Random planar graphs and the London street network

In this paper we analyse the street network of London both in its primary and dual representation. To understand its properties, we consider three idealised models based on a grid, a static random planar graph and a growing random planar graph. Comparing the models and the street network, we find that the streets of London form a self-organising system whose growth is characterised by a strict interaction between the metrical and informational space. In particular, a principle of least effort appears to create a balance between the physical and the mental effort required to navigate the city

Application of deep learning models to improve ulcerative colitis endoscopic disease activity scoring under multiple scoring systems

Background and Aims Lack of clinical validation and inter-observer variability are two limitations of endoscopic assessment and scoring of disease severity in patients with ulcerative colitis [UC]. We developed a deep learning [DL] model to improve, accelerate and automate UC detection, and predict the Mayo Endoscopic Subscore [MES] and the Ulcerative Colitis Endoscopic Index of Severity [UCEIS]. Methods A total of 134 prospective videos [1550 030 frames] were collected and those with poor quality were excluded. The frames were labelled by experts based on MES and UCEIS scores. The scored frames were used to create a preprocessing pipeline and train multiple convolutional neural networks [CNNs] with proprietary algorithms in order to filter, detect and assess all frames. These frames served as the input for the DL model, with the output being continuous scores for MES and UCEIS [and its components]. A graphical user interface was developed to support both labelling video sections and displaying the predicted disease severity assessment by the artificial intelligence from endoscopic recordings. Results Mean absolute error [MAE] and mean bias were used to evaluate the distance of the continuous model’s predictions from ground truth, and its possible tendency to over/under-predict were excellent for MES and UCEIS. The quadratic weighted kappa used to compare the inter-rater agreement between experts’ labels and the model’s predictions showed strong agreement [0.87, 0.88 at frame-level, 0.88, 0.90 at section-level and 0.90, 0.78 at video-level, for MES and UCEIS, respectively]. Conclusions We present the first fully automated tool that improves the accuracy of the MES and UCEIS, reduces the time between video collection and review, and improves subsequent quality assurance and scoring

Urban road networks -- Spatial networks with universal geometric features? A case study on Germany's largest cities

Urban road networks have distinct geometric properties that are partially determined by their (quasi-) two-dimensional structure. In this work, we study these properties for 20 of the largest German cities. We find that the small-scale geometry of all examined road networks is extremely similar. The object-size distributions of road segments and the resulting cellular structures are characterised by heavy tails. As a specific feature, a large degree of rectangularity is observed in all networks, with link angle distributions approximately described by stretched exponential functions. We present a rigorous statistical analysis of the main geometric characteristics and discuss their mutual interrelationships. Our results demonstrate the fundamental importance of cost-efficiency constraints for in time evolution of urban road networks.Comment: 16 pages; 8 figure

Analyzing and Modeling Real-World Phenomena with Complex Networks: A Survey of Applications

The success of new scientific areas can be assessed by their potential for contributing to new theoretical approaches and in applications to real-world problems. Complex networks have fared extremely well in both of these aspects, with their sound theoretical basis developed over the years and with a variety of applications. In this survey, we analyze the applications of complex networks to real-world problems and data, with emphasis in representation, analysis and modeling, after an introduction to the main concepts and models. A diversity of phenomena are surveyed, which may be classified into no less than 22 areas, providing a clear indication of the impact of the field of complex networks.Comment: 103 pages, 3 figures and 7 tables. A working manuscript, suggestions are welcome

Design and Synthesis of Highly Potent HIV‑1 Protease Inhibitors Containing Tricyclic Fused Ring Systems as Novel P2 Ligands: Structure–Activity Studies, Biological and X‑ray Structural Analysis

The design, synthesis, and biological evaluation of a new class of HIV-1 protease inhibitors containing stereochemically defined fused tricyclic polyethers as the P2 ligands and a variety of sulfonamide derivatives as the P2′ ligands are described. A number of ring sizes and various substituent effects were investigated to enhance the ligand–backbone interactions in the protease active site. Inhibitors <b>5c</b> and <b>5d</b> containing this unprecedented fused 6–5–5 ring system as the P2 ligand, an aminobenzothiazole as the P2′ ligand, and a difluorophenylmethyl as the P1 ligand exhibited exceptional enzyme inhibitory potency and maintained excellent antiviral activity against a panel of highly multidrug-resistant HIV-1 variants. The umbrella-like P2 ligand for these inhibitors has been synthesized efficiently in an optically active form using a Pauson–Khand cyclization reaction as the key step. The racemic alcohols were resolved efficiently using a lipase catalyzed enzymatic resolution. Two high resolution X-ray structures of inhibitor-bound HIV-1 protease revealed extensive interactions with the backbone atoms of HIV-1 protease and provided molecular insight into the binding properties of these new inhibitors

Design and Synthesis of Highly Potent HIV‑1 Protease Inhibitors Containing Tricyclic Fused Ring Systems as Novel P2 Ligands: Structure–Activity Studies, Biological and X‑ray Structural Analysis

The design, synthesis, and biological evaluation of a new class of HIV-1 protease inhibitors containing stereochemically defined fused tricyclic polyethers as the P2 ligands and a variety of sulfonamide derivatives as the P2′ ligands are described. A number of ring sizes and various substituent effects were investigated to enhance the ligand–backbone interactions in the protease active site. Inhibitors <b>5c</b> and <b>5d</b> containing this unprecedented fused 6–5–5 ring system as the P2 ligand, an aminobenzothiazole as the P2′ ligand, and a difluorophenylmethyl as the P1 ligand exhibited exceptional enzyme inhibitory potency and maintained excellent antiviral activity against a panel of highly multidrug-resistant HIV-1 variants. The umbrella-like P2 ligand for these inhibitors has been synthesized efficiently in an optically active form using a Pauson–Khand cyclization reaction as the key step. The racemic alcohols were resolved efficiently using a lipase catalyzed enzymatic resolution. Two high resolution X-ray structures of inhibitor-bound HIV-1 protease revealed extensive interactions with the backbone atoms of HIV-1 protease and provided molecular insight into the binding properties of these new inhibitors

Design and Development of Highly Potent HIV‑1 Protease Inhibitors with a Crown-Like Oxotricyclic Core as the P2-Ligand To Combat Multidrug-Resistant HIV Variants

Design, synthesis, and evaluation of a new class of exceptionally potent HIV-1 protease inhibitors are reported. Inhibitor <b>5</b> displayed superior antiviral activity and drug-resistance profiles. In fact, this inhibitor showed several orders of magnitude improved antiviral activity over the FDA approved drug darunavir. This inhibitor incorporates an unprecedented 6–5–5 ring-fused crown-like tetrahydro­pyranofuran as the P2 ligand and an aminobenzo­thiazole as the P2′ ligand with the (<i>R</i>)-hydroxyethyl­sulfonamide isostere. The crown-like P2 ligand for this inhibitor has been synthesized efficiently in an optically active form using a chiral Diels–Alder catalyst providing a key intermediate in high enantiomeric purity. Two high resolution X-ray structures of inhibitor-bound HIV-1 protease revealed extensive interactions with the backbone atoms of HIV-1 protease and provided molecular insight into the binding properties of these new inhibitors

On the thresholds in linear and nonlinear Boolean equations

We introduce a generalized XORSAT model, named as Massive Algebraic System (Hereafter abbreviated as MAS) consisting of linear and nonlinear Boolean equations. Through adjusting the proportion of nonlinear equations, denoted by p, this MAS model smoothly interpolates between XORSAT (p = 0) and MAS-nonlinear (p = 1). We conduct a systematic and complete study about a series of phase transitions in the space of solutions at given p and also present how the phase diagram evolves with the increase of p. First of all, using the probabilistic method and energetic 1RSB cavity method, we compute the satisfiability thresholds for any given p ∈ [0,1) and determine a region where the satisfaction of problem all depends on its subproblem MAS-nonlinear. Furthermore, we locate three important non-satisfiability transitions, i.e. clustering, condensation and freezing, using entropic 1RSB cavity method, and find the space of solution undergoing different phase transition processes with the increase of p

Indolcarboxamide is a preclinical candidate for treating multidrug-resistant tuberculosis

10.1126/scitranslmed.3007355Science Translational Medicine5214