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- Tehreem, Syeda, et al.
(author)
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A UPLC-DAD-Based Bio-Screening Assay for the Evaluation of the Angiotensin Converting Enzyme Inhibitory Potential of Plant Extracts and Compounds : Pyrroquinazoline Alkaloids from Adhatoda vasica as a Case Study
- 2021
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In: Molecules. - : MDPI. - 1431-5157 .- 1420-3049. ; 26:22
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Journal article (peer-reviewed)abstract
- Angiotensin converting enzyme (ACE) plays a crucial role in regulating blood pressure in the human body. Identification of potential ACE inhibitors from medicinal plants supported the idea of repurposing these medicinal plants against hypertension. A method based on ultra-performance liquid chromatography (UPLC) coupled with a diode array detector (DAD) was used for the rapid screening of plant extracts and purified compounds to determine their ACE inhibitory activity. Hippuryl-histidiyl-leucine (HHL) was used as a substrate, which is converted into hippuric acid (HA) by the action of ACE. A calibration curve of the substrate HHL was developed with the linear regression 0.999. The limits of detection and quantification of this method were found to be 0.134 and 0.4061 mM, respectively. Different parameters of ACE inhibitory assay were optimized, including concentration, incubation time and temperature. The ACE inhibition potential of Adhatoda vasica (methanolic-aqueous extract) and its isolated pyrroquinazoline alkaloids, vasicinol (1), vasicine (2) and vasicinone (3) was evaluated. Compounds 1-3 were characterized by various spectroscopic techniques. The IC50 values of vasicinol (1), vasicine (2) and vasicinone (3) were found to be 6.45, 2.60 and 13.49 mM, respectively. Molecular docking studies of compounds 1-3 were also performed. Among these compounds, vasicinol (1) binds as effectively as captopril, a standard drug of ACE inhibition.
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| 2. |
- Quoreshi, A.M.M. Shahiduzzaman, et al.
(author)
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Equity Market Contagion in Return Volatility during Euro Zone and Global Financial Crises: Evidence from FIMACH Model
- 2019
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In: Journal of Risk and Financial Management. - : MDPI. - 1911-8074. ; 12:2
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Journal article (peer-reviewed)abstract
- The current paper studies equity markets for the contagion of squared index returns as a proxy for stock market volatility, which has not been studied earlier. The study examines squared stock index returns of equity in 35 markets, including the US, UK, Euro Zone and BRICS (Brazil, Russia, India, China and South Africa) countries, as a proxy for the measurement of volatility. Results from the conditional heteroskedasticity long memory model show the evidence of long memory in the squared stock returns of all 35 stock indices studied. Empirical findings show the evidence of contagion during the global financial crisis (GFC) and Euro Zone crisis (EZC). The intensity of contagion varies depending on its sources. This implies that the effects of shocks are not symmetric and may have led to some structural changes. The effect of contagion is also studied by decomposing the level series into explained and unexplained behaviors.
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| 3. |
- Quoreshi, Shahiduzzaman, et al.
(author)
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A Review of Inma Integer-valued Model Class, Application and Further Development
- 2020
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In: Filomat. - : University of Nis. - 0354-5180. ; 34:1, s. 143-152
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Journal article (peer-reviewed)abstract
- In this paper, we review INMA time series of integer-valued model class, and discuss its further development. These models have been developed for analyzing high frequency financial count data. A vivid description of high frequency data in the context of market micro structure is given. The most distinguishing feature that makes the INMA model class different from its continuous variable MA counterpart is that multiplication of variables with real valued parameters no longer remains a viable operation when the result is to be integer-valued. In the estimation of these models, no underlying distributions are assumed. Hence, the discussion of estimations are limited to CL, FGLS and GMM. A further development of estimation procedures for these models have also been reviewed. We suggest that the models could be estimated with Quasi Maximum Likelihood and propose in addition a Generalized Method of Moment of Quasi Maximum Likelihood. We have also discussed how INMA model class can be extended with different underlying distributions for innovations.
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| 4. |
- Quoreshi, Shahiduzzaman, et al.
(author)
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Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework
- 2019
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In: Journal of Risk and Financial Management. - : MDPI. - 1911-8074. ; 12:2
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Journal article (peer-reviewed)abstract
- This paper introduces Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data of unknown underlying distribution. The moments with conditional heteroscedasticity have been discussed. In a Monte Carlo experiment, it was found that the QML estimator performs as well as CLS and FGLS in terms of eliminating serial correlations, but the estimator can be sensitive to start value. Hence, two-stage QML has been suggested. In empirical estimation on two stock transaction data for Ericsson and AstraZeneca, the 2SQML turns out relatively more efficient than CLS and FGLS. The empirical results suggest that both of the series have long memory properties that imply that the impact of macroeconomic news or rumors in one point of time has a persistence impact on future transactions.
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