Comparison of environmental indicator sets using a unified indicator classification framework

Environmental indicator sets (EIS) are tools to monitor and assess sustainability, and many environmental organizations have embraced their use. Due to the large number of EIS, it is a challenge to compare and reconcile their differences and gain a comprehensive view of their utility. To compare EIS, the first step is to classify their component indicators, for which several frameworks exist. Among the most widely used, is the causal-chain framework, also referred to as PSR after its categories of Pressure, State and Response. Other frameworks classify indicators by subject, yet none is widely applied. Aiming to compare EIS, we first proposed a unified classification criteria for indicators using PSR and five subject categories (i.e., biodiversity and ecosystem health, E; natural resources, N; physical and chemical contamination, C; human environment, H; and general, G). Then, we used these classification criteria to describe and compare fourteen existing environmental indicator sets. Finally, we compared EIS based on their production characteristics and goals. Across the fourteen EIS, we analyzed 706 indicators (which represent ∼1200 variables) and selected 16 and 79 keywords for classification in the PSR and ENCHG categories respectively. We found on average that the ratio of categories in the causal chain framework was 2.5S:1.5P:1R, while we observed a large variability across EIS. For the subject categories, C-E-N were nearly equally represented among EIS, and better represented than H-G. Also, the evaluated EIS showed a polarization between C-H and E categories that we interpreted as a human vs. natural-ecosystem welfare focus. Finally, we identified three broad categories of EIS based primarily on the organization that produced them, non-governmental organizations, governmental organizations, and international organizations. Our results can contribute to the design and implementation of scientifically robust and representative EIS, which are key to incorporate environmental data to policymaking in the search of sustainability.     

When to use what: Methods for weighting and aggregating sustainability indicators

ContextSustainability indices (SIs) have become increasingly important to sustainability research and practice. However, while the validity of SIs is heavily dependent on how their components are weighted and aggregated, the typology and applicability of the existing weighting and aggregation methods remain poorly understood.ObjectivesTo close the knowledge gap regarding when to use which weighting and aggregation methods for constructing SIs, we review the most commonly used methods for weighting and aggregating SIs, discuss their benefits and drawbacks, and suggest a process-oriented approach for choosing appropriate weighting and aggregation methods depending on research objectives.MethodsOur review synthesis was based on peer-reviewed journal articles, books, and reports by international organizations, governmental agencies, and research institutions. After carefully examining their principles, characteristics, and applications, we selected and classified the frequently used methods for indicator weighting and aggregation.ResultsWe systematically discuss the benefits and drawbacks of nine weighting methods and three aggregation methods. We propose a four-step process for choosing the most suitable weighting and aggregation methods based on: research purposes, spatial and temporal scales, and sustainability perspectives.ConclusionsIn this research, we chose the most commonly used methods for weighting and aggregating SIs and analyzed the characteristics, strengths and weaknesses of each method. We found that choosing appropriate weighting and aggregation methods for a specific sustainability assessment project is an extremely important and challenging task. To meet this challenge, we propose a process-oriented approach for properly selecting methods according to the purpose, scale and sustainability concept. This approach can facilitate the proper selection of these methods in sustainability research and practice.     

Functional dual hydrophilic dendrimer‐modified metal‐organic framework for the selective enrichment of N‐glycopeptides

Analysis of protein glycosylation remains a significant challenge due to the low abundance of glycoproteins or N‐glycopeptides. Here we have synthesized an amino‐functionalized metal‐organic framework (MOF) MIL‐101(Cr)‐NH₂ whose surface is grafted with a hydrophilic dendrimer poly(amidoamine) (PAMAM) for N‐glycopeptide enrichment based on the hydrophilic interactions. The selected substrate MOF MIL‐101(Cr) owns high surface area which provides nice support for peptide adsorption. In addition, the MOF displayed a good hydrophilic property after being modified with amino groups. Most importantly, the grafted hydrophilic dendrimer PAMAM was firstly applied in the postsynthetic modification of MOFs. And this functionalization route using macromolecular dendrimer opens a new perspective in MOFs design. Owing to its long dendritic chains and abundant amino groups, our material displayed dual hydrophilic property. In the enrichment of standard glycoprotein HRP digestion, the functional MOF material was shown to have low detection limit (1 fmol/μL) and good selectivity when the concentration of nonglycopeptides was 100 fold higher than the target N‐glycopeptides. All the results proved that MIL‐101(Cr)‐NH₂@PAMAM has great potential in the glycoproteome analysis.     

Consensus and comprehensive linkage maps of bovine chromosome 7

The objective of this project was to integrate the currently available linkage maps for bovine chromosome 7 (BTA7) by combining data sets from eight research groups. A total of 54 unique markers were typed in eight pedigrees. Multilocus linkage analysis with CRI-MAP produced a bovine chromosome 7 consensus framework map of 27 loci ordered with odds greater than 1000:1. Furthermore, we present a bovine chromosome 7 comprehensive map integrating 54 loci. The locus order is in general agreement with the recently published linkage maps except for one discrepancy. The order of loci BM9289, BMS713, and ILSTS001 was reversed in the consensus framework map relative to the published USDA-MARC bovine chromosome 7 linkage map.     

GTP-dependent recognition of the methionine moiety on initiator tRNA by translation factor eIF2

Eukaryotic translation initiation factor 2 (eIF2) is a G-protein that functions as a central switch in the initiation of protein synthesis. In its GTP-bound state it delivers the methionyl initiator tRNA (Met-tRNA(i)) to the small ribosomal subunit and releases it upon GTP hydrolysis following the recognition of the initiation codon. We have developed a complete thermodynamic framework for the assembly of the Saccharomyces cerevisiae eIF2.GTP.Met-tRNA(i) ternary complex and have determined the effect of the conversion of GTP to GDP on eIF2's affinity for Met-tRNA(i) in solution. In its GTP-bound state the factor forms a positive interaction with the methionine moiety on Met-tRNA(i) that is disrupted when GTP is replaced with GDP, while contacts between the factor and the body of the tRNA remain intact. This positive interaction with the methionine residue on the tRNA may serve to ensure that only charged initiator tRNA enters the initiation pathway. The toggling on and off of the factor's interaction with the methionine residue is likely to play an important role in the mechanism of initiator tRNA release upon initiation codon recognition. In addition, we show that the conserved base-pair A1:U72, which is known to be a critical identity element distinguishing initiator from elongator methionyl tRNA, is required for recognition of the methionine moiety by eIF2. Our data suggest that a role of this base-pair is to orient the methionine moiety on the initiator tRNA in its recognition pocket on eIF2.     

Construction of a new porcine whole-genome framework map using a radiation hybrid panel

We have constructed a radiation hybrid (RH) map of the porcine genome using an RH panel generated by an irradiation dose of 5000-rad (Sus scrofa radiation hybrid map, SSRH map). Normal porcine aortic endothelial cells were irradiated and fused with a thymidine kinase-deficient mouse cell line, L-M (TK-). A total of 110 cell lines were selected and used for further analysis. Among 1091 microsatellite (MS) markers selected for mapping, 842 markers (77%) could be typed on the panel. The framework map comprised 342 MS markers and an additional 247 MS markers were then added to generate the whole-genome map. The average retention frequency for the data set was 30.6%. The total map length was 5596.2 centiRay (cR). Using an estimated physical length of 2718 Mbp, the average ratio between cR and physical distance over the porcine genome was estimated to be 0.49 Mb/cR.     

Utilization of the Streptoalloteichus hindustanus resistance determinant ShBle as a protein framework: effect of mutation upon ShBle dimerization and interaction of C-terminal displayed peptide epitopes

We have selected the Streptoalloteichus hindustanus bleomycin-resistance protein ShBle, a 28-kDa homodimer, as a scaffold for the display of bioactive peptides and other peptide epitopes. To create a monomeric scaffold, we investigated the effect of mutating residue proline 9 to glycine. This residue plays a critical role in ShBle dimerization by affecting the position of the eight N-terminal residues which secure the interaction between the monomeric subunits. We demonstrate that this mutation weakens the dimerization interaction, resulting in establishment of a stable equilibrium between monomeric and dimeric ShBle species in solution. Circular dichroism and SDS–PAGE data indicate that the Pro9Gly mutation does not disrupt the structure of the molecule. Production of a fully monomeric form of ShBle required complete removal of the eight-residue N-terminal peptide, and the interaction across the now solvent-exposed hydrophobic interface of the ShBle monomer was insufficient to drive dimerization. To demonstrate efficient display of epitope tags on the ShBle protein, we displayed dual-octapeptide FLAG tags at the protein C-terminus. These additions did not interfere with protein folding or activity. The resulting ShBle scaffold was used to compare the efficiency of two commercial FLAG-specific antibodies by biosensor.     

The Disturbed Resource-Flux Invasion Matrix: A New Framework for Patterns of Plant Invasion

Attempts to classify certain habitats as vulnerable to invasion or plant traits as invasive have met with limited success and applicability. Clearly, not all plant invaders are able to exploit all habitats and not all habitats are equally susceptible to invasion. Here we argue that it is critical for a successful model for invasions to incorporate both environmental and species traits and present just such a framework. Although disturbance has been targeted as a crucial event which renders habitats vulnerable to invasion, disturbances are often integral parts of ecosystems (e.g. floods, tree-falls, fire, etc.) and are not always associated with invasion events. We argue that disturbances that are associated with invasions alter historical patterns of turnover, or flux, of resources in an ecosystem. Given this perspective on the relationship between invasions and disturbances, and the need to integrate species traits with those of invaded ecosystems, we have developed an approach to characterize plant invasion patterns that we call the Disturbed Resource-Flux Invasion Matrix or DRIM. This is a 16-cell matrix that classifies habitats by the quality of changes in physical and chemical resource flux either increasing or decreasing flux relative to historical patterns. Within each matrix cell, it is then possible to apply basic ecological principles to target species traits that can facilitate successful invasion of habitats experiencing that particular kind of disturbance. We present examples from the literature of how habitats and species can be classified according to the DRIM, and demonstrate the application of this theoretical model.     

Enhanced Cathodic Oxygen Reduction and Power Production of Microbial Fuel Cell Based on Noble‐Metal‐Free Electrocatalyst Derived from Metal‐Organic Frameworks

Microbial fuel cell (MFC) can generate electricity from organic substances based on anodic electrochemically active microorganisms and cathodic oxygen reduction reaction (ORR), thus exhibiting promising potential for harvesting electric energy from organic wastewater. The ORR performance is crucial to both power production efficiency and overall cost of MFC. A new type of metal‐organic‐framework‐derived electrocatalysts containing cobalt and nitrogen‐doped carbon (CoNC) is developed, which is effective to enhance activity, selectivity, and stability toward four‐electron ORR in pH‐neutral electrolyte. When glucose is used as the substrate, the maximum power density of 1665 mW m^?2 is achieved for the optimized CoNC pyrolyzed at 900 °C, which is 39.8% higher than that of 1191 mW m^?2 for commercial Pt/C catalyst in the single‐chamber MFC. The improved performance of CoNC catalyst can be attributed to large surface area, microporous nature, and the involvement of nitrogen‐coordinated cobalt species. These properties enable the efficient ORR by increasing the active sites and enhancing mass transfer of oxygen and protons at “water‐flooding” three‐phase boundary where ORR occurs. This work provides a proof‐of‐concept demonstration of a noble‐metal‐free high‐efficiency and cost‐effective ORR electrocatalyst for effective recovery of electricity from biomass materials and organic wastewater in MFC.