A generalized response surface model with varying relative potency for assessing drug interaction

When multiple drugs are administered simultaneously, investigators are often interested in assessing whether the drug combinations are synergistic, additive, or antagonistic. Based on the Loewe additivity reference model, many existing response surface models require constant relative potency and some of them use a single parameter to capture synergy, additivity, or antagonism. However, the assumption of constant relative potency is too restrictive, and these models using a single parameter to capture drug interaction are inadequate to describe the phenomenon when synergy, additivity, and antagonism are interspersed in different regions of drug combinations. We propose a generalized response surface model with a function of doses instead of one single parameter to identify and quantify departure from additivity. The proposed model can incorporate varying relative potencies among multiple drugs as well. Examples and simulations are given to demonstrate that the proposed model is effective in capturing different patterns of drug interaction.     

Industrial Waste Reuse and By‐product Synergy Optimization

By‐product synergy is a growing practice worldwide. It consists in the maximization of resources utilization with the replacement of raw materials by by‐products as inputs for industrial processes. In order to support decision making in such strategic projects, appropriate tools must be developed. This article presents the results of a research project, which includes the development of a multiobjective mathematical programming model for the optimization of by‐product flows, synergy configurations, and investment decisions in eco‐industrial networks. This model is evaluated using data related to the Kalundborg industrial symbiosis (IS) in order to illustrate its utilization, as well as to assess, in a retrospective manner, the behavior of the companies involved with respect to both economic and environmental benefits of synergies. The experiments also illustrate the influence of the municipality on synergy implementation and how a scenario‐based approach can be used to anticipate raw material price increase. The results are generally coherent with the actual timing of synergy initializations. Further, the considerable effect of water price on the length of investments’ payback period illustrates the impact of policies and regulations on IS.     

Dynamic Modeling of In‐Use Cement Stocks in the United States

A dynamic substance‐flow model is developed to characterize the stocks and flows of cement utilized during the 20th century in the United States, using the generic cement life cycle as a systems boundary. The motivation for estimating historical inventories of cement stocks and flows is to provide accurate estimates of contemporary cement in‐use stocks in U.S. infrastructure and future discards to relevant stakeholders in U.S. infrastructure, such as the federal and state highway administrators, departments of transportation, public and private utilities, and the construction and cement industries. Such information will assist in planning future rehabilitation projects and better life cycle management of infrastructure systems. In the present policy environment of climate negotiations, estimates of in‐use cement infrastructure can provide insights about to what extent built environment can act as a carbon sink over its lifetime. The rate of addition of new stock, its composition, and the repair of existing stock are key determinants of infrastructure sustainability. Based upon a probability of failure approach, a dynamic stock and flow model was developed utilizing three statistical lifetime distributions—Weibull, gamma, and lognormal—for each cement end‐use. The model‐derived estimate of the “in‐use” cement stocks in the United States is in the range of 4.2 to 4.4 billion metric tons (gigatonnes, Gt). This indicates that 82% to 87% of cement utilized during the last century is still in use. On a per capita basis, this is equivalent to 14.3 to 15.0 tonnes of in‐use cement stock per person. The in‐use cement stock per capita has doubled over the last 50 years, although the rate of growth has slowed.     

A Probabilistic Dynamic Material Flow Analysis Model for Chinese Urban Housing Stock

The stock‐driven dynamic material flow analysis (MFA) model is one of the prevalent tools to investigate the evolution and related material metabolism of the building stock. There exists substantial uncertainty inherent to input parameters of the stock‐driven dynamic building stock MFA model, which has not been comprehensively evaluated yet. In this study, a probabilistic, stock‐driven dynamic MFA model is established and China's urban housing stock is selected as the empirical case. This probabilistic dynamic MFA model has the ability to depict the future evolution pathway of China's housing stock and capture uncertainties in its material stock, inflow, and outflow. By means of probabilistic methods, a detailed and transparent estimation of China's housing stock and its material metabolism behavior is presented. Under a scenario with a saturation level of the population, urbanization, and living space, the median value of the urban housing stock area, newly completed area, and demolished area would peak at around 49, 2.2, and 2.2 billion square meters, respectively. The corresponding material stock and flows are 79, 3.5, and 3.3 billion tonnes, respectively. Uncertainties regarding housing stock and its material stock and flows are non‐negligible. Relative uncertainties of the material stock and flows are above 50%. The uncertainty importance analysis demonstrates that the material intensity and the total population are major contributions to the uncertainty. Policy makers in the housing sector should consider the material efficiency as an essential policy to mitigate material flows of the urban building stock and to lower the risk of policy failures.     

Improving the efficiency of a hospital emergency department: a simulation study with indirectly imputed service-time distributions

This paper presents a case study which uses simulation to analyze patient flows in a hospital emergency department in Hong Kong. We first analyze the impact of the enhancements made to the system after the relocation of the Emergency Department. After that, we developed a simulation model (using ARENA) to capture all the key relevant processes of the department. When developing the simulation model, we faced the challenge that the data kept by the Emergency Department were incomplete so that the service-time distributions were not directly obtainable. We propose a simulation–optimization approach (integrating simulation with meta-heuristics) to obtain a good set of estimate of input parameters of our simulation model. Using the simulation model, we evaluated the impact of possible changes to the system by running different scenarios. This provides a tool for the operations manager in the Emergency Department to “foresee” the impact on the daily operations when making possible changes (such as, adjusting staffing levels or shift times), and consequently make much better decisions.     

Large-amplitude,short-wave peristalsis and its implications for transport

Valveless, tubular pumps are widespread in the animal kingdom, but the mechanism by which these pumps generate fluid flow is often in dispute. Where the pumping mechanism of many organs was once described as peristalsis, other mechanisms, such as dynamic suction pumping, have been suggested as possible alternative mechanisms. Peristalsis is often evaluated using criteria established in a technical definition for mechanical pumps, but this definition is based on a small-amplitude, long-wave approximation which biological pumps often violate. In this study, we use a direct numerical simulation of large-amplitude, short-wave peristalsis to investigate the relationships between fluid flow, compression frequency, compression wave speed, and tube occlusion. We also explore how the flows produced differ from the criteria outlined in the technical definition of peristalsis. We find that many of the technical criteria are violated by our model: Fluid flow speeds produced by peristalsis are greater than the speeds of the compression wave; fluid flow is pulsatile; and flow speed have a nonlinear relationship with compression frequency when compression wave speed is held constant. We suggest that the technical definition is inappropriate for evaluating peristalsis as a pumping mechanism for biological pumps because they too frequently violate the assumptions inherent in these criteria. Instead, we recommend that a simpler, more inclusive definition be used for assessing peristalsis as a pumping mechanism based on the presence of non-stationary compression sites that propagate unidirectionally along a tube without the need for a structurally fixed flow direction.     

Systematic exploration of synergistic drug pairs

Drug synergy allows a therapeutic effect to be achieved with lower doses of component drugs. Drug synergy can result when drugs target the products of genes that act in parallel pathways (‘specific synergy’). Such cases of drug synergy should tend to correspond to synergistic genetic interaction between the corresponding target genes. Alternatively, ‘promiscuous synergy’ can arise when one drug non‐specifically increases the effects of many other drugs, for example, by increased bioavailability. To assess the relative abundance of these drug synergy types, we examined 200 pairs of antifungal drugs in S. cerevisiae. We found 38 antifungal synergies, 37 of which were novel. While 14 cases of drug synergy corresponded to genetic interaction, 92% of the synergies we discovered involved only six frequently synergistic drugs. Although promiscuity of four drugs can be explained under the bioavailability model, the promiscuity of Tacrolimus and Pentamidine was completely unexpected. While many drug synergies correspond to genetic interactions, the majority of drug synergies appear to result from non‐specific promiscuous synergy.     

Contributions of phase resetting and interlimb coordination to the adaptive control of hindlimb obstacle avoidance during locomotion in rats: a simulation study

Obstacle avoidance during locomotion is essential for safe, smooth locomotion. Physiological studies regarding muscle synergy have shown that the combination of a small number of basic patterns produces the large part of muscle activities during locomotion and the addition of another pattern explains muscle activities for obstacle avoidance. Furthermore, central pattern generators in the spinal cord are thought to manage the timing to produce such basic patterns. In the present study, we investigated sensory-motor coordination for obstacle avoidance by the hindlimbs of the rat using a neuromusculoskeletal model. We constructed the musculoskeletal part of the model based on empirical anatomical data of the rat and the nervous system model based on the aforementioned physiological findings of central pattern generators and muscle synergy. To verify the dynamic simulation by the constructed model, we compared the simulation results with kinematic and electromyographic data measured during actual locomotion in rats. In addition, we incorporated sensory regulation models based on physiological evidence of phase resetting and interlimb coordination and examined their functional roles in stepping over an obstacle during locomotion. Our results show that the phase regulation based on interlimb coordination contributes to stepping over a higher obstacle and that based on phase resetting contributes to quick recovery after stepping over the obstacle. These results suggest the importance of sensory regulation in generating successful obstacle avoidance during locomotion.     

Dynamic modelling of prosthetic chorded mitral valves using the immersed boundary method

Current artificial heart valves either have limited lifespan or require the recipient to be on permanent anticoagulation therapy. In this paper, effort is made to assess a newly developed bileaflet valve prosthesis made of synthetic flexible leaflet materials, whose geometry and material properties are based on those of the native mitral valve, with a view to providing superior options for mitral valve replacement. Computational analysis is employed to evaluate the geometric and material design of the valve, by investigation of its mechanical behaviour and unsteady flow characteristics. The immersed boundary (IB) method is used for the dynamic modelling of the large deformation of the valve leaflets and the fluid-structure interactions. The IB simulation is first validated for the aortic prosthesis subjected to a hydrostatic loading. The predicted displacement fields by IB are compared with those obtained using ANSYS, as well as with experimental measurements. Good quantitative agreement is obtained. Moreover, known failure regions of aortic prostheses are identified. The dynamic behaviour of the valve designs is then simulated under four physiological pulsatile flows. Experimental pressure gradients for opening and closure of the valves are in good agreement with IB predictions for all flow rates for both aortic and mitral designs. Importantly, the simulations predicted improved physiological haemodynamics for the novel mitral design. Limitation of the current IB model is also discussed. We conclude that the IB model can be developed to be an extremely effective dynamic simulation tool to aid prosthesis design.     

Quantifying Synergy: A Systematic Review of Mixture Toxicity Studies within Environmental Toxicology

Cocktail effects and synergistic interactions of chemicals in mixtures are an area of great concern to both the public and regulatory authorities. The main concern is whether some chemicals can enhance the effect of other chemicals, so that they jointly exert a larger effect than predicted. This phenomenon is called synergy. Here we present a review of the scientific literature on three main groups of environmentally relevant chemical toxicants: pesticides, metal ions and antifouling compounds. The aim of the review is to determine 1) the frequency of synergy, 2) the extent of synergy, 3) whether any particular groups or classes of chemicals tend to induce synergy, and 4) which physiological mechanisms might be responsible for this synergy. Synergy is here defined as mixtures with minimum two-fold difference between observed and predicted effect concentrations using Concentration Addition (CA) as a reference model and including both lethal and sub-lethal endpoints. The results showed that synergy occurred in 7%, 3% and 26% of the 194, 21 and 136 binary pesticide, metal and antifoulants mixtures included in the data compilation on frequency. The difference between observed and predicted effect concentrations was rarely more than 10-fold. For pesticides, synergistic mixtures included cholinesterase inhibitors or azole fungicides in 95% of 69 described cases. Both groups of pesticides are known to interfere with metabolic degradation of other xenobiotics. For the four synergistic metal and 47 synergistic antifoulant mixtures the pattern in terms of chemical groups inducing synergy was less clear. Hypotheses in terms of mechanisms governing these interactions are discussed. It was concluded that true synergistic interactions between chemicals are rare and often occur at high concentrations. Addressing the cumulative rather than synergistic effect of co-occurring chemicals, using standard models as CA, is therefore regarded as the most important step in the risk assessment of chemical cocktails.     

The effect of high intensity mixing on the enzymatic hydrolysis of concentrated cellulose fiber suspensions

Enzymatic hydrolysis of lignocellulosic biomass in a high shear environment was examined. The conversion of cellulose to glucose in samples mixed in a torque rheometer producing shear flows similar to those found in twin screw extruders was greater than that of unmixed samples. In addition, there is a synergistic effect of mixing and enzymatic hydrolysis; mixing increases the rate of cellulose conversion while the increased conversion facilitates mixing. The synergy appears to result in part from particle size reduction, which is more significant when hydrolysis occurs during intense mixing.     

Synergistic activation of RSK correlates with c-fos induction in MO7e cells stimulated with GM-CSF plus Steel factor

Steel factor (SLF) plus GM-CSF induces proliferative synergy in factor-dependent cell line MO7e and hematopoietic progenitor cells. We previously reported ERK1/2 involvement in this synergy, but its downstream signaling molecules are not defined. Here, we investigated activation of the 90-kDa ribosomal S6 kinase (RSK) proteins by measuring the phosphorylation status and in vitro kinase activity in MO7e cells. Both GM-CSF and SLF induced activation of RSK, and the combined stimulation with these two cytokines induced synergistic and persistent activation of RSK. RSK activity was reduced by PI3 kinase inhibitor LY294002 or MEK1 inhibitor PD98059, suggesting that the ERK as well as the PI3 kinase pathways are involved in regulation of RSK activity. Sensitivities of RSK activity to inhibitory drugs correlated well with those of c-fos gene induction. Taken together, synergistic activation of RSK may contribute, at least in part, to the synergistic induction of c-fos after combined stimulation with GM-CSF plus SLF.     

A Visco-hyperelastic Model With Damage for the Knee Ligaments Under Dynamic Constraints

The aim of this study was to identify the behaviour laws governing the knee ligaments, accounting for the damage incurred by the structure under dynamic constraints. The model is developed using a thermodynamic formulation based on the coupling between a viscoelastic model and a damage model. Identification is carried out using the results of dynamic traction tests performed on a bone ligament/bone complex to which traction velocities of around 1.98 m/s were applied. The results show the ability of the model to account for the brittle and ductile failure processes occurring in the cruciate and lateral ligaments, respectively.     

Wall Street's assessment of plastic surgery--related technology: a clinical and financial analysis

Many plastic surgeons develop technologies that are manufactured by Wall Street-financed companies. Others participate in the stock market as investors. This study examines the bioengineered skin industry to determine whether it integrates clinical and financial information as Wall Street tenets would predict, and to see whether the financial performance of these companies provides any lessons for practicing plastic surgeons. In efficient markets, the assumptions on which independent financial analysts base their company sales and earnings projections are clinically reasonable, the volatility of a company's stock price does not irrationally differ from that of its industry sector, and the buy/sell recommendations of analysts are roughly congruent. For the companies in this study, these key financial parameters were compared with a benchmark index of 69 biotech companies of similar age and annual revenues (Student's t test). Five bioengineered skin companies were included in the study. Analysts estimated that each company would sell its product to between 24 and 45 percent of its target clinical population. The average stock price volatility was significantly higher for study companies than for those in the benchmark index (p < 0.05). Similarly, buy/sell recommendations of analysts for the study companies were significantly less congruent than those for the benchmark companies (p < 0.05). These results indicate clinically unrealistic projections for market penetration, significantly high price volatility, and significantly high discordance among professional analysts. In all cases, the market is inefficient-an unusual finding on Wall Street. A likely explanation for this market failure is a cycle of poor clinical correlation when assigning sales projections, which in turn leads to price volatility and discordance of buy/sell recommendations. This study's findings have implications for plastic surgeons who develop new technology or who participate in the equities markets as investors. Plastic surgeons who develop new medical devices or technology cannot universally depend on the market to drive clinically reasonable financial performance. Although inflated sales estimates have benefits in the short term, failure to meet projections exacts severe financial penalties. Plastic surgeons who invest in the stock market, because of their unique clinical experience, may sometimes be in the position to evaluate new technologies and companies better than Wall Street experts. Well-timed trades that use this expertise can result in opportunities for profit.     

Energy simulation and LCA for macro-scale analysis of eco-innovations in the housing stock

Purpose

Energy consumption of buildings is one of the major drivers of environmental impacts. Life cycle assessment (LCA) may support the assessment of burdens and benefits associated to eco-innovations aiming at reducing these environmental impacts. Energy efficiency policies however typically focus on the meso- or macro-scale, while interventions are typically taken at the micro-scale. This paper presents an approach that bridges this gap by using the results of energy simulations and LCA studies at the building level to estimate the effect of micro-scale eco-innovations on the macro-scale, i.e. the housing stock in Europe.

Methods

LCA and dynamic energy simulations are integrated to accurately assess the life cycle environmental burdens and benefits of eco-innovation measures at the building level. This allows quantitatively assessing the effectiveness of these measures to lower the energy use and environmental impact of buildings. The analysis at this micro-scale focuses on 24 representative residential buildings within the EU. For the upscaling to the EU housing stock, a hybrid approach is used. The results of the micro-scale analysis are upscaled to the EU housing stock scale by adopting the eco-innovation measures to (part of) the EU building stock (bottom–up approach) and extrapolating the relative impact reduction obtained for the reference buildings to the baseline stock model. The reference buildings in the baseline stock model have been developed by European Commission-Joint Research Centre based on a statistical analysis (top–down approach) of the European housing stock. The method is used to evaluate five scenarios covering various aspects: building components (building envelope insulation), technical installations (renewable energy), user behaviour (night setback of the setpoint temperature), and a combined scenario.

Results and discussion

Results show that the proposed combination of bottom–up and top–down approaches allow accurately assessing the impact of eco-innovation measures at the macro-scale. The results indicate that a combination of policy measures is necessary to lower the environmental impacts of the building stock to a significative extent.

Conclusions

Interventions addressing energy efficiency at building level may lead to the need of a trade-off between resource efficiency and environmental impacts. LCA integrated with dynamic energy simulation may help unveiling the potential improvements and burdens associated to eco-innovations.

     

Maintenance and Expansion: Modeling Material Stocks and Flows for Residential Buildings and Transportation Networks in the EU25

Material stocks are an important part of the social metabolism. Owing to long service lifetimes of stocks, they not only shape resource flows during construction, but also during use, maintenance, and at the end of their useful lifetime. This makes them an important topic for sustainable development. In this work, a model of stocks and flows for nonmetallic minerals in residential buildings, roads, and railways in the EU25, from 2004 to 2009 is presented. The changing material composition of the stock is modeled using a typology of 72 residential buildings, four road and two railway types, throughout the EU25. This allows for estimating the amounts of materials in in‐use stocks of residential buildings and transportation networks, as well as input and output flows. We compare the magnitude of material demands for expansion versus those for maintenance of existing stock. Then, recycling potentials are quantitatively explored by comparing the magnitude of estimated input, waste, and recycling flows from 2004 to 2009 and in a business‐as‐usual scenario for 2020. Thereby, we assess the potential impacts of the European Waste Framework Directive, which strives for a significant increase in recycling. We find that in the EU25, consisting of highly industrialized countries, a large share of material inputs are directed at maintaining existing stocks. Proper management of existing transportation networks and residential buildings is therefore crucial for the future size of flows of nonmetallic minerals.     

海洋甲壳类生物资源评估方法研究进展

目前甲壳类生物资源,如蟹、龙虾、对虾及南极磷虾等组成了全球庞大且极具商业价值的渔业.虽然这些渔业的重要性逐步提升,规模也在扩大,但相对于其他渔业,适合且有效的海洋甲壳类资源评估与管理方法仍需进一步发展.本文回顾和评价了各种用于甲壳类生物资源评估的方法与模型,对剩余产量模型、时滞差分模型、损耗模型及体长结构模型等应用到甲壳类生物资源评估的4种主要模型进行了归纳和分析,简要地总结了这几种模型在应用时所需要的假设前提以及对所需数据的要求等,并对比分析了几种模型的优、缺点.此外,本文还列举了关于资源评估方法中模型的假设要求.参数的估算方法、不确定性来源及一般性解决办法等.最后,本文对甲壳类资源评估方法的发展方向和前景进行了展望.     

Evaluation of Modeling Approaches to Determine End‐of‐Life Flows Associated with Buildings: A Viennese Case Study on Wood and Contaminants

Dynamic material flow analysis enables the forecasting of secondary raw material potential for waste volumes in future periods, by assessing past, present, and future stocks and flows of materials in the anthroposphere. Analyses of waste streams of buildings stocks are uncertain with respect to data and model structure. Wood construction in Viennese buildings serve as a case study to compare different modeling approaches for determining end‐of‐life (EoL) wood and corresponding contaminant flows (lead, chlorine, and polycyclic aromatic hydrocarbons). A delayed input and a leaching stock modeling approach are used to determine wood stocks and flows from 1950 until 2100. Cross‐checking with independent estimates and sensitivity analyses are used to evaluate the results’ plausibility. In the situation of the given data in the present case study, the delay approach is a better choice for historical observations of EoL wood and for analyses at a substance level. It has some major drawbacks for future predictions at the goods level, though, as the durability of a large number of historical buildings with considerably higher wood content is not reflected in the model. The wood content parameter differs strongly for the building periods and has therefore the highest influence on the results. Based on this knowledge, general recommendations can be derived for analyses on waste flows of buildings at a goods and substance level.     

An optimization model for automated selection of economic and ecologic delivery profiles in area forwarding based inbound logistics networks

Area Forwarding Based Inbound Logistics Networks are used by several large companies whose suppliers are spread widely to reduce costs by consolidating transported goods in an early stage of the transport. Managing material flows in those networks is a complex task, especially if the synergy effects in the main leg shall be used to reduce costs and environmental pollution. One technique to decrease steering overhead is the use of delivery profiles, which provide a fixed delivery frequency for each supplier and ease planning for supply chain partners. The selection of a delivery profile has effects on both economic and ecologic outcome of the transportation system and thus should be done carefully. In this work we present a new mixed integer programming model which is able to simultaneously deal with the complex tariff systems used in area forwarding and delivery profile selection in acceptable computing time. Our solution methodology exploits problem specific structure to decompose the model into several parts. On the basis of an industrial case study we evaluate the planning solutions obtained by our model compared to the plans currently implemented in practise. Results are analysed both in terms of monetary savings as well as optimisation runtime.