Adapting lacunarity techniques for gradient-based analyses of landscape surfaces

Typically, landscapes are modeled in the form of categorical map patterns, i.e. as mosaics made up of basic elements which are presumed to possess sharp and well-defined boundary lines. Many landscape ecological concepts are based upon this perception. In reality, however, the spatial value progressions of environmental parameters tend to be “gradual” rather than “abrupt”. Therefore, gradient approaches have shifted to the forefront of scientific interest recently. Appropriate methods are needed for the implementation of such approaches. Lacunarity analysis may provide a suitable starting point in this context. We propose adapted versions of standard lacunarity techniques for analyzing ecological gradients in general and the heterogeneity of physical landscape surfaces in particular. A simple way of customizing lacunarity analysis for quantifying the heterogeneity of digital elevation models is to use the value range for defining the box mass used in the calculation process. Furthermore, we demonstrate how lacunarity analysis can be combined with metrics derived from surface metrology, such as the “Average Surface Roughness”. Finally, the “classical” lacunarity approach is used in combination with simple landform indices. The methods are tested using different data sets, including high-resolution digital elevation models. In summary, lacunarity analysis is adopted in order to establish a gradient-based approach for terrain analysis and proves to be a valuable concept for comparing three-dimensional surface patterns in terms of their degree of “heterogeneity”. The proposed developments are meant to serve as a stimulus for making increased use of this simple but effective technique in landscape ecology. They offer a large potential for expanding the methodical spectrum of landscape structure analysis towards gradient-based approaches. Methods like lacunarity analysis are promising, since they do not rely on predefined landscape units or patches and thus enable ecologists to effectively deal with the complexity of natural systems.     

A random-walk interpretation of incentive effects in visual discrimination

Previous studies have shown that changes in stimulus discriminability and changes in reward density affect pigeon reaction-time (RT) distributions in different ways. A random-walk model (“RWP”) accounts for these differences and assigns a single parameter to each of the independent variables. This paper briefly reviews the model and illustrates its findings with hue discrimination data. A new analysis then presents fits to data showing that increased reward for stimulus “A” lengthens RT of pecks to an alternative stimulus “B”, and that this effect on RT distributions is much the same as the effect caused by reduction of reward to B. RWP account for both effects by changes in its “bias” parameter. The remainder of the paper comments on the relations between reward, RT, incentive and bias.     

Limiting the sedimentation coefficient for sedimentation velocity data analysis: partial boundary modeling and g(s) approaches revisited

Brown and coworkers (Eur. Biophys. J. 38 (2009) 1079–1099) introduced partial boundary modeling (PBM) to simplify sedimentation velocity data analysis by excluding species outside the range of interest (e.g., aggregates, impurities) via restricting the sedimentation coefficient range being fitted. They strongly criticized the alternate approach of fitting g(s^∗) distributions using similar range limits, arguing that (i) it produces “nonoptimal fits in the original data space” and (ii) the g(s^∗) data transformations lead to gross underestimates of the parameter confidence intervals. It is shown here that neither of those criticisms is valid. These two approaches are not truly fitting the same data or in equivalent ways; thus, they should not actually give the same best-fit parameters. The confidence limits for g(s^∗) fits derived using F statistics, bootstrap, or a new Monte Carlo algorithm are in good agreement and show no evidence for significant statistical distortion. Here 15 g(s^∗) measurements on monoclonal antibody samples gave monomer mass estimates with experimental standard deviations of less than 1%, close to the confidence limit estimates. Tests on both real and simulated data help to clarify the strengths and drawbacks of both approaches. New algorithms for computing g(s^∗) and a scan-differencing approach for PBM are introduced.     

The sense of water in the blowfly Protophormia terraenovae

The gustatory system of the blowfly, Protophormia terraenovae, is a relatively simple biological model for studies on chemosensory input and behavioral output. It appears to have renewed interest as a model for studies on the role of water channels, namely aquaporins or aquaglyceroporins, in water detection. To this end, we investigated the presence of water channels, their role in “water” and “salt” cell responsiveness and the transduction mechanism involved. For the first time our electrophysiological results point to the presence of an aquaglyceroporin in the chemoreceptor membrane of the “water” cell in the blowfly taste chemosensilla whose transduction mechanism ultimately involves an intracellular calcium increase and consequently cell depolarization. This hypothesis is also supported by calcium imaging data following proper stimulation. This mechanism is triggered by “water” cell stimulation with hypotonic solutions and/or solutes such as glycerol which crosses the membrane by way of aquaglyceroporins. Behavioral output indicates that the “sense” of water in blowflies is definitely not dependent on the “water” cell only, but also on the “salt” cell sensitivity. These findings also hypothesize a new role for aquaglyceroporin in spiking cell excitability.     

Physics and chemistry-driven artificial neural network for predicting bioactivity of peptides and proteins and their design

Predicting the bioactivity of peptides and proteins is an important challenge in drug development and protein engineering. In this study we introduce a novel approach, the so-called “physics and chemistry-driven artificial neural network (Phys-Chem ANN)”, to deal with such a problem. Unlike the existing ANN approaches, which were designed under the inspiration of biological neural system, the Phys-Chem ANN approach is based on the physical and chemical principles, as well as the structural features of proteins. In the Phys-Chem ANN model the “hidden layers” are no longer virtual “neurons”, but real structural units of proteins and peptides. It is a hybridization approach, which combines the linear free energy concept of quantitative structure-activity relationship (QSAR) with the advanced mathematical technique of ANN. The Phys-Chem ANN approach has adopted an iterative and feedback procedure, incorporating both machine-learning and artificial intelligence capabilities. In addition to making more accurate predictions for the bioactivities of proteins and peptides than is possible with the traditional QSAR approach, the Phys-Chem ANN approach can also provide more insights about the relationship between bioactivities and the structures involved than the ANN approach does. As an example of the application of the Phys-Chem ANN approach, a predictive model for the conformational stability of human lysozyme is presented.     

基因工程培育可恢复的植物雄性不育系的研究进展

植物雄性不育是植物杂种优势利用的资源, 具有重要的生产利用价值。植物雄性不育可从自然突变、人工诱变和远缘杂交中发现, 现在可通过细胞工程和基因工程等方法来创造。文章综述了利用基因工程方法制备雄性不育品系及其相应的育性恢复策略, 分为“单组分策略”和“双组分策略”。其中利用“单组分策略”制备的不育植株是条件型雄性不育(可逆转的雄性不育), 它能在特定的条件下实现雄性可育与不育的转换, 实践中可直接作为两用系(不育系和保持系)用于两系法杂交制种; “双组分策略”是利用基因互作和亲本杂交直接培育雄性不育系, 或利用基因互作原理分别研制不育系和恢复系, 用于三系法生产杂交种。文章分析了 “单组分策略”和“双组分策略”的基因工程方法培育雄性不育系及其相应育性恢复策略优缺点, 对以上两种技术路线在实际应用中的现状作了分析和展望。     

Light adaptation in cone photoreceptors: The occurrence and significance of unitary adaptive strength

The behavior of peak response-log intensity functions generated by the dark glasses model is examined and is shown to describe previously observed light adapted behavior in cone photoreceptors. The models of Boynton and Whitten (1970) and Norman and Werblin (1974) are closely related to the dark glasses model — the Boynton-Whitten model being more specific and the Normann-Werblin model more general. For the models, a certain parameter relationship will produce systems which have optimal intensity discriminative capacities. When the data are fitted, this parameter relationship — unitary adaptive strengh — seems to emerge. Possible evolutionary and psychophysical implications are discussed.     

The distribution of the coalescence time and the number of pairwise nucleotide differences in a model of population divergence or speciation with an initial period of gene flow

This paper is concerned with a model of “isolation with an initial period of migration”, where a panmictic ancestral population split into n descendant populations which exchanged migrants symmetrically at a constant rate for a period of time and subsequently became completely isolated. In the limit as the population split occurred an infinitely long time ago, the model becomes an “isolation after migration” model, describing completely isolated descendant populations which arose from a subdivided ancestral population. The probability density function of the coalescence time of a pair of genes and the probability distribution of the number of pairwise nucleotide differences are derived for both models. Whilst these are theoretical results of interest in their own right, they also give an exact analytical expression for the likelihood, for data consisting of the numbers of nucleotide differences between pairs of DNA sequences where each pair is at a different, independent locus. The behaviour of the distribution of the number of pairwise nucleotide differences under these models is illustrated and compared to the corresponding distributions under the “isolation with migration” and “complete isolation” models. It is shown that the distribution of the number of nucleotide differences between a pair of DNA sequences from different descendant populations in the model of “isolation with an initial period of migration” can be quite different from that under the “isolation with migration model”, even if the average migration rate over time (and hence the total number of migrants) is the same in both scenarios. It is also illustrated how the results can be extended to other demographic scenarios that can be described by a combination of isolated panmictic populations and “symmetric island” models.     

A unified approach to the Richards-model family for use in growth analyses: Why we need only two model forms

This paper advances a unified approach to the modeling of sigmoid organismal growth. There are numerous studies on growth, and there have been several proposals and applications of candidate models. Still, a lack of interpretation of the parameter values persists and, consequently, differences in growth patterns have riddled this field. A candidate regression model as a tool should be able to assess and compare growth-curve shapes, systematically and precisely. The Richards models constitute a useful family of growth models that amongst a multitude of parameterizations, re-parameterizations and special cases, include familiar models such as the negative exponential, the logistic, the Bertalanffy and the Gompertz. We have reviewed and systemized this family of models. We demonstrate that two specific parameterizations (or re-parameterizations) of the Richards model are able to substitute, and thus to unify all other forms and models. This unified-Richards model (with its two forms) constitutes a powerful tool for an interpretation of important characteristics of observed growth patterns, namely, [I] maximum (relative) growth rate (i.e., slope at inflection), [II] age at maximum growth rate (i.e., time at inflection), [III] relative mass or length at maximum growth rate (i.e., relative value at an inflection), [IV] value at age zero (i.e., birth, hatching or germination), and [V] asymptotic value (i.e., adult weight or length). These five parameters can characterize uniquely any sigmoid-growth data. To date most studies only compare what is referred to as the “growth-rate constant” or simply “growth rate” (k). This parameter can be interpreted as neither relative nor actual growth rate, but only as a parameter that affects the slope at inflection. We fitted the unified-Richards and five other candidate models to six artificial data sets, generated from the same models, and made a comparison based on the corrected Akaike’s Information Criterion (AICc). The outcome may in part be the result of the random generation of data points. Still, in conclusion, the unified-Richards model performed consistently well for all data sets, despite the penalty imposed by the AICc.     

Improved methods for fitting sedimentation coefficient distributions derived by time-derivative techniques

Time-derivative approaches to analyzing sedimentation velocity data have proven to be highly successful and have now been used routinely for more than a decade. For samples containing a small number of noninteracting species, the sedimentation coefficient distribution function, g(s *), traditionally has been fitted by Gaussian functions to derive the concentration, sedimentation coefficient, and diffusion coefficient of each species. However, the accuracy obtained by that approach is limited, even for noise-free data, and becomes even more compromised as more scans are included in the analysis to improve the signal/noise ratio (because the time span of the data becomes too large). Two new methods are described to correct for the effects of long time spans: one approach that uses a Taylor series expansion to correct the theoretical function and a second approach that creates theoretical g(s *) curves from Lamm equation models of the boundaries. With this second approach, the accuracy of the fitted parameters is approximately 0.1% and becomes essentially independent of the time span; therefore, it is possible to obtain much higher signal/noise when needed. This second approach is also compared with other current methods of analyzing sedimentation velocity data.     

Computer simulation of sedimentation in the ultracentrifuge: V. Ideal and non-ideal monomer-trimer systems

Treatments of velocity sedimentation which neglect diffusion (“asymptotic” solutions) predict that a minimum will appear in the gradient curves given by certain rapidly equilibrating monomer-trimer and monomer-dimer-trimer systems. The velocity sedimentation of a variety of such systems has been simulated by a computer model. The model takes into account the diffusion of the solutes. Both ideal and non-ideal sedimentation have been examined. Sedimentation is assumed to have been done in water at 60,000 rpm in a standard ultracentrifuge rotor.     

Comparing two methods of calculating the probability of absence: the Negative Predictive Value, and a Credible Interval

If sampling fails to reveal the presence of an invasive species with potential to actually be present, how may we calculate the probability that it is truly absent, e.g. didymo (Didymosphenia geminate) in New Zealand’s North Island. In statistical terms this is a Bayesian question, concerning the probability of a hypothesis (presence/absence), given the obtained data (all results negative). “Classical” theory doesn’t answer this question, because it inverts the required considerations by calculating the probability of all samples being absent if the invasive was actually present. Accordingly, the Bayesian view of “probability” must be adopted in order to answer the question. That definition differs from classical probability in that it always includes an element of subjective belief, particularly in the choice of an appropriate “prior probability” (this is our belief as to the presence of the invasive organism before collecting new data). Bayesian methods can therefore be somewhat controversial – but we seem forced to use them. One Bayesian approach is to use the “Negative Predictive Value”, in which a point estimate of the probability of presence (or absence) prior to sample collection (the “prior probability”) is updated using data once collected using Bayes’ rule. This is in common use in medical studies, where the prior probability is the background disease prevalence, which is generally well understood. It is sometimes used in environmental ‘hot-spot’ investigations. An alternative approach is to recognise the uncertainty in the prior belief by using a distribution of prior probability and updating that using data once collected to give a Credible Interval in which the probability of presence (or absence) should lie – if all our assumptions have been satisfied. We will compare the merits of these approaches considering didymo, southern salt marsh mosquito (Aedes camptorhychus) and the sea squirt Styela clava.     

Beyond dual-lattice models: Incorporating plant strategies when modeling the interplay between facilitation and competition along environmental severity gradients

We introduce a spatially explicit model that evaluates how the trade-offs between the life strategies of two interacting plant species affect the outcome of their interaction along environmental severity gradients. In our model, we represent the landscape as a two-dimensional lattice, with environmental severity increasing from left to right. Two species with different strategies, a competitor and a stress-tolerant, interact in the lattice. We find that facilitation expands the realized niche of the competitor into harsh environments by suppressing the stress-tolerant species. Most of their coexisting range is dominated by a positive effect of one species on another, with a reciprocal negative effect from the species receiving the benefits on its benefactor (“+, −”), whereas mutualistic (“+, +”) interactions are only found in the harshest part of the environmental gradient. Contrarily as assumed by models commonly used in facilitation research (e.g. dual-lattice models), our results indicate that “+, +” interactions are not dominant, and that their differences with “+, −” interactions along environmental severity gradients depend on the strategies of the interacting species. By integrating the trade-off between competitive ability and stress tolerance, our model provides a new framework to investigate the interplay of facilitative and competitive interactions along environmental gradients and their impacts on processes such as population dynamics and community organization.     

Population continuity, demic diffusion and Neolithic origins in central-southern Germany: The evidence from body proportions

The transition to agro-pastoralism in central Europe has been framed within a dichotomy of “regional continuity” versus exogenous “demic diffusion”. While substantial genetic support exists for a model of demographic diffusion from an ancestral source in the Near East, archaeological data furnish weak support for the “wave of advance” model. Nevertheless, archaeological evidence attests the widespread introduction of an exogenous “package” comprising ceramics, cereals, pulses and domesticated animals to central Europe at 5600 cal BCE.Body proportions are under strong climatic selection and evince remarkable stability within regional lineages. As such, they offer a viable and robust alternative to cranio-facial data in assessing hypothesised continuity and replacement with the transition to agro-pastoralism in central Europe. Humero-clavicular, brachial and crural indices in a large sample (n=75) of Linienbandkeramik (LBK), Late Neolithic and Early Bronze Age specimens from the middle Elbe-Saale-Werra valley (MESV) were compared with Eurasian and African terminal Pleistocene, European Mesolithic and geographically disparate recent human specimens.Mesolithic Europeans display considerable variation in humero-clavicular and brachial indices yet none approach the extreme “hyper-polar” morphology of LBK humans from the MESV. In contrast, Late Neolithic and Early Bronze Age peoples display elongated brachial and crural indices reminiscent of terminal Pleistocene and “tropically adapted” recent humans. These marked morphological changes likely reflect exogenous immigration during the terminal Fourth millennium cal BC. Population expansion and diffusion is a function of increased mobility and settlement dispersal concomitant with significant technological and subsistence changes in later Neolithic societies during the late fourth millennium cal BCE.     

The kinetics of amylolysis : Part III. Effect of self-inhibition on the kinetic constants of beta-amylolysis

For beta-amylolysis, the number of bonds split per effective enzyme-substrate encounter has been determined with amyloses having various degrees of polymerization (d.p.), labelled with ¹⁴C. The degradation is shifted in the direction of the “single chain mechanism” with increasing d.p. By taking into account the “inactive, non-reacting” collisions leading to “self-inhibition”, the number of bonds split per “reactive” and “non-reactive” enzyme-substrate encounter was established. From these data, and from the inhibition constant of the inner D-glucose residues of the amylose chain, in conjunction with the Michaelis constant extrapolated to d.p.  4, the actual rate constants for the formation and dissociation of the “reactive” enzyme-substrate complexes and for the formation and dissociation of the “non-reactive” enzyme-substrate complexes were determined. It was found that the rate constants for the formation of the “reactive” complexes decrease slowly with the increase of “self-inhibition”, whereas those for the dissociation of these complexes decrease to a greater extent.     

Baroreflex variability and “resetting”: A new perspective

A new framework is proposed for the interpretation of spontaneous cardiac baroreflex sensitivity data and the general concept of baroreflex resetting. The framework is used to explore baroreflex function along two separate lines of inquiry: one following a direct intervention in baroreflex function in individual subjects, another in a group of subjects where baroreflex function may have been compromised by coronary artery disease or aging. It is found that under baseline conditions the baroreflex is in a “free-floating” state in which the gain or “sensitivity” is highly variable, while under orthostatic stress or in the absence of or reduced vagal input the gain is more tightly controlled with an expected decline in sensitivity but a very large decline in the variability of that sensitivity. It is concluded that baroreflex “resetting” is better viewed not simply as a change in baroreflex sensitivity but rather as a change in the “focus” or “attention” of the baroreflex as expressed by an observed decline in the variability of the measured gain. The results do not support the interpretation of baroreflex “resetting” as a departure from or return to a universal “set point” as in homeostasis or open loop models.     

α-Actinin-4-Mediated FSGS: An Inherited Kidney Disease Caused by an Aggregated and Rapidly Degraded Cytoskeletal Protein

Focal segmental glomerulosclerosis (FSGS) is a common pattern of renal injury, seen as both a primary disorder and as a consequence of underlying insults such as diabetes, HIV infection, and hypertension. Point mutations in theα-actinin-4 gene ACTN4 cause an autosomal dominant form of human FSGS. We characterized the biological effect of these mutations by biochemical assays, cell-based studies, and the development of a new mouse model. We found that a fraction of the mutant protein forms large aggregates with a high sedimentation coefficient. Localization of mutant α-actinin-4 in transfected and injected cells, as well as in situ glomeruli, showed aggregates of the mutant protein. Video microscopy showed the mutant α-actinin-4 to be markedly less dynamic than the wild-type protein. We developed a “knockin” mouse model by replacing Actn4 with a copy of the gene bearing an FSGS-associated point mutation. We used cells from these mice to show increased degradation of mutant α-actinin-4, mediated, at least in part, by the ubiquitin–proteasome pathway. We correlate these findings with studies of α-actinin-4 expression in human samples. “Knockin” mice with a disease-associated Actn4 mutation develop a phenotype similar to that observed in humans. Comparison of the phenotype in wild-type, heterozygous, and homozygous Actn4 “knockin” and “knockout” mice, together with our in vitro data, suggests that the phenotypes in mice and humans involve both gain-of-function and loss-of-function mechanisms.     

Use of fluorescence lifetime technology to provide efficient protection from false hits in screening applications

This article describes novel data analysis of fluorescence lifetime-based protein kinase assays to identify and correct for compound interference in several practical cases. This ability, together with inherent advantages of fluorescence lifetime technology (FLT) as a homogeneous, antibody-free format independent of sample concentration, volume, excitation intensity, and geometry, makes fluorescence lifetime a practical alternative to the established “gold standards” of radiometric and mobility shift (Caliper) assays. The analysis is based on a photochemical model that sets constraints on the values of fluorescence lifetimes in the time responses of the assay. The addition of an exponential component with free floating lifetime to the constrained model, in which the lifetimes are constants predetermined from control measurements and the preexponential coefficients are “floating” parameters, allows the relative concentration of phosphorylated and nonphosphorylated substrates to be calculated even in the presence of compound fluorescence. The method is exemplified using both simulated data and experimental results measured from mixtures of dye-labeled phosphorylated and nonphosphorylated kinase substrates. A change of the fluorescence lifetime is achieved by the phosphorylated substrate-specific interaction with a bifunctional ligand, where one binding site interacts with the phosphate group and the other interacts with the dye.