Touch DNA sampling with SceneSafe Fast™ minitapes.

To achieve optimal results in the forensic analysis of trace DNA, choosing the right collection technique is crucial. Three common approaches are currently well-established for DNA retrieval from items of clothing, notably cutting, swabbing and tape-lifting. The latter two are non-destructive and therefore preferable on items of value. Even though the most recently established technique of DNA retrieval by adhesive tapes is widely used since quite some years now, little information has been published so far on how well it performs compared to other methods. Even more important, when it comes to choosing the right DNA extraction method for forensic lifting-tapes, the available information one can rely on as a forensic geneticist is quite scarce. In our study we compared the two widely used, commercially available and automation suitable magnetic bead-based extraction methods "iPrep Forensic Kit" and "PrepFiler Express BTA™ Kit" to conventional organic solvent extraction. The results demonstrate that DNA extraction from standardized saliva samples applied to SceneSafe Fast™ minitapes is most efficient with phenol-chloroform. We also provide evidence that SceneSafe Fast™ minitapes perform better than wet cotton swabs in the sampling of touch DNA from cotton fabric. Applying the tape only once in every spot on the tissue is thereby sufficient for a considerably better collection performance of the tapes compared to swabbing.

Beyond scale-free small-world networks: cortical columns for quick brains.

We study to what extent cortical columns with their particular wiring boost neural computation. Upon a vast survey of columnar networks performing various real-world cognitive tasks, we detect no signs of enhancement. It is on a mesoscopic--intercolumnar--scale that the existence of columns, largely irrespective of their inner organization, enhances the speed of information transfer and minimizes the total wiring length required to bind distributed columnar computations towards spatiotemporally coherent results. We suggest that brain efficiency may be related to a doubly fractal connectivity law, resulting in networks with efficiency properties beyond those by scale-free networks.