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Agricultural products are vitally important for sustaining life on earth and their production has notably grown over the years worldwide in general and in Brazil particularly. Elevating agricultural practices consequently leads to a proportionate increase in the usage of pesticides that are crucially important for enhanced crop yield and protection. These compounds have been employed excessively in alarming concentrations, causing the contamination of soil, water, and air. Additionally, they pose serious threats to human health. The current study introduces an innovative tool for producing appropriate materials coupled with an electrochemical sensor designed to measure carbendazim levels. The sensor is developed using a molecularly imprinted polymer (MIP) mounted on a glassy carbon electrode. This electrode is equipped with multi-walled carbon nanotubes (MWCNTs) for improved performance. The combined system demonstrates promising potential for accurately quantifying carbendazim. The morphological characteristics of the synthesized materials were investigated using field emission scanning electron microscopy (FESEM) and the Fourier-transform infrared (FTIR) technique. The analytical curve was drawn using the electrochemical method in the range of 2 to 20 ppm while for HPLC 2-12 ppm; the results are presented as the maximum adsorption capacity of the MIP (82.4%) when compared with NIP (41%) using the HPLC method. The analysis conducted using differential pulse voltammetry (DPV) yielded a limit of detection (LOD) of 1.0 ppm and a repeatability of 5.08% (n = 10). The results obtained from the analysis of selectivity demonstrated that the proposed electrochemical sensor is remarkably efficient for the quantitative assessment of carbendazim, even in the presence of another interferent. The sensor was successfully tested for river water samples for carbendazim detection, and recovery rates ranging from 94 to 101% were obtained for HPLC and 94 to 104% for the electrochemical method. The results obtained show that the proposed electrochemical technique is viable for the application and quantitative determination of carbendazim in any medium.

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Antibiotics, as a class of environmental pollutants, pose a significant challenge due to their persistent nature and resistance to easy degradation. This study delves into modeling and optimizing conventional Fenton degradation of antibiotic sulfamethoxazole (SMX) and total organic carbon (TOC) under varying levels of H2O2, Fe2+ concentration, pH, and temperature using statistical and artificial intelligence techniques including Multiple Regression Analysis (MRA), Support Vector Regression (SVR) and Artificial Neural Network (ANN). In statistical metrics, the ANN model demonstrated superior predictive accuracy compared to its counterparts, with lowest RMSE values of 0.986 and 1.173 for SMX and TOC removal, respectively. Sensitivity showcased H2O2/Fe2+ ratio, time and pH as pivotal for SMX degradation, while in simultaneous SMX and TOC reduction, fine tuning the time, pH, and temperature was essential. Leveraging a Hybrid Genetic Algorithm-Desirability Optimization approach, the trained ANN model revealed an optimal desirability of 0.941 out of 1000 solutions which yielded a 91.18% SMX degradation and 87.90% TOC removal under following specific conditions: treatment time of 48.5 min, Fe2+: 7.05 mg L-1, H2O2: 128.82 mg L-1, pH: 5.1, initial SMX: 97.6 mg L-1, and a temperature: 29.8 °C. LC/MS analysis reveals multiple intermediates with higher m/z (242, 270 and 288) and lower m/z (98, 108, 156 and 173) values identified, however no aliphatic hydrocarbon was isolated, because of the low mineralization performance of Fenton process. Furthermore, some inorganic fragments like NH4+ and NO3- were also determined in solution. This comprehensive research enriches AI modeling for intricate Fenton-based contaminant degradation, advancing sustainable antibiotic removal strategies.

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In the current study, the solubility and permeability of Osthole-loaded microemulsion were enhanced, which increased bioavailability. In addition, Carbomer 940 was added for prolonged drug delivery. The microemulsion was prepared after the screening of Kukui oil, Labrasol (surfactant), and transcutol-P (co-surfactant). Pseudoternary phase diagrams were employed to find the microemulsion region. Box Behnken Design (BBD) was employed for optimizing microemulsions. Variables were related and compared using mathematical equations and response surface plots (RSP). MEBG was then compared with control gel on the basis of stability studies, drug permeation, skin irritation studies, and anti-inflammatory studies. Microemulsion preparations depicted a pH of 5.27 - 5.80, a conductivity of 139 - 185 µS/cm, a poly-dispersity index of 0.116 - 0.388, a refractive index of 1.330 - 1.427, an average droplet size of 64 - 89 nm, homogeneity, spherical shape, viscosity 52 - 185 cP. Predicted values of Optimized microemulsions showed more reasonable agreement than experimental values. The microemulsion was stable and non-irritating on Rabbit skin. MEBG showed a significant difference from control gel for percent edema inhibition from the standard. The permeation enhancing capability of MEBG using a suitable viscosity fabricates it promising carrier for transdermal delivery of Osthole.

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The purpose of present study was to prepare transdermal therapeutic system that could enhance dissolution of poorly aqueous soluble drug Celecoxib and thus increase its skin permeation. Solubility studies screened triacetin as oil, cremophor RH 40 as surfactant and Polyethylene Glycol 400 as co-surfactant. Pseudoternary phase diagrams were constructed to find out microemulsion region. Independent variables (oil, Smix and water) concentration was used at high (+1) and low levels (-1) that would generate 17 different combinations of microemulsions. Microemulsions were characterized, optimized and evaluated. pH, viscosity, conductivities, refractive index, droplet size and poly-dispersity-index was investigated. Prepared microemulsions were oil in water, thermodynamically stable, isotropic, transparent, deflocculated and within narrow range of size. Mathematical equations and response surface plots related the independent and dependent variables. Optimum microemulsion ME6 was further incorporated with carbomer 940 gel base to produce microemulsion based gel. ME6 and its gel showed significant difference (p<0.05) from control gel. Stability studies showed prepared MEBG of celecoxib was stable during storage period. Skin irritation studies found the gel was safe and non-irritating to skin. Anti-inflammatory studies showed significant difference (p<0.05) compared to control gel. Thus, the therapeutic system was successfully developed and optimized using Box Behnken statistical design.

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In this study, computational and statistical models were applied to optimize the inherent parameters of an electrochemical decontamination of synozol red. The effect of various experimental variables such as current density, initial pH and concentration of electrolyte on degradation were assessed at Ti/RuO0·3TiO0·7O2 anode. Response surface methodology (RSM) based central composite design was applied to investigate interdependency of studied variables and train an artificial neural network (ANN) to envisage the experimental training data. The presence of fifteen neurons proved to have optimum performance based on maximum R2, mean absolute error, absolute average deviation and minimum mean square error. In comparison to RSM and empirical kinetics models, better prediction and interpretation of the experimental results were observed by ANN model. The sensitive analysis revealed the comparative significance of experimental variables are pH = 61.03%>current density = 17.29%>molar concentration of NaCl = 12.7%>time = 8.98%. The optimized process parameters obtained from genetic algorithm showed 98.6% discolorization of dye at pH 2.95, current density = 5.95 mA cm-2, NaCl of 0.075 M in 29.83 min of electrolysis. The obtained results revealed that the use of statistical and computational modeling is an adequate approach to optimize the process variables of electrochemical treatment.

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Abstract This paper presents the first comprehensive report on traditional uses of medicinal shrubs of Rawalakot city, district Poonch, Azad Jammu and Kashmir, Pakistan. Ethobotanical data obtained from 120 informants were analyzed by relative frequency citation, use value, family use value, informant consensus factor, fidelity level and Jaccard index. In total, 41 shrubs belonging to 24 families and 34 genera were documented. Rosaceae was reported the most dominant family in the area (six species) and Berberidaceae showed maximum family use value (0.68). Leaves (35%) and fruits (33%) were the most commonly used plant parts and most of the medicines were prepared in the form of decoction. The high informant consensus factor value (0.94) was recorded for diabetic disease category. Medicinal plants with high fidelity level values (100% each) were Berberis lycium, Cydonia oblanga, Ricinus communis, Ziziphus jujuba and Nerium oleander. Berberis lycium was the most significant shrub in the area with highest use value (0.68). Relative frequency citation value was maximum for Rubus ellipticus (0.30), Nerium oleander and Indigofera heterantha (0.10 each). Percentage of similar plant uses ranged from 21.05 to 0.62% and dissimilarity percentage ranged from 32.50 to 0.66%. Out of the 41 shrub species, six were reported with new therapeutic uses and may represent new bioresources. These were Debregeasia salicifolia (diabetes), Desmodium elegans (anti-cancerous), Hibiscus rosa-sinensis (jaundice), Hypericum oblongifolium (arthritis), Sarcococca saligna (tuberculosis), Rubus niveus (chronic cough) and Otostegia limbata (renal disorders). We suggest that species reported with high use value should be involved in cultivation and agricultural practices for their sustainable use and those reported with new therapeutic uses should be employed in further biotechnological, pharmacological and clinical studies in order to validate their traditional uses.

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The appearance of pharmaceutical compounds and their bioactive transformation products in aquatic environments is becoming an issue of increasing concern. In this study, the electrochemical oxidation of the widely used antibiotic sulfamethoxazole (SMX) was investigated using a commercial mixed oxide anode (Ti/Ru0.3Ti0.7O2) and a single compartment filter press-type flow reactor. The kinetics of SMX degradation was determined as a function of electrolyte composition, applied current density, and initial pH. Almost complete (98 %) degradation of SMX could be achieved within 30 min of electrolysis in 0.1 mol L(-1) NaCl solution at pH 3 with applied current densities ≥20 mA cm(-2). Nine major intermediates of the reaction were identified by LC-ESI-Q-TOF-MS (e.g., C6H9NO2S (m/z = 179), C6H4NOCl (m/z = 141), and C6H6O2 (m/z = 110)). The degradation followed various routes involving cleavage of the oxazole and benzene rings by hydroxyl and/or chlorine radicals, processes that could occur before or after rupture of the N-S bond, followed by oxidation of the remaining moieties. Analysis of the total organic carbon content revealed that the antibiotic was partially mineralized under the conditions employed and some inorganic ions, including NO3 (-) and SO4 (2-), could be identified. The results presented herein demonstrate the efficacy of the electrochemical process using a Ti/Ru0.3Ti0.7O2 anode for the remediation of wastewater containing the antibiotic SMX.

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