scholarly journals Analysis of Antimalarial Synergy between Bestatin and Endoprotease Inhibitors Using Statistical Response-Surface Modelling

2001 ◽  
Vol 45 (11) ◽  
pp. 3175-3181 ◽  
Author(s):  
Clare S. Gavigan ◽  
Stella G. Machado ◽  
John P. Dalton ◽  
Angus Bell

ABSTRACT The pathway of hemoglobin degradation by erythrocytic stages of the human malarial parasite Plasmodium falciparum involves initial cleavages of globin chains, catalyzed by several endoproteases, followed by liberation of amino acids from the resulting peptides, probably by aminopeptidases. This pathway is considered a promising chemotherapeutic target, especially in view of the antimalarial synergy observed between inhibitors of aspartyl and cysteine endoproteases. We have applied response-surface modelling to assess antimalarial interactions between endoprotease and aminopeptidase inhibitors using cultured P. falciparum parasites. The synergies observed were consistent with a combined role of endoproteases and aminopeptidases in hemoglobin catabolism in this organism. As synergies between antimicrobial agents are often inferred without proper statistical analysis, the model used may be widely applied in studies of antimicrobial drug interactions.

Metals ◽  
2017 ◽  
Vol 7 (6) ◽  
pp. 191 ◽  
Author(s):  
Hassan Abdulhadi ◽  
Syarifah Ahmad ◽  
Izwan Ismail ◽  
Mahadzir Ishak ◽  
Ghusoon Mohammed

Author(s):  
Siti Khadijah Hubadillah ◽  
Mohd Hafiz Dzarfan Othman ◽  
Paran Gani ◽  
Ahmad Fauzi Ismail ◽  
Mukhlis A. Rahman ◽  
...  

2020 ◽  
Vol 61 (5) ◽  
pp. 2177-2192 ◽  
Author(s):  
Siva Krishna Dasari ◽  
Abbas Cheddad ◽  
Petter Andersson

AbstractThe design of aircraft engines involves computationally expensive engineering simulations. One way to solve this problem is the use of response surface models to approximate the high-fidelity time-consuming simulations while reducing computational time. For a robust design, sensitivity analysis based on these models allows for the efficient study of uncertain variables’ effect on system performance. The aim of this study is to support sensitivity analysis for a robust design in aerospace engineering. For this, an approach is presented in which random forests (RF) and multivariate adaptive regression splines (MARS) are explored to handle linear and non-linear response types for response surface modelling. Quantitative experiments are conducted to evaluate the predictive performance of these methods with Turbine Rear Structure (a component of aircraft) case study datasets for response surface modelling. Furthermore, to test these models’ applicability to perform sensitivity analysis, experiments are conducted using mathematical test problems (linear and non-linear functions) and their results are presented. From the experimental investigations, it appears that RF fits better on non-linear functions compared with MARS, whereas MARS fits well on linear functions.


2005 ◽  
Vol 58 (2) ◽  
pp. 65-73 ◽  
Author(s):  
STEPHEN P WALKER ◽  
ALI DEMIRCI ◽  
ROBERT E GRAVES ◽  
STEPHEN B SPENCER ◽  
ROBERT F ROBERTS

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