Some contributions of signal detection theory to the analysis of stimulus control in animals

This paper reviews some applications of Signal Detection Theory (SDT) to the quantitative analysis of non-human animal discrimination. The basic detection model is briefly outlined and the separation of sensitivity and bias is illustrated. Several other applications and ideas are reviewed, including the rating method, some implications of signal and criterion variance, and the measurement of 'guesses' not encompassed by standard SDT. The conceptual framework and analytic tools of SDT help to clarify processes underlying stimulus control and provide direction to more complete process models.     

Applying QTL analysis to conservation genetics

Both analytical and molecular tools currently exist that can be used to prolifically apply quantitative trait loci (QTL) analysis to the study of natural populations. In this communication, we review and exemplify the use of QTL mapping tools and genetic modeling for conservation geneticists. We simulate populations inspired by relevant cases that can be encountered in the field and analyze them using the recently developed flexible intercross analysis (FIA) method. We then reanalyze these results with the also recently developed natural and orthogonal interactions (NOIA) model of genetic effects. Next, we further exemplify the potential of genetic modeling for the interpretation of the output of QTL analyses by reviewing studies on hybrids between wild individuals and their domesticated relatives. Based on the results here presented we emphasize several points that are pertinent in conservation genetics including (i) the advantages of FIA as a powerful tool to be applied to line crosses in which the parental lines are not inbred, (ii) the importance of obtaining estimates of genetic effects that are adequate to address the research issue under consideration, (iii) the versatility of genetic modeling, particularly NOIA, to dissect complex genetic architectures and (iv) the possibility of using currently available methods to address non-equilibrium multiallelic systems.     

Engineering self-contained DNA circuit for proximity recognition and localized signal amplification of target biomolecules

Biomolecular interactions have important cellular implications, however, a simple method for the sensing of such proximal events is lacking in the current molecular toolbox. We designed a dynamic DNA circuit capable of recognizing targets in close proximity to initiate a pre-programmed signal transduction process resulting in localized signal amplification. The entire circuit was engineered to be self-contained, i.e. it can self-assemble onto individual target molecules autonomously and form localized signal with minimal cross-talk. α-thrombin was used as a model protein to evaluate the performance of the individual modules and the overall circuit for proximity interaction under physiologically relevant buffer condition. The circuit achieved good selectivity in presence of non-specific protein and interfering serum matrix and successfully detected for physiologically relevant α-thrombin concentration (50 nM–5 μM) in a single mixing step without any further washing. The formation of localized signal at the interaction site can be enhanced kinetically through the control of temperature and probe concentration. This work provides a basic general framework from which other circuit modules can be adapted for the sensing of other biomolecular or cellular interaction of interest.     

Batesian mimicry and signal detection theory

Signal Detection Theory can be used to provide a mathematical model describing the choice of a predator trying to distinguish between a model and a Batesian mimic. The mathematical model yields a number of a deductions, in particular that it may or may not assist the mimic population if mimics more closely resemble their models. The assumptions underlying the analysis are discussed in some detail.     

Applying hidden Markov models to the analysis of single ion channel activity

Hidden Markov models have recently been used to model single ion channel currents as recorded with the patch clamp technique from cell membranes. The estimation of hidden Markov models parameters using the forward-backward and Baum-Welch algorithms can be performed at signal to noise ratios that are too low for conventional single channel kinetic analysis; however, the application of these algorithms relies on the assumptions that the background noise be white and that the underlying state transitions occur at discrete times. To address these issues, we present an "H-noise" algorithm that accounts for correlated background noise and the randomness of sampling relative to transitions. We also discuss three issues that arise in the practical application of the algorithm in analyzing single channel data. First, we describe a digital inverse filter that removes the effects of the analog antialiasing filter and yields a sharp frequency roll-off. This enhances the performance while reducing the computational intensity of the algorithm. Second, the data may be contaminated with baseline drifts or deterministic interferences such as 60-Hz pickup. We propose an extension of previous results to consider baseline drift. Finally, we describe the extension of the algorithm to multiple data sets.     

Trace analysis of endogenous and exogenous biomolecules from archaeological skeleton materials

An analytical procedure was developed for the determination of pharmacologically active substances in archaeological skeleton materials. In comparative model studies, added ("spiked") test biomolecules of varying chemical behaviours were extracted from sample matrices and percentage of the analytes recovered were estimated using gas chromatography/mass spectrometry (GC/MS) or high performance liquid chromatography (HPLC). For the sterols and steroids studied, several organic solvents were appropriate. Extraction yields for the alkaloid nicotine, representing non-endogenous basic agents, were increased by alkalizing with triethylamine or by extracting with a two-phase system consisting of an alkaline aqueous and an organic layer (toluene). The flavonol quercetin was extractable only in an acidic environment. In a screening for native biomolecules using GC/MS, nicotine was identified in individual samples, in addition to lipophilic substances such as the endogenous cholesterol and its degradation products and two phytosterols which may have migrated into the bones from the surrounding soil.     

Applying DNA computation to intractable problems in social network analysis

From ancient times to the present day, social networks have played an important role in the formation of various organizations for a range of social behaviors. As such, social networks inherently describe the complicated relationships between elements around the world. Based on mathematical graph theory, social network analysis (SNA) has been developed in and applied to various fields such as Web 2.0 for Web applications and product developments in industries, etc. However, some definitions of SNA, such as finding a clique, N-clique, N-clan, N-club and K-plex, are NP-complete problems, which are not easily solved via traditional computer architecture. These challenges have restricted the uses of SNA. This paper provides DNA-computing-based approaches with inherently high information density and massive parallelism. Using these approaches, we aim to solve the three primary problems of social networks: N-clique, N-clan, and N-club. Their accuracy and feasible time complexities discussed in the paper will demonstrate that DNA computing can be used to facilitate the development of SNA.     

Applying MSSIM combined chaos game representation to genome sequences analysis

Converting DNA sequence to image by using chaos game representation (CGR) is an effective genome sequence pretreatment technology, which provides the basis for further analysis between the different genes. In this paper, we have constructed 10 mammal species, 48 hepatitis E virus (HEV), and 10 kinds of bacteria genetic CGR images, respectively, to calculate the mean structural similarity (MSSIM) coefficient between every two CGR images. From our analysis, the MSSIM coefficient of gene CGR images can accurately reflect the similarity degrees between different genomes. Hierarchical clustering analysis was used to calculate the class affiliation and construct a dendrogram. Large numbers of experiments showed that this method gives comparable results to the traditional Clustal X phylogenetic tree construction method, and is significantly faster in the clustering analysis process. Meanwhile MSSIM combined CGR method was also able to efficiently clustering of large genome sequences, which the traditional multiple sequence alignment methods (e.g. Clustal X, Clustal Omega, Clustal W, et al.) cannot classify.     

Applying competition theory to invasion: resource impacts indicate invasion mechanisms in California shrublands

Despite widespread work documenting invasion, it remains a challenge to determine invasion mechanisms and incorporate them into invasive species management. Competition theory presents a strong model for evaluating the role of resource reduction and requirements in invasion. Additionally, alternative models suggest fluctuations in resources, niche differences, or non-resource priority effects are key factors determining invasion success. We propose a comparative framework that incorporates resource impacts of native and invasive species, performance in controlled invasion trials, and long-term natural invasion patterns to elucidate relative importance of these invasion mechanisms. To demonstrate this framework, we established monocultures of two representative native and two invasive plant species in Southern California’s coastal sage scrub (CSS), measured resource impacts (i.e., R*), and conducted invasion trials to test whether resource impacts predicted invasion success. We then related experimental results to field invasion patterns. Compared to exotic herbaceous species, native shrubs were associated with greater resource depletion of key resources: light, soil water (at multiple depths), and soil inorganic nitrogen (particularly at depth). In invasion trials, natives resisted invasion by the exotics, as resource depletion measures would predict. However, these results did not follow long-term natural invasion patterns indicating that these exotic species invade areas once dominated by native shrubland. Applying our results to the invasion framework, we conclude that disturbance, or a similar mechanism causing resources to fluctuate, is needed for exotics to invade CSS habitats. This resource-based comparative analysis of invasion mechanisms can point out important processes and help suggest effective management actions.     

Adaptive bone-remodeling theory applied to prosthetic-design analysis

The subject of this article is the development and application of computer-simulation methods to predict stress-related adaptive bone remodeling, in accordance with 'Wolff's Law'. These models are based on the Finite Element Method (FEM) in combination with numerical formulations of adaptive bone-remodeling theories. In the adaptive remodeling models presented, the Strain Energy Density (SED) is used as a feed-back control variable to determine shape or bone density adaptations to alternative functional requirements, whereby homeostatic SED distribution is assumed as the remodeling objective. These models are applied to investigate the relation between 'stress shielding' and bone resorption in the femoral cortex around intramedullary prostheses, such as used in Total Hip Arthroplasty (THA). It is shown that the amount of bone resorption depends mainly on the rigidity and the bonding characteristics of the implant. Homeostatic SED can be obtained when the resorption process occurs at the periosteal surface, rather than inside the cortex, provided that the stem is adequately flexible.     

Coupling biomolecules to fullerenes through a molecular adapter

A novel biotinylated fullerene has been synthesized to facilitate the attachment of biotin-conjugated proteins to C(60) through the use of streptavidin as a molecular adapter. The strong biotin-streptavidin interaction enables the attachment of fullerenes to streptavidin and, because of the availability of four biotin-binding sites on streptavidin, to biotinylated biomolecules. The feasibility of this approach is demonstrated by using biotinylated alkaline phosphatase. Due to the insolubility of fullerenes in aqueous media, the immobilized enzyme can be eventually recovered by simple centrifugation with no significant loss in activity.