5 research outputs found

    Avoiding Twisted Pixels: Ethical Guidelines for the Appropriate Use and Manipulation of Scientific Digital Images

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    Digital imaging has provided scientists with new opportunities to acquire and manipulate data using techniques that were difficult or impossible to employ in the past. Because digital images are easier to manipulate than film images, new problems have emerged. One growing concern in the scientific community is that digital images are not being handled with sufficient care. The problem is twofold: (1) the very small, yet troubling, number of intentional falsifications that have been identified, and (2) the more common unintentional, inappropriate manipulation of images for publication. Journals and professional societies have begun to address the issue with specific digital imaging guidelines. Unfortunately, the guidelines provided often do not come with instructions to explain their importance. Thus they deal with what should or should not be done, but not the associated ‘why’ that is required for understanding the rules. This article proposes 12 guidelines for scientific digital image manipulation and discusses the technical reasons behind these guidelines. These guidelines can be incorporated into lab meetings and graduate student training in order to provoke discussion and begin to bring an end to the culture of “data beautification”

    Digital Images Are Data: And Should Be Treated as Such

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    The scientific community has become very concerned about inappropriate image manipulation. In journals that check figures after acceptance, 20–25% of the papers contained at least one figure that did not comply with the journal’s instructions to authors. The scientific press continues to report a small, but steady stream of cases of fraudulent image manipulation. Inappropriate image manipulation taints the scientific record, damages trust within science, and degrades science’s reputation with the general public. Scientists can learn from historians and photojournalists, who have provided a number of examples of attempts to alter or misrepresent the historical record. Scientists must remember that digital images are numerically sampled data that represent the state of a specific sample when examined with a specific instrument. These data should be carefully managed. Changes made to the original data need to be tracked like the protocols used for other experimental procedures. To avoid pitfalls, unexpected artifacts, and unintentional misrepresentation of the image data, a number of image processing guidelines are offered

    A QUICK Screen for Lrrk2 Interaction Partners – Leucine-rich Repeat Kinase 2 is Involved in Actin Cytoskeleton Dynamics*

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    Mutations in human leucine-rich repeat kinase 2 (Lrrk2), a protein of yet unknown function, are linked to Parkinson's disease caused by degeneration of midbrain dopaminergic neurons. The protein comprises several domains including a GTPase and a kinase domain both affected by several pathogenic mutations. To elucidate the molecular interaction network of endogenous Lrrk2 under stoichiometric constraints, we applied QUICK (quantitative immunoprecipitation combined with knockdown) in NIH3T3 cells. The identified interactome reveals actin isoforms as well as actin-associated proteins involved in actin filament assembly, organization, rearrangement, and maintenance, suggesting that the biological function of Lrrk2 is linked to cytoskeletal dynamics. In fact, we demonstrate Lrrk2 de novo binding to F-actin and its ability to modulate its assembly in vitro. When tested in intact cells, knockdown of Lrrk2 causes morphological alterations in NIH3T3 cells. In developing dopaminergic midbrain primary neurons, Lrrk2 knockdown results in shortened neurite processes, indicating a physiological role of Lrrk2 in cytoskeletal organization and dynamics of dopaminergic neurons. Hence, our results demonstrate that molecular interactions as well as the physiological function of Lrrk2 are closely related to the organization of the actin-based cytoskeleton, a crucial feature of neuronal development and neuron function
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