Нарушения в геноме хозяина при экспериментальном гименолепидозе в зависимости от дозы введенного инвазивного материала при заряжении

ГИМЕНОЛЕПИДО

How to Win First-Order Safety Games

First-order (FO) transition systems have recently attracted attention for the verification of parametric systems such as network protocols, software-defined networks or multi-agent workflows like conference management systems. Functional correctness or noninterference of these systems have conveniently been formulated as safety or hypersafety properties, respectively. In this article, we take the step from verification to synthesis---tackling the question whether it is possible to automatically synthesize predicates to enforce safety or hypersafety properties like noninterference. For that, we generalize FO transition systems to FO safety games. For FO games with monadic predicates only, we provide a complete classification into decidable and undecidable cases. For games with non-monadic predicates, we concentrate on universal first-order invariants, since these are sufficient to express a large class of properties---for example noninterference. We identify a non-trivial sub-class where invariants can be proven inductive and FO winning strategies be effectively constructed. We also show how the extraction of weakest FO winning strategies can be reduced to SO quantifier elimination itself. We demonstrate the usefulness of our approach by automatically synthesizing nontrivial FO specifications of messages in a leader election protocol as well as for paper assignment in a conference management system to exclude unappreciated disclosure of reports

Expression of NES-hTERT in Cancer Cells Delays Cell Cycle Progression and Increases Sensitivity to Genotoxic Stress

Telomerase is a reverse transcriptase associated with cellular immortality through telomere maintenance. This enzyme is activated in 90% of human cancers, and inhibitors of telomerase are currently in clinical trials to counteract tumor growth. Many aspects of telomerase biology have been investigated for therapy, particularly inhibition of the enzyme, but little was done regarding its subcellular shuttling. We have recently shown that mutations in the nuclear export signal of hTERT, the catalytic component of telomerase, led to a mutant (NES-hTERT) that failed to immortalize cells despite nuclear localization and catalytic activity. Expression of NES-hTERT in primary fibroblast resulted in telomere-based premature senescence and mitochondrial dysfunction. Here we show that expression of NES-hTERT in LNCaP, SQ20B and HeLa cells rapidly and significantly decreases their proliferation rate and ability to form colonies in soft agar while not interfering with endogenous telomerase activity. The cancer cells showed increased DNA damage at telomeric and extra-telomeric sites, and became sensitive to ionizing radiation and hydrogen peroxide exposures. Our data show that expression of NES-hTERT efficiently counteracts cancer cell growth in vitro in at least two different ways, and suggest manipulation with the NES of hTERT or its subcellular shuttling as a new strategy for cancer treatment

At the coalface and the cutting edge: general practitioners’ accounts of the rewards of engaging with HIV medicine

The interviews we conducted with GPs suggest that an engagement with HIV medicine enables clinicians to develop strong and long-term relationships with and expertise about the care needs of people living with HIV ‘at the coalface’, while also feeling connected with a broader network of medical practitioners and other professionals concerned with and contributing to the ever-changing world of science: ‘the cutting edge’. The general practice HIV prescriber is being modelled here as the interface between these two worlds, offering a rewarding opportunity for general practitioners to feel intimately connected to both community needs and scientific change

A framework for the extraction and modeling of fact-finding reasoning from legal decisions: lessons from the Vaccine/Injury Project Corpus

This article describes the Vaccine/Injury Project Corpus, a collection of legal decisions awarding or denying compensation for health injuries allegedly due to vaccinations, together with models of the logical structure of the reasoning of the factfinders in those cases. This unique corpus provides useful data for formal and informal logic theory, for natural-language research in linguistics, and for artificial intelligence research. More importantly, the article discusses lessons learned from developing protocols for manually extracting the logical structure and generating the logic models. It identifies sub-tasks in the extraction process, discusses challenges to automation, and provides insights into possible solutions for automation. In particular, the framework and strategies developed here, together with the corpus data, should allow top-down and contextual approaches to automation, which can supplement bottom-up linguistic approaches. Illustrations throughout the article use examples drawn from the Corpus