Association between FABP2 Ala54Thr polymorphisms and type 2 diabetes mellitus risk: a HuGE Review and Meta‐Analysis

Many studies have examined the association between the FABP2 (rs1799883) Ala54Thr gene polymorphism and type 2 diabetes mellitus risk (T2DM) in various populations, but their results have been inconsistent. To assess this relationship more precisely, A HuGE review and meta‐analysis were performed. The PubMed and CNKI database was searched for case‐control studies published up to April 2014. Data were extracted and pooled odds ratios (OR) with 95% confidence intervals (CI) were calculated. Ultimately, 13 studies, comprising 2020 T2DM cases and 2910 controls were included. Overall, for the Thr carriers (Ala/Thr and Thr/Thr) versus the wild‐type homozygotes (Ala/Ala), the pooled OR was 1.18 (95% CI = 1.04–1.34, P = 0.062 for heterogeneity), for Thr/Thr versus Ala/Ala the pooled OR was 1.17 (95% CI = 1.05–1.41 P = 0.087 for heterogeneity). In the stratified analysis by ethnicity, the significantly risks were found among Asians but not Caucasians. This meta‐analysis suggests that the FABP2 (rs1799883) Ala54Thr polymorphisms are associated with increased susceptibility to T2DM risk among Asians but not Caucasians.     

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.     

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.     

Chromatographic separation of extruded iron-sulfur cores from the apoproteins of Clostridium pasteurianum and spinach ferredoxins in aqueous Triton X-100/urea

Iron-sulfur core extrusions from spinach [( 2Fe-2S]) and Clostridium pasteurianum (2[4Fe-4S]) ferredoxins in aqueous Triton X-100/urea containing excess benzenethiol yield quantitatively [FenSn(SPh)4]2- with n = 2 and n = 4, respectively. The iron-sulfur cluster can be separated from the corresponding apoprotein by rapid passage of the extrusion mixture over a small anaerobic column of Whatman DE-52 anion-exchange cellulose. Essentially quantitative recovery of [FenSn (SPh)4]2- is achieved in the eluate. The apoprotein remaining on the column can be eluted with 0.5 M NaCl. Most of the residual Triton X-100 and benzenethiol can be removed by passage of the apoprotein eluate over a small column of Bio-Beads SM-2, a hydrophobic polystyrene adsorbent. Apoprotein recovery is comparable to that obtained by other chromatographic methods. At least with spinach ferredoxin, the apoprotein prepared in this fashion can be reconstituted. The procedures developed in this work are potentially most applicable to selective removal of [2Fe-2S] and [4Fe-4S] centers from a multicenter enzyme without irreversible denaturation.     

Structural Decomposition Analysis of Raw Material Consumption

The aim of this article is to quantify the drivers for the changes in raw material consumption (domestic material consumption expressed in the form of all materials extracted and used in the production phase) in terms of technology, which refers to the concept of sustainable production; the product structure of final demand, which refers to the concept of sustainable consumption; and the volume of final demand, which is related to economic growth. We also aim to determine to what extent the technological development and a shift in product structure of the final demand compensate for the growth in final consumption volume. Therefore, we apply structural decomposition analysis (SDA) to the change in raw material consumption (RMC) of the Czech Republic between 2000 and 2007. To present the study in a broader context, we also show other material flow indicators for the Czech Republic for 2000 and 2007. Our findings of SDA show that final demand structure has a very limited effect on the change in material flows. The rapid change in final demand volume was not compensated for crude oil, metal ores, construction materials, food crops, and timber. For the material category of non‐iron metal ores, even the change in technology contributes to an increase in material flows. The largest relative increases are reported for non‐iron metal ores (38%) and construction materials (30%). The main changes in material flows related to the Czech Republic are driven by exports and enabled by imports, the main source of these increased material flows. This emphasizes the increasing role of international trade.     

Amino acid analysis of bone from a possible case of prehistoric iron deficiency anemia from the American southwest

It is possible that dietary conditions can result in the production of abnormal bone protein. For example, a heavily maize-dependent diet could be deficient in one or more essential amino acids necessary to normal human biochemistry and consequently necessary for normal bone protein synthesis. Amino acid analysis of bone tissues, thus, could provide a useful diagnostic tool in paleopathology. To test this potential we have compared the amino acid analyses of bone samples from a prehistoric Southwest Indian child exhibiting porotic hyperostosis with samples taken from (1) two children's skeletons lacking bone lesions but from the same area and time, (2) a modern child who died from accidental causes, and (3) adult human compact bone. Analytical results of the nonpathological prehistoric specimens were virtually identical to that of the modern infant, indicating remarkable preservation of bone protein. The pathological bone sample differed from the three control specimens by having as much as 25% less of those amino acids containing hydroxyl group and acidic side chains. We interpret the amino acid profile for the diseased child as indicating the presence of a greater proportion of helical protein (or less noncollagenous protein) as well as a lowered degree of hydroxylation of proline and lysine. One explanation for our data is that protein biosynthesis is altered in the child exhibiting porotic hyperostosis, and either some proteins important in the early phases of mineralization are not produced in sufficient quantity, or some necessary enzyme cofactors (e.g., dietary ferrous ions) are missing. We conclude that our data are compatible with, but do not prove, the hypothesis that the porotic hyperostosis exhibited by the Southwest Indian child is the result of iron deficiency anemia.     

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 order-specific monoclonal antibody to Diptera reveals the impact of alternative prey on spider feeding behavior in a complex food web

Generalist predators have the capacity to restrict pest population growth, especially early in the season before densities increase. However, their polyphagous feeding habits sometimes translate into reduced pest consumption when they target alternative prey. An order-specific monoclonal antibody was developed to examine the strength of trophic connections between Diptera, a major category of non-pest prey, and linyphiid spiders in alfalfa. We report the development and characterization of a monoclonal antibody with order-level specificity to Diptera. This antibody elicited strong absorbance to 22 Diptera from 13 families, no false-positive reactivity to non-dipteran invertebrates, and antigen detection periods following prey consumption that were comparable between spiders. Over 900 field-collected females of the linyphiid spiders Erigone autumnalis and Bathyphantes pallidus were screened for Diptera antigen. Significantly more B. pallidus screened positive for Diptera (40%) compared to E. autumnalis (16%), indicating differential reliance on these prey. In parallel with the collection of spiders for gut-content analysis, prey availability was estimated at web sites. The two spiders exhibited different feeding responses to prey availability. Consumption of Diptera by B. pallidus was strongly correlated with Diptera abundance whilst the availability of other potential prey did not influence predation rates. Conversely, E. autumnalis did not prey upon Diptera in proportion to availability, but increased Collembola activity-density reduced dipteran consumption. Integration of molecular gut-content analysis with precise sampling of prey demonstrated how two closely related linyphiid spiders exhibit different feeding responses to the availability of prey under natural field conditions. Elucidating the feeding preferences of natural enemies is critical to effective incorporation of biological control by generalist predators in the management of agricultural pests.     

K+(Rb+) and Ca2+ fluxes in young winter wheat plants exposed to sub-zero temperatures

Ice crystal formation temperature was determined in the region of the crown in one group of 7-day-old intact unhardened high-salt plants of winter wheat (Triticum aestivum L. cv. Weibulls Starke II) with TA (Thermal Analysis) and DTA (Differential Thermal Analysis) methods. After exposure of another group of plants, grown for the first 7 days in the same way as the first group, to various sub-zero temperatures (-1 to 5°C), influx in roots of Rb⁺(⁸⁶Rb⁺) and Ca²⁺(⁴⁵Ca²⁺) and contents of K⁺ and Ca²⁺ were determined at intervals during 7 days of recovery. Ice crystal formation in the crown tissue was probably extracellular and took place at about -4°C. There was a large loss of K⁺ from the roots after treatment at sub-zero temperatures. This loss increased as the temperature of the sub-zero treatment decreased. During recovery, roots of plants exposed to -1, -2 and -3°C gradually reabsorbed K⁺. Reabsorption of K⁺ in roots of plants exposed to -4°C was greatly impaired. Rb⁺ influx decreased and Ca²⁺ influx increased after sub-zero temperature treatments of the plants. Active Rb⁺ influx mechanisms and active extrusion of Ca²⁺ were impaired or irreversibly damaged by the exposure. While Rb⁺ influx mechanisms were apparently repaired during recovery in plants exposed to temperatures down to -3°C, Ca²⁺ extrusion mechanisms were not. The temperature for ice crystal formation in the region of the crown tissue coincides with the temperature at which the plants lost the ability to reabsorb K⁺ and to repair Rb⁺ influx mechanisms during the recovery period. Plants were lethally damaged at temperatures below ?4°C.     

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.