Supplementary Material for: Effectiveness of Barrier Creams against Irritant Contact Dermatitis

<b><i>Introduction:</i></b> Skin tissue is frequently exposed to various irritant substances in the workplace, particularly in wet work, which can lead to the development of occupational contact dermatitis. ‘Barrier' creams (BCs) are well known, and their applications are still the subject of many studies and controversies. <b><i>Methods:</i></b> We searched all controlled trials investigating BCs against cutaneous irritants in humans published between 1956 and December 2014 from MEDLINE, PubMed, reference lists and existing reviews. <b><i>Results:</i></b> Thirty-nine studies about the effects of BCs against skin irritants in humans were selected. Among these, 27 trials in healthy volunteers were found to show many differences with regard to BCs and irritants used, their quantities, test locations, procedures and assessment methods. Finally, 14 patch test trials assessed by clinical scoring and evaporimetry emerged. Although the findings were generally positive, only few findings could be cross-checked from all the data, and vehicles seem to be as effective as BCs. <b><i>Conclusion:</i></b> Although this review highlights the poor quality and the lack of standardization of most studies, BCs seem to have protective effects against irritants. Further well-designed, adequately powered randomized controlled trials with clinical and biophysical assessments are required

Haruspex: A Neural Network for the Automatic Identification of Oligonucleotides and Protein Secondary Structure in Cryo‐Electron Microscopy Maps

In recent years, three‐dimensional density maps reconstructed from single particle images obtained by electron cryo‐microscopy (cryo‐EM) have reached unprecedented resolution. However, map interpretation can be challenging, in particular if the constituting structures require de‐novo model building or are very mobile. Herein, we demonstrate the potential of convolutional neural networks for the annotation of cryo‐EM maps: our network Haruspex has been trained on a carefully curated set of 293 experimentally derived reconstruction maps to automatically annotate RNA/DNA as well as protein secondary structure elements. It can be straightforwardly applied to newly reconstructed maps in order to support domain placement or as a starting point for main‐chain placement. Due to its high recall and precision rates of 95.1 % and 80.3 %, respectively, on an independent test set of 122 maps, it can also be used for validation during model building. The trained network will be available as part of the CCP‐EM suite