Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin.

Fragment screening is a technique that helps to identify promising starting points for ligand design. Given that crystals of the target protein are available and display reproducibly high-resolution X-ray diffraction properties, crystallography is among the most preferred methods for fragment screening because of its sensitivity. Additionally, it is the only method providing detailed 3D information of the binding mode of the fragment, which is vital for subsequent rational compound evolution. The routine use of the method depends on the availability of suitable fragment libraries, dedicated means to handle large numbers of samples, state-of-the-art synchrotron beamlines for fast diffraction measurements and largely automated solutions for the analysis of the results. Here, the complete practical workflow and the included tools on how to conduct crystallographic fragment screening (CFS) at the Helmholtz-Zentrum Berlin (HZB) are presented. Preceding this workflow, crystal soaking conditions as well as data collection strategies are optimized for reproducible crystallographic experiments. Then, typically in a one to two-day procedure, a 96-membered CFS-focused library provided as dried ready-to-use plates is employed to soak 192 crystals, which are then flash-cooled individually. The final diffraction experiments can be performed within one day at the robot-mounting supported beamlines BL14.1 and BL14.2 at the BESSY  II electron storage ring operated by the HZB in Berlin-Adlershof (Germany). Processing of the crystallographic data, refinement of the protein structures, and hit identification is fast and largely automated using specialized software pipelines on dedicated servers, requiring little user input. Using the CFS workflow at the HZB enables routine screening experiments. It increases the chances for successful identification of fragment hits as starting points to develop more potent binders, useful for pharmacological or biochemical applications.

A Standardized Project Gutenberg Corpus for Statistical Analysis of Natural Language and Quantitative Linguistics.

The use of Project Gutenberg (PG) as a text corpus has been extremely popular in statistical analysis of language for more than 25 years. However, in contrast to other major linguistic datasets of similar importance, no consensual full version of PG exists to date. In fact, most PG studies so far either consider only a small number of manually selected books, leading to potential biased subsets, or employ vastly different pre-processing strategies (often specified in insufficient details), raising concerns regarding the reproducibility of published results. In order to address these shortcomings, here we present the Standardized Project Gutenberg Corpus (SPGC), an open science approach to a curated version of the complete PG data containing more than 50,000 books and more than 3 × 10 9 word-tokens. Using different sources of annotated metadata, we not only provide a broad characterization of the content of PG, but also show different examples highlighting the potential of SPGC for investigating language variability across time, subjects, and authors. We publish our methodology in detail, the code to download and process the data, as well as the obtained corpus itself on three different levels of granularity (raw text, timeseries of word tokens, and counts of words). In this way, we provide a reproducible, pre-processed, full-size version of Project Gutenberg as a new scientific resource for corpus linguistics, natural language processing, and information retrieval.

Tunable Flexibility and Porosity of the Metal-Organic Framework DUT-49 through Postsynthetic Metal Exchange.

As a prominent and representative example of flexible metal-organic frameworks (MOFs), DUT-49(Cu) has gained attention due to the unique phenomenon of negative gas adsorption (NGA), originating from an unprecedented structural contraction during the gas adsorption. Herein, postsynthetic metal exchange is demonstrated to afford DUT-49 frameworks with a wide variety of metal cations, e.g., Mn2+, Fe2+, Ni2+, Zn2+, Cu2+, and Cd2+. The single-crystal-to-single-crystal conversion allowed characterization of the new MOFs by single crystal X-ray diffraction, indicating identical structure and topology compared with that of previously explored DUT-49(Cu) framework. This approach is proven successful in achieving Mn-Mn and Cd-Cd dimers, which are rare examples of M-M paddle-wheel SBUs. The relative stability and flexibility of the resulted frameworks are observed to be highly sensitive to the metal ion of the framework, following the trends predicted by the Irving-Williams series. DUT-49(Ni) was recognized as a second material from the DUT-49 series showing adsorption-induced transitions. A sequential increase in framework flexibility from rigid to flexible and from flexible to NGA has been achieved through selective incorporation of metal centers into the structure. Finally, heterometallic structures are formed by selective and controlled exchange of metal ions to finely tune the flexibility and NGA phenomenon of the framework.

Testing Statistical Laws in Complex Systems.

The availability of large datasets requires an improved view on statistical laws in complex systems, such as Zipf's law of word frequencies, the Gutenberg-Richter law of earthquake magnitudes, or scale-free degree distribution in networks. In this Letter, we discuss how the statistical analysis of these laws are affected by correlations present in the observations, the typical scenario for data from complex systems. We first show how standard maximum-likelihood recipes lead to false rejections of statistical laws in the presence of correlations. We then propose a conservative method (based on shuffling and undersampling the data) to test statistical laws and find that accounting for correlations leads to smaller rejection rates and larger confidence intervals on estimated parameters.

Large-scale analysis of micro-level citation patterns reveals nuanced selection criteria.

The analysis of citations to scientific publications has become a tool that is used in the evaluation of a researcher's work; especially in the face of an ever-increasing production volume1-6. Despite the acknowledged shortcomings of citation analysis and the ongoing debate on the meaning of citations7,8, citations are still primarily viewed as endorsements and as indicators of the influence of the cited reference, regardless of the context of the citation. However, only recently has attention9,10 been given to the connection between contextual information and the success of citing and cited papers, primarily because of the lack of extensive databases that cover both types of metadata. Here we address this issue by studying the usage of citations throughout the full text of 156,558 articles published by the Public Library of Science (PLoS), and by tracing their bibliometric history from among 60 million records obtained from the Web of Science. We find universal patterns of variation in the usage of citations across paper sections11. Notably, we find differences in microlevel citation patterns that were dependent on the ultimate impact of the citing paper itself; publications from high-impact groups tend to cite younger references, as well as more very young and better-cited references. Our study provides a quantitative approach to addressing the long-standing issue that not all citations count the same.

MXCuBE2: the dawn of MXCuBE Collaboration.

MXCuBE2 is the second-generation evolution of the MXCuBE beamline control software, initially developed and used at ESRF - the European Synchrotron. MXCuBE2 extends, in an intuitive graphical user interface (GUI), the functionalities and data collection methods available to users while keeping all previously available features and allowing for the straightforward incorporation of ongoing and future developments. MXCuBE2 introduces an extended abstraction layer that allows easy interfacing of any kind of macromolecular crystallography (MX) hardware component, whether this is a diffractometer, sample changer, detector or optical element. MXCuBE2 also works in strong synergy with the ISPyB Laboratory Information Management System, accessing the list of samples available for a particular experimental session and associating, either from instructions contained in ISPyB or from user input via the MXCuBE2 GUI, different data collection types to them. The development of MXCuBE2 forms the core of a fruitful collaboration which brings together several European synchrotrons and a software development factory and, as such, defines a new paradigm for the development of beamline control platforms for the European MX user community.

Reply to "Far away from the lamppost".

In this Formal Comment, the authors of the recent publication "Large-scale investigation of the reasons why potentially important genes are ignored" maintain that it can be read as an opportunity to explore the unknown.

Large-scale investigation of the reasons why potentially important genes are ignored.

Biomedical research has been previously reported to primarily focus on a minority of all known genes. Here, we demonstrate that these differences in attention can be explained, to a large extent, exclusively from a small set of identifiable chemical, physical, and biological properties of genes. Together with knowledge about homologous genes from model organisms, these features allow us to accurately predict the number of publications on individual human genes, the year of their first report, the levels of funding awarded by the National Institutes of Health (NIH), and the development of drugs against disease-associated genes. By explicitly identifying the reasons for gene-specific bias and performing a meta-analysis of existing computational and experimental knowledge bases, we describe gene-specific strategies for the identification of important but hitherto ignored genes that can open novel directions for future investigation.

A network approach to topic models.

One of the main computational and scientific challenges in the modern age is to extract useful information from unstructured texts. Topic models are one popular machine-learning approach that infers the latent topical structure of a collection of documents. Despite their success-particularly of the most widely used variant called latent Dirichlet allocation (LDA)-and numerous applications in sociology, history, and linguistics, topic models are known to suffer from severe conceptual and practical problems, for example, a lack of justification for the Bayesian priors, discrepancies with statistical properties of real texts, and the inability to properly choose the number of topics. We obtain a fresh view of the problem of identifying topical structures by relating it to the problem of finding communities in complex networks. We achieve this by representing text corpora as bipartite networks of documents and words. By adapting existing community-detection methods (using a stochastic block model (SBM) with nonparametric priors), we obtain a more versatile and principled framework for topic modeling (for example, it automatically detects the number of topics and hierarchically clusters both the words and documents). The analysis of artificial and real corpora demonstrates that our SBM approach leads to better topic models than LDA in terms of statistical model selection. Our work shows how to formally relate methods from community detection and topic modeling, opening the possibility of cross-fertilization between these two fields.

Using text analysis to quantify the similarity and evolution of scientific disciplines.

We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20 M papers from the past three decades reveals that the linguistic similarity is related but different from experts and citation-based classifications, leading to an improved view on the organization of science. A temporal analysis of the similarity of fields shows that some fields (e.g. computer science) are becoming increasingly central, but that on average the similarity between pairs of disciplines has not changed in the last decades. This suggests that tendencies of convergence (e.g. multi-disciplinarity) and divergence (e.g. specialization) of disciplines are in balance.

A robust data-driven approach identifies four personality types across four large data sets.

Understanding human personality has been a focus for philosophers and scientists for millennia1. It is now widely accepted that there are about five major personality domains that describe the personality profile of an individual2,3. In contrast to personality traits, the existence of personality types remains extremely controversial4. Despite the various purported personality types described in the literature, small sample sizes and the lack of reproducibility across data sets and methods have led to inconclusive results about personality types5,6. Here we develop an alternative approach to the identification of personality types, which we apply to four large data sets comprising more than 1.5 million participants. We find robust evidence for at least four distinct personality types, extending and refining previously suggested typologies. We show that these types appear as a small subset of a much more numerous set of spurious solutions in typical clustering approaches, highlighting principal limitations in the blind application of unsupervised machine learning methods to the analysis of big data.

[Guidelines in Practice: The New S3 Guideline "Sleeping Disorders - Sleep-Related Abnormal Breathing"]. / Leitlinien in der Praxis: Die neue S3-Leitlinie "Nicht erholsamer Schlaf/Schlafstörungen" ­ Kapitel "Schlafbezogene Atmungsstörungen".

Sleep related breathing disorders include central sleep apnea (CSA), obstructive sleep apnea (OSA), sleep-related hypoventilation, and sleep-related hypoxia. These disorders are frequent and growing in clinical relevance. The related chapter of the S3 guideline "Non-restorative sleep/Sleep disorders", published by the German Sleep Society (DGSM), has recently been updated in November 2016. Epidemiology, diagnostics, therapeutic procedures, and classification of sleep related disorders have been revised. Concerning epidemiology, a considerably higher mortality rate among pregnant women with OSA has been emphasized. With regards to diagnostics, the authors point out that respiratory polygraphy may be sufficient in diagnosing OSA, if a typical clinical condition is given. For CSA, recommendations were changed to diagnose CSA with low apnea rates present. Significant changes for treating CSA in patients with left ventricular dysfunction have been introduced. In addition, there is now to be differentiated between sleep-related hypoventilation and sleep-related hypoxaemia. Obesity hypoventilation syndrome is discussed in more detail. This article sums up and comments on the published changes.

[Sleep disorders: principles, basic diagnostics and elementary measures and recommendations]. / Schlafstörungen--ein praktischer Leitfaden. Grundlagen, Basis-Diagnostik, einfache Maßnahmen und Empfehlungen.

Sleep disorders are frequent. Economic costs and impairment of quality of life can be substantial. Usually, patients suffer from insomnia or hypersomnia. Several effective therapeutic options are available. Sleep disorders appear independently or accompany a multitude of organic and psychiatric diseases. Fatigue has to be distinguished from sleep disorders clearly. For classification, the ICSD-3, published by the American Academy of Sleep Medicine, is used. Patients should be explicitly asked for their sleep quality, for many do not report actively. Patient's history and clinical examination usually narrow the diagnosis to a large extent. Clinical diagnostics should be carried out according to the diagnostic algorithm by the German Sleep Society (DGSM). An optimal sleep hygiene and if necessary weight reduction are crucial and can prevent chronification and health consequences. In addition, assistive technology, drug therapy, behaviour therapy, and in few cases surgery are available.

Extracting information from S-curves of language change.

It is well accepted that adoption of innovations are described by S-curves (slow start, accelerating period and slow end). In this paper, we analyse how much information on the dynamics of innovation spreading can be obtained from a quantitative description of S-curves. We focus on the adoption of linguistic innovations for which detailed databases of written texts from the last 200 years allow for an unprecedented statistical precision. Combining data analysis with simulations of simple models (e.g. the Bass dynamics on complex networks), we identify signatures of endogenous and exogenous factors in the S-curves of adoption. We propose a measure to quantify the strength of these factors and three different methods to estimate it from S-curves. We obtain cases in which the exogenous factors are dominant (in the adoption of German orthographic reforms and of one irregular verb) and cases in which endogenous factors are dominant (in the adoption of conventions for romanization of Russian names and in the regularization of most studied verbs). These results show that the shape of S-curve is not universal and contains information on the adoption mechanism.

Photoelectric-enhanced radiation therapy with quasi-monochromatic computed tomography.

Photoelectric-enhanced radiation therapy is a bimodal therapy, consisting of the administration of highly radiation-absorbing substances into the tumor area and localized regional irradiation with orthovoltage x-rays. Irradiation can be performed by a modified computed tomography (CT) unit equipped with an additional x-ray optical module which converts the polychromatic, fan-shaped CT beam into a monochromatized and focused beam for energy-tuned photoelectric-enhanced radiotherapy. A dedicated x-ray optical module designed for spatial collimation, focusing, and monochromatization was mounted at the exit of the x-ray tube of a clinical CT unit. Spectrally resolved measurements of the resulting beam were performed using an energy-dispersive detection system calibrated by synchrotron radiation. The spatial photon fluence was determined by film dosimetry. Depth-dose measurements were performed and compared to the polychromatic CT and a therapeutic 6 MV beam. The spatial dose distribution in phantoms using a rotating radiation source (quasimonochromatic CT and 6 MV, respectively) was investigated by gel dosimetry. The photoelectric dose enhancement for an iodine fraction of 1% in tissue was calculated and verified experimentally. The x-ray optical module selectively filters the energy of the tungsten Kalpha emission line with an FWHM of 5 keV. The relative photon fluence distribution demonstrates the focusing characteristic of the x-ray optical module. A beam width of about 3 mm was determined at the isocenter of the CT gantry. The depth-dose measurements resulted in a half-depth value of approximately 36 mm for the CT beams (quasi-monochromatic, polychromatic) compared to 154 mm for the 6 MV beam. The rotation of the radiation source leads to a steep dose gradient at the center of rotation; the gel dosimetry yields an entrance-to-peak dose ratio of 1:10.8 for the quasi-monochromatic CT and 1:37.3 for a 6 MV beam of the same size. The photoelectric dose enhancement factor increases from 2.2 to 2.4 by using quasi-monochromatic instead of polychromatic radiation. An additional increase in the radiation dose by a factor of 1.4 due to the focusing characteristic of the x-ray optical module was calculated. Photoelectric-enhanced radiation therapy based on a clinical CT unit combined with an x-ray optical module is a novel therapy option in radiation oncology. The optimized quasi-monochromatic radiation is strongly focused and ensures high photoelectric dose enhancement for iodine.

Nondestructive characterization of nanoscale layered samples.

Multilayered samples consisting of Al, Co and Ni nanolayers were produced by MBE and characterized nondestructively by means of SRXRF, mu-XRF, WDXRF, RBS, XRR, and destructively with SIMS. The main aims were to identify the elements, to determine their purity and their sequence, and also to examine the roughness, density, homogeneity and thickness of each layer. Most of these important properties could be determined by XRF methods, e.g., on commercial devices. For the thickness, it was found that all of the results obtained via XRR, RBS, SIMS and various XRF methods (SRXRF, mu-XRF, WDXRF) agreed with each other within the limits of uncertainty, and a constant deviation from the presets used in the MBE production method was observed. Some serious preliminary discrepancies in the results from the XRF methods were examined, but all deviations could be explained by introducing various corrections into the evaluation methods and/or redetermining some fundamental parameters.

Imaging-therapy computed tomography with quasi-monochromatic X-rays.

INTRODUCTION: Computed tomography (CT) is a widespread and highly precise technique working in the energy range around 50-100 keV. For radiotherapy, however, the MeV energy range enables a better dose distribution. This gap between diagnosis and therapy can be overcome by the use of a modified CT machine in combination with heavy elements targeted to the tumour and used as photoelectric radiation enhancer. MATERIALS AND METHODS: The experimental setup consists of an X-ray optical module mounted at the exit of the X-ray tube of a clinical CT. The module converts the standard fan-shaped beam into a high intensity, monochromatized and focused beam. The radiation was characterized using an energy-dispersive detection system calibrated by synchrotron radiation and gel dosimetry. The photoelectric radiation enhancement for different elements was calculated and experimentally verified. RESULTS: The X-ray optical module filters selectively the energy of the tungsten K alpha-emission line (59.3 keV) with a full width at half maximum (FWHM) of 5 keV and focused the radiation onto a focal spot which coincides with the isocentre of the gantry. This results in a steep dose gradient at the centre of rotation qualified for locoregional radiation therapy. The photon energy of the quasi-monochromatic radiation agrees with the energy range of maximal photoelectric dose enhancement for gadolinium and iodine. CONCLUSION: An additional X-ray optical module optimized for targeted therapy and photoelectric dose enhancement allows the combination of diagnosis and radiotherapy on a clinical CT.

Detection of TAP-tagged proteins in Western blot, confocal laser scanning microscopy and FACS using the ZZ-domain.

Tandem affinity purification of protein complexes has become an important tool in the field of proteomic research. Analysis of the proper intracellular localization of TAP-tagged proteins by immunohistochemistry by specific antibodies is often impossible due to the simultaneous detection of the endogenously synthesized native protein. Here we show that the highly specific interaction of the ZZ-domain of Protein A, which constitutes part of the original TAP-tag, to rabbit IgGs can be used to detect TAP-tagged proteins in fixated cells by Confocal Laser Scanning Microscopy just by the use of labeled secondary antibodies. In addition, such interactions can be exploited for the analysis of transfected cells in FACS and Western blot experiments. Thus, we present valuable tools for the analysis of recombinant proteins on the basis of IgG-ZZ interactions, which can be used even if target specific first antibodies are not available or lack sufficient specificity.