Components of metabolic syndrome predicting diabetes: no role of inflammation or dyslipidemia

Objective: The diagnostic criteria and the clinical usefulness of the metabolic syndrome (MetSy) are currently questioned. The objective was to describe the structure of MetSy and to evaluate its components for prediction of diabetes type 2 (T2DM). Research Methods and Procedures: This was a case‐referent study nested within a population‐based health survey. Among 33,336 participants, we identified 177 initially non‐diabetic individuals who developed T2DM after 0.1 to 10.5 years (mean, 5.4 years), and, for each diabetes case, two referents matched for sex, age, and year of health survey. Baseline variables included oral glucose tolerance test, BMI, blood pressure, blood lipids, adipokines, inflammatory markers, insulin resistance, and β‐cell function. Exploratory and confirmative factor analyses were applied to hypothesize the structure of the MetSy. The prediction of T2DM by the different factors was evaluated by multivariate logistic regression analysis. Results: A hypothetical five‐factor model of intercorrelated composite factors was generated. The inflammation, dyslipidemia, and blood pressure factors were predicitive only in univariate analysis. In multivariable analyses, two factors independently and significantly predicted T2DM: an obesity/insulin resistance factor and a glycemia factor. The composite factors did not improve the prediction of T2DM compared with single variables. Among the original variables, fasting glucose, proinsulin, BMI, and blood pressure values were predictive of T2DM. Discussion: Our data support the concept of a MetSy, and we propose five separate clusters of components. The inflammation and dyslipidemia factors were not independently associated with diabetes risk. In contrast, obesity and accompanying insulin resistance and β‐cell decompensation seem to be two core perturbations promoting and predicting progression to T2DM.     

Autophagy and cell-death proteases in plants: two wheels of a funeral cart

Apoptosis is an evolutionarily young cell-death strategy evolved to disassemble animal cells through the action of the caspase family of proteases and phagocytic clearance. This strategy does not work in plants, which instead feature a phylogenetically older autophagic programmed cell death (PCD), as a bona fide type of cellular suicide. Recent work has begun to address the mechanistic roles for autophagic and proteolytic components, as well as their possible cooperation in plant PCD. A recent study has shown autophagosomal localization of a key cell-death proteolytic activity at the early stage of plant PCD. Here we focus on the relationship between autophagic and proteoloytic components in plant PCD at the cellular and organismal levels.     

Butterfly–host plant synchrony determines patterns of host use across years and regions

Variation in the degree of synchrony among host plants and herbivores can disrupt or intensify species interactions, alter the strength of natural selection on traits associated with phenological timing, and drive novel host plant associations. We used field observations from three regions during four seasons to examine how timing of the butterfly herbivore Anthocharis cardamines relative to six host plant species (Arabis hirsuta, Cardamine pratensis, Arabis glabra, Arabidopsis thaliana, Thlaspi caerulescens and Capsella bursa‐pastoris) influenced host species use and the choice of host plant individuals within populations. Butterflies laid a larger fraction of their eggs on species that were closer to the butterfly's preferred stage of development than on other host species. Within host plant populations, butterflies showed a stronger preference for individuals with a late phenology when plants within the population were on average more developed at the time of butterfly flight. Our results suggest that changes in synchrony between herbivores and their host plants are associated with changes in both host species use and the choice of host plant individuals differing in phenology within populations. This is likely to be an important mechanism generating variation in interaction intensities and trait selection in the wild, and therefore also relevant for understanding how anthropogenic induced changes, such as global warming, will influence natural communities.     

Diapause decision in the small tortoiseshell butterfly,Aglais urticae

Insects in temperate areas spend the inhospitable winter conditions in a resting stage known as diapause. In species that diapause in the larval or pupal stage, the decision whether to diapause or develop directly is customarily taken during the late instars, with long days (i.e., long light phases) and high temperatures promoting direct development. Among butterflies that overwinter as adults, data are rare and variable, but imply that the larval daylength conditions can affect the pathway decision. We studied the small tortoiseshell, Aglais urticae L. (Lepidoptera: Nymphalidae, Nymphalini), which is partially bivoltine from Central Scandinavia and southwards, and tested whether the pathway decision is taken in the larval or adult stage. We reared larvae under long‐day (L22:D2) or short‐day (L12:D12) photoperiods, and recorded the pathway taken by the eclosing adults by scoring their propensity to mate and produce eggs. We also tested whether the larval photoperiod influenced adult ability to diapause by assessing adult survival. The results clearly indicate that (1) there is no detectable effect of larval photoperiod treatment on the pathway decision taken by adults whether to enter diapause or to develop directly, (2) some individuals are obligately univoltine and insensitive to photoperiod during adulthood, whereas (3) other individuals can facultatively enter diapause or direct development, depending on the photoperiod experienced after adult eclosion.     

Transformation of nuclear and plastomic plant genomes by biolistic particle bombardment

Microprojectile bombardment is a powerful method for the transformation of various organisms and tissues. For plants, the biolistic approach is primarily used for transformation of cereals and other monocotyledons, as well as for dicotyledonous plants shown to be recalcitrant to Agrobacterium-based transformation of organellar genomes, and transformation of plant and algal chloroplasts has recently been reported. In this protocol paper we provide methods for nuclear and plastomic transformation of plants using the biolistic technique.     

A possible role for p190RhoGAP in PKCepsilon-induced morphological effects

We have previously shown that protein kinase C (PKC) epsilon induces neurite outgrowth via its regulatory domain. This is accompanied by PKC-induced stress fibre loss. Here, we show that the regulatory domain (RD) of PKCepsilon induces processes also in NIH-3T3 fibroblasts, similar to what has been observed with p190RhoGAP. This study also shows that p190RhoGAP induces neurite outgrowth in SK-N-BE(2) neuroblastoma cells. We therefore investigated whether p190RhoGAP may be downstream of PKCepsilon. We could detect a co-localization of p190RhoGAP and PKCepsilon at membrane ruffles and an increased association between the proteins in fibroblasts treated with 12-O-tetradecanoylphorbol-13-acetate (TPA). The association is also seen in neuroblastoma cells, and nerve growth factor (NGF) treatment of SH-SYSY/TrkA cells decreases the interaction. However, overexpressed PKCepsilon did not coprecipitate overexpressed p190RhoGAP in CHO cells, indicating that the proteins do not interact directly. This raises the possibility that p190RhoGAP is involved in mediating the morphological effects of PKCepsilon.     

Joint explorative analysis of neuroreceptor subsystems in the human brain: application to receptor-transporter correlation using PET data

Positron emission tomography (PET) has proved to be a highly successful technique in the qualitative and quantitative exploration of the human brain's neurotransmitter-receptor systems. In recent years, the number of PET radioligands, targeted to different neuroreceptor systems of the human brain, has increased considerably. This development paves the way for a simultaneous analysis of different receptor systems and subsystems in the same individual. The detailed exploration of the versatility of neuroreceptor systems requires novel technical approaches, capable of operating on huge parametric image datasets. An initial step of such explorative data processing and analysis should be the development of novel exploratory data-mining tools to gain insight into the "structure" of complex multi-individual, multi-receptor data sets. For practical reasons, a possible and feasible starting point of multi-receptor research can be the analysis of the pre- and post-synaptic binding sites of the same neurotransmitter. In the present study, we propose an unsupervised, unbiased data-mining tool for this task and demonstrate its usefulness by using quantitative receptor maps, obtained with positron emission tomography, from five healthy subjects on (pre-synaptic) serotonin transporters (5-HTT or SERT) and (post-synaptic) 5-HT(1A) receptors. Major components of the proposed technique include the projection of the input receptor maps to a feature space, the quasi-clustering and classification of projected data (neighbourhood formation), trans-individual analysis of neighbourhood properties (trajectory analysis), and the back-projection of the results of trajectory analysis to normal space (creation of multi-receptor maps). The resulting multi-receptor maps suggest that complex relationships and tendencies in the relationship between pre- and post-synaptic transporter-receptor systems can be revealed and classified by using this method. As an example, we demonstrate the regional correlation of the serotonin transporter-receptor systems. These parameter-specific multi-receptor maps can usefully guide the researchers in their endeavour to formulate models of multi-receptor interactions and changes in the human brain.     

Switching the mode of metabolism in the yeast Saccharomyces cerevisiae

The biochemistry of most metabolic pathways is conserved from bacteria to humans, although the control mechanisms are adapted to the needs of each cell type. Oxygen depletion commonly controls the switch from respiration to fermentation. However, Saccharomyces cerevisiae also controls that switch in response to the external glucose level. We have generated an S. cerevisiae strain in which glucose uptake is dependent on a chimeric hexose transporter mediating reduced sugar uptake. This strain shows a fully respiratory metabolism also at high glucose levels as seen for aerobic organisms, and switches to fermentation only when oxygen is lacking. These observations illustrate that manipulating a single step can alter the mode of metabolism. The novel yeast strain is an excellent tool to study the mechanisms underlying glucose-induced signal transduction.