RESUMO
Industrial wastewater often consists of toxic chemicals and pollutants, which are extremely harmful to the environment. Heavy metals are toxic chemicals and considered one of the major hazards to the aquatic ecosystem. Analytical techniques, such as potentiometric methods, are some of the methods to detect heavy metals in wastewaters. In this work, the quantitative structure-property relationship (QSPR) was applied using a range of machine learning techniques to predict the stability constant (logßML) and potentiometric sensitivity (PSML) of 200 ligands in complexes with the heavy metal ions Cu2+, Cd2+, and Pb2+. In result, the logßML models developed for four ions showed good performance with square correlation coefficients (R2) ranging from 0.80 to 1.00 for the training and 0.72 to 0.85 for the test sets. Likewise, the PSML displayed acceptable performance with an R2 of 0.87 to 1.00 for the training and 0.73 to 0.95 for the test sets. By screening a virtual database of coumarin-like structures, several new ligands bearing the coumarin moiety were identified. Three of them, namely NEW02, NEW03, and NEW07, showed very good sensitivity and stability in the metal complexes. Subsequent quantum-chemical calculations, as well as physicochemical/toxicological profiling were performed to investigate their metal-binding ability and developability of the designed sensors. Finally, synthesis schemes are proposed to obtain these three ligands with major efficiency from simple resources. The three coumarins designed clearly demonstrated capability to be suitable as good florescent chemosensors towards heavy metals. Overall, the computational methods applied in this study showed a very good performance as useful tools for designing novel fluorescent probes and assessing their sensing abilities.
RESUMO
BACKGROUND: This study aims to investigate the frequencies and association of CYP3A5 polymorphism with tacrolimus concentration among renal transplant recipients in Vietnam. METHODS: Sixty-eight kidney transplant recipients were included in this study from the department of nephrology and dialysis, Military Hospital 103. Blood samples were collected for monitoring of tacrolimus levels and determination of CYP3A5 genetic polymorphism. RESULTS: A total of 68 patients studied. The CYP3A5*3*3, CYP3A5*1*3, and CYP3A5*1*1 genotypes were detected in 48 (70.6%), 16 (23.5%), and 4 (5.9%), respectively. Tacrolimus concentrations were much lower in CYP3A5 expressors than in CYP3A5 nonexpressors on the first day, month 1, 3, 6, and 12 (5.98 ± 1.05 vs 6.57 ± 1.03, P = .03; 5.79 ± 1.13 vs 6.82 ± 1.05, P < .001; 4.76 ± 1.48 vs 6.73 ± 1.09, P < .001; 4.29 ± 1.64 vs 6.46 ± 1.23, P < .001; 4.20 ± 1.36 vs 6.04 ± 1.26, P < .001), respectively. Notably, the concentration/dose ratio in the CYP3A5 expressors was lower than in CYP3A5 nonexpressors at time points of follow up (P < .001). However, there were no significant differences in the age, sex, HLA mismatch, type of donors, acute rejection, and creatinine levels at time points between group of CYP3A5 expressors and those of CYP3A5 nonexpressors. CONCLUSION: In conclusion, this research indicated the significant association of CYP3A5 genetic polymorphism with daily dose and tacrolimus concentrations in renal transplant recipients. This study provided a closer step to individualize the dose of tacrolimus in renal transplant patients in Vietnam.
