An in-depth Comparison of the Pediatric and Adult Urinary N-glycomes

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Highlights

• •N-glycan patterns are distinct in pediatric and adult urine.
• •Sex differences of N-glycans are much larger in adults.
• •Pediatric urine has almost no sex differences in N-glycan levels.
• •In adults, the majority of N-glycans were more abundant in males.

     

How do elevated CO2 and O3 affect the interception and utilization of radiation by a soybean canopy?

Net productivity of vegetation is determined by the product of the efficiencies with which it intercepts light (?_i) and converts that intercepted energy into biomass (?_c). Elevated carbon dioxide (CO₂) increases photosynthesis and leaf area index (LAI) of soybeans and thus may increase ?_i and ?_c; elevated O₃ may have the opposite effect. Knowing if elevated CO₂ and O₃ differentially affect physiological more than structural components of the ecosystem may reveal how these elements of global change will ultimately alter productivity. The effects of elevated CO₂ and O₃ on an intact soybean ecosystem were examined with Soybean Free Air Concentration Enrichment (SoyFACE) technology where large field plots (20‐m diameter) were exposed to elevated CO₂ (～550 μmol mol^?1) and elevated O₃ (1.2 × ambient) in a factorial design. Aboveground biomass, LAI and light interception were measured during the growing seasons of 2002, 2003 and 2004 to calculate ?_i and ?_c. A 15% increase in yield (averaged over 3 years) under elevated CO₂ was caused primarily by a 12% stimulation in ?_c , as ?_i increased by only 3%. Though accelerated canopy senescence under elevated O₃ caused a 3% decrease in ?_i, the primary effect of O₃ on biomass was through an 11% reduction in ?_c. When CO₂ and O₃ were elevated in combination, CO₂ partially reduced the negative effects of elevated O₃. Knowing that changes in productivity in elevated CO₂ and O₃ were influenced strongly by the efficiency of conversion of light energy into energy in plant biomass will aid in optimizing soybean yields in the future. Future modeling efforts that rely on ?_c for calculating regional and global plant productivity will need to accommodate the effects of global change on this important ecosystem attribute.     

Leaf micromorphology inAgathis and its taxonomic implications

This study surveys the micromorphological surface structure of the leaves of the conifer genusAgathis (Araucariaceae) from throughout the range of the genus (Malaysia to New Zealand and Fiji) as seen with the scanning electron microscope. These data confirm that the vegetative parts ofAgathis are taxonomically highly conservative, but suggest the Melanesian and New Zealand elements to be distinctive from those of the rest of the genus, and from one another. Conclusions are compared with those that have been derived from studies based on other characters.     

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.

     

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.     

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.