Process Of Natural Selection Research Articles

Antibiotic Prescribing and Antimicrobial Resistance from an Australian Perspective.

In Australia, the overuse or inappropriate prescribing of antimicrobials in health (human and animal) and agriculture is a concern that has increased over the years. This has given bacteria, fungi, parasites, and some viruses through exposure more opportunity to develop resistance. A process of artificial and natural selection, which favors microorganisms in developing the strongest natural defenses increasing prevalence of antimicrobial resistance (AMR). Appropriate use of antimicrobials can be lifesaving to humans and animals, but inappropriate use needs to be closely monitored and acted on to promote improved safety and quality of care. Inappropriate use includes prescribing antimicrobials when they are not necessary, prescribing the wrong type of antimicrobial and prescribing them for the incorrect duration. This short report reviews and summarizes some of the efforts used in Australia to control AMR and antibiotic prescribing.

Multifunctional Biomedical Materials Derived from Biological Membranes.

The delicate structure and fantastic functions of biological membranes are the successful evolutionary results of a long-term natural selection process. Their excellent biocompatibility and biofunctionality are widely utilized to construct multifunctional biomedical materials mainly by directly camouflaging materials with single or mixed biological membranes, decorating or incorporating materials with membrane-derived vesicles(e.g., exosomes), and designing multifunctional materials with the structure/functions of biological membranes. Here, the structure-function relationship of some important biological membranes and biomimetic membranes are discussed, such as various cell membranes, extracellular vesicles, and membranes from bacteria and organelles. Selected literature examples of multifunctional biomaterials derived from biological membranes for biomedical applications, such as drug- and gene-delivery systems, tissue-repair scaffolds, bioimaging, biosensors, and biological detection, are also highlighted. These designed materials show excellent properties, such as long circulation time, disease-targeted therapy, excellent biocompatibility, and selective recognition. Finally, perspectives and challenges associated with the clinical applications of biological-membrane-derived materials are discussed.

Diagnosis of Alzheimer's disease and behavioural variant frontotemporal dementia with machine learning-aided neuropsychological assessment using feature engineering and genetic algorithms.

Neuropsychological assessment is considered a valid tool in the diagnosis of neurodegenerative disorders. However, there is an important overlap in cognitive profiles between Alzheimer's disease (AD) and behavioural variant frontotemporal dementia (bvFTD), and the usefulness in diagnosis is uncertain. We aimed to develop machine learning-based models for the diagnosis using cognitive tests. Three hundred and twenty-nine participants (170 AD, 72 bvFTD, 87 healthy control [HC]) were enrolled. Evolutionary algorithms, inspired by the process of natural selection, were applied for both mono-objective and multi-objective classification and feature selection. Classical algorithms (NativeBayes, Support Vector Machines, among others) were also used, and a meta-model strategy. Accuracies for the diagnosis of AD, bvFTD and the differential diagnosis between them were higher than 84%. Algorithms were able to significantly reduce the number of tests and scores needed. Free and Cued Selective Reminding Test, verbal fluency and Addenbrooke's Cognitive Examination were amongst the most meaningful tests. Our study found high levels of accuracy for diagnosis using exclusively neuropsychological tests, which supports the usefulness of cognitive assessment in diagnosis. Machine learning may have a role in improving the interpretation and test selection.

The Core Mechanism of Natural Selection: How the Natural Cycle of Potassium Resources Affects the Biological Evolution and the Change of Human Society

Darwin’s theory of evolution believes that biological evolution is a process of natural selection. This theory has been supported by much evidence, but the internal biological mechanism is not clear. Here, I elaborate on the cycle of potassium resources on the earth and the biological utilization and efficiency, which may be the core mechanism of natural selection and affect the evolution of organisms and the development of human society.

Is Gain of Function a Reliable Tool for Establishing Sars-Cov-2 Origin?

The present opinion article, while dealing with the debated origin of “Severe Acute Respiratory Syndrome-Coronavirus-2” (SARS-CoV-2), the betacoronavirus responsible for “Corona Virus Disease-2019” (COVID-19), provides a speculative insight into the so-called “gain of function” (GOF), a process resulting in the acquirement of new phenotypic features on behalf of the viral pathogen. More in detail, a GOF-related phenomenon leading to increased SARS-CoV-2 virulence and/or transmissibility—as clearly exemplified by the “delta” and the “omicron” as well as by other “variants of concern”—would not necessarily imply that viral genetic manipulations made in the laboratory are its exclusive drivers, provided that GOF may also occur as a consequence of a natural selection process. In order to gain a better understanding of SARS-CoV-2 GOF and GOF-associated phenomena, an in-depth knowledge of the complex viral-host interaction dynamics is absolutely needed, while also paying special attention to the human-animal-viral ecological interfaces within an “ad hoc” multidisciplinary, “holistic”, scientific evidence-based and “One Health”-based approach.

Triggering Factors for Organism' Evolution

The purpose of the article is to know the trigerring factor for arganism’ Evolution. Evolution is defined as the change in the heritable features of a population of organisms from one generation to the next, or from one generation to the next. Evolution, according to the contemporary conception, is characterized by changes in the attributes of living organisms through time, with these changes being guided by the process of natural selection

An ordered crossover based approach to designing labeling diversity mappers

AbstractGenetic algorithms (GAs) are population‐based search optimization techniques that mimic the process of evolution and natural selection. GAs are an effective way of finding feasible solutions to complex problems. Recently, GAs were applied to the labeling diversity (LD) problem that produced local optimal mappers for M‐QAM, M‐PSK, and M‐APSK constellations. However, the GA did not implement biological processes during the mating process; hence it could not be classified as a GA, but rather a genetic‐inspired algorithm (GIA). In this article, we investigate the application of six distinct crossover techniques to further improve the GIAs ability to produce more closer‐to‐optimal mapper designs. By using biological crossover techniques, offspring produced acquires genetic diversity from parent chromosomes. Single parent crossover techniques do not produce diversified offspring, thus diversity being acquired only by mutation. The Davis ordered crossover (OX1) was chosen as a suitable technique to be applied to the proposed GA. The proposed GA was tested on 16QAM, 16PSK, 16APSK, and three 16APSK constellations that do not exhibit diagonal symmetry. In the case of the 16QAM and 16PSK constellations, the proposed GA matched but did not improve upon existing mapper designs. In the case of the 16APSK and 11+5APSK constellations, the proposed GA produced mapper designs exhibited diversity gains of dB over the existing GIA mapper designs at the BER of. The asymmetric 16APSK and single symmetry 16APSK constellations exhibited diversity gains ofand dB over existing GIA mapper designs at the BER ofand. More significantly, the proposed GA achieved a significant improvement in time complexity. However, the proposed GA was shown to have higher computational complexity ofover the GIA with a complexity of. Mutation rate studies have shown that for single‐parent crossover techniques, higher mutation rates are needed, thus making the process is purely random. In the case of the two‐parent crossover technique, randomness is reduced and genetic diversity is increased, hence lower mutation rates were required due to a more guided search.

Sperm Selection for ICSI: Do We Have a Winner?

In assisted reproductive technology (ART), the aim of sperm cells’ preparation is to select competent spermatozoa with the highest fertilization potential and in this context, the intracytoplasmic sperm injection (ICSI) represents the most applied technique for fertilization. This makes the process of identifying the perfect spermatozoa extremely important. A number of methods have now been developed to mimic some of the natural selection processes that exist in the female reproductive tract. Although many studies have been conducted to identify the election technique, many doubts and disagreements still remain. In this review, we will discuss all the sperm cell selection techniques currently available for ICSI, starting from the most basic methodologies and continuing with those techniques suitable for sperm cells with reduced motility. Furthermore, different techniques that exploit some sperm membrane characteristics and the most advanced strategy for sperm selection based on microfluidics, will be examined. Finally, a new sperm selection method based on a micro swim-up directly on the ICSI dish will be analyzed. Eventually, advantages and disadvantages of each technique will be debated, trying to draw reasonable conclusions on their efficacy in order to establish the gold standard method.

DNA Methylation Differences Between Zona Pellucida-Bound and Manually Selected Spermatozoa Are Associated With Autism Susceptibility.

Children conceived through intracytoplasmic sperm injection (ICSI) have been reported to have a higher risk of many abnormalities and disorders, including autism and intellectual disability, which may be due to bypassing of the natural sperm selection process during ICSI. Zona pellucida (ZP)-bound spermatozoa (ZPBS) have normal morphology and nuclear DNA. Using these spermatozoa for ICSI results in better outcomes compared with conventional ICSI. However, differences besides morphology that exist between sperm selected by ZP and by an embryologist and whether these differences affect the risk of autism in offspring after ICSI are unclear. To explore these questions, we compared genome-wide DNA methylation profiles between ZPBS and manually selected spermatozoa (MSS)using single-cell bisulfite sequencing. Global DNA methylation levels were significantly lower in ZPBS than in MSS. Using gene ontology (GO) analysis, genes overlapping differentially methylated regions (DMRs) were enriched in biological processes involving neurogenesis. Furthermore, we found that 47.8% of autism candidate genes were associated with DMRs, compared with 37.1% of matched background genes (P<0.001). This was mainly because of the high proportion of autism candidate genes with bivalent chromatin structure. In conclusion, bivalent chromatin structure results in large differences in the methylation of autism genes between MSS and ZPBS. ICSI using MSS, which increases the risk of methylation mutations compared with ZPBS, may lead to a higher risk of autism in offspring.

Simulating nature in sperm selection for assisted reproduction.

Sperm selection in the female reproductive tract (FRT) is sophisticated. Only about 1,000 sperm out of millions in an ejaculate reach the fallopian tube and thus have a chance of fertilizing an oocyte. In assisted reproduction techniques, sperm are usually selected using their density or motility, characteristics that do not reflect their fertilization competence and, therefore, might result in failure to fertilize the oocyte. Although sperm processing in in vitro fertilization (IVF) and intrauterine insemination (IUI) bypasses many of the selection processes in the FRT, selection by the cumulus mass and the zona pellucida remain intact. By contrast, the direct injection of a sperm into an oocyte in intracytoplasmic sperm injection (ICSI) bypasses all natural selection barriers and, therefore, increases the risk of transferring paternal defects such as fragmented DNA and genomic abnormalities in sperm to the resulting child. Research into surrogate markers of fertilization potential and into simulating the natural sperm selection processes has progressed. However, methods of sperm isolation - such as hyaluronic acid-based selection and microfluidic isolation based on sperm tactic responses - use only one or two parameters and are not comparable with the multistep sperm selection processes naturally occurring within the FRT. Fertilization-competent sperm require a panel of molecules, including zona pellucida-binding proteins and ion channel proteins, that enable them to progress through the FRT to achieve fertilization. The optimal artificial sperm selection method will, therefore, probably need to use a multiparameter tool that incorporates the molecular signature of sperm with high fertilization potential, and their responses to external cues, within a microfluidic system that can replicate the physiological processes of the FRT in vitro.

Tumor Heterogeneity and Consequences for Bladder Cancer Treatment.

Simple SummaryBladder cancer is a heterogeneous disease that is composed of epithelia with varying transcriptional, mutational and lineage signatures. The epithelia of bladder tumors can also undergo pronounced changes in transcriptional and phenotypical qualities in response to progression, treatment related stresses and cues from the tumor microenvironment (TME). We hypothesize that changes in epithelial tumor heterogeneity (EpTH) occur due to the evolving content of epithelial subpopulations through both Darwinian and Lamarckian-like natural selection processes. We further conjecture that lineage-defined subpopulations can change through nongenomic and genomic cellular mechanisms that include cellular plasticity and acquired driver mutations, respectively. We propose that such processes are dynamic and contribute towards clinical treatment challenges including progression to drug resistance. In this article, we assess mechanisms that may support dynamic tumor heterogeneity with the overall goal of emphasizing the application of these concepts to the clinical setting.Acquired therapeutic resistance remains a major challenge in cancer management and associates with poor oncological outcomes in most solid tumor types. A major contributor is tumor heterogeneity (TH) which can be influenced by the stromal; immune and epithelial tumor compartments. We hypothesize that heterogeneity in tumor epithelial subpopulations—whether de novo or newly acquired—closely regulate the clinical course of bladder cancer. Changes in these subpopulations impact the tumor microenvironment including the extent of immune cell infiltration and response to immunotherapeutics. Mechanisms driving epithelial tumor heterogeneity (EpTH) can be broadly categorized as mutational and non-mutational. Mechanisms regulating lineage plasticity; acquired cellular mutations and changes in lineage-defined subpopulations regulate stress responses to clinical therapies. If tumor heterogeneity is a dynamic process; an increased understanding of how EpTH is regulated is critical in order for clinical therapies to be more sustained and durable. In this review and analysis, we assess the importance and regulatory mechanisms governing EpTH in bladder cancer and the impact on treatment response.

Genetic Feature Selection Applied to KOSPI and Cryptocurrency Price Prediction

Feature selection reduces the dimension of input variables by eliminating irrelevant features. We propose feature selection techniques based on a genetic algorithm, which is a metaheuristic inspired by a natural selection process. We compare two types of feature selection for predicting a stock market index and cryptocurrency price. The first method is a newly devised genetic filter involving a fitness function designed to increase the relevance between the target and the selected features and decrease the redundancy between the selected features. The second method is a genetic wrapper, whereby we can find the better feature subsets related to KOPSI by exploring the solution space more thoroughly. Both genetic feature selection methods improved the predictive performance of various regression functions. Our best model was applied to predict the KOSPI, cryptocurrency price, and their respective trends after COVID-19.

Comparison of myonuclear domain in phylogenetically paired tropical and temperate bird species

The life‐history theory of evolution posits that organisms are maximized for reproductive success through the processes of natural selection. Though believed to impact nearly every aspect of an organism, the life‐history theory of evolution shines little attention on the cellular aspects of organismal physiology. Tropical bird species, compared with temperate birds, are typically placed on the ‘slow' pace‐of‐life spectrum, and demonstrate a ‘slow' pace of life across every level of organization. Previously, we demonstrated that phylogenetically paired tropical birds have significantly smaller muscle fiber diameters than their temperate counterparts. No other muscle‐related properties have been addressed and correlated to life‐histories in the literature. Myonuclear domain (MND), the cytoplasmic volume that each myonucleus serves, is an under‐appreciated skeletal muscle property that has been largely ignored in bird muscle literature. Here, we measured MND in muscle cross‐sections in phylogenetically paired species of tropical and temperate birds. We found that tropical bird species had significantly higher numbers of nuclei per mm of fiber as compared with temperate bird species. This may be due to the fact that tropical birds could have a higher population of slow‐ oxidative fiber and/or due to developing in warmer climates, as compared with temperate birds. In both tropical and temperate birds, we found significantly positive associations between muscle fiber diameter and MND and between muscle cross‐sectional areas and number of nuclei per mm of fiber in tropical birds and temperate birds, as previously noted in other bird species.

Electrokinesis hypothesis of neuron selection for synapse formation and pruning

What neurons are connected and what neurons are disconnected? These are crucial questions since they determine the structural connectivity of the brain. We address this matter in question and propose a speculative hypothesis. We claim that the neuron selection for synapse formation and pruning process is an electrokinesis-based stochastic physical process. Propagating input signals generate a varying electromagnetic field in the interstitial fluid, which is filled with ions. Varying electromagnetic field exerts Lorentz force on the ions and causes local fluid flows. These fluid flows alter the position of presynaptic boutons and dendritic spines, and hence the likelihood of making contact. Above a certain level of field strength, the likelihood of pruning increases. If the proposed hypothesis is correct, in addition to explaining the natural process of neuron selection for synapse formation and pruning, it can also explain why and why not brain stimulation techniques work. Additionally, it will provide a controllable mechanism to alter brain connectivity as desired, which may have a profound impact on many connectivity-based psychiatric and neurological diseases.

The EnigmaticCulex pipiens(Diptera: Culicidae) Species Complex: Phylogenetic Challenges and Opportunities From a Notoriously Tricky Mosquito Group

AbstractOur understanding of how natural selection and demographic processes produce and maintain biological diversity remains limited. However, developments in high-throughput genomic sequencing coupled with new analytical tools and phylogenetic methods now allow detailed analyses of evolutionary patterns in genes and genomes responding to specific demographic events, ecological changes, or other selection pressures. Here, we propose that the mosquitoes in the Culex pipiens complex, which include taxa of significant medical importance, provide an exceptional system for examining the mechanisms underlying speciation and taxonomic radiation. Furthermore, these insects may shed light on the influences that historical and contemporary admixture have on taxonomic integrity. Such studies will have specific importance for mitigating the disease and nuisance burdens caused by these mosquitoes. More broadly, they could inform predictions about future evolutionary trajectories in response to changing environments and patterns of evolution in other cosmopolitan and invasive species that have developed recent associations with humans.

Analysis and simulation of fracture behavior in naturally occurring Bouligand structures

Through natural selection processes, refined biological materials could be created that adapt to various environments and exhibit specific functions. Such materials include typical Bouligand structures that can be widely observed in marine creatures that have hard shells. Consisting of a helicoidal arrangement of aligned fibrils, layered single-twisted Bouligand-type structures (SBS) display exceptional fracture and damage resistance. A much more primitive and rarer type of this formation, the double-twisted Bouligand-type structures (DBS), has been discovered in ancient fish scales, and this architecture could provide added rigidity and significantly contribute to toughness when facing fracture risk. In this work, we describe a computational modeling approach to investigating fracture behaviors and toughening mechanisms in Bouligand structures. To achieve qualitative insights into the fracture behaviors of DBS and SBS, we applied these two configurations, which were identified from corresponding biological materials, to analyze load-displacement responses during single edge notched (SEN) tensile testing; the toughening mechanism is also discussed further. The results clearly show that the arrangement of helix fibrils and interlaminar properties play a major role in the resulting fracture behaviors of Bouligand architectures. This is of interest for the future design of engineering materials and structures that require composites with enhanced toughness, and could deepen our understanding of the structure-property relationship of Bouligand-type structures in bionic design. Statement of significanceIn this work, a novel numerical modeling approach based on the extended finite element method (XFEM) has been established to evaluate the fracture behavior of a naturally-occurring Bouligand-type helicoidal structure subjected to the single edge notched (SEN) tensile loading. The roles of the biological features (i.e., layered arrangement of collagen fibrils and interbundle fibrils) on the fracture resistance and toughening mechanism of the Bouligand-type structures have been uncovered and analyzed quantitatively. This is of interest for future design of engineering materials and structures that require composites with enhanced toughness, and can deepen the understanding of the structure-property relationship of the Bouligand-type structure in bionic design.

Multivariable analysis for selection of natural fibers as fillers for a sustainable food packaging industry

There is a rising demand for advanced new materials in food packaging to meet the growing economic and sustainability requirements. Natural fibers have excellent mechanical and thermal isolation properties and lower production costs than synthetic fibers, making them suitable candidates for the development of sustainable food packaging. Other characteristics of natural fibers, i.e., low cost, easy availability, and low impact on the environment, making these materials a promising option for food packaging. The primary focus of this study is to utilize multivariable analysis, an analytic hierarchy process and a multi-criteria decision analysis to select appropriate natural fiber reinforcement for food packaging from commonly used plant fibers (coir, date palm, hemp, sisal, jute, flax, corn stalk, banana, bamboo, cotton). The multivariable selection system is used to compare crucial food packaging materials’ requirements and production parameters gathered different properties including density, Young modulus, elongation to break, moisture content, thermal conductivity, cost, availability, etc, to help identify appropriate natural fibers. From the results, selecting the most appropriate natural fiber depends on the design requirements, cost, and availability; all these parameters are also affected by the geological conditions and customer needs. Single parameter comparison is used to compare the investigated natural fiber; then analytic hierarchy process is used to rank the highest priority parameters for the natural fiber selection process. The results showed that density (22%), cost (13.6%), moisture content (11.7%), thermal conductivity (10.7%), elongation at break (7.7%), and Young modulus (7.4%) are rated in the order of priority. Hemp, banana and sisal fibers are ranked as the best choices for the food packaging by the multi-criteria decision analysis, i.e. TOPSIS. Examples are presented considering the multivariable analysis using radar charts to identify the best natural fibers source for countries such as Kingdom of Saudi Arabia, Pakistan, Bangladesh, and India. Date palm is a preferred natural fiber source for food packaging reinforcement in Saudi Arabia and Pakistan, whereas bamboo and jute are better choices for India and Bangladesh.

Sustainable Development, COVID-19 and Small Business in Greece: Small Is Not Beautiful

The aim of this article is s to show that contrary to the common parlance and to the widespread belief that treats small business as “the backbone of the economy”, in the sense of being the prime motor of wealth and prosperity, therefore the underlying logic is what is good for small business will also help government achieves overall economic policy goals, the prevailing dominant idea that formulates and drives the Greek economic policy is quite the opposite. Based on textual analysis, from Greece’s Structural Adjustment Programs, to the various assessment reports, till the latest “Development Plan for the Greek Economy”, we attempt to reveal that the prevailing idea that penetrates the abovementioned texts is that “small is not beautiful”. Specifically, after indicating a policy paradox regarding the limited financial support that Greek small businesses received or expected to receive despite their vital importance to the Greek economy, we expose the “structural impediment” idea. According to the latter the existence of a large share of small business in the Greek economy is being considered as a structural impediment for economic growth and prosperity. The implication is a policy dictum that favours a form of an evolutionary natural selection process, whereby only those establishments successful enough to grow will be able to survive, thus the vast bulk of the remaining small firms will exit the market.

Clonal Evolution of Multiple Myeloma-Clinical and Diagnostic Implications.

Plasma cell dyscrasias are a heterogeneous group of diseases characterized by the expansion of bone marrow plasma cells. Malignant transformation of plasma cells depends on the continuity of events resulting in a sequence of well-defined disease stages, from monoclonal gammopathy of undetermined significance (MGUS) through smoldering myeloma (SMM) to symptomatic multiple myeloma (MM). Evolution of a pre-malignant cell into a malignant cell, as well as further tumor progression, dissemination, and relapse, require development of multiple driver lesions conferring selective advantage of the dominant clone and allowing subsequent evolution under selective pressure of microenvironment and treatment. This process of natural selection facilitates tumor plasticity leading to the formation of genetically complex and heterogenous tumors that are notoriously difficult to treat. Better understanding of the mechanisms underlying tumor evolution in MM and identification of lesions driving the evolution from the premalignant clone is therefore a key to development of effective treatment and long-term disease control. Here, we review recent advances in clonal evolution patterns and genomic landscape dynamics of MM, focusing on their clinical implications.

Global optimisation in Hilbert spaces using the survival of the fittest algorithm

Global optimisation problems in high-dimensional and infinite-dimensional spaces arise in various real-world applications such as engineering, economics and finance, geophysics, biology, machine learning, optimal control, etc. Among stochastic approaches to global optimisation, biology-inspired methods are currently very popular in the literature. Bio-inspired approaches imitate natural ecological and evolutionary processes and are reported to be efficient in a large number of practical study cases. However, many bio-inspired methods can possess some vital drawbacks. For example, due to their semi-empirical nature, convergence to the globally optimal solution cannot always be guaranteed. Another major obstacle is that the existing methods often struggle with higher dimensionality of the space of parameters, which results in a slow convergence. Moreover, it is often difficult to adjust the dimensionality of the space of parameters in the corresponding computer code for a practical realisation of the optimisation method. Here, we present a bio-inspired global stochastic optimisation method applicable in Hilbert function spaces. The proposed method is an evolutionary algorithm inspired by the Darwin’s famous idea of survival of the fittest and is, therefore, referred to as the ‘Survival of the Fittest Algorithm’ (SoFA). Mathematically, the convergence of SoFA is a consequence of the fundamental property of localisation of probabilistic measure in a Hilbert space and we rigorously prove the convergence of the introduced algorithm for a generic class of functionals. The approach is simple in terms of practical coding. As an insightful, real-world problem, we apply our method to find the globally optimal trajectory for the daily vertical migration of zooplankton in the ocean and lakes, this phenomenon is considered to be the largest synchronised movement of biomass on Earth. We maximise fitness in a function space derived from a von-Foerster stage-structured population model with biologically realistic parameters. We show that for problems of fitness maximisation in high-dimensional spaces, SoFA provides better performance as compared to some other stochastic global optimisation algorithms. We highlight the links between the new optimisation algorithm and natural selection processes in ecosystems occurring within a population via gradual exclusion of competitive con-specific strains.