Solving the prisoner's dilemma trap in Hamilton's model of temporarily formed random groups.

Explaining the evolution of cooperation in the strong altruism scenario, where a cooperator does not benefit from her contribution to the public goods, is a challenging problem that requires positive assortment among cooperators (i.e., cooperators must tend to associate with other cooperators) or punishment of defectors. The need for these drastic measures stems from the analysis of a group selection model of temporarily formed random groups introduced by Hamilton nearly fifty years ago to describe the fate of altruistic behavior in a population. Challenging conventional wisdom, we show analytically here that strong altruism evolves in Hamilton's original model in the case of biparental sexual reproduction. Moreover, when the cost of cooperation is small and the amplified contribution shared by group members is large, cooperation is the only stable strategy in equilibrium. Thus, our results provide a solution to the 'problem of origination' of strong altruism, i.e. how cooperation can take off from an initial low frequency of cooperators. We discuss a possible reassessment of cooperation in cases of viral co-infection, as cooperation may even be favored in situations where the prisoner's dilemma applies.

A novel block-coordinate gradient descent algorithm for simultaneous grouped selection of fixed and random effects in joint modeling.

Joint models for longitudinal and time-to-event data are receiving increasing attention owing to its capability of capturing the possible association between these two types of data. Typically, a joint model consists of a longitudinal submodel for longitudinal processes and a survival submodel for the time-to-event response, and links two submodels by common covariates that may carry both fixed and random effects. However, research gaps still remain on how to simultaneously select fixed and random effects from the two submodels under the joint modeling framework efficiently and effectively. In this article, we propose a novel block-coordinate gradient descent (BCGD) algorithm to simultaneously select multiple longitudinal covariates that may carry fixed and random effects in the joint model. Specifically, for the multiple longitudinal processes, a linear mixed effect model is adopted where random intercepts and slopes serve as essential covariates of the trajectories, and for the survival submodel, the popular proportional hazard model is employed. A penalized likelihood estimation is used to control the dimensionality of covariates in the joint model and estimate the unknown parameters, especially when estimating the covariance matrix of random effects. The proposed BCGD method can successfully capture the useful covariates of both fixed and random effects with excellent selection power, and efficiently provide a relatively accurate estimate of fixed and random effects empirically. The simulation results show excellent performance of the proposed method and support its effectiveness. The proposed BCGD method is further applied on two real data sets, and we examine the risk factors for the effects of different heart valves, differing on type of tissue, implanted in the aortic position and the risk factors for the diagnosis of primary biliary cholangitis.

The Norm of Reciprocity in Intergroup Context: A Normative-Identity Model.

Reciprocity, regarded as a fundamental psychological phenomenon, may underlie a wide range of interpersonal and intergroup behaviors. Various disciplines such as behavioral economics, anthropology, sociology, and psychology as well documented how reciprocity is a strong determinant of human behavior. On the other hand, less is known about intergroup reciprocity, its functions and consequences as well as the psychological mechanisms through which these effects manifest, remain mostly unknown. In this paper, we propose a model to understand how the reciprocity norm operates in the intergroup contexts, through employing the Personal Norm of Reciprocity model (Perugini et al., 2003) and the Self-Categorization Theory (Turner et al., 1987). We suggest that the conditions that give rise to intergroup reciprocal behavior are ingroup identification, labeling outgroup behavior as a favor or transgression, and the internalization of the reciprocity norm. We also propose that the intergroup outcomes, such as ingroup favoritism, discrimination, collective action, and conflict resolution, might become more understandable when taking into account the reciprocity as an explanatory variable.

Exposing the error hidden in plain sight: A critique of Calder's (1983) group selectionist seed-dispersal hypothesis for mistletoe "mimicry" of host plants.

Some mistletoe species (Loranthaceae) resemble their host plants to a striking degree. Various mechanisms have been proposed for the developmental origins of novel traits that cause mistletoes to appear similar to their hosts, as well as for the adaptive phenotypic evolution of such traits. Calder (1983) proposed a logically flawed group selectionist seed-dispersal hypothesis for mistletoes to resemble their hosts. Calder's (1983) hypothesis does not provide a viable potential explanation for mistletoe resemblance to hosts.

Did dawkins recant his selfish gene argument against group selection?

In 2007, David S. Wilson and Edward O. Wilson (27) pointed out that, Richard Dawkins had admitted that, contrary to what he had claimed in his book The Selfish Gene (1976) (7), the idea that only the gene is a fundamental unit of selection cannot be used as an argument against the notion of group selection. This elicited a sharp denial from Dawkins (30), which was followed by an explanatory reply by Wilson and Wilson (33) and another vehement denial by Dawkins (34). I analyse the prehistory of this surprisingly complex and convoluted dispute and subsequently disentangle it. My conclusion is that much of it is based on a series of misunderstandings. First, Wilson's and Wilson's (27) original interpretation of Dawkins' selfish gene argument was incorrect. Second, in their explanatory reply (33), they distinguished between two kinds of group selection: the idea that groups can be units of selection (theoretical group selection) and the idea that group selection plays a functional role in evolution (functional group selection). They clarified that their claim concerned theoretical group selection, not functional group selection. Third, that clarified claim was correct and not correct. It was incorrect because Dawkins has never explicitly acknowledged that he had erred by developing his selfish gene theory as an implicit argument against this kind of group selection. However, the distinction that he made, by 1978, between two kinds of unit of selection, replicators (genes) and vehicles (somas), does imply such an acknowledgment since it holds that groups can be units of selection (vehicles). In this important sense, Wilson's and Wilson's clarified claim (33) was correct. Fourth, Dawkins' second denial (34) concerned functional group selection, not theoretical group selection.

Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study.

BACKGROUND: The aim of this work is to evaluate the performance of radiomics predictions for a range of molecular, genomic and clinical targets in patients with clear cell renal cell carcinoma (ccRCC) and demonstrate the impact of novel feature selection strategies and sub-segmentations on model interpretability. METHODS: Contrast-enhanced CT scans from the first 101 patients recruited to the TRACERx Renal Cancer study (NCT03226886) were used to derive radiomics classification models to predict 20 molecular, histopathology and clinical target variables. Manual 3D segmentation was used in conjunction with automatic sub-segmentation to generate radiomics features from the core, rim, high and low enhancing sub-regions, and the whole tumour. Comparisons were made between two classification model pipelines: a Conventional pipeline reflecting common radiomics practice, and a Proposed pipeline including two novel feature selection steps designed to improve model interpretability. For both pipelines nested cross-validation was used to estimate prediction performance and tune model hyper-parameters, and permutation testing was used to evaluate the statistical significance of the estimated performance measures. Further model robustness assessments were conducted by evaluating model variability across the cross-validation folds. RESULTS: Classification performance was significant (p < 0.05, H0:AUROC = 0.5) for 11 of 20 targets using either pipeline and for these targets the AUROCs were within ± 0.05 for the two pipelines, except for one target where the Proposed pipeline performance increased by > 0.1. Five of these targets (necrosis on histology, presence of renal vein invasion, overall histological stage, linear evolutionary subtype and loss of 9p21.3 somatic alteration marker) had AUROC > 0.8. Models derived using the Proposed pipeline contained fewer feature groups than the Conventional pipeline, leading to more straightforward model interpretations without loss of performance. Sub-segmentations lead to improved performance and/or improved interpretability when predicting the presence of sarcomatoid differentiation and tumour stage. CONCLUSIONS: Use of the Proposed pipeline, which includes the novel feature selection methods, leads to more interpretable models without compromising prediction performance. TRIAL REGISTRATION: NCT03226886 (TRACERx Renal).

Forward genetic analysis of monensin and diclazuril resistance in Eimeria tenella.

Worldwide distributed coccidiosis is caused by infection of both Eimeria species and Cystoisospora in the host intestine and causes huge economic losses to the livestock industry, especially the poultry industry. The control of such diseases relies mainly on chemoprophylaxis with anticoccidials, which has led to a very common drug resistance in this field. However, the genetic mechanisms underlying resistance to many anticoccidial drugs remain unknown. In this study, strains of E. tenella resistant to 250 mg/kg monensin were generated and characterized. Forward genetic approaches based on pooled genome sequencing, including experimental evolution and linkage group selection, were used to locate candidate targets responsible for resistance to monensin and diclazuril in E. tenella. A total of 16 nonsynonymous mutants in protein-coding genes were identified in monensin-resistant strains, and two genomic regions with strong selection signals were also detected in diclazuril-resistant strains. Our study reveals the genetic characterization of the experimental evolution and linkage group selection in Eimeria species, and also provides important information that contributes to the understanding of the molecular mechanism of drug resistance in coccidia.

Social evolution as moral truth tracking in natural law.

Morality can be adaptive or maladaptive. From this fact come polarizing disputes on the meta-ethical status of moral adaptation. The realist tracking account of morality claims that it is possible to track objective moral truths and that these truths correspond to moral rules that are adaptive. In contrast, evolutionary anti-realism rejects the existence of moral objectivity and thus asserts that adaptive moral rules cannot represent objective moral truths, since those truths do not exist. This article develops a novel evolutionary view of natural law to defend the realist tracking account. It argues that we can identify objective moral truths through cultural group selection and that adaptive moral rules are likely to reflect such truths.

Evolutionarily stable strategy analysis and its links to demography and genetics through invasion fitness.

Evolutionarily stable strategy (ESS) analysis pioneered by Maynard Smith and Price took off in part because it often does not require explicit assumptions about the genetics and demography of a population in contrast to population genetic models. Though this simplicity is useful, it obscures the degree to which ESS analysis applies to populations with more realistic genetics and demography: for example, how does ESS analysis handle complexities such as kin selection, group selection and variable environments when phenotypes are affected by multiple genes? In this paper, I review the history of the ESS concept and show how early uncertainty about the method lead to important mathematical theory linking ESS analysis to general population genetic models. I use this theory to emphasize the link between ESS analysis and the concept of invasion fitness. I give examples of how invasion fitness can measure kin selection, group selection and the evolution of linked modifier genes in response to variable environments. The ESSs in these examples depend crucially on demographic and genetic parameters, which highlights how ESS analysis will continue to be an important tool in understanding evolutionary patterns as new models address the increasing abundance of genetic and long-term demographic data in natural populations. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

Human major transitions from the perspective of distributed adaptations.

Distributed adaptations are cases in which adaptation is dependent on the population as a whole: the adaptation is conferred by a structural or compositional aspect of the population; the adaptively relevant information cannot be reduced to information possessed by a single individual. Possible examples of human-distributed adaptations are song lines, traditions, trail systems, game drive lanes and systems of water collection and irrigation. Here we discuss the possible role of distributed adaptations in human cultural macro-evolution. Several kinds of human-distributed adaptations are presented, and their evolutionary implications are highlighted. In particular, we discuss the implications of population size, density and bottlenecks on the distributed adaptations that a population may possess and how they in turn would affect the population's resilience to ecological change. We discuss the implications that distributed adaptations may have for human collective action and the possibility that they played a role in colonization of new areas and niches, in seasonal migration, and in setting constraints for minimal inter-population connectivity. This article is part of the theme issue 'Human socio-cultural evolution in light of evolutionary transitions'.

Can models of evolutionary transition clarify the debates over the Neolithic Revolution?

The 'Neolithic Revolution,' sometimes referred to as the emergence of agriculture at its earliest in the southern Levant, is the most significant shift in human history, shaping the world we live in today. Yet, after 100 years of study, its major cause, tempo (gradual or revolutionary), and impact of human intentionality remain disputed. Here, we examine the research potential of an evolutionary transition in individuality (ETI) to clarify this dramatic shift. Applying an ETI research perspective reveals how different causes and conditions lead to the same result, enabling a holistic view rather than a reduction of 'Neolithic' to 'agriculture,' or to one major climatic condition, inheritance system or standard evolutionary model, thus allowing us to clarify and bypass some of these heated, unresolved disputes. Additionally, unlike current archaeological emphasis on 'where,' 'when,' 'why' and 'how' questions, the ETI perspective offers a productive path for resolving a fundamental preliminary anomaly: why and how could the Neolithic lifeway evolve at all, given the selfish interest of individuals in a hunter-gatherer group? We do not intend to solve the shift to Neolithic lifeways, only to offer a fresh lens for examining it, emphasizing the relevance of tracking within and between group differences. This article is part of the theme issue 'Human socio-cultural evolution in light of evolutionary transitions'.

Intra-colony venom diversity contributes to maintaining eusociality in a cooperatively breeding ant.

BACKGROUND: Eusociality is widely considered to evolve through kin selection, where the reproductive success of an individual's close relative is favored at the expense of its own. High genetic relatedness is thus considered a prerequisite for eusociality. While ants are textbook examples of eusocial animals, not all ants form colonies of closely related individuals. One such example is the ectatommine ant Rhytidoponera metallica, which predominantly forms queen-less colonies that have such a low intra-colony relatedness that they have been proposed to represent a transient, unstable form of eusociality. However, R. metallica is among the most abundant and widespread ants on the Australian continent. This apparent contradiction provides an example of how inclusive fitness may not by itself explain the maintenance of eusociality and raises the question of what other selective advantages maintain the eusocial lifestyle of this species. RESULTS: We provide a comprehensive portrait of the venom of R. metallica and show that the colony-wide venom consists of an exceptionally high diversity of functionally distinct toxins for an ant. These toxins have evolved under strong positive selection, which is normally expected to reduce genetic variance. Yet, R. metallica exhibits remarkable intra-colony variation, with workers sharing only a relatively small proportion of toxins in their venoms. This variation is not due to the presence of chemical castes, but has a genetic foundation that is at least in part explained by toxin allelic diversity. CONCLUSIONS: Taken together, our results suggest that the toxin diversity contained in R. metallica colonies may be maintained by a form of group selection that selects for colonies that can exploit more resources and defend against a wider range of predators. We propose that increased intra-colony genetic variance resulting from low kinship may itself provide a selective advantage in the form of an expanded pharmacological venom repertoire. These findings provide an example of how group selection on adaptive phenotypes may contribute to maintaining eusociality where a prerequisite for kin selection is diminished.

Robust Bayesian variable selection for gene-environment interactions.

Gene-environment (G× E) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and data contamination in disease phenotypes of G× E studies have been commonly encountered, leading to the development of a broad spectrum of robust regularization methods. Nevertheless, within the Bayesian framework, the issue has not been taken care of in existing studies. We develop a fully Bayesian robust variable selection method for G× E interaction studies. The proposed Bayesian method can effectively accommodate heavy-tailed errors and outliers in the response variable while conducting variable selection by accounting for structural sparsity. In particular, for the robust sparse group selection, the spike-and-slab priors have been imposed on both individual and group levels to identify important main and interaction effects robustly. An efficient Gibbs sampler has been developed to facilitate fast computation. Extensive simulation studies, analysis of diabetes data with single-nucleotide polymorphism measurements from the Nurses' Health Study, and The Cancer Genome Atlas melanoma data with gene expression measurements demonstrate the superior performance of the proposed method over multiple competing alternatives.

The genome loading model for the origin and maintenance of sex in eukaryotes.

Understanding why sexual reproduction-which involves syngamy (union of gametes) and meiosis-emerged and how it has subsisted for millions of years remains a fundamental problem in biology. Considered as the essence of sex, meiotic recombination is initiated by a DNA double-strand break (DSB) that forms on one of the pairing homologous chromosomes. This DNA lesion is subsequently repaired by gene conversion, the non-reciprocal transfer of genetic information from the intact homolog. A major issue is which of the pairing homologs undergoes DSB formation. Accumulating evidence shows that chromosomal sites where the pairing homologs locally differ in size, i.e., are heterozygous for an insertion or deletion, often display disparity in gene conversion. Biased conversion tends to duplicate insertions and lose deletions. This suggests that DSB is preferentially formed on the "shorter" homologous region, which thereby acts as the recipient for DNA transfer. Thus, sex primarily functions as a genome (re)loading mechanism. It ensures the restoration of formerly lost DNA sequences (deletions) and allows the efficient copying and, mainly in eukaryotes, subsequent spreading of newly emerged sequences (insertions) arising initially in an individual genome, even if they confer no advantage to the host. In this way, sex simultaneously repairs deletions and increases genetic variability underlying adaptation. The model explains a remarkable increase in DNA content during the evolution of eukaryotic genomes.

Kin selection theory and the design of cooperative crops.

In agriculture and plant breeding, plant traits may be favoured because they benefit neighbouring plants and ultimately increase total crop yield. This idea of promoting cooperation among crop plants has existed almost as long as W.D. Hamilton's inclusive fitness (kin selection) theory, the leading framework for explaining cooperation in biology. However, kin selection thinking has not been adequately applied to the idea of cooperative crops. Here, I give an overview of modern kin selection theory and consider how it explains three key strategies for designing cooperative crops: (1) selection for a less-competitive plant type (a 'communal ideotype'); (2) group-level selection for yield; and (3) exploiting naturally selected cooperation. The first two strategies, using artificial selection, have been successful in the past but suffer from limitations that could hinder future progress. Instead, I propose an alternative strategy and a new 'colonial ideotype' that exploits past natural selection for cooperation among the modules (e.g., branches or stems) of individual plants. More generally, I suggest that Hamiltonian agriculture-a kin selection view of agriculture and plant breeding-transforms our understanding of how to improve crops of the future.

Hemispheric Asymmetry of the Hand Motor Representations in Patients with Highly Malignant Brain Tumors: Implications for Surgery and Clinical Practice.

We addressed both brain pre-surgical functional and neurophysiological aspects of the hand representation in 18 right-handed patients harboring a highly malignant brain tumor in the sensorimotor (SM) cortex (10 in the left hemisphere, LH, and 8 in the right hemisphere, RH) and 10 healthy controls, who performed an fMRI hand-clenching task with both hands alternatively. We extracted the main ROI in the SM cortex and compared ROI values and volumes between hemispheres and groups, in addition to their motor neurophysiological measures. Hemispheric asymmetry in the fMRI signal was observed for healthy controls, namely higher signal for the left-hand movements, but not for either patients' groups. ROI values, although altered in patients vs. controls, did not differ significantly between groups. ROI volumes associated with right-hand movement were lower for both patients' groups vs. controls, and those associated with left-hand movement were lower in the RH group vs. all groups. These results are relevant to interpret potential preoperative plasticity and make inferences about postoperative plasticity and can be integrated in the surgical planning to increase surgery success and postoperative prognosis and quality of life.

Baseline laboratory parameters for preliminary diagnosis of COVID-19 among children: a cross-sectional study

ABSTRACT BACKGROUND: Clinical judgment of initial baseline laboratory tests plays an important role in triage and preliminary diagnosis among coronavirus disease 2019 (COVID-19) patients. OBJECTIVES: To determine the differences in laboratory parameters between COVID-19 and COVID-like patients, and between COVID-19 and healthy children. Additionally, to ascertain whether healthy children or patients with COVID-like symptoms would form a better control group. DESIGN AND SETTING: Cross-sectional study at the Institute for Child and Youth Health Care of Vojvodina, Novi Sad, Serbia. METHODS: A retrospective study was conducted on 42 pediatric patients of both sexes with COVID-19. Hematological parameters (white blood cell count, absolute lymphocyte count and platelet count) and biochemical parameters (natremia, kalemia, chloremia, aspartate aminotransferase [AST], alanine aminotransferase [ALT], lactate dehydrogenase [LDH] and C-reactive protein [CRP]) were collected. The first control group was formed by 80 healthy children and the second control group was formed by 55 pediatric patients with COVID-like symptoms. RESULTS: Leukocytosis, lymphopenia, thrombocytosis, elevated systemic inflammatory index and neutrophil-lymphocyte ratio, hyponatremia, hypochloremia and elevated levels of AST, ALT, LDH and CRP were present in COVID patients, in comparison with healthy controls, while in comparison with COVID-like controls only lymphopenia was determined. CONCLUSIONS: The presence of leukocytosis, lymphopenia, thrombocytosis, elevated systemic inflammatory index and neutrophil-lymphocyte ratio, hyponatremia, hypochloremia and elevated levels of AST, ALT, LDH and CRP may help healthcare providers in early identification of COVID-19 patients. Healthy controls were superior to COVID-like controls since they provided better insight into the laboratory characteristics of children with novel betacoronavirus (SARS-CoV-2) infection.

Bulk segregant linkage mapping for rodent and human malaria parasites.

In 2005 Richard Carter's group surprised the malaria genetics community with an elegant approach to rapidly mapping the genetic basis of phenotypic traits in rodent malaria parasites. This approach, which he termed "linkage group selection", utilized bulk pools of progeny, rather than individual clones, and exploited simple selection schemes to identify genome regions underlying resistance to drug treatment (or other phenotypes). This work was the first application of "bulk segregant" methodologies for genetic mapping in microbes: this approach is now widely used in yeast, and across multiple recombining pathogens ranging from Aspergillus fungi to Schistosome parasites. Genetic crosses of human malaria parasites (for which Richard Carter was also a pioneer) can now be conducted in humanized mice, providing new opportunities for exploiting bulk segregant approaches for a wide variety of malaria parasite traits. We review the application of bulk segregant approaches to mapping malaria parasite traits and suggest additional developments that may further expand the utility of this powerful approach.

Organizational Development as Generative Entrenchment.

A critical task for organizations is how to best structure themselves to efficiently allocate information and resources to individuals tasked with solving sub-components of the organization's central problems. Despite this criticality, the processes by which organizational structures form remain largely opaque within organizational theory, with most approaches focused on how structure is influenced by individual managerial heuristics, normative cultural perceptions, and trial-and-error. Here, we propose that a broad understanding of organizational formation can be aided by appealing to generative entrenchment, a theory from developmental biology that helps explain why phylogenetically diverse animals appear similar as embryos. Drawing inferences from generative entrenchment and applying it to organizational differentiation, we argue that the reason many organizations appear structurally similar is due to core informational restraints on individual actors beginning at the top and descending to the bottom of these informational hierarchies, which reinforces these structures via feedback between separate levels. We further argue that such processes can lead to the emergence of a variety of group-level traits, an important but undertheorized class of phenomena in cultural evolution.

A colony-level optimization model provides a potential mechanism for the evolution of novel castes in eusocial ant colonies.

Ant species often have multiple morphologically distinct 'castes' within a single colony. Given that most of these castes are involved in non-reproductive tasks, and since such individuals thus never reproduce, the question of how ant castes can evolve is a non-trivial one. Over the years, several models have been proposed in order to explain the evolution of castes in ant colonies. Here, we attempt to answer this question using an economics-based approach, developing an optimization model that implements adaptation and selection at the colony level. We argue that due to the nature of ant colonies, selection is shifted to the group level, and, due to this, individual ants are sheltered from negative selection. We show that our framework can explain the evolution of novel castes in ant colonies, and discuss the novelty of our model with regard to previous models that have been proposed. We also show that our model is consistent with several empirical observations of ant colonies.