On dynamic network entropy in cancer

The cellular phenotype is described by a complex network of molecular interactions. Elucidating network properties that distinguish disease from the healthy cellular state is therefore of critical importance for gaining systems-level insights into disease mechanisms and ultimately for developing improved therapies. By integrating gene expression data with a protein interaction network to induce a stochastic dynamics on the network, we here demonstrate that cancer cells are characterised by an increase in the dynamic network entropy, compared to cells of normal physiology. Using a fundamental relation between the macroscopic resilience of a dynamical system and the uncertainty (entropy) in the underlying microscopic processes, we argue that cancer cells will be more robust to random gene perturbations. In addition, we formally demonstrate that gene expression differences between normal and cancer tissue are anticorrelated with local dynamic entropy changes, thus providing a systemic link between gene expression changes at the nodes and their local network dynamics. In particular, we also find that genes which drive cell-proliferation in cancer cells and which often encode oncogenes are associated with reductions in the dynamic network entropy. In summary, our results support the view that the observed increased robustness of cancer cells to perturbation and therapy may be due to an increase in the dynamic network entropy that allows cells to adapt to the new cellular stresses. Conversely, genes that exhibit local flux entropy decreases in cancer may render cancer cells more susceptible to targeted intervention and may therefore represent promising drug targets.Comment: 10 pages, 3 figures, 4 tables. Submitte

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic

The NARCONON™ drug education curriculum for high school students: A non-randomized, controlled prevention trial

<p>Abstract</p> <p>Background</p> <p>An estimated 13 million youths aged 12 to 17 become involved with alcohol, tobacco and other drugs annually. The number of 12- to 17-year olds abusing controlled prescription drugs increased an alarming 212 percent between 1992 and 2003. For many youths, substance abuse precedes academic and health problems including lower grades, higher truancy, drop out decisions, delayed or damaged physical, cognitive, and emotional development, or a variety of other costly consequences. For thirty years the Narconon program has worked with schools and community groups providing single educational modules aimed at supplementing existing classroom-based prevention activities. In 2004, Narconon International developed a multi-module, universal prevention curriculum for high school ages based on drug abuse etiology, program quality management data, prevention theory and best practices. We review the curriculum and its rationale and test its ability to change drug use behavior, perceptions of risk/benefits, and general knowledge.</p> <p>Methods</p> <p>After informed parental consent, approximately 1000 Oklahoma and Hawai'i high school students completed a modified <it>Center for Substance Abuse Prevention (CSAP) Participant Outcome Measures for Discretionary Programs </it>survey at three testing points: baseline, one month later, and six month follow-up. Schools assigned to experimental conditions scheduled the Narconon curriculum between the baseline and one-month follow-up test; schools in control conditions received drug education after the six-month follow-up. Student responses were analyzed controlling for baseline differences using analysis of covariance.</p> <p>Results</p> <p>At six month follow-up, youths who received the Narconon drug education curriculum showed reduced drug use compared with controls across all drug categories tested. The strongest effects were seen in all tobacco products and cigarette frequency followed by marijuana. There were also significant reductions measured for alcohol and amphetamines. The program also produced changes in knowledge, attitudes and perception of risk.</p> <p>Conclusion</p> <p>The eight-module Narconon curriculum has thorough grounding in substance abuse etiology and prevention theory. Incorporating several historically successful prevention strategies this curriculum reduced drug use among youths.</p

Microbial community composition in sediments resists perturbation by nutrient enrichment

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in The ISME Journal 5 (2011): 1540–1548, doi:10.1038/ismej.2011.22.Functional redundancy in bacterial communities is expected to allow microbial assemblages to survive perturbation by allowing continuity in function despite compositional changes in communities. Recent evidence suggests, however, that microbial communities change both composition and function as a result of disturbance. We present evidence for a third response: resistance. We examined microbial community response to perturbation caused by nutrient enrichment in salt marsh sediments using deep pyrosequencing of 16S rRNA and functional gene microarrays targeting the nirS gene. Composition of the microbial community, as demonstrated by both genes, was unaffected by significant variations in external nutrient supply, despite demonstrable and diverse nutrient–induced changes in many aspects of marsh ecology. The lack of response to external forcing demonstrates a remarkable uncoupling between microbial composition and ecosystem-level biogeochemical processes and suggests that sediment microbial communities are able to resist some forms of perturbation.Funding for this research came from NSF(DEB-0717155 to JEH, DBI-0400819 to JLB). Support for the sequencing facility came from NIH and NSF (NIH/NIEHS-P50-ES012742-01 and NSF/OCE 0430724-J Stegeman PI to HGM and MLS, and WM Keck Foundation to MLS). Salary support provided from Princeton University Council on Science and Technology to JLB. Support for development of the functional gene microarray provided by NSF/OCE99-081482 to BBW. The Plum Island fertilization experiment was funded by NSF (DEB 0213767 and DEB 0816963)

The future of video analytics for surveillance and its ethical implications

The current state of the art and direction of research in computer vision aimed at automating the analysis of CCTV images is presented. This includes low level identification of objects within the field of view of cameras, following those objects over time and between cameras, and the interpretation of those objects’ appearance and movements with respect to models of behaviour (and therefore intentions inferred). The potential ethical problems (and some potential opportunities) such developments may pose if and when deployed in the real world are presented, and suggestions made as to the necessary new regulations which will be needed if such systems are not to further enhance the power of the surveillers against the surveilled

Botulinum toxin: Description of injection techniques and examination of controversies surrounding toxin diffusion

10.1111/j.1600-0404.2007.00931.xActa Neurologica Scandinavica117273-8

Warming stimulates sediment denitrification at the expense of anaerobic ammonium oxidation.

Temperature is one of the fundamental environmental variables governing microbially mediated denitrification and anaerobic ammonium oxidation (anammox) in sediments. The GHG nitrous oxide (N2O) is produced during denitrification, but not by anammox, and knowledge of how these pathways respond to global warming remains limited. Here, we show that warming directly stimulates denitrification-derived N2O production and that the warming response for N2O production is slightly higher than the response for denitrification in subtropical sediments. Moreover, denitrification had a higher optimal temperature than anammox. Integrating our data into a global compilation indicates that denitrifiers are more thermotolerant, whereas anammox bacteria are relatively psychrotolerant. Crucially, recent summer temperatures in low-latitude sediments have exceeded the optimal temperature of anammox, implying that further warming may suppress anammox and direct more of the nitrogen flow towards denitrification and associated N2O production, leading to a positive climate feedback at low latitudes