bluuebunny/crossref_metadata_2025 huggingface dataset:
High-sensitivity detection of BCR-ABL kinase domain mutations in imatinib-naive patients: correlation with clonal cytogenetic evolution but not response to therapy
Authors: Willis Stephanie G. , Lange Thoralf , Demehri Shadmehr , Otto Sandra , Crossman Lucy , Niederwieser Dietger , Stoffregen Eric P. , McWeeney Shannon , Kovacs Ines , Park Byung , Druker Brian J. , Deininger Michael W.
Published: May 2005

Mutations in the kinase domain (KD) of BCR-ABL are the leading cause of acquired imatinib resistance. In some cases, identical mutations were detected at relapse and in pretherapeutic specimens, consistent with selection of resistant clones in the presence of drug. However, the incidence of KD mutations in imatinibnaive patients, irrespective of response to therapy, is unknown. We studied mutation frequency in 66 patients with chronic myelogenous leukemia (CML), using cDNA sequencing and allele-specific oligonucleotide-polymerase chain reaction (ASO-PCR) assays for 8 common mutations. Thirteen patients were positive by ASO-PCR only, 1 by ASO-PCR and sequencing, and 1 by sequencing only (overall frequency, 22.7%). T315I was most frequent (12% of patients). Eleven of the 14 patients with positive ASO-PCR had follow-up samples available for sequencing. Wild-type sequence was detected in 6 of 11, 2 different mutations in 1 of 11, and identical mutations in 4 of 11 patients, 2 of whom had achieved major cytogenetic response. In multivariate analysis mutation detection was associated with clonal cytogenetic evolution, exposure to 6-Thioguanine, and a low platelet count, but not with response to imatinib, event-free survival, and overall survival. KD mutants present at low levels do not invariably lead to relapse, and additional factors are required to induce a fully drug-resistant phenotype. (Blood. 2005; 106:2128-2137)
Genome comparison without alignment using shortest unique substrings
Authors: Haubold Bernhard , Pierstorff Nora , Möller Friedrich , Wiehe Thomas
Published: May 2005

Background

Sequence comparison by alignment is a fundamental tool of molecular biology. In this paper we show how a number of sequence comparison tasks, including the detection of unique genomic regions, can be accomplished efficiently without an alignment step. Our procedure for nucleotide sequence comparison is based on shortest unique substrings. These are substrings which occur only once within the sequence or set of sequences analysed and which cannot be further reduced in length without losing the property of uniqueness. Such substrings can be detected using generalized suffix trees.

Results

We find that the shortest unique substrings in Caenorhabditis elegans, human and mouse are no longer than 11 bp in the autosomes of these organisms. In mouse and human these unique substrings are significantly clustered in upstream regions of known genes. Moreover, the probability of finding such short unique substrings in the genomes of human or mouse by chance is extremely small. We derive an analytical expression for the null distribution of shortest unique substrings, given the GC-content of the query sequences. Furthermore, we apply our method to rapidly detect unique genomic regions in the genome of Staphylococcus aureus strain MSSA476 compared to four other staphylococcal genomes.

Conclusion

We combine a method to rapidly search for shortest unique substrings in DNA sequences and a derivation of their null distribution. We show that unique regions in an arbitrary sample of genomes can be efficiently detected with this method. The corresponding programs shustring (SHortest Unique subSTRING) and shulen are written in C and available at http://adenine.biz.fh-weihenstephan.de/shustring/.
arrayCGHbase: an analysis platform for comparative genomic hybridization microarrays
Authors: Menten Björn , Pattyn Filip , De Preter Katleen , Robbrecht Piet , Michels Evi , Buysse Karen , Mortier Geert , De Paepe Anne , van Vooren Steven , Vermeesch Joris , Moreau Yves , De Moor Bart , Vermeulen Stefan , Speleman Frank , Vandesompele Jo
Published: May 2005

Background

The availability of the human genome sequence as well as the large number of physically accessible oligonucleotides, cDNA, and BAC clones across the entire genome has triggered and accelerated the use of several platforms for analysis of DNA copy number changes, amongst others microarray comparative genomic hybridization (arrayCGH). One of the challenges inherent to this new technology is the management and analysis of large numbers of data points generated in each individual experiment.

Results

We have developed arrayCGHbase, a comprehensive analysis platform for arrayCGH experiments consisting of a MIAME (Minimal Information About a Microarray Experiment) supportive database using MySQL underlying a data mining web tool, to store, analyze, interpret, compare, and visualize arrayCGH results in a uniform and user-friendly format. Following its flexible design, arrayCGHbase is compatible with all existing and forthcoming arrayCGH platforms. Data can be exported in a multitude of formats, including BED files to map copy number information on the genome using the Ensembl or UCSC genome browser.

Conclusion

ArrayCGHbase is a web based and platform independent arrayCGH data analysis tool, that allows users to access the analysis suite through the internet or a local intranet after installation on a private server. ArrayCGHbase is available at http://medgen.ugent.be/arrayCGHbase/.
Overview of BioCreAtIvE: critical assessment of information extraction for biology
Authors: Hirschman Lynette , Yeh Alexander , Blaschke Christian , Valencia Alfonso
Published: May 2005

Background

The goal of the first BioCreAtIvE challenge (Critical Assessment of Information Extraction in Biology) was to provide a set of common evaluation tasks to assess the state of the art for text mining applied to biological problems. The results were presented in a workshop held in Granada, Spain March 28–31, 2004. The articles collected in this BMC Bioinformatics supplement entitled "A critical assessment of text mining methods in molecular biology" describe the BioCreAtIvE tasks, systems, results and their independent evaluation.

Results

BioCreAtIvE focused on two tasks. The first dealt with extraction of gene or protein names from text, and their mapping into standardized gene identifiers for three model organism databases (fly, mouse, yeast). The second task addressed issues of functional annotation, requiring systems to identify specific text passages that supported Gene Ontology annotations for specific proteins, given full text articles.

Conclusion

The first BioCreAtIvE assessment achieved a high level of international participation (27 groups from 10 countries). The assessment provided state-of-the-art performance results for a basic task (gene name finding and normalization), where the best systems achieved a balanced 80% precision / recall or better, which potentially makes them suitable for real applications in biology. The results for the advanced task (functional annotation from free text) were significantly lower, demonstrating the current limitations of text-mining approaches where knowledge extrapolation and interpretation are required. In addition, an important contribution of BioCreAtIvE has been the creation and release of training and test data sets for both tasks. There are 22 articles in this special issue, including six that provide analyses of results or data quality for the data sets, including a novel inter-annotator consistency assessment for the test set used in task 2.
Data preparation and interannotator agreement: BioCreAtIvE Task 1B
Authors: Colosimo Marc E , Morgan Alexander A , Yeh Alexander S , Colombe Jeffrey B , Hirschman Lynette
Published: May 2005

Background

We prepared and evaluated training and test materials for an assessment of text mining methods in molecular biology. The goal of the assessment was to evaluate the ability of automated systems to generate a list of unique gene identifiers from PubMed abstracts for the three model organisms Fly, Mouse, and Yeast. This paper describes the preparation and evaluation of answer keys for training and testing. These consisted of lists of normalized gene names found in the abstracts, generated by adapting the gene list for the full journal articles found in the model organism databases. For the training dataset, the gene list was pruned automatically to remove gene names not found in the abstract; for the testing dataset, it was further refined by manual annotation by annotators provided with guidelines. A critical step in interpreting the results of an assessment is to evaluate the quality of the data preparation. We did this by careful assessment of interannotator agreement and the use of answer pooling of participant results to improve the quality of the final testing dataset.

Results

Interannotator analysis on a small dataset showed that our gene lists for Fly and Yeast were good (87% and 91% three-way agreement) but the Mouse gene list had many conflicts (mostly omissions), which resulted in errors (69% interannotator agreement). By comparing and pooling answers from the participant systems, we were able to add an additional check on the test data; this allowed us to find additional errors, especially in Mouse. This led to 1% change in the Yeast and Fly "gold standard" answer keys, but to an 8% change in the mouse answer key.

Conclusion

We found that clear annotation guidelines are important, along with careful interannotator experiments, to validate the generated gene lists. Also, abstracts alone are a poor resource for identifying genes in paper, containing only a fraction of genes mentioned in the full text (25% for Fly, 36% for Mouse). We found that there are intrinsic differences between the model organism databases related to the number of synonymous terms and also to curation criteria. Finally, we found that answer pooling was much faster and allowed us to identify more conflicting genes than interannotator analysis.
Automatically annotating documents with normalized gene lists
Authors: Crim Jeremiah , McDonald Ryan , Pereira Fernando
Published: May 2005

Background

Document gene normalization is the problem of creating a list of unique identifiers for genes that are mentioned within a document. Automating this process has many potential applications in both information extraction and database curation systems. Here we present two separate solutions to this problem. The first is primarily based on standard pattern matching and information extraction techniques. The second and more novel solution uses a statistical classifier to recognize valid gene matches from a list of known gene synonyms.

Results

We compare the results of the two systems, analyze their merits and argue that the classification based system is preferable for many reasons including performance, simplicity and robustness. Our best systems attain a balanced precision and recall in the range of 74%–92%, depending on the organism.
ProMiner: rule-based protein and gene entity recognition
Authors: Hanisch Daniel , Fundel Katrin , Mevissen Heinz-Theodor , Zimmer Ralf , Fluck Juliane
Published: May 2005

Background

Identification of gene and protein names in biomedical text is a challenging task as the corresponding nomenclature has evolved over time. This has led to multiple synonyms for individual genes and proteins, as well as names that may be ambiguous with other gene names or with general English words. The Gene List Task of the BioCreAtIvE challenge evaluation enables comparison of systems addressing the problem of protein and gene name identification on common benchmark data.

Methods

The ProMiner system uses a pre-processed synonym dictionary to identify potential name occurrences in the biomedical text and associate protein and gene database identifiers with the detected matches. It follows a rule-based approach and its search algorithm is geared towards recognition of multi-word names [1]. To account for the large number of ambiguous synonyms in the considered organisms, the system has been extended to use specific variants of the detection procedure for highly ambiguous and case-sensitive synonyms. Based on all detected synonyms for one abstract, the most plausible database identifiers are associated with the text. Organism specificity is addressed by a simple procedure based on additionally detected organism names in an abstract.

Results

The extended ProMiner system has been applied to the test cases of the BioCreAtIvE competition with highly encouraging results. In blind predictions, the system achieved an F-measure of approximately 0.8 for the organisms mouse and fly and about 0.9 for the organism yeast.
A simple approach for protein name identification: prospects and limits
Authors: Fundel Katrin , Güttler Daniel , Zimmer Ralf , Apostolakis Joannis
Published: May 2005

Background

Significant parts of biological knowledge are available only as unstructured text in articles of biomedical journals. By automatically identifying gene and gene product (protein) names and mapping these to unique database identifiers, it becomes possible to extract and integrate information from articles and various data sources.

We present a simple and efficient approach that identifies gene and protein names in texts and returns database identifiers for matches. It has been evaluated in the recent BioCreAtIvE entity extraction and mention normalization task by an independent jury.

Methods

Our approach is based on the use of synonym lists that map the unique database identifiers for each gene/protein to the different synonym names. For yeast and mouse, synonym lists were used as provided by the organizers who generated them from public model organism databases. The synonym list for fly was generated directly from the corresponding organism database. The lists were then extensively curated in largely automated procedure and matched against MEDLINE abstracts by exact text matching. Rule-based and support vector machine-based post filters were designed and applied to improve precision.

Results

Our procedure showed high recall and precision with F-measures of 0.897 for yeast and 0.764/0.773 for mouse in the BioCreAtIvE assessment (Task 1B) and 0.768 for fly in a post-evaluation.

Conclusion

The results were close to the best over all submissions. Depending on the synonym properties it can be crucial to consider context and to filter out erroneous matches. This is especially important for fly, which has a very challenging nomenclature for the protein name identification task. Here, the support vector machine-based post filter proved to be very effective.
Evaluation of BioCreAtIvE assessment of task 2
Authors: Blaschke Christian , Leon Eduardo Andres , Krallinger Martin , Valencia Alfonso
Published: May 2005

Background

Molecular Biology accumulated substantial amounts of data concerning functions of genes and proteins. Information relating to functional descriptions is generally extracted manually from textual data and stored in biological databases to build up annotations for large collections of gene products. Those annotation databases are crucial for the interpretation of large scale analysis approaches using bioinformatics or experimental techniques. Due to the growing accumulation of functional descriptions in biomedical literature the need for text mining tools to facilitate the extraction of such annotations is urgent. In order to make text mining tools useable in real world scenarios, for instance to assist database curators during annotation of protein function, comparisons and evaluations of different approaches on full text articles are needed.

Results

The Critical Assessment for Information Extraction in Biology (BioCreAtIvE) contest consists of a community wide competition aiming to evaluate different strategies for text mining tools, as applied to biomedical literature. We report on task two which addressed the automatic extraction and assignment of Gene Ontology (GO) annotations of human proteins, using full text articles. The predictions of task 2 are based on triplets of protein – GO term – article passage. The annotation-relevant text passages were returned by the participants and evaluated by expert curators of the GO annotation (GOA) team at the European Institute of Bioinformatics (EBI). Each participant could submit up to three results for each sub-task comprising task 2. In total more than 15,000 individual results were provided by the participants. The curators evaluated in addition to the annotation itself, whether the protein and the GO term were correctly predicted and traceable through the submitted text fragment.

Conclusion

Concepts provided by GO are currently the most extended set of terms used for annotating gene products, thus they were explored to assess how effectively text mining tools are able to extract those annotations automatically. Although the obtained results are promising, they are still far from reaching the required performance demanded by real world applications. Among the principal difficulties encountered to address the proposed task, were the complex nature of the GO terms and protein names (the large range of variants which are used to express proteins and especially GO terms in free text), and the lack of a standard training set. A range of very different strategies were used to tackle this task. The dataset generated in line with the BioCreative challenge is publicly available and will allow new possibilities for training information extraction methods in the domain of molecular biology.
An evaluation of GO annotation retrieval for BioCreAtIvE and GOA
Authors: Camon Evelyn B , Barrell Daniel G , Dimmer Emily C , Lee Vivian , Magrane Michele , Maslen John , Binns David , Apweiler Rolf
Published: May 2005

Background

The Gene Ontology Annotation (GOA) database http://www.ebi.ac.uk/GOA aims to provide high-quality supplementary GO annotation to proteins in the UniProt Knowledgebase. Like many other biological databases, GOA gathers much of its content from the careful manual curation of literature. However, as both the volume of literature and of proteins requiring characterization increases, the manual processing capability can become overloaded.

Consequently, semi-automated aids are often employed to expedite the curation process. Traditionally, electronic techniques in GOA depend largely on exploiting the knowledge in existing resources such as InterPro. However, in recent years, text mining has been hailed as a potentially useful tool to aid the curation process.

To encourage the development of such tools, the GOA team at EBI agreed to take part in the functional annotation task of the BioCreAtIvE (Critical Assessment of Information Extraction systems in Biology) challenge.

BioCreAtIvE task 2 was an experiment to test if automatically derived classification using information retrieval and extraction could assist expert biologists in the annotation of the GO vocabulary to the proteins in the UniProt Knowledgebase.

GOA provided the training corpus of over 9000 manual GO annotations extracted from the literature. For the test set, we provided a corpus of 200 new Journal of Biological Chemistry articles used to annotate 286 human proteins with GO terms. A team of experts manually evaluated the results of 9 participating groups, each of which provided highlighted sentences to support their GO and protein annotation predictions. Here, we give a biological perspective on the evaluation, explain how we annotate GO using literature and offer some suggestions to improve the precision of future text-retrieval and extraction techniques. Finally, we provide the results of the first inter-annotator agreement study for manual GO curation, as well as an assessment of our current electronic GO annotation strategies.

Results

The GOA database currently extracts GO annotation from the literature with 91 to 100% precision, and at least 72% recall. This creates a particularly high threshold for text mining systems which in BioCreAtIvE task 2 (GO annotation extraction and retrieval) initial results precisely predicted GO terms only 10 to 20% of the time.

Conclusion

Improvements in the performance and accuracy of text mining for GO terms should be expected in the next BioCreAtIvE challenge. In the meantime the manual and electronic GO annotation strategies already employed by GOA will provide high quality annotations.
A sentence sliding window approach to extract protein annotations from biomedical articles
Authors: Krallinger Martin , Padron Maria , Valencia Alfonso
Published: May 2005

Background

Within the emerging field of text mining and statistical natural language processing (NLP) applied to biomedical articles, a broad variety of techniques have been developed during the past years. Nevertheless, there is still a great ned of comparative assessment of the performance of the proposed methods and the development of common evaluation criteria. This issue was addressed by the Critical Assessment of Text Mining Methods in Molecular Biology (BioCreative) contest. The aim of this contest was to assess the performance of text mining systems applied to biomedical texts including tools which recognize named entities such as genes and proteins, and tools which automatically extract protein annotations.

Results

The "sentence sliding window" approach proposed here was found to efficiently extract text fragments from full text articles containing annotations on proteins, providing the highest number of correctly predicted annotations. Moreover, the number of correct extractions of individual entities (i.e. proteins and GO terms) involved in the relationships used for the annotations was significantly higher than the correct extractions of the complete annotations (protein-function relations).

Conclusion

We explored the use of averaging sentence sliding windows for information extraction, especially in a context where conventional training data is unavailable. The combination of our approach with more refined statistical estimators and machine learning techniques might be a way to improve annotation extraction for future biomedical text mining applications.
BioCreAtIvE Task 1A: gene mention finding evaluation
Authors: Yeh Alexander , Morgan Alexander , Colosimo Marc , Hirschman Lynette
Published: May 2005

Background

The biological research literature is a major repository of knowledge. As the amount of literature increases, it will get harder to find the information of interest on a particular topic. There has been an increasing amount of work on text mining this literature, but comparing this work is hard because of a lack of standards for making comparisons. To address this, we worked with colleagues at the Protein Design Group, CNB-CSIC, Madrid to develop BioCreAtIvE (Critical Assessment for Information Extraction in Biology), an open common evaluation of systems on a number of biological text mining tasks. We report here on task 1A, which deals with finding mentions of genes and related entities in text. "Finding mentions" is a basic task, which can be used as a building block for other text mining tasks. The task makes use of data and evaluation software provided by the (US) National Center for Biotechnology Information (NCBI).

Results

15 teams took part in task 1A. A number of teams achieved scores over 80% F-measure (balanced precision and recall). The teams that tried to use their task 1A systems to help on other BioCreAtIvE tasks reported mixed results.

Conclusion

The 80% plus F-measure results are good, but still somewhat lag the best scores achieved in some other domains such as newswire, due in part to the complexity and length of gene names, compared to person or organization names in newswire.
Finding genomic ontology terms in text using evidence content
Authors: Couto Francisco M , Silva Mário J , Coutinho Pedro M
Published: May 2005

Background

The development of text mining systems that annotate biological entities with their properties using scientific literature is an important recent research topic. These systems need first to recognize the biological entities and properties in the text, and then decide which pairs represent valid annotations.

Methods

This document introduces a novel unsupervised method for recognizing biological properties in unstructured text, involving the evidence content of their names.

Results

This document shows the results obtained by the application of our method to BioCreative tasks 2.1 and 2.2, where it identified Gene Ontology annotations and their evidence in a set of articles.

Conclusion

From the performance obtained in BioCreative, we concluded that an automatic annotation system can effectively use our method to identify biological properties in unstructured text.
Mining protein function from text using term-based support vector machines
Authors: Rice Simon B , Nenadic Goran , Stapley Benjamin J
Published: May 2005

Background

Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents.

Results

The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent.

Conclusion

A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2.
Data-poor categorization and passage retrieval for Gene Ontology Annotation in Swiss-Prot
Authors: Ehrler Frédéric , Geissbühler Antoine , Jimeno Antonio , Ruch Patrick
Published: May 2005

Background

In the context of the BioCreative competition, where training data were very sparse, we investigated two complementary tasks: 1) given a Swiss-Prot triplet, containing a protein, a GO (Gene Ontology) term and a relevant article, extraction of a short passage that justifies the GO category assignement; 2) given a Swiss-Prot pair, containing a protein and a relevant article, automatic assignement of a set of categories.

Methods

Sentence is the basic retrieval unit. Our classifier computes a distance between each sentence and the GO category provided with the Swiss-Prot entry. The Text Categorizer computes a distance between each GO term and the text of the article. Evaluations are reported both based on annotator judgements as established by the competition and based on mean average precision measures computed using a curated sample of Swiss-Prot.

Results

Our system achieved the best recall and precision combination both for passage retrieval and text categorization as evaluated by official evaluators. However, text categorization results were far below those in other data-poor text categorization experiments The top proposed term is relevant in less that 20% of cases, while categorization with other biomedical controlled vocabulary, such as the Medical Subject Headings, we achieved more than 90% precision. We also observe that the scoring methods used in our experiments, based on the retrieval status value of our engines, exhibits effective confidence estimation capabilities.

Conclusion

From a comparative perspective, the combination of retrieval and natural language processing methods we designed, achieved very competitive performances. Largely data-independent, our systems were no less effective that data-intensive approaches. These results suggests that the overall strategy could benefit a large class of information extraction tasks, especially when training data are missing. However, from a user perspective, results were disappointing. Further investigations are needed to design applicable end-user text mining tools for biologists.
BioCreAtIvE Task1A: entity identification with a stochastic tagger
Authors: Kinoshita Shuhei , Cohen K Bretonnel , Ogren Philip V , Hunter Lawrence
Published: May 2005

Background

Our approach to Task 1A was inspired by Tanabe and Wilbur's ABGene system [1, 2]. Like Tanabe and Wilbur, we approached the problem as one of part-of-speech tagging, adding a GENE tag to the standard tag set. Where their system uses the Brill tagger, we used TnT, the Trigrams 'n' Tags HMM-based part-of-speech tagger [3]. Based on careful error analysis, we implemented a set of post-processing rules to correct both false positives and false negatives. We participated in both the open and the closed divisions; for the open division, we made use of data from NCBI.

Results

Our base system without post-processing achieved a precision and recall of 68.0% and 77.2%, respectively, giving an F-measure of 72.3%. The full system with post-processing achieved a precision and recall of 80.3% and 80.5% giving an F-measure of 80.4%. We achieved a slight improvement (F-measure = 80.9%) by employing a dictionary-based post-processing step for the open division. We placed third in both the open and the closed division.

Conclusion

Our results show that a part-of-speech tagger can be augmented with post-processing rules resulting in an entity identification system that competes well with other approaches.
Genetic islands of Streptococcus agalactiae strains NEM316 and 2603VR and their presence in other Group B Streptococcal strains
Authors: Herbert Mark A , Beveridge Catriona JE , McCormick David , Aten Emmelien , Jones Nicola , Snyder Lori AS , Saunders Nigel J
Published: May 2005

Background

Streptococcus agalactiae (Group B Streptococcus; GBS) is a major contributor to obstetric and neonatal bacterial sepsis. Serotype III strains cause the majority of late-onset sepsis and meningitis in babies, and thus appear to have an enhanced invasive capacity compared with the other serotypes that cause disease predominantly in immunocompromised pregnant women. We compared the serotype III and V whole genome sequences, strains NEM316 and 2603VR respectively, in an attempt to identify genetic attributes of strain NEM316 that might explain the propensity of strain NEM316 to cause late-onset disease in babies. Fourteen putative pathogenicity islands were described in the strain NEM316 whole genome sequence. Using PCR- and targeted microarray- strategies, the presence of these islands were assessed in a diverse strain collection including 18 colonizing isolates from healthy pregnant women, and 13 and 8 invasive isolates from infants with early- and late-onset sepsis, respectively.

Results

Side-by-side comparison of the strain NEM316 and strain 2603VR genomes revealed that they are extremely similar, with the only major difference being the capsulation loci and mobile genetic elements. PCR and Comparative Genome Hybridization (CGH) were used to define the presence of each island in 39 GBS isolates. Only islands I, VI, XII, and possibly X, met criteria of a true pathogenicity island, but no significant correlation was found between the presence of any of the fourteen islands and whether the strains were invasive or colonizing. Possible associations were seen between the presence of island VI and late-onset sepsis, and island X and early-onset sepsis, which warrant further investigation.

Conclusion

The NEM316 and 2603VR strains are remarkable in that their whole genome sequences are so similar, suggesting that the capsulation loci or other genetic differences, such as pathogenicity islands, are the main determinants of the propensity of serotype III strains to cause late-onset disease. This study supports the notion that GBS strain NEM316 has four putative pathogenicity islands, but none is absolutely necessary for disease causation, whether early- or late-onset sepsis. Mobile genetic elements are a common feature of GBS isolates, with each strain having its own peculiar burden of transposons, phages, integrases and integrated plasmids. The majority of these are unlikely to influence the disease capacity of an isolate. Serotype associated disease phenotypes may thus be solely related to differences in the capsulation loci.
Comparison of two recombinant erythropoietin formulations in patients with anemia due to end-stage renal disease on hemodialysis: A parallel, randomized, double blind study
Authors: Pérez-Oliva Jorge F , Casanova-González Martha , García-García Idrian , Porrero-Martín Pedro J , Valenzuela-Silva Carmen M , Hernández-Montero Tairí , Lagarde-Ampudia Marcia , Casanova-Kutsareva Yuri , Ávila-Albuerne Yisel , Vargas-Batista Alicia , Bobillo-López Hailen , Herrera-Valdés Raúl , López-Saura Pedro A ,   the Bioequivalence Study of Erythropoietin Group
Published: May 2005

Background

Recombinant human erythropoietin (EPO) is used for the treatment of last stage renal anemia. A new EPO preparation was obtained in Cuba in order to make this treatment fully nationally available. The aim of this study was to compare the pharmacokinetic, pharmacodynamic and safety properties of two recombinant EPO formulations in patients with anemia due to end-stage renal disease on hemodialysis.

Methods

A parallel, randomized, double blind study was performed. A single 100 IU/Kg EPO dose was administered subcutaneously. Heberitro (Heber Biotec, Havana, formulation A), a newly developed product and Eprex (CILAG AG, Switzerland, formulation B), as reference treatment were compared. Thirty-four patients with anemia due to end-stage renal disease on hemodialysis were included. Patients had not received EPO previously. Serum EPO level was measured by enzyme immunoassay (EIA) during 120 hours after administration. Clinical and laboratory variables were determined as pharmacodynamic and safety criteria until 216 hours.

Results

Both groups of patients were similar regarding all demographic and baseline characteristics. EPO kinetics profiles were similar for both formulations; the pharmacokinetic parameters were very close (i.e., AUC: 4667 vs. 4918 mIU.h/mL; Cmax: 119.1 vs. 119.7 mIU/mL; Tmax: 13.9 vs. 18.1 h; half-life, 20.0 vs. 22.5 h for formulations A and B, respectively). The 90% confidence intervals for the ratio between both products regarding these metrics were close to the 0.8 – 1.25 range, considered necessary for bioequivalence. Differences did not reach 20% in any case and were not determined by a formulation effect, but probably by a patients' variability effect. Concerning pharmacodynamic features, a high similitude in reticulocyte counts increments until 216 hours and the percentage decrease in serum iron until 120 hours was observed. There were no differences between formulations regarding the adverse events and their intensity. The more frequent events were pain at injection site (35.3%) and hypertension (29%). Additionally, further treatment of the patients with the study product yielded satisfactory increases in hemoglobin and hematocrit values.

Conclusion

The formulations are comparable. The newly developed product should be acceptable for long-term application.
Adenovirus-mediated interleukin-12 gene transfer combined with cytosine deaminase followed by 5-fluorocytosine treatment exerts potent antitumor activity in Renca tumor-bearing mice
Authors: Hwang Kyung-Sun , Cho Won-Kyung , Yoo Jinsang , Yun Hwan-Jung , Kim Samyong , Im Dong-Soo
Published: May 2005

Background

Therapeutic gene transfer affords a clinically feasible and safe approach to cancer treatment but a more effective modality is needed to improve clinical outcomes. Combined transfer of therapeutic genes with different modes of actions may be a means to this end. Interleukin-12 (IL-12), a heterodimeric immunoregulatory cytokine composed of covalently linked p35 and p40 subunits, has antitumor activity in animal models. The enzyme/prodrug strategy using cytosine deaminase (CD) and 5-fluorocytosine (5-FC) has been used for cancer gene therapy. We have evaluated the antitumor effect of combining IL-12 with CD gene transfer in mice bearing renal cell carcinoma (Renca) tumors.

Methods

Adenoviral vectors were constructed encoding one or both subunits of murine IL-12 (Ad.p35, Ad.p40 and Ad.IL-12) or cytosine deaminase (Ad.CD). The functionality of the IL-12 or CD gene products expressed from these vectors was validated by splenic interferon (IFN)-γ production or viability assays in cultured cells. Ad.p35 plus Ad.p40, or Ad.IL-12, with or without Ad.CD, were administered (single-dose) intratumorally to Renca tumor-bearing mice. The animals injected with Ad.CD also received 5-FC intraperitoneally. The antitumor effects were then evaluated by measuring tumor regression, mean animal survival time, splenic natural killer (NK) cell activity and IFN-γ production.

Results

The inhibition of tumor growth in mice treated with Ad.p35 plus Ad.p40 and Ad.CD, followed by injection of 5-FC, was significantly greater than that in mice treated with Ad.CD/5-FC, a mixture of Ad.p35 plus Ad.p40, or Ad.GFP (control). The combined gene transfer increased splenic NK cell activity and IFN-γ production by splenocytes. Ad.CD/5-FC treatment significantly increased the antitumor effect of Ad.IL-12 in terms of tumor growth inhibition and mean animal survival time.

Conclusion

The results suggest that adenovirus-mediated IL-12 gene transfer combined with Ad.CD followed by 5-FC treatment may be useful for treating cancers.
Colon cancer in Luxembourg: a national population-based data report, 1988–1998
Authors: Scheiden René , Pescatore Paul , Wagener Yolande , Kieffer Nelly , Capesius Catherine
Published: May 2005

Background

Over the last two decades time trends in incidence rates of colorectal cancer, changes in the proportions of stage at diagnosis and changes in the anatomic sub-site distribution of colon cancers have been reported in some European countries. In order to determine a strategy for early detection of colon cancer in the Grand-Duchy of Luxembourg, all consecutive colon adenocarcinomas diagnosed during the period 1988–1998 at a nation-wide level were reviewed.

Methods

The population-based data of the national Morphologic Tumour Registry report all new high-grade adenomas (i.e. high-grade intraepithelial adenomatous neoplasias) and all consecutive new invasive adenocarcinomas of the colon diagnosed in the central department of pathology. Attention has been focused on variations in incidence, stage, anatomical site distribution and survival rates. Rectal cancers were excluded.

Results

Over the study period, 254 new colonic high-grade adenomas and 1379 new invasive adenocarcinomas were found; the crude incidence rates of colon adenocarcinomas grew steadily by 30%. Comparing the two 5-year periods 1988–1992 and 1994–1998, the crude incidence rates of high-grade adenomas (stage 0) rose by 190%, that of stage I cases by 14.3%, stage II cases 12.9% and stage III cases 38.5%, whereas the crude incidence rates of stage IV cases decreased by 11.8%. The high-grade adenoma/adenocarcinoma ratio increased. The right-sided colonic adenocarcinomas in elderly patients (>69 years) increased by 76%. The observed survival rates correlated with tumour stages. The overall observed 5-year survival rate (stage I-IV) was 51 ± 3% (95% confidence interval).

Conclusion

The increasing incidence rates of colon adenocarcinomas, the persistence of advanced tumour stages (stage III), the mortality rates which remain stable, and the changing trends in the age- and sub-site distribution underline the need for preventive measures at the age of 50 in asymptomatic patients to reduce mortality from colo(rectal) cancer.
Efficacy of Wnt-1 monoclonal antibody in sarcoma cells
Authors: Mikami Iwao , You Liang , He Biao , Xu Zhidong , Batra Sonny , Lee Amie Y , Mazieres Julien , Reguart Noemi , Uematsu Kazutsugu , Koizumi Kiyoshi , Jablons David M
Published: May 2005

Background

Sarcomas are one of the most refractory diseases among malignant tumors. More effective therapies based on an increased understanding of the molecular biology of sarcomas are needed as current forms of therapy remain inadequate. Recently, it has been reported that Wnt-1/β-catenin signaling inhibits apoptosis in several cancers. In this study, we investigated the efficacy of a monoclonal anti-Wnt-1 antibody in sarcoma cells.

Methods

We treated cell lines A-204, SJSA-1, and fresh primary cultures of lung metastasis of sarcoma with a monoclonal anti-Wnt-1 antibody. Wnt-1 siRNA treatment was carried out in A-204. We assessed cell death using Crystal Violet staining. Apoptosis induction was estimated by flow cytometry analysis (Annexin V and PI staining). Cell signaling changes were determined by western blotting analysis.

Results

We detected Wnt-1 expression in all tissue samples and cell lines. Significant apoptosis induction was found in monoclonal anti-Wnt-1 antibody treated cells compared to control monoclonal antibody treated cells (p < 0.02). Similarly, we observed increased apoptosis in Wnt-1 siRNA treated cells. Blockade of Wnt-1 signaling in both experiments was confirmed by analyzing intracellular levels of Dishevelled-3 and of cytosolic β-catenin. Furthermore, the monoclonal anti-Wnt-1 antibody also induced cell death in fresh primary cultures of metastatic sarcoma in which Wnt-1 signaling was active.

Conclusion

Our results indicate that Wnt-1 blockade by either monoclonal antibody or siRNA induces cell death in sarcoma cells. These data suggest that Wnt-1 may be a novel therapeutic target for the treatment of a subset of sarcoma cells in which Wnt-1/β-catenin signaling is active.
Bupivacaine versus lidocaine analgesia for neonatal circumcision
Authors: Stolik-Dollberg Orit C , Dollberg Shaul
Published: May 2005

Background

Analgesia for neonatal circumcision was recently advocated for every male infant, and its use is considered essential by the American Academy of Pediatrics. We compared the post-operative analgesic quality of bupivacaine to that of lidocaine for achieving dorsal penile nerve block (DPNB) when performing neonatal circumcision.

Methods

Data were obtained from 38 neonates following neonatal circumcision. The infants had received DPNB analgesia with either lidocaine or bupivacaine. The outcome variable was the administration by the parents of acetaminophen during the ensuing 24 hours.

Results

Seventeen infants received lidocaine and 19 received bupivacaine DPNB. Ten infants in the lidocaine group (59%) were given acetaminophen following circumcision compared to only 3 (16%) in the bupivacaine group (P < 0.01). Regression analysis showed that the only significant variable associated with the need for acetaminophen was the use of lidocaine (R2 = 20.6; P = 0.006).

Conclusion

DPNB with bupivacaine for neonatal circumcision apparently confers better analgesia than lidocaine as judged by the requirement of acetaminophen over the ensuing 24-hour period.
Optimal fetal growth for the Caucasian singleton and assessment of appropriateness of fetal growth: an analysis of a total population perinatal database
Authors: Blair Eve M , Liu Yingxin , de Klerk Nicholas H , Lawrence David M
Published: May 2005

Background

The appropriateness of an individual's intra uterine growth is now considered an important determinant of both short and long term outcomes, yet currently used measures have several shortcomings. This study demonstrates a method of assessing appropriateness of intrauterine growth based on the estimation of each individual's optimal newborn dimensions from routinely available perinatal data. Appropriateness of growth can then be inferred from the ratio of the value of the observed dimension to that of the optimal dimension.

Methods

Fractional polynomial regression models including terms for non-pathological determinants of fetal size (gestational duration, fetal gender and maternal height, age and parity) were used to predict birth weight, birth length and head circumference from a population without any major risk factors for sub-optimal intra-uterine growth. This population was selected from a total population of all singleton, Caucasian births in Western Australia 1998–2002. Births were excluded if the pregnancy was exposed to factors known to influence fetal growth pathologically. The values predicted by these models were treated as the optimal values, given infant gender, gestational age, maternal height, parity, and age.

Results

The selected sample (N = 62,746) comprised 60.5% of the total Caucasian singleton birth cohort. Equations are presented that predict optimal birth weight, birth length and head circumference given gestational duration, fetal gender, maternal height, age and parity. The best fitting models explained 40.5% of variance for birth weight, 32.2% for birth length, and 25.2% for head circumference at birth.

Conclusion

Proportion of optimal birth weight (length or head circumference) provides a method of assessing appropriateness of intrauterine growth that is less dependent on the health of the reference population or the quality of their morphometric data than is percentile position on a birth weight distribution.
Pretreatment Beck Depression Inventory score is an important predictor for Post-treatment score in infertile patients: a before-after study
Authors: Khademi Afsaneh , Alleyassin Ashraf , Aghahosseini Marzieh , Ramezanzadeh Fatemeh , Abhari Ali Ahmadi
Published: May 2005

Background

The experience of infertility can be extremely stressful. Some of the risk factors for depression in infertility are being female, repeated unsuccessful treatment cycles or a 2 to 3 year history of infertility, low socioeconomic status, foreign nationality, lack of partner support, life events and previous depression. In this study, we analyzed the Beck Depression Inventory score at the beginning and the end of infertility treatment, to determine which factors may influence the BDI score after treatment of infertility.

Methods

In a before-after study, in a university-affiliated teaching hospital, 251 women who had been visited for assisted reproductive technology infertility treatment participated in the study. BDI score was assessed before and after treatment of infertility.

Results

The mean BDI score rose after unsuccessful treatment and dropped after successful treatment. Those with lower education levels had a higher BDI score before treatment. BDI score after treatment was positively correlated with pretreatment BDI scoreand duration of infertility.

Conclusion

BDI score after treatment was strongly connected to the BDI score before treatment, the result of therapy and to the duration of infertility. The influence of duration of infertility on BDI score after treatment of infertility is weak. So a simple method to screen patients at risk of depression after infertility treatment is determining pretreatment BDI score and predicting the result of infertility treatment by other risk factors.