Correlates of Cooperation in a One-Shot High-Stakes Televised Prisoners' Dilemma

Explaining cooperation between non-relatives is a puzzle for both evolutionary biology and the social sciences. In humans, cooperation is often studied in a laboratory setting using economic games such as the prisoners' dilemma. However, such experiments are sometimes criticized for being played for low stakes and by misrepresentative student samples. Golden balls is a televised game show that uses the prisoners' dilemma, with a diverse range of participants, often playing for very large stakes. We use this non-experimental dataset to investigate the factors that influence cooperation when “playing” for considerably larger stakes than found in economic experiments. The game show has earlier stages that allow for an analysis of lying and voting decisions. We found that contestants were sensitive to the stakes involved, cooperating less when the stakes were larger in both absolute and relative terms. We also found that older contestants were more likely to cooperate, that liars received less cooperative behavior, but only if they told a certain type of lie, and that physical contact was associated with reduced cooperation, whereas laughter and promises were reliable signals or cues of cooperation, but were not necessarily detected

DroID: the Drosophila Interactions Database, a comprehensive resource for annotated gene and protein interactions

<p>Abstract</p> <p>Background</p> <p>Charting the interactions among genes and among their protein products is essential for understanding biological systems. A flood of interaction data is emerging from high throughput technologies, computational approaches, and literature mining methods. Quick and efficient access to this data has become a critical issue for biologists. Several excellent multi-organism databases for gene and protein interactions are available, yet most of these have understandable difficulty maintaining comprehensive information for any one organism. No single database, for example, includes all available interactions, integrated gene expression data, and comprehensive and searchable gene information for the important model organism, <it>Drosophila melanogaster</it>.</p> <p>Description</p> <p>DroID, the <it>Drosophila </it>Interactions Database, is a comprehensive interactions database designed specifically for <it>Drosophila</it>. DroID houses published physical protein interactions, genetic interactions, and computationally predicted interactions, including interologs based on data for other model organisms and humans. All interactions are annotated with original experimental data and source information. DroID can be searched and filtered based on interaction information or a comprehensive set of gene attributes from Flybase. DroID also contains gene expression and expression correlation data that can be searched and used to filter datasets, for example, to focus a study on sub-networks of co-expressed genes. To address the inherent noise in interaction data, DroID employs an updatable confidence scoring system that assigns a score to each physical interaction based on the likelihood that it represents a biologically significant link.</p> <p>Conclusion</p> <p>DroID is the most comprehensive interactions database available for <it>Drosophila</it>. To facilitate downstream analyses, interactions are annotated with original experimental information, gene expression data, and confidence scores. All data in DroID are freely available and can be searched, explored, and downloaded through three different interfaces, including a text based web site, a Java applet with dynamic graphing capabilities (IM Browser), and a Cytoscape plug-in. DroID is available at <url>http://www.droidb.org</url>.</p

Neutrophil Extracellular Traps in Breast Cancer and Beyond: Current Perspectives on NET Stimuli, Thrombosis and Metastasis, and Clinical Utility for Diagnosis and Treatment

Abstract The formation of neutrophil extracellular traps (NETs), known as NETosis, was first observed as a novel immune response to bacterial infection, but has since been found to occur abnormally in a variety of other inflammatory disease states including cancer. Breast cancer is the most commonly diagnosed malignancy in women. In breast cancer, NETosis has been linked to increased disease progression, metastasis, and complications such as venous thromboembolism. NET-targeted therapies have shown success in preclinical cancer models and may prove valuable clinical targets in slowing or halting tumor progression in breast cancer patients. We will briefly outline the mechanisms by which NETs may form in the tumor microenvironment and circulation, including the crosstalk between neutrophils, tumor cells, endothelial cells, and platelets as well as the role of cancer-associated extracellular vesicles in modulating neutrophil behavior and NET extrusion. The prognostic implications of cancer-associated NETosis will be explored in addition to development of novel therapeutics aimed at targeting NET interactions to improve outcomes in patients with breast cancer

Mutator Suppression and Escape from Replication Error–Induced Extinction in Yeast

Cells rely on a network of conserved pathways to govern DNA replication fidelity. Loss of polymerase proofreading or mismatch repair elevates spontaneous mutation and facilitates cellular adaptation. However, double mutants are inviable, suggesting that extreme mutation rates exceed an error threshold. Here we combine alleles that affect DNA polymerase δ (Pol δ) proofreading and mismatch repair to define the maximal error rate in haploid yeast and to characterize genetic suppressors of mutator phenotypes. We show that populations tolerate mutation rates 1,000-fold above wild-type levels but collapse when the rate exceeds 10−3 inactivating mutations per gene per cell division. Variants that escape this error-induced extinction (eex) rapidly emerge from mutator clones. One-third of the escape mutants result from second-site changes in Pol δ that suppress the proofreading-deficient phenotype, while two-thirds are extragenic. The structural locations of the Pol δ changes suggest multiple antimutator mechanisms. Our studies reveal the transient nature of eukaryotic mutators and show that mutator phenotypes are readily suppressed by genetic adaptation. This has implications for the role of mutator phenotypes in cancer

Aquaporins: important but elusive drug targets.

The aquaporins (AQPs) are a family of small, integral membrane proteins that facilitate water transport across the plasma membranes of cells in response to osmotic gradients. Data from knockout mice support the involvement of AQPs in epithelial fluid secretion, cell migration, brain oedema and adipocyte metabolism, which suggests that modulation of AQP function or expression could have therapeutic potential in oedema, cancer, obesity, brain injury, glaucoma and several other conditions. Moreover, loss-of-function mutations in human AQPs cause congenital cataracts (AQP0) and nephrogenic diabetes insipidus (AQP2), and autoantibodies against AQP4 cause the autoimmune demyelinating disease neuromyelitis optica. Although some potential AQP modulators have been identified, challenges associated with the development of better modulators include the druggability of the target and the suitability of the assay methods used to identify modulators

Synchrotron phase-contrast X-ray imaging reveals fluid dosing dynamics for gene transfer into mouse airways

Although airway gene transfer research in mouse models relies on bolus fluid dosing into the nose or trachea, the dynamics and immediate fate of delivered gene transfer agents are poorly understood. In particular, this is because there are no in vivo methods able to accurately visualize the movement of fluid in small airways of intact animals. Using synchrotron phase-contrast X-ray imaging, we show that the fate of surrogate fluid doses delivered into live mouse airways can now be accurately and non-invasively monitored with high spatial and temporal resolution. This new imaging approach can help explain the non-homogenous distributions of gene expression observed in nasal airway gene transfer studies, suggests that substantial dose losses may occur at deliver into mouse trachea via immediate retrograde fluid motion and shows the influence of the speed of bolus delivery on the relative targeting of conducting and deeper lung airways. These findings provide insight into some of the factors that can influence gene expression in vivo, and this method provides a new approach to documenting and analyzing dose delivery in small-animal models.M Donnelley, KKW Siu, RA Jamison and DW Parson

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field