Clinical trial protocol of the ASTER trial: a double-blind, randomized, placebo-controlled phase III trial evaluating the use of acetylsalicylic acid (ASA) for enhanced early detection of colorectal neoplasms

Immunochemical fecal occult blood tests (iFOBTs) are increasingly used for colorectal cancer (CRC) screening. In our preceding observational study, sensitivity for detecting advanced colorectal neoplasms by iFOBT was 70.8% among users of low-dose acetylsalicylic acid compared with 35.9% among non-users (p = 0.001), whereas there were only very small differences in specificity. In receiver operating characteristics (ROC) analyses, the area under the curve (AUC) was much higher for acetylsalicylic acid users than for non-users, with particularly strong differences in men (0.87 versus 0.68, p = 0.003). These findings suggested that use of acetylsalicylic acid before conduct of iFOBT might be a promising approach to improve non-invasive screening for CRC. Methods/design: In this randomized, double-blind, placebo-controlled trial, the diagnostic performance of two iFOBTs for detecting advanced colorectal neoplasms after a single low-dose of acetylsalicylic acid (300 mg) compared to placebo is evaluated. Acetylsalicylic acid or placebo is administered at least 5 days before a planned, study-independent colonoscopic screening in 2400 participants aged 40 to 80 years. Stool samples are obtained before and on three different days after the single dose of acetylsalicylic acid or placebo. In addition, optional blood samples are taken for future biomarker analyses. The diagnostic performance of the iFOBTs will be compared to the results of the colonoscopy as a gold standard for the diagnosis of colorectal neoplasms. Additionally, gender-specific performance of the tests and gain in diagnostic performance by test application on multiple days will be evaluated. Discussion: If the findings from our preceding observational study will be confirmed in this large trial, the proposed low-risk, inexpensive intervention would considerably improve the diagnostic accuracy of iFOBTs and thus lead to enhanced early detection of colorectal neoplasms. Thus, the results of this trial may have a large public health impact. Trial registration This trial was registered before recruitment of the participants in www.clinicaltrialsregister.eu on the 30th of May 2012: EudraCT No.: 2011–005603-32 and in www.drks.de on 13th of March 2012: German Clinical Trials Register DRKS-ID: DRKS00003252

A Comprehensive Benchmark of Kernel Methods to Extract Protein–Protein Interactions from Literature

The most important way of conveying new findings in biomedical research is scientific publication. Extraction of protein–protein interactions (PPIs) reported in scientific publications is one of the core topics of text mining in the life sciences. Recently, a new class of such methods has been proposed - convolution kernels that identify PPIs using deep parses of sentences. However, comparing published results of different PPI extraction methods is impossible due to the use of different evaluation corpora, different evaluation metrics, different tuning procedures, etc. In this paper, we study whether the reported performance metrics are robust across different corpora and learning settings and whether the use of deep parsing actually leads to an increase in extraction quality. Our ultimate goal is to identify the one method that performs best in real-life scenarios, where information extraction is performed on unseen text and not on specifically prepared evaluation data. We performed a comprehensive benchmarking of nine different methods for PPI extraction that use convolution kernels on rich linguistic information. Methods were evaluated on five different public corpora using cross-validation, cross-learning, and cross-corpus evaluation. Our study confirms that kernels using dependency trees generally outperform kernels based on syntax trees. However, our study also shows that only the best kernel methods can compete with a simple rule-based approach when the evaluation prevents information leakage between training and test corpora. Our results further reveal that the F-score of many approaches drops significantly if no corpus-specific parameter optimization is applied and that methods reaching a good AUC score often perform much worse in terms of F-score. We conclude that for most kernels no sensible estimation of PPI extraction performance on new text is possible, given the current heterogeneity in evaluation data. Nevertheless, our study shows that three kernels are clearly superior to the other methods

Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011

We present the preparation, resources, results and analysis of three tasks of the BioNLP Shared Task 2011: the main tasks on Infectious Diseases (ID) and Epigenetics and Post-translational Modifications (EPI), and the supporting task on Entity Relations (REL). The two main tasks represent extensions of the event extraction model introduced in the BioNLP Shared Task 2009 (ST'09) to two new areas of biomedical scientific literature, each motivated by the needs of specific biocuration tasks. The ID task concerns the molecular mechanisms of infection, virulence and resistance, focusing in particular on the functions of a class of signaling systems that are ubiquitous in bacteria. The EPI task is dedicated to the extraction of statements regarding chemical modifications of DNA and proteins, with particular emphasis on changes relating to the epigenetic control of gene expression. By contrast to these two application-oriented main tasks, the REL task seeks to support extraction in general by separating challenges relating to part-of relations into a subproblem that can be addressed by independent systems. Seven groups participated in each of the two main tasks and four groups in the supporting task. The participating systems indicated advances in the capability of event extraction methods and demonstrated generalization in many aspects: from abstracts to full texts, from previously considered subdomains to new ones, and from the ST'09 extraction targets to other entities and events. The highest performance achieved in the supporting task REL, 58% F-score, is broadly comparable with levels reported for other relation extraction tasks. For the ID task, the highest-performing system achieved 56% F-score, comparable to the state-of-the-art performance at the established ST'09 task. In the EPI task, the best result was 53% F-score for the full set of extraction targets and 69% F-score for a reduced set of core extraction targets, approaching a level of performance sufficient for user-facing applications. In this study, we extend on previously reported results and perform further analyses of the outputs of the participating systems. We place specific emphasis on aspects of system performance relating to real-world applicability, considering alternate evaluation metrics and performing additional manual analysis of system outputs. We further demonstrate that the strengths of extraction systems can be combined to improve on the performance achieved by any system in isolation. The manually annotated corpora, supporting resources, and evaluation tools for all tasks are available from http://www.bionlp-st.org and the tasks continue as open challenges for all interested parties

Law in the virtual battlespace: the Tallin Manual and the Jus in Bello

Reports of cyber operations have increased so dramatically in recent years that they have become commonplace. The reality that most attacks to date have resulted in relatively benign consequences - inconvenience and offence through defacement of government websites and/or temporary suspension of access - only serves to heighten awareness of the damage that could result from much more serious attacks on networks controlling, for example, vital public transport and emergency infrastructure, the financial system and sensitive communications networks. The threat of apocalyptic consequences has galvanized States into proactive cyber defence measures - spawning an entirely new category of bureaucracy that until recently might readily have been cynically dismissed as manipulative fear-mongering to justify yet more human and financial resources allocated to the public sector. That governments should proactively mitigate emergent and potentially catastrophic risks is an a priori notion. Citizens of a State whose government did not take cyber defence seriously would be entitled to feel aggrieved - particularly in the aftermath of a serious cyber attack where the lack of proaction on the part of central authorities was exposed. In contrast, expectations should be significantly lower for any proactive clarification of the applicable international law. The making of new, or even the clarification of the content of existing, international law has tended to be more reactive - requiring a major catalyst to expose the need for either clarification or regulation. It has been rare in the history of international law for new development to pre-empt subsequent catastrophe