Circadian pattern and burstiness in mobile phone communication

The temporal communication patterns of human individuals are known to be inhomogeneous or bursty, which is reflected as the heavy tail behavior in the inter-event time distribution. As the cause of such bursty behavior two main mechanisms have been suggested: a) Inhomogeneities due to the circadian and weekly activity patterns and b) inhomogeneities rooted in human task execution behavior. Here we investigate the roles of these mechanisms by developing and then applying systematic de-seasoning methods to remove the circadian and weekly patterns from the time-series of mobile phone communication events of individuals. We find that the heavy tails in the inter-event time distributions remain robustly with respect to this procedure, which clearly indicates that the human task execution based mechanism is a possible cause for the remaining burstiness in temporal mobile phone communication patterns.Comment: 17 pages, 12 figure

Excess protein enabled dog domestication during severe Ice Age winters

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Correlated dynamics in egocentric communication networks

We investigate the communication sequences of millions of people through two different channels and analyze the fine grained temporal structure of correlated event trains induced by single individuals. By focusing on correlations between the heterogeneous dynamics and the topology of egocentric networks we find that the bursty trains usually evolve for pairs of individuals rather than for the ego and his/her several neighbors thus burstiness is a property of the links rather than of the nodes. We compare the directional balance of calls and short messages within bursty trains to the average on the actual link and show that for the trains of voice calls the imbalance is significantly enhanced, while for short messages the balance within the trains increases. These effects can be partly traced back to the technological constrains (for short messages) and partly to the human behavioral features (voice calls). We define a model that is able to reproduce the empirical results and may help us to understand better the mechanisms driving technology mediated human communication dynamics.Comment: 7 pages, 6 figure

Discovering and Predicting Temporal Patterns of WiFi-interactive Social Populations

Extensive efforts have been devoted to characterizing the rich connectivity patterns among the nodes (components) of such complex networks (systems), and in the course of development of research in this area, people have been prompted to address on a fundamental question: How does the fascinating yet complex topological features of a network affect or determine the collective behavior and performance of the networked system? While elegant attempts to address this core issue have been made, for example, from the viewpoints of synchronization, epidemics, evolutionary cooperation, and the control of complex networks, theoretically or empirically, this widely concerned key question still remains open in the newly emergent field of network science. Such fruitful advances also push the desire to understand (mobile) social networks and characterize human social populations with the interdependent collective dynamics as well as the behavioral patterns. Nowadays, a great deal of digital technologies are unobtrusively embedded into the physical world of human daily activities, which offer unparalleled opportunities to explosively digitize human physical interactions, who is contacting with whom at what time. Such powerful technologies include the Bluetooth, the active Radio Frequency Identification (RFID) technology, wireless sensors and, more close to our interest in this paper, the WiFi technology. As a snapshot of the modern society, a university is in the coverage of WiFi signals, where the WiFi system records the digital access logs of the authorized WiFi users when they access the campus wireless services. Such WiFi access records, as the indirect proxy data, work as the effective proxy of a large-scale population's social interactions.Comment: 11 pages, 10 page

Infrared microspectroscopic determination of collagen cross-links in articular cartilage

Collagen forms an organized network in articular cartilage to give tensile stiffness to the tissue. Due to its long half-life, collagen is susceptible to cross-links caused by advanced glycation end-products. The current standard method for determination of cross-link concentrations in tissues is the destructive high-performance liquid chromatography (HPLC). The aim of this study was to analyze the cross-link concentrations nondestructively from standard unstained histological articular cartilage sections by using Fourier transform infrared (FTIR) microspectroscopy. Half of the bovine articular cartilage samples (n = 27) were treated with threose to increase the collagen cross-linking while the other half (n = 27) served as a control group. Partial least squares (PLS) regression with variable selection algorithms was used to predict the cross-link concentrations from the measured average FTIR spectra of the samples, and HPLC was used as the reference method for cross-link concentrations. The correlation coefficients between the PLS regression models and the biochemical reference values were r = 0.84 (p <0.001), r = 0.87 (p <0.001) and r = 0.92 (p <0.001) for hydroxylysyl pyridinoline (HP), lysyl pyridinoline (LP), and pentosidine (Pent) cross-links, respectively. The study demonstrated that FTIR microspectroscopy is a feasible method for investigating cross-link concentrations in articular cartilage. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.Peer reviewe

Bursty egocentric network evolution in Skype

In this study we analyze the dynamics of the contact list evolution of millions of users of the Skype communication network. We find that egocentric networks evolve heterogeneously in time as events of edge additions and deletions of individuals are grouped in long bursty clusters, which are separated by long inactive periods. We classify users by their link creation dynamics and show that bursty peaks of contact additions are likely to appear shortly after user account creation. We also study possible relations between bursty contact addition activity and other user-initiated actions like free and paid service adoption events. We show that bursts of contact additions are associated with increases in activity and adoption - an observation that can inform the design of targeted marketing tactics.Comment: 7 pages, 6 figures. Social Network Analysis and Mining (2013

Spatiotemporal correlations of handset-based service usages

We study spatiotemporal correlations and temporal diversities of handset-based service usages by analyzing a dataset that includes detailed information about locations and service usages of 124 users over 16 months. By constructing the spatiotemporal trajectories of the users we detect several meaningful places or contexts for each one of them and show how the context affects the service usage patterns. We find that temporal patterns of service usages are bound to the typical weekly cycles of humans, yet they show maximal activities at different times. We first discuss their temporal correlations and then investigate the time-ordering behavior of communication services like calls being followed by the non-communication services like applications. We also find that the behavioral overlap network based on the clustering of temporal patterns is comparable to the communication network of users. Our approach provides a useful framework for handset-based data analysis and helps us to understand the complexities of information and communications technology enabled human behavior.Comment: 11 pages, 15 figure

Three-Dimensional cryoEM Reconstruction of Native LDL Particles to 16 angstrom Resolution at Physiological Body Temperature

Background Low-density lipoprotein (LDL) particles, the major carriers of cholesterol in the human circulation, have a key role in cholesterol physiology and in the development of atherosclerosis. The most prominent structural components in LDL are the core-forming cholesteryl esters (CE) and the particle-encircling single copy of a huge, non-exchangeable protein, the apolipoprotein B-100 (apoB-100). The shape of native LDL particles and the conformation of native apoB-100 on the particles remain incompletely characterized at the physiological human body temperature (37°C). Methodology/Principal Findings To study native LDL particles, we applied cryo-electron microscopy to calculate 3D reconstructions of LDL particles in their hydrated state. Images of the particles vitrified at 6°C and 37°C resulted in reconstructions at ~16 Å resolution at both temperatures. 3D variance map analysis revealed rigid and flexible domains of lipids and apoB-100 at both temperatures. The reconstructions showed less variability at 6°C than at 37°C, which reflected increased order of the core CE molecules, rather than decreased mobility of the apoB-100. Compact molecular packing of the core and order in a lipid-binding domain of apoB-100 were observed at 6°C, but not at 37°C. At 37°C we were able to highlight features in the LDL particles that are not clearly separable in 3D maps at 6°C. Segmentation of apoB-100 density, fitting of lipovitellin X-ray structure, and antibody mapping, jointly revealed the approximate locations of the individual domains of apoB-100 on the surface of native LDL particles. Conclusions/Significance Our study provides molecular background for further understanding of the link between structure and function of native LDL particles at physiological body temperature.Peer reviewe

Human mast cell neutral proteases generate modified LDL particles with increased proteoglycan binding

Background and aims: Subendothelial interaction of LDL with extracellular matrix drives atherogenesis. This interaction can be strengthened by proteolytic modification of LDL. Mast cells (MCs) are present in atherosclerotic lesions, and upon activation, they degranulate and release a variety of neutral proteases. Here we studied the ability of MC proteases to cleave apoB-100 of LDL and affect the binding of LDL to proteoglycans. Methods: Mature human MCs were differentiated from human peripheral blood-derived CD34(+) progenitors in vitro and activated with calcium ionophore to generate MC-conditioned medium. LDL was incubated in the MC-conditioned medium or with individual MC proteases, and the binding of native and modified LDL to isolated human aortic proteoglycans or to human atherosclerotic plaques ex vivo was determined. MC proteases in atherosclerotic human coronary artery lesions were detected by immunofluorescence and qPCR. Results: Activated human MCs released the neutral proteases tryptase, chymase, carboxypeptidase A3, cathepsin G, and granzyme B. Of these, cathepsin G degraded most efficiently apoB-100, induced LDL fusion, and enhanced binding of LDL to isolated human aortic proteoglycans and human atherosclerotic lesions ex vivo. Double immunofluoresence staining of human atherosclerotic coronary arteries for tryptase and cathepsin G indicated that lesional MCs contain cathepsin G. In the lesions, expression of cathepsin G correlated with the expression of tryptase and chymase, but not with that of neutrophil proteinase 3. Conclusions: The present study suggests that cathepsin G in human atherosclerotic lesions is largely derived from MCs and that activated MCs may contribute to atherogenesis by enhancing LDL retention. (C) 2018 Elsevier B.V. All rights reserved.Peer reviewe