Spectroscopic Studies of Copper and Silver Binding to Metallothioneins

Mammalian metallothionein is remarkable in its metal binding properties: well-characterized species exist for metal to sulfur ratios of M7S20, M12S20, and M18S20, where M = Cd(ll), Zn(ll), Hg(ll), Ag(I), Au(I), and Cu(I). Circular dichroism and luminescence spectra provide rich details of a complicated metal binding chemistry when metals are added directly to the metal free- or zinc-containing protein. CD spectral data unambiguously identify key metal to protein stoichiometric ratios that result in well-defined structures. Emission spectra in the 450-750 nm region have been reported for metallothioneins containing Ag(I), Au(I), and Cu(I). The luminescence of Cu-MT can also be detected directly from mammalian and yeast cells. Qualitative and quantitative interpretations show that the final structure adopted by Ag-MT is not the same as that formed by Cu(I) ions in Cu-MT. XAFS structural data are reported for a number of metallothioneins, including Ag12-MT and Ag17-MT. Electrospray ionization mass spectrometry provides details on the species formed when Ag(I) binds to metallothionein. Mass spectral data are reported for metal-free MT 2A and Agn-MT (n = 14-18)

Alternative Defrost Strategies for Residential Heat Pumps

Heat pumps are an energy efficient way to provide adequate heating to an indoor space. In contrast to electric or gas heating, a heat pump works to draw the free heat from the cold outdoor ambient and transfer thermal energy to the heated space. When the outdoor ambient is cold and humidity conditions are right, however, frost will start to develop on the heat pump’s outdoor coil. Frost on the coil surface blocks air flow through the coil thus reducing the heat pump’s efficiency and overall performance. Control of frosting and defrosting is particularly important to the successful use of heat pumps in cold climates. To restore the unit’s heating capacity and efficiency, a defrost cycle is needed to remove the accumulated frost developed on the coil. While defrosting restores heat pump efficiency, this period of operation itself requires additional power and ultimately results in an energy penalty. Improving defrost performance and/or reducing the number and duration of required defrost periods would significantly improve heat pump operation. Heat pump researchers and manufacturers have spent a great amount of effort on the topic of defrosting. A comprehensive review of efforts within the last 15 years was conducted to summarize existing defrosting technologies and identify those solutions that may be more feasible or readily commercialized to reduce the defrost penalty. This summary highlights technologies that may reduce or eliminate the negative impacts of the defrosting period including approaches using hot gas bypass, coil coatings and advanced control strategies. The potential impact of the identified technologies is energy and demand savings, improved performance for comfort, and removal of a significant barrier to widespread adoption of air-source heat pumps in all climates

63^{63}Cu(I) binding to human kidney 68^{68}Zn7_7-βα MT1A: determination of Cu(I)-thiolate cluster domain specificity from ESI-MS and room temperature phosphorescence spectroscopy

Mammalian metallothioneins (MTs) are important proteins in Zn(II) and Cu(I) homeostasis with the Zn(II) and Cu(I) binding to the 20 cysteines in metal-thiolate clusters. Previous electrospray ionization (ESI) mass spectrometric (MS) analyses of Cu(I) binding to Zn$_7$-MT were complicated by significant overlap of the natural abundance isotopic patterns for Zn(II) and Cu(I) leading to impossibly ambiguous stoichiometries. In this paper, isotopically pure $^{63}$Cu(I) and $^{68}$Zn(II) allowed determination of the specific stoichiometries in the $^{68}$Zn,$^{63}$Cu-βα MT1A species formed following the stepwise addition of $^{63}$Cu(I) to $^{68}$Zn$_7$-βα MT1A. These species were characterized by ESI-MS and room temperature emission spectroscopy. The key species that form and their emission band centres are Zn$_5$Cu$_5$-βα MT1A (λ = 684 nm), Zn$_4$Cu$_6$-βα MT1A (λ = 750 nm), Zn$_3$Cu$_9$-βα MT1A (λ = 750 nm), Zn$_2$Cu$_{10}$-βα MT1A (λ = 750 nm), and Zn$_1$Cu$_{14}$-βα MT1A (λ = 634 nm). The specific domain stoichiometry of each species was determined by assessing the species forming following $^{63}$Cu(I) addition to the $^{68}$Zn$_3$-β MT1A and $^{68}$Zn$_4$-α MT1A domain fragments. The domain fragment emission suggests that Zn$_5$Cu$_5$-βα MT1A contains a Zn$_1$Cu$_5$-β cluster and the Zn$_4$Cu$_6$-βα MT1A, Zn$_3$Cu$_9$-βα MT1A, and Zn$_2$Cu$_{10}$-βα MT1A each contain a Cu$_6$-β cluster. The species forming with >10 mol. eq. of $^{63}$Cu(I) in βα-MT1A exhibit emission from the Cu$_6$-β cluster and an α domain cluster. This high emission intensity is seen at the end of the titrations of $^{68}$Zn$_7$-βα MT1A and the $^{68}$Zn$_4$-α MT1A domain fragment suggesting that the initial presence of the Zn(II) results in clustered Cu(I) binding in the α domain

Quasi Steady-State Modeling Approach for Low Computational Cost Design Optimization of Heat Exchangers for Phase Change Material (PCM) Thermal Batteries

Energy storage devices are key components to enable stable, more efficient, and controllable energy flow in systems. Furthermore, they are facilitators for maximizing the use of renewable primary energy sources, which often do not meet immediate supply-demand needs. Thermal batteries can be configured as tube and flat fin heat exchangers using water as working fluid inside the tubes and surrounded by a Phase-Change Material (PCM) on the external surface. These components typically require transient high-order modeling physics to simulate their behavior that are generally computationally intensive. This paper presents a low computational cost tool for design optimization of the heat exchangers for these batteries during discharge, i.e., solidification of the PCM. The approach consists of evaluating the heat transfer rate for an average PCM mass fraction of 50% and assuming a quasi-steady-state condition. The PCM thermal resistance is predicted using metamodels derived from validated CFD simulations. Using experimental data, the solver prediction matched the heat transfer rate during phase change from 2.3% to 22.9% for the same battery at different water inlet temperatures. The proposed solver is more than four orders of magnitude faster than the full transient model for a single design. This allows for using optimization such as Multi-Objective Genetic Algorithms (MOGA) to explore novel designs in only a few minutes. Finally, the optimization study suggested that for a particular battery, there is a trade-off where one may save more than 22% in material cost for the same performance or increase more than 6% in thermal performance for the same cost. Two distinct points in a Pareto front were selected and evaluated with the full transient model; the results provided good evidence that the proposed solver is sufficiently robust in predicting battery thermal performance and degradation

Acid secretion by the boring organ of the burrowing giant clam, Tridacna crocea

The giant clam Tridacna crocea, native to Indo-Pacific coral reefs, is noted for its unique ability to bore fully into coral rock and is a major agent of reef bioerosion. However, T. crocea\u27s mechanism of boring has remained a mystery despite decades of research. By exploiting a new, two-dimensional pH-sensing technology and manipulating clams to press their presumptive boring tissue (the pedal mantle) against pH-sensing foils, we show that this tissue lowers the pH of surfaces it contacts by greater than or equal to 2 pH units below seawater pH day and night. Acid secretion is likely mediated by vacuolar-type H+-ATPase, which we demonstrate (by immunofluorescence) is abundant in the pedal mantle outer epithelium. Our discovery of acid secretion solves this decades-old mystery and reveals that, during bioerosion, T. crocea can liberate reef constituents directly to the soluble phase, rather than producing sediment alone as earlier assumed

Can sacrificial feeding areas protect aquatic plants from herbivore grazing? Using behavioural ecology to inform wildlife management

Effective wildlife management is needed for conservation, economic and human well-being objectives. However, traditional population control methods are frequently ineffective, unpopular with stakeholders, may affect non-target species, and can be both expensive and impractical to implement. New methods which address these issues and offer effective wildlife management are required. We used an individual-based model to predict the efficacy of a sacrificial feeding area in preventing grazing damage by mute swans (Cygnus olor) to adjacent river vegetation of high conservation and economic value. The accuracy of model predictions was assessed by a comparison with observed field data, whilst prediction robustness was evaluated using a sensitivity analysis. We used repeated simulations to evaluate how the efficacy of the sacrificial feeding area was regulated by (i) food quantity, (ii) food quality, and (iii) the functional response of the forager. Our model gave accurate predictions of aquatic plant biomass, carrying capacity, swan mortality, swan foraging effort, and river use. Our model predicted that increased sacrificial feeding area food quantity and quality would prevent the depletion of aquatic plant biomass by swans. When the functional response for vegetation in the sacrificial feeding area was increased, the food quantity and quality in the sacrificial feeding area required to protect adjacent aquatic plants were reduced. Our study demonstrates how the insights of behavioural ecology can be used to inform wildlife management. The principles that underpin our model predictions are likely to be valid across a range of different resource-consumer interactions, emphasising the generality of our approach to the evaluation of strategies for resolving wildlife management problems

Solvent effects on the photochemical and fluorescence properties of zinc phthalocyanine derivatives

The effects of solvents on the singlet oxygen, photobleaching and fluorescence quantum yields for zinc phthalocyanine (ZnPc) and its derivatives; (pyridino)zinc phthalocyanine ((py)ZnPc), zinc octaphenoxyphthalocyanine (ZnOPPc) and zinc octaestronephthalocyanine (ZnOEPc), is presented. The effects of the solvents on the ground state spectra are also discussed. The largest red shift of the Q band was observed in aromatic solvents, the highest shift being observed for 1-chloronaphthalene. Higher singlet fluorescence quantum yields were observed in THF for ZnPc and ZnOPPC. Also in the same solvent phototransformation rather than photobleaching was observed for ZnOPPc. Split Q band in the emission and excitation spectra of ZnOPPc was observed in some solvents and this is explained in terms of the lowering of symmetry following excitation

Predicting how many animals will be where: how to build, calibrate and evaluate individual-based models

Individual-based models (IBMs) can simulate the actions of individual animals as they interact with one another and the landscape in which they live. When used in spatially-explicit landscapes IBMs can show how populations change over time in response to management actions. For instance, IBMs are being used to design strategies of conservation and of the exploitation of fisheries, and for assessing the effects on populations of major construction projects and of novel agricultural chemicals. In such real world contexts, it becomes especially important to build IBMs in a principled fashion, and to approach calibration and evaluation systematically. We argue that insights from physiological and behavioural ecology offer a recipe for building realistic models, and that Approximate Bayesian Computation (ABC) is a promising technique for the calibration and evaluation of IBMs. IBMs are constructed primarily from knowledge about individuals. In ecological applications the relevant knowledge is found in physiological and behavioural ecology, and we approach these from an evolutionary perspective by taking into account how physiological and behavioural processes contribute to life histories, and how those life histories evolve. Evolutionary life history theory shows that, other things being equal, organisms should grow to sexual maturity as fast as possible, and then reproduce as fast as possible, while minimising per capita death rate. Physiological and behavioural ecology are largely built on these principles together with the laws of conservation of matter and energy. To complete construction of an IBM information is also needed on the effects of competitors, conspecifics and food scarcity; the maximum rates of ingestion, growth and reproduction, and life-history parameters. Using this knowledge about physiological and behavioural processes provides a principled way to build IBMs, but model parameters vary between species and are often difficult to measure. A common solution is to manually compare model outputs with observations from real landscapes and so to obtain parameters which produce acceptable fits of model to data. However, this procedure can be convoluted and lead to over-calibrated and thus inflexible models. Many formal statistical techniques are unsuitable for use with IBMs, but we argue that ABC offers a potential way forward. It can be used to calibrate and compare complex stochastic models and to assess the uncertainty in their predictions. We describe methods used to implement ABC in an accessible way and illustrate them with examples and discussion of recent studies. Although much progress has been made, theoretical issues remain, and some of these are outlined and discussed