Simple molecules as complex systems.
Ontology highlight
ABSTRACT:
SUBMITTER: Furtenbacher T
PROVIDER: S-EPMC3983599 | biostudies-other | 2014
REPOSITORIES: biostudies-other
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Project description:Over the past three decades, carbon nanotubes and fullerenes have become remarkable objects for starting the implementation of new models and technologies in different branches of science. To a great extent, this is defined by the unique electronic and spatial properties of nanocavities due to the ramified ?-electron systems. This provides an opportunity for the formation of endohedral complexes containing non-covalently bonded atoms or molecules inside fullerenes and nanotubes. The guest species are exposed to the force field of the nanocavity, which can be described as a combination of electronic and steric requirements. Its action significantly changes conformational properties of even relatively simple molecules, including ethane and its analogs, as well as compounds with C-O, C-S, B-B, B-O, B-N, N-N, Al-Al, Si-Si and Ge-Ge bonds. Besides that, the cavity of the host molecule dramatically alters the stereochemical characteristics of cyclic and heterocyclic systems, affects the energy of pyramidal nitrogen inversion in amines, changes the relative stability of cis and trans isomers and, in the case of chiral nanotubes, strongly influences the properties of R- and S- enantiomers. The present review aims at primary compilation of such unusual stereochemical effects and initial evaluation of the nature of the force field inside nanotubes and fullerenes.
| S-EPMC7287839 | biostudies-literature
Project description:BackgroundEnsuring patients benefit from the latest medical and technical advances remains a major challenge, with rational-linear and reductionist approaches to translating evidence into practice proving inefficient and ineffective. Complexity thinking, which emphasises interconnectedness and unpredictability, offers insights to inform evidence translation theories and strategies. Drawing on detailed insights into complex micro-systems, this research aimed to advance empirical and theoretical understanding of the reality of making and sustaining improvements in complex healthcare systems.MethodsUsing analytical auto-ethnography, including documentary analysis and literature review, we assimilated learning from 5 years of observation of 22 evidence translation projects (UK). We used a grounded theory approach to develop substantive theory and a conceptual framework. Results were interpreted using complexity theory and 'simple rules' were identified reflecting the practical strategies that enhanced project progress.ResultsThe framework for Successful Healthcare Improvement From Translating Evidence in complex systems (SHIFT-Evidence) positions the challenge of evidence translation within the dynamic context of the health system. SHIFT-Evidence is summarised by three strategic principles, namely (1) 'act scientifically and pragmatically' - knowledge of existing evidence needs to be combined with knowledge of the unique initial conditions of a system, and interventions need to adapt as the complex system responds and learning emerges about unpredictable effects; (2) 'embrace complexity' - evidence-based interventions only work if related practices and processes of care within the complex system are functional, and evidence-translation efforts need to identify and address any problems with usual care, recognising that this typically includes a range of interdependent parts of the system; and (3) 'engage and empower' - evidence translation and system navigation requires commitment and insights from staff and patients with experience of the local system, and changes need to align with their motivations and concerns. Twelve associated 'simple rules' are presented to provide actionable guidance to support evidence translation and improvement in complex systems.ConclusionBy recognising how agency, interconnectedness and unpredictability influences evidence translation in complex systems, SHIFT-Evidence provides a tool to guide practice and research. The 'simple rules' have potential to provide a common platform for academics, practitioners, patients and policymakers to collaborate when intervening to achieve improvements in healthcare.
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Project description:Simple temporal models that ignore the spatial nature of interactions and track only changes in mean quantities, such as global densities, are typically used under the unrealistic assumption that individuals are well mixed. These so-called mean-field models are often considered overly simplified, given the ample evidence for distributed interactions and spatial heterogeneity over broad ranges of scales. Here, we present one reason why such simple population models may work even when mass-action assumptions do not hold: spatial structure is present but it relates to global densities in a special way. With an individual-based predator-prey model that is spatial and stochastic, and whose mean-field counterpart is the classic Lotka-Volterra model, we show that the global densities and densities of pairs (or spatial covariances) establish a bi-power law at the stationary state and also in their transient approach to this state. This relationship implies that the dynamics of global densities can be written simply as a function of those densities alone without invoking pairs (or higher order moments). The exponents of the bi-power law for the predation rate exhibit a remarkable robustness to changes in model parameters. Evidence is presented for a connection of our findings to the existence of a critical phase transition in the dynamics of the spatial system. We discuss the application of similar modified mean-field equations to other ecological systems for which similar transitions have been described, both in models and empirical data.Electronic supplementary material The online version of this article (doi:10.1007/s12080-011-0116-2) contains supplementary material, which is available to authorized users.
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Project description:BackgroundPhysiologic signals, such as cardiac interbeat intervals, exhibit complex fluctuations. However, capturing important dynamical properties, including nonstationarities may not be feasible from conventional time series graphical representations.MethodsWe introduce a simple-to-implement visualisation method, termed dynamical density delay mapping ("D3-Map" technique) that provides an animated representation of a system's dynamics. The method is based on a generalization of conventional two-dimensional (2D) Poincaré plots, which are scatter plots where each data point, x(n), in a time series is plotted against the adjacent one, x(n?+?1). First, we divide the original time series, x(n) (n?=?1,…, N), into a sequence of segments (windows). Next, for each segment, a three-dimensional (3D) Poincaré surface plot of x(n), x(n?+?1), h[x(n),x(n?+?1)] is generated, in which the third dimension, h, represents the relative frequency of occurrence of each (x(n),x(n?+?1)) point. This 3D Poincaré surface is then chromatised by mapping the relative frequency h values onto a colour scheme. We also generate a colourised 2D contour plot from each time series segment using the same colourmap scheme as for the 3D Poincaré surface. Finally, the original time series graph, the colourised 3D Poincaré surface plot, and its projection as a colourised 2D contour map for each segment, are animated to create the full "D3-Map."ResultsWe first exemplify the D3-Map method using the cardiac interbeat interval time series from a healthy subject during sleeping hours. The animations uncover complex dynamical changes, such as transitions between states, and the relative amount of time the system spends in each state. We also illustrate the utility of the method in detecting hidden temporal patterns in the heart rate dynamics of a patient with atrial fibrillation. The videos, as well as the source code, are made publicly available.ConclusionsAnimations based on density delay maps provide a new way of visualising dynamical properties of complex systems not apparent in time series graphs or standard Poincaré plot representations. Trainees in a variety of fields may find the animations useful as illustrations of fundamental but challenging concepts, such as nonstationarity and multistability. For investigators, the method may facilitate data exploration.
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Project description:The potential of genomic DNA is realized when new modalities are invented that manipulate large DNAs with minimal breakage or loss of sample. Here, we describe a polydimethylsiloxane-polycarbonate membrane device to remove small molecules from a sample while retaining large DNAs. Dialysis rates dramatically change as DNA size in kb (M) increases and DNA dimensions become comparable to pore size, and chain characteristics go from rod-like to Gaussian. Consequently, we describe empirical rates of dialysis, R, as a function of M as falling into two regimes: DNAs ≤ 1 kb show R(M) ∼e - t/τ M (t = time, τM = time constant), while DNAs ≥1.65 kb slowly passage with R(M) ∼M -1.68; such partitioning potentiates single-molecule imaging.
| S-EPMC6494463 | biostudies-literature
Project description:BackgroundEvidence translation and improvement research indicate that healthcare contexts are complex systems, characterized by uncertainty and surprise, which often defy orchestrated intervention attempts. This article reflects on the implications of complexity on attempts to translate evidence, and on a newly published framework for Successful Healthcare Improvements From Translating Evidence in complex systems (SHIFT-Evidence).DiscussionSHIFT-Evidence positions the challenge of evidence translation within the complex and evolving context of healthcare, and recognizes the wider issues practitioners routinely face. It is empirically grounded, and designed to be comprehensive, practically relevant and actionable. SHIFT-evidence is summarized by three principles designed to be intuitive and memorable: 'act scientifically and pragmatically'; 'embrace complexity'; and 'engage and empower'. Common challenges and strategies to overcome them are summarized in 12 'simple rules' that provide actionable guidance.ConclusionSHIFT-Evidence provides a practical tool to guide practice and research of evidence translation and improvement within complex dynamic healthcare settings. Implications are that improvement initiatives and research study designs need to take into account the unique initial conditions in each local setting; conduct needs to respond to unpredictable effects and address dependent problems; and evaluation needs to be sensitive to evolving priorities and the emergent range of activities required to achieve improvement.
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