The coevolution of cooperation and dispersal in social groups and its implications for the emergence of multicellularity

Background Recent work on the complexity of life highlights the roles played by evolutionary forces at different levels of individuality. One of the central puzzles in explaining transitions in individuality for entities ranging from complex cells, to multicellular organisms and societies, is how different autonomous units relinquish control over their functions to others in the group. In addition to the necessity of reducing conflict over effecting specialized tasks, differentiating groups must control the exploitation of the commons, or else be out-competed by more fit groups. Results We propose that two forms of conflict – access to resources within groups and representation in germ line – may be resolved in tandem through individual and group-level selective effects. Specifically, we employ an optimization model to show the conditions under which different within-group social behaviors (cooperators producing a public good or cheaters exploiting the public good) may be selected to disperse, thereby not affecting the commons and functioning as germ line. We find that partial or complete dispersal specialization of cheaters is a general outcome. The propensity for cheaters to disperse is highest with intermediate benefit:cost ratios of cooperative acts and with high relatedness. An examination of a range of real biological systems tends to support our theory, although additional study is required to provide robust tests. Conclusion We suggest that trait linkage between dispersal and cheating should be operative regardless of whether groups ever achieve higher levels of individuality, because individual selection will always tend to increase exploitation, and stronger group structure will tend to increase overall cooperation through kin selected benefits. Cheater specialization as dispersers offers simultaneous solutions to the evolution of cooperation in social groups and the origin of specialization of germ and soma in multicellular organisms.

A case of distinct difference between the measured blood Ethanol concentration and the concentration estimated by Widmark's equation

In the last century, several mathematical models have been developed to calculate blood ethanol concentrations (BAC) from the amount of ingested ethanol and vice versa. The most common one in the field of forensic sciences is Widmark's equation. A drinking experiment with 10 voluntary test persons was performed with a target BAC of 1.2 g/kg estimated using Widmark's equation as well as Watson's factor. The ethanol concentrations in the blood were measured using headspace gas chromatography/flame ionization and additionally with an alcohol Dehydrogenase (ADH)-based method. In a healthy 75-year-old man a distinct discrepancy between the intended and the determined blood ethanol concentration was observed. A blood ethanol concentration of 1.83 g/kg was measured and the man showed signs of intoxication. A possible explanation for the discrepancy is a reduction of the total body water content in older people. The incident showed that caution is advised when using the different mathematical models in aged people. When estimating ethanol concentrations, caution is recommended with calculated results due to potential discrepancies between mathematical models and biological systems

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Extended kalman filter for estimation of parameters in nonlinear state-space models of biochemical networks.

It is system dynamics that determines the function of cells, tissues and organisms. To develop mathematical models and estimate their parameters are an essential issue for studying dynamic behaviors of biological systems which include metabolic networks, genetic regulatory networks and signal transduction pathways, under perturbation of external stimuli. In general, biological dynamic systems are partially observed. Therefore, a natural way to model dynamic biological systems is to employ nonlinear state-space equations. Although statistical methods for parameter estimation of linear models in biological dynamic systems have been developed intensively in the recent years, the estimation of both states and parameters of nonlinear dynamic systems remains a challenging task. In this report, we apply extended Kalman Filter (EKF) to the estimation of both states and parameters of nonlinear state-space models. To evaluate the performance of the EKF for parameter estimation, we apply the EKF to a simulation dataset and two real datasets: JAK-STAT signal transduction pathway and Ras/Raf/MEK/ERK signaling transduction pathways datasets. The preliminary results show that EKF can accurately estimate the parameters and predict states in nonlinear state-space equations for modeling dynamic biochemical networks.

Gold nanoparticle aerosols for rodent inhalation and translocation studies

The intensive use of nano-sized particles in many different applications necessitates studies on their risk assessment as there are still open questions on their safe handling and utilization. For reliable risk assessment, the interaction of nanoparticles (NP) with biological systems after various routes of exposure needs to be investigated using well-characterized NP. We report here on the generation of gold-NP (Au-NP) aerosols for inhalation studies with the spark ignition technique, and their characterization in terms of chemical composition, physical structure, morphology, and specific surface area, and on interaction with lung tissues and lung cells after 1 h inhalation by mice. The originally generated agglomerated Au-NP were converted into compact spherical Au-NP by thermal annealing at 600 °C, providing particles of similar mass, but different size and specific surface area. Since there are currently no translocation data available on inhaled Au-NP in the 10–50 nm diameter range, the emphasis was to generate NP as small as 20 nm for inhalation in rodents. For anticipated in vivo systemic translocation and dosimetry analyses, radiolabeled Au-NP were created by proton irradiating the gold electrodes of the spark generator, thus forming gamma ray emitting 195Au with 186 days half-life, allowing long-term biokinetic studies. The dissolution rate of 195Au from the NP was below detection limits. The highly concentrated, polydisperse Au-NP aerosol (1–2 × 107 NP/cm3) proved to be constant over several hours in terms of its count median mobility diameter, its geometric standard deviation and number concentration. After collection on filters particles can be re-suspended and used for instillation or ingestion studies.

Differential dynamic properties of scleroderma fibroblasts in response to perturbation of environmental stimuli.

Diseases are believed to arise from dysregulation of biological systems (pathways) perturbed by environmental triggers. Biological systems as a whole are not just the sum of their components, rather ever-changing, complex and dynamic systems over time in response to internal and external perturbation. In the past, biologists have mainly focused on studying either functions of isolated genes or steady-states of small biological pathways. However, it is systems dynamics that play an essential role in giving rise to cellular function/dysfunction which cause diseases, such as growth, differentiation, division and apoptosis. Biological phenomena of the entire organism are not only determined by steady-state characteristics of the biological systems, but also by intrinsic dynamic properties of biological systems, including stability, transient-response, and controllability, which determine how the systems maintain their functions and performance under a broad range of random internal and external perturbations. As a proof of principle, we examine signal transduction pathways and genetic regulatory pathways as biological systems. We employ widely used state-space equations in systems science to model biological systems, and use expectation-maximization (EM) algorithms and Kalman filter to estimate the parameters in the models. We apply the developed state-space models to human fibroblasts obtained from the autoimmune fibrosing disease, scleroderma, and then perform dynamic analysis of partial TGF-beta pathway in both normal and scleroderma fibroblasts stimulated by silica. We find that TGF-beta pathway under perturbation of silica shows significant differences in dynamic properties between normal and scleroderma fibroblasts. Our findings may open a new avenue in exploring the functions of cells and mechanism operative in disease development.

Indium-111 labeled gold nanoparticles for in-vivo molecular targeting.

The present report describes the synthesis and biological evaluation of a molecular imaging platform based on gold nanoparticles directly labeled with indium-111. The direct labeling approach facilitated radiolabeling with high activities while maintaining excellent stability within the biological environment. The resulting imaging platform exhibited low interference of the radiolabel with targeting molecules, which is highly desirable for in-vivo probe tracking and molecular targeted tumor imaging. The indium-111 labeled gold nanoparticles were synthesized using a simple procedure that allowed stable labeling of the nanoparticle core with various indium-111 activities. Subsequent surface modification of the particle cores with RGD-based ligands at various densities allowed for molecular targeting of the αvß3 integrin in-vitro and for molecular targeted imaging in human melanoma and glioblastoma models in-vivo. The results demonstrate the vast potential of direct labeling with radioisotopes for tracking gold nanoparticles within biological systems.

Quantification of nanoparticles at the single-cell level: an overview about state-of-the-art techniques and their limitations.

With the increasing production and use of engineered nanoparticles it is crucial that their interaction with biological systems is understood. Due to the small size of nanoparticles, their identification and localization within single cells is extremely challenging. Therefore, various cutting-edge techniques are required to detect and to quantify metals, metal oxides, magnetic, fluorescent, as well as electron-dense nanoparticles. Several techniques will be discussed in detail, such as inductively coupled plasma atomic emission spectroscopy, flow cytometry, laser scanning microscopy combined with digital image restoration, as well as quantitative analysis by means of stereology on transmission electron microscopy images. An overview will be given regarding the advantages of those visualization/quantification systems, including a thorough discussion about limitations and pitfalls.

Development of a Novel Green Fluorescent Protein-Based Binding Assay to Study the Association of Plakins with Intermediate Filament Proteins.

Protein-protein interactions are fundamental for most biological processes, such as the formation of cellular structures and enzymatic complexes or in signaling pathways. The identification and characterization of protein-protein interactions are therefore essential for understanding the mechanisms and regulation of biological systems. The organization and dynamics of the cytoskeleton, as well as its anchorage to specific sites in the plasma membrane and organelles, are regulated by the plakins. These structurally related proteins anchor different cytoskeletal networks to each other and/or to other cellular structures. The association of several plakins with intermediate filaments (IFs) is critical for maintenance of the cytoarchitecture. Pathogenic mutations in the genes encoding different plakins can lead to dramatic manifestations, occurring principally in the skin, striated muscle, and/or nervous system, due to cytoskeletal disorganization resulting in abnormal cell fragility. Nevertheless, it is still unclear how plakins bind to IFs, although some general rules are slowly emerging. We here describe in detail a recently developed protein-protein fluorescence binding assay, based on the production of recombinant proteins tagged with green fluorescent protein (GFP) and their use as fluid-phase fluorescent ligands on immobilized IF proteins. Using this method, we have been able to assess the ability of C-terminal regions of GFP-tagged plakin proteins to bind to distinct IF proteins and IF domains. This simple and sensitive technique, which is expected to facilitate further studies in this area, can also be potentially employed for any kind of protein-protein interaction studies.

Nitrate limitation and ocean acidification interact with UV-B to reduce photosynthetic performance in the diatom

It has been proposed that ocean acidification (OA) will interact with other environmental factors to influence the overall impact of global change on biological systems. Accordingly we investigated the influence of nitrogen limitation and OA on the physiology of diatoms by growing the diatom Phaeodactylum tricornutum Bohlin under elevated (1000 µatm; high CO2- HC) or ambient (390 µatm; low CO2-LC) levels of CO2 with replete (110 µmol/L; high nitrate-HN) or reduced (10 ?mol/L; low nitrate-LN) levels of NO3- and subjecting the cells to solar radiation with or without UV irradiance to determine their susceptibility to UV radiation (UVR, 280-400 nm). Our results indicate that OA and UVB induced significantly higher inhibition of both the photosynthetic rate and quantum yield under LN than under HN conditions. UVA or/and UVB increased the cells' non-photochemical quenching (NPQ) regardless of the CO2 levels. Under LN and OA conditions, activity of superoxide dismutase and catalase activities were enhanced, along with the highest sensitivity to UVB and the lowest ratio of repair to damage of PSII. HC-grown cells showed a faster recovery rate of yield under HN but not under LN conditions. We conclude therefore that nutrient limitation makes cells more prone to the deleterious effects of UV radiation and that HC conditions (ocean acidification) exacerbate this effect. The finding that nitrate limitation and ocean acidification interact with UV-B to reduce photosynthetic performance of the diatom P. tricornutum implies that ocean primary production and the marine biological C pump will be affected by OA under multiple stressors.

Effect of simulated ocean acidification on the acute toxicity of Cu and Cd to Tigriopus japonicus

Heavy metals pollution in marine environments has caused great damage to marine biological and ecological systems. Heavy metals accumulate in marine creatures, after which they are delivered to higher trophic levels of marine organisms through the marine food chain, which causes serious harm to marine biological systems and human health. Additionally, excess carbon dioxide in the atmosphere has caused ocean acidification. Indeed, about one third of the CO2 released into the atmosphere by anthropogenic activities since the beginning of the industrial revolution has been absorbed by the world's oceans, which play a key role in moderating climate change. Modeling has shown that, if current trends in CO2 emissions continue, the average pH of the ocean will reach 7.8 by the end of this century, corresponding to 0.5 units below the pre-industrial level, or a three-fold increase in H+ concentration. The ocean pH has not been at this level for several millions of years. Additionally, these changes are occurring at speeds 100 times greater than ever previously observed. As a result, several marine species, communities and ecosystems might not have time to acclimate or adapt to these fast changes in ocean chemistry. In addition, decreasing ocean pH has the potential to seriously affect the growth, development and reproduction reproductive processes of marine organisms, as well as threaten normal development of the marine ecosystem. Copepods are an important part of the meiofauna that play an important role in the marine ecosystem. Pollution of the marine environment can influence their growth and development, as well as the ecological processes they are involved in. Accordingly, there is important scientific value to investigation of the response of copepods to ocean acidification and heavy metals pollution. In the present study, we evaluated the effects of simulated future ocean acidification and the toxicological interaction between ocean acidity and heavy metals of Cu and Cd on T. japonicus. To accomplish this, harpacticoids were exposed to Cu and Cd concentration gradient seawater that had been equilibrated with CO2 and air to reach pH 8.0, 7.7, 7.3 and 6.5 for 96 h. Survival was not significantly suppressed under single sea water acidification, and the final survival rates were greater than 93% in both the experimental groups and the controls. The toxicity of Cu to T. japonicus was significantly affected by sea water acidification, with the 96h LC50 decreasing by nearly threefold from 1.98 to 0.64 mg/L with decreasing pH. The 96 h LC50 of Cd decreased with decreasing pH, but there was no significant difference in mortality among pH treatments. The results of the present study demonstrated that the predicted future ocean acidification has the potential to negatively affect survival of T. japonicus by exacerbating the toxicity of Cu. The calculated safe concentrations of Cu were 11.9 (pH 7.7) and 10.5 (pH 7.3) µg/L, which were below the class I value and very close to the class II level of the China National Quality Standard for Sea Water. Overall, these results indicate that the Chinese coastal sea will face a

A Model of Emotion as Patterned Metacontrol

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent ?in practical, economical, evolutionary terms? is the reduction of the dimensionality of the configuration space. This reduction is achieved both by functionalisation —or, to be more precise, by interface minimization— and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. In this paper we will show a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems.

A Model of Emotion as Patterned Metacontrol

Adaptive agents use feedback as a key strategy to cope with un- certainty and change in their environments. The information fed back from the sensorimotor loop into the control subsystem can be used to change four different elements of the controller: parameters associated to the control model, the control model itself, the functional organization of the agent and the functional realization of the agent. There are many change alternatives and hence the complexity of the agent’s space of potential configurations is daunting. The only viable alternative for space- and time-constrained agents —in practical, economical, evolutionary terms— is to achieve a reduction of the dimensionality of this configuration space. Emotions play a critical role in this reduction. The reduction is achieved by func- tionalization, interface minimization and by patterning, i.e. by selection among a predefined set of organizational configurations. This analysis lets us state how autonomy emerges from the integration of cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency. Emotion-based morphofunctional systems are able to exhibit complex adaptation patterns at a reduced cognitive cost. In this article we show a general model of how emotion supports functional adaptation and how the emotional biological systems operate following this theoretical model. We will also show how this model is also of applicability to the construction of a wide spectrum of artificial systems1.

Impact testing in melon (Cucumis melo L.)

The application of Rheology to study biological systems is a new and very extensive matter, in which melon is absolutely unknown. The goal of this work is to determine some physical characteristics of this fruit, immediately after harvest and during its conservation in cold storage. Portugal and Spain are the most interested countries in these studies, as they are important producers of melon. The varieties Branco da Leziria and Piel de sapo were chosen because they are the most popular in both countries. The fruit were studied on the day they were harvested, and then were conserved in cold storage in the "Instituto del Frio" in Madrid, and they were periodically tested again. Thus during seven days the same fruits, and new fruits, were picked up and tested. On the first day of testing we had 20 fruits to study and at the end of the testing period we had used 80 fruits. The results from the non-destructive impact test were very significant and they may contribute to standardise methods to measure fruit maturity. These results were confirmed by those obtained from compression tests. The results obtained during the Impact tests with melon were similar to those obtained previously with other fruits. There is a close relationship between the results of the Impact tests and Compression tests. Tests like Impact and Compression can be adapted to melon, varieties 'Piel de Sapo" and 'Branco de Leziria', allowing us to continue further work with this species. The great number of data obtained during performance of the tests allowed us to go on with this work and to contribute to standardise methods of measurement and expression of characteristics of a new biological product. During the "Impact damage in fruits and vegetables" workshop, held in Zaragoza in 1990, these matters were included in the priority list.

Rapid prototyping for biomedical engineering: current capabilities and Challenges

A new set of manufacturing technologies has emerged in the past decades to address market requirements in a customized way and to provide support for research tasks that require prototypes. These new techniques and technologies are usually referred to as rapid prototyping and manufacturing technologies, and they allow prototypes to be produced in a wide range of materials with remarkable precision in a couple of hours. Although they have been rapidly incorporated into product development methodologies, they are still under development, and their applications in bioengineering are continuously evolving. Rapid prototyping and manufacturing technologies can be of assistance in every stage of the development process of novel biodevices, to address various problems that can arise in the devices' interactions with biological systems and the fact that the design decisions must be tested carefully. This review focuses on the main fields of application for rapid prototyping in biomedical engineering and health sciences, as well as on the most remarkable challenges and research trends.