资源环境科技发展态势分析平台

Data analysis workflows in many scientific domains have become increasingly complex and flexible. Here we assess the effect of this flexibility on the results of functional magnetic resonance imaging by asking 70 independent teams to analyse the same dataset, testing the same 9 ex-ante hypotheses(1). The flexibility of analytical approaches is exemplified by the fact that no two teams chose identical workflows to analyse the data. This flexibility resulted in sizeable variation in the results of hypothesis tests, even for teams whose statistical maps were highly correlated at intermediate stages of the analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Notably, a meta-analytical approach that aggregated information across teams yielded a significant consensus in activated regions. 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(2-5). Our findings show that analytical flexibility can have substantial effects on scientific conclusions, and identify factors that may be related to variability in the analysis of functional magnetic resonance imaging. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for performing and reporting multiple analyses of the same data. Potential approaches that could be used to mitigate issues related to analytical variability are discussed.

The results obtained by seventy different teams analysing the same functional magnetic resonance imaging dataset show substantial variation, highlighting the influence of analytical choices and the importance of sharing workflows publicly and performing multiple analyses.

The mechanics of the cellular microenvironment continuously modulates cell functions such as growth, survival, apoptosis, differentiation and morphogenesis via cytoskeletal remodelling and actomyosin contractility(1-3). Although all of these processes consume energy(4,5), it is unknown whether and how cells adapt their metabolic activity to variable mechanical cues. Here we report that the transfer of human bronchial epithelial cells from stiff to soft substrates causes a downregulation of glycolysis via proteasomal degradation of the rate-limiting metabolic enzyme phosphofructokinase (PFK). PFK degradation is triggered by the disassembly of stress fibres, which releases the PFK-targeting E3 ubiquitin ligase tripartite motif (TRIM)-containing protein 21 (TRIM21). Transformed non-small-cell lung cancer cells, which maintain high glycolytic rates regardless of changing environmental mechanics, retain PFK expression by downregulating TRIM21, and by sequestering residual TRIM21 on a stress-fibre subset that is insensitive to substrate stiffness. Our data reveal a mechanism by which glycolysis responds to architectural features of the actomyosin cytoskeleton, thus coupling cell metabolism to the mechanical properties of the surrounding tissue. These processes enable normal cells to tune energy production in variable microenvironments, whereas the resistance of the cytoskeleton in response to mechanical cues enables the persistence of high glycolytic rates in cancer cells despite constant alterations of the tumour tissue.

Glycolysis in normal epithelial cells responds to microenvironmental mechanics via the modulation of actin bundles that sequester the phosphofructokinase-targeting ubiquitin ligase TRIM21, a process superseded by persistent actin bundles in cancer cells.

Genome editing, which involves the precise manipulation of cellular DNA sequences to alter cell fates and organism traits, has the potential to both improve our understanding of human genetics and cure genetic disease. Here I discuss the scientific, technical and ethical aspects of using CRISPR (clustered regularly interspaced short palindromic repeats) technology for therapeutic applications in humans, focusing on specific examples that highlight both opportunities and challenges. Genome editing is-or will soon be-in the clinic for several diseases, with more applications under development. The rapid pace of the field demands active efforts to ensure that this breakthrough technology is used responsibly to treat, cure and prevent genetic disease.