bluuebunny/crossref_metadata_2025_split huggingface dataset:
Trends in Intense Precipitation in the Climate Record
Authors: Groisman Pavel Ya , Knight Richard W. , Easterling David R. , Karl Thomas R. , Hegerl Gabriele C. , Razuvaev Vyacheslav N. 
Published: May 2005

AbstractObserved changes in intense precipitation (e.g., the frequency of very heavy precipitation or the upper 0.3% of daily precipitation events) have been analyzed for over half of the land area of the globe. These changes have been linked to changes in intense precipitation for three transient climate model simulations, all with greenhouse gas concentrations increasing during the twentieth and twenty-first centuries and doubling in the later part of the twenty-first century. It was found that both the empirical evidence from the period of instrumental observations and model projections of a greenhouse-enriched atmosphere indicate an increasing probability of intense precipitation events for many extratropical regions including the United States. Although there can be ambiguity as to the impact of more frequent heavy precipitation events, the thresholds of the definitions of these events were raised here, such that they are likely to be disruptive. Unfortunately, reliable assertions of very heavy and extreme precipitation changes are possible only for regions with dense networks due to the small radius of correlation for many intense precipitation events.
Interdecadal Change in Properties of El Niño–Southern Oscillation in an Intermediate Coupled Model
Authors: Zhang Rong-Hua , Busalacchi Antonio J. 
Published: May 2005

AbstractThe role of subsurface temperature variability in modulating El Niño–Southern Oscillation (ENSO) properties is examined using an intermediate coupled model (ICM), consisting of an intermediate dynamic ocean model and a sea surface temperature (SST) anomaly model. An empirical procedure is used to parameterize the temperature of subsurface water entrained into the mixed layer (Te) from sea level (SL) anomalies via a singular value decomposition (SVD) analysis for use in simulating sea surface temperature anomalies (SSTAs). The ocean model is coupled to a statistical atmospheric model that estimates wind stress anomalies also from an SVD analysis. Using the empirical Te models constructed from two subperiods, 1963–79 (T63–79e) and 1980–96 (T80–96e), the coupled system exhibits strikingly different properties of interannual variability (the oscillation period, spatial structure, and temporal evolution). For the T63–79e model, the system features a 2-yr oscillation and westward propagation of SSTAs on the equator, while for the T80–96e model, it is characterized by a 5-yr oscillation and eastward propagation. These changes in ENSO properties are consistent with the behavior shift of El Niño observed in the late 1970s. Heat budget analyses further demonstrate a controlling role played by the vertical advection of subsurface temperature anomalies in determining the ENSO properties.
Contribution of Changes in Sea Surface Temperature and Aerosol Loading to the Decreasing Precipitation Trend in Southern China
Authors: Cheng Yanjie , Lohmann Ulrike , Zhang Junhua , Luo Yunfeng , Liu Zuoting , Lesins Glen 
Published: May 2005

Abstract
The effects of increasing sea surface temperature (SST) and aerosol loading in a drought region in Southern China are studied using aerosol optical depth (AOD), low-level cloud cover (LCC), visibility, and precipitation from observed surface data; wind, temperature, specific humidity, and geopotential height from the NCEP–NCAR reanalysis fields; and SST from the NOAA archive data. The results show a warming of the SST in the South China Sea and the Indian Ocean, and a strengthening of the West Pacific Subtropical High (WPSH) in the early summer during the last 40 yr, with the high pressure system extending farther westward over the continent in Southern China. Because the early summer average temperature contrast between the land and ocean decreased, the southwesterly monsoon from the ocean onto mainland China weakened and a surface horizontal wind divergence anomaly occurred over Southern China stabilizing the boundary layer. Thus, less moisture was transported to Southern China, causing a drying trend. Despite this, surface observations show that AOD and LCC have increased, while visibility has decreased. Precipitation has decreased in this region in the early summer, consistent with both the second aerosol indirect effect (reduction in precipitation efficiency caused by the more numerous and smaller cloud droplets) and dynamically induced changes from convective to more stratiform clouds. The second aerosol indirect effect and increases in SST and greenhouse gases (GHG) were simulated separately with the ECHAM4 general circulation model (GCM). The GCM results suggest that both effects contribute to the changes in LCC and precipitation in the drought region in Southern China. The flooding trend in Eastern China, however, is more likely caused by strengthened convective precipitation associated with increases in SST and GHG.
A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility: Part I: Low-Level Cloud Macrophysical, Microphysical, and Radiative Properties
Authors: Dong Xiquan , Minnis Patrick , Xi Baike 
Published: May 2005

Abstract
A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 h of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant mixed-phase low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (re) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (τ), effective solar transmission (γ), and cloud/top-of-atmosphere albedos (Rcldy/RTOA) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations. In general, more stratus clouds occur during winter and spring than in summer. Cloud-layer altitudes and physical thicknesses were higher and greater in summer than in winter with averaged physical thicknesses of 0.85 and 0.73 km for day and night, respectively. The seasonal variations of LWP, LWC, N, τ, Rcldy, and RTOA basically follow the same pattern with maxima and minima during winter and summer, respectively. There is no significant variation in mean re, however, despite a summertime peak in aerosol loading. Although a considerable degree of variability exists, the 6-yr average values of LWP, LWC, re, N, τ, γ, Rcldy, and RTOA are 151 gm−2 (138), 0.245 gm−3 (0.268), 8.7 μm (8.5), 213 cm−3 (238), 26.8 (24.8), 0.331, 0.672, and 0.563 for daytime (nighttime). A new conceptual model of midlatitude continental low clouds at the ARM SGP site has been developed from this study. The low stratus cloud amount monotonically increases from midnight to early morning (0930 LT), and remains large until around local noon, then declines until 1930 LT when it levels off for the remainder of the night. In the morning, the stratus cloud layer is low, warm, and thick with less LWC, while in the afternoon it is high, cold, and thin with more LWC. Future parts of this series will consider other cloud types and cloud radiative forcing at the ARM SCF.
Observed Trends and Teleconnections of the Siberian High: A Recently Declining Center of Action
Authors: Panagiotopoulos Fotis , Shahgedanova Maria , Hannachi Abdelwaheb , Stephenson David B. 
Published: May 2005

Abstract
This study investigates variability in the intensity of the wintertime Siberian high (SH) by defining a robust SH index (SHI) and correlating it with selected meteorological fields and teleconnection indices. A dramatic trend of –2.5 hPa decade−1 has been found in the SHI between 1978 and 2001 with unprecedented (since 1871) low values of the SHI. The weakening of the SH has been confirmed by analyzing different historical gridded analyses and individual station observations of sea level pressure (SLP) and excluding possible effects from the conversion of surface pressure to SLP.
SHI correlation maps with various meteorological fields show that SH impacts on circulation and temperature patterns extend far outside the SH source area extending from the Arctic to the tropical Pacific. Advection of warm air from eastern Europe has been identified as the main mechanism causing milder than normal conditions over the Kara and Laptev Seas in association with a strong SH. Despite the strong impacts of the variability in the SH on climatic variability across the Northern Hemisphere, correlations between the SHI and the main teleconnection indices of the Northern Hemisphere are weak. Regression analysis has shown that teleconnection indices are not able to reproduce the interannual variability and trends in the SH. The inclusion of regional surface temperature in the regression model provides closer agreement between the original and reconstructed SHI.
Formation, Mechanisms, and Predictability of the Aleutian–Icelandic Low Seesaw in Ensemble AGCM Simulations
Authors: Honda Meiji , Kushnir Yochanan , Nakamura Hisashi , Yamane Shozo , Zebiak Stephen E. 
Published: May 2005

Abstract
The potential predictability associated with the remote influence of midlatitude tropospheric anomalies over the North Pacific or the North Atlantic, via a seesawlike interannual oscillation between the surface Aleutian and Icelandic lows (AL and IL, respectively) is investigated. Data from a 24-member ensemble of 50-yr atmospheric general circulation model simulation forced with observed sea surface temperature (SST) conditions are analyzed by separating the total simulated fluctuations into the external component forced by the prescribed SST and the internal component generated by atmospheric internal dynamics. The AL–IL seesaw can be identified in both the external and internal components of the variability. In the external variability, determined through the ensemble mean, the seesaw is gradually formed from December to March through the development of a Pacific–North American (PNA) pattern–like wave train, remotely forced by the El Niño–Southern Oscillation. The amplitudes of the externally forced North Atlantic anomalies are only about half as large as the North Pacific anomalies. The potential predictability of the Atlantic anomalies, defined as the ratio of the SST-forced variance to the total variance, does not exceed the 20% level. In the internal component of the variability, determined from the deviations of each ensemble member from the ensemble mean, the negative correlation between the AL and IL anomalies is modest but persistent through winter. It is confirmed that, regardless of the polarity of the AL–IL seesaw, the IL anomalies are formed through eastward wave activity propagation of the stationary Rossby wave train emanating from the AL region in the form of what may be called a “PNAA pattern,” the extension of the PNA-like wave train into the Atlantic. Thus, the midwinter development of North Pacific anomalies is found to be a necessary, though not sufficient, condition for the seesaw formation. The persistence of the North Pacific anomalies beyond a 1-month time span appears to augment the probability of the seesaw formation by sustaining eastward wave activity propagation to the North Atlantic.
Short-term variability of biomarkers of proteinase activity in patients with emphysema associated with type Z alpha-1-antitrypsin deficiency
Authors: Stolk Jan , Veldhuisen Barbara , Annovazzi Laura , Zanone Chiara , Versteeg Elly M , van Kuppevelt Toine H , Nieuwenhuizen Willem , Iadarola Paolo , Luisetti Maurizio 
Published: May 2005

Abstract

Background
The burden of proteinases from inflammatory cells in the lung of subjects with type Pi ZZ of alpha-1-antitrypsin deficiency is higher than in those without the deficiency. Cross-sectional studies have shown increased levels of biomarkers of extracellular matrix degradation in vivo. Longitudinal variability of these biomarkers is unknown but desirable for clinical studies with proteinase inhibitors.

Methods
We measured three different types of biomarkers, including desmosines, elastase-formed fibrinogen fragments and heparan sulfate epitope JM403, in plasma and urine for a period of 7 weeks in a group of 12 patients who participated in a placebo-controlled study to assess the safety of a single inhalation of hyaluronic acid.

Results
Effect of study medication on any of the biomarkers was not seen. Baseline desmosines in plasma and urine correlated with baseline CO diffusion capacity (R = 0.81, p = 0.01 and R = 0.65, p = 0.05). Mean coefficient of variation within patients (CVi) for plasma and urine desmosines was 18.7 to 13.5%, respectively. Change in urinary desmosine levels correlated significantly with change in plasma desmosine levels (R = 0.84, p < 0.01). Mean CVi for fibrinogen fragments in plasma was 20.5% and for JM403 in urine was 27.8%. No correlations were found between fibrinogen fragments or JM403 epitope and desmosines.

Conclusion
We found acceptable variability in our study parameters, indicating the feasibility of their use in an evaluation of biochemical efficacy of alpha-1-antitrypsin augmentation therapy in Pi Z subjects.
Characterization of the aggregates formed during recombinant protein expression in bacteria
Authors: Schrödel Andrea , de Marco Ario 
Published: May 2005

Abstract

Background
The first aim of the work was to analyze in detail the complexity of the aggregates formed upon overexpression of recombinant proteins in E. coli. A sucrose step gradient succeeded in separating aggregate subclasses of a GFP-GST fusion protein with specific biochemical and biophysical features, providing a novel approach for studying recombinant protein aggregates.

Results
The total lysate separated into 4 different fractions whereas only the one with the lowest density was detected when the supernatant recovered after ultracentrifugation was loaded onto the sucrose gradient. The three further aggregate sub-classes were otherwise indistinctly precipitated in the pellet. The distribution of the recombinant protein among the four subclasses was strongly dependent on the DnaK availability, with larger aggregates formed in Dnak- mutants. The aggregation state of the GFP-GST recovered from each of the four fractions was further characterized by examining three independent biochemical parameters. All of them showed an increased complexity of the recombinant protein aggregates starting from the top of the sucrose gradient (lower mass aggregates) to the bottom (larger mass aggregates). These results were also confirmed by electron microscopy analysis of the macro-structure formed by the different aggregates. Large fibrils were rapidly assembled when the recombinant protein was incubated in the presence of cellular extracts, but the GFP-GST fusion purified soon after lysis failed to undergo amyloidation, indicating that other cell components probably participate in the active formation of large aggregates. Finally, we showed that aggregates of lower complexity are more efficiently disaggregated by a combination of molecular chaperones.

Conclusion
An additional analytical tool is now available to investigate the aggregation process and separate subclasses by their mass. It was possible to demonstrate the complexity of the aggregation pattern of a recombinant protein expressed in bacteria and to characterize biochemically the different aggregate subclasses. Furthermore, we have obtained evidence that the cellular environment plays a role in the development of the aggregates and the problem of the artifact generation of aggregates has been discussed using in vitro models. Finally, the possibility of separating aggregate fractions with different complexities offers new options for biotechnological strategies aimed at improving the yield of folded and active recombinant proteins.
Considerations when using the significance analysis of microarrays (SAM) algorithm
Authors: Larsson Ola , Wahlestedt Claes , Timmons James A 
Published: May 2005

Abstract
Background
Users of microarray technology typically strive to use universally acceptable data analysis strategies to determine significant expression changes in their experiments. One of the most frequently utilised methods for gene expression data analysis is SAM (significance analysis of microarrays). The impact of selection thresholds, on the output from SAM, may critically alter the conclusion of a study, yet this consideration has not been systematically evaluated in any publication.

Results
We have examined the effect of discrete data selection criteria (qualification criteria for inclusion) and response thresholds (out-put filtering) on the number of significant genes reported by SAM. The use of a reduced data set by applying arbitrary restrictions vis-à-vis abundance calls (e.g. from D-chip) or application of the fold change (FC) option within SAM (named the FC hurdle hereafter), can substantially alter the significant gene list when running SAM in Microsoft Excel. We determined that for a given final FC criteria (e.g. 1.5 fold change) the FC hurdle applied within Microsoft Excel SAM alters the number of reported genes above the final FC criteria. The reason is that the FC hurdle changes the composition of the control data set, such that a different significance level (q-value) is obtained for any given gene. This effect can be so large that it changes subsequent post hoc analysis interpretation, such as ontology overrepresentation analysis.

Conclusion
Our results argue for caution when using SAM. All data sets analysed with SAM could be reanalysed taking into account the potential impact of the use of arbitrary thresholds to trim data sets before significance testing.
Vestige: Maximum likelihood phylogenetic footprinting
Authors: Wakefield Matthew J , Maxwell Peter , Huttley Gavin A 
Published: May 2005

Abstract
Background
Phylogenetic footprinting is the identification of functional regions of DNA by their evolutionary conservation. This is achieved by comparing orthologous regions from multiple species and identifying the DNA regions that have diverged less than neutral DNA. Vestige is a phylogenetic footprinting package built on the PyEvolve toolkit that uses probabilistic molecular evolutionary modelling to represent aspects of sequence evolution, including the conventional divergence measure employed by other footprinting approaches. In addition to measuring the divergence, Vestige allows the expansion of the definition of a phylogenetic footprint to include variation in the distribution of any molecular evolutionary processes. This is achieved by displaying the distribution of model parameters that represent partitions of molecular evolutionary substitutions. Examination of the spatial incidence of these effects across regions of the genome can identify DNA segments that differ in the nature of the evolutionary process.

Results
Vestige was applied to a reference dataset of the SCL locus from four species and provided clear identification of the known conserved regions in this dataset. To demonstrate the flexibility to use diverse models of molecular evolution and dissect the nature of the evolutionary process Vestige was used to footprint the Ka/Ks ratio in primate BRCA1 with a codon model of evolution. Two regions of putative adaptive evolution were identified illustrating the ability of Vestige to represent the spatial distribution of distinct molecular evolutionary processes.

Conclusion
Vestige provides a flexible, open platform for phylogenetic footprinting. Underpinned by the PyEvolve toolkit, Vestige provides a framework for visualising the signatures of evolutionary processes across the genome of numerous organisms simultaneously. By exploiting the maximum-likelihood statistical framework, the complex interplay between mutational processes, DNA repair and selection can be evaluated both spatially (along a sequence alignment) and temporally (for each branch of the tree) providing visual indicators to the attributes and functions of DNA sequences.
Gene finding in the chicken genome
Authors: Eyras Eduardo , Reymond Alexandre , Castelo Robert , Bye Jacqueline M , Camara Francisco , Flicek Paul , Huckle Elizabeth J , Parra Genis , Shteynberg David D , Wyss Carine , Rogers Jane , Antonarakis Stylianos E , Birney Ewan , Guigo Roderic , Brent Michael R 
Published: May 2005

Abstract
Background
Despite the continuous production of genome sequence for a number of organisms, reliable, comprehensive, and cost effective gene prediction remains problematic. This is particularly true for genomes for which there is not a large collection of known gene sequences, such as the recently published chicken genome. We used the chicken sequence to test comparative and homology-based gene-finding methods followed by experimental validation as an effective genome annotation method.

Results
We performed experimental evaluation by RT-PCR of three different computational gene finders, Ensembl, SGP2 and TWINSCAN, applied to the chicken genome. A Venn diagram was computed and each component of it was evaluated. The results showed that de novo comparative methods can identify up to about 700 chicken genes with no previous evidence of expression, and can correctly extend about 40% of homology-based predictions at the 5' end.

Conclusions
De novo comparative gene prediction followed by experimental verification is effective at enhancing the annotation of the newly sequenced genomes provided by standard homology-based methods.
Generating quantitative models describing the sequence specificity of biological processes with the stabilized matrix method
Authors: Peters Bjoern , Sette Alessandro 
Published: May 2005

Abstract
Background
Many processes in molecular biology involve the recognition of short sequences of nucleic-or amino acids, such as the binding of immunogenic peptides to major histocompatibility complex (MHC) molecules. From experimental data, a model of the sequence specificity of these processes can be constructed, such as a sequence motif, a scoring matrix or an artificial neural network. The purpose of these models is two-fold. First, they can provide a summary of experimental results, allowing for a deeper understanding of the mechanisms involved in sequence recognition. Second, such models can be used to predict the experimental outcome for yet untested sequences. In the past we reported the development of a method to generate such models called the Stabilized Matrix Method (SMM). This method has been successfully applied to predicting peptide binding to MHC molecules, peptide transport by the transporter associated with antigen presentation (TAP) and proteasomal cleavage of protein sequences.

Results
Herein we report the implementation of the SMM algorithm as a publicly available software package. Specific features determining the type of problems the method is most appropriate for are discussed. Advantageous features of the package are: (1) the output generated is easy to interpret, (2) input and output are both quantitative, (3) specific computational strategies to handle experimental noise are built in, (4) the algorithm is designed to effectively handle bounded experimental data, (5) experimental data from randomized peptide libraries and conventional peptides can easily be combined, and (6) it is possible to incorporate pair interactions between positions of a sequence.

Conclusion
Making the SMM method publicly available enables bioinformaticians and experimental biologists to easily access it, to compare its performance to other prediction methods, and to extend it to other applications.