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| Articles
by
S. Rezaee |
Total Records (
3 ) for
S. Rezaee |
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S. Rezaee
,
A. Khalaj
,
N. Adibpour
and
M Saffary
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Background and purpose of the study. 3(2H)-Isothiazolones have shown antimicrobial
activity and have been used as preservative in different products. However, reports
on their structure-antimicrobial activity relationship are scanty. The aim of
this study was to determine the relationship between lipophilicity and antimicrobial
activity of several 2- (4-substituted phenyl) -3(2H)-isothiazolones of which some
have shown antibacterial activities similar or higher than gentamycin, ceftazidime,
ceftriaxone, ciprofloxacin , and antifungal activites similar or higher than itraconazole
and ketoconazole as reference drugs.
Methods. Partition coefficient (log Po/w) of the tested compounds was determined
experimentally by a reversed- phase high performance liquid chromatography method
using octadecyl-poly(vinyl alcohol) (ODP) column and methanol-water gradient as
mobile phase and theoretically by Clog P and ALOGPS computer programs.
Results. The HPLC and theoretical log Po/w values showed potential correlations
which indicate that both experimental and theoretical methods are equally suitable
to predict lipophilicity of 3(2H)-isothiazolones. There were also significant
correlations between MICs (minimum inhibitory concentrations) of 5-chloro substituted
3(2H)- isothiazolnes against Salmonella typhimurium and Escherichia coli and experimentally
determined log Po/wvalues, as well as MICs of 5-unsubstituted 3(2H)- isothiazolnes
against E. coli and ALOGPS values. The antifungal activity of the tested compounds
against Tricophyton. mentagrophytes and M.canis increased with increase in the
experimental and theoretical log P values , but this increase was only significant
for the activity against Microsporum. canis. |
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H. Jahanifar
,
A. Heydari
,
N. Hasanzadeh
,
H.R. Zamanizadeh
,
S. Rezaee
and
L. Naraghi
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In this research, antibiotic-resistant mutants of antagonistic
bacteria to rifampicin (Rif) and nalidixic acid (Nal) were developed via
spontaneous mutation and their effectiveness in controlling cotton seedling
damping-off disease was compared with their wild types. Four wild types
isolates belonged to Pseudomonas fluorescens and their mutants
were tested against pre-and post emergence damping-off disease of cotton
in greenhouse. The experiment was conducted in a completely randomized
design with ten treatments and four replicates. A virulent isolate of
Rhizoctonia solani, the causal agent of cotton seedling
damping-off disease was used in the study and the effectiveness of bacterial
isolates was evaluated based on the number of healthy seedlings 15, 30,
45 and 60 days after sowing. Results indicated that all Rif-Nal resistant
mutants showed more effectiveness in disease control than their wild types
15 and 30 days after sowing. However, at days 45 and 60 after sowing,
only three mutants were more effective than their wild types in controlling
cotton seedling damping-off disease. Results of this study suggest that
spontaneous mutation may affect and enhance the activity and performance
of antagonistic bacteria. |
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A.-H. Mohammadpour
,
F. Nazemian
,
B. Abtahi
,
M. Naghibi
,
S. Rezaee
,
M.-R.A. Nazari
and
O. Rajabi
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Area under the concentration curve (AUC) of mycophenolic acid (MPA) could help to optimize therapeutic drug monitoring during the early post–renal transplant period. The aim of this study was to develop a limited sampling strategy to estimate an abbreviated MPA AUC within the first month after renal transplantation. In this study we selected 19 patients in the early posttransplant period with normal renal graft function (glomerular filtration rate > 70 mL/min). Plasma MPA concentrations were measured using reverse-phase high-performance liquid chromatography. MPA AUC0–12h was calculated using the linear trapezoidal rule. Multiple stepwise regression analysis was used to determine the minimal and convenient time points of MPA levels that could be used to derive model equations best fitted to MPA AUC0–12h. The regression equation for AUC estimation that gave the best performance was AUC = 14.46 * C10 + 15.547 (r2 = .882). The validation of the method was performed using the jackknife method. Mean prediction error of this model was not different from zero (P > .05) and had a high root mean square prediction error (8.06). In conclusion, this limited sampling strategy provided an effective approach for therapeutic drug monitoring during the early posttransplant period. |
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