Emergent decision-making in biological signal transduction networks

The complexity of biochemical intracellular signal transduction networks has led to speculation that the high degree of interconnectivity that exists in these networks transforms them into an information processing network. To test this hypothesis directly, a large scale model was created with the logical mechanism of each node described completely to allow simulation and dynamical analysis. Exposing the network to tens of thousands of random combinations of inputs and analyzing the combined dynamics of multiple outputs revealed a robust system capable of clustering widely varying input combinations into equivalence classes of biologically relevant cellular responses. This capability was nontrivial in that the network performed sharp, nonfuzzy classifications even in the face of added noise, a hallmark of real-world decision-making

Boolean Network Topologies and the Determinative Power of Nodes

Boolean networks have been used extensively for modeling networks whose node activity could be simplified to a binary outcome, such as on-off. Each node is influenced by the states of the other nodes via a logical Boolean function. The network is described by its topological properties which refer to the links between nodes, and its dynamical properties which refer to the way each node uses the information obtained from other nodes to update its state. This work explores the correlation between the information stored in the Boolean functions for each node in a property known as the determinative power and some topological properties of each node, in particular the clustering coefficient and the betweenness centrality. The determinative power of nodes is defined using concepts from information theory, in particular the mutual information. The primary motivation is to construct models of real world networks to examine if the determinative power is sensitive to any of the considered topological properties. The findings indicate that, for a homogeneous network in which all nodes obey the same threshold function under three different topologies, the determinative power can have a negative correlation with the clustering coefficient and a positive correlation with the betweenness centrality, depending on the topological properties of the network. A statistical analysis on a collection of 36 Boolean models of signal transduction networks reveals that the correlations observed in the theoretical cases are suppressed in the biological networks, thus supporting previous research results

Emergent decision-making in biological signal transduction networks

The complexity of biochemical intracellular signal transduction networks has led to speculation that the high degree of interconnectivity that exists in these networks transforms them into an information processing network. To test this hypothesis directly, a large scale model was created with the logical mechanism of each node described completely to allow simulation and dynamical analysis. Exposing the network to tens of thousands of random combinations of inputs and analyzing the combined dynamics of multiple outputs revealed a robust system capable of clustering widely varying input combinations into equivalence classes of biologically relevant cellular responses. This capability was nontrivial in that the network performed sharp, nonfuzzy classifications even in the face of added noise, a hallmark of real-world decision-making

Boolean Modeling of Biochemical Networks

The use of modeling to observe and analyze the mechanisms of complex biochemical network function is becoming an important methodological tool in the systems biology era. Number of different approaches to model these networks have been utilized-- they range from analysis of static connection graphs to dynamical models based on kinetic interaction data. Dynamical models have a distinct appeal in that they make it possible to observe these networks in action, but they also pose a distinct challenge in that they require detailed information describing how the individual components of these networks interact in living cells. Because this level of detail is generally not known, dynamic modeling requires simplifying assumptions in order to make it practical. In this review Boolean modeling will be discussed, a modeling method that depends on the simplifying assumption that all elements of a network exist only in one of two states

Identifying designatable units for intraspecific conservation prioritization : a hierarchical approach applied to the lake whitefish species complex (Coregonus spp.)

The concept of the designatable unit (DU) affords a practical approach to identifying diversity below the species level for conservation prioritization. However, its suitability for defining conservation units in ecologically diverse, geographically widespread and taxonomically challenging species complexes has not been broadly evaluated. The lake whitefish species complex (Coregonus spp.) is geographically widespread in the Northern Hemisphere, and it contains a great deal of variability in ecology and evolutionary legacy within and among populations, as well as a great deal of taxonomic ambiguity. Here, we employ a set of hierarchical criteria to identify DUs within the Canadian distribution of the lake white- fish species complex. We identified 36 DUs based on (i) reproductive isolation, (ii) phylogeographic groupings, (iii) local adaptation and (iv) biogeographic regions. The identification of DUs is required for clear discussion regarding the conservation prioritization of lake whitefish populations. We suggest conservation priorities among lake whitefish DUs based on biological consequences of extinction, risk of extinction and distinctiveness. Our results exemplify the need for extensive genetic and biogeographic analyses for any species with broad geographic distributions and the need for detailed evaluation of evolutionary history and adaptive ecological divergence when defining intraspecific conservation units

Interspecies and Interregional Analysis of the Comparative Histologic Thickness and Laser Doppler Blood Flow Measurements at Five Cutaneous Sites in Nine Species

Studies in dermatology, cutaneous pharmacology, and toxicology utilize skin from different animal species and body sites. However, regional differences exist in topical chemical percutaneous absorption studies in man and in animals. The objective of this study was to compare epidermal thickness and number of cell layers across species and body sites using both formalin-fixed paraffin and frozen sections. Cutaneous blood flow determined by laser Doppler velocimetry (LDV)was compared to histologic data. Six animals of each of the following species were used: monkeys, pigs, dogs, cats, cows, horses, rabbits, rats, and mice. Cutaneous blood flow was determined and 6-mm skin biopsies were taken directly from the following sites: buttocks, ear, humeroscapular joint, thoracolumbar junction, and abdominal area. When the two histologic methods were compared across all species and body sites, the thickness of the epidermis was significantly greater, and the thickness of the stratum corneum significantly less, in paraffin sections versus frozen sections (p < 0.05). There were no differences in the number of viable cell layers determined by both methods. The values for LDV-determined blood flow did not significantly correlate (p > 0.05) to epidermal or stratum corneum thickness. However, regional and species differences were noted in all these parameters. In conclusion, these data indicate that thickness and LDV blood flow are independent and must be evaluated separately when comparisons are made between species and body sites. This work provides a data base for future comparative studies in which a knowledge of skin thickness or blood flow might be important variables

Editorial: Environmental data, governance and the sustainable city

The availability of new types of environmental data has the potential to change the ways in which cities are governed to improve their sustainability, resilience, and livability. Distributed sensors delivering real-time data can improve the monitoring and management of urban systems, as well as enabling robust assessments of policy and planning interventions. Real-time high-resolution sensor data provides a wealth of new opportunities for understanding systems and the interaction of physical, technical and anthropogenic activity. These benefits include long (multi-year) data baselines of high-resolution data enabling new statistical and artificial intelligence approaches; real-time analytics and visualizations supporting decision support systems; vulnerability or incipient failure detection to enable (proactive) maintenance rather than (subsequent, reactive) repair; parameterization of urban digital twins of physical and natural systems for simulation and prediction and what-if scenario testing; post-event analysis and post-intervention analysis across multiple phenomena at different timescales; and digital playback of systems when singularities, oversights, mistakes or other unforeseen events occur

Prospectus, March 4, 1987

https://spark.parkland.edu/prospectus_1987/1007/thumbnail.jp

Attenuation of ocean surface waves in pancake and frazil sea ice along the coast of the Chukchi Sea

Alaskan Arctic coastlines are protected seasonally from ocean waves by the presence of coastal and shorefast sea ice. This study presents field observations collected during the autumn 2019 freeze up near Icy Cape, a coastal headland in the Chukchi Sea of the Western Arctic. The evolution of the coupled air-ice-ocean-wave system during a four-day wave event was monitored using drifting wave buoys, a cross-shore mooring array, and ship-based measurements. The incident wave field with peak period of 2.5 s was attenuated by coastal pancake and frazil sea ice, reducing significant wave height by 40\% over less than 5 km of cross-shelf distance spanning water depths from 13 to 30 m. Spectral attenuation coefficients are evaluated with respect to wave and ice conditions and the proximity to the ice edge. Attenuation rates are found to be three times higher within 500 m of the ice edge, relative to values farther in the ice cover. Attenuation coefficients are in the range of $\langle 2.3,2.7\rangle$ \si{\meter^{-1}}, and follow a power-law dependence on frequency

Problem gambling: a suitable case for social work?

Problem gambling attracts little attention from health and social care agencies in the UK. Prevalence surveys suggest that 0.6% of the population are problem gamblers and it is suggested that for each of these individuals, 10–17 other people, including children and other family members, are affected. Problem gambling is linked to many individual and social problems including: depression, suicide, significant debt, bankruptcy, family conflict, domestic violence, neglect and maltreatment of children and offending. This makes the issue central to social work territory. Yet, the training of social workers in the UK has consistently neglected issues of addictive behaviour. Whilst some attention has been paid in recent years to substance abuse issues, there has remained a silence in relation to gambling problems. Social workers provide more help for problems relating to addictions than other helping professions. There is good evidence that treatment, and early intervention for gambling problems, including psycho-social and public health approaches, can be very effective. This paper argues that problem gambling should be moved onto the radar of the social work profession, via inclusion on qualifying and post-qualifying training programmes and via research and dissemination of good practice via institutions such as the Social Care Institute for Excellence (SCIE). Keywords: problem gambling; addictive behaviour; socia