Establishment and characterization of METON myoepithelioma cell line derived from human palatal myoepithelioma: apical reference to the diverse differentiation potential

Myoepithelioma is an extremely rare condition that accounts for 1–1.5 % of salivary gland tumors. It was formerly regarded as a subtype of pleomorphic adenoma, in which myoepithelial structural components predominated, but was listed as a separate disease entity in the 1991 World Health Organization classification (Seifert in Histological typing of salivary gland tumours. Springer, Berlin, 1991). Its histology is highly varied and recurrence is frequent (El-Naggar et al. in J Larygol Otol 103:1192–1197, 1989), with cases of malignant transformation having been reported (Seifert in Histological typing of salivary gland tumours. Springer, Berlin, 1991; Barnes et al. in Pathology and Genetics of head and neck tumours. IARC Press, Lyon, 2005), making this a difficult tumor to control in many cases. This is thought to be due to the multiple differentiation potential of myoepithelial cells, but the details are unknown. There have been a number of reports of the establishment of cell lines (Shirasuna et al. Cancer. 45:297–305, 1980; Jaeger et al. Oral Surg Oral Med Oral Pathol Oral Radiol Endod 84:663–667, 1997), but numerous points remain unclear. We established a myoepithelial cell line designated METON, and investigated its characteristics. METON consists of cells with two different morphologies: spindle-shaped cells and epithelial-like cells. Then. we also used single-cell cloning method to establish various subclones (epithelial-like, spindle-like, and mixed epithelial-like/spindle-like cell lines). Among these, pluripotency markers were expressed by the mixed epithelial-like/spindle-like cell lines. The newly established cell line expressing these pluripotency markers will be extremely useful for elucidating the diverse histologies of salivary gland tumors.     

A radically non-morphemic approach to bidirectional syncretism

This paper addresses the question of how certain kinds of overlapping syncretisms in inflectional paradigms can be accounted for that Baerman et al. (Language 80:807–824, 2005) refer to as convergent/divergent bidirectional syncretisms (based on earlier work by Stump, Inflectional morphology, 2001). Bidirectional syncretism strongly resists accounts in terms of standard rules of exponence (or similar devices) that correlate inflection markers with (often underspecified) morpho-syntactic specifications (such rules are used in many morphological theories; e.g., Anderson, A-morphous morphology, 1992; Halle and Marantz in The view from building, pp. 111–176, 1993; Aronoff, Morphology by itself, 1994; Wunderlich in Yearbook of morphology 1995, pp. 93–114, 1996; and Stump, Inflectional morphology, 2001). The reason is that it is difficult to capture overlapping distributions by natural classes. In view of this, rules of referral have been proposed to derive bidirectional syncretism (Stump, Inflectional morphology, 2001; Baerman et al. (Language 80:807–824, 2005)). In contrast, I would like to pursue the hypothesis that systematic instances of overlapping syncretism ultimately motivate a new approach to inflectional morphology—one that fully dispenses with the assumption that morphological exponents are paired with morpho-syntactic feature specifications (and that therefore qualifies as radically non-morphemic): First, rules of exponence are replaced with feature co-occurrence restrictions (FCRs; Gazdar et al., Generalized Phrase Structure Grammar, 1985). For phonologically determined natural classes of exponents, FCRs state incompatibilites with morpho-syntactic feature specifications. Second, marker competition is resolved by a principle of Phonology-driven Marker Selection (PMS). PMS takes over the role of the Specificity (Blocking, Elsewhere, Panini) Principle of standard analyses. Empirically, the main focus is on Bonan declension; the analysis is subsequently extended to Gujarati conjugation and Latin o-declension, with further remarks on bidirectional syncretism in other inflectional paradigms.     

Plant biotechnology for food security and bioeconomy

This year is a special year for plant biotechnology. It was 30 years ago, on January 18 1983, one of the most important dates in the history of plant biotechnology, that three independent groups described Agrobacterium tumefaciens—mediated genetic transformation at the Miami Winter Symposium, leading to the production of normal, fertile transgenic plants (Bevan et al. in Nature 304:184–187, 1983; Fraley et al. in Proc Natl Acad Sci USA 80:4803–4807, 1983; Herrera-Estrella et al. in EMBO J 2:987–995, 1983; Vasil in Plant Cell Rep 27:1432–1440, 2008). Since then, plant biotechnology has rapidly advanced into a useful and valuable tool and has made a significant impact on crop production, development of a biotech industry and the bio-based economy worldwide.     

Mathematical Model of Growth Factor Driven Haptotaxis and Proliferation in a Tissue Engineering Scaffold

Motivated by experimental work (Miller et al. in Biomaterials 27(10):2213–2221, 2006, 32(11):2775–2785, 2011) we investigate the effect of growth factor driven haptotaxis and proliferation in a perfusion tissue engineering bioreactor, in which nutrient-rich culture medium is perfused through a 2D porous scaffold impregnated with growth factor and seeded with cells. We model these processes on the timescale of cell proliferation, which typically is of the order of days. While a quantitative representation of these phenomena requires more experimental data than is yet available, qualitative agreement with preliminary experimental studies (Miller et al. in Biomaterials 27(10):2213–2221, 2006) is obtained, and appears promising. The ultimate goal of such modeling is to ascertain initial conditions (growth factor distribution, initial cell seeding, etc.) that will lead to a final desired outcome.     

Daphnias: from the individual based model to the large population equation

The class of deterministic ‘Daphnia’ models treated by Diekmann et al. (J Math Biol 61:277–318, 2010) has a long history going back to Nisbet and Gurney (Theor Pop Biol 23:114–135, 1983) and Diekmann et al. (Nieuw Archief voor Wiskunde 4:82–109, 1984). In this note, we formulate the individual based models (IBM) supposedly underlying those deterministic models. The models treat the interaction between a general size-structured consumer population (‘Daphnia’) and an unstructured resource (‘algae’). The discrete, size and age-structured Daphnia population changes through births and deaths of its individuals and through their aging and growth. The birth and death rates depend on the sizes of the individuals and on the concentration of the algae. The latter is supposed to be a continuous variable with a deterministic dynamics that depends on the Daphnia population. In this model setting we prove that when the Daphnia population is large, the stochastic differential equation describing the IBM can be approximated by the delay equation featured in (Diekmann et al., loc. cit.).     

Modeling Endocrine Control of the Pituitary–Ovarian Axis: Androgenic Influence and Chaotic Dynamics

Mathematical models of the hypothalamus-pituitary-ovarian axis in women were first developed by Schlosser and Selgrade in 1999, with subsequent models of Harris-Clark et al. (Bull. Math. Biol. 65(1):157–173, 2003) and Pasteur and Selgrade (Understanding the dynamics of biological systems: lessons learned from integrative systems biology, Springer, London, pp. 38–58, 2011). These models produce periodic in-silico representation of luteinizing hormone (LH), follicle stimulating hormone (FSH), estradiol (E2), progesterone (P4), inhibin A (InhA), and inhibin B (InhB). Polycystic ovarian syndrome (PCOS), a leading cause of cycle irregularities, is seen as primarily a hyper-androgenic disorder. Therefore, including androgens into the model is necessary to produce simulations relevant to women with PCOS. Because testosterone (T) is the dominant female androgen, we focus our efforts on modeling pituitary feedback and inter-ovarian follicular growth properties as functions of circulating total T levels. Optimized parameters simultaneously simulate LH, FSH, E2, P4, InhA, and InhB levels of Welt et al. (J. Clin. Endocrinol. Metab. 84(1):105–111, 1999) and total T levels of Sinha-Hikim et al. (J. Clin. Endocrinol. Metab. 83(4):1312–1318, 1998). The resulting model is a system of 16 ordinary differential equations, with at least one stable periodic solution. Maciel et al. (J. Clin. Endocrinol. Metab. 89(11):5321–5327, 2004) hypothesized that retarded early follicle growth resulting in “stockpiling” of preantral follicles contributes to PCOS etiology. We present our investigations of this hypothesis and show that varying a follicular growth parameter produces preantral stockpiling and a period-doubling cascade resulting in apparent chaotic menstrual cycle behavior. The new model may allow investigators to study possible interventions returning acyclic patients to regular cycles and guide developments of individualized treatments for PCOS patients.     

Feature extraction from spike trains with Bayesian binning: ‘Latency is where the signal starts’

The peristimulus time histogram (PSTH) and its more continuous cousin, the spike density function (SDF) are staples in the analytic toolkit of neurophysiologists. The former is usually obtained by binning spike trains, whereas the standard method for the latter is smoothing with a Gaussian kernel. Selection of a bin width or a kernel size is often done in an relatively arbitrary fashion, even though there have been recent attempts to remedy this situation (DiMatteo et al., Biometrika 88(4):1055–1071, 2001; Shimazaki and Shinomoto 2007a, Neural Comput 19(6):1503–1527, 2007b, c; Cunningham et al. 2008). We develop an exact Bayesian, generative model approach to estimating PSTHs. Advantages of our scheme include automatic complexity control and error bars on its predictions. We show how to perform feature extraction on spike trains in a principled way, exemplified through latency and firing rate posterior distribution evaluations on repeated and single trial data. We also demonstrate using both simulated and real neuronal data that our approach provides a more accurate estimates of the PSTH and the latency than current competing methods. We employ the posterior distributions for an information theoretic analysis of the neural code comprised of latency and firing rate of neurons in high-level visual area STSa. A software implementation of our method is available at the machine learning open source software repository (www.mloss.org, project ‘binsdfc’).     

Multiparametric bifurcations of an epidemiological model with strong Allee effect

In this paper we completely study bifurcations of an epidemic model with five parameters introduced by Hilker et al. (Am Nat 173:72–88, 2009), which describes the joint interplay of a strong Allee effect and infectious diseases in a single population. Existence of multiple positive equilibria and all kinds of bifurcation are examined as well as related dynamical behavior. It is shown that the model undergoes a series of bifurcations such as saddle-node bifurcation, pitchfork bifurcation, Bogdanov–Takens bifurcation, degenerate Hopf bifurcation of codimension two and degenerate elliptic type Bogdanov–Takens bifurcation of codimension three. Respective bifurcation surfaces in five-dimensional parameter spaces and related dynamical behavior are obtained. These theoretical conclusions confirm their numerical simulations and conjectures by Hilker et al., and reveal some new bifurcation phenomena which are not observed in Hilker et al. (Am Nat 173:72–88, 2009). The rich and complicated dynamics exhibit that the model is very sensitive to parameter perturbations, which has important implications for disease control of endangered species.     

Mathematical modelling and numerical simulations of actin dynamics in the eukaryotic cell

The aim of this article is to study cell deformation and cell movement by considering both the mechanical and biochemical properties of the cortical network of actin filaments and its concentration. Actin is a polymer that can exist either in filamentous form (F-actin) or in monometric form (G-actin) (Chen et al. in Trends Biochem Sci 25:19–23, 2000) and the filamentous form is arranged in a paired helix of two protofilaments (Ananthakrishnan et al. in Recent Res Devel Biophys 5:39–69, 2006). By assuming that cell deformations are a result of the cortical actin dynamics in the cell cytoskeleton, we consider a continuum mathematical model that couples the mechanics of the network of actin filaments with its bio-chemical dynamics. Numerical treatment of the model is carried out using the moving grid finite element method (Madzvamuse et al. in J Comput Phys 190:478–500, 2003). Furthermore, by assuming slow deformations of the cell, we use linear stability theory to validate the numerical simulation results close to bifurcation points. Far from bifurcation points, we show that the mathematical model is able to describe the complex cell deformations typically observed in experimental results. Our numerical results illustrate cell expansion, cell contraction, cell translation and cell relocation as well as cell protrusions. In all these results, the contractile tonicity formed by the association of actin filaments to the myosin II motor proteins is identified as a key bifurcation parameter.     

Reconstruction of extended Petri nets from time-series data by using logical control functions

The aim of this work is to extend a previously presented algorithm (Durzinsky et al. 2008b in Computational methods in systems biology, LNCS, vol 5307. Springer, Heidelberg, pp 328–346; Marwan et al. 2008 in Math Methods Oper Res 67:117–132) for the reconstruction of standard place/transition Petri nets from time-series of experimental data sets. This previously reported method finds provably all networks capable to reproduce the experimental observations. In this paper we enhance this approach to generate extended Petri nets involving mechanisms formally corresponding to catalytic or inhibitory dependencies that mediate the involved reactions. The new algorithm delivers the set of all extended Petri nets being consistent with the time-series data used for reconstruction. It is illustrated using the phosphate regulatory network of enterobacteria as a case study.     

Mitochondrial complex I inhibitors, acetogenins, induce HepG2 cell death through the induction of the complete apoptotic mitochondrial pathway

The development of new anti-neoplastic drugs is a key issue for cancer chemotherapy due to the reality that, most likely, certain cancer cells are resistant to current chemotherapy. The past two decades have witnessed tremendous advances in our understanding of the pathogenesis of cancer. These advances have allowed identification new targets as oncogenes, tumor supressor genes and the possible implication of the mitochondria (Fulda et al. Nat Rev Drug Discov 9:447–464, 2010). Annonaceous Acetogenins (ACGs) have been described as the most potent inhibitors of the respiratory chain because of their interaction with mitochondrial Complex I (Degli Esposti and Ghelli Biochim Biophys Acta 1187:116–120, 1994; Zafra-Polo et al. Phytochemistry 42:253–271, 1996; Miyoshi et al. Biochim Biophys Acta 1365:443–452, 1998; Tormo et al. Arch Biochem Biophys 369:119–126, 1999; Motoyama et al. Bioorg Med Chem Lett 12:2089–2092, 2002). To explore a possible application of natural products from Annonaceous plants to cancer treatment, we have selected four bis-tetrahydrofuranic ACGs, three from Annona cherimolia (cherimolin-1, motrilin and laherradurin) and one from Rollinia mucosa (rollinianstatin-1) in order to fully describe their mechanisms responsible within the cell (Fig. 1). In this study, using a hepato-carcinoma cell line (HepG2) as a model, we showed that the bis-THF ACGs caused cell death through the induction of the apoptotic mitochondrial pathway. Their potency and behavior were compared with the classical mitochondrial respiratory chain Complex I inhibitor rotenone in every apoptotic pathway step.

An analysis of a ‘community-driven’ reconstruction of the human metabolic network

Following a strategy similar to that used in baker’s yeast (Herrgård et al. Nat Biotechnol 26:1155–1160, 2008). A consensus yeast metabolic network obtained from a community approach to systems biology (Herrgård et al. 2008; Dobson et al. BMC Syst Biol 4:145, 2010). Further developments towards a genome-scale metabolic model of yeast (Dobson et al. 2010; Heavner et al. BMC Syst Biol 6:55, 2012). Yeast 5—an expanded reconstruction of the Saccharomyces cerevisiae metabolic network (Heavner et al. 2012) and in Salmonella typhimurium (Thiele et al. BMC Syst Biol 5:8, 2011). A community effort towards a knowledge-base and mathematical model of the human pathogen Salmonella typhimurium LT2 (Thiele et al. 2011), a recent paper (Thiele et al. Nat Biotechnol 31:419–425, 2013). A community-driven global reconstruction of human metabolism (Thiele et al. 2013) described a much improved ‘community consensus’ reconstruction of the human metabolic network, called Recon 2, and the authors (that include the present ones) have made it freely available via a database at http://humanmetabolism.org/ and in SBML format at Biomodels (http://identifiers.org/biomodels.db/MODEL1109130000). This short analysis summarises the main findings, and suggests some approaches that will be able to exploit the availability of this model to advantage.     

A model of direction selectivity in the starburst amacrine cell network

Displaced starburst amacrine cells (SACs) are retinal interneurons that exhibit GABA _A receptor-mediated and Cl ^? cotransporter-mediated, directionally selective (DS) light responses in the rabbit retina. They depolarize to stimuli that move centrifugally through the receptive field surround and hyperpolarize to stimuli that move centripetally through the surround (Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006). They also play a key role in the activity of DS ganglion cells (DS GC; Amthor et al, Vis Neurosci 19:495–509 2002; Euler et al, Nature 418:845–852, 2002; Fried et al, Nature 420:411– 414, 2002; Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006; Lee and Zhou, Neuron 51:787–799 2006; Yoshida et al, Neuron 30:771–780, 2001). In this paper we present a model of strong DS behavior of SACs which relies on the GABA-mediated communication within a tightly interconnected network of these cells and on the glutamate signal that the SACs receive from bipolar cells (a presynaptic cell that receives input from cones). We describe how a moving light stimulus can produce a large, sustained depolarization of the SAC dendritic tips that point in the direction that the stimulus moves (i.e., centrifugal motion), but produce a minimal depolarization of the dendritic tips that point in the opposite direction (i.e., centripetal motion). This DS behavior, which is quantified based on the relative size and duration of the depolarizations evoked by stimulus motion at dendritic tips pointing in opposite directions, is robust to changes of many different parameter values and consistent with experimental data. In addition, the DS behavior is strengthened under the assumptions that the Cl^? cotransporters Na^?+?-K^?+?-Cl^?? and K^?+?-Cl^?? are located in different regions of the SAC dendritic tree (Gavrikov et al, PNAS 103(49):18793–18798, 2006) and that GABA evokes a long-lasting response (Gavrikov et al, PNAS 100(26):16047–16052, 2003, PNAS 103(49):18793–18798, 2006; Lee and Zhou, Neuron 51:787–799, 2006). A possible mechanism is discussed based on the generation of waves of local glutamate and GABA secretion, and their postsynaptic interplay as the waves travel between cell compartments.     

Stress treatments and in vitro culture conditions influence microspore embryogenesis and growth of callus from anther walls of sweet pepper (Capsicum annuum L.)

Production of doubled haploids (DHs) is a convenient tool to obtain pure lines for breeding purposes. Until now, the easiest and most useful approach to obtain pepper DHs is via anther culture. However, this method has an associated possibility of producing calli from anther wall tissues that would be coexisting in the anther locule with embryos derived from microspores. Using two established protocols for anther culture, Dumas de Vaulx et al. (Agronomie 2:983–988, 1981) and Supena et al. (Sci Hort 107:226–232, 2006a; Plant Cell Rep 25:1–10, 2006b) callus and embryo development was assessed in four sweet pepper cultivars. For all genotypes tested, the protocol of Dumas de Vaulx et al. (Agronomie 2:983–988, 1981) promoted both embryo development and callus growth, whereas the protocol of Supena et al. (Sci Hort 107:226–232, 2006a; Plant Cell Rep 25:1–10, 2006b) produced no callus but only embryos. However, differences in embryo production were observed among these genotypes. In parallel, anthers were exposed to a 35 °C inductive heat shock for 4, 8, 12 and 16 days, prior to culture at 25 °C. The duration of the heat shock had significant effects in embryo production, but also in callus generation. Callus generation increased with prolonged exposures to 35 °C. Embryo and callus origin was analyzed by flow cytometry, light microscopy and molecular markers. Tests conducted demonstrated a gametophytic origin for all of the embryos tested, and a sporophytic origin for all of the calli. Together, our results reveal that culture conditions have a significant influence on the presence of calli derived from anther walls, which could be minimized by reducing heat shock exposure and/or using a shed-microspore approach.     

Gene regulatory network modeling using literature curated and high throughput data

Building on the linear matrix inequality (LMI) formulation developed recently by Zavlanos et al. (Automatica: Special Issue Syst Biol 47(6):1113–1122, 2011), we present a theoretical framework and algorithms to derive a class of ordinary differential equation (ODE) models of gene regulatory networks using literature curated data and microarray data. The solution proposed by Zavlanos et al. (Automatica: Special Issue Syst Biol 47(6):1113–1122, 2011) requires that the microarray data be obtained as the outcome of a series of controlled experiments in which the network is perturbed by over-expressing one gene at a time. We note that this constraint may be relaxed for some applications and, in addition, demonstrate how the conservatism in these algorithms may be reduced by using the Perron–Frobenius diagonal dominance conditions as the stability constraints. Due to the LMI formulation, it follows that the bounded real lemma may easily be used to make use of additional information. We present case studies that illustrate how these algorithms can be used on datasets to derive ODE models of the underlying regulatory networks.     

Estimating the division rate for the growth-fragmentation equation

Growth-fragmentation equations arise in many different contexts, ranging from cell division, protein polymerization, neurosciences etc. Direct observation of temporal dynamics being often difficult, it is of main interest to develop theoretical and numerical methods to recover reaction rates and parameters of the equation from indirect observation of the solution. Following the work done in Perthame and Zubelli (Inverse Probl 23:1037–1052, 2007) and Doumic et al. (2009) for the specific case of the cell division equation, we address here the general question of recovering the fragmentation rate of the equation from the observation of the time-asymptotic solution, when the fragmentation kernel and the growth rates are fully general. We give both theoretical results and numerical methods, and discuss the remaining issues.     

Detection of Legionella spp. and Legionella pneumophila in water samples of Spain by specific real-time PCR

Legionella pneumophila is the primary cause of the legionellosis diseases (90 %) (Yu et al. in J Infect Dis 186:127–128, 2002; Doleans et al. in J Clin Microbiol 42:458–460, 2004; Den Boer et al. in Clin Microbiol Infect 14:459–466, 2008). In this study, methodologies based on molecular biology were developed in order to provide a quick diagnosis of the bacterial presence in water samples of Spain. Multiplex real-time polymerase chain reaction assays were realized to target the 16S rRNA and macrophage infectivity potentiator (mip) genes of, respectively, Legionella spp. and L. pneumophila including in the design of an internal control. The results obtained by the culture and the gene amplification methods agreed in 94.44 % for the 16S rRNA gene, and a concordance of 66.67 % of the cases was obtained for the mip gene.     

Comment on: “root orientation can affect detection accuracy of ground-penetrating radar”

Introduction

In a recent paper, Tanikawa et al. Plant Soil 373:317–327, (2013) reported a considerable impact of root orientation on the accuracy of root detection and root diameter estimation by ground-penetrating radar (GPR).

Methods

In Tanikawa et al. Plant Soil 373:317–327, (2013), buried root samples in a sand box were scanned from multiple cross angles between root orientation and GPR transecting line under controlled conditions. Changes in radar waveform parameter of roots to different cross angles were investigated.

Results

Tanikawa et al. Plant Soil 373:317–327, (2013) clarified that 1) the variation in amplitude area (a signal strength related waveform parameter) to different cross angles fitted a sinusoidal waveform; and 2) the impact of root orientation on root diameter estimation by GPR could be mathematically corrected by applying a grid transect survey. However, we found that the quantitative relationship established in Tanikawa et al. Plant Soil 373:317–327, (2013) between amplitude area and cross angle was incorrect, and the application of a grid transect survey still underestimated root diameter.

Conclusion

The change in amplitude area to cross angle between transecting line and root orientation fits a sinusoidal waveform but different to that reported in Tanikawa et al. Plant Soil 373:317–327, (2013). The polarization of GPR wave may explain such sinusoidal variation in amplitude area to cross angle. The effect of root orientation on GPR-based root diameter estimation remains to be calibrated.