Substance P antagonists and analgesia: a review of the hypothesis

This review focused entirely on the hypothesis that a substance P/neurokinin antagonist should have, and the experimental evidence examining whether they do have, analgesic/antinociceptive properties. Such a hypothesis is reasonable considering the wealth of evidence implicating substance P in the nociceptive process and the demonstration that antibodies to substance P produce or potentiate antinociception. However, despite the availability of several putative antagonists, their pharmacological purity, specificity and selectivity are questionable. Thus, the investigator may not have, as yet, the appropriate tool drug with which to work. Much of the information concerning these points is generated utilizing in vitro (referring to isolated tissue preparations) bioassay tests which may not adequately reflect nor predict their pharmacology in the CNS. Differences in species responsiveness further complicate experimental design and interpretation. Apart from these factors, the choice of test or tests becomes an important consideration. What test, if any, adequately and appropriately reflects the endogenous physiological activity of substance P in nociception and predicts clinically useful activity of an antagonist? Several different models have been described and I have emphasized that conclusions based on a single model should be interpreted with caution. If the ultimate intent of the study is to further define the role of substance P in nociception, then most of the models discussed are adequate. However, if the intent is to demonstrate that a substance P/neurokinin antagonist should have therapeutically useful analgesic activity, it is incumbant on the investigator to demonstrate that, in their model, substance P release is a primary event, the resultant analgesia correlates to the occupancy of the neurokinin receptor by antagonist (ultimately important for all conclusions) and that the model adequately reflects activity of known analgesics in clinical use (validation of the model). In conclusion, given the complexities and contradictions of existing information, the hypothesis that a substance P/neurokinin antagonist should have analgesic/antinociceptive properties remains to be proven.     

Protein dynamics and 1/f noise.

It has long been recognized that protein dynamical processes occur over a wide temporal range. However, the functionality of this spectrum of events remains unclear. In this work, a generalized noise function analysis is applied to a collection of diverse protein dynamical systems. It is shown that a power law model with an oscillatory component can adequately describe the time course of a variety of processes. These results suggest that under the appropriate conditions, proteins are in a metastable state. A microscopic, chemical kinetic model based on a Poisson distribution of activation energies is presented. From this model specific functional forms for the parameters of the generalized noise model can be derived. Additionally, a model is presented to described kinetic hole burning effects observed at low temperatures. Scaling laws are derived for these models that provide a connection with the generalized noise analysis.     

Some Pragmatic Aspects of Navaho Peyotism

Abstract

The Peyote religion has often been characterized as promoting passivity, resignation, and escape into a subjective world of visions as a substitute for the dissatisfying social and economic conditions resulting from white domination. Data gathered on the Navaho reservation are presented which indicate that it is more appropriate to view Peyotism as an active attempt to transform these conditions, an interpretation which more adequately matches the Malinowskian model of magico-religiousphenomena.     

Allelic Richness following Population Founding Events – A Stochastic Modeling Framework Incorporating Gene Flow and Genetic Drift

Allelic richness (number of alleles) is a measure of genetic diversity indicative of a population''s long-term potential for adaptability and persistence. It is used less commonly than heterozygosity as a genetic diversity measure, partially because it is more mathematically difficult to take into account the stochastic process of genetic drift for allelic richness. This paper presents a stochastic model for the allelic richness of a newly founded population experiencing genetic drift and gene flow. The model follows the dynamics of alleles lost during the founder event and simulates the effect of gene flow on maintenance and recovery of allelic richness. The probability of an allele''s presence in the population was identified as the relevant statistical property for a meaningful interpretation of allelic richness. A method is discussed that combines the probability of allele presence with a population''s allele frequency spectrum to provide predictions for allele recovery. The model''s analysis provides insights into the dynamics of allelic richness following a founder event, taking into account gene flow and the allele frequency spectrum. Furthermore, the model indicates that the “One Migrant per Generation” rule, a commonly used conservation guideline related to heterozygosity, may be inadequate for addressing preservation of diversity at the allelic level. This highlights the importance of distinguishing between heterozygosity and allelic richness as measures of genetic diversity, since focusing merely on the preservation of heterozygosity might not be enough to adequately preserve allelic richness, which is crucial for species persistence and evolution.     

Statistical models of shape for the analysis of protein spots in two-dimensional electrophoresis gel images

In image analysis of two-dimensional electrophoresis gels, individual spots need to be identified and quantified. Two classes of algorithms are commonly applied to this task. Parametric methods rely on a model, making strong assumptions about spot appearance, but are often insufficiently flexible to adequately represent all spots that may be present in a gel. Nonparametric methods make no assumptions about spot appearance and consequently impose few constraints on spot detection, allowing more flexibility but reducing robustness when image data is complex. We describe a parametric representation of spot shape that is both general enough to represent unusual spots, and specific enough to introduce constraints on the interpretation of complex images. Our method uses a model of shape based on the statistics of an annotated training set. The model allows new spot shapes, belonging to the same statistical distribution as the training set, to be generated. To represent spot appearance we use the statistically derived shape convolved with a Gaussian kernel, simulating the diffusion process in spot formation. We show that the statistical model of spot appearance and shape is able to fit to image data more closely than the commonly used spot parameterizations based solely on Gaussian and diffusion models. We show that improvements in model fitting are gained without degrading the specificity of the representation.     

Growth behavior of microorganisms using UV-Vis spectroscopy: Escherichia coli

Multiwavelength transmission spectra of microorganisms and cell suspensions consist of combined absorption and scattering phenomena resulting from the interaction of light with microorganisms or cells typically suspended in a nonabsorbing media. The distribution of intensities as a function of wavelength depends on the size, shape, and optical properties of the sample. The optical properties are functions of the chemical composition and the state of aggregation, or association, of the chromophoric groups contained in the microorganisms. This article explores the growth behavior of Escherichia coli from the perspective of multiwavelength UV-Vis spectroscopy. Experimentally, it is demonstrated that the spectral signatures of the microorganism evolve as a function of time. It is also demonstrated that the spectral changes observed during growth are consistent with data reported elsewhere. From the theoretical point of view, it is demonstrated that the spectral signatures can be adequately represented with an interpretation model based on light-scattering theory. The parameters from the interpretation model reflect changes in size and chemical composition known to take place in the microorganisms during growth.     

Role of a mitochondrial gene in the conformation and optical properties of mitochondrial cytochromes in Neurospora crassa

The mitochondrial cytochrome spectrum of the poky strain of Neurospora crassa and its variation during the life cycle have been analyzed. Two factors are taken into account in addition to those usually considered; absorption in the near-ultraviolet Soret region and the physical nature of the electronic transitions which give rise to the absorption bands. From this extended analysis, a hypothesis based on the chemical nature of the axial environment of the heme groups has been constructed to account for spectroscopic observations. A model has been developed that provides a biochemical mechanism by which a genetic defect in mitochondrial DNA can lead to structural defects in the axial environment of the hemes and thus to an altered cytochrome spectrum. Previously reported absences or deficiencies of cytochromes based on visible absorption spectroscopy may in some cases indicate the absence or deficiency of only the particular polypeptide subunits of a complex which are synthesized within the mitochondria. This interpretation is consistent with the various manifestations of the poky phenotype which have been observed.     

Effect of magnesium stearate on the content uniformity of active ingredient in pharmaceutical powder mixtures

The objective of this study was to determine the effect of magnesium stearate on the physical stability of polydisperse powder mixtures. The effects of concentration of magnesium stearate and the time of lubrication of mixtures with magnesium stearate on the content uniformity of the active ingredient in the mixtures were evaluated in a model mixture of lactose and aspirin. These effects were compared in a random mixture of non-interacting components and a mixture based on particle interaction. A statistical model that adequately described the relationship between the factors examined and the response was generated. The model indicated the presence of an interaction between magnesium stearate concentration and lubrication time. At a given concentration of magnesium stearate, there was a significant reduction in the content uniformity of aspirin as the time of lubrication of the mixture with magnesium stearate was increased. This effect was larger in mixtures based on particle interaction than in random mixtures of non-interacting components.     

Enhancing the performance and interpretation of freshwater biological indices: An application in arid zone streams

We assessed the performance of biological indices developed for invertebrate assemblages occurring in arid zone streams: a multimetric index (MMI) and an O/E index of taxonomic completeness. Our overall goal was to advance our understanding of the factors that affect performance and interpretation of biological indices. Our specific objectives were to (1) develop biological indices that are insensitive to natural environmental gradients, (2) develop a general method to determine if the biological potential of an assessed site is adequately represented by the population of reference sites, (3) develop a robust method to select metrics for inclusion in MMIs that ensures maximum independence of metrics, and (4) determine if a fundamental sample property (the evenness of taxa counts within a sample) affects index performance. Random Forest modeling revealed that both individual metrics and taxa composition were strongly associated with natural environmental heterogeneity, which meant both the MMI and O/E index needed to be based on site-specific expectations. We produced a precise, responsive, and ecologically robust MMI by using principal components analysis to identify 7 statistically independent metrics from a list of 31 candidate assemblage-level metrics. However, the O/E index we developed was relatively imprecise compared with O/E indices developed for other regions. This imprecision may be the consequence of low predictability in local taxa composition associated with the relatively high spatial isolation of aquatic habitats within arid regions. We were also able to assess the likelihood that the biological potential of assessed sites were adequately characterized by the population of reference sites by developing and applying a multivariate, nearest-neighbor test that determined if an assessed site occurred within the environmental space of the reference site network. This approach is robust and applicable to all biological indices. We also demonstrate that the evenness of taxa counts within a sample is positively related to estimates of sample taxa richness and thus the scores of both indices. The relationship between richness and sample evenness can potentially compromise inferences regarding biological condition, and post hoc adjustments for the effects of evenness on index scores might be desirable. Further improvements in the performance and interpretation of biological indices will require simultaneous consideration of the effects of incomplete sampling on characterization of biological assemblages and the physical and biological factors that influence community assembly.     

Population genetics of polymorphism and divergence for diploid selection models with arbitrary dominance

We develop a Poisson random-field model of polymorphism and divergence that allows arbitrary dominance relations in a diploid context. This model provides a maximum-likelihood framework for estimating both selection and dominance parameters of new mutations using information on the frequency spectrum of sequence polymorphisms. This is the first DNA sequence-based estimator of the dominance parameter. Our model also leads to a likelihood-ratio test for distinguishing nongenic from genic selection; simulations indicate that this test is quite powerful when a large number of segregating sites are available. We also use simulations to explore the bias in selection parameter estimates caused by unacknowledged dominance relations. When inference is based on the frequency spectrum of polymorphisms, genic selection estimates of the selection parameter can be very strongly biased even for minor deviations from the genic selection model. Surprisingly, however, when inference is based on polymorphism and divergence (McDonald-Kreitman) data, genic selection estimates of the selection parameter are nearly unbiased, even for completely dominant or recessive mutations. Further, we find that weak overdominant selection can increase, rather than decrease, the substitution rate relative to levels of polymorphism. This nonintuitive result has major implications for the interpretation of several popular tests of neutrality.     

Bioclimatic discriminant capacity of terrestrial mammal faunas

A new method of environmental inference is presented. This method uses the climatic restriction index (CRI) for each mammal species, based on its geographical range within different climatic regimes, and a set of calculated summary indexes known as the bioclimatic spectrum. Analysis of 50 faunas throughout the world shows that terrestrial mammal communities are effective tools for accurate climatic inference at large spatial scale. The results also indicate that the use of entire mammalian fauna is the best inference system, followed by those based on separate groups such as Insectivora, Rodentia, micromammals and macromammals. Removing Chiroptera from the analysis does not change the results significantly. Bioclimatic analysis appears to be a good method for environmental interpretation. This new method ensures a high qualitative precision. It provides an empirical model for mammal community characterization that must be taken into account for palaeoclimatic reconstructions of continental environments.     

The landscape of mitochondrial DNA variation in human colorectal cancer on the background of phylogenetic knowledge

Recently, an increasing number of studies indicate that mutations in mitochondrial genome may contribute to cancer development or metastasis. Hence, it is important to determine whether the mitochondrial DNA might be a good, clinically applicable marker of cancer. This review describes hereditary as well as somatic mutations reported in mitochondrial DNA of colorectal cancer cells. We showed here that the entire mitochondrial genome mutational spectra are different in colorectal cancer and non-tumor cells. We also placed the described mutations on the phylogenetic context, which highlighted the recurrent problem of data quality. Therefore, the most important rules for adequately assessing the quality of mitochondrial DNA sequence analysis in cancer have been summarized. As follows from this review, neither the reliable spectrum of mtDNA somatic mutations nor the association between hereditary mutations and colorectal cancer risk have been resolved. This indicates that only high resolution studies on mtDNA variability, followed by a proper data interpretation employing phylogenetic knowledge may finally verify the utility of mtDNA sequence (if any) in clinical practice.     

The landscape of mitochondrial DNA variation in human colorectal cancer on the background of phylogenetic knowledge

Recently, an increasing number of studies indicate that mutations in mitochondrial genome may contribute to cancer development or metastasis. Hence, it is important to determine whether the mitochondrial DNA might be a good, clinically applicable marker of cancer. This review describes hereditary as well as somatic mutations reported in mitochondrial DNA of colorectal cancer cells. We showed here that the entire mitochondrial genome mutational spectra are different in colorectal cancer and non-tumor cells. We also placed the described mutations on the phylogenetic context, which highlighted the recurrent problem of data quality. Therefore, the most important rules for adequately assessing the quality of mitochondrial DNA sequence analysis in cancer have been summarized. As follows from this review, neither the reliable spectrum of mtDNA somatic mutations nor the association between hereditary mutations and colorectal cancer risk have been resolved. This indicates that only high resolution studies on mtDNA variability, followed by a proper data interpretation employing phylogenetic knowledge may finally verify the utility of mtDNA sequence (if any) in clinical practice.     

From inverse problems in mathematical physiology to quantitative differential diagnoses

The improved capacity to acquire quantitative data in a clinical setting has generally failed to improve outcomes in acutely ill patients, suggesting a need for advances in computer-supported data interpretation and decision making. In particular, the application of mathematical models of experimentally elucidated physiological mechanisms could augment the interpretation of quantitative, patient-specific information and help to better target therapy. Yet, such models are typically complex and nonlinear, a reality that often precludes the identification of unique parameters and states of the model that best represent available data. Hypothesizing that this non-uniqueness can convey useful information, we implemented a simplified simulation of a common differential diagnostic process (hypotension in an acute care setting), using a combination of a mathematical model of the cardiovascular system, a stochastic measurement model, and Bayesian inference techniques to quantify parameter and state uncertainty. The output of this procedure is a probability density function on the space of model parameters and initial conditions for a particular patient, based on prior population information together with patient-specific clinical observations. We show that multimodal posterior probability density functions arise naturally, even when unimodal and uninformative priors are used. The peaks of these densities correspond to clinically relevant differential diagnoses and can, in the simplified simulation setting, be constrained to a single diagnosis by assimilating additional observations from dynamical interventions (e.g., fluid challenge). We conclude that the ill-posedness of the inverse problem in quantitative physiology is not merely a technical obstacle, but rather reflects clinical reality and, when addressed adequately in the solution process, provides a novel link between mathematically described physiological knowledge and the clinical concept of differential diagnoses. We outline possible steps toward translating this computational approach to the bedside, to supplement today's evidence-based medicine with a quantitatively founded model-based medicine that integrates mechanistic knowledge with patient-specific information.     

Self-organization vs Watchmaker: stochastic gene expression and cell differentiation

Cell differentiation and organism development are traditionally described in deterministic terms of program and design, echoing a conventional clockwork perception of the cell on another scale. However, the current experimental reality of stochastic gene expression and cell plasticity is poorly consistent with the ideas of design, purpose and determinism, suggesting that the habit of classico-mechanistic interpretation of life phenomena may handicap our ability to adequately comprehend and model biological systems. An alternative conceptualization of cell differentiation and development is proposed where the developing organism is viewed as a dynamic self-organizing system of adaptive interacting agents. This alternative interpretation appears to be more consistent with the probabilistic nature of gene expression and the phenomena of cell plasticity, and is coterminous with the novel emerging image of the cell as a self-organizing molecular system. I suggest that stochasticity, as a principle of differentiation and adaptation, and self-organization, as a concept of emergence, have the potential to provide an interpretational framework that unites phenomena across different scales of biological organization, from molecules to societies.Edited by R.J. Sommer     

Interpretation of thermal perturbation spectra of proteins.

The thermal perturbation difference spectrum of reduced lysozyme has a long wave length extremum at 304 nm at pH 6.15 and a very small extremum at 306 nm at pH 1.5. These results differ from those of Leach & Smith (1972), which showed an extremum at 293 nm, the same as for model tryptophyl compounds. Our result may arise from a conformational difference between the two sample temperatures. The interpretation of thermal perturbation spectra of proteins is discussed. Contributions from thermally induced concentration differences, buried chromophores, and chromophores in crevices are considered in the interpretation of the thermal perturbation spectrum of bovine serum albumin. It is suggested that chromophores in pauci-aqueous crevices may appear buried toward thermal perturbation spectroscopy but accessible toward solvent perturbation and chemical reagents.     

In vitro ovine articular chondrocyte proliferation: experiments and modelling

This study focuses on analysis of in vitro cultures of chondrocytes from ovine articular cartilage. Isolated cells were seeded in Petri dishes, then expanded to confluence and phenotypically characterized by flow cytometry. The sigmoidal temporal profile of total counts was obtained by classic haemocytometry and corresponding cell size distributions were measured electronically using a Coulter Counter. A mathematical model recently proposed ( 1 ) was adopted for quantitative interpretation of these experimental data. The model is based on a 1‐D (that is, mass‐structured), single‐staged population balance approach capable of taking into account contact inhibition at confluence. The model’s parameters were determined by fitting measured total cell counts and size distributions. Model reliability was verified by predicting cell proliferation counts and corresponding size distributions at culture times longer than those used when tuning the model’s parameters. It was found that adoption of cell mass as the intrinsic characteristic of a growing chondrocyte population enables sigmoidal temporal profiles of total counts in the Petri dish, as well as cell size distributions at ‘balanced growth’, to be adequately predicted.     

Chlorophyll fluorescence emission spectrum inside a leaf.

Chlorophyll a fluorescence can be used as an early stress indicator. Fluorescence is also connected to photosynthesis so it can be proposed for global monitoring of vegetation status from a satellite platform. Nevertheless, the correct interpretation of fluorescence requires accurate physical models. The spectral shape of the leaf fluorescence free of any re-absorption effect plays a key role in the models and is difficult to measure. We present a vegetation fluorescence emission spectrum free of re-absorption based on a combination of measurements and modelling. The suggested spectrum takes into account the photosystem I and II spectra and their relative contribution to fluorescence. This emission spectrum is applicable to describe vegetation fluorescence in biospectroscopy and remote sensing.     

Mechanisms of the Effect of Dimephosphone on Synaptic Transmission in the Frog Neuromuscular Junction

We studied the influence of dimephosphone, an organophosphorus drug with a broad spectrum of therapeutic effects on the peripheral and central nervous systems, on postsynaptic end-plate currents (EPC) in the frog neuromuscular junction. Dimephosphone was demonstrated to decrease in a voltage-independent manner the EPC amplitude and to prolong the EPC decay. These effects are not related to inhibition of acetylcholinesterase. We propose a theoretical interpretation of the observed phenomena based on the model of blockade of an open ion channel of the acetylcholine receptor and conclude that postsynaptic receptors are one of the most probable targets for the action of dimephosphone.