scholarly journals The fractal nature of nature: power laws, ecological complexity and biodiversity

2002 ◽  
Vol 357 (1421) ◽  
pp. 619-626 ◽  
Author(s):  
James H. Brown ◽  
Vijay K. Gupta ◽  
Bai-Lian Li ◽  
Bruce T. Milne ◽  
Carla Restrepo ◽  
...  
Keyword(s):  
Power Laws ◽  
Biological Processes ◽  
Fractal Nature ◽  
Future Prospects ◽  
Wide Range ◽  
Ecological Complexity ◽  
Self Similar ◽  
Underlying Mechanisms ◽  
Diversity Of Life ◽  
Fundamental Physical

Underlying the diversity of life and the complexity of ecology is order that reflects the operation of fundamental physical and biological processes. Power laws describe empirical scaling relationships that are emergent quantitative features of biodiversity. These features are patterns of structure or dynamics that are self–similar or fractal–like over many orders of magnitude. Power laws allow extrapolation and prediction over a wide range of scales. Some appear to be universal, occurring in virtually all taxa of organisms and types of environments. They offer clues to underlying mechanisms that powerfully constrain biodiversity. We describe recent progress and future prospects for understanding the mechanisms that generate these power laws, and for explaining the diversity of species and complexity of ecosystems in terms of fundamental principles of physical and biological science.

scholarly journals The Anticancer Effects of Paeoniflorin and Its Underlying Mechanisms

2019 ◽  
Vol 14 (9) ◽  
pp. 1934578X1987640
Author(s):  
Li-Juan Deng ◽  
Yu-He Lei ◽  
Tsz-Fung Chiu ◽  
Ming Qi ◽  
Hua Gan ◽  
...  
Keyword(s):  
Recent Progress ◽  
Antitumor Effect ◽  
Molecular Mechanisms ◽  
Experimental Studies ◽  
Future Prospects ◽  
Anticancer Effects ◽  
Wide Range ◽  
Underlying Mechanisms

Paeoniflorin (PF) is an important pharmacological component of some Chinese traditional herbal formulas, such as Bai Shao, Chi Shao, and Dan Pi, which have been clinically used for centuries. Although many experimental studies have explored a wide range of pharmacological properties of PF, including anticancer, anti-inflammatory, antioxidant, immunoregulatory, and prevention of insulin resistance, there is no review to describe these reported effects systematically, especially the antitumor effect and the underlying mechanisms. In this review, we summarize the recent progress on the anticancer profiles both in vitro and in vivo of PF. Moreover, we highlight the integrated molecular mechanisms of PF and contemplate its future prospects as a potential anticancer drug.

scholarly journals Self-similar synchronization of calcium and membrane potential transitions during AP cycles predict HR across species

2020 ◽  
Author(s):  
Syevda Tagirova Sirenko ◽  
Kenta Tsutsui ◽  
Kirill Tarasov ◽  
Dongmei Yang ◽  
Ashley N Wirth ◽  
...  
Keyword(s):  
Heart Rate ◽  
Animal Models ◽  
Animal Studies ◽  
Power Laws ◽  
Single Species ◽  
Cellular Mechanisms ◽  
Wide Range ◽  
Self Similar

AbstractBackgroundTranslation of knowledge of sinoatrial nodal “SAN” automaticity gleaned from animal studies to human dysrhythmias, e.g. “Sick Sinus” Syndrome (SSS) requiring electronic pacemaker insertion has been sub-optimal, largely because heart rate (HR) varies widely across species.ObjectivesTo discover regulatory universal mechanisms of normal automaticity in SAN pacemaker cells that are self-similar across species.MethodSub-cellular Ca2+ releases, whole cell AP-induced Ca2+ transients and APs were recorded in isolated mouse, guinea-pig, rabbit and human SAN cells. Parametric Ca2+ and Vm Kinetic Transitions (PCVKT) during phases of AP cycles from their ignition to recovery were quantified.ResultsAlthough both action potential cycle lengths (APCL) and PCVKT during AP cycles differed across species by ten-fold, trans-species scaling of PCVKT during AP cycles and scaling, of PCVKT to APCL in cells in vitro, EKG RR intervals in vivo, and BM were self-similar (obeyed power laws) across species. Thus, APCL in vitro, HR in vivo, and BM of any species can be predicted by PCVKT during AP cycles in SAN cells measured in any single species in vitro.ConclusionsIn designing optimal HR to match widely different BM and energy requirements from mice to humans, nature did not “reinvent pacemaker cell wheels”, but differentially scaled kinetics of gears that regulate the rates at which the “wheels spin”. This discovery will facilitate the development of novel pharmalogic therapies and biologic pacemakers featuring a normal, wide-range rate regulation in animal models and the translation of these to humans to target recalcitrant human SSS.Condensed AbstractStudies in animal models are an important facet of cardiac arrhythmia research. Because HR differs by over ten-fold between some animals and humans, translation of knowledge about regulatory mechanisms of SAN normal automaticity gleaned from studies in animal models to target human SSS has been sub-optimal. Our findings demonstrating that trans-species self-similarity of sub-cellular and cellular mechanisms that couple Ca2+ to Vm during AP cycles can predict heart rate in vivo from mice to humans will inform on the design of novel studies in animal models and facilitate translation of this knowledge to target human disease.

scholarly journals Energetics of mesoscale cell turbulence in two-dimensional monolayers

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Shao-Zhen Lin ◽  
Wu-Yang Zhang ◽  
Dapeng Bi ◽  
Bo Li ◽  
Xi-Qiao Feng
Keyword(s):  
Kinetic Energy ◽  
Tumor Metastasis ◽  
Cell Types ◽  
Boltzmann Distribution ◽  
Scaling Exponent ◽  
Biological Processes ◽  
Two Dimensional ◽  
Cell Monolayers ◽  
Wide Range ◽  
Epithelial Cell Monolayers

AbstractInvestigation of energy mechanisms at the collective cell scale is a challenge for understanding various biological processes, such as embryonic development and tumor metastasis. Here we investigate the energetics of self-sustained mesoscale turbulence in confluent two-dimensional (2D) cell monolayers. We find that the kinetic energy and enstrophy of collective cell flows in both epithelial and non-epithelial cell monolayers collapse to a family of probability density functions, which follow the q-Gaussian distribution rather than the Maxwell–Boltzmann distribution. The enstrophy scales linearly with the kinetic energy as the monolayer matures. The energy spectra exhibit a power-decaying law at large wavenumbers, with a scaling exponent markedly different from that in the classical 2D Kolmogorov–Kraichnan turbulence. These energetic features are demonstrated to be common for all cell types on various substrates with a wide range of stiffness. This study provides unique clues to understand active natures of cell population and tissues.

scholarly journals Parasites—the new frontier: celebrating Darwin 200

2009 ◽  
Vol 5 (5) ◽  
pp. 625-627 ◽  
Author(s):  
Paul Schmid-Hempel
Keyword(s):  
Population Biology ◽  
Life Histories ◽  
Evolutionary Ecology ◽  
Adaptive Value ◽  
Wide Range ◽  
New Frontier ◽  
Underlying Mechanisms ◽  
The One ◽  
Immune Defences ◽  
Recurrent Theme

To Darwin, parasites were fascinating examples of adaptation but their significance as selective factors for a wide range of phenomena has only been studied in depth over the last few decades. This work has had its roots in behavioural/evolutionary ecology on the one hand, and in population biology/ecology on the other, thus shaping a new comprehensive field of ‘evolutionary parasitology’. Taking parasites into account has been a success story and has shed new light on several old questions such as sexual selection, the evolution of sex and recombination, changes in behaviour, adaptive life histories, and so forth. In the process, the topic of ecological immunology has emerged, which analyses immune defences in a framework of costs and benefits. Throughout, a recurrent theme is how to appropriately integrate the underlying mechanisms as evolved boundary conditions into a framework of studying the adaptive value of traits. On the conceptual side, major questions remain and await further study.

scholarly journals Universal void density profiles from simulation and SDSS

2014 ◽  
Vol 11 (S308) ◽  
pp. 542-545 ◽  
Author(s):  
S. Nadathur ◽  
S. Hotchkiss ◽  
J. M. Diego ◽  
I. T. Iliev ◽  
S. Gottlöber ◽  
...  
Keyword(s):  
Fundamental Property ◽  
Watershed Algorithm ◽  
Void Size ◽  
Self Similarity ◽  
Density Profiles ◽  
Watershed Transform ◽  
Future Studies ◽  
Main Galaxy ◽  
Wide Range ◽  
Self Similar

AbstractWe discuss the universality and self-similarity of void density profiles, for voids in realistic mock luminous red galaxy (LRG) catalogues from the Jubilee simulation, as well as in void catalogues constructed from the SDSS LRG and Main Galaxy samples. Voids are identified using a modified version of the ZOBOV watershed transform algorithm, with additional selection cuts. We find that voids in simulation areself-similar, meaning that their average rescaled profile does not depend on the void size, or – within the range of the simulated catalogue – on the redshift. Comparison of the profiles obtained from simulated and real voids shows an excellent match. The profiles of real voids also show auniversalbehaviour over a wide range of galaxy luminosities, number densities and redshifts. This points to a fundamental property of the voids found by the watershed algorithm, which can be exploited in future studies of voids.

scholarly journals A lognormal distribution of the lengths of terminal twigs on self-similar branches of elm trees

2017 ◽  
Vol 284 (1846) ◽  
pp. 20162395 ◽  
Author(s):  
Kohei Koyama ◽  
Ken Yamamoto ◽  
Masayuki Ushio
Keyword(s):  
Lognormal Distribution ◽  
Species Abundance ◽  
Self Similarity ◽  
Lognormal Distributions ◽  
Multiplicative Effect ◽  
Wide Range ◽  
Error Distributions ◽  
Species Abundance Distributions ◽  
Self Similar ◽  
Ulmus Davidiana

Lognormal distributions and self-similarity are characteristics associated with a wide range of biological systems. The sequential breakage model has established a link between lognormal distributions and self-similarity and has been used to explain species abundance distributions. To date, however, there has been no similar evidence in studies of multicellular organismal forms. We tested the hypotheses that the distribution of the lengths of terminal stems of Japanese elm trees ( Ulmus davidiana ), the end products of a self-similar branching process, approaches a lognormal distribution. We measured the length of the stem segments of three elm branches and obtained the following results: (i) each occurrence of branching caused variations or errors in the lengths of the child stems relative to their parent stems; (ii) the branches showed statistical self-similarity; the observed error distributions were similar at all scales within each branch and (iii) the multiplicative effect of these errors generated variations of the lengths of terminal twigs that were well approximated by a lognormal distribution, although some statistically significant deviations from strict lognormality were observed for one branch. Our results provide the first empirical evidence that statistical self-similarity of an organismal form generates a lognormal distribution of organ sizes.

scholarly journals Reversing resistance: different routes and common themes across pathogens

2017 ◽  
Vol 284 (1863) ◽  
pp. 20171619 ◽  
Author(s):  
Richard C. Allen ◽  
Jan Engelstädter ◽  
Sebastian Bonhoeffer ◽  
Bruce A. McDonald ◽  
Alex R. Hall
Keyword(s):  
Fitness Cost ◽  
Biological Processes ◽  
Short Supply ◽  
Compensatory Evolution ◽  
Wide Range ◽  
Different Types ◽  
Cost Of Resistance

Resistance spreads rapidly in pathogen or pest populations exposed to biocides, such as fungicides and antibiotics, and in many cases new biocides are in short supply. How can resistance be reversed in order to prolong the effectiveness of available treatments? Some key parameters affecting reversion of resistance are well known, such as the fitness cost of resistance. However, the population biological processes that actually cause resistance to persist or decline remain poorly characterized, and consequently our ability to manage reversion of resistance is limited. Where do susceptible genotypes that replace resistant lineages come from? What is the epidemiological scale of reversion? What information do we need to predict the mechanisms or likelihood of reversion? Here, we define some of the population biological processes that can drive reversion, using examples from a wide range of taxa and biocides. These processes differ primarily in the origin of revertant genotypes, but also in their sensitivity to factors such as coselection and compensatory evolution that can alter the rate of reversion, and the likelihood that resistance will re-emerge upon re-exposure to biocides. We therefore argue that discriminating among different types of reversion allows for better prediction of where resistance is most likely to persist.

scholarly journals A Review on Additive Manufacturing of Micromixing Devices

Micromachines ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 73
Author(s):  
Marina Garcia-Cardosa ◽  
Francisco-Javier Granados-Ortiz ◽  
Joaquín Ortega-Casanova
Keyword(s):  
Life Cycle ◽  
Additive Manufacturing ◽  
High Performance ◽  
Future Prospects ◽  
High Quality ◽  
Printing Technology ◽  
Wide Range ◽  
The Moment ◽  
Manufacturing Technologies

In recent years, additive manufacturing has gained importance in a wide range of research applications such as medicine, biotechnology, engineering, etc. It has become one of the most innovative and high-performance manufacturing technologies of the moment. This review aims to show and discuss the characteristics of different existing additive manufacturing technologies for the construction of micromixers, which are devices used to mix two or more fluids at microscale. The present manuscript discusses all the choices to be made throughout the printing life cycle of a micromixer in order to achieve a high-quality microdevice. Resolution, precision, materials, and price, amongst other relevant characteristics, are discussed and reviewed in detail for each printing technology. Key information, suggestions, and future prospects are provided for manufacturing of micromixing machines based on the results from this review.

scholarly journals The RhoA-ROCK pathway in the regulation of T and B cell responses

F1000Research ◽  
2016 ◽  
Vol 5 ◽  
pp. 2295 ◽  
Author(s):  
Edd Ricker ◽  
Luvana Chowdhury ◽  
Woelsung Yi ◽  
Alessandra B. Pernis
Keyword(s):  
Immune Responses ◽  
Biological Processes ◽  
Dynamic Interactions ◽  
Cell Responses ◽  
Important Mediator ◽  
Downstream Effectors ◽  
Wide Range ◽  
Response To Stress ◽  
The Impact ◽  
Rho Kinases

Effective immune responses require the precise regulation of dynamic interactions between hematopoietic and non-hematopoietic cells. The Rho subfamily of GTPases, which includes RhoA, is rapidly activated downstream of a diverse array of biochemical and biomechanical signals, and is emerging as an important mediator of this cross-talk. Key downstream effectors of RhoA are the Rho kinases, or ROCKs. The ROCKs are two serine-threonine kinases that can act as global coordinators of a tissue’s response to stress and injury because of their ability to regulate a wide range of biological processes. Although the RhoA-ROCK pathway has been extensively investigated in the non-hematopoietic compartment, its role in the immune system is just now becoming appreciated. In this commentary, we provide a brief overview of recent findings that highlight the contribution of this pathway to lymphocyte development and activation, and the impact that dysregulation in the activation of RhoA and/or the ROCKs may exert on a growing list of autoimmune and lymphoproliferative disorders.

scholarly journals Deep6mA: A deep learning framework for exploring similar patterns in DNA N6-methyladenine sites across different species

2021 ◽  
Vol 17 (2) ◽  
pp. e1008767
Author(s):  
Zutan Li ◽  
Hangjin Jiang ◽  
Lingpeng Kong ◽  
Yuanyuan Chen ◽  
Kun Lang ◽  
...  
Keyword(s):  
Deep Learning ◽  
Prediction Accuracy ◽  
Cross Validation ◽  
Biological Processes ◽  
Biological Functions ◽  
Learning Framework ◽  
Wide Range ◽  
Genomic Scale ◽  
Downstream Gene Expression ◽  
Fold Cross Validation

N6-methyladenine (6mA) is an important DNA modification form associated with a wide range of biological processes. Identifying accurately 6mA sites on a genomic scale is crucial for under-standing of 6mA’s biological functions. However, the existing experimental techniques for detecting 6mA sites are cost-ineffective, which implies the great need of developing new computational methods for this problem. In this paper, we developed, without requiring any prior knowledge of 6mA and manually crafted sequence features, a deep learning framework named Deep6mA to identify DNA 6mA sites, and its performance is superior to other DNA 6mA prediction tools. Specifically, the 5-fold cross-validation on a benchmark dataset of rice gives the sensitivity and specificity of Deep6mA as 92.96% and 95.06%, respectively, and the overall prediction accuracy is 94%. Importantly, we find that the sequences with 6mA sites share similar patterns across different species. The model trained with rice data predicts well the 6mA sites of other three species: Arabidopsis thaliana, Fragaria vesca and Rosa chinensis with a prediction accuracy over 90%. In addition, we find that (1) 6mA tends to occur at GAGG motifs, which means the sequence near the 6mA site may be conservative; (2) 6mA is enriched in the TATA box of the promoter, which may be the main source of its regulating downstream gene expression.

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