How the cuticles of the roughly 4.5 million species of ecdysozoan animals are constructed is not well understood. Here, we systematically mine gene expression datasets to uncover the spatiotemporal blueprint for how the chitin-based pharyngeal cuticle of the nematode Caenorhabditis elegans is built. We demonstrate that the blueprint correctly predicts expression patterns and functional relevance to cuticle development. We find that as larvae prepare to molt, catabolic enzymes are upregulated and the genes that encode chitin synthase, chitin cross-linkers, and homologs of amyloid regulators subsequently peak in expression. 48% of the gene products secreted during the molt are predicted to be intrinsically disordered proteins (IDPs), many of which belong to four distinct families whose transcripts are expressed in overlapping waves. These include the IDPAs, IDPBs, and IDPCs, which are introduced for the first time here. All four families have sequence properties that drive phase separation and we demonstrate phase-separation for one exemplar in vitro. This systematic analysis represents the first blueprint for cuticle construction and highlights the massive contribution that phase-separating materials make to the structure.

The Protein Data Bank ( PDB ) contains more than 135 000 entries at present. From these, relatively few amyloid structures can be identified, since amyloids are insoluble in water. Therefore, most amyloid structures deposited in the PDB are in the form of solid state NMR data. Based on the geometric analysis of these deposited structures, we have prepared an automatically updated web server, which generates a list of the deposited amyloid structures, and also entries of globular proteins that have amyloid‐like substructures of given size and characteristics. We have found that by applying only appropriately selected geometric conditions, it is possible to identify deposited amyloid structures and a number of globular proteins with amyloid‐like substructures. We have analyzed these globular proteins and have found proof in the literature that many of them form amyloids more easily than many other globular proteins. Our results relate to the method of Stanković et al . [Stanković I et al . (2017) IPSI BgD Tran Int Res 13, 47–51], who applied a hybrid textual‐search and geometric approach for finding amyloids in the PDB . If one intends to identify a subset of the PDB for certain applications, the identification algorithm needs to be re‐run periodically, since in 2017 on average 30 new entries per day were deposited in the data bank. Our web server is updated regularly and automatically, and the identified amyloid and partial amyloid structures can be viewed or their list can be downloaded from the following website https://pitgroup.org/amyloid .

The spread of robot-assisted minimal invasive surgery presents new challenges to surgeons and researchers alike. The novel surgical tools, methods and processes require different skills from the clinicians, thus surgical training and skillassessment has become increasingly important. In this article, we describe the modification process of a widely used training device, the Fundamentals of Robotic Surgery (FRS) Dome, that was made capable of automatic skill-assessment too, by applying different sensors on it. The basic principles and methods of the sensorization process are shown, together with the first results obtained on the amended training platform.

The Protein Data Bank (PDB) today contains more than 174,000 entries with the 3-dimensional structures of biological macromolecules. Using the rich resources of this repository, it is possible identifying subsets with specific, interesting properties for different applications. Our research group prepared an automatically updated list of amyloid- and probably amyloidogenic molecules, the PDB_Amyloid collection, which is freely available at the address http://pitgroup.org/amyloid. This resource applies exclusively the geometric properties of the steric structures for identifying amyloids. In the present contribution, we analyze the starting (i.e., prefix) subsequences of the characteristic, parallel beta-sheets of the structures in the PDB_Amyloid collection, and identify further appearances of these length-5 prefix subsequences in the whole PDB data set. We have identified this way numerous proteins, whose normal or irregular functions involve amyloid formation, structural misfolding, or anti-coagulant properties, simply by containing these prefixes: including the T-cell receptor (TCR), bound with the major histocompatibility complexes MHC-1 and MHC-2; the p53 tumor suppressor protein; a mycobacterial RNA polymerase transcription initialization complex; the human bridging integrator protein BIN-1; and the tick anti-coagulant peptide TAP.