Systematics within Gyps vultures: a clade at risk

Background  

Populations of the Oriental White-backed Vulture (Gyps bengalensis) have declined by over 95% within the past decade. This decline is largely due to incidental consumption of the non-steroidal anti-inflammatory veterinary pharmaceutical diclofenac, commonly used to treat domestic livestock. The conservation status of other Gyps vultures in southern Asia is also of immediate concern, given the lack of knowledge regarding status of their populations and the continuing existence of taxonomic uncertainties. In this study, we assess phylogenetic relationships for all recognized species and the majority of subspecies within the genus Gyps. The continuing veterinary use of diclofenac is an unknown but potential risk to related species with similar feeding habits to Gyps bengalensis. Therefore, an accurate assessment of the phylogenetic relationships among Gyps vultures should aid in their conservation by clarifying taxonomic uncertainties, and enabling inference of their respective relatedness to susceptible G. bengalensis.     

Patterns of divergence during evolution of alpha 1-proteinase inhibitors in mammals

alpha 1-Proteinase inhibitor (alpha 1-PI), a member of the serine proteinase inhibitor superfamily, has a primary role in controlling neutrophil elastase activity within the mammalian circulation. Several studies have indicated that the reactive center region of alpha 1-PI, the amino acid sequence of which is critical to recognition of and binding to target proteinases, is highly divergent within and among species. This appears to be a consequence of accelerated rates of evolution that may have been driven by positive Darwinian selection. In order to examine this and other features of alpha 1-PI evolution in more detail, we have isolated and sequenced cDNAs representing alpha 1- PI mRNAs of the mouse species Mus saxicola and Mus minutoides and have compared these with a number of other mammalian alpha 1-PI mRNAs. Relative to other mammalian mRNAs, the extent of nonsynonymous substitution is generally high throughout the alpha 1-PI mRNA molecule, indicating greater overall rates of amino acid substitution. Within and among mouse species, the 5'-half of the mRNA, but not the 3'-half, has been homogenized by concerted evolution. Finally, the reactive center is under diversifying or positive Darwinian selection in murid rodents (rats, mice) and guinea pigs yet is under purifying selection in primates and artiodactyls. The significance of these findings to alpha 1-PI function and the possible selective forces driving evolution of serpins in general are discussed.      

Mitochondrial DNA polymorphisms in subterranean mole-rats of the Spalax ehrenbergi superspecies in Israel, and its peripheral isolates

Patterns of mitochondrial DNA (mtDNA) variation were examined in 133 mole-rats constituting all four chromosomal species (2n = 52, 2n = 54, 2n = 58, and 2n = 60) of the Spalax ehrenbergi superspecies in Israel, as well as the peripheral isolates of 2n = 60. In the main range of the complex, a total of 28 mtDNA haplotypes were found in 64 mole-rats, with most haplotypes being unique to either a single chromosomal species or population. mtDNA divergence increased from low to high diploid number in a north-to-south direction in Israel. Overall levels of mtDNA diversity were unexpectedly the highest in the 2n = 60, the youngest species of the complex. The mtDNA haplotypes can be separated into two major groups, 2n = 52-54 and 2n = 58-60, and a phylogenetic analysis for each group revealed evidence of a few haplotypes not sorted by diploid number. The overall patterns of mtDNA divergence seen within and among the four chromosomal species are consistent with the parapatric mode of speciation as suggested from previous studies of allozyme and DNA hybridization. In a separate data set the patterns of mtDNA variation were examined across the main geographic range and across peripheral semi-isolates and isolates of the 2n = 60 chromosomal species. Fifteen haplotypes were found in 69 mole-rats. High levels of mtDNA diversity characterized the main range, semi-isolated, and even some desert isolated populations. The peripheral isolates contain much mtDNA diversity, including novel haplotypes.      

Risk assessment for quantitative responses using a mixture model

A problem that frequently occurs in biological experiments with laboratory animals is that some subjects are less susceptible to the treatment than others. A mixture model has traditionally been proposed to describe the distribution of responses in treatment groups for such experiments. Using a mixture dose-response model, we derive an upper confidence limit on additional risk, defined as the excess risk over the background risk due to an added dose. Our focus will be on experiments with continuous responses for which risk is the probability of an adverse effect defined as an event that is extremely rare in controls. The asymptotic distribution of the likelihood ratio statistic is used to obtain the upper confidence limit on additional risk. The method can also be used to derive a benchmark dose corresponding to a specified level of increased risk. The EM algorithm is utilized to find the maximum likelihood estimates of model parameters and an extension of the algorithm is proposed to derive the estimates when the model is subject to a specified level of added risk. An example is used to demonstrate the results, and it is shown that by using the mixture model a more accurate measure of added risk is obtained.     

Phylogenetic utility of the nuclear gene arginine decarboxylase: an example from Brassicaceae

Arginine decarboxylase (ADC) is an important enzyme in the production of putrescine and polyamines in plants. It is encoded by a single or low-copy nuclear gene that lacks introns in sequences studied to date. The rate of Adc amino acid sequence evolution is similar to that of ndhF for the angiosperm family studied. Highly conserved regions provide several target sites for PCR priming and sequencing and aid in nucleotide and amino acid sequence alignment across a range of taxonomic levels, while a variable region provides an increased number of potentially informative characters relative to ndhF for the taxa surveyed. The utility of the Adc gene in plant molecular systematic studies is demonstrated by analysis of its partial nucleotide sequences obtained from 13 representatives of Brassicaceae and 3 outgroup taxa, 2 from the mustard oil clade (order Capparales) and 1 from the related order Malvales. Two copies of the Adc gene, Adc1 and Adc2, are found in all members of the Brassicaceae studied to data except the basal genus Aethionema. The resulting Adc gene tree provides robust phylogenetic data regarding relationships within the complex mustard family, as well as independent support for proposed tribal realignments based on other molecular data sets such as those from chloroplast DNA.      

Determination of Sample Sizes for Demonstrating Efficacy of Radiation Countermeasures

Summary .  In response to the ever increasing threat of radiological and nuclear terrorism, active development of nontoxic new drugs and other countermeasures to protect against and/or mitigate adverse health effects of radiation is ongoing. Although the classical LD₅₀ study used for many decades as a first step in preclinical toxicity testing of new drugs has been largely replaced by experiments that use fewer animals, the need to evaluate the radioprotective efficacy of new drugs necessitates the conduct of traditional LD₅₀ comparative studies ( FDA, 2002 ,  Federal Register   67, 37988–37998). There is, however, no readily available method to determine the number of animals needed for establishing efficacy in these comparative potency studies. This article presents a sample-size formula based on Student's  t  for comparative potency testing. It is motivated by the U.S. Food and Drug Administration's (FDA's) requirements for robust efficacy data in the testing of response modifiers in total body irradiation experiments where human studies are not ethical or feasible. Monte Carlo simulation demonstrated the formula's performance for Student's  t , Wald, and likelihood ratio tests in both logistic and probit models. Importantly, the results showed clear potential for justifying the use of substantially fewer animals than are customarily used in these studies. The present article may thus initiate a dialogue among researchers who use animals for radioprotection survival studies, institutional animal care and use committees, and drug regulatory bodies to reach a consensus on the number of animals needed to achieve statistically robust results for demonstrating efficacy of radioprotective drugs.     

Multiplicity-adjusted inferences in risk assessment: benchmark analysis with quantal response data

A primary objective in quantitative risk or safety assessment is characterization of the severity and likelihood of an adverse effect caused by a chemical toxin or pharmaceutical agent. In many cases data are not available at low doses or low exposures to the agent, and inferences at those doses must be based on the high-dose data. A modern method for making low-dose inferences is known as benchmark analysis, where attention centers on the dose at which a fixed benchmark level of risk is achieved. Both upper confidence limits on the risk and lower confidence limits on the "benchmark dose" are of interest. In practice, a number of possible benchmark risks may be under study; if so, corrections must be applied to adjust the limits for multiplicity. In this short note, we discuss approaches for doing so with quantal response data.     

Classification methods for the development of genomic signatures from high-dimensional data

Personalized medicine is defined by the use of genomic signatures of patients to assign effective therapies. We present Classification by Ensembles from Random Partitions (CERP) for class prediction and apply CERP to genomic data on leukemia patients and to genomic data with several clinical variables on breast cancer patients. CERP performs consistently well compared to the other classification algorithms. The predictive accuracy can be improved by adding some relevant clinical/histopathological measurements to the genomic data.