Mosaic Theory Research Articles

The geographic mosaic of arms race coevolution is closely matched to prey population structure.

Reciprocal adaptation is the hallmark of arms race coevolution. Local coadaptation between natural enemies should generate a geographic mosaic pattern where both species have roughly matched abilities across their shared range. However, mosaic variation in ecologically relevant traits can also arise from processes unrelated to reciprocal selection, such as population structure or local environmental conditions. We tested whether these alternative processes can account for trait variation in the geographic mosaic of arms race coevolution between resistant garter snakes (Thamnophis sirtalis) and toxic newts (Taricha granulosa). We found that predator resistance and prey toxin levels are functionally matched in co‐occurring populations, suggesting that mosaic variation in the armaments of both species results from the local pressures of reciprocal selection. By the same token, phenotypic and genetic variation in snake resistance deviates from neutral expectations of population genetic differentiation, showing a clear signature of adaptation to local toxin levels in newts. Contrastingly, newt toxin levels are best predicted by genetic differentiation among newt populations, and to a lesser extent, by the local environment and snake resistance. Exaggerated armaments suggest that coevolution occurs in certain hotspots, but prey population structure seems to be of particular influence on local phenotypic variation in both species throughout the geographic mosaic. Our results imply that processes other than reciprocal selection, like historical biogeography and environmental pressures, represent an important source of variation in the geographic mosaic of coevolution. Such a pattern supports the role of “trait remixing” in the geographic mosaic theory, the process by which non‐adaptive forces dictate spatial variation in the interactions among species.

The geographic mosaic in parallel: Matching patterns of newt tetrodotoxin levels and snake resistance in multiple predator-prey pairs.

The Geographic Mosaic Theory of Coevolution predicts that coevolutionary arms races will vary over time and space because of the diverse ecological settings and population histories of interacting species across the landscape. Thus, understanding coevolution may require investigating broad sets of populations sampled across the range of the interaction. In addition, comparing coevolutionary dynamics between similar systems may reveal the importance of specific factors that structure coevolution. Here, we examine geographic patterns of prey traits and predator traits in the relatively unstudied interaction between the Sierra garter snake (Thamnophis couchii) and sympatric prey, the rough-skinned newt (Taricha granulosa), Sierra newt (Ta. sierrae) and California newt (Ta. torosa). This system parallels, in space and phenotypes, a classic example of coevolution between predatory common garter snakes (Th. sirtalis) and their toxic newt prey exhibiting hotspots of newt tetrodotoxin (TTX) levels and matching snake TTX resistance. We quantified prey and predator traits from hundreds of individuals across their distributions, and functional trait matching at sympatric sites. We show strong regional patterns of trait covariation across the shared ranges of Th. couchii and newt prey. Traits differ significantly among localities, with lower newt TTX levels and snake TTX resistance at the northern latitudes, and higher TTX levels and snake resistance at southern latitudes. Newts and snakes in northern populations show the highest degree of functional trait matching despite possessing the least extreme traits. Conversely, newts and snakes in southern populations show the greatest mismatch despite possessing exaggerated traits, with some snakes so resistant to TTX they would be unaffected by any sympatric newt. Nevertheless, individual variation was substantial, and appears to offer the opportunity for continued reciprocal selection in most populations. Overall, the three species of newts appear to be engaged in a TTX-mediated arms race with Th. couchii. These patterns are congruent with those seen between newts and Th. sirtalis, including the same latitudinal gradient in trait covariation, and the potential 'escape' from the arms race by snake predators. Such concordance in broad scale patterns across two distinct systems suggests common phenomena might structure geographic mosaics in similar ways.

Trajectory Monitoring in Portfolio Management and Issuer Intentionality Scoring

Two-degrees alignment has become a major issue for climate-aware portfolio management. There are sophisticated initiatives aiming to predict corporate emission intensities from 2030 up to 2100. In this paper, we focus on the significance of the ‘current policy scenario’, where corporates would simply stay on their current trajectories for their emission intensities. UNEP has illustrated how far the global current policy scenario is from a global two-degrees scenario. We want to understand this ‘current policy scenario’, broken down asset-by-asset within the significant emission sectors, and from a global index point of view. We will address choices of emission intensity metrics and of weighting schemes. Enabling the low-carbon transition while maintaining a long-term focus in investment decision-making is a relevant approach. In this paper, we intend to illustrate the virtue of the long-term choice with a simple three-year observation gap in the power generation sector’s intensities. To complement our ‘current policy’, which focuses on the emissions track-record of firms, we illustrate a mosaic theory approach to quantifying the intentionality of a firm to green itself. Anticipating positive impacts requires that investors have identified their key questions for firms' intentions.

Local Adaptation of Bacterial Symbionts within a Geographic Mosaic of Antibiotic Coevolution.

The geographic mosaic theory of coevolution (GMC) posits that coevolutionary dynamics go beyond local coevolution and are comprised of the following three components: geographic selection mosaics, coevolutionary hot spots, and trait remixing. It is unclear whether the GMC applies to bacteria, as horizontal gene transfer and cosmopolitan dispersal may violate theoretical assumptions. Here, we test key GMC predictions in an antibiotic-producing bacterial symbiont (genus Pseudonocardia) that protects the crops of neotropical fungus-farming ants (Apterostigma dentigerum) from a specialized pathogen (genus Escovopsis). We found that Pseudonocardia antibiotic inhibition of common Escovopsis pathogens was elevated in A. dentigerum colonies from Panama compared to those from Costa Rica. Furthermore, a Panama Canal Zone population of Pseudonocardia on Barro Colorado Island (BCI) was locally adapted, whereas two neighboring populations were not, consistent with a GMC-predicted selection mosaic and a hot spot of adaptation surrounded by areas of maladaptation. Maladaptation was shaped by incongruent Pseudonocardia-Escovopsis population genetic structure, whereas local adaptation was facilitated by geographic isolation on BCI after the flooding of the Panama Canal. Genomic assessments of antibiotic potential of 29 Pseudonocardia strains identified diverse and unique biosynthetic gene clusters in BCI strains despite low genetic diversity in the core genome. The strength of antibiotic inhibition was not correlated with the presence/absence of individual biosynthetic gene clusters or with parasite location. Rather, biosynthetic gene clusters have undergone selective sweeps, suggesting that the trait remixing dynamics conferring the long-term maintenance of antibiotic potency rely on evolutionary genetic changes within already-present biosynthetic gene clusters and not simply on the horizontal acquisition of novel genetic elements or pathways.IMPORTANCE Recently, coevolutionary theory in macroorganisms has been advanced by the geographic mosaic theory of coevolution (GMC), which considers how geography and local adaptation shape coevolutionary dynamics. Here, we test GMC in an ancient symbiosis in which the ant Apterostigma dentigerum cultivates fungi in an agricultural system analogous to human farming. The cultivars are parasitized by the fungus Escovopsis The ants maintain symbiotic actinobacteria with antibiotic properties that help combat Escovopsis infection. This antibiotic symbiosis has persisted for tens of millions of years, raising the question of how antibiotic potency is maintained over these time scales. Our study tests the GMC in a bacterial defensive symbiosis and in a multipartite symbiosis framework. Our results show that this multipartite symbiotic system conforms to the GMC and demonstrate that this theory is applicable in both microbes and indirect symbiont-symbiont interactions.

The geographical and seasonal mosaic in a plant-herbivore interaction: patterns of defences and herbivory by a specialist and a non-specialist

In order to evaluate the geographic mosaic theory of coevolution, it is crucial to investigate geographical variation on the outcome of ecological interactions and the functional traits which dictate these outcomes. Plant populations are attacked by specialist and non-specialist herbivores and may have different types of chemical and biotic defences. We investigated geographical and seasonal variation in the interaction between the plant Crotalaria pallida and its two major herbivores (the specialist Utetheisa ornatrix and the non-specialist Etiella zinckenella). We first showed that attack by the two herbivores and a chemical and a biotic defence vary greatly in time and space. Second, we performed a common garden experiment that revealed genetic variation among populations in herbivore resistance and a chemical defence, but no genetic variation in a biotic defence. Third, we sampled 20 populations on a much larger geographical scale and showed great variation in attack rates by the two herbivores and a chemical defence. Finally, we showed that herbivory is not correlated with a chemical defence in the 20 field populations. Our study shows that to understand the evolution of ecological interactions it is crucial to investigate how the outcome of the interaction and the important species traits vary geographically and seasonally.

Did the Siebel Systems Case Limit the SEC’s Ability to Enforce Regulation Fair Disclosure?

We examine whether a shock to the enforceability of Regulation Fair Disclosure (Reg FD) limited its ability to restrict the flow of private information between managers and investors. While prior work provides evidence that Reg FD reduced managers’ selective disclosure of material information immediately following its promulgation, we posit that private information flows returned as a result of the SEC’s public enforcement failure in SEC v. Siebel Systems, Inc. Using multiple settings, we find consistent evidence suggesting that Siebel changed the cost-benefit tradeoff for Reg FD compliance and effectively reversed the initial effects of the regulation. We also find that Siebel disrupted the equilibrium of selective disclosure activity, resulting in an unleveling effect among investors with respect to private information advantages. Finally, we find that Siebel also had real effects by altering managers’ capital structure decisions. Our findings run counter to the prevailing “mosaic theory” and gradual learning explanations for private information advantages in the extended post-Reg FD period and highlight the importance of enforcement in achieving intended regulatory outcomes.

Assessing Specialized Metabolite Diversity in the Cosmopolitan Plant Genus Euphorbia L.

Coevolutionary theory suggests that an arms race between plants and herbivores yields increased plant specialized metabolite diversity and the geographic mosaic theory of coevolution predicts that coevolutionary interactions vary across geographic scales. Consequently, plant specialized metabolite diversity is expected to be highest in coevolutionary hotspots, geographic regions, which exhibit strong reciprocal selection on the interacting species. Despite being well-established theoretical frameworks, technical limitations have precluded rigorous hypothesis testing. Here we aim at understanding how geographic separation over evolutionary time may have impacted chemical differentiation in the cosmopolitan plant genus Euphorbia. We use a combination of state-of-the-art computational mass spectral metabolomics tools together with cell-based high-throughput immunomodulatory testing. Our results show significant differences in specialized metabolite diversity across geographically separated phylogenetic clades. Chemical structural diversity of the highly toxic Euphorbia diterpenoids is significantly reduced in species native to the Americas, compared to Afro-Eurasia. The localization of these compounds to young stems and roots suggest a possible ecological relevance in herbivory defense. This is further supported by reduced immunomodulatory activity in the American subclade as well as herbivore distribution patterns. We conclude that computational mass spectrometric metabolomics coupled with relevant ecological data provide a strong tool for exploring plant specialized metabolite diversity in a chemo-evolutionary framework.

Growth rate of quantum knot mosaics

Since the Jones polynomial was discovered, the connection between knot theory and quantum physics has been of great interest. Knot mosaic theory was introduced by Lomonaco and Kauffman in the paper ‘Quantum knots and mosaics’ to give a precise and workable definition of quantum knots, intended to represent an actual physical quantum system. This paper is inspired by an open question about the knot mosaic enumeration suggested by them. A knot (m, n)-mosaic is an $$m \times n$$ array of 11 mosaic tiles representing a knot or a link diagram by adjoining properly. The total number $$D_{m,n}$$ of knot (m, n)-mosaics, which indicates the dimension of the Hilbert space of the quantum knot system, is known to grow in a quadratic exponential rate. Recently, the first author showed the existence of the knot mosaic constant $$\delta = \lim _{m, n \rightarrow \infty } (D_{m,n})^{\frac{1}{mn}}$$ and proved $$4 \le \delta \le \frac{5+ \sqrt{13}}{2} = 4.302\cdots $$ by developing an algorithm producing the exact enumeration of knot mosaics, which uses a recursion formula of state matrices. In this paper, we give a simpler proof of the lower bound and improve the upper bound of the knot mosaic constant as $$\begin{aligned} 4 \le \delta \le 4.113\cdots \end{aligned}$$by introducing two new concepts: quasimosaics and cling mosaics.

Geographic mosaic theory of coevolution in plant and pollinator interaction: Process, evidence, prospect

Coevolution refers to evolutionary changes in the traits of two or more interacting species caused by reciprocal natural selection. Geographic mosaic theory of coevolution (GMC) proposes that the dynamics of coevolution between pairs or group of species often occur at different geographic scales. There are three hypotheses on the coevolutionary process. (1) Different evolutionary interaction trajectories among populations are likely to generate a selection mosaic. (2) A mixture of coevolutionary hotspots and coldspots. Hot spots are the subset of communities in which much of the coevolutionary change occurs and coldspots refer to areas where coevolutionary selection hardly occurs or completely does not occur. (3) There is a continual population remixing of the range of coevolving traits, resulting from the selection mosaic, coevolutionary hotspots, gene flow, random genetic drift, and local extinction of subpopulations. Studies of GMC between plants and pollinators indicate that shifts of effective pollinators among different geographic populations may cause divergence in floral traits (i.e., pollination ecotype). Changes of pollinator assemblages or species components have been illustrated coevolving with floral morphology or reward among populations from different altitudes or habitats. Here, recent case studies of GMC between plants and pollinators are grouped into five categories: Floral morphology and pollinator components, corolla tube/nectar spur and pollinator feeding structure, floral color, floral scents, floral rewards and pollinator assemblages. Floral tube or nectar spur length is positively related to pollinator body structures, such as the proboscis and leg length. The adaptation of flower color and pollinator vision provides a series of examples for the GMC. With the increase of altitude, flower color changed from blue and ultraviolet blue adapted to bee vision to blue-green and green adapted to fly vision. Recent study indicated that the difference in cycad odor components related to a shift of beetle species in different regions, suggesting a potential coevolutionary relationship between flower odor and pollinators. Studies showed that where bees foraged more nectar, flowers secreted more nectar, suggesting that floral reward amounts and types coevolve with pollinators among different geographic populations. An examination of GMC in plant-pollinator interactions involves three steps in general: (1) Detection of the relationship between floral traits and pollinator shift or body structure. (2) Transplanting experiments to detect differences in seed set between native phenotypes and transplanted phenotypes. (3) Single pollinator visit experiment to detect pollen output differences between native and transplanted phenotypes. Experimental evolutionary biology not only can test whether floral variation is related to pollinator shifts, but also make people aware of the impact of the reduction or loss of pollinators on the evolutionary consequences. To illustrate GMC between plants and pollinators, it is essential to isolate the evolutionary changes in traits caused by biotic factors or abiotic factors in future. It would be highly appreciated if genome scans and analysis are used in further studies to explore the genome-wide patterns of GMC between plants and pollinators.

The development, misuse and evidence of the concept “coevolution”

Natural selection is one of the most important components of organic evolution, while the concept of coevolution proposes that reciprocal selection generated by interacting species could also drive their organic evolution. Formally raised in 1964, the concept of coevolution has extensively developed, but been misused or even abused. Although continuously emerging studies have verified that some ecological interactions are indeed coevolution, queries of whether it is an acceptable concept remain. To clarify the precise use of the concept, we list and re-induce mistakes in using or misunderstanding of coevolution. Here a concise principle for correct usage is suggested, i.e. confirming three aspects: species interaction, reciprocal selection as well as co-phylogenesis. Bibliometric methods are applied to quantify the development of the coevolution concept, showing the bursting expansion of the term “coevolution” into study fields beyond evolutionary biology, and revealing that current usage of “coevolution” still remains within a reasonable range. Currently, studies of ecological interactions are commonly considered as in the coevolution field. Differences and commonsense of the other six related terms, namely coadaptation, cooperation, interaction, interplay, mutualism and symbiosis, are briefly discussed. Finally, case studies of frontier topics of coevolution, geographic mosaic theory of coevolution, are introduced. A better understanding of the coevolution concept could be achieved if misuse or abuse is avoided. This paper may provide references for future coevolution studies.

Ant behaviour and brain gene expression of defending hosts depend on the ecological success of the intruding social parasite.

The geographical mosaic theory of coevolution predicts that species interactions vary between locales. Depending on who leads the coevolutionary arms race, the effectivity of parasite attack or host defence strategies will explain parasite prevalence. Here, we compare behaviour and brain transcriptomes of Temnothorax longispinosus ant workers when defending their nest against an invading social parasite, the slavemaking ant Temnothorax americanus. A full-factorial design allowed us to test whether behaviour and gene expression are linked to parasite pressure on host populations or to the ecological success of parasite populations. Albeit host defences had been shown before to covary with local parasite pressure, we found parasite success to be much more important. Our chemical and behavioural analyses revealed that parasites from high prevalence sites carry lower concentrations of recognition cues and are less often attacked by hosts. This link was further supported by gene expression analysis. Our study reveals that host-parasite interactions are strongly influenced by social parasite strategies, so that variation in parasite prevalence is determined by parasite traits rather than the efficacy of host defence. Gene functions associated with parasite success indicated strong neuronal responses in hosts, including long-term changes in gene regulation, indicating an enduring impact of parasites on host behaviour. This article is part of the theme issue 'The coevolutionary biology of brood parasitism: from mechanism to pattern'.

On the Meaning of “Coevolution” in Social-Ecological Studies

Researchers studying linked Social-Ecological Systems (SESs) often use the notion of coevolution in describing the relation between humans and the rest of nature. However, most descriptions of the concept of socio-ecological coevolution remain elusive and poorly articulated. The objective of the following paper is to further specify and enrich the meaning of “coevolution” in social-ecological studies. After a critical analysis of two accounts of coevolution in ecological economics, the paper uses the frameworks of Niche Construction Theory and the Geographic Mosaic Theory to define social-ecological coevolution as the reciprocal adaptation of human-social and ecological ensembles through human and ecological niche construction activities. In sum, this conceptual analysis suggests that an ecologization of Darwinian coevolution can bring clarity to profound functional integration that takes place between humans and ecological systems, and at the same time opens fruitful avenues for social-ecological research.

Polygenic Adaptation Underlies Evolution of Brain Structures and Behavioral Traits

Many of the characteristics of psychiatric disorders, including their early age of onset, moderate to high prevalence (i.e., 1% for schizophrenia, >15% for major depression), reduced fecundity, and high heritability have led many to speculate on how risk alleles have persisted throughout evolutionary history. While several potential mechanisms for maintaining high allele frequency of risk variants have been hypothesized (e.g., weak positive selection, balancing selection), few have been empirically tested. Given the recent analytic advancements in detecting polygenic adaptation, we systematically evaluated evidence for selection across a total of twenty-five complex traits including ten neuropsychiatric disorders, three personality traits, total intracranial volume, seven subcortical brain structure volume traits, and four complex traits with no known neuropsychiatric associations. We tested each set of trait-associated variants for evidence of classical hard sweeps (i.e., extreme integrated haplotype scores, iHS), partial sweeps (i.e., extreme population differentiation, Fst), rapid evolution since divergence from Neanderthal (i.e., Neanderthal depletion score, NDS), ancient polygenic selection (i.e., Qx scores), and very recent polygenic selection within the past 2,000 years (i.e., trait singleton density scores, tSDS). Variants associated with schizophrenia (Qx = 208.36, p < 0.001), extraversion (Qx = 88.04, p = 0.001), subjective well-being (Qx = 113.90, p < 0.001), hippocampus volume (Qx = 108.98, p < 0.001), and putamen volume (Qx = 115.76, p < 0.001) were enriched for signatures of weak polygenic adaptation after accounting for genetic drift. However, a limitation of this approach is that the null model of neutral drift is computed with respect to ancestral and derived allelic annotations, therefore it is not possible to determine whether polygenic adaptation has favored risk/trait-increasing alleles or protective/trait-decreasing alleles. Thus, we also employed a directional test of selection (tSDS) which overcomes this limitation. Remarkably, tSDS is powered to detect very recent selection that has been active only in the past ~2,000 years. Here, we find that signatures of recent polygenic adaptation are enriched among SCZ-protective alleles (Z=-3.06, p=0.002) total intracranial volume-increasing alleles (Z=3.09, p = 0.002), but putamen (Z=-4.93, p < 0.001), amygdala (Z=-3.49, p<0.001) and pallidum (Z=-3.39, p<0.001) volume-decreasing alleles. These results provide the first genome-wide genetic evidence in support of the mosaic theory of brain evolution in humans, suggesting that individual brain regions can evolve and vary in size independent of one another. No trait studied displayed significant consistent evidence of classical hard sweeps or partial sweeps. To characterize the biological processes and functional elements potentially targeted by polygenic adaptation, we conducted expression Quantitative Trait Locus (eQTL) and gene set enrichment analyses. SNPs associated with schizophrenia were enriched for eQTLs in brain (p = 0.007) while immune eQTLs were overrepresented among putamen (p = 0.001) and intracranial volume (p = 0.001) associated variants. Our results suggest that alleles associated with behavioral and brain structure volume traits have experienced polygenic adaptation acting through neurodevelopmental and immune-mediated pathways.

Feedbacks link ecosystem ecology and evolution across spatial and temporal scales: Empirical evidence and future directions

Abstract Unifying ecosystem ecology and evolutionary biology promises a more complete understanding of the processes that link different levels of biological organization across space and time. Feedbacks across levels of organization link theory associated with eco‐evolutionary dynamics, niche construction and the geographic mosaic theory of co‐evolution. We describe a conceptual model, which builds upon previous work that shows how feedback among different levels of biological organization can link ecosystem and evolutionary processes over space and time. We provide empirical examples across terrestrial and aquatic systems that indicate broad generality of the conceptual framework and discuss its macroevolutionary consequences. Our conceptual model is based on three premises: genetically based species interactions can vary spatially and temporally from positive to neutral (i.e. no net feedback) to negative and drive evolutionary change; this evolutionary change can drive divergence in niche construction and ecosystem function; and lastly, such ecosystem‐level effects can reinforce spatiotemporal variation in evolutionary dynamics. Just as evolution can alter ecosystem function locally and across the landscape differently, variation in ecosystem processes can drive evolution locally and across the landscape differently. By highlighting our current knowledge of eco‐evolutionary feedbacks in ecosystems, as well as information gaps, we provide a foundation for understanding the interplay between biodiversity and ecosystem function through an eco‐evolutionary lens. A plain language summary is available for this article.

The geographic mosaic of coevolution in mutualistic networks

Ecological interactions shape adaptations through coevolution not only between pairs of species but also through entire multispecies assemblages. Local coevolution can then be further altered through spatial processes that have been formally partitioned in the geographic mosaic theory of coevolution. A major current challenge is to understand the spatial patterns of coadaptation that emerge across ecosystems through the interplay between gene flow and selection in networks of interacting species. Here, we combine a coevolutionary model, network theory, and empirical information on species interactions to investigate how gene flow and geographical variation in selection affect trait patterns in mutualistic networks. We show that gene flow has the surprising effect of favoring trait matching, especially among generalist species in species-rich networks typical of pollination and seed dispersal interactions. Using an analytical approximation of our model, we demonstrate that gene flow promotes trait matching by making the adaptive landscapes of different species more similar to each other. We use this result to show that the progressive loss of gene flow associated with habitat fragmentation may undermine coadaptation in mutualisms. Our results therefore provide predictions of how spatial processes shape the evolution of species-rich interactions and how the widespread fragmentation of natural landscapes may modify the coevolutionary process.

Evolutionary Responses to Conditionality in Species Interactions across Environmental Gradients.

The outcomes of many species interactions are conditional on the environments in which they occur. Often, interactions grade from being more positive under stressful or low-resource conditions to more antagonistic or neutral under benign conditions. Here, we take predictions about two well-supported ecological theories on conditionality-limiting resource models and the stress-gradient hypothesis-and combine them with those from the geographic mosaic theory of coevolution (GMTC) to generate predictions for systematic patterns of adaptation and coadaptation between partners along abiotic gradients. When interactions become more positive in stressful environments, mutations that increase fitness in one partner may also increase fitness in the other; because fitnesses are aligned, selection should favor greater mutualistic adaptation and coadaptation between interacting species in stressful ends of environmental gradients. As a corollary, in benign environments antagonistic coadaptation could result in Red Queen or arms-race dynamics or the reduction of antagonism through character displacement and niche partitioning. Here, we distinguish between generally mutualistic or antagonistic adaptation (i.e., mutations in one partner that have similar effects across multiple populations of the other) and specific adaptations to sympatric partners (local adaptation), which can occur either alone or simultaneously. We then outline the kinds of data required to test these predictions, develop experimental designs and statistical methods, and demonstrate these using simulations based on GMTC models. Our methods can be applied to a range of conditional outcomes and may also be useful in assisted translocation approaches in the face of climate change.

43 森林モザイク論（特集 林業技術問題(XIX)）

43 森林モザイク論（特集 林業技術問題(XIX)）

Mosaic Theory and Cyberharassment: Using Privacy Principles to Clarify the Law of Digital Harms and Free Speech

The Supreme Court of the United States, in the 2012 case United States v. Jones, laid a jurisprudential foundation for using mosaic theory to identify and address harms caused when innocuous bits of information are aggregated and used to invade the privacy of a targeted individual. Although mosaic theory has been applied almost exclusively in Fourth Amendment privacy cases, information mosaics can be used to facilitate online harassment. However, courts have not articulated frameworks for recognizing informational harms caused by mosaics. Additionally, although state cyberharassment laws exempt constitutionally protected informational uses from prosecution, neither state legislatures nor courts have articulated the extent of such protected activities in the cyberharassment context. Mosaic theory provides a useful theoretical and heuristic lens for understanding the limits of informational uses and harms in the cyberharassment context. Using the lens of mosaic theory, this article explores the ways information mosaics can be used to harass targeted individuals. The article concludes that states should pursue incremental modifications to their cyberharassment laws to address the harms caused by persistent, intentional, targeted uses of information mosaics against targets and that they better articulate frameworks for understanding which information-sharing activities are exempt from prosecution.

Gut Microbiota: Potential for a Unifying Hypothesis for Prevention and Treatment of Hypertension.

Despite major advances in pharmacological and device-based therapies, systemic hypertension (HTN) continues to be the major, modifiable risk factor for most cardiovascular disease and a leading cause of morbidity and mortality. Treatment resistant HTN (RH) is present in ≈15% to 20% of hypertensive patients, with few treatment options. These facts provide an opportunity to develop novel hypotheses to advance this field. Over 60 years ago, Irvine Page1 proposed a mosaic theory where interplay of multiple factors integrate to increase blood pressure (BP). This fostered establishment of cellular, molecular, and physiological mechanisms altered in HTN. However, how these diverse factors integrate to impair BP control remains a challenge. Furthermore, why some factors are prohypertensive in one individual and not in another, and where prohypertensive signals originate, remains an enigma. In this Viewpoint, we propose that the gut and gut microbiota could be one missing link and provide a potential unifying concept. We summarize most recent evidence for involvement of gut microbiota in BP control and HTN. We present our thoughts on the current state and relevant knowledge gaps to be addressed to determine whether targeting gut microbiota and related pathology would be a next frontier in HTN therapeutics. Gut dysbiosis and microbial functions contribute to pathological effects beyond the gastrointestinal system. Gut microbiota play a role in BP regulation, and gut dysbiosis has been observed in multiple animal models of HTN.2–5 Our group was among the first to document HTN-associated gut dysbiosis and an increased Firmicutes/Bacteroidetes ratio.2,3 This was associated with a decrease in acetate- and butyrate-producing bacteria and an increase in the lactate-producing bacteria. High-fiber diet and acetate supplementation correct gut dysbiosis, increase the abundance of acetate-producing bacteria, and are associated with lower BP in DOCA-salt mice.5 Stroke-prone spontaneously hypertensive rats exhibit …

Period and toroidal knot mosaics

Knot mosaic theory was introduced by Lomonaco and Kauffman in the paper on ‘Quantum knots and mosaics’ to give a precise and workable definition of quantum knots, intended to represent an actual physical quantum system. A knot [Formula: see text]-mosaic is an [Formula: see text] matrix whose entries are eleven mosaic tiles, representing a knot or a link by adjoining properly. In this paper, we introduce two variants of knot mosaics: period knot mosaics and toroidal knot mosaics, which are common features in physics and mathematics. We present an algorithm producing the exact enumeration of period knot [Formula: see text]-mosaics for any positive integers [Formula: see text] and [Formula: see text], toroidal knot [Formula: see text]-mosaics for co-prime integers [Formula: see text] and [Formula: see text], and furthermore toroidal knot [Formula: see text]-mosaics for a prime number [Formula: see text]. We also analyze the asymptotics of the growth rates of their cardinality.