On the fractal structure of the rescaled evolution set of Carlitz sequences of polynomials

AbstractSelf-similarity properties of the coefficient patterns of the so-called m-Carlitz sequences of polynomials are considered. These properties are coded in an associated fractal set – the rescaled evolution set. We extend previous results on linear cellular automata with states in a finite field. Applications are given for the sequence of Legendre polynomials and sequences associated with the zero Bessel function

Critical growth of cerebral tissue in organoids: theory and experiments

We develop a Fokker-Planck theory of tissue growth with three types of cells (symmetrically dividing, asymmetrically dividing and non-dividing) as main agents to study the growth dynamics of human cerebral organoids. Fitting the theory to lineage tracing data obtained in next generation sequencing experiments, we show that the growth of cerebral organoids is a critical process. We derive analytical expressions describing the time evolution of clonal lineage sizes and show how power-law distributions arise in the limit of long times due to the vanishing of a characteristic growth scale

Fast- or Slow-inactivated State Preference of Na+ Channel Inhibitors: A Simulation and Experimental Study

Sodium channels are one of the most intensively studied drug targets. Sodium channel inhibitors (e.g., local anesthetics, anticonvulsants, antiarrhythmics and analgesics) exert their effect by stabilizing an inactivated conformation of the channels. Besides the fast-inactivated conformation, sodium channels have several distinct slow-inactivated conformational states. Stabilization of a slow-inactivated state has been proposed to be advantageous for certain therapeutic applications. Special voltage protocols are used to evoke slow inactivation of sodium channels. It is assumed that efficacy of a drug in these protocols indicates slow-inactivated state preference. We tested this assumption in simulations using four prototypical drug inhibitory mechanisms (fast or slow-inactivated state preference, with either fast or slow binding kinetics) and a kinetic model for sodium channels. Unexpectedly, we found that efficacy in these protocols (e.g., a shift of the “steady-state slow inactivation curve”), was not a reliable indicator of slow-inactivated state preference. Slowly associating fast-inactivated state-preferring drugs were indistinguishable from slow-inactivated state-preferring drugs. On the other hand, fast- and slow-inactivated state-preferring drugs tended to preferentially affect onset and recovery, respectively. The robustness of these observations was verified: i) by performing a Monte Carlo study on the effects of randomly modifying model parameters, ii) by testing the same drugs in a fundamentally different model and iii) by an analysis of the effect of systematically changing drug-specific parameters. In patch clamp electrophysiology experiments we tested five sodium channel inhibitor drugs on native sodium channels of cultured hippocampal neurons. For lidocaine, phenytoin and carbamazepine our data indicate a preference for the fast-inactivated state, while the results for fluoxetine and desipramine are inconclusive. We suggest that conclusions based on voltage protocols that are used to detect slow-inactivated state preference are unreliable and should be re-evaluated

The algebra of the general Markov model on phylogenetic trees and networks

It is known that the Kimura 3ST model of sequence evolution on phylogenetic trees can be extended quite naturally to arbitrary split systems. However, this extension relies heavily on mathematical peculiarities of the K3ST model, and providing an analogous augmentation of the general Markov model has thus far been elusive. In this paper we rectify this shortcoming by showing how to extend the general Markov model on trees to to include arbitrary splits; and even further to more general network models. This is achieved by exploring the algebra of the generators of the continuous-time Markov chain together with the "splitting" operator that generates the branching process on phylogenetic trees. For simplicity we proceed by discussing the two state case and note that our results are easily extended to more states with little complication. Intriguingly, upon restriction of the two state general Markov model to the parameter space of the binary symmetric model, our extension is indistinguishable from the previous approach only on trees; as soon as any incompatible splits are introduced the two approaches give rise to differing probability distributions with disparate structure. Through exploration of a simple example, we give a tentative argument that our approach to extending to more general networks has desirable properties that the previous approaches do not share. In particular, our construction allows for the possibility of convergent evolution of previously divergent lineages; a property that is of significant interest for biological applications.Comment: 17 pages, 5 figure

Polycyclic aromatic hydrocarbons degradation by composting in a soot-contaminated alkaline soil

none7noThis study deals with the biodegradation of the polycyclic aromatic hydrocarbons (PAH)s present in a soil contaminated by soot waste, characterised by a total PAHs content in the 200 mg kg−1 range. A challenging characteristic of the waste soil treated was its high alkalinity, with a pH of about 12.8. The waste came from a soot-contaminated area located in the industrial zone of Porto Marghera, Venice (Italy). The biodegradation process employed was the composting of the waste with sewage sludge and yard waste. The process was carried out on a pilot scale using a closed tank with forced aeration for a period of 60 days, followed by 70 days with natural aeration. The time evolution of the process was monitored by following the time change in the concentration of the 16 US-EPA PAHs, as well as temperature, pH, electrical conductivity, C and N contents. Also phytotoxicity parameters, such as the growth and respiration indexes, were monitored. An induction time of about 30 days was observed, which corresponded to the time required before observing a significant self-drop in the waste pH and an increase in mass temperature. Afterward, a progressive drop in the PAHs concentration was observed, up to reaching after 130 days an overall degradation percentage in the order of 68%. The degradation was more effective on rather low molecular weight PAHs (2–4 rings).mixedMoretto, L.M.; Silvestri, S.; Ugo, P; Zorzi, G.; Abbondanzi, F.; Baiocchi, C.; Iacondini, A.Moretto, L.M.; Silvestri, S.; Ugo, P; Zorzi, G.; Abbondanzi, F.; Baiocchi, C.; Iacondini, A

Genetic diversity of Leishmania amazonensis strains isolated in northeastern Brazil as revealed by DNA sequencing, PCR-based analyses and molecular karyotyping

Abstract\ud \ud \ud \ud Background\ud \ud Leishmania (Leishmania) amazonensis infection in man results in a clinical spectrum of disease manifestations ranging from cutaneous to mucosal or visceral involvement. In the present study, we have investigated the genetic variability of 18 L. amazonensis strains isolated in northeastern Brazil from patients with different clinical manifestations of leishmaniasis. Parasite DNA was analyzed by sequencing of the ITS flanking the 5.8 S subunit of the ribosomal RNA genes, by RAPD and SSR-PCR and by PFGE followed by hybridization with gene-specific probes.\ud \ud \ud \ud Results\ud \ud ITS sequencing and PCR-based methods revealed genetic heterogeneity among the L. amazonensis isolates examined and molecular karyotyping also showed variation in the chromosome size of different isolates. Unrooted genetic trees separated strains into different groups.\ud \ud \ud \ud Conclusion\ud \ud These results indicate that L. amazonensis strains isolated from leishmaniasis patients from northeastern Brazil are genetically diverse, however, no correlation between genetic polymorphism and phenotype were found.We thank Lucile FloeterWinter for critical reading of the manuscript and Artur T.L. de Queiroz for initial help with phylogenetic analysis. This work is supported by grants from CNPq, FAPESB and PAPES/FIOCRUZ. J.P.C. de Oliveira was supported by a CNPq fellowship; C.I.O. and F.M.C.F were supported by a FAPESB fellowship. AAC, AB, and CIO are senior investigators from CNPq. AB is a senior investigator for Instituto de Investigação em Imunologia (iii).We thank Lucile Floeter-Winter for critical reading of the manuscript and Artur T.L. de Queiroz for initial help with phylogenetic analysis. This work is supported by grants from CNPq, FAPESB and PAPES/FIOCRUZ. J.P.C. de Oliveira was supported by a CNPq fellowship; C.I.O. and F.M.C.F were supported by a FAPESB fellowship. AAC, AB, and CIO are senior investigators from CNPq. AB is a senior investigator for Instituto de Investigação em Imunologia (iii)

Gene expression profiling for molecular distinction and characterization of laser captured primary lung cancers

<p>Abstract</p> <p>Methods</p> <p>We examined gene expression profiles of tumor cells from 29 untreated patients with lung cancer (10 adenocarcinomas (AC), 10 squamous cell carcinomas (SCC), and 9 small cell lung cancer (SCLC)) in comparison to 5 samples of normal lung tissue (NT). The European and American methodological quality guidelines for microarray experiments were followed, including the stipulated use of laser capture microdissection for separation and purification of the lung cancer tumor cells from surrounding tissue.</p> <p>Results</p> <p>Based on differentially expressed genes, different lung cancer samples could be distinguished from each other and from normal lung tissue using hierarchical clustering. Comparing AC, SCC and SCLC with NT, we found 205, 335 and 404 genes, respectively, that were at least 2-fold differentially expressed (estimated false discovery rate: < 2.6%). Different lung cancer subtypes had distinct molecular phenotypes, which also reflected their biological characteristics. Differentially expressed genes in human lung tumors which may be of relevance in the respective lung cancer subtypes were corroborated by quantitative real-time PCR.</p> <p>Genetic programming (GP) was performed to construct a classifier for distinguishing between AC, SCC, SCLC, and NT. Forty genes, that could be used to correctly classify the tumor or NT samples, have been identified. In addition, all samples from an independent test set of 13 further tumors (AC or SCC) were also correctly classified.</p> <p>Conclusion</p> <p>The data from this research identified potential candidate genes which could be used as the basis for the development of diagnostic tools and lung tumor type-specific targeted therapies.</p