Presence in the kidneys of nephrothelium precursor cells

The method of histoautoradiography was used to study dynamics of indices of impulse and diluted marks in 2 cellular subpopulations of the kidney cortex: in the intertubular cells (IT-cells) and in the endothelium-like cells (E-cells) of the convoluted tubules. It is shown that under conditions of pathology (sublimate nephrosis) a part of IT-cells transforms into E-cells. A conclusion is made that IT-cells may be considered predecessor cells of the nephrothelium.     

Complete separation of tyrosinated, detyrosinated, and nontyrosinatable brain tubulin subpopulations using affinity chromatography

The maximum achievable tyrosination level of neurotubulin, in vitro, is about 50%. We have developed a method to obtain a complete separation of the tyrosinatable and nontyrosinatable species. We use an immunoaffinity column, with coupled YL 1/2 monoclonal antibody (anti-Tyr-tubulin) and rapid desalting methods. Both subpopulations can be obtained in a polymerizable, apparently native, form. We find that about 35% of the brain tubulin is truly nontyrosinatable, despite the fact that it is assembly competent. Using a polyclonal antibody directed against nontyrosinatable tubulin, we find that it recognizes a specific epitope on the alpha-subunit of the dimer. The existence of an abundant tubulin subspecies, structurally different from tyrosinatable tubulin, should obviously be kept in mind in immunofluorescence studies of the distribution of nontyrosinated tubulin in brain tissues. Furthermore, we have extensively investigated the effect of tubulin tyrosination on microtubule dynamics. Despite the homogeneity of the populations under comparison, we find no significant effect of tyrosination on microtubule dynamics. Similarly, the stabilizing effects of microtubule associated proteins and of STOP protein were identical in both subpopulations. The drug taxol seems more efficient in stabilizing detyrosinated microtubules, but the difference is moderate. Taken together, these findings suggest that tubulin tyrosination does not effect microtubule stabilization, neither through modifications of the intrinsic tubulin properties nor through a differential binding of stabilizing proteins. Finally, the complete separation of two tubulin species (tyrosinated or detyrosinated) with similar kinetic properties, but immunologically different, should be of value in many kinetic studies of microtubule assembly.     

Analysis and simulation of double-layer neural networks with mutually inhibiting interconnections

Double-layer neural networks with mutually inhibiting interconnections are analyzed using a continuous-variable model of the neuron. The first layer consists of excitatory neurons while the second layer consists of inhibitory neurons. Both feedforward and feedback interconnections exist between the two layers. An autonomous system of nonlinear differential equations is introduced to describe the network dynamics, and the stability conditions for some classes of equilibria are investigated in detail. Several simulation results are also presented. It is shown that even those networks which are formed with rather powerless synapses are capable of carrying out input pattern sharpening, temporary information storage, and periodic signal generation.     

PINP: A New Method of Tagging Neuronal Populations for Identification during In Vivo Electrophysiological Recording

Neural circuits are exquisitely organized, consisting of many different neuronal subpopulations. However, it is difficult to assess the functional roles of these subpopulations using conventional extracellular recording techniques because these techniques do not easily distinguish spikes from different neuronal populations. To overcome this limitation, we have developed PINP (Photostimulation-assisted Identification of Neuronal Populations), a method of tagging neuronal populations for identification during in vivo electrophysiological recording. The method is based on expressing the light-activated channel channelrhodopsin-2 (ChR2) to restricted neuronal subpopulations. ChR2-tagged neurons can be detected electrophysiologically in vivo since illumination of these neurons with a brief flash of blue light triggers a short latency reliable action potential. We demonstrate the feasibility of this technique by expressing ChR2 in distinct populations of cortical neurons using two different strategies. First, we labeled a subpopulation of cortical neurons—mainly fast-spiking interneurons—by using adeno-associated virus (AAV) to deliver ChR2 in a transgenic mouse line in which the expression of Cre recombinase was driven by the parvalbumin promoter. Second, we labeled subpopulations of excitatory neurons in the rat auditory cortex with ChR2 based on projection target by using herpes simplex virus 1 (HSV1), which is efficiently taken up by axons and transported retrogradely; we find that this latter population responds to acoustic stimulation differently from unlabeled neurons. Tagging neurons is a novel application of ChR2, used in this case to monitor activity instead of manipulating it. PINP can be readily extended to other populations of genetically identifiable neurons, and will provide a useful method for probing the functional role of different neuronal populations in vivo.     

Computer simulation of brainstem respiratory activity.

A mathematical model of the medullary respiratory oscillator, composed of two mutually inhibiting populations (inspiratory and expiratory) of computer-simulated neurons, is presented. Each population consists of randomly interconnected subpopulations of excitatory and inhibitory neurons, is presented. Each population consists of randomly interconnected subpopulations of excitatory and inhibitory neurons. Neuronal coupling is such that either the inspiratory or expiratory population alone is capable of cyclic activity. Weak inhibitory connections between inspiratory and expiratory populations provide satisfactory reciprocating activity independent of the natural frequency of either population alone. Initiation and persistence of rhythmic activity is dependent on a diffused noncyclic excitatory input. Vagal discharge, simulated by phasic inhibition of inspiratory neurons, results in increased respiratory frequency with decreased inspiratory activity. In the absence of simulated vagal discharge, uniform facilitation of synaptic connections increases averaged activities of inspiratory and expiratory populations, with minor effect on frequency. In the presence of simulated vagal discharge, facilitation of synaptic connections increases both frequency and amplitude. The simulated effects of synaptic facilitation, with and without vagal discharge, mimic the physiological response to CO2 in the intact and vagotimized animal.     

Metapopulation dynamics and the quality of the matrix

In both strictly theoretical and more applied contexts it has been historically assumed that metapopulations exist within a featureless, uninhabitable matrix and that dynamics within the matrix are unimportant. In this article, we explore the range of theoretical consequences that result from relaxing this assumption. We show, with a variety of modeling techniques, that matrix quality can be extremely important in determining metapopulation dynamics. A higher-quality matrix generally buffers against extinction. However, in some situations, an increase in matrix quality can generate chaotic subpopulation dynamics, where stability had been the rule in a lower-quality matrix. Furthermore, subpopulations acting as source populations in a low-quality matrix may develop metapopulation dynamics as the quality of the matrix increases. By forcing metapopulation dynamics on a formerly heterogeneous (but stable within subpopulations) population, the probability of simultaneous extinction of all subpopulations actually increases. Thus, it cannot be automatically assumed that increasing matrix quality will lower the probability of global extinction of a population.     

Separate neurochemical classes of sympathetic postganglionic neurons project to the left ventricle of the rat heart

The sympathetic innervation of the rat heart was investigated by retrograde neuronal tracing and multiple label immunohistochemistry. Injections of Fast Blue made into the left ventricular wall labelled sympathetic neurons that were located along the medial border of both the left and right stellate ganglia. Cardiac projecting sympathetic postganglionic neurons could be grouped into one of four neurochemical populations, characterised by their content of calbindin and/or neuropeptide Y (NPY). The subpopulations of neurons contained immunoreactivity to both calbindin and NPY, immunoreactivity to calbindin only, immunoreactivity to NPY only and no immunoreactivity to calbindin or NPY. Sympathetic postganglionic neurons were also labelled in vitro with rhodamine dextran applied to the cut end of a cardiac nerve. The same neurochemical subpopulations of sympathetic neurons were identified by using this technique but in different proportions to those labelled from the left ventricle. Preganglionic terminals that were immunoreactive for another calcium-binding protein, calretinin, preferentially surrounded retrogradely labelled neurons that were immunoreactive for both calbindin and NPY. The separate sympathetic pathways projecting to the rat heart may control different cardiac functions.     

The applicability of metapopulation theory to large mammals

Metapopulation theory has become a common framework in conservation biology and it is sometimes suggested that a metapopulation approach should be used for management of large mammals. However, it has also been suggested that metapopulation theory would not be applicable to species with long generations compared to those with short ones. In this paper, we review how and on what empirical ground metapopulation terminology has been applied to insects, small mammals and large mammals. The review showed that the metapopulation term sometimes was used for population networks which only fulfilled the broadest possible definition of a metapopulation, i.e. they were subpopulations connected by migrating individuals. We argue that the metapopulation concept should be reserved for networks that also show some kind of metapopulation dynamics. Otherwise it applies to almost all populations and loses its substance. We found much empirical support for metapopulation dynamics in both insects and small mammals, but not in large mammals. A possible reason is the methods used to confirm the existence of metapopulation dynamics. For insects and small mammals, the common approach is to study population turnover through patch occupancy data. Such data is difficult to obtain for large mammals, since longer temporal scales need to be covered to record extinctions and colonizations. Still, many populations of large mammals are exposed to habitat fragmentation and the resulting subpopulations sometimes have high risks of extinction. If there is migration between the subpopulations, the metapopulation framework could provide valuable information on their population dynamics. We suggest that a metapopulation approach can be interesting for populations of large mammals, when there are discrete breeding subpopulations and when these subpopulations have different growth rates and demographic fates. Thus, a comparison of the subpopulations’ demographic fates, rather than subpopulation turnover, can be a feasible alternative for studies of metapopulation dynamics in large mammals.     

Control of macrophage lineage populations by CSF-1 receptor and GM-CSF in homeostasis and inflammation

There is recent interest in the role of monocyte/macrophage subpopulations in pathology. How the hemopoietic growth factors, macrophage-colony stimulating factor (M-CSF or CSF-1) and granulocyte macrophage (GM)-CSF, regulate their in vivo development and function is unclear. A comparison is made here on the effect of CSF-1 receptor (CSF-1R) and GM-CSF blockade/depletion on such subpopulations, both in the steady state and during inflammation. In the steady state, administration of neutralizing anti-CSF-1R monoclonal antibody (mAb) rapidly (within 3-4 days) lowered, specifically, the number of the more mature Ly6C(lo) peripheral blood murine monocyte population and resident peritoneal macrophages; it also reduced the accumulation of murine exudate (Ly6C(lo)) macrophages in two peritonitis models and alveolar macrophages in lung inflammation, consistent with a non-redundant role for CSF-1 (or interleukin-34) in certain inflammatory reactions. A neutralizing mAb to GM-CSF also reduced inflammatory macrophage numbers during antigen-induced peritonitis and lung inflammation. In GM-CSF gene-deficient mice, a detailed kinetic analysis of monocyte/macrophage and neutrophil dynamics in antigen-induced peritonitis suggested that GM-CSF was acting, in part, systemically to maintain the inflammatory reaction. A model is proposed in which CSF-1R signaling controls the development of the macrophage lineage at a relatively late stage under steady state conditions and during certain inflammatory reactions, whereas in inflammation, GM-CSF can be required to maintain the response by contributing to the prolonged extravasation of immature monocytes and neutrophils. A correlation has been observed between macrophage numbers and the severity of certain inflammatory conditions, and it could be that CSF-1 and GM-CSF contribute to the control of these numbers in the ways proposed.     

Macroscopic Equations Governing Noisy Spiking Neuronal Populations with Linear Synapses

Deriving tractable reduced equations of biological neural networks capturing the macroscopic dynamics of sub-populations of neurons has been a longstanding problem in computational neuroscience. In this paper, we propose a reduction of large-scale multi-population stochastic networks based on the mean-field theory. We derive, for a wide class of spiking neuron models, a system of differential equations of the type of the usual Wilson-Cowan systems describing the macroscopic activity of populations, under the assumption that synaptic integration is linear with random coefficients. Our reduction involves one unknown function, the effective non-linearity of the network of populations, which can be analytically determined in simple cases, and numerically computed in general. This function depends on the underlying properties of the cells, and in particular the noise level. Appropriate parameters and functions involved in the reduction are given for different models of neurons: McKean, Fitzhugh-Nagumo and Hodgkin-Huxley models. Simulations of the reduced model show a precise agreement with the macroscopic dynamics of the networks for the first two models.     

Flow cytometric quantitative determination of ingestion by phagocytes needs the distinguishing of overlapping populations of binding and ingesting cells.

BACKGROUND: The use of flow cytometry with fluorescently labeled particles provides the means to examine quantitatively the phagocytotic capacity of an individual phagocyte. This report describes an improved flow cytometric method of analysis for kinetic measurement of phagocytosis of fluorescein isothiocyanate (FITC)-labeled zymosan particles by human leukocytes. METHODS: FITC-labeled zymosan was incubated with leukocyte suspension, and at selected time intervals fluorescence positive neutrophils were divided by phagocytotic gates into three subpopulations: neutrophils that were neither binding nor ingesting particles, neutrophils that were only binding particles (binding cells), and neutrophils that were binding and ingesting particles (ingesting cells). For the distinction between internalized and surface-bound FITC-labeled zymosan, trypan blue (1.2 mg/ml) was used to quench surface-bound fluorescence. RESULTS: The technical challenges related to settings of phagocytotic gates and derivation of phagocytotic equations were presented. From 28 control samples, numerical values of mean fluorescence intensities and percentages of phagocytotic subpopulations inside phagocytotic gates before and after quenching were inserted into phagocytotic equations and corrected phagocytotic parameters were calculated. Calculated parameters were surprisingly constant across individuals. CONCLUSIONS: Essential elements of the present method appeared to be partial quenching of extracellular fluorescence with trypan blue and distinguishing between overlapping populations of binding and ingesting cells. Corrections using derived phagocytotic equations proved necessary for accurate kinetic phagocytotic measurements. Corrections were less necessary when the ingestion process was finished.     

Periodicity and boundedness of solutions of generalized differential equations of growth

Sufficient conditions are given for the existence of periodic solutions of differential equations, having as special cases the equations used to describe the competition between two species. The Poincaré bifurcation theory is used to secure one set of conditions, and another set of conditions is secured through a generalization of a method of V. Volterra. The question of boundedness is considered and conditions implying boundedness and conditions implying that populations are bounded away from zero are given. Several integrable classes of systems are discovered and a particular example having periodic solutions is examined in detail. This research was supported by the Air Force Office of Scientific Research under Grant 62-207.     

Genetic Adaptation to Captivity and Inbreeding Depression in Small Laboratory Populations of Drosophila Melanogaster

The rate of adaptation to a competitive laboratory environment and the associated inbreeding depression in measures of reproductive fitness have been observed in populations of Drosophila melanogaster with mean effective breeding size of the order of 50 individuals. Two large wild-derived populations and a long-established laboratory cage population were used as base stocks, from which subpopulations were extracted and slowly inbred under crowded conditions over a period of 210 generations. Comparisons have been made of the competitive ability and reproductive fitness of these subpopulations, the panmictic populations produced from them by hybridization and random mating and the wild- or cage-base populations from which they were derived. After an average of ~180 generations in the laboratory, the wild-derived panmictic populations exceeded the resampled natural populations by 75% in fitness under competitive conditions. The cage-derived panmictic population, after a total of 17 years in the laboratory, showed a 90% superiority in competitive ability over the corresponding wild population. In the inbred lines derived from the wild-base stocks, the average rate of adaptation was estimated to be 0.33 +/- 0.06% per generation. However, the gain in competitive ability was more than offset by inbreeding depression at an initial rate of ~2% per generation. The effects of both adaptation and inbreeding on reproductive ability in a noncompetitive environment were found to be minor by comparison. The maintenance of captive populations under noncompetitive conditions can therefore be expected to minimize adaptive changes due to natural selection in the changed environment.     

The adaptive dynamics of function-valued traits

This study extends the framework of adaptive dynamics to function-valued traits. Such adaptive traits naturally arise in a great variety of settings: variable or heterogeneous environments, age-structured populations, phenotypic plasticity, patterns of growth and form, resource gradients, and in many other areas of evolutionary ecology. Adaptive dynamics theory allows analysing the long-term evolution of such traits under the density-dependent and frequency-dependent selection pressures resulting from feedback between evolving populations and their ecological environment. Starting from individual-based considerations, we derive equations describing the expected dynamics of a function-valued trait in asexually reproducing populations under mutation-limited evolution, thus generalizing the canonical equation of adaptive dynamics to function-valued traits. We explain in detail how to account for various kinds of evolutionary constraints on the adaptive dynamics of function-valued traits. To illustrate the utility of our approach, we present applications to two specific examples that address, respectively, the evolution of metabolic investment strategies along resource gradients, and the evolution of seasonal flowering schedules in temporally varying environments.     

Dynamics of Competition between Subnetworks of Spiking Neuronal Networks in the Balanced State

We explore and analyze the nonlinear switching dynamics of neuronal networks with non-homogeneous connectivity. The general significance of such transient dynamics for brain function is unclear; however, for instance decision-making processes in perception and cognition have been implicated with it. The network under study here is comprised of three subnetworks of either excitatory or inhibitory leaky integrate-and-fire neurons, of which two are of the same type. The synaptic weights are arranged to establish and maintain a balance between excitation and inhibition in case of a constant external drive. Each subnetwork is randomly connected, where all neurons belonging to a particular population have the same in-degree and the same out-degree. Neurons in different subnetworks are also randomly connected with the same probability; however, depending on the type of the pre-synaptic neuron, the synaptic weight is scaled by a factor. We observed that for a certain range of the “within” versus “between” connection weights (bifurcation parameter), the network activation spontaneously switches between the two sub-networks of the same type. This kind of dynamics has been termed “winnerless competition”, which also has a random component here. In our model, this phenomenon is well described by a set of coupled stochastic differential equations of Lotka-Volterra type that imply a competition between the subnetworks. The associated mean-field model shows the same dynamical behavior as observed in simulations of large networks comprising thousands of spiking neurons. The deterministic phase portrait is characterized by two attractors and a saddle node, its stochastic component is essentially given by the multiplicative inherent noise of the system. We find that the dwell time distribution of the active states is exponential, indicating that the noise drives the system randomly from one attractor to the other. A similar model for a larger number of populations might suggest a general approach to study the dynamics of interacting populations of spiking networks.     

Antibody affinities and relative titers in polyclonal populations: surface plasmon resonance analysis of anti-DNA antibodies

This paper presents the equations and methodology for the measurement and interpretation of apparent dissociation constants for polyclonal populations of antibodies, where antigen is kept trace relative to antibody concentration. Surface plasmon resonance is used to determine K(d)s for the binding of anti-DNA antibodies to trace amounts of DNA antigen on a chip. Since the approach taken relies on equilibrium measurements, kinetic mass transport artifacts are avoided. The apparent K(d) is a weighted average of all the K(d)s for the clonally related subpopulations within the polyclonal pool, where each weighting factor is the relative titer (fractional presence) of the subpopulation. Titration curves appear as if there is one monoclonal population with that titer-weighted-average K(d). Implications of changes in the antibody affinity distribution within the population are discussed. The equations described herein provide a better physical understanding of the apparent K(d) that is obtained when a heterogeneous population of receptors is titrated against a trace ligand.     

The effect of migration on metapopulation stability is qualitatively unaffected by demographic and spatial heterogeneity

Coupled map lattices (CMLs), using two coupled logistic equations, have been extensively used to model the dynamics of two-patch ecological systems. Such studies have revealed that migration rate plays an important role in determining the dynamics of the system, particularly when the two maps differ in their intrinsic growth rate parameter, r. However, under more realistic assumptions, a metapopulation can be expected to consist of more than two subpopulations, each with its own demographic parameters, which will in part be a function of the environment of that patch. The role of the spatial arrangement of heterogeneous (i.e. with different r values) subpopulations in shaping the dynamics of such a metapopulation has rarely been investigated. Here, we study the effect of demographic and spatial heterogeneity on the stability of one- and two-dimensional systems of 64 coupled Ricker maps with different r values, under periodic and absorbing boundary conditions. We show that the effects of migration rate on metapopulation stability do not depend upon either the precise spatial arrangement of the subpopulations in the lattice, or on the presence of a moderate proportion of vacant (uninhabitable) patches in the lattice. The results, thus, suggest that metapopulation models are robust to variation in spatial arrangement of patch quality and, hence, of demographic parameters. We also show that for any given arrangement of the patches, maximum stability of the metapopulation occurs when the migration levels are intermediate, a result that agrees well with previous studies on two-map CML systems.     

Determination of rate constants of antigen-antibody reaction. A theory

A new method of determination of rate constants for antigen-antibody interactions is proposed. This method is based on a solid phase immunoenzymatic analysis of the dynamics of elution of immobilized antigen-bound antibodies in the presence of a free antigen. The kinetics of this process is described by a system of differential equations, whose solution results in expression defining the dynamics of antibody interaction with immobilized and free antigens. Simple formulas were derived for the calculation of the rate and equilibrium constants for the antibody-antigen reaction on the basis of experimental kinetic curves. The use of theoretical kinetic curves for antibody elution showed that these formulas reflect with a high degree of accuracy the kinetic properties of the reaction under study.     

Carbonic anhydrase activity in primary sensory neurons

Neuronal subpopulations of dorsal root ganglion (DRG) cells in the chicken exhibit carbonic anhydrase (CA) activity. To determine whether CA activity is expressed by DRG cells maintained in in vitro cultures, dissociated DRG cells from 10-day-old chick embryos were cultured on a collagen substrate. The influence exerted by environmental factors on the enzyme expression was tested under various conditions of culture. Neuron-enriched cell cultures and mixed DRG-cell cultures (including numerous non-neuronal cells) were performed either in a defined medium or in a horse serum-supplemented medium. In all the tested conditions, subpopulations of cultured sensory neurons expressed CA activity in their cell bodies, while their neurites were rarely stained; in each case, the percentage of CA-positive neurons declined with the age of the cultures. The number and the persistence of neurons possessing CA activity as well as the intensity of the reaction were enhanced by addition of horse serum. In contrast, the expression of the neuronal CA activity was not affected by the presence of non-neuronal cells or by the rise of CO2 concentration. Thus, the appearance and disappearance of neuronal subpopulations expressing CA activity may be decisively influenced by factors contained in the horse serum. The loss of CA-positive neurons with time could result from a cell selection or from genetic repression. Analysis of the time curves does not support a preferential cell death of CA-positive neurons but suggests that the eventual conversion of CA-positive neurons into CA-negative neurons results from a loss of the enzyme activity. These results indicate that the phenotypic expression of cultured sensory neurons is dependent on defined environmental factors.     

Describing the geographic spread of dengue disease by traveling waves

Dengue is a human disease transmitted by the mosquito Aedes aegypti. For this reason geographical regions infested by this mosquito species are under the risk of dengue outbreaks. In this work, we propose a mathematical model to study the spatial dissemination of dengue using a system of partial differential reaction-diffusion equations. With respect to the human and mosquito populations, we take into account their respective subclasses of infected and uninfected individuals. The dynamics of the mosquito population considers only two subpopulations: the winged form (mature female mosquitoes), and an aquatic population (comprising eggs, larvae and pupae). We disregard the long-distance movement by transportation facilities, for which reason the diffusion is considered restricted only to the winged form. The human population is considered homogeneously distributed in space, in order to describe localized dengue dissemination during a short period of epidemics. The cross-infection is modeled by the law of mass action. A threshold value as a function of the model's parameters is obtained, which determines the rate of dengue dissemination and the risk of dengue outbreaks. Assuming that an area was previously colonized by the mosquitoes, the rate of disease dissemination is determined as a function of the model's parameters. This rate of dissemination of dengue disease is determined by applying the traveling wave solutions to the corresponding system of partial differential equations.