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.     

Plant intraspecific functional trait variation is related to within‐habitat heterogeneity and genetic diversity in Trifolium montanum L.

Intraspecific trait variation (ITV), based on available genetic diversity, is one of the major means plant populations can respond to environmental variability. The study of functional trait variation and diversity has become popular in ecological research, for example, as a proxy for plant performance influencing fitness. Up to now, it is unclear which aspects of intraspecific functional trait variation (iFD_CV) can be attributed to the environment or genetics under natural conditions. Here, we examined 260 individuals from 13 locations of the rare (semi‐)dry calcareous grassland species Trifolium montanum L. in terms of iFD_CV, within‐habitat heterogeneity, and genetic diversity. The iFD_CV was assessed by measuring functional traits (releasing height, biomass, leaf area, specific leaf area, leaf dry matter content, F_v/F_m, performance index, stomatal pore surface, and stomatal pore area index). Abiotic within‐habitat heterogeneity was derived from altitude, slope exposure, slope, leaf area index, soil depth, and further soil factors. Based on microsatellites, we calculated expected heterozygosity (H_e) because it best‐explained, among other indices, iFD_CV. We performed multiple linear regression models quantifying relationships among iFD_CV, abiotic within‐habitat heterogeneity and genetic diversity, and also between separate functional traits and abiotic within‐habitat heterogeneity or genetic diversity. We found that abiotic within‐habitat heterogeneity influenced iFD_CV twice as strong compared to genetic diversity. Both aspects together explained 77% of variation in iFD_CV ( = .77, F_{2, 10} = 21.66, p < .001). The majority of functional traits (releasing height, biomass, specific leaf area, leaf dry matter content, F_v/F_m, and performance index) were related to abiotic habitat conditions indicating responses to environmental heterogeneity. In contrast, only morphology‐related functional traits (releasing height, biomass, and leaf area) were related to genetics. Our results suggest that both within‐habitat heterogeneity and genetic diversity affect iFD_CV and are thus crucial to consider when aiming to understand or predict changes of plant species performance under changing environmental conditions.     

Rethinking trophic niches: Speed and body mass colimit prey space of mammalian predators

1. Realized trophic niches of predators are often characterized along a one‐dimensional range in predator–prey body mass ratios. This prey range is constrained by an “energy limit” and a “subdue limit” toward small and large prey, respectively. Besides these body mass ratios, maximum speed is an additional key component in most predator–prey interactions.
2. Here, we extend the concept of a one‐dimensional prey range to a two‐dimensional prey space by incorporating a hump‐shaped speed‐body mass relation. This new “speed limit” additionally constrains trophic niches of predators toward fast prey.
3. To test this concept of two‐dimensional prey spaces for different hunting strategies (pursuit, group, and ambush predation), we synthesized data on 63 terrestrial mammalian predator–prey interactions, their body masses, and maximum speeds.
4. We found that pursuit predators hunt smaller and slower prey, whereas group hunters focus on larger but mostly slower prey and ambushers are more flexible. Group hunters and ambushers have evolved different strategies to occupy a similar trophic niche that avoids competition with pursuit predators. Moreover, our concept suggests energetic optima of these hunting strategies along a body mass axis and thereby provides mechanistic explanations for why there are no small group hunters (referred to as “micro‐lions”) or mega‐carnivores (referred to as “mega‐cheetahs”).
5. Our results demonstrate that advancing the concept of prey ranges to prey spaces by adding the new dimension of speed will foster a new and mechanistic understanding of predator trophic niches and improve our predictions of predator–prey interactions, food web structure, and ecosystem functions.

     

Mobilization of iron from ferritin by isolated mitochondria effects of species compatibility between ferritin and mitochondria and iron content of ferritin

Mitochondria mobilize iron from ferritin by a mechanism that depends on external FMN. With rat liver mitochondria, the rate of mobilization of iron is higher from rat liver ferritin than from horse spleen ferritin. With horse liver mitochondria, the rate of iron mobilization is higher from horse spleen ferritin than from rat liver ferritin. The results are explained by a higher affinity between mitochondria and ferritins of the same species. The mobilization of iron increases with the iron content of the ferritin and then levels off. A maximum is reached with ferritins containing about 1 200 iron atoms per molecule. The results represent further evidence that ferritin may function as a direct iron donor to the mitochondria.     

The RAINFOR database: monitoring forest biomass and dynamics

Problem: Data from over 100 permanent sample plots which have been studied for 10–20 years need a suitable system for storage which allows simple data manipulation and retrieval for analysis. Methods: A relational database linking tree records, taxonomic nomenclature and corresponding environmental data has been built in MS Access as part of the RAINFOR project. Conclusion: The database allows flexible and long‐term use of a large amount of data: more than 100 tree plots across Amazonia, incorporating over 80 000 records of individual trees and over 300 000 total records of tree diameter measurements from successive censuses. The database is designed to enable linkages to existing soil, floristic or plant‐trait databases. This database will be a useful tool for exploring the impact of environmental factors on forest structure and dynamics at local to continental scales, and long term changes in forest ecology. As an early example of its potential, we explore the impact of different methodological assumptions on estimates of tropical forest biomass and carbon storage.     

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.