Projects 2 and 3: vulnerability and protective factors in early developmental stages of substance use disorders.
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Adolescent↗
Biomedical subjects
P Schuster
Publications and source records attributed to P Schuster.
[Lymphomatoid granulomatosis--remission induction with interferon-alpha 2b].
HISTORY AND ADMISSION FINDINGS: A 72-year-old woman was admitted to hospital because of nonproductive cough, acrodistal sensorimotor axonal polyneuropathy, fatigue and 10 kg weight loss over the preceding 9 months. INVESTIGATIONS: Chest radiogram showed multiple round foci in both lungs. No organs other than the lungs and the peripheral nervous system were affected. Open lung biopsy revealed a pleomorphic angioinvasive lymphocytic infiltrations. DIAGNOSIS, TREATMENT AND COURSE: The findings indicated lymphomatoid granulomatosis (LG). Wegener granulomatosis was excluded on the basis of the clinical, serological and histopathological findings. Treatment with alpha-interferon (IFN-alpha) produced complete remission within 4 months. Interruption of treatment immediately resulted in a recurrence. CONCLUSION: Together with previously reported cases this patient's response to IFN-alpha suggests that IFN-alpha is a less toxic alternative to cyclophosphamide and corticosteroid administration in the early stages of LG.
Aged↗
Genotypes with phenotypes: adventures in an RNA toy world.
Evolution has created the complexity of the animate world and deciphering the language of evolution is the key towards understanding nature. The dynamics of evolution is simplified by considering it as a superposition of three less sophisticated processes: population dynamics, population support dynamics, and genotype-phenotype mapping. Evolution of molecules in laboratory assays provides a sufficiently simple system for the quantitative analysis of the three phenomena. Coarse-grained notions of structures like RNA secondary structures are used as model phenotypes. They provide an excellent tool for a comprehensive analysis of the entire complex of molecular evolution. The mapping from RNA genotypes into secondary structures is highly redundant. In order to find at least one sequence for every common structures one need only search a (relatively) small part of sequence space. The existence of selectively neutral phenotypes plays an important role for the the success and the efficiency of evolutionary optimization. Molecular evolution found a highly promising technological application in the design of biomolecules with predefined properties.
Journal Article↗
Generic properties of combinatory maps: neutral networks of RNA secondary structures.
Random graph theory is used to model and analyse the relationships between sequences and secondary structures of RNA molecules, which are understood as mappings from sequence space into shape space. These maps are non-invertible since there are always many orders of magnitude more sequences than structures. Sequences folding into identical structures form neutral networks. A neutral network is embedded in the set of sequences that are compatible with the given structure. Networks are modeled as graphs and constructed by random choice of vertices from the space of compatible sequences. The theory characterizes neutral networks by the mean fraction of neutral neighbors (lambda). The networks are connected and percolate sequence space if the fraction of neutral nearest neighbors exceeds a threshold value (lambda > lambda *). Below threshold (lambda < lambda *), the networks are partitioned into a largest "giant" component and several smaller components. Structures are classified as "common" or "rare" according to the sizes of their pre-images, i.e. according to the fractions of sequences folding into them. The neutral networks of any pair of two different common structures almost touch each other, and, as expressed by the conjecture of shape space covering sequences folding into almost all common structures, can be found in a small ball of an arbitrary location in sequence space. The results from random graph theory are compared to data obtained by folding large samples of RNA sequences. Differences are explained in terms of specific features of RNA molecular structures.
Base Sequence↗
Autocatalytic networks with intermediates. I: Irreversible reactions.
A class of autocatalytic reaction networks based on template-dependent replication and specific catalysis is considered. Trimolecular "elementary steps" of simple replicator dynamics are resolved into two consecutive irreversible reactions. The extreme cases, competition for common resources and hypercycle-like cooperative feedback, were analyzed in some detail. Although the dynamics of the extended networks resembles corresponding replicator dynamics in general, there are significant differences. Most notably, the interior fixed points in the cooperative model turned out to be asymptotically stable for an arbitrary number of species, whereas simple replicator dynamic predicts an asymptotically stable periodic orbit fixed for four species and fewer and a stable periodic orbit for all other cases.
Bioreactors↗
RNA structures and folding: from conventional to new issues in structure predictions.
Prediction and modeling of RNA structures has become an indispensable tool of biological research disciplines. Currently, reliable predictions require massive input of experimental data. Structure-forming elements are conventional base pairs, as well as a rapidly increasing repertoire of novel structural motifs. New developments extend structural analysis beyond the one-sequence/one-structure paradigm and allow questions that are relevant to molecular evolution to be answered.
Algorithms↗
Approximate scaling properties of RNA free energy landscapes.
RNA free energy landscapes are analysed by means of "time-series" that are obtained from random walks restricted to excursion sets. The power spectra, the scaling of the jump size distribution, and the scaling of the curve length measured with different yard stick lengths are used to describe the structure of these "time series". Although they are stationary by construction, we find that their local behavior is consistent with both AR(1) and self-affine processes. Random walks confined to excursion sets (i.e., with the restriction that the fitness value exceeds a certain threshold at each step) exhibit essentially the same statistics as free random walks. We find that an AR(1) time series is in general approximately self-affine on timescales up to approximately the correlation length. We present an empirical relation between the correlation parameter rho of the AR(1) model and the exponents characterizing self-affinity.
Animals↗
Permanence of sparse catalytic networks.
Some global dynamical properties of catalytic networks, in particular permanence, are closely related with a directed graph representing the differential equation. It can be shown that for every directed graph with a Hamiltonian circuit there is a choice of rate constants such that the system is permanent. On the other hand, one can find properties of the graphs, for example, reducibility or the presence of endpoints, that are incompatible with permanence.
Biological Evolution↗
Error propagation in reproduction of diploid organisms. A case study on single peaked landscapes.
Two versions of the diploid selection mutation equation as adapted to sequence space are studied. Focussing on diploid generalizations of the well-established single peaked landscape, quantitative effects of dominance on error thresholds in infinite populations are found, as well as unexpected qualitative features like multiple equilibria. Analogues of these phenomena are also recovered in stochastic versions for finite populations.
Animals↗
How to search for RNA structures. Theoretical concepts in evolutionary biotechnology.
The relation between RNA sequences and minimum free energy secondary structures is viewed as a mapping from sequence space into shape space. The properties of such mappings depend strongly on the ratios of the numbers of sequences and structures and, hence, substantial differences are observed between samples of structures derived from AUGC, pure AU or pure GC sequences. Statistical analysis of large samples is used to demonstrate that structures from AUGC sequences are much less sensitive to point mutations than those from sequences containing exclusively AU or GC. The frequency with which a structure is realized in sequence space is inversely proportional to some power c > 1 of the structure's frequency rank, thus following a (generalized) Zipf law. For long sequences the exponent approaches c = 1. An inverse folding algorithm is used to compute samples of sequences folding into the same secondary structure. These sequences are distributed randomly in sequence space. Common structures form extended neutral networks along which populations can migrate through the entire sequence space without changing structure. In this migration, moves of Hamming distance d = 1 and d = 2 are accepted in order to allow for base and base pair exchanges, respectively. Around any arbitrarily chosen sequence a ball that contains sequences folding into all common structures can be drawn. This ball has a diameter that is much smaller than the diameter of sequence space. Hence, only a small fraction of sequence space needs to be searched in order to find a given structure. The results derived from the mapping of sequences into structures are used to suggest a rationale for evolutionary searches on RNA structures: selection cycles with high and low mutation rates applied in alternation. Generalizations of the results to RNA 3-D structures and protein structures are discussed.
Algorithms↗
From sequences to shapes and back: a case study in RNA secondary structures.
RNA folding is viewed here as a map assigning secondary structures to sequences. At fixed chain length the number of sequences far exceeds the number of structures. Frequencies of structures are highly non-uniform and follow a generalized form of Zipf's law: we find relatively few common and many rare ones. By using an algorithm for inverse folding, we show that sequences sharing the same structure are distributed randomly over sequence space. All common structures can be accessed from an arbitrary sequence by a number of mutations much smaller than the chain length. The sequence space is percolated by extensive neutral networks connecting nearest neighbours folding into identical structures. Implications for evolutionary adaptation and for applied molecular evolution are evident: finding a particular structure by mutation and selection is much simpler than expected and, even if catalytic activity should turn out to be sparse of RNA structures, it can hardly be missed by evolutionary processes.
Base Composition↗
Immune networks modeled by replicator equations.
In order to evaluate the role of idiotypic networks in the operation of the immune system a number of mathematical models have been formulated. Here we examine a class of B-cell models in which cell proliferation is governed by a non-negative, unimodal, symmetric response function f (h), where the field h summarizes the effect of the network on a single clone. We show that by transforming into relative concentrations, the B-cell network equations can be brought into a form that closely resembles the replicator equation. We then show that when the total number of clones in a network is conserved, the dynamics of the network can be represented by the dynamics of a replicator equation. The number of equilibria and their stability are then characterized using methods developed for the study of second-order replicator equations. Analogies with standard Lotka-Volterra equations are also indicated. A particularly interesting result of our analysis is the fact that even though the immune network equations are not second-order, the number and stability of their equilibria can be obtained by a superposition of second-order replicator systems. As a consequence, the problem of finding all of the equilibrium points of the nonlinear network equations can be reduced to solving linear equations.
Animals↗
Statistics of RNA melting kinetics.
We present and study the behavior of a simple kinetic model for the melting of RNA secondary structures, given that those structures are known. The model is then used as a map that assigns structure dependent overall rate constants of melting (or refolding) to a sequence. This induces a "landscape" of reaction rates, or activation energies, over the space of sequences with fixed length. We study the distribution and the correlation structure of these activation energies.
Base Sequence↗
Landscapes: complex optimization problems and biopolymer structures.
The evolution of RNA molecules in replication assays, viroids and RNA viruses can be viewed as an adaptation process on a 'fitness' landscape. The dynamics of evolution is hence tightly linked to the structure of the underlying landscape. Global features of landscapes can be described by statistical measures like number of optima, lengths of walks and correlation functions. The evolution of a quasispecies on such landscapes exhibits three dynamical regimes depending on the replication fidelity: Above the "localization threshold" the population is centered around a (local) optimum. Between localization and "dispersion threshold" the population is still centered around a consensus sequence, which, however, changes in time. For very large mutation rates the population spreads in sequence space like a gas. The critical mutation rates separating the three domains depend strongly on characteristics properties of the fitness landscapes. Statistical characteristics of RNA landscapes are accessible by mathematical analysis and computer calculations on the level of secondary structures: these RNA landscapes belong to the same class as well known optimization problems and simple spin glass models. The notion of a landscape is extended to combinatory maps, thereby allowing for a direct statistical investigation of the sequence structure relationships of RNA at the level of secondary structures. Frequencies of structures are highly non-uniform: we find relatively few common and many rare ones, as expressed by a generalized form of Zipf's law. Using an algorithm for inverse folding we show that sequences sharing the same structure are distributed randomly over sequence space. Together with calculations of structure correlations and a survey of neutral mutations this provides convincing evidence that RNA landscapes are as simple as they could possibly be for evolutionary adaptation: Any desired secondary structure can be found close to an arbitrary initial sequence and at the same time almost all bases can be substituted sequentially without ever changing the shape of the molecule. Consequences of these results for evolutionary optimization, the early stages of life, and molecular biotechnology are discussed.
Adaptation, Biological↗
[Aneurysm of the left atrial appendage with intact pericardium].
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Adult↗
Statistics of RNA secondary structures.
A statistical reference for RNA secondary structures with minimum free energies is computed by folding large ensembles of random RNA sequences. Four nucleotide alphabets are used: two binary alphabets, AU and GC, the biophysical AUGC and the synthetic GCXK alphabet. RNA secondary structures are made of structural elements, such as stacks, loops, joints, and free ends. Statistical properties of these elements are computed for small RNA molecules of chain lengths up to 100. The results of RNA structure statistics depend strongly on the particular alphabet chosen. The statistical reference is compared with the data derived from natural RNA molecules with similar base frequencies. Secondary structures are represented as trees. Tree editing provides a quantitative measure for the distance dt, between two structures. We compute a structure density surface as the conditional probability of two structures having distance t given that their sequences have distance h. This surface indicates that the vast majority of possible minimum free energy secondary structures occur within a fairly small neighborhood of any typical (random) sequence. Correlation lengths for secondary structures in their tree representations are computed from probability densities. They are appropriate measures for the complexity of the sequence-structure relation. The correlation length also provides a quantitative estimate for the mean sensitivity of structures to point mutations.
Base Sequence↗
RNA multi-structure landscapes. A study based on temperature dependent partition functions.
Statistical properties of RNA folding landscapes obtained by the partition function algorithm (McCaskill 1990) are investigated in detail. The pair correlation of free energies as a function of the Hamming distance is used as a measure for the ruggedness of the landscape. The calculation of the partition function contains information about the entire ensemble of secondary structures as a function of temperature and opens the door to all quantities of thermodynamic interest, in contrast with the conventional minimal free energy approach. A metric distance of structure ensembles is introduced and pair correlations at the level of the structures themselves are computed. Just as with landscapes based on most stable secondary structure prediction, the landscapes defined on the full biophysical GCAU alphabet are much smoother than the landscapes restricted to pure GC sequences and the correlation lengths are almost constant fractions of the chain lengths. Correlation functions for multi-structure landscape exhibit an increased correlation length, especially near the melting temperature. However, the main effect on evolution is rather an effective increase in sampling for finite populations where each sequence explores multiple structures.
Base Composition↗
RNA based evolutionary optimization.
The notion of an RNA world has been introduced for a prebiotic scenario that is dominated by RNA molecules and their properties, in particular their capabilities to act as templates for reproduction and as catalysts for several cleavage and ligation reactions of polynucleotides and polypeptides. This notion is used here also for simple experimental assays which are well suited to study evolution in the test tube. In molecular evolution experiments fitness is determined in essence by the molecular structures of RNA molecules. Evidence is presented for adaptation to environment in cell-free media. RNA based molecular evolution experiments have led to interesting spin-offs in biotechnology, commonly called 'applied molecular evolution', which make use of Darwinian trial-and-error strategies in order to synthesize new pharmacological compounds and other advanced materials on a biological basis. Error-propagation in RNA replication leads to formation of mutant spectra called 'quasispecies'. An increase in the error rate broadens the mutant spectrum. There exists a sharply defined threshold beyond which heredity breaks down and evolutionary adaptation becomes impossible. Almost all RNA viruses studied so far operate at conditions close to this error threshold. Quasispecies and error thresholds are important for an understanding of RNA virus evolution, and they may help to develop novel antiviral strategies. Evolution of RNA molecules can be studied and interpreted by considering secondary structures. The notion of sequence space introduces a distance between pairs of RNA sequences which is tantamount to counting the minimal number of point mutations required to convert the sequences into each other. The mean sensitivity of RNA secondary structures to mutation depends strongly on the base pairing alphabet: structures from sequences which contain only one base pair (GC or AU are much less stable against mutation than those derived from the natural (AUGC) sequences. Evolutionary optimization of two-letter sequences in thus more difficult than optimization in the world of natural RNA sequences with four bases. This fact might explain the usage of four bases in the genetic language of nature. Finally we study the mapping from RNA sequences into secondary structures and explore the topology of RNA shape space. We find that 'neutral paths' connecting neighbouring sequences with identical structures go very frequently through entire sequence space. Sequences folding into common structures are found everywhere in sequence space.(ABSTRACT TRUNCATED AT 400 WORDS)
Adaptation, Physiological↗