Effects of Dipyridamole on the Short-Term Evolution of Glomerulonephritis

Nephron ◽  
1991 ◽  
Vol 58 (1) ◽  
pp. 13-16 ◽  
Author(s):  
S. Camara ◽  
J.P. de la Cruz ◽  
M.A. Frutos ◽  
P. Sanchez ◽  
Lopez de Novales ◽  
...  
Keyword(s):  
Short Term ◽  
Term Evolution

SHORT-TERM EVOLUTION OF FLOW & MORPHOLOGY IN AN ERODIBLE MEANDERING CHANNEL WITH & WITHOUT GROYNES

2018 ◽  
Vol 74 (4) ◽  
pp. I_1147-I_1152
Author(s):  
Saroj KARKI ◽  
Yuji HASEGAWA ◽  
Masakazu HASHIMOTO ◽  
Hajime NAKAGAWA ◽  
Kenji KAWAIKE
Keyword(s):  
Short Term ◽  
Meandering Channel ◽  
Term Evolution ◽  
Flow Morphology

Physical modeling of the cross-shore short-term evolution of protected and unprotected beach nourishments

2010 ◽  
Vol 37 (8-9) ◽  
pp. 777-789 ◽  
Author(s):  
M. Di Risio ◽  
I. Lisi ◽  
G.M. Beltrami ◽  
P. De Girolamo
Keyword(s):  
Physical Modeling ◽  
Short Term ◽  
Term Evolution ◽  
The Cross

scholarly journals Agrichemicals boost the effects of antibiotics on antibiotic resistance evolution

2018 ◽  
Author(s):  
Brigitta Kurenbach ◽  
Amy M Hill ◽  
William Godsoe ◽  
Sophie van Hamelsveld ◽  
Jack A Heinemann
Keyword(s):  
Antibiotic Resistance ◽  
Acquired Resistance ◽  
Genotypic Diversity ◽  
Microbial Populations ◽  
Phenotypic Variance ◽  
Short Term ◽  
Resistance Evolution ◽  
Term Evolution ◽  
Comprehensive Test ◽  
Selection For

Antibiotic resistance is medicine’s climate change: caused by human activity, and resulting in more extreme outcomes. Resistance emerges in microbial populations when antibiotics act on phenotypic variance within the population. This can arise from either genotypic diversity (resulting from a mutation or horizontal gene transfer), or from ‘adaptive’ differences in gene expression due to environmental variation. Adaptive changes can increase fitness allowing bacteria to survive at higher concentrations of the antibiotic. They can also decrease fitness, potentially leading to selection for antibiotic resistance at lower concentrations. There are opportunities for other environmental stressors to promote antibiotic resistance in ways that are hard to predict using conventional assays. Exploiting our observation that commonly used herbicides can increase or decrease the minimum inhibitory concentration (MIC) of different antibiotics, we provide the first comprehensive test of the hypothesis that the rate of antibiotic resistance evolution under specified conditions can increase, regardless of whether a herbicide increases or decreases the antibiotic MIC. Short term evolution experiments were used for various herbicide and antibiotic combinations. We found conditions where acquired resistance arises more frequently regardless of whether the exogenous non-antibiotic agent increased or decreased antibiotic effectiveness. This “damned if you do/damned if you don’t” outcome suggests that the emergence of antibiotic resistance is exacerbated by additional environmental factors that influence competition between bacteria. Our work demonstrates that bacteria may acquire antibiotic resistance in the environment at rates substantially faster than predicted from laboratory conditions.

Growth phase-dependent UV-C resistance of Bacillus subtilis: data from a short-term evolution experiment

2011 ◽  
Vol 193 (11) ◽  
pp. 823-832 ◽  
Author(s):  
Marko Wassmann ◽  
Ralf Moeller ◽  
Günther Reitz ◽  
Petra Rettberg
Keyword(s):  
Bacillus Subtilis ◽  
Growth Phase ◽  
Short Term ◽  
Term Evolution ◽  
Evolution Experiment ◽  
Uv C

scholarly journals Modeling and Predicting the Short-Term Evolution of the Geomagnetic Field

2018 ◽  
Vol 123 (6) ◽  
pp. 4539-4560 ◽  
Author(s):  
Julien Bärenzung ◽  
Matthias Holschneider ◽  
Johannes Wicht ◽  
Sabrina Sanchez ◽  
Vincent Lesur
Keyword(s):  
Geomagnetic Field ◽  
Short Term ◽  
Term Evolution

scholarly journals Possible evolution of the circum-galactic medium around QSOs with QSO age and cosmic time revealed by Ly α haloes

2019 ◽  
Vol 488 (1) ◽  
pp. 120-134 ◽  
Author(s):  
Rieko Momose ◽  
Tomotsugu Goto ◽  
Yousuke Utsumi ◽  
Tetsuya Hashimoto ◽  
Chia-Ying Chiang ◽  
...  
Keyword(s):  
Growth Rate ◽  
Surface Brightness ◽  
Narrow Band ◽  
Cosmic Time ◽  
Black Hole Mass ◽  
Host Galaxies ◽  
Short Term ◽  
Term Evolution ◽  
Similar Growth ◽  
Lower Redshift

ABSTRACT We first present new Subaru narrow-band observations of the Ly α halo around the quasi-stellar object (QSO) CFHQ J232908−030158 at z = 6.42, which appears the most luminous and extended halo at z > 5 (LLy α = 9.8 × 1043 erg s−1 within 37 pkpc diameter). Then, combining these measurements with available data in the literature, we find two different evolutions of QSOs’ Ly α haloes. First is a possible short-term evolution with QSO age seen in four z > 6 QSOs. We find the anticorrelation between the Ly α halo scales with QSOs’ infrared (IR) luminosity, with J2329−0301’s halo being the brightest and largest. It indicates that ionizing photons escape more easily out to circum-galactic regions when host galaxies are less dusty. We also find a positive correlation between IR luminosity and black hole mass (MBH). Given MBH as an indicator of QSO age, we propose a hypothesis that a large Ly α halo mainly exists around QSOs in the young phase of their activity due to a small amount of dust. The second is an evolution with cosmic time seen over z ∼ 2–5. We find the increase of surface brightness towards lower redshift with a similar growth rate to that of dark matter haloes (DHs) that evolve to MDH = 1012–1013 M⊙ at z = 2. The extent of Ly α haloes is also found to increase at a rate scaling with the virial radius of growing DHs, $r_\text{vir} \propto M_\text{DH}^{1/3}(1+z)^{-1}$. These increases are consistent with a scenario that the circum-galactic medium around QSOs evolves in mass and size keeping pace with hosting DHs.

scholarly journals Spectral evolution of weakly nonlinear random waves: kinetic description versus direct numerical simulations

2018 ◽  
Vol 844 ◽  
pp. 766-795 ◽  
Author(s):  
Sergei Y. Annenkov ◽  
Victor I. Shrira
Keyword(s):  
Time Scale ◽  
Kinetic Equations ◽  
Wave Spectra ◽  
Kinetic Description ◽  
Spectral Evolution ◽  
Short Term ◽  
Weakly Nonlinear ◽  
Term Evolution ◽  
Integral Characteristics

Kinetic equations are widely used in many branches of science to describe the evolution of random wave spectra. To examine the validity of these equations, we study numerically the long-term evolution of water wave spectra without wind input using three different models. The first model is the classical kinetic (Hasselmann) equation (KE). The second model is the generalised kinetic equation (gKE), derived employing the same statistical closure as the KE but without the assumption of quasistationarity. The third model, which we refer to as the DNS-ZE, is a direct numerical simulation algorithm based on the Zakharov integrodifferential equation, which plays the role of the primitive equation for a weakly nonlinear wave field. It does not employ any statistical assumptions. We perform a comparison of the spectral evolution of the same initial distributions without forcing, with/without a statistical closure and with/without the quasistationarity assumption. For the initial conditions, we choose two narrow-banded spectra with the same frequency distribution and different degrees of directionality. The short-term evolution ($O(10^{2})$ wave periods) of both spectra has been previously thoroughly studied experimentally and numerically using a variety of approaches. Our DNS-ZE results are validated both with existing short-term DNS by other methods and with available laboratory observations of higher-order moment (kurtosis) evolution. All three models demonstrate very close evolution of integral characteristics of the spectra, approaching with time the theoretical asymptotes of the self-similar stage of evolution. Both kinetic equations give almost identical spectral evolution, unless the spectrum is initially too narrow in angle. However, there are major differences between the DNS-ZE and gKE/KE predictions. First, the rate of angular broadening of initially narrow angular distributions is much larger for the gKE and KE than for the DNS-ZE, although the angular width does appear to tend to the same universal value at large times. Second, the shapes of the frequency spectra differ substantially (even when the nonlinearity is decreased), the DNS-ZE spectra being wider than the KE/gKE ones and having much lower spectral peaks. Third, the maximal rates of change of the spectra obtained with the DNS-ZE scale as the fourth power of nonlinearity, which corresponds to the dynamical time scale of evolution, rather than the sixth power of nonlinearity typical of the kinetic time scale exhibited by the KE. The gKE predictions fall in between. While the long-term DNS show excellent agreement with the KE predictions for integral characteristics of evolving wave spectra, the striking systematic discrepancies for a number of specific spectral characteristics call for revision of the fundamentals of the wave kinetic description.

scholarly journals Long-term evolution is surprisingly predictable in lattice proteins

2013 ◽  
Vol 10 (82) ◽  
pp. 20130026 ◽  
Author(s):  
Michael E. Palmer ◽  
Arnav Moudgil ◽  
Marcus W. Feldman
Keyword(s):  
Natural Selection ◽  
Basins Of Attraction ◽  
Long Term Outcomes ◽  
Short Term ◽  
Term Selection ◽  
Term Evolution ◽  
Evolutionary Success ◽  
Lattice Proteins

It has long been debated whether natural selection acts primarily upon individual organisms, or whether it also commonly acts upon higher-level entities such as lineages. Two arguments against the effectiveness of long-term selection on lineages have been (i) that long-term evolutionary outcomes will not be sufficiently predictable to support a meaningful long-term fitness and (ii) that short-term selection on organisms will almost always overpower long-term selection. Here, we use a computational model of protein folding and binding called ‘lattice proteins’. We quantify the long-term evolutionary success of lineages with two metrics called the k -fitness and k -survivability. We show that long-term outcomes are surprisingly predictable in this model: only a small fraction of the possible outcomes are ever realized in multiple replicates. Furthermore, the long-term fitness of a lineage depends only partly on its short-term fitness; other factors are also important, including the ‘evolvability’ of a lineage—its capacity to produce adaptive variation. In a system with a distinct short-term and long-term fitness, evolution need not be ‘short-sighted’: lineages may be selected for their long-term properties, sometimes in opposition to short-term selection. Similar evolutionary basins of attraction have been observed in vivo , suggesting that natural biological lineages will also have a predictive long-term fitness.

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