scholarly journals Development of High-Protein Vegetable Creams by Using Single-Cell Ingredients from Some Microalgae Species

Foods ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2550
Author(s):  
Fatma Boukid ◽  
Josep Comaposada ◽  
Albert Ribas-Agustí ◽  
Massimo Castellari

The aim of this paper was to develop high-protein vegetable creams through the incorporation of microalgae. Single-cell ingredients from Arthrospiraplatensis (spirulina), Chlorella vulgaris, Tetraselmis chui, and Nannochloropsis oceanica were incorporated at two levels of addition (1.5% and 3.0%) to a standard vegetable cream (STD). Effects of incorporation were assessed in terms of physicochemical and rheological attributes as well as nutritional labeling facts. Creams formulated with 3% A. platensis, N. oceanica, or T. chui showed strong color differences (6 < ΔE < 12) compared to STD; creams formulated with 1.5% A. platensis, T. chui, or N. oceanica showed perceptible differences (3 < ΔE < 6); and those made with C. vulgaris at 1.5 and 3% exhibited small differences (ΔE < 2). Moisture content, water activity, pH, syneresis, and °Brix did not show significant changes. Adding microalgae increased Bostwick consistency and decreased the consistency coefficient (K) except in creams made with A. platensis, which showed comparable values to STD. Principal component analysis indicated that creams made with 1.5% C. vulgaris were the most similar to STD considering all evaluated parameters. Estimation of the nutritional labeling facts showed that the four formulations could be labeled as having “high protein content” following the present EU legislation.

2019 ◽  
Author(s):  
Florian Wagner ◽  
Dalia Barkley ◽  
Itai Yanai

AbstractSingle-cell RNA-Seq measurements are commonly affected by high levels of technical noise, posing challenges for data analysis and visualization. A diverse array of methods has been proposed to computationally remove noise by sharing information across similar cells or genes, however their respective accuracies have been difficult to establish. Here, we propose a simple denoising strategy based on principal component analysis (PCA). We show that while PCA performed on raw data is biased towards highly expressed genes, this bias can be mitigated with a cell aggregation step, allowing the recovery of denoised expression values for both highly and lowly expressed genes. We benchmark our resulting ENHANCE algorithm and three previously described methods on simulated data that closely mimic real datasets, showing that ENHANCE provides the best overall denoising accuracy, recovering modules of co-expressed genes and cell subpopulations. Implementations of our algorithm are available at https://github.com/yanailab/enhance.


Blood ◽  
2013 ◽  
Vol 122 (21) ◽  
pp. 2625-2625 ◽  
Author(s):  
Jørn Skavland ◽  
Håkon Reikvam ◽  
Øystein Bruserud ◽  
Bjorn T. Gjertsen

Abstract Introduction Dysregulation and mutations in signaling genes of cancer cells characterize more than half of the acute myeloid leukemia (AML) patients, and contribute to chemoresistance through regulation of cellular processes including apoptosis and DNA repair. We investigated if determination of single cell basal phosphorylation of signaling proteins reflected mutation of FLT3 and NPM1, cytogenetics, response to first course of chemotherapy or overall survival. Methods We employed flow cytometric single cell analysis of phosphoproteins central to signal transduction pathways in myeloid cancer cells and analyzed peripheral blood leukocytes from 93 acute myeloid leukemia (AML) patients. Blood samples from consecutively diagnosed AML patients with high peripheral blood blast counts (>7x109/L, >70% blasts) were collected after informed consent was given and biobanked by cryo-preservation. AML samples was thawed and equilibrated for one hour in a defined serum-free medium (StemSpan SFEM medium, Stem Cell Technologies) which include insulin and transferrin. All samples were viability controlled and validated for growth factor response. Basal phosphorylation was determined using 17 phosphorylation specific antibodies: All staining panels contain the same 4 surface antibodies and a live dead discriminator; CD33(P67.6) PerCP-Cy5.5, CD38(HB7) PE-Cy7, CD34(581) PE, CD45(MEM-28) PE-Dynamics590 and phospho c-PARP(Asp214) Alexa Flour 700. Two phosphospecific antibodies were added to each panel with the respective direct conjugated dye Alexa Flour 488 and Alexa Flour 647; p38(pT180/pY182) and ERK2(pT202/pY204), SRC(pY418) and Akt(pT308), PDK1(pS241) and Akt(pS473), STAT1(pY701) and ribosomal protein S6(pS235/36), STAT3(pY705) and STAT5(pY694), CREB(pS133) and STAT3(pS727), ribosomal protein S6(pS240) and NFkB(pS529), 4EBP(pT37/pT45) and STAT6(Y641), without p-antibody and JNK(pT183/pY185). The lowest median signal for each phosphoprotein in AML cells and lymphocytes, respectively, were used as reference value for calculation of basal phosphorylation. Hierarchical clustering with the use of complete linkage were created using TM4, and Principal Component Analysis was carried out using Unscrambler X (CAMO Software). Results Unsupervised clustering revealed two distinct signature clusters based on low or elevated phosphorylation level among AML cells. A similar cluster signature was absent in endogenous non-leukemic lymphocytes from the same patients. No correlations between basal phosphorylation and prognostic mutations (FLT3 or NPM1), cytogenetics or response to first course of chemotherapy were found. In AML patients treated with intensive chemotherapy (n=45) the cluster with low phosphorylation level (n=19) correlated with significant (p=0.007) shorter overall survival. Principal component analysis verified the cluster analysis and guided a reduction to only three phosphoproteins (STAT3, 4EBP1, ribosomal protein S6) with statistically significant (p=0.014) stratification of survival. Conclusion Leukemic cells demonstrated a phosphorylation profile that reflected survival of the intensively treated patients, but surprisingly not correlated with mutational status of FLT3, NPM1, cytogenetics or first course remission status. This suggests that phosphoprotein determination in leukemic cells provide prognostic information so far not available with current diagnostics. The robust and relatively simple method of single cell signal profiling should be tested in clinical trials to examine its feasibility in therapy response prediction. More extensive mutational and epigenetic analyses are needed in search for the molecular origin of the low/high signal profiles. (A) Unsupervised hierarchical cluster analysis based on three phospho protein analysis stratified in two distinct clusters of patients receiving standard intensive induction chemotherapy (n=45; daunorubicin + cytarabine or idarubicin + cytarabine (3+7) similar to HOVON AML protocols 103 and 102, respectively). (B) Kaplan-Meier plot was performed calculating P value with the use mantel-Cox log-rank test. Disclosures: No relevant conflicts of interest to declare.


2000 ◽  
Vol 12 (5) ◽  
pp. 1057-1066 ◽  
Author(s):  
Brian Blais ◽  
Leon N. Cooper ◽  
Harel Shouval

Most simple and complex cells in the cat striate cortex are both orientation and direction selective. In this article we use single-cell learning rules to develop both orientation and direction selectivity in a natural scene environment. We show that a simple principal component analysis rule is inadequate for developing direction selectivity, but that the BCM rule as well as similar higher-order rules can. We also demonstrate that the convergence of lagged and nonlagged cells depends on the velocity of motion in the environment, and that strobe rearing disrupts this convergence, resulting in a loss of direction selectivity.


2018 ◽  
Vol 25 (12) ◽  
pp. 1365-1373 ◽  
Author(s):  
Snehalika Lall ◽  
Debajyoti Sinha ◽  
Sanghamitra Bandyopadhyay ◽  
Debarka Sengupta

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