This paper describes the current update on macromolecular model validation services that are provided at the MolProbity website, emphasizing changes and additions since the previous review in 2010. There have been many infrastructure improvements, including rewrite of previous Java utilities to now use existing or newly written Python utilities in the open-source CCTBX portion of the Phenix software system. This improves long-term maintainability and enhances the thorough integration of MolProbity-style validation within Phenix. There is now a complete MolProbity mirror site at http://molprobity.manchester.ac.uk. GitHub serves our open-source code, reference datasets, and the resulting multi-dimensional distributions that define most validation criteria. Coordinate output after Asn/Gln/His "flip" correction is now more idealized, since the post-refinement step has apparently often been skipped in the past. Two distinct sets of heavy-atom-to-hydrogen distances and accompanying van der Waals radii have been researched and improved in accuracy, one for the electron-cloud-center positions suitable for X-ray crystallography and one for nuclear positions. New validations include Additional Supporting Information may be found in the online version of this article.Grant sponsor: National Institutes of health; Grant numbers: R01-GM073919 to DCR, P01-GM063210 subcontract to JSR, R01-GM088674 to JSR, R01-GM073930 to DCR and its ARRA supplement, and DUMC bridge funding. messages at input about problem-causing format irregularities, updates of Ramachandran and rotamer criteria from the million quality-filtered residues in a new reference dataset, the CaBLAM Ca-CO virtual-angle analysis of backbone and secondary structure for cryoEM or low-resolution X-ray, and flagging of the very rare cis-nonProline and twisted peptides which have recently been greatly overused. Due to wide application of MolProbity validation and corrections by the research community, in Phenix, and at the worldwide Protein Data Bank, newly deposited structures have continued to improve greatly as measured by MolProbity's unique all-atom clashscore.

We have recently completed a full re-architecturing of the Rosetta molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy to use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as Rosetta3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This document describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform.

When the Gibbs sampler is used to estimate posterior distributions (Gelfand and Smith, 1990), the question of how many iterations are required is central to its implementation. When interest focuses on quantiles of functionals of the posterior distribution, we describe an easily-implemented method for determining the total number of iterations required, and also the number of initial iterations that should be discarded to allow for \burn-in". The method uses only the Gibbs iterates themselves, and does not, for example, require external speci cation of characteristics of the posterior density. Here the method is described for the situation where one long run is generated, but it can also be easily applied if there are several runs from di erent starting points. It also applies more generally to Markov chain Monte Carlo schemes other than the Gibbs sampler. It can also be used when several quantiles are to be estimated, when the quantities of interest are probabilities rather than full posterior distributions, and when the draws from the posterior distribution are required to be approximately independent. The method is applied to several di erent posterior distributions. These include a multivariate normal posterior distribution with independent parameters, a bimodal distribution, a \cigar-shaped" multivariate normal distribution in ten dimensions, and a highly complex 190-dimensional posterior distribution arising in spatial statistics. In each case the method appears to give satisfactory results. The results suggest that reasonable accuracy may often be achieved with 5,000 iterations or less; this can frequently be reduced to less than 1,000 if the posterior tails are known to be light. However, there are frequent \exceptions" when the required number of iterations is much higher. One important such exception is when there are high posterior correlations between the parameters; even crude correlation-removing This research was supported by ONR contract N-00014-88-K-0265 and by NIH grant no. 5R01HD26330-02. The authors are grateful to Jeremy York for providing the data for Examples 4 and 5, for helping with the analysis and for useful discussions and suggestions, and to Julian Besag and an anonymous referee for helpful comments. A Fortran program called \Gibbsit" that implements the methods described here may be obtained from StatLib by sending an e-mail message to

The spleen is the largest secondary lymphoid organ in the body and, as such, hosts a wide range of immunologic functions alongside its roles in hematopoiesis and red blood cell clearance. The physical organization of the spleen allows it to filter blood of pathogens and abnormal cells and facilitate low-probability interactions between antigen-presenting cells (APCs) and cognate lymphocytes. APCs specific to the spleen regulate the T and B cell response to these antigenic targets in the blood. This review will focus on cell types, cell organization, and immunologic functions specific to the spleen and how these affect initiation of adaptive immunity to systemic blood-borne antigens. Potential differences in structure and function between mouse and human spleen will also be discussed.

The Rosetta software suite for macromolecular modeling, docking, and design is widely used in pharmaceutical, industrial, academic, non-profit, and government laboratories. Despite its broad modeling capabilities, Rosetta remains consistently among leading software suites when compared to other methods created for highly specialized protein modeling and design tasks. Developed for over two decades by a global community of over 60 laboratories, Rosetta has undergone multiple refactorings, and now comprises over three million lines of code. Here we discuss methods developed in the last five years in Rosetta, involving the latest protocols for structure prediction; protein-protein and protein-small molecule docking; protein structure and interface design; loop modeling; the incorporation of various types of experimental data; modeling of peptides, antibodies and proteins in the immune system, nucleic acids, non-standard chemistries, carbohydrates, and membrane proteins. We briefly discuss improvements to the energy function, user interfaces, and usability of the software. Rosetta is available at www.rosettacommons.org.