Early Miocene herpetofaunas from the Greek localities of Aliveri and Karydia – bridging a gap in the knowledge of amphibians and reptiles from the early Neogene of southeastern Europe

Abstract

We here describe new remains of amphibians and reptiles from the early Miocene (MN 4) of two different Greek localities, Aliveri and Karydia. The newly described material consists of urodelans, alytids, indeterminate anurans, turtles, crocodylians, lacertids, indeterminate scincomorphs, anguids, colubrids, viperids, and indeterminate snakes. The presence of the frog Latonia cf. gigantea in Greece is documented for the first time. Additionally, the presence of viperids in Aliveri implies a much wider distribution for these snakes during the early Miocene of Europe. Of special interest is the presence of a peculiar colubrid that seems to possess a hitherto unknown vertebral structure, which is herein defined as the ‘paracentral ridge’. Although incomplete, the new material has important taxonomic and biogeographic implications, as it enhances our understanding of southeastern European herpetofaunas from the early Miocene, a time period that was characterised by major dispersal and extinction events and climatic change that affected the whole continent.     

The highly conserved extracellular peptide, DSYG(893-896), is a critical structure for sodium pump function.

The peptide sequence DSYG(893-896) of the sheep sodium pump alpha 1 subunit is highly conserved among all K(+)-transporting P-type ATPases. To obtain information about its function, single mutations were introduced and the mutants were expressed in yeast and analysed for enzymatic activity, ion recognition, and alpha/beta subunit interactions. Mutants of Ser894 or Tyr895 were all active. Conservative phenylalanine and tryptophan mutants of Tyr895 displayed properties that were similar to the properties of the wild-type enzyme. Replacement of the same amino acid by cysteine, however, produced heat-sensitive enzymes, indicating that the aromatic group contributes to the stability of the enzyme. Mutants of the neighbouring Ser894 recognized K(+) with altered apparent affinities. Thus, the Ser894-->Asp mutant displayed a threefold higher apparent affinity for K(+) (EC(50) = 1.4 +/- 0.06 mm) than the wild-type enzyme (EC(50) = 3.8 +/- 0.33 mm). In contrast, the mutant Ser894-->Ile had an almost sixfold lower apparent affinity for K(+) (EC(50) = 21.95 +/- 1.41 mm). Mutation of Asp893 or Gly896 produced inactive proteins. When an anti-beta 1 subunit immunoglobulin was used to co-immunoprecipitate the alpha 1 subunit, neither the Gly896-->Arg nor the Gly896-->Ile mutant could be visualized by subsequent probing with an anti-alpha 1 subunit immunoglobulin. On the other hand, co-immunoprecipitation was obtained with the inactive Asp893-->Arg and Asp893-->Glu mutants. Thus, it might be that Asp893 is involved in enzyme conformational transitions required for ATP hydrolysis and/or ion translocation. The results obtained here demonstrate the importance of the highly conserved peptide DSYG(893-896) for the function of alpha/beta heterodimeric P-type ATPases.     

MSLN Gene Silencing Has an Anti-Malignant Effect on Cell Lines Overexpressing Mesothelin Deriving from Malignant Pleural Mesothelioma

Genes involved in the carcinogenetic mechanisms underlying malignant pleural mesothelioma (MPM) are still poorly characterized. So far, mesothelin (MSLN) has aroused the most interest. It encodes for a membrane glycoprotein, frequently over-expressed in various malignancies such as MPM, and ovarian and pancreatic cancers. It has been proposed as a diagnostic and immunotherapeutic target with promising results. However, an alternative therapeutic approach seems to rise, whereby synthetic molecules, such as antisense oligonucleotides, could be used to inhibit MSLN activity. To date, such a gene-level inhibition has been attempted in two studies only, both on pancreatic and ovarian carcinoma cell lines, with the use of silencing RNA approaches. With regard to MPM, only one cell line (H2373) has been employed to study the effects of MSLN depletion. Indeed, the knowledge on the role of MSLN in MPM needs expanding. Accordingly, we investigated the expression of MSLN in a panel of three MPM cell lines, i.e. NCI-H28, Mero-14, and IstMes2; one non-MPM cell line was used as reference (Met5A). MSLN knock-down experiments on MSLN-overexpressing cells were also performed through silencing RNA (siRNA) to verify whether previous findings could be generalized to a different set of cell cultures. In agreement with previous studies, transient MSLN-silencing caused decreased proliferation rate and reduced invasive capacity and sphere formation in MSLN-overexpressing Mero-14 cells. Moreover, MSLN-siRNA combined with cisplatin, triggered a marked increase in apoptosis and a decrease in proliferation as compared to cells treated with each agent alone, thereby suggesting a sensitizing effect of siRNA towards cisplatin. In summary, our findings confirm that MSLN should be considered a key molecular target for novel gene-based targeted therapies of cancer.     

Reduction of apoptosis and preservation of mitochondrial integrity under ischemia/reperfusion injury is mediated by estrogen receptor β

Background

Estrogen improves cardiac recovery after ischemia/reperfusion (I/R) by yet incompletely understood mechanisms. Mitochondria play a crucial role in I/R injury through cytochrome c-dependent apoptosis activation. We tested the hypothesis that 17β-estradiol (E2) as well as a specific ERβ agonist improve cardiac recovery through estrogen receptor (ER)β-mediated mechanisms by reducing mitochondria-induced apoptosis and preserving mitochondrial integrity.

Methods

We randomized ovariectomized C57BL/6N mice 24h before I/R to pre-treatment with E2 or a specific ERβ agonist (ERβA). Isolated hearts were perfused for 20min prior to 30min global ischemia followed by 40min reperfusion.

Results

Compared with controls, ERβA and E2 treated groups showed a significant improvement in cardiac recovery, i.e. an increase in left ventricular developed pressure, dP/dtmax and dP/dtmin. ERβA and E2 pre-treatment led to a significant reduction in apoptosis with decreased cytochrome c release from the mitochondria and increased mitochondrial levels of anti-apoptotic Bcl2 and ACAA2. Protein levels of mitochondrial translocase inner membrane (TIM23) and mitochondrial complex I of respiratory chain were increased by ERβA and E2 pre-treatment. Furthermore, we found a significant increase of myosin light chain 2 (MLC2) phosphorylation together with ERK1/2 activation in E2, but not in ERβA treated groups.

Conclusions

Activation of ERβ is essential for the improvement of cardiac recovery after I/R through the inhibition of apoptosis and preservation of mitochondrial integrity and can be a achieved by a specific ERβ agonist. Furthermore, E2 modulates MLC2 activation after I/R independent of ERβ.

     

Topographical Estimation of Visual Population Receptive Fields by fMRI

Visual cortex is retinotopically organized so that neighboring populations of cells map to neighboring parts of the visual field. Functional magnetic resonance imaging allows us to estimate voxel-based population receptive fields (pRF), i.e., the part of the visual field that activates the cells within each voxel. Prior, direct, pRF estimation methods¹ suffer from certain limitations: 1) the pRF model is chosen a-priori and may not fully capture the actual pRF shape, and 2) pRF centers are prone to mislocalization near the border of the stimulus space. Here a new topographical pRF estimation method² is proposed that largely circumvents these limitations. A linear model is used to predict the Blood Oxygen Level-Dependent (BOLD) signal by convolving the linear response of the pRF to the visual stimulus with the canonical hemodynamic response function. PRF topography is represented as a weight vector whose components represent the strength of the aggregate response of voxel neurons to stimuli presented at different visual field locations. The resulting linear equations can be solved for the pRF weight vector using ridge regression³, yielding the pRF topography. A pRF model that is matched to the estimated topography can then be chosen post-hoc, thereby improving the estimates of pRF parameters such as pRF-center location, pRF orientation, size, etc. Having the pRF topography available also allows the visual verification of pRF parameter estimates allowing the extraction of various pRF properties without having to make a-priori assumptions about the pRF structure. This approach promises to be particularly useful for investigating the pRF organization of patients with disorders of the visual system.     

Genetic skeletal disorders of the fetus and infant: Pathologic and molecular findings in a series of 41 cases

BACKGROUND: Genetic skeletal disorders of the fetus and infant are a large group of genetic disorders, comprising the groups formerly assigned as skeletal dysplasias (osteochondrodysplasias), dysostoses, and malformation syndromes with a skeletal component. Genetic skeletal disorders may be prenatally detected by ultrasonography or result in intrauterine or early postnatal death, constituting one difficult diagnostic field met by the pathologist who performs the perinatal autopsy. METHODS: In this retrospective study, we have gathered radiologic, physical, histopathologic, and molecular data regarding 41 cases of genetic skeletal disorders diagnosed among 1980 fetal and perinatal autopsies over a 10‐year period. RESULTS: Our series of cases were classified according to the 2006 Nosology and Classification of Genetic Skeletal Disorders. The overall frequency of genetic skeletal disorders was 1:48 autopsies. The FGFR3 group and osteogenesis imperfecta type 2 were the more frequently encountered disorders. The mean gestational age at autopsy was 21.9 weeks (range, 12–37 weeks). A final diagnosis was obtained in 95% of cases. Genetic skeletal disorders were detected by prenatal ultrasound in 90% of cases, with a correct typing of the disorder achieved in only 34%. Molecular analysis was confirmative in 5 cases. CONCLUSIONS: The central role of the perinatal pathologist in collaboration with specialized services is essential for the correct interpretation of the radiologic, physical, and histopathologic findings, to accurately classify specific types of genetic skeletal disorders and enable genetic counseling. Birth Defects Research (Part A), 2009. © 2009 Wiley‐Liss, Inc.     

Evidence that Aspartate Aminotransferase Activity and Ketodicarboxylate Carrier Function Are Essential for Biosynthesis of Transmitter Glutamate

Based on the selective inhibition of glutamate release in cerebellar granule cells in primary cultures by the aspartate aminotransferase inhibitor, aminooxyacetic acid, and by the ketodicarboxylate carrier inhibitor, phenylsuccinate, a novel model for synthesis of transmitter glutamate is suggested: Glutamate is formed from glutamine in the mitochondrial intramembrane space by phosphate-activated glutaminase, transported across the inner membrane in exchange with aspartate, transaminated in the matrix to alpha-ketoglutarate, which via the ketodicarboxylate carrier is transferred to the cytoplasm, and transaminated to form transmitter glutamate. Such a mechanism would explain the functional role of aspartate aminotransferase in glutamatergic neurons.     

Data-driven flow-map models for data-efficient discovery of dynamics and fast uncertainty quantification of biological and biochemical systems

Computational models are increasingly used to investigate and predict the complex dynamics of biological and biochemical systems. Nevertheless, governing equations of a biochemical system may not be (fully) known, which would necessitate learning the system dynamics directly from, often limited and noisy, observed data. On the other hand, when expensive models are available, systematic and efficient quantification of the effects of model uncertainties on quantities of interest can be an arduous task. This paper leverages the notion of flow-map (de)compositions to present a framework that can address both of these challenges via learning data-driven models useful for capturing the dynamical behavior of biochemical systems. Data-driven flow-map models seek to directly learn the integration operators of the governing differential equations in a black-box manner, irrespective of structure of the underlying equations. As such, they can serve as a flexible approach for deriving fast-to-evaluate surrogates for expensive computational models of system dynamics, or, alternatively, for reconstructing the long-term system dynamics via experimental observations. We present a data-efficient approach to data-driven flow-map modeling based on polynomial chaos Kriging. The approach is demonstrated for discovery of the dynamics of various benchmark systems and a coculture bioreactor subject to external forcing, as well as for uncertainty quantification of a microbial electrosynthesis reactor. Such data-driven models and analyses of dynamical systems can be paramount in the design and optimization of bioprocesses and integrated biomanufacturing systems.