Evolutionary Principles Research Articles

Enhanced machine learning based feature subset through FFS enabled classification for cervical cancer diagnosis

A dataset that has massive features and imbalanced classes may be challenging for obtaining adequate accuracy in classification approaches of Machine Learning (ML). The purpose of this research is to find the optimal feature subset for cervical cancer diagnosis with efficient classification approach by estimating the performance of various Machine Learning predictive models. Filter-based feature selection techniques of Relief and Information Gain are applied in this study to calculate the rank for each feature that can be applied to order and select highest scoring features for feature selection. An optimal feature subset is generated with wrapper approach through Recursive Feature Elimination which uses a Random Forest procedure and Genetic Algorithm has been employed based on evolutionary principle. The predictive models are established with 10fold cross validation using prevalent classification algorithms like Random Forest, C5.0, K-Nearest Neighbour and Naïve Bayes. The results showed an enhancement in the average performance of these classifiers concurrently and the classification error for these classifiers decreases substantially. The experiments also exhibited that by employing this approach an optimal and reduced feature subset is desirable for the enrichment of classification accuracy with a lower computational cost. The features generated by fused approach of Relief and Genetic algorithm methods were able to predict the results in an efficient manner, hence an optimal feature subset has been nominated through this procedure. Maximum number of classifiers have shown good results in terms of performance outcomes. In addition, Random Forest method has shown advanced accuracy rate with an improved percentage of sensitivity and specificity results. Also, this work established that the best and optimal feature subset selection through Fused Feature Selection (FFS) approach could reduce the complexity of the predictive model.

Forensic aspects of trauma to the male external genitalia (TMEG), analysis of a series of 84 cases

ObjectivesDescribe the medico-legal aspects of trauma to the male external genitalia by specifying their epidemiological, clinical, paraclinical, therapeutic and evolutionary characteristics. Materials and methodsRetrospective study spread over a period of 3 years (2017–2019) concerning adult patients with trauma to the male external genitalia consulting in the surgical emergency and forensic medicine departments of the Ibn Rochd University Hospital Center in Casablanca. ResultsWe collected 84 cases of TMEG within the framework of evaluation of bodily injury aimed at fixing the duration of Total Temporary Incapacity (TTI) and the rate of Permanent Partial Incapacity (PPI). There was a predominance of bursa trauma (85.7%) followed by penis trauma (14.5%). The average age of the patients was 39 years (17–61 years). Road accidents are the cause of 42% of cases. Regarding bursa trauma, the clinical symptomatology was dominated by pain (100%) and increased scrotal volume (50%). Scrotal ultrasound found the main lesion to be scrotal hematomas (35.71%) followed by ruptures of the tunica albuginea (9.5%). Surgical exploration was indicated in 45.23% of cases, of which (38%) was conservative treatment.For trauma to the penis, the clinical examination revealed 1 case of fracture of the cavernous body, a hematoma of the penis in only 1 patient, a superficial wound of the penis in 1 patient and the rest of the patients (9 cases) showed no lesions. Surgical treatment was indicated in only one patient. The average duration of temporary total incapacity was 17.5 days and the average rate of partial permanent incapacity was 4%. ConclusionPhysicians who are experts in the evaluation of bodily injury are frequently confronted with the evaluation of the damage resulting from the TMEG. The medico-legal evaluation of these traumas remains difficult and very varied requiring a perfect knowledge of the mechanisms of these traumas, of the therapeutic and evolutionary principles helping in the judicial decision.

DIPG-41. Multi-omic profiling of patient-derived subclones identifies aggressive cellular subpopulations in paediatric diffuse high-grade gliomas (PDHGGs)

Abstract Paediatric-type diffuse high-grade gliomas are classified into distinct subgroups based upon their location and defining molecular alterations, with very poor clinical outcomes in patients >3yrs. This extensive inter-tumour heterogeneity is further complicated by a wide diversity of genotypically- and phenotypically-distinct subclonal populations within individual tumours, providing a substantial barrier to developing effective treatments. We have sought to understand the dynamic cellular make-up of PDHGGs such that novel strategies aimed at targeting specific subpopulations based upon their contribution to disease progression as whole may be employed. Two complementary approaches have been undertaken to address this – first by carrying out single-cell profiling of bulk specimens, and the second isolation and propagation of single-cell-derived stem cell-like cultures in vitro. To-date we have studied 10 cases and a total of 218 subclonal colonies from both DMG-H3K27 and DHG-WT. In a spinal metastatic case of DMG-H3K27, lpWGS-FISH highlighted subpopulations driven by mis-segregation of amplified oncogenic ecDNA, and mutually exclusive subpopulations defined by MYCN, PDGFRA and CCND1. Through integrated analysis of scRNA-seq and scATAC-seq, we show distinct chromatin accessibility profiles to underlie gene expression signatures defining unique subpopulations of cells. In addition to cycling populations and those associated with lineage-specificity, we identified ‘aggressive’ subpopulations defined by significant upregulation of immediate early response genes such as FOS/FOSL1/JUN, those associated with promotion of invasion-migration such as SERPINs and MMPs. These subpopulations could be mapped to isolated single-cell-derived subclones with highly proliferative or motile phenotypes, defined by comprehensive profiling of expressed and secreted proteins. Differential cis-regulation driving cell identity-tumorigenesis was found in one example to occur via a trans-histone mechanism mediated by an H4-lysine-methyltransferase, KMT5B. Application of functionally-defined interventional strategies aimed at disrupting the interactions between these subpopulations based upon evolutionary biology principles may offer a novel approach to treat these otherwise incurable tumours in children and young adults.

Assessing the role of supplementation stocking: A perspective

AbstractAlthough it is widely accepted that stocking hatchery‐cultured fish can increase the number of fish, decades of scientific evidence have shown that most often those stocking efforts fail to provide the desired “demographic boost” to a naturally reproducing, self‐sustaining target population. Despite this evidence, fish stocking remains a mainstay of fisheries management programmes, even as the biodiversity of wild fish populations and other aquatic organisms are at serious risk due to habitat loss and/or overexploitation across the globe. In this perspective piece, we summarise the reasons why wild and hatchery‐produced fish are not equivalent and describe the genetic and ecological risks associated with stocking programmes. We then present our perspective on the institutional changes that need to occur to assess these risks and offer ways to transition fisheries management strategies to become more effective in conserving levels of aquatic biodiversity from populations to landscapes. We propose that a critical first step to control ill‐conceived fish stocking programmes is to have each country develop, implement, and enforce a scientifically sound National Fish Stocking Policy. To achieve the long‐term sustainability of native fish populations, it is imperative that ecological and evolutionary principles be better integrated into future conservation strategies and management actions.

Targeting bacterial outer-membrane remodelling to impact antimicrobial drug resistance.

The cell envelope is essential for survival and adaptation of bacteria. Bacterial membrane proteins include the major porins that mediate the influx of nutrients and several classes of antimicrobial drugs. Consequently, membrane remodelling is closely linked to antimicrobial resistance (AMR). Knowledge of bacterial membrane protein biogenesis and turnover underpins our understanding of bacterial membrane remodelling and the consequences that this process have in the evolution of AMR phenotypes. At the population level, the evolution of phenotypes is a reversible process, and we can use these insights to deploy evolutionary principles to resensitize bacteria to existing antimicrobial drugs. In our opinion, fundamental knowledge is opening a new way of thinking towards sustainable solutions to the mounting crisis in AMR. Here we discuss what is known about outer-membrane remodelling in bacteria and how the process could be targeted as a means to restore sensitivity to antimicrobial drugs. Bacteriophages are highlighted as a powerful means to exert this control over membrane remodelling but they require careful selection so as to reverse, and not exacerbate, AMR phenotypes.

Proposing a neural framework for the evolution of elaborate courtship displays

In many vertebrates, courtship occurs through the performance of elaborate behavioral displays that are as spectacular as they are complex. The question of how sexual selection acts upon these animals’ neuromuscular systems to transform a repertoire of pre-existing movements into such remarkable (if not unusual) display routines has received relatively little research attention. This is a surprising gap in knowledge, given that unraveling this extraordinary process is central to understanding the evolution of behavioral diversity and its neural control. In many vertebrates, courtship displays often push the limits of neuromuscular performance, and often in a ritualized manner. These displays can range from songs that require rapid switching between two independently controlled ‘voice boxes’ to precisely choreographed acrobatics. Here, we propose a framework for thinking about how the brain might not only control these displays, but also shape their evolution. Our framework focuses specifically on a major midbrain area, which we view as a likely important node in the orchestration of the complex neural control of behavior used in the courtship process. This area is the periaqueductal grey (PAG), as studies suggest that it is both necessary and sufficient for the production of many instinctive survival behaviors, including courtship vocalizations. Thus, we speculate about why the PAG, as well as its key inputs, might serve as targets of sexual selection for display behavior. In doing so, we attempt to combine core ideas about the neural control of behavior with principles of display evolution. Our intent is to spur research in this area and bring together neurobiologists and behavioral ecologists to more fully understand the role that the brain might play in behavioral innovation and diversification.

A topology framework for macromolecular complexes and condensates

Macromolecular assemblies such as protein complexes and protein/RNA condensates are involved in most fundamental cellular processes. The arrangement of subunits within these nano-assemblies is critical for their biological function and is determined by the topology of physical contacts within and between the subunits forming the complex. Describing the spatial arrangement of these interactions is of central importance to understand their functional and stability consequences. In this concept article, we propose a circuit topology-based formalism to define the topology of a complex consisting of linear polymeric chains with inter- and intrachain interactions. We apply our method to a system of model polymer chains as well as protein assemblies. We show that circuit topology can categorize different forms of chain assemblies. Our multi-chain circuit topology should aid analysis and predictions of mechanistic and evolutionary principles in the design of macromolecular assemblies.

Biological adaptation in light of the Lewontin-Williams (a)symmetry.

Neo‐Darwinism characterizes biological adaptation as a one‐sided process, in which organisms adapt to their environment but not vice versa. This asymmetric relationship—here called Williams’ asymmetry—is called into question by Niche Construction Theory, which emphasizes that organisms and their environments often mutually affect each other. Here, we clarify that Williams’ asymmetry is specifically concerned with (quasi)‐directed modifications toward phenotypes that increase individual fitness. This directedness—which drives the adaptive fit between organism and environment—entails far more than the mere presence of cause‐effect relationships. We argue that difficulties with invoking fitness as the guiding principle of adaptive evolution are resolved with an appropriate definition of fitness and that objections against Williams’ asymmetry reflect confusions about the nature of biological adaptation.

Abstract IA020: Dynamics of response and resistance to cancer therapy

Abstract Despite the effectiveness of many cancer therapies in reducing tumor burden for significant amounts of time in a subset of patients, primary and acquired resistance to treatment remain one of the biggest challenges in the effort to cure cancer. Successful management, or prevention, of resistance requires deciphering the mechanisms by which it arises, and in particular whether it stems from pre-existing cell populations or arises de novo during therapy. Using evolutionary principles and mathematical techniques together with patient data, we aim to develop a precise mathematical understanding of the dynamics of response and resistance to various cancer therapies, including targeted therapies and immunotherapy. Our work shows that therapies that maximize the killing rate of cancer cells may not be optimal, and that instead the parameters determining the fraction of resistant cells and their growth rate have a larger effect on the long-term control of cancer. Citation Format: Ivana Bozic. Dynamics of response and resistance to cancer therapy [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr IA020.

Abstract IA023: Selection for a glycolytic phenotype

Abstract In early breast carcinogenesis, neoplastic cells grow in multiple layers towards the lumens of ducts, which subjects the periluminal cells to harsh conditions of low oxygen, low pH, and nutrient deprivation. Adaptation to these harsh conditions is a pre-requisite for survival of incipient tumor cells and also responsible for selecting cells with a more aggressive phenotype. Based on the first principle of Darwinian evolution, common phenotypes of cancer cells must have conferred a selective advantage at some point during their evolutionary trajectory. Adaptations are initially acute and reversible, but eventually Darwinian selection results in cells with hardwired phenotypes. A prominent example of this is aerobic glycolysis, or the Warburg Effect (WE), wherein cells are hard-wired to ferment glucose, even in the presence of oxygen. WE provides and evolutionary advantage which leads to higher fitness of the cancer cells, who have acquired mechanisms of adaptation, such as autophagy and lysosome redistribution. Notably, a WE is highly correlated with a cancer’s metastatic potential and poor outcome. Hence, a major question in carcinogenesis is: “What are the mechanisms by which a harsh microenvironment eventually selects for hard-wired (heritable) phenotypes, such as a WE?”. Rather than simply selection of pre-existing phenotypes, we contend that the microenvironment actively induces phenotypic diversity through a systematic set of epigenetic and genetic alterations. Citation Format: Mehdi Damaghi. Selection for a glycolytic phenotype [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr IA023.

Abstract PR014: Design and construction of evolutionary-guided "selection gene drive" therapy

Abstract Targeted therapies that are rationally designed to inhibit driver oncogenes generally offer more durable responses for cancer patients compared to standard chemotherapies. However, in virtually all cases, the development of drug resistance inevitably subverts eradication attempts. In tyrosine kinases inhibitors (TKIs), resistance is often addressed with next-generation TKIs or combination therapies. Appropriate treatment strategies are selected based on the nature of resistance outgrowth. However, intra- and intertumoral heterogeneity makes it impossible to predict a priori which resistance variants will drive relapse in a given patient, and thus what therapeutic strategy will be optimal. Here, we propose a resistance-agnostic treatment approach that seeks to leverage evolutionary principles, rather than combat them. We designed and demonstrated the capability of a gene therapy, which we term “dual-switch selection gene drives”, that can be used to engineer cancer cells in order to guide the tumor’s evolutionary trajectory towards eradication. The dual-switch gene drive system is a genetic circuit composed of two genes that can be delivered to tumor cells on a single vector in situ. The “switch one” gene is a drug target analog that acts as an inducible, transient resistance marker, enabling rapid selection of modified cells. The “switch two” gene is the therapeutic payload of the system. Its role is to kill tumor cells by activating an inert small molecule. Importantly, the activity of the therapeutic gene is diffuse, and this bystander effect is maximized by hitchhiking off the inducible resistance gene. We developed stochastic dynamic models of tumor evolution to predict parameter regimes where eradication is possible. With these design criteria, we constructed and evaluated our system. First, we generated a panel of optimized “switch one” genes co-opting the kinase domains for a range of TKI targets, including EGFR, ALK, and RET. We demonstrated that these synthetic genes could induce a conditional resistance phenotype and be used to select for modified cells in a mixed population. Next, we evaluated the suicide gene cytosine deaminase (CD), which converts the inert prodrug 5-FC into the nucleoside analog 5-FU. Cell viability assays for mixed populations of wild-type and CD-expressing cells confirmed a strong bystander effect in this system. Finally, we assembled a single vector harboring both switches. In a pooled experiment, gene drive cells were able to drive the mixed population to eradication, even when pre-existing resistance to the TKI was introduced. Our dual-switch design demonstrates the potential to target pre-existing resistant subpopulations, without foreknowledge of the exact nature of resistance. Given that drug resistance, and thus treatment failure, is inevitable in most cancers, our treatment strategy enables us to decide the terms of relapse. Rather than combat drug resistance, we can leverage it to amplify a therapeutic gene’s effect and ultimately collapse a complex tumor population. Citation Format: Scott M. Leighow, Haider Inam, Justin R. Pritchard. Design and construction of evolutionary-guided "selection gene drive" therapy [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR014.

Evolutionary Principles of Bacterial Signaling Capacity and Complexity.

ABSTRACTMicrobes rely on signal transduction systems to sense and respond to environmental changes for survival and reproduction. It is generally known that niche adaptation plays an important role in shaping the signaling repertoire. However, the evolution of bacterial signaling capacity lacks systematic studies with a temporal direction. In particular, it is unclear how complexity evolved from simplicity or vice versa for signaling networks. Here, we examine the evolutionary processes of major signal transduction systems in Campylobacterota (formerly Epsilonproteobacteria), a phylum with sufficient evolutionary depth and ecological diversity. We discovered that chemosensory system increases complexity by horizontal gene transfer (HGT) of entire chemosensory classes, and different chemosensory classes rarely mix their components. Two-component system gains complexity by atypical histidine kinases fused with receiver domain to achieve multistep or branched signal transduction process. The presence and complexity of c-di-GMP-mediated system is related to the size of signaling network, and c-di-GMP pathways are easy to rewire, since enzymes and effectors can be linked without direct protein-protein interaction. Overall, signaling capacity and complexity rise and drop together in Campylobacterota, determined by sensory demand, genetic resources, and coevolution within the genomic context. These findings reflect plausible evolutionary principles for other cellular networks and genome evolution of the Bacteria domain.

Zng1 is a GTP-dependent zinc transferase needed for activation of methionine aminopeptidase.

The evolution of zinc (Zn) as a protein cofactor altered the functional landscape of biology, but dependency on Zn also created an Achilles' heel, necessitating adaptive mechanisms to ensure Zn availability to proteins. A debated strategy is whether metallochaperones exist to prioritize essential Zn-dependent proteins. Here, we present evidence for a conserved family of putative metal transferases in human and fungi, which interact with Zn-dependent methionine aminopeptidase type I (MetAP1/Map1p/Fma1). Deletion of the putative metal transferase in Saccharomyces cerevisiae (ZNG1; formerly YNR029c) leads to defective Map1p function and a Zn-deficiency growth defect. Invitro, Zng1p can transfer Zn2+ or Co2+ to apo-Map1p, but unlike characterized copper chaperones, transfer is dependent on GTP hydrolysis. Proteomics reveal mis-regulation of the Zap1p transcription factor regulon because of loss of ZNG1 and Map1p activity, suggesting that Zng1p is required to avoid a compounding effect of Map1p dysfunction on survival during Zn limitation.

Effects of situated learning and clarification of misconceptions on contextual reasoning about natural selection

BackgroundNatural selection is a core principle of evolution. Understanding natural selection enables students to think about the evolution and the variability of life. Despite its great importance, understanding natural selection is challenging for students. This is evident in the phenomenon of contextual reasoning, showing that students can often explain natural selection in one context (e.g., trait gain) but not in another (e.g., trait loss). The study pursues the following aims: First, to examine the link between contextual reasoning and situated learning. Second, to explore whether different instructional strategies differ in their associated cognitive load. Third, to investigate whether clarifying common misconceptions about natural selection (no vs. yes) is an effective strategy to regular instructions when aiming to increase key concepts and reduce misconceptions. Fourth, to exploratively examine the effectiveness of different instructional strategies.MethodIn a 2 × 2 factorial intervention study with a total of N = 373 secondary school students, we varied the instructional material of a 90-min intervention in terms of the evolutionary context (trait gain vs. trait loss) and the availability of additional support in the form of a clarification of misconceptions (no vs. yes). We measured students’ cognitive load immediately after instruction and assessed their ability to reason about natural selection (i.e., use of key concepts and misconceptions) later.ResultsWe documented low knowledge about evolution in the pre-test and persisting misconceptions in the post-test. The results showed that the intervention context of trait loss elicited a higher intrinsic and extraneous cognitive load than trait gain. Moreover, when the clarification of misconceptions is analyzed in connection to the intervention context, it reveals a potential for reducing misconceptions in some contexts. Students who have learned in trait gain contexts with a clarification used significantly fewer misconceptions in later reasoning than students who learned in trait gain contexts without a clarification of misconceptions.ConclusionOur study creates new insights into learning about natural selection by outlining the complex interplay between situated learning, cognitive load, clarification of misconceptions, and contextual reasoning. Additionally, it advises researchers and educators on potential instructional strategies.

Overlap not gap: Understanding the relationship between animal communication and language with Prototype Theory

What is the relationship between language and animal communication? This has largely been discussed within research on language evolution and disciplines beyond linguistics, but impacts upon the study of language generally. There are two extant views on the nature of this relationship: either there is a stark divide, with language considered as completely unique to humans, or there is a linear continuum from animal communication to language, aligning with gradualist evolutionary principles. Yet, each view involves considerable limitations. Moreover, there is no agreed-upon definition of language, which further complicates the determination of its relationship with animal communication. Withdrawing from attempts to define language with traditional fixed criteria (as characteristic of classical categorisation), this article suggests a different approach to conceptualising language and assessing the concept’s applicability to other species. Categorising phenomena through family resemblances and graded typicality of features (as in prototype-based categorisation) enables a new approach to conceptualising language, its typological diversity amongst humans, and the systematic integration of animal communication. Ultimately, with an illustrative model, this article proposes a strong overlap of animal communication with language. This approach illuminates more of the nature of language, facilitates more cohesive interdisciplinary research, and introduces potentially positive ethical implications for non-humans.

Prediction in the Aging Brain: Merging Cognitive, Neurological, and Evolutionary Perspectives.

Although the aging brain is typically characterized by declines in a variety of cognitive functions, there has been growing attention to cognitive functions that may stabilize or improve with age. We integrate evidence from behavioral, computational, and neurological domains under the hypothesis that over the life span the brain becomes more effective at predicting (i.e., utilizing knowledge) compared to learning. Moving beyond mere description of the empirical literature-with the aim of arriving at a deeper understanding of cognitive aging-we provide potential explanations for a learning-to-prediction shift based on evolutionary models and principles of senescence and plasticity. The proposed explanations explore whether the occurrence of a learning-to-prediction shift can be explained by (changes in) the fitness effects of learning and prediction over the life span. Prediction may optimize (a) the allocation of limited resources across the life span, and/or (b) late-life knowledge transfer (social learning). Alternatively, late-life prediction may reflect a slower decline in prediction compared to learning. By discussing these hypotheses, we aim to provide a foundation for an integrative neurocognitive-evolutionary perspective on aging and to stimulate further theoretical and empirical work.

Subcortical Cognition: The Fruit Below the Rind.

Cognitive neuroscience has highlighted the cerebral cortex while often overlooking subcortical structures. This cortical proclivity is found in basic and translational research on many aspects of cognition, especially higher cognitive domains such as language, reading, music, and math. We suggest that, for both anatomical and evolutionary reasons, multiple subcortical structures play substantial roles across higher and lower cognition. We present a comprehensive review of existing evidence, which indeed reveals extensive subcortical contributions in multiple cognitive domains. We argue that the findings are overall both real and important. Next, we advance a theoretical framework to capture the nature of (sub)cortical contributions to cognition. Finally, we propose how new subcortical cognitive roles can be identified by leveraging anatomical and evolutionary principles, and we describe specific methods that can be used to reveal subcortical cognition. Altogether, this review aims to advance cognitive neuroscience by highlighting subcortical cognition and facilitating its future investigation.

Directionality theory and the second law of thermodynamics

The statistical mechanics of molecular collisions in a macroscopic body is encoded by the parameter Thermodynamic entropy — a statistical measure of the number of molecular configurations that correspond to a given macrostate. Irreversibility in the flow of energy in macroscopic bodies is determined by random molecular interactions and expressed by the Second Law of Thermodynamics: In isolated systems, that is systems closed to the input of energy and matter, thermodynamic entropy increases.The evolutionary dynamics of a population of replicating organisms is encoded by the parameter Evolutionary entropy, a statistical measure of the number and diversity of metabolic cycles generated by the replication and viability of the individual organisms. Irreversibility in the transformation of energy in populations of organisms is determined by random mutation and natural selection. Changes in the organization of metabolic energy are described by the Directionality Principle of Evolution: Evolutionary entropy increases, when the energy source is limited and constant and decreases when the energy source is abundant and inconstant.This article shows that, when R→0, and N→∞ (where R denotes the production rate of the external energy source; N the number of replicating organisms) evolutionary entropy, a measure of spatio-temporal organization, and thermodynamic entropy, a measure of positional disorder, coincide. We invoke this relation between thermodynamic and evolutionary entropy to show that the Directionality Principle for Evolution is a generalization of the Second Law of Thermodynamics.

Evo-Ayu: Integrating Ayurveda with Evolutionary Biology

Evolution refers to a change in the relative frequency of alternative alleles in a population or species. Evolutionary biology studies evolution at two levels- micro-evolution and macro-evolution. Micro-evolution studies the processes that change allele frequency over time within a population. Macro-evolution studies the tree of life. Using the concepts from evolutionary biology to understand human health and disease is the basis of evolutionary medicine. Evolutionary medicine has improved our understanding of infectious diseases, genetics, ageing etc. Would an integration of evolutionary ideas with Ayurveda be equally rewarding? Ayurveda accepts Saankhya philosophy’s ideas about the origin of life. Satkaarya Vaada, which forms the basis of Ayurvedic understanding of disease and health, doesn’t provide satisfying answers to the cardinal problem of evolutionary biology - the appearance of design in the living world. Ayurvedic ideas about inheritance also contradict the germ-plasm theory of inheritance. Yet, Ayurveda has much to contribute to the study of phenotypes. Ayurvedic concepts of Deha-prakriti, Saara, Desha etc. provide exciting opportunities to test evolutionary principles within the Ayurvedic framework. Integrating Ayurveda with Evolutionary biology could help us rethink Ayurvedic concepts in the light of evolution.

Guest Editorial Special Issue on Multitask Evolutionary Computation

It is our pleasure to introduce this special issue on multitask evolutionary computation (MTEC), focusing on novel methodologies and applications of evolutionary algorithms (EAs) crafted to perform multiple search and optimization tasks jointly. EAs are population-based methods inspired by principles of natural evolution that have provided a gradient-free path to solving complex learning and optimization problems. However, unlike the natural world where evolution has engendered diverse species and produced differently skilled subpopulations, <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in silico</i> EAs are typically designed to evolve a set of solutions specialized for just a single target task. This convention of problem solving in isolation tends to curtail the power of <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">implicit parallelism</i> of a population. Skills evolved for a given problem instance do not naturally transfer to populations tasked to solve another. Hence, convergence rates remain restrained, even in settings where related tasks with overlapping search spaces, similar optimal solutions, or with other forms of reusable information, are routinely recurring.