A comprehensive and integrative reconstruction of evolutionary history for Anomura (Crustacea: Decapoda)

Background The infraorder Anomura has long captivated the attention of evolutionary biologists due to its impressive morphological diversity and ecological adaptations. To date, 2500 extant species have been described but phylogenetic relationships at high taxonomic levels remain unresolved. Here, we reconstruct the evolutionary history—phylogeny, divergence times, character evolution and diversification—of this speciose clade. For this purpose, we sequenced two mitochondrial (16S and 12S) and three nuclear (H3, 18S and 28S) markers for 19 of the 20 extant families, using traditional Sanger and next-generation 454 sequencing methods. Molecular data were combined with 156 morphological characters in order to estimate the largest anomuran phylogeny to date. The anomuran fossil record allowed us to incorporate 31 fossils for divergence time analyses. Results Our best phylogenetic hypothesis (morphological + molecular data) supports most anomuran superfamilies and families as monophyletic. However, three families and eleven genera are recovered as para- and polyphyletic. Divergence time analysis dates the origin of Anomura to the Late Permian ~259 (224–296) MYA with many of the present day families radiating during the Jurassic and Early Cretaceous. Ancestral state reconstruction suggests that carcinization occurred independently 3 times within the group. The invasion of freshwater and terrestrial environments both occurred between the Late Cretaceous and Tertiary. Diversification analyses found the speciation rate to be low across Anomura, and we identify 2 major changes in the tempo of diversification; the most significant at the base of a clade that includes the squat-lobster family Chirostylidae. Conclusions Our findings are compared against current classifications and previous hypotheses of anomuran relationships. Many families and genera appear to be poly- or paraphyletic suggesting a need for further taxonomic revisions at these levels. A divergence time analysis provides key insights into the origins of major lineages and events and the timing of morphological (body form) and ecological (habitat) transitions. Living anomuran biodiversity is the product of 2 major changes in the tempo of diversification; our initial insights suggest that the acquisition of a crab-like form did not act as a key innovation.

Cardiac Neural Crest Cells and Their Role in Murine Purkinje Fiber Development

The heart beat is regulated by the cardiac conduction system (CCS), a specialized group of cells that transmit electrical impulses around the heart chambers. During development, ventricular CCS cells originate from embryonic cardiomyocytes and not from the neural crest. Nonetheless, discoveries in chick implied that the cardiac neural crest (CNC) cells contribute to proper development of the ventricular CCS. In this report, the Splotch mouse mutant (Pax3sp), in which the CNC cells do not migrate to the heart, was used to investigate whether these cells also affect proper CCS development in mammals. Homozygote mutants (Pax3Sp!Sp) are lethal on 111 Embryonic Day 13 (E13), and can be phenotyped by spina bifida and exencephaly. Pax3Spi+ mice were crossed to obtain wild type, Pax3 Spi+ and Pax3 Sp!Sp embryos. Comparison of hematoxylin and eosin stained histological sections showed less trabeculation in El2.5 cardiac ventricles of Pax3Sp!Sp. Furthermore, immunofluorescence analysis with the Purkinje fiber marker Cx40 showed a qualitative difference between wild type and mutant hearts. Quantitative analysis indicated that Pax3 Sp!Sp ventricles had fewer Cx40 expressing cells, as well as less Cx40 being expressed per cell when compared to wild type ventricles. Immunofluorescence with the H3 histome mitosis antibody showed fewer proliferating cells in the ventricles of mutant embryos when compared to controls. These results suggest that CNCC affect the morphogenesis of cardiac ventricles and the development of the ventricular CCS by contributing cellular proliferation.

Factors influencing university performance of associate in arts graduates transferring to the state university system

The purpose of this study was to examine the factorsbehind the failure rates of Associate in Arts (AA)graduates from Miami-Dade Community College (M-DCC) transferring to the Florida State University System (SUS). In M-DCC's largest disciplines, the university failure rate was 13% for Business & Management, 13% for Computer Science, and 14% for Engineering. Hypotheses tested were: Hypothesis 1 (H1): The lower division (LD) overall cumulative GPA and/or the LD major field GPA for AA graduates are predictive of the SUS GPA for the Business Management, Computer Science, and Engineering disciplines. Hypothesis 2 (H2): Demographic variables (age, race, gender) are predictive of performance at the university among M-DCC AA graduates in Engineering, Business & Management, and Computer Science. Hypothesis 3 (H3): Administrative variables (CLAST -College Level Academic Skills Test subtests) are predictive of university performance (GPA) for the Business/Management, Engineering, and Computer Science disciplines. Hypothesis 4 (H4): LD curriculum variables (course credits, course quality points) are predictive of SUS performance for the Engineering, Business/Management and Computer Science disciplines. Multiple Regression was the inferential procedureselected for predictions. Descriptive statistics weregenerated on the predictors. Results for H1 identified the LD GPA as the most significant variable in accounting for the variability of the university GPA for the Business & Management, Computer Science, and Engineering disciplines. For H2, no significant results were obtained for theage and gender variables, but the ethnic subgroups indicated significance at the .0001 level. However, differentials in GPA may not have been due directly to the race factor but, rather, to curriculum choices and performance outcomes while in the LD. The CLAST computation variable (H3) was a significant predictor of the SUS GPA. This is most likely due to the mathematics structure pervasive in these disciplines. For H4, there were two curriculum variables significant in explaining the variability of the university GPA (number of required critical major credits completed and quality of the student's performance for these credits). Descriptive statistics on the predictors indicated that 78% of those failing in the State University System had a LD major GPA (calculated with the critical required university credits earned and quality points of these credits) of less than 3.0; and 83% of those failing at the university had an overall community college GPA of less than 3.0.