Aristotle’s assertoric syllogistic and modern relevance logic

This paper sets out to evaluate the claim that Aristotle’s Assertoric Syllogistic is a relevance logic or shows significant similarities with it. I prepare the grounds for a meaningful comparison by extracting the notion of relevance employed in the most influential work on modern relevance logic, Anderson and Belnap’s Entailment. This notion is characterized by two conditions imposed on the concept of validity: first, that some meaning content is shared between the premises and the conclusion, and second, that the premises of a proof are actually used to derive the conclusion. Turning to Aristotle’s Prior Analytics, I argue that there is evidence that Aristotle’s Assertoric Syllogistic satisfies both conditions. Moreover, Aristotle at one point explicitly addresses the potential harmfulness of syllogisms with unused premises. Here, I argue that Aristotle’s analysis allows for a rejection of such syllogisms on formal grounds established in the foregoing parts of the Prior Analytics. In a final section I consider the view that Aristotle distinguished between validity on the one hand and syllogistic validity on the other. Following this line of reasoning, Aristotle’s logic might not be a relevance logic, since relevance is part of syllogistic validity and not, as modern relevance logic demands, of general validity. I argue that the reasons to reject this view are more compelling than the reasons to accept it and that we can, cautiously, uphold the result that Aristotle’s logic is a relevance logic

Anchored enrichment dataset for true flies (order Diptera) reveals insights into the phylogeny of flower flies (family Syrphidae)

Background: Anchored hybrid enrichment is a form of next-generation sequencing that uses oligonucleotide probes to target conserved regions of the genome flanked by less conserved regions in order to acquire data useful for phylogenetic inference from a broad range of taxa. Once a probe kit is developed, anchored hybrid enrichment is superior to traditional PCR-based Sanger sequencing in terms of both the amount of genomic data that can be recovered and effective cost. Due to their incredibly diverse nature, importance as pollinators, and historical instability with regard to subfamilial and tribal classification, Syrphidae (flower flies or hoverflies) are an ideal candidate for anchored hybrid enrichment-based phylogenetics, especially since recent molecular phylogenies of the syrphids using only a few markers have resulted in highly unresolved topologies. Over 6200 syrphids are currently known and uncovering their phylogeny will help us to understand how these species have diversified, providing insight into an array of ecological processes, from the development of adult mimicry, the origin of adult migration, to pollination patterns and the evolution of larval resource utilization. Results: We present the first use of anchored hybrid enrichment in insect phylogenetics on a dataset containing 30 flower fly species from across all four subfamilies and 11 tribes out of 15. To produce a phylogenetic hypothesis, 559 loci were sampled to produce a final dataset containing 217,702 sites. We recovered a well resolved topology with bootstrap support values that were almost universally >95 %. The subfamily Eristalinae is recovered as paraphyletic, with the strongest support for this hypothesis to date. The ant predators in the Microdontinae are sister to all other syrphids. Syrphinae and Pipizinae are monophyletic and sister to each other. Larval predation on soft-bodied hemipterans evolved only once in this family. Conclusions: Anchored hybrid enrichment was successful in producing a robustly supported phylogenetic hypothesis for the syrphids. Subfamilial reconstruction is concordant with recent phylogenetic hypotheses, but with much higher support values. With the newly designed probe kit this analysis could be rapidly expanded with further sampling, opening the door to more comprehensive analyses targeting problem areas in syrphid phylogenetics and ecology.Peer reviewe

Exact model reduction of combinatorial reaction networks

Receptors and scaffold proteins usually possess a high number of distinct binding domains inducing the formation of large multiprotein signaling complexes. Due to combinatorial reasons the number of distinguishable species grows exponentially with the number of binding domains and can easily reach several millions. Even by including only a limited number of components and binding domains the resulting models are very large and hardly manageable. A novel model reduction technique allows the significant reduction and modularization of these models

Mutations in or near the Transmembrane Domain Alter PMEL Amyloid Formation from Functional to Pathogenic

PMEL is a pigment cell-specific protein that forms physiological amyloid fibrils upon which melanins ultimately deposit in the lumen of the pigment organelle, the melanosome. Whereas hypomorphic PMEL mutations in several species result in a mild pigment dilution that is inherited in a recessive manner, PMEL alleles found in the Dominant white (DW) chicken and Silver horse (HoSi)—which bear mutations that alter the PMEL transmembrane domain (TMD) and that are thus outside the amyloid core—are associated with a striking loss of pigmentation that is inherited in a dominant fashion. Here we show that the DW and HoSi mutations alter PMEL TMD oligomerization and/or association with membranes, with consequent formation of aberrantly packed fibrils. The aberrant fibrils are associated with a loss of pigmentation in cultured melanocytes, suggesting that they inhibit melanin production and/or melanosome integrity. A secondary mutation in the Smoky chicken, which reverts the dominant DW phenotype, prevents the accumulation of PMEL in fibrillogenic compartments and thus averts DW–associated pigment loss; a secondary mutation found in the Dun chicken likely dampens a HoSi–like dominant mutation in a similar manner. We propose that the DW and HoSi mutations alter the normally benign amyloid to a pathogenic form that antagonizes melanosome function, and that the secondary mutations found in the Smoky and Dun chickens revert or dampen pathogenicity by functioning as null alleles, thus preventing the formation of aberrant fibrils. We speculate that PMEL mutations can model the conversion between physiological and pathological amyloid

MetaPIGA v2.0: maximum likelihood large phylogeny estimation using the metapopulation genetic algorithm and other stochastic heuristics

<p>Abstract</p> <p>Background</p> <p>The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most comparative studies involving molecular sequences. Still, the choice of a phylogeny inference software is often dictated by a combination of parameters not related to the raw performance of the implemented algorithm(s) but rather by practical issues such as ergonomics and/or the availability of specific functionalities.</p> <p>Results</p> <p>Here, we present MetaPIGA v2.0, a robust implementation of several stochastic heuristics for large phylogeny inference (under maximum likelihood), including a Simulated Annealing algorithm, a classical Genetic Algorithm, and the Metapopulation Genetic Algorithm (metaGA) together with complex substitution models, discrete Gamma rate heterogeneity, and the possibility to partition data. MetaPIGA v2.0 also implements the Likelihood Ratio Test, the Akaike Information Criterion, and the Bayesian Information Criterion for automated selection of substitution models that best fit the data. Heuristics and substitution models are highly customizable through manual batch files and command line processing. However, MetaPIGA v2.0 also offers an extensive graphical user interface for parameters setting, generating and running batch files, following run progress, and manipulating result trees. MetaPIGA v2.0 uses standard formats for data sets and trees, is platform independent, runs in 32 and 64-bits systems, and takes advantage of multiprocessor and multicore computers.</p> <p>Conclusions</p> <p>The metaGA resolves the major problem inherent to classical Genetic Algorithms by maintaining high inter-population variation even under strong intra-population selection. Implementation of the metaGA together with additional stochastic heuristics into a single software will allow rigorous optimization of each heuristic as well as a meaningful comparison of performances among these algorithms. MetaPIGA v2.0 gives access both to high customization for the phylogeneticist, as well as to an ergonomic interface and functionalities assisting the non-specialist for sound inference of large phylogenetic trees using nucleotide sequences. MetaPIGA v2.0 and its extensive user-manual are freely available to academics at <url>http://www.metapiga.org</url>.</p

Dinosaurs reveal the geographical signature of an evolutionary radiation

Dinosaurs dominated terrestrial ecosystems across the globe for over 100 million years and provide a classic example of an evolutionary radiation. However, little is known about how these animals radiated geographically to become globally distributed. Here, we use a biogeographical model to reconstruct the dinosaurs’ ancestral locations, revealing the spatial mechanisms that underpinned this 170-million-year-long radiation. We find that dinosaurs spread rapidly initially, followed by a significant continuous and gradual reduction in their speed of movement towards the Cretaceous/Tertiary boundary (66 million years ago). This suggests that the predominant mode of dinosaur speciation changed through time with speciation originally largely driven by geographical isolation—when dinosaurs speciated more, they moved further. This was gradually replaced by increasing levels of sympatric speciation (species taking advantage of ecological opportunities within their existing environment) as terrestrial space became a limiting factor. Our results uncover the geographical signature of an evolutionary radiation

A Passerine Bird's Evolution Corroborates the Geologic History of the Island of New Guinea

New Guinea is a biologically diverse island, with a unique geologic history and topography that has likely played a role in the evolution of species. Few island-wide studies, however, have examined the phylogeographic history of lowland species. The objective of this study was to examine patterns of phylogeographic variation of a common and widespread New Guinean bird species (Colluricincla megarhyncha). Specifically, we test the mechanisms hypothesized to cause geographic and genetic variation (e.g., vicariance, isolation by distance and founder-effect with dispersal). To accomplish this, we surveyed three regions of the mitochondrial genome and a nuclear intron and assessed differences among 23 of the 30 described subspecies from throughout their range. We found support for eight highly divergent lineages within C. megarhyncha. Genetic lineages were found within continuous lowland habitat or on smaller islands, but all individuals within clades were not necessarily structured by predicted biogeographic barriers. There was some evidence of isolation by distance and potential founder-effects. Mitochondrial DNA sequence divergence among lineages was at a level often observed among different species or even genera of birds (5–11%), suggesting lineages within regions have been isolated for long periods of time. When topographical barriers were associated with divergence patterns, the estimated divergence date for the clade coincided with the estimated time of barrier formation. We also found that dispersal distance and range size are positively correlated across lineages. Evidence from this research suggests that different phylogeographic mechanisms concurrently structure lineages of C. megarhyncha and are not mutually exclusive. These lineages are a result of evolutionary forces acting at different temporal and spatial scales concordant with New Guinea's geological history

Long-Branch Attraction Bias and Inconsistency in Bayesian Phylogenetics

Bayesian inference (BI) of phylogenetic relationships uses the same probabilistic models of evolution as its precursor maximum likelihood (ML), so BI has generally been assumed to share ML's desirable statistical properties, such as largely unbiased inference of topology given an accurate model and increasingly reliable inferences as the amount of data increases. Here we show that BI, unlike ML, is biased in favor of topologies that group long branches together, even when the true model and prior distributions of evolutionary parameters over a group of phylogenies are known. Using experimental simulation studies and numerical and mathematical analyses, we show that this bias becomes more severe as more data are analyzed, causing BI to infer an incorrect tree as the maximum a posteriori phylogeny with asymptotically high support as sequence length approaches infinity. BI's long branch attraction bias is relatively weak when the true model is simple but becomes pronounced when sequence sites evolve heterogeneously, even when this complexity is incorporated in the model. This bias—which is apparent under both controlled simulation conditions and in analyses of empirical sequence data—also makes BI less efficient and less robust to the use of an incorrect evolutionary model than ML. Surprisingly, BI's bias is caused by one of the method's stated advantages—that it incorporates uncertainty about branch lengths by integrating over a distribution of possible values instead of estimating them from the data, as ML does. Our findings suggest that trees inferred using BI should be interpreted with caution and that ML may be a more reliable framework for modern phylogenetic analysis

Millipede taxonomy after 250 years: classification and taxonomic practices in a mega-diverse yet understudied arthropod group.

BACKGROUND: The arthropod class Diplopoda is a mega-diverse group comprising >12,000 described millipede species. The history of taxonomic research within the group is tumultuous and, consequently, has yielded a questionable higher-level classification. Few higher-taxa are defined using synapomorphies, and the practice of single taxon descriptions lacking a revisionary framework has produced many monotypic taxa. Additionally, taxonomic and geographic biases render global species diversity estimations unreliable. We test whether the ordinal taxa of the Diplopoda are consistent with regards to underlying taxonomic diversity, attempt to provide estimates for global species diversity, and examine millipede taxonomic effort at a global geographic scale. METHODOLOGY/PRINCIPAL FINDINGS: A taxonomic distinctness metric was employed to assess uniformity of millipede ordinal taxa. We found that ordinal-level taxa are not uniform and are likely overinflated with higher-taxa when compared to related groups. Several methods of estimating global species richness were employed (Bayesian, variation in taxonomic productivity, extrapolation from nearly fully described taxa). Two of the three methods provided estimates ranging from 13,413-16,760 species. Variations in geographic diversity show biases to North America and Europe and a paucity of works on tropical taxa. CONCLUSIONS/SIGNIFICANCE: Before taxa can be used in an extensible way, they must be definable with respect to the diversity they contain and the diagnostic characters used to delineate them. The higher classification for millipedes is shown to be problematic from a number of perspectives. Namely, the ordinal taxa are not uniform in their underlying diversity, and millipedes appear to have a disproportionate number of higher-taxa. Species diversity estimates are unreliable due to inconsistent taxonomic effort at temporal, geographic, and phylogenetic scales. Lack of knowledge concerning many millipede groups compounds these issues. Diplopods are likely not unique in this regard as these issues may persist in many other diverse yet poorly studied groups