bluuebunny/crossref_metadata_2025_split huggingface dataset:
The question of a relation between the Parallel Growths of Crystals and Isomorphous Miscibility, and the bearing of Parallel Growths on questions of Isomorphism
Authors: Barker Thomas Vipond 
Published: December 2006

One of the most important and striking properties of isomorphous substances is their capacity for forming microscopically homogeneous mixed crystals, the physical properties of which are, as Retgers has especially shown, intermediate between the properties of the constituents. With the great majority of isomorphous substances the mixed crystals can be obtained in all proportions, but with others the miscibility is limited.The first case of restricted miscibility was discovered by Retgers in potassium phosphate (mol. vo1.=58.25) and ammonium phosphate (64.17) crystallizing in the tetragonal system ; he did not determine the exact proportions which each salt can take up of the other, but estimated them to be about 20 per cent. each way.
On the occurrence of Gyrolite in County Antrim
Authors: Fleischmann F. N. A. 
Published: December 2006

Although the mineral gyrolite has long been known to occur in the British Isles, namely in the basalt lavas of Skye, Mull, and the Treshnish Islands, &c., off the west coast of Scotland, and has more recently been described from the cliffs between Ardtornish Bay and the fault of Dearg Allt in Argyllshire on the mainland, no instance of its occurrence in the lavas of the north of Ireland has hitherto been recorded.The examination, however, of a large number of specimens collected both for me and by myself during the past year and a half has shown that the mineral, though occurring in small quantity relative to the other zeolites with which it is associated, is fairly widely distributed throughout the harder lavas in the neighbourhood of Belfast.
Selective targeting of the LIGHT-HVEM costimulatory system for the treatment of graft-versus-host disease
Authors: Xu Yanhui , Flies Andrew S. , Flies Dallas B. , Zhu Gefeng , Anand Sudarshan , Flies Sarah J. , Xu Haiying , Anders Robert A. , Hancock Wayne W. , Chen Lieping , Tamada Koji 
Published: December 2006

Abstract
Decoy lymphotoxin β receptor (LTβR) has potent immune inhibitory activities and thus represents a promising biologic for the treatment of inflammation, autoimmune diseases, and graft-versus-host disease (GVHD). As this reagent interrupts multiple molecular interactions, including LTβ-LTβR and LIGHT-HVEM/LTβR, underlying molecular mechanisms have yet to be fully understood. In this study, we demonstrate that blockade of the LIGHT-HVEM pathway is sufficient to induce amelioration of GVHD in mouse models. Anti–host cytotoxic T lymphocyte (CTL) activity following in vivo transfer of allogeneic lymphocytes was completely abrogated when LIGHT- or HVEM-deficient (KO) T cells were used as donor cells. Accordingly, survival of the recipient mice following the transfer of allogeneic bone marrow cells plus LIGHT-KO or HVEM-KO T cells was significantly prolonged. In the absence of LIGHT-HVEM costimulation, alloreactive donor T cells undergo vigorous apoptosis while their proliferative potential remains intact. Furthermore, we prepared a neutralizing monoclonal antibody (mAb) specific to HVEM and showed that administration of anti–HVEM mAb profoundly ameliorated GVHD and led to complete hematopoietic chimerism with donor cells. Collectively, our results demonstrate an indispensable role of LIGHT-HVEM costimulation in the pathogenesis of GVHD and illustrate a novel target for selective immunotherapy in allogeneic bone marrow transplantation.
Intensity-based hierarchical Bayes method improves testing for differentially expressed genes in microarray experiments
Authors: Sartor Maureen A , Tomlinson Craig R , Wesselkamper Scott C , Sivaganesan Siva , Leikauf George D , Medvedovic Mario 
Published: December 2006

AbstractBackgroundThe small sample sizes often used for microarray experiments result in poor estimates of variance if each gene is considered independently. Yet accurately estimating variability of gene expression measurements in microarray experiments is essential for correctly identifying differentially expressed genes. Several recently developed methods for testing differential expression of genes utilize hierarchical Bayesian models to "pool" information from multiple genes. We have developed a statistical testing procedure that further improves upon current methods by incorporating the well-documented relationship between the absolute gene expression level and the variance of gene expression measurements into the general empirical Bayes framework.ResultsWe present a novel Bayesian moderated-T, which we show to perform favorably in simulations, with two real, dual-channel microarray experiments and in two controlled single-channel experiments. In simulations, the new method achieved greater power while correctly estimating the true proportion of false positives, and in the analysis of two publicly-available "spike-in" experiments, the new method performed favorably compared to all tested alternatives. We also applied our method to two experimental datasets and discuss the additional biological insights as revealed by our method in contrast to the others. The R-source code for implementing our algorithm is freely available athttp://eh3.uc.edu/ibmt.ConclusionWe use a Bayesian hierarchical normal model to define a novel Intensity-Based Moderated T-statistic (IBMT). The method is completely data-dependent using empirical Bayes philosophy to estimate hyperparameters, and thus does not require specification of any free parameters. IBMT has the strength of balancing two important factors in the analysis of microarray data: the degree of independence of variances relative to the degree of identity (i.e.t-tests vs. equal variance assumption), and the relationship between variance and signal intensity. When this variance-intensity relationship is weak or does not exist, IBMT reduces to a previously described moderated t-statistic. Furthermore, our method may be directly applied to any array platform and experimental design. Together, these properties show IBMT to be a valuable option in the analysis of virtually any microarray experiment.
NERBio: using selected word conjunctions, term normalization, and global patterns to improve biomedical named entity recognition
Authors: Tsai Richard Tzong-Han , Sung Cheng-Lung , Dai Hong-Jie , Hung Hsieh-Chuan , Sung Ting-Yi , Hsu Wen-Lian 
Published: December 2006

Abstract

Background
Biomedical named entity recognition (Bio-NER) is a challenging problem because, in general, biomedical named entities of the same category (e.g., proteins and genes) do not follow one standard nomenclature. They have many irregularities and sometimes appear in ambiguous contexts. In recent years, machine-learning (ML) approaches have become increasingly common and now represent the cutting edge of Bio-NER technology. This paper addresses three problems faced by ML-based Bio-NER systems. First, most ML approaches usually employ singleton features that comprise one linguistic property (e.g., the current word is capitalized) and at least one class tag (e.g., B-protein, the beginning of a protein name). However, such features may be insufficient in cases where multiple properties must be considered. Adding conjunction features that contain multiple properties can be beneficial, but it would be infeasible to include all conjunction features in an NER model since memory resources are limited and some features are ineffective. To resolve the problem, we use a sequential forward search algorithm to select an effective set of features. Second, variations in the numerical parts of biomedical terms (e.g., "2" in the biomedical term IL2) cause data sparseness and generate many redundant features. In this case, we apply numerical normalization, which solves the problem by replacing all numerals in a term with one representative numeral to help classify named entities. Third, the assignment of NE tags does not depend solely on the target word's closest neighbors, but may depend on words outside the context window (e.g., a context window of five consists of the current word plus two preceding and two subsequent words). We use global patterns generated by the Smith-Waterman local alignment algorithm to identify such structures and modify the results of our ML-based tagger. This is called pattern-based post-processing.

Results
To develop our ML-based Bio-NER system, we employ conditional random fields, which have performed effectively in several well-known tasks, as our underlying ML model. Adding selected conjunction features, applying numerical normalization, and employing pattern-based post-processing improve the F-scores by 1.67%, 1.04%, and 0.57%, respectively. The combined increase of 3.28% yields a total score of 72.98%, which is better than the baseline system that only uses singleton features.

Conclusion
We demonstrate the benefits of using the sequential forward search algorithm to select effective conjunction feature groups. In addition, we show that numerical normalization can effectively reduce the number of redundant and unseen features. Furthermore, the Smith-Waterman local alignment algorithm can help ML-based Bio-NER deal with difficult cases that need longer context windows.
Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach
Authors: Lin HH , Han LY , Zhang HL , Zheng CJ , Xie B , Cao ZW , Chen YZ 
Published: December 2006

Abstract
Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting metal-binding proteins irrespective of sequence similarity. This work explores support vector machines (SVM) as such a method. SVM prediction systems were developed by using 53,333 metal-binding and 147,347 non-metal-binding proteins, and evaluated by an independent set of 31,448 metal-binding and 79,051 non-metal-binding proteins. The computed prediction accuracy is 86.3%, 81.6%, 83.5%, 94.0%, 81.2%, 85.4%, 77.6%, 90.4%, 90.9%, 74.9% and 78.1% for calcium-binding, cobalt-binding, copper-binding, iron-binding, magnesium-binding, manganese-binding, nickel-binding, potassium-binding, sodium-binding, zinc-binding, and all metal-binding proteins respectively. The accuracy for the non-member proteins of each class is 88.2%, 99.9%, 98.1%, 91.4%, 87.9%, 94.5%, 99.2%, 99.9%, 99.9%, 98.0%, and 88.0% respectively. Comparable accuracies were obtained by using a different SVM kernel function. Our method predicts 67% of the 87 metal-binding proteins non-homologous to any protein in the Swissprot database and 85.3% of the 333 proteins of known metal-binding domains as metal-binding. These suggest the usefulness of SVM for facilitating the prediction of metal-binding proteins. Our software can be accessed at the SVMProt server http://jing.cz3.nus.edu.sg/cgi-bin/svmprot.cgi.
SVM-based prediction of caspase substrate cleavage sites
Authors: Wee Lawrence JK , Tan Tin Wee , Ranganathan Shoba 
Published: December 2006

Abstract

Background
Caspases belong to a class of cysteine proteases which function as critical effectors in apoptosis and inflammation by cleaving substrates immediately after unique sites. Prediction of such cleavage sites will complement structural and functional studies on substrates cleavage as well as discovery of new substrates. Recently, different computational methods have been developed to predict the cleavage sites of caspase substrates with varying degrees of success. As the support vector machines (SVM) algorithm has been shown to be useful in several biological classification problems, we have implemented an SVM-based method to investigate its applicability to this domain.

Results
A set of unique caspase substrates cleavage sites were obtained from literature and used for evaluating the SVM method. Datasets containing (i) the tetrapeptide cleavage sites, (ii) the tetrapeptide cleavage sites, augmented by two adjacent residues, P1' and P2' amino acids and (iii) the tetrapeptide cleavage sites with ten additional upstream and downstream flanking sequences (where available) were tested. The SVM method achieved an accuracy ranging from 81.25% to 97.92% on independent test sets. The SVM method successfully predicted the cleavage of a novel caspase substrate and its mutants.

Conclusion
This study presents an SVM approach for predicting caspase substrate cleavage sites based on the cleavage sites and the downstream and upstream flanking sequences. The method shows an improvement over existing methods and may be useful for predicting hitherto undiscovered cleavage sites.
An evaluation of human protein-protein interaction data in the public domain
Authors: Mathivanan Suresh , Periaswamy Balamurugan , Gandhi TKB , Kandasamy Kumaran , Suresh Shubha , Mohmood Riaz , Ramachandra YL , Pandey Akhilesh 
Published: December 2006

Abstract

Background
Protein-protein interaction (PPI) databases have become a major resource for investigating biological networks and pathways in cells. A number of publicly available repositories for human PPIs are currently available. Each of these databases has their own unique features with a large variation in the type and depth of their annotations.

Results
We analyzed the major publicly available primary databases that contain literature curated PPI information for human proteins. This included BIND, DIP, HPRD, IntAct, MINT, MIPS, PDZBase and Reactome databases. The number of binary non-redundant human PPIs ranged from 101 in PDZBase and 346 in MIPS to 11,367 in MINT and 36,617 in HPRD. The number of genes annotated with at least one interactor was 9,427 in HPRD, 4,975 in MINT, 4,614 in IntAct, 3,887 in BIND and <1,000 in the remaining databases. The number of literature citations for the PPIs included in the databases was 43,634 in HPRD, 11,480 in MINT, 10,331 in IntAct, 8,020 in BIND and <2,100 in the remaining databases.

Conclusion
Given the importance of PPIs, we suggest that submission of PPIs to repositories be made mandatory by scientific journals at the time of manuscript submission as this will minimize annotation errors, promote standardization and help keep the information up to date. We hope that our analysis will help guide biomedical scientists in selecting the most appropriate database for their needs especially in light of the dramatic differences in their content.
Evaluation and comparison of mammalian subcellular localization prediction methods
Authors: Sprenger Josefine , Fink J Lynn , Teasdale Rohan D 
Published: December 2006

Abstract

Background
Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance.

Results
In order to perform a comprehensive survey of prediction methods, we selected only methods that accepted large batches of protein sequences, were publicly available, and were able to predict localization to at least nine of the major subcellular locations (nucleus, cytosol, mitochondrion, extracellular region, plasma membrane, Golgi apparatus, endoplasmic reticulum (ER), peroxisome, and lysosome). The selected methods were CELLO, MultiLoc, Proteome Analyst, pTarget and WoLF PSORT. These methods were evaluated using 3763 mouse proteins from SwissProt that represent the source of the training sets used in development of the individual methods. In addition, an independent evaluation set of 2145 mouse proteins from LOCATE with a bias towards the subcellular localization underrepresented in SwissProt was used. The sensitivity and specificity were calculated for each method and compared to a theoretical value based on what might be observed by random chance.

Conclusion
No individual method had a sufficient level of sensitivity across both evaluation sets that would enable reliable application to hypothetical proteins. All methods showed lower performance on the LOCATE dataset and variable performance on individual subcellular localizations was observed. Proteins localized to the secretory pathway were the most difficult to predict, while nuclear and extracellular proteins were predicted with the highest sensitivity.
Prediction of desmoglein-3 peptides reveals multiple shared T-cell epitopes in HLA DR4- and DR6- associated Pemphigus vulgaris
Authors: Tong Joo Chuan , Tan Tin Wee , Sinha Animesh A , Ranganathan Shoba 
Published: December 2006

AbstractBackgroundPemphigus vulgaris (PV) is a severe autoimmune blistering skin disorder that is strongly associated with major histocompatibility complex class II alleles DRB1*0402 and DQB1*0503. The target antigen of PV, desmoglein 3 (Dsg3), is crucial for initiating T-cell response in early disease. Although a number of T-cell specificities within Dsg3 have been reported, the number is limited and the role of T-cells in the pathogenesis of PV remains poorly understood. We report here a structure-based model for the prediction of peptide binding to DRB1*0402 and DQB1*0503. The scoring functions were rigorously trained, tested and validated using experimentally verified peptide sequences.ResultsHigh predictivity is obtained for both DRB1*0402 (r2= 0.90,s= 1.20 kJ/mol,q2= 0.82,spress= 1.61 kJ/mol) and DQB1*0503 (r2= 0.95,s= 1.20 kJ/mol,q2= 0.75,spress= 2.15 kJ/mol) models, compared to experimental data. We investigated the binding patterns of Dsg3 peptides and illustrate the existence of multiple immunodominant epitopes that may be responsible for both disease initiation and propagation in PV. Further analysis reveals that DRB1*0402 and DQB1*0503 may share similar specificities by binding peptides at different binding registers, thus providing a molecular mechanism for the dual HLA association observed in PV.ConclusionCollectively, the results of this study provide interesting new insights into the pathology of PV. This is the first report illustrating high-level of cross-reactivity between both PV-implicated alleles, DRB1*0402 and DQB1*0503, as well as the existence of a potentially large number of T-cell epitopes throughout the entire Dsg3 extracellular domain (ECD) and transmembrane region. Our results reveal that DR4 and DR6 PV may initiate in the ECD and transmembrane region respectively, with implications for immunotherapeutic strategies for the treatment of this autoimmune disease.
Computational promoter analysis of mouse, rat and human antimicrobial peptide-coding genes
Authors: Brahmachary Manisha , Schönbach Christian , Yang Liang , Huang Enli , Tan Sin Lam , Chowdhary Rajesh , Krishnan SPT , Lin Chin-Yo , Hume David A , Kai Chikatoshi , Kawai Jun , Carninci Piero , Hayashizaki Yoshihide , Bajic Vladimir B 
Published: December 2006

Abstract

Background
Mammalian antimicrobial peptides (AMPs) are effectors of the innate immune response. A multitude of signals coming from pathways of mammalian pathogen/pattern recognition receptors and other proteins affect the expression of AMP-coding genes (AMPcgs). For many AMPcgs the promoter elements and transcription factors that control their tissue cell-specific expression have yet to be fully identified and characterized.

Results
Based upon the RIKEN full-length cDNA and public sequence data derived from human, mouse and rat, we identified 178 candidate AMP transcripts derived from 61 genes belonging to 29 AMP families. However, only for 31 mouse genes belonging to 22 AMP families we were able to determine true orthologous relationships with 30 human and 15 rat sequences. We screened the promoter regions of AMPcgs in the three species for motifs by an ab initio motif finding method and analyzed the derived promoter characteristics. Promoter models were developed for alpha-defensins, penk and zap AMP families. The results suggest a core set of transcription factors (TFs) that regulate the transcription of AMPcg families in mouse, rat and human. The three most frequent core TFs groups include liver-, nervous system-specific and nuclear hormone receptors (NHRs). Out of 440 motifs analyzed, we found that three represent potentially novel TF-binding motifs enriched in promoters of AMPcgs, while the other four motifs appear to be species-specific.

Conclusion
Our large-scale computational analysis of promoters of 22 families of AMPcgs across three mammalian species suggests that their key transcriptional regulators are likely to be TFs of the liver-, nervous system-specific and NHR groups. The computationally inferred promoter elements and potential TF binding motifs provide a rich resource for targeted experimental validation of TF binding and signaling studies that aim at the regulation of mouse, rat or human AMPcgs.
XenopusDab2 is required for embryonic angiogenesis
Authors: Cheong Seong-Moon , Choi Sun-Cheol , Han Jin-Kwan 
Published: December 2006

Abstract

Background
The molecular mechanisms governing the formation of the embryonic vascular system remain poorly understood. Here, we show that Disabled-2 (Dab2), a cytosolic adaptor protein, has a pivotal role in the blood vessel formation in Xenopus early embryogenesis.

Results

Xenopus Disabled-2 (XDab2) is spatially localized to the blood vessels including the intersomitic veins (ISV) in early embryos. Both antisense morpholino oligonucleotide (MO)-mediated knockdown and overexpression of XDab2 inhibit the formation of ISV, which arise from angiogenesis. In addition, we found that activin-like signaling is essential for this angiogenic event. Functional assays in Xenopus animal caps reveal that activin-like signals induce VEGF expression and this induction can be inhibited by XDab2 depletion. However, XDab2 MO has no effects on the induction of other target genes by activin-like signals. Furthermore, we show that the disruption of the sprouting ISV in XDab2-depleted embryos can be rescued by coexpression of VEGF.

Conclusion
Taking together, we suggest that XDab2 regulates the embryonic angiogenesis by mediating the VEGF induction by activin-like signaling in Xenopus early development.