Does a reduction in the price of rhino horn prevent poaching?

Rhino poaching around the world has increased inordinately, to the extent that concerns exist over the possible survival of the species. An open access rhino poaching model is developed for South African rhino. The model is a hybrid dynamical model, as both a system dynamics model as well as a Bayesian network model are developed. The system dynamics model is used to estimate the unknown parameter values (through optimisation) and also to determine the intervals for the parameters. These intervals are then used in the Bayesian Belief Network model to assess uncertainty. Hybrid approaches improve the ability to validate models compared with conventional modelling. The resultant model indicates that reducing the price of rhino horn would not be effective at curbing poaching, unless poacher costs are also increased. However, increasing poacher costs is not a realistic policy option since these costs are largely beyond the control of decision-makers. The insensitivity of price to poaching effort has implications for methods proposed to reduce the value of rhinos, such as introducing synthetic rhino horn and the de-horning of rhinos.     

GABAB receptors suppress burst-firing in reticular thalamic neurons

Burst-firing in thalamic neurons is known to play a key role in mediating thalamocortical (TC) oscillations that are associated with non-REM sleep and some types of epileptic seizure. Within the TC system the primary output of GABAergic neurons in the reticular thalamic nucleus (RTN) is thought to induce the de-inactivation of T-type calcium channels in thalamic relay (TR) neurons, promoting burst-firing drive to the cortex and the propagation of TC network activity. However, RTN neurons also project back onto other neurons within the RTN. The role of this putative negative feedback upon the RTN itself is less well understood, although is hypothesized to induce de-synchronization of RTN neuron firing leading to the suppression of TC oscillations. Here we tested two hypotheses concerning possible mechanisms underlying TC oscillation modulation. Firstly, we assessed the burst-firing behavior of RTN neurons in response to GABA_B receptor activation using acute brain slices. The selective GABA_B receptor agonist baclofen was found to induce suppression of burst-firing concurrent with effects on membrane input resistance. Secondly, RTN neurons express Ca_V3.2 and Ca_V3.3 T-type calcium channel isoforms known to contribute toward TC burst-firing and we examined the modulation of these channels by GABA_B receptor activation. Utilizing exogenously expressed T-type channels we assessed whether GABA_B receptor activation could directly alter T-type calcium channel properties. Overall, GABA_B receptor activation had only modest effects on Ca_V3.2 and Ca_V3.3 isoforms. The only effect that could be predicted to suppress burst-firing was a hyperpolarized shift in the voltage-dependence of inactivation, potentially causing lower channel availability at membrane potentials critical for burst-firing. Conversely, other effects observed such as a hyperpolarized shift in the voltage-dependence of activation of both Ca_V3.2 and Ca_V3.3 as well as increased time constant of activation of the Ca_V3.3 isoform would be expected to enhance burst-firing. Together, we hypothesize that GABA_B receptor activation mediates multiple downstream effectors that combined act to suppress burst-firing within the RTN. It appears unlikely that direct GABA_B receptor-mediated modulation of T-type calcium channels is the major mechanistic contributor to this suppression.     

Systems pharmacology and enhanced pharmacodynamic models for understanding antibody-based drug action and toxicity

Pharmacokinetic (PK) and pharmacodynamic (PD) models seek to describe the temporal pattern of drug exposures and their associated pharmacological effects produced at micro- and macro-scales of organization. Antibody-based drugs have been developed for a large variety of diseases, with effects exhibited through a comprehensive range of mechanisms of action. Mechanism-based PK/PD and systems pharmacology models can play a major role in elucidating and integrating complex antibody pharmacological properties, such as nonlinear disposition and dynamical intracellular signaling pathways triggered by ligation to their cognate targets. Such complexities can be addressed through the use of robust computational modeling techniques that have proven powerful tools for pragmatic characterization of experimental data and for theoretical exploration of antibody efficacy and adverse effects. The primary objectives of such multi-scale mathematical models are to generate and test competing hypotheses and to predict clinical outcomes. In this review, relevant systems pharmacology and enhanced PD (ePD) models that are used as predictive tools for antibody-based drug action are reported. Their common conceptual features are highlighted, along with approaches used for modeling preclinical and clinically available data. Key examples illustrate how systems pharmacology and ePD models codify the interplay among complex biology, drug concentrations, and pharmacological effects. New hybrid modeling concepts that bridge cutting-edge systems pharmacology models with established PK/ePD models will be needed to anticipate antibody effects on disease in subpopulations and individual patients.     

Understanding the Organization of Industrial Ecosystems

Industrial symbiosis (IS) has been used to describe the physical exchange and shared management of input and output materials by geographically proximate firms. Firms that engage in IS are said to belong to an industrial ecosystem. Symbiosis has been found to be motivated by economic considerations, such as lowering costs for waste disposal, as well as by environmental ones, such as accessing limited water supplies. Communication and trust among managers are thought to play important roles in exchanges; however, empirical studies have not been previously conducted. This study used social network analysis (SNA) to identify the prevalence of industrial symbiosis linkages in Barceloneta, Puerto Rico. The study quantified patterns in various relationships among firms and managers, including formal relations through supply chains, and informal ones through interpersonal interactions. SNA and statistical methods were used to explore how these ties correlate with observed industrial symbiosis activities. IS linkages were found to be less prevalent than product sales among firms and were concentrated among pharmaceutical firms at the core of the regional network. Trust among managers and position in the social hierarchy were found to be correlated with IS but not supply chain links. SNA was useful for examining the organization of different relationships in the industrial ecosystem, but contextual information is still needed to add meaning to its findings.     

Improved sequence-based prediction of protein secondary structures by combining vacuum-ultraviolet circular dichroism spectroscopy with neural network

Synchrotron-radiation vacuum-ultraviolet circular dichroism (VUVCD) spectroscopy can significantly improve the predictive accuracy of the contents and segment numbers of protein secondary structures by extending the short-wavelength limit of the spectra. In the present study, we combined VUVCD spectra down to 160 nm with neural-network (NN) method to improve the sequence-based prediction of protein secondary structures. The secondary structures of 30 target proteins (test set) were assigned into alpha-helices, beta-strands, and others by the DSSP program based on their X-ray crystal structures. Combining the alpha-helix and beta-strand contents estimated from the VUVCD spectra of the target proteins improved the overall sequence-based predictive accuracy Q(3) for three secondary-structure components from 59.5 to 60.7%. Incorporating the position-specific scoring matrix in the NN method improved the predictive accuracy from 70.9 to 72.1% when combining the secondary-structure contents, to 72.5% when combining the numbers of segments, and finally to 74.9% when filtering the VUVCD data. Improvement in the sequence-based prediction of secondary structures was also apparent in two other indices of the overall performance: the correlation coefficient (C) and the segment overlap value (SOV). These results suggest that VUVCD data could enhance the predictive accuracy to over 80% when combined with the currently best sequence-prediction algorithms, greatly expanding the applicability of VUVCD spectroscopy to protein structural biology.     

The solitary (primary) cilium--a mechanosensory toggle switch in bone and cartilage cells

Osteocytes and articular chondrocytes sense and respond to the strains imposed on bones and joints by various activities such as breathing and walking. This mechanoresponsiveness is needed to maintain bone and cartilage microstructure and strength. In bone the large number of osteocytes form a vast osteointernet in which the gap junctionally interconnected members are lodged in an extensive lacunocanalicular network. The much smaller number of articular chondrocytes are not interconnected in a chondrointernet. Instead, they are separately lodged in capsules called chondrons. While there are many possible strain-sensing devices, it now appears that the non-motile solitary (primary) cilia protruding like aerials from osteocytes (as well as osteoblasts) and chondrocytes are switches that when toggled by cyclical pulses of lacunocanalicular fluid or cartilage compression send signals such as Ca²⁺ surges into the cell to trigger a cascade of events that include appropriate gene activations to maintain and strengthen bone and cartilage. Moreover, the chondrocyte cilium with its Ihh(Indian hedgehog)-activated Smo receptor is a key player along with PTHrP in endochondral bone formation.     

Success and its limits among structural models of complex food webs

1. Following the development of the relatively successful niche model, several other simple structural food web models have been proposed. These models predict the detailed structure of complex food webs given only two input parameters, the numbers of species and the number of feeding links among them. 2. The models claim different degrees of success but have not been compared consistently with each other or with the empirical data. We compared the performance of five structural models rigorously against 10 empirical food webs from a variety of aquatic and terrestrial habitats containing 25-92 species and 68-997 links. 3. All models include near-hierarchical ordering of species' consumption and have identical distributions of the number of prey of each consumer species, but differ in the extent to which species' diets are required to be contiguous and the rules used to assign feeding links. 4. The models perform similarly on a range of food-web properties, including the fraction of top, intermediate and basal species, the standard deviations of generality and connectivity and the fraction of herbivores and omnivores. 5. For other properties, including the standard deviation of vulnerability, the fraction of cannibals and species in loops, mean trophic level, path length, clustering coefficient, maximum similarity and diet discontinuity, there are significant differences in the performance of the different models. 6. While the empirical data do not support the niche model's assumption of diet contiguity, models which relax this assumption all have worse overall performance than the niche model. All the models under-estimate severely the fraction of species that are herbivores and exhibit other important failures that need to be addressed in future research.     

基于贝叶斯网络的DNA序列剪接位点预测

采用基于贝叶斯网络的建模方法,预测真核生物DNA序列中的剪接位点．分别建立了供体位点和受体位点模型,并根据两种位点的生物学特性,对模型的拓扑结构和上下游节点的选择进行了优化．通过贝叶斯网络的最大似然学习算法求出模型参数后,利用10分组交互验证方法对测试数据进行剪接位点预测。结果显示,受体位点的平均预测准确率为92．5％,伪受体位点的平均预测准确率为94．0％,供体位点的平均预测准确率为92．3％,伪供体位点的平均预测准确率为93．5％,整体效果要好于基于使用独立和条件概率矩阵、以及隐Markov模型的预测方法．表明利用贝叶斯网络对剪接位点建模是预测剪接位点的一种有效手段．