Isolation and characterization of highly polymorphic microsatellite loci in the 2‐Spot Ladybird,Adalia bipunctata

Contrary to theoretical predictions, female 2‐spot ladybirds (Adalia bipunctata) mate many more times than necessary to maintain high fertilisation success and may gain through the acquisition of material or genetic benefits. In order to investigate this mating system in detail, microsatellite markers have been isolated using a modified enrichment technique. Thirty‐nine loci were successfully amplified by polymerase chain reaction (PCR), of which only two were monomorphic. Detailed characterization of ten loci revealed very high levels of polymorphism. These markers are likely to be invaluable tools with which to study population genetics and patterns of paternity in this species.     

Flood Risk Analysis Based on Information Diffusion Theory

Due to the fact that the flood data series of small drainage basins is relatively short, available data are often not sufficient for flood risk analysis. This presents the problem of risk analysis using very small data samples. One method that can be applied is to regard the available small samples as fuzzy information and optimize them using information diffusion technology to yield analytical results with greater reliability. In this article a risk analysis method based on information diffusion theory is applied to create a new flood risk analysis model. Application of the model is illustrated taking the Jinhuajiang and Qujiang drainage basins as examples. This is a new attempt at applying information diffusion theory in flood risk analysis. Computations based on this analytical flood risk model can yield an estimated flood damage value that is relatively accurate. This study indicates that the aforementioned model exhibits fairly stable analytical results, even when using a small set of sample data. The results also indicate that information diffusion technology is highly capable of extracting useful information and therefore improves system recognition accuracy. This method can be easily applied and the analytical results produced are easy to understand. Results are accurate enough to act as a guide in disaster situations.     

On the electron delocalization in cyclopropenylidenes - An experimental charge-density approach

The extent and nature of cyclic electron delocalization in free and coordinated cyclopropenylidene carbenes has been analyzed by combined experimental and theoretical charge-density studies. The significant asymmetry of the C-C bond lengths in substituted cyclopropenylidene carbenes was identified as cooperative effect which depends on contributions of both σ- and π-bonding. We show that analyses of (i) the topology of the Laplacian of the electron density distribution and (ii) the out-of-plane atomic quadrupole moments - the charge-density analogues of p_π occupation - allow to distinguish between the influence of σ- and π-electrons on cyclic electron delocalization. These studies hint for pronounced electron localization in the carbene lone pair region which dominates the electronic structure of free cyclopropenylidene carbenes and hinders the establishment of true aromaticity. We further investigated the electron donating/withdrawing ability of cyclopropenylidene ligands relative to N-heterocyclic carbenes. The experimental benchmark systems LCr(CO)₅ (L = 2,3-diphenylcyclopropenylidene and 1,2-dimethylimidazol-2-ylidene) show that the cyclopropenylidene ligand clearly displays the higher π-acceptor capability relative to N-heterocyclic carbenes.     

Can minimum convex polygon home ranges be used to draw biologically meaningful conclusions?

Many conclusions about mammalian ranging behaviour have been drawn based on minimum convex polygon (MCP) estimates of home range size, although several studies have revealed its unpredictable nature compared to that of the kernel density estimator. We investigated to what extent the choice of home range estimator affected the biological interpretation in comparative studies. We found no discrepancy when the question asked covered a wide range of taxa, as real and very large differences in range size were likely to have masked smaller differences due to the choice of home range estimator. However, when the question asked concerned within-species characteristics, the choice of home range estimator explained as much of the variation in range size as did the ecological variable in question. The implications for macro-ecological and intraspecific studies are discussed.     

Mass spectrometry techniques for imaging and detection of metallodrugs

Undoubtedly, metallomic approaches based on mass spectrometry have evolved into essential tools supporting the drug development of novel metal-based anticancer drugs. This article will comment on the state-of-the-art instrumentation and highlight some of the recent analytical advances beyond routine, especially focusing on the latest developments in inductively coupled plasma-mass spectrometry (ICP-MS). Mass spectrometry-based bioimaging and single-cell methods will be presented, paving the way to exciting investigations of metal-based anticancer drugs in heterogeneous and structurally, as well as functionally complex solid tumor tissues.     

An Arabidopsis lipid map reveals differences between tissues and dynamic changes throughout development

Mass spectrometry is the predominant analytical tool used in the field of plant lipidomics. However, there are many challenges associated with the mass spectrometric detection and identification of lipids because of the highly complex nature of plant lipids. Studies into lipid biosynthetic pathways, gene functions in lipid metabolism, lipid changes during plant growth and development, and the holistic examination of the role of plant lipids in environmental stress responses are often hindered. Here, we leveraged a robust pipeline that we previously established to extract and analyze lipid profiles of different tissues and developmental stages from the model plant Arabidopsis thaliana. We analyzed seven tissues at several different developmental stages and identified more than 200 lipids from each tissue analyzed. The data were used to create a web-accessible in silico lipid map that has been integrated into an electronic Fluorescent Pictograph (eFP) browser. This in silico library of Arabidopsis lipids allows the visualization and exploration of the distribution and changes of lipid levels across selected developmental stages. Furthermore, it provides information on the characteristic fragments of lipids and adducts observed in the mass spectrometer and their retention times, which can be used for lipid identification. The Arabidopsis tissue lipid map can be accessed at http://bar.utoronto.ca/efp_arabidopsis_lipid/cgi-bin/efpWeb.cgi .     

A comparative Proteomics Analysis Identified Differentially Expressed Proteins in Pancreatic Cancer–Associated Stellate Cell Small Extracellular Vesicles

Human pancreatic stellate cells (HPSCs) are an essential stromal component and mediators of pancreatic ductal adenocarcinoma (PDAC) progression. Small extracellular vesicles (sEVs) are membrane-enclosed nanoparticles involved in cell-to-cell communications and are released from stromal cells within PDAC. A detailed comparison of sEVs from normal pancreatic stellate cells (HPaStec) and from PDAC-associated stellate cells (HPSCs) remains a gap in our current knowledge regarding stellate cells and PDAC. We hypothesized there would be differences in sEVs secretion and protein expression that might contribute to PDAC biology. To test this hypothesis, we isolated sEVs using ultracentrifugation followed by characterization by electron microscopy and Nanoparticle Tracking Analysis. We report here our initial observations. First, HPSC cells derived from PDAC tumors secrete a higher volume of sEVs when compared to normal pancreatic stellate cells (HPaStec). Although our data revealed that both normal and tumor-derived sEVs demonstrated no significant biological effect on cancer cells, we observed efficient uptake of sEVs by both normal and cancer epithelial cells. Additionally, intact membrane-associated proteins on sEVs were essential for efficient uptake. We then compared sEV proteins isolated from HPSCs and HPaStecs cells using liquid chromatography–tandem mass spectrometry. Most of the 1481 protein groups identified were shared with the exosome database, ExoCarta. Eighty-seven protein groups were differentially expressed (selected by 2-fold difference and adjusted p value ≤0.05) between HPSC and HPaStec sEVs. Of note, HPSC sEVs contained dramatically more CSE1L (chromosome segregation 1–like protein), a described marker of poor prognosis in patients with pancreatic cancer. Based on our results, we have demonstrated unique populations of sEVs originating from stromal cells with PDAC and suggest that these are significant to cancer biology. Further studies should be undertaken to gain a deeper understanding that could drive novel therapy.     

Multiomic Metabolic Enrichment Network Analysis Reveals Metabolite–Protein Physical Interaction Subnetworks Altered in Cancer

Metabolism is recognized as an important driver of cancer progression and other complex diseases, but global metabolite profiling remains a challenge. Protein expression profiling is often a poor proxy since existing pathway enrichment models provide an incomplete mapping between the proteome and metabolism. To overcome these gaps, we introduce multiomic metabolic enrichment network analysis (MOMENTA), an integrative multiomic data analysis framework for more accurately deducing metabolic pathway changes from proteomics data alone in a gene set analysis context by leveraging protein interaction networks to extend annotated metabolic models. We apply MOMENTA to proteomic data from diverse cancer cell lines and human tumors to demonstrate its utility at revealing variation in metabolic pathway activity across cancer types, which we verify using independent metabolomics measurements. The novel metabolic networks we uncover in breast cancer and other tumors are linked to clinical outcomes, underscoring the pathophysiological relevance of the findings.