Some Work and Some Play: Microscopic and Macroscopic Approaches to Labor and Leisure

Given the option, humans and other animals elect to distribute their time between work and leisure, rather than choosing all of one and none of the other. Traditional accounts of partial allocation have characterised behavior on a macroscopic timescale, reporting and studying the mean times spent in work or leisure. However, averaging over the more microscopic processes that govern choices is known to pose tricky theoretical problems, and also eschews any possibility of direct contact with the neural computations involved. We develop a microscopic framework, formalized as a semi-Markov decision process with possibly stochastic choices, in which subjects approximately maximise their expected returns by making momentary commitments to one or other activity. We show macroscopic utilities that arise from microscopic ones, and demonstrate how facets such as imperfect substitutability can arise in a more straightforward microscopic manner.     

Protein Networks Reveal Detection Bias and Species Consistency When Analysed by Information-Theoretic Methods

We apply our recently developed information-theoretic measures for the characterisation and comparison of protein–protein interaction networks. These measures are used to quantify topological network features via macroscopic statistical properties. Network differences are assessed based on these macroscopic properties as opposed to microscopic overlap, homology information or motif occurrences. We present the results of a large–scale analysis of protein–protein interaction networks. Precise null models are used in our analyses, allowing for reliable interpretation of the results. By quantifying the methodological biases of the experimental data, we can define an information threshold above which networks may be deemed to comprise consistent macroscopic topological properties, despite their small microscopic overlaps. Based on this rationale, data from yeast–two–hybrid methods are sufficiently consistent to allow for intra–species comparisons (between different experiments) and inter–species comparisons, while data from affinity–purification mass–spectrometry methods show large differences even within intra–species comparisons.     

Long-Term Evolution of Email Networks: Statistical Regularities,Predictability and Stability of Social Behaviors

In social networks, individuals constantly drop ties and replace them by new ones in a highly unpredictable fashion. This highly dynamical nature of social ties has important implications for processes such as the spread of information or of epidemics. Several studies have demonstrated the influence of a number of factors on the intricate microscopic process of tie replacement, but the macroscopic long-term effects of such changes remain largely unexplored. Here we investigate whether, despite the inherent randomness at the microscopic level, there are macroscopic statistical regularities in the long-term evolution of social networks. In particular, we analyze the email network of a large organization with over 1,000 individuals throughout four consecutive years. We find that, although the evolution of individual ties is highly unpredictable, the macro-evolution of social communication networks follows well-defined statistical patterns, characterized by exponentially decaying log-variations of the weight of social ties and of individuals’ social strength. At the same time, we find that individuals have social signatures and communication strategies that are remarkably stable over the scale of several years.     

Allocation procedure in multi-output process: an illustration of ISO 14041

Allocation results for a multi-output process in a life cycle assessment study depend on the definition of the unit process which can vary with the depth of a study. The unit process may be a manufacturing site, a sub-process, or an operational unit (e.g. distillation column or reactor). There are three different approaches to define a unit process: macroscopic approach, quasi-microscopic approach, and microscopic approach. In the macroscopic approach, a unit process is the manufacturing site, while a unit process in the quasi-microscopic approach is a sub-process of the manufacturing site. An operational unit becomes the unit process in the microscopic approach. In the quasi-microscopic and the microscopic approaches, a process can be subdivided into a joint process, a physically separated process which is physically apart from other processes, and a fully separated process. Each type can be a unit process. Therefore, the multi-output process in the quasi-microscopic and the microscopic approaches can be subdivided among two or more unit processes depending on the actual operations. The allocation in the fully separated process can be avoided because this process fulfills one function. In the joint process and the physically separated process, which deliver two or more functions, allocation is still required. Ammonia manufacturing, where carbon dioxide is formed as a byproduct is given to show a specific detailed example of the allocation procedure by subdivision in ISO 14041. It is shown that the quasi-microscopic and the microscopic approaches can reduce the multi-output allocation of a given chemical product. Furthermore, the quasi-microscopic and the microscopic approaches are very useful in identifying key pollution prevention issues related with one product or function.     

A microscopic model of enzyme kinetics.

Many in vivo enzymatic processes, such as those of the tissue factor pathway of blood coagulation, occur in environments with facilitated substrate delivery or enzymes bound to cellular or lipid surfaces, which are quite different from the ideal fluid environment for which the Michaelis-Menten equation was derived. To describe the kinetics of such reactions, we propose a microscopic model that focuses on the kinetics of a single-enzyme molecule. This model provides the foundation for macroscopic models of the system kinetics of reactions occurring in both ideal and nonideal environments. For ideal reaction systems, the corresponding macroscopic models thus derived are consistent with the Michaelis-Menten equation. It is shown that the apparent Km is in fact a function of the mechanism of substrate delivery and should be interpreted as the substrate level at which the enzyme vacancy time equals the residence time of ES-complexes; it is suggested that our microscopic model parameters characterize more accurately an enzyme and its catalytic efficiency than does the classical Km. This model can also be incorporated into computer simulations of more complex reactions as an alternative to explicit analytical formulation of a macroscopic model.     

Visual cortex: cartography, connectivity, and concurrent processing.

The mammalian visual cortex contains a complex mosaic of areas that are richly connected with one another. Recent progress has advanced our understanding of both macroscopic and microscopic aspects of cortical organization, and of information flow within and between functionally specialized processing streams.     

Definitions of state variables and state space for brain-computer interface

Neocortical state variables are defined and evaluated at three levels: microscopic using multiple spike activity (MSA), mesoscopic using local field potentials (LFP) and electrocorticograms (ECoG), and macroscopic using electroencephalograms (EEG) and brain imaging. Transactions between levels occur in all areas of cortex, upwardly by integration (abstraction, generalization) and downwardly by differentiation (speciation). The levels are joined by circular causality: microscopic activity upwardly creates mesoscopic order parameters, which downwardly constrain the microscopic activity that creates them. Integration dominates in sensory cortices. Microscopic activity evoked by receptor input in sensation induces emergence of mesoscopic activity in perception, followed by integration of perceptual activity into macroscopic activity in concept formation. The reverse process dominates in motor cortices, where the macroscopic activity embodying the concepts supports predictions of future states as goals. These macroscopic states are conceived to order mesoscopic activity in patterns that constitute plans for actions to achieve the goals. These planning patterns are conceived to provide frames in which the microscopic activity evolves in trajectories that adapted to the immediate environmental conditions detected by new stimuli. This circular sequence forms the action-perception cycle. Its upward limb is understood through correlation of sensory cortical activity with behavior. Now brain-machine interfaces (BMI) offer a means to understand the downward sequence through correlation of behavior with motor cortical activity, beginning with macroscopic goal states and concluding with recording of microscopic MSA trajectories that operate neuroprostheses. Part 1 develops a hypothesis that describes qualitatively the neurodynamics that supports the action-perception cycle and derivative reflex arc. Part 2 describes episodic, “cinematographic” spatial pattern formation and predicts some properties of the macroscopic and mesoscopic frames by which the embedded trajectories of the microscopic activity of cortical sensorimotor neurons might be organized and controlled. URL: http://sulcus.berkeley.edu     

Effect of tortuous extracellular pathways on resistance measurements

There are many instances in which we are limited to measuring macroscopic quantities such as a bulk flow or an average field. In biology, wer are frequently interested in using such macroscopic measurements, for example, the total current from a tissue, to determine the microscopic properties of the cells or tubules of the tissue. The microstructure of the tissue will generally increase the resistance to flow over what would be measured in an unstructured medium. This paper derives a fairly general expression for the relationship between effective resistance to macroscopic flow and the specific resistance of the medium conducting the microscopic flow. This expression, called a tortuosity factor, is defined entirely in terms of measurable morphometric and geometric parameters of the tissue.     

Geometric triangular chiral hexagon crystal-like complexes organization in pathological tissues biological collision order

The present study describes and documents self-assembly of geometric triangular chiral hexagon crystal like complex organizations (GTCHC) in human pathological tissues. The authors have found this architectural geometric expression at macroscopic and microscopic levels mainly in cancer processes. This study is based essentially on macroscopic and histopathologic analyses of 3000 surgical specimens: 2600 inflammatory lesions and 400 malignant tumours. Geometric complexes identified photographically at macroscopic level were located in the gross surgical specimen, and these areas were carefully dissected. Samples were taken to carry out histologic analysis. Based on the hypothesis of a collision genesis mechanism and because it is difficult to carry out an appropriate methodological observation in biological systems, the authors designed a model base on other dynamic systems to obtain indirect information in which a strong white flash wave light discharge, generated by an electronic device, hits over the lines of electrical conductance structured in helicoidal pattern. In their experimental model, the authors were able to reproduce and to predict polarity, chirality, helicoid geometry, triangular and hexagonal clusters through electromagnetic sequential collisions. They determined that similar events among constituents of extracelular matrix which drive and produce piezoelectric activity are responsible for the genesis of GTCHC complexes in pathological tissues. This research suggests that molecular crystals represented by triangular chiral hexagons derived from a collision-attraction event against collagen type I fibrils emerge at microscopic and macroscopic scales presenting a lateral assembly of each side of hypertrophy helicoid fibers, that represent energy flow in cooperative hierarchically chiral electromagnetic interaction in pathological tissues and arises as a geometry of the equilibrium in perturbed biological systems. Further interdisciplinary studies must be carried out to reproduce, manipulate and amplify their activity and probably use them as a base to develop new therapeutic strategies in cancer.     

A multilevel approach to cancer growth modeling

Cancer growth models may be divided into macroscopic models, which describe the tumor as a single entity, and microscopic ones, which consider the tumor as a complex system whose behavior emerges from the local dynamics of its basic components, the neoplastic cells. Mesoscopic models (e.g. as based on the Local Interaction Simulation Approach [Delsanto, P.P., Mignogna, R., Scalerandi, M., Schechter, R., 1998. In: Delsanto, P.P. Saenz, A.W. (Eds.), New Perspectives on Problems in Classical and Quantum Physics, vol. 2. Gordon & Breach, New Delhi, p. 5174]), which explicitly consider the behavior of cell clusters and their interactions, may be used instead of the microscopic ones, in order to study the properties of cancer biology that strongly depend on the interactions of small groups of cells at intermediate spatial and temporal scales. All these approaches have been developed independently, which limits their usefulness, since they all include relevant features and information that should be cross-correlated for a deeper understanding of the mechanisms involved. In this contribution we consider multicellular tumor spheroids as biological reference systems and propose an intermediate model to bridge the gap between a macroscopic formulation of tumor growth and a mesoscopic one. Thus we are able to establish, as an important result of our formalism, a direct correspondence between parameters characterizing processes occurring at different scales. In particular, we analyze their dependence on an important limiting factor to tumor growth, i.e. the extra-cellular matrix pressure. Since the macro and meso-models stem from totally different roots (energy conservation and clinical observations vs. cell groups dynamics), their consistency may be used to validate both approaches. It may also be interesting to note that the proposed formalism fits well into a recently proposed conjecture of growth laws universality.     

Structural and organisational conditions for being a machine

Although the analogy between macroscopic machines and biological molecular devices plays an important role in the conceptual framework of both neo-mechanistic accounts and nanotechnology, it has recently been claimed that certain complex molecular devices (consisting of biological or synthetic macromolecular aggregates) cannot be considered machines since they are subject to physicochemical forces that are different from those of macroscopic machines. However, the structural and physicochemical conditions that allow both macroscopic machines and microscopic devices to work and perform new functions, through a combination of elemental functional parts, have not yet been examined. In order to fill this void, this paper has a threefold aim: first, to clarify the structural and organisational conditions of macroscopic machines and microscopic devices; second, to determine whether the machine-like analogy fits nanoscale devices; and third, to assess whether the machine-like analogy is appropriate for describing the behaviour of some biological macromolecules. Finally, the paper gives an account of ‘machine’ which, while acknowledging the physicochemical and organisational differences between man-made machines and biological microscopic devices, nevertheless identifies a common conceptual core that allows us to consider the latter ‘machines’.     

From macroscopic measurements to microscopic mechanisms of protein aggregation

The ability to relate bulk experimental measurements of amyloid formation to the microscopic assembly processes that underlie protein aggregation is critical in order to achieve a quantitative understanding of this complex phenomenon. In this review, we focus on the insights from classical and modern theories of linear growth phenomena and discuss how theory allows the roles of growth and nucleation processes to be defined through the analysis of experimental in vitro time courses of amyloid formation. Moreover, we discuss the specific signatures in the time course of the reactions that correspond to the actions of primary and secondary nucleation processes, and outline strategies for identifying and characterising the nature of the dominant process responsible in each case for the generation of new aggregates. We highlight the power of a global analysis of experimental time courses acquired under different conditions, and discuss how such an analysis allows a rigorous connection to be established between the macroscopic measurements and the rates of the individual microscopic processes that underlie the phenomenon of amyloid formation.     

Students' cellular and molecular explanations of genetic phenomena

Genetic concepts are assigned to three principal levels of organisation: macroscopic level, microscopic level, and submicroscopic level. In order to probe Israeli students' understanding at each level, and to gain a sense of their ability to connect ideas and concepts across different levels, we asked three different types of question. Two of the question types ask students to make a bridge between levels by asking them to explain a phenomenon at one level using concepts and processes from a different level. For example, to explain the appearance of phenotypic traits (macroscopic level) using concepts like genes or chromosomes (microscopic level). One question dealt with the molecular level only. We investigated three populations: 9^th graders, 12^th graders, and pre-service teachers. Based on our findings we suggest improvements both in terms of teaching methods and curriculum content.     

A synaptic model for the kindling effect

In this work we present a model of the kindling effect based on the Hopf bifurcation for a system of ordinary differential equations. The model shows how quantitative changes in the physiological parameters at the microscopic, synaptic scale, produce the afterdischarge which is a macroscopic effect at the neuronal network scale. The presynaptic mechanisms are based on the vesicular hypothesis, or more generally on the quantal theory of synaptic transmission. The postsynaptic processes rely on Granit's law. This model gives a consistent framework which organizes and explains several experimental observations.     

Definitions of state variables and state space for brain–computer interface

The hypothesis is proposed that the central dynamics of the action–perception cycle has five steps: emergence from an existing macroscopic brain state of a pattern that predicts a future goal state; selection of a mesoscopic frame for action control; execution of a limb trajectory by microscopic spike activity; modification of microscopic cortical spike activity by sensory inputs; construction of mesoscopic perceptual patterns; and integration of a new macroscopic brain state. The basis is the circular causality between microscopic entities (neurons) and the mesoscopic and macroscopic entities (populations) self-organized by axosynaptic interactions. Self-organization of neural activity is bidirectional in all cortices. Upwardly the organization of mesoscopic percepts from microscopic spike input predominates in primary sensory areas. Downwardly the organization of spike outputs that direct specific limb movements is by mesoscopic fields constituting plans to achieve predicted goals. The mesoscopic fields in sensory and motor cortices emerge as frames within macroscopic activity. Part 1 describes the action–perception cycle and its derivative reflex arc qualitatively. Part 2 describes the perceptual limb of the arc from microscopic MSA to mesoscopic wave packets, and from these to macroscopic EEG and global ECoG fields that express experience-dependent knowledge in successive states. These macroscopic states are conceived to embed and control mesoscopic frames in premotor and motor cortices that are observed in local ECoG and LFP of frontoparietal areas. The fields sampled by ECoG and LFP are conceived as local patterns of neural activity in which trajectories of multiple spike activities (MSA) emerge that control limb movements. Mesoscopic frames are located by use of the analytic signal from the Hilbert transform after band pass filtering. The state variables in frames are measured to construct feature vectors by which to describe and classify frame patterns. Evidence is cited to justify use of linear analysis. The aim of the review is to enable researchers to conceive and identify goal-oriented states in brain activity for use as commands, in order to relegate the details of execution to adaptive control devices outside the brain. http://sulcus.berkeley.edu     

Comparison of the soluble organic matrices of healthy and diseased shells of Pinctada margaritifera (L.) and Pecten maximus L. (Mollusca, Bivalvia)

Pinctada margaritifera and Pecten maximus are among the mollusks of commercial value. Both are known to show abnormal calcification processes that strongly increase the mortality rate. Several parameters of the soluble organic matrices extracted from the shells of P. margaritifera and P. maximus are analyzed: bulk composition, molecular weights, and acidity. The composition of the matrices of healthy and diseased shells were compared, showing that the protein and the sugar contents are variously modified. Differences between healthy and diseased shells are dissimilar in the two species. This is in accordance with the previously described macroscopic and microscopic alterations (red color, numerous brown membranes). This study does not allow identification the origin of the disease, but provides new insights on the role of sugars in biomineralization processes.     

The common patterns of nature

We typically observe large‐scale outcomes that arise from the interactions of many hidden, small‐scale processes. Examples include age of disease onset, rates of amino acid substitutions and composition of ecological communities. The macroscopic patterns in each problem often vary around a characteristic shape that can be generated by neutral processes. A neutral generative model assumes that each microscopic process follows unbiased or random stochastic fluctuations: random connections of network nodes; amino acid substitutions with no effect on fitness; species that arise or disappear from communities randomly. These neutral generative models often match common patterns of nature. In this paper, I present the theoretical background by which we can understand why these neutral generative models are so successful. I show where the classic patterns come from, such as the Poisson pattern, the normal or Gaussian pattern and many others. Each classic pattern was often discovered by a simple neutral generative model. The neutral patterns share a special characteristic: they describe the patterns of nature that follow from simple constraints on information. For example, any aggregation of processes that preserves information only about the mean and variance attracts to the Gaussian pattern; any aggregation that preserves information only about the mean attracts to the exponential pattern; any aggregation that preserves information only about the geometric mean attracts to the power law pattern. I present a simple and consistent informational framework of the common patterns of nature based on the method of maximum entropy. This framework shows that each neutral generative model is a special case that helps to discover a particular set of informational constraints; those informational constraints define a much wider domain of non‐neutral generative processes that attract to the same neutral pattern.     

A reaction-diffusion model to predict the influence of neo-matrix on the subsequent development of tissue-engineered cartilage

Extracellular matrix (ECM) in chondrocytes-seeded agarose aggregates to form islands of matrix. These islands need to coalesce to develop functional cartilage. Hence, macroscopic properties are determined by transport and aggregation of macromolecules at the microscale, which varies temporally and spatially. This study evaluates the importance of the mutual interaction between matrix components and matrix development. Fluorescence recovery after photobleaching measurements demonstrates that diffusivity depends on the presence and density of ECM. A reaction-diffusion model describing synthesis, transport and immobilisation of ECM predicts steep gradients in ECM around chondrocytes, resembling histology. Steric hindrance of diffusion by ECM is essential for the formation of these gradients. Finally, microscopic ECM concentration is linked with macroscopic mechanical properties. Construct softening is predicted when temporal and spatial variations in diffusivity are considered. In conclusion, non-constant diffusion renders significant effects on both the microscopic ECM development and the macroscopic mechanical properties of developing tissue-engineered cartilage.