Optimization of graphene polypyrrole for enhanced adsorption of moxifloxacin antibiotic: an experimental design approach and isotherm investigation.

The presence of antibiotics in water systems had raised a concern about their potential harm to the aquatic environment and human health as well as the possible development of antibiotic resistance. Herein, this study investigates the power of adsorption using graphene-polypyrrole (GRP-PPY) nanoparticles as a promising approach for the removal of Moxifloxacin HCl (MXF) as a model antibiotic drug. GRP-PPY nanoparticles synthesis was performed with a simple and profitable method, leading to the formation of high surface area particles with excellent adsorption properties. Characterization was assessed with various techniques, including Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), X-ray diffraction (XRD) and Brunauer-Emmett-Teller (BET). Box-Behnken experimental design was developed to optimize the adsorption process. Critical parameters such as initial antibiotic concentration, nanoparticle concentration, and pH were investigated. The Freundlich isotherm model provided a good fit to the experimental data, indicating multilayer adsorption of MXF onto the GRP-PPY-NP. As a result, a high adsorption capacity of MXF (92%) was obtained in an optimum condition of preparing 30 µg/mL of the drug to be adsorbed by 1 mg/mL of GRP-PPY-NP in pH 9 within 1 h in a room temperature. Moreover, the regeneration and reusability of GRP-PPY-NP were investigated. They could be effectively regenerated for 3 cycles using appropriate desorption agents without significant loss in adsorption capacity. Overall, this study highlights the power of GRP-PPY-NP as a highly efficient adsorbent for the removal of MXF from wastewater as it is the first time to use this NP for a pharmaceutical product which shows the study's novelty, and the findings provide valuable insights into the development of sustainable and effective wastewater treatment technologies for combating antibiotic contamination in aquatic environments.

An integrated framework to develop an efficient valid green (EVG) HPLC method for the assessment of antimicrobial pollutants with potential threats to human health in aquatic systems.

The persistence of antimicrobial drugs in aquatic environments has raised critical concerns about their possible impact on drinkable water quality and human health. The Nile River is experiencing water pollution owing to increasing discharges of highly contaminated home and industrial effluents and inadequate water management systems. Investigations of the presence of three antimicrobial agents, ciprofloxacin (CIP), sulfamethoxazole (SMZ), and albendazole (ALB), in the Egyptian aquatic system are recommended using a chromatographic method because of their reported existence in the African aquatic environment. In this study, an integrated framework, Efficient Valid Green (EVG), for analytical techniques is proposed and displayed via its radar chart. The EVG framework is achieved through three main pillars: efficiency, validation, and greenness. The proposed EVG-HPLC method was developed and optimized using the AQbD methodology via a face-centered composite (FCC) design by identifying the proper critical method parameters (CMPs) that influence critical quality attributes (CQAs). The method was fully validated according to ICH guidelines, including a factorial robustness study within concentration ranges of 1-100 µg mL-1, 2-100 µg mL-1, and 10-100 µg mL-1 for CIP, SMZ, and ALB, respectively. The proposed method was evaluated in terms of greenness using AGREE (score 0.55) and ComplexGAPI metrics. The optimized chromatographic conditions included a C18 column and a mobile phase of water : acetonitrile : methanol in a ratio of 60 : 19 : 21, v/v/v, respectively, with an aqueous solution of pH 3.5 adjusted with phosphoric acid at a flow rate of 1.57 mL min-1 at 285 nm. The raw water samples collected from Nile River freshwater at different locations were treated using Oasis® PRiME HLB cartridges with satisfactory recoveries for the three analytes (>90%), and the three drugs were detected using the proposed EVG-HPLC method.

All-solid-state chip utilizing molecular imprinted polymer for erythromycin detection in milk samples: Printed circuit board-based potentiometric system.

Detection of erythromycin (ERY) residues in commercial milk samples is crucial for the safety assessment. Herein, a printed circuit board was patterned as a feasible miniaturized potentiometric sensor for ERY determination in dairy samples. The proposed chip design fits to a 3.5-mm female audio plug to facilitate the potential measurements of working electrode versus reference one in this all-solid-state system. The sensor utilizes molecular imprinted polymer (MIP) for the selective recognition of the studied drug in such challenging matrix. The electrode stability is achieved through the addition of poly (3,4-ethylenedioxythiophene) nano-dispersion on its surface. The proposed device detects down to 6.6 × 10-8 M ERY with a slope of 51 mV/decade in the 1 × 10-7-1 × 10-3 M range. The results display high accuracy (99.9% ± 2.6) with satisfactory relative standard deviation for repeatability (1.6%) and reproducibility (5.0%). The effect of common antibiotic classes, namely, amphenicols, beta-lactams, fluoroquinolones, sulfonamides, and tetracyclines, can be neglected as evidenced by their calculated binding capacities towards the proposed MIP. The calculated selectivity coefficients also show a good electrode performance in the presence of naturally present inorganic ions allowing its application to different milk samples.

A trimodal detection paper chip for undisclosed drug "sibutramine" in nutraceuticals.

Nutraceuticals are promoted and marketed with the stated label of being natural as well as safe herbal products. In order to enhance their effectiveness, nutraceuticals are usually adulterated with undeclared constituents. Slimming herbs may contain sibutramine (SBT) which is an FDA-banned ingredient due to its fatal outcomes. This current work's aim is to design a trimodal sensor for SBT detection in different herbal slimming formulations. Screen-printed silver and multi-walled carbon nanotube inks were employed for the potentiometric sensor. The sensor was designed to fill a reaction well in which a carbon dot-silver nanoparticle pair was applied for fluorimetric and colorimetric purposes. The trimodal sensor was designed to fit an 8 mm 2-pin LED strip connector. Potentiometric measurement took place upon application of one sample aliquot then the optical reaction proceeded next in a specified zone for optical detection. These multiple detection mechanisms achieved the required selectivity for SBT determination in the presence of other slimming products' additives. This trimodal sensor satisfied World Health Organization standards for point-of-care devices demonstrating the suggested device as a dynamic part for rapid on-site detection of undisclosed SBT.

Green potentiometric electrode for determination of salbutamol in biological samples.

Clinical drug analyses and identification of pharmaceuticals in biological samples are highly crucial for therapeutic drug monitoring, pharmacokinetic studies, and screening of illicit drugs. Various analytical tools, such as potentiometric electrodes, are used to conduct these investigations. These potentiometric electrodes are superior to other techniques in terms of greenness and cost efficacy, and thus present a good alternative for researchers. In this study, we develop an advanced electrode for the in-situ monitoring of salbutamol in plasma, this electrode was synthesized using multiwalled carbon nanotubes (MWCNT) as hydrophobic conductive substance and copper oxide nanoparticle (CuO NP) as a surface modifier, the developed electrode was compared to traditional liquid contact electrode as well as solid contact electrode and proved its superiority. The use of MWCNT improved the stability of the electrode via preventing the formation of this water layer and the CuO NP improved the sensitivity due to its high surface area and rich electronic properties. CuO NP modified electrode was used for the determination of salbutamol with a Nernstian slope of 57.4 over a linearity range of range 1.0 × 10-7- 1.0 × 10-2 M, and a detection limit of 4.0 × 10-7 M. The proposed electrode was effectively applied for the determination of the cited drug in rat plasma without interference and compared with chromatographic reported method. The proposed method is economic as it has a low sample analysis cost, time saving and needs fewer manipulation steps and a simple convenient device. It also proved to be a greener method when compared with chromatographic methods using an eco-scale metric system.

Artificial networks for spectral resolution of antibiotic residues in bovine milk; solidification of floating organic droplet in dispersive liquid-liquid microextraction for sample treatment.

The intensive use of antibiotics in livestock practice has a negative impact on human health and increases the antibiotic resistance. In this study feasible data interpretation algorithm along with efficient extraction protocol were combined for selective analysis of three antibiotics in milk samples. Trimethoprim, sulphamethoxazole and oxytetracycline are widely used antibiotics in veterinary pharmaceuticals. The studied antibiotics were efficiently extracted from milk samples with solidification of floating organic droplet in dispersive liquid-liquid microextraction. This extraction protocol was optimized not only to maximize extraction recoveries but also to approach the lower residue limits specified by European Union. Artificial neural networks succeeded in resolving spectral overlap between the studied drugs. The network architecture was optimized and validated for accurate and precise analysis. The proposed method outweighs the reported chromatographic methods for being simple and inexpensive and compared favorable to official methods.

Application of Chemometrics for Spectral Resolving and Determination of Three Analgesics in Water Samples.

BACKGROUND: Chemometrics is a discipline that allows the spectral resolution of drugs in a complicated matrix (e.g., environmental water samples) as an alternative to chromatographic methods. OBJECTIVE: Three analgesics were traced in wastewater samples with simple and cost-effective multivariate approaches using spectrophotometric data. METHODS AND RESULTS: Four chemometric approaches were applied for the simultaneous determination of diclofenac, paracetamol, and ibuprofen. Partial least squares (PLS), principal component regression (PCR), artificial neural networks (ANN), and multivariate curve resolution (MCR)-alternating least squares (ALS) were selected. The presented methods were compared and validated for their qualitative and quantitative analyses. Moreover, statistical comparison between the results obtained by the proposed methods and the official methods showed no significant differences. CONCLUSIONS: The proposed multivariate calibrations were accurate and specific for quantitative analysis of the studied components. MCR-ALS is the only method that has the capacity for both the quantitative and qualitative analysis of the studied drugs. HIGHLIGHTS: Four chemometric approaches were used for analysis of severally overlapped ternary mixture of three analgesics. The analytical performance of PCR, PLS, MCR-ALS, and ANN was compared and validated in terms of root mean square error of calibration (RMSEC), SE of prediction, and recoveries. ANN gave the highest predicted concentrations with the lowest RMSEC and root mean square error of prediction. MCR-ALS has the capacity for both qualitative and quantitative measurement. The methods have been effectively applied for real samples and compared to official methods.

Derivative constant wavelength synchronous fluorescence spectrometry for the simultaneous detection of cefadrine and cefadroxil in water samples.

A sensitive accurate spectrofluorimetric technique was developed to detect cefadroxil and cefradine traces in water samples simultaneously, by applying a procedure based on the formation of hydrolysis products corresponding to these compounds by sodium hydroxide (1 N NaOH) treatment. The conventional and the synchronous fluorescence spectra of these hydrolyzed products were totally overlapped making resolving of this mixture impossible. The second-derivative constant-wavelength synchronous fluorescence spectra allowed their detection simultaneously in a single scan after experimental conditions optimization, which was measured at 390 nm and 379 nm for cefadroxil and cefradine, respectively at Δλ = 30.0. The calibration curves between derivative synchronous fluorescence intensity and drugs concentration showed suitable linear correlation in the range of 0.1 to 5 µg.mL-1 for cefadroxil and 0.5-10 µg.mL-1 for cefradine. The proposed fluorimetric method is superior in being simple, environmental friendly and cost effective in comparison to the previously published reported methods.

Chemometrics for resolving spectral data of cephalosporines and tracing their residue in waste water samples.

Chemometrics approaches have been used in this work to trace cephalosporins in aquatic system. Principal component regression (PCR), partial least squares (PLS), multivariate curve resolution-alternating least squares (MCR-ALS), and artificial neural networks (ANN) were compared to resolve the severally overlapped spectrum of three selected cephalosporins; cefprozil, cefradine and cefadroxil. The analytical performance of chemometric methods was compared in terms of errors. Artificial neural networks provide good recoveries with lowest error. Satisfactory results were obtained for the proposed chemometric methods whereas ANN showed better analytical performance. The qualitative meaning in MCR-ALS transformation provided very well correlations between the pure and estimated spectra of the three components. This multivariate processing of spectrophotometric data could successfully detect the studied antibiotics in waste water samples and compared favorably to alternative costly chromatographic methods.

Validated univariate and multivariate spectrophotometric methods for the determination of pharmaceuticals mixture in complex wastewater.

Five, accurate, precise, and sensitive univariate and multivariate spectrophotometric methods were developed for the simultaneous determination of a ternary mixture containing Trimethoprim (TMP), Sulphamethoxazole (SMZ) and Oxytetracycline (OTC) in waste water samples collected from different cites either production wastewater or livestock wastewater after their solid phase extraction using OASIS HLB cartridges. In univariate methods OTC was determined at its λmax 355.7 nm (0D), while (TMP) and (SMZ) were determined by three different univariate methods. Method (A) is based on successive spectrophotometric resolution technique (SSRT). The technique starts with the ratio subtraction method followed by ratio difference method for determination of TMP and SMZ. Method (B) is successive derivative ratio technique (SDR). Method (C) is mean centering of the ratio spectra (MCR). The developed multivariate methods are principle component regression (PCR) and partial least squares (PLS). The specificity of the developed methods is investigated by analyzing laboratory prepared mixtures containing different ratios of the three drugs. The obtained results are statistically compared with those obtained by the official methods, showing no significant difference with respect to accuracy and precision at p=0.05.