Farm‐scale dispersal of Bactericera cockerelli in potato crops measured using Bt mark‐capture techniques

Natural populations of Bactericera cockerelli (Sulc) (Hemiptera: Triozidae), also known as tomato/potato psyllid, were marked in potato [Solanum tuberosum L. (Solanaceae)] crops using Bacillus thuringiensis Berliner (Bt) to investigate the impact of dispersal on crop infestation and management of potential insecticide resistance in New Zealand. The technique was adapted from previous studies that used conventional spray applications of Bt to mark Phthorimaea operculella (Zeller) (Lepidoptera: Gelechiidae), and identified marked individuals with selective microbiological assays and identification of characteristic crystal inclusions. Initially, marking rates of B. cockerelli were improved by using ultra‐low volume applications of undiluted Bt, but this result was not consistent. Several other pests and natural enemies were also marked. In mark‐capture studies, marked B. cockerelli were captured over 3 days on yellow sticky traps in small trap plots of potatoes at 60, 120, 180, 250, and 350 m from the sprayed crop. Bactericera cockerelli flight activity occurred throughout daylight hours with evidence of bimodal diurnal peaks. Significantly greater numbers of B. cockerelli were captured in downwind traps. The combined dispersal curve derived from two mark‐capture experiments estimated a mean dispersal distance for B. cockerelli of 100 m in 3 days and indicated that 10% of the population dispersed further than ca. 250 m. Over the period of a growing season, this level of dispersal suggests that B. cockerelli can disperse throughout a vegetable‐growing region, with implications for crop infestation and management of potential insecticide resistance.     

Predicting the timing of maturational spurts in skeletal age

Measures of maturity provide windows into the timing and tempo of childhood growth and maturation. Delayed maturation in a single child, or systemically in a population, can result from either genetic or environmental factors. In terms of the skeleton, delayed maturation may result in short stature or indicate another underlying issue. Thus, prediction of the timing of a maturational spurt is often desirable in order to determine the likelihood that a child will catch up to their chronological age peers. Serial data from the Fels Longitudinal Study were used to predict future skeletal age conditional on current skeletal age and to predict the timing of maturational spurts. For children who were delayed relative to their chronological age peers, the likelihood of catch‐up maturation increased through the average age of onset of puberty and decreased prior to the average age of peak height velocity. For boys, the probability of an imminent maturational spurt was higher for those who were less mature. For girls aged 11 to 13 years, however, this probability was higher for those who were more mature, potentially indicating the presence of a skeletal maturation plateau between multiple spurts. The prediction model, available on the web, is most relevant to children of European ancestry living in the Midwestern US. Our model may also provide insight into the tempo of maturation for children in other populations, but must be applied with caution if those populations are known to have high burdens of environmental stressors not typical of the Midwestern US. Am J Phys Anthropol, 2013. © 2012 Wiley Periodicals, Inc.     

Molecular systematics of pinniped hookworms (Nematoda: Uncinaria): species delimitation,host associations and host-induced morphometric variation

Hookworms of the genus Uncinaria have been widely reported from juvenile pinnipeds, however investigations of their systematics has been limited, with only two species described, Uncinaria lucasi from northern fur seals (Callorhinus ursinus) and Uncinaria hamiltoni from South American sea lions (Otaria flavescens). Hookworms were sampled from these hosts and seven additional species including Steller sea lions (Eumetopias jubatus), California sea lions (Zalophus californianus), South American fur seals (Arctocephalus australis), Australian fur seals (Arctocephalus pusillus), New Zealand sea lions (Phocarctos hookeri), southern elephant seals (Mirounga leonina), and the Mediterranean monk seal (Monachus monachus). One hundred and thirteen individual hookworms, including an outgroup species, were sequenced for four genes representing two loci (nuclear ribosomal DNA and mitochondrial DNA). Phylogenetic analyses of these sequences recovered seven independent evolutionary lineages or species, including the described species and five undescribed species. The molecular evidence shows that U. lucasi parasitises both C. ursinus and E. jubatus, whereas U. hamiltoni parasitises O. flavescens and A. australis. The five undescribed hookworm species were each associated with single host species (Z. californianus, A. pusillus, P. hookeri, M. leonina and M. monachus). For parasites of otarids, patterns of Uncinaria host-sharing and phylogenetic relationships had a strong biogeographic component with separate clades of parasites from northern versus southern hemisphere hosts. Comparison of phylogenies for these hookworms and their hosts suggests that the association of U. lucasi with northern fur seals results from a host-switch from Steller sea lions. Morphometric data for U. lucasi shows marked host-associated size differences for both sexes, with U. lucasi individuals from E. jubatus significantly larger. This result suggests that adult growth of U. lucasi is reduced within the host species representing the more recent host–parasite association. Intraspecific host-induced size differences are inconsistent with the exclusive use of morphometrics to delimit and diagnose species of Uncinaria from pinnipeds.     

Design and synthesis of 1-aryl-5-anilinoindazoles as c-Jun N-terminal kinase inhibitors

Starting from pyrazole HTS hit (1), a series of 1-aryl-1H-indazoles have been synthesized as JNK3 inhibitors with moderate selectivity against JNK1. SAR studies led to the synthesis of 5r as double digital nanomolar JNK3 inhibitor with good in vivo exposure.     

Hydroxyquinoline-derived compounds and analoguing of selective Mcl-1 inhibitors using a functional biomarker

Anti-apoptotic Bcl-2 family proteins are important oncology therapeutic targets. To date, BH3 mimetics that abrogate anti-apoptotic activity have largely been directed at Bcl-2 and/or Bcl-xL. One observed mechanism of resistance to these inhibitors is increased Mcl-1 levels in cells exposed to such therapeutics. For this reason, and because Mcl-1 is important in the onset of lymphoid, myeloid, and other cancers, it has become a target of great interest. However, small molecule inhibitors displaying potency and selectivity for Mcl-1 are lacking. Identifying such compounds has been challenging due to difficulties in translating the target selectivity observed at the biochemical level to the cellular level. Herein we report the results of an HTS strategy coupled with directed hit optimization. Compounds identified have selective Mcl-1 inhibitory activity with greater than 100-fold reduced affinity for Bcl-xL. The selectivity of these compounds at the cellular level was validated using BH3 profiling, a novel personalized diagnostic approach. This assay provides an important functional biomarker that allows for the characterization of cells based upon their dependencies on various anti-apoptotic Bcl-2 proteins. We demonstrate that cells dependent on Mcl-1 or Bcl-2/Bcl-xL for survival are commensurately responsive to compounds that genuinely target those proteins. The identification of compound 9 with uniquely validated and selective Mcl-1 inhibitory activity provides a valuable tool to those studying the intrinsic apoptosis pathway and highlights an important approach in the development of a first-in-class cancer therapeutic.     

Advantages of nonlinear mixed models for fitting avian growth curves

Our understanding of avian growth rates can benefit from the use of two statistical approaches that explicitly model the sources of intraspecific variation. First, random effects can evaluate whether there are consistent differences between individuals and groups of siblings within a population, and also account for any lack of statistical independence among data points. Second, nonlinear fixed‐effect functions can be extended to test specific biological hypotheses of interest, such as for differences between groups or populations. We illustrate the advantages of these methods by using nonlinear mixed models to study variation in the growth trajectories of nestling orange‐crowned warblers Oreothylpis celata. Specifically, we quantify the sources of variation within populations, analyze the effects of asynchronous hatching, and test for a difference in the growth rates of populations in Alaska and California, which are at the northern and southern limits of the species’ breeding distribution. We found that growth rates did not consistently vary between nests and individuals within populations and were not affected by asynchronous hatching, but were higher in Alaska than in California. Our extensions of traditional methods allowed us to accurately quantify this difference between populations, which is consistent with life history theory but has rarely been demonstrated in previous comparisons of intraspecific passerine populations. The methods we present can be applied to any taxonomic group and adjusted to fit any nonlinear function, and we provide code and implementation advice to facilitate the use of this analytical framework in future studies.     

Effects of an Ecosystem Engineer on Belowground Movement of Microarthropods

Ecosystem engineers affect other species by changing physical environments. Such changes may influence movement of organisms, particularly belowground where soil permeability can restrict dispersal. We investigated whether earthworms, iconic ecosystem engineers, influence microarthropod movement. Our experiment tested whether movement is affected by tunnels (i.e., burrows), earthworm excreta (mucus, castings), or earthworms themselves. Earthworm burrows form tunnel networks that may facilitate movement. This effect may be enhanced by excreta, which could provide resources for microarthropods moving along the network. Earthworms may also promote movement via phoresy. Conversely, negative effects could occur if earthworms alter predator-prey relationships or change competitive interactions between microarthropods. We used microcosms consisting of a box connecting a “source” container in which microarthropods were present and a “destination” container filled with autoclaved soil. Treatments were set up within the boxes, which also contained autoclaved soil, as follows: 1) control with no burrows; 2) artificial burrows with no excreta; 3) abandoned burrows with excreta but no earthworms; and 4) earthworms (Lumbricus rubellus) present in burrows. Half of the replicates were sampled once after eight days, while the other half were sampled repeatedly to examine movement over time. Rather than performing classical pairwise comparisons to test our hypotheses, we used AIC_c to assess support for three competing models (presence of tunnels, excreta, and earthworms). More individuals of Collembola, Mesostigmata, and all microarthropods together dispersed when tunnels were present. Models that included excreta and earthworms were less well supported. Total numbers of dispersing Oribatida and Prostigmata+Astigmata were not well explained by any models tested. Further research is needed to examine the impact of soil structure and ecosystem engineering on movement belowground, as the substantial increase in movement of some microarthropods when corridors were present suggests these factors can strongly affect colonization and community assembly.     

Evaluation of a Model for Glycemic Prediction in Critically Ill Surgical Patients

We evaluated a neural network model for prediction of glucose in critically ill trauma and post-operative cardiothoracic surgical patients. A prospective, feasibility trial evaluating a continuous glucose-monitoring device was performed. After institutional review board approval, clinical data from all consenting surgical intensive care unit patients were converted to an electronic format using novel software. This data was utilized to develop and train a neural network model for real-time prediction of serum glucose concentration implementing a prediction horizon of 75 minutes. Glycemic data from 19 patients were used to “train” the neural network model. Subsequent real-time simulated testing was performed in 5 patients to whom the neural network model was naive. Performance of the model was evaluated by calculating the mean absolute difference percent (MAD%), Clarke Error Grid Analysis, and calculation of the percent of hypoglycemic (≤70 mg/dL), normoglycemic (>70 and <150 mg/dL), and hyperglycemic (≥150 mg/dL) values accurately predicted by the model; 9,405 data points were analyzed. The models successfully predicted trends in glucose in the 5 test patients. Clark Error Grid Analysis indicated that 100.0% of predictions were clinically acceptable with 87.3% and 12.7% of predicted values falling within regions A and B of the error grid respectively. Overall model error (MAD%) was 9.0% with respect to actual continuous glucose modeling data. Our model successfully predicted 96.7% and 53.6% of the normo- and hyperglycemic values respectively. No hypoglycemic events occurred in these patients. Use of neural network models for real-time prediction of glucose in the surgical intensive care unit setting offers healthcare providers potentially useful information which could facilitate optimization of glycemic control, patient safety, and improved care. Similar models can be implemented across a wider scale of biomedical variables to offer real-time optimization, training, and adaptation that increase predictive accuracy and performance of therapies.