Spatial Organization in Proteinaceous Membrane‐Stabilized Coacervate Protocells

As a model protocell, the membrane‐free coacervate microdroplet is widely utilized in functional studies to provide insights into the physicochemical properties of the cell and to engineer cytomimetic soft technologies; however, the lack of a discrete membrane contributes to its instability and limits further application. Herein, a strategy is developed to fabricate a hybrid protocell based on the self‐assembly of a proteinaceous membrane at the surface of coacervate microdroplets driven by a combination of electrostatic adhesion and steric/hydrophilic surface buoyancy. The semipermeable proteinaceous membrane can enhance coacervate stability obviously without compromising sequestration behavior. Significantly, such hybrid protocells demonstrate spatial organization whereby various functional enzymes can be located in discrete regions, which facilitates an on/off modulation for a cascade enzymatic reaction along with enhanced chemical communication between subpopulations.     

Quantum Sensing in a Physiological‐Like Cell Niche Using Fluorescent Nanodiamonds Embedded in Electrospun Polymer Nanofibers

Fluorescent nanodiamonds (fNDs) containing nitrogen vacancy (NV) centers are promising candidates for quantum sensing in biological environments. This work describes the fabrication and implementation of electrospun poly lactic‐co‐glycolic acid (PLGA) nanofibers embedded with fNDs for optical quantum sensing in an environment, which recapitulates the nanoscale architecture and topography of the cell niche. A protocol that produces uniformly dispersed fNDs within electrospun nanofibers is demonstrated and the resulting fibers are characterized using fluorescent microscopy and scanning electron microscopy (SEM). Optically detected magnetic resonance (ODMR) and longitudinal spin relaxometry results for fNDs and embedded fNDs are compared. A new approach for fast detection of time varying magnetic fields external to the fND embedded nanofibers is demonstrated. ODMR spectra are successfully acquired from a culture of live differentiated neural stem cells functioning as a connected neural network grown on fND embedded nanofibers. This work advances the current state of the art in quantum sensing by providing a versatile sensing platform that can be tailored to produce physiological‐like cell niches to replicate biologically relevant growth environments and fast measurement protocols for the detection of co‐ordinated endogenous signals from clinically relevant populations of electrically active neuronal circuits.     

Combined innovation and export strategies of KIBS in different regional settings

This paper examines how KIBS establishments combine innovation and exports, and which factors are associated with these combinations. In particular, we hypothesize that KIBS establishments which both export and innovate will be over-represented in metropolitan regions, and under-represented in peripheral regions. Our analysis draws upon a sample of 429 innovative KIBS establishments in the province of Quebec (Canada). We show that strategies differ across space (but not as expected – metropolitan and peripheral strategies are similar), that T-KIBS’ strategies are associated with non-market information sources, and that P-KIBS' strategies are associated with information purchasing. P-KIBS’ and T-KIBS’ strategies vary with the performance of in-house R&D. Taken together, these results suggest that whereas KIBS’ choice of export and innovation strategies do not reflect their ‘hard’ or ‘soft’ nature, the factors associated with this choice do. The similarity between metropolitan and peripheral regions reflects the fact that Quebec’s resource-based peripheral economy is international and innovative.     

Object-based fusion for urban tree species classification from hyperspectral,panchromatic and nDSM data

This study aims at identifying the best object-based fusion strategy that takes advantage of the complementarity of several heterogeneous airborne data sources for improving the classification of 15 tree species in an urban area (Toulouse, France). The airborne data sources are: hyperspectral Visible Near-Infrared (160 spectral bands, spatial resolution of 0.4 m) and Short-Wavelength Infrared (256 spectral bands, 1.6 m), panchromatic (14 cm), and a normalized Digital Surface Model (12.5 cm). Object-based feature and decision level fusion strategies are proposed and compared when applied to a reference site where the species are previously identified during ground truth collection. This allows the best fusion strategy to be selected with a view to introducing the method in an automatic process (tree crown delineation and species classification) on a test site, independent of the reference site used for learning. In particular, a decision level fusion is selected: based on the Support Vector Machine algorithm, Visible Near-Infrared and Short-Wavelength Infrared classifications use Minimum Noise Fraction components at the original spatial resolution, whereas panchromatic and normalized Digital Surface Model classifications use, respectively, Haralick’s and structural features computed at the object scale. After the computation of a decision profile for each source at the object level based on the classification algorithms’ membership probabilities, these decision profiles are combined and a decision rule is applied to predict the species. Focusing on the reference site, the Visible Near-Infrared exhibits the best performances with F-score values higher than 60% for 13 species out of 15. The Short-Wavelength Infrared is the most powerful for three species with F-score greater than 60% for seven common species with the Visible Near-Infrared. The panchromatic and normalized Digital Surface Model contribute marginally. The best fusion strategy (decision fusion) does not improve significantly the overall accuracy with 77% (kappa = 74%) against 75% (kappa = 72%) for the Visible Near-Infrared but in general, it improves the results for cases where complementarities have been observed. When applied to the test site and assessed for the two majority species (Tilia tomentosa and Platanus x hispanica), the selected approach gives consistent results with an overall accuracy of 63% against 55% for the Visible Near-Infrared.     

Protein nutrition of dairy cows receiving grass silage diets. Effects on silage intake and milk production of postruminal supplements of casein or soya-protein isolate and the effects of intravenous infusions of a mixture of methionine,phenylalanine and tryptophan

Milk production responses to protein supplementation of grass silage diets were investigated in two experiments with dairy cows. In Experiment 1. four cows received a basal diet of grass silage ad libitum plus a barley/soya supplement at 5 kg day^?1. The cows received the following treatments in a 4 × 4 Latin square design with 10-day periods: (1) basal diet, (2) basal diet plus 230 g casein day^?1 infused into the abomasum; (3) basal diet plus 225 g soya protein isolate (SPI) day^?1 into the abomasum; and (4) basal diet plus a dietary addition of 1.2 kg fishmeal-based product (AP) day^?1. All three supplements increased (P < 0.05) the yield of milk and milk protein relative to the basal diet, the values being 16.9. 535:18.8. 610; 19.5, 625; and 18.5 kg day^?1 and 582 g day^?1 for the basal. AP, casein and SPI treatments respectively. Responses to casein were greater (P < 0.05) than to SPI. Changes in the concentrations of amino acids in blood plasma suggested that methionine, tryptophan and phenylalanine were in shortest supply relative to demand, and their potential role as limiting amino acids was investigated in a second experiment. In Experiment 2, four dairy cows were used in a 4 × 4 Latin square design with 10-day periods. The four treatments were (1) a diet of grass silage ad libitum plus 5 kg day^?1 of a barley/soya supplement containing 176 g CP kg^?1 DM (LP); (2) LP plus an intravenous infusion of 5.0 g methionine, 9.1 g phenylalanine and 2.2 g tryptophan day^?1; (3) grass silage ad libitum plus 5 kg day^?1 of a barley/soya supplement containing 334 g CP kg^?1 DM (HP); and (4) HP plus the intravenous infusion of methionine, phenylalanine and tryptophan. The HP treatment produced a higher yield (P < 0.05) of milk protein than the LP treatment (722 vs. 667 g day^?1) but the amino acid infusion had no effect with either treatment. The elimination of methionine, phenylalanine and tryptophan (and, in previous experiments, methionine and lysine) as candidates for limiting amino acids on diets of grass silage plus soya-based supplements questions whether the differences in responses to casein and SPI can be explained in terms of their amino acid compositions. The role of factors such as peplides, producing during digestion, some of which may be biologically active, deserves investigation.     

Bromine, Chlorine, and Iodine Determination in Soybean and its Products by ICP-MS After Digestion Using Microwave-Induced Combustion

A method for bromine, chlorine, and iodine determination in soybean and related products was developed by inductively coupled plasma mass spectrometry (ICP-MS) after digestion by microwave-induced combustion (MIC). Samples were pressed as pellets and combusted using pressurized oxygen (20 bar) and ammonium nitrate solution (50 μL of 6 mol L^?1) as the igniter. Analytes were absorbed in alkaline solution (100 mmol L^?1 NH₄OH), and a reflux step of 5 min, microwave power of 1,400 W, was applied after combustion in order to improve analyte recoveries. For Cl determination by ICP-MS, a dynamic reaction cell was used with ammonia as the reaction gas. The accuracy was evaluated using certified reference materials (CRMs) and spiked samples. Using MIC, the agreement with CRM values and spike recoveries was higher than 95 % for all analytes for certified reference materials of a similar composition (National Institute of Standards and Technology (NIST), corn bran and NIST, whole milk). Limits of detection were 0.03, 1.2, and 0.002 μg g^?1 for Br, Cl, and I, respectively. The residual carbon content in the digests obtained after MIC procedure was lower than 0.5 %. Blanks were always negligible and no memory effects were observed. Digestion by MIC allowed processing up to eight samples by each run in 25 min with high efficiency of digestion providing a suitable medium for further bromine, chlorine, and iodine determination by ICP-MS.     

Continuous analysis of dissolved gaseous mercury (DGM) and mercury flux in two freshwater lakes in Kejimkujik Park,Nova Scotia: evaluating mercury flux models with quantitative data

Diurnal patterns for dissolved gaseous mercury (DGM) concentration, mercury flux, several water variables (pH, oxidation reduction potential (ORP), water temperature), and meteorological variables (wind speed, air temperature, % relative humidity, solar radiation) were measured in two lakes with contrasting dissolved organic carbon (DOC) concentrations in Kejimkujik Park, Nova Scotia. A continuous analysis system made it possible to measure quick changes in DGM over time. Consistently higher DGM concentrations were found in the high DOC lake as compared to the low DOC lake. An examination of current mercury flux models using this quantitative data indicated some good correlations between the date and predicted flux (r ranging from 0.27 to 0.83) but generally poor fit (standard deviation of residuals ranging from 0.97 to 3.39). Cross-correlation analysis indicated that DGM dynamics changed in response to solar radiation with lag-times of 65 and 90 min. This relationship with solar radiation was used to develop new predictive models of DGM and mercury flux dynamics for each lake. We suggest that a generalized approach using time-shifted solar radiation date to predict DGM can be incorporated into existing mercury flux models. It is clear from the work presented that DOC and wind speed may also play important roles in DGM and mercury flux dynamics, and these roles have not been adequately accounted for in current predictive models.     

Application of an isothermal,three-phase catalytic reactor model to predict unsteady-state fixed-bed performance

CatReac, a three-phase catalytic mathematical model, was developed for analysis and optimization of the volatile reactor assembly used in International Space Station water processor. This wet oxidation process is used to remove low molecular weight contaminants such as acetic acid, acetone, ethanol, 1-propanol, 2-propanol, and propionic acid, which are not removed by the other treatment processes. The Langmuir-Hinshelwood (Hinshelwood, C. N. The Kinetics of Chemical Change in Gaseous Systems, 3rd ed.; Oxford: London, 1933; pp 301-347) isothermal adsorption expression was successfully used to describe the reaction kinetics of compounds on the catalyst surface for the compounds mentioned above. Small-column experiments combined with the use of the Arrhenius equation were successfully used to predict the Langmuir-Hinshelwood parameters under different temperatures for a temperature range from 93 to 149 degrees C. Full-scale and small-column experiments were successfully used to validate the model predictions for unsteady-state fixed-bed operations.