An inexpensive photosynthetic irradiance sensor for ecological field studies

The design and characteristics of inexpensive and simply constructed equal-energy response photosynthetic irradiance sensors is described for use particularly where several cells are required in comparative ecological studies either above or below water. The dimensions of the sensors can be changed proportionally to suit different applications or components. The response of the sensor to irradiance at varying angles corresponds very closely to that required by the cosine law. The sensor is comparatively insensitive to other environmental variables in field use and gave a stable output; the long term drift was proportional to electrical output but in continuous use, drift is regular and could reach -0.08 year^-1 of the total. The spectral range and cosine response is discussed in comparison to other more expensive (x 5–10) commercially available, sensors and to local standards.     

MV-mimicking micelles loaded with PEG-serine-ACP nanoparticles to achieve biomimetic intra/extra fibrillar mineralization of collagen in vitro

Since their discovery, matrix vesicles (MVs) containing minerals have received considerable attention for their role in the mineralization of bone, dentin and calcified cartilage. Additionally, MVs' association with collagen fibrils, which serve as the scaffold for calcification in the organic matrix, has been repeatedly highlighted. The primary purpose of the present study was to establish a MVs–mimicking model (PEG-S-ACP/micelle) in vitro for studying the exact mechanism of MVs-mediated extra/intra fibrillar mineralization of collagen in vivo. In this study, high-concentration serine was used to stabilize the amorphous calcium phosphate (S-ACP), which was subsequently mixed with polyethylene glycol (PEG) to form PEG-S-ACP nanoparticles. The nanoparticles were loaded in the polysorbate 80 micelle through a micelle self-assembly process in an aqueous environment. This MVs–mimicking model is referred to as the PEG-S-ACP/micelle model. By adjusting the pH and surface tension of the PEG-S-ACP/micelle, two forms of minerals (crystalline mineral nodules and ACP nanoparticles) were released to achieve the extrafibrillar and intrafibrillar mineralization, respectively. This in vitro mineralization process reproduced the mineral nodules mediating in vivo extrafibrillar mineralization and provided key insights into a possible mechanism of biomineralization by which in vivo intrafibrillar mineralization could be induced by ACP nanoparticles released from MVs. Also, the PEG-S-ACP/micelle model provides a promising methodology to prepare mineralized collagen scaffolds for repairing bone defects in bone tissue engineering.     

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.     

Structure-wise discrimination of adenine and guanine by proteins on the basis of their nonbonded interactions

We have analyzed the nonbonded interactions of the structurally similar moieties, adenine and guanine forming complexes with proteins. The results comprise (a) the amino acid–ligand atom preferences, (b) solvent accessibility of ligand atoms before and after complex formation with proteins, and (c) preferred amino acid residue atoms involved in the interactions. We have observed that the amino acid preferences involved in the hydrogen bonding interactions vary for adenine and guanine. The structural variation between the purine atoms is clearly reflected by their burial tendency in the solvent environment. Correlation of the mean amino acid preference values show the variation that exists between adenine and guanine preferences of all the amino acid residues. All our observations provide evidence for the discriminating nature of the proteins in recognizing adenine and guanine.     

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.     

Mitogen-Activated Protein Kinase Kinase 3 Is Required for Regulation during Dark-Light Transition

Plant growth and development are coordinately orchestrated by environmental cues and phytohormones. Light acts as a key environmental factor for fundamental plant growth and physiology through photosensory phytochromes and underlying molecular mechanisms. Although phytochromes are known to possess serine/threonine protein kinase activities, whether they trigger a signal transduction pathway via an intracellular protein kinase network remains unknown. In analyses of mitogen-activated protein kinase kinase (MAPKK, also called MKK) mutants, the mkk3 mutant has shown both a hypersensitive response in plant hormone gibberellin (GA) and a less sensitive response in red light signaling. Surprisingly, light-induced MAPK activation in wild-type (WT) seedlings and constitutive MAPK phosphorylation in dark-grown mkk3 mutant seedlings have also been found, respectively. Therefore, this study suggests that MKK3 acts in negative regulation in darkness and in light-induced MAPK activation during dark-light transition.     

The reactivity of neonatal rabbits to the mammary pheromone as a probe for viability

Newborn rabbits depend on a daily nursing interaction with the mother to gain milk and to survive. During this interaction, they localise and seize the nipples displaying a typical behaviour triggered by maternal odour cues. The mammary pheromone constitutes such a signal in domestic rabbits: it elicits sucking-related movements in more than 90% of the pups. However, some newborns remain unresponsive to the presentation of the pheromone, even pups apparently healthy and highly motivated to suck. The main goal of the present study was therefore to explore the link between the unresponsiveness of rabbit pups to the mammary pheromone and their growth and survival in breeding conditions. To that end, 293 newborns from 30 litters were tested for their head searching-oral grasping responses to the mammary pheromone on days 1 and 3, and their milk intake and mortality were followed up from days 1 to 21. It was hypothesised that unresponsive newborns would have subsequent difficulties in finding nipples, sucking and surviving. Early weight and success in milk intake were further considered as mediating factors in growth and viability. The results showed that pups that were unresponsive to the mammary pheromone on day 1 were less successful in gaining milk and had a higher rate of mortality than the responsive pups. However, this impact was modulated by the weight of pups: it appeared only in the lightest newborns. Moreover, this impact vanished on day 3. On the other hand, the pup weight and sucking success on days 1 to 3 strongly influenced viability and growth during the period extending from days 1 to 21. Taken together, the results show that the day-1 responsiveness of rabbit pups to the mammary pheromone can be considered as an indicator of individual viability in pups having a small weight (<48 g on day 1). The predictive validity of the pups’ pheromonal reactivity seems however time-limited as it works only during the first, but crucial, postnatal days.