Evolution of ochratoxin A content during red and rose vinification

BACKGROUND: This work aims to investigate the effects of the common vinification steps on the fate of the ochratoxin A (OTA) during wine making. Two assays of red and rose microvinification, with artificially contaminated grapes, were performed. The content of this mycotoxin was also monitored throughout the process of red wine making from naturally contaminated grapes in a winery. RESULTS: The results from the different assays revealed that the maceration of pomace have a significant effect on the increase of OTA content in red wine (P < 0.05) whereas the alcoholic fermentation had a reducing effect. However, the spontaneous malolactic fermentation showed no significant effect on the OTA content in wine (P > 0.05). Storage of red wine in tanks followed by draining caused a significant decrease of OTA of about 55%. Clarification with a gelatin oenological fining agent contributed to the removal of up to 58% of OTA from red wine. CONCLUSION: Overall, a consistent decrease in OTA concentration was noticed throughout either red or rose vinification. This work has contributed to the understanding of the fate of OTA during different vinification processes, especially from naturally contaminated grapes. Copyright © 2008 Society of Chemical Industry     

SURFACE EXCITATION PARAMETER IN QUANTITATIVE SURFACE ANALYSIS BY ELECTRON SPECTROSCOPY

The investigation of influence of surface effects on the energy spectra of electrons is essential for comprehensive understanding of electron-solid interactions as well as quantitative analysis. The accuracy of the analysis depends on the models for elastic and inelastic interactions. Electrons impinging on a solid or escaping from it suffer losses in the surface layer. The energy loss spectra therefore have contributions from surface excitations. The role of surface excitations is characterized by surface excitation parameter (SEP), which indicates the number of surface plasmons created by an electron crossing the surface. The imaginary part of complex self-energy of an electron is related to the energy.‘ loss cross section. SEP is numerically computed using self-energy formalism and compared with the results as described and calculated by different workers.     

ENERGY-LOSS FUNCTIONS DERIVED FROM REELS SPECTRA FOR ALUMINUM

The effective energy loss functions for Al have been derived from differential inverse inelastic mean free path based on the extended Landau approach. It has been revealed that the effective energy loss function is very close in value to the theoretical surface energy loss function in the lower energy loss region but graduaUy approaches the theoretical bulk energy loss function in the higher energy loss region. Moreover, the intensity corresponding to surface excitation in effective energy loss functions decreases with the increase of primary electron energy. These facts show that the present effective energy loss function describes not only surface excitation but also bulk excitation. At last, REELS spectra simulated by Monte Carlo method based on use of the effective energy loss functions has reproduced the experimental REELS spectra with considerable success.     

From Blood to Regenerative Tissue: How Autologous Platelet-Rich Fibrin Can Be Combined with Other Materials to Ensure Controlled Drug and Growth Factor Release

The purpose of this review is to examine the latest literature on the use of autologous platelet-rich fibrin as a drug and growth factor carrier system in maxillofacial surgery. Autologous platelet-rich fibrin (PRF) is a unique system that combines properties such as biocompatibility and biodegradability, in addition to containing growth factors and peptides that provide tissue regeneration. This opens up new horizons for the use of all beneficial ingredients in the blood sample for biomedical purposes. By itself, PRF has an unstable effect on osteogenesis: therefore, advanced approaches, including the combination of PRF with materials or drugs, are of great interest in clinics. The main advantage of drug delivery systems is that by controlling drug release, high drug concentrations locally and fewer side effects within other tissue can be achieved. This is especially important in tissues with limited blood supply, such as bone tissue compared to soft tissue. The ability of PRF to degrade naturally is considered an advantage for its use as a “warehouse” of controlled drug release systems. We are focusing on this concentrate, as it is easy to use in manipulations and can be delivered directly to the surgical site. The target audience for this review are researchers and medical doctors who are involved in the development and research of PRFs further studies. Likewise, surgeons who use PRF in their work to treat patients and who advice patients to take the medicine orally.     

Injectable Platelet-Rich Fibrin as a Drug Carrier Increases the Antibacterial Susceptibility of Antibiotic—Clindamycin Phosphate

The aim of this study was to investigate the change in clindamycin phosphate antibacterial properties against Gram-positive bacteria using the platelet-rich fibrin as a carrier matrix, and evaluate the changes in the antibiotic within the matrix. The antibacterial properties of CLP and its combination with PRF were tested in a microdilution test against reference cultures and clinical isolates of Staphylococcus aureus (S. aureus) or Staphylococcus epidermidis (S. epidermidis). Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) analysis was done to evaluate the changes in the PRF_CLP matrix. Release kinetics of CLP was defined with ultra-performance liquid chromatography (UPLC). According to FTIR data, the use of PRF as a carrier for CLP ensured the structural changes in the CLP toward a more active form of clindamycin. A significant decrease in minimal bactericidal concentration values (from 1000 µg/mL to 62 µg/mL) against reference cultures and clinical isolates of S. aureus and S. epidermidis was observed for the CLP and PRF samples if compared to pure CLP solution. In vitro cell viability tests showed that PRF and PRF with CLP have higher cell viability than 70% after 24 h and 48 h time points. This article indicates that CLP in combination with PRF showed higher antibacterial activity against S. aureus and S. epidermidis compared to pure CLP solution. This modified PRF could be used as a novel method to increase drug delivery and efficacy, and to reduce the risk of postoperative infection.     

Channel coordination with quantity discounts and/or cooperative advertising

We assess the interactive effects of two commonly used channel coordination mechanisms (quantity discounts (QDs) and cooperative advertising (CA)). We use a game-theoretic model and solve four non-cooperative games. In the first game, neither QDs nor CA is implemented. Cooperative advertising alone is offered in the second game, while quantity discounts alone are offered in the third game. In the fourth game, both QDs and CA are implemented. We obtain analytical solutions and compare equilibrium results across games to assess the effectiveness of CA (QDs) when implemented alone or jointly with QDs (CA). The main findings suggest that the profitability of each of these mechanisms is affected by whether the other is implemented or not in the channel. For example, while CA benefits the manufacturer when implemented alone, it can increase or decrease the manufacturer’s profit when added to QDs. Looking at which coordination mechanism is most effective when used alone, we find that both the manufacturer and the supply chain prefer QDs to CA. Finally, the retailer may not benefit from either one or both of these coordination mechanisms, especially if marketing efforts are not highly effective.     

Plasma Levels of 14:0, 16:0, 16:1n-7, and 20:3n-6 are Positively Associated,but 18:0 and 18:2n-6 are Inversely Associated with Markers of Inflammation in Young Healthy Adults

Inflammation is a recognized risk factor for the development of chronic diseases, such as type 2 diabetes and atherosclerosis. Evidence suggests that individual fatty acids (FA) may have distinct influences on inflammatory processes. The goal of this study was to conduct a cross-sectional analysis to examine the associations between circulating FA and markers of inflammation in a population of young healthy Canadian adults. FA, high-sensitivity C-reactive protein (hsCRP), and cytokines were measured in fasted plasma samples from 965 young adults (22.6 ± 0.1 years). Gas chromatography was used to measure FA. The following cytokines were analyzed with a multiplex assay: regulated upon activation normal T cell expressed and secreted (RANTES/CCL5), interleukin 1-receptor antagonist (IL-1Ra), interferon-γ (IFN-γ), interferon-γ inducible protein 10 (IP-10), and platelet-derived growth factor β (PDGF-ββ). Numerous statistically significant associations (p < 0.05, corrected for multiple testing) were identified between individual FA and markers of inflammation using linear regression. Myristic (14:0), palmitic (16:0), palmitoleic (16:1n-7), and dihomo-γ-linolenic (20:3n-6) acids were positively associated with all markers of inflammation. In contrast, stearic acid (18:0) was inversely associated with hsCRP and RANTES, and linoleic acid (18:2n-6) was inversely associated with hsCRP, RANTES and PDGF-ββ. In conclusion, our results indicate that specific FA are distinctly correlated with various markers of inflammation. Moreover, the findings of this study suggest that FA profiles in young adults may serve as an early indicator for the development of future complications comprising an inflammatory component.     

Blood vessel segmentation and extraction using H-minima method based on image processing techniques

Multimedia Tools and Applications - In this paper, the H-minima transform is used for blood vessel segmentation. The aim of this study is to get the high accuracy of blood vessel segmentation in...     

Generative adversarial network (GAN) and enhanced root mean square error (ERMSE): deep learning for stock price movement prediction

The prediction of stock price movement direction is significant in financial circles and academic. Stock price contains complex, incomplete, and fuzzy information which makes it an extremely difficult task to predict its development trend. Predicting and analysing financial data is a nonlinear, time-dependent problem. With rapid development in machine learning and deep learning, this task can be performed more effectively by a purposely designed network. This paper aims to improve prediction accuracy and minimizing forecasting error loss through deep learning architecture by using Generative Adversarial Networks. It was proposed a generic model consisting of Phase-space Reconstruction (PSR) method for reconstructing price series and Generative Adversarial Network (GAN) which is a combination of two neural networks which are Long Short-Term Memory (LSTM) as Generative model and Convolutional Neural Network (CNN) as Discriminative model for adversarial training to forecast the stock market. LSTM will generate new instances based on historical basic indicators information and then CNN will estimate whether the data is predicted by LSTM or is real. It was found that the Generative Adversarial Network (GAN) has performed well on the enhanced root mean square error to LSTM, as it was 4.35% more accurate in predicting the direction and reduced processing time and RMSE by 78 s and 0.029, respectively. This study provides a better result in the accuracy of the stock index. It seems that the proposed system concentrates on minimizing the root mean square error and processing time and improving the direction prediction accuracy, and provides a better result in the accuracy of the stock index.

     

Detection and spatial analysis of selective logging with geometrically corrected Landsat images

The Brazilian Amazonian rain forests are under imminent threat of serious degradation and ultimately deforestation. Human activities such as selective logging are an important cause. Selectively logged locations are difficult to detect from medium-resolution Landsat images, due to their relatively small sizes and subtle spatial patterns. Spectral linear unmixing provides an effective tool for the purpose. The orientation of geometrically corrected images, however, artificially introduces zero-reflectance background pixels. These change the variance–covariance structure of the image bands and hinder the identification of pure endmembers. In this study, we compare image cropping and image rotation as two alternative approaches. Selectively logged forests were detected in northern Rondônia state, north-western Mato Grosso state and south-eastern Amazonas state in Brazil by applying spectral unmixing. The study shows that image rotation is a better approach as it preserves the image extent and thus provides information on forest degradation over a wider region. Spatial statistical analysis of the detected locations shows strong clustering within the study area. We conclude that the endmembers used in this study represent basic components of a degraded forest environment. As spectral unmixing of remote-sensing images avoids collection of field data, it may broadly be applied towards other Amazonian regions as well.