bluuebunny/crossref_metadata_2025_split huggingface dataset:
Overexpressed β-Catenin Blocks Nitric Oxide–Induced Apoptosis in Colonic Cancer Cells
Authors: Wang Hongying , MacNaughton Wallace K. 
Published: October 2005

Abstractβ-Catenin plays an important role in colonic tumorigenesis whereas inducible nitric oxide synthase and nitric oxide are elevated in colonic inflammation. Resistance of colonic epithelial cells to the induction of apoptosis may contribute to tumor development. Nitric oxide can stimulate apoptosis and, paradoxically, is implicated in the development of colon cancer. Our hypothesis was that β-catenin could increase the resistance of colonic cancer cells to nitric oxide–induced apoptotic cell death. Here we show, using a β-catenin overexpression system, that increased cytosolic β-catenin renders colonic epithelial cells more resistant to nitric oxide–induced apoptotic cell death, independently of nitric oxide–induced accumulation of p53. Furthermore, we show that this occurs through inhibition of nitric oxide–induced release of cytochrome c from mitochondria and by blocking both the nitric oxide–induced suppression of the antiapoptotic protein, Bcl-xL, and the phosphorylation of Akt. We contend that increased nitric oxide production, such as that which occurs in chronic colonic inflammation, may select the cells with oncogenic mutant β-catenin regulatory genes and contribute to human colonic carcinogenesis and tumor progression.
Downscaling Precipitation and Temperature with Temporal Neural Networks
Authors: Coulibaly Paulin , Dibike Yonas B. , Anctil François 
Published: September 2005

Abstract
The issues of downscaling the outputs of a global climate model (GCM) to a scale that is appropriate to hydrological impact studies are investigated using a temporal neural network approach. The time-lagged feed-forward neural network (TLFN) is proposed for downscaling daily total precipitation and daily maximum and minimum temperature series for the Serpent River watershed in northern Quebec (Canada). The downscaling models are developed and validated using large-scale predictor variables derived from the National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis dataset. Atmospheric predictors such as specific humidity, wind velocity, and geopotential height are identified as the most relevant inputs to the downscaling models. The performance of the TLFN downscaling model is also compared to a statistical downscaling model (SDSM). The downscaling results suggest that the TLFN is an efficient method for downscaling both daily precipitation and temperature series. The best downscaling models were then applied to the outputs of the Canadian Global Climate Model (CGCM1), forced with the Intergovernmental Panel on Climate Change (IPCC) IS92a scenario. Changes in average precipitation between the current and the future scenarios predicted by the TLFN are generally found to be smaller than those predicted by the SDSM model. Furthermore, application of the downscaled data for hydrologic impact analysis in the Serpent River resulted in an overall increasing trend in mean annual flow as well as earlier spring peak flow. The results also demonstrate the emphasis that should be given in identifying the appropriate downscaling tools for impact studies by showing how a future climate scenario downscaled with different downscaling methods could result in significantly different hydrologic impact simulation results for the same watershed.
Issues in Simulating the Annual Precipitation of a Semiarid Region in Central Spain
Authors: Hasler N. , Avissar R. , Liston G. E. 
Published: September 2005

Abstract
Running regional climate models at a high resolution may improve their ability to simulate regional precipitation patterns, making them suitable for studying the impact of human-induced land-cover changes on hydrometeorology. The performance of the Regional Atmospheric Modeling System (RAMS) run in the high-resolution climate mode (4-km grid mesh) has been tested over a small domain in a semiarid region in central Spain. Three 1-yr simulations representing dry, intermediate, and wet conditions were compared to observations collected in 35 rain gauges. The model captured general spatiotemporal features of precipitation, such as the timing of precipitation events and approximate location of storms. A high correlation (0.82) between monthly domain-averaged observed and modeled precipitation was obtained. However, the model had a systematic dry bias, averaging −0.29 mm day−1, equivalent to 26% of annual rainfall. The small domain size, chosen because of computational limits, induced strong lateral boundary forcing, which, combined with uncertainty in NCEP relative humidity fields, was a likely cause for this dry bias.
Trends and Variability in Snowmelt Runoff in the Western United States
Authors: McCabe Gregory J. , Clark Martyn P. 
Published: September 2005

Abstract
The timing of snowmelt runoff (SMR) for 84 rivers in the western United States is examined to understand the character of SMR variability and the climate processes that may be driving changes in SMR timing. Results indicate that the timing of SMR for many rivers in the western United States has shifted to earlier in the snowmelt season. This shift occurred as a step change during the mid-1980s in conjunction with a step increase in spring and early-summer atmospheric pressures and temperatures over the western United States. The cause of the step change has not yet been determined.
Validation and Error Characterization of the GPCP-1DD Precipitation Product over the Contiguous United States
Authors: McPhee James , Margulis Steven A. 
Published: September 2005

Abstract
A validation and error characterization study of the Global Precipitation Climatology Project, 1 degree daily (GPCP-1DD) precipitation product over the contiguous United States is presented. Daily precipitation estimates over a 1° grid are compared against aggregated precipitation values obtained from the forcing field of the North American Land Data Assimilation System (LDAS). LDAS daily values are consistent with the National Centers for Environmental Prediction Climate Prediction Center (CPC) gauge-based daily precipitation product and hence are regarded as realistic ground-truth values with full coverage of the United States. Continuous and categorical measures of skill are presented, so that both the ability of GPCP-1DD to identify a precipitation event and its accuracy in determining cumulative precipitation amounts are evaluated. Daily values are aggregated into seasonal averages, and spatial averages are computed for five arbitrarily defined zones that cover most of the study area. Results show that in general there is good agreement between GPCP-1DD and LDAS values, except for areas where GPCP-1DD is unable to identify high-intensity events, particularly the Pacific coast north of parallel 40°N. Computation of continuous statistics shows that average bias is negligible in most areas of the United States except for humid regions north of parallel 40°N. However, the rmse statistics shows that differences in estimated precipitation for individual 1° cells can be significant, exceeding in most cases the magnitude of the average precipitation. Beyond the validation, the error characterization presented here can significantly enhance the utility of the GPCP-1DD product by providing necessary inputs for ensemble hydrologic modeling and forecasting.
Intercomparison of Rain Gauge, Radar, and Satellite-Based Precipitation Estimates with Emphasis on Hydrologic Forecasting
Authors: Yilmaz Koray K. , Hogue Terri S. , Hsu Kuo-lin , Sorooshian Soroosh , Gupta Hoshin V. , Wagener Thorsten 
Published: September 2005

Abstract
This study compares mean areal precipitation (MAP) estimates derived from three sources: an operational rain gauge network (MAPG), a radar/gauge multisensor product (MAPX), and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN) satellite-based system (MAPS) for the time period from March 2000 to November 2003. The study area includes seven operational basins of varying size and location in the southeastern United States. The analysis indicates that agreements between the datasets vary considerably from basin to basin and also temporally within the basins. The analysis also includes evaluation of MAPS in comparison with MAPG for use in flow forecasting with a lumped hydrologic model [Sacramento Soil Moisture Accounting Model (SAC-SMA)]. The latter evaluation investigates two different parameter sets, the first obtained using manual calibration on historical MAPG, and the second obtained using automatic calibration on both MAPS and MAPG, but over a shorter time period (23 months). Results indicate that the overall performance of the model simulations using MAPS depends on both the bias in the precipitation estimates and the size of the basins, with poorer performance in basins of smaller size (large bias between MAPG and MAPS) and better performance in larger basins (less bias between MAPG and MAPS). When using MAPS, calibration of the parameters significantly improved the model performance.
The Operational Eta Model Precipitation and Surface Hydrologic Cycle of the Columbia and Colorado Basins
Authors: Luo Yan , Berbery Ernesto H. , Mitchell Kenneth E. 
Published: September 2005

Abstract
The surface hydrology of the United States’ western basins is investigated using the National Centers for Environmental Prediction operational Eta Model forecasts. During recent years the model has been subject to changes and upgrades that positively affected its performance. These effects on the surface hydrologic cycle are discussed by analyzing the period June 1995–May 2003. Prior to the model assessment, three gauge-based precipitation analyses that are potential sources of model validation are appraised. A fairly large disparity between the gridded precipitation analyses is found in the long-term area averages over the Columbia basin (∼23% difference) and over the Colorado basin (∼12% difference). These discrepancies are due to the type of analysis scheme employed and whether an orographic correction was applied.
The basin-averaged Eta Model precipitation forecasts correlate well with the observations at monthly time scales and, after 1999, show a small bias. Over the Columbia basin, the model precipitation bias is typically positive. This bias is significantly smaller with respect to orographically corrected precipitation analyses, indicating that the model’s large-scale precipitation processes respond reasonably well to orographic effects, though manifesting a higher bias during the cool season. Over the Colorado basin, the model precipitation bias is typically negative, and notably more so with respect to 1) the orographically corrected precipitation analyses and 2) the warm season, indicating shortfalls in the convection scheme over arid high mountains.
The mean fields of the hydrological variables in the Eta Model are in qualitative agreement with those from the Variable Infiltration Capacity (VIC) macroscale hydrologic model at regional-to-large scales. As expected, the largest differences are found near mountains and the western coastline. While the mean fields of precipitation, evaporation, runoff, and normalized soil moisture are in general agreement, important differences arise in their mean annual cycle over the two basins: snowmelt in the Eta Model precedes that of VIC by 2 months, and this phase shift is also reflected in the other variables. In the last 3–4 yr of the study period, notable improvements are evident in the quality of the model’s precipitation forecast and in the reduction of the residual term of the surface water balance, suggesting that at least similar (or better) quality will be found in studies based on NCEP’s recently completed Eta Model–based North American regional reanalysis.
Multiscale Variability of the River Runoff System in China and Its Long-Term Link to Precipitation and Sea Surface Temperature
Authors: Xue Yongkang , Ji Jinjun , Sun Shufen , Wu Guoxiong , Lau K-M. , Poccard Isabelle , Kang Hyun-Suk , Zhang Renhe , Schaake John C. , Zhang Jian Yun , Jiao Yanjun 
Published: September 2005

Abstract
This is an exploratory study to investigate the spatial and temporal characteristics of east China’s (EC) river runoff and their relationship with precipitation and sea surface temperature (SST) at the continental scale. Monthly mean data from 72 runoff stations and 160 precipitation stations in EC, covering a period between 1951 and 1983, are used for this study. The station river runoff data have been spatially interpolated onto 1° grid boxes as runoff depth based on an extracted drainage network. Comparing runoff depth with precipitation shows that seasonal variation in runoff is consistent with the development of the summer monsoon, including the delayed response of runoff in several subregions. The dominant spatial scales and temporal patterns of summer runoff and precipitation are studied with empirical orthogonal function (EOF) analysis and wavelet analyses. The analyses show interannual, biennial, and longer-term variations in the EOF modes. South–north dipole anomaly patterns for the first two runoff EOF’s spatial distributions have been identified. The first/second runoff principal components (PCs) are highly correlated with the second/first precipitation PCs, respectively. The summer runoff’s EOF PCs also show significant correlations with the multivariate El Niño–Southern Oscillation index (MEI) of the summer and winter months, while the summer precipitation PCs do not. Statistic analysis shows that EOF1 of runoff and EOF2 of precipitation are related to El Niño, while EOF2 of runoff and EOF1 of precipitation are related to a dipole SST anomaly over the northwestern Pacific. The interdecadal relationship between summer runoff, precipitation, and SST variability is further studied by singular value decomposition (SVD) analysis. Pronounced warming (SST) and drying (runoff) trends in first SVD PCs have been identified. These SVDs are used to reconstruct a decadal anomaly pattern, which produces flooding in part of the Chang Jiang River basin and dryness in the northern EC, consistent with observations.
Validation of GOES-Based Insolation Estimates Using Data from the U.S. Climate Reference Network
Authors: Otkin Jason A. , Anderson Martha C. , Mecikalski John R. , Diak George R. 
Published: September 2005

Abstract
Reliable procedures that accurately map surface insolation over large domains at high spatial and temporal resolution are a great benefit for making the predictions of potential and actual evapotranspiration that are required by a variety of hydrological and agricultural applications. Here, estimates of hourly and daily integrated insolation at 20-km resolution, based on Geostationary Operational Environmental Satellite (GOES) visible imagery are compared to pyranometer measurements made at 11 sites in the U.S. Climate Reference Network (USCRN) over a continuous 15-month period. Such a comprehensive survey is necessary in order to examine the accuracy of the satellite insolation estimates over a diverse range of seasons and land surface types. The relatively simple physical model of insolation that is tested here yields good results, with seasonally averaged model errors of 62 (19%) and 15 (10%) W m−2 for hourly and daily-averaged insolation, respectively, including both clear- and cloudy-sky conditions. This level of accuracy is comparable, or superior, to results that have been obtained with more complex models of atmospheric radiative transfer. Model performance can be improved in the future by addressing a small elevation-related bias in the physical model, which is likely the result of inaccurate model precipitable water inputs or cloud-height assessments.
The Stroke unit Discharge Guideline, a prognostic framework for the discharge outcome from the hospital stroke unit. A prospective cohort study
Authors: Meijer R , van Limbeek J , Peusens G , Rulkens M , Dankoor K , Vermeulen M , de Haan R J 
Published: September 2005

Objective: To investigate which factors during the subacute phase post stroke have predictive value for the discharge outcome from the hospital stroke unit. Methods: In a prospective cohort of 338 patients admitted to a hospital stroke unit 26 potentially prognostic factors, arranged in clinical and social subdomains, were scored and analysed by binary logistic regression analysis. The outcome of the research consisted of the various discharge destinations. Results: The overall predictive value of the discharge model is high (91%). Factors predictive of a poor discharge outcome are a low Barthel Index score (odds ratio (OR) 0.78 per point increase; p &lt 0.001), a poor sitting balance (OR 5.96; p &lt 0.001), a depression (OR 7.23; p &lt 0.001), poststroke cognitive disability (OR 3.51; p = 0.007) and older age (OR 1.05 per point increase; p = 0.008). If present, a personality disorder, premorbid cognitive disability and premorbid functional disability all show a tendency towards poor discharge outcome, but these factors did not reach statistical significance in this study, possibly due to their low prevalence. Readiness of the family circle to provide support was only significant in the univariate analysis. Conclusions: Somatic, biological and psychological factors predict the discharge outcome. Functional and cognitive factors play a decisive role in the future ability to live independently after a stroke. The prognostic importance of social factors could not be demonstrated. Urinary incontinence did not emerge as a prognostic factor. This is in contrast to scientific findings till now, but in accordance with clinical experience.
A new method for predicting functional recovery of stroke patients with hemiplegia: logarithmic modelling
Authors: Koyama Tetsuo , Matsumoto Kenji , Okuno Taiji , Domen Kazuhisa 
Published: September 2005

Objective: To examine the validity and applicability of logarithmic modelling for predicting functional recovery of stroke patients with hemiplegia. Design: Longitudinal postal survey. Subjects: Stroke patients with hemiplegia staying in a long-term rehabilitation facility, who had been referred from acute medical service 30-60 days after onset. Methods: Functional Independence Measure (FIM) scores were periodically assessed during hospitalization. For each individual, a logarithmic formula that was scaled by an interval increase in FIM scores during the initial 2-6 weeks was used for predicting functional recovery. Results: For the study, we recruited 18 patients who showed a wide variety of disability levels on admission (FIM scores 25-107). For each patient, the predicted FIM scores derived from the logarithmic formula matched the actual change in FIM scores. The changes predicted the recovery of motor rather than cognitive functions. Regression analysis showed a close fit between logarithmic modelling and actual FIM scores (across-subject R2 = 0.945). Conclusions: Provided with two initial time-point samplings, logarithmic modelling allows accurate prediction of functional recovery for individuals. Because the modelling is mathematically simple, it can be widely applied in daily clinical practice.
Electromyography characterization of stretch responses in hemiparetic stroke patients and their relationship with the Modified Ashworth Scale
Authors: Cooper A , Musa I M , van Deursen R , Wiles C M 
Published: September 2005

Objectives: To determine the validity of the Modified Ashworth Scale as a measure of spasticity by determining its relationship to surface electromyography activity and contracture. Design: A controlled study of hemiparetic stroke patients with spasticity. Setting: A physiotherapy department in a secondary care hospital. Subjects: Thirty-one stroke patients and 20 healthy volunteers. Main measures: The resistance to passive movement around the knee and ankle of the affected and unaffected legs was rated using the Modified Ashworth Scale. Passive range of movement was measured with a goniometer. Surface electromyography recordings of four lower limb muscles were taken during passive stretches of the knee and ankle. Results: Hemiparetic patients produced surface electromyography responses to stretch that were of greater amplitude (unaffected limbs: mean = 25.82 mV (43.85), affected limbs: mean = 24.77 mV (35.46)) than those of healthy volunteers (mean = 15.85 (29.96)). The affected muscles of hemiparetic patients were more likely to produce surface electromyography responses to stretch of a sustained duration (45% of cases) compared with unaffected limbs (24% of cases) and those of healthy volunteers (16% of cases). The Modified Ashworth Scale showed a positive correlation with the magnitude ( p &lt 0.05) and duration ( p &lt 0.001) of the surface electromyography response. High scores on the Modified Ashworth Scale were associated with contracture ( p &lt 0.001). Contracted muscles produced significantly greater surface electromyography reflex responses compared with noncontracted muscles ( p &lt 0.05). Conclusion: The Modified Ashworth Scale reflects spasticity in terms of surface electromyography stretch responses produced by passive movement, but the relationship of spasticity to contracture remains unclear.
Reliability of the Positive and Negative Affect Schedule (PANAS) in medical rehabilitation
Authors: Ostir Glenn V , Smith Pamela M , Smith David , Ottenbacher Kenneth J 
Published: September 2005

Objective: To examine the reliability of the Positive and Negative Affect Schedule (PANAS) in patients 90 and 100 days after discharge from inpatient medical rehabilitation. Design: A prospective study. Subjects: A convenience sample of 31 medical rehabilitation patients. Main measures: The PANAS. Results: The average age was 74 years, 80.7% were female and the average length of stay was 13 days. The test-retest intraclass correlation (ICC) values for the positive and negative affect scales (at the 90 and 100 day follow-up assessment) were 0.79 and 0.93, respectively. Conclusions: Our results show that the PANAS has excellent reliability among a sample of patients who received inpatient medical rehabilitation.