11 research outputs found

    Bird evolution: testing the Metaves clade with six new mitochondrial genomes

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    Background Evolutionary biologists are often misled by convergence of morphology and this has been common in the study of bird evolution. However, the use of molecular data sets have their own problems and phylogenies based on short DNA sequences have the potential to mislead us too. The relationships among clades and timing of the evolution of modern birds (Neoaves) has not yet been well resolved. Evidence of convergence of morphology remain controversial. With six new bird mitochondrial genomes (hummingbird, swift, kagu, rail, flamingo and grebe) we test the proposed Metaves/Coronaves division within Neoaves and the parallel radiations in this primary avian clade. Results Our mitochondrial trees did not return the Metaves clade that had been proposed based on one nuclear intron sequence. We suggest that the high number of indels within the seventh intron of the ÎČ-fibrinogen gene at this phylogenetic level, which left a dataset with not a single site across the alignment shared by all taxa, resulted in artifacts during analysis. With respect to the overall avian tree, we find the flamingo and grebe are sister taxa and basal to the shorebirds (Charadriiformes). Using a novel site-stripping technique for noise-reduction we found this relationship to be stable. The hummingbird/swift clade is outside the large and very diverse group of raptors, shore and sea birds. Unexpectedly the kagu is not closely related to the rail in our analysis, but because neither the kagu nor the rail have close affinity to any taxa within this dataset of 41 birds, their placement is not yet resolved. Conclusion Our phylogenetic hypothesis based on 41 avian mitochondrial genomes (13,229 bp) rejects monophyly of seven Metaves species and we therefore conclude that the members of Metaves do not share a common evolutionary history within the Neoaves

    The impact of fossil calibrations, codon positions and relaxed clocks on the divergence time estimates of the native Australian rodents (Conilurini).

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    The native rodents are the most species-rich placental mammal group on the Australian continent. Fossils of native Australian rodents belonging to the group Conilurini are known from Northern Australia at 4.5Ma. These fossil assemblages already display a rich diversity of rodents, but the exact timing of their arrival on the Australian continent is not yet established. The complete mitochondrial genomes of two native Australian rodents, Leggadina lakedownensis (Lakeland Downs mouse) and Pseudomys chapmani (Western Pebble-mound mouse) were sequenced for investigating their evolutionary history. The molecular data were used for studying the phylogenetic position and divergence times of the Australian rodents, using 12 calibration points and various methods. Phylogenetic analyses place the native Australian rodents as the sister-group to the genus Mus. The Mus-Conilurini calibration point (7.3-11.0Ma) is highly critical for estimating rodent divergence times, while the influence of the different algorithms on estimating divergence times is negligible. The influence of the data type was investigated, indicating that amino acid data are more likely to reflect the correct divergence times than nucleotide sequences. The study on the problems related to estimating divergence times in fast-evolving lineages such as rodents, emphasize the choice of data and calibration points as being critical. Furthermore, it is essential to include accurate calibration points for fast-evolving groups, because the divergence times can otherwise be estimated to be significantly older. The divergence times of the Australian rodents are highly congruent and are estimated to 6.5-7.2Ma, a date that is compatible with their fossil record

    Artificiella neurala nÀtverk underlÀttar svÄra medicinska beslut. Exempel frÄn pankreatologin.

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    Artificial neural networks (ANNs) is a nonlinear pattern recognition technique inspired by the function of the human brain. ANNs have been used successfully in analysis of complex medical relationships, for example prognostic predictions of various forms of cancer. Acute pancreatitis and pancreatic cancer are commonly recognized to be extremely difficult conditions in making diagnostic and prognostic predictions with traditional methods. The two pancreatic disorders thus represent suitable candidates for analysis by ANNs. We hereby present a systematic review of the applications of ANNs in the treatment of acute pancreatitis and pancreatic cancer

    Bird evolution: testing the Metaves clade with six new mitochondrial genomes-1

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    <p><b>Copyright information:</b></p><p>Taken from "Bird evolution: testing the Metaves clade with six new mitochondrial genomes"</p><p>http://www.biomedcentral.com/1471-2148/8/20</p><p>BMC Evolutionary Biology 2008;8():20-20.</p><p>Published online 23 Jan 2008</p><p>PMCID:PMC2259304.</p><p></p> 41 complete mtDNA sequences using a Galloanserae outgroup. Members of Metaves (Fain and Houde 2004) are indicated with black spots. Bayesian probabilities of 1.0 are indicated on branches as (*), branches with probabilities less than 0.99 not marked

    Regional Differences in Islet Distribution in the Human Pancreas - Preferential Beta-Cell Loss in the Head Region in Patients with Type 2 Diabetes

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    While regional heterogeneity in islet distribution has been well studied in rodents, less is known about human pancreatic histology. To fill gaps in our understanding, regional differences in the adult human pancreas were quantitatively analyzed including the pathogenesis of type 2 diabetes (T2D). Cadaveric pancreas specimens were collected from the head, body and tail regions of each donor, including subjects with no history of diabetes or pancreatic diseases (n = 23) as well as patients with T2D (n = 12). The study further included individuals from whom islets were isolated (n = 7) to study islet yield and function in a clinical setting of islet transplantation. The whole pancreatic sections were examined using an innovative large-scale image capture and unbiased detailed quantitative analyses of the characteristics of islets from each individual (architecture, size, shape and distribution). Islet distribution/density is similar between the head and body regions, but is >2-fold higher in the tail region. In contrast to rodents, islet cellular composition and architecture were similar throughout the pancreas and there was no difference in glucose-stimulated insulin secretion in islets isolated from different regions of the pancreas. Further studies revealed preferential loss of large islets in the head region in patients with T2D. The present study has demonstrated distinct characteristics of the human pancreas, which should provide a baseline for the future studies integrating existing research in the field and helping to advance bi-directional research between humans and preclinical models
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