RESUMO
We synthesized and explored biological and environmental applications of novel silver nanoparticles (AgNps) stabilized by short chain heterocyclic thiol namely Ethyl 6-methyl-4-phenyl-2-thioxo1,2,3,4-dihydropyrim-idine-5-carboxylate (DHPM). Dihydropyrimidines (DHPM), a biological active class of compounds that contain a single thiol group at the focal point which strongly stabilized the nascent AgNps. The short alkyl chain of (DHPM) effectively controlled the growth kinetics and surface morphology of AgNps. The synthesized Dihydropyrimidine stabilized silver nanoparticles (DHPM-AgNps) were investigated using Ultraviolet- visible spectroscopy (UV-Vis), Atomic force Microscopy (AFM) and Fourier-transform infrared spectroscopy (FTIR). AFM exhibited the size and shape of the DHPM-AgNps with an average diameter of 10 ± 1 nm. Our prepared DHPM-AgNps were examined for urease enzyme inhibition activity. The synthesized DHPM-AgNps showed significant level of urease inhibition activity (% of inhibition 40.3±0.28%) when compared with standard thiourea inhibition activity (% of inhibition value 79.6± 0.47%.). Moreover prepared DHPM-AgNps system successfully applied for the reduction of para-nitrophenol (p-Nip). It reduces the para-nitrophenol (p-Nip) to para-aminophenol (p-Amp) within one second in the presence of NaBH4 under ambient temperature and pressure conditions, which followed the pseudo-first-order rate kinetics. This study will provide useful guidelines for designing efficient catalysts and stabilizing agents for Silver Nanoparticles.
Assuntos
Nanopartículas Metálicas , Prata , Nanopartículas Metálicas/química , Nitrofenóis/química , Prata/farmacologia , Compostos de Sulfidrila , UreaseRESUMO
PURPOSE: To date there has not been an extensive analysis of the outcomes of biomarker use in oncology. METHODS: Data were pooled across four indications in oncology drawing upon trial outcomes from www.clinicaltrials.gov: breast cancer, non-small cell lung cancer (NSCLC), melanoma and colorectal cancer from 1998 to 2017. We compared the likelihood drugs would progress through the stages of clinical trial testing to approval based on biomarker status. This was done with multi-state Markov models, tools that describe the stochastic process in which subjects move among a finite number of states. RESULTS: Over 10000 trials were screened, which yielded 745 drugs. The inclusion of biomarker status as a covariate significantly improved the fit of the Markov model in describing the drug trajectories through clinical trial testing stages. Hazard ratios based on the Markov models revealed the likelihood of drug approval with biomarkers having nearly a fivefold increase for all indications combined. A 12, 8 and 7-fold hazard ratio was observed for breast cancer, melanoma and NSCLC, respectively. Markov models with exploratory biomarkers outperformed Markov models with no biomarkers. CONCLUSION: This is the first systematic statistical evidence that biomarkers clearly increase clinical trial success rates in three different indications in oncology. Also, exploratory biomarkers, long before they are properly validated, appear to improve success rates in oncology. This supports early and aggressive adoption of biomarkers in oncology clinical trials.