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PubMed2026

A step-wise, deterministic and fatal mouse model of myeloid neoplasm with spontaneous acquisition of patient-relevant RTK-RAS mutations.

Leukaemia arises through the stepwise transformation of healthy haematopoietic cells, yet the asymptomatic premalignant phase and its progression to overt disease remain poorly understood. To model this process, we engineered a patient-derived CEBPA mutation into Hoxb8-FL multipotent murine progenitors and transplanted them into syngeneic mice, capturing a clinically silent premalignant stage. All recipients developed overt disease after ~12 months with 100% penetrance and all acquired secondary RTK-RAS mutations, often with identical amino acid changes to those in patients. Single-cell transcriptomics and phenotypic profiling showed that premalignant mutant cells adopt a plasmacytoid dendritic progenitor-like state in vitro which generates both myeloid and B-lymphoid lineages during premalignancy in vivo, with individual tumours restricted to one lineage. The specificity for RTK-RAS mutations coupled with ongoing differentiation, reflects clinically relevant biological contexts thus providing a tractable model of myeloid neoplasm for mechanistic studies and drug discovery.

Journal Article↗
PubMed1995

Dynamical analysis of neuromuscular transmission jitter.

Utilizing prolonged axonal stimulation single fiber EMG, neuromuscular transmission becomes a time-series of interpotential intervals (IPIs). In this form, the underlying processes of neuromuscular transmission can be studied using standard numerical techniques to determine whether these processes can be described by a simple mathematical model. In particular, neuromuscular transmission jitter can be examined in this way. In this article, we attempt to determine whether healthy jitter is noise or deterministic chaos. The presence of deterministic chaos was assessed by analysis of the IPI time-series using visual inspection of both phase-space plots and their principal component dimensions, and using the Grassberger-Procaccia algorithm to determine the correlation dimension of the time-series dynamics. These graphical and mathematical techniques provided little evidence for the existence of deterministic chaos. Linear autoregression time-series prediction also failed to account for the variability of the data and IPI histograms exhibited simple gaussian distributions. These results suggest normal neuromuscular transmission jitter is the result of intrinsic noise.

Action Potentials↗
PubMed1991

A stochastic model for the development of an AIDS epidemic in a heterosexual population.

A non-age-dependent model, describing the evolution of a bisexual population, is developed in this paper and applied to projecting an AIDS epidemic in a heterosexual population. Included in the formulation are frequency- and non-frequency-dependent rules of partnership formation as well as five states of HIV disease, affecting the probability of infection per sexual contact. Results from computer experiments, designed to study the development of an AIDS epidemic in a heterosexual population fed by single males with a 50% prevalence of HIV infection prior to becoming active in heterosexual partnerships, are reported. In these experiments, the only source of HIV infection for females was sexual contacts with infected males within partnerships. Data on the probability of infection per sexual contact with an infected partner and the number of sexual contacts per month were incorporated into the model. However, the numbers used for the initial population of singles, couples, and those becoming sexually active per month were hypothetical. Even though the prevalence of HIV infection among males entering heterosexual partnerships was high, after 30 years the projected prevalence of HIV infection among females ranged from about 10 to 15% depending in part on the expected duration of partnerships and on whether the frequency- or non-frequency-dependent model was used. In these experiments, solutions of the embedded, nonlinear, deterministic equations for the incidence of HIV infection and the cumulative number of deaths due to AIDS proved to be good measures of central tendency for the sample functions of the stochastic population process.

Acquired Immunodeficiency Syndrome↗
PubMed1992

Quantal noise and decision rules in dynamic models of light adaptation.

To evaluate some of the consequences of including probabilistic processes (e.g. quantal noise) in a computable model of light-adaptation dynamics, we considered the behavior of a general class of models. These models contain four stages: (1) early noise; (2) a deterministic filtering and gain-changing stage; (3) late noise; (4) a decision rule that is either an ideal (signal-known-exactly) detector or a peak-trough detector. With the ideal detector and without late noise, the observer's sensitivity as a function of mean luminance and temporal frequency is not affected by the filtering and gain-changing stage. Consequently, if the early noise is entirely quantal fluctuations, sensitivity will always be a square-root function of mean luminance and a uniform (flat) function of temporal frequency. This latter prediction is contradicted by all known data; either the ideal-detector is the wrong decision rule or sensitivity is almost always limited by sources of noise other than quantal fluctuations. With the peak-trough detector, however, with or without late noise, the observer's sensitivity as a function of temporal frequency does reflect the sensitivity of the low-level filtering and gain-changing stage. Late noise is needed, however, if the observer's sensitivity as a function of mean luminance is to go through both a square-root and a Weber region. Comparing these conclusions to similar work on the spatial frequency dimension highlights differences between the spatial and temporal frequency domains. Finally, on the basis of these analyses and evidence from the literature, we question whether quantal fluctuations limit visual sensitivity under any condition.

Adaptation, Ocular↗
PubMed2001

Non-thermal melting in semiconductors measured at femtosecond resolution.

Ultrafast time-resolved optical spectroscopy has revealed new classes of physical, chemical and biological reactions, in which directed, deterministic motions of atoms have a key role. This contrasts with the random, diffusive motion of atoms across activation barriers that typically determines kinetic rates on slower timescales. An example of these new processes is the ultrafast melting of semiconductors, which is believed to arise from a strong modification of the inter-atomic forces owing to laser-induced promotion of a large fraction (10% or more) of the valence electrons to the conduction band. The atoms immediately begin to move and rapidly gain sufficient kinetic energy to induce melting--much faster than the several picoseconds required to convert the electronic energy into thermal motions. Here we present measurements of the characteristic melting time of InSb with a recently developed technique of ultrafast time-resolved X-ray diffraction that, in contrast to optical spectroscopy, provides a direct probe of the changing atomic structure. The data establish unambiguously a loss of long-range order up to 900 A inside the crystal, with time constants as short as 350 femtoseconds. This ability to obtain the quantitative structural characterization of non-thermal processes should find widespread application in the study of ultrafast dynamics in other physical, chemical and biological systems.

Journal Article↗
PubMed2003

A two-stage interval-stochastic programming model for waste management under uncertainty.

This study introduces a two-stage interval-stochastic programming (TISP) model for the planning of solid-waste management systems under uncertainty. The model is derived by incorporating the concept of two-stage stochastic programming within an interval-parameter optimization framework. The approach has the advantage that policy determined by the authorities, and uncertain information expressed as intervals and probability distributions, can be effectively communicated into the optimization processes and resulting solutions. In the modeling formulation, penalties are imposed when policies expressed as allowable waste-loading levels are violated. In its solution algorithm, the TISP model is converted into two deterministic submodels, which correspond to the lower and upper bounds for the desired objective-function value. Interval solutions, which are stable in the given decision space with associated levels of system-failure risk, can then be obtained by solving the two submodels sequentially. Two special characteristics of the proposed approach make it unique compared with other optimization techniques that deal with uncertainties. First, the TISP model provides a linkage to predefined policies determined by authorities that have to be respected when a modeling effort is undertaken; second, it furnishes the reflection of uncertainties presented as both probabilities and intervals. The developed model is applied to a hypothetical case study of regional solid-waste management. The results indicate that reasonable solutions have been generated. They provide desired waste-flow patterns with minimized system costs and maximized system feasibility. The solutions present as stable interval solutions with different risk levels in violating the waste-loading criterion and can be used for generating decision alternatives.

Environment↗
PubMed2002

A CT image based deterministic approach to dosimetry and radiography simulations.

An integral transport equation based deterministic approach has been developed to compute individual specific absorbed dose distributions and photon flux distributions on a detector for image formation studies. An algorithm has been designed to take advantage of parallel processing platforms capable of processing large amounts of data imposed by the small pixel sizes of CT images. CT images have been used to form voxels that would represent both tissue variations and body geometry. Absorbed dose distributions calculated using the Visible Human dataset are provided.

Algorithms↗
PubMed2001

New data and tools for integrating discrete and continuous population modeling strategies.

Realistic population models have interactions between individuals. Such interactions cause populations to behave as systems with nonlinear dynamics. Much population data analysis is done using linear models assuming no interactions between individuals. Such analyses miss strong influences on population behavior and can lead to serious errors--especially for infectious diseases. To promote more effective population system analyses, we present a flexible and intuitive modeling framework for infection transmission systems. This framework will help population scientists gain insight into population dynamics, develop theory about population processes, better analyze and interpret population data, design more powerful and informative studies, and better inform policy decisions. Our framework uses a hierarchy of infection transmission system models. Four levels are presented here: deterministic compartmental models using ordinary differential equations (DE); stochastic compartmental (SC) models that relax assumptions about population size and include stochastic effects; individual event history models (IEH) that relax the SC compartmental structure assumptions by allowing each individual to be unique. IEH models also track each individual's history, and thus, allow the simulation of field studies. Finally, dynamic network (DNW) models relax the assumption of the previous models that contacts between individuals are instantaneous events that do not affect subsequent contacts. Eventually it should be possible to transit between these model forms at the click of a mouse. An example is presented dealing with Cryptosporidium. It illustrates how transiting model forms helps assess water contamination effects, evaluate control options, and design studies of infection transmission systems using nucleotide sequences of infectious agents.

Data Interpretation, Statistical↗
PubMed1993

Statistical moments in pharmacokinetics: models and assumptions.

The modelling basis of statistical moments in pharmacokinetics is considered and the associated assumptions and restrictions highlighted. Both deterministic and statistical models are described and they are seen to give identical results on the basis of equivalent assumptions. It is shown that it is not necessary to assume that all kinetic processes are first order and that some of the pharmacokinetic parameters may be dependent on the dose of administered drug and on the route of administration.

Models, Statistical↗
PubMed1977

Mutation-selection balance with stochastic selection.

Diffusion theory has been used to analyze a model of mutation-selection balance in which the selection process is assumed to be stochastic in time. The limiting outcome of the mutation-stochastic selection process is determined qualitatively by the geometric mean fitnesses of the genotypes, and the conditions for fixation or polymorphism are similar to those that determine the outcome of the mutation-selection process when selection is constant. However, in the case of a completely recessive allele, detailed numerical study of the polymorphism associated with stochastic selection has shown that the average allele frequency maintained is greater than the equilibrium frequency expected when selection is constant, even when the geometric mean fitness of the recessive homozygotes is identical in the stochastic and deterministic models. Thus, allele frequencies in natural populations that are too high to be plausibly explained by a balance between mutation and constant selection can be accounted for if selection is stochastic.

Alleles↗
PubMed2000

Impossibility of deleting an unknown quantum state

A photon in an arbitrary polarization state cannot be cloned perfectly. But suppose that at our disposal we have several copies of a photon in an unknown state. Is it possible to delete the information content of one or more of these photons by a physical process? Specifically, if two photons are in the same initial polarization state, is there a mechanism that produces one photon in the same initial state and the other in some standard polarization state? If this could be done, then one would create a standard blank state onto which one could copy an unknown state approximately, by deterministic cloning or exactly, by probabilistic cloning. This could in principle be useful in quantum computation, where one could store new information in an already computed state by deleting the old information. Here we show, however, that the linearity of quantum theory does not allow us to delete a copy of an arbitrary quantum state perfectly. Though in a classical computer information can be deleted (reversibly) against a copy, the analogous task cannot be accomplished, even irreversibly, with quantum information.

Journal Article↗
PubMed1991

Radiobiological fundamentals in radioepidemiology and radiation protection.

Radiation is a convenient tool to study fundamental processes of life. Biological effects of irradiation may result from indirect actions which are mediated by free radicals (e.g. OH-radicals) or from direct actions which involve ionizations in the DNA and other biomolecules. Damage to the DNA is the principal, but not exclusive target for cell death, loss of reproductive integrity, mutation, cancer, developmental anomalies and other radiobiological effects. Repair of damaged DNA and cellular recovery processes play an essential role in affecting the survival of cells. Dose, dose rate, radiation quality, biological and chemical modifiers also have a pronounced effect upon the extent of radiation responses. The biological effects of ionizing radiation are somatic or hereditary and can further be classified into stochastic and deterministic effects. For radiation epidemiology and protection the stochastic action is more relevant because the probability of an effect is a function of dose, without a threshold. Induction of cancer, hereditary diseases and probably also mental retardation are regarded as stochastic effects.

Cell Survival↗
PubMed2002

Who killed Laius?: On Sophocles' enigmatic message.

Using Laplanche's basic conceptualisation of the role of the other in unconscious processes, the author proposes a reading of Sophocles' tragedy, Oedipus the King, according to basic principles of dream interpretation. This reading corroborates contemporary literary perspectives suggesting that Sophocles' tragedy may not only convey the myth but also provide a critical analysis of how myths work. Important textual inconsistencies and incoherence, which have been noted through the centuries, suggest the existence of another, repressed story. Moreover, the action of the play points to enigmatic parental messages of infanticide and the silencing of Oedipus's story, as well as their translation into primordial guilt, as the origins of the tragic denouement. Oedipus's self-condemnation of parricide follows these enigmatic codes and is unrelated to, and may even contradict, the evidence offered in the tragedy as to the identity of Laius's murderers. Moreover, Sophocles' text provides a complex intertwining of hermeneutic and deterministic perspectives. Through the use of the mythical deterministic content, the formal characteristics of Sophocles' text, mainly its complex time perspective and extensive use of double meaning, dramatise in the act of reading an acute awareness of interpretation. This reading underscores the fundamental role of the other in the constitution of unconscious processes.

Adult↗
PubMed2002

WHO KILLED LAIUS?: ON SOPHOCLES' ENIGMATIC MESSAGE.

Using Laplanche's basic conceptualisation of the role of the other in unconscious processes, the author proposes a reading of Sophocles' tragedy, Oedipus the King, according to basic principles of dream interpretation. This reading corroborates contemporary literary perspectives suggesting that Sophocles' tragedy may not only convey the myth but also provide a critical analysis of how myths work. Important textual inconsistencies and incoherence, which have been noted through the centuries, suggest the existence of another, repressed story. Moreover, the action of the play points to enigmatic parental messages of infanticide and the silencing of Oedipus's story, as well as their translation into primordial guilt, as the origins of the tragic denouement. Oedipus's self-condemnation of parricide follows these enigmatic codes and is unrelated to, and may even contradict, the evidence offered in the tragedy as to the identity of Laius's murderers. Moreover, Sophocles' text provides a complex intertwining of hermeneutic and deterministic perspectives. Through the use of the mythical deterministic content, the formal characteristics of Sophocles' text, mainly its complex time perspective and extensive use of double meaning, dramatise in the act of reading an acute awareness of interpretation. This reading underscores the fundamental role of the other in the constitution of unconscious processes.

Journal Article↗
PubMed1999

Population dynamics under parasitic sex ratio distortion.

We analyse the population dynamic effects of sex ratio distortion by vertically transmitted, feminizing parasites. We show that, for diploid hosts, sex ratio distortion may lead to extinction as males become too rare to maintain the host population through reproduction. Feminizers can magnify Allee effects, broadening the range of conditions leading to extinction of small populations. Depending on male mating constraints and strength of density dependence, feminizers may either increase or decrease the equilibrium host density. Under conditions leading to deterministic host extinction, stochastic elimination of the parasite may allow the host population to recover. Hence, infection by parasitic sex ratio distorters may be transient in finite populations. We consider the implications of this process for parasite prevalence, host population regulation, and sex ratio evolution.

Animals↗
PubMed1999

The kinetics of nerve-evoked quantal secretion.

Current views on quantal release of neurotransmitters hold that after the vesicle migrates towards release sites (active zones), multiple protein interactions mediate the docking of the vesicle to the presynaptic membrane and the formation of a multimolecular protein complex (the 'fusion machine') which ultimately makes the vesicle competent to release a quantum in response to the action potential. Classical biophysical studies of quantal release have modelled the process by a binomial system where n vesicles (sites) competent for exocytosis release a quantum, with probability p, in response to the action potential. This is likely to be an oversimplified model. Furthermore, statistical and kinetic studies have given results which are difficult to reconcile within this framework. Here, data are presented and discussed which suggest a revision of the biophysical model. Transient silencing of release is shown to occur following the pulse of synchronous transmitter release, which is evoked by the presynaptic action potential. This points to a schema where the vesicle fusion complex assembly is a reversible, stochastic process. Asynchronous exocytosis may occur at several intermediate stages in the process, along paths which may be differentially regulated by divalent cations or other factors. The fusion complex becomes competent for synchronous release (armed vesicles) only at appropriately organized sites. The action potential then triggers (deterministically rather than stochastically) the synchronous discharge of all armed vesicles. The existence of a specific conformation for the fusion complex to be competent for synchronous evoked fusion reconciles statistical and kinetic results during repetitive stimulation and helps explain the specific effects of toxins and genetic manipulation on the synchronization of release in response to an action potential.

Action Potentials↗
PubMed1983

Theoretical framework for spectrum analysis in ultrasonic tissue characterization.

An analytic model is described for application in ultrasonic tissue characterization. The model is applicable to clinical broadband pulse echo systems. It treats spectra derived from received echo signals and relates them to physical tissue properties. The model can be applied to deterministic tissue structures (e.g., retinal detachments, larger blood vessels, and surface layers of the kidney) and to stochastic tissue structures (e.g., various tumors). The beam patterns included in the model are those generated by focused transducers typically used in high-resolution clinical ultrasound. Appropriate calibration procedures are also treated; these are needed for interpretation of absolute spectral parameters. The results obtained with the analytic model have been used to design a digital processing system and the associated techniques which are now being applied during examinations of the eye and abdominal organs. The results have proven useful in interpreting data from various types of tissues. To illustrate the application of these results, representative clinical data, obtained from the digital system, are presented for two types of tissue architectures. The first case is a detached retina representing a deterministic structure characterized by well-defined thickness and reflection coefficients. The second case is asteroid hyalosis and represents a stochastic entity in which the positions of small scattering particles are best described in statistical terms, and characterization is accompanied by means of normalized power spectra.

Eye Diseases↗
PubMed1994

Chaos and physiology: deterministic chaos in excitable cell assemblies.

In this review we examined the emerging science of deterministic chaos (nonlinear systems theory) and its application to selected physiological systems. Although many of the popular images of fractals represent fascination and beauty that by analogy corresponds to nature as we see it, the question remains as to its ultimate meaning for physiological processes. It was our intent to help clarify this somewhat popular, somewhat obscure area of nonlinear dynamics in the context of an ever-changing procedural base. We examined not only the basic concepts of chaos, but also its applications ranging from observations in single cells to the complexity of the EEG. We have not suggested that nonlinear dynamics will answer all of our questions; however, we did attempt to illustrate ways in which this approach may help us to answer new questions and to rearticulate old ones. Chaos is revolutionary in that the overall approach requires us to adopt a different frame of reference which, at times, may move us away from previous concerns and methods of data analysis. In sections I-IV, we summarized the nonlinear dynamics approach and described its application to physiology and neural systems. First, we presented a general overview of the application of nonlinear dynamical techniques to neural systems. We discussed the manner in which even apparently simple deterministic systems can behave in an unpredictable manner. Second, we described the principles of nonlinear dynamical systems including the derived analytical techniques. We now see a variety of procedures for delineating whether frenetic chaotic behavior results from a nonlinear dynamical system with a few degrees of freedom, or whether it is caused by an infinite number of variables, i.e., noise. Third, we approached the applications of nonlinear procedures to the cardiovascular systems and to the neurosciences. In terms of time series, we described initial studies which applied the now "traditional" measures of dimensionality (e.g., based on the algorithm by Grassberger and Procaccia) and information change (e.g., Lyapunov exponents). Examples include our own work and that of Pritchard et al., demonstrating that the dynamics of neural mass activity reflect psychopathological states. Today, however, the trend has expanded to include the use of surrogate data and statistical null hypotheses testing to examine whether a given time series can be considered different from that of white or colored noise (cf. Ref. 262). One of the most important potential applications is that of quantifying changes in nonlinear dynamics to predict future states of the system.(ABSTRACT TRUNCATED AT 400 WORDS)

Animals↗