions (DTIs). Unfortunately, most of these network-based approaches can only predict binary interactions between drugs and targets, and information about different types of interactions has not been well exploited for DTI prediction in previous studies. On the other hand, incorporating additional information about drug-target relationships or drug modes of action can improve prediction of DTIs. Furthermore, the predicted types of DTIs can broaden our understanding about the molecular basis of drug action. We propose a first machine learning approach to integrate multiple types of DTIs and predict unknown drug-target relationships or drug modes of action. We cast the new DTI prediction problem into a two-layer graphical model, called restricted Boltzmann machine, and apply a practical learning algorithm to train our model and make predictions. Tests on two public databases show that our restricted Boltzmann machine model can effectively capture the latent features of a DTI network and achieve excellent performance on predicting different types of DTIs, with the area under precision-recall curve up to 89.6. In addition, we demonstrate that integrating multiple types of DTIs can significantly outperform other predictions either by simply mixing multiple types of interactions without distinction or using only a single interaction type. Further tests show that our approach can infer a high fraction of novel DTIs that has been validated by known experiments in the literature or other databases. These results indicate that our approach can have highly practical relevance to DTI prediction and drug repositioning, and hence advance the drug discovery process. Software and datasets are available on request. Supplementary data are

HART-II: Prediction of Blade-Vortex Interaction Loading

NASA Technical Reports Server (NTRS)

Lim, Joon W.; Tung, Chee; Yu, Yung H.; Burley, Casey L.; Brooks, Thomas; Boyd, Doug; vanderWall, Berend; Schneider, Oliver; Richard, Hugues; Raffel, Markus

2003-01-01

During the HART-I data analysis, the need for comprehensive wake data was found including vortex creation and aging, and its re-development after blade-vortex interaction. In October 2001, US Army AFDD, NASA Langley, German DLR, French ONERA and Dutch DNW performed the HART-II test as an international joint effort. The main objective was to focus on rotor wake measurement using a PIV technique along with the comprehensive data of blade deflections, airloads, and acoustics. Three prediction teams made preliminary correlation efforts with HART-II data: a joint US team of US Army AFDD and NASA Langley, German DLR, and French ONERA. The predicted results showed significant improvements over the HART-I predicted results, computed about several years ago, which indicated that there has been better understanding of complicated wake modeling in the comprehensive rotorcraft analysis. All three teams demonstrated satisfactory prediction capabilities, in general, though there were slight deviations of prediction accuracies for various disciplines.

Prediction complements explanation in understanding the developing brain.

PubMed

Rosenberg, Monica D; Casey, B J; Holmes, Avram J

2018-02-21

A central aim of human neuroscience is understanding the neurobiology of cognition and behavior. Although we have made significant progress towards this goal, reliance on group-level studies of the developed adult brain has limited our ability to explain population variability and developmental changes in neural circuitry and behavior. In this review, we suggest that predictive modeling, a method for predicting individual differences in behavior from brain features, can complement descriptive approaches and provide new ways to account for this variability. Highlighting the outsized scientific and clinical benefits of prediction in developmental populations including adolescence, we show that predictive brain-based models are already providing new insights on adolescent-specific risk-related behaviors. Together with large-scale developmental neuroimaging datasets and complementary analytic approaches, predictive modeling affords us the opportunity and obligation to identify novel treatment targets and individually tailor the course of interventions for developmental psychopathologies that impact so many young people today.

[Predictive factors of clinically significant drug-drug interactions among regimens based on protease inhibitors, non-nucleoside reverse transcriptase inhibitors and raltegravir].

PubMed

Cervero, Miguel; Torres, Rafael; Jusdado, Juan José; Pastor, Susana; Agud, Jose Luis

2016-04-15

To determine the prevalence and types of clinically significant drug-drug interactions (CSDI) in the drug regimens of HIV-infected patients receiving antiretroviral treatment. retrospective review of database. Centre: Hospital Universitario Severo Ochoa, Infectious Unit. one hundred and forty-two participants followed by one of the authors were selected from January 1985 to December 2014. from their outpatient medical records we reviewed information from the last available visit of the participants, in relation to HIV infection, comorbidities, demographics and the drugs that they were receiving; both antiretroviral drugs and drugs not related to HIV infection. We defined CSDI from the information sheet and/or database on antiretroviral drug interactions of the University of Liverpool (http://www.hiv-druginteractions.org) and we developed a diagnostic tool to predict the possibility of CSDI. By multivariate logistic regression analysis and by estimating the diagnostic performance curve obtained, we identified a quick tool to predict the existence of drug interactions. Of 142 patients, 39 (29.11%) had some type of CSDI and in 11.2% 2 or more interactions were detected. In only one patient the combination of drugs was contraindicated (this patient was receiving darunavir/r and quetiapine). In multivariate analyses, predictors of CSDI were regimen type (PI or NNRTI) and the use of 3 or more non-antiretroviral drugs (AUC 0.886, 95% CI 0.828 to 0.944; P=.0001). The risk was 18.55 times in those receiving NNRTI and 27,95 times in those receiving IP compared to those taking raltegravir. Drug interactions, including those defined as clinically significant, are common in HIV-infected patients treated with antiretroviral drugs, and the risk is greater in IP-based regimens. Raltegravir-based prescribing, especially in patients who receive at least 3 non-HIV drugs could avoid interactions. Copyright © 2016 Elsevier España, S.L.U. All rights reserved.

Hierarchical Ensemble Methods for Protein Function Prediction

PubMed Central

2014-01-01

Protein function prediction is a complex multiclass multilabel classification problem, characterized by multiple issues such as the incompleteness of the available annotations, the integration of multiple sources of high dimensional biomolecular data, the unbalance of several functional classes, and the difficulty of univocally determining negative examples. Moreover, the hierarchical relationships between functional classes that characterize both the Gene Ontology and FunCat taxonomies motivate the development of hierarchy-aware prediction methods that showed significantly better performances than hierarchical-unaware “flat” prediction methods. In this paper, we provide a comprehensive review of hierarchical methods for protein function prediction based on ensembles of learning machines. According to this general approach, a separate learning machine is trained to learn a specific functional term and then the resulting predictions are assembled in a “consensus” ensemble decision, taking into account the hierarchical relationships between classes. The main hierarchical ensemble methods proposed in the literature are discussed in the context of existing computational methods for protein function prediction, highlighting their characteristics, advantages, and limitations. Open problems of this exciting research area of computational biology are finally considered, outlining novel perspectives for future research. PMID:25937954

Do Serum Creatinine Levels Show Clinically Significant Fluctuations on Serial Determinations on the Siemens Advia 1800 Analyzer?

PubMed

Levitan, Daniel; Harper, Aaron E; Sun, Yi; Scarpa Carniello, Jose V; Momeni, Amir; Kagan, Joshua; Alexis, Herol; Eid, Ikram; Harris, Loretta; Marshal, Barbara; Tafani, Edlira; Pincus, Matthew

2017-01-01

The goal of this work was to determine whether there are clinically significant fluctuations in the level of serum creatinine on serial determinations, especially in the borderline range (1.1-1.3 mg/dl), after specimen storage. Sixty-one serum samples were analyzed. They were divided into three categories based on the initial serum creatinine measurement: low (≤1.0 mg/dl), borderline (1.1-1.3 mg/dl), and high (≥1.4 mg/dl). The specimens were stored at 4°C and run on the Siemens Advia 1800 chemistry analyzer on days 1, 3, and 11. Statistical comparisons of the three groups were made using the unpaired t-test, yielding a two-tailed P-value for each group comparison. The P-values ranged from 0.0829 to 0.3892, indicating no statistically significant difference between the standard deviations of each group. Mild-to-moderate fluctuations in precision occur in successive serum creatinine determinations. The overwhelming majority of these fluctuations should not affect clinical decision making. © 2016 Wiley Periodicals, Inc.

Ocean eddies and climate predictability

NASA Astrophysics Data System (ADS)

Kirtman, Ben P.; Perlin, Natalie; Siqueira, Leo

2017-12-01

A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

Ocean eddies and climate predictability.

PubMed

Kirtman, Ben P; Perlin, Natalie; Siqueira, Leo

2017-12-01

A suite of coupled climate model simulations and experiments are used to examine how resolved mesoscale ocean features affect aspects of climate variability, air-sea interactions, and predictability. In combination with control simulations, experiments with the interactive ensemble coupling strategy are used to further amplify the role of the oceanic mesoscale field and the associated air-sea feedbacks and predictability. The basic intent of the interactive ensemble coupling strategy is to reduce the atmospheric noise at the air-sea interface, allowing an assessment of how noise affects the variability, and in this case, it is also used to diagnose predictability from the perspective of signal-to-noise ratios. The climate variability is assessed from the perspective of sea surface temperature (SST) variance ratios, and it is shown that, unsurprisingly, mesoscale variability significantly increases SST variance. Perhaps surprising is the fact that the presence of mesoscale ocean features even further enhances the SST variance in the interactive ensemble simulation beyond what would be expected from simple linear arguments. Changes in the air-sea coupling between simulations are assessed using pointwise convective rainfall-SST and convective rainfall-SST tendency correlations and again emphasize how the oceanic mesoscale alters the local association between convective rainfall and SST. Understanding the possible relationships between the SST-forced signal and the weather noise is critically important in climate predictability. We use the interactive ensemble simulations to diagnose this relationship, and we find that the presence of mesoscale ocean features significantly enhances this link particularly in ocean eddy rich regions. Finally, we use signal-to-noise ratios to show that the ocean mesoscale activity increases model estimated predictability in terms of convective precipitation and atmospheric upper tropospheric circulation.

The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing

PubMed Central

Weber, Kirsten; Lau, Ellen F.; Stillerman, Benjamin; Kuperberg, Gina R.

2016-01-01

Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions—a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to

The Yin and the Yang of Prediction: An fMRI Study of Semantic Predictive Processing.

PubMed

Weber, Kirsten; Lau, Ellen F; Stillerman, Benjamin; Kuperberg, Gina R

2016-01-01

Probabilistic prediction plays a crucial role in language comprehension. When predictions are fulfilled, the resulting facilitation allows for fast, efficient processing of ambiguous, rapidly-unfolding input; when predictions are not fulfilled, the resulting error signal allows us to adapt to broader statistical changes in this input. We used functional Magnetic Resonance Imaging to examine the neuroanatomical networks engaged in semantic predictive processing and adaptation. We used a relatedness proportion semantic priming paradigm, in which we manipulated the probability of predictions while holding local semantic context constant. Under conditions of higher (versus lower) predictive validity, we replicate previous observations of reduced activity to semantically predictable words in the left anterior superior/middle temporal cortex, reflecting facilitated processing of targets that are consistent with prior semantic predictions. In addition, under conditions of higher (versus lower) predictive validity we observed significant differences in the effects of semantic relatedness within the left inferior frontal gyrus and the posterior portion of the left superior/middle temporal gyrus. We suggest that together these two regions mediated the suppression of unfulfilled semantic predictions and lexico-semantic processing of unrelated targets that were inconsistent with these predictions. Moreover, under conditions of higher (versus lower) predictive validity, a functional connectivity analysis showed that the left inferior frontal and left posterior superior/middle temporal gyrus were more tightly interconnected with one another, as well as with the left anterior cingulate cortex. The left anterior cingulate cortex was, in turn, more tightly connected to superior lateral frontal cortices and subcortical regions-a network that mediates rapid learning and adaptation and that may have played a role in switching to a more predictive mode of processing in response to the

Dopamine reward prediction error coding.

PubMed

Schultz, Wolfram

2016-03-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards-an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware.

Dopamine reward prediction error coding

PubMed Central

Schultz, Wolfram

2016-01-01

Reward prediction errors consist of the differences between received and predicted rewards. They are crucial for basic forms of learning about rewards and make us strive for more rewards—an evolutionary beneficial trait. Most dopamine neurons in the midbrain of humans, monkeys, and rodents signal a reward prediction error; they are activated by more reward than predicted (positive prediction error), remain at baseline activity for fully predicted rewards, and show depressed activity with less reward than predicted (negative prediction error). The dopamine signal increases nonlinearly with reward value and codes formal economic utility. Drugs of addiction generate, hijack, and amplify the dopamine reward signal and induce exaggerated, uncontrolled dopamine effects on neuronal plasticity. The striatum, amygdala, and frontal cortex also show reward prediction error coding, but only in subpopulations of neurons. Thus, the important concept of reward prediction errors is implemented in neuronal hardware. PMID:27069377

An accelerating precursor to predict "time-to-failure" in creep and volcanic eruptions

NASA Astrophysics Data System (ADS)

Hao, Shengwang; Yang, Hang; Elsworth, Derek

2017-09-01

Real-time prediction by monitoring of the evolution of response variables is a central goal in predicting rock failure. A linear relation Ω˙Ω¨-1 = C(tf - t) has been developed to describe the time to failure, where Ω represents a response quantity, C is a constant and tf represents the failure time. Observations from laboratory creep failure experiments and precursors to volcanic eruptions are used to test the validity of the approach. Both cumulative and simple moving window techniques are developed to perform predictions and to illustrate the effects of data selection on the results. Laboratory creep failure experiments on granites show that the linear relation works well during the final approach to failure. For blind prediction, the simple moving window technique is preferred because it always uses the most recent data and excludes effects of early data deviating significantly from the predicted trend. When the predicted results show only small fluctuations, failure is imminent.

Neural Generalized Predictive Control: A Newton-Raphson Implementation

NASA Technical Reports Server (NTRS)

Soloway, Donald; Haley, Pamela J.

1997-01-01

An efficient implementation of Generalized Predictive Control using a multi-layer feedforward neural network as the plant's nonlinear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. The main cost of the Newton-Raphson algorithm is in the calculation of the Hessian, but even with this overhead the low iteration numbers make Newton-Raphson faster than other techniques and a viable algorithm for real-time control. This paper presents a detailed derivation of the Neural Generalized Predictive Control algorithm with Newton-Raphson as the minimization algorithm. Simulation results show convergence to a good solution within two iterations and timing data show that real-time control is possible. Comments about the algorithm's implementation are also included.

Prediction of Geomagnetic Activity and Key Parameters in High-latitude Ionosphere

NASA Technical Reports Server (NTRS)

Khazanov, George V.; Lyatsky, Wladislaw; Tan, Arjun; Ridley, Aaron

2007-01-01

Prediction of geomagnetic activity and related events in the Earth's magnetosphere and ionosphere are important tasks of US Space Weather Program. Prediction reliability is dependent on the prediction method, and elements included in the prediction scheme. Two of the main elements of such prediction scheme are: an appropriate geomagnetic activity index, and an appropriate coupling function (the combination of solar wind parameters providing the best correlation between upstream solar wind data and geomagnetic activity). We have developed a new index of geomagnetic activity, the Polar Magnetic (PM) index and an improved version of solar wind coupling function. PM index is similar to the existing polar cap PC index but it shows much better correlation with upstream solar wind/IMF data and other events in the magnetosphere and ionosphere. We investigate the correlation of PM index with upstream solar wind/IMF data for 10 years (1995-2004) that include both low and high solar activity. We also have introduced a new prediction function for the predicting of cross-polar-cap voltage and Joule heating based on using both PM index and upstream solar wind/IMF data. As we show such prediction function significantly increase the reliability of prediction of these important parameters. The correlation coefficients between the actual and predicted values of these parameters are approx. 0.9 and higher.

The role of anti-cyclic citrullinated peptide antibodies in predicting rheumatoid arthritis.

PubMed

Rexhepi, Sylejman; Rexhepi, Mjellma; Sahatçiu-Meka, Vjollca; Tafaj, Argjend; Izairi, Remzi; Rexhepi, Blerta

2011-01-01

The study presents the results of predicting role of anti-cyclic citrullinated peptide antibodies in rheumatoid arthritis, compared to rheumatoid factor. 32 patients with rheumatoid arthritis were identified from a retrospective chart review. The results of our study show that presence of the rheumatoid factor has less diagnostic and prognostic significance than the anti-cyclic citrullinated peptide, and suggests its superiority in predicting an erosive disease course.

Thermodynamic ocean-atmosphere Coupling and the Predictability of Nordeste rainfall

NASA Astrophysics Data System (ADS)

Chang, P.; Saravanan, R.; Giannini, A.

2003-04-01

The interannual variability of rainfall in the northeastern region of Brazil, or Nordeste, is known to be very strongly correlated with sea surface temperature (SST) variability, of Atlantic and Pacific origin. For this reason the potential predictability of Nordeste rainfall is high. The current generation of state-of-the-art atmospheric models can replicate the observed rainfall variability with high skill when forced with the observed record of SST variability. The correlation between observed and modeled indices of Nordeste rainfall, in the AMIP-style integrations with two such models (NSIPP and CCM3) analyzed here, is of the order of 0.8, i.e. the models explain about 2/3 of the observed variability. Assuming that thermodynamic, ocean-atmosphere heat exchange plays the dominant role in tropical Atlantic SST variability on the seasonal to interannual time scale, we analyze its role in Nordeste rainfall predictability using an atmospheric general circulation model coupled to a slab ocean model. Predictability experiments initialized with observed December SST show that thermodynamic coupling plays a significant role in enhancing the persistence of SST anomalies, both in the tropical Pacific and in the tropical Atlantic. We show that thermodynamic coupling is sufficient to provide fairly accurate forecasts of tropical Atlantic SST in the boreal spring that are significantly better than the persistence forecasts. The consequences for the prediction of Nordeste rainfall are analyzed.

Validity of the MCAT in Predicting Performance in the First Two Years of Medical School.

ERIC Educational Resources Information Center

Jones, Robert F.; Thomae-Forgues, Maria

1984-01-01

The first systematic summary of predictive validity research on the new Medical College Admission Test (MCAT) is presented. The results show that MCAT scores have significant predictive validity with respect to first- and second-year medical school course grades. Further directions for MCAT validity research are described. (Author/MLW)

Predicting Work Activities with Divergent Thinking Tests: A Longitudinal Study

ERIC Educational Resources Information Center

Clapham, Maria M.; Cowdery, Edwina M.; King, Kelly E.; Montang, Melissa A.

2005-01-01

This study examined whether divergent thinking test scores obtained from engineering students during college predicted creative work activities fifteen years later. Results showed that a subscore of the "Owens Creativity Test", which assesses divergent thinking about mechanical objects, correlated significantly with self-ratings of…

Durable terrestrial bedrock predicts submarine canyon formation

USGS Publications Warehouse

Smith, Elliot; Finnegan, Noah J.; Mueller, Erich R.; Best, Rebecca J.

2017-01-01

Though submarine canyons are first-order topographic features of Earth, the processes responsible for their occurrence remain poorly understood. Potentially analogous studies of terrestrial rivers show that the flux and caliber of transported bedload are significant controls on bedrock incision. Here we hypothesize that coarse sediment load could exert a similar role in the formation of submarine canyons. We conducted a comprehensive empirical analysis of canyon occurrence along the West Coast of the contiguous United States which indicates that submarine canyon occurrence is best predicted by the occurrence of durable crystalline bedrock in adjacent terrestrial catchments. Canyon occurrence is also predicted by the flux of bed sediment to shore from terrestrial streams. Surprisingly, no significant correlation was observed between canyon occurrence and the slope or width of the continental shelf. These findings suggest that canyon incision is promoted by greater yields of durable terrestrial clasts to the shore.

Mixing-model Sensitivity to Initial Conditions in Hydrodynamic Predictions

NASA Astrophysics Data System (ADS)

Bigelow, Josiah; Silva, Humberto; Truman, C. Randall; Vorobieff, Peter

2017-11-01

Amagat and Dalton mixing-models were studied to compare their thermodynamic prediction of shock states. Numerical simulations with the Sandia National Laboratories shock hydrodynamic code CTH modeled University of New Mexico (UNM) shock tube laboratory experiments shocking a 1:1 molar mixture of helium (He) and sulfur hexafluoride (SF6) . Five input parameters were varied for sensitivity analysis: driver section pressure, driver section density, test section pressure, test section density, and mixture ratio (mole fraction). We show via incremental Latin hypercube sampling (LHS) analysis that significant differences exist between Amagat and Dalton mixing-model predictions. The differences observed in predicted shock speeds, temperatures, and pressures grow more pronounced with higher shock speeds. Supported by NNSA Grant DE-0002913.

Children with autism show specific handwriting impairments

PubMed Central

Fuentes, Christina T.; Mostofsky, Stewart H.; Bastian, Amy J.

2009-01-01

Background: Handwriting skills, which are crucial for success in school, communication, and building children’s self-esteem, have been observed to be poor in individuals with autism. Little information exists on the handwriting of children with autism, without delineation of specific features that can contribute to impairments. As a result, the specific aspects of handwriting in which individuals with autism demonstrate difficulty remain unknown. Methods: A case-control study of handwriting samples from children with and without autism spectrum disorders (ASD) was performed using the Minnesota Handwriting Assessment. Samples were scored on an individual letter basis in 5 categories: legibility, form, alignment, size, and spacing. Subjects were also tested on the Wechsler Intelligence Scale for Children–IV and the Physical and Neurological Examination for Subtle (Motor) Signs. Results: We found that children with ASD do indeed show overall worse performance on a handwriting task than do age- and intelligence-matched controls. More specifically, children with ASD show worse quality of forming letters but do not show differences in their ability to correctly size, align, and space their letters. Within the ASD group, motor skills were significantly predictive of handwriting performance, whereas age, gender, IQ, and visuospatial abilities were not. Conclusions: We addressed how different elements of handwriting contribute to impairments observed in children with autism. Our results suggest that training targeting letter formation, in combination with general training of fine motor control, may be the best direction for improving handwriting performance in children with autism. GLOSSARY ADI-R = Autism Diagnostic Interview–Revised; ADOS-G = Autism Diagnostic Observation Schedule–Generic; ASD = autism spectrum disorders; DICA-IV = Diagnostic Interview for Children and Adolescents, 4th edition; DSM-IV = Diagnostic and Statistical Manual of Mental Disorders, 4th

Testing the Predictive Validity of the Hendrich II Fall Risk Model.

PubMed

Jung, Hyesil; Park, Hyeoun-Ae

2018-03-01

Cumulative data on patient fall risk have been compiled in electronic medical records systems, and it is possible to test the validity of fall-risk assessment tools using these data between the times of admission and occurrence of a fall. The Hendrich II Fall Risk Model scores assessed during three time points of hospital stays were extracted and used for testing the predictive validity: (a) upon admission, (b) when the maximum fall-risk score from admission to falling or discharge, and (c) immediately before falling or discharge. Predictive validity was examined using seven predictive indicators. In addition, logistic regression analysis was used to identify factors that significantly affect the occurrence of a fall. Among the different time points, the maximum fall-risk score assessed between admission and falling or discharge showed the best predictive performance. Confusion or disorientation and having a poor ability to rise from a sitting position were significant risk factors for a fall.

Using prediction markets to estimate the reproducibility of scientific research.

PubMed

Dreber, Anna; Pfeiffer, Thomas; Almenberg, Johan; Isaksson, Siri; Wilson, Brad; Chen, Yiling; Nosek, Brian A; Johannesson, Magnus

2015-12-15

Concerns about a lack of reproducibility of statistically significant results have recently been raised in many fields, and it has been argued that this lack comes at substantial economic costs. We here report the results from prediction markets set up to quantify the reproducibility of 44 studies published in prominent psychology journals and replicated in the Reproducibility Project: Psychology. The prediction markets predict the outcomes of the replications well and outperform a survey of market participants' individual forecasts. This shows that prediction markets are a promising tool for assessing the reproducibility of published scientific results. The prediction markets also allow us to estimate probabilities for the hypotheses being true at different testing stages, which provides valuable information regarding the temporal dynamics of scientific discovery. We find that the hypotheses being tested in psychology typically have low prior probabilities of being true (median, 9%) and that a "statistically significant" finding needs to be confirmed in a well-powered replication to have a high probability of being true. We argue that prediction markets could be used to obtain speedy information about reproducibility at low cost and could potentially even be used to determine which studies to replicate to optimally allocate limited resources into replications.

The prognostic significance of HOTAIR for predicting clinical outcome in patients with digestive system tumors.

PubMed

Ma, Gaoxiang; Wang, Qiaoyan; Lv, Chunye; Qiang, Fulin; Hua, Qiuhan; Chu, Haiyan; Du, Mulong; Tong, Na; Jiang, Yejuan; Wang, Meilin; Zhang, Zhengdong; Wang, Jian; Gong, Weida

2015-12-01

Although some studies have assessed the prognostic value of HOTAIR in patients with digestive system tumors, the relationship between the HOTAIR and outcome of digestive system tumors remains unknown. The PubMed was searched to identify the eligible studies. Here, we performed a meta-analysis with 11 studies, including a total of 903 cases. Pooled hazard ratios (HRs) and 95 % confidence interval (CI) of HOTAIR for cancer survival were calculated. We found that the pooled HR elevated HOTAIR expression in tumor tissues was 2.36 (95 % CI 1.88-2.97) compared with patients with low HOTAIR expression. Moreover, subgroup analysis revealed that HOTAIR overexpression was also markedly associated with short survival for esophageal squamous cell carcinoma (HR 2.19, 95 % CI 1.62-2.94) and gastric cancer (HR 1.66, 95 % CI 1.02-2.68). In addition, up-regulated HOTAIR was significantly related to survival of digestive system cancer among the studies with more follow-up time (follow time ≥ 5 years) (HR 2.51, 95 % CI 1.99-3.17). When stratified by HR resource and number of patients, the result indicated consistent results with the overall analysis. Subgroup analysis on ethnicities did not change the prognostic influence of elevated HOTAIR expression. Additionally, we conducted an independent validation cohort including 71 gastric cancer cases, in which patients with up-regulated HOTAIR expression had an unfavorable outcome with HR of 2.10 (95 % CI 1.10-4.03). The results suggest that aberrant HOTAIR expression may serve as a candidate positive marker to predict the prognosis of patients with carcinoma of digestive system.

Enuresis, Firesetting, and Cruelty to Animals: Does the Ego Triad Show Predictive Validity?

ERIC Educational Resources Information Center

Slavkin, Michael Lawrence

2001-01-01

The hypothesis tested in this study was that the presence of enuresis and cruelty to animals in juvenile firesetters would be significantly related to recidivistic firesetting. No relationship was found between firesetting recidivism and enuresis. However, juveniles who were identified as being cruel to animals were more likely to engage in…

Frequency, probability, and prediction: easy solutions to cognitive illusions?

PubMed

Griffin, D; Buehler, R

1999-02-01

Many errors in probabilistic judgment have been attributed to people's inability to think in statistical terms when faced with information about a single case. Prior theoretical analyses and empirical results imply that the errors associated with case-specific reasoning may be reduced when people make frequentistic predictions about a set of cases. In studies of three previously identified cognitive biases, we find that frequency-based predictions are different from-but no better than-case-specific judgments of probability. First, in studies of the "planning fallacy, " we compare the accuracy of aggregate frequency and case-specific probability judgments in predictions of students' real-life projects. When aggregate and single-case predictions are collected from different respondents, there is little difference between the two: Both are overly optimistic and show little predictive validity. However, in within-subject comparisons, the aggregate judgments are significantly more conservative than the single-case predictions, though still optimistically biased. Results from studies of overconfidence in general knowledge and base rate neglect in categorical prediction underline a general conclusion. Frequentistic predictions made for sets of events are no more statistically sophisticated, nor more accurate, than predictions made for individual events using subjective probability. Copyright 1999 Academic Press.

Predictive sufficiency and the use of stored internal state

NASA Technical Reports Server (NTRS)

Musliner, David J.; Durfee, Edmund H.; Shin, Kang G.

1994-01-01

In all embedded computing systems, some delay exists between sensing and acting. By choosing an action based on sensed data, a system is essentially predicting that there will be no significant changes in the world during this delay. However, the dynamic and uncertain nature of the real world can make these predictions incorrect, and thus, a system may execute inappropriate actions. Making systems more reactive by decreasing the gap between sensing and action leaves less time for predictions to err, but still provides no principled assurance that they will be correct. Using the concept of predictive sufficiency described in this paper, a system can prove that its predictions are valid, and that it will never execute inappropriate actions. In the context of our CIRCA system, we also show how predictive sufficiency allows a system to guarantee worst-case response times to changes in its environment. Using predictive sufficiency, CIRCA is able to build real-time reactive control plans which provide a sound basis for performance guarantees that are unavailable with other reactive systems.

Predicting asthma exacerbations using artificial intelligence.

PubMed

Finkelstein, Joseph; Wood, Jeffrey

2013-01-01

Modern telemonitoring systems identify a serious patient deterioration when it already occurred. It would be much more beneficial if the upcoming clinical deterioration were identified ahead of time even before a patient actually experiences it. The goal of this study was to assess artificial intelligence approaches which potentially can be used in telemonitoring systems for advance prediction of changes in disease severity before they actually occur. The study dataset was based on daily self-reports submitted by 26 adult asthma patients during home telemonitoring consisting of 7001 records. Two classification algorithms were employed for building predictive models: naïve Bayesian classifier and support vector machines. Using a 7-day window, a support vector machine was able to predict asthma exacerbation to occur on the day 8 with the accuracy of 0.80, sensitivity of 0.84 and specificity of 0.80. Our study showed that methods of artificial intelligence have significant potential in developing individualized decision support for chronic disease telemonitoring systems.

Simplified ultrasound protocol for the exclusion of clinically significant carotid artery stenosis.

PubMed

Högberg, Dominika; Dellagrammaticas, Demosthenes; Kragsterman, Björn; Björck, Martin; Wanhainen, Anders

2016-08-01

To evaluate a simplified ultrasound protocol for the exclusion of clinically significant carotid artery stenosis for screening purposes. A total of 9,493 carotid arteries in 4,748 persons underwent carotid ultrasound examination. Most subjects were 65-year-old men attending screening for abdominal aortic aneurysm. The presence of a stenosis on B-mode and/or a mosaic pattern in post-stenotic areas on colour Doppler and maximum peak systolic velocity (PSV) in the internal carotid artery (ICA) were recorded. A carotid stenosis was defined as The North American Symptomatic Carotid Endarterectomy Trial (NASCET) >20% and a significant stenosis as NASCET >50%. The kappa (κ) statistic was used to assess agreement between methods. Sensitivity, specificity, positive predictive (PPV), and negative predictive (NPV) values were calculated for the greyscale/mosaic method compared to conventional assessment by means of PSV measurement. An ICA stenosis was found in 121 (1.3%) arteries; 82 (0.9%) were graded 20%-49%, 16 (0.2%) were 50%-69%, and 23 (0.2%) were 70%-99%. Eighteen (0.2%) arteries were occluded. Overall, the greyscale/mosaic protocol showed a moderate agreement with ICA PSV measurements for the detection of carotid artery stenosis, κ = 0.455. The sensitivity, specificity, PPV, and NPV for detection of >20% ICA stenosis were 91% (95% CI 0.84-0.95), 97% (0.97-0.98), 31% (0.26-0.36), and 97% (0.97-0.97), respectively. The corresponding figures for >50% stenosis were 90% (0.83-0.95), 97% (0.97-0.98), 11% (0.08-0.15), and 100% (0.99-1.00). Compared with PSV measurements, the simplified greyscale/mosaic protocol had a high negative predictive value for detection of >50% carotid stenosis, suggesting that it may be suitable as a screening method to exclude significant disease.

Improved prediction of biochemical recurrence after radical prostatectomy by genetic polymorphisms.

PubMed

Morote, Juan; Del Amo, Jokin; Borque, Angel; Ars, Elisabet; Hernández, Carlos; Herranz, Felipe; Arruza, Antonio; Llarena, Roberto; Planas, Jacques; Viso, María J; Palou, Joan; Raventós, Carles X; Tejedor, Diego; Artieda, Marta; Simón, Laureano; Martínez, Antonio; Rioja, Luis A

2010-08-01

Single nucleotide polymorphisms are inherited genetic variations that can predispose or protect individuals against clinical events. We hypothesized that single nucleotide polymorphism profiling may improve the prediction of biochemical recurrence after radical prostatectomy. We performed a retrospective, multi-institutional study of 703 patients treated with radical prostatectomy for clinically localized prostate cancer who had at least 5 years of followup after surgery. All patients were genotyped for 83 prostate cancer related single nucleotide polymorphisms using a low density oligonucleotide microarray. Baseline clinicopathological variables and single nucleotide polymorphisms were analyzed to predict biochemical recurrence within 5 years using stepwise logistic regression. Discrimination was measured by ROC curve AUC, specificity, sensitivity, predictive values, net reclassification improvement and integrated discrimination index. The overall biochemical recurrence rate was 35%. The model with the best fit combined 8 covariates, including the 5 clinicopathological variables prostate specific antigen, Gleason score, pathological stage, lymph node involvement and margin status, and 3 single nucleotide polymorphisms at the KLK2, SULT1A1 and TLR4 genes. Model predictive power was defined by 80% positive predictive value, 74% negative predictive value and an AUC of 0.78. The model based on clinicopathological variables plus single nucleotide polymorphisms showed significant improvement over the model without single nucleotide polymorphisms, as indicated by 23.3% net reclassification improvement (p = 0.003), integrated discrimination index (p <0.001) and likelihood ratio test (p <0.001). Internal validation proved model robustness (bootstrap corrected AUC 0.78, range 0.74 to 0.82). The calibration plot showed close agreement between biochemical recurrence observed and predicted probabilities. Predicting biochemical recurrence after radical prostatectomy based on

Improved Short-Term Clock Prediction Method for Real-Time Positioning.

PubMed

Lv, Yifei; Dai, Zhiqiang; Zhao, Qile; Yang, Sheng; Zhou, Jinning; Liu, Jingnan

2017-06-06

The application of real-time precise point positioning (PPP) requires real-time precise orbit and clock products that should be predicted within a short time to compensate for the communication delay or data gap. Unlike orbit correction, clock correction is difficult to model and predict. The widely used linear model hardly fits long periodic trends with a small data set and exhibits significant accuracy degradation in real-time prediction when a large data set is used. This study proposes a new prediction model for maintaining short-term satellite clocks to meet the high-precision requirements of real-time clocks and provide clock extrapolation without interrupting the real-time data stream. Fast Fourier transform (FFT) is used to analyze the linear prediction residuals of real-time clocks. The periodic terms obtained through FFT are adopted in the sliding window prediction to achieve a significant improvement in short-term prediction accuracy. This study also analyzes and compares the accuracy of short-term forecasts (less than 3 h) by using different length observations. Experimental results obtained from International GNSS Service (IGS) final products and our own real-time clocks show that the 3-h prediction accuracy is better than 0.85 ns. The new model can replace IGS ultra-rapid products in the application of real-time PPP. It is also found that there is a positive correlation between the prediction accuracy and the short-term stability of on-board clocks. Compared with the accuracy of the traditional linear model, the accuracy of the static PPP using the new model of the 2-h prediction clock in N, E, and U directions is improved by about 50%. Furthermore, the static PPP accuracy of 2-h clock products is better than 0.1 m. When an interruption occurs in the real-time model, the accuracy of the kinematic PPP solution using 1-h clock prediction product is better than 0.2 m, without significant accuracy degradation. This model is of practical significance

New Computational Methods for the Prediction and Analysis of Helicopter Noise

NASA Technical Reports Server (NTRS)

Strawn, Roger C.; Oliker, Leonid; Biswas, Rupak

1996-01-01

This paper describes several new methods to predict and analyze rotorcraft noise. These methods are: 1) a combined computational fluid dynamics and Kirchhoff scheme for far-field noise predictions, 2) parallel computer implementation of the Kirchhoff integrations, 3) audio and visual rendering of the computed acoustic predictions over large far-field regions, and 4) acoustic tracebacks to the Kirchhoff surface to pinpoint the sources of the rotor noise. The paper describes each method and presents sample results for three test cases. The first case consists of in-plane high-speed impulsive noise and the other two cases show idealized parallel and oblique blade-vortex interactions. The computed results show good agreement with available experimental data but convey much more information about the far-field noise propagation. When taken together, these new analysis methods exploit the power of new computer technologies and offer the potential to significantly improve our prediction and understanding of rotorcraft noise.

Significant Scales in Community Structure

NASA Astrophysics Data System (ADS)

Traag, V. A.; Krings, G.; van Dooren, P.

2013-10-01

Many complex networks show signs of modular structure, uncovered by community detection. Although many methods succeed in revealing various partitions, it remains difficult to detect at what scale some partition is significant. This problem shows foremost in multi-resolution methods. We here introduce an efficient method for scanning for resolutions in one such method. Additionally, we introduce the notion of ``significance'' of a partition, based on subgraph probabilities. Significance is independent of the exact method used, so could also be applied in other methods, and can be interpreted as the gain in encoding a graph by making use of a partition. Using significance, we can determine ``good'' resolution parameters, which we demonstrate on benchmark networks. Moreover, optimizing significance itself also shows excellent performance. We demonstrate our method on voting data from the European Parliament. Our analysis suggests the European Parliament has become increasingly ideologically divided and that nationality plays no role.

Significant correlation between spleen volume and thrombocytopenia in liver transplant patients: a concept for predicting persistent thrombocytopenia.

PubMed

Ohira, Masahiro; Ishifuro, Minoru; Ide, Kentaro; Irei, Toshimitsu; Tashiro, Hirotaka; Itamoto, Toshiyuki; Ito, Katsuhide; Chayama, Kazuaki; Asahara, Toshimasa; Ohdan, Hideki

2009-02-01

Interferon (IFN) therapy with or without ribavirin treatment is well established as a standard antiviral treatment for hepatitis C virus (HCV)-infected patients. However, susceptibility to thrombocytopenia is a major obstacle for initiating or continuing this therapy, particularly in liver transplant (LTx) recipients with HCV. Studies have reported that splenectomy performed concurrently with LTx is a feasible strategy for conditioning patients for anti-HCV IFN therapy. However, the relationship between the severity of splenomegaly and alterations in the blood cytopenia in LTx recipients remains to be clarified. Here, we analyzed the relationship between spleen volume (SV) and thrombocytopenia in 45 patients who underwent LTx at Hiroshima University Hospital. The extent of pre-LTx splenomegaly [the SV to body surface area (BSA) ratio in an individual] was inversely correlated with both the post-LTx white blood cell count and platelet (PLT) count (P < 0.001). Furthermore, the PLT count of patients with thrombocytopenia (PLT count significantly in the group without splenomegaly (SV/BSA value < 400) versus that in the group with splenomegaly (P = 0.005). Thus, if both splenomegaly and thrombocytopenia coexist (PLT count or= 400), persistent thrombocytopenia is predictable after LTx. (c) 2009 AASLD.

Statistical Analysis of the AIAA Drag Prediction Workshop CFD Solutions

NASA Technical Reports Server (NTRS)

Morrison, Joseph H.; Hemsch, Michael J.

2007-01-01

The first AIAA Drag Prediction Workshop (DPW), held in June 2001, evaluated the results from an extensive N-version test of a collection of Reynolds-Averaged Navier-Stokes CFD codes. The code-to-code scatter was more than an order of magnitude larger than desired for design and experimental validation of cruise conditions for a subsonic transport configuration. The second AIAA Drag Prediction Workshop, held in June 2003, emphasized the determination of installed pylon-nacelle drag increments and grid refinement studies. The code-to-code scatter was significantly reduced compared to the first DPW, but still larger than desired. However, grid refinement studies showed no significant improvement in code-to-code scatter with increasing grid refinement. The third AIAA Drag Prediction Workshop, held in June 2006, focused on the determination of installed side-of-body fairing drag increments and grid refinement studies for clean attached flow on wing alone configurations and for separated flow on the DLR-F6 subsonic transport model. This report compares the transonic cruise prediction results of the second and third workshops using statistical analysis.

The interactional significance of formulas in autistic language.

PubMed

Dobbinson, Sushie; Perkins, Mick; Boucher, Jill

2003-01-01

The phenomenon of echolalia in autistic language is well documented. Whilst much early research dismissed echolalia as merely an indicator of cognitive limitation, later work identified particular discourse functions of echolalic utterances. The work reported here extends the study of the interactional significance of echolalia to formulaic utterances. Audio and video recordings of conversations between the first author and two research participants were transcribed and analysed according to a Conversation Analysis framework and a multi-layered linguistic framework. Formulaic language was found to have predictable interactional significance within the language of an individual with autism, and the generic phenomenon of formulaicity in company with predictable discourse function was seen to hold across the research participants, regardless of cognitive ability. The implications of formulaicity in autistic language for acquisition and processing mechanisms are discussed.

U.S. Civil Air Show Crashes, 1993 to 2013

PubMed Central

Ballard, Sarah-Blythe; Osorio, Victor B.

2016-01-01

This study provides new public health data about U.S. civil air shows. Risk factors for fatalities in civil air show crashes were analyzed. The value of the FIA score in predicting fatal outcomes was evaluated. With the use of the FAA’s General Aviation and Air Taxi Survey and the National Transportation Safety Board’s data, the incidence of civil air show crashes from 1993 to 2013 was calculated. Fatality risk factors for crashes were analyzed by means of regression methods. The FIA index was validated to predict fatal outcomes by using the factors of fire, instrument conditions, and away-from-airport location, and was evaluated through receiver operating characteristic (ROC) curves. The civil air show crash rate was 31 crashes per 1,000 civil air events. Of the 174 civil air show crashes that occurred during the study period, 91 (52%) involved at least one fatality; on average, 1.1 people died per fatal crash. Fatalities were associated with four major risk factors: fire [adjusted odds ratio (AOR) = 7.1, 95% confidence interval (CI) = 2.4 to 20.6, P < .001], pilot error (AOR = 5.2, 95% CI = 1.8 to 14.5, P = .002), aerobatic flight (AOR = 3.6, 95% CI = 1.6 to 8.2, P = .002), and off-airport location (AOR = 3.4, 95% CI = 1.5 to 7.5, P = .003). The area under the FIA score’s ROC curve was 0.71 (95% CI = 0.64 to 0.78). Civil air show crashes were marked by a high risk of fatal outcomes to pilots in aerobatic performances but rare mass casualties. The FIA score was not a valid measurement of fatal risk in civil air show crashes. PMID:27773963

A multiparametric magnetic resonance imaging-based risk model to determine the risk of significant prostate cancer prior to biopsy.

PubMed

van Leeuwen, Pim J; Hayen, Andrew; Thompson, James E; Moses, Daniel; Shnier, Ron; Böhm, Maret; Abuodha, Magdaline; Haynes, Anne-Maree; Ting, Francis; Barentsz, Jelle; Roobol, Monique; Vass, Justin; Rasiah, Krishan; Delprado, Warick; Stricker, Phillip D

2017-12-01

To develop and externally validate a predictive model for detection of significant prostate cancer. Development of the model was based on a prospective cohort including 393 men who underwent multiparametric magnetic resonance imaging (mpMRI) before biopsy. External validity of the model was then examined retrospectively in 198 men from a separate institution whom underwent mpMRI followed by biopsy for abnormal prostate-specific antigen (PSA) level or digital rectal examination (DRE). A model was developed with age, PSA level, DRE, prostate volume, previous biopsy, and Prostate Imaging Reporting and Data System (PIRADS) score, as predictors for significant prostate cancer (Gleason 7 with >5% grade 4, ≥20% cores positive or ≥7 mm of cancer in any core). Probability was studied via logistic regression. Discriminatory performance was quantified by concordance statistics and internally validated with bootstrap resampling. In all, 393 men had complete data and 149 (37.9%) had significant prostate cancer. While the variable model had good accuracy in predicting significant prostate cancer, area under the curve (AUC) of 0.80, the advanced model (incorporating mpMRI) had a significantly higher AUC of 0.88 (P < 0.001). The model was well calibrated in internal and external validation. Decision analysis showed that use of the advanced model in practice would improve biopsy outcome predictions. Clinical application of the model would reduce 28% of biopsies, whilst missing 2.6% significant prostate cancer. Individualised risk assessment of significant prostate cancer using a predictive model that incorporates mpMRI PIRADS score and clinical data allows a considerable reduction in unnecessary biopsies and reduction of the risk of over-detection of insignificant prostate cancer at the cost of a very small increase in the number of significant cancers missed. © 2017 The Authors BJU International © 2017 BJU International Published by John Wiley & Sons Ltd.

Prognostic significance of muc4 expression in gallbladder carcinoma.

PubMed

Lee, Hyeon Kook; Cho, Min-Sun; Kim, Tae Hun

2012-10-27

Mucins are high molecular glycoproteins and play protective and lubricating roles in various epithelial tissues. Deregulated expression of mucins is involved in carcinogenesis and tumor invasion. MUC4 expression has been identified as a poor prognostic factor in pancreatobiliary carcinomas. To date, the relation between MUC4 expression and prognosis in gallbladder carcinoma remains to be determined. Authors examined MUC4 expression in gallbladder carcinoma and investigated its impact on prognosis. The expression profiles of MUC4, MUC1, MUC2 mucins in gallbladder carcinoma tissues from 63 patients were investigated using immunohistochemical staining. For gallbladder carcinoma, positive staining of MUC4, MUC1, and MUC2 was 55.6%, 81.0%, 28.6%, respectively. There was a significant correlation between the expression of MUC4 and the expression of MUC1 or MUC2 (p = 0.004, p = 0.009, respectively). Univariate analysis showed that MUC4 expression (p = 0.047), differentiation (p < 0.05), T-stage (p < 0.05) and lymph node metastasis (p < 0.001) were significantly associated with poor survival. Expression of MUC1 and MUC2 was not correlated to survival. The backward stepwise multivariate analysis showed that MUC4 expression (p = 0.039) and lymph node metastasis (p = 0.001) were significant independent risk factors. In combined assessment of MUC4 and MUC2 expression, MUC4 positive and MUC2 negative group showed a significantly worse outcome than MUC4 negative groups(MUC4-/MUC2+ and MUC4-/MUC2-) and MUC4/MUC2 co-expression group(MUC4+/MUC2+) (p < 0.05). MUC4 expression in gallbladder carcinoma is an independent poor prognostic factor. Therefore, MUC4 expression may be a useful marker to predict the outcome of patients with surgically resected gallbladder carcinoma. MUC2 expression may have prognostic value when combined with MUC4 expression.

Prognostic significance of muc4 expression in gallbladder carcinoma

PubMed Central

2012-01-01

Background Mucins are high molecular glycoproteins and play protective and lubricating roles in various epithelial tissues. Deregulated expression of mucins is involved in carcinogenesis and tumor invasion. MUC4 expression has been identified as a poor prognostic factor in pancreatobiliary carcinomas. To date, the relation between MUC4 expression and prognosis in gallbladder carcinoma remains to be determined. Authors examined MUC4 expression in gallbladder carcinoma and investigated its impact on prognosis. Methods The expression profiles of MUC4, MUC1, MUC2 mucins in gallbladder carcinoma tissues from 63 patients were investigated using immunohistochemical staining. Results For gallbladder carcinoma, positive staining of MUC4, MUC1, and MUC2 was 55.6%, 81.0%, 28.6%, respectively. There was a significant correlation between the expression of MUC4 and the expression of MUC1 or MUC2 (p = 0.004, p = 0.009, respectively). Univariate analysis showed that MUC4 expression (p = 0.047), differentiation (p < 0.05), T-stage (p < 0.05) and lymph node metastasis (p < 0.001) were significantly associated with poor survival. Expression of MUC1 and MUC2 was not correlated to survival. The backward stepwise multivariate analysis showed that MUC4 expression (p = 0.039) and lymph node metastasis (p = 0.001) were significant independent risk factors. In combined assessment of MUC4 and MUC2 expression, MUC4 positive and MUC2 negative group showed a significantly worse outcome than MUC4 negative groups(MUC4-/MUC2+ and MUC4-/MUC2-) and MUC4/MUC2 co-expression group(MUC4+/MUC2+) (p < 0.05). Conclusions MUC4 expression in gallbladder carcinoma is an independent poor prognostic factor. Therefore, MUC4 expression may be a useful marker to predict the outcome of patients with surgically resected gallbladder carcinoma. MUC2 expression may have prognostic value when combined with MUC4 expression. PMID:23101681

Combined use of serum MCP-1/IL-10 ratio and uterine artery Doppler index significantly improves the prediction of preeclampsia.

PubMed

Cui, Shihong; Gao, Yanan; Zhang, Linlin; Wang, Yuan; Zhang, Lindong; Liu, Pingping; Liu, Ling; Chen, Juan

2017-10-01

Monocyte chemotactic protein-1 (MCP-1, or CCL2) is a member of the chemokine subfamily involved in recruitment of monocytes in inflammatory tissues. IL-10 is a key regulator for maintaining the balance of anti-inflammatory and pro-inflammatory milieu at the feto-maternal interface. Doppler examination has been routinely performed for the monitoring and management of preeclampsia patients. This study evaluates the efficiency of these factors alone, or in combination, for the predication of preeclampsia. The serum levels of MCP-1 and IL-10 in 78 preeclampsia patients and 143 age-matched normal controls were measured. The Doppler ultrasonography was performed and Artery Pulsatility Index (PI) and Resistance Index (RI) were calculated for the same subjects. It was found that while the second-trimester serum MCP-1, IL-10, MCP-1/IL-10 ratio, PI, and RI showed some power in predicting preeclampsia, the combination of MCP-1/IL-10 and PI and RI accomplishes the highest efficiency, achieving an AUC of 0.973 (95% CI, 0.000-1.000, P<0.001), a sensitivity of 94%, and a specificity of 80%. The use of MCP-1/IL-10 ratio in combination with ultrasound findings appears to provide a promising modality for predicting preeclampsia. Future studies using a larger sample can be conducted to construct an algorithm capable of quantitative assessment on the risk of preeclampsia. Copyright © 2016 Elsevier B.V. All rights reserved.

In silico prediction of novel therapeutic targets using gene-disease association data.

PubMed

Ferrero, Enrico; Dunham, Ian; Sanseau, Philippe

2017-08-29

Target identification and validation is a pressing challenge in the pharmaceutical industry, with many of the programmes that fail for efficacy reasons showing poor association between the drug target and the disease. Computational prediction of successful targets could have a considerable impact on attrition rates in the drug discovery pipeline by significantly reducing the initial search space. Here, we explore whether gene-disease association data from the Open Targets platform is sufficient to predict therapeutic targets that are actively being pursued by pharmaceutical companies or are already on the market. To test our hypothesis, we train four different classifiers (a random forest, a support vector machine, a neural network and a gradient boosting machine) on partially labelled data and evaluate their performance using nested cross-validation and testing on an independent set. We then select the best performing model and use it to make predictions on more than 15,000 genes. Finally, we validate our predictions by mining the scientific literature for proposed therapeutic targets. We observe that the data types with the best predictive power are animal models showing a disease-relevant phenotype, differential expression in diseased tissue and genetic association with the disease under investigation. On a test set, the neural network classifier achieves over 71% accuracy with an AUC of 0.76 when predicting therapeutic targets in a semi-supervised learning setting. We use this model to gain insights into current and failed programmes and to predict 1431 novel targets, of which a highly significant proportion has been independently proposed in the literature. Our in silico approach shows that data linking genes and diseases is sufficient to predict novel therapeutic targets effectively and confirms that this type of evidence is essential for formulating or strengthening hypotheses in the target discovery process. Ultimately, more rapid and automated target

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.

The Yin and Yang of support from significant others: Influence of general social support and partner support of avoidance in the context of treatment for social anxiety disorder.

PubMed

Rapee, Ronald M; Peters, Lorna; Carpenter, Leigh; Gaston, Jonathan E

2015-06-01

Support from social networks is generally considered to protect against mental disorder but in some circumstances support for negative behaviours (such as avoidance) may be counterproductive. Given the critical interplay between social anxiety disorder and social interactions, it is surprising that the relationship of support from significant others to this disorder has received so little attention. The current study evaluated the reciprocal relationships between perceived social support and perceived partner support for avoidance behaviours (avoidance support) among a sample of 131 participants with social anxiety disorder who were assessed three times within the context of a treatment outcome study. A new measure of partner support for avoidance behaviours was developed, called the Avoidance Support Measure, and showed adequate internal consistency and construct validity. Correlations at baseline showed significant negative relationships between perceived social support and social anxiety and significant positive relationships between avoidance support and social anxiety. Path analysis showed that perceived social support at Times 1 and 2 negatively predicted future social anxiety at Times 2 and 3. On the other hand, only a single predictive relationship involving avoidance support was significant and showed that social anxiety at Time 1 positively predicted avoidance support at Time 2. These early results point to the different ways that support from significant others might relate to social anxiety and suggest that further work in this area may be fruitful. Copyright © 2015 Elsevier Ltd. All rights reserved.

Minimotif Miner 3.0: database expansion and significantly improved reduction of false-positive predictions from consensus sequences.

PubMed

Mi, Tian; Merlin, Jerlin Camilus; Deverasetty, Sandeep; Gryk, Michael R; Bill, Travis J; Brooks, Andrew W; Lee, Logan Y; Rathnayake, Viraj; Ross, Christian A; Sargeant, David P; Strong, Christy L; Watts, Paula; Rajasekaran, Sanguthevar; Schiller, Martin R

2012-01-01

Minimotif Miner (MnM available at http://minimotifminer.org or http://mnm.engr.uconn.edu) is an online database for identifying new minimotifs in protein queries. Minimotifs are short contiguous peptide sequences that have a known function in at least one protein. Here we report the third release of the MnM database which has now grown 60-fold to approximately 300,000 minimotifs. Since short minimotifs are by their nature not very complex we also summarize a new set of false-positive filters and linear regression scoring that vastly enhance minimotif prediction accuracy on a test data set. This online database can be used to predict new functions in proteins and causes of disease.

Dispersion-correcting potentials can significantly improve the bond dissociation enthalpies and noncovalent binding energies predicted by density-functional theory

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

DiLabio, Gino A., E-mail: Gino.DiLabio@nrc.ca; Department of Chemistry, University of British Columbia, Okanagan, 3333 University Way, Kelowna, British Columbia V1V 1V7; Koleini, Mohammad

2014-05-14

Dispersion-correcting potentials (DCPs) are atom-centered Gaussian functions that are applied in a manner that is similar to effective core potentials. Previous work on DCPs has focussed on their use as a simple means of improving the ability of conventional density-functional theory methods to predict the binding energies of noncovalently bonded molecular dimers. We show in this work that DCPs developed for use with the LC-ωPBE functional along with 6-31+G(2d,2p) basis sets are capable of simultaneously improving predicted noncovalent binding energies of van der Waals dimer complexes and covalent bond dissociation enthalpies in molecules. Specifically, the DCPs developed herein for themore » C, H, N, and O atoms provide binding energies for a set of 66 noncovalently bonded molecular dimers (the “S66” set) with a mean absolute error (MAE) of 0.21 kcal/mol, which represents an improvement of more than a factor of 10 over unadorned LC-ωPBE/6-31+G(2d,2p) and almost a factor of two improvement over LC-ωPBE/6-31+G(2d,2p) used in conjunction with the “D3” pairwise dispersion energy corrections. In addition, the DCPs reduce the MAE of calculated X-H and X-Y (X,Y = C, H, N, O) bond dissociation enthalpies for a set of 40 species from 3.2 kcal/mol obtained with unadorned LC-ωPBE/6-31+G(2d,2p) to 1.6 kcal/mol. Our findings demonstrate that broad improvements to the performance of DFT methods may be achievable through the use of DCPs.« less

Discriminative prediction of mammalian enhancers from DNA sequence

PubMed Central

Lee, Dongwon; Karchin, Rachel; Beer, Michael A.

2011-01-01

Accurately predicting regulatory sequences and enhancers in entire genomes is an important but difficult problem, especially in large vertebrate genomes. With the advent of ChIP-seq technology, experimental detection of genome-wide EP300/CREBBP bound regions provides a powerful platform to develop predictive tools for regulatory sequences and to study their sequence properties. Here, we develop a support vector machine (SVM) framework which can accurately identify EP300-bound enhancers using only genomic sequence and an unbiased set of general sequence features. Moreover, we find that the predictive sequence features identified by the SVM classifier reveal biologically relevant sequence elements enriched in the enhancers, but we also identify other features that are significantly depleted in enhancers. The predictive sequence features are evolutionarily conserved and spatially clustered, providing further support of their functional significance. Although our SVM is trained on experimental data, we also predict novel enhancers and show that these putative enhancers are significantly enriched in both ChIP-seq signal and DNase I hypersensitivity signal in the mouse brain and are located near relevant genes. Finally, we present results of comparisons between other EP300/CREBBP data sets using our SVM and uncover sequence elements enriched and/or depleted in the different classes of enhancers. Many of these sequence features play a role in specifying tissue-specific or developmental-stage-specific enhancer activity, but our results indicate that some features operate in a general or tissue-independent manner. In addition to providing a high confidence list of enhancer targets for subsequent experimental investigation, these results contribute to our understanding of the general sequence structure of vertebrate enhancers. PMID:21875935

A Predictive Model of Intein Insertion Site for Use in the Engineering of Molecular Switches

PubMed Central

Apgar, James; Ross, Mary; Zuo, Xiao; Dohle, Sarah; Sturtevant, Derek; Shen, Binzhang; de la Vega, Humberto; Lessard, Philip; Lazar, Gabor; Raab, R. Michael

2012-01-01

Inteins are intervening protein domains with self-splicing ability that can be used as molecular switches to control activity of their host protein. Successfully engineering an intein into a host protein requires identifying an insertion site that permits intein insertion and splicing while allowing for proper folding of the mature protein post-splicing. By analyzing sequence and structure based properties of native intein insertion sites we have identified four features that showed significant correlation with the location of the intein insertion sites, and therefore may be useful in predicting insertion sites in other proteins that provide native-like intein function. Three of these properties, the distance to the active site and dimer interface site, the SVM score of the splice site cassette, and the sequence conservation of the site showed statistically significant correlation and strong predictive power, with area under the curve (AUC) values of 0.79, 0.76, and 0.73 respectively, while the distance to secondary structure/loop junction showed significance but with less predictive power (AUC of 0.54). In a case study of 20 insertion sites in the XynB xylanase, two features of native insertion sites showed correlation with the splice sites and demonstrated predictive value in selecting non-native splice sites. Structural modeling of intein insertions at two sites highlighted the role that the insertion site location could play on the ability of the intein to modulate activity of the host protein. These findings can be used to enrich the selection of insertion sites capable of supporting intein splicing and hosting an intein switch. PMID:22649521

Link prediction in multiplex online social networks.

PubMed

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

Link prediction in multiplex online social networks

NASA Astrophysics Data System (ADS)

Jalili, Mahdi; Orouskhani, Yasin; Asgari, Milad; Alipourfard, Nazanin; Perc, Matjaž

2017-02-01

Online social networks play a major role in modern societies, and they have shaped the way social relationships evolve. Link prediction in social networks has many potential applications such as recommending new items to users, friendship suggestion and discovering spurious connections. Many real social networks evolve the connections in multiple layers (e.g. multiple social networking platforms). In this article, we study the link prediction problem in multiplex networks. As an example, we consider a multiplex network of Twitter (as a microblogging service) and Foursquare (as a location-based social network). We consider social networks of the same users in these two platforms and develop a meta-path-based algorithm for predicting the links. The connectivity information of the two layers is used to predict the links in Foursquare network. Three classical classifiers (naive Bayes, support vector machines (SVM) and K-nearest neighbour) are used for the classification task. Although the networks are not highly correlated in the layers, our experiments show that including the cross-layer information significantly improves the prediction performance. The SVM classifier results in the best performance with an average accuracy of 89%.

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

PubMed

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

2015-07-01

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

The role of model errors represented by nonlinear forcing singular vector tendency error in causing the "spring predictability barrier" within ENSO predictions

NASA Astrophysics Data System (ADS)

Duan, Wansuo; Zhao, Peng

2017-04-01

Within the Zebiak-Cane model, the nonlinear forcing singular vector (NFSV) approach is used to investigate the role of model errors in the "Spring Predictability Barrier" (SPB) phenomenon within ENSO predictions. NFSV-related errors have the largest negative effect on the uncertainties of El Niño predictions. NFSV errors can be classified into two types: the first is characterized by a zonal dipolar pattern of SST anomalies (SSTA), with the western poles centered in the equatorial central-western Pacific exhibiting positive anomalies and the eastern poles in the equatorial eastern Pacific exhibiting negative anomalies; and the second is characterized by a pattern almost opposite the first type. The first type of error tends to have the worst effects on El Niño growth-phase predictions, whereas the latter often yields the largest negative effects on decaying-phase predictions. The evolution of prediction errors caused by NFSV-related errors exhibits prominent seasonality, with the fastest error growth in the spring and/or summer seasons; hence, these errors result in a significant SPB related to El Niño events. The linear counterpart of NFSVs, the (linear) forcing singular vector (FSV), induces a less significant SPB because it contains smaller prediction errors. Random errors cannot generate a SPB for El Niño events. These results show that the occurrence of an SPB is related to the spatial patterns of tendency errors. The NFSV tendency errors cause the most significant SPB for El Niño events. In addition, NFSVs often concentrate these large value errors in a few areas within the equatorial eastern and central-western Pacific, which likely represent those areas sensitive to El Niño predictions associated with model errors. Meanwhile, these areas are also exactly consistent with the sensitive areas related to initial errors determined by previous studies. This implies that additional observations in the sensitive areas would not only improve the accuracy of

Identification of sequence motifs significantly associated with antisense activity.

PubMed

McQuisten, Kyle A; Peek, Andrew S

2007-06-07

Predicting the suppression activity of antisense oligonucleotide sequences is the main goal of the rational design of nucleic acids. To create an effective predictive model, it is important to know what properties of an oligonucleotide sequence associate significantly with antisense activity. Also, for the model to be efficient we must know what properties do not associate significantly and can be omitted from the model. This paper will discuss the results of a randomization procedure to find motifs that associate significantly with either high or low antisense suppression activity, analysis of their properties, as well as the results of support vector machine modelling using these significant motifs as features. We discovered 155 motifs that associate significantly with high antisense suppression activity and 202 motifs that associate significantly with low suppression activity. The motifs range in length from 2 to 5 bases, contain several motifs that have been previously discovered as associating highly with antisense activity, and have thermodynamic properties consistent with previous work associating thermodynamic properties of sequences with their antisense activity. Statistical analysis revealed no correlation between a motif's position within an antisense sequence and that sequences antisense activity. Also, many significant motifs existed as subwords of other significant motifs. Support vector regression experiments indicated that the feature set of significant motifs increased correlation compared to all possible motifs as well as several subsets of the significant motifs. The thermodynamic properties of the significantly associated motifs support existing data correlating the thermodynamic properties of the antisense oligonucleotide with antisense efficiency, reinforcing our hypothesis that antisense suppression is strongly associated with probe/target thermodynamics, as there are no enzymatic mediators to speed the process along like the RNA Induced

Right hemisphere structures predict poststroke speech fluency.

PubMed

Pani, Ethan; Zheng, Xin; Wang, Jasmine; Norton, Andrea; Schlaug, Gottfried

2016-04-26

We sought to determine via a cross-sectional study the contribution of (1) the right hemisphere's speech-relevant white matter regions and (2) interhemispheric connectivity to speech fluency in the chronic phase of left hemisphere stroke with aphasia. Fractional anisotropy (FA) of white matter regions underlying the right middle temporal gyrus (MTG), precentral gyrus (PreCG), pars opercularis (IFGop) and triangularis (IFGtri) of the inferior frontal gyrus, and the corpus callosum (CC) was correlated with speech fluency measures. A region within the superior parietal lobule (SPL) was examined as a control. FA values of regions that significantly predicted speech measures were compared with FA values from healthy age- and sex-matched controls. FA values for the right MTG, PreCG, and IFGop significantly predicted speech fluency, but FA values of the IFGtri and SPL did not. A multiple regression showed that combining FA of the significant right hemisphere regions with the lesion load of the left arcuate fasciculus-a previously identified biomarker of poststroke speech fluency-provided the best model for predicting speech fluency. FA of CC fibers connecting left and right supplementary motor areas (SMA) was also correlated with speech fluency. FA of the right IFGop and PreCG was significantly higher in patients than controls, while FA of a whole CC region of interest (ROI) and the CC-SMA ROI was significantly lower in patients. Right hemisphere white matter integrity is related to speech fluency measures in patients with chronic aphasia. This may indicate premorbid anatomical variability beneficial for recovery or be the result of poststroke remodeling. © 2016 American Academy of Neurology.

Right hemisphere structures predict poststroke speech fluency

PubMed Central

Pani, Ethan; Zheng, Xin; Wang, Jasmine; Norton, Andrea

2016-01-01

Objective: We sought to determine via a cross-sectional study the contribution of (1) the right hemisphere's speech-relevant white matter regions and (2) interhemispheric connectivity to speech fluency in the chronic phase of left hemisphere stroke with aphasia. Methods: Fractional anisotropy (FA) of white matter regions underlying the right middle temporal gyrus (MTG), precentral gyrus (PreCG), pars opercularis (IFGop) and triangularis (IFGtri) of the inferior frontal gyrus, and the corpus callosum (CC) was correlated with speech fluency measures. A region within the superior parietal lobule (SPL) was examined as a control. FA values of regions that significantly predicted speech measures were compared with FA values from healthy age- and sex-matched controls. Results: FA values for the right MTG, PreCG, and IFGop significantly predicted speech fluency, but FA values of the IFGtri and SPL did not. A multiple regression showed that combining FA of the significant right hemisphere regions with the lesion load of the left arcuate fasciculus—a previously identified biomarker of poststroke speech fluency—provided the best model for predicting speech fluency. FA of CC fibers connecting left and right supplementary motor areas (SMA) was also correlated with speech fluency. FA of the right IFGop and PreCG was significantly higher in patients than controls, while FA of a whole CC region of interest (ROI) and the CC-SMA ROI was significantly lower in patients. Conclusions: Right hemisphere white matter integrity is related to speech fluency measures in patients with chronic aphasia. This may indicate premorbid anatomical variability beneficial for recovery or be the result of poststroke remodeling. PMID:27029627

Frame prediction using recurrent convolutional encoder with residual learning

NASA Astrophysics Data System (ADS)

Yue, Boxuan; Liang, Jun

2018-05-01

The prediction for the frame of a video is difficult but in urgent need in auto-driving. Conventional methods can only predict some abstract trends of the region of interest. The boom of deep learning makes the prediction for frames possible. In this paper, we propose a novel recurrent convolutional encoder and DE convolutional decoder structure to predict frames. We introduce the residual learning in the convolution encoder structure to solve the gradient issues. The residual learning can transform the gradient back propagation to an identity mapping. It can reserve the whole gradient information and overcome the gradient issues in Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN). Besides, compared with the branches in CNNs and the gated structures in RNNs, the residual learning can save the training time significantly. In the experiments, we use UCF101 dataset to train our networks, the predictions are compared with some state-of-the-art methods. The results show that our networks can predict frames fast and efficiently. Furthermore, our networks are used for the driving video to verify the practicability.

The influence of weather on migraine – are migraine attacks predictable?

PubMed Central

Hoffmann, Jan; Schirra, Tonio; Lo, Hendra; Neeb, Lars; Reuter, Uwe; Martus, Peter

2015-01-01

Objective The study aimed at elucidating a potential correlation between specific meteorological variables and the prevalence and intensity of migraine attacks as well as exploring a potential individual predictability of a migraine attack based on meteorological variables and their changes. Methods Attack prevalence and intensity of 100 migraineurs were correlated with atmospheric pressure, relative air humidity, and ambient temperature in 4-h intervals over 12 consecutive months. For each correlation, meteorological parameters at the time of the migraine attack as well as their variation within the preceding 24 h were analyzed. For migraineurs showing a positive correlation, logistic regression analysis was used to assess the predictability of a migraine attack based on meteorological information. Results In a subgroup of migraineurs, a significant weather sensitivity could be observed. In contrast, pooled analysis of all patients did not reveal a significant association. An individual prediction of a migraine attack based on meteorological data was not possible, mainly as a result of the small prevalence of attacks. Interpretation The results suggest that only a subgroup of migraineurs is sensitive to specific weather conditions. Our findings may provide an explanation as to why previous studies, which commonly rely on a pooled analysis, show inconclusive results. The lack of individual attack predictability indicates that the use of preventive measures based on meteorological conditions is not feasible. PMID:25642431

Prediction of FAD binding sites in electron transport proteins according to efficient radial basis function networks and significant amino acid pairs.

PubMed

Le, Nguyen-Quoc-Khanh; Ou, Yu-Yen

2016-07-30

Cellular respiration is a catabolic pathway for producing adenosine triphosphate (ATP) and is the most efficient process through which cells harvest energy from consumed food. When cells undergo cellular respiration, they require a pathway to keep and transfer electrons (i.e., the electron transport chain). Due to oxidation-reduction reactions, the electron transport chain produces a transmembrane proton electrochemical gradient. In case protons flow back through this membrane, this mechanical energy is converted into chemical energy by ATP synthase. The convert process is involved in producing ATP which provides energy in a lot of cellular processes. In the electron transport chain process, flavin adenine dinucleotide (FAD) is one of the most vital molecules for carrying and transferring electrons. Therefore, predicting FAD binding sites in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. We used an independent data set to evaluate the performance of the proposed method, which had an accuracy of 69.84 %. We compared the performance of the proposed method in analyzing two newly discovered electron transport protein sequences with that of the general FAD binding predictor presented by Mishra and Raghava and determined that the accuracy of the proposed method improved by 9-45 % and its Matthew's correlation coefficient was 0.14-0.5. Furthermore, the proposed method enabled reducing the number of false positives significantly and can provide useful information for biologists. We developed a method that is based on PSSM profiles and SAAPs for identifying FAD binding sites in newly discovered electron transport protein sequences. This approach achieved a significant improvement after we added SAAPs to PSSM features to analyze FAD binding proteins in the electron transport chain. The proposed method can serve as an effective tool for predicting FAD binding sites in electron

Predictability of the 2012 Great Arctic Cyclone on medium-range timescales

NASA Astrophysics Data System (ADS)

Yamagami, Akio; Matsueda, Mio; Tanaka, Hiroshi L.

2018-03-01

Arctic Cyclones (ACs) can have a significant impact on the Arctic region. Therefore, the accurate prediction of ACs is important in anticipating their associated environmental and societal costs. This study investigates the predictability of the 2012 Great Arctic Cyclone (AC12) that exhibited a minimum central pressure of 964 hPa on 6 August 2012, using five medium-range ensemble forecasts. We show that the development and position of AC12 were better predicted in forecasts initialized on and after 4 August 2012. In addition, the position of AC12 was more predictable than its development. A comparison of ensemble members, classified by the error in predictability of the development and position of AC12, revealed that an accurate prediction of upper-level fields, particularly temperature, was important for the prediction of this event. The predicted position of AC12 was influenced mainly by the prediction of the polar vortex, whereas the predicted development of AC12 was dependent primarily on the prediction of the merging of upper-level warm cores. Consequently, an accurate prediction of the polar vortex position and the development of the warm core through merging resulted in better prediction of AC12.

Predicting dual-task performance with the Multiple Resources Questionnaire (MRQ).

PubMed

Boles, David B; Bursk, Jonathan H; Phillips, Jeffrey B; Perdelwitz, Jason R

2007-02-01

The objective was to assess the validity of the Multiple Resources Questionnaire (MRQ) in predicting dual-task interference. Subjective workload measures such as the Subjective Workload Assessment Technique (SWAT) and NASA Task Load Index are sensitive to single-task parameters and dual-task loads but have not attempted to measure workload in particular mental processes. An alternative is the MRQ. In Experiment 1, participants completed simple laboratory tasks and the MRQ after each. Interference between tasks was then correlated to three different task similarity metrics: profile similarity, based on r(2) between ratings; overlap similarity, based on summed minima; and overall demand, based on summed ratings. Experiment 2 used similar methods but more complex computer-based games. In Experiment 1 the MRQ moderately predicted interference (r = +.37), with no significant difference between metrics. In Experiment 2 the metric effect was significant, with overlap similarity excelling in predicting interference (r = +.83). Mean ratings showed high diagnosticity in identifying specific mental processing bottlenecks. The MRQ shows considerable promise as a cognitive-process-sensitive workload measure. Potential applications of the MRQ include the identification of dual-processing bottlenecks as well as process overloads in single tasks, preparatory to redesign in areas such as air traffic management, advanced flight displays, and medical imaging.

Efficient differentially private learning improves drug sensitivity prediction.

PubMed

Honkela, Antti; Das, Mrinal; Nieminen, Arttu; Dikmen, Onur; Kaski, Samuel

2018-02-06

Users of a personalised recommendation system face a dilemma: recommendations can be improved by learning from data, but only if other users are willing to share their private information. Good personalised predictions are vitally important in precision medicine, but genomic information on which the predictions are based is also particularly sensitive, as it directly identifies the patients and hence cannot easily be anonymised. Differential privacy has emerged as a potentially promising solution: privacy is considered sufficient if presence of individual patients cannot be distinguished. However, differentially private learning with current methods does not improve predictions with feasible data sizes and dimensionalities. We show that useful predictors can be learned under powerful differential privacy guarantees, and even from moderately-sized data sets, by demonstrating significant improvements in the accuracy of private drug sensitivity prediction with a new robust private regression method. Our method matches the predictive accuracy of the state-of-the-art non-private lasso regression using only 4x more samples under relatively strong differential privacy guarantees. Good performance with limited data is achieved by limiting the sharing of private information by decreasing the dimensionality and by projecting outliers to fit tighter bounds, therefore needing to add less noise for equal privacy. The proposed differentially private regression method combines theoretical appeal and asymptotic efficiency with good prediction accuracy even with moderate-sized data. As already the simple-to-implement method shows promise on the challenging genomic data, we anticipate rapid progress towards practical applications in many fields. This article was reviewed by Zoltan Gaspari and David Kreil.

Accurate Binding Free Energy Predictions in Fragment Optimization.

PubMed

Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody

2015-11-23

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

Creating Significant Learning Experiences across Disciplines

ERIC Educational Resources Information Center

Levine, Laura E.; Fallahi, Carolyn R.; Nicoll-Senft, Joan M.; Tessier, Jack T.; Watson, Cheryl L.; Wood, Rebecca M.

2008-01-01

The purpose of this study was to use Fink's (2003) taxonomy of significant learning to redesign courses and assess student learning. Significant improvements were found across the semester for students in the six courses, but there were differences in which taxa showed improvement in each course. The meta-analysis showed significant, positive…

Randomised control trial showed that delayed cord clamping and milking resulted in no significant differences in iron stores and physical growth parameters at one year of age.

PubMed

Agarwal, Shivam; Jaiswal, Vijay; Singh, Dharamveer; Jaiswal, Prateek; Garg, Amit; Upadhyay, Amit

2016-11-01

Placental redistribution has been shown to improve haematological outcomes in the immediate neonatal period and early infancy. This study compared the effects of delayed cord clamping (DCC) and umbilical cord milking (UCM) on haematological and growth parameters at 12 months of age. This was a follow-up study of a randomised control trial, conducted in a tertiary care paediatric centre from August 2013 to August 2014. We studied 200 apparently healthy Indian infants randomised at birth to receive DCC for 60-90 seconds or UCM. The outcome measures were iron status and physical growth parameters at 12 months. Of the 200 babies, 161 completed the follow-up and baseline characteristics were comparable in both groups. The mean haemoglobin in the DCC group (102.2 (17.2) g/L and serum ferritin 16.44 (2.77) μg/L) showed no significant differences to the UCM group (98.6 (17.1) g/L and 18.2 (2.8) μg/L) at one year. In addition, there were no significant differences in weight, height and mid-upper arm circumference in the two groups. Term-born Indian infants who had DCC at 60-90 seconds or UCM showed no significant differences in ferritin and haemoglobin levels and growth parameters at 12 months of age. ©2016 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Prediction of resource volumes at untested locations using simple local prediction models

USGS Publications Warehouse

Attanasi, E.D.; Coburn, T.C.; Freeman, P.A.

2006-01-01

This paper shows how local spatial nonparametric prediction models can be applied to estimate volumes of recoverable gas resources at individual undrilled sites, at multiple sites on a regional scale, and to compute confidence bounds for regional volumes based on the distribution of those estimates. An approach that combines cross-validation, the jackknife, and bootstrap procedures is used to accomplish this task. Simulation experiments show that cross-validation can be applied beneficially to select an appropriate prediction model. The cross-validation procedure worked well for a wide range of different states of nature and levels of information. Jackknife procedures are used to compute individual prediction estimation errors at undrilled locations. The jackknife replicates also are used with a bootstrap resampling procedure to compute confidence bounds for the total volume. The method was applied to data (partitioned into a training set and target set) from the Devonian Antrim Shale continuous-type gas play in the Michigan Basin in Otsego County, Michigan. The analysis showed that the model estimate of total recoverable volumes at prediction sites is within 4 percent of the total observed volume. The model predictions also provide frequency distributions of the cell volumes at the production unit scale. Such distributions are the basis for subsequent economic analyses. ?? Springer Science+Business Media, LLC 2007.

The presence, predictive utility, and clinical significance of body dysmorphic symptoms in women with eating disorders

PubMed Central

2013-01-01

Background Both eating disorders (EDs) and body dysmorphic disorder (BDD) are disorders of body image. This study aimed to assess the presence, predictive utility, and impact of clinical features commonly associated with BDD in women with EDs. Methods Participants recruited from two non-clinical cohorts of women, symptomatic and asymptomatic of EDs, completed a survey on ED (EDE-Q) and BDD (BDDE-SR) psychopathology, psychological distress (K-10), and quality of life (SF-12). Results A strong correlation was observed between the total BDDE-SR and the global EDE-Q scores (r = 0.79, p < 0.001). Multivariate analyses demonstrated that participants with probable EDs (n = 61) and BDD (n = 23) scored higher on 28 of the 30 BDDE-SR items compared to healthy controls (n = 173; all p < 0.05), indicating greater severity of BDD symptoms. BDD participants also scored higher than ED participants on 15 of the 30 BDDE-SR items (all p < 0.05). The remaining 15 items that ED and BDD participants scored similarly on (all p > 0.05) measured appearance checking, reassurance-seeking, camouflaging, comparison-making, and social avoidance. In addition to these behaviors, inspection of sensitivity (Se) and specificity (Sp) revealed that BDDE-SR items measuring preoccupation and dissatisfaction with appearance were most predictive of ED cases (Se and Sp > 0.60). Higher total BDDE-SR scores were associated with greater distress on the K-10 and poorer quality of life on the SF-12 (all p < 0.01). Conclusions Clinical features central to the model of BDD are common in, predictive of, and associated with impairment in women with EDs. Practice implications are that these features be included in the assessment and treatment of EDs. PMID:24999401

The Predictive Validity of Savry Ratings for Assessing Youth Offenders in Singapore

PubMed Central

Chu, Chi Meng; Goh, Mui Leng; Chong, Dominic

2015-01-01

Empirical support for the usage of the SAVRY has been reported in studies conducted in many Western contexts, but not in a Singaporean context. This study compared the predictive validity of the SAVRY ratings for violent and general recidivism against the Youth Level of Service/Case Management Inventory (YLS/CMI) ratings within the Singaporean context. Using a sample of 165 male young offenders (Mfollow-up = 4.54 years), results showed that the SAVRY Total Score and Summary Risk Rating, as well as YLS/CMI Total Score and Overall Risk Rating, predicted violent and general recidivism. SAVRY Protective Total Score was only significantly predictive of desistance from general recidivism, and did not show incremental predictive validity for violent and general recidivism over the SAVRY Total Score. Overall, the results suggest that the SAVRY is suited (to varying degrees) for assessing the risk of violent and general recidivism in young offenders within the Singaporean context, but might not be better than the YLS/CMI. PMID:27231403

Combining Structural Modeling with Ensemble Machine Learning to Accurately Predict Protein Fold Stability and Binding Affinity Effects upon Mutation

PubMed Central

Garcia Lopez, Sebastian; Kim, Philip M.

2014-01-01

Advances in sequencing have led to a rapid accumulation of mutations, some of which are associated with diseases. However, to draw mechanistic conclusions, a biochemical understanding of these mutations is necessary. For coding mutations, accurate prediction of significant changes in either the stability of proteins or their affinity to their binding partners is required. Traditional methods have used semi-empirical force fields, while newer methods employ machine learning of sequence and structural features. Here, we show how combining both of these approaches leads to a marked boost in accuracy. We introduce ELASPIC, a novel ensemble machine learning approach that is able to predict stability effects upon mutation in both, domain cores and domain-domain interfaces. We combine semi-empirical energy terms, sequence conservation, and a wide variety of molecular details with a Stochastic Gradient Boosting of Decision Trees (SGB-DT) algorithm. The accuracy of our predictions surpasses existing methods by a considerable margin, achieving correlation coefficients of 0.77 for stability, and 0.75 for affinity predictions. Notably, we integrated homology modeling to enable proteome-wide prediction and show that accurate prediction on modeled structures is possible. Lastly, ELASPIC showed significant differences between various types of disease-associated mutations, as well as between disease and common neutral mutations. Unlike pure sequence-based prediction methods that try to predict phenotypic effects of mutations, our predictions unravel the molecular details governing the protein instability, and help us better understand the molecular causes of diseases. PMID:25243403

Predicting MHC-II binding affinity using multiple instance regression

PubMed Central

EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2011-01-01

Reliably predicting the ability of antigen peptides to bind to major histocompatibility complex class II (MHC-II) molecules is an essential step in developing new vaccines. Uncovering the amino acid sequence correlates of the binding affinity of MHC-II binding peptides is important for understanding pathogenesis and immune response. The task of predicting MHC-II binding peptides is complicated by the significant variability in their length. Most existing computational methods for predicting MHC-II binding peptides focus on identifying a nine amino acids core region in each binding peptide. We formulate the problems of qualitatively and quantitatively predicting flexible length MHC-II peptides as multiple instance learning and multiple instance regression problems, respectively. Based on this formulation, we introduce MHCMIR, a novel method for predicting MHC-II binding affinity using multiple instance regression. We present results of experiments using several benchmark datasets that show that MHCMIR is competitive with the state-of-the-art methods for predicting MHC-II binding peptides. An online web server that implements the MHCMIR method for MHC-II binding affinity prediction is freely accessible at http://ailab.cs.iastate.edu/mhcmir. PMID:20855923

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.

Postprocessing for Air Quality Predictions

NASA Astrophysics Data System (ADS)

Delle Monache, L.

2017-12-01

In recent year, air quality (AQ) forecasting has made significant progress towards better predictions with the goal of protecting the public from harmful pollutants. This progress is the results of improvements in weather and chemical transport models, their coupling, and more accurate emission inventories (e.g., with the development of new algorithms to account in near real-time for fires). Nevertheless, AQ predictions are still affected at times by significant biases which stem from limitations in both weather and chemistry transport models. Those are the result of numerical approximations and the poor representation (and understanding) of important physical and chemical process. Moreover, although the quality of emission inventories has been significantly improved, they are still one of the main sources of uncertainties in AQ predictions. For operational real-time AQ forecasting, a significant portion of these biases can be reduced with the implementation of postprocessing methods. We will review some of the techniques that have been proposed to reduce both systematic and random errors of AQ predictions, and improve the correlation between predictions and observations of ground-level ozone and surface particulate matter less than 2.5 µm in diameter (PM2.5). These methods, which can be applied to both deterministic and probabilistic predictions, include simple bias-correction techniques, corrections inspired by the Kalman filter, regression methods, and the more recently developed analog-based algorithms. These approaches will be compared and contrasted, and strength and weaknesses of each will be discussed.

Neural Correlates of Semantic Prediction and Resolution in Sentence Processing.

PubMed

Grisoni, Luigi; Miller, Tally McCormick; Pulvermüller, Friedemann

2017-05-03

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system-in dorsolateral hand motor areas for expected hand-related words (e.g., "write"), but in ventral motor cortex for face-related words ("talk"). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding. SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before they

Neural Correlates of Semantic Prediction and Resolution in Sentence Processing

PubMed Central

2017-01-01

Most brain-imaging studies of language comprehension focus on activity following meaningful stimuli. Testing adult human participants with high-density EEG, we show that, already before the presentation of a critical word, context-induced semantic predictions are reflected by a neurophysiological index, which we therefore call the semantic readiness potential (SRP). The SRP precedes critical words if a previous sentence context constrains the upcoming semantic content (high-constraint contexts), but not in unpredictable (low-constraint) contexts. Specific semantic predictions were indexed by SRP sources within the motor system—in dorsolateral hand motor areas for expected hand-related words (e.g., “write”), but in ventral motor cortex for face-related words (“talk”). Compared with affirmative sentences, negated ones led to medial prefrontal and more widespread motor source activation, the latter being consistent with predictive semantic computation of alternatives to the negated expected concept. Predictive processing of semantic alternatives in negated sentences is further supported by a negative-going event-related potential at ∼400 ms (N400), which showed the typical enhancement to semantically incongruent sentence endings only in high-constraint affirmative contexts, but not to high-constraint negated ones. These brain dynamics reveal the interplay between semantic prediction and resolution (match vs error) processing in sentence understanding. SIGNIFICANCE STATEMENT Most neuroscientists agree on the eminent importance of predictive mechanisms for understanding basic as well as higher brain functions. This contrasts with a sparseness of brain measures that directly reflects specific aspects of prediction, as they are relevant in the processing of language and thought. Here we show that when critical words are strongly expected in their sentence context, a predictive brain response reflects meaning features of these anticipated symbols already before

[Quantitative Prediction of Drug-Drug Interaction Caused by CYP Inhibition and Induction from In Vivo Data and Its Application in Daily Clinical Practices-Proposal for the Pharmacokinetic Interaction Significance Classification System (PISCS)].

PubMed

Ohno, Yoshiyuki

2018-01-01

　Drug-drug interactions (DDIs) can affect the clearance of various drugs from the body; however, these effects are difficult to sufficiently evaluate in clinical studies. This article outlines our approach to improving methods for evaluating and providing drug information relative to the effects of DDIs. In a previous study, total exposure changes to many substrate drugs of CYP caused by the co-administration of inhibitor or inducer drugs were successfully predicted using in vivo data. There are two parameters for the prediction: the contribution ratio of the enzyme to oral clearance for substrates (CR), and either the inhibition ratio for inhibitors (IR) or the increase in clearance of substrates produced by induction (IC). To apply these predictions in daily pharmacotherapy, the clinical significance of any pharmacokinetic changes must be carefully evaluated. We constructed a pharmacokinetic interaction significance classification system (PISCS) in which the clinical significance of DDIs was considered in a systematic manner, according to pharmacokinetic changes. The PISCS suggests that many current 'alert' classifications are potentially inappropriate, especially for drug combinations in which pharmacokinetics have not yet been evaluated. It is expected that PISCS would contribute to constructing a reliable system to alert pharmacists, physicians and consumers of a broad range of pharmacokinetic DDIs in order to more safely manage daily clinical practices.

Value of supervised learning events in predicting doctors in difficulty.

PubMed

Patel, Mumtaz; Agius, Steven; Wilkinson, Jack; Patel, Leena; Baker, Paul

2016-07-01

In the UK, supervised learning events (SLE) replaced traditional workplace-based assessments for foundation-year trainees in 2012. A key element of SLEs was to incorporate trainee reflection and assessor feedback in order to drive learning and identify training issues early. Few studies, however, have investigated the value of SLEs in predicting doctors in difficulty. This study aimed to identify principles that would inform understanding about how and why SLEs work or not in identifying doctors in difficulty (DiD). A retrospective case-control study of North West Foundation School trainees' electronic portfolios was conducted. Cases comprised all known DiD. Controls were randomly selected from the same cohort. Free-text supervisor comments from each SLE were assessed for the four domains defined in the General Medical Council's Good Medical Practice Guidelines and each scored blindly for level of concern using a three-point ordinal scale. Cumulative scores for each SLE were then analysed quantitatively for their predictive value of actual DiD. A qualitative thematic analysis was also conducted. The prevalence of DiD in this sample was 6.5%. Receiver operator characteristic curve analysis showed that Team Assessment of Behaviour (TAB) was the only SLE strongly predictive of actual DiD status. The Educational Supervisor Report (ESR) was also strongly predictive of DiD status. Fisher's test showed significant associations of TAB and ESR for both predicted and actual DiD status and also the health and performance subtypes. None of the other SLEs showed significant associations. Qualitative data analysis revealed inadequate completion and lack of constructive, particularly negative, feedback. This indicated that SLEs were not used to their full potential. TAB and the ESR are strongly predictive of DiD. However, SLEs are not being used to their full potential, and the quality of completion of reports on SLEs and feedback needs to be improved in order to better identify

Noninvasive scoring system for significant inflammation related to chronic hepatitis B

NASA Astrophysics Data System (ADS)

Hong, Mei-Zhu; Ye, Linglong; Jin, Li-Xin; Ren, Yan-Dan; Yu, Xiao-Fang; Liu, Xiao-Bin; Zhang, Ru-Mian; Fang, Kuangnan; Pan, Jin-Shui

2017-03-01

Although a liver stiffness measurement-based model can precisely predict significant intrahepatic inflammation, transient elastography is not commonly available in a primary care center. Additionally, high body mass index and bilirubinemia have notable effects on the accuracy of transient elastography. The present study aimed to create a noninvasive scoring system for the prediction of intrahepatic inflammatory activity related to chronic hepatitis B, without the aid of transient elastography. A total of 396 patients with chronic hepatitis B were enrolled in the present study. Liver biopsies were performed, liver histology was scored using the Scheuer scoring system, and serum markers and liver function were investigated. Inflammatory activity scoring models were constructed for both hepatitis B envelope antigen (+) and hepatitis B envelope antigen (-) patients. The sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve were 86.00%, 84.80%, 62.32%, 95.39%, and 0.9219, respectively, in the hepatitis B envelope antigen (+) group and 91.89%, 89.86%, 70.83%, 97.64%, and 0.9691, respectively, in the hepatitis B envelope antigen (-) group. Significant inflammation related to chronic hepatitis B can be predicted with satisfactory accuracy by using our logistic regression-based scoring system.

Predicting Sargassum blooms in the Caribbean Sea from MODIS observations

NASA Astrophysics Data System (ADS)

Wang, Mengqiu; Hu, Chuanmin

2017-04-01

Recurrent and significant Sargassum beaching events in the Caribbean Sea (CS) have caused serious environmental and economic problems, calling for a long-term prediction capacity of Sargassum blooms. Here we present predictions based on a hindcast of 2000-2016 observations from Moderate Resolution Imaging Spectroradiometer (MODIS), which showed Sargassum abundance in the CS and the Central West Atlantic (CWA), as well as connectivity between the two regions with time lags. This information was used to derive bloom and nonbloom probability matrices for each 1° square in the CS for the months of May-August, predicted from bloom conditions in a hotspot region in the CWA in February. A suite of standard statistical measures were used to gauge the prediction accuracy, among which the user's accuracy and kappa statistics showed high fidelity of the probability maps in predicting both blooms and nonblooms in the eastern CS with several months of lead time, with overall accuracy often exceeding 80%. The bloom probability maps from this hindcast analysis will provide early warnings to better study Sargassum blooms and prepare for beaching events near the study region. This approach may also be extendable to many other regions around the world that face similar challenges and opportunities of macroalgal blooms and beaching events.

Nuclear Cataract Shows Significant Familial Aggregation in an Older Population after Adjustment for Possible Shared Environmental Factors

PubMed Central

Congdon, Nathan; Broman, Karl W.; Lai, Hong; Munoz, Beatriz; Bowie, Heidi; Gilber, Donna; Wojciechowski, Robert; Alston, Christine; West, Sheila K.

2011-01-01

Purpose To quantify the association between siblings in age-related nuclear cataract, after adjusting for known environmental and personal risk factors. Methods All participants (probands) in the Salisbury Eye Evaluation (SEE) project and their locally resident siblings underwent digital slit lamp photography and were administered a questionnaire to assess risk factors for cataract including: age, gender, lifetime sun exposure, smoking and diabetes history, and use of alcohol and medications such as estrogens and steroids. In addition, blood pressure, body mass index, and serum antioxidants were measured in all participants. Lens photographs were graded by trained observers masked to the subjects' identity, using the Wilmer Cataract Grading System. The odds ratio for siblings for affectedness with nuclear cataract and the sibling correlation of nuclear cataract grade, after adjusting for covariates, were estimated with generalized estimating equations. Results Among 307 probands (mean age, 77.6 ± 4.5 years) and 434 full siblings (mean age, 72.4 ± 7.4 years), the average sibship size was 2.7 per family. After adjustment for covariates, the probability of development of nuclear cataract was significantly increased (odds ratio [OR] = 2.07, 95% confidence interval [CI], 1.30–3.30) among individuals with a sibling with nuclear cataract (nuclear grade ≥ 3.0). The final fitted model indicated a magnitude of heritability for nuclear cataract of 35.6% (95% CI: 21.0%–50.3%) after adjustment for the covariates. Conclusions Findings in this study are consistent with a genetic effect for age-related nuclear cataract, a common and clinically significant form of lens opacity. PMID:15223793

Suppression of p53-inducible gene 3 is significant for glioblastoma progression and predicts poor patient prognosis.

PubMed

Quan, Jishu; Li, Yong; Jin, Meihua; Chen, Dunfu; Yin, Xuezhe; Jin, Ming

2017-03-01

Glioblastoma is the most malignant and invasive brain tumor with extremely poor prognosis. p53-inducible gene 3, a downstream molecule of the tumor suppressor p53, has been found involved in apoptosis and oxidative stress response. However, the functions of p53-inducible gene 3(PIG3) in cancer are far from clear including glioblastoma. In this study, we found that p53-inducible gene 3 expression was suppressed in glioblastoma tissues compared with normal tissues. And the expression of p53-inducible gene 3 was significantly associated with the World Health Organization grade. Patients with high p53-inducible gene 3 expression have a significantly longer median survival time (15 months) than those with low p53-inducible gene 3 expression (8 months). According to Cox regression analysis, p53-inducible gene 3 was an independent prognostic factor with multivariate hazard ratio of 0.578 (95% confidence interval, 0.352-0.947; p = 0.030) for overall survival. Additionally, gain and loss of function experiments showed that knockdown of p53-inducible gene 3 significantly increased the proliferation and invasion ability of glioblastoma cells while overexpression of p53-inducible gene 3 inhibited the proliferation and invasion ability. The results of in vivo glioblastoma models further confirmed that p53-inducible gene 3 suppression promoted glioblastoma progression. Altogether, our data suggest that high expression of p53-inducible gene 3 is significant for glioblastoma inhibition and p53-inducible gene 3 independently indicates good prognosis in patients, which might be a novel prognostic biomarker or potential therapeutic target in glioblastoma.

Outcomes in Women With Cytology Showing Atypical Squamous Cells of Undetermined Significance With vs Without Human Papillomavirus Testing.

PubMed

Cuzick, Jack; Myers, Orrin; Lee, Ji-Hyun; Shi, Yang; Gage, Julia C; Hunt, William C; Robertson, Michael; Wheeler, Cosette M

2017-10-01

Little is known about the long-term yield of high-grade cervical intraepithelial neoplasia (CIN) and the influence on biopsy and treatment rates of human papillomavirus (HPV) triage of cytology showing atypical squamous cells of undetermined significance (hereafter ASC-US cytology). To examine 5-year outcomes after ASC-US cytology with vs without HPV testing. In this observational study, all cervical cytology and HPV testing reports from January 1, 2007, to December 31, 2012, were obtained for women throughout New Mexico and linked to pathology reports. The dates of the analysis were May 4, 2015, to January 13, 2017. Influence of HPV testing on disease yield, time to histologically confirmed disease, and biopsy or loop electrosurgical excision procedure rates. A total of 457 317 women (mean [SD] age, 39.8 [12.5] years) with a screening test were recorded between 2008 and 2012, and 20 677 (4.5%) of the first cytology results per woman were reported as ASC-US. CIN grade 3 or more severe (CIN3+) lesions were detected in 2.49% of women with HPV testing vs 2.15% of women without HPV testing (P = .23). Time to CIN3+ detection was much shorter in those with HPV testing vs those without testing (median, 103 vs 393 days; P < .001). CIN grade 1 was detected in 11.6% of women with HPV testing vs 6.6% without testing (relative risk, 1.76; 95% CI, 1.56-2.00; P < .001). Loop electrosurgical excision procedure rates within 5 years were 20.0% higher in those who underwent HPV testing, resulting in more CIN2+ and CIN3+ detection. Human papillomavirus testing led to faster and more complete diagnosis of cervical disease, but 55.8% more biopsies and 20.0% more loop electrosurgical excision procedures were performed. In those tested, virtually all high-grade disease occurred in the 43.1% of women who were HPV positive, allowing clinical resources to be focused on women who need them most. These data provide essential information for cervical screening guidelines and

Outcomes in Women With Cytology Showing Atypical Squamous Cells of Undetermined Significance With vs Without Human Papillomavirus Testing

PubMed Central

Cuzick, Jack; Myers, Orrin; Lee, Ji-Hyun; Shi, Yang; Gage, Julia C.; Hunt, William C.; Robertson, Michael

2017-01-01

Importance Little is known about the long-term yield of high-grade cervical intraepithelial neoplasia (CIN) and the influence on biopsy and treatment rates of human papillomavirus (HPV) triage of cytology showing atypical squamous cells of undetermined significance (hereafter ASC-US cytology). Objective To examine 5-year outcomes after ASC-US cytology with vs without HPV testing. Design, Setting, and Participants In this observational study, all cervical cytology and HPV testing reports from January 1, 2007, to December 31, 2012, were obtained for women throughout New Mexico and linked to pathology reports. The dates of the analysis were May 4, 2015, to January 13, 2017. Main Outcomes and Measures Influence of HPV testing on disease yield, time to histologically confirmed disease, and biopsy or loop electrosurgical excision procedure rates. Results A total of 457 317 women (mean [SD] age, 39.8 [12.5] years) with a screening test were recorded between 2008 and 2012, and 20 677 (4.5%) of the first cytology results per woman were reported as ASC-US. CIN grade 3 or more severe (CIN3+) lesions were detected in 2.49% of women with HPV testing vs 2.15% of women without HPV testing (P = .23). Time to CIN3+ detection was much shorter in those with HPV testing vs those without testing (median, 103 vs 393 days; P < .001). CIN grade 1 was detected in 11.6% of women with HPV testing vs 6.6% without testing (relative risk, 1.76; 95% CI, 1.56-2.00; P < .001). Loop electrosurgical excision procedure rates within 5 years were 20.0% higher in those who underwent HPV testing, resulting in more CIN2+ and CIN3+ detection. Conclusions and Relevance Human papillomavirus testing led to faster and more complete diagnosis of cervical disease, but 55.8% more biopsies and 20.0% more loop electrosurgical excision procedures were performed. In those tested, virtually all high-grade disease occurred in the 43.1% of women who were HPV positive, allowing clinical resources to be

PPCM: Combing multiple classifiers to improve protein-protein interaction prediction

DOE PAGES

Yao, Jianzhuang; Guo, Hong; Yang, Xiaohan

2015-08-01

Determining protein-protein interaction (PPI) in biological systems is of considerable importance, and prediction of PPI has become a popular research area. Although different classifiers have been developed for PPI prediction, no single classifier seems to be able to predict PPI with high confidence. We postulated that by combining individual classifiers the accuracy of PPI prediction could be improved. We developed a method called protein-protein interaction prediction classifiers merger (PPCM), and this method combines output from two PPI prediction tools, GO2PPI and Phyloprof, using Random Forests algorithm. The performance of PPCM was tested by area under the curve (AUC) using anmore » assembled Gold Standard database that contains both positive and negative PPI pairs. Our AUC test showed that PPCM significantly improved the PPI prediction accuracy over the corresponding individual classifiers. We found that additional classifiers incorporated into PPCM could lead to further improvement in the PPI prediction accuracy. Furthermore, cross species PPCM could achieve competitive and even better prediction accuracy compared to the single species PPCM. This study established a robust pipeline for PPI prediction by integrating multiple classifiers using Random Forests algorithm. Ultimately, this pipeline will be useful for predicting PPI in nonmodel species.« less

Evaluation of MEGAN predicted biogenic isoprene emissions at urban locations in Southeast Texas

NASA Astrophysics Data System (ADS)

Kota, Sri Harsha; Schade, Gunnar; Estes, Mark; Boyer, Doug; Ying, Qi

2015-06-01

Summertime isoprene emissions in the Houston area predicted by the Model of Emissions of Gases and Aerosol from Nature (MEGAN) version 2.1 during the 2006 TexAQS study were evaluated using a source-oriented Community Multiscale Air Quality (CMAQ) Model. Predicted daytime isoprene concentrations at nine surface sites operated by the Texas Commission of Environmental Quality (TCEQ) were significantly higher than local observations when biogenic emissions dominate the total isoprene concentrations, with mean normalized bias (MNB) ranges from 2.0 to 7.7 and mean normalized error (MNE) ranges from 2.2 to 7.7. Predicted upper air isoprene and its first generation oxidation products of methacrolein (MACR) and methyl vinyl ketone (MVK) were also significantly higher (MNB = 8.6, MNE = 9.1) than observations made onboard of NOAA's WP-3 airplane, which flew over the urban area. Over-prediction of isoprene and its oxidation products both at the surface and the upper air strongly suggests that biogenic isoprene emissions in the Houston area are significantly overestimated. Reducing the emission rates by approximately 3/4 was necessary to reduce the error between predictions and observations. Comparison of gridded leaf area index (LAI), plant functional type (PFT) and gridded isoprene emission factor (EF) used in MEGAN modeling with estimates of the same factors from a field survey north of downtown Houston showed that the isoprene over-prediction is likely caused by the combined effects of a large overestimation of the gridded EF in urban Houston and an underestimation of urban LAI. Nevertheless, predicted ozone concentrations in this region were not significantly affected by the isoprene over-predictions, while predicted isoprene SOA and total SOA concentrations can be higher by as much as 50% and 13% using the higher isoprene emission rates, respectively.

Meta-path based heterogeneous combat network link prediction

NASA Astrophysics Data System (ADS)

Li, Jichao; Ge, Bingfeng; Yang, Kewei; Chen, Yingwu; Tan, Yuejin

2017-09-01

The combat system-of-systems in high-tech informative warfare, composed of many interconnected combat systems of different types, can be regarded as a type of complex heterogeneous network. Link prediction for heterogeneous combat networks (HCNs) is of significant military value, as it facilitates reconfiguring combat networks to represent the complex real-world network topology as appropriate with observed information. This paper proposes a novel integrated methodology framework called HCNMP (HCN link prediction based on meta-path) to predict multiple types of links simultaneously for an HCN. More specifically, the concept of HCN meta-paths is introduced, through which the HCNMP can accumulate information by extracting different features of HCN links for all the six defined types. Next, an HCN link prediction model, based on meta-path features, is built to predict all types of links of the HCN simultaneously. Then, the solution algorithm for the HCN link prediction model is proposed, in which the prediction results are obtained by iteratively updating with the newly predicted results until the results in the HCN converge or reach a certain maximum iteration number. Finally, numerical experiments on the dataset of a real HCN are conducted to demonstrate the feasibility and effectiveness of the proposed HCNMP, in comparison with 30 baseline methods. The results show that the performance of the HCNMP is superior to those of the baseline methods.

Significance of peak height velocity as a predictive factor for curve progression in patients with idiopathic scoliosis

PubMed Central

2015-01-01

progression in patients with IS. Conclusions These findings indicate that 31.5 degrees of spinal curvature when patients are at PHV is a significant predictive indicator for progression of the curve to a magnitude requiring surgery. We suggest that the curve-progression risk assessment in patients with IS should include PHV, along with measures of skeletal and non-skeletal maturities. PMID:25815057

The significance of blue color in dermatoscopy.

PubMed

Popadić, Mirjana; Sinz, Christoph; Kittler, Harald

2017-03-01

Skin lesions with blue color are frequently excised to rule out malignancy. The objective of the present study was to investigate the significance of blue color. We retrospectively scanned dermatoscopic images for blue color and classified them according to pattern analysis. Of 1,123 pigmented skin lesions, 144 (12.8 %) showed blue color, 92 of which (63.9 %) were malignant. Among lesions with blue color, the most common benign diagnoses were nevi (n = 35, 24.3 %) and seborrheic keratoses (n = 8, 5.6 %). Of 103 (71.5 %) lesions with a structureless blue pattern, eight (7.8 %) were entirely blue and 95 (92.2 %) were partly blue, of which 81 (78.6 %) showed peripheral or patchy and 14 (13.6 %) central blue color. Most lesions with peripheral or patchy blue color were melanomas (n = 47, 58 %), whereas most lesions with central blue color were nevi (n = 9, 64.3 %). Of 28 lesions with blue clods, 17 (60.7 %) were basal cell carcinomas. With respect to malignancy, the positive predictive value of blue color was 63.9 % (95 % CI: 56.0-71.8 %). Among malignant lesions with blue color, structureless peripheral or patchy blue color is a clue for melanoma, while blue clods point to basal cell carcinoma. Pitfalls include seborrheic keratoses, which may show blue color, as well as some nevi, especially combined nevi. © 2017 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.

Prediction of psychological functioning one year after the predictive test for Huntington's disease and impact of the test result on reproductive decision making.

PubMed Central

Decruyenaere, M; Evers-Kiebooms, G; Boogaerts, A; Cassiman, J J; Cloostermans, T; Demyttenaere, K; Dom, R; Fryns, J P; Van den Berghe, H

1996-01-01

For people at risk for Huntington's disease, the anxiety and uncertainty about the future may be very burdensome and may be an obstacle to personal decision making about important life issues, for example, procreation. For some at risk persons, this situation is the reason for requesting predictive DNA testing. The aim of this paper is two-fold. First, we want to evaluate whether knowing one's carrier status reduces anxiety and uncertainty and whether it facilitates decision making about procreation. Second, we endeavour to identify pretest predictors of psychological adaptation one year after the predictive test (psychometric evaluation of general anxiety, depression level, and ego strength). The impact of the predictive test result was assessed in 53 subjects tested, using pre- and post-test psychometric measurement and self-report data of follow up interviews. Mean anxiety and depression levels were significantly decreased one year after a good test result; there was no significant change in the case of a bad test result. The mean personality profile, including ego strength, remained unchanged one year after the test. The study further shows that the test result had a definite impact on reproductive decision making. Stepwise multiple regression analyses were used to select the best predictors of the subject's post-test reactions. The results indicate that a careful evaluation of pretest ego strength, depression level, and coping strategies may be helpful in predicting post-test reactions, independently of the carrier status. Test result (carrier/ non-carrier), gender, and age did not significantly contribute to the prediction. About one third of the variance of post-test anxiety and depression level and more than half of the variance of ego strength was explained, implying that other psychological or social aspects should also be taken into account when predicting individual post-test reactions. PMID:8880572

Scalable Joint Models for Reliable Uncertainty-Aware Event Prediction.

PubMed

Soleimani, Hossein; Hensman, James; Saria, Suchi

2017-08-21

Missing data and noisy observations pose significant challenges for reliably predicting events from irregularly sampled multivariate time series (longitudinal) data. Imputation methods, which are typically used for completing the data prior to event prediction, lack a principled mechanism to account for the uncertainty due to missingness. Alternatively, state-of-the-art joint modeling techniques can be used for jointly modeling the longitudinal and event data and compute event probabilities conditioned on the longitudinal observations. These approaches, however, make strong parametric assumptions and do not easily scale to multivariate signals with many observations. Our proposed approach consists of several key innovations. First, we develop a flexible and scalable joint model based upon sparse multiple-output Gaussian processes. Unlike state-of-the-art joint models, the proposed model can explain highly challenging structure including non-Gaussian noise while scaling to large data. Second, we derive an optimal policy for predicting events using the distribution of the event occurrence estimated by the joint model. The derived policy trades-off the cost of a delayed detection versus incorrect assessments and abstains from making decisions when the estimated event probability does not satisfy the derived confidence criteria. Experiments on a large dataset show that the proposed framework significantly outperforms state-of-the-art techniques in event prediction.

Factor analysis shows association between family activity environment and children's health behaviour.

PubMed

Hendrie, Gilly A; Coveney, John; Cox, David N

2011-12-01

To characterise the family activity environment in a questionnaire format, assess the questionnaire's reliability and describe its predictive ability by examining the relationships between the family activity environment and children's health behaviours - physical activity, screen time and fruit and vegetable intake. This paper describes the creation of a tool, based on previously validated scales, adapted from the food domain. Data are from 106 children and their parents (Adelaide, South Australia). Factor analysis was used to characterise factors within the family activity environment. Pearson-Product Moment correlations between the family environment and child outcomes, controlling for demographic variation, were examined. Three factors described the family activity environment - parental activity involvement, opportunity for role modelling and parental support for physical activity - and explained 37.6% of the variance. Controlling for demographic factors, the scale was significantly correlated with children's health behaviour - physical activity (r=0.27), screen time (r=-0.24) and fruit and vegetable intake (r=0.34). The family activity environment questionnaire shows high internal consistency and moderate predictive ability. This study has built on previous research by taking a more comprehensive approach to measuring the family activity environment. This research suggests the family activity environment should be considered in family-based health promotion interventions. © 2011 The Authors. ANZJPH © 2011 Public Health Association of Australia.

Examining Predictive Validity of Oral Reading Fluency Slope in Upper Elementary Grades Using Quantile Regression.

PubMed

Cho, Eunsoo; Capin, Philip; Roberts, Greg; Vaughn, Sharon

2017-07-01

Within multitiered instructional delivery models, progress monitoring is a key mechanism for determining whether a child demonstrates an adequate response to instruction. One measure commonly used to monitor the reading progress of students is oral reading fluency (ORF). This study examined the extent to which ORF slope predicts reading comprehension outcomes for fifth-grade struggling readers ( n = 102) participating in an intensive reading intervention. Quantile regression models showed that ORF slope significantly predicted performance on a sentence-level fluency and comprehension assessment, regardless of the students' reading skills, controlling for initial ORF performance. However, ORF slope was differentially predictive of a passage-level comprehension assessment based on students' reading skills when controlling for initial ORF status. Results showed that ORF explained unique variance for struggling readers whose posttest performance was at the upper quantiles at the end of the reading intervention, but slope was not a significant predictor of passage-level comprehension for students whose reading problems were the most difficult to remediate.

Implicit but not explicit self-esteem predicts future depressive symptomatology.

PubMed

Franck, Erik; De Raedt, Rudi; De Houwer, Jan

2007-10-01

To date, research on the predictive validity of implicit self-esteem for depressive relapse is very sparse. In the present study, we assessed implicit self-esteem using the Name Letter Preference Task and explicit self-esteem using the Rosenberg self-esteem scale in a group of currently depressed patients, formerly depressed individuals, and never depressed controls. In addition, we examined the predictive validity of explicit, implicit, and the interaction of explicit and implicit self-esteem in predicting future symptoms of depression in formerly depressed individuals and never depressed controls. The results showed that currently depressed individuals reported a lower explicit self-esteem as compared to formerly depressed individuals and never depressed controls. In line with previous research, all groups showed a positive implicit self-esteem not different from each other. Furthermore, after controlling for initial depressive symptomatology, implicit but not explicit self-esteem significantly predicted depressive symptoms at six months follow-up. Although implicit self-esteem assessed with the Name Letter Preference Test was not different between formerly depressed individuals and never depressed controls, the findings suggest it is an interesting variable in the study of vulnerability for depression relapse.

Baseline predictability of daily east Asian summer monsoon circulation indices

NASA Astrophysics Data System (ADS)

Ai, Shucong; Chen, Quanliang; Li, Jianping; Ding, Ruiqiang; Zhong, Quanjia

2017-05-01

The nonlinear local Lyapunov exponent (NLLE) method is adopted to quantitatively determine the predictability limit of East Asian summer monsoon (EASM) intensity indices on a synoptic timescale. The predictability limit of EASM indices varies widely according to the definitions of indices. EASM indices defined by zonal shear have a limit of around 7 days, which is higher than the predictability limit of EASM indices defined by sea level pressure (SLP) difference and meridional wind shear (about 5 days). The initial error of EASM indices defined by SLP difference and meridional wind shear shows a faster growth than indices defined by zonal wind shear. Furthermore, the indices defined by zonal wind shear appear to fluctuate at lower frequencies, whereas the indices defined by SLP difference and meridional wind shear generally fluctuate at higher frequencies. This result may explain why the daily variability of the EASM indices defined by zonal wind shear tends be more predictable than those defined by SLP difference and meridional wind shear. Analysis of the temporal correlation coefficient (TCC) skill for EASM indices obtained from observations and from NCEP's Global Ensemble Forecasting System (GEFS) historical weather forecast dataset shows that GEFS has a higher forecast skill for the EASM indices defined by zonal wind shear than for indices defined by SLP difference and meridional wind shear. The predictability limit estimated by the NLLE method is shorter than that in GEFS. In addition, the June-September average TCC skill for different daily EASM indices shows significant interannual variations from 1985 to 2015 in GEFS. However, the TCC for different types of EASM indices does not show coherent interannual fluctuations.

Enuresis, firesetting, and cruelty to animals: does the ego triad show predictive validity?

PubMed

Slavkin, M L

2001-01-01

The hypothesis tested in this study was that the presence of enuresis and cruelty to animals in juvenile firesetters would be significantly related to recidivistic firesetting. This hypothesis was related to Yarnell's belief in an ego triad among juvenile firesetters, which linked the occurrence of enuresis, cruelty to animals and others, and firesetting. No relationship was found between groups for firesetting recidivism and enuresis. However, juveniles who were identified as being cruel to animals were more likely than those who were not cruel to animals to engage in recidivistic firesetting behaviors.

Significant growth in. LED use predicted.

PubMed

Simpson, Mike

2012-03-01

Although LED lighting has its critics, a number of whom (see article 'LED--panacea or marketing hype', HEJ--February 2012) are concerned about what they claim are some manufacturers' 'exaggerated claims' about lighting efficiency and lamp lifetime, Philips Lighting believes that, such are the advances being made in this innovative lighting technology, that LED's overall share of the European lighting market will have risen from around 7% in 2008 to 25% by 2020 and that, a decade later, it will account for a remarkable 75% of lighting sales. In the UK, Philips' technical and design director for Lighting, Mike Simpson, told HEJ editor, Jonathan Baillie, healthcare estates and facilities managers are increasingly recognising the potential to save energy, reduce carbon emissions, and cut maintenance costs, using LED.

A Noise Trimming and Positional Significance of Transposon Insertion System to Identify Essential Genes in Yersinia pestis

NASA Astrophysics Data System (ADS)

Yang, Zheng Rong; Bullifent, Helen L.; Moore, Karen; Paszkiewicz, Konrad; Saint, Richard J.; Southern, Stephanie J.; Champion, Olivia L.; Senior, Nicola J.; Sarkar-Tyson, Mitali; Oyston, Petra C. F.; Atkins, Timothy P.; Titball, Richard W.

2017-02-01

Massively parallel sequencing technology coupled with saturation mutagenesis has provided new and global insights into gene functions and roles. At a simplistic level, the frequency of mutations within genes can indicate the degree of essentiality. However, this approach neglects to take account of the positional significance of mutations - the function of a gene is less likely to be disrupted by a mutation close to the distal ends. Therefore, a systematic bioinformatics approach to improve the reliability of essential gene identification is desirable. We report here a parametric model which introduces a novel mutation feature together with a noise trimming approach to predict the biological significance of Tn5 mutations. We show improved performance of essential gene prediction in the bacterium Yersinia pestis, the causative agent of plague. This method would have broad applicability to other organisms and to the identification of genes which are essential for competitiveness or survival under a broad range of stresses.

A Noise Trimming and Positional Significance of Transposon Insertion System to Identify Essential Genes in Yersinia pestis

PubMed Central

Yang, Zheng Rong; Bullifent, Helen L.; Moore, Karen; Paszkiewicz, Konrad; Saint, Richard J.; Southern, Stephanie J.; Champion, Olivia L.; Senior, Nicola J.; Sarkar-Tyson, Mitali; Oyston, Petra C. F.; Atkins, Timothy P.; Titball, Richard W.

2017-01-01

Massively parallel sequencing technology coupled with saturation mutagenesis has provided new and global insights into gene functions and roles. At a simplistic level, the frequency of mutations within genes can indicate the degree of essentiality. However, this approach neglects to take account of the positional significance of mutations - the function of a gene is less likely to be disrupted by a mutation close to the distal ends. Therefore, a systematic bioinformatics approach to improve the reliability of essential gene identification is desirable. We report here a parametric model which introduces a novel mutation feature together with a noise trimming approach to predict the biological significance of Tn5 mutations. We show improved performance of essential gene prediction in the bacterium Yersinia pestis, the causative agent of plague. This method would have broad applicability to other organisms and to the identification of genes which are essential for competitiveness or survival under a broad range of stresses. PMID:28165493

Left atrial strain predicts hemodynamic parameters in cardiovascular patients.

PubMed

Hewing, Bernd; Theres, Lena; Spethmann, Sebastian; Stangl, Karl; Dreger, Henryk; Knebel, Fabian

2017-08-01

We aimed to evaluate the predictive value of left atrial (LA) reservoir, conduit, and contractile function parameters as assessed by speckle tracking echocardiography (STE) for invasively measured hemodynamic parameters in a patient cohort with myocardial and valvular diseases. Sixty-nine patients undergoing invasive hemodynamic assessment were enrolled into the study. Invasive hemodynamic parameters were obtained by left and right heart catheterization. Transthoracic echocardiography assessment of LA reservoir, conduit, and contractile function was performed by STE. Forty-nine patients had sinus rhythm (SR) and 20 patients had permanent atrial fibrillation (AF). AF patients had significantly reduced LA reservoir function compared to SR patients. In patients with SR, LA reservoir, conduit, and contractile function inversely correlated with pulmonary capillary wedge pressure (PCWP), left ventricular end-diastolic pressure, and mean pulmonary artery pressure (PAP), and showed a moderate association with cardiac index. In AF patients, there were no significant correlations between LA reservoir function and invasively obtained hemodynamic parameters. In SR patients, LA contractile function with a cutoff value of 16.0% had the highest diagnostic accuracy (area under the curve, AUC: 0.895) to predict PCWP ≥18 mm Hg compared to the weaker diagnostic accuracy of average E/E' ratio with an AUC of 0.786 at a cutoff value of 14.3. In multivariate analysis, LA contractile function remained significantly associated with PCWP ≥18 mm Hg. In a cohort of patients with a broad spectrum of cardiovascular diseases LA strain shows a valuable prediction of hemodynamic parameters, specifically LV filling pressures, in the presence of SR. © 2017, Wiley Periodicals, Inc.

Validation of DAB2IP methylation and its relative significance in predicting outcome in renal cell carcinoma

PubMed Central

Zhao, Liang-Yun; Kapur, Payal; Wu, Kai-Jie; Wang, Bin; Yu, Yan-Hong; Liao, Bing; He, Da-Lin; Chen, Wei; Margulis, Vitaly; Hsieh, Jer-Tsong; Luo, Jun-Hang

2016-01-01

We have recently reported tumor suppressive role of DAB2IP in RCC development. In this study, We identified one CpG methylation biomarker (DAB2IP CpG1) located UTSS of DAB2IP that was associated with poor overall survival in a cohort of 318 ccRCC patients from the Cancer Genome Atlas (TCGA). We further validated the prognostic accuracy of DAB2IP CpG methylation by pyrosequencing quantitative methylation assay in 224 ccRCC patients from multiple Chinese centers (MCHC set), and 239 patients from University of Texas Southwestern Medical Center at Dallas (UTSW set) by using FFPE samples. DAB2IP CpG1 can predict the overall survival of patients in TCGA, MCHC, and UTSW sets independent of patient age, Fuhrman grade and TNM stage (all p<0.05). DAB2IP CpG1 successfully categorized patients into high-risk and low-risk groups with significant differences of clinical outcome in respective clinical subsets, regardless of age, sex, grade, stage, or race (HR: 1.63-7.83; all p<0.05). The detection of DAB2IP CpG1 methylation was minimally affected by ITH in ccRCC. DAB2IP mRNA expression was regulated by DNA methylation in vitro. DAB2IP CpG1 methylation is a practical and repeatable biomarker for ccRCC, which can provide prognostic value that complements the current staging system. PMID:27129174

Ubiquitous Geometry: Some Examples Showing the Significance of Size and Shape in the Works of Man and Nature.

ERIC Educational Resources Information Center

Bachman, C. H.

1988-01-01

Presents examples to show the ubiquitous nature of geometry. Illustrates the relationship between the perimeter and area of two-dimensional objects and between the area and volume of three-dimensional objects. Provides examples of distribution systems, optimum shapes, structural strength, biological heat engines, man's size, and reflection and…

Cluster analysis as a prediction tool for pregnancy outcomes.

PubMed

Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

2015-03-01

Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

Genome-wide analysis of adolescent psychotic-like experiences shows genetic overlap with psychiatric disorders.

PubMed

Pain, Oliver; Dudbridge, Frank; Cardno, Alastair G; Freeman, Daniel; Lu, Yi; Lundstrom, Sebastian; Lichtenstein, Paul; Ronald, Angelica

2018-03-31

This study aimed to test for overlap in genetic influences between psychotic-like experience traits shown by adolescents in the community, and clinically-recognized psychiatric disorders in adulthood, specifically schizophrenia, bipolar disorder, and major depression. The full spectra of psychotic-like experience domains, both in terms of their severity and type (positive, cognitive, and negative), were assessed using self- and parent-ratings in three European community samples aged 15-19 years (Final N incl. siblings = 6,297-10,098). A mega-genome-wide association study (mega-GWAS) for each psychotic-like experience domain was performed. Single nucleotide polymorphism (SNP)-heritability of each psychotic-like experience domain was estimated using genomic-relatedness-based restricted maximum-likelihood (GREML) and linkage disequilibrium- (LD-) score regression. Genetic overlap between specific psychotic-like experience domains and schizophrenia, bipolar disorder, and major depression was assessed using polygenic risk score (PRS) and LD-score regression. GREML returned SNP-heritability estimates of 3-9% for psychotic-like experience trait domains, with higher estimates for less skewed traits (Anhedonia, Cognitive Disorganization) than for more skewed traits (Paranoia and Hallucinations, Parent-rated Negative Symptoms). Mega-GWAS analysis identified one genome-wide significant association for Anhedonia within IDO2 but which did not replicate in an independent sample. PRS analysis revealed that the schizophrenia PRS significantly predicted all adolescent psychotic-like experience trait domains (Paranoia and Hallucinations only in non-zero scorers). The major depression PRS significantly predicted Anhedonia and Parent-rated Negative Symptoms in adolescence. Psychotic-like experiences during adolescence in the community show additive genetic effects and partly share genetic influences with clinically-recognized psychiatric disorders, specifically schizophrenia and

Predictive modeling of surimi cake shelf life at different storage temperatures

NASA Astrophysics Data System (ADS)

Wang, Yatong; Hou, Yanhua; Wang, Quanfu; Cui, Bingqing; Zhang, Xiangyu; Li, Xuepeng; Li, Yujin; Liu, Yuanping

2017-04-01

The Arrhenius model of the shelf life prediction which based on the TBARS index was established in this study. The results showed that the significant changed of AV, POV, COV and TBARS with temperature increased, and the reaction rate constants k was obtained by the first order reaction kinetics model. Then the secondary model fitting was based on the Arrhenius equation. There was the optimal fitting accuracy of TBARS in the first and the secondary model fitting (R2≥0.95). The verification test indicated that the relative error between the shelf life model prediction value and actual value was within ±10%, suggesting the model could predict the shelf life of surimi cake.

Learning Temporal Statistics for Sensory Predictions in Aging.

PubMed

Luft, Caroline Di Bernardi; Baker, Rosalind; Goldstone, Aimee; Zhang, Yang; Kourtzi, Zoe

2016-03-01

Predicting future events based on previous knowledge about the environment is critical for successful everyday interactions. Here, we ask which brain regions support our ability to predict the future based on implicit knowledge about the past in young and older age. Combining behavioral and fMRI measurements, we test whether training on structured temporal sequences improves the ability to predict upcoming sensory events; we then compare brain regions involved in learning predictive structures between young and older adults. Our behavioral results demonstrate that exposure to temporal sequences without feedback facilitates the ability of young and older adults to predict the orientation of an upcoming stimulus. Our fMRI results provide evidence for the involvement of corticostriatal regions in learning predictive structures in both young and older learners. In particular, we showed learning-dependent fMRI responses for structured sequences in frontoparietal regions and the striatum (putamen) for young adults. However, for older adults, learning-dependent activations were observed mainly in subcortical (putamen, thalamus) regions but were weaker in frontoparietal regions. Significant correlations of learning-dependent behavioral and fMRI changes in these regions suggest a strong link between brain activations and behavioral improvement rather than general overactivation. Thus, our findings suggest that predicting future events based on knowledge of temporal statistics engages brain regions involved in implicit learning in both young and older adults.

A correlational and predictive study of creativity and personality of college students.

PubMed

Sanz de Acedo Baquedano, María Teresa; Sanz de Acedo Lizarraga, María Luisa

2012-11-01

The goals of this study were to examine the relationship between creativity and personality, to identify what personality variables better predict creativity, and to determine whether significant differences exist among them in relation to gender. The research was conducted with a sample of 87 students at the Universidad Pública de Navarra, Spain. We administered the Creative Intelligence Test (CREA), which provides a cognitive measure for creativity and the Situational Personality Questionnaire (SPQ), which is composed of 15 personality features. Positive and significant correlations between creativity and independence, cognitive control, and tolerance personality scales were found. Negative and significant correlations between creativity and anxious, dominant, and aggressive personalities were also found. Moreover, four personality variables that positively predicted creativity (efficacy, independence, cognitive control, and integrity-honesty) and another four that negatively predicted creativity (emotional stability, anxiety, dominance, and leadership) were identified. The results did not show significant differences in creativity and personality in relation to gender, except in self-concept and in social adjustment. In conclusion, the results from this study can potentially be used to expand the types of features that support creative personalities.

Prediction of Balance Compensation After Vestibular Schwannoma Surgery.

PubMed

Parietti-Winkler, Cécile; Lion, Alexis; Frère, Julien; Perrin, Philippe P; Beurton, Renaud; Gauchard, Gérome C

2016-06-01

Background Balance compensation after vestibular schwannoma (VS) surgery is under the influence of specific preoperative patient and tumor characteristics. Objective To prospectively identify potential prognostic factors for balance recovery, we compared the respective influence of these preoperative characteristics on balance compensation after VS surgery. Methods In 50 patients scheduled for VS surgical ablation, we measured postural control before surgery (BS), 8 (AS8) days after, and 90 (AS90) days after surgery. Based on factors found previously in the literature, we evaluated age, body mass index and preoperative physical activity (PA), tumor grade, vestibular status, and preference for visual cues to control balance as potential prognostic factors using stepwise multiple regression models. Results An asymmetric vestibular function was the sole significant explanatory factor for impaired balance performance BS, whereas the preoperative PA alone significantly contributed to higher performance at AS8. An evaluation of patients' balance recovery over time showed that PA and vestibular status were the 2 significant predictive factors for short-term postural compensation (BS to AS8), whereas none of these preoperative factors was significantly predictive for medium-term postoperative postural recovery (AS8 to AS90). Conclusions We identified specific preoperative patient and vestibular function characteristics that may predict postoperative balance recovery after VS surgery. Better preoperative characterization of these factors in each patient could inform more personalized presurgical and postsurgical management, leading to a better, more rapid balance recovery, earlier return to normal daily activities and work, improved quality of life, and reduced medical and societal costs. © The Author(s) 2015.

Ensemble-based docking: From hit discovery to metabolism and toxicity predictions

DOE PAGES

Evangelista, Wilfredo; Weir, Rebecca; Ellingson, Sally; ...

2016-07-29

The use of ensemble-based docking for the exploration of biochemical pathways and toxicity prediction of drug candidates is described. We describe the computational engineering work necessary to enable large ensemble docking campaigns on supercomputers. We show examples where ensemble-based docking has significantly increased the number and the diversity of validated drug candidates. Finally, we illustrate how ensemble-based docking can be extended beyond hit discovery and toward providing a structural basis for the prediction of metabolism and off-target binding relevant to pre-clinical and clinical trials.

Clinical significance of tryptophan catabolism in Hodgkin lymphoma.

PubMed

Masaki, Ayako; Ishida, Takashi; Maeda, Yasuhiro; Ito, Asahi; Suzuki, Susumu; Narita, Tomoko; Kinoshita, Shiori; Takino, Hisashi; Yoshida, Takashi; Ri, Masaki; Kusumoto, Shigeru; Komatsu, Hirokazu; Inagaki, Hiroshi; Ueda, Ryuzo; Choi, Ilseung; Suehiro, Youko; Iida, Shinsuke

2018-01-01

Indoleamine 2,3-dioxygenase 1 (IDO) is an enzyme catabolizing tryptophan (Trp) into the kynurenine (Kyn) pathway. The purpose of the present study was to determine the clinical significance of Trp catabolism in newly diagnosed Hodgkin lymphoma (HL) patients. We quantified serum Trp and Kyn in 52 HL patients, and analyzed their associations with different clinical parameters including serum soluble CD30 concentration. The IDO expression was evaluated in the patients' affected lymph nodes. The cohort comprised 22 male and 30 female patients (age range, 15-81 years; median, 45 years), with a 5-year overall survival (OS) of 88.6%. The OS was significantly shorter for patients with a high Kyn/Trp ratio (OS at 5 years, 60.0% vs 92.2%), for those with stage IV disease, and for those with lymphocytopenia (<600/mm 3 and/or <8% white blood cell count). The latter two parameters are components of the international prognostic score for advanced HL. In contrast, there were no significant differences in OS according to age, serum albumin, hemoglobin, sex, white blood cell count, or serum soluble CD30 (≥ or <285.6 ng/mL). Multivariate analysis using the three variables stage, lymphocytopenia, and serum Kyn/Trp ratio showed that only the latter significantly affected OS. Indoleamine 2,3-dioxygenase 1 was produced by macrophages/dendritic cells, but not by HL tumor cells, and IDO levels determined by immunohistochemistry had a significant positive correlation with the serum Kyn/Trp ratio. In conclusion, quantification of serum Kyn and Trp is useful for predicting prognosis of individual HL patients. © 2017 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

Significance of Vestibular Testing on Distinguishing the Nerve of Origin for Vestibular Schwannoma and Predicting the Preservation of Hearing

PubMed Central

He, Yu-Bo; Yu, Chun-Jiang; Ji, Hong-Ming; Qu, Yan-Ming; Chen, Ning

2016-01-01

Background: Determining the nerve of origin for vestibular schwannoma (VS), as a method for predicting hearing prognosis, has not been systematically considered. The vestibular test can be used to investigate the function of the superior vestibular nerve (SVN) and the inferior vestibular nerve (IVN). This study aimed to preoperatively distinguish the nerve of origin for VS patients using the vestibular test, and determine if this correlated with hearing preservation. Methods: A total of 106 patients with unilateral VS were enrolled in this study prospectively. Each patient received a caloric test, vestibular-evoked myogenic potential (VEMP) test, and cochlear nerve function test (hearing) before the operation and 1 week, 3, and 6 months, postoperatively. All patients underwent surgical removal of the VS using the suboccipital approach. During the operation, the nerve of tumor origin (SVN or IVN) was identified by the surgeon. Tumor size was measured by preoperative magnetic resonance imaging. Results: The nerve of tumor origin could not be unequivocally identified in 38 patients (38/106, 35.80%). These patients were not subsequently evaluated. In 26 patients (nine females, seventeen males), tumors arose from the SVN and in 42 patients (18 females, 24 males), tumors arose from the IVN. Comparing with the nerve of origins (SVN and IVN) of tumors, the results of the caloric tests and VEMP tests were significantly different in tumors originating from the SVN and the IVN in our study. Hearing was preserved in 16 of 26 patients (61.54%) with SVN-originating tumors, whereas hearing was preserved in only seven of 42 patients (16.67%) with IVN-originating tumors. Conclusions: Our data suggest that caloric and VEMP tests might help to identify whether VS tumors originate from the SVN or IVN. These tests could also be used to evaluate the residual function of the nerves after surgery. Using this information, we might better predict the preservation of hearing for patients

Seasonal prediction of Indian summer monsoon rainfall in NCEP CFSv2: forecast and predictability error

NASA Astrophysics Data System (ADS)

Pokhrel, Samir; Saha, Subodh Kumar; Dhakate, Ashish; Rahman, Hasibur; Chaudhari, Hemantkumar S.; Salunke, Kiran; Hazra, Anupam; Sujith, K.; Sikka, D. R.

2016-04-01

A detailed analysis of sensitivity to the initial condition for the simulation of the Indian summer monsoon using retrospective forecast by the latest version of the Climate Forecast System version-2 (CFSv2) is carried out. This study primarily focuses on the tropical region of Indian and Pacific Ocean basin, with special emphasis on the Indian land region. The simulated seasonal mean and the inter-annual standard deviations of rainfall, upper and lower level atmospheric circulations and Sea Surface Temperature (SST) tend to be more skillful as the lead forecast time decreases (5 month lead to 0 month lead time i.e. L5-L0). In general spatial correlation (bias) increases (decreases) as forecast lead time decreases. This is further substantiated by their averaged value over the selected study regions over the Indian and Pacific Ocean basins. The tendency of increase (decrease) of model bias with increasing (decreasing) forecast lead time also indicates the dynamical drift of the model. Large scale lower level circulation (850 hPa) shows enhancement of anomalous westerlies (easterlies) over the tropical region of the Indian Ocean (Western Pacific Ocean), which indicates the enhancement of model error with the decrease in lead time. At the upper level circulation (200 hPa) biases in both tropical easterly jet and subtropical westerlies jet tend to decrease as the lead time decreases. Despite enhancement of the prediction skill, mean SST bias seems to be insensitive to the initialization. All these biases are significant and together they make CFSv2 vulnerable to seasonal uncertainties in all the lead times. Overall the zeroth lead (L0) seems to have the best skill, however, in case of Indian summer monsoon rainfall (ISMR), the 3 month lead forecast time (L3) has the maximum ISMR prediction skill. This is valid using different independent datasets, wherein these maximum skill scores are 0.64, 0.42 and 0.57 with respect to the Global Precipitation Climatology Project

Identification of an miRNA candidate reflects the possible significance of transcribed microsatellites in the hairpin precursors of black pepper.

PubMed

Joy, Nisha; Soniya, Eppurathu Vasudevan

2012-06-01

Plant miRNAs (18-24nt) are generated by the RNase III-type Dicer endonuclease from the endogenous hairpin precursors ('pre-miRNAs') with significant regulatory functions. The transcribed regions display a higher frequency of microsatellites, when compared to other regions of the genomic DNA. Simple sequence repeats (SSRs) resulting from replication slippage occurring in transcripts affect the expression of genes. The available experimental evidence for the incidence of SSRs in the miRNA precursors is limited. Considering the potential significance of SSRs in the miRNA genes, we carried out a preliminary analysis to verify the presence of SSRs in the pri-miRNAs of black pepper (Piper nigrum L.). We isolated a (CT) dinucleotide SSR bearing transcript using SMART strategy. The transcript was predicted to be a 'pri-miRNA candidate' with Dicer sites based on miRNA prediction tools and MFOLD structural predictions. The presence of this 'miRNA candidate' was confirmed by real-time TaqMan assays. The upstream sequence of the 'miRNA candidate' by genome walking when subjected to PlantCARE showed the presence of certain promoter elements, and the deduced amino acid showed significant similarity with NAP1 gene, which affects the transcription of many genes. Moreover the hairpin-like precursor overlapped the neighbouring NAP1 gene. In silico analysis revealed distinct putative functions for the 'miRNA candidate', of which majority were related to growth. Hence, we assume that this 'miRNA candidate' may get activated during transcription of NAP gene, thereby regulating the expression of many genes involved in developmental processes.

Evaluating pictogram prediction in a location-aware augmentative and alternative communication system.

PubMed

Garcia, Luís Filipe; de Oliveira, Luís Caldas; de Matos, David Martins

2016-01-01

This study compared the performance of two statistical location-aware pictogram prediction mechanisms, with an all-purpose (All) pictogram prediction mechanism, having no location knowledge. The All approach had a unique language model under all locations. One of the location-aware alternatives, the location-specific (Spec) approach, made use of specific language models for pictogram prediction in each location of interest. The other location-aware approach resulted from combining the Spec and the All approaches, and was designated the mixed approach (Mix). In this approach, the language models acquired knowledge from all locations, but a higher relevance was assigned to the vocabulary from the associated location. Results from simulations showed that the Mix and Spec approaches could only outperform the baseline in a statistically significant way if pictogram users reuse more than 50% and 75% of their sentences, respectively. Under low sentence reuse conditions there were no statistically significant differences between the location-aware approaches and the All approach. Under these conditions, the Mix approach performed better than the Spec approach in a statistically significant way.

Can paediatric early warning scores (PEWS) be used to guide the need for hospital admission and predict significant illness in children presenting to the emergency department? An assessment of PEWS diagnostic accuracy using sensitivity and specificity.

PubMed

Lillitos, Peter J; Hadley, Graeme; Maconochie, Ian

2016-05-01

Designed to detect early deterioration of the hospitalised child, paediatric early warning scores (PEWS) validity in the emergency department (ED) is less validated. We aimed to evaluate sensitivity and specificity of two commonly used PEWS (Brighton and COAST) in predicting hospital admission and, for the first time, significant illness. Retrospective analysis of PEWS data for paediatric ED attendances at St Mary's Hospital, London, UK, in November 2012. Patients with missing data were excluded. Diagnoses were grouped: medical and surgical. To classify diagnoses as significant, established guidelines were used and, where not available, common agreement between three acute paediatricians. 1921 patients were analysed. There were 211 admissions (11%). 1630 attendances were medical (86%) and 273 (14%) surgical. Brighton and COAST PEWS performed similarly. hospital admission: PEWS of ≥3 was specific (93%) but poorly sensitive (32%). The area under the receiver operating curve (AUC) was low at 0.690. Significant illness: for medical illness, PEWS ≥3 was highly specific (96%) but poorly sensitive (44%). The AUC was 0.754 and 0.755 for Brighton and COAST PEWS, respectively. Both scores performed poorly for predicting significant surgical illness (AUC 0.642). PEWS ≥3 performed well in predicting significant respiratory illness: sensitivity 75%, specificity 91%. Both Brighton and COAST PEWS scores performed similarly. A score of ≥3 has good specificity but poor sensitivity for predicting hospital admission and significant illness. Therefore, a high PEWS should be taken seriously but a low score is poor at ruling out the requirement for admission or serious underlying illness. PEWS was better at detecting significant medical illness compared with detecting the need for admission. PEWS performed poorly in detecting significant surgical illness. PEWS may be particularly useful in evaluating respiratory illness in a paediatric ED. Published by the BMJ Publishing Group

Improved NASA-ANOPP Noise Prediction Computer Code for Advanced Subsonic Propulsion Systems

NASA Technical Reports Server (NTRS)

Kontos, K. B.; Janardan, B. A.; Gliebe, P. R.

1996-01-01

Recent experience using ANOPP to predict turbofan engine flyover noise suggests that it over-predicts overall EPNL by a significant amount. An improvement in this prediction method is desired for system optimization and assessment studies of advanced UHB engines. An assessment of the ANOPP fan inlet, fan exhaust, jet, combustor, and turbine noise prediction methods is made using static engine component noise data from the CF6-8OC2, E(3), and QCSEE turbofan engines. It is shown that the ANOPP prediction results are generally higher than the measured GE data, and that the inlet noise prediction method (Heidmann method) is the most significant source of this overprediction. Fan noise spectral comparisons show that improvements to the fan tone, broadband, and combination tone noise models are required to yield results that more closely simulate the GE data. Suggested changes that yield improved fan noise predictions but preserve the Heidmann model structure are identified and described. These changes are based on the sets of engine data mentioned, as well as some CFM56 engine data that was used to expand the combination tone noise database. It should be noted that the recommended changes are based on an analysis of engines that are limited to single stage fans with design tip relative Mach numbers greater than one.

Obesity in show cats.

PubMed

Corbee, R J

2014-12-01

Obesity is an important disease with a high prevalence in cats. Because obesity is related to several other diseases, it is important to identify the population at risk. Several risk factors for obesity have been described in the literature. A higher incidence of obesity in certain cat breeds has been suggested. The aim of this study was to determine whether obesity occurs more often in certain breeds. The second aim was to relate the increased prevalence of obesity in certain breeds to the official standards of that breed. To this end, 268 cats of 22 different breeds investigated by determining their body condition score (BCS) on a nine-point scale by inspection and palpation, at two different cat shows. Overall, 45.5% of the show cats had a BCS > 5, and 4.5% of the show cats had a BCS > 7. There were significant differences between breeds, which could be related to the breed standards. Most overweight and obese cats were in the neutered group. It warrants firm discussions with breeders and cat show judges to come to different interpretations of the standards in order to prevent overweight conditions in certain breeds from being the standard of beauty. Neutering predisposes for obesity and requires early nutritional intervention to prevent obese conditions. Journal of Animal Physiology and Animal Nutrition © 2014 Blackwell Verlag GmbH.

The Neural Correlates of Hierarchical Predictions for Perceptual Decisions.

PubMed

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

2018-05-23

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

Rotor Broadband Noise Prediction with Comparison to Model Data

NASA Technical Reports Server (NTRS)

Brooks, Thomas F.; Burley, Casey L.

2001-01-01

This paper reports an analysis and prediction development of rotor broadband noise. The two primary components of this noise are Blade-Wake Interaction (BWI) noise, due to the blades' interaction with the turbulent wakes of the preceding blades, and "Self" noise, due to the development and shedding of turbulence within the blades' boundary layers. Emphasized in this report is the new code development for Self noise. The analysis and validation employs data from the HART program, a model BO-105 rotor wind tunnel test conducted in the German-Dutch Wind Tunnel (DNW). The BWI noise predictions are based on measured pressure response coherence functions using cross-spectral methods. The Self noise predictions are based on previously reported semiempirical modeling of Self noise obtained from isolated airfoil sections and the use of CAMRAD.Modl to define rotor performance and local blade segment flow conditions. Both BWI and Self noise from individual blade segments are Doppler shifted and summed at the observer positions. Prediction comparisons with measurements show good agreement for a range of rotor operating conditions from climb to steep descent. The broadband noise predictions, along with those of harmonic and impulsive Blade-Vortex Interaction (BVI) noise predictions, demonstrate a significant advance in predictive capability for main rotor noise.

Significance of vapor phase chemical reactions on CVD rates predicted by chemically frozen and local thermochemical equilibrium boundary layer theories

NASA Technical Reports Server (NTRS)

Gokoglu, Suleyman A.

1988-01-01

This paper investigates the role played by vapor-phase chemical reactions on CVD rates by comparing the results of two extreme theories developed to predict CVD mass transport rates in the absence of interfacial kinetic barrier: one based on chemically frozen boundary layer and the other based on local thermochemical equilibrium. Both theories consider laminar convective-diffusion boundary layers at high Reynolds numbers and include thermal (Soret) diffusion and variable property effects. As an example, Na2SO4 deposition was studied. It was found that gas phase reactions have no important role on Na2SO4 deposition rates and on the predictions of the theories. The implications of the predictions of the two theories to other CVD systems are discussed.

The predictive power of Japanese candlestick charting in Chinese stock market

NASA Astrophysics Data System (ADS)

Chen, Shi; Bao, Si; Zhou, Yu

2016-09-01

This paper studies the predictive power of 4 popular pairs of two-day bullish and bearish Japanese candlestick patterns in Chinese stock market. Based on Morris' study, we give the quantitative details of definition of long candlestick, which is important in two-day candlestick pattern recognition but ignored by several previous researches, and we further give the quantitative definitions of these four pairs of two-day candlestick patterns. To test the predictive power of candlestick patterns on short-term price movement, we propose the definition of daily average return to alleviate the impact of correlation among stocks' overlap-time returns in statistical tests. To show the robustness of our result, two methods of trend definition are used for both the medium-market-value and large-market-value sample sets. We use Step-SPA test to correct for data snooping bias. Statistical results show that the predictive power differs from pattern to pattern, three of the eight patterns provide both short-term and relatively long-term prediction, another one pair only provide significant forecasting power within very short-term period, while the rest three patterns present contradictory results for different market value groups. For all the four pairs, the predictive power drops as predicting time increases, and forecasting power is stronger for stocks with medium market value than those with large market value.

Fusion of Protegrin-1 and Plectasin to MAP30 Shows Significant Inhibition Activity against Dengue Virus Replication

PubMed Central

Rothan, Hussin A.; Bahrani, Hirbod; Mohamed, Zulqarnain; Abd Rahman, Noorsaadah; Yusof, Rohana

2014-01-01

Dengue virus (DENV) broadly disseminates in tropical and sub-tropical countries and there are no vaccine or anti-dengue drugs available. DENV outbreaks cause serious economic burden due to infection complications that requires special medical care and hospitalization. This study presents a new strategy for inexpensive production of anti-DENV peptide-fusion protein to prevent and/or treat DENV infection. Antiviral cationic peptides protegrin-1 (PG1) and plectasin (PLSN) were fused with MAP30 protein to produce recombinant antiviral peptide-fusion protein (PG1-MAP30-PLSN) as inclusion bodies in E. coli. High yield production of PG1-MAP30-PLSN protein was achieved by solubilization of inclusion bodies in alkaline buffer followed by the application of appropriate refolding techniques. Antiviral PG1-MAP30-PLSN protein considerably inhibited DENV protease (NS2B-NS3pro) with half-maximal inhibitory concentration (IC50) 0.5±0.1 μM. The real-time proliferation assay (RTCA) and the end-point proliferation assay (MTT assay) showed that the maximal-nontoxic dose of the peptide-fusion protein against Vero cells is approximately 0.67±0.2 μM. The cell-based assays showed considerable inhibition of the peptide-fusion protein against binding and proliferating stages of DENV2 into the target cells. The peptide-fusion protein protected DENV2-challeged mice with 100% of survival at the dose of 50 mg/kg. In conclusion, producing recombinant antiviral peptide-fusion protein by combining short antiviral peptide with a central protein owning similar activity could be useful to minimize the overall cost of short peptide production and take advantage of its synergistic antiviral activities. PMID:24722532

Performance of bed-load transport equations relative to geomorphic significance: Predicting effective discharge and its transport rate

Treesearch

Jeffrey J. Barry; John M. Buffington; Peter Goodwin; John .G. King; William W. Emmett

2008-01-01

Previous studies assessing the accuracy of bed-load transport equations have considered equation performance statistically based on paired observations of measured and predicted bed-load transport rates. However, transport measurements were typically taken during low flows, biasing the assessment of equation performance toward low discharges, and because equation...

Lossless Video Sequence Compression Using Adaptive Prediction

NASA Technical Reports Server (NTRS)

Li, Ying; Sayood, Khalid

2007-01-01

We present an adaptive lossless video compression algorithm based on predictive coding. The proposed algorithm exploits temporal, spatial, and spectral redundancies in a backward adaptive fashion with extremely low side information. The computational complexity is further reduced by using a caching strategy. We also study the relationship between the operational domain for the coder (wavelet or spatial) and the amount of temporal and spatial redundancy in the sequence being encoded. Experimental results show that the proposed scheme provides significant improvements in compression efficiencies.

CT volumetric measurement of colorectal cancer helps predict tumor staging and prognosis

PubMed Central

Park, Jin Young; Lee, Sang Min; Lee, Jeong Sub; Han, Joon Koo

2017-01-01

Purpose To evaluate feasibility of CT colonography (CTC) volumetry of colorectal cancer (CRC) and its correlation with disease stage and patients’ survival. Materials and methods CTC volumetry was performed for 126 patients who underwent preoperative CTC. Reproducibility of tumor volume (Tvol) between two readers was assessed. One-way ANOVA and ROC analysis evaluated correlation between Tvol and pTNM staging. ROC analysis compared diagnostic performance to predict pTNM staging between Tvol and radiologist. Kaplan-Meier test compared overall survival. Results Reproducibility among readers was excellent (interclass correlation = 0.9829). Mean Tvol showed an incremental trend with T stage and Tvol of pT4b stage was significantly larger than other stages (P<0.0001). Az value (0.780) of Tvol to predict pT4b stage was significantly larger than that (0.591) of radiologist (P = 0.004). However, Tvol was not significantly different according to pN stage. Az values (0.723~0.857) of Tvol to predict M1 or M1b were comparable to those (0.772~0.690) of radiologist (P>0.05). Smaller tumor burden (≤12.85cm3), ≤T3, N0, M0 stages, and curative surgery were significantly associated with patients’ longer survival (P<0.05). Conclusion CT volumetry has a limited value to predict N stage; however, it may outperform the radiologist’s performance when predicting pT4b and M1b stage and can be a useful prognostic marker. PMID:28570580

Biological significance of long non-coding RNA FTX expression in human colorectal cancer

PubMed Central

Guo, Xiao-Bo; Hua, Zhu; Li, Chen; Peng, Li-Pan; Wang, Jing-Shen; Wang, Bo; Zhi, Qiao-Ming

2015-01-01

The purpose of this study was to determine the expression of long non-coding RNA (lncRNA) FTX and analyze its prognostic and biological significance in colorectal cancer (CRC). A quantitative reverse transcription PCR was performed to detect the expression of long non-coding RNA FTX in 35 pairs of colorectal cancer and corresponding noncancerous tissues. The expression of long non-coding RNA FTX was detected in 187 colorectal cancer tissues and its correlations with clinicopathological factors of patients were examined. Univariate and multivariate analyses were performed to analyze the prognostic significance of Long Non-coding RNA FTX expression. The effects of long non-coding RNA FTX expression on malignant phenotypes of colorectal cancer cells and its possible biological significances were further determined. Long non-coding RNA FTX was significantly upregulated in colorectal cancer tissues, and low long non-coding RNA FTX expression was significantly correlated with differentiation grade, lymph vascular invasion, and clinical stage. Patients with high long non-coding RNA FTX showed poorer overall survival than those with low long non-coding RNA FTX. Multivariate analyses indicated that status of long non-coding RNA FTX was an independent prognostic factor for patients. Functional analyses showed that upregulation of long non-coding RNA FTX significantly promoted growth, migration, invasion, and increased colony formation in colorectal cancer cells. Therefore, long non-coding RNA FTX may be a potential biomarker for predicting the survival of colorectal cancer patients and might be a molecular target for treatment of human colorectal cancer. PMID:26629053

Biological significance of long non-coding RNA FTX expression in human colorectal cancer.

PubMed

Guo, Xiao-Bo; Hua, Zhu; Li, Chen; Peng, Li-Pan; Wang, Jing-Shen; Wang, Bo; Zhi, Qiao-Ming

2015-01-01

The purpose of this study was to determine the expression of long non-coding RNA (lncRNA) FTX and analyze its prognostic and biological significance in colorectal cancer (CRC). A quantitative reverse transcription PCR was performed to detect the expression of long non-coding RNA FTX in 35 pairs of colorectal cancer and corresponding noncancerous tissues. The expression of long non-coding RNA FTX was detected in 187 colorectal cancer tissues and its correlations with clinicopathological factors of patients were examined. Univariate and multivariate analyses were performed to analyze the prognostic significance of Long Non-coding RNA FTX expression. The effects of long non-coding RNA FTX expression on malignant phenotypes of colorectal cancer cells and its possible biological significances were further determined. Long non-coding RNA FTX was significantly upregulated in colorectal cancer tissues, and low long non-coding RNA FTX expression was significantly correlated with differentiation grade, lymph vascular invasion, and clinical stage. Patients with high long non-coding RNA FTX showed poorer overall survival than those with low long non-coding RNA FTX. Multivariate analyses indicated that status of long non-coding RNA FTX was an independent prognostic factor for patients. Functional analyses showed that upregulation of long non-coding RNA FTX significantly promoted growth, migration, invasion, and increased colony formation in colorectal cancer cells. Therefore, long non-coding RNA FTX may be a potential biomarker for predicting the survival of colorectal cancer patients and might be a molecular target for treatment of human colorectal cancer.

CSmetaPred: a consensus method for prediction of catalytic residues.

PubMed

Choudhary, Preeti; Kumar, Shailesh; Bachhawat, Anand Kumar; Pandit, Shashi Bhushan

2017-12-22

Knowledge of catalytic residues can play an essential role in elucidating mechanistic details of an enzyme. However, experimental identification of catalytic residues is a tedious and time-consuming task, which can be expedited by computational predictions. Despite significant development in active-site prediction methods, one of the remaining issues is ranked positions of putative catalytic residues among all ranked residues. In order to improve ranking of catalytic residues and their prediction accuracy, we have developed a meta-approach based method CSmetaPred. In this approach, residues are ranked based on the mean of normalized residue scores derived from four well-known catalytic residue predictors. The mean residue score of CSmetaPred is combined with predicted pocket information to improve prediction performance in meta-predictor, CSmetaPred_poc. Both meta-predictors are evaluated on two comprehensive benchmark datasets and three legacy datasets using Receiver Operating Characteristic (ROC) and Precision Recall (PR) curves. The visual and quantitative analysis of ROC and PR curves shows that meta-predictors outperform their constituent methods and CSmetaPred_poc is the best of evaluated methods. For instance, on CSAMAC dataset CSmetaPred_poc (CSmetaPred) achieves highest Mean Average Specificity (MAS), a scalar measure for ROC curve, of 0.97 (0.96). Importantly, median predicted rank of catalytic residues is the lowest (best) for CSmetaPred_poc. Considering residues ranked ≤20 classified as true positive in binary classification, CSmetaPred_poc achieves prediction accuracy of 0.94 on CSAMAC dataset. Moreover, on the same dataset CSmetaPred_poc predicts all catalytic residues within top 20 ranks for ~73% of enzymes. Furthermore, benchmarking of prediction on comparative modelled structures showed that models result in better prediction than only sequence based predictions. These analyses suggest that CSmetaPred_poc is able to rank putative catalytic

Effects of stressor predictability and controllability on sleep, temperature, and fear behavior in mice.

PubMed

Yang, Linghui; Wellman, Laurie L; Ambrozewicz, Marta A; Sanford, Larry D

2011-06-01

Predictability and controllability are important factors in the persisting effects of stress. We trained mice with signaled, escapable shock (SES) and with signaled, inescapable shock (SIS) to determine whether shock predictability can be a significant factor in the effects of stress on sleep. Male BALB/cJ mice were implanted with transmitters for recording EEG, activity, and temperature via telemetry. After recovery from surgery, baseline sleep recordings were obtained for 2 days. The mice were then randomly assigned to SES (n = 9) and yoked SIS (n = 9) conditions. The mice were presented cues (90 dB, 2 kHz tones) that started 5.0 sec prior to and co-terminated with footshocks (0.5 mA; 5.0 sec maximum duration). SES mice always received shock but could terminate it by moving to the non-occupied chamber in a shuttlebox. SIS mice received identical tones and shocks, but could not alter shock duration. Twenty cue-shock pairings (1.0-min interstimulus intervals) were presented on 2 days (ST1 and ST2). Seven days after ST2, SES and SIS mice, in their home cages, were presented with cues identical to those presented during ST1 and ST2. NA. NA. NA. On each training and test day, EEG, activity and temperature were recorded for 20 hours. Freezing was scored in response to the cue alone. Compared to SIS mice, SES mice showed significantly increased REM after ST1 and ST2. Compared to SES mice, SIS mice showed significantly increased NREM after ST1 and ST2. Both groups showed reduced REM in response to cue presentation alone. Both groups showed similar stress-induced increases in temperature and freezing in response to the cue alone. These findings indicate that predictability (modeled by signaled shock) can play a significant role in the effects of stress on sleep.

Single drug biomarker prediction for ER- breast cancer outcome from chemotherapy.

PubMed

Chen, Yong-Zi; Kim, Youngchul; Soliman, Hatem H; Ying, GuoGuang; Lee, Jae K

2018-06-01

ER-negative breast cancer includes most aggressive subtypes of breast cancer such as triple negative (TN) breast cancer. Excluded from hormonal and targeted therapies effectively used for other subtypes of breast cancer, standard chemotherapy is one of the primary treatment options for these patients. However, as ER- patients have shown highly heterogeneous responses to different chemotherapies, it has been difficult to select most beneficial chemotherapy treatments for them. In this study, we have simultaneously developed single drug biomarker models for four standard chemotherapy agents: paclitaxel (T), 5-fluorouracil (F), doxorubicin (A) and cyclophosphamide (C) to predict responses and survival of ER- breast cancer patients treated with combination chemotherapies. We then flexibly combined these individual drug biomarkers for predicting patient outcomes of two independent cohorts of ER- breast cancer patients who were treated with different drug combinations of neoadjuvant chemotherapy. These individual and combined drug biomarker models significantly predicted chemotherapy response for 197 ER- patients in the Hatzis cohort (AUC = 0.637, P  = 0.002) and 69 ER- patients in the Hess cohort (AUC = 0.635, P  = 0.056). The prediction was also significant for the TN subgroup of both cohorts (AUC = 0.60, 0.72, P  = 0.043, 0.009). In survival analysis, our predicted responder patients showed significantly improved survival with a >17 months longer median PFS than the predicted non-responder patients for both ER- and TN subgroups (log-rank test P -value = 0.018 and 0.044). This flexible prediction capability based on single drug biomarkers may allow us to even select new drug combinations most beneficial to individual patients with ER- breast cancer. © 2018 The authors.

Right Lateral Cerebellum Represents Linguistic Predictability.

PubMed

Lesage, Elise; Hansen, Peter C; Miall, R Chris

2017-06-28

Mounting evidence indicates that posterolateral portions of the cerebellum (right Crus I/II) contribute to language processing, but the nature of this role remains unclear. Based on a well-supported theory of cerebellar motor function, which ascribes to the cerebellum a role in short-term prediction through internal modeling, we hypothesize that right cerebellar Crus I/II supports prediction of upcoming sentence content. We tested this hypothesis using event-related fMRI in male and female human subjects by manipulating the predictability of written sentences. Our design controlled for motor planning and execution, as well as for linguistic features and working memory load; it also allowed separation of the prediction interval from the presentation of the final sentence item. In addition, three further fMRI tasks captured semantic, phonological, and orthographic processing to shed light on the nature of the information processed. As hypothesized, activity in right posterolateral cerebellum correlated with the predictability of the upcoming target word. This cerebellar region also responded to prediction error during the outcome of the trial. Further, this region was engaged in phonological, but not semantic or orthographic, processing. This is the first imaging study to demonstrate a right cerebellar contribution in language comprehension independently from motor, cognitive, and linguistic confounds. These results complement our work using other methodologies showing cerebellar engagement in linguistic prediction and suggest that internal modeling of phonological representations aids language production and comprehension. SIGNIFICANCE STATEMENT The cerebellum is traditionally seen as a motor structure that allows for smooth movement by predicting upcoming signals. However, the cerebellum is also consistently implicated in nonmotor functions such as language and working memory. Using fMRI, we identify a cerebellar area that is active when words are predicted and

Suppression of Striatal Prediction Errors by the Prefrontal Cortex in Placebo Hypoalgesia.

PubMed

Schenk, Lieven A; Sprenger, Christian; Onat, Selim; Colloca, Luana; Büchel, Christian

2017-10-04

Classical learning theories predict extinction after the discontinuation of reinforcement through prediction errors. However, placebo hypoalgesia, although mediated by associative learning, has been shown to be resistant to extinction. We tested the hypothesis that this is mediated by the suppression of prediction error processing through the prefrontal cortex (PFC). We compared pain modulation through treatment cues (placebo hypoalgesia, treatment context) with pain modulation through stimulus intensity cues (stimulus context) during functional magnetic resonance imaging in 48 male and female healthy volunteers. During acquisition, our data show that expectations are correctly learned and that this is associated with prediction error signals in the ventral striatum (VS) in both contexts. However, in the nonreinforced test phase, pain modulation and expectations of pain relief persisted to a larger degree in the treatment context, indicating that the expectations were not correctly updated in the treatment context. Consistently, we observed significantly stronger neural prediction error signals in the VS in the stimulus context compared with the treatment context. A connectivity analysis revealed negative coupling between the anterior PFC and the VS in the treatment context, suggesting that the PFC can suppress the expression of prediction errors in the VS. Consistent with this, a participant's conceptual views and beliefs about treatments influenced the pain modulation only in the treatment context. Our results indicate that in placebo hypoalgesia contextual treatment information engages prefrontal conceptual processes, which can suppress prediction error processing in the VS and lead to reduced updating of treatment expectancies, resulting in less extinction of placebo hypoalgesia. SIGNIFICANCE STATEMENT In aversive and appetitive reinforcement learning, learned effects show extinction when reinforcement is discontinued. This is thought to be mediated by

Using connectome-based predictive modeling to predict individual behavior from brain connectivity

PubMed Central

Shen, Xilin; Finn, Emily S.; Scheinost, Dustin; Rosenberg, Monica D.; Chun, Marvin M.; Papademetris, Xenophon; Constable, R Todd

2017-01-01

Neuroimaging is a fast developing research area where anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale datasets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: 1) feature selection, 2) feature summarization, 3) model building, and 4) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a significant amount of the variance in these measures. It has been demonstrated that the CPM protocol performs equivalently or better than most of the existing approaches in brain-behavior prediction. However, because CPM focuses on linear modeling and a purely data-driven driven approach, neuroscientists with limited or no experience in machine learning or optimization would find it easy to implement the protocols. Depending on the volume of data to be processed, the protocol can take 10–100 minutes for model building, 1–48 hours for permutation testing, and 10–20 minutes for visualization of results. PMID:28182017

A human intervention study with foods containing natural Ah-receptor agonists does not significantly show AhR-mediated effects as measured in blood cells and urine.

PubMed

de Waard, Pim W J; Peijnenburg, Ad A C M; Baykus, Hakan; Aarts, Jac M M J G; Hoogenboom, Ron L A P; van Schooten, Frederik J; de Kok, Theo M C M

2008-10-22

Binding and activation of the aryl hydrocarbon receptor (AhR) is thought to be an essential step in the toxicity of the environmental pollutants dioxins and dioxin-like PCBs. However, also a number of natural compounds, referred to as NAhRAs (natural Ah-receptor agonists), which are present in, for example, fruits and vegetables, can bind and activate this receptor. To study their potential effects in humans, we first investigated the effect of the prototypical AhR agonist 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) on gene expression in ex vivo exposed freshly isolated human lymphocytes, and compared the resulting gene expression profile with those caused by the well-known NAhRA indolo[3,2-b]carbazole (ICZ), originating from cruciferous vegetables, and by a hexane extract of NAhRA-containing grapefruit juice (GJE). Only ICZ induced a gene expression profile similar to TCDD in the lymphocytes, and both significantly up-regulated CYP1B1 and TIPARP (TCDD-inducible poly (ADP-ribose) polymerase) mRNA. Next, we performed a human intervention study with NAhRA-containing cruciferous vegetables and grapefruit juice. The expression of the prototypical AhR-responsive genes CYP1A1, CYP1B1 and NQO1 in whole blood cells and in freshly isolated lymphocytes was not significantly affected. Also enzyme activities of CYP1A2, CYP2A6, N-acetyltransferase 2 (NAT2) and xanthine oxidase (XO), as judged by caffeine metabolites in urine, were unaffected, except for a small down-regulation of NAT2 activity by grapefruit juice. Examination of blood plasma with DR CALUX showed a 12% increased AhR agonist activity 3 and 24 h after consumption of cruciferous vegetables, but did not show a significant effect of grapefruit juice consumption. We conclude that intake of NAhRAs from food may result in minor AhR-related effects measurable in human blood and urine.

Analyzing and Predicting Effort Associated with Finding and Fixing Software Faults

NASA Technical Reports Server (NTRS)

Hamill, Maggie; Goseva-Popstojanova, Katerina

2016-01-01

Context: Software developers spend a significant amount of time fixing faults. However, not many papers have addressed the actual effort needed to fix software faults. Objective: The objective of this paper is twofold: (1) analysis of the effort needed to fix software faults and how it was affected by several factors and (2) prediction of the level of fix implementation effort based on the information provided in software change requests. Method: The work is based on data related to 1200 failures, extracted from the change tracking system of a large NASA mission. The analysis includes descriptive and inferential statistics. Predictions are made using three supervised machine learning algorithms and three sampling techniques aimed at addressing the imbalanced data problem. Results: Our results show that (1) 83% of the total fix implementation effort was associated with only 20% of failures. (2) Both safety critical failures and post-release failures required three times more effort to fix compared to non-critical and pre-release counterparts, respectively. (3) Failures with fixes spread across multiple components or across multiple types of software artifacts required more effort. The spread across artifacts was more costly than spread across components. (4) Surprisingly, some types of faults associated with later life-cycle activities did not require significant effort. (5) The level of fix implementation effort was predicted with 73% overall accuracy using the original, imbalanced data. Using oversampling techniques improved the overall accuracy up to 77%. More importantly, oversampling significantly improved the prediction of the high level effort, from 31% to around 85%. Conclusions: This paper shows the importance of tying software failures to changes made to fix all associated faults, in one or more software components and/or in one or more software artifacts, and the benefit of studying how the spread of faults and other factors affect the fix implementation

Ensemble framework based real-time respiratory motion prediction for adaptive radiotherapy applications.

PubMed

Tatinati, Sivanagaraja; Nazarpour, Kianoush; Tech Ang, Wei; Veluvolu, Kalyana C

2016-08-01

Successful treatment of tumors with motion-adaptive radiotherapy requires accurate prediction of respiratory motion, ideally with a prediction horizon larger than the latency in radiotherapy system. Accurate prediction of respiratory motion is however a non-trivial task due to the presence of irregularities and intra-trace variabilities, such as baseline drift and temporal changes in fundamental frequency pattern. In this paper, to enhance the accuracy of the respiratory motion prediction, we propose a stacked regression ensemble framework that integrates heterogeneous respiratory motion prediction algorithms. We further address two crucial issues for developing a successful ensemble framework: (1) selection of appropriate prediction methods to ensemble (level-0 methods) among the best existing prediction methods; and (2) finding a suitable generalization approach that can successfully exploit the relative advantages of the chosen level-0 methods. The efficacy of the developed ensemble framework is assessed with real respiratory motion traces acquired from 31 patients undergoing treatment. Results show that the developed ensemble framework improves the prediction performance significantly compared to the best existing methods. Copyright © 2016 IPEM. Published by Elsevier Ltd. All rights reserved.

Predicting the dynamics of bacterial growth inhibition by ribosome-targeting antibiotics

NASA Astrophysics Data System (ADS)

Greulich, Philip; Doležal, Jakub; Scott, Matthew; Evans, Martin R.; Allen, Rosalind J.

2017-12-01

Understanding how antibiotics inhibit bacteria can help to reduce antibiotic use and hence avoid antimicrobial resistance—yet few theoretical models exist for bacterial growth inhibition by a clinically relevant antibiotic treatment regimen. In particular, in the clinic, antibiotic treatment is time-dependent. Here, we use a theoretical model, previously applied to steady-state bacterial growth, to predict the dynamical response of a bacterial cell to a time-dependent dose of ribosome-targeting antibiotic. Our results depend strongly on whether the antibiotic shows reversible transport and/or low-affinity ribosome binding (‘low-affinity antibiotic’) or, in contrast, irreversible transport and/or high affinity ribosome binding (‘high-affinity antibiotic’). For low-affinity antibiotics, our model predicts that growth inhibition depends on the duration of the antibiotic pulse, and can show a transient period of very fast growth following removal of the antibiotic. For high-affinity antibiotics, growth inhibition depends on peak dosage rather than dose duration, and the model predicts a pronounced post-antibiotic effect, due to hysteresis, in which growth can be suppressed for long times after the antibiotic dose has ended. These predictions are experimentally testable and may be of clinical significance.

Predicting the dynamics of bacterial growth inhibition by ribosome-targeting antibiotics

PubMed Central

Greulich, Philip; Doležal, Jakub; Scott, Matthew; Evans, Martin R; Allen, Rosalind J

2017-01-01

Understanding how antibiotics inhibit bacteria can help to reduce antibiotic use and hence avoid antimicrobial resistance—yet few theoretical models exist for bacterial growth inhibition by a clinically relevant antibiotic treatment regimen. In particular, in the clinic, antibiotic treatment is time-dependent. Here, we use a theoretical model, previously applied to steady-state bacterial growth, to predict the dynamical response of a bacterial cell to a time-dependent dose of ribosome-targeting antibiotic. Our results depend strongly on whether the antibiotic shows reversible transport and/or low-affinity ribosome binding (‘low-affinity antibiotic’) or, in contrast, irreversible transport and/or high affinity ribosome binding (‘high-affinity antibiotic’). For low-affinity antibiotics, our model predicts that growth inhibition depends on the duration of the antibiotic pulse, and can show a transient period of very fast growth following removal of the antibiotic. For high-affinity antibiotics, growth inhibition depends on peak dosage rather than dose duration, and the model predicts a pronounced post-antibiotic effect, due to hysteresis, in which growth can be suppressed for long times after the antibiotic dose has ended. These predictions are experimentally testable and may be of clinical significance. PMID:28714461

Systematic review of FDG-PET prediction of complete pathological response and survival in rectal cancer.

PubMed

Memon, Sameer; Lynch, A Craig; Akhurst, Timothy; Ngan, Samuel Y; Warrier, Satish K; Michael, Michael; Heriot, Alexander G

2014-10-01

Advances in the management of rectal cancer have resulted in an increased application of multimodal therapy with the aim of tailoring therapy to individual patients. Complete pathological response (pCR) is associated with improved survival and may be potentially managed without radical surgical resection. Over the last decade, there has been increasing interest in the ability of functional imaging to predict complete response to treatment. The aim of this review was to assess the role of (18)F-flurordeoxyglucose positron emission tomography (FDG-PET) in prediction of pCR and prognosis in resectable locally advanced rectal cancer. A search of the MEDLINE and Embase databases was conducted, and a systematic review of the literature investigating positron emission tomography (PET) in the prediction of pCR and survival in rectal cancer was performed. Seventeen series assessing PET prediction of pCR were included in the review. Seven series assessed postchemoradiation SUVmax, which was significantly different between response groups in all six studies that assessed this. Nine series assessed the response index (RI) for SUVmax, which was significantly different between response groups in seven series. Thirteen studies investigated PET response for prediction of survival. Metabolic complete response assessed by SUV2max or visual response and RISUVmax showed strong associations with disease-free survival (DFS) and overall survival (OS). SUV2max and RISUVmax appear to be useful FDG-PET markers for prediction of pCR and these parameters also show strong associations with DFS and OS. FDG-PET may have a role in outcome prediction in patients with advanced rectal cancer.

Complex mixtures of dissolved pesticides show potential aquatic toxicity in a synoptic study of Midwestern U.S. streams

USGS Publications Warehouse

Nowell, Lisa H.; Moran, Patrick W.; Schmidt, Travis S.; Norman, Julia E.; Nakagaki, Naomi; Shoda, Megan E.; Mahler, Barbara J.; Van Metre, Peter C.; Stone, Wesley W.; Sandstrom, Mark W.; Hladik, Michelle L.

2018-01-01

Aquatic organisms in streams are exposed to pesticide mixtures that vary in composition over time in response to changes in flow conditions, pesticide inputs to the stream, and pesticide fate and degradation within the stream. To characterize mixtures of dissolved-phase pesticides and degradates in Midwestern streams, a synoptic study was conducted at 100 streams during May–August 2013. In weekly water samples, 94 pesticides and 89 degradates were detected, with a median of 25 compounds detected per sample and 54 detected per site. In a screening-level assessment using aquatic-life benchmarks and the Pesticide Toxicity Index (PTI), potential effects on fish were unlikely in most streams. For invertebrates, potential chronic toxicity was predicted in 53% of streams, punctuated in 12% of streams by acutely toxic exposures. For aquatic plants, acute but likely reversible effects on biomass were predicted in 75% of streams, with potential longer-term effects on plant communities in 9% of streams. Relatively few pesticides in water—atrazine, acetochlor, metolachlor, imidacloprid, fipronil, organophosphate insecticides, and carbendazim—were predicted to be major contributors to potential toxicity. Agricultural streams had the highest potential for effects on plants, especially in May–June, corresponding to high spring-flush herbicide concentrations. Urban streams had higher detection frequencies and concentrations of insecticides and most fungicides than in agricultural streams, and higher potential for invertebrate toxicity, which peaked during July–August. Toxicity-screening predictions for invertebrates were supported by quantile regressions showing significant associations for the Benthic Invertebrate-PTI and imidacloprid concentrations with invertebrate community metrics for MSQA streams, and by mesocosm toxicity testing with imidacloprid showing effects on invertebrate communities at environmentally relevant concentrations. This study documents the most

[Prognostic significance of the cyclic AMP concentration in acute leukemias].

PubMed

Paietta, E; Mittermayer, K; Schwarzmeier, J D

1979-01-01

In patients with acute leukemia (myeloblastic, lymphoblastic, undifferentiated) proliferation kinetics and cyclic adenosine-3', 5'-monophosphate (cAMP) concentration of the leukemic cells were studied for their significance in the prediction of responsiveness to cytostatic therapy. Patients with good clinical response had significantly faster turnover and lower cAMP-levels than those who failed to respond to treatment.

US Intergroup Anal Carcinoma Trial: Tumor Diameter Predicts for Colostomy

PubMed Central

Ajani, Jaffer A.; Winter, Kathryn A.; Gunderson, Leonard L.; Pedersen, John; Benson, Al B.; Thomas, Charles R.; Mayer, Robert J.; Haddock, Michael G.; Rich, Tyvin A.; Willett, Christopher G.

2009-01-01

Purpose The US Gastrointestinal Intergroup Radiation Therapy Oncology Group 98-11 anal carcinoma trial showed that cisplatin-based concurrent chemoradiotherapy resulted in a significantly higher rate of colostomy compared with mitomycin-based therapy. Established prognostic variables for patients with anal carcinoma include tumor diameter, clinical nodal status, and sex, but pretreatment variables that would predict the likelihood of colostomy are unknown. Methods A secondary analysis was performed by combining patients in the two treatment arms to evaluate whether new predictive and prognostic variables would emerge. Univariate and multivariate analyses were carried out to correlate overall survival (OS), disease-free survival, and time to colostomy (TTC) with pretreatment and treatment variables. Results Of 682 patients enrolled, 644 patients were assessable and analyzed. In the multivariate analysis, tumor-related prognosticators for poorer OS included node-positive cancer (P ≤ .0001), large (> 5 cm) tumor diameter (P = .01), and male sex (P = .016). In the treatment-related categories, cisplatin-based therapy was statistically significantly associated with a higher rate of colostomy (P = .03) than was mitomycin-based therapy. In the pretreatment variables category, only large tumor diameter independently predicted for TTC (P = .008). Similarly, the cumulative 5-year colostomy rate was statistically significantly higher for large tumor diameter than for small tumor diameter (Gray's test; P = .0074). Clinical nodal status and sex were not predictive of TTC. Conclusion The combined analysis of the two arms of RTOG 98-11, representing the largest prospective database, reveals that tumor diameter (irrespective of the nodal status) is the only independent pretreatment variable that predicts TTC and 5-year colostomy rate in patients with anal carcinoma. PMID:19139424

Relevance of genetic relationship in GWAS and genomic prediction.

PubMed

Pereira, Helcio Duarte; Soriano Viana, José Marcelo; Andrade, Andréa Carla Bastos; Fonseca E Silva, Fabyano; Paes, Geísa Pinheiro

2018-02-01

The objective of this study was to analyze the relevance of relationship information on the identification of low heritability quantitative trait loci (QTLs) from a genome-wide association study (GWAS) and on the genomic prediction of complex traits in human, animal and cross-pollinating populations. The simulation-based data sets included 50 samples of 1000 individuals of seven populations derived from a common population with linkage disequilibrium. The populations had non-inbred and inbred progeny structure (50 to 200) with varying number of members (5 to 20). The individuals were genotyped for 10,000 single nucleotide polymorphisms (SNPs) and phenotyped for a quantitative trait controlled by 10 QTLs and 90 minor genes showing dominance. The SNP density was 0.1 cM and the narrow sense heritability was 25%. The QTL heritabilities ranged from 1.1 to 2.9%. We applied mixed model approaches for both GWAS and genomic prediction using pedigree-based and genomic relationship matrices. For GWAS, the observed false discovery rate was kept below the significance level of 5%, the power of detection for the low heritability QTLs ranged from 14 to 50%, and the average bias between significant SNPs and a QTL ranged from less than 0.01 to 0.23 cM. The QTL detection power was consistently higher using genomic relationship matrix. Regardless of population and training set size, genomic prediction provided higher prediction accuracy of complex trait when compared to pedigree-based prediction. The accuracy of genomic prediction when there is relatedness between individuals in the training set and the reference population is much higher than the value for unrelated individuals.

Estimating Hydraulic Parameters When Poroelastic Effects Are Significant

USGS Publications Warehouse

Berg, S.J.; Hsieh, P.A.; Illman, W.A.

2011-01-01

For almost 80 years, deformation-induced head changes caused by poroelastic effects have been observed during pumping tests in multilayered aquifer-aquitard systems. As water in the aquifer is released from compressive storage during pumping, the aquifer is deformed both in the horizontal and vertical directions. This deformation in the pumped aquifer causes deformation in the adjacent layers, resulting in changes in pore pressure that may produce drawdown curves that differ significantly from those predicted by traditional groundwater theory. Although these deformation-induced head changes have been analyzed in several studies by poroelasticity theory, there are at present no practical guidelines for the interpretation of pumping test data influenced by these effects. To investigate the impact that poroelastic effects during pumping tests have on the estimation of hydraulic parameters, we generate synthetic data for three different aquifer-aquitard settings using a poroelasticity model, and then analyze the synthetic data using type curves and parameter estimation techniques, both of which are based on traditional groundwater theory and do not account for poroelastic effects. Results show that even when poroelastic effects result in significant deformation-induced head changes, it is possible to obtain reasonable estimates of hydraulic parameters using methods based on traditional groundwater theory, as long as pumping is sufficiently long so that deformation-induced effects have largely dissipated. ?? 2011 The Author(s). Journal compilation ?? 2011 National Ground Water Association.

Aberrant GSTP1 promoter methylation predicts short-term prognosis in acute-on-chronic hepatitis B liver failure.

PubMed

Gao, S; Sun, F-K; Fan, Y-C; Shi, C-H; Zhang, Z-H; Wang, L-Y; Wang, K

2015-08-01

Glutathione-S-transferase P1 (GSTP1) methylation has been demonstrated to be associated with oxidative stress induced liver damage in acute-on-chronic hepatitis B liver failure (ACHBLF). To evaluate the methylation level of GSTP1 promoter in acute-on-chronic hepatitis B liver failure and determine its predictive value for prognosis. One hundred and five patients with acute-on-chronic hepatitis B liver failure, 86 with chronic hepatitis B (CHB) and 30 healthy controls (HC) were retrospectively enrolled. GSTP1 methylation level in peripheral mononuclear cells (PBMC) was detected by MethyLight. Clinical and laboratory parameters were obtained. GSTP1 methylation levels were significantly higher in patients with acute-on-chronic hepatitis B liver failure (median 16.84%, interquartile range 1.83-59.05%) than those with CHB (median 1.25%, interquartile range 0.48-2.47%; P < 0.01) and HC (median 0.80%, interquartile range 0.67-1.27%; P < 0.01). In acute-on-chronic hepatitis B liver failure group, nonsurvivors showed significantly higher GSTP1 methylation levels (P < 0.05) than survivors. GSTP1 methylation level was significantly correlated with total bilirubin (r = 0.29, P < 0.01), prothrombin time activity (r = -0.24, P = 0.01) and model for end-stage liver disease (MELD) score (r = 0.26, P = 0.01). When used to predict 1- or 2-month mortality of acute-on-chronic hepatitis B liver failure, GSTP1 methylation showed significantly better predictive value than MELD score [area under the receiver operating characteristic curve (AUC) 0.89 vs. 0.72, P < 0.01; AUC 0.83 vs. 0.70, P < 0.05 respectively]. Meanwhile, patients with GSTP1 methylation levels above the cut-off points showed significantly poorer survival than those below (P < 0.05). Aberrant GSTP1 promoter methylation exists in acute-on-chronic hepatitis B liver failure and shows high predictive value for short-term mortality. It might serve as a potential prognostic marker for acute-on-chronic hepatitis B liver failure

Physical Stress Echocardiography: Prediction of Mortality and Cardiac Events in Patients with Exercise Test showing Ischemia.

PubMed

Araujo, Ana Carla Pereira de; Santos, Bruno F de Oliveira; Calasans, Flavia Ricci; Pinto, Ibraim M Francisco; Oliveira, Daniel Pio de; Melo, Luiza Dantas; Andrade, Stephanie Macedo; Tavares, Irlaneide da Silva; Sousa, Antonio Carlos Sobral; Oliveira, Joselina Luzia Menezes

2014-11-01

Background: Studies have demonstrated the diagnostic accuracy and prognostic value of physical stress echocardiography in coronary artery disease. However, the prediction of mortality and major cardiac events in patients with exercise test positive for myocardial ischemia is limited. Objective: To evaluate the effectiveness of physical stress echocardiography in the prediction of mortality and major cardiac events in patients with exercise test positive for myocardial ischemia. Methods: This is a retrospective cohort in which 866 consecutive patients with exercise test positive for myocardial ischemia, and who underwent physical stress echocardiography were studied. Patients were divided into two groups: with physical stress echocardiography negative (G1) or positive (G2) for myocardial ischemia. The endpoints analyzed were all-cause mortality and major cardiac events, defined as cardiac death and non-fatal acute myocardial infarction. Results: G2 comprised 205 patients (23.7%). During the mean 85.6 ± 15.0-month follow-up, there were 26 deaths, of which six were cardiac deaths, and 25 non-fatal myocardial infarction cases. The independent predictors of mortality were: age, diabetes mellitus, and positive physical stress echocardiography (hazard ratio: 2.69; 95% confidence interval: 1.20 - 6.01; p = 0.016). The independent predictors of major cardiac events were: age, previous coronary artery disease, positive physical stress echocardiography (hazard ratio: 2.75; 95% confidence interval: 1.15 - 6.53; p = 0.022) and absence of a 10% increase in ejection fraction. All-cause mortality and the incidence of major cardiac events were significantly higher in G2 (p < 0. 001 and p = 0.001, respectively). Conclusion: Physical stress echocardiography provides additional prognostic information in patients with exercise test positive for myocardial ischemia.Fundamento: Estudos têm demonstrado a acurácia diagnóstica e o valor prognóstico da ecocardiografia com estresse f

Multipolar Electrostatic Energy Prediction for all 20 Natural Amino Acids Using Kriging Machine Learning.

PubMed

Fletcher, Timothy L; Popelier, Paul L A

2016-06-14

A machine learning method called kriging is applied to the set of all 20 naturally occurring amino acids. Kriging models are built that predict electrostatic multipole moments for all topological atoms in any amino acid based on molecular geometry only. These models then predict molecular electrostatic interaction energies. On the basis of 200 unseen test geometries for each amino acid, no amino acid shows a mean prediction error above 5.3 kJ mol(-1), while the lowest error observed is 2.8 kJ mol(-1). The mean error across the entire set is only 4.2 kJ mol(-1) (or 1 kcal mol(-1)). Charged systems are created by protonating or deprotonating selected amino acids, and these show no significant deviation in prediction error over their neutral counterparts. Similarly, the proposed methodology can also handle amino acids with aromatic side chains, without the need for modification. Thus, we present a generic method capable of accurately capturing multipolar polarizable electrostatics in amino acids.

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

Revising the predictions of inflation for the cosmic microwave background anisotropies.

PubMed

Agulló, Iván; Navarro-Salas, José; Olmo, Gonzalo J; Parker, Leonard

2009-08-07

We point out that, if quantum field renormalization is taken into account and the counterterms are evaluated at the Hubble-radius crossing time or few e-foldings after it, the predictions of slow-roll inflation for both the scalar and the tensorial power spectrum change significantly. This leads to a change in the consistency condition that relates the tensor-to-scalar amplitude ratio with spectral indices. A reexamination of the potentials varphi;{2} and varphi;{4} shows that both are compatible with five-year WMAP data. Only when the counterterms are evaluated at much larger times beyond the end of inflation does one recover the standard predictions. The alternative predictions presented here may soon come within the range of measurement of near-future experiments.

United States Marine Corps Career Designation Board: Significant Factors in Predicting Selection

DTIC Science & Technology

2014-03-01

estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services...Advisor Dina Shatnawi Second Reader William Gates Dean, Graduate School of Business and Public Policy iv THIS PAGE INTENTIONALLY...but also do it in a way that would be easiest for me to use. Doreen assisted in extracting the necessary FITREP data, which added significant value

Encoding of Vicarious Reward Prediction in Anterior Cingulate Cortex and Relationship with Trait Empathy

PubMed Central

Apps, Matthew A.J.; Roiser, Jonathan P.; Viding, Essi

2015-01-01

Empathy—the capacity to understand and resonate with the experiences of others—can depend on the ability to predict when others are likely to receive rewards. However, although a plethora of research has examined the neural basis of predictions about the likelihood of receiving rewards ourselves, very little is known about the mechanisms that underpin variability in vicarious reward prediction. Human neuroimaging and nonhuman primate studies suggest that a subregion of the anterior cingulate cortex in the gyrus (ACCg) is engaged when others receive rewards. Does the ACCg show specialization for processing predictions about others' rewards and not one's own and does this specialization vary with empathic abilities? We examined hemodynamic responses in the human brain time-locked to cues that were predictive of a high or low probability of a reward either for the subject themselves or another person. We found that the ACCg robustly signaled the likelihood of a reward being delivered to another. In addition, ACCg response significantly covaried with trait emotion contagion, a necessary foundation for empathizing with other individuals. In individuals high in emotion contagion, the ACCg was specialized for processing others' rewards exclusively, but for those low in emotion contagion, this region also responded to information about the subject's own rewards. Our results are the first to show that the ACCg signals probabilistic predictions about rewards for other people and that the substantial individual variability in the degree to which the ACCg is specialized for processing others' rewards is related to trait empathy. SIGNIFICANCE STATEMENT Successfully cooperating, competing, or empathizing with others can depend on our ability to predict when others are going to get something rewarding. Although many studies have examined how the brain processes rewards we will get ourselves, very little is known about vicarious reward processing. Here, we show that a

Validation of High Frequency (HF) Propagation Prediction Models in the Arctic region

NASA Astrophysics Data System (ADS)

Athieno, R.; Jayachandran, P. T.

2014-12-01

Despite the emergence of modern techniques for long distance communication, Ionospheric communication in the high frequency (HF) band (3-30 MHz) remains significant to both civilian and military users. However, the efficient use of the ever-varying ionosphere as a propagation medium is dependent on the reliability of ionospheric and HF propagation prediction models. Most available models are empirical implying that data collection has to be sufficiently large to provide good intended results. The models we present were developed with little data from the high latitudes which necessitates their validation. This paper presents the validation of three long term High Frequency (HF) propagation prediction models over a path within the Arctic region. Measurements of the Maximum Usable Frequency for a 3000 km range (MUF (3000) F2) for Resolute, Canada (74.75° N, 265.00° E), are obtained from hand-scaled ionograms generated by the Canadian Advanced Digital Ionosonde (CADI). The observations have been compared with predictions obtained from the Ionospheric Communication Enhanced Profile Analysis Program (ICEPAC), Voice of America Coverage Analysis Program (VOACAP) and International Telecommunication Union Recommendation 533 (ITU-REC533) for 2009, 2011, 2012 and 2013. A statistical analysis shows that the monthly predictions seem to reproduce the general features of the observations throughout the year though it is more evident in the winter and equinox months. Both predictions and observations show a diurnal and seasonal variation. The analysed models did not show large differences in their performances. However, there are noticeable differences across seasons for the entire period analysed: REC533 gives a better performance in winter months while VOACAP has a better performance for both equinox and summer months. VOACAP gives a better performance in the daily predictions compared to ICEPAC though, in general, the monthly predictions seem to agree more with the

Near Real-Time Optimal Prediction of Adverse Events in Aviation Data

NASA Technical Reports Server (NTRS)

Martin, Rodney Alexander; Das, Santanu

2010-01-01

The prediction of anomalies or adverse events is a challenging task, and there are a variety of methods which can be used to address the problem. In this paper, we demonstrate how to recast the anomaly prediction problem into a form whose solution is accessible as a level-crossing prediction problem. The level-crossing prediction problem has an elegant, optimal, yet untested solution under certain technical constraints, and only when the appropriate modeling assumptions are made. As such, we will thoroughly investigate the resilience of these modeling assumptions, and show how they affect final performance. Finally, the predictive capability of this method will be assessed by quantitative means, using both validation and test data containing anomalies or adverse events from real aviation data sets that have previously been identified as operationally significant by domain experts. It will be shown that the formulation proposed yields a lower false alarm rate on average than competing methods based on similarly advanced concepts, and a higher correct detection rate than a standard method based upon exceedances that is commonly used for prediction.

Measuring and Predicting Tag Importance for Image Retrieval.

PubMed

Li, Shangwen; Purushotham, Sanjay; Chen, Chen; Ren, Yuzhuo; Kuo, C-C Jay

2017-12-01

Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual modalities during MIR training. This will further lead to degenerated retrieval performance at query time. To address this issue, we investigate the problem of tag importance prediction, where the goal is to automatically predict the tag importance and use it in image retrieval. To achieve this, we first propose a method to measure the relative importance of object and scene tags from image sentence descriptions. Using this as the ground truth, we present a tag importance prediction model to jointly exploit visual, semantic and context cues. The Structural Support Vector Machine (SSVM) formulation is adopted to ensure efficient training of the prediction model. Then, the Canonical Correlation Analysis (CCA) is employed to learn the relation between the image visual feature and tag importance to obtain robust retrieval performance. Experimental results on three real-world datasets show a significant performance improvement of the proposed MIR with Tag Importance Prediction (MIR/TIP) system over other MIR systems.

Does dissociation of emotional and physiological reactivity predict blood pressure change at 3- and 10-year follow-up?

PubMed

Levin, Anna Y; Linden, Wolfgang

2008-02-01

One of the major theories of psychosomatic medicine is that pervasive dissociations between physiological reactivity and simultaneous emotion awareness may be an important marker for the long-term development of cardiac problems. Subjective autonomic discrepancy (SAD) scores are proposed as a method of capturing the dissociation between physiological and emotional reactivity and increasing the explanatory power of predictive models of cardiac health outcomes. It was found that SAD scores for blood pressure indices show trait-like stability over a period of 3 years. Although linear 3-year prediction of systolic blood pressure came close to traditional definitions of significance, neither a linear nor a quadratic model was found to show significant prospective validity in predicting ambulatory blood pressure change over a 10-year period. Dissociation between physiological arousal and emotional awareness does not appear to be an important variable in the identification of individuals at risk for later cardiovascular health problems.

An Intercomparison of Lidar Ozone and Temperature Measurements From the SOLVE Mission With Predicted Model Values

NASA Technical Reports Server (NTRS)

Burris, John; McGee, Thomas J.; Hoegy, Walt; Lait, Leslie; Sumnicht, Grant; Twigg, Larry; Heaps, William

2000-01-01

Temperature profiles acquired by Goddard Space Flight Center's AROTEL lidar during the SOLVE mission onboard NASA's DC-8 are compared with predicted values from several atmospheric models (DAO, NCEP and UKMO). The variability in the differences between measured and calculated temperature fields was approximately 5 K. Retrieved temperatures within the polar vortex showed large regions that were significantly colder than predicted by the atmospheric models.

Validated predictive modelling of the environmental resistome

PubMed Central

Amos, Gregory CA; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

2015-01-01

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome. PMID:25679532

Validated predictive modelling of the environmental resistome.

PubMed

Amos, Gregory C A; Gozzard, Emma; Carter, Charlotte E; Mead, Andrew; Bowes, Mike J; Hawkey, Peter M; Zhang, Lihong; Singer, Andrew C; Gaze, William H; Wellington, Elizabeth M H

2015-06-01

Multi-drug-resistant bacteria pose a significant threat to public health. The role of the environment in the overall rise in antibiotic-resistant infections and risk to humans is largely unknown. This study aimed to evaluate drivers of antibiotic-resistance levels across the River Thames catchment, model key biotic, spatial and chemical variables and produce predictive models for future risk assessment. Sediment samples from 13 sites across the River Thames basin were taken at four time points across 2011 and 2012. Samples were analysed for class 1 integron prevalence and enumeration of third-generation cephalosporin-resistant bacteria. Class 1 integron prevalence was validated as a molecular marker of antibiotic resistance; levels of resistance showed significant geospatial and temporal variation. The main explanatory variables of resistance levels at each sample site were the number, proximity, size and type of surrounding wastewater-treatment plants. Model 1 revealed treatment plants accounted for 49.5% of the variance in resistance levels. Other contributing factors were extent of different surrounding land cover types (for example, Neutral Grassland), temporal patterns and prior rainfall; when modelling all variables the resulting model (Model 2) could explain 82.9% of variations in resistance levels in the whole catchment. Chemical analyses correlated with key indicators of treatment plant effluent and a model (Model 3) was generated based on water quality parameters (contaminant and macro- and micro-nutrient levels). Model 2 was beta tested on independent sites and explained over 78% of the variation in integron prevalence showing a significant predictive ability. We believe all models in this study are highly useful tools for informing and prioritising mitigation strategies to reduce the environmental resistome.

Improved MEGAN predictions of biogenic isoprene in the contiguous United States

NASA Astrophysics Data System (ADS)

Wang, Peng; Schade, Gunnar; Estes, Mark; Ying, Qi

2017-01-01

Isoprene emitted from biogenic sources significantly contributes to ozone and secondary organic aerosol formation in the troposphere. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) has been widely used to estimate isoprene emissions from local to global scales. However, previous studies have shown that MEGAN significantly over-predicts isoprene emissions in the contiguous United States (US). In this study, ambient isoprene concentrations in the US were simulated by the Community Multiscale Air Quality (CMAQ) model (v5.0.1) using biogenic emissions estimated by MEGAN v2.10 with several different gridded isoprene emission factor (EF) fields. Best isoprene predictions were obtained with the EF field based on the Biogenic Emissions Landcover Database v4 (BELD4) from US EPA for its Biogenic Emission Inventory System (BEIS) model v3.61 (MEGAN-BEIS361). A seven-month simulation (April to October 2011) of isoprene emissions with MEGAN-BEIS361 and ambient concentrations using CMAQ shows that observed spatial and temporal variations (both diurnal and seasonal) of isoprene concentrations can be well predicted at most non-urban monitors using isoprene emission estimation from the MEGAN-BEIS361 without significant biases. The predicted monthly average vertical column density of formaldehyde (HCHO), a reactive volatile organic compound with significant contributions from isoprene oxidation, generally agree with the spatial distribution of HCHO column density derived using satellite data collected by the Ozone Monitoring Instrument (OMI), although summer month vertical column densities in the southeast US were overestimated, which suggests that isoprene emission might still be overestimated in that region. The agreement between observation and prediction may be further improved if more accurate PAR values, such as those derived from satellite-based observations, were used in modeling the biogenic emissions.

Ecological and evolutionary significance of genomic GC content diversity in monocots

PubMed Central

Šmarda, Petr; Bureš, Petr; Horová, Lucie; Leitch, Ilia J.; Mucina, Ladislav; Pacini, Ettore; Tichý, Lubomír; Grulich, Vít; Rotreklová, Olga

2014-01-01

Genomic DNA base composition (GC content) is predicted to significantly affect genome functioning and species ecology. Although several hypotheses have been put forward to address the biological impact of GC content variation in microbial and vertebrate organisms, the biological significance of GC content diversity in plants remains unclear because of a lack of sufficiently robust genomic data. Using flow cytometry, we report genomic GC contents for 239 species representing 70 of 78 monocot families and compare them with genomic characters, a suite of life history traits and climatic niche data using phylogeny-based statistics. GC content of monocots varied between 33.6% and 48.9%, with several groups exceeding the GC content known for any other vascular plant group, highlighting their unusual genome architecture and organization. GC content showed a quadratic relationship with genome size, with the decreases in GC content in larger genomes possibly being a consequence of the higher biochemical costs of GC base synthesis. Dramatic decreases in GC content were observed in species with holocentric chromosomes, whereas increased GC content was documented in species able to grow in seasonally cold and/or dry climates, possibly indicating an advantage of GC-rich DNA during cell freezing and desiccation. We also show that genomic adaptations associated with changing GC content might have played a significant role in the evolution of the Earth’s contemporary biota, such as the rise of grass-dominated biomes during the mid-Tertiary. One of the major selective advantages of GC-rich DNA is hypothesized to be facilitating more complex gene regulation. PMID:25225383

Effects of Stressor Predictability and Controllability on Sleep, Temperature, and Fear Behavior in Mice

PubMed Central

Yang, Linghui; Wellman, Laurie L.; Ambrozewicz, Marta A.; Sanford, Larry D.

2011-01-01

Study Objectives: Predictability and controllability are important factors in the persisting effects of stress. We trained mice with signaled, escapable shock (SES) and with signaled, inescapable shock (SIS) to determine whether shock predictability can be a significant factor in the effects of stress on sleep. Design: Male BALB/cJ mice were implanted with transmitters for recording EEG, activity, and temperature via telemetry. After recovery from surgery, baseline sleep recordings were obtained for 2 days. The mice were then randomly assigned to SES (n = 9) and yoked SIS (n = 9) conditions. The mice were presented cues (90 dB, 2 kHz tones) that started 5.0 sec prior to and co-terminated with footshocks (0.5 mA; 5.0 sec maximum duration). SES mice always received shock but could terminate it by moving to the non-occupied chamber in a shuttlebox. SIS mice received identical tones and shocks, but could not alter shock duration. Twenty cue-shock pairings (1.0-min interstimulus intervals) were presented on 2 days (ST1 and ST2). Seven days after ST2, SES and SIS mice, in their home cages, were presented with cues identical to those presented during ST1 and ST2. Setting: NA. Patients or Participants: NA. Interventions: NA. Measurements and Results: On each training and test day, EEG, activity and temperature were recorded for 20 hours. Freezing was scored in response to the cue alone. Compared to SIS mice, SES mice showed significantly increased REM after ST1 and ST2. Compared to SES mice, SIS mice showed significantly increased NREM after ST1 and ST2. Both groups showed reduced REM in response to cue presentation alone. Both groups showed similar stress-induced increases in temperature and freezing in response to the cue alone. Conclusions: These findings indicate that predictability (modeled by signaled shock) can play a significant role in the effects of stress on sleep. Citation: Yang L; Wellman LL; Ambrozewicz MA; Sanford LD. Effects of stressor predictability and

Lymphatic invasion and the Shields index in predicting melanoma metastases.

PubMed

Špirić, Zorica; Erić, Mirela; Eri, Živka

2017-11-01

Findings of the prognostic significance of lymphatic invasion are contradictory. To determine an as efficient cutaneous melanoma metastasis predictor as possible, Shields et al. created a new prognostic index. This study aimed to examine whether the lymphatic invasion analysis and the Shields index calculation can be used in predicting lymph node status in patients with cutaneous melanoma. Lymphatic invasion of 100 melanoma specimens was detected by dual immunohistochemistry staining for the lymphatic endothelial marker D2-40 and melanoma cell S-100 protein. The Shields index was calculated as a logarithm by multiplying the melanoma thickness, square of peritumoural lymphatic vessel density and the number "2" for the present lymphatic invasion. No statistically significant difference was observed between lymph node metastatic and nonmetastatic melanomas regarding the lymphatic invasion. Metastatic melanomas showed a significantly higher Shields index value than nonmetastatic melanomas (p = 0.00). Area under the receiver operator characteristic (ROC) curve (AUC) proved that the Shields index (AUC = 0.86, 95% confidence interval (CI) 0.79-0.93, p = 0.00) was the most accurate predictor of lymph node status, followed by the melanoma thickness (AUC = 0.76, 95% CI 0.67-0.86, p = 0.00) and American Joint Committee on Cancer (AJCC) staging (AUC = 0.75, 95% CI 0.66-0.85, p = 0.00), while lymphatic invasion was not successful in predicting (AUC = 0.56, 95% CI 0.45-0.67, p = 0.31). The Shields index achieved 81.3% sensitivity and 75% specificity (cut-off mean value). Our findings show that D2-40/S-100 immunohistochemical analysis of lymphatic invasion cannot be used for predicting the lymph node status, while the Shields index calculation predicts disease outcome more accurately than the melanoma thickness and AJCC staging. Copyright © 2017 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights

Hepatobiliary Clearance Prediction: Species Scaling From Monkey, Dog, and Rat, and In Vitro-In Vivo Extrapolation of Sandwich-Cultured Human Hepatocytes Using 17 Drugs.

PubMed

Kimoto, Emi; Bi, Yi-An; Kosa, Rachel E; Tremaine, Larry M; Varma, Manthena V S

2017-09-01

Hepatobiliary elimination can be a major clearance pathway dictating the pharmacokinetics of drugs. Here, we first compared the dose eliminated in bile in preclinical species (monkey, dog, and rat) with that in human and further evaluated single-species scaling (SSS) to predict human hepatobiliary clearance. Six compounds dosed in bile duct-cannulated (BDC) monkeys showed biliary excretion comparable to human; and the SSS of hepatobiliary clearance with plasma fraction unbound correction yielded reasonable predictions (within 3-fold). Although dog SSS also showed reasonable predictions, rat overpredicted hepatobiliary clearance for 13 of 24 compounds. Second, we evaluated the translatability of in vitro sandwich-cultured human hepatocytes (SCHHs) to predict human hepatobiliary clearance for 17 drugs. For drugs with no significant active uptake in SCHH studies (i.e., with or without rifamycin SV), measured intrinsic biliary clearance was directly scalable with good predictability (absolute average fold error [AAFE] = 1.6). Drugs showing significant active uptake in SCHH, however, showed improved predictability when scaled based on extended clearance term (AAFE = 2.0), which incorporated sinusoidal uptake along with a global scaling factor for active uptake and the canalicular efflux clearance. In conclusion, SCHH is a useful tool to predict human hepatobiliary clearance, whereas BDC monkey model may provide further confidence in the prospective predictions. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

The frequency and significance of WT-1 expression in serous endometrial carcinoma.

PubMed

Hedley, Catherine; Sriraksa, Ruethairat; Showeil, Rania; Van Noorden, Susan; El-Bahrawy, Mona

2014-09-01

Serous endometrial carcinoma is an aggressive type of endometrial carcinoma. Wilms tumor gene 1 (WT-1) is commonly expressed in ovarian serous carcinomas and considered a diagnostic marker of these tumors. However, it is generally believed that WT-1 is rarely expressed by endometrial serous carcinoma. The aim of this study was to evaluate the frequency and significance of WT-1 expression in endometrial serous carcinoma. We studied the expression of WT-1 in formalin-fixed, paraffin-embedded tumor sections from 77 cases of endometrial serous carcinoma. Thirty-four tumors showed positive expression for WT-1 (44%). There was a statistically significant association between the presence of WT-1 expression and disease-free survival (DFS), where patients with tumors expressing WT-1 had a shorter DFS compared with those with no WT-1 expression (P = .031; median DFS, 15 and 38 months, respectively). By multivariate Cox regression analysis, DFS was independent from other clinicopathological data (tumor stage, presence of lymphovascular space invasion, cervical involvement, and extrauterine spread), indicating that WT-1 expression is independently associated with DFS. Our study shows that WT-1 is expressed in a considerable percentage of endometrial serous carcinomas, suggesting a role for WT-1 in the pathology of these tumors. This has therapeutic significance, as WT-1 is an emerging target for immunotherapy. Moreover, our results show that WT-1 has prognostic value, being predictive of DFS. As a potential prognostic marker and therapeutic target, we recommend that WT-1 expression should be included in histopathologic reports of endometrial serous carcinoma. Copyright © 2014 Elsevier Inc. All rights reserved.

Small artery elasticity predicts future cardiovascular events in chinese patients with angiographic coronary artery disease.

PubMed

Wan, Zhaofei; Liu, Xiaojun; Wang, Xinhong; Liu, Fuqiang; Liu, Weimin; Wu, Yue; Pei, Leilei; Yuan, Zuyi

2014-04-01

Arterial elasticity has been shown to predict cardiovascular disease (CVD) in apparently healthy populations. The present study aimed to explore whether arterial elasticity could predict CVD events in Chinese patients with angiographic coronary artery disease (CAD). Arterial elasticity of 365 patients with angiographic CAD was measured. During follow-up (48 months; range 6-65), 140 CVD events occurred (including 34 deaths). Univariate Cox analysis demonstrated that both large arterial elasticity and small arterial elasticity were significant predictors of CVD events. Multivariate Cox analysis indicated that small arterial elasticity remained significant. Kaplan-Meier analysis showed that the probability of having a CVD event/CVD death increased with a decrease of small arterial elasticity (P < .001, respectively). Decreased small arterial elasticity independently predicts the risk of CVD events in Chinese patients with angiographic CAD.

Network traffic anomaly prediction using Artificial Neural Network

NASA Astrophysics Data System (ADS)

Ciptaningtyas, Hening Titi; Fatichah, Chastine; Sabila, Altea

2017-03-01

As the excessive increase of internet usage, the malicious software (malware) has also increase significantly. Malware is software developed by hacker for illegal purpose(s), such as stealing data and identity, causing computer damage, or denying service to other user[1]. Malware which attack computer or server often triggers network traffic anomaly phenomena. Based on Sophos's report[2], Indonesia is the riskiest country of malware attack and it also has high network traffic anomaly. This research uses Artificial Neural Network (ANN) to predict network traffic anomaly based on malware attack in Indonesia which is recorded by Id-SIRTII/CC (Indonesia Security Incident Response Team on Internet Infrastructure/Coordination Center). The case study is the highest malware attack (SQL injection) which has happened in three consecutive years: 2012, 2013, and 2014[4]. The data series is preprocessed first, then the network traffic anomaly is predicted using Artificial Neural Network and using two weight update algorithms: Gradient Descent and Momentum. Error of prediction is calculated using Mean Squared Error (MSE) [7]. The experimental result shows that MSE for SQL Injection is 0.03856. So, this approach can be used to predict network traffic anomaly.

Executive Functions Predict the Success of Top-Soccer Players

PubMed Central

Vestberg, Torbjörn; Gustafson, Roland; Maurex, Liselotte; Ingvar, Martin; Petrovic, Predrag

2012-01-01

While the importance of physical abilities and motor coordination is non-contested in sport, more focus has recently been turned toward cognitive processes important for different sports. However, this line of studies has often investigated sport-specific cognitive traits, while few studies have focused on general cognitive traits. We explored if measures of general executive functions can predict the success of a soccer player. The present study used standardized neuropsychological assessment tools assessing players' general executive functions including on-line multi-processing such as creativity, response inhibition, and cognitive flexibility. In a first cross-sectional part of the study we compared the results between High Division players (HD), Lower Division players (LD) and a standardized norm group. The result shows that both HD and LD players had significantly better measures of executive functions in comparison to the norm group for both men and women. Moreover, the HD players outperformed the LD players in these tests. In the second prospective part of the study, a partial correlation test showed a significant correlation between the result from the executive test and the numbers of goals and assists the players had scored two seasons later. The results from this study strongly suggest that results in cognitive function tests predict the success of ball sport players. PMID:22496850

Efficacy of the Supports Intensity Scale (SIS) to Predict Extraordinary Support Needs

ERIC Educational Resources Information Center

Wehmeyer, Michael; Chapman, Theodore E.; Little, Todd D.; Thompson, James R.; Schalock, Robert; Tasse, Marc J.

2009-01-01

Data were collected on 274 adults to investigate the efficacy of the Supports Intensity Scale (SIS) as a tool to measure the support needs of individuals with intellectual and related developmental disabilities. Findings showed that SIS scores contributed significantly to a model that predicted greater levels of support need. Moreover, scores from…

Earthquake prediction analysis based on empirical seismic rate: the M8 algorithm

NASA Astrophysics Data System (ADS)

Molchan, G.; Romashkova, L.

2010-12-01

The quality of space-time earthquake prediction is usually characterized by a 2-D error diagram (n, τ), where n is the fraction of failures-to-predict and τ is the local rate of alarm averaged in space. The most reasonable averaging measure for analysis of a prediction strategy is the normalized rate of target events λ(dg) in a subarea dg. In that case the quantity H = 1 - (n + τ) determines the prediction capability of the strategy. The uncertainty of λ(dg) causes difficulties in estimating H and the statistical significance, α, of prediction results. We investigate this problem theoretically and show how the uncertainty of the measure can be taken into account in two situations, viz., the estimation of α and the construction of a confidence zone for the (n, τ)-parameters of the random strategies. We use our approach to analyse the results from prediction of M >= 8.0 events by the M8 method for the period 1985-2009 (the M8.0+ test). The model of λ(dg) based on the events Mw >= 5.5, 1977-2004, and the magnitude range of target events 8.0 <= M < 8.5 are considered as basic to this M8 analysis. We find the point and upper estimates of α and show that they are still unstable because the number of target events in the experiment is small. However, our results argue in favour of non-triviality of the M8 prediction algorithm.

Weighted Feature Significance: A Simple, Interpretable Model of Compound Toxicity Based on the Statistical Enrichment of Structural Features

PubMed Central

Huang, Ruili; Southall, Noel; Xia, Menghang; Cho, Ming-Hsuang; Jadhav, Ajit; Nguyen, Dac-Trung; Inglese, James; Tice, Raymond R.; Austin, Christopher P.

2009-01-01

In support of the U.S. Tox21 program, we have developed a simple and chemically intuitive model we call weighted feature significance (WFS) to predict the toxicological activity of compounds, based on the statistical enrichment of structural features in toxic compounds. We trained and tested the model on the following: (1) data from quantitative high–throughput screening cytotoxicity and caspase activation assays conducted at the National Institutes of Health Chemical Genomics Center, (2) data from Salmonella typhimurium reverse mutagenicity assays conducted by the U.S. National Toxicology Program, and (3) hepatotoxicity data published in the Registry of Toxic Effects of Chemical Substances. Enrichments of structural features in toxic compounds are evaluated for their statistical significance and compiled into a simple additive model of toxicity and then used to score new compounds for potential toxicity. The predictive power of the model for cytotoxicity was validated using an independent set of compounds from the U.S. Environmental Protection Agency tested also at the National Institutes of Health Chemical Genomics Center. We compared the performance of our WFS approach with classical classification methods such as Naive Bayesian clustering and support vector machines. In most test cases, WFS showed similar or slightly better predictive power, especially in the prediction of hepatotoxic compounds, where WFS appeared to have the best performance among the three methods. The new algorithm has the important advantages of simplicity, power, interpretability, and ease of implementation. PMID:19805409

The cortisol awakening response predicts major depression: predictive stability over a 4-year follow-up and effect of depression history.

PubMed

Vrshek-Schallhorn, S; Doane, L D; Mineka, S; Zinbarg, R E; Craske, M G; Adam, E K

2013-03-01

The cortisol awakening response (CAR) has been shown to predict major depressive episodes (MDEs) over a 1-year period. It is unknown whether this effect: (a) is stable over longer periods of time; (b) is independent of prospective stressful life events; and (c) differentially predicts first onsets or recurrences of MDEs. A total of 270 older adolescents (mean age 17.06 years at cortisol measurement) from the larger prospective Northwestern-UCLA Youth Emotion Project completed baseline diagnostic and life stress interviews, questionnaires, and a 3-day cortisol sampling protocol measuring the CAR and diurnal rhythm, as well as up to four annual follow-up interviews of diagnoses and life stress. Non-proportional person-month survival analyses revealed that higher levels of the baseline CAR significantly predict MDEs for 2.5 years following cortisol measurement. However, the strength of prediction of depressive episodes significantly decays over time, with the CAR no longer significantly predicting MDEs after 2.5 years. Elevations in the CAR did not significantly increase vulnerability to prospective major stressful life events. They did, however, predict MDE recurrences more strongly than first onsets. These results suggest that a high CAR represents a time-limited risk factor for onsets of MDEs, which increases risk for depression independently of future major stressful life events. Possible explanations for the stronger effect of the CAR for predicting MDE recurrences than first onsets are discussed.

Predictable patterns of the May-June rainfall anomaly over East Asia

NASA Astrophysics Data System (ADS)

Xing, Wen; Wang, Bin; Yim, So-Young; Ha, Kyung-Ja

2017-02-01

During early summer (May-June, MJ), East Asia (EA) subtropical front is a defining feature of Asian monsoon, which produces the most prominent precipitation band in the global subtropics. Here we show that dynamical prediction of early summer EA (20°N-45°N, 100°E-130°E) rainfall made by four coupled climate models' ensemble hindcast (1979-2010) yields only a moderate skill and cannot be used to estimate predictability. The present study uses an alternative, empirical orthogonal function (EOF)-based physical-empirical (P-E) model approach to predict rainfall anomaly pattern and estimate its potential predictability. The first three leading modes are physically meaningful and can be, respectively, attributed to (a) the interaction between the anomalous western North Pacific subtropical high and underlying Indo-Pacific warm ocean, (b) the forcing associated with North Pacific sea surface temperature (SST) anomaly, and (c) the development of equatorial central Pacific SST anomalies. A suite of P-E models is established to forecast the first three leading principal components. All predictors are 0 month ahead of May, so the prediction here is named as a 0 month lead prediction. The cross-validated hindcast results demonstrate that these modes may be predicted with significant temporal correlation skills (0.48-0.72). Using the predicted principal components and the corresponding EOF patterns, the total MJ rainfall anomaly was hindcasted for the period of 1979-2015. The time-mean pattern correlation coefficient (PCC) score reaches 0.38, which is significantly higher than dynamical models' multimodel ensemble skill (0.21). The estimated potential maximum attainable PCC is around 0.65, suggesting that the dynamical prediction models may have large rooms to improve. Limitations and future work are discussed.

Model to predict hyperbilirubinemia in healthy term and near-term newborns with exclusive breast feeding.

PubMed

Huang, Hsin-Chung; Yang, Hwai-I; Chang, Yu-Hsun; Chang, Rui-Jane; Chen, Mei-Huei; Chen, Chien-Yi; Chou, Hung-Chieh; Hsieh, Wu-Shiun; Tsao, Po-Nien

2012-12-01

The aim of this study was to identify high-risk newborns who will subsequently develop significant hyperbilirubinemia Days 4 to 10 of life by using the clinical data from the first three days of life. We retrospectively collected exclusively breastfeeding healthy term and near-term newborns born in our nursery between May 1, 2002, to June 30, 2005. Clinical data, including serum bilirubin were collected and the significant predictors were identified. Bilirubin level ≥15mg/dL during Days 4 to 10 of life was defined as significant hyperbilirubinemia. A prediction model to predict subsequent hyperbilirubinemia was established. This model was externally validated in another group of newborns who were enrolled by the same criteria to test its discrimination capability. Totally, 1979 neonates were collected and 1208 cases were excluded by our exclusion criteria. Finally, 771 newborns were enrolled and 182 (23.6%) cases developed significant hyperbilirubinemia during Days 4 to 10 of life. In the logistic regression analysis, gestational age, maximal body weight loss percentage, and peak bilirubin level during the first 72 hours of life were significantly associated with subsequent hyperbilirubinemia. A prediction model was derived with the area under receiver operating characteristic (AUROC) curve of 0.788. Model validation in the separate study (N = 209) showed similar discrimination capability (AUROC = 0.8340). Gestational age, maximal body weight loss percentage, and peak serum bilirubin level during the first 3 days of life have highest predictive value of subsequent significant hyperbilirubinemia. We provide a good model to predict the risk of subsequent significant hyperbilirubinemia. Copyright © 2012. Published by Elsevier B.V.

Biomarkers improve mortality prediction by prognostic scales in community-acquired pneumonia.

PubMed

Menéndez, R; Martínez, R; Reyes, S; Mensa, J; Filella, X; Marcos, M A; Martínez, A; Esquinas, C; Ramirez, P; Torres, A

2009-07-01

Prognostic scales provide a useful tool to predict mortality in community-acquired pneumonia (CAP). However, the inflammatory response of the host, crucial in resolution and outcome, is not included in the prognostic scales. The aim of this study was to investigate whether information about the initial inflammatory cytokine profile and markers increases the accuracy of prognostic scales to predict 30-day mortality. To this aim, a prospective cohort study in two tertiary care hospitals was designed. Procalcitonin (PCT), C-reactive protein (CRP) and the systemic cytokines tumour necrosis factor alpha (TNFalpha) and interleukins IL6, IL8 and IL10 were measured at admission. Initial severity was assessed by PSI (Pneumonia Severity Index), CURB65 (Confusion, Urea nitrogen, Respiratory rate, Blood pressure, > or = 65 years of age) and CRB65 (Confusion, Respiratory rate, Blood pressure, > or = 65 years of age) scales. A total of 453 hospitalised CAP patients were included. The 36 patients who died (7.8%) had significantly increased levels of IL6, IL8, PCT and CRP. In regression logistic analyses, high levels of CRP and IL6 showed an independent predictive value for predicting 30-day mortality, after adjustment for prognostic scales. Adding CRP to PSI significantly increased the area under the receiver operating characteristic curve (AUC) from 0.80 to 0.85, that of CURB65 from 0.82 to 0.85 and that of CRB65 from 0.79 to 0.85. Adding IL6 or PCT values to CRP did not significantly increase the AUC of any scale. When using two scales (PSI and CURB65/CRB65) and CRP simultaneously the AUC was 0.88. Adding CRP levels to PSI, CURB65 and CRB65 scales improves the 30-day mortality prediction. The highest predictive value is reached with a combination of two scales and CRP. Further validation of that improvement is needed.

Reliability of windstorm predictions in the ECMWF ensemble prediction system

NASA Astrophysics Data System (ADS)

Becker, Nico; Ulbrich, Uwe

2016-04-01

Windstorms caused by extratropical cyclones are one of the most dangerous natural hazards in the European region. Therefore, reliable predictions of such storm events are needed. Case studies have shown that ensemble prediction systems (EPS) are able to provide useful information about windstorms between two and five days prior to the event. In this work, ensemble predictions with the European Centre for Medium-Range Weather Forecasts (ECMWF) EPS are evaluated in a four year period. Within the 50 ensemble members, which are initialized every 12 hours and are run for 10 days, windstorms are identified and tracked in time and space. By using a clustering approach, different predictions of the same storm are identified in the different ensemble members and compared to reanalysis data. The occurrence probability of the predicted storms is estimated by fitting a bivariate normal distribution to the storm track positions. Our results show, for example, that predicted storm clusters with occurrence probabilities of more than 50% have a matching observed storm in 80% of all cases at a lead time of two days. The predicted occurrence probabilities are reliable up to 3 days lead time. At longer lead times the occurrence probabilities are overestimated by the EPS.

The Arctic Predictability and Prediction on Seasonal-to-Interannual TimEscales (APPOSITE) data set

NASA Astrophysics Data System (ADS)

Day, J. J.; Tietsche, S.; Collins, M.; Goessling, H. F.; Guemas, V.; Guillory, A.; Hurlin, W. J.; Ishii, M.; Keeley, S. P. E.; Matei, D.; Msadek, R.; Sigmond, M.; Tatebe, H.; Hawkins, E.

2015-10-01

Recent decades have seen significant developments in seasonal-to-interannual timescale climate prediction capabilities. However, until recently the potential of such systems to predict Arctic climate had not been assessed. This paper describes a multi-model predictability experiment which was run as part of the Arctic Predictability and Prediction On Seasonal to Inter-annual Timescales (APPOSITE) project. The main goal of APPOSITE was to quantify the timescales on which Arctic climate is predictable. In order to achieve this, a coordinated set of idealised initial-value predictability experiments, with seven general circulation models, was conducted. This was the first model intercomparison project designed to quantify the predictability of Arctic climate on seasonal to inter-annual timescales. Here we present a description of the archived data set (which is available at the British Atmospheric Data Centre) and an update of the project's results. Although designed to address Arctic predictability, this data set could also be used to assess the predictability of other regions and modes of climate variability on these timescales, such as the El Niño Southern Oscillation.

Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

DOE PAGES

Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav; ...

2016-04-07

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the predictionmore » of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). Furthermore, a path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current ( Dst), AE, and wave activity.« less

Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis

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

Simms, Laura E.; Engebretson, Mark J.; Pilipenko, Viacheslav

The daily maximum relativistic electron flux at geostationary orbit can be predicted well with a set of daily averaged predictor variables including previous day's flux, seed electron flux, solar wind velocity and number density, AE index, IMF Bz, Dst, and ULF and VLF wave power. As predictor variables are intercorrelated, we used multiple regression analyses to determine which are the most predictive of flux when other variables are controlled. Empirical models produced from regressions of flux on measured predictors from 1 day previous were reasonably effective at predicting novel observations. Adding previous flux to the parameter set improves the predictionmore » of the peak of the increases but delays its anticipation of an event. Previous day's solar wind number density and velocity, AE index, and ULF wave activity are the most significant explanatory variables; however, the AE index, measuring substorm processes, shows a negative correlation with flux when other parameters are controlled. This may be due to the triggering of electromagnetic ion cyclotron waves by substorms that cause electron precipitation. VLF waves show lower, but significant, influence. The combined effect of ULF and VLF waves shows a synergistic interaction, where each increases the influence of the other on flux enhancement. Correlations between observations and predictions for this 1 day lag model ranged from 0.71 to 0.89 (average: 0.78). Furthermore, a path analysis of correlations between predictors suggests that solar wind and IMF parameters affect flux through intermediate processes such as ring current ( Dst), AE, and wave activity.« less

Thermal barrier coating life prediction model development

NASA Technical Reports Server (NTRS)

Hillery, R. V.; Pilsner, B. H.; Mcknight, R. L.; Cook, T. S.; Hartle, M. S.

1988-01-01

This report describes work performed to determine the predominat modes of degradation of a plasma sprayed thermal barrier coating system and to develop and verify life prediction models accounting for these degradation modes. The primary TBC system consisted of a low pressure plasma sprayed NiCrAlY bond coat, an air plasma sprayed ZrO2-Y2O3 top coat, and a Rene' 80 substrate. The work was divided into 3 technical tasks. The primary failure mode to be addressed was loss of the zirconia layer through spalling. Experiments showed that oxidation of the bond coat is a significant contributor to coating failure. It was evident from the test results that the species of oxide scale initially formed on the bond coat plays a role in coating degradation and failure. It was also shown that elevated temperature creep of the bond coat plays a role in coating failure. An empirical model was developed for predicting the test life of specimens with selected coating, specimen, and test condition variations. In the second task, a coating life prediction model was developed based on the data from Task 1 experiments, results from thermomechanical experiments performed as part of Task 2, and finite element analyses of the TBC system during thermal cycles. The third and final task attempted to verify the validity of the model developed in Task 2. This was done by using the model to predict the test lives of several coating variations and specimen geometries, then comparing these predicted lives to experimentally determined test lives. It was found that the model correctly predicts trends, but that additional refinement is needed to accurately predict coating life.

Predicting subscriber dissatisfaction and improving retention in the wireless telecommunications industry.

PubMed

Mozer, M C; Wolniewicz, R; Grimes, D B; Johnson, E; Kaushansky, H

2000-01-01

Competition in the wireless telecommunications industry is fierce. To maintain profitability, wireless carriers must control churn, which is the loss of subscribers who switch from one carrier to another.We explore techniques from statistical machine learning to predict churn and, based on these predictions, to determine what incentives should be offered to subscribers to improve retention and maximize profitability to the carrier. The techniques include logit regression, decision trees, neural networks, and boosting. Our experiments are based on a database of nearly 47,000 U.S. domestic subscribers and includes information about their usage, billing, credit, application, and complaint history. Our experiments show that under a wide variety of assumptions concerning the cost of intervention and the retention rate resulting from intervention, using predictive techniques to identify potential churners and offering incentives can yield significant savings to a carrier. We also show the importance of a data representation crafted by domain experts. Finally, we report on a real-world test of the techniques that validate our simulation experiments.

Obesity in show dogs.

PubMed

Corbee, R J

2013-10-01

Obesity is an important disease with a growing incidence. Because obesity is related to several other diseases, and decreases life span, it is important to identify the population at risk. Several risk factors for obesity have been described in the literature. A higher incidence of obesity in certain breeds is often suggested. The aim of this study was to determine whether obesity occurs more often in certain breeds. The second aim was to relate the increased prevalence of obesity in certain breeds to the official standards of that breed. To this end, we investigated 1379 dogs of 128 different breeds by determining their body condition score (BCS). Overall, 18.6% of the show dogs had a BCS >5, and 1.1% of the show dogs had a BCS>7. There were significant differences between breeds, which could be correlated to the breed standards. It warrants firm discussions with breeders and judges in order to come to different interpretations of the standards to prevent overweight conditions from being the standard of beauty. © 2012 Blackwell Verlag GmbH.

Which cue to ‘want’? Opioid stimulation of central amygdala makes goal-trackers show stronger goal-tracking, just as sign-trackers show stronger sign-tracking

PubMed Central

DiFeliceantonio, Alexandra G.; Berridge, Kent C.

2012-01-01

Pavlovian cues that have been paired with reward can gain incentive salience. Drug addicts find drug cues motivationally attractive and binge eaters are attracted by food cues. But the level of incentive salience elicited by a cue re-encounter still varies across time and brain states. In an animal model, cues become attractive and ‘wanted’ in an ‘autoshaping’ paradigm, where different targets of incentive salience emerge for different individuals. Some individuals (sign-trackers) find a predictive discrete cue attractive while others find a reward contiguous and goal cue more attractive (location where reward arrives: goal-trackers). Here we assessed whether central amygdala mu opioid receptor stimulation enhances the phasic incentive salience of the goal-cue for goal-trackers during moments of predictive cue presence (expressed in both approach and consummatory behaviors to goal cue), just as it enhances the attractiveness of the predictive cue target for sign-trackers. Using detailed video analysis we measured the approaches, nibbles, sniffs, and bites directed at their preferred target for both sign-trackers and goal-trackers. We report that DAMGO microinjections in central amygdala made goal-trackers, like sign-trackers, show phasic increases in appetitive nibbles and sniffs directed at the goal-cue expressed selectively whenever the predictive cue was present. This indicates enhancement of incentive salience attributed by both goal trackers and sign-trackers, but attributed in different directions: each to their own target cue. For both phenotypes, amygdala opioid stimulation makes the individual’s prepotent cue into a stronger motivational magnet at phasic moments triggered by a CS that predicts the reward UCS. PMID:22391118

[Serum PTH levels as a predictive factor of hypocalcaemia after total thyroidectomy].

PubMed

Díez Alonso, Manuel; Sánchez López, José Daniel; Sánchez-Seco Peña, María Isabel; Ratia Jiménez, Tomás; Arribas Gómez, Ignacio; Rodríguez Pascual, Angel; Martín-Duce, Antonio; Guadalix Hidalgo, Gregorio; Hernández Domínguez, Sara; Granell Vicent, Javier

2009-02-01

Postoperative parathyroid hormone (PTH) levels as a predictor of hypocalcaemia in patients subjected to total thyroidectomy is analyzed. Prospective study involving 67 patients who underwent total thyroidectomy due to a benign disease. Serum PTH and ionised calcium were measured 20 h after surgery. Sensitivity, specificity and predictive values of PTH and ionised calcium levels were calculated to predict clinical and analytical hypocalcaemia. A total of 42 (62.7%) patients developed hypocalcaemia (ionised calcium<0.95 mmol/l), but only 20 (29.9%) presented with symptoms. PTH concentration the day after surgery was significantly lower in the group that developed symptomatic hypocalcaemia (5.57+/-6.4 pg/ml) than in the asymptomatic (21.5+/-15.3 pg/ml) or normocalcaemic (26.8+/-24.9 pg/ml) groups (p=0.001). Taking the value of 13 pg/ml as a cut-off point of PTH levels, sensitivity, specificity, positive predictive value and negative predictive value were 54%, 72%, 76% and 48%, respectively. On the other hand, sensitivity for predicting symptomatic hypocalcaemia was 95% and specificity was 76%. The test showed a high incidence of false positives (11/30, 36%). Negative predictive value was 97% and positive predictive value was 65%. In multivariate analysis, PTH and ionised calcium were the only perioperative factors that showed an independent predictive value as risk indicators of symptomatic hypocalcaemia. Normal PTH levels 20 h after surgery practically rule out the subsequent appearance of hypocalcaemia symptoms. On the other hand, low PTH levels are not necessarily associated to symptomatic hypocalcaemia due to the high number of false positives.

Predictability Experiments With the Navy Operational Global Atmospheric Prediction System

NASA Astrophysics Data System (ADS)

Reynolds, C. A.; Gelaro, R.; Rosmond, T. E.

2003-12-01

There are several areas of research in numerical weather prediction and atmospheric predictability, such as targeted observations and ensemble perturbation generation, where it is desirable to combine information about the uncertainty of the initial state with information about potential rapid perturbation growth. Singular vectors (SVs) provide a framework to accomplish this task in a mathematically rigorous and computationally feasible manner. In this study, SVs are calculated using the tangent and adjoint models of the Navy Operational Global Atmospheric Prediction System (NOGAPS). The analysis error variance information produced by the NRL Atmospheric Variational Data Assimilation System is used as the initial-time SV norm. These VAR SVs are compared to SVs for which total energy is both the initial and final time norms (TE SVs). The incorporation of analysis error variance information has a significant impact on the structure and location of the SVs. This in turn has a significant impact on targeted observing applications. The utility and implications of such experiments in assessing the analysis error variance estimates will be explored. Computing support has been provided by the Department of Defense High Performance Computing Center at the Naval Oceanographic Office Major Shared Resource Center at Stennis, Mississippi.

Prediction of individual season of birth using MRI.

PubMed

Pantazatos, Spiro P

2014-03-01

Previous research suggests statistical associations between season of birth (SOB) with prevalence of neurobehavioral disorders such as schizophrenia and bipolar disorder, personality traits such as novelty and sensation seeking, and suicidal behavior. These effects are thought to be mediated by seasonal differences in perinatal photoperiod, which was recently shown to imprint circadian clock neurons and behavior in rodents. However, it is unknown whether SOB is associated with any measurable differences in the normal human adult brain, and whether individual SOB can be deduced based on phenotype. Here I show that SOB predicts morphological differences in brain structure, and that MRI scans carry spatially distributed information allowing significantly above chance prediction of an individual's SOB. Using an open source database of over 550 structural brain scans, Voxel-Based Morphometry (VBM) analysis showed a significant SOB effect in the left superior temporal gyrus (STG) in males (p=0.009, FWE whole-brain corrected), with greater gray matter volumes in fall and winter births. A cosinor analysis revealed a significant annual periodicity in the left STG gray matter volume (Zero Amplitude Test: p<5×10(-7)), with a peak towards the end of December and a nadir towards the end of June, suggesting that perinatal photoperiod accounts for this SOB effect. Whole-brain VBM maps were used as input features to multivariate machine-learning based analyses to classify SOB. Significantly greater than chance prediction was achieved in females (overall accuracy 35%, p<0.001), but not in males (overall accuracy 26%, p=0.45). Pairwise binary classification in females revealed that the highest discrimination was obtained for winter vs. summer classification (peak area under the ROC curve=0.71, p<0.0005). Discriminating regions included fusiform and middle temporal gyrus, inferior and superior parietal lobe, cerebellum, and dorsolateral and dorsomedial prefrontal cortex. Results

Low LET protons focused to submicrometer shows enhanced radiobiological effectiveness

NASA Astrophysics Data System (ADS)

Schmid, T. E.; Greubel, C.; Hable, V.; Zlobinskaya, O.; Michalski, D.; Girst, S.; Siebenwirth, C.; Schmid, E.; Molls, M.; Multhoff, G.; Dollinger, G.

2012-10-01

This study shows that enhanced radiobiological effectiveness (RBE) values can be generated focusing low linear energy transfer (LET) radiation and thus changing the microdose distribution. 20 MeV protons (LET = 2.65 keV µm-1) are focused to submicrometer diameter at the ion microprobe superconducting nanoprobe for applied nuclear (Kern) physics experiments of the Munich tandem accelerator. The RBE values, as determined by measuring micronuclei (RBEMN = 1.48 ± 0.07) and dicentrics (RBED = 1.92 ± 0.15), in human-hamster hybrid (AL) cells are significantly higher when 117 protons were focused to a submicrometer irradiation field within a 5.4 × 5.4 µm2 matrix compared to quasi homogeneous in a 1 × 1 µm2 matrix applied protons (RBEMN = 1.28 ± 0.07; RBED = 1.41 ± 0.14) at the same average dose of 1.7 Gy. The RBE values are normalized to standard 70 kV (dicentrics) or 200 kV (micronuclei) x-ray irradiation. The 117 protons applied per point deposit the same amount of energy like a 12C ion with 55 MeV total energy (4.48 MeV u-1). The enhancements are about half of that obtained for 12C ions (RBEMN = 2.20 ± 0.06 and RBED = 3.21 ± 0.10) and they are attributed to intertrack interactions of the induced damages. The measured RBE values show differences from predictions of the local effect model (LEM III) that is used to calculate RBE values for irradiation plans to treat tumors with high LET particles.

Significance of KRAS, NRAS, BRAF and PIK3CA mutations in metastatic colorectal cancer patients receiving Bevacizumab: a single institution experience

PubMed Central

Baltruškevičienė, Edita; Mickys, Ugnius; Žvirblis, Tadas; Stulpinas, Rokas; Pipirienė Želvienė, Teresė; Aleknavičius, Eduardas

2016-01-01

Background. KRAS mutation is an important predictive and prognostic factor for patients receiving anti-EGFR therapy. An expanded KRAS, NRAS, BRAF, PIK3CA mutation analysis provides additional prognostic information, but its role in predicting bevacizumab efficacy is unclear. The aim of our study was to evaluate the incidence of KRAS, NRAS, BRAF and PIK3CA mutations in metastatic colorectal cancer patients receiving first line oxaliplatin based chemotherapy with or without bevacizumab and to evaluate their prognostic and predictive significance. Methods. 55 patients with the first-time diagnosed CRC receiving FOLFOX ± bevacizumab were involved in the study. Tumour blocks were tested for KRAS mutations in exons 2, 3 and 4, NRAS mutations in exons 2, 3 and 4, BRAF mutation in exon 15 and PIK3CA mutations in exons 9 and 20. The association between mutations and clinico-pathological factors, treatment outcomes and survival was analyzed. Results. KRAS mutations were detected in 67.3% of the patients, BRAF in 1.8%, PIK3CA in 5.5% and there were no NRAS mutations. A significant association between the high CA 19–9 level and KRAS mutation was detected (mean CA 19–9 levels were 276 and 87 kIU/l, respectively, p = 0.019). There was a significantly higher response rate in the KRAS, NRAS, BRAF and PIK3CA wild type cohort receiving bevacizumab compared to any gene mutant type (100 and 60%, respectively, p = 0.030). The univariate Cox regression analysis did not confirm KRAS and other tested mutations as prognostic factors for PFS or OS. Conclusions. Our study revealed higher KRAS and lower NRAS, BRAF and PIK3CA mutation rates in the Lithuanian population than those reported in the literature. KRAS mutation was associated with the high CA 19–9 level and mucinous histology type, but did not show any predictive or prognostic significance. The expanded KRAS, NRAS, BRAF and PIK3CA mutation analysis provided additional significant predictive information. PMID:28356789

Small Molecules Showing Significant Protection of Mice against Botulinum Neurotoxin Serotype A

DTIC Science & Technology

2010-04-13

Botulinum neurotoxin serotype A (BoNTA) causes a life-threatening neuroparalytic disease known as botulism that could afflict large, unprotected...that is effective for treating infant botulism at a cost of US $45,300 per treatment regimen. Antibodies can neutralize the extracellular but not the...Inhibitors, Therapeutics, Antidotes, Countermeasures, Botulism , Botulinum Neurotoxins, In Vivo Study, and Mouse Protection. Yuan-Ping Pang, Jon Davis

Methane mitigation shows significant benefits towards achieving the 1.5 degree target.

NASA Astrophysics Data System (ADS)

Collins, W.; Webber, C.; Cox, P. M.; Huntingford, C.; Lowe, J. A.; Sitch, S.

2017-12-01

Most analyses of allowable carbon emissions to achieve the 1.5 degree target implicitly assume that the ratio of CO2 to non-CO2 greenhouse gases remains near constant, and that all radiative forcing factors have similar impacts on land and ocean carbon storage. Here we determine how plausible reductions in methane emissions will make the carbon targets more feasible. We account for the latest estimates of the methane radiative effect as well as the indirect effects of methane on ozone. We particularly address the differing effects of methane and CO2 mitigation on the land carbon storage including via reduced concentrations of surface ozone. The methodology uses an intermediate complexity climate model (IMOGEN) coupled to a land surface model (JULES) which represents the details of the terrestrial carbon cycle. The carbon emissions inputs to IMOGEN are varied to find allowable pathways consistent with the Paris 1.5 K or 2.0 K targets. The IMOGEN physical parameters are altered to represent the climate characteristics of 38 CMIP5 models (such as climate sensitivity) to provide bounds on the range of allowable CO2 emissions. We examine the effects of three different methane mitigation options that are broadly consistent with the ranges in the SSP scenarios: little mitigation, cost-optimal mitigation, and maximal mitigation. The land and ocean carbon storage increases with methane mitigation, allowing more flexibility in CO2 emission reduction. This is mostly since CO2 fertilisation is reduced less with high methane mitigation, with a small contribution from reduced plant damage with lower surface ozone levels.

Albumin and C-reactive protein have prognostic significance in patients with community-acquired pneumonia.

PubMed

Lee, Jae Hyuk; Kim, Jooyeong; Kim, Kyuseok; Jo, You Hwan; Rhee, JoongEui; Kim, Tae Youn; Na, Sang Hoon; Hwang, Seung Sik

2011-06-01

This study aims to determine the association of commonly used biochemical markers, such as albumin and C-reactive protein (CRP), with mortality and the prognostic performance of these markers combined with the pneumonia severity index (PSI) for mortality and adverse outcomes in patients with community-acquired pneumonia (CAP). The data were gathered prospectively for patients hospitalized with CAP via the emergency department. Laboratory values, including CRP and albumin, clinical variables, and the PSI were measured. Primary outcomes were 28-day mortality and survival times. Secondary outcome was admission to the intensive care unit, vasopressor use, or the need for mechanical ventilation during the hospital stay. A total of 424 patients were included. The 28-day mortality was 13.7%. C-reactive protein and albumin were significantly different between survivors and nonsurvivors. In logistic regression analysis, CRP and albumin were independently associated with 28-day mortality (P < .05). Receiver operating characteristic curves showed improved mortality prediction by adding CRP or albumin to the PSI scale. The Cox proportional hazards analysis showed that high serum albumin (≥3.3 mg/dL) had a hazard ratio of 0.5 (95% confidence interval, 0.3-0.9), and high CRP (≥14.3 mg/dL) had a hazard ratio of 2.0 (95% confidence interval, 1.1-3.4). For predicting secondary outcome, adding albumin to PSI increased areas under the curve significantly, but CRP did not. Albumin and CRP were associated with 28-day mortality in hospitalized patients with CAP, and these markers increased prognostic performance when combined with the PSI scale. Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.

Predicting phonetic transcription agreement: Insights from research in infant vocalizations

PubMed Central

RAMSDELL, HEATHER L.; OLLER, D. KIMBROUGH; ETHINGTON, CORINNA A.

2010-01-01

The purpose of this study is to provide new perspectives on correlates of phonetic transcription agreement. Our research focuses on phonetic transcription and coding of infant vocalizations. The findings are presumed to be broadly applicable to other difficult cases of transcription, such as found in severe disorders of speech, which similarly result in low reliability for a variety of reasons. We evaluated the predictiveness of two factors not previously documented in the literature as influencing transcription agreement: canonicity and coder confidence. Transcribers coded samples of infant vocalizations, judging both canonicity and confidence. Correlation results showed that canonicity and confidence were strongly related to agreement levels, and regression results showed that canonicity and confidence both contributed significantly to explanation of variance. Specifically, the results suggest that canonicity plays a major role in transcription agreement when utterances involve supraglottal articulation, with coder confidence offering additional power in predicting transcription agreement. PMID:17882695

Component-based model to predict aerodynamic noise from high-speed train pantographs

NASA Astrophysics Data System (ADS)

Latorre Iglesias, E.; Thompson, D. J.; Smith, M. G.

2017-04-01

At typical speeds of modern high-speed trains the aerodynamic noise produced by the airflow over the pantograph is a significant source of noise. Although numerical models can be used to predict this they are still very computationally intensive. A semi-empirical component-based prediction model is proposed to predict the aerodynamic noise from train pantographs. The pantograph is approximated as an assembly of cylinders and bars with particular cross-sections. An empirical database is used to obtain the coefficients of the model to account for various factors: incident flow speed, diameter, cross-sectional shape, yaw angle, rounded edges, length-to-width ratio, incoming turbulence and directivity. The overall noise from the pantograph is obtained as the incoherent sum of the predicted noise from the different pantograph struts. The model is validated using available wind tunnel noise measurements of two full-size pantographs. The results show the potential of the semi-empirical model to be used as a rapid tool to predict aerodynamic noise from train pantographs.

Predictive momentum management for a space station measurement and computation requirements

NASA Technical Reports Server (NTRS)

Adams, John Carl

1986-01-01

An analysis is made of the effects of errors and uncertainties in the predicting of disturbance torques on the peak momentum buildup on a space station. Models of the disturbance torques acting on a space station in low Earth orbit are presented, to estimate how accurately they can be predicted. An analysis of the torque and momentum buildup about the pitch axis of the Dual Keel space station configuration is formulated, and a derivation of the Average Torque Equilibrium Attitude (ATEA) is presented, for the case of no MRMS (Mobile Remote Manipulation System) motion, Y vehicle axis MRMS motion, and Z vehicle axis MRMS motion. Results showed the peak momentum buildup to be approximately 20000 N-m-s and to be relatively insensitive to errors in the predicting torque models, for Z axis motion of the MRMS was found to vary significantly with model errors, but not exceed a value of approximately 15000 N-m-s for the Y axis MRMS motion with 1 deg attitude hold error. Minimum peak disturbance momentum was found not to occur at the ATEA angle, but at a slightly smaller angle. However, this minimum peak momentum attitude was found to produce significant disturbance momentum at the end of the predicting time interval.

The baseline serum value of α-amylase is a significant predictor of distance running performance.

PubMed

Lippi, Giuseppe; Salvagno, Gian Luca; Danese, Elisa; Tarperi, Cantor; La Torre, Antonio; Guidi, Gian Cesare; Schena, Federico

2015-02-01

This study was planned to investigate whether serum α-amylase concentration may be associated with running performance, physiological characteristics and other clinical chemistry analytes in a large sample of recreational athletes undergoing distance running. Forty-three amateur runners successfully concluded a 21.1 km half-marathon at 75%-85% of their maximal oxygen uptake (VO2max). Blood was drawn during warm up and 15 min after conclusion of the run. After correction for body weight change, significant post-run increases were observed for serum values of alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, bilirubin, creatine kinase (CK), iron, lactate dehydrogenase (LDH), triglycerides, urea and uric acid, whereas the values of body weight, glomerular filtration rate, total and low density lipoprotein-cholesterol were significantly decreased. The concentration of serum α-amylase was unchanged. In univariate analysis, significant associations with running performance were found for gender, VO2max, training regimen and pre-run serum values of α-amylase, CK, glucose, high density lipoprotein-cholesterol, LDH, urea and uric acid. In multivariate analysis, only VO2max (p=0.042) and baseline α-amylase (p=0.021) remained significant predictors of running performance. The combination of these two variables predicted 71% of variance in running performance. The baseline concentration of serum α-amylase was positively correlated with variation of serum glucose during the trial (r=0.345; p=0.025) and negatively with capillary blood lactate at the end of the run (r=-0.352; p=0.021). We showed that the baseline serum α-amylase concentration significantly and independently predicts distance running performance in recreational runners.

Age distribution of human gene families shows significant roles of both large- and small-scale duplications in vertebrate evolution.

PubMed

Gu, Xun; Wang, Yufeng; Gu, Jianying

2002-06-01

The classical (two-round) hypothesis of vertebrate genome duplication proposes two successive whole-genome duplication(s) (polyploidizations) predating the origin of fishes, a view now being seriously challenged. As the debate largely concerns the relative merits of the 'big-bang mode' theory (large-scale duplication) and the 'continuous mode' theory (constant creation by small-scale duplications), we tested whether a significant proportion of paralogous genes in the contemporary human genome was indeed generated in the early stage of vertebrate evolution. After an extensive search of major databases, we dated 1,739 gene duplication events from the phylogenetic analysis of 749 vertebrate gene families. We found a pattern characterized by two waves (I, II) and an ancient component. Wave I represents a recent gene family expansion by tandem or segmental duplications, whereas wave II, a rapid paralogous gene increase in the early stage of vertebrate evolution, supports the idea of genome duplication(s) (the big-bang mode). Further analysis indicated that large- and small-scale gene duplications both make a significant contribution during the early stage of vertebrate evolution to build the current hierarchy of the human proteome.

MS2PIP prediction server: compute and visualize MS2 peak intensity predictions for CID and HCD fragmentation.

PubMed

Degroeve, Sven; Maddelein, Davy; Martens, Lennart

2015-07-01

We present an MS(2) peak intensity prediction server that computes MS(2) charge 2+ and 3+ spectra from peptide sequences for the most common fragment ions. The server integrates the Unimod public domain post-translational modification database for modified peptides. The prediction model is an improvement of the previously published MS(2)PIP model for Orbitrap-LTQ CID spectra. Predicted MS(2) spectra can be downloaded as a spectrum file and can be visualized in the browser for comparisons with observations. In addition, we added prediction models for HCD fragmentation (Q-Exactive Orbitrap) and show that these models compute accurate intensity predictions on par with CID performance. We also show that training prediction models for CID and HCD separately improves the accuracy for each fragmentation method. The MS(2)PIP prediction server is accessible from http://iomics.ugent.be/ms2pip. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

A predictive index of axillary nodal involvement in operable breast cancer.

PubMed Central

De Laurentiis, M.; Gallo, C.; De Placido, S.; Perrone, F.; Pettinato, G.; Petrella, G.; Carlomagno, C.; Panico, L.; Delrio, P.; Bianco, A. R.

1996-01-01

We investigated the association between pathological characteristics of primary breast cancer and degree of axillary nodal involvement and obtained a predictive index of the latter from the former. In 2076 cases, 17 histological features, including primary tumour and local invasion variables, were recorded. The whole sample was randomly split in a training (75% of cases) and a test sample. Simple and multiple correspondence analysis were used to select the variables to enter in a multinomial logit model to build an index predictive of the degree of nodal involvement. The response variable was axillary nodal status coded in four classes (N0, N1-3, N4-9, N > or = 10). The predictive index was then evaluated by testing goodness-of-fit and classification accuracy. Covariates significantly associated with nodal status were tumour size (P < 0.0001), tumour type (P < 0.0001), type of border (P = 0.048), multicentricity (P = 0.003), invasion of lymphatic and blood vessels (P < 0.0001) and nipple invasion (P = 0.006). Goodness-of-fit was validated by high concordance between observed and expected number of cases in each decile of predicted probability in both training and test samples. Classification accuracy analysis showed that true node-positive cases were well recognised (84.5%), but there was no clear distinction among the classes of node-positive cases. However, 10 year survival analysis showed a superimposible prognostic behaviour between predicted and observed nodal classes. Moreover, misclassified node-negative patients (i.e. those who are predicted positive) showed an outcome closer to patients with 1-3 metastatic nodes than to node-negative ones. In conclusion, the index cannot completely substitute for axillary node information, but it is a predictor of prognosis as accurate as nodal involvement and identifies a subgroup of node-negative patients with unfavourable prognosis. PMID:8630286

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).

The Predictive Validity of Four Intelligence Tests for School Grades: A Small Sample Longitudinal Study

PubMed Central

Gygi, Jasmin T.; Hagmann-von Arx, Priska; Schweizer, Florine; Grob, Alexander

2017-01-01

Intelligence is considered the strongest single predictor of scholastic achievement. However, little is known regarding the predictive validity of well-established intelligence tests for school grades. We analyzed the predictive validity of four widely used intelligence tests in German-speaking countries: The Intelligence and Development Scales (IDS), the Reynolds Intellectual Assessment Scales (RIAS), the Snijders-Oomen Nonverbal Intelligence Test (SON-R 6-40), and the Wechsler Intelligence Scale for Children (WISC-IV), which were individually administered to 103 children (Mage = 9.17 years) enrolled in regular school. School grades were collected longitudinally after 3 years (averaged school grades, mathematics, and language) and were available for 54 children (Mage = 11.77 years). All four tests significantly predicted averaged school grades. Furthermore, the IDS and the RIAS predicted both mathematics and language, while the SON-R 6-40 predicted mathematics. The WISC-IV showed no significant association with longitudinal scholastic achievement when mathematics and language were analyzed separately. The results revealed the predictive validity of currently used intelligence tests for longitudinal scholastic achievement in German-speaking countries and support their use in psychological practice, in particular for predicting averaged school grades. However, this conclusion has to be considered as preliminary due to the small sample of children observed. PMID:28348543

Prediction using patient comparison vs. modeling: a case study for mortality prediction.

PubMed

Hoogendoorn, Mark; El Hassouni, Ali; Mok, Kwongyen; Ghassemi, Marzyeh; Szolovits, Peter

2016-08-01

Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application of off-the-shelf machine learning techniques difficult. In this paper, we study two approaches to making predictions that have hardly been compared in the past: (1) extracting high-level (temporal) features from EMRs and building a predictive model, and (2) defining a patient similarity metric and predicting based on the outcome observed for similar patients. We analyze and compare both approaches on the MIMIC-II ICU dataset to predict patient mortality and find that the patient similarity approach does not scale well and results in a less accurate model (AUC of 0.68) compared to the modeling approach (0.84). We also show that mortality can be predicted within a median of 72 hours.

A general framework for multivariate multi-index drought prediction based on Multivariate Ensemble Streamflow Prediction (MESP)

NASA Astrophysics Data System (ADS)

Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.

2016-08-01

Drought is among the costliest natural hazards worldwide and extreme drought events in recent years have caused huge losses to various sectors. Drought prediction is therefore critically important for providing early warning information to aid decision making to cope with drought. Due to the complicated nature of drought, it has been recognized that the univariate drought indicator may not be sufficient for drought characterization and hence multivariate drought indices have been developed for drought monitoring. Alongside the substantial effort in drought monitoring with multivariate drought indices, it is of equal importance to develop a drought prediction method with multivariate drought indices to integrate drought information from various sources. This study proposes a general framework for multivariate multi-index drought prediction that is capable of integrating complementary prediction skills from multiple drought indices. The Multivariate Ensemble Streamflow Prediction (MESP) is employed to sample from historical records for obtaining statistical prediction of multiple variables, which is then used as inputs to achieve multivariate prediction. The framework is illustrated with a linearly combined drought index (LDI), which is a commonly used multivariate drought index, based on climate division data in California and New York in the United States with different seasonality of precipitation. The predictive skill of LDI (represented with persistence) is assessed by comparison with the univariate drought index and results show that the LDI prediction skill is less affected by seasonality than the meteorological drought prediction based on SPI. Prediction results from the case study show that the proposed multivariate drought prediction outperforms the persistence prediction, implying a satisfactory performance of multivariate drought prediction. The proposed method would be useful for drought prediction to integrate drought information from various sources

SAE for the prediction of road traffic status from taxicab operating data and bus smart card data

NASA Astrophysics Data System (ADS)

Zhengfeng, Huang; Pengjun, Zheng; Wenjun, Xu; Gang, Ren

Road traffic status is significant for trip decision and traffic management, and thus should be predicted accurately. A contribution is that we consider multi-modal data for traffic status prediction than only using single source data. With the substantial data from Ningbo Passenger Transport Management Sector (NPTMS), we wished to determine whether it was possible to develop Stacked Autoencoders (SAEs) for accurately predicting road traffic status from taxicab operating data and bus smart card data. We show that SAE performed better than linear regression model and Back Propagation (BP) neural network for determining the relationship between road traffic status and those factors. In a 26-month data experiment using SAE, we show that it is possible to develop highly accurate predictions (91% test accuracy) of road traffic status from daily taxicab operating data and bus smart card data.

Significant-Loophole-Free Test of Bell's Theorem with Entangled Photons.

PubMed

Giustina, Marissa; Versteegh, Marijn A M; Wengerowsky, Sören; Handsteiner, Johannes; Hochrainer, Armin; Phelan, Kevin; Steinlechner, Fabian; Kofler, Johannes; Larsson, Jan-Åke; Abellán, Carlos; Amaya, Waldimar; Pruneri, Valerio; Mitchell, Morgan W; Beyer, Jörn; Gerrits, Thomas; Lita, Adriana E; Shalm, Lynden K; Nam, Sae Woo; Scheidl, Thomas; Ursin, Rupert; Wittmann, Bernhard; Zeilinger, Anton

2015-12-18

Local realism is the worldview in which physical properties of objects exist independently of measurement and where physical influences cannot travel faster than the speed of light. Bell's theorem states that this worldview is incompatible with the predictions of quantum mechanics, as is expressed in Bell's inequalities. Previous experiments convincingly supported the quantum predictions. Yet, every experiment requires assumptions that provide loopholes for a local realist explanation. Here, we report a Bell test that closes the most significant of these loopholes simultaneously. Using a well-optimized source of entangled photons, rapid setting generation, and highly efficient superconducting detectors, we observe a violation of a Bell inequality with high statistical significance. The purely statistical probability of our results to occur under local realism does not exceed 3.74×10^{-31}, corresponding to an 11.5 standard deviation effect.

On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

NASA Astrophysics Data System (ADS)

Velarde, P.; Valverde, L.; Maestre, J. M.; Ocampo-Martinez, C.; Bordons, C.

2017-03-01

In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.

The Surgical Apgar Score Predicts Not Only Short-Term Complications But Also Long-Term Prognosis After Esophagectomy.

PubMed

Nakagawa, Akio; Nakamura, Tetsu; Oshikiri, Taro; Hasegawa, Hiroshi; Yamamoto, Masashi; Kanaji, Shingo; Matsuda, Yoshiko; Yamashita, Kimihiro; Matsuda, Takeru; Sumi, Yasuo; Suzuki, Satoshi; Kakeji, Yoshihiro

2017-12-01

The surgical Apgar score (SAS) quantifies three intraoperative factors and predicts postoperative complications, but few reports describe its usefulness in esophagectomy, and no studies to date show its correlation with long-term prognosis after esophagectomy. This study investigated 400 cases in which esophagectomy was performed on esophageal malignant tumors at the authors' hospital from January 2007 to January 2017. In this study, SAS was defined as the sum of the scores of three parameters, namely, estimated blood loss, lowest mean arterial pressure, and lowest heart rate, with values extracted from medical records. Postoperative complications classified as Clavien-Dindo grade 3 or higher were also extracted. The study retrospectively compared the relationship of SAS to postoperative complications and survival. Univariate analysis showed that postoperative complications were significantly associated with hypertension (p = 0.017), thoracotomy (p = 0.012), and SAS ≤ 5 (p < 0.0001), and multivariate analysis showed that hypertension (p = 0.049) and SAS ≤ 5 (p < 0.0001) were significant predictive factors for complications. In the prognostic analysis, log-rank analysis showed that patients with an SAS ≤ 5 had a significantly poorer prognosis than those with a SAS > 5 (p = 0.043), especially for complications classified as clinical stage 2 or higher (p = 0.027). In the multivariate analysis, SAS ≤ 5 was identified as a significantly poor prognostic factor for complications classified as clinical stage 2 or higher (p = 0.029). In this study, SAS was useful not only for predicting short-term complications, but also as a long-term prognostic factor after esophagectomy.

Significance of lipoprotein(a) levels in familial hypercholesterolemia and coronary artery disease.

PubMed

Li, Sha; Wu, Na-Qiong; Zhu, Cheng-Gang; Zhang, Yan; Guo, Yuan-Lin; Gao, Ying; Li, Xiao-Lin; Qing, Ping; Cui, Chuan-Jue; Xu, Rui-Xia; Sun, Jing; Liu, Geng; Dong, Qian; Li, Jian-Jun

2017-05-01

Patients with familial hypercholesterolemia (FH) are often characterized by premature coronary artery disease (CAD) with heterogeneity at onset. The aim of the present study was to investigate the associations of lipoprotein (a) [Lp(a)] with the FH phenotype, genotype and roles of Lp(a) in determining CAD risk among patients with and without FH. We enrolled 8050 patients undergoing coronary angiography, from our Lipid clinic. Clinical FH was diagnosed using the Dutch Lipid Clinic Network criteria. Mutational analysis (LDLR, APOB, PCSK9) in definite/probable FH was performed by target exome sequencing. Lp(a) levels were increased, with a clinical FH diagnosis (unlikely, possible, definite/probable FH) independent of the patients status, with Lp(a)-hyperlipoproteinemia [Lp(a)-HLP] (median 517.70 vs. 570.98 vs. 604.65 mg/L, p < 0.001) or without (median 89.20 vs. 99.20 vs. 133.67 mg/L, p < 0.001). Patients with Lp(a)-HLP had a higher prevalence of definite/probable FH than those without (6.1% vs. 2.4%, p < 0.05). However, no significant difference in Lp(a) was observed in patients with definite/probable FH phenotype carrying LDLR or LDLR-independent (APOB, PCSK9) or neither mutations (p > 0.05). Multivariate analysis showed that Lp(a) and FH phenotype were both significant determinants in predicting the early onset and severity of CAD. Subsequently, patients with Lp(a)-HLP in definite/probable FH increased significantly the CAD risk (all p < 0.05). Lp(a) levels were higher in patients with FH phenotype than in those without, but no difference were found in FH patients of different mutated backgrounds. Moreover, Lp(a) and FH played a synergistic role in predicting the early onset and severity of CAD. Copyright © 2017 Elsevier B.V. All rights reserved.

In Silico Labeling: Predicting Fluorescent Labels in Unlabeled Images.

PubMed

Christiansen, Eric M; Yang, Samuel J; Ando, D Michael; Javaherian, Ashkan; Skibinski, Gaia; Lipnick, Scott; Mount, Elliot; O'Neil, Alison; Shah, Kevan; Lee, Alicia K; Goyal, Piyush; Fedus, William; Poplin, Ryan; Esteva, Andre; Berndl, Marc; Rubin, Lee L; Nelson, Philip; Finkbeiner, Steven

2018-04-19

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine-learning approach, which we call "in silico labeling" (ISL), reliably predicts some fluorescent labels from transmitted-light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire. Copyright © 2018 Elsevier Inc. All rights reserved.

Are Predictive Equations for Estimating Resting Energy Expenditure Accurate in Asian Indian Male Weightlifters?

PubMed

Joseph, Mini; Gupta, Riddhi Das; Prema, L; Inbakumari, Mercy; Thomas, Nihal

2017-01-01

The accuracy of existing predictive equations to determine the resting energy expenditure (REE) of professional weightlifters remains scarcely studied. Our study aimed at assessing the REE of male Asian Indian weightlifters with indirect calorimetry and to compare the measured REE (mREE) with published equations. A new equation using potential anthropometric variables to predict REE was also evaluated. REE was measured on 30 male professional weightlifters aged between 17 and 28 years using indirect calorimetry and compared with the eight formulas predicted by Harris-Benedicts, Mifflin-St. Jeor, FAO/WHO/UNU, ICMR, Cunninghams, Owen, Katch-McArdle, and Nelson. Pearson correlation coefficient, intraclass correlation coefficient, and multiple linear regression analysis were carried out to study the agreement between the different methods, association with anthropometric variables, and to formulate a new prediction equation for this population. Pearson correlation coefficients between mREE and the anthropometric variables showed positive significance with suprailiac skinfold thickness, lean body mass (LBM), waist circumference, hip circumference, bone mineral mass, and body mass. All eight predictive equations underestimated the REE of the weightlifters when compared with the mREE. The highest mean difference was 636 kcal/day (Owen, 1986) and the lowest difference was 375 kcal/day (Cunninghams, 1980). Multiple linear regression done stepwise showed that LBM was the only significant determinant of REE in this group of sportspersons. A new equation using LBM as the independent variable for calculating REE was computed. REE for weightlifters = -164.065 + 0.039 (LBM) (confidence interval -1122.984, 794.854]. This new equation reduced the mean difference with mREE by 2.36 + 369.15 kcal/day (standard error = 67.40). The significant finding of this study was that all the prediction equations underestimated the REE. The LBM was the sole determinant of REE in this population

Advanced lung adenocarcinomas with ROS1-rearrangement frequently show hepatoid cell

PubMed Central

Kong, Mei; Zhou, Jianya; Ding, Wei; Zhou, Jianying

2016-01-01

Defining distinctive histologic characteristics of ROS1-rearranged non-small-cell lung carcinomas (NSCLCs) may help identify cases that merit molecular testing. However, the majority of previous reports have focused on surgical specimens but only limited studies assessed histomorphology of advanced NSCLCs. In order to identify the clinical and histological characteristics of ROS1-rearranged advanced NSCLCs, we examined five hundred sixteen Chinese patients with advanced NSCLCs using ROS1 fluorescence in situ hybridization and real-time polymerase chain reaction and then analyzed for clinical and pathological features. We performed univariate and multivariate analyses to identify predictive factors associated with ROS1 rearrangement. 19 tumors were identified with ROS1 rearrangement (3.7% of adenocarcinomas). 16 ROS1+ and 122 ROS1- samples with available medical records and enough tumor cells were included for histological analysis. Compared with ROS1-negative advanced NSCLCs, ROS1-rearranged advanced NSCLCs were associated with a younger age at presentation. ROS1 rearrangements were not significantly associated with sex, smoking history, drinking history and metastatic sites. The most common histological pattern was solid growth (12/16), followed by acinar (4/16) growth. 66.7% cases with solid growth pattern showed hepatoid cytology (8/12) and 75% cases with acinar growth pattern showed a cribriform structure (3/4). 18.8% cases were found to have abundant extracellular mucus or signet-ring cells (3/16). Only one case with solid growth pattern showed psammomatous calcifications. In conclusion, age, hepatoid cytology and cribriform structure are the independent predictors for ROS1-rearranged advanced NSCLCs, recognizing these may be helpful in finding candidates for genomic alterations, especially when available tissue samples are limited. PMID:27708233

[Clinical value of angiogenin in predicting the prognosis of patients with idiopathic pulmonary fibrosis].

PubMed

Bai, Yanling; Zhu, Haiyan; Sun, Qiyu; Gu, Guozhong; Zhang, Lingyu; Li, Ying; Yang, Baofeng