Biologically-informed neural networks guide mechanistic modeling from sparse experimental data

Biologically-informed neural networks (BINNs), an extension of physics-informed neural networks [1], are introduced and used to discover the underlying dynamics of biological systems from sparse experimental data. In the present work, BINNs are trained in a supervised learning framework to approximate in vitro cell biology assay experiments while respecting a generalized form of the governing reaction-diffusion partial differential equation (PDE). By allowing the diffusion and reaction terms to be multilayer perceptrons (MLPs), the nonlinear forms of these terms can be learned while simultaneously converging to the solution of the governing PDE. Further, the trained MLPs are used to guide the selection of biologically interpretable mechanistic forms of the PDE terms which provides new insights into the biological and physical mechanisms that govern the dynamics of the observed system. The method is evaluated on sparse real-world data from wound healing assays with varying initial cell densities [2]

Learning differential equation models from stochastic agent-based model simulations

Agent-based models provide a flexible framework that is frequently used for modelling many biological systems, including cell migration, molecular dynamics, ecology, and epidemiology. Analysis of the model dynamics can be challenging due to their inherent stochasticity and heavy computational requirements. Common approaches to the analysis of agent-based models include extensive Monte Carlo simulation of the model or the derivation of coarse-grained differential equation models to predict the expected or averaged output from the agent-based model. Both of these approaches have limitations, however, as extensive computation of complex agent-based models may be infeasible, and coarse-grained differential equation models can fail to accurately describe model dynamics in certain parameter regimes. We propose that methods from the equation learning field provide a promising, novel, and unifying approach for agent-based model analysis. Equation learning is a recent field of research from data science that aims to infer differential equation models directly from data. We use this tutorial to review how methods from equation learning can be used to learn differential equation models from agent-based model simulations. We demonstrate that this framework is easy to use, requires few model simulations, and accurately predicts model dynamics in parameter regions where coarse-grained differential equation models fail to do so. We highlight these advantages through several case studies involving two agent-based models that are broadly applicable to biological phenomena: a birth-death-migration model commonly used to explore cell biology experiments and a susceptible-infected-recovered model of infectious disease spread

Analyzing Collective Motion with Machine Learning and Topology

We use topological data analysis and machine learning to study a seminal model of collective motion in biology [D'Orsogna et al., Phys. Rev. Lett. 96 (2006)]. This model describes agents interacting nonlinearly via attractive-repulsive social forces and gives rise to collective behaviors such as flocking and milling. To classify the emergent collective motion in a large library of numerical simulations and to recover model parameters from the simulation data, we apply machine learning techniques to two different types of input. First, we input time series of order parameters traditionally used in studies of collective motion. Second, we input measures based in topology that summarize the time-varying persistent homology of simulation data over multiple scales. This topological approach does not require prior knowledge of the expected patterns. For both unsupervised and supervised machine learning methods, the topological approach outperforms the one that is based on traditional order parameters.Comment: Published in Chaos 29, 123125 (2019), DOI: 10.1063/1.512549

Discovery of directional and nondirectional pioneer transcription factors by modeling DNase profile magnitude and shape

We describe protein interaction quantitation (PIQ), a computational method for modeling the magnitude and shape of genome-wide DNase I hypersensitivity profiles to identify transcription factor (TF) binding sites. Through the use of machine-learning techniques, PIQ identified binding sites for >700 TFs from one DNase I hypersensitivity analysis followed by sequencing (DNase-seq) experiment with accuracy comparable to that of chromatin immunoprecipitation followed by sequencing (ChIP-seq). We applied PIQ to analyze DNase-seq data from mouse embryonic stem cells differentiating into prepancreatic and intestinal endoderm. We identified 120 and experimentally validated eight 'pioneer' TF families that dynamically open chromatin. Four pioneer TF families only opened chromatin in one direction from their motifs. Furthermore, we identified 'settler' TFs whose genomic binding is principally governed by proximity to open chromatin. Our results support a model of hierarchical TF binding in which directional and nondirectional pioneer activity shapes the chromatin landscape for population by settler TFs.National Institutes of Health (U.S.) (Common Fund 5UL1DE019581)National Institutes of Health (U.S.) (Common Fund RL1DE019021)National Institutes of Health (U.S.) (Common Fund 5TL1EB008540)National Institutes of Health (U.S.) (Grant 1U01HG007037)National Institutes of Health (U.S.) (Grant 5P01NS055923

Cosmological phase transitions in warped space: gravitational waves and collider signatures

We study the electroweak phase transition within a 5D warped model including a scalar potential with an exponential behavior, and strong back-reaction over the metric, in the infrared. By means of a novel treatment of the superpotential formalism, we explore parameter regions that were previously inaccessible. We nd that for large enough values of the t'Hooft parameter (e.g. N = 25) the holographic phase transition occurs, and it can force the Higgs to undergo a rst order electroweak phase transition, suitable for electroweak baryogenesis. The model exhibits gravitational waves and colliders signatures. It typically predicts a stochastic gravitational wave background observable both at the Laser Interferometer Space Antenna and at the Einstein Telescope. Moreover the radion tends to be heavy enough such that it evades current constraints, but may show up in future LHC runs.The work of EM is supported by the Spanish MINEICO under Grant FPA2015-64041-C2-1-P and FIS2017-85053-C2-1-P, by the Junta de Andaluc a under Grant FQM-225, by the Basque Government under Grant IT979-16, and by the Spanish Consolider Ingenio 2010 Programme CPAN (CSD2007-00042). The research of EM is also supported by the Ram on y Cajal Program of the Spanish MINEICO, and by the Universidad del Pa s Vasco UPV/EHU, Bilbao, Spain, as a Visiting Professor. GN is supported by the Swiss National Science Foundation (SNF) under grant 200020-168988. The work of MQ is partly supported by Spanish MINEICO under Grant CICYT-FEDER-FPA2014- 55613-P and FPA2017-88915-P, by the Severo Ochoa Excellence Program of MINEICO under Grant SEV-2016-0588, and by CNPq PVE fellowship project 405559/2013-5

Use of tobacco and alcohol by Swiss primary care physicians: a cross-sectional survey

BACKGROUND: Health behaviours among doctors has been suggested to be an important marker of how harmful lifestyle behaviours are perceived. In several countries, decrease in smoking among physicians was spectacular, indicating that the hazard was well known. Historical data have shown that because of their higher socio-economical status physicians take up smoking earlier. When the dangers of smoking become better known, physicians began to give up smoking at a higher rate than the general population. For alcohol consumption, the situation is quite different: prevalence is still very high among physicians and the dangers are not so well perceived. To study the situation in Switzerland, data of a national survey were analysed to determine the prevalence of smoking and alcohol drinking among primary care physicians. METHODS: 2'756 randomly selected practitioners were surveyed to assess subjective mental and physical health and their determinants, including smoking and drinking behaviours. Physicians were categorised as never smokers, current smokers and former smokers, as well as non drinkers, drinkers (AUDIT-C < 4 for women and < 5 for men) and at risk drinkers (higher scores). RESULTS: 1'784 physicians (65%) responded (men 84%, mean age 51 years). Twelve percent were current smokers and 22% former smokers. Sixty six percent were drinkers and 30% at risk drinkers. Only 4% were never smokers and non drinkers. Forty eight percent of current smokers were also at risk drinkers and 16% of at risk drinkers were also current smokers. Smoking and at risk drinking were more frequent among men, middle aged physicians and physicians living alone. When compared to a random sample of the Swiss population, primary care physicians were two to three times less likely to be active smokers (12% vs. 30%), but were more likely to be drinkers (96% vs. 78%), and twice more likely to be at risk drinkers (30% vs. 15%). CONCLUSION: The prevalence of current smokers among Swiss primary care physicians was much lower than in the general population in Switzerland, reflecting that the hazards of smoking are well known to doctors. However, the opposite was found for alcohol use, underlining the importance of making efforts in this area to increase awareness among physicians of the dangers of alcohol consumption

Laser Interferometer Space Antenna

Following the selection of The Gravitational Universe by ESA, and the successful flight of LISA Pathfinder, the LISA Consortium now proposes a 4 year mission in response to ESA's call for missions for L3. The observatory will be based on three arms with six active laser links, between three identical spacecraft in a triangular formation separated by 2.5 million km. LISA is an all-sky monitor and will offer a wide view of a dynamic cosmos using Gravitational Waves as new and unique messengers to unveil The Gravitational Universe. It provides the closest ever view of the infant Universe at TeV energy scales, has known sources in the form of verification binaries in the Milky Way, and can probe the entire Universe, from its smallest scales near the horizons of black holes, all the way to cosmological scales. The LISA mission will scan the entire sky as it follows behind the Earth in its orbit, obtaining both polarisations of the Gravitational Waves simultaneously, and will measure source parameters with astrophysically relevant sensitivity in a band from below $10^{-4}\,$Hz to above $10^{-1}\,$Hz.Comment: Submitted to ESA on January 13th in response to the call for missions for the L3 slot in the Cosmic Vision Programm

An international review of tobacco smoking in the medical profession: 1974–2004

Background\ud Tobacco smoking by physicians represents a contentious issue in public health, and regardless of what country it originates from, the need for accurate, historical data is paramount. As such, this article provides an international comparison of all modern literature describing the tobacco smoking habits of contemporary physicians.\ud \ud Methods\ud A keyword search of appropriate MeSH terms was initially undertaken to identify relevant material, after which the reference lists of manuscripts were also examined to locate further publications.\ud \ud Results\ud A total of 81 English-language studies published in the past 30 years met the inclusion criteria. Two distinct trends were evident. Firstly, most developed countries have shown a steady decline in physicians' smoking rates during recent years. On the other hand, physicians in some developed countries and newly-developing regions still appear to be smoking at high rates. The lowest smoking prevalence rates were consistently documented in the United States, Australia and the United Kingdom. Comparison with other health professionals suggests that fewer physicians smoke when compared to nurses, and sometimes less often than dentists.\ud \ud Conclusion\ud Overall, this review suggests that while physicians' smoking habits appear to vary from region to region, they are not uniformly low when viewed from an international perspective. It is important that smoking in the medical profession declines in future years, so that physicians can remain at the forefront of anti-smoking programs and lead the way as public health exemplars in the 21st century