Curcumin-based photosensitization inactivates Aspergillus flavus and reduces aflatoxin B1 in maize kernels

Different methods have been applied in controlling contamination of foods and feeds by the carcinogenic fungal toxin, aflatoxin, but nevertheless the problem remains pervasive in developing countries. Curcumin is a natural polyphenolic compound from the spice turmeric (Curcuma longa L.) that has been identified as an efficient photosensitiser for inactivation of Aspergillus flavus conidia. Curcumin mediated photoinactivation of A. flavus has revealed the potential of this technology to be an effective method for reducing population density of the aflatoxin-producing fungus in foods. This study demonstrates the influence of pH and temperature on efficiency of photoinactivation of the fungus and how treating spore-contaminated maize kernels affects aflatoxin production. The results show the efficiency of curcumin mediated photoinactivation of fungal conidia and hyphae were not affected by temperatures between 15 and 35 °C or pH range of 1.5–9.0. The production of aflatoxin B was significantly lower (p < 0.05), with an average of 82.4 μg/kg as compared to up to 305.9 μg/kg observed in untreated maize kept under similar conditions. The results of this study indicate that curcumin mediated photosensitization can potentially be applied under simple environmental conditions to achieve significant reduction of post-harvest contamination of aflatoxin B in maize

Mesenchymal stem cell therapy promotes renal repair by limiting glomerular podocyte and progenitor cell dysfunction in adriamycin-induced nephropathy

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Evaluation of the zucker diabetic fatty (ZDF) rat as a model for human disease based on urinary peptidomic profiles

Representative animal models for diabetes-associated vascular complications are extremely relevant in assessing potential therapeutic drugs. While several rodent models for type 2 diabetes (T2D) are available, their relevance in recapitulating renal and cardiovascular features of diabetes in man is not entirely clear. Here we evaluate at the molecular level the similarity between Zucker diabetic fatty (ZDF) rats, as a model of T2D-associated vascular complications, and human disease by urinary proteome analysis. Urine analysis of ZDF rats at early and late stages of disease compared to age- matched LEAN rats identified 180 peptides as potentially associated with diabetes complications. Overlaps with human chronic kidney disease (CKD) and cardiovascular disease (CVD) biomarkers were observed, corresponding to proteins marking kidney damage (eg albumin, alpha-1 antitrypsin) or related to disease development (collagen). Concordance in regulation of these peptides in rats versus humans was more pronounced in the CVD compared to the CKD panels. In addition, disease-associated predicted protease activities in ZDF rats showed higher similarities to the predicted activities in human CVD. Based on urinary peptidomic analysis, the ZDF rat model displays similarity to human CVD but might not be the most appropriate model to display human CKD on a molecular level

A Multi-Institutional Approach to Delivering Shared Curricula for Developing a Next-Generation Energy Workforce

In this paper, we consider collaborative power systems education through the FEEDER consortium. To increase students\u27 access to power engineering educational content, the consortium of seven universities was formed. A framework is presented to characterize different collaborative education activities among the universities. Three of these approaches of collaborative educational activities are presented and discussed. These include 1) cross-institutional blended courses (“MS-MD”); 2) cross-institutional distance courses (“SS-MD”); and 3) single-site special experiential courses and concentrated on-site programs available to students across consortium institutions (“MS-SD”). This paper presents the advantages and disadvantages of each approach

Will systems biology offer new holistic paradigms to life sciences?

A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the “essence of complexity” given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms

Evaluation of regression models in metabolic physiology: predicting fluxes from isotopic data without knowledge of the pathway

This study explores the ability of regression models, with no knowledge of the underlying physiology, to estimate physiological parameters relevant for metabolism and endocrinology. Four regression models were compared: multiple linear regression (MLR), principal component regression (PCR), partial least-squares regression (PLS) and regression using artificial neural networks (ANN). The pathway of mammalian gluconeogenesis was analyzed using [U−(13)C]glucose as tracer. A set of data was simulated by randomly selecting physiologically appropriate metabolic fluxes for the 9 steps of this pathway as independent variables. The isotope labeling patterns of key intermediates in the pathway were then calculated for each set of fluxes, yielding 29 dependent variables. Two thousand sets were created, allowing independent training and test data. Regression models were asked to predict the nine fluxes, given only the 29 isotopomers. For large training sets (>50) the artificial neural network model was superior, capturing 95% of the variability in the gluconeogenic flux, whereas the three linear models captured only 75%. This reflects the ability of neural networks to capture the inherent non-linearities of the metabolic system. The effect of error in the variables and the addition of random variables to the data set was considered. Model sensitivities were used to find the isotopomers that most influenced the predicted flux values. These studies provide the first test of multivariate regression models for the analysis of isotopomer flux data. They provide insight for metabolomics and the future of isotopic tracers in metabolic research where the underlying physiology is complex or unknown

Renal progenitors derived from human iPSCs engraft and restore function in a mouse model of acute kidney injury

Acute kidney injury (AKI) is one of the most relevant health issues, leading to millions of deaths. The magnitude of the phenomenon remarks the urgent need for innovative and effective therapeutic approaches. Cell-based therapy with renal progenitor cells (RPCs) has been proposed as a possible strategy. Studies have shown the feasibility of directing embryonic stem cells or induced Pluripotent Stem Cells (iPSCs) towards nephrogenic intermediate mesoderm and metanephric mesenchyme (MM). However, the functional activity of iPSC-derived RPCs has not been tested in animal models of kidney disease. Here, through an efficient inductive protocol, we directed human iPSCs towards RPCs that robustly engrafted into damaged tubuli and restored renal function and structure in cisplatin-mice with AKI. These results demonstrate that iPSCs are a valuable source of engraftable cells with regenerative activity for kidney disease and create the basis for future applications in stem cell-based therapy

Effect of the Monocyte Chemoattractant Protein-1/CC Chemokine Receptor 2 System on Nephrin Expression in Streptozotocin-Treated Mice and Human Cultured Podocytes

OBJECTIVE-Monocyte chemoattractant protein-1 (MCP-1), a chemokine binding to the CC chemokine receptor 2 (CCR2) and promoting monocyte infiltration, has been implicated in the pathogenesis of diabetic nephropathy. To assess the potential relevance of the MCP-1/CCR2 system in the pathogenesis of diabetic proteinuria, we studied in vitro if MCP-1 binding to the CCR2 receptor modulates nephrin expression in cultured podocytes. Moreover, we investigated in vivo if glomerular CCR2 expression is altered in kidney biopsies from patients with diabetic nephropathy and whether lack of MCP-1 affects proteinuria and expression of nephrin in experimental diabetes. RESEARCH DESIGN AND METHODS-Expression of nephrin was assessed in human podocytes exposed to rh-MCP-1 by immunofluorescence and real-time PCR. Glomerular CCR2 expression was studied in 10 kidney sections from patients with overt nephropathy and eight control subjects by immunohistochemistry. Both wild-type and MCP-1 knockout mice were made diabetic with streptozotocin. Ten weeks after the onset of diabetes, albuminuria and expression of nephrin, synaptopodin, and zonula occludens-1 were examined by immunofluorescence and immunoblotting. RESULTS-In human podocytes, MCP-1 binding to the CCR2 receptor induced a significant reduction in nephrin both mRNA and protein expression via a Rho-dependent mechanism. The MCP-1 receptor, CCR2, was overexpressed in the glomerular podocytes of patients with overt nephropathy. In experimental diabetes, MCP-1 was overexpressed within the glomeruli and the absence of MCP-1 reduced both albuminuria and downregulation of nephrin and synaptopodin. CONCLUSIONS-These findings suggest that the MCP-1/CCR2 system may be relevant in the pathogenesis of proteinuria in diabetes