A thermodynamic approach for assessing agroecosystem sustainability

By revisiting theoretical concepts in biogeography and the importance of thermodynamic laws in biosphere-atmosphere interactions, ecological sustainability in agricultural systems may be better defined. In this case study, we employed a multidisciplinary methodology for exploring agroecosystem sustainability by using eddy covariance (EC) data to compute thermodynamic entropy production (σ) and relate it to water, energy and carbon cycling in croplands and grasslands of the Central US. From 2002 to 2012, the biophysical metric of σ was compared across AmeriFlux sites, each with site-specific land management practices of irrigation, crop rotation, and tillage. Results show that σ is most correlated with net ecosystem exchange (NEE) of carbon, and when cropland and grassland sites are close to being carbon neutral, σ values range from 0.51–1.0 W K⁻¹ m⁻² for grasslands, 0.81–1.0 W K⁻¹ m⁻² for rainfed croplands, and 0.81–1.1 W K⁻¹ m⁻² for irrigated croplands. Irrigated maize stressed by hydrologic and high temperature anomalies associated with the 2012 drought exhibit the greatest increase in σ, indicating the possibility of decreased sustainability compared to rainfed croplands and grasslands. These results suggest that maximizing carbon uptake with irrigation and fertilizer use tends to move agroecosystems further away from thermodynamic equilibrium, which has implications for ecological sustainability and greenhouse gas (GHG) mitigation in climate-smart agriculture. The underlying theoretical concepts, multidisciplinary methodology, and use of eddy covariance data for biophysical indicators in this study contribute to a unique understanding of ecological sustainability in agricultural systems.     

A graph theoretical approach for assessing bio-macromolecular complex structural stability

Fast and proper assessment of bio macro-molecular complex structural rigidity as a measure of structural stability can be useful in systematic studies to predict molecular function, and can also enable the design of rapid scoring functions to rank automatically generated bio-molecular complexes. Based on the graph theoretical approach of Jacobs et al. [Jacobs DJ, Rader AJ, Kuhn LA, Thorpe MF (2001) Protein flexibility predictions using graph theory. Proteins: Struct Funct Genet 44:150–165] for expressing molecular flexibility, we propose a new scheme to analyze the structural stability of bio-molecular complexes. This analysis is performed in terms of the identification in interacting subunits of clusters of flappy amino acids (those constituting regions of potential internal motion) that undergo an increase in rigidity at complex formation. Gains in structural rigidity of the interacting subunits upon bio-molecular complex formation can be evaluated by expansion of the network of intra-molecular inter-atomic interactions to include inter-molecular inter-atomic interaction terms. We propose two indices for quantifying this change: one local, which can express localized (at the amino acid level) structural rigidity, the other global to express overall structural stability for the complex. The new system is validated with a series of protein complex structures reported in the protein data bank. Finally, the indices are used as scoring coefficients to rank automatically generated protein complex decoys.     

Toxicogenomic approach for assessing toxicant-related disease

The problems of identifying environmental factors involved in the etiology of human disease and performing safety and risk assessments of drugs and chemicals have long been formidable issues. Three principal components for predicting potential human health risks are: (1) the diverse structure and properties of thousands of chemicals and other stressors in the environment; (2) the time and dose parameters that define the relationship between exposure and disease; and (3) the genetic diversity of organisms used as surrogates to determine adverse chemical effects. The global techniques evolving from successful genomics efforts are providing new exciting tools with which to address these intractable problems of environmental health and toxicology. In order to exploit the scientific opportunities, the National Institute of Environmental Health Sciences has created the National Center for Toxicogenomics (NCT). The primary mission of the NCT is to use gene expression technology, proteomics and metabolite profiling to create a reference knowledge base that will allow scientists to understand mechanisms of toxicity and to be able to predict the potential toxicity of new chemical entities and drugs. A principal scientific objective underpinning the use of microarray analysis of chemical exposures is to demonstrate the utility of signature profiling of the action of drugs or chemicals and to utilize microarray methodologies to determine biomarkers of exposure and potential adverse effects. The initial approach of the NCT is to utilize proof-of-principle experiments in an effort to "phenotypically anchor" the altered patterns of gene expression to conventional parameters of toxicity and to define dose and time relationships in which the expression of such signature genes may precede the development of overt toxicity. The microarray approach is used in conjunction with proteomic techniques to identify specific proteins that may serve as signature biomarkers. The longer-range goal of these efforts is to develop a reference relational database of chemical effects in biological systems (CEBS) that can be used to define common mechanisms of toxicity, chemical and drug actions, to define cellular pathways of response, injury and, ultimately, disease. In order to implement this strategy, the NCT has created a consortium of research organizations and private sector companies to actively collaborative in populating the database with high quality primary data. The evolution of discrete databases to a knowledge base of toxicogenomics will be accomplished through establishing relational interfaces with other sources of information on the structure and activity of chemicals such as that of the National Toxicology Program (NTP) and with databases annotating gene identity, sequence, and function.     

A lifestage approach to assessing children's exposure

Understanding and characterizing risks to children has been the focus of considerable research efforts at the U.S. Environmental Protection Agency (EPA). Potential health risks resulting from environmental exposures before conception and during pre‐ and postnatal development are often difficult to recognize and assess because of a potential time lag between the relevant periods of exposure during development and associated outcomes that may be expressed at later lifestages. Recognizing this challenge, a lifestage approach for assessing exposure and risk is presented in the recent EPA report titled A Framework for Assessing Health Risks of Environmental Exposures to Children (U.S. EPA, 2006 ). This EPA report emphasizes the need to account for the potential exposures to environmental agents during all stages of development, and consideration of the relevant adverse health outcomes that may occur as a result of such exposures. It identifies lifestage‐specific issues associated with exposure characterization for regulatory risk assessment, summarizes the lifestage‐specific approach to exposure characterization presented in the Framework, and discusses emerging research needs for exposure characterization in the larger public‐health context. This lifestage approach for characterizing children's exposures to environmental contaminants ensures a more complete evaluation of the potential for vulnerability and exposure of sensitive populations throughout the life cycle. Birth Defects Res (Part B) 2008. © 2008 Wiley‐Liss, Inc.     

A ratiometric fluorescent probe for assessing mitochondrial phospholipid peroxidation within living cells

Mitochondrial oxidative damage contributes to a wide range of pathologies, and lipid peroxidation of the mitochondrial inner membrane is a major component of this disruption. However, despite its importance, there are no methods to assess mitochondrial lipid peroxidation within cells specifically. To address this unmet need we have developed a ratiometric, fluorescent, mitochondria-targeted lipid peroxidation probe, MitoPerOx. This compound is derived from the C11-BODIPY(581/591) probe, which contains a boron dipyromethane difluoride (BODIPY) fluorophore conjugated via a dienyl link to a phenyl group. In response to lipid peroxidation the fluorescence emission maximum shifts from ～590 to ～520nm. To target this probe to the matrix-facing surface of the mitochondrial inner membrane we attached a triphenylphosphonium lipophilic cation, which leads to its selective uptake into mitochondria in cells, driven by the mitochondrial membrane potential. Here we report on the development and characterization of MitoPerOx. We found that MitoPerOx was taken up very rapidly into mitochondria within cells, where it responded to changes in mitochondrial lipid peroxidation that could be measured by fluorimetry, confocal microscopy, and epifluorescence live cell imaging. Importantly, the peroxidation-sensitive change in fluorescence at 520nm relative to that at 590nm enabled the use of the probe as a ratiometric fluorescent probe, greatly facilitating assessment of mitochondrial lipid peroxidation in cells.     

A novel approach for assessing factors affecting biodiversity based on networks analysis

We propose in this work a novel approach aiming at assessing cause and effect relationships between variables that can affect target biodiversity issues. These cause–effect relations are used to build a network whose nodes represent variables linked by directed arcs. The arcs have associated a value that represents trends of cause–effect relations. An important novelty of this approach is the use of product and addition operations between trends of cause–effect relations for assessing factors that can affect target variables. For the analysis of the network we use the concept of paths. Paths are defined as sequences of cause–effect relations from source variables to target variables. For example, the path from population increment that causes effects on the increment of transport routes, which in turn causes effects on the loss of vegetation cover. This approach was applied to the assessment of vegetation cover in the Morelos State, México during the period 2000–2010. The results show a promising practical alternative to assess the potential effects on biodiversity issues based on the analysis of the paths represented in the network.     

A novel approach for assessing the susceptibility of Escherichia coli to antibiotics

The dynamic growth process of Escherichia coli CVCC249 under different concentrations of antibiotics was analyzed. The results suggested that the main reason that definitive results cannot be obtained by antibiotic susceptibility testing (AST) is that the ratio of drug concentration to the population of bacteria and the combined effect of drug concentration and action time cannot be completely determined with the methods used. Based on the analysis of the growth process with a series of concentrations of gentamicin acting for a certain time, and according to the forward difference method, a novel method for AST was proposed. The net increase in turbidity of the bacterial population was used to eliminate the existing effects of resting cells, and then the recurrent coefficient for a growing sequence was used to characterize the effect of antibiotics on bacterial division, and the contour plot was used to display and analyze the combined effect of drug concentration and action time. The inhibition rate of the antibiotics can be characterized as the dynamic change in the composite function of the antibiotic concentration and action time, which indicated that the inhibition rate was dependent on the combined effect of time and concentration of antibiotics. The effectiveness of this new method has been verified with different kinds of antibiotics, such as enrofloxacin, levofloxacin, and ceftriaxone, having different antibacterial mechanisms.     

A method for assessing evergreen habitats using phytodiversity and geospatial techniques in tropical rain forests of Southern Western Ghats (India)

We have used data generated using remote sensing and geographical information systems to categorize habitats, and then determined the relationship between the habitat categorizations and species-distribution patterns. A biologically rich hotspot—Kalakad-Mundanthurai Tiger Reserve, located at Southern Western Ghats, India, was chosen for this study. In order to spatially delineate areas of high species richness/diversity and endemic habitat zones, we have identified evergreen habitats in conjunction with landscape metrics, species assemblage, micro-habitats like slope, topography, species endemism, and proportion of core and edge species. A total of 236 species and 2,920 individuals were recorded using systematic stratified plots of 0.1 ha covering 47 plots. Hierarchical cluster analysis was done using Ward’s method. Plot information was used to identify clusters based on species density. The analysis showed five species assemblages that are quite distinct from each other in terms of dominant species. The distribution of endemic and edge species, land cover heterogeneity, and continuity of patches in these clusters were evaluated to understand the degree of disturbance and intactness at landscape scale. Integration of species assemblages and topography brought out four major elevation-slope complexes. Information on species composition (robust field survey) with spectral (hybrid classification) properties has shown 72% overall accuracy and distinguished four evergreen sub-groups and other land cover classes. The developed approach assumes great importance in the assessment of biodiversity and prioritizing the areas of conservation.     

A novel approach for assessing macromolecular complexes combining soft-docking calculations with NMR data

We present a novel and efficient approach for assessing protein-protein complex formation, which combines ab initio docking calculations performed with the protein docking algorithm BiGGER and chemical shift perturbation data collected with heteronuclear single quantum coherence (HSQC) or TROSY nuclear magnetic resonance (NMR) spectroscopy. This method, termed "restrained soft-docking," is validated for several known protein complexes. These data demonstrate that restrained soft-docking extends the size limitations of NMR spectroscopy and provides an alternative method for investigating macromolecular protein complexes that requires less experimental time, effort, and resources. The potential utility of this novel NMR and simulated docking approach in current structural genomic initiatives is discussed.     

A qualitative approach to assessing body compartments using bioelectrical variables

A total of twelve subsamples of healthy European adults (207 males, 208 females) and Ecuadorian school children (300 males, 300 females) were studied with regard to their normal balance of body composition by calculating their bioelectrical values measured by a Phase-Sensitive Impedance Analyzer (BIA 101, Akern s.r.l., Florence, Italy). The method involved bivariate analysis of reactance and phase angle and the associated Bioelectrical nomogram (i.e. 'Biagram') which gives valuable information on the ratio of extra-cellular to body cell masses and confirmed that the vast majority of the subjects were in good physical condition. The few cases of outliers were attributable to slight dehydration after excessive physical activity in the adult sample or to slight overhydration or malnutrition in the child sample. The results of the qualitative approach in various areas of assessment of body composition in healthy and diseased subjects implies its usefulness as a tool in epidemiological studies.     

A phylogenetic approach to assessing the targets of microbial warfare

Bacteriocins are the most abundant and diverse defense systems in bacteria. As a result of the specific mechanisms of bacteriocin recognition and translocation into the target cell it is assumed that these toxins mediate intra-specific or population-level interactions. However, no published studies specifically address this question. We present here a survey of bacteriocin production in a collection of enteric bacteria isolated from wild mammals in Australia. A subset of the bacteriocin-producing strains was assayed for the ability to kill a broad range of enteric bacteria from the same bacterial collection. A novel method of estimating killing breadth was developed and used to compare the surveyed bacteriocins in terms of the phylogenetic range over which they kill. The most striking result is that although bacteriocin-producers kill members of their own species most frequently, some kill phylogenetically distant taxa more frequently than they kill closer relatives. This study calls into question the role these toxins play in natural populations. A significant number of bacteriocins are highly effective in killing inter-specific strains and thus bacteriocins may serve to mediate bacterial community interactions.     

An enhanced quantile approach for assessing differential gene expressions

Summary .   Due to the small number of replicates in typical gene microarray experiments, the performance of statistical inference is often unsatisfactory without some form of information-sharing across genes. In this article, we propose an enhanced quantile rank score test (EQRS) for detecting differential expression in GeneChip studies by analyzing the quantiles of gene intensity distributions through probe-level measurements. A measure of sign correlation, δ, plays an important role in the rank score tests. By sharing information across genes, we develop a calibrated estimate of δ, which reduces the variability at small sample sizes. We compare the EQRS test with four other approaches for determining differential expression: the gene-specific quantile rank score test, the quantile rank score test assuming a common δ, a modified t -test using summarized probe-set-level intensities, and the Mack–Skillings rank test on probe-level data. The proposed EQRS is shown to be favorable for preserving false discovery rates and for being robust against outlying arrays. In addition, we demonstrate the merits of the proposed approach using a GeneChip study comparing gene expression in the livers of mice exposed to chronic intermittent hypoxia and of those exposed to intermittent room air.     

A new approach for assessing cumulative lysosomal degradation of proteins or other macromolecules.

A general method is proposed for the direct estimation of the degradation in various tissues of macromolecules that are metabolized by a lysosomal mechanism. This involves coupling to the macromolecule a small molecule that is cleaved from it only after entry into the lysosome, that is not metabolized but is “trapped” in the lysosome, and that therefore accumulates as a direct function of the amount of macromolecule degraded. The feasibility of the method was shown using low density lipoprotein and serum albumin doubly labeled with covalently bound [¹⁴C]sucrose and ¹²⁵I. Uptake by normal fibroblasts, measured in terms of ¹⁴C accumulated in the cells, correlated very closely with uptake measured in terms of ¹²⁵I-labeled metabolites in the medium plus ¹²⁵I in the cells.     

Robust variance-components approach for assessing genetic linkage in pedigrees.

To assess evidence for genetic linkage from pedigrees, I developed a limited variance-components approach. In this method, variability among trait observations from individuals within pedigrees is expressed in terms of fixed effects from covariates and effects due to an unobservable trait-affecting major locus, random polygenic effects, and residual nongenetic variance. The effect attributable to a locus linked to a marker is a function of the additive and dominance components of variance of the locus, the recombination fraction, and the proportion of genes identical by descent at the marker locus for each pair of sibs. For unlinked loci, the polygenic variance component depends only on the relationship between the relative pair. Parameters can be estimated by either maximum-likelihood methods or quasi-likelihood methods. The forms of quasi-likelihood estimators are provided. Hypothesis tests derived from the maximum-likelihood approach are constructed by appeal to asymptotic theory. A simulation study showed that the size of likelihood-ratio tests was appropriate but that the monogenic component of variance was generally underestimated by the likelihood approach.     

A new statistical approach for assessing similarity of species composition with incidence and abundance data

The classic Jaccard and Sørensen indices of compositional similarity (and other indices that depend upon the same variables) are notoriously sensitive to sample size, especially for assemblages with numerous rare species. Further, because these indices are based solely on presence–absence data, accurate estimators for them are unattainable. We provide a probabilistic derivation for the classic, incidence‐based forms of these indices and extend this approach to formulate new Jaccard‐type or Sørensen‐type indices based on species abundance data. We then propose estimators for these indices that include the effect of unseen shared species, based on either (replicated) incidence‐ or abundance‐based sample data. In sampling simulations, these new estimators prove to be considerably less biased than classic indices when a substantial proportion of species are missing from samples. Based on species‐rich empirical datasets, we show how incorporating the effect of unseen shared species not only increases accuracy but also can change the interpretation of results.     

A novel approach for assessing protein synthesis in channel catfish, Ictalurus punctatus

A comprehensive understanding of animal growth requires adequate knowledge of protein synthesis (PS), which in fish, has traditionally been determined by the flooding dose method. However, this procedure is limited to short-term assessments and may not accurately describe fish growth over extended periods of time. Since deuterium oxide (²H₂O) has been used to non-invasively quantify PS in mammals over short- and long-term periods, we aimed at determining if ²H₂O could also be used to measure PS in channel catfish. Fish were stocked in a 40-L aquarium with ~ 4% ²H₂O and sampled at 4, 8 and 24 h (n = 6 at each time period) to determine ²H-labeling of body water (plasma), as well as protein-free and protein-bound ²H-labeled alanine. The labeling of body water reflected that of aquarium water and the labeling of protein-free alanine remained constant over 24 h and was ~ 3.8 times greater than that of body water. By measuring ²H-labeled alanine incorporation after 24 h of ²H₂O exposure we were able to calculate a rate of PS: 0.04 ± 0.01% h^− 1. These results demonstrate that PS in fish can be effectively measured using ²H₂O and, because this method yields integrative measures of PS, is relatively inexpensive and accounts for perturbations such as feeding, it is a novel and practical assessment option.     

A multivariate approach for assessing leaf photo‐assimilation performance using the IPL index

The detection of leaf functionality is of pivotal importance for plant scientists from both theoretical and practical point of view. Leaves are the sources of dry matter and food, and they sequester CO₂ as well. Under the perspective of climate change and primary resource scarcity (i.e. water, fertilizers and soil), assessing leaf photo‐assimilation in a rapid but comprehensive way can be helpful for understanding plant behavior under different environmental conditions and for managing the agricultural practices properly. Several approaches have been proposed for this goal, however, some of them resulted very efficient but little reliable. On the other hand, the high reliability and exhaustive information of some models used for estimating net photosynthesis are at the expense of time and ease of measurement. The present study employs a multivariate statistical approach to assess a model aiming at estimating leaf photo‐assimilation performance, using few and easy‐to‐measure variables. The model, parameterized for apple and pear and subjected to internal and external cross validation, involves chlorophyll fluorescence, carboxylative activity of ribulose‐1,5‐bisphosphate carboxylase/oxygenase (RuBisCo), air and leaf temperature. Results prove that this is a fair‐predictive model allowing reliable variable assessment. The dependent variable, called I_PL index, was found strongly and linearly correlated to net photosynthesis. I_PL and the model behind it seem to be (1) reliable, (2) easy and fast to measure and (3) usable in vivo and in the field for such cases where high amount of data is required (e.g. precision agriculture and phenotyping studies).     

中国最受关注濒危物种保护现状快速评价的新方法探讨

本文尝试制订了一套评分标准, 对中国174个国家I级保护动植物物种和IUCN物种红色名录中极危(CR)、濒危(EN)级别的鸟类的保护成效进行了快速评价。选取种群数量和趋势、信息完善程度、模拟分布区中适宜生境面积变化趋势和模拟分布区被保护区覆盖程度等4个指标进行评分。数据来源包括公开发表的研究文献、遥感数据、实地调查和公众收集。结果表明, 174个物种的保护状况整体呈变差趋势, 4项指标平均值均为负值。单个物种保护状况改善的有26种, 维持原状的有32种, 变差的有116种。本文还对2000-2013年间发表的涉及746个受威胁物种的9,338篇研究文献进行了梳理, 结果表明被研究物种数和文献数都逐年上升, 但每年被研究的物种不到1/3。研究集中于明星物种和有经济价值的物种, 如大熊猫(Ailuropoda melanoleuca)的文献占了全部的11.33%, 大多数物种研究不足。分析表明即使是集中了最多保护资源的濒危物种, 其保护状况仍然是变差的。     

Experimental approach for assessing the outcome accuracy of antibody microarray experiments

An experimental strategy for quality control of antibody microarray analyses is proposed. The method utilizes proteins that are prepared for regular antibody microarray experiments. There is no need to use exogenous positive or negative reference markers and no need to determine the absolute concentration of each individual protein in the sample. Validation experiments support the basic principle of the proposed approach. This method can be a useful tool for assessing the outcome accuracy of microarray experiments.     

A sequential approach to minimise threats within selected conservation areas

Core–periphery models allow predictions of persistence to be madewith relatively little data. The rationale is that populations in the core oftheir geographical or ecological ranges occupy suitable habitats and exhibithigher and less variable densities. Populations along the peripheries tend to bemore fragmented and therefore less likely to receive immigrants from otherpopulations. A population's probability of persistence is expected to correlatepositively with habitat suitability and immigration rate and to correlatenegatively with demographic variability. These predictions may be invalidated bythe effect of threats, which may cause some peripheral populations to persistrather than populations in the core. We expect that predictions of persistencefrom core–periphery models will be improved by incorporating informationon threats, and illustrate one way in which threat could be integrated withinquantitative area-selection methods. We illustrate this for Europe by showingthat important areas for biodiversity, selected with presence data, haveconsistently more people than expected by chance, but that incorporating humandensity as a constraint to area selection can reduce substantially this level ofpressure. We also show that areas selected using simple core–peripherymodels have fewer people than areas selected with presence data only. Theseresults support the idea that there are opportunities to identify importantareas for the persistence of species that are located in areas with low humandensity.