Forecasting the potential distribution of Spodoptera exigua and S. littoralis (Lepidoptera,Noctuidae) in Iran

The beet armyworm, Spodoptera exigua (Hübner, 1808) and the Egyptian cotton leafworm, S. littoralis (Boisduval, 1833), are amongst the most notorious agricultural pest species in Iran. Spodoptera exigua is considered a serious pest of different crops, whereas S. littoralis is known as an important pest of cotton.In this paper, the potential distribution areas of these species in Iran and the important climatic factors affecting their distribution were predicted using the MaxEnt model and the ArcGIS. The results indicate that the main environmental variables contributing to S. exigua’s distribution were precipitation of the coldest quarter (bio19), average wind speed in April (wind4), and annual precipitation (bio12). Also, minimum temperature of the coldest month (bio6), mean temperature of coldest quarter (bio11), altitude and average wind speed in May (wind5) were dominant climatic factors that affected the potential distribution of S. littoralis. These species overlapped in most parts of coastal areas in the southern and northern parts of Iran, with an average overlapping range of 33.2%. Considering their preferred host plants in Iran, it is necessary to strengthen biosurveillance programes and management of these two species in their suitable areas to prevent further invasion, which endangers agricultural security.     

Selection for novel metabolic capabilities in Salmonella enterica

Bacteria are known to display extensive metabolic diversity and many studies have shown that they can use an extensive repertoire of small molecules as carbon‐ and energy sources. However, it is less clear to what extent a bacterium can expand its existing metabolic capabilities by acquiring mutations that, for example, rewire its metabolic pathways. To investigate this capability and potential for evolution of novel phenotypes, we sampled large populations of mutagenized Salmonella enterica to select very rare mutants that can grow on minimal media containing 124 low molecular weight compounds as sole carbon sources. We found mutants growing on 18 of these novel carbon sources, and identified the causal mutations that allowed growth for four of them. Mutations that relieve physiological constraints or increase expression of existing pathways were found to be important contributors to the novel phenotypes. For the remaining 14 novel phenotypes, whole genome sequencing of independent mutants and genetic analysis suggested that these novel metabolic phenotypes result from a combination of multiple mutations. This work, by virtue of identifying the genetic and mechanistic basis for new metabolic capabilities, sheds light on the properties of adaptive landscapes underlying the evolution of novel phenotypes.     

Extracellular vesicles derived from Echinococcus granulosus hydatid cyst fluid from patients: isolation,characterization and evaluation of immunomodulatory functions on T cells

Cystic echinococcosis is a chronic and complex zoonotic disease. The mechanisms underlying the parasite’s establishment, growth and persistence are not completely understood, and are thought be modulated by a crosstalk through extracellular vesicles. Here, EVs were isolated from the hydatid cyst fluid of patients with cystic echinococcosis and protoscolex culture supernatant. Proteomic analysis of these EVs revealed several parasite- and human-derived proteins. Very few studies have performed proteomic analysis of EVs isolated from HCF and PCS. Our proteomic analysis of the EVs derived from HCF and PCS facilitated identification of 1175 proteins, wherein 1026 and 38 proteins were exclusively identified in the EVs derived from HCF (HCF-EVs) and PCS (PCS-EVs), respectively, and 111 proteins were shared in both. The results of co-culture of PCS-EVs with murine peripheral blood mononuclear cells showed that PCS-EVs significantly regulated T lymphocyte functions in a dose-dependent manner. Collectively, our results provide valuable information on parasite survival strategies and new insights into the role of these EVs in the establishment and persistence of hydatid cysts.     

Minimizing model fitting objectives that contain spurious local minima by bootstrap restarting

Objective functions that arise when fitting nonlinear models often contain local minima that are of little significance except for their propensity to trap minimization algorithms. The standard methods for attempting to deal with this problem treat the objective function as fixed and employ stochastic minimization approaches in the hope of randomly jumping out of local minima. This article suggests a simple trick for performing such minimizations that can be employed in conjunction with most conventional nonstochastic fitting methods. The trick is to stochastically perturb the objective function by bootstrapping the data to be fit. Each bootstrap objective shares the large-scale structure of the original objective but has different small-scale structure. Minimizations of bootstrap objective functions are alternated with minimizations of the original objective function starting from the parameter values with which minimization of the previous bootstrap objective terminated. An example is presented, fitting a nonlinear population dynamic model to population dynamic data and including a comparison of the suggested method with simulated annealing. Convergence diagnostics are discussed.     

Estimating equations with nonignorably missing response data

Troxel, Lipsitz, and Brennan (1997, Biometrics 53, 857-869) considered parameter estimation from survey data with nonignorable nonresponse and proposed weighted estimating equations to remove the biases in the complete-case analysis that ignores missing observations. This paper suggests two alternative modifications for unbiased estimation of regression parameters when a binary outcome is potentially observed at successive time points. The weighting approach of Robins, Rotnitzky, and Zhao (1995, Journal of the American Statistical Association 90, 106-121) is also modified to obtain unbiased estimating functions. The suggested estimating functions are unbiased only when the missingness probability is correctly specified, and misspecification of the missingness model will result in biases in the estimates. Simulation studies are carried out to assess the performance of different methods when the covariate is binary or normal. For the simulation models used, the relative efficiency of the two new methods to the weighting methods is about 3.0 for the slope parameter and about 2.0 for the intercept parameter when the covariate is continuous and the missingness probability is correctly specified. All methods produce substantial biases in the estimates when the missingness model is misspecified or underspecified. Analysis of data from a medical survey illustrates the use and possible differences of these estimating functions.     

Serum-free cryopreservation of porcine hepatocytes

The use of porcine hepatocytes in xenotransplantation, bioartificial liver support or pharmacological approaches demands serum-free cryopreservation protocols yielding high quality, viable, functional hepatocytes. Here, primary porcine hepatocytes were frozen without serum in liquid nitrogen by the use of a computer-assisted freezing device. After thawing, more than 90% of the initial hepatocytes were lost, in part because of damage to genomic DNA. When cryoprotectants were used, the loss was lowered to 70% of the initial cell number; 90% of the remaining cells excluded trypan blue indicating a high degree of viability. Cells were seeded serum-free onto collagen-coated plastic dishes to determine proliferation and retainment of specific functions representing prominent features of hepatocytes in vivo. Whereas no cells adhered to the substratum effectively in conventional culture medium, the addition of conditioned medium derived from hepatic non-parenchymal cells improved attachment. Cells proliferated, retained hepatocyte-specific functions, such as urea production and cytochrome P450 activity, and expressed liver-specific genes to levels observed in non-cryopreserved hepatocytes. Thus, serum-free cryopreserved primary porcine hepatocytes may serve as a valid source of cells for downstream applications. The cells seem to function adequately when an appropriate environment is chosen for recovery after cryopreservation, an ultimate demand for the clinical application of human hepatocytes.     

Permanence of single-species stage-structured models

In this paper, we consider population survival by using single-species stage-structured models. As a criterion of population survival, we employ the mathematical notation of permanence. Permanence of stage-structured models has already been studied by Cushing (1998). We generalize his result of permanence, and obtain a condition which guarantees that population survives. The condition is applicable to a wide class of stage-structured models. In particular, we apply our results to the Neubert-Caswell model, which is a typical stage-structured model, and obtain a condition for population survival of the model.The research is partially supported by the Ministry of Education, Science and Culture, Japan, under Grant in Aid for Scientific Research (A) 13304006.     

A dynamic, architectural plant model simulating resource-dependent growth

BACKGROUND AND AIMS: Physiological and architectural plant models have originally been developed for different purposes and therefore have little in common, thus making combined applications difficult. There is, however, an increasing demand for crop models that simulate the genetic and resource-dependent variability of plant geometry and architecture, because man is increasingly able to transform plant production systems through combined genetic and environmental engineering. MODEL: GREENLAB is presented, a mathematical plant model that simulates interactions between plant structure and function. Dual-scale automaton is used to simulate plant organogenesis from germination to maturity on the basis of organogenetic growth cycles that have constant thermal time. Plant fresh biomass production is computed from transpiration, assuming transpiration efficiency to be constant and atmospheric demand to be the driving force, under non-limiting water supply. The fresh biomass is then distributed among expanding organs according to their relative demand. Demand for organ growth is estimated from allometric relationships (e.g. leaf surface to weight ratios) and kinetics of potential growth rate for each organ type. These are obtained through parameter optimization against empirical, morphological data sets by running the model in inverted mode. Potential growth rates are then used as estimates of relative sink strength in the model. These and other 'hidden' plant parameters are calibrated using the non-linear, least-square method. KEY RESULTS AND CONCLUSIONS: The model reproduced accurately the dynamics of plant growth, architecture and geometry of various annual and woody plants, enabling 3D visualization. It was also able to simulate the variability of leaf size on the plant and compensatory growth following pruning, as a result of internal competition for resources. The potential of the model's underlying concepts to predict the plant's phenotypic plasticity is discussed.     

The biological clock: the bodyguard of temporal homeostasis

In order for any organism to function properly, it is crucial that it be table to control the timing of its biological functions. An internal biological clock, located, in mammals, in the suprachiasmatic nucleus of the hypothalamus (SCN), therefore carefully guards this temporal homeostasis by delivering its message of time throughout the body. In view of the large variety of body functions (behavioral, physiological, and endocrine) as well as the large variety in their preferred time of main activity along the light:dark cycle, it seems logical to envision different means of time distribution by the SCN. In the present review, we propose that even though it presents a unimodal circadian rhythm of general electrical and metabolic activity, the SCN seems to use several sorts of output connections that are active at different times along the light: dark cycle to control the rhythmic expression of different body functions. Although the SCN is suggested to use diffusion of synchronizing factors in the rhythmic control of behavioral functions, it also needs neuronal connections for the control of endocrine functions. The distribution of the time-of-day message to neuroendocrine systems is either directly onto endocrine neurons or via intermediate neurons located in specific SCN targets. In addition, the SCN uses its connections with the autonomic nervous system for spreading its time-of-day message, either by setting the sensitivity of endocrine glands (i.e., thyroid, adrenal, ovary) or by directly controlling an endocrine output (i.e., melatonin synthesis). Moreover, the SCN seems to use different neurotransmitters released at different times along the light: dark cycle for each of the different connection types presented. Clearly, the temporal homeostasis of endocrine functions results from a diverse set of biological clock outputs.