Validating module network learning algorithms using simulated data

In recent years, several authors have used probabilistic graphical models to learn expression modules and their regulatory programs from gene expression data. Here, we demonstrate the use of the synthetic data generator SynTReN for the purpose of testing and comparing module network learning algorithms. We introduce a software package for learning module networks, called LeMoNe, which incorporates a novel strategy for learning regulatory programs. Novelties include the use of a bottom-up Bayesian hierarchical clustering to construct the regulatory programs, and the use of a conditional entropy measure to assign regulators to the regulation program nodes. Using SynTReN data, we test the performance of LeMoNe in a completely controlled situation and assess the effect of the methodological changes we made with respect to an existing software package, namely Genomica. Additionally, we assess the effect of various parameters, such as the size of the data set and the amount of noise, on the inference performance. Overall, application of Genomica and LeMoNe to simulated data sets gave comparable results. However, LeMoNe offers some advantages, one of them being that the learning process is considerably faster for larger data sets. Additionally, we show that the location of the regulators in the LeMoNe regulation programs and their conditional entropy may be used to prioritize regulators for functional validation, and that the combination of the bottom-up clustering strategy with the conditional entropy-based assignment of regulators improves the handling of missing or hidden regulators.Comment: 13 pages, 6 figures + 2 pages, 2 figures supplementary informatio

Inside and out: the activities of senescence in cancer.

The core aspect of the senescent phenotype is a stable state of cell cycle arrest. However, this is a disguise that conceals a highly active metabolic cell state with diverse functionality. Both the cell-autonomous and the non-cell-autonomous activities of senescent cells create spatiotemporally dynamic and context-dependent tissue reactions. For example, the senescence-associated secretory phenotype (SASP) provokes not only tumour-suppressive but also tumour-promoting responses. Senescence is now increasingly considered to be an integrated and widespread component that is potentially important for tumour development, tumour suppression and the response to therapy.This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/nrc377

Performance studies of the CMS strip tracker before installation

Peer reviewe

Evaluating Sex and Age Differences in ADI-R and ADOS Scores in a Large European Multi-site Sample of Individuals with Autism Spectrum Disorder

Research on sex-related differences in Autism Spectrum Disorder (ASD) has been impeded by small samples. We pooled 28 datasets from 18 sites across nine European countries to examine sex differences in the ASD phenotype on the ADI-R (376 females, 1763 males) and ADOS (233 females, 1187 males). On the ADI-R, early childhood restricted and repetitive behaviours were lower in females than males, alongside comparable levels of social interaction and communication difficulties in females and males. Current ADI-R and ADOS scores showed no sex differences for ASD severity. There were lower socio-communicative symptoms in older compared to younger individuals. This large European ASD sample adds to the literature on sex and age variations of ASD symptomatology

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Interplay between n-3 and n-6 long-chain polyunsaturated fatty acids and the endocannabinoid system in brain protection and repair.

The brain is enriched in arachidonic acid (ARA) and docosahexaenoic acid (DHA), long-chain polyunsaturated fatty acids (LCPUFA) of the n-6 and n-3 series, respectively. Both are essential for optimal brain development and function. Dietary enrichment with DHA and other long-chain n-3 PUFA, such as eicosapentaenoic acid (EPA) have shown beneficial effects on learning and memory, neuroinflammatory processes and synaptic plasticity and neurogenesis. ARA, DHA and EPA are precursors to a diverse repertoire of bioactive lipid mediators, including endocannabinoids. The endocannabinoid system comprises cannabinoid receptors, their endogenous ligands, the endocannabinoids, and their biosynthetic and degradation enzymes. Anandamide (AEA) and 2-archidonoylglycerol (2-AG) are the most widely studied endocannabinoids, and are both derived from phospholipid-bound ARA. The endocannabinoid system also has well established roles in neuroinflammation, synaptic plasticity and neurogenesis, suggesting an overlap in the neuroprotective effects observed with these different classes of lipids. Indeed, growing evidence suggests a complex interplay between n-3 and n-6 LCPUFA and the endocannabinoid system. For example, long-term DHA and EPA supplementation reduces AEA and 2-AG levels, with reciprocal increases in levels of the analogous endocannabinoid-like DHA and EPA-derived molecules. This review summarises current evidence of this interplay and discusses the therapeutic potential for brain protection and repair

Völkisch und sozial? : Neonazistische Agitation gegen die neue EU-Freizügigkeit für Arbeitnehmerinnen

Wnt/β-catenin signalling pathway is crucial for the formation of many tissues and organs during development. In recent years, this pathway has also been found to regulate the biology of stem cells in the intestine and probably in other organs in adult life. Abnormal activation of Wnt/β-catenin signalling, which controls the expression of a high number of genes, is critical for the initiation and progression of most colorectal cancers. In line with this, the gene expression signature induced by activation of the Wnt/β-catenin pathway defines the intestinal stem cells present at the bottom of the crypts and also colon cancer stem cells. This supports the importance of inhibitors of the Wnt/β-catenin pathway as potential agents in colorectal cancer therapy. However, the complexity, wide activity in the organism modulating the biology of several cell types, and characteristics of this pathway have delayed the identification of suitable targets and so, the development of such inhibitors that are only now reaching the clinic.Peer reviewe

Catheter Balloon Adjustment of the Pulmonary Artery Band: Feasibility and Safety

The study aimed to assess the feasibility and safety of increasing pulmonary artery band (PAB) diameter by catheter-based PAB balloon dilation (PABBD). Eight dilations were performed between October 2006 and December 2008. Hemoclips were used to fix PABs surgically in a procedure designed to permit progressive clip dislodgment in a controlled manner. The PABBD resulted in gradual band loosening until the desired physiologic state was achieved. At time of PABBD, the patients had a mean age of 6 months (range 3–14 months) and a mean weight of 5 kg (range 2.6–7.3 kg). The median time from PAB placement until PABBD was 4.5 months (range 1–9 months). The single-balloon technique was used in seven cases (serial dilations in 5 cases) and the double-balloon technique in one case. The PABBDs were successful for all the patients, who experienced a mean saturation increase of 75–89% (P = 0.01) (mean increase of 20%), a mean PAB gradient decrease from 69 to 36 mmHg (P = 0.002) (mean decrease of 49%), and a mean band site diameter increase from 4.1 to 6.1 mm (P = 0.01) (mean increase of 45%). The only complication was transient pulmonary edema in one patient. The PABBD procedure is a feasible and safe method for increasing pulmonary blood flow in a staged manner and may eliminate the need for surgical band removal in some cases

DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines

Integrated data analysis (IDA) pipelines---that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring---become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used---increasingly heterogeneous---hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, data formats and representations, as well as execution strategies differ substantially. DAPHNE is an open and extensible system infrastructure for such IDA pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware (HW) accelerators, and computational storage for increasing productivity and eliminating unnecessary overheads. In this paper, we make a case for IDA pipelines, describe the overall DAPHNE system architecture, its key components, and the design of a vectorized execution engine for computational storage, HW accelerators, as well as local and distributed operations. Preliminary experiments that compare DAPHNE with MonetDB, Pandas, DuckDB, and TensorFlow show promising results

DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines

Integrated data analysis (IDA) pipelines—that combine data management (DM) and query processing, high-performance computing (HPC), and machine learning (ML) training and scoring—become increasingly common in practice. Interestingly, systems of these areas share many compilation and runtime techniques, and the used—increasingly heterogeneous—hardware infrastructure converges as well. Yet, the programming paradigms, cluster resource management, data formats and representations, as well as execution strategies differ substantially. DAPHNE is an open and extensible system infrastructure for such IDA pipelines, including language abstractions, compilation and runtime techniques, multi-level scheduling, hardware (HW) accelerators, and computational storage for increasing productivity and eliminating unnecessary overheads. In this paper, we make a case for IDA pipelines, describe the overall DAPHNE system architecture, its key components, and the design of a vectorized execution engine for computational storage, HW accelerators, as well as local and distributed operations. Preliminary experiments that compare DAPHNE with MonetDB, Pandas, DuckDB, and TensorFlow show promising results