Modeling electromagnetic fields detectability in a HH-like neuronal system: stochastic resonance and window behavior

Noise has already been shown to play a constructive role in neuronal processing and reliability, according to stochastic resonance (SR). Here another issue is addressed, concerning noise role in the detectability of an exogenous signal, here representing an electromagnetic (EM) field. A Hodgkin–Huxley like neuronal model describing a myelinated nerve fiber is proposed and validated, excited with a suprathreshold stimulation. EM field is introduced as an additive voltage input and its detectability in neuronal response is evaluated in terms of the output signal-to-noise ratio. Noise intensities maximizing spiking activity coherence with the exogenous EM signal are clearly shown, indicating a stochastic resonant behavior, strictly connected to the model frequency sensitivity. In this study SR exhibits a window of occurrence in the values of field frequency and intensity, which is a kind of effect long reported in bioelectromagnetic experimental studies. The spatial distribution of the modeled structure also allows to investigate possible effects on action potentials saltatory propagation, which results to be reliable and robust over the presence of an exogenous EM field and biological noise. The proposed approach can be seen as assessing biophysical bases of medical applications funded on electric and magnetic stimulation where the role of noise as a cooperative factor has recently gained growing attention. This work investigates the role of noise as a cooperative factor for the detection of an exogenous electromagnetic field in a compartimental model of a myelinated nerve fiber. The occurrence of stochastic resonance is discussed in relation to neuronal frequency sensitivity.     

On the role of reinfection in the transmission of infectious diseases

We introduce a spatial stochastic model for the spread of tuberculosis. After a primary infection, an individual may become sick (and infectious) through an endogenous reinfection or through an exogenous reinfection. We show that even in the absence of endogenous reinfection an epidemic is possible if the exogenous reinfection parameter is high enough. This is in sharp contrast with what happens for a mean field model corresponding to our spatial stochastic model.     

Reactive oxygen species and protein oxidation in aging: a look back, a look ahead.

The existence of free radicals, as chemical entities, was inferred 100 years ago but not universally accepted for some 30-40 years. The existence and importance of free radicals in biological systems was not recognized until the mid 1950s, by a small number of visionary scientists who can be credited with founding the field of reactive oxygen biochemistry. For most of the remaining 20th century, reactive oxygen species (ROS) were considered a type of biochemical "rusting agent" that caused stochastic tissue damage and disease. As we enter the 21st century, reactive oxygen biochemistry is maturing as a discipline and establishing its importance among the biomedical sciences. It is now recognized that virtually every disease state involves some degree of oxidative stress. Moreover, we are now beginning to recognize that ROS are produced in a well-regulated manner to help maintain homeostasis on the cellular level in normal, healthy tissue. This review summarizes the history of reactive oxygen biochemistry, outlining major paradigm shifts that the field has undergone and continues to experience. The contributions of Earl Stadtman to the recent history of the field (1980-present) are especially highlighted. The role of ROS in signal transduction is presented in some detail as central to the latest paradigm shift. Emerging technologies, particularly proteomic technologies, are discussed that will facilitate further evolution in the field of reactive oxygen biochemistry.     

Self-Organization of Polarized Cell Signaling via Autocrine Circuits: Computational Model Analysis

Recent studies have suggested that autocrine signaling through epidermal growth factor receptor (EGFR) might be involved in generating or maintaining an intrinsic polarity in tissue cells, possibly via spatial localization of EGFR-mediated signaling. The difficulty of experimental investigation of autocrine signaling makes especially valuable an application of computational modeling for critical hypotheses about the dynamic operation of the underlying signaling circuits, both intracellular and extracellular. Toward this end, we develop and analyze here a spatially distributed dynamic computational model of autocrine EGFR signaling. Under certain conditions, the model spontaneously evolves into a state wherein sustained signaling is spatially localized on smaller than cell dimension, conferring a polarity to the otherwise nonpolar model cell. Conditions of a sufficiently large rate of autocrine EGFR ligand release and of a sufficiently small exogenous ligand concentration are qualitatively consistent with experimental observations of EGFR-mediated migration. Thus, computational analysis supports the concept that autocrine EGFR signaling circuits could play a role in helping generate and/or maintain an intrinsic cell spatial polarity, possibly related to migration as well as tissue organization. We additionally offer particular suggestions for critical nodes in the EGFR signaling circuits governing this self-organization capability.     

Persistence of structured populations in random environments

Environmental fluctuations often have different impacts on individuals that differ in size, age, or spatial location. To understand how population structure, environmental fluctuations, and density-dependent interactions influence population dynamics, we provide a general theory for persistence for density-dependent matrix models in random environments. For populations with compensating density dependence, exhibiting “bounded” dynamics, and living in a stationary environment, we show that persistence is determined by the stochastic growth rate (alternatively, dominant Lyapunov exponent) when the population is rare. If this stochastic growth rate is negative, then the total population abundance goes to zero with probability one. If this stochastic growth rate is positive, there is a unique positive stationary distribution. Provided there are initially some individuals in the population, the population converges in distribution to this stationary distribution and the empirical measures almost surely converge to the distribution of the stationary distribution. For models with overcompensating density-dependence, weaker results are proven. Methods to estimate stochastic growth rates are presented. To illustrate the utility of these results, applications to unstructured, spatially structured, and stage-structured population models are given. For instance, we show that diffusively coupled sink populations can persist provided that within patch fitness is sufficiently variable in time but not strongly correlated across space.     

A multi-scaled approach for simulating chemical reaction systems

In this paper we give an overview of some very recent work, as well as presenting a new approach, on the stochastic simulation of multi-scaled systems involving chemical reactions. In many biological systems (such as genetic regulation and cellular dynamics) there is a mix between small numbers of key regulatory proteins, and medium and large numbers of molecules. In addition, it is important to be able to follow the trajectories of individual molecules by taking proper account of the randomness inherent in such a system. We describe different types of simulation techniques (including the stochastic simulation algorithm, Poisson Runge–Kutta methods and the balanced Euler method) for treating simulations in the three different reaction regimes: slow, medium and fast. We then review some recent techniques on the treatment of coupled slow and fast reactions for stochastic chemical kinetics and present a new approach which couples the three regimes mentioned above. We then apply this approach to a biologically inspired problem involving the expression and activity of LacZ and LacY proteins in E. coli, and conclude with a discussion on the significance of this work.     

Analysis of expression profiles of selected genes associated with the regenerative property and the receptivity to gene transfer during somatic embryogenesis in Triticum aestivum L.

The physiological, biochemical and molecular mechanisms regulating the initiation of a regenerative pathway remain partially unknown. Efforts to identify the biological features that confer transformation ability, or the tendency of some cells to induce transgene silencing, would help to improve plant genetic engineering. The objective of our study was to monitor the evolution of plant cell competencies in relation to both in vitro tissue culture regeneration and the genetic transformation properties. We used a simple wheat regeneration procedure as an experimental model for studying the regenerative capacity of plant cells and their receptivity to direct gene transfer over the successive steps of the regenerative pathway. Target gene profiling studies and biochemical assays were conducted to follow some of the mechanisms triggered during the somatic-to-embryogenic transition (i.e. dedifferentiation, cell division activation, redifferentiation) and affecting the accessibility of plant cells to receive and stably express the exogenous DNA introduced by bombardment. Our results seem to indicate that the control of cell-cycle (S-phase) and host defense strategies can be crucial determinants of genetic transformation efficiency. The results from studies conducted at macro-, micro- and molecular scales are then integrated into a holistic approach that addresses the question of tissue culture and transgenesis competencies more broadly. Through this multilevel analysis we try to establish functional links between both regenerative capacity and transformation receptiveness, and thereby to provide a more global and integrated vision of both processes, at the core of defense/adaptive mechanisms and survival, between undifferentiated cell proliferation and organization.     

Differences in sensitivity of biological functions mediated by epidermal growth factor receptor activation with respect to endogenous and exogenous ligands.

Despite constitutive expression of autocrine transforming growth factor-alpha (TGF-alpha) in growth factor-independent colon carcinoma cells, the epidermal growth factor receptor (EGFr) is not saturated and can be further activated by exogenous EGFr ligand. Given that the activation of EGFr by exogenous growth factor has no further effect on DNA synthesis, the question arises as to what function this additional EGFr activation might have. We report that EGF induces integrin alpha2 expression, integrin-mediated adhesion, and micromotility of HCT116 cells. The stimulatory effect of ligand on these biological functions is abrogated by treatment with AG1478- and EGFr-blocking monoclonal antibody. This provides evidence that the biological responses are EGFr-mediated and EGFr is located upstream of integrin alpha2 expression. Therefore, although exogenous EGF has no effect on DNA synthesis beyond that induced by autocrine TGF-alpha (at subsaturating levels of EGFr occupation) exogenous growth factor does induce integrin alpha2 expression, cell adhesion, and micromotion. An important finding revealed by this study is the documentation of biological responses of EGFr-mediated functions, including DNA synthesis, cell adhesion, and micromotion, which differ in sensitivity with respect to different degrees of EGFr activation at the basal state and in response to exogenous ligand.     

Reconstructing pedigrees: a stochastic perspective

A pedigree is a directed graph that describes how individuals are related through ancestry in a sexually-reproducing population. In this paper we explore the question of whether one can reconstruct a pedigree by just observing sequence data for present day individuals. This is motivated by the increasing availability of genomic sequences, but in this paper we take a more theoretical approach and consider what models of sequence evolution might allow pedigree reconstruction (given sufficiently long sequences). Our results complement recent work that showed that pedigree reconstruction may be fundamentally impossible if one uses just the degrees of relatedness between different extant individuals. We find that for certain stochastic processes, pedigrees can be recovered up to isomorphism from sufficiently long sequences.     

The place of metabolism in the origin of life

Metabolism and replication are generally considered essential features of biological life. Workers in the field of the origin of life are mostly split into two groups, depending on which of these two functions is postulated to have occurred first. Because of difficulties encountered by the replication-first (or genetics-first) approach, some workers have postulated that a highly developed metabolism must have originated before replication and the formation of a genetic apparatus. However, as supporters of a replication-first approach have pointed out, and as is discussed in this article, the alternative metabolism-first approach has fundamental problems that have not been sufficiently addressed.     

Analysis of operating principles with S-system models

Operating principles address general questions regarding the response dynamics of biological systems as we observe or hypothesize them, in comparison to a priori equally valid alternatives. In analogy to design principles, the question arises: Why are some operating strategies encountered more frequently than others and in what sense might they be superior? It is at this point impossible to study operation principles in complete generality, but the work here discusses the important situation where a biological system must shift operation from its normal steady state to a new steady state. This situation is quite common and includes many stress responses. We present two distinct methods for determining different solutions to this task of achieving a new target steady state. Both methods utilize the property of S-system models within Biochemical Systems Theory (BST) that steady states can be explicitly represented as systems of linear algebraic equations. The first method uses matrix inversion, a pseudo-inverse, or regression to characterize the entire admissible solution space. Operations on the basis of the solution space permit modest alterations of the transients toward the target steady state. The second method uses standard or mixed integer linear programming to determine admissible solutions that satisfy criteria of functional effectiveness, which are specified beforehand. As an illustration, we use both methods to characterize alternative response patterns of yeast subjected to heat stress, and compare them with observations from the literature.     

Adaptive sex allocation in birds: the complexities of linking theory and practice

We review some recent theoretical and empirical developments in the study of sex allocation in birds. The advent of reliable molecular sexing techniques has led to a sharp increase in the number of studies that report biased offspring sex ratios in birds. However, compelling evidence for adaptive sex allocation in birds is still very scant. We argue that there are two reasons for this: (i) standard sex allocation models, very helpful in understanding sex allocation of invertebrates, do not sufficiently take the complexities of bird life histories and physiology into account. Recent theoretical work might bring us a step closer to more realistic models; (ii) experimental field and laboratory studies on sex allocation in birds are scarce. Recent experimental work both in the laboratory and in the field shows that this is a promising approach.     

莱茵衣藻叶绿体生物反应器研究进展

莱茵衣藻(Chlamydomonas reinharditi)是一种遗传机制已研究比较清楚的模式植物。近年来,生物反应器是当今世界上各国生物技术研究的一个热点,随着生物技术的发展,已成功实现衣藻作为生物反应器生产重组蛋白及抗体,生产的部分产品已经实现了商品化,与其他生物反应器相比,其在外源基因表达水平和转基因植物安全性等方面有明显的优势,尤其是在控制转基因沉默和遗传稳定性方面展示了极大的优越性。因此,莱茵衣藻是一种具有很好发展前景的生物反应器,必将在未来的药用蛋白生物技术领域发挥重要作用。主要对提高基因在莱茵衣藻叶绿体中表达的策略,转化技术的特点及其未来的发展前景等方面进行了简单评述。     

Genetic code,attributive mappings and stochastic matrices

In this paper we construct three primitive mappings based on three kinds of genetic attribute equivalences. We then apply the mappings and basic addition operation to the universal genetic code to generate three square matrices. We show that these square matrices are stochastic in nature. They demonstrate some fractal similarity properties and resemble the similar properties to the original stochastic matrices.     

Can stochastic geographical evolution re‐create macroecological richness–environment correlations?

Aim Richness gradients are frequently correlated with environmental characteristics at broad geographic scales. In particular, richness is often associated with energy and climate, while environmental heterogeneity is rarely its best correlate. These correlations have been interpreted as evidence in favour of environmental determinants of diversity gradients, particularly energy and climate. This interpretation assumes that the expected‐by‐random correlation between richness and environment is zero, and that this is equally true for all environmental characteristics. However, these expectations might be unrealistic. We investigated to what degree basic evolutionary/biogeographical processes occurring independently of environment could lead to richness gradients that correlate with environmental characteristics by chance alone. Location Africa, Australia, Eurasia and the New World. Methods We produced artificial richness gradients based on a stochastic simulation model of geographic diversification of clades. In these simulations, species speciate, go extinct and expand or shift their distributions independently of any environmental characteristic. One thousand two hundred repetitions of this model were run, and the resulting stochastic richness gradients were regressed against real‐world environmental variables. Stochastic species–environment relationships were then compared among continents and among three environmental characteristics: energy, environmental heterogeneity and climate seasonality. Results Simulations suggested that a significant degree of correlation between richness gradients and environment is expected even when clades diversify and species distribute stochastically. These correlations vary considerably in strength; but in the best cases, environment can spuriously account for almost 80% of variation in stochastic richness. Additionally, expected‐by‐chance relationships were different among continents and environmental characteristics, producing stronger spurious relationships with energy and climate than with heterogeneity. Main conclusions We conclude that some features of empirical species–environment relationships can be reproduced just by chance when taking into account evolutionary/biogeographical processes underlying the construction of species richness gradients. Future tests of environmental effects on richness should consider structure in richness–environment correlations that can be produced by simple evolutionary null models. Research should move away from the naive non‐biological null hypotheses that are implicit in traditional statistical tests.     

Understanding plant reproductive diversity

Flowering plants display spectacular floral diversity and a bewildering array of reproductive adaptations that promote mating, particularly outbreeding. A striking feature of this diversity is that related species often differ in pollination and mating systems, and intraspecific variation in sexual traits is not unusual, especially among herbaceous plants. This variation provides opportunities for evolutionary biologists to link micro-evolutionary processes to the macro-evolutionary patterns that are evident within lineages. Here, I provide some personal reflections on recent progress in our understanding of the ecology and evolution of plant reproductive diversity. I begin with a brief historical sketch of the major developments in this field and then focus on three of the most significant evolutionary transitions in the reproductive biology of flowering plants: the pathway from outcrossing to predominant self-fertilization, the origin of separate sexes (females and males) from hermaphroditism and the shift from animal pollination to wind pollination. For each evolutionary transition, I consider what we have discovered and some of the problems that still remain unsolved. I conclude by discussing how new approaches might influence future research in plant reproductive biology.     

Resource availability determines the importance of niche‐based versus stochastic community assembly in grasslands

Niche‐based selection and stochastic processes can operate simultaneously to generate spatial and temporal variation in species composition. Yet, the conditions under which ecological dynamics are dominated by niche‐based versus stochastic processes are poorly understood. Using a field experiment in early‐successional temperate grassland and null models of beta diversity, this study investigates the effects of soil nutrient supply on the relative importance of niche‐based selection versus stochastic dynamics for variation in species composition among sites. Nutrient availability was manipulated experimentally, individual seed mixtures with 25 species were sown in each experimental plot, and then stochastic and deterministic niche‐based assembly processes were allowed to happen. We found that compositional variation among grassland plots with low nutrient supply was driven by stochastic immigration and extinctions. In contrast, nutrient enrichment reduced the importance of stochasticity and imposed a deterministic environmental filter that homogenized communities through the selection of few species with greater competitive ability for light. This demonstrates that soil nutrient availability is a critical environmental feature that dictates the degree to which terrestrial plant communities are controlled by niche‐based selection versus stochastic assembly processes. Our study shows further that alternative states of eutrophic grasslands emerge from initial stochastic variation in the composition of a particular functional group of species that can become dominant at high nutrient supply. We discuss potential mechanisms underlying the shift from stochastic to niche‐driven dynamics along soil nutrient gradients.     

大肠杆菌和酵母表达系统的研究进展

20世纪70年代以来,分子生物学及基因组学迅猛发展,其在生物及医学领域发挥着越来越重要的作用。在发酵工业中,分子生物学技术广泛应用于菌种的遗传改造和基因工程菌株的构建,以期提高发酵产物的产量并丰富发酵产物的类型。其中,利用原核及真核表达系统进行外源基因的扩增、表达以生产蛋白疫苗、核酸疫苗和酶制剂等是近十年来发酵工业的新兴领域。本文从表达载体和宿主菌改造两方面综述近些年来大肠杆菌及酵母表达系统的新进展与新技术。