MicroRNAs as Biomarkers of Systemic Changes in Response to Endurance Exercise—A Comprehensive Review

Endurance sports have an unarguably beneficial influence on cardiovascular health and general fitness. Regular physical activity is considered one of the most powerful tools in the prevention of cardiovascular disease. MicroRNAs are small particles that regulate the post-transcription gene expression. Previous studies have shown that miRNAs might be promising biomarkers of the systemic changes in response to exercise, before they can be detected by standard imaging or laboratory methods. In this review, we focused on four important physiological processes involved in adaptive changes to various endurance exercises (namely, cardiac hypertrophy, cardiac myocyte damage, fibrosis, and inflammation). Moreover, we discussed miRNAs’ correlation with cardiopulmonary fitness parameter (VO2max). After a detailed literature search, we found that miR-1, miR-133, miR-21, and miR-155 are crucial in adaptive response to exercise.

Characterization of high fludioxonil resistance in Botrytis cinerea isolates from calibrachoa flowers

The fungicide fludioxonil is one of the most effective single-site fungicides available for managing flower blight caused by Botrytis cinerea on fruit and ornamental crops. Though low and moderate levels of resistance to fludioxonil have been reported in the pathogen across the United States and Europe, high resistance has only been reported from greenhouses in China. In this study, two B. cinerea isolates with high resistance (EC50 >100 µg/mL) to fludioxonil were detected on ornamental calibrachoa flowers grown in a greenhouse. These isolates exhibited stable resistance for over 20 generations, produced symptoms on calibrachoa flowers sprayed with label rates of fludioxonil, and displayed in vitro fitness penalties with decreased mycelial growth (p<0.0001) and sporulation (p<0.0001) compared to sensitive isolates. Highly resistant isolates were identified as MDR1h, containing the ΔLV497 deletion in mrr1. However, resistance levels and in vitro fitness parameter characteristics were not consistent with this phenotype. One isolate contained the mutation L267V between HAMP domains 1 and 2 of the Bos-1 gene, and both isolates exhibited high osmotic sensitivity and reduced glycerol accumulation in the presence of fludioxonil, indicating that high resistance of these isolates may be associated with the HOG1 MAPK pathway.

Application of Genetic Algorithm in Common Optimization Problems

Use of non-deterministic algorithms for solving multi-variable optimization problems is widely used nowadays. Genetic Algorithm belongs to a group of stochastic biomimicry algorithms, it allows us to achieve optimal or near-optimal results in large optimization problems in exceptionally short time (compared to standard optimization methods). Major advantage of Genetic Algorithm is the ability to fuse genes, to mutate and do selection based on fitness parameter. These methods protect us from being trapped in local optima (Most of deterministic algorithms are prone to getting stuck on local optima). In this paper we experimentally show the upper hand of Genetic Algorithms compared to other traditional optimization methods by solving complex optimization problem.

Computer simulation for the growing probability of additional offspring with an advantageous reversal allele in the decoupled continuous-time mutation–selection model

This study calculated the growing probability of additional offspring with the advantageous reversal allele in an asymmetric sharply-peaked landscape using the decoupled continuous-time mutation–selection model. The growing probability was calculated for various population sizes, N, sequence lengths, L, selective advantages, s, fitness parameters, k and measuring parameters, C. The saturated growing probability in the stochastic region was approximately the effective selective advantage, [Formula: see text], when [Formula: see text] and [Formula: see text]. The present study suggests that the growing probability in the stochastic region in the decoupled continuous-time mutation–selection model can be described using the theoretical formula for the growing probability in the Moran two-allele model. The selective advantage ratio, which represents the ratio of the effective selective advantage to the selective advantage, does not depend on the population size, selective advantage, measuring parameter and fitness parameter; instead the selective advantage ratio decreases with the increasing sequence length.

In situ growth optimization in focused electron-beam induced deposition

We present the application of an evolutionary genetic algorithm for the in situ optimization of nanostructures that are prepared by focused electron-beam-induced deposition (FEBID). It allows us to tune the properties of the deposits towards the highest conductivity by using the time gradient of the measured in situ rate of change of conductance as the fitness parameter for the algorithm. The effectiveness of the procedure is presented for the precursor W(CO)6 as well as for post-treatment of Pt–C deposits, which were obtained by the dissociation of MeCpPt(Me)3. For W(CO)6-based structures an increase of conductivity by one order of magnitude can be achieved, whereas the effect for MeCpPt(Me)3 is largely suppressed. The presented technique can be applied to all beam-induced deposition processes and has great potential for a further optimization or tuning of parameters for nanostructures that are prepared by FEBID or related techniques.

Coronal Loop Mapping to Infer the Best Magnetic Field Models for Active Region Prominences

This article comments on the results of a new, rapid, and flexible manual method to map on-disk individual coronal loops of a two-dimensional EUV image into the three-dimensional coronal loops. The method by Gary, Hu, and Lee (2013) employs cubic Bézier splines to map coronal loops using only four free parameters per loop. A set of 2D splines for coronal loops is transformed to the best 3D pseudo-magnetic field lines for a particular coronal model. The results restrict the magnetic field models derived from extrapolations of magnetograms to those admissible and inadmissible via a fitness parameter. This method uses the minimization of the misalignment angles between the magnetic field model and the best set of 3D field lines that match a set of closed coronal loops. We comment on the implication of the fitness parameter in connection with the magnetic free energy and comment on extensions of our earlier work by considering the issues of employing open coronal loops or employing partial coronal loop.

Birth–death fixation probabilities for structured populations

This paper presents an adaptation of the Moran birth–death model of evolutionary processes on graphs. The present model makes use of the full population state space consisting of 2 N binary-valued vectors, and a Markov process on this space with a transition matrix defined by the edge weight matrix for any given graph. While the general case involves solution of 2 N – 2 linear equations, symmetry considerations substantially reduce this for graphs with large automorphism groups, and a number of simple examples are considered. A parameter called graph determinacy is introduced, measuring the extent to which the fate of any randomly chosen population state is determined. Some simple graphs that suppress or enhance selection are analysed, and comparison of several examples to the Moran process on a complete graph indicates that in some cases a graph may enhance selection relative to a complete graph for only limited values of the fitness parameter.

COMPUTER SIMULATION FOR THE CROSSING TIME IN A DIPLOID, ASYMMETRIC, SHARPLY-PEAKED LANDSCAPE IN THE INFINITE POPULATION LIMIT

This study calculated the crossing time in the diploid mutation–selection model in an infinite population limit for various dominance parameters, h, and selective advantages, by switching on a diploid, asymmetric, sharply-peaked landscape, from an initial state which is the steady state in a diploid, sharply-peaked landscape. The crossing time for h < 1 was found to diverge at the critical fitness parameter, which increased with increasing selective advantage and decreased with increasing sequence length. When the sequence length was increased with a fixed extension parameter, there was no crossing time for h < 1 when the sequence length was longer than the critical sequence length, which increased with increasing selective advantage. The crossing time for h ≤ 1 was found to be an exponentially increasing function of the sequence length, and the crossing time for h > 1 became saturated at a long sequence length. The crossing time decreased with increasing selective advantage, mainly because the larger selective advantage caused the increase in relative density of the reversal allele to grow exponentially at an earlier time.

CALCULATION OF THE RELATIVE DENSITY AND THE CROSSING TIME THROUGH THE FITNESS BARRIER IN AN ASYMMETRIC SHARPLY-PEAKED LANDSCAPE

We have calculated the relative density and crossing time through the fitness barrier by switching on an asymmetric sharply-peaked landscape, from the initial state which is the quasispecies in a sharply-peaked landscape. It is found that the increment of the relative density with the reversal sequence is a linearly increasing function of time unless a new stationary state in an asymmetric sharply-peaked landscape is reached. It is also found that the relative density with the reversal sequence at the new stationary state [Formula: see text] is in inverse proportion to the asymmetric parameter when the asymmetric parameter is greater than the saturation asymmetric parameter. We have derived the approximate formulae for the relaxation time, the saturation asymmetric parameter, and the relative density with the reversal sequence [Formula: see text], which nicely fit computer simulation results. It is found that the crossing time diverges at the critical fitness parameter in the asymmetric sharply-peaked landscape, in contrast with the symmetric sharply-peaked landscape where the crossing time scales as a power law in the fitness parameter. It is also found that the critical fitness parameter decreases as the asymmetric parameter and sequence length increase.