Reliable kinetic modeling of bimolecular reactions from multivariate spectroscopic data often relies on the pseudo-first-order (PFO) approximation. In this approximation, one reactant is assumed to be in constant excess. While this simplification facilitates exponential fitting, its quantitative validity under realistic experimental conditions remains unclear. In this study, we evaluated the accuracy of the PFO approximation compared to the true second-order kinetic model using simulated spectroscopic data generated from a bilinear Beer-Lambert law. The simulations covered factorial combinations of four concentration ratios ([B](0)/[A](0) = 1, 10, 50, and 100), four second-order rate constants (k = 0.04-0.60 M-1 s(-1)), and three noise levels (sigma = 0.0005-0.01 AU). We employed global nonlinear least-squares fitting with a Newton-Gauss/Levenberg-Marquardt algorithm to simultaneously recover the kinetic parameters (k or k(obs)) and pure component spectra. The results showed that the PFO model systematically underestimates the true second-order rate constant when the excess reactant is depleted by more than a few percent. Under near-stoichiometric conditions ([B](0)/[A](0) approximate to 1), recovery errors ranged from 15% to 45% and decreased monotonically with increasing excess. Recovery errors fell below 1 percent only when [B](0)/[A](0) was greater than or equal to 50. Noise had a negligible influence on the mean parameter estimates, but it markedly increased their uncertainties. Therefore, for multivariate spectroscopic kinetic data, the full second-order model should be the default fitting strategy, and the PFO approximation should be reserved for extreme cases of reactant excess where its assumptions are valid.
In this work, chitosan was obtained from shrimp shell waste by acid-alkali extraction. It was then cross-linked with glutaraldehyde to form chitosan hydrogels. The obtained solid particles with average sizes of about 50 mu m (high molecular weight) and 39 mu m (low molecular weight) were prepared and used as adsorbents for Pb (II) and Cd (II) ions from aqueous solutions. The effects of contact time, solution pH, temperature, adsorbent amount, and initial metal ion concentration were investigated. The prepared adsorbents were characterized using SEM, FTIR, and XRD analyses. 200 mg of low molecular weight modified chitosan was able to adsorb 20 mg/L of lead and 2 mg/L of cadmium to the extent of 87.2% and 91.2%, respectively, in 24 h at 30 degrees C and pH=7. The adsorption isotherm of this reaction follows the Langmuir model, and the adsorption process follows a pseudo-second-order kinetic model. The effect of other ions on the adsorption rate was investigated, and it was found that the presence of other metal cations can reduce the adsorption of Pb and Cd by about 15%. The validity and reliability of the method were confirmed through recovery experiments on real contaminated samples, yielding recoveries of 85.8% for Cd and 89.6% for Pb. The reusability of the adsorbent was investigated, and after 6 consecutive adsorption-desorption cycles, the removal efficiency decreased by 10-14%. This study shows that chitosan hydrogels derived from marine biowaste have significant potential as economical, sustainable, and environmentally friendly adsorbents for the treatment of heavy metal-contaminated wastewater.
Exosomes are promising cancer biomarkers but require sensitive, low-cost detection methods. We present a label-free, paper-based electrochemical immunosensor that utilizes a ternary Hemin-mesoporous carbon foam (MCF)-multiwall carbon nanotube (MWCNT) nanocomposite as both an electrode modifier and an internal probe. Hemin-loaded MCF integrated with carboxylated MWCNTs produces a conductive, high-surface-area platform that enables direct signal generation without the need for external labels. The composite was immobilized on a carbon-ink three-electrode paper strip via anti-CD9 antibodies for exosome capture. Electrochemical characterization verified composite formation, antibody attachment, and target binding. Under optimized conditions, the sensor showed a linear response from 5 x 10(2) to 5 x 10(5) exosomes mu l(-1) and a limit of detection of 150 exosomes mu l(-1). DPV currents decreased with increasing exosome load due to the formation of an insulating protein layer, allowing quantification from Delta I. The device exhibited high selectivity, good reproducibility, and stability. Analysis of diluted human serum produced recoveries consistent with ELISA. This low-cost, disposable platform is suitable for rapid exosome analysis and adaptable to multiplexed point-of-care diagnostics.
The development of sensitive and simple methods for determining chemical drugs is of great interest due to their potential side effects. Herein, an electrochemical sensor has been proposed to determine floxuridine (Flx) by utilizing the layered double hydroxide of nickel and cobalt (NiCo-LDH). NiCo-LDH was electrodeposited on the surface of a glassy carbon electrode modified with multi-walled carbon nanotubes (GCE/CNT). LDH synthesis via the electrodeposition technique enjoys advantages such as extreme speed and simplicity. The morphology of the surface of the fabricated sensor was characterized by scanning electron microscopy, and the elemental analysis was performed by energy-dispersive X-ray spectroscopy. To investigate the reactivity of the Flx molecule and identify the sites susceptible to electrochemical oxidation, the structure of Flx was examined by density functional theory (DFT). Comparing the electrochemical behavior of GCE/CNT and GCE/CNT/NiCo-LDH for the determination of Flx in alkaline medium revealed that only NiCo-LDH has an electrocatalytic effect towards the oxidation of Flx. Under optimized conditions, the calibration curve obtained using the differential pulse voltammetry technique was linear from 1.5 x 10(-6) to 2.0 x 10(-4 )M with a detection limit of 5.64 x 10(-8) M. Furthermore, the proposed sensor has good selectivity, excellent precision, and accuracy, and was successfully applied to measure Flx in pharmaceutical and human serum samples with a recovery range of 96.8-104.6%.
The measurement of tramadol as a potent analgesic is essential for the precise control of its dosage to prevent side effects and dependence. This study introduces an innovative electrochemical sensor that utilizes a carbon paste electrode modified with palladium nanoparticlesbonded aluminum oxide nanocomposite (PdNP@Al2O3), resulting in the PdNP@Al2O3 nanocomposite synergistically enhancing the electrocatalytic activity. A multi-technique electrochemical investigation combining cyclic voltammetry (CV), differential pulse voltammetry (DPV), impedance spectroscopy (EIS), chronoamperometry, and chronocoulometry revealed superior redox behavior of tramadol on the PdNP@Al2O3-modified electrode compared to unmodified counterparts. Systematic optimization of operational parameters (scan rate: 5-120 mV s(-1), pH: 3.0-9.0, etc.) yielded a robust sensor with a linear response spanning (0.02-120 mu M) and a record-low detection limit of (1.0 nM). In order to determine the selectivity of the method, the effect of different interference species was studied. Tramadol measurement with the above electrode in real samples, as tablets and blood serum, was examined. Tramadol was also measured in the presence of the narcotic drug morphine to investigate the electrode performance in the presence of other drugs.
Herbal medicines, derived from various parts of plants such as leaves, roots, and flowers, have been a keystone of traditional healing practices for centuries. Their origins date back to ancient times, including the Indian mythological era of Hanuman, where the Ramayana, a revered Hindu epic, mentions the use of herbal remedies like Sanjeevani, a miraculous healing herb. Sanjeevani was valued for its healing properties and passed down through generations. In Islamic tradition, the Quran highlights the medicinal benefits of plants, such as olive oil, honey, and black seeds, among others. The Prophet Mohammed (PBUH) also recommended herbs like Ajwa dates (Phoenix dactylifera) for treating ailments. Christianity acknowledges herbal healing, with references like the "balm of Gilead." This shared recognition of the healing power of plants across faiths demonstrates a deep understanding of herbal medicine and the connection between body, mind, and spirit. Today, herbal medicine is increasingly seen as a credible alternative to modern pharmaceuticals due to its cost-effectiveness and reduced side effects. With growing interest in natural healthcare, verifying the safety and efficacy of herbal remedies is vital. This review examines various extraction techniques and analytical methods for analyzing herbal medicines. These include Soxhlet Extraction, Supercritical Fluid Extraction (SFE), Sonication, and Microwave-Assisted Extraction (MAE), along with Mass Spectrometry (MS), Nuclear Magnetic Resonance (NMR) Spectroscopy, and High-Performance Liquid Chromatography (HPLC). These techniques ensure product quality, safety, and consistency, unlocking the full potential of herbal medicines for a healthier and more sustainable future.
This study presents the synthesis, characterization, and application of Ni-0.Zn-5(0).5Fe2O4 magnetic nanoparticles for the removal of heavy metal ions Pb(II), Cd(II), and Cu(II) from aqueous solutions. The nanoparticles were synthesized via a chemical co-precipitation method and characterized using FT-IR, XRD, SEM, and EDS techniques, confirming their crystalline structure, morphology, and elemental composition. The average crystallite size was found to be 10.4 nm, while SEM analysis showed an average particle size of 31.0 nm. The adsorption performance was evaluated under varying conditions of pH, adsorbent dosage, and contact time. Optimal removal was achieved at pH 5.0 for Pb-2(+) and pH 5.5 for Cd-2(+) and Cu-2(+), with respective contact times of 10, 35, and 40 minutes. Adsorption isotherm studies indicated that Pb-2(+) followed the Freundlich model, while Cd-2(+) and Cu-2(+) fit the Sips model, with maximum adsorption capacities of 77.25, 49.32, and 15.71 mg g-1, respectively. Kinetic data were best described by the pseudo-second-order model, suggesting chemisorption as the dominant mechanism. Desorption experiments demonstrated efficient recovery of adsorbed ions using dilute HNO3 and acetic acid, and the nanoparticles retained high removal efficiency over multiple reuse cycles. Compared to other adsorbents, Ni-0.Zn-5(0).5Fe2O4 nanoparticles exhibited superior performance, highlighting their potential as a cost-effective and reusable adsorbent for environmental remediation of heavy metal contaminants.
Dengue hemorrhagic fever (DHF) is still a serious health problem in Indonesia. Early detection of the NS1 antigen is an important approach because this antigen appears from the first day of infection. This study aims to develop a colorimetric biosensor based on gold nanoparticles (AuNPs) for the rapid and selective detection of NS1 antigen. AuNPs were synthesized using alpha-cyclodextrin (alpha-CDs) as a reducing and stabilizing agent through a heating method at 98 degrees C for 15 min. Furthermore, the surface of AuNPs was modified with mercaptoundecanoic acid (MUA) to add carboxylic groups, activated with EDC/NHS to allow bioconjugation with NS1 antibodies (AuNPsmAb). The UV-Vis characterization results showed a shift in the Surface Plasmon Resonance (SPR) peak from 517 nm to 530 nm after interaction with the NS1 antigen, accompanied by a decrease in absorbance from 0.304 to 0.108 and a color change in the solution from reddish-purple to faint purple in less than 5 min. The biosensor showed good sensitivity with a Limit of Detection (LOD) of 22.02 ng ml(-1), linearity R-2 = 0.996, and stability up to 14 days. Selectivity testing against interferents such as glucose, cholesterol, and uric acid showed no cross-reactivity. Applicative tests with human serum proved the effectiveness of detection in real conditions. With the advantages of a fast, practical method that does not require complex equipment, this AuNPs-mAb biosensor has the potential to be an efficient early diagnostic tool for dengue virus infection. It can be further developed for nanoparticle-based clinical applications.
Accurate quantification of food colorants is essential to ensure regulatory compliance, verify product authenticity, and protect consumer safety. Synthetic dyes such as sunset yellow FCF, tartrazine, and amaranth are sometimes used in food products without proper declaration, raising concerns about potential health risks and labeling accuracy. This study applies multivariate curve resolution-alternating least squares (MCR-ALS) to spectrophotometric acid-base titration data for the quantification of colorant mixtures without the need for chemical separation. A major advantage of this method is its ability to resolve rank-deficient systems by augmenting sample data with only a single pure standard, thereby eliminating the need for full calibration of all interfering components. This second-order strategy enables accurate quantification even in the presence of spectral overlap and unknown background signals. By organizing pH-dependent spectral data from samples and standards into a column-wise augmented matrix, the method ensures reliable results even in complex matrices. The method yielded satisfactory recoveries (98-108%) when applied to real samples, including saffron, saffron ink, and an orange soft drink. Owing to the second-order advantage of MCR-ALS, analyses in real samples were successfully resolved despite strong spectral overlap between natural and synthetic colorants, with no interference from the naturally occurring compounds. Overall, the method provides a practical solution for multicomponent analysis in complex food matrices.
The progress of analytical chemistry is pervasive in all fields, which leads to significant consumption of organic solvents and dangerous reagents, with a growth in the creation of waste to be treated. Given the increasing prevalence of diabetes and the need for precise monitoring of medication levels, a robust analytical technique is essential for ensuring therapeutic efficacy and safety. In this work, we developed a simple, fast, cost-effective, and environmentally friendly approach for the simultaneous determination of three antidiabetic drugs, such as linagliptin (LGT), empagliflozin (EPZ), and gliclazide (GLZ) in the synthetic mixtures and pharmaceutical formulation, using UV-Vis spectroscopy and multivariate calibration 1 (MVC1) toolbox. Three methods of this toolbox were studied, including partial least squares (PLS), principal component regression (PCR), and hybrid linear analysis (HLA) with full-spectrum and selected wavelengths. All methods showed more accurate prediction results based on the recovery values. The developed methods demonstrated high accuracy, precision, and reproducibility across a wide range of concentrations, proving effective for the simultaneous analysis of these antidiabetic agents in pharmaceutical formulations. This research highlights the potential of UV-Vis spectroscopy and the MVC1 toolbox as reliable tools for routine analysis in quality control laboratories and clinical settings.
A highly sensitive and reliable ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method was developed and validated for the simultaneous determination of four nitrofuran metabolites (NFMs), namely 3-amino-2-oxazolidinone (AOZ), 3-amino-5-morpholinomethyl-2-oxazolidinone (AMOZ), 1-aminohydantoin (AHD), and semicarbazide (SEM), in aquatic products and seafood. The method involved a simple and efficient sample preparation procedure based on liquid-liquid extraction (LLE), which significantly reduced analysis time and lowered the limit of detection (LOD) to 0.003 mu g/kg. The method exhibited excellent linearity (R-2 > 0.9998), satisfactory recovery (94-112.9%), and good repeatability with relative standard deviation (RSD) values below 12%. The validated method was successfully applied to analyze 237 shrimp samples, 12 frog samples, 7 catfish samples, 10 seafood roll samples, and 10 squid samples collected from markets in Ho Chi Minh City, Vietnam. The results revealed the presence of AOZ in 5.91 % of shrimp samples, 14.3% of catfish samples, and 25% of frog samples, with concentrations ranging from 0.11 to 22.9 mu g/kg. These findings highlight the importance of establishing and enforcing effective control measures to ensure food safety and protect consumer health.
Azithromycin, a macrolide antibiotic, has been investigated as a treatment for COVID-19, but subsequent clinical trials revealed mixed results, leading health organizations to recommend against its routine use outside clinical trials. Despite this, its use surged in Iraq during the pandemic. Azithromycin is excreted in urine, contributing to its presence in wastewater, where it poses risks to aquatic ecosystems and can promote antibiotic resistance. This study bridges significant gaps in monitoring pharmaceutical pollutants by optimizing advanced techniques for azithromycin detection. The current study also bridges a significant technological gap by incorporating an optimized Solid Phase Extraction (SPE) method coupled with Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). Optimization of several steps, including extraction and LC-MS/MS, is involved in the development of a method. The key SPE parameters, including Sample preparation, solvent compositions, and elution solvents, have been carefully optimized. The flow rate was carried out at 4 min l(-1). The recovery of azithromycin was greatest at 10% methanol in water (pH 4) when used as a washing solvent. Ammonium hydroxide amended with the eluting solvent also improved the recovery rates. The LC-MS/MS method for the analysis of azithromycin showed excellent linearity and precision with detection and quantification limits at 0.03 and 0.1 mu g l(-1), respectively. The reliability of the method was confirmed by recovery studies. The optimized method was then employed for the evaluation of the azithromycin content in the wastewater samples, which amounts to 223 +/- 4, 184 +/- 2, and 168 +/- 5 ng l(-1) obtained at SDI, SIZ, and Samarra hospital, respectively, with Relative recovery ranging from 96.2% to 101.4%.
Accurately classifying cancer subtypes using high-dimensional gene expression data is a critical challenge in bioinformatics and clinical diagnostics. This study compares the performance of hard and soft Partial Least Squares Discriminant Analysis (PLS-DA) models in distinguishing acute myeloid leukemia (AML) from acute lymphoblastic leukemia (ALL) using a microarray dataset comprising 72 bone marrow samples and 7,129 gene expression variables. Both models were implemented using the PLSDAGUI software. Hard PLS-DA, based on linear discriminant analysis (LDA), enforces exclusive class assignments, whereas soft PLS-DA, incorporating quadratic discriminant analysis (QDA), allows for probabilistic and overlapping class memberships. The results showed that both approaches performed comparably during the training phase. However, during the test phase, soft PLS-DA occasionally exhibited lower sensitivity, particularly for ambiguous samples. This apparent drawback may, in fact, reflect its more realistic and cautious treatment of class uncertainty, which avoids forced misclassifications. These results underscore the complementary strengths of the two methods and highlight the importance of soft classification in scenarios involving high biological complexity and class overlap.
Fluorescein (FL), a widely used synthetic organic compound prized for its intense fluorescence and visibility, has extensive applications in medicine, biology, and environmental monitoring. However, the increasing prevalence of FL in wastewater streams raises significant environmental concerns, necessitating effective removal strategies. In this study, the magnetic nanocomposite, Fe3O4@SiO2-PANI, was synthesized and investigated for its efficacy in removing and quantifying FL using UV-visible spectrophotometry. The research illustrates the steps involved in synthesizing the nanosorbent and details its structural characteristics using FT-IR, SEM, and EDX methods. Additionally, it emphasizes how effectively the nanocomposite can extract FL when particular conditions are applied. The process involved using the nanosorbent with a mass of 65.0 mg along with a phosphate buffer solution at 0.1 M to maintain a consistent pH level of 10.0. These conditions were held for an accumulation time of 30 min. Additionally, the optimal parameters for the desorption process were attained, which included 2.5 ml of HCl (0.1 M) and a contact time of 30 min. The technique employed allowed for a linear calibration curve that facilitated the measurement of FL concentrations ranging between 0.27 and 5.3 mg l(-1). Notably, the method was precise in detecting FL at a lower limit of 0.011 mg l(-1) and quantifying it at levels down to 0.037 mg l(-1). The optimized conditions yielded an adsorbent capacity of 549.45 mg/g, along with a removal percentage exceeding 94.
This research presents the design of an electrochemical sensor for the detection and determination of glutathione, utilizing carbon paste electrodes modified with copper nanoclusters (Cu NCs). The characterization of the Cu NCs was conducted using several analytical Microscopy (TEM), X-ray Diffraction (XRD), and Energy-Dispersive X-ray spectroscopy (EDX). The study explored the electrochemical properties of glutathione through Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV). The results indicated that the sensor displayed a notable electro-oxidation response at a low oxidation potential of 0.43 V in a phosphate buffer solution with a pH of 2.00. Under optimized experimental conditions, the peak current exhibited a linear correlation with glutathione concentrations ranging from 5.0 mu M to 600.0 mu M, achieving a detection limit of 0.6 mu M (S/N = 3). Additionally, the voltammetric response demonstrated excellent reproducibility, with a relative standard deviation of 2.7% (n = 3), confirming the sensor's reliability for analytical purposes. The sensor measured glutathione concentrations in biological samples, including urine and pharmaceutical tablets, with a recovery ranging from 88.0% to 109.7%. The results show the sensor's potential to detect glutathione in biological matrices for both clinical and research applications.
In this study, a highly sensitive recyclable colorimetric chemosensor for the detection and determination of copper(II) and L-cysteine (Cys) was presented, which uses an optical color change based on an indicator displacement assay (IDA). This chemosensor was designed and fabricated using the xanthine dye, bromopyrogallol red (BPR), an easy-to-prepare dye. The label exchange between BPR and Cys occurred upon adding cysteine to the BPR-copper(II) complex, resulting in a clear and immediate color change from blue to purple in DMSO/MES buffer at 10.0 mM, pH 5.0 (1:4 v/v). The proposed method exhibits a detection limit of 80.0 nM and a reasonable linear range from 0.79 to 21.00 mu M for cysteine. Furthermore, based on the absorbance changes and color changes produced, this chemosensor is proposed as an "IMPLICATION" logic gate (IMP) to evaluate the inputs of Cu2+ and cysteine. Based on the fast response and repeatability, a molecularscale sequential memory unit is designed to exhibit "keypad lock" behavior. The extended receptor offers satisfactory repeatability and good accuracy and is used for the selective determination of cysteine in human blood plasma and urine. Furthermore, the method's accuracy was compared with the results of the proposed method by high-performance liquid chromatography (HPLC).
Thin films of f-MWCNT (functionalised multiwalled carbon nanotubes) were formed on the surface of Indium-Tin-Oxide (ITO) electrode of size 1 x 2 cm(2) by pouring 10 mu l of prepared solution of f-MWCNT (1 mg ml-1). After drying the electrode, optimised gold-platinum alloy nanoparticles (Au3Pt1NP ) were electrochemically deposited on the surface of the modified ITO electrode under the optimised deposition conditions for solution and number of deposition cycles [1-5]. Deposition of layers of f-MWCNT and Au3Pt1NP (alloy nanoparticles of gold and platinum in 3:1 ratio) on ITO surface were confirmed by Field Emission Scanning Electron Microscopy (FESEM), Energy Dispersive X-ray Analysis (EDAX) and X-ray diffraction (XRD) techniques while to investigate the electrochemical properties, electrochemical methods (cyclic voltammetry (CV), differential pulse voltammetry (DPV) and Electrochemical Impedance Spectroscopy (EIS) were used which indicated improved electrochemical performance of f-MWCNT/ITO electrode. This electrode was further modified with Serum Amyloid A protein (SAA) specific antibodies immobilisation (SAA-Ab/f-MWCNT/ITO) and used to detect protein biomarker Serum Amyloid A (APOSAA). Electrochemical sensing studies by prepared immunoelectrode confirmed detection in a linearity range of 10 fg ml(-1) to 10(8) fg ml(-1). By using equation 3 sigma/sensitivity, the limit of detection (LOD) was found to be 8.78 fg ml(-1). Excellent selectivity of fabricated immunoelectrode for SAA biomarker, its stability up to five weeks with 89.18% of current retention, and reproducibility studies with relative standard deviation of 3.95% indicate the successful fabrication of immunosensor that can be used to detect SAA biomarker.
A novel extractive spectrophotometric method has been developed for the determination of palladium(II), iridium(III), and ruthenium(III) using 2-(2-(1-(thiophene-2-yl) ethylidene) hydrazinyl) benzoic acid (TEHBA) as a selective complexing agent. In acidic medium palladium(II), iridium(III), and ruthenium(III) react with 2-(2-(1-(thiophene-2-yl) ethylidene) hydrazinyl) benzoic acid (TEHBA) and form stable complexes that are quantitatively extracted into a suitable extracting solvent. The absorption spectrum of these complexes was taken in the wavelength range of 200-400 nm. Beer's law is obeyed between the concentration range 2-20 mu g ml(-1), 10-60 mu g ml(-1), and 10-50 mu g ml(-1) in the final solution of palladium(II), iridium(III), and ruthenium(III) subsequently. Molar absorptivity and Sandel's sensitivity values were also calculated for respective metal ions. The stoichiometry of the Ir(III)-TEHBA and Ru(III)-TEHBA complexes was computed as 1:1. However, the ratio of the Pd(II)-TEHBA complex was calculated as 1:2 by using the mole ratio method. These metal-to-ligand complexes are highly stable and selective, showing negligible interference from common metal ions even in large excess. The unique binding properties of the ligand and the observed metal-ligand stoichiometry, supported by UV-visible spectral analysis, reveal new insights into these complexes' electronic interactions and geometry. The high selectivity and stability of these systems underscore their potential for practical use in analytical and environmental chemistry. Developed methods offer low-cost, sensitive, and reproducible approaches for Pd(II), Ir(III), and Ru(III) quantification in environmental synthetic samples. Additionally, the developed procedures illustrate a sequential extraction and separation of palladium(II), iridium(III), and ruthenium(III) and boast their simplicity of use.
Herein, we present the development and validation of a Reverse Phase High-Performance Liquid Chromatography (RP-HPLC) method for the analysis of 1-(4-chlorophenyl) pyrrolidine-2,5-dione (CPS), an important intermediate and active pharmaceutical ingredient. CPS, also known as chlorophenyl pyrrolidine succinimide, consists of a chlorophenyl group, which enhances lipophilicity and receptor binding; a pyrrolidine ring, contributing to structural stability; and a succinimide moiety, which facilitates biological activity. The Box-Behnken Design (BBD), a type of response surface methodology, was employed to optimize chromatographic conditions, including the mobile phase composition, flow rate, detection wavelength, and other parameters, with a strong focus on sensitivity, clarity, accuracy, and robustness. The optimized RP-HPLC method achieved a favorable retention time of 4.567 min for CPS at a detection wavelength of 222 nm. The method demonstrated excellent linearity (r(2) = 0.9988), good accuracy (recovery range: 98-102%), and precision (%RSD < 2%). The specificity of the method was confirmed by the absence of interference from excipients and degradation products. The limits of detection (LOD) and quantification (LOQ) were calculated to be 0.1837 ppm and 0.5569 ppm, respectively. Stability studies under various stress conditions demonstrated that the method is stability-indicating and capable of separating CPS from its degradation products. This study highlights the effectiveness of the Box-Behnken Design in the systematic development of an RP-HPLC method and underscores the importance of the Quality by Design (QbD) approach in ensuring method reliability and regulatory compliance. Accurate, precise, and reproducible results were obtained by strictly adhering to ICH guidelines.
According to the World Health Organization, with more than 2.3 million cases of breast cancer annually, this disease is reported as the most common cause of death among women. Therefore, early detection of breast cancer is very important to reduce the mortality rate of women. In general, evaluation of cancer tissues is one of the most reliable and at the same time the most time-consuming methods, and considering the low concentration of cancer cells at the beginning of the disease, new methods with greater sensitivity are needed. In this case, molecularly imprinted polymers are man-made receptors with special binding holes that are the same size, shape, and function as template molecules that are used in diagnostic sensors. Also, molecularly imprinted polymers have been employed as among the most interesting biomaterials for therapeutic approaches. Considering the global Breast Cancer Awareness Month campaign and the importance of this issue for better understanding, the detection of biomarkers of breast cancer by molecularly imprinted polymers and the role of molecularly imprinted polymers in the treatment of breast cancer is discussed, in this review. The purpose of this article is to help readers and researchers comprehend how molecularly imprinted polymers could be used to identify breast cancer biomarkers as a diagnostic element in sensors.
