DEVELOPMENT AND VALIDATION OF STABILITY-INDICATING RP-HPLC ASSAY METHOD FOR AZACITIDINE AND ITS BULK DRUG

Objective: A novel gradient reverse phase High Performance Liquid Chromatographic (HPLC) method was developed for the quantification of Azacitidine impurities and degradation products in the Azacitidine tablets. Methods: The effective separation was achieved on an YMC ODS AQ-5, (250 x 4.6 mm), 5 µm column using a gradient mode by the mobile phase A: 3.1g of ammonium acetate dissolved in 1000 mL of water filtered through 0.45μm filter paper and mobile phase B: mixture of buffer – A, methanol and acetonitrile In the ratio of 500:300:200 v/v. The flow rate of the mobile phase was 1.0 mL/minute and the total elution time, including the column equilibration was approximately 60 minutes. The UV detection was carried at the wavelength 242 nm and experiments were conducted at 35 0 C. Results: The retention times of Azacitidine and its impurities are 15.3, 3.9, 4.9, 25.0 and 33 respectively. Azacitidine tablets were subjected to the stress conditions of oxidation, acid, base, hydrolytic, thermal and light degradation. The assay method was found to be linear in the range of 400 μg·mL–1 to with 1000 μg·mL–1 correlation coefficient is 0.998 and the linearity of the impurities was established from LOQ to 150%. Recoveries of assay and impurities were found between 99.0% and 103.6%. Conclusion: The developed method was validated in terms of system suitability, specificity, linearity range, precision, accuracy, limits of detection and quantification for the impurities following the ICH guidelines. Therefore, the proposed method is suitable for the simultaneous determination of Azacitidine and its four related impurities

Phycobilins as Potent Food Bioactive Broad-Spectrum Inhibitors Against Proteases of SARS-CoV-2 and Other Coronaviruses: A Preliminary Study

In the 21st century, we have witnessed three coronavirus outbreaks: SARS in 2003, MERS in 2012, and the ongoing pandemic coronavirus disease 2019 (COVID-19). The search for efficient vaccines and development and repurposing of therapeutic drugs are the major approaches in the COVID-19 pandemic research area. There are concerns about the evolution of mutant strains (e.g., VUI – 202012/01, a mutant coronavirus in the United Kingdom), which can potentially reduce the impact of the current vaccine and therapeutic drug development trials. One promising approach to counter the mutant strains is the “development of effective broad-spectrum antiviral drugs” against coronaviruses. This study scientifically investigates potent food bioactive broad-spectrum antiviral compounds by targeting main protease (Mpro) and papain-like protease (PLpro) proteases of coronaviruses (CoVs) using in silico and in vitro approaches. The results reveal that phycocyanobilin (PCB) shows potential inhibitor activity against both proteases. PCB had the best binding affinity to Mpro and PLpro with IC50 values of 71 and 62 μm, respectively. Also, in silico studies with Mpro and PLpro enzymes of other human and animal CoVs indicate broad-spectrum inhibitor activity of the PCB. As with PCB, other phycobilins, such as phycourobilin (PUB), phycoerythrobilin (PEB), and phycoviolobilin (PVB) show similar binding affinity to SARS-CoV-2 Mpro and PLpro

Genomic Modeling as an Approach to Identify Surrogates for Use in Experimental Validation of SARS-CoV-2 and HuNoV Inactivation by UV-C Treatment

Severe Acute Respiratory Syndrome coronavirus-2 (SARS-CoV-2) is responsible for the COVID-19 pandemic that continues to pose significant public health concerns. While research to deliver vaccines and antivirals are being pursued, various effective technologies to control its environmental spread are also being targeted. Ultraviolet light (UV-C) technologies are effective against a broad spectrum of microorganisms when used even on large surface areas. In this study, we developed a pyrimidine dinucleotide frequency based genomic model to predict the sensitivity of select enveloped and non-enveloped viruses to UV-C treatments in order to identify potential SARS-CoV-2 and human norovirus surrogates. The results revealed that this model was best fitted using linear regression with r2 = 0.90. The predicted UV-C sensitivity (D90 – dose for 90% inactivation) for SARS-CoV-2 and MERS-CoV was found to be 21.5 and 28 J/m2, respectively (with an estimated 18 J/m2 obtained from published experimental data for SARS-CoV-1), suggesting that coronaviruses are highly sensitive to UV-C light compared to other ssRNA viruses used in this modeling study. Murine hepatitis virus (MHV) A59 strain with a D90 of 21 J/m2 close to that of SARS-CoV-2 was identified as a suitable surrogate to validate SARS-CoV-2 inactivation by UV-C treatment. Furthermore, the non-enveloped human noroviruses (HuNoVs), had predicted D90 values of 69.1, 89, and 77.6 J/m2 for genogroups GI, GII, and GIV, respectively. Murine norovirus (MNV-1) of GV with a D90 = 100 J/m2 was identified as a potential conservative surrogate for UV-C inactivation of these HuNoVs. This study provides useful insights for the identification of potential non-pathogenic (to humans) surrogates to understand inactivation kinetics and their use in experimental validation of UV-C disinfection systems. This approach can be used to narrow the number of surrogates used in testing UV-C inactivation of other human and animal ssRNA viral pathogens for experimental validation that can save cost, labor and time

Impact of Carbon and Nitrogen Sources on L-Asparaginase Production by Isolated Bacillus circulans (MTCC 8574): Application of Saturated Plackett-Burman Design

The present work aimed to study the impact of different carbon and nitrogen sources on the effective production of L-asparaginase by isolated Bacillus circulans using Plackett-Burman design (PBD). Among carbon sources; lactose, galactose, starch, sucrose, maltose, arabinose and among nitrogen sources; proline, tryptone, sodium glutamate, corn steep liquor, beef extract, ammonium chloride, yeast extract at selected concentration produced a maximum of 105 and 164 U mL–1 L-asparaginase enzyme, respectively. Initial analysis of L-asparaginase data with different carbon and nitrogen sources as per PBD did not reveal standardized effects as well as ‘p’ and ‘t’ values. Regression coefficient and t-values were calculated by subjecting the experimental data to statistical analysis after pooling the least two nutrient components into error. Among selected 26 components, xylose, galactose, yeast extract and proline denoted least significance, while glucose, mannose, ammonium chloride and ammonium sulphate showed maximum significance on enzyme production. Saturated PBD can be effectively utilized for analysis of the data by pooling the least significant factors based on the effects on metabolite/product/enzyme production. Ammonium chloride and glucose were observed to be the most significant carbon and nitrogen sources, respectively in L-asparaginase production in this bacterial strain. The presented approach is highly useful in bioprocess optimization procedure where all selected parameters show little degree of freedom and subsequent significant factors

UV-C inactivation of microorganisms in droplets on food contact surfaces using UV-C light-emitting diode devices

The main objective of this study was to investigate the effectiveness of ultraviolet light (UV-C) emitting diodes for the decontamination of stainless steel food contact surfaces. Listeria monocytogenes (ATCC 19115), Escherichia coli (ATCC 25922), and Salmonella enterica serovar Typhimurium (ATCC 700720) were chosen as challenge microorganisms. Target microorganisms were subjected to UV-C dosages of 0, 2, 4, 6, and 8 mJ cm−2 at an average fluence of 0.163 mW/cm2 using a near-collimated beam operating at 279 nm wavelength. Escherichia coli showed lower sensitivity to UV-C light compared to Salmonella Typhimurium and followed first-order kinetics. Escherichia coli and Salmonella Typhimurium were reduced by more than 3-log10 cycles at the maximum UV dosage of 12 mJ cm−2 . In contrast, Listeria monocytogenes followed the Weibull model with an apparent shoulder in the initial doses. A maximum reduction of 4.4-log10 was achieved at the highest exposure level. This study showed that UV-C LED devices represent an excellent alternative for the inactivation of foodborne microorganisms in droplets. Results clearly demonstrate that UV-C LED devices can serve as an additional sanitation method to routine cleaning practices, which are commonly utilized in the food industry

Corporate Governance, Board Characteristics and Performance of Indian Banks: An Empirical Study

The paper examines the corporate governance, board characteristics, performance and asset quality of Indian banks and investigates the impact of a set of board characteristics on performance and asset quality of banks. We use a sample of 34 scheduled commercial banks, for ten years from 2009 to 2018, accounting for about 90 per cent of the total banking assets and banking business India. We measure bank performance by return on assets (ROA) and asset quality of banks by ratio of net non-performing assets (NNPA) and document evidence on the role of the board characteristics on performance and asset quality of banks. The study finds that the board size and percentage of independent directors have significantly positive impact on ROA. The percentage of executive directors is having significantly negative relationship with the ROA. The board size and percentage of independent directors have significantly negative relationship with banks' NNPAs. The research suggests that the board of directors play a significant role in bank governance in India. The paper contributes to the literature on the corporate governance of banks in India, which is one of the emerging economies of the world. The research results provide some insights of corporate governance to the RBI for considering appropriate policy guidelines on corporate governance to banking industry in India. Keywords: Corporate governance, Board characteristics; Performance of banks, Non-performing assets JEL Classifications: G21, G28, G32 DOI: https://doi.org/10.32479/ijefi.953

Performance of a UV-A LED system for degradation of aflatoxins B1 and M1 in pure water: kinetics and cytotoxicity study

The efficacy of a UV-A light emitting diode system (LED) to reduce the concentrations of aflatoxin B1, aflatoxin M1 (AFB1, AFM1) in pure water was studied. This work investigates and reveals the kinetics and main mechanism(s) responsible for the destruction of aflatoxins in pure water and assesses the cytotoxicity in liver hepatocellular cells. Irradiation experiments were conducted using an LED system operating at 365 nm (monochromatic wave-length). Known concentrations of aflatoxins were spiked in water and irradiated at UV-A doses ranging from 0 to 1,200 mJ/cm2. The concentration of AFB1 and AFM1 was determined by HPLC with fluorescence detection. LC–MS/MS product ion scans were used to identify and semi-quantify degraded products of AFB1 and AFM1. It was observed that UV-A irradiation significantly reduced aflatoxins in pure water. In comparison to control, at dose of 1,200 mJ/cm2 UV-A irradiation reduced AFB1 and AFM1 concentrations by 70 ± 0.27 and 84 ± 1.95%, respectively. We hypothesize that the formation of reactive species initiated by UV-A light may have caused photolysis of AFB1 and AFM1 molecules in water. In cell culture studies, our results demonstrated that the increase of UV-A dosage decreased the aflatoxins-induced cytotoxicity in HepG2 cells, and no significant aflatoxin-induced cytotoxicity was observed at UV-A dose of 1,200 mJ/cm2. Further results from this study will be used to compare aflatoxins detoxification kinetics and mechanisms involved in liquid foods such as milk and vegetable oils

Phycobilins as Potent Food Bioactive Broad-Spectrum Inhibitors Against Proteases of SARS-CoV-2 and Other Coronaviruses: A Preliminary Study

In the 21st century, we have witnessed three coronavirus outbreaks: SARS in 2003, MERS in 2012, and the ongoing pandemic coronavirus disease 2019 (COVID-19). The search for efficient vaccines and development and repurposing of therapeutic drugs are the major approaches in the COVID-19 pandemic research area. There are concerns about the evolution of mutant strains (e.g., VUI – 202012/01, a mutant coronavirus in the United Kingdom), which can potentially reduce the impact of the current vaccine and therapeutic drug development trials. One promising approach to counter the mutant strains is the “development of effective broad-spectrum antiviral drugs” against coronaviruses. This study scientifically investigates potent food bioactive broad-spectrum antiviral compounds by targeting main protease (Mpro) and papain-like protease (PLpro) proteases of coronaviruses (CoVs) using in silico and in vitro approaches. The results reveal that phycocyanobilin (PCB) shows potential inhibitor activity against both proteases. PCB had the best binding affinity to Mpro and PLpro with IC50 values of 71 and 62 μm, respectively. Also, in silico studies with Mpro and PLpro enzymes of other human and animal CoVs indicate broad-spectrum inhibitor activity of the PCB. As with PCB, other phycobilins, such as phycourobilin (PUB), phycoerythrobilin (PEB), and phycoviolobilin (PVB) show similar binding affinity to SARS-CoV-2 Mpro and PLpro

Adaptive Query Image Searching Methods Using Improved Hash Coding and Unified Color and Intensity level Matrices

In this thesis we had implemented Hash coding with bit wise hamming distance for similarity measurement between the feature vectors of query and database, which will be more secured and real time based application. By using the hash coding method the computational time is high and the accuracy will be much lower. Hence, hash coding will be extended with inclusion of gray scale matrices (GSM), which will represent the features of gray scale texture values in the image, but it will not consider the color information in the image. To incorporate both gray scale and color information, we proposed a novel scheme in which both color and intensity variations are represented in a single composite feature known as Unified Color and Intensity level Matrices (UCILM). The proposed scheme has been merged with hash coding to improve the efficiency of the retrieval system. This addition work had improved the system accuracy as well as the precision time with almost 88% of relevant image retrieval