Contextual weighting for Support Vector Machines in literature mining: an application to gene versus protein name disambiguation

BACKGROUND: The ability to distinguish between genes and proteins is essential for understanding biological text. Support Vector Machines (SVMs) have been proven to be very efficient in general data mining tasks. We explore their capability for the gene versus protein name disambiguation task. RESULTS: We incorporated into the conventional SVM a weighting scheme based on distances of context words from the word to be disambiguated. This weighting scheme increased the performance of SVMs by five percentage points giving performance better than 85% as measured by the area under ROC curve and outperformed the Weighted Additive Classifier, which also incorporates the weighting, and the Naive Bayes classifier. CONCLUSION: We show that the performance of SVMs can be improved by the proposed weighting scheme. Furthermore, our results suggest that in this study the increase of the classification performance due to the weighting is greater than that obtained by selecting the underlying classifier or the kernel part of the SVM

Immunization with HIV protease peptides linked to syngeneic erythrocytes

New potent vaccine adjuvants are desirable for increasing the efficacy of novel vaccine modalities such as DNA and peptides. We therefore tested if syngeneic erythrocytes could serve as delivery vectors for selected HIV peptides and compared the potency of these constructs to immunization with peptides in phosphate buffered saline or in incomplete Freunds adjuvant. Immunization of mice with peptides in a low dose (5 ng) coupled to erythrocytes induced a weak immune response in mice. These peptides alone (5 μg) gave no immune responses, while formulating the peptides (50 μg) in IFA induced strong homologous immunity as well as prominent cross reactivity to a related mutant epitope. Thus, vaccine delivery using syngeneic erythrocytes, although attractive for clinical use, might be of limited value due to the low amount of antigen that can be loaded per erythrocyte

Intrauterine exposure to mild analgesics is a risk factor for development of male reproductive disorders in human and rat

International audienceBACKGROUND: More than half of pregnant women in the Western world report intake of mild analgesics, and some of these drugs have been associated with anti-androgenic effects in animal experiments. Intrauterine exposure to anti-androgens is suspected to contribute to the recent increase in male reproductive problems, and many of the anti-androgenic compounds are like the mild analgesics potent inhibitors of prostaglandin synthesis. Therefore, it appears imperative to further investigate the potential endocrine disrupting properties of mild analgesics. METHODS: In a prospective birth cohort study, 2297 Danish and Finnish pregnant women completed a questionnaire and 491 of the Danish mothers participated in a telephone interview, reporting on their use of mild analgesics during pregnancy. The testicular position of newborns was assessed by trained paediatricians. In rats, the impact of mild analgesics on anogenital distance (AGD) after intrauterine exposure was examined together with the effect on ex vivo gestational day 14.5 testes. RESULTS: In the Danish birth cohort, the use of mild analgesics was dose-dependently associated with congenital cryptorchidism. In particular, use during the second trimester increased the risk. This risk was further increased after the simultaneous use of different analgesics. The association was not found in the Finnish birth cohort. Intrauterine exposure of rats to paracetamol led to a reduction in the AGD and mild analgesics accordingly reduced testosterone production in ex vivo fetal rat testes. CONCLUSION: There was an association between the timing and the duration of mild analgesic use during pregnancy and the risk of cryptorchidism. These findings were supported by anti-androgenic effects in rat models leading to impaired masculinization. Our results suggest that intrauterine exposure to mild analgesics is a risk factor for development of male reproductive disorders

BioInfer: a corpus for information extraction in the biomedical domain

BACKGROUND: Lately, there has been a great interest in the application of information extraction methods to the biomedical domain, in particular, to the extraction of relationships of genes, proteins, and RNA from scientific publications. The development and evaluation of such methods requires annotated domain corpora. RESULTS: We present BioInfer (Bio Information Extraction Resource), a new public resource providing an annotated corpus of biomedical English. We describe an annotation scheme capturing named entities and their relationships along with a dependency analysis of sentence syntax. We further present ontologies defining the types of entities and relationships annotated in the corpus. Currently, the corpus contains 1100 sentences from abstracts of biomedical research articles annotated for relationships, named entities, as well as syntactic dependencies. Supporting software is provided with the corpus. The corpus is unique in the domain in combining these annotation types for a single set of sentences, and in the level of detail of the relationship annotation. CONCLUSION: We introduce a corpus targeted at protein, gene, and RNA relationships which serves as a resource for the development of information extraction systems and their components such as parsers and domain analyzers. The corpus will be maintained and further developed with a current version being available at

Immunization of mice with the nef gene from Human Immunodeficiency Virus type 1: Study of immunological memory and long-term toxicology

<p>Abstract</p> <p>Background</p> <p>The human immunodeficiency virus type 1 (HIV-1) regulatory protein, Nef, is an attractive vaccine target because it is involved in viral pathogenesis, is expressed early in the viral life cycle and harbors many T and B cell epitopes. Several clinical trials include gene-based vaccines encoding this protein. However, Nef has been shown to transform certain cell types <it>in vitro</it>. Based on these findings we performed a long-term toxicity and immunogenicity study of Nef, encoded either by Modified Vaccinia virus Ankara or by plasmid DNA. BALB/c mice were primed twice with either DNA or MVA encoding Nef and received a homologous or heterologous boost ten months later. In the meantime, the Nef-specific immune responses were monitored and at the time of sacrifice an extensive toxicological evaluation was performed, where presence of tumors and other pathological changes were assessed.</p> <p>Results</p> <p>The toxicological evaluation showed that immunization with MVAnef is safe and does not cause cellular transformation or other toxicity in somatic organs.</p> <p>Both DNAnef and MVAnef immunized animals developed potent Nef-specific cellular responses that declined to undetectable levels over time, and could readily be boosted after almost one year. This is of particular interest since it shows that plasmid DNA vaccine can also be used as a potent late booster of primed immune responses. We observed qualitative differences between the T cell responses induced by the two different vectors: DNA-encoded nef induced long-lasting CD8⁺T cell memory responses, whereas MVA-encoded nef induced CD4⁺T cell memory responses. In terms of the humoral immune responses, we show that two injections of MVAnef induce significant anti-Nef titers, while repeated injections of DNAnef do not. A single boost with MVAnef could enhance the antibody response following DNAnef prime to the same level as that observed in animals immunized repeatedly with MVAnef. We also demonstrate the possibility to boost HIV-1 Nef-specific immune responses using the MVAnef construct despite the presence of potent anti-vector immunity.</p> <p>Conclusion</p> <p>This study shows that the nef gene vectored by MVA does not induce malignancies or other adverse effects in mice. Further, we show that when the nef gene is delivered by plasmid or by a viral vector, it elicits potent and long-lasting immune responses and that these responses can be directed towards a CD4⁺or a CD8⁺T cell response depending on the choice of vector.</p

Efficient cross-validation for kernelized least-squares regression with sparse basis expansions

We propose an efficient algorithm for calculating hold-out and cross-validation (CV) type of estimates for sparse regularized least-squares predictors. Holding out H data points with our method requires O(min(H2 n,Hn2)) time provided that a predictor with n basis vectors is already trained. In addition to holding out training examples, also some of the basis vectors used to train the sparse regularized least-squares predictor with the whole training set can be removed from the basis vector set used in the hold-out computation. In our experiments, we demonstrate the speed improvements provided by our algorithm in practice, and we empirically show the benefits of removing some of the basis vectors during the CV rounds