bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tumor Cell and Tumor Vasculature Expression of B7-H3 Predict Survival in Clear Cell Renal Cell Carcinoma
Authors: Crispen Paul L. , Sheinin Yuri , Roth Timothy J. , Lohse Christine M. , Kuntz Susan M. , Frigola Xavier , Thompson R. Houston , Boorjian Stephen A. , Dong Haidong , Leibovich Bradley C. , Blute Michael L. , Kwon Eugene D. 
Published: August 2008

Abstract
Purpose: Although the prognostic value of B7-H1 and B7-H4 expression by tumor cells in clear cell renal cell carcinoma (ccRCC) has been established, the role of B7-H3 is unknown. As such, we evaluated the association of B7-H3 expression with clinicopathologic outcomes in patients treated for ccRCC.
Experimental Design: Nephrectomy specimens from 743 consecutive patients treated for ccRCC at our institution from 1990 to 1999 were evaluated for B7-H3 expression by immunohistochemical staining. Associations of B7-H3 expression with clinical and pathologic features were evaluated using χ2 and Fisher's exact tests. Associations of B7-H3 expression with death from RCC were evaluated using Cox proportional hazards regression models.
Results: B7-H3 expression by tumor cells or tumor vasculature was noted in 17% and 95% of specimens, respectively. The presence of either tumor cell or diffuse tumor vasculature expression of B7-H3 was present in 46% of specimens and was associated with multiple adverse clinical and pathologic features. After multivariable adjustment, the presence of either tumor cell or diffuse tumor vasculature B7-H3 expression was significantly associated with an increased risk of death from RCC (risk ratio, 1.38; 95% confidence interval, 1.03-1.84; P = 0.029).
Conclusions: Both tumor cell and tumor vasculature B7-H3 expression convey important information to predict ccRCC outcomes. Collectively, our past and present studies pertaining to B7-H ligand expression indicate that ccRCC may use redundant mechanisms to compromise host antitumoral immunity. Future studies will focus on the effect of combined B7-H ligand expression in RCC.
Effects of Accentual Fall on Phrase-Final Vowel Duration in Japanese
Authors: Mori Yôko , Erickson Donna 
Published: August 2008

Abstract
This study explores the effect of accentual fall on phrase-final vowel duration in read declarative sentences of Standard Japanese. The results show that an intonational phrase-final vowel is significantly shorter when the final phrase has an accentual pitch fall than when it does not. Previous studies have reported a vowel-shortening effect for the final position of Japanese declarative sentences; the new finding reported in this paper is that this shortening effect is enhanced by the pitch fall of an accent in the sentence-final phrase.
Kaiser Konstantin der Große und der Apostel Paulus
Authors: Staats Reinhart 
Published: August 2008

AbstractThe article tries to demonstrate the leading theological ideas underlying several statements of the first Christian emperor. Sources were drawn from the Constantinian legislation and the direct quotations of Constantine from the texts of Eusebius, omitting the often strange interpretations of this churchfather. There are seven parallels between Constantine's laws and the letters of the apostle Paul, three of them evident: 1. Sunday as a day of rest corresponds to Constantine's title “fundator quietis” and coins with the inscription “beata tranquillitas” (cf. 1 Tim 2,2). 2. The laws on slavery, especially the release of slaves “in ecclesiae gremio” (cf. letter to Philemon, 1 Cor 7,21 etc.) 3. The episcopal court “audientia episcopalis” (cf. 1Cor 6, 1-8). Four other parallels between the apostle's life and the life of Constantine are discussed. Finally, all the western theologians and bishops behind Constantine in the years after 310 will be introduced.
Development and Evaluation of a Coupled Photosynthesis-Based Gas Exchange Evapotranspiration Model (GEM) for Mesoscale Weather Forecasting Applications
Authors: Niyogi Dev , Alapaty Kiran , Raman Sethu , Chen Fei 
Published: August 2008

Abstract
Current land surface schemes used for mesoscale weather forecast models use the Jarvis-type stomatal resistance formulations for representing the vegetation transpiration processes. The Jarvis scheme, however, despite its robustness, needs significant tuning of the hypothetical minimum-stomatal resistance term to simulate surface energy balances. In this study, the authors show that the Jarvis-type stomatal resistance/transpiration model can be efficiently replaced in a coupled land–atmosphere model with a photosynthesis-based scheme and still achieve dynamically consistent results. To demonstrate this transformative potential, the authors developed and coupled a photosynthesis, gas exchange–based surface evapotranspiration model (GEM) as a land surface scheme for mesoscale weather forecasting model applications. The GEM was dynamically coupled with a prognostic soil moisture–soil temperature model and an atmospheric boundary layer (ABL) model. This coupled system was then validated over different natural surfaces including temperate C4 vegetation (prairie grass and corn field) and C3 vegetation (soybean, fallow, and hardwood forest) under contrasting surface conditions (such as different soil moisture and leaf area index). Results indicated that the coupled model was able to realistically simulate the surface fluxes and the boundary layer characteristics over different landscapes. The surface energy fluxes, particularly for latent heat, are typically within 10%–20% of the observations without any tuning of the biophysical–vegetation characteristics, and the response to the changes in the surface characteristics is consistent with observations and theory. This result shows that photosynthesis-based transpiration/stomatal resistance models such as GEM, despite various complexities, can be applied for mesoscale weather forecasting applications. Future efforts for understanding the different scaling parameterizations and for correcting errors for low soil moisture and/or wilting vegetation conditions are necessary to improve model performance. Results from this study suggest that the GEM approach using the photosynthesis-based soil vegetation atmosphere transfer (SVAT) scheme is thus superior to the Jarvis-based approaches. Currently GEM is being implemented within the Noah land surface model for the community Weather Research and Forecasting (WRF) Advanced Research Version Modeling System (ARW) and the NCAR high-resolution land data assimilation system (HRLDAS), and validation is under way.
Surface Heterogeneity Effects on Regional-Scale Fluxes in Stable Boundary Layers: Surface Temperature Transitions
Authors: Stoll Rob , Porté-Agel Fernando 
Published: August 2008

Abstract
Large-eddy simulation, with recently developed dynamic subgrid-scale models, is used to study the effect of heterogeneous surface temperature distributions on regional-scale turbulent fluxes in the stable boundary layer (SBL). Simulations are performed of a continuously turbulent SBL with surface heterogeneity added in the form of streamwise transitions in surface temperature. Temperature differences between patches of 6 and 3 K are explored with patch length scales ranging from one-half to twice the equivalent homogeneous boundary layer height. The surface temperature heterogeneity has important effects on the mean wind speed and potential temperature profiles as well as on the surface heat flux distribution. Increasing the difference between the patch temperatures results in decreased magnitude of the average surface heat flux, with a corresponding increase in the mean potential temperature in the boundary layer. The simulation results are also used to test existing models for average surface fluxes over heterogeneous terrain. The tested models fail to fully represent the average turbulent heat flux, with models that break the domain into homogeneous subareas grossly underestimating the heat flux magnitude over patches with relatively colder surface temperatures. Motivated by these results, a new parameterization based on local similarity theory is proposed. The new formulation is found to correct the bias over the cold patches, resulting in improved average surface heat flux calculations.
Long-Range Niño-3.4 Predictions Using Pairwise Dynamic Combinations of Multiple Models
Authors: Chowdhury Shahadat , Sharma Ashish 
Published: August 2008

Abstract
The interest in climate prediction has seen a rise in the number of modeling alternatives in recent years. One way to reduce the predictive uncertainty from any such modeling procedure is to combine or average the modeled outputs. Multiple model results can be combined such that the combination weights may either be static or vary over time. This research develops a methodology for combining forecasts from multiple models in a dynamic setting. The authors mix models on a pairwise basis using importance weights that vary in time, reflecting the persistence of individual model skills. Such an approach is referred to here as a dynamic pairwise combination tree and is presented as an improvement over the case where the importance weights are static or constant over time. The pairwise importance weight is modeled as a product of a “mixture ratio” and a “bias direction,” the former representing the fraction of the absolute residual error associated with each of the paired models, and the latter representing an indicator of the sign of the two residual errors. The mixture ratio is modeled using a generalized autoregressive model and the bias direction using ordered logistic regression.
The method is applied to combine three climate models, the variables of interest being the monthly sea surface temperature anomalies averaged over the Niño-3.4 region from 1956 to 2001. The authors test the combined model skill using a “leave ± 6 months out cross-validation” approach along with validation in 10-yr blocks. This study attained a small but consistent improvement of the predictive skill of the dynamically combined models compared to the existing practice of static weight combination.
The Mid-1970s Climate Shift in the Pacific and the Relative Roles of Forced versus Inherent Decadal Variability
Authors: Meehl Gerald A. , Hu Aixue , Santer Benjamin D. 
Published: August 2008

Abstract
A significant shift from cooler to warmer tropical Pacific sea surface temperatures (SSTs), part of a pattern of basinwide SST anomalies involved with a transition to the positive phase of the Interdecadal Pacific Oscillation (IPO), occurred in the mid-1970s with effects that extended globally. One view is that this change was entirely natural and was a product of internally generated decadal variability of the Pacific climate system. However, during the mid-1970s there was also a significant increase of global temperature and changes to a number of other quantities that have been associated with changes in external forcings, particularly increases of greenhouse gases from the burning of fossil fuels. Analysis of observations, an unforced control run from a global coupled climate model, and twentieth-century simulations with changes in external forcings show that the observed 1970s climate shift had a contribution from changes in external forcing superimposed on what was likely an inherent decadal fluctuation of the Pacific climate system. Thus, this inherent decadal variability associated with the IPO delayed until the 1970s what likely would have been a forced climate shift in the 1960s from a negative to positive phase of the IPO.
Methods and processes for the reanalysis of the NINDS tissue plasminogen activator for acute ischemic stroke treatment trial
Authors: Hertzberg Vicki , Ingall Timothy , O'Fallon William , Asplund Kjell , Goldfrank Lewis , Louis Thomas , Christianson Teresa 
Published: August 2008

Background Treatment group imbalances in baseline stroke severity in the NINDS intravenous t-PA for acute stroke treatment trial led to controversy regarding the efficacy of tissue plasminogen activator (t-PA) in the treatment of acute ischemic stroke. Purpose Describe the steps used to independently re-evaluate this trial. Methods NIH appointed an independent multidisciplinary committee that gained access to the original data. We undertook analyses of t-PA efficacy accounting for this imbalance, as well as analyses to identify subgroups that experienced additional harm or benefit from t-PA. Analyses of time from stroke onset to treatment (OTT), blood pressure, and intracerebral hemorrhage are given as illustrations. Results Despite subgroup imbalances in baseline stroke severity, when t-PA was administered to acute ischemic stroke patients according to study protocol, there was a statistically significant and clinically important benefit of t-PA treatment resulting in a higher likelihood of having a favorable clinical outcome at 3 months. Moreover, we were unable to identify subgroups of patients between which t-PA treatment effect differed, albeit these analyses had low power. These data failed to support the NINDS investigators' conclusion that effect of t-PA therapy diminished with increasing values of OTT within the protocol-specified 3 h time limit. In addition, the blood pressure measurements were highly variable and inconsistently determined so as to be too unreliable for inclusion in analysis. Conclusion With new NIH requirements for data-sharing, the frequency of re-analysis of clinical trial data may increase substantially. This re-evaluation provides a blueprint for future re-evaluations of other trials. These best practices include re-analysis of the study data, after suitable replication, by an independent multidisciplinary committee, including a skilled statistical programmer analyst. Primary investigators should address significant errors determined in such re-analyses. Clinical Trials 2008; 5: 308—315. http://ctj.sagepub.com
Restricted randomization of ZAMSTAR: a 2 × 2 factorial cluster randomized trial
Authors: Sismanidis Charalambos , Moulton Lawrence H , Ayles Helen , Fielding Katherine , Schaap Ab , Beyers Nulda , Bond Ginny , Godfrey-Faussett Peter , Hayes Richard 
Published: August 2008

Background A small number of clusters and substantial variation between clusters increase the chance of unbalanced randomization in cluster randomized trials. Baseline imbalances between groups may distort intervention effects. When adjusting for imbalances in the cluster-level analysis, this results in loss of degrees of freedom. Variance reduction that can be achieved through stratification and blocking is limited. Restricted randomization is an alternative approach that ensures balanced allocation. Purpose We present the randomization scheme used in the ZAMSTAR trial of tuberculosis control interventions in Southern Africa. Methods We used stratification and restriction to randomize 24 clusters (16 Zambian, 8 South African) into four intervention groups in a 2 × 2 factorial design. Stratification was by country and tuberculous infection prevalence and restriction by tuberculous infection prevalence, HIV prevalence, urban/rural, social context, and geographical location. Balance was defined in terms of covariate-specific tolerance thresholds for the measure of imbalance. For binary (0/1) covariates we defined imbalance = max(Si) - min(Si), where, Si was the number of 1s in group i = 1,2,3,4. For continuous covariates we defined imbalance = (max(Mi) - min(Mi))/ min(Mi ), where, M i was the average in group i = 1,2,3,4. We used simulation to estimate the restriction factor (proportion of unacceptable allocations) both for individual covariates and overall. Simulation was also used to investigate the validity of the restricted randomization design, with the use of the validity matrix, by monitoring the probability that any given pair of clusters is allocated to the same intervention group. Results There were 3 657 930 400 possible ways of allocating the 24 clusters to the four groups after stratification. With a combined restriction factor of 0.998 this still left 7 million acceptable allocations. The final allocation was selected at a public ceremony from a randomly-generated list of acceptable allocations. The design of the allocation process was observed to be valid. Limitations The restricted randomization scheme significantly decreased the total number of available allocations of clusters into intervention groups. Conclusion Our restricted randomization was successful in that it achieved good balance while preserving the impartiality and validity of the trial. Clinical Trials 2008; 5: 316—327. http://ctj.sagepub.com
Generation of HIV-1–specific CD8+ cell responses following allogeneic hematopoietic cell transplantation
Authors: Woolfrey Ann E. , Malhotra Uma , Harrington Robert D. , McNevin John , Manley Thomas J. , Riddell Stanley R. , Coombs Robert W. , Appelbaum Frederick R. , Corey Larry , Storb Rainer 
Published: August 2008

AbstractThis study tested whether donor-derived HIV-specific immune responses could be detected when viral replication was completely suppressed by the continuous administration of highly active antiretroviral therapy (HAART). A regimen of fludarabine and 200 cGy total body irradiation was followed by infusion of allogeneic donor peripheral blood cells and posttransplantation cyclosporine and mycophenolate mofetil. Viral load, lymphocyte counts, and HIV-1–specific CD8+ cell immune responses were compared before and after hematopoietic cell transplantation (HCT). Uninterrupted administration of HAART was feasible during nonmyeloablative conditioning and after HCT. The HIV RNA remained undetectable and no HIV-associated infections were observed. CD8+ T-cell responses targeting multiple epitopes were detected before HCT. After HCT a different pattern of donor-derived HIV-specific CTL responses emerged by day +80, presumably primed in vivo. We conclude that allogeneic HCT offers the unique ability to characterize de novo HIV-1–specific immune responses. This clinical trial was registered at ClinicalTrials.gov (identifier: NCT00112593).
Neutrophil elastase reduces secretion of secretory leukoproteinase inhibitor (SLPI) by lung epithelial cells: role of charge of the proteinase-inhibitor complex
Authors: Sullivan Anita L , Dafforn Timothy , Hiemstra Pieter S , Stockley Robert A 
Published: August 2008

Abstract

Background
Secretory leukoproteinase inhibitor (SLPI) is an important inhibitor of neutrophil elastase (NE), a proteinase implicated in the pathogenesis of lung diseases such as COPD. SLPI also has antimicrobial and anti-inflammatory properties, but the concentration of SLPI in lung secretions in COPD varies inversely with infection and the concentration of NE. A fall in SLPI concentration is also seen in culture supernatants of respiratory cells exposed to NE, for unknown reasons. We investigated the hypothesis that SLPI complexed with NE associates with cell membranes in vitro.

Methods
Respiratory epithelial cells were cultured in the presence of SLPI, varying doses of proteinases over time, and in different experimental conditions. The likely predicted charge of the complex between SLPI and proteinases was assessed by theoretical molecular modelling.

Results
We observed a rapid, linear decrease in SLPI concentration in culture supernatants with increasing concentration of NE and cathepsin G, but not with other serine proteinases. The effect of NE was inhibited fully by a synthetic NE inhibitor only when added at the same time as NE. Direct contact between NE and SLPI was required for a fall in SLPI concentration. Passive binding to cell culture plate materials was able to remove a substantial amount of SLPI both with and without NE. Theoretical molecular modelling of the structure of SLPI in complex with various proteinases showed a greater positive charge for the complex with NE and cathepsin G than for other proteinases, such as trypsin and mast cell tryptase, that also bind SLPI but without reducing its concentration.

Conclusion
These data suggest that NE-mediated decrease in SLPI is a passive, charge-dependent phenomenon in vitro, which may correlate with changes observed in vivo.
New time-scale criteria for model simplification of bio-reaction systems
Authors: Choi Junwon , Yang Kyung-won , Lee Tai-yong , Lee Sang Yup 
Published: August 2008

Abstract

Background
Quasi-steady state approximation (QSSA) based on time-scale analysis is known to be an effective method for simplifying metabolic reaction system, but the conventional analysis becomes time-consuming and tedious when the system is large. Although there are automatic methods, they are based on eigenvalue calculations of the Jacobian matrix and on linear transformations, which have a high computation cost. A more efficient estimation approach is necessary for complex systems.

Results
This work derived new time-scale factor by focusing on the problem structure. By mathematically reasoning the balancing behavior of fast species, new time-scale criteria were derived with a simple expression that uses the Jacobian matrix directly. The algorithm requires no linear transformation or decomposition of the Jacobian matrix, which has been an essential part for previous automatic time-scaling methods. Furthermore, the proposed scale factor is estimated locally. Therefore, an iterative procedure was also developed to find the possible multiple boundary layers and to derive an appropriate reduced model.

Conclusion
By successive calculation of the newly derived time-scale criteria, it was possible to detect multiple boundary layers of full ordinary differential equation (ODE) models. Besides, the iterative procedure could derive the appropriate reduced differential algebraic equation (DAE) model with consistent initial values, which was tested with simple examples and a practical example.
A structural approach for finding functional modules from large biological networks
Authors: Mete Mutlu , Tang Fusheng , Xu Xiaowei , Yuruk Nurcan 
Published: August 2008

AbstractBackgroundBiological systems can be modeled as complex network systems with many interactions between the components. These interactions give rise to the function and behavior of that system. For example, the protein-protein interaction network is the physical basis of multiple cellular functions. One goal of emerging systems biology is to analyze very large complex biological networks such as protein-protein interaction networks, metabolic networks, and regulatory networks to identify functional modules and assign functions to certain components of the system. Network modules do not occur by chance, so identification of modules is likely to capture the biologically meaningful interactions in large-scale PPI data. Unfortunately, existing computer-based clustering methods developed to find those modules are either not so accurate or too slow.ResultsWe devised a new methodology called SCAN (Structural Clustering Algorithm for Networks) that can efficiently find clusters or functional modules in complex biological networks as well as hubs and outliers. More specifically, we demonstrated that we can find functional modules in complex networks and classify nodes into various roles based on their structures. In this study, we showed the effectiveness of our methodology using the budding yeast (Saccharomyces cerevisiae) protein-protein interaction network. To validate our clustering results, we compared our clusters with the known functions of each protein. Our predicted functional modules achieved very high purity comparing with state-of-the-art approaches. Additionally the theoretical and empirical analysis demonstrated a linear running-time of the algorithm, which is the fastest approach for networks.ConclusionWe compare our algorithm with well-known modularity based clustering algorithm CNM. We successfully detect functional groups that are annotated with putative GO terms. Top-10 clusters with minimum p-value theoretically prove that newly proposed algorithm partitions network more accurately then CNM. Furthermore, manual interpretations of functional groups found by SCAN show superior performance over CNM.