Antibacterial substances belong to a group of compounds that attack dangerous microorganisms. Therefore, killing bacteria or reducing their metabolic activity will lessen their adverse effects on a biological system. They originated from either synthetic materials, microbes, or mold. Many of these medications treat the gram-negative bacteria from the critical precedence group, such as pseudomonas, carbapenem-resistant acinetobacter, and enterobacterales. This study aims to investigate the simultaneous analysis of specific antibacterial spectrophotometrically. The WHO maintains this list of priority infections with antibiotic resistance. Drug combinations in single dosage forms are becoming increasingly popular in the pharmaceutical industry. This has created a significant issue for pharmaceutical administrators, particularly in combating fake medications and pharmaceutical analysts and developing reliable and accurate methodologies with minimal overlapping effects on quantification. The basics of several spectrophotometric methods utilized to conduct multicomponent analysis are collected in the current work, and the validation criteria that are an essential component of the approaches are also described. Numerous analytical techniques, including high-performance liquid chromatography, electrochemical methods, flow injection techniques, gas chromatography, spectrofluorometric techniques, capillary electrophoresis, and spectrophotometric techniques, have been reported to determine antibacterials. This study conducts a concise narrative evaluation of the many spectrophotometric methods that have been published for the simultaneous investigation of Levofloxacin, Sulfamethoxazole, Metronidazole, and Rifampicin in their pure forms, pharmaceutical dosage forms, and biological samples due to their sensitivity, simplicity, and cost-effectiveness.
Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.
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he development of multidrug resistance in Gram-negative bacteria is a major problem faced antimicrobial therapy and management of infectious diseases. Too many resistance mechanisms were developed since the antimicrobial agents were produced and actually used. The mechanisms involved in antimicrobial agents' resistance are, modifying enzymes, alteration of the target site of antimicrobials and prevention of antimicrobials accumulation inside the bacterial cells. The latest is accomplished by two mechanisms: alteration of outer membrane permeability and efflux pumps. Efflux pumps are either chromosomal or plasmid-encoded although chromosomal encoded efflux pumps are common in Gram-negative bacteria. Resistance nodulation division (RND) efflu
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The Cu(II) was found using a quick and uncomplicated procedure that involved reacting it with a freshly synthesized ligand to create an orange complex that had an absorbance peak of 481.5 nm in an acidic solution. The best conditions for the formation of the complex were studied from the concentration of the ligand, medium, the eff ect of the addition sequence, the eff ect of temperature, and the time of complex formation. The results obtained are scatter plot extending from 0.1–9 ppm and a linear range from 0.1–7 ppm. Relative standard deviation (RSD%) for n = 8 is less than 0.5, recovery % (R%) within acceptable values, correlation coeffi cient (r) equal 0.9986, coeffi cient of determination (r2) equal to 0.9973, and percentage capita
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