On the origin of mitochondria: a multilayer network approach.

Backgound: The endosymbiotic theory is widely accepted to explain the origin of mitochondria from a bacterial ancestor. While ample evidence supports the intimate connection of Alphaproteobacteria to the mitochondrial ancestor, pinpointing its closest relative within sampled Alphaproteobacteria is still an open evolutionary debate. Many different phylogenetic methods and approaches have been used to answer this challenging question, further compounded by the heterogeneity of sampled taxa, varying evolutionary rates of mitochondrial proteins, and the inherent biases in each method, all factors that can produce phylogenetic artifacts. By harnessing the simplicity and interpretability of protein similarity networks, herein we re-evaluated the origin of mitochondria within an enhanced multilayer framework, which is an extension and improvement of a previously developed method. Methods: We used a dataset of eight proteins found in mitochondria (N = 6 organisms) and bacteria (N = 80 organisms). The sequences were aligned and resulting identity matrices were combined to generate an eight-layer multiplex network. Each layer corresponded to a protein network, where nodes represented organisms and edges were placed following mutual sequence identity. The Multi-Newman-Girvan algorithm was applied to evaluate community structure, and bifurcation events linked to network partition allowed to trace patterns of divergence between studied taxa. Results: In our network-based analysis, we first examined the topology of the 8-layer multiplex when mitochondrial sequences disconnected from the main alphaproteobacterial cluster. The resulting topology lent firm support toward an Alphaproteobacteria-sister placement for mitochondria, reinforcing the hypothesis that mitochondria diverged from the common ancestor of all Alphaproteobacteria. Additionally, we observed that the divergence of Rickettsiales was an early event in the evolutionary history of alphaproteobacterial clades. Conclusion: By leveraging complex networks methods to the challenging question of circumscribing mitochondrial origin, we suggest that the entire Alphaproteobacteria clade is the closest relative to mitochondria (Alphaproteobacterial-sister hypothesis), echoing recent findings based on different datasets and methodologies.

Biological taxon names are descriptive names.

The so-called 'type method' widely employed in biological taxonomy is often seen as conforming to the causal-historical theory of reference. In this paper, I argue for an alternative account of reference for biological nomenclature in which taxon names are understood as descriptive names (the 'DN account'). A descriptive name, as the concept came to be known from the work of Gareth Evans, is a referring expression introduced by a definite description. There are three main differences between the DN and the causal account. First, according to the DN account, rather than fixing a name to a referent, the assignment of a type specimen to serve as the name-bearer for a taxon should be seen as performatively establishing a synonymy between a name and a definite description of the form "the taxon whose type is t". Each taxon name is therefore associated with a criterion of application, a semantic rule that establishes the connection between the name and the descriptive content. This is the second major difference from the causal account: taxon names do have some descriptive content associated with them. The final locus of dissent concerns the strength of the modality resulting from the usage of taxon names. In order to address this point, I use the DN account to focus on the debate between Matt Haber and Joeri Witteveen concerning misidentification of type specimens, misapplication of names, and the truth conditions of Joseph LaPorte's de dicto necessary sentence "Necessarily, any species with a type specimen contains its type specimen". Using a pragmatic variant of the distinction between attributive and referential uses of descriptions, I argue that a metalinguistic version of the de dicto sentence is in fact falsified, as previously argued by Haber.

Comparison of complex networks and tree-based methods of phylogenetic analysis and proposal of a bootstrap method.

Complex networks have been successfully applied to the characterization and modeling of complex systems in several distinct areas of Biological Sciences. Nevertheless, their utilization in phylogenetic analysis still needs to be widely tested, using different molecular data sets and taxonomic groups, and, also, by comparing complex networks approach to current methods in phylogenetic analysis. In this work, we compare all the four main methods of phylogenetic analysis (distance, maximum parsimony, maximum likelihood, and Bayesian) with a complex networks method that has been used to provide a phylogenetic classification based on a large number of protein sequences as those related to the chitin metabolic pathway and ATP-synthase subunits. In order to perform a close comparison to these methods, we selected Basidiomycota fungi as the taxonomic group and used a high-quality, manually curated and characterized database of chitin synthase sequences. This enzymatic protein plays a key role in the synthesis of one of the exclusive features of the fungal cell wall: the presence of chitin. The communities (modules) detected by the complex network method corresponded exactly to the groups retrieved by the phylogenetic inference methods. Additionally, we propose a bootstrap method for the complex network approach. The statistical results we have obtained with this method were also close to those obtained using traditional bootstrap methods.

Classificações interativas: o caso do Transtorno de Déficit de Atenção com Hiperatividade infantil / Interactive classifications: the case of Attention-Deficit Hyperactivity Disorder in children / Clasificaciones interactivas: el caso del Trastorno de Déficit de Atención con Hiper-actividad infantil

O filósofo da ciência Ian Hacking diz que nosso mundo é um mundo de classificações e que essas classificações têm efeitos particulares quando se referem a comportamentos de pessoas. Neste trabalho, pretende-se discutir como o diagnóstico do Transtorno de Déficit de Atenção com Hiperatividade (TDAH) infantil pode funcionar como uma classificação e, assim, afetar o comportamento das crianças diagnosticadas. Inicialmente, é realizada uma discussão sobre a função das classificações na ciência. A partir dessas considerações, um modelo mais geral sobre a interação entre classificações e classificados é proposto, tendo como base a distinção de Ian Hacking entre tipos indiferentes e tipos interativos, e também a noção de efeito de arco proposta por esse autor. Por fim, o modelo é aplicado ao TDAH, onde são realizadas considerações relacionadas às noções de controle social de Peter Conrad.

The philosopher of science Ian Hacking writes that our world is one of classifications, and these classifications, or names, have a particular effect when they refer to the behavior of people. This article seeks to present what Attention-Deficit Hyperactivity Disorder (ADHD) is and how it appeared in children. Then, it discusses the conversion of undesirable behaviors into symptoms which underlies the identification of ADHD as a disease. From these considerations, a more general model about the interaction between classifications and classified people is proposed, based on Hacking's distinction between indifferent and interactive kinds, and also on the concept of looping effect proposed by that author. Finally, the model is applied to ADHD, and some considerations are made regarding the concept of social control put forth by Peter Conrad.

El filósofo de la ciencia Ian Hacking dice que nuestro mundo es un mundo de clasificaciones y que estas clasificaciones tienen efectos particulares cuando se refieren comportamientos de personas. En este trabajo se pretende discutir como el diagnóstico del Trastorno de Déficit de Atención con Hiper-actividad (TDAH) infantil puede funcionar como una clasificación y así afectar el comportamiento de los niños diagnosticados. Inicialmente se realiza una discusión sobre la función de las clasificaciones en la ciencia. A partir de estas consideraciones un modelo más general sobre la interacción entre clasificaciones y clasificados se propone con base en la distinción de Ian Hacking entre tipos indiferentes e tipos interactivos así como también la noción de efecto de arco propuesta por este autor. Por fin el modelo se aplica al TDAH donde se realizan consideraciones relacionadas a las nociones de control social de Peter Conrad.