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259 results for “sucrose”
Multiscale assessment of the effect of a stearic-palmitic sucrose ester on the crystallization of anhydrous milk fat
<p>Dataset belonging to publication 'Multiscale assessment of the effect of a stearic-palmitic sucrose ester on the crystallization of anhydrous milk fat'.</p> <p>Available via: <a title="Persistent link using digital object identifier" href="https://doi.org/10.1016/j.foodres.2024.115243" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.foodres.2024.115243</a>.</p> <p> </p> <p>PLM = polarized light microscopy</p> <p>CryoSEM = cryo-scanning electron microscopy</p> <p>> data obtained after de-oiling fat samples with isobutanol (4x) and aceton (1x), see publication</p> <p>SAXS = small-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of empty capillary, see publication</p> <p>WAXS = wide-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of empty capillary, see publication</p> <p>USAXS = ultra-small-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of the capillary at 70°C, see publication</p> <p>DSC = differential scanning calorimetry</p> <p>> Samples are heated at 70°C for 10 min, and then crystallized following a certain protocol (see publication).</p> <p>> Samples are maintained one hour at their respective isothermal crystallization temperature.</p> <p>> Samples are rehaeted at 5°C/min to 70°C.</p> <p>SE = sucrose ester (SP30, HLB6)</p> <p>AMF = anhydrous milk fat</p> <p>AMFE = anhydrous milk fat + 0.5 wt% SE</p> <p>FC = fast cooling (20°C/min)</p> <p>SC = slow cooling (1°C/min)</p> <p> </p> <p>Project funding agency: Fonds Wetenschappelijk Onderzoek (FWO). Grant number: 1128923N. </p>
Continuous process technology for glucoside production from sucrose using a whole cell-derived solid catalyst of sucrose phosphorylase
<p>We provide here the underlying data of the publication "Continuous process technology for glucoside production from sucrose using a whole cell-derived solid catalyst of sucrose phosphorylase". Please find the abstract below.</p> <p>Advanced biotransformation processes typically involve the upstream processing part performed continuously and interlinked tightly with the product isolation. Key in their development is a catalyst that is highly active, operationally robust, conveniently produced and recyclable. A promising strategy to obtain such catalyst is to encapsulate enzymes as permeabilized whole cells in porous polymer materials. Here, we show immobilization of the sucrose phosphorylase from Bifidobacterium adolescentis (P134Q-variant) by encapsulating the corresponding E. coli cells into polyacrylamide. Applying the solid catalyst, we demonstrate continuous production of the commercial extremolyte 2-α-D-glucosyl-glycerol (2-GG) from sucrose and glycerol. The solid catalyst exhibited similar activity (≥70%) as the cell free extract (~800 U g-1 cell wet weight) and showed excellent in-operando stability (40 °C) over 6 weeks in a packed-bed reactor. Systematic study of immobilization parameters related to catalyst activity led to the identification of cell loading and catalyst particle size as important factors of process optimization. Using glycerol in excess (1.8 M), we analyzed sucrose conversion dependent on space velocity (0.075 – 0.750 h-1) and revealed conditions for full conversion of up to 900 mM sucrose. The maximum 2-GG space-time yield reached was 45 g L-1 h-1 for a product concentration of 120 g L-1. Collectively, our study establishes a step-economic route towards a practical whole cell-derived solid catalyst of sucrose phosphorylase, enabling continuous production of glucosides from sucrose. This strengthens the current biomanufacturing of 2-GG, but also has significant replication potential for other sucrose-derived glucosides, promoting their industrial scale production using sucrose phosphorylase. </p>
Fig. 3 in Asymbiotic germination, multiplication and development of Alatiglossum fuscopetalum (Orchidaceae) as affected by culture medium, sucrose and growth regulators
Fig. 3. Growth index of Alatiglossum fuscopetalum on Murashige and Skoog (MS and ½MS), Knudson (KN), and Vacin and Went (VW) media, 90 days after the onset of seed germination. Histobars with the same letters are not significantly different according to the Tukey's test at the 5% probability level.
Fig. 2 in Asymbiotic germination, multiplication and development of Alatiglossum fuscopetalum (Orchidaceae) as affected by culture medium, sucrose and growth regulators
Fig. 2. Germination percentages of Alatiglossum fuscopetalum seeds on Murashige and Skoog (MS and ½MS), Knudson (KN), and Vacin and Went (VW) media. Histobars with the same letters are not significantly different according to the Tukey's test at the 5% probability level.
Figs. 1 A-D in Asymbiotic germination, multiplication and development of Alatiglossum fuscopetalum (Orchidaceae) as affected by culture medium, sucrose and growth regulators
Figs. 1 A-D. Protocorm developmental stages of Alatiglossum fuscopetalum from seed germination in vitro. A. Stage 1 swollen green embryos (protocorm phase); B. Stage 2 protocorm bearing one leaf; C. Stage 3 protocorm bearing two leaves; D. Stage 4 protocorm with leaves and one root (seedling stage). Bars = 1 mm.
Three‐level hybrid modeling for systematic optimization of biocatalytic synthesis: α‐glucosyl glycerol production by enzymatic trans‐glycosylation from sucrose
<p>We provide here the underlying data of the publication "Three‐level hybrid modeling for systematic optimization of biocatalytic synthesis: α‐glucosyl glycerol production by enzymatic trans‐glycosylation from sucrose". Please find the abstract below.</p> <p>Mechanism-based kinetic models are rigorous tools to analyze enzymatic reactions, but their extension to actual conditions of the biocatalytic synthesis can be difficult. Here, we demonstrate (mechanistic-empirical) hybrid modeling for systematic optimization of the sucrose phosphorylase-catalyzed glycosylation of glycerol from sucrose, to synthesize the cosmetic ingredient α-glucosyl glycerol (GG). The empirical model part was developed to capture nonspecific effects of high sucrose concentrations (up to 1.5 M) on microscopic steps of the enzymatic trans-glycosylation mechanism. Based on verified predictions of the enzyme performance under initial rate conditions (Level 1), the hybrid model was expanded by microscopic terms of the reverse reaction to account for the full-time course of GG synthesis (Level 2). Lastly (Level 3), the application of the hybrid model for comprehensive window-of-operation analysis and constrained optimization of the GG production (~250 g/L) was demonstrated. Using two candidate sucrose phosphorylases (from <em>Leuconostoc mesenteroides</em> and <em>Bifidobacterium adolescentis</em>), we reveal the hybrid model as a powerful tool of “process decision making” to guide rational selection of the best-suited enzyme catalyst. Our study exemplifies a closing of the gap between enzyme kinetic models considered for mechanistic research and applicable in technologically relevant reaction conditions; and it highlights the important benefit thus realizable for biocatalytic process development.</p>
Fig. 2 in Sucrose triggers honeydew preference in the ghost ant, Tapinoma melanocephalum (Hymenoptera: Formicidae)
Fig. 2. Foraging preference of ghost ants. The data are presented as the mean ± SE, and an asterisk above the bars indicates statistically significant differences between mealybug and aphid (paired-sample t-test, P = 0.05).
Fig. 3 in Sucrose triggers honeydew preference in the ghost ant, Tapinoma melanocephalum (Hymenoptera: Formicidae)
Fig. 3. Foraging preferences of ghost ants (A) when different sugars were offered simultaneously (Xy, Gl, Fr, Su, Tr, Me, Ra, Rh, M-H, and A-H denote xylose, glucose, fructose, sucrose, trehalose, melezitose, raffinose, rhamnose, mealybug honeydew, and aphid honeydew, respectively); and (B) when different concentrations of sucrose were offered simultaneously. The data are presented as the mean ± SE, and different letters above the bars indicate statistically significant differences between the treatments (Mann–Whitney U test, P = 0.05).
Fig. 1. Cumulative Solenopsis invicta worker ant mortality among Solenopsis invicta virus 3 in Diet with sucrose ameliorates Solenopsis invicta virus 3 (Solinviviridae: Invictavirus) infection in Solenopsis invicta (Hymenoptera: Formicidae) worker ants
Fig. 1. Cumulative Solenopsis invicta worker ant mortality among Solenopsis invicta virus 3-infected and -uninfected colonies provided a diet of crickets (Acheta domesticus) and either supplemented (open symbols) or not supplemented (solid symbols) with a 10% sucrose solution. Analysis of Variance by treatment was conducted for d 21 values and found to be significant (F = 10.0; df = 3,14; P <0.0009). Scheffe's multiple comparison procedure was used to separate the means. Symbols with the same letter are not statistically different.
Fig. 2. Solenopsis invicta virus 3 in Diet with sucrose ameliorates Solenopsis invicta virus 3 (Solinviviridae: Invictavirus) infection in Solenopsis invicta (Hymenoptera: Formicidae) worker ants
Fig. 2. Solenopsis invicta virus 3 genome equivalents per ng RNA from dead Solenopsis invicta worker ants among Solenopsis invicta virus 3-infected and -uninfected colonies provided a diet of crickets (Acheta domesticus) and either supplemented (open symbols) or not supplemented (solid symbols) with a 10% sucrose solution. Solenopsis invicta virus 3 was not detected in the Solenopsis invicta virus 3-uninfected group. Student's t-test was conducted to compare the virus quantity in colonies with and without the sucrose supplement by d. Solenopsis invicta virus 3 genome equivalents per ng RNA was greater significantly in colonies without sugar supplementation on d 12 (t = 2.5; df = 9; P <0.033) and 19 (t = 2.4; df = 9; P <0.037).
Classification and quantification of sucrose from sugar beetand sugarcane using optical spectroscopy and chemometrics
<p>Sucrose, obtained from either sugar beet or sugarcane, is one of the main ingredients used in the food industry. Due to the same molecular structure, chemical methods cannot distinguish sucrose from both sources. More practical and affordable methods would be valuable. Sucrose samples (cane and beet) were collected from nine countries, 25% (w/w) aqueous solutions were prepared and their absorbances recorded from 200 to 1380 nm. Spectral differences were observable in the ultraviolet–visible (UV–Vis) region from 200 to 600 nm due to impurities in sugar. Linear discriminant analysis (LDA), classification and regression trees, and soft independent modeling of class analogy were tested for the UV–Vis region. All methods showed high performance accuracies. LDA, after selection of five wavelengths, gave 100% correct classification with a simple interpretation. In addition, binary mixtures of the sugar samples were prepared for quantitative analysis by means of partial least squares regression and multiple linear regression (MLR). MLR with first derivative Savitzky–Golay were most accept- able with root mean square error of cross-validation, prediction, and the ratio of (standard error of) prediction to (standard) deviation values of 3.92%, 3.28%, and 9.46, respectively. Using UV–Vis spectra and chemometrics, the results show promise to distinguish between the two different sources of sucrose. An affordable and quick analysis method to differentiate between sugars, produced from either sugar beet or sugarcane, is suggested. This method does not involve complex chemical analysis or high-level experts and can be used in research or by industry to detect the source of the sugar which is important for some countries’ agricultural policies.</p>
From nucleation to fat crystal network: effect of stearic-palmitic sucrose ester on static crystallization of palm oil
<p>Dataset belonging to publication 'From nucleation to fat crystal network: effect of stearic-palmitic sucrose ester on static crystallization of palm oil', <a href="https://doi.org/10.3390/foods13091372">https://doi.org/10.3390/foods13091372</a>.</p> <p> </p> <p>PLM = polarized light microscopy</p> <p>CryoSEM = cryo-scanning electron microscopy</p> <p>> data obtained after de-oiling fat samples with isobutanol (4x) and aceton (1x), see publication</p> <p>SAXS = small-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of empty capillary, see publication</p> <p>> for SE heating and cooling cycles, data is recorded from 70°C (1h) to 20°C (1h), and 4 repeated cycles </p> <p>WAXS = wide-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of empty capillary, see publication</p> <p>> for SE heating and cooling cycles, data is recorded from 70°C (1h) to 20°C (1h), and 4 repeated cycles </p> <p>USAXS = ultra-small-angle X-ray scattering</p> <p>> data obtained after subtraction of intensity of the capillary at 70°C, see publication</p> <p>DSC = differential scanning calorimetry</p> <p>> Samples are heated at 70°C for 10 min, and then crystallized following a certain protocol (see publication).</p> <p>> Samples are maintained one hour at their respective isothermal crystallization temperature.</p> <p>> Samples are rehaeted at 5°C/min to 70°C.</p> <p>SE = sucrose ester (SP30, HLB6)</p> <p>PO = palm oil</p> <p>POE = palm oil + 0.5 wt% SE</p> <p>FC = fast cooling (20°C/min)</p> <p>SC = slow cooling (1°C/min)</p>
Fig. 1 in Sucrose triggers honeydew preference in the ghost ant, Tapinoma melanocephalum (Hymenoptera: Formicidae)
Fig. 1. Experimental apparatus used to evaluate foraging preferences of ghost ants.
Whole-Genome Resequencing identifies SNPs in Sucrose Synthase and Sugar Transporter Genes Associated with Sweetness in Coconut
<p><span>This vcf file constitute underlying raw data material for the manuscript</span> "<span>Whole-Genome Resequencing identifies SNPs in Sucrose Synthase and Sugar Transporter Genes Associated with Sweetness in Coconut"</span>. <span>The SNP genotype data came from a whole-genome resequencing and were called using an unpublished coconut reference genome. SNPs with a non-missing and minor allele frequency (MAF) less than 5% were removed. Finally, 19,149,289 SNPs were selected and used in the population study and gene mining.</span></p>
Data for: The Neonicotinoid Imidacloprid Impairs Sucrose Solution Consumption, Learning and Locomotor Activity Levels In Bumblebees (Bombus Terrestris)
<p># README</p> <p>The following files are for creating the figures from the paper: </p> <p>## `plot_flowervisits_nectar.ipynb`</p> <p>Jupyter notebook that creates the figures concerning flower visits, nectar consumption and the proportion of empty honeypots.</p> <p>## `plot_activity.py`</p> <p>Python script that takes trajectory fragments from video analysis and computes the locomotor activity level through making histograms of bumblebee speeds. Makes two figures that are equivalent to the figure on locomotor activity in the paper.</p> <p>## `statistical analysis.py`</p> <p>R markdown notebook that performs all the hypothesis testing for the paper.</p> <p>## Data</p> <p>These files contain the data, and are located in the folder called `data`. </p> <p>`activity/activityproportions.csv` contains the computed locomotor activity level for easy plotting.</p> <p>`boldata/boldata.csv` contains data about the nectar bag weight before and after experiment and the counted number of empty and full honeypots. Used by `plot_flowervisits_nectar.ipynb`</p> <p>`flower_data/flowerData.csv` contains the computed number of visits to blue and yellow flowers per hive for easy plotting.</p> <p>`humlevideo_production/*/traj*_trajectories*.csv` contains constructed trajectories from all experiments seen from both cameras. These are being used by the script `plot_activity`.</p> <p>`humlevideo_production/*/traj*.json` contains data about the occurence of bees on flowers in each frame in each experiment.</p> <p>`landinger_csv` contains data about landings, that have been extracted from the `humlevideo_production/*/traj*.json` files. Used by `plot_flowervisits_nectar.ipynb`.</p> <p> </p>
A Trial Comparing Ferumoxytol to Iron Sucrose for the Treatment of Iron Deficiency Anemia in Adult Subjects With Chronic Kidney Disease
ClinicalTrials.gov study NCT01052779. IPD Sharing: Not stated. Countries: 7. Publications: 3.
Iron Isomaltoside/Ferric Derisomaltose vs Iron Sucrose for Treatment of Iron Deficiency Anemia in Non-Dialysis-Dependent Chronic Kidney Disease
ClinicalTrials.gov study NCT02940860. IPD Sharing: NO. Countries: 1. Publications: 1.
Effects of Added D-fagomine on Glycaemic Responses to Sucrose
ClinicalTrials.gov study NCT01811303. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Compare Efficacy/Safety of Repeat Doses of Ferumoxytol With Iron Sucrose in CKD Subjects With IDA and on Hemodialysis
ClinicalTrials.gov study NCT01227616. IPD Sharing: Not stated. Countries: 3. Publications: 2.
Oral Liposomal Iron Versus Injectable Iron Sucrose for Anemia Treatment in Non-Dialysis Chronic Kidney Disease Patients
ClinicalTrials.gov study NCT06556134. IPD Sharing: NO. Countries: 1. Publications: 3.
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