Optimization techniques in respiratory control system models

One of the most complex physiological systems whose modeling is still an open study is the respiratory control system where different models have been proposed based on the criterion of minimizing the work of breathing (WOB). The aim of this study is twofold: to compare two known models of the respiratory control system which set the breathing pattern based on quantifying the respiratory work; and to assess the influence of using direct-search or evolutionary optimization algorithms on adjustment of model parameters. This study was carried out using experimental data from a group of healthy volunteers under CO2 incremental inhalation, which were used to adjust the model parameters and to evaluate how much the equations of WOB follow a real breathing pattern. This breathing pattern was characterized by the following variables: tidal volume, inspiratory and expiratory time duration and total minute ventilation. Different optimization algorithms were considered to determine the most appropriate model from physiological viewpoint. Algorithms were used for a double optimization: firstly, to minimize the WOB and secondly to adjust model parameters. The performance of optimization algorithms was also evaluated in terms of convergence rate, solution accuracy and precision. Results showed strong differences in the performance of optimization algorithms according to constraints and topological features of the function to be optimized. In breathing pattern optimization, the sequential quadratic programming technique (SQP) showed the best performance and convergence speed when respiratory work was low. In addition, SQP allowed to implement multiple non-linear constraints through mathematical expressions in the easiest way. Regarding parameter adjustment of the model to experimental data, the evolutionary strategy with covariance matrix and adaptation (CMA-ES) provided the best quality solutions with fast convergence and the best accuracy and precision in both models. CMAES reached the best adjustment because of its good performance on noise and multi-peaked fitness functions. Although one of the studied models has been much more commonly used to simulate respiratory response to CO2 inhalation, results showed that an alternative model has a more appropriate cost function to minimize WOB from a physiological viewpoint according to experimental data.Postprint (author's final draft

Multiple independent origins of auto-pollination in tropical orchids (Bulbophyllum) in light of the hypothesis of selfing as an evolutionary dead end

Background: The transition from outcrossing to selfing has long been portrayed as an ‘evolutionary dead end because, first, reversals are unlikely and, second, selfing lineages suffer from higher rates of extinction owing to a reduced potential for adaptation and the accumulation of deleterious mutations. We tested these two predictions in a clade of Madagascan Bulbophyllum orchids (30 spp.), including eight species where auto-pollinating morphs (i.e., selfers, without a ‘rostellum) co-exist with their pollinator-dependent conspecifics (i.e., outcrossers, possessing a rostellum). Specifically, we addressed this issue on the basis of a time-calibrated phylogeny by means of ancestral character reconstructions and within the state-dependent evolution framework of BiSSE (Binary State Speciation and Extinction), which allowed jointly estimating rates of transition, speciation, and extinction between outcrossing and selfing. Results: The eight species capable of selfing occurred in scattered positions across the phylogeny, with two likely originating in the Pliocene (ca. 4.43.1 Ma), one in the Early Pleistocene (ca. 2.4 Ma), and five since the mid-Pleistocene (ca. 1.3 Ma). We infer that this scattered phylogenetic distribution of selfing is best described by models including up to eight independent outcrossing-to-selfing transitions and very low rates of speciation (and either moderate or zero rates of extinction) associated with selfing. Conclusions: The frequent and irreversible outcrossing-to-selfing transitions in Madagascan Bulbophyllum are clearly congruent with the first prediction of the dead end hypothesis. The inability of our study to conclusively reject or support the likewise predicted higher extinction rate in selfing lineages might be explained by a combination of methodological limitations (low statistical power of our BiSSE approach to reliably estimate extinction in small-sized trees) and evolutionary processes (insufficient time elapsed for selfers to go extinct). We suggest that, in these tropical orchids, a simple genetic basis of selfing (via loss of the ‘rostellum) is needed to explain the strikingly recurrent transitions to selfing, perhaps reflecting rapid response to parallel and novel selective environments over Late Quaternary ( 1.3 Ma) time scales.P20726-B03P17124-B0(VLID)243455

Phylogenetic framework for coevolutionary studies: A compass for exploring jungles of tangled trees

Phylogenetics is used to detect past evolutionary events, from how species originated to how their ecological interactions with other species arose, which can mirror cophylogenetic patterns. Cophylogenetic reconstructions uncover past ecological relationships between taxa through inferred coevolutionary events on trees, for example, codivergence, duplication, host-switching, and loss. These events can be detected by cophylogenetic analyses based on nodes and the length and branching pattern of the phylogenetic trees of symbiotic associations, for example, host-parasite. In the past 2 decades, algorithms have been developed for cophylogetenic analyses and implemented in different software, for example, statistical congruence index and event-based methods. Based on the combination of these approaches, it is possible to integrate temporal information into cophylogenetical inference, such as estimates of lineage divergence times between 2 taxa, for example, hosts and parasites. Additionally, the advances in phylogenetic biogeography applying methods based on parametric process models and combined Bayesian approaches, can be useful for interpreting coevolutionary histories in a scenario of biogeographical area connectivity through time. This article briefly reviews the basics of parasitology and provides an overview of software packages in cophylogenetic methods. Thus, the objective here is to present a phylogenetic framework for coevolutionary studies, with special emphasis on groups of parasitic organisms. Researchers wishing to undertake phylogeny-based coevolutionary studies can use this review as a "compass" when "walking" through jungles of tangled phylogenetic trees.Facultad de Ciencias Naturales y Muse

Hiding in plain sight: accounting for rate heterogeneity in trait evolution models

Within the last four decades, phylogenetic comparative methods have become the defacto method of analysis for comparative biologists. The availability of high-quality comparative datasets has been matched by an explosion of possible phylogenetic models. In large part, the efforts to increase the realism of phylogenetic comparative methods has been successful as evidenced by their widespread use. To this extensive literature, my contributions are modest. I have focused my dissertation work on two main themes. First, most phenotypic evolution is not independent of other phenotypes. Changes in a particular character may influence changes in another and modeling these characters in isolation can mislead our inferences. Second, evolutionary change is heterogeneous. Not all species are going to change in the same way at all times and failing to account for that will mislead our inferences. The intersection of these two themes, character dependence and rate heterogeneity, is more natural than it may first appear. This dissertation has four chapters addressing various issues in current phylogenetic comparative methods. In Chapter I, I extend discrete character models to allow for any number of characters with any number of observed or hidden states. In Chapter II, I apply hidden Markov models to the issue of false correlation between discrete character evolution. I demonstrate that allowing for character independent rate heterogeneity through the application of hidden Markov models, is one way to account for this statistical bias. In Chapter III, I develop a new model called hOUwie which detects correlation between discrete and continuous characters and estimates their joint evolution. In Chapter IV, I apply the hOUwie model to 33 clades of angiosperms and attempt to understand the evolutionary patterns of plant life history as it relates to climatic variation

Phylogenetic Relationships and Evolution of Snakes

Snakes represent an impressive evolutionary radiation of over 3,500 widely-distributed species, categorized into 515 genera, encompassing a diverse range of morphologies and ecologies. This diversity is likely attributable to their distinctive morphology, which has allowed them to populate a wide range of habitat types within most major ecosystems. In my first chapter, I provide the largest-yet estimate of the snake tree of life using maximum likelihood on a supermatrix of 1745 taxa (1652 snake species + 7 outgroup taxa) and 9,523 base pairs from 10 loci (5 nuclear, 5 mitochondrial), including previously unsequenced genera (2) and species (61). I then use this phylogeny to test hypotheses regarding heterogeneity in diversification rates and how this shaped overall patterns of snake diversity in Chapter 2. I also used the species-level phylogeny to test the evolution of habitat use in snakes, morphological variation, and whether distantly-related species exhibit morphological convergence in Chapter 3. Finally, in Chapter 4 I investigate how prehensile tails effect striking performance in arboreal snakes