The dynamics of gas-bubble formation at saturated conditions in porous media flow.

We investigate the stability of gas bubbles formed at saturated (bubble-point) conditions during two-component ([Formula: see text], [Formula: see text]O), two-phase (gas, liquid) flow by developing and analyzing a [Formula: see text] dynamical system describing flow through a single pore to study the dynamics of gas bubble formation and evolution. Our analysis indicates that three regimes occur at conditions pertinent to petroleum reservoirs. These regimes correspond to a critical point changing type from an unstable node to an unstable spiral and then to a stable spiral as flow rates increase. In the stable spiral case gas bubbles will achieve a steady-state finite size only if they form within the attractor region of the stable spiral. Otherwise, all gas bubbles that form undergo, possibly oscillatory, growth and then dissolve completely. Under steady flow conditions, this formation and dissolution repeats cyclically.

The Fragility of Individual-Based Explanations of Social Hierarchies: A Test Using Animal Pecking Orders.

The standard approach in accounting for hierarchical differentiation in biology and the social sciences considers a hierarchy as a static distribution of individuals possessing differing amounts of some valued commodity, assumes that the hierarchy is generated by micro-level processes involving individuals, and attempts to reverse engineer the processes that produced the hierarchy. However, sufficient experimental and analytical results are available to evaluate this standard approach in the case of animal dominance hierarchies (pecking orders). Our evaluation using evidence from hierarchy formation in small groups of both hens and cichlid fish reveals significant deficiencies in the three tenets of the standard approach in accounting for the organization of dominance hierarchies. In consequence, we suggest that a new approach is needed to explain the organization of pecking orders and, very possibly, by implication, for other kinds of social hierarchies. We develop an example of such an approach that considers dominance hierarchies to be dynamic networks, uses dynamic sequences of interaction (dynamic network motifs) to explain the organization of dominance hierarchies, and derives these dynamic sequences directly from observation of hierarchy formation. We test this dynamical explanation using computer simulation and find a good fit with actual dynamics of hierarchy formation in small groups of hens. We hypothesize that the same dynamic sequences are used in small groups of many other animal species forming pecking orders, and we discuss the data required to evaluate our hypothesis. Finally, we briefly consider how our dynamic approach may be generalized to other kinds of social hierarchies using the example of the distribution of empty gastropod (snail) shells occupied in populations of hermit crabs.

Data-based analysis of winner-loser models of hierarchy formation in animals.

We review winner-loser models, the currently popular explanation for the occurrence of linear dominance hierarchies, via a three-part approach. (1) We isolate the two most significant components of the mathematical formulation of three of the most widely-cited models and rigorously evaluate the components' predictions against data collected on hierarchy formation in groups of hens. (2) We evaluate the experimental support in the literature for the basic assumptions contained in winner-loser models. (3) We apply new techniques to the hen data to uncover several behavioral dynamics of hierarchy formation not previously described. The mathematical formulations of these models do not show satisfactory agreement with the hen data, and key model assumptions have either little or no conclusive support from experimental findings in the literature. In agreement with the latest experimental results concerning social cognition, the new behavioral dynamics of hierarchy formation discovered in the hen data suggest that members of groups are intensely aware both of their own interactions as well as interactions occurring among other members of their group. We suggest that more adequate models of hierarchy formation should be based upon behavioral dynamics that reflect more sophisticated levels of social cognition.

Continuous shifts in the active set of spinal interneurons during changes in locomotor speed.

The classic 'size principle' of motor control describes how increasingly forceful movements arise by the recruitment of motoneurons of progressively larger size and force output into the active pool. We explored the activity of pools of spinal interneurons in larval zebrafish and found that increases in swimming speed were not associated with the simple addition of cells to the active pool. Instead, the recruitment of interneurons at faster speeds was accompanied by the silencing of those driving movements at slower speeds. This silencing occurred both between and within classes of rhythmically active premotor excitatory interneurons. Thus, unlike motoneurons, there is a continuous shift in the set of cells driving the behavior, even though changes in the speed of the movements and the frequency of the motor pattern appear to be smoothly graded. We conclude that fundamentally different principles may underlie the recruitment of motoneuron and interneuron pools.

Chronic alcohol drinking alters neuronal dendritic spines in the brain reward center nucleus accumbens.

Alcohol is known to affect glutamate transmission. However, how chronic alcohol affects the synaptic structure mediating glutamate transmission is unknown. Repeated alcohol exposure in a subject with familial alcoholic history often leads to alcohol addiction. The current study adopts alcohol-preferring rats, which are known to develop high drinking. Two-photon microscopy analysis indicates that chronic alcohol of 14 weeks either, under continuous alcohol (C-Alc) or with repeated deprivation (RD-Alc), causes dysmorphology--thickened, beaded, and disoriented dendrites that are reminiscent of reactive astrocytes--in a subpopulation of medium spiny neurons. The density of dendritic spines was found differentially lower in the nucleus accumbens of RD-Alc and C-Alc groups as compared with those of Water groups. Large-sized spines and multiple-headed spines were increased in the RD-Alc group. The NMDA receptor subunit NR1 proteins, as analyzed with Western blot, were upregulated in C-Alc, but not in RD-Alc. The upregulated NMDA receptor subunits of NR1 however, are predominantly a splice variant isoform with truncated exon 21, which is required for membrane-bound trafficking or anchoring into a spine synaptic site. These maladaptations may contribute to the transformation of spines. The changes, in density and head-size of spines and the corresponding NMDA receptors, demonstrated an alteration of microcircuitry for glutamate reception. The current study demonstrates for the first time that chronic alcohol exposure causes structural alteration of dendrites and their spines in the key reward brain region in animals that have a genetic background leading to alcohol addiction.

The geometry of primary drainage.

We show that arc menisci configuration under primary drainage in capillary tube cross sections and, by extension, in throats in the void structure of rock and soil, can be understood in terms of the computational geometry theory of medial axis analysis. The solution for arc meniscus configuration is developed for cross sections of arbitrary, simply connected polygonal shape at both entry- and over-pressure values during primary drainage for arbitrary values of wetting angle. Using this solution technique, we have obtained highly accurate solutions of entry pressure arc meniscus radius for over 21,500 throats obtained from analysis of computed tomography images in a suite of 4 Fontainebleau core samples ranging from 7.5 to 22% porosity. We show that the ratio A/P, of throat area to throat perimeter, is an excellent predictor of entry pressure meniscus radius (and hence entry pressure) for primary drainage for real pores, while inscribed radius and area equivalent radius over-predict entry pressure meniscus radius by factors of 1.5-3, and are consequently poor predictors.

Automated algorithms for multiscale morphometry of neuronal dendrites.

We describe the synthesis of automated neuron branching morphology and spine detection algorithms to provide multiscale three-dimensional morphological analysis of neurons. The resulting software is applied to the analysis of a high-resolution (0.098 microm x 0.098 microm x 0.081 microm) image of an entire pyramidal neuron from layer III of the superior temporal cortex in rhesus macaque monkey. The approach provides a highly automated, complete morphological analysis of the entire neuron; each dendritic branch segment is characterized by several parameters, including branch order, length, and radius as a function of distance along the branch, as well as by the locations, lengths, shape classification (e.g., mushroom, stubby, thin), and density distribution of spines on the branch. Results for this automated analysis are compared to published results obtained by other computer-assisted manual means.

Experience-dependent changes in basal dendritic branching of layer 2/3 pyramidal neurons during a critical period for developmental plasticity in rat barrel cortex.

In rat barrel cortex, development of layer 2/3 receptive fields can be disrupted by sensory deprivation, with a critical period ending around postnatal day (PND) 14. To determine if experience-dependent plasticity of dendritic morphology could contribute to the reorganization of synaptic inputs, we analyzed dendritic structure in acute brain slices using two-photon laser scanning microscopy (2PLSM) and automated segmentation and analysis software. Layer 2/3 pyramidal cells from control and deprived rats were imaged from PND 9 to PND 20, spanning the critical period. Detailed analyses were performed on basal arbors, which receive the majority of synaptic input from layer 4. Some parameters (number of primary dendrites, volume subtended, aspect ratios) were stable, suggesting that development of several important properties of basal arbors has ceased by age PND 9. However, the spatial organization of secondary branching changed with age and experience. In older neurons there was a larger fraction of branch points farther from the soma. Deprivation from age PND 9 delayed these changes in secondary branching. This effect of deprivation was rapid (detectable at PND 10) and present at all ages observed. Deprivation initiated at PND 15 had no effect on basal branching measured at PND 20. Thus the spatial organization of secondary dendritic branching is experience-dependent and shares a critical period with receptive field plasticity.

An algorithm for neurite outgrowth reconstruction.

We present a numerical method which provides the ability to analyze digitized microscope images of retinal explants and quantify neurite outgrowth. Few parameters are required as input and limited user interaction is necessary to process an entire experiment of images. This eliminates fatigue related errors and user-related bias common to manual analysis. The method does not rely on stained images and handles images of variable quality. The algorithm is used to determine time and dose dependent, in vitro, neurotoxic effects of 1 GeV per nucleon iron particles in retinal explants. No neurotoxic effects are detected until 72 h after exposure; at 72 h, significant reductions of neurite outgrowth occurred at doses higher than 10 cGy.

An image analysis algorithm for dendritic spines.

The structure of neuronal dendrites and their spines underlie the connectivity of neural networks. Dendrites, spines, and their dynamics are shaped by genetic programs as well as sensory experience. Dendritic structures and dynamics may therefore be important predictors of the function of neural networks. Based on new imaging approaches and increases in the speed of computation, it has become possible to acquire large sets of high-resolution optical micrographs of neuron structure at length scales small enough to resolve spines. This advance in data acquisition has not been accompanied by comparable advances in data analysis techniques; the analysis of dendritic and spine morphology is still accomplished largely manually. In addition to being extremely time intensive, manual analysis also introduces systematic and hard-to-characterize biases. We present a geometric approach for automatically detecting and quantifying the three-dimensional structure of dendritic spines from stacks of image data acquired using laser scanning microscopy. We present results on the measurement of dendritic spine length, volume, density, and shape classification for both static and time-lapse images of dendrites of hippocampal pyramidal neurons. For spine length and density, the automated measurements in static images are compared with manual measurements. Comparisons are also made between automated and manual spine length measurements for a time-series data set. The algorithm performs well compared to a human analyzer, especially on time-series data. Automated analysis of dendritic spine morphology will enable objective analysis of large morphological data sets. The approaches presented here are generalizable to other aspects of neuronal morphology.