SGK1, a Serine/Threonine Kinase, Inhibits Prototype Foamy Virus Replication.

Foamy viruses (FVs) are complex retroviruses belonging to the Spumaretrovirinae subfamily of the Retroviridae family. In contrast to human immunodeficiency virus (HIV), another member of the Retroviridae family, FVs are nonpathogenic in their natural hosts or in experimentally infected animals. Prototype foamy virus (PFV) is the only foamy virus that can infect humans through cross-species transmission and does not show any pathogenicity after infection. Consequently, PFV is considered a safe and efficient gene transfer vector. Understanding the host proteins involved in the replication of PFV and the mechanism of interaction between the host and the virus might lead to studies to improve the efficiency of gene transfer. To date, only a few host factors have been identified that affect PFV replication. In the present study, we report that PFV infection enhances the promoter activity of SGK1 (encoding serum/glucocorticoid regulated kinase 1) via the Tas protein signaling pathway, and then upregulates the mRNA and protein levels of SGK1. Overexpression of SGK1 reduced PFV replication, whereas its depletion using small interfering RNA increased PFV replication. SGK1 inhibits PFV replication by impairing the function of the PFV Tas activation domain in a kinase-independent manner and reducing the stability of the Gag protein in a kinase-dependent manner. In addition, both human and bovine SGK1 proteins inhibit the replication of bovine foamy virus (BFV) and PFV. These findings not only improved our understanding of the function of SGK1 and its relationship with foamy viruses, but also contributed to determining the antiviral mechanism of the host. IMPORTANCE Foamy viruses can integrate into the host chromosome and are nonpathogenic in natural hosts or in experimentally infected animals. Therefore, foamy viruses are considered to be safe and efficient gene transfer vectors. Persistent infection of foamy viruses is partly caused by the restrictive effect of host factors on the virus. However, only a few cellular proteins are known to influence the replication of foamy viruses. In this study, we report that SGK1 inhibits the replication of prototype foamy virus by affecting the function of the transcription activator, Tas, and reducing the stability of the structural protein, Gag. These results will increase our understanding of the interaction between the virus and host factors, deepening our perception of host antiviral defenses and the function of SGK1, and could improve the gene transfer efficiency of foamy viruses.

Applications of emerging imaging techniques for meat quality and safety detection and evaluation: A review.

With improvement in people's living standards, many people nowadays pay more attention to quality and safety of meat. However, traditional methods for meat quality and safety detection and evaluation, such as manual inspection, mechanical methods, and chemical methods, are tedious, time-consuming, and destructive, which cannot meet the requirements of modern meat industry. Therefore, seeking out rapid, non-destructive, and accurate inspection techniques is important for the meat industry. In recent years, a number of novel and noninvasive imaging techniques, such as optical imaging, ultrasound imaging, tomographic imaging, thermal imaging, and odor imaging, have emerged and shown great potential in quality and safety assessment. In this paper, a detailed overview of advanced applications of these emerging imaging techniques for quality and safety assessment of different types of meat (pork, beef, lamb, chicken, and fish) is presented. In addition, advantages and disadvantages of each imaging technique are also summarized. Finally, future trends for these emerging imaging techniques are discussed, including integration of multiple imaging techniques, cost reduction, and developing powerful image-processing algorithms.

Non-destructive prediction of thiobarbituricacid reactive substances (TBARS) value for freshness evaluation of chicken meat using hyperspectral imaging.

This study examined the potential of hyperspectral imaging (HSI) for rapid prediction of 2-thiobarbituric acid reactive substances (TBARS) content in chicken meat during refrigerated storage. Using the spectral data and the reference values of TBARS, a partial least square regression (PLSR) model was established and yielded acceptable results with regression coefficients in prediction (Rp) of 0.944 and root mean squared errors estimated by prediction (RMSEP) of 0.081. To simplify the calibration model, ten optimal wavelengths were selected by successive projections algorithm (SPA). Then, a new SPA-PLSR model based on the selected wavelengths was built and showed good results with Rp of 0.801 and RMSEP of 0.157. Finally, an image algorithm was developed to achieve image visualization of TBARS values in some representative samples. The encouraging results of this study demonstrated that HSI is suitable for determination of TBARS values for freshness evaluation in chicken meat.

Quantitative determination of total pigments in red meats using hyperspectral imaging and multivariate analysis.

This study investigated the potential of hyperspectral imaging (HSI) for quantitative determination of total pigments in red meats, including beef, goose, and duck. Partial least squares regression (PLSR) was applied to correlate the spectral data with the reference values of total pigments measured by a traditional method. In order to simplify the PLSR model based on the full spectra, eleven optimal wavelengths were selected using successive projections algorithm (SPA). The new SPA-PLSR model yielded good results with the coefficient of determination (R(2)p) of 0.953, root mean square error (RMSEP) of 9.896, and ratio of prediction to deviation (RPD) of 4.628. Finally, distribution maps of total pigments in red meats were developed using an image processing algorithm. The overall results from this study indicated HSI had the capability for predicting total pigments in red meats.

Potential of hyperspectral imaging for rapid prediction of hydroxyproline content in chicken meat.

In this study, the potential of hyperspectral imaging (HSI) for predicting hydroxyproline content in chicken meat was investigated. Spectral data contained in the hyperspectral images (400-1000 nm) of chicken meat was extracted, and a partial least square regression (PLSR) model was then developed for predicting hydroxyproline content. The model yielded acceptable results with regression coefficient in prediction (Rp) of 0.874 and root mean error squares in prediction (RMESP) of 0.046. Based on the eight optimal wavelengths selected by regression coefficients (RC) from the PLSR model, a new RC-PLSR model was built and good results were shown with high Rp of 0.854 and low RMSEP of 0.049. Finally, distribution maps of hydroxyproline were created by transferring the RC-PLSR model to each pixel in the hyperspectral images. The results demonstrated that HSI has the capability for rapid and non-destructive determination of hydroxyproline content in chicken meat.

Applications of hyperspectral imaging in chicken meat safety and quality detection and evaluation: a review.

Currently, the issue of food safety and quality is a great public concern. In order to satisfy the demands of consumers and obtain superior food qualities, non-destructive and fast methods are required for quality evaluation. As one of these methods, hyperspectral imaging (HSI) technique has emerged as a smart and promising analytical tool for quality evaluation purposes and has attracted much interest in non-destructive analysis of different food products. With the main advantage of combining both spectroscopy technique and imaging technique, HSI technique shows a convinced attitude to detect and evaluate chicken meat quality objectively. Moreover, developing a quality evaluation system based on HSI technology would bring economic benefits to the chicken meat industry. Therefore, in recent years, many studies have been conducted on using HSI technology for the safety and quality detection and evaluation of chicken meat. The aim of this review is thus to give a detailed overview about HSI and focus on the recently developed methods exerted in HSI technology developed for microbiological spoilage detection and quality classification of chicken meat. Moreover, the usefulness of HSI technique for detecting fecal contamination and bone fragments of chicken carcasses are presented. Finally, some viewpoints on its future research and applicability in the modern poultry industry are proposed.