Clusters of circulating tumor cells traverse capillary-sized vessels

Multicellular aggregates of circulating tumor cells (CTC clusters) are potent initiators of distant organ metastasis. However, it is currently assumed that CTC clusters are too large to pass through narrow vessels to reach these organs. Here, we present evidence that challenges this assumption through the use of microfluidic devices designed to mimic human capillary constrictions and CTC clusters obtained from patient and cancer cell origins. Over 90% of clusters containing up to 20 cells successfully traversed 5- to 10-μm constrictions even in whole blood. Clusters rapidly and reversibly reorganized into single-file chain-like geometries that substantially reduced their hydrodynamic resistances. Xenotransplantation of human CTC clusters into zebrafish showed similar reorganization and transit through capillary-sized vessels in vivo. Preliminary experiments demonstrated that clusters could be disrupted during transit using drugs that affected cellular interaction energies. These findings suggest that CTC clusters may contribute a greater role to tumor dissemination than previously believed and may point to strategies for combating CTC cluster-initiated metastasis

Practical Issues in Imputation-Based Association Mapping

Imputation-based association methods provide a powerful framework for testing untyped variants for association with phenotypes and for combining results from multiple studies that use different genotyping platforms. Here, we consider several issues that arise when applying these methods in practice, including: (i) factors affecting imputation accuracy, including choice of reference panel; (ii) the effects of imputation accuracy on power to detect associations; (iii) the relative merits of Bayesian and frequentist approaches to testing imputed genotypes for association with phenotype; and (iv) how to quickly and accurately compute Bayes factors for testing imputed SNPs. We find that imputation-based methods can be robust to imputation accuracy and can improve power to detect associations, even when average imputation accuracy is poor. We explain how ranking SNPs for association by a standard likelihood ratio test gives the same results as a Bayesian procedure that uses an unnatural prior assumption—specifically, that difficult-to-impute SNPs tend to have larger effects—and assess the power gained from using a Bayesian approach that does not make this assumption. Within the Bayesian framework, we find that good approximations to a full analysis can be achieved by simply replacing unknown genotypes with a point estimate—their posterior mean. This approximation considerably reduces computational expense compared with published sampling-based approaches, and the methods we present are practical on a genome-wide scale with very modest computational resources (e.g., a single desktop computer). The approximation also facilitates combining information across studies, using only summary data for each SNP. Methods discussed here are implemented in the software package BIMBAM, which is available from http://stephenslab.uchicago.edu/software.html

Significance analysis of microarray for relative quantitation of LC/MS data in proteomics

<p>Abstract</p> <p>Background</p> <p>Although fold change is a commonly used criterion in quantitative proteomics for differentiating regulated proteins, it does not provide an estimation of false positive and false negative rates that is often desirable in a large-scale quantitative proteomic analysis. We explore the possibility of applying the Significance Analysis of Microarray (SAM) method (PNAS 98:5116-5121) to a differential proteomics problem of two samples with replicates. The quantitative proteomic analysis was carried out with nanoliquid chromatography/linear iron trap-Fourier transform mass spectrometry. The biological sample model included two <it>Mycobacterium smegmatis </it>unlabeled cell cultures grown at pH 5 and pH 7. The objective was to compare the protein relative abundance between the two unlabeled cell cultures, with an emphasis on significance analysis of protein differential expression using the SAM method. Results using the SAM method are compared with those obtained by fold change and the conventional <it>t</it>-test.</p> <p>Results</p> <p>We have applied the SAM method to solve the two-sample significance analysis problem in liquid chromatography/mass spectrometry (LC/MS) based quantitative proteomics. We grew the pH5 and pH7 unlabelled cell cultures in triplicate resulting in 6 biological replicates. Each biological replicate was mixed with a common ¹⁵N-labeled reference culture cells for normalization prior to SDS/PAGE fractionation and LC/MS analysis. For each biological replicate, one center SDS/PAGE gel fraction was selected for triplicate LC/MS analysis. There were 121 proteins quantified in at least 5 of the 6 biological replicates. Of these 121 proteins, 106 were significant in differential expression by the <it>t</it>-test (<it>p </it>< 0.05) based on peptide-level replicates, 54 were significant in differential expression by SAM with Δ = 0.68 cutoff and false positive rate at 5%, and 29 were significant in differential expression by the <it>t</it>-test (<it>p </it>< 0.05) based on protein-level replicates. The results indicate that SAM appears to overcome the false positives one encounters using the peptide-based <it>t</it>-test while allowing for identification of a greater number of differentially expressed proteins than the protein-based <it>t</it>-test.</p> <p>Conclusion</p> <p>We demonstrate that the SAM method can be adapted for effective significance analysis of proteomic data. It provides much richer information about the protein differential expression profiles and is particularly useful in the estimation of false discovery rates and miss rates.</p

Seasonal changes in patterns of gene expression in avian song control brain regions.

This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Photoperiod and hormonal cues drive dramatic seasonal changes in structure and function of the avian song control system. Little is known, however, about the patterns of gene expression associated with seasonal changes. Here we address this issue by altering the hormonal and photoperiodic conditions in seasonally-breeding Gambel's white-crowned sparrows and extracting RNA from the telencephalic song control nuclei HVC and RA across multiple time points that capture different stages of growth and regression. We chose HVC and RA because while both nuclei change in volume across seasons, the cellular mechanisms underlying these changes differ. We thus hypothesized that different genes would be expressed between HVC and RA. We tested this by using the extracted RNA to perform a cDNA microarray hybridization developed by the SoNG initiative. We then validated these results using qRT-PCR. We found that 363 genes varied by more than 1.5 fold (>log(2) 0.585) in expression in HVC and/or RA. Supporting our hypothesis, only 59 of these 363 genes were found to vary in both nuclei, while 132 gene expression changes were HVC specific and 172 were RA specific. We then assigned many of these genes to functional categories relevant to the different mechanisms underlying seasonal change in HVC and RA, including neurogenesis, apoptosis, cell growth, dendrite arborization and axonal growth, angiogenesis, endocrinology, growth factors, and electrophysiology. This revealed categorical differences in the kinds of genes regulated in HVC and RA. These results show that different molecular programs underlie seasonal changes in HVC and RA, and that gene expression is time specific across different reproductive conditions. Our results provide insights into the complex molecular pathways that underlie adult neural plasticity

Assessment of Local Public Health Workers' Willingness to Respond to Pandemic Influenza through Application of the Extended Parallel Process Model

Local public health agencies play a central role in response to an influenza pandemic, and understanding the willingness of their employees to report to work is therefore a critically relevant concern for pandemic influenza planning efforts. Witte's Extended Parallel Process Model (EPPM) has been found useful for understanding adaptive behavior in the face of unknown risk, and thus offers a framework for examining scenario-specific willingness to respond among local public health workers. We thus aim to use the EPPM as a lens for examining the influences of perceived threat and efficacy on local public health workers' response willingness to pandemic influenza.We administered an online, EPPM-based survey about attitudes/beliefs toward emergency response (Johns Hopkins approximately Public Health Infrastructure Response Survey Tool), to local public health employees in three states between November 2006-December 2007. A total of 1835 responses were collected for an overall response rate of 83%. With some regional variation, overall 16% of the workers in 2006-7 were not willing to "respond to a pandemic flu emergency regardless of its severity". Local health department employees with a perception of high threat and high efficacy--i.e., those fitting a 'concerned and confident' profile in the EPPM analysis--had the highest declared rates of willingness to respond to an influenza pandemic if required by their agency, which was 31.7 times higher than those fitting a 'low threat/low efficacy' EPPM profile.In the context of pandemic influenza planning, the EPPM provides a useful framework to inform nuanced understanding of baseline levels of--and gaps in--local public health workers' response willingness. Within local health departments, 'concerned and confident' employees are most likely to be willing to respond. This finding may allow public health agencies to design, implement, and evaluate training programs focused on emergency response attitudes in health departments

Enzymatic capacities of metabolic fuel use in cuttlefish (Sepia officinalis) and responses to food deprivation: insight into the metabolic organization and starvation survival strategy of cephalopods

Food limitation is a common challenge for animals. Cephalopods are sensitive to starvation because of high metabolic rates and growth rates related to their "live fast, die young" life history. We investigated how enzymatic capacities of key metabolic pathways are modulated during starvation in the common cuttlefish (Sepia officinalis) to gain insight into the metabolic organization of cephalopods and their strategies for coping with food limitation. In particular, lipids have traditionally been considered unimportant fuels in cephalopods, yet, puzzlingly, many species (including cuttlefish) mobilize the lipid stores in their digestive gland during starvation. Using a comprehensive multi-tissue assay of enzymatic capacities for energy metabolism, we show that, during long-term starvation (12 days), glycolytic capacity for glucose use is decreased in cuttlefish tissues, while capacities for use of lipid-based fuels (fatty acids and ketone bodies) and amino acid fuels are retained or increased. Specifically, the capacity to use the ketone body acetoacetate as fuel is widespread across tissues and gill has a previously unrecognized capacity for fatty acid catabolism, albeit at low rates. The capacity for de novo glucose synthesis (gluconeogenesis), important for glucose homeostasis, likely is restricted to the digestive gland, contrary to previous reports of widespread gluconeogenesis among cephalopod tissues. Short-term starvation (3-5 days) had few effects on enzymatic capacities. Similar to vertebrates, lipid-based fuels, putatively mobilized from fat stores in the digestive gland, appear to be important energy sources for cephalopods, especially during starvation when glycolytic capacity is decreased perhaps to conserve available glucose

Protein Expression in the Nucleus Accumbens of Rats Exposed to Developmental Vitamin D Deficiency

Introduction: Developmental vitamin D (DVD) deficiency is a candidate risk factor for schizophrenia. Animal models have confirmed that DVD deficiency is associated with a range of altered genomic, proteomic, structural and behavioural outcomes in the rat. Because the nucleus accumbens has been implicated in neuropsychiatric disorders, in the current study we examined protein expression in this region in adult rats exposed to DVD deficienc

Post-supereruption recovery at Toba Caldera

Large calderas, or supervolcanoes, are sites of the most catastrophic and hazardous events on Earth, yet the temporal details of post-supereruption activity, or resurgence, remain largely unknown, limiting our ability to understand how supervolcanoes work and address their hazards. Toba Caldera, Indonesia, caused the greatest volcanic catastrophe of the last 100 kyr, climactically erupting ~74 ka. Since the supereruption, Toba has been in a state of resurgence but its magmatic and uplift history has remained unclear. Here we reveal that new 14 C, zircon U-Th crystallization and (U-Th)/He ages show resurgence commenced at 69.7±4.5 ka and continued until at least ~2.7 ka, progressing westward across the caldera, as reflected by post-caldera effusive lava eruptions and uplifted lake sediment. The major stratovolcano north of Toba, Sinabung, shows strong geochemical kinship with Toba, and zircons from recent eruption products suggest Toba's climactic magma reservoir extends beneath Sinabung and is being tapped during eruptions

Comparative Developmental Expression Profiling of Two C. elegans Isolates

Gene expression is known to change during development and to vary among genetically diverse strains. Previous studies of temporal patterns of gene expression during C. elegans development were incomplete, and little is known about how these patterns change as a function of genetic background. We used microarrays that comprehensively cover known and predicted worm genes to compare the landscape of genetic variation over developmental time between two isolates of C. elegans. We show that most genes vary in expression during development from egg to young adult, many genes vary in expression between the two isolates, and a subset of these genes exhibit isolate-specific changes during some developmental stages. This subset is strongly enriched for genes with roles in innate immunity. We identify several novel motifs that appear to play a role in regulating gene expression during development, and we propose functional annotations for many previously unannotated genes. These results improve our understanding of gene expression and function during worm development and lay the foundation for linkage studies of the genetic basis of developmental variation in gene expression in this important model organism

A strategy to discover new organizers identifies a putative heart organizer

Organizers are regions of the embryo that can both induce new fates and impart pattern on other regions. So far, surprisingly few organizers have been discovered, considering the number of patterned tissue types generated during development. This may be because their discovery has relied on transplantation and ablation experiments. Here we describe a new approach, using chick embryos, to discover organizers based on a common gene expression signature, and use it to uncover the anterior intestinal portal (AIP) endoderm as a putative heart organizer. We show that the AIP can induce cardiac identity from non-cardiac mesoderm and that it can pattern this by specifying ventricular and suppressing atrial regional identity. We also uncover some of the signals responsible. The method holds promise as a tool to discover other novel organizers acting during development