Cytophotometric analyses of thalamic neuronal RNA in soman intoxicated rats

Quantitative azure B-RNA cytophotometry was used to monitor metabolic responses of individual neurons within the ventrobasal nuclear complex (VBC) and nucleus reticularis (NR) of the rat thalamus following administration of soman (0.5, 0.9 or 1.5 LD₅₀, sc). A dose-dependent depression in brain acetylcholinesterase (AChE) was evidenced. With respect to thalamic RNA responses, a complex pattern of RNA alterations was evidenced, with these two regions generally exhibiting opposite patterns of dose-related RNA changes. With sub-lethal dosages of soman, RNA accumulation was evidenced in the acetylcholine (ACh) mediated excitatory VBC region and RNA depletion in the ACh mediated inhibitory NR neurons. With a lethal dose, an opposite RNA response pattern observed in both thalamic regions. It is postulated that the observed RNA response pattern with sub-lethal dosages of soman is what one would anticipate with cholinergic brainstem reticular formation activation. The absence of such a response with lethal doses strongly suggests some disruption of functional excitatory cholinergic activity and perhaps also an impairment of inhibitory cholinergic synaptic activity.     

Statistical analyses of repeated measures in physiological research: a tutorial

Experimental designs involving repeated measurements on experimental units are widely used in physiological research. Often, relatively many consecutive observations on each experimental unit are involved and the data may be quite nonlinear. Yet evidently, one of the most commonly used statistical methods for dealing with such data sets in physiological research is the repeated-measurements ANOVA model. The problem herewith is that it is not well suited for data sets with many consecutive measurements; it does not deal with nonlinear features of the data, and the interpretability of the model may be low. The use of inappropriate statistical models increases the likelihood of drawing wrong conclusions. The aim of this article is to illustrate, for a reasonably typical repeated-measurements data set, how fundamental assumptions of the repeated-measurements ANOVA model are inappropriate and how researchers may benefit from adopting different modeling approaches using a variety of different kinds of models. We emphasize intuitive ideas rather than mathematical rigor. We illustrate how such models represent alternatives that 1) can have much higher interpretability, 2) are more likely to meet underlying assumptions, 3) provide better fitted models, and 4) are readily implemented in widely distributed software products.     

Statistical approach in search for optimal signal in simple olfactory neuronal models

Several models (concentration detectors and a flux detector) for coding of odor intensity in olfactory sensory neurons are investigated. Behavior of the system is described by different stochastic processes of binding the odorant molecules to the receptors and their activation. Characteristics how well the odorant concentration can be estimated from the knowledge of response, the number of activated neurons, are studied. The approach is based on the Fisher information and analogous measures. These measures of optimality are computed and applied to locate the odorant concentration which is most suitable for coding. The results are compared with the classical deterministic approach which judges the optimal odorant concentration via steepness of the input-output function.     

Statistical power in physical anthropology: a technical report

A statistical power analysis of The American Journal of Physical Anthropology (Volume 44, 1976) was conducted. Twenty-five articles, which included 3,304 major significance tests, constituted the final sample. Resultant power estimates of 0.38, 0.62, and 0.81, corresponding to small, medium, and large population effects respectively, were obtained. Although the medium effect size estimate falls short of the recommended 0.80 level, the statistical power of physical anthropological research fares well relative to several of the social scientific fields of inquiry.     

Cytophotometric analyses of mesencephalic reticular formation neuronal RNA in soman intoxicated rats

Quantitative azure B cytophotometry was used to monitor ribonucleic acid (RNA) responses of individual neurons within the nucleus cuneiformis (NC) and ventrotegmental nucleus (VTN) of the rat mesencephalic reticular formation following single subcutaneous soman (pinacolyl methylphosphonofluoridate) injections (0.5, 0.9 or 1.5 LD₅₀). The sub-lethal (0.5 LD₅₀) dosage of soman produced RNA accumulation in NC neurons, but VTN-RNA levels were not significantly altered. In contrast, both reticular nuclei exhibited prominent RNA depletion with higher soman dosages, the severity of which was greater with lethal (1.5 LD₅₀) than near-lethal (0.9 LD₅₀) dosages. These data indicate that metabolic correlates of enhanced activation of cholinergic reticular nuclei are present only with sub-lethal dosages, and that higher dosages produce characteristics of impaired activation of ascending cholinergic pathways. At present, mechanisms underlying soman-induced metabolic and neurologic deficits remain speculative.     

Mutant ubiquitin found in Alzheimer's disease causes neuritic beading of mitochondria in association with neuronal degeneration

A dinucleotide deletion in human ubiquitin (Ub) B messenger RNA leads to formation of polyubiquitin (UbB)+1, which has been implicated in neuronal cell death in Alzheimer's and other neurodegenerative diseases. Previous studies demonstrate that UbB+1 protein causes proteasome dysfunction. However, the molecular mechanism of UbB+1-mediated neuronal degeneration remains unknown. We now report that UbB+1 causes neuritic beading, impairment of mitochondrial movements, mitochondrial stress and neuronal degeneration in primary neurons. Transfection of UbB+1 induced a buildup of mitochondria in neurites and dysregulation of mitochondrial motor proteins, in particular, through detachment of P74, the dynein intermediate chain, from mitochondria and decreased mitochondria-microtubule interactions. Altered distribution of mitochondria was associated with activation of both the mitochondrial stress and p53 cell death pathways. These results support the hypothesis that neuritic clogging of mitochondria by UbB+1 triggers a cascade of events characterized by local activation of mitochondrial stress followed by global cell death. Furthermore, UbB+1 small interfering RNA efficiently blocked expression of UbB+1 protein, attenuated neuritic beading and preserved cellular morphology, suggesting a potential neuroprotective strategy for certain neurodegenerative disorders.     

Statistical distributions of test statistics used for quantitative trait association mapping in structured populations

Background

Spurious associations between single nucleotide polymorphisms and phenotypes are a major issue in genome-wide association studies and have led to underestimation of type 1 error rate and overestimation of the number of quantitative trait loci found. Many authors have investigated the influence of population structure on the robustness of methods by simulation. This paper is aimed at developing further the algebraic formalization of power and type 1 error rate for some of the classical statistical methods used: simple regression, two approximate methods of mixed models involving the effect of a single nucleotide polymorphism (SNP) and a random polygenic effect (GRAMMAR and FASTA) and the transmission/disequilibrium test for quantitative traits and nuclear families. Analytical formulae were derived using matrix algebra for the first and second moments of the statistical tests, assuming a true mixed model with a polygenic effect and SNP effects.

Results

The expectation and variance of the test statistics and their marginal expectations and variances according to the distribution of genotypes and estimators of variance components are given as a function of the relationship matrix and of the heritability of the polygenic effect. These formulae were used to compute type 1 error rate and power for any kind of relationship matrix between phenotyped and genotyped individuals for any level of heritability. For the regression method, type 1 error rate increased with the variability of relationships and with heritability, but decreased with the GRAMMAR method and was not affected with the FASTA and quantitative transmission/disequilibrium test methods.

Conclusions

The formulae can be easily used to provide the correct threshold of type 1 error rate and to calculate the power when designing experiments or data collection protocols. The results concerning the efficacy of each method agree with simulation results in the literature but were generalized in this work. The power of the GRAMMAR method was equal to the power of the FASTA method at the same type 1 error rate. The power of the quantitative transmission/disequilibrium test was low. In conclusion, the FASTA method, which is very close to the full mixed model, is recommended in association mapping studies.     

Spatial heterogeneity in a grassland community: Use of power law

A new regression analysis was proposed to evaluate the degree of spatial heterogeneity for individual species comprising a plant grassland community. The weighted average of the heterogeneity value of all the species comprising the community provides a measure of community-level heterogeneity. A field survey was carried out, as an example, in order to analyze the spatial heterogeneity of a pasture with grazing cows, using 100 quadrats 50 cm × 50 cm, each of which was divided into four smaller quadrats 25 cm × 25 cm, on a 50 m long line-transect. The frequency of occurrence for all the species in each small quadrat was recorded. The regression associated with the ratio of the theoretical and observed variances of occurence counts was used to analyse the frequency distribution of species in a pasture community. A good fit to the regression for the whole community was obtained. These results indicate that (i) each species in the example was distributed more heterogeneously than a random pattern; and (ii) the regression could well describe the spatial heterogeneity of the grassland plant community. In most of the observed species, spatial heterogeneity is often characterized by species-specific propagation traits and the architecture of plant bodies. Thus, the spatial patterns of a grassland community can be evaluated in detail by this power-law approach. This measure is suitable for field surveys and comparative studies of grassland communities, and for other plant communities that are generally short in height.     

A mathematical note on the fahraeuslindqvist effect in power law fluid

An axisymmetric flow of a power law fluid through circular tubes under constant pressure gradient with the flow parameters varying radially is analyzed theoretically. The main finding is that for the Fahraeus-Lindqvist (F-L) effect to occur, it is necessary to have at least one of the parametersK (consistency) andn (index) as a discontinuous function ofr in the absence of wall slip; and with slip condition the parameters could be continuous functions ofr under specific conditions. In both the cases the existence of more than one discontinuity cannot be ruled out. The results obtained are consistent with experimental findings of blood flow through narrow tubes.     

Reciprocal translocations in mice found in the vicinity of the Chernobyl nuclear power station

A study was made of the incidence of genetic damage to germ cells of male mice taken from or exposed within the thirty-kilometer zone of Chernobyl, the contaminated no-man's-land around the reactor that failed. At all contamination levels mouse spermatocytes exhibited reciprocal translocations, a relatively low frequency of which increased with increasing dose rate. Heterozygotes, with respect to reciprocal translocations (5%), were found among males exposed to enhanced radiation background as early embryos.     

Statistical issues in quality control of proteomic analyses: good experimental design and planning

Quality control is becoming increasingly important in proteomic investigations as experiments become more multivariate and quantitative. Quality control applies to all stages of an investigation and statistics can play a key role. In this review, the role of statistical ideas in the design and planning of an investigation is described. This involves the design of unbiased experiments using key concepts from statistical experimental design, the understanding of the biological and analytical variation in a system using variance components analysis and the determination of a required sample size to perform a statistically powerful investigation. These concepts are described through simple examples and an example data set from a 2-D DIGE pilot experiment. Each of these concepts can prove useful in producing better and more reproducible data.     

Statistical analyses of developmental sequences: the craniofacial region in marsupial and placental mammals

Heterochrony is most often thought to involve changes in the rate of development or maturation (rate changes). However, heterochrony can also involve changes in the timing of specific developmental events relative to other events (sequence changes). Sequence changes have received much less attention than have changes in developmental rates, in part because few methods exist for comparing developmental sequences. Here, we present two methods to statistically evaluate developmental sequence changes. First, Kendall's coefficient of concordance (W) is used to quantify overall similarity of developmental sequences in two or more groups of organisms, and second, ANOVA is used to identify the individual events that differ most in their relative developmental timing. Computer simulation is used to control for the nonindependence of species. We examine the sequence of developmental events in the craniofacial region of marsupial and placental mammals. We conclude that the most important differences in development in the two clades relate to the relative sequence of development of the central nervous system and somatic elements of the craniofacial region. The rationale behind the methods and their limitations are discussed, and the results from this study are compared with a previous analysis.     

DNA analyses support the hypothesis that infanticide is adaptive in langur monkeys.

Although the killing of dependent infants by adult males is a widespread phenomenon among primates, its causes and consequences still remain hotly debated. According to the sexual selection hypothesis, infanticidal males will gain a reproductive advantage provided that only unrelated infants are killed and that the males increase their chances of siring the next infants. Alternatively, the social pathology hypothesis interprets infanticide as a result of crowded living conditions and, thus, as not providing any advantage. Based on DNA analyses of wild Hanuman langurs (Presbytis entellus) we present the first evidence that male attackers were not related to their infant victims. Furthermore, in all cases the presumed killers were the likely fathers of the subsequent infants. Our data, therefore, strongly support the sexual selection hypothesis interpreting infanticide as an evolved, adaptive male reproductive tactic.