Authentication and Discrimination of Green Tea Samples Using UV-Visible, FTIR and HPLC Techniques Coupled with Chemometrics Analysis

Green tea is a popular beverage consumed worldwide. Its quality should be controlled adequately as the quality is influenced by several factors in addition to adulterations. This study aimed to develop a simple method for assessing the quality of green tea samples obtained from the South and the East Asian regions. The UV-Visible, FTIR and HPLC data from 38 samples were subjected to multivariate analyses using the unsupervised recognition techniques comprising Hierarchical Cluster Analysis (HCA) and Principal Component Analysis (PCA). The model for their authentication was constructed and validated by applying the supervised recognition techniques as Soft Independent Modeling of Class Analogy (SIMCA) and Partial Least Square Discriminant Analysis (PLS-DA). The percentages of caffeine in the identified samples were determined using a validated HPLC assay in addition to in vitro determination of their antioxidant activity using DPPH radical-scavenging capacity assay. HCA and PCA based on UV data successfully distributed the tested samples into informative clusters. However, that obtained from visible data could only differentiate samples with respect to their powdered condition. On the contrary, PCA from FTIR and HPLC data could hardly discriminate any of the samples. The models constructed using SIMCA and PLS-DA showed a good class separation between the South and the East Asian samples. The percentages of caffeine in the identified samples and the IC50 in DPPH assay are greatly diverse among all the tested samples. Thus, UV spectroscopy and chemometrics have provided a simple and quick tool for the quality control of commercial green tea samples

Studying the Effect of Adding Titanium Dioxide (TiO2) Nanoparticles on the Compressive Strength of Chemical and Heat-activated Acrylic Denture Base Resins

Problem: The commonly used acrylic resins for fabricating denture base suffer from poor mechanical properties. Aim: This study aimed to assess the effect of incorporating Titanium Dioxide (TiO2) nanoparticles (NPs) as a reinforcement agent on the compressive strength of acrylic denture base materials. Materials and methods: Thirty-two cylindrical specimens (22 mm in height and 12 mm in diameter) were prepared from PMMA resins with and without TiO2 NPs. They were allocated into two main groups according to the materials used such as cold cure and heat cure denture base resins and then subdivided into two subgroups each containing eight specimens: control (without nanoparticles) and experimental (with 2 wt.% TiO2 NPs). TiO2 NPs were synthesized via a chemical processing route and particle morphology and size distribution were assessed using SEM and AFM while XRD technique was employed to determine the crystalline structure of the NPs. Compression test was performed on the specimens using a universal Instron testing machine to compare the compressive strength. Results: Size of crystalline TiO2 NPs varied between 40-80 nm. The mean compressive strength for the cold cure acrylic resin (control group) and its nanocomposite (experimental group) were found as 15.37 MPa and 17.42 MPa while for the heat cure acrylic resin and its nanocomposite were 23.04 MPa and 24.30 MPa. A statistically significant difference was recorded in the compressive strength between the cold cure acrylic resin and its nanocomposite. However, the difference was non-significant in the case of heat cure acrylic resin. Conclusion: The compressive strength of both cold cure and heat cure acrylic resins increased after incorporation TiO2 NPs

Author Correction: Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

Author Correction: Genomic risk score offers predictive performance comparable to clinical risk factors for ischaemic stroke.

An amendment to this paper has been published and can be accessed via a link at the top of the paper

The interferon-stimulated gene product oligoadenylate synthetase-like protein enhances replication of Kaposi’s sarcoma-associated herpesvirus (KSHV) and interacts with the KSHV ORF20 protein

Kaposi’s sarcoma-associated herpesvirus (KSHV) is one of the few oncogenic human viruses known to date. Its large genome encodes more than 85 proteins and includes both unique viral proteins as well as proteins conserved amongst herpesviruses. KSHV ORF20 is a member of the herpesviral core UL24 family, but the function of ORF20 and its role in the viral life cycle is not well understood. ORF20 encodes three largely uncharacterized isoforms, which we found were localized predominantly in the nuclei and nucleoli. Quantitative affinity purification coupled to mass spectrometry (q-AP-MS) identified numerous specific interacting partners of ORF20, including ribosomal proteins and the interferon-stimulated gene product (ISG) oligoadenylate synthetase-like protein (OASL). Both endogenous and transiently transfected OASL co-immunoprecipitated with ORF20, and this interaction was conserved among all ORF20 isoforms and multiple ORF20 homologs of the UL24 family in other herpesviruses. Characterization of OASL interacting partners by q-AP-MS identified a very similar interactome to that of ORF20. Both ORF20 and OASL copurified with 40S and 60S ribosomal subunits, and when they were co-expressed, they associated with polysomes. Although ORF20 did not have a global effect on translation, ORF20 enhanced RIG-I induced expression of endogenous OASL in an IRF3-dependent but IFNAR-independent manner. OASL has been characterized as an ISG with antiviral activity against some viruses, but its role for gammaherpesviruses was unknown. We show that OASL and ORF20 mRNA expression were induced early after reactivation of latently infected HuARLT-rKSHV.219 cells. Intriguingly, we found that OASL enhanced infection of KSHV. During infection with a KSHV ORF20stop mutant, however, OASL-dependent enhancement of infectivity was lost. Our data have characterized the interaction of ORF20 with OASL and suggest ORF20 usurps the function of OASL to benefit KSHV infection

Analysis of MicroRNA Expression in Embryonic Developmental Toxicity Induced by MC-RR

As cynobacterial blooms frequently occur in fresh waters throughout the world, microcystins (MCs) have caused serious damage to both wildlife and human health. MCs are known to have developmental toxicity, however, the possible molecular mechanism is largely unknown. This is the first toxicological study to integrate post-transcriptomic, proteomic and bioinformatics analysis to explore molecular mechanisms for developmental toxicity of MCs in zebrafish. After being microinjected directly into embryos, MC-RR dose-dependently decreased survival rates and increased malformation rates of embryos, causing various embryo abnormalities including loss of vascular integrity and hemorrhage. Expressions of 31 microRNAs (miRNAs) and 78 proteins were significantly affected at 72 hours post-fertilisation (hpf). Expressions of miR-430 and miR-125 families were also significantly changed. The altered expressions of miR-31 and miR-126 were likely responsible for the loss of vascular integrity. MC-RR significantly reduced the expressions of a number of proteins involved in energy metabolism, cell division, protein synthesis, cytoskeleton maintenance, response to stress and DNA replication. Bioinformatics analysis shows that several aberrantly expressed miRNAs and proteins (involved in various molecular pathways) were predicted to be potential MC-responsive miRNA-target pairs, and that their aberrant expressions should be the possible molecular mechanisms for the various developmental defects caused by MC-RR

Synthesis of an ordered mesoporous carbon with graphitic characteristics and its application for dye adsorption

An ordered mesoporous carbon (OMC) was prepared by a chemical vapor deposition technique using liquid petroleum gas (LPG) as the carbon source. During synthesis, LPG was effectively adsorbed in the ordered mesopores of SBA-15 silica and converted to a graphitic carbon at 800 °C. X-ray diffraction and nitrogen adsorption/desorption data and high-resolution transmission electron microscopy (HRTEM) of the OMC confirmed its ordered mesoporous structure. The OMC was utilized as an adsorbent in the removal of dyes from aqueous solution. A commercial powder activated carbon (AC) was also investigated to obtain comparative data. The efficiency of the OMC for dye adsorption was tested using acidic dye acid orange 8 (AO8) and basic dyes methylene blue (MB) and rhodamine B (RB). The results show that adsorption was affected by the molecular size of the dye, the textural properties of carbon adsorbent and surface-dye interactions. The adsorption capacities of the OMC for acid orange 8 (AO8), methylene blue (MB) and rhodamine B (RB) were determined to be 222, 833, and 233 mg/g, respectively. The adsorption capacities of the AC for AO8, MB, and RB were determined to be 141, 313, and 185 mg/ g, respectively. The OMC demonstrated to be an excellent adsorbent for the removal of MB from wastewater.Web of Scienc

Implied cost of capital investment strategies - evidence from international stock markets

Investors can generate excess returns by implementing trading strategies based on publicly available equity analyst forecasts. This paper captures the information provided by analysts by the implied cost of capital (ICC), the internal rate of return that equates a firm's share price to the present value of analysts' earnings forecasts. We find that U.S. stocks with a high ICC outperform low ICC stocks on average by 6.0% per year. This spread is significant when controlling the investment returns for their risk exposure as proxied by standard pricing models. Further analysis across the world's largest equity markets validates these results

Effects of leucine supplemented diet on intestinal absorption in tumor bearing pregnant rats

BACKGROUND: It is known that amino acid oxidation is increased in tumor-bearing rat muscles and that leucine is an important ketogenic amino acid that provides energy to the skeletal muscle. METHODS: To evaluate the effects of a leucine supplemented diet on the intestinal absorption alterations produced by Walker 256, growing pregnant rats were distributed into six groups. Three pregnant groups received a normal protein diet (18% protein): pregnant (N), tumor-bearing (WN), pair-fed rats (Np). Three other pregnant groups were fed a diet supplemented with 3% leucine (15% protein plus 3% leucine): leucine (L), tumor-bearing (WL) and pair-fed with leucine (Lp). Non pregnant rats (C), which received a normal protein diet, were used as a control group. After 20 days, the animals were submitted to intestinal perfusion to measure leucine, methionine and glucose absorption. RESULTS: Tumor-bearing pregnant rats showed impairment in food intake, body weight gain and muscle protein content, which were less accentuated in WL than in WN rats. These metabolic changes led to reduction in both fetal and tumor development. Leucine absorption slightly increased in WN group. In spite of having a significant decrease in leucine and methionine absorption compared to L, the WL group has shown a higher absorption rate of methionine than WN group, probably due to the ingestion of the leucine supplemented diet inducing this amino acid uptake. Glucose absorption was reduced in both tumor-bearing groups. CONCLUSIONS: Leucine supplementation during pregnancy in tumor-bearing rats promoted high leucine absorption, increasing the availability of the amino acid for neoplasic cells and, mainly, for fetus and host utilization. This may have contributed to the better preservation of body weight gain, food intake and muscle protein observed in the supplemented rats in relation to the non-supplemented ones

A multi-biometric iris recognition system based on a deep learning approach

YesMultimodal biometric systems have been widely applied in many real-world applications due to its ability to deal with a number of significant limitations of unimodal biometric systems, including sensitivity to noise, population coverage, intra-class variability, non-universality, and vulnerability to spoofing. In this paper, an efficient and real-time multimodal biometric system is proposed based on building deep learning representations for images of both the right and left irises of a person, and fusing the results obtained using a ranking-level fusion method. The trained deep learning system proposed is called IrisConvNet whose architecture is based on a combination of Convolutional Neural Network (CNN) and Softmax classifier to extract discriminative features from the input image without any domain knowledge where the input image represents the localized iris region and then classify it into one of N classes. In this work, a discriminative CNN training scheme based on a combination of back-propagation algorithm and mini-batch AdaGrad optimization method is proposed for weights updating and learning rate adaptation, respectively. In addition, other training strategies (e.g., dropout method, data augmentation) are also proposed in order to evaluate different CNN architectures. The performance of the proposed system is tested on three public datasets collected under different conditions: SDUMLA-HMT, CASIA-Iris- V3 Interval and IITD iris databases. The results obtained from the proposed system outperform other state-of-the-art of approaches (e.g., Wavelet transform, Scattering transform, Local Binary Pattern and PCA) by achieving a Rank-1 identification rate of 100% on all the employed databases and a recognition time less than one second per person