Metabolic peculiarities of Aspergillus niger disclosed by comparative metabolic genomics

A genome-scale metabolic network and an in-depth genomic comparison of Aspergillus niger with seven other fungi is presented, revealing more than 1,100 enzyme-coding genes that are unique to A. niger

The intra- and extracellular proteome of Aspergillus niger growing on defined medium with xylose or maltose as carbon substrate

The filamentous fungus Aspergillus niger is well-known as a producer of primary metabolites and extracellular proteins. For example, glucoamylase is the most efficiently secreted protein of Aspergillus niger, thus the homologous glucoamylase (glaA) promoter as well as the glaA signal sequence are widely used for heterologous protein production. Xylose is known to strongly repress glaA expression while maltose is a potent inducer of glaA promoter controlled genes. For a more profound understanding of A. niger physiology, a comprehensive analysis of the intra- and extracellular proteome of Aspergillus niger AB1.13 growing on defined medium with xylose or maltose as carbon substrate was carried out using 2-D gel electrophoresis/Maldi-ToF and nano-HPLC MS/MS

New perspectives on citizen journalism: Introduction to special issue

In the aftermath of the South Asian tsunami of 26 December 2004, the term ‘citizen journalism’ swiftly gained currency with global news organisations finding themselves in the difficult position of being largely dependent on ‘amateur’ photographs, video footage and eyewitness accounts to tell the story of what was transpiring on the ground in the most severely affected areas. Despite its ambiguities, the term was widely perceived to capture the countervailing ethos of the ordinary person’s capacity to contribute to professional news coverage, thereby providing commentators with a useful label to characterise an ostensibly new genre of user-generated content

Emerging trends for nonthermal decontamination of raw and processed meat: ozonation, high-hydrostatic pressure and cold plasma

Meat may contain natural, spoilage, and pathogenic microorganisms based on the origin and characteristics of its dietary matrix. Several decontamination substances are used during or after meat processing, which include chlorine, organic acids, inorganic phosphates, benzoates, propionates, bacteriocins, or oxidizers. Unfortunately, traditional decontamination methods are often problematic because of their adverse impact on the quality of the raw carcass or processed meat. The extended shelf-life of foods is a response to the pandemic trend, whereby consumers are more likely to choose durable products that can be stored for a longer period between visits to food stores. This includes changing purchasing habits from “just in time” products “for now” to “just in case” products, a trend that will not fade away with the end of the pandemic. To address these concerns, novel carcass-decontamination technologies, such as ozone, high-pressure processing and cold atmospheric plasma, together with active and clean label ingredients, have been investigated for their potential applications in the meat industry. Processing parameters, such as exposure time and processing intensity have been evaluated for each type of matrix to achieve the maximum reduction of spoilage microorganism counts without affecting the physicochemical, organoleptic, and functional characteristics of the meat products. Furthermore, combined impact (hurdle concept) was evaluated to enhance the understanding of decontamination efficiency without undesirable changes in the meat products. Most of these technologies are beneficial as they are cost-effective, chemical-free, eco-friendly, easy to use, and can treat foods in sealed packages, preventing the product from post-process contamination. Interestingly, their synergistic combination with other hurdle approaches can help to substitute the use of chemical food preservatives, which is an aspect that is currently quite desirable in the majority of consumers. Nonetheless, some of these techniques are difficult to store, requiring a large capital investment for their installation, while a lack of certification for industrial utilization is also problematic. In addition, most of them suffer from a lack of sufficient data regarding their mode of action for inactivating microorganisms and extending shelf-life stability, necessitating a need for further research in this area.Axencia Galega de Innovación | Ref. IN607A2019/0

Probing the impact of sustainable emerging sonication and DBD plasma technologies on the quality of wheat sprouts juice

Financiado para publicación en acceso aberto: Universidade de Vigo/CISUGSonication and dielectric barrier discharge (DBD) plasma are sustainable emerging food processing technologies. The study investigates the impact of sonication, DBD-plasma, and thermal treatment (TT) on wheat sprout juice. The obtained results indicated a significant (p < 0.05) increase in chlorophyll, total phenolics, flavonoids, DPPH assay, and ORAC assay after DBD-plasma (40 V) and sonication (30 mins) treatment as compared to TT and untreated samples. Both emerging technologies significantly (p < 0.05) reduce the polyphenol oxidase and peroxidase activities, but the TT sample had the highest reduction. Moreover, the synergistic application of both technologies significantly reduced the E. coli/Coliform, aerobics, yeast and mold up to the 2 log reduction, but the TT sample had a complete reduction. DBD-plasma and sonication processing significantly decreased (p < 0.05) the particle size, reducing apparent viscosity (η) and consistency index (K); while increasing the flow behavior (n), leading to higher stability of wheat sprout juice. To assess the impact of emerging techniques on nutrient concentration, we used surface-enhance Raman spectroscopy (SERS) as an emerging method. Silver-coated gold nano-substrates were used to compare the nutritional concentration of wheat sprout juice treated with sonication, DBD-plasma, and TT-treated samples. Results showed sharp peaks for samples treated with DBD-plasma followed by sonication, untreated, and TT. The obtained results, improved quality of wheat sprout juice, and lower microbial and enzymatic loads were confirmed, showing the suitability of these sustainable processing techniques for food processing and further research

A risk prediction model for type 2 diabetes mellitus complicated with retinopathy based on machine learning and its application in health management

ObjectiveThis study aimed to establish a risk prediction model for diabetic retinopathy (DR) in the Chinese type 2 diabetes mellitus (T2DM) population using few inspection indicators and to propose suggestions for chronic disease management.MethodsThis multi-centered retrospective cross-sectional study was conducted among 2,385 patients with T2DM. The predictors of the training set were, respectively, screened by extreme gradient boosting (XGBoost), a random forest recursive feature elimination (RF-RFE) algorithm, a backpropagation neural network (BPNN), and a least absolute shrinkage selection operator (LASSO) model. Model I, a prediction model, was established through multivariable logistic regression analysis based on the predictors repeated ≥3 times in the four screening methods. Logistic regression Model II built on the predictive factors in the previously released DR risk study was introduced into our current study to evaluate the model’s effectiveness. Nine evaluation indicators were used to compare the performance of the two prediction models, including the area under the receiver operating characteristic curve (AUROC), accuracy, precision, recall, F1 score, balanced accuracy, calibration curve, Hosmer-Lemeshow test, and Net Reclassification Index (NRI).ResultsWhen including predictors, such as glycosylated hemoglobin A1c, disease course, postprandial blood glucose, age, systolic blood pressure, and albumin/urine creatinine ratio, multivariable logistic regression Model I demonstrated a better prediction ability than Model II. Model I revealed the highest AUROC (0.703), accuracy (0.796), precision (0.571), recall (0.035), F1 score (0.066), Hosmer-Lemeshow test (0.887), NRI (0.004), and balanced accuracy (0.514).ConclusionWe have built an accurate DR risk prediction model with fewer indicators for patients with T2DM. It can be used to predict the individualized risk of DR in China effectively. In addition, the model can provide powerful auxiliary technical support for the clinical and health management of patients with diabetes comorbidities

High-pressure processing of fish and shellfish products: Safety, quality, and research prospects

Seafood products have been one of the main drivers behind the popularity of high-pressure processing (HPP) in the food industry owing to a high demand for fresh ready-to-eat seafood products and food safety. This review provides an overview of the advanced knowledge available on the use of HPP for production of wholesome and highly nutritive clean label fish and shellfish products. Out of 653 explored items, 65 articles published during 2016-2021 were used. Analysis of the literature showed that most of the earlier work evaluated the HPP effect on physicochemical and sensorial properties, and limited information is available on nutritional aspects. HPP has several applications in the seafood industry. Application of HPP (400-600 MPa) eliminates common seafood pathogens, such as Vibrio and Listeria spp., and slows the growth of spoilage microorganisms. Use of cold water as a pressure medium induces minimal changes in sensory and nutritional properties and helps in the development of clean label seafood products. This technology (200-350 MPa) is also useful to shuck oysters, lobsters, crabs, mussels, clams, and scallops to increase recovery of the edible meat. High-pressure helps to preserve organoleptic and functional properties for an extended time during refrigerated storage. Overall, HPP helps seafood manufacturers to maintain a balance between safety, quality, processing efficiency, and regulatory compliance. Further research is required to understand the mechanisms of pressure-induced modifications and clean label strategies to minimize these modifications