Microscopy-BIDS: An extension to the brain imaging data structure for microscopy data

The Brain Imaging Data Structure (BIDS) is a specification for organizing, sharing, and archiving neuroimaging data and metadata in a reusable way. First developed for magnetic resonance imaging (MRI) datasets, the community-led specification evolved rapidly to include other modalities such as magnetoencephalography, positron emission tomography, and quantitative MRI (qMRI). In this work, we present an extension to BIDS for microscopy imaging data, along with example datasets. Microscopy-BIDS supports common imaging methods, including 2D/3D, ex/in vivo, micro-CT, and optical and electron microscopy. Microscopy-BIDS also includes comprehensible metadata definitions for hardware, image acquisition, and sample properties. This extension will facilitate future harmonization efforts in the context of multi-modal, multi-scale imaging such as the characterization of tissue microstructure with qMRI

Evolution of associative learning in chemical networks

Organisms that can learn about their environment and modify their behaviour appropriately during their lifetime are more likely to survive and reproduce than organisms that do not. While associative learning – the ability to detect correlated features of the environment – has been studied extensively in nervous systems, where the underlying mechanisms are reasonably well understood, mechanisms within single cells that could allow associative learning have received little attention. Here, using in silico evolution of chemical networks, we show that there exists a diversity of remarkably simple and plausible chemical solutions to the associative learning problem, the simplest of which uses only one core chemical reaction. We then asked to what extent a linear combination of chemical concentrations in the network could approximate the ideal Bayesian posterior of an environment given the stimulus history so far? This Bayesian analysis revealed the ’memory traces’ of the chemical network. The implication of this paper is that there is little reason to believe that a lack of suitable phenotypic variation would prevent associative learning from evolving in cell signalling, metabolic, gene regulatory, or a mixture of these networks in cells

Phenotype-dependent apoptosis signalling in mesothelioma cells after selenite exposure

<p>Abstract</p> <p>Background</p> <p>Selenite is a promising anticancer agent which has been shown to induce apoptosis in malignant mesothelioma cells in a phenotype-dependent manner, where cells of the chemoresistant sarcomatoid phenotype are more sensitive.</p> <p>Methods</p> <p>In this paper, we investigate the apoptosis signalling mechanisms in sarcomatoid and epithelioid mesothelioma cells after selenite treatment. Apoptosis was measured with the Annexin-PI assay. The mitochondrial membrane potential, the expression of Bax, Bcl-XL, and the activation of caspase-3 were assayed with flow cytometry and a cytokeratin 18 cleavage assay. Signalling through JNK, p38, p53, and cathepsins B, D, and E was investigated with chemical inhibitors. Furthermore, the expression, nuclear translocation and DNA-binding activity of p53 was investigated using ICC, EMSA and the monitoring of p21 expression as a downstream event. Levels of thioredoxin (Trx) were measured by ELISA.</p> <p>Results</p> <p>In both cell lines, 10 μM selenite caused apoptosis and a marked loss of mitochondrial membrane potential. Bax was up-regulated only in the sarcomatoid cell line, while the epithelioid cell line down-regulated Bcl-XL and showed greater caspase-3 activation. Nuclear translocation of p53 was seen in both cell lines, but very little p21 expression was induced. Chemical inhibition of p53 did not protect the cells from apoptosis. p53 lost its DNA binding ability after selenite treatment and was enriched in an inactive form. Levels of thioredoxin decreased after selenite treatment. Chemical inhibition of MAP kinases and cathepsins showed that p38 and cathepsin B had some mediatory effect while JNK had an anti-apoptotic role.</p> <p>Conclusion</p> <p>We delineate pathways of apoptosis signalling in response to selenite, showing differences between epithelioid and sarcomatoid mesothelioma cells. These differences may partly explain why sarcomatoid cells are more sensitive to selenite.</p

Response to Comment on “Estimating the reproducibility of psychological science”

Gilbert et al. conclude that evidence from the Open Science Collaboration's Reproducibility Project: Psychology indicates high reproducibility, given the study methodology. Their very optimistic assessment is limited by statistical misconceptions and by causal inferences from selectively interpreted, correlational data. Using the Reproducibility Project: Psychology data, both optimistic and pessimistic conclusions about reproducibility are possible, and neither are yet warranted.status: publishe

Syndecan-1 and FGF-2, but Not FGF Receptor-1, Share a Common Transport Route and Co-Localize with Heparanase in the Nuclei of Mesenchymal Tumor Cells

Syndecan-1 forms complexes with growth factors and their cognate receptors in the cell membrane. We have previously reported a tubulin-mediated translocation of syndecan-1 to the nucleus. The transport route and functional significance of nuclear syndecan-1 is still incompletely understood. Here we investigate the sub-cellular distribution of syndecan-1, FGF-2, FGFR-1 and heparanase in malignant mesenchymal tumor cells, and explore the possibility of their coordinated translocation to the nucleus. To elucidate a structural requirement for this nuclear transport, we have transfected cells with a syndecan-1/EGFP construct or with a short truncated version containing only the tubulin binding RMKKK sequence. The sub-cellular distribution of the EGFP fusion proteins was monitored by fluorescence microscopy. Our data indicate that syndecan-1, FGF-2 and heparanase co-localize in the nucleus, whereas FGFR-1 is enriched mainly in the perinuclear area. Overexpression of syndecan-1 results in increased nuclear accumulation of FGF-2, demonstrating the functional importance of syndecan-1 for this nuclear transport. Interestingly, exogenously added FGF-2 does not follow the route taken by endogenous FGF-2. Furthermore, we prove that the RMKKK sequence of syndecan-1 is necessary and sufficient for nuclear translocation, acting as a nuclear localization signal, and the Arginine residue is vital for this localization. We conclude that syndecan-1 and FGF-2, but not FGFR-1 share a common transport route and co-localize with heparanase in the nucleus, and this transport is mediated by the RMKKK motif in syndecan-1. Our study opens a new perspective in the proteoglycan field and provides more evidence of nuclear interactions of syndecan-1

Telomere length and bipolar disorder

Variation in telomere length is heritable and is currently considered a promising biomarker of susceptibility for neuropsychiatric disorders, particularly because of its association with memory function and hippocampal morphology. Here, we investigate telomere length in connection to familial risk and disease expression in bipolar disorder (BD). We used quantitative polymerase chain reactions and a telomere-sequence to single-copy-gene-sequence ratio method to determine telomere length in genomic DNA extracted from buccal smears from 63 patients with BD, 74 first-degree relatives (49 relatives had no lifetime psychopathology and 25 had a non-BD mood disorder) and 80 unrelated healthy individuals. Participants also underwent magnetic resonance imaging to determine hippocampal volumes and cognitive assessment to evaluate episodic memory using the verbal paired associates test. Telomere length was shorter in psychiatrically-well relatives (p=0.007) compared to unrelated healthy participants. Telomere length was also shorter in relatives (regardless of psychiatric status; p<0.01) and patients with BD not on lithium (p=0.02) compared to lithium-treated patients with BD. In the entire sample, telomere length was positively associated with left and right hippocampal volume and with delayed recall. This study provides evidence that shortened telomere length is associated with familial risk for BD. Lithium may have neuroprotective properties that require further investigation using prospective designs

Justify your alpha

Benjamin et al. proposed changing the conventional “statistical significance” threshold (i.e.,the alpha level) from p ≤ .05 to p ≤ .005 for all novel claims with relatively low prior odds. They provided two arguments for why lowering the significance threshold would “immediately improve the reproducibility of scientific research.” First, a p-value near .05provides weak evidence for the alternative hypothesis. Second, under certain assumptions, an alpha of .05 leads to high false positive report probabilities (FPRP2 ; the probability that a significant finding is a false positive

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability-for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples