Dynamics of Newly Established Elk Populations

Abstract: The dynamics of newly established elk (Cervus elaphus) populations can provide insights about maximum sustainable rates of reproduction, survival, and increase. However, data used to estimate rates of increase typically have been limited to counts and rarely have included complementary estimates of vital rates. Complexities of population dynamics cannot be understood without considering population processes as well as population states. We estimated pregnancy rates, survival rates, age ratios, and sex ratios for reintroduced elk at Theodore Roosevelt National Park, North Dakota, USA; combined vital rates in a population projection model; and compared model projections with observed elk numbers and population ratios. Pregnancy rates in January (early in the second trimester of pregnancy) averaged 54.1% (SE = 5.4%) for subadults and 91.0% (SE = 1.7%) for adults, and 91.6% of pregnancies resulted in recruitment at 8 months. Annual survival rates of adult females averaged 0.96 (95% CI = 0.94-0.98) with hunting included and 0.99 (95% CI = 0.97-0.99) with hunting excluded from calculations. Our fitted model explained 99.8% of past variation in population estimates and represents a useful new tool for short-term management planning. Although we found no evidence of temporal variation in vital rates, variation in population composition caused substantial variation in projected rates of increase (Λ = 1.20-1.36). Restoring documented hunter harvests and removals of elk by the National Park Service led to a potential rate of Λ = 1.26. Greater rates of increase substantiated elsewhere were within the expected range of chance variation, given our model and estimates of vital rates. Rates of increase realized by small elk populations are too variable to support inferences about habitat quality or density dependence.     

High-throughput sequencing of hair follicle development-related micrornas in cashmere goat at various fetal periods

Inner Mongolia cashmere goat marks a precious gerplasm genetic resource due to its excellent cashmere traits. Therefore, it is of crucial importance to investigate the cashmere development mechanism of cashmere goat and to search for the important cashmere growth-related candidate genes. Fetal skin samples at 10 different periods of cashmere goat were collected in this research. Moreover, high-throughput sequencing was conducted on RNA samples from side skin of cashmere goat fetuses collected at three critical periods of skin hair follicle initiation, growth and development (namely, 45, 55 and 65?days) after balanced mix in line with the previous research results. Meanwhile, 3 samples at corresponding periods were used as the biological duplications. Data regarding microRNA and mRNA expression in skin and hair follicles of cashmere goats at various fetal periods were obtained using the high-throughput sequencing method. The results indicated that microRNAs in the oar-let-7 and oar-miR-200 families in 55?days and 66?days of pregnancy samples had been notably up-regulated relative to those in 45?days of pregnancy samples. This revealed that they might be the critical microRNAs in hair follicle development.     

Enhancing ligand–protein binding in affinity thermoprecipitation: Elucidation of spacer effects

Copolymers of N‐isopropylacrylamide and N‐acryloyl amino acid spacers of varying chain length were synthesized. p‐Aminobenzamidine (PABA) was chemically linked to the pendant carboxyl groups of these polymers to obtain thermoprecipitating affinity polymers. The inhibition constant (K_i) of these polymers for trypsin decreased, i.e., the efficiency of PABA–trypsin binding increased with increase in the spacer chain length. The polymer to which PABA was linked through a spacer of five methylene groups exhibited eleven times lower K_i than that of the polymer containing PABA without a spacer. Investigations on model inhibitors N‐acyl‐p‐aminobenzamidines showed that this enhancement in trypsin binding by the polymers was due to the spacer as well as to microenvironmental effects. Recovery and specific activity of the trypsin recovered increased with the spacer chain length. Separation of trypsin from a mixture of trypsin and chymotrypsin was also enhanced with the spacer chain length. The inhibition constants of these affinity polymers were not adversely affected by the crowding effect. © 1999 John Wiley & Sons, Inc. Biotechnol Bioeng 64: 418–425, 1999.     

Study design and parameter estimability for spatial and temporal ecological models

The statistical tools available to ecologists are becoming increasingly sophisticated, allowing more complex, mechanistic models to be fit to ecological data. Such models have the potential to provide new insights into the processes underlying ecological patterns, but the inferences made are limited by the information in the data. Statistical nonestimability of model parameters due to insufficient information in the data is a problem too‐often ignored by ecologists employing complex models. Here, we show how a new statistical computing method called data cloning can be used to inform study design by assessing the estimability of parameters under different spatial and temporal scales of sampling. A case study of parasite transmission from farmed to wild salmon highlights that assessing the estimability of ecologically relevant parameters should be a key step when designing studies in which fitting complex mechanistic models is the end goal.     

Synthesis, protonation and electrochemical properties of trinuclear NiFe2 complexes Fe2(CO)6(μ3-S)2[Ni(Ph2PCH2)2NR] (R = n-Bu, Ph) with an internal pendant nitrogen base as a proton relay

Two trinuclear NiFe₂ complexes Fe₂(CO)₆(μ₃-S)₂[Ni(Ph₂PCH₂)₂NR] (R = n-Bu, 1; Ph, 2) containing an internal base were prepared as biomimetic models for the active sites of FeFe and NiFe hydrogenases. Treatment of complex Fe₂(CO)₆(μ₃-S)₂[Ni(Ph₂PCH₂)₂N(n-Bu)] (1) with HOTf gave an N-protonated complex [Fe₂(CO)₆(μ₃-S)₂{Ni(Ph₂PCH₂)₂NH(n-Bu)}][OTf] ([1H][OTf]). The structures of complexes 1, 2 and [1H][OTf] were determined by X-ray crystallography, which shows that the proton held by the N atom of [1H][OTf] lies in an equatorial position. Cyclic voltammograms of complexes 1 and [1H][OTf] were studied and compared with that of Fe₂(CO)₆(μ₃-S)₂[Ni(dppe)].     

Complex Segregation Analysis of Pedigrees from the Gilda Radner Familial Ovarian Cancer Registry Reveals Evidence for Mendelian Dominant Inheritance

Background

Familial component is estimated to account for about 10% of ovarian cancer. However, the mode of inheritance of ovarian cancer remains poorly understood. The goal of this study was to investigate the inheritance model that best fits the observed transmission pattern of ovarian cancer among 7669 members of 1919 pedigrees ascertained through probands from the Gilda Radner Familial Ovarian Cancer Registry at Roswell Park Cancer Institute, Buffalo, New York.

Methodology/Principal Findings

Using the Statistical Analysis for Genetic Epidemiology program, we carried out complex segregation analyses of ovarian cancer affection status by fitting different genetic hypothesis-based regressive multivariate logistic models. We evaluated the likelihood of sporadic, major gene, environmental, general, and six types of Mendelian models. Under each hypothesized model, we also estimated the susceptibility allele frequency, transmission probabilities for the susceptibility allele, baseline susceptibility and estimates of familial association. Comparisons between models were carried out using either maximum likelihood ratio test in the case of hierarchical models, or Akaike information criterion for non-nested models. When assessed against sporadic model without familial association, the model with both parent-offspring and sib-sib residual association could not be rejected. Likewise, the Mendelian dominant model that included familial residual association provided the best-fitting for the inheritance of ovarian cancer. The estimated disease allele frequency in the dominant model was 0.21.

Conclusions/Significance

This report provides support for a genetic role in susceptibility to ovarian cancer with a major autosomal dominant component. This model does not preclude the possibility of polygenic inheritance of combined effects of multiple low penetrance susceptibility alleles segregating dominantly.