The role of apoptosis in tumor progression and metastasis

Metastasis, the process by which cancer spreads from a primary to a secondary site, is responsible for the majority of cancer related deaths. Yet despite the detrimental effects of metastasis, it is an extremely inefficient process by which very few of the cells that leave the primary tumor give rise to secondary tumors. Metastasis can be considered as a series of sequential steps that begins with a cell leaving a primary tumor, and concludes with the formation of a metastatic tumor in a distant site. During the process of metastasis cells are subjected to various apoptotic stimuli. Thus, in addition to genetic changes that promote unregulated proliferation, successful metastatic cells must have a decreased sensitivity to apoptotic stimuli. As many cancer cells exhibit aberrations in the level and function of key apoptotic regulators, exploiting these alterations to induce tumor cell apoptosis offers a promising therapeutic target. This review will examine the apoptotic regulators that are often aberrantly expressed in metastatic cells; the role that these regulators may play in metastasis; the steps of metastasis and their susceptibility to apoptosis; and finally, current and future cancer prognostics and treatment targets based on apoptotic regulators.     

Eukaryotic chemotaxis: distinctions between directional sensing and polarization

Directional sensing and polarization are fundamental cellular responses that play a central role in health and disease. In this review we define each process and evaluate a series of models previously proposed to explain these phenomena. New findings show that directional sensing by G protein-coupled receptors is localized at a discrete step in the signaling pathway downstream of G protein activation but upstream of the accumulation of PIP3. Local levels of PIP3, whether triggered by chemoattractants, particle binding, or spontaneous events, determine the sites of new actin-filled projections. Robust control of the temporal and spatial levels of PIP3 is achieved by reciprocal regulation of PI3K and PTEN. These observations suggest that a local excitation-global inhibition model can account for the localization of PI3K and PTEN and thereby explain directional sensing. However, elements of other models, including positive feedback and the reaction of the cytoskeleton, must be invoked to account for polarization.     

Locations of radiation-produced DNA double strand breaks along chromosomes: a stochastic cluster process formalism.

Ionizing radiation produces DNA double strand breaks (DSBs) in chromosomes. For densely ionizing radiation, the DSBs are not spaced randomly along a chromosome: recent data for size distributions of DNA fragments indicate break clustering on kbp-Mbp scales. Different DSB clusters on a chromosome are typically made by different, statistically independent, stochastically structured radiation tracks, and the average number of tracks involved can be small. We therefore model DSB positions along a chromosome as a stationary Poisson cluster process, i.e. a stochastic process consisting of secondary point processes whose locations are determined by a primary point process that is Poisson. Each secondary process represents a break cluster, typically consisting of 1-10 DSBs in a comparatively localized stochastic pattern determined by chromatin geometry and radiation track structure. Using this Poisson cluster process model, which we call the randomly located clusters (RLC) formalism, theorems are derived for how the DNA fragment-size distribution depends on radiation dose. The RLC dose-response relations become non-linear when the dose becomes so high that DSB clusters from different tracks overlap or adjoin closely. The RLC formalism generalizes previous models, fits current data adequately and facilitates mechanistically based extrapolations from high-dose experiments to the much lower doses of interest for most applications.     

Selection and fitness in bacteriocin-producing bacteria.

Bacteriocins are proteinaceous anticompetitor molecules produced by bacteria against closely related species. A number of theoretical models have been used to explain experimental data that indicate high polymorphisms among bacteriocins and a frequency-dependent nature of selection for bacteriocin-producing strains. The majority of these experimental data were, however, obtained from investigations into the colicin group of bacteriocins produced by Gram-negative bacteria. The conclusions drawn from these models have been extrapolated to other bacteriocins and allelopathic compounds in general. Examination of more recent experimental investigations into the bacteriocins of Gram-positive bacteria indicate a lower degree of polymorphism and a less frequency dependent mode of selection among these strains them among the colicin-producing strains. Here we examine these contradictions in the light of the assumptions and conclusions of the theoretical models and reported data. We show that fitness costs as indicated by decreased relative maximum growth rate associated with bacteriocin production may be much lower in many cases than is assumed in the present models. A lower fitness cost associated with bacteriocin production adequately explains the newer data from Gram-positive bacteria cited here, and indicates that extrapolation of existing models to all bacteriocins and other allelopathic compounds is not appropriate.     

The movement of bound ligands over cell surfaces

The long range movements of membrane-bound ligands into surface caps and into the pseudopods of phagocytizing cells, the uropods of motile cells and the cleavage furrow of dividing cells appear to be analogous processes. A common mechanism to explain these movements must take into account several new and central observations: ligand-receptor complexes can migrate to regions of existing microfilament accumulation; laser photobleaching studies with fluorescent Con A indicate that ligand-receptor movement occurs unidirectionally; video computer analyses of Con A redistribution show that movement may exceed the maximum rates measured for protein diffusion in membranes. These observations are not consistent with models in which ligand-receptor movement occurs by diffusion or by direct interaction with contractile microfilaments. However, they can be satisfied by a new model that proposes the entrainment of selected membrane determinants on membrane waves directed towards regions such as caps, pseudopodia, uropods or cleavage furrow. These oriented waves are initiated by tension due to asymmetric microfilamentmembrane interaction.     

Measuring probabilistic reaction norms for age and size at maturation

We present a new probabilistic concept of reaction norms for age and size at maturation that is applicable when observations are carried out at discrete time intervals. This approach can also be used to estimate reaction norms for age and size at metamorphosis or at other ontogenetic transitions. Such estimations are critical for understanding phenotypic plasticity and life-history changes in variable environments, assessing genetic changes in the presence of phenotypic plasticity, and calibrating size- and age-structured population models. We show that previous approaches to this problem, based on regressing size against age at maturation, give results that are systematically biased when compared to the probabilistic reaction norms. The bias can be substantial and is likely to lead to qualitatively incorrect conclusions; it is caused by failing to account for the probabilistic nature of the maturation process. We explain why, instead, robust estimations of maturation reaction norms should be based on logistic regression or on other statistical models that treat the probability of maturing as a dependent variable. We demonstrate the utility of our approach with two examples. First, the analysis of data generated for a known reaction norm highlights some crucial limitations of previous approaches. Second, application to the northeast arctic cod (Gadus morhua) illustrates how our approach can be used to shed new light on existing real-world data.     

Quantum physics in neuroscience and psychology: a neurophysical model of mind-brain interaction

Neuropsychological research on the neural basis of behaviour generally posits that brain mechanisms will ultimately suffice to explain all psychologically described phenomena. This assumption stems from the idea that the brain is made up entirely of material particles and fields, and that all causal mechanisms relevant to neuroscience can therefore be formulated solely in terms of properties of these elements. Thus, terms having intrinsic mentalistic and/or experiential content (e.g. 'feeling', 'knowing' and 'effort') are not included as primary causal factors. This theoretical restriction is motivated primarily by ideas about the natural world that have been known to be fundamentally incorrect for more than three-quarters of a century. Contemporary basic physical theory differs profoundly from classic physics on the important matter of how the consciousness of human agents enters into the structure of empirical phenomena. The new principles contradict the older idea that local mechanical processes alone can account for the structure of all observed empirical data. Contemporary physical theory brings directly and irreducibly into the overall causal structure certain psychologically described choices made by human agents about how they will act. This key development in basic physical theory is applicable to neuroscience, and it provides neuroscientists and psychologists with an alternative conceptual framework for describing neural processes. Indeed, owing to certain structural features of ion channels critical to synaptic function, contemporary physical theory must in principle be used when analysing human brain dynamics. The new framework, unlike its classic-physics-based predecessor, is erected directly upon, and is compatible with, the prevailing principles of physics. It is able to represent more adequately than classic concepts the neuroplastic mechanisms relevant to the growing number of empirical studies of the capacity of directed attention and mental effort to systematically alter brain function.     

The secondary sex ratio in Israel: 1980-1995

This study deals with models and hypotheses that attempt to explain the underlying mechanisms determining the sex ratios at birth in human populations. Since the factors responsible are still questionable and research results are contradictory, we examine data available in Israel on the sex ratios at birth among two different sociodemographic groups, Jews and Moslems. Results suggest a difference between Jewish and Moslem patterns of secondary sex ratios with respect to parental age, education, and birth number. The difference may be described as a more regular and, by existing models, a more predictable pattern of secondary sex ratio among Moslems than among Jews. The possibility that Jewish religious laws play a role in this difference is discussed.     

Epidermal cell proliferation. II. A comprehensive mathematical model of cell proliferation and migration in the basal layer predicts some unusual properties of epidermal stem cells

The clustering of 3HTdR labelled cells in the epidermal basal layer and their changes with time have been modelled mathematically and cannot be adequately fitted by an earlier model of the cell kinetic organisation of the skin. A more refined model analysis was performed based on Monte Carlo computer simulations of cell layers which take cell division, cell aging and lateral as well as vertical cell migration into account. A large variety of hypothetical scenarios was tested to see if each could provide a fit to the clustering data. The analysis provides further support for the concept of a cell kinetic heterogeneity with a stem-transit-postmitotic differentiation scheme. In the best overall model scheme three transit divisions are predicted but unlike in the earlier model it is now postulated that postmitotic cells can be produced at all stages in the lineage rather than only at the end of the amplification scheme. Most important, the model predicts that stem cells and most of the transit cells differ in the way they process 3HTdR label. Grain dilution is an important mechanism to explain the fate of some labelled cells in the tissue, but on its own it can only consistently explain the data if the stem cells have a very low labelling index (LI less than or equal to 1%) which implies a very short biologically unreasonable S-phase. If a higher LI (longer S-phase) is assumed for the stem-cells other mechanisms must be predicted to explain the lack of large clusters and the increase in time of the singles. The selective segregation of chromosomes at mitosis is one such mechanism. However, on its own a large number of cells would have to behave in this way (i.e. both stem and T1 cells). If combined with other assumptions such as some grain dilution this selective segregation may be restricted only to stem cells. In addition the model allows cell production and migration rates to be estimated and the analysis can be related to the EPU-concept. Indeed the model itself would tend to automatically generate an EPU like structure. The model quantitatively reproduces LI, PLM, CL and clustering data.     

Simulation of exposure and SAR estimation for adult and child heads exposed to radiofrequency energy from portable communication devices

The level and distribution of radiofrequency energy absorbed in a child's head during the use of a mobile phone compared to those in an adult head has been a controversial issue in recent years. It has been suggested that existing methods that are used to determine specific absorption rate (SAR) and assess compliance with exposure standards using an adult head model may not adequately account for potentially higher levels of exposure in children due to their smaller head size. The present study incorporates FDTD computations of locally averaged SAR in two different anatomically correct adult and child head models using the IEEE standard (Std. C95.3-2002) SAR averaging algorithm. The child head models were obtained by linear scaling of the adult head model to replicate the conditions of previous studies reported in the literature and also by transforming the different adult head models based on data on the external shapes of children's heads. The tissue properties of the adult and corresponding child head models were kept the same. In addition, modeling and experimental measurements were made using three spheres filled with a tissue-equivalent mixture to approximate heads of increasing size. Results show that the peak local average SAR over 1 g and 10 g of tissue and the electromagnetic energy penetration depths are about the same in all of the head models under the same exposure conditions. When making interlaboratory comparisons, the model and the SAR averaging algorithm used must be standardized to minimize controversy.     

Equity in the NHS. Monitoring and promoting equity in primary and secondary care.

Although need is often assumed to be the most important factor in determining the use of health services, there are many inequities in the provision and use of NHS services in both primary and secondary care. For example, existing data from district child health information services have been combined with census data for small areas to show wide variations in immunisation rates between affluent and deprived areas. Purchasers of health care are already responsible for assessing health needs and evaluating services, and the process of monitoring equity is a logical extension of these activities. Routine data sources used to collect activity data in both primary and secondary care can be used to assess needs for care and monitor how well these needs are met. Purchasers and providers should collaborate to improve the usefulness of these routine data and to develop a framework for monitoring and promoting equity more systematically.     

Competition between Primary Nucleation and Autocatalysis in Amyloid Fibril Self-Assembly

Kinetic measurements of the self-assembly of proteins into amyloid fibrils are often used to make inferences about molecular mechanisms. In particular, the lag time—the quiescent period before aggregates are detected—is often found to scale with the protein concentration as a power law, whose exponent has been used to infer the presence or absence of autocatalytic growth processes such as fibril fragmentation. Here we show that experimental data for lag time versus protein concentration can show signs of kinks: clear changes in scaling exponent, indicating changes in the dominant molecular mechanism determining the lag time. Classical models for the kinetics of fibril assembly suggest that at least two mechanisms are at play during the lag time: primary nucleation and autocatalytic growth. Using computer simulations and theoretical calculations, we investigate whether the competition between these two processes can account for the kinks which we observe in our and others’ experimental data. We derive theoretical conditions for the crossover between nucleation-dominated and growth-dominated regimes, and analyze their dependence on system volume and autocatalysis mechanism. Comparing these predictions to the data, we find that the experimentally observed kinks cannot be explained by a simple crossover between nucleation-dominated and autocatalytic growth regimes. Our results show that existing kinetic models fail to explain detailed features of lag time versus concentration curves, suggesting that new mechanistic understanding is needed. More broadly, our work demonstrates that care is needed in interpreting lag-time scaling exponents from protein assembly data.     

New perspectives on hereditary influences in metastatic progression

Metastasis, the process by which cancer cells spread to distant sites and form secondary tumors, depends upon the ability of cells to escape the primary tumor, and colonize and proliferate in a novel microenvironment. Many mechanisms have been proposed to explain this phenomenon although no theory has comprehensively explained all biological observations. There is growing evidence that host hereditary factors modulate the ability of tumor cells to form metastatic lesions, and host genetic polymorphism could be a significant variable in this process. This review is intended to illustrate the role of hereditary variation in metastatic progression, how this integrates with currently proposed metastatic mechanisms, and the potential clinical impact on this frequently fatal consequence of cancer.     

Dormancy signatures and metastasis in estrogen receptor positive and negative breast cancer

Breast cancers can recur after removal of the primary tumor and treatment to eliminate remaining tumor cells. Recurrence may occur after long periods of time during which there are no clinical symptoms. Tumor cell dormancy may explain these prolonged periods of asymptomatic residual disease and treatment resistance. We generated a dormancy gene signature from published experimental models and applied it to both breast cancer cell line expression data as well as four published clinical studies of primary breast cancers. We found that estrogen receptor (ER) positive breast cell lines and primary tumors have significantly higher dormancy signature scores (P<0.0000001) than ER- cell lines and tumors. In addition, a stratified analysis combining all ER+ tumors in four studies indicated 2.1 times higher hazard of recurrence among patients whose tumors had low dormancy scores (LDS) compared to those whose tumors had high dormancy scores (HDS) (p<0.000005). The trend was shown in all four individual studies. Suppression of two dormancy genes, BHLHE41 and NR2F1, resulted in increased in vivo growth of ER positive MCF7 cells. The patient data analysis suggests that disseminated ER positive tumor cells carrying a dormancy signature are more likely to undergo prolonged dormancy before resuming metastatic growth. Furthermore, genes identified with this approach might provide insight into the mechanisms of dormancy onset and maintenance as well as dormancy models using human breast cancer cell lines.     

One Giant Leap for Categorizers: One Small Step for Categorization Theory

We explore humans’ rule-based category learning using analytic approaches that highlight their psychological transitions during learning. These approaches confirm that humans show qualitatively sudden psychological transitions during rule learning. These transitions contribute to the theoretical literature contrasting single vs. multiple category-learning systems, because they seem to reveal a distinctive learning process of explicit rule discovery. A complete psychology of categorization must describe this learning process, too. Yet extensive formal-modeling analyses confirm that a wide range of current (gradient-descent) models cannot reproduce these transitions, including influential rule-based models (e.g., COVIS) and exemplar models (e.g., ALCOVE). It is an important theoretical conclusion that existing models cannot explain humans’ rule-based category learning. The problem these models have is the incremental algorithm by which learning is simulated. Humans descend no gradient in rule-based tasks. Very different formal-modeling systems will be required to explain humans’ psychology in these tasks. An important next step will be to build a new generation of models that can do so.     

A simple mathematical model helps to explain the immunodominance of CD8 T cells in influenza A virus infections

Understanding immunodominance, the phenomenon of epitope-specific T cells expanding in an often distinctly hierarchical fashion, is important for the design of T-cell-based intervention strategies. Several recent studies have investigated immunodominance of H-2D(b)-restricted CD8(+) T cells specific for the nucleoprotein NP366 and acid polymerase PA224 epitopes during influenza A virus infection of C57BL/6 mice. CD8(+) T cells specific for these two epitopes are codominant during primary infection; NP366 dominates during secondary infection. While a number of explanations for this observation have been proposed, none of them can fully account for all the observed data. In this article, we use a simple mathematical model to explain the seemingly inconsistent data. We show that the dynamic interactions between CD8(+) T cells and antigen presentation lead to a situation where CD8(+) T cells are limiting during the initial response whereas antigen is limiting in the secondary response. This "numbers game" between antigen and CD8(+) T cells can reproduce the observed immunodominance of the NP336- and PA224-specific CD8(+) T cells, thereby explaining the reported experimental data.     

The genetic architecture of disease resistance in plants and the maintenance of recombination by parasites

Parasites represent strong selection on host populations because they are ubiquitous and can drastically reduce host fitness. It has been hypothesized that parasite selection could explain the widespread occurrence of recombination because it is a coevolving force that favours new genetic combinations in the host. A review of deterministic models for the maintenance of recombination reveals that for recombination to be favoured, multiple genes that interact with each other must be under selection. To evaluate whether parasite selection can explain the maintenance of recombination, we review 85 studies that investigated the genetic architecture of plant disease resistance and discuss whether they conform to the requirements that emerge from theoretical models. General characteristics of disease resistance in plants and problems in evaluating resistance experimentally are also discussed. We found strong evidence that disease resistance in plants is determined by multiple loci. Furthermore, in most cases where loci were tested for interactions, epistasis between loci that affect resistance was found. However, we found weak support for the idea that specific allelic combinations determine resistance to different host genotypes and there was little data on whether epistasis between resistance genes is negative or positive. Thus, the current data indicate that it is possible that parasite selection can favour recombination, but more studies in natural populations that specifically address the nature of the interactions between resistance genes are necessary. The data summarized here suggest that disease resistance is a complex trait and that environmental effects and fitness trade-offs should be considered in future models of the coevolutionary dynamics of host and parasites.     

Solvent cage effects: the influence of radical mass and volume on the recombination dynamics of radical cage pairs generated by photolysis of [CpCH2CH2N(CH3)C(O)(CH2)nCH3Mo(CO)3]2 (n = 3, 8, 13, 18) (Cp = eta 5-C5H4) complexes

The photochemistry of the [(CpR)Mo(CO)(3)](2) molecules, where CpR = eta(5)-C(5)H(4)(CH(2))(2)C(O)NCH(3)(CH(2))(n)CH(3) (n = 3, 8, 13, and 18), was examined using femtosecond pump-probe transient absorption spectroscopy. The goal of this study was to investigate the importance of radical size and mass on the dynamics and efficiency of geminate radical-radical recombination. The femtosecond results demonstrated the lack of any size/mass dependence of the recombination efficiency. This finding contrasts with results from a prior study that did find a size/mass dependence using a steady-state photochemical technique. To explain these conflicting results, it is proposed that the femtosecond pump-probe results are a measurement of the efficiency of primary geminate recombination whereas the steady-state method results are a measurement of the sum of primary and secondary geminate recombination efficiencies. The size/mass dependence is evident in the latter because secondary geminate recombination is a slower diffusive recombination process and therefore depends on the steric properties of the radicals. Although the existence of primary and secondary recombination channels is often taken for granted, experimental differentiation of primary and secondary caging has proven to be difficult because it is not possible for a single experimental technique to span the entire timescale for recombination of a radical cage pair and adequately resolve these recombination pathways.