Early oviposition experience affects patch residence time in a foraging parasitoid

Parasitoids learn olfactory and visual cues that are associated with their hosts, and use these cues to forage more efficiently. Classical conditioning theory predicts that encounters with high-quality hosts will lead to better learning of host-associated cues than encounters with low-quality hosts. We tested this prediction in a two-phase laboratory experiment with the parasitoid Trichogramma thalense Pinto & Oatman (Hymenoptera: Trichogrammatidae) and the host Anagasta kuehniella Zeller (Lepidoptera: Pyralidae).Host quality during the first exposure to hosts affected later foraging behavior for some experimental treatments, as predicted. We used a learning model, followed by patch-time optimization, to interpret our findings. We first simulated the parasitoids' host encounters during the experiment, and predicted their estimate of patch quality after each encounter. We then used dynamic optimization to predict the parasitoids' optimal patch residence times. The model reproduces the trends of the experimental results.     

An in situ study of beta-glucosidase activity in normal and gaucher fibroblasts with fluorogenic probes

Beta-glucosidase activity was evaluated in situ by means of fluorogenic probes in normal human fibroblasts and fibroblasts from homozygous carriers of the Gaucher trait. Probe internalization, targeting to lysosomes and post-cleavage probe retention were the primary concerns. Internalization and targeting were attempted by in situ photosensitized labilization of lysosomal membranes, lysosomotropic detergents and the use of low density lipid (LDL) or the receptor ligand apolipoprotein E (ApoE). Post-cleavage increase of fluorescence with fluoresceinyl (bis) betaglucopyranoside was appreciably above the rather large pre-cleavage emission. In cells incubated overnight with nonylumbelliferylbetaglucoside (UG9) in the presence of bovine serum albumin and in the absence of ApoE, the probe was dealt with as a cytotoxic agent, accumulating in a paranuclear cap, most likely comprising elements of the endoplasmic reticulum (ER) and Golgi apparatus. Targeting of UG9 to lysosomes occurred within 1 to 3 h of preincubation in the presence of ApoE. There was some evidence of specificity, as Gaucher fibroblasts exhibited weaker cleavage of UG9 (by 50 per cent or more) compared to normal fibroblasts, but in the Gaucher cells there was some residual beta-glucosidase activity. Cleavage of UG9 was nearly totally suppressed in Gaucher cells treated with the beta-glucosidase inhibitor, conduritol B epoxide, for 24 h to 7 days. Suppression in the control fibroblasts was evident but to a lesser degree. The in situ method of fluorogenic assay established for beta-glucosidase deficiency, is in principle applicable to enzyme deficiencies in other lysosomal storage diseases, or to evaluate enhanced enzyme activity following gene therapy.     

Modeling optimal responses and fitness consequences in a changing Arctic

Animals must balance a series of costs and benefits while trying to maximize their fitness. For example, an individual may need to choose how much energy to allocate to reproduction versus growth, or how much time to spend on vigilance versus foraging. Their decisions depend on complex interactions between environmental conditions, behavioral plasticity, reproductive biology, and energetic demands. As animals respond to novel environmental conditions caused by climate change, the optimal decisions may shift. Stochastic dynamic programming provides a flexible modeling framework with which to explore these trade‐offs, but this method has not yet been used to study possible changes in optimal trade‐offs caused by climate change. We created a stochastic dynamic programming model capturing trade‐off decisions required by an individual adult female polar bear (Ursus maritimus) as well as the fitness consequences of her decisions. We predicted optimal foraging decisions throughout her lifetime as well as the energetic thresholds below which it is optimal for her to abandon a reproductive attempt. To explore the effects of climate change, we shortened the spring feeding period by up to 3 weeks, which led to predictions of riskier foraging behavior and higher reproductive thresholds. The resulting changes in fitness may be interpreted as a best‐case scenario, where bears adapt instantaneously and optimally to new environmental conditions. If the spring feeding period was reduced by 1 week, her expected fitness declined by 15%, and if reduced by 3 weeks, expected fitness declined by 68%. This demonstrates an effective way to explore a species' optimal response to a changing landscape of costs and benefits and highlights the fact that small annual effects can result in large cumulative changes in expected lifetime fitness.     

Selection of favorable alleles of genes controlling flowering and senescence improves malt barley quality

Molecular Breeding - Maize amylose is a type of high value-added starch used for medical, food, and chemical applications. Mutations in the starch branching enzyme (SBEIIb), with recessive ae...     

Density dependence, lifespan and the evolutionary dynamics of longevity

Longevity is a life-history trait that is shaped by natural selection. Evolution will shape mortality trajectories and lifespans, but until now the evolutionary analysis of longevity is based principally on a density-independent (Euler-Lotka) framework. The effects of density dependence on the evolution of lifespan and mortality remain largely unexplored. We investigate the influence of different population demographies on the evolution of longevity, and show how these can be linked to adaptive radiations. We present a range of models to explore the intraspecific and interspecific density effects on longevity and, consequently, diversification. We show how the magnitude, type, and timing of mutation can also affect fitness, invasion and diversification. We argue that fitness of alternative strategies under a range of different demographic structures leads to flat, as opposed to rugged, landscapes and that these flat fitness surfaces are important in the evolution of lifespan and senescence.     

Stochastic Dynamics of Interacting Haematopoietic Stem Cell Niche Lineages

Since we still know very little about stem cells in their natural environment, it is useful to explore their dynamics through modelling and simulation, as well as experimentally. Most models of stem cell systems are based on deterministic differential equations that ignore the natural heterogeneity of stem cell populations. This is not appropriate at the level of individual cells and niches, when randomness is more likely to affect dynamics. In this paper, we introduce a fast stochastic method for simulating a metapopulation of stem cell niche lineages, that is, many sub-populations that together form a heterogeneous metapopulation, over time. By selecting the common limiting timestep, our method ensures that the entire metapopulation is simulated synchronously. This is important, as it allows us to introduce interactions between separate niche lineages, which would otherwise be impossible. We expand our method to enable the coupling of many lineages into niche groups, where differentiated cells are pooled within each niche group. Using this method, we explore the dynamics of the haematopoietic system from a demand control system perspective. We find that coupling together niche lineages allows the organism to regulate blood cell numbers as closely as possible to the homeostatic optimum. Furthermore, coupled lineages respond better than uncoupled ones to random perturbations, here the loss of some myeloid cells. This could imply that it is advantageous for an organism to connect together its niche lineages into groups. Our results suggest that a potential fruitful empirical direction will be to understand how stem cell descendants communicate with the niche and how cancer may arise as a result of a failure of such communication.