BACKGROUND:Altered amino acid metabolism is a feature of gastric cancer. Type 2 diabetes (T2D), a prevalent metabolic comorbidity, may affect circulating amino acid profiles; this study aimed to quantify its impact. RESEARCH DESIGN AND METHODS:A validated targeted LC-MS/MS assay profiled 22 serum amino acids in 156 participants, including gastric cancer patients with and without type 2 diabetes and controls. RESULTS:Adjusted models showed that many observed differences were attributable to type 2 diabetes and body mass index. Type 2 diabetes was associated with lower ornithine (β =  -1.16; q = 0.0019) and interacted with gastric cancer for arginine (β_int =  -1.10; q = 0.0044) and phenylalanine (β_int =  +1.05; q = 0.0112). After adjustment, only valine, taurine, and total amino acids remained lower in gastric cancer. Body mass index was inversely associated with glutamine and positively associated with glutamate. CONCLUSIONS:Covariate-adjusted analysis distinguishes cancer-related from comorbidity-driven alterations and identifies type 2 diabetes as a key modifier of amino acid metabolism. Metabolic covariates should be considered when interpreting amino acid alterations in advanced gastric cancer biomarker studies. However, the findings should be interpreted in light of the predominantly advanced-stage gastric cancer cohort and require validation in larger prospective studies.

In this study, a sensitive, rapid, economical, and simple derivatization-based spectrophotometric procedure was developed and validated for the determination of pregabalin in bulk substance and pharmaceutical formulations. The procedure is based on the formation of a chromogenic imine derivative through the reaction of the primary amine group of pregabalin with 2-naphthaldehyde in a basic medium. Experimental design methodology was applied to screen and optimize the critical reaction parameters, including K2CO3 concentration, temperature, and ethanol volume. A central composite design was employed to evaluate factor effects and to establish the optimal derivatization conditions. After derivatization, absorbance measurements were performed at 228 nm in the UV spectrum and at 236 nm for the first-derivative spectrophotometric mode. The procedure showed linearity in the concentration range of 2–30 µg/mL for the direct UV measurement and 2–50 µg/mL for the first-derivative measurement, with coefficients of determination greater than 0.999. The analytical performance of the procedure was validated according to ICH Q2(R1) guidelines with respect to linearity, precision, accuracy, limits of detection and quantification, and stability. The results demonstrate that the proposed derivatization-based spectrophotometric procedure provides a reliable, reproducible, and cost-effective alternative for the quantitative analysis of pregabalin in pharmaceutical quality control laboratories.

This study aimed to develop an artificial intelligence (AI)-based UV–Vis spectrophotometric method for simultaneously quantifying naringin and naringenin in Thymus canoviridis methanol extract. Conventional spectrophotometric techniques often face challenges in analyzing mixtures of compounds with overlapping spectra, making accurate quantification difficult. This limitation calls for advanced modelling approaches that incorporate machine learning to enhance prediction accuracy while aligning with green chemistry principles. Binary mixtures of naringin and naringenin were prepared at concentrations ranging from 5 to 40 μg/mL. UV–Vis spectra were collected over the 240–450 nm range. The trained machine learning models included Support Vector Regression (SVR), Linear Regression, Lasso Regression, Ridge Regression, and Elastic Net. These models were used to predict the concentrations of both flavonoids from their spectral data. Performance was evaluated using Mean Absolute Error (MAE) and the coefficient of determination (R2). The Ridge Regression model showed superior predictive performance, achieving MAEs of 0.882 for naringin and 0.378 for naringenin, with R2 values of 0.9912 and 0.9984, respectively. The model was successfully applied to the Thymus canoviridis extract, enabling precise quantification of both compounds without chemical separation. The method’s green chemistry profile was assessed using the AGREE and ComplexGAPI tools. AGREE scored it 0.72, reflecting strong green chemistry compliance, while ComplexGAPI revealed an overall environmentally favorable profile with some moderate environmental burdens related to solvent use. This study presents a green UV–Vis spectrophotometric method enhanced by AI for the simultaneous quantification of naringin and naringenin in plant extracts. By leveraging AI for spectral differentiation, the method achieves high accuracy and reliability without requiring chemical separation. This approach represents a significant advancement in plant metabolite analysis, facilitating high-throughput screening in phytochemical studies. The method's minimal solvent use, low waste generation, and energy efficiency make it a sustainable alternative to traditional techniques, suited for environmentally conscious phytochemical analysis.

This study presents an efficient and eco-friendly approach for the removal of the antibiotic moxifloxacin (MX) from wastewater via hollow carbon spheres (HCSs) as adsorbents, demonstrating for the first time the use of defect-rich and highly porous HCSs for MX adsorption under optimized conditions via central composite design (CCD). HCSs, selected for their high surface area and hollow structure, were employed as adsorbents in the MX removal process. The optimization of key variables, including the initial MX concentration, pH, ionic strength, and contact time, was achieved through CCD. High-performance liquid chromatography with a C18 column was used to quantify the MX concentrations before and after adsorption. The quadratic regression model was analyzed via analysis of variance (P < 0.01) to ensure statistical robustness. The CCD model identified the optimal conditions for MX adsorption, yielding a significant quadratic model (P < 0.01) and a high adsorption capacity of 823 µg/mg. The optimal conditions were a pH of 10.0, ionic strength of 0.3 M, MX concentration of 15 µg/mL, and contact time of 1 h. Adsorption followed the Langmuir isotherm model, indicating a monolayer adsorption mechanism. The mean recovery of MX on the HCSs was 97.9 ± 2.7

Progesterone is a steroid hormone primarily associated with pregnancy. A simple, rapid, and reliable high-performance liquid chromatography (HPLC) method has been developed and validated for the quantification of progesterone in human plasma. The method consists of a simple liquid-liquid extraction of progesterone and internal standard (estriol) from human plasma using a mixture of hexane and diethyl ether. The chromatographic determination of progesterone was performed using an acetonitrile-water (70:30, v/v) mobile phase with a C18 reversed-phase column. The method achieved an extraction recovery of greater than 96.4% from spiked plasma samples. Intra- and inter-day precision were generally acceptable, with relative SD% less than <= 6.60% and accuracy (relative error %) better than 3.64%. The developed and validated method was used to successfully quantify progesterone levels in plasma samples collected from women during the third trimester of pregnancy. Furthermore, a statistical comparison was conducted between progesterone concentrations in plasma samples obtained from 2 groups of pregnant women: group 1 (n = 9) at 30-35 weeks and group 2 (n = 9) at 36-41 weeks.The developed and validated HPLC method described in this study enables the successful determination of progesterone in human plasma, offering advantages such as shorter analysis time, simplicity, cost-effectiveness, and potential routine use during pregnancy.

In this study, the polarographic behavior of irbesartan was investigated using the cyclic polarographic method. A mercury drop electrode was used to quantify the peak currents in comparison to Ag/AgCl at 0.10 V/s. Additionally, quick and easy square wave and differential pulse polarographic methods were developed and validated to determine irbesartan in pharmaceutical preparations. For both methods, the calibration curves were linear at concentrations between 5 and 70 μg/mL. The precision was given by relative standard deviation and was less than 2.61%. Accuracy was given with relative error and did not exceed 1.24%. The suggested methods are extremely accurate and precise. No interference was found under the chosen experimental conditions. In pharmaceutical preparations, irbesartan had an average recovery of 99.8%. Therefore, the methods are applicable to the determination of irbesartan in pharmaceutical preparations.

Understanding the pharmacodynamics of ritonavir through metabolomics offers insights into its side effects and helps in the development of safer therapies. This study aimed to investigate the effects of ritonavir treatment on the metabolic profiles of rabbits via a metabolomics approach, with the objective of elucidating its impact on various biochemical pathways and identifying relevant biomarkers. The rabbits were divided into control and ritonavir-treated groups, and their plasma samples were analyzed via ultra-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/Q-TOF/MS/MS). Metabolites were identified on the basis of the masscharge ratio (m/z) and validated via XCMS software. Metabolites with a fold change ≥ 1.5 and P ≤ 0.01 were analyzed via principal component analysis (PCA) and orthogonal partial least squares discrimination analysis (OPLS-DA) to distinguish between the groups. MetaboAnalyst 6.0 was used for pathway analysis to identify metabolic pathways affected by ritonavir. The PCA and OPLS-DA models revealed clear separation between the control and ritonavir-treated groups, with high R² and Q² values indicating robust model performance. Pathway analysis revealed that ritonavir treatment significantly affected several metabolic pathways, including those related to ether lipid, phenylalanine, sphingolipid, and glycerophospholipid metabolism. Particularly significant changes were observed in metabolites related to lipid metabolism, oxidative stress responses and cellular signaling. Ritonavir significantly impacts metabolic pathways, particularly those involved in lipid metabolism, and oxidative stress responses, which may influence immune responses and drug interactions. This study also highlights the potential of integrating metabolomics with personalized medicine approaches to optimize ritonavir treatment strategies and reduce adverse effects. These findings indicate that ritonavir significantly influences cellular homeostasis and metabolic processes in addition to its antiviral properties. This highlights the necessity of comprehending the metabolic effects of ritonavir to enhance its clinical application, especially in the management of COVID-19. Further research is warranted to explore these alterations and their implications for therapeutic strategies.

The effect of total gastrectomy (TG) on plasma free amino acid (PFAA) concentrations in patients with stage II gastric cancer was investigated in the study. Nineteen patients' plasma samples were collected before and three months post-gastrectomy, and PFAA levels were quantified using LC-MS/MS. For gradient elution of amino acids, the mobile phases (A: 3% formic acid-5% methanol-30 mM ammonium formate, B: acetonitrile) and a Hypersil C18 column (100 mm x 2.1 m, 1.9 µm) were used. The findings revealed substantial modifications in the profile of PFAA after TG. In particular, the concentrations of twenty amino acids increased significantly, including branched-chain amino acids, L-glutamate, L-alanine, L-methionine, glycine, L-cystine, and L-histidine. Conversely, L-arginine was also reduced statistically. These alterations in the PFAA profile indicate the favorable effects of TG on various physiological processes, such as enhanced immune function, improved tissue healing, and increased energy production. Investigating the effects of various surgical techniques on PFAA profiles is a promising approach for optimizing surgical procedures, improving metabolic function, increasing immunological responses, and improving overall quality of life. These findings highlight the significance of evaluating amino acid metabolism as an important part of treatment, given its potential to improve clinical outcomes and general well-being.

Chlorogenic acid (CA) exhibits diverse biological activities, including antioxidant and antiinflammatory effects. This research aims to develop, optimize, and validate an HPLC method to quantify CA in methanol and investigate its in vitro proliferative and cell migration effects on human-dermal-fibroblast (HDF) cell lines in a dose-dependent manner. The HPLC experimental conditions were optimized using the central composite design (CCD) method for determining CA. Chromatographic separation occurred at a wavelength of 330 nm. Under the optimized conditions, the method exhibited linearity across a concentration range of 0.1-100 µg/mL, demonstrating sensitivity (LOQ:0.1µg/mL), precision (RSD%≤3.32), and accuracy (RE%≤4.05). To evaluate the in vitro proliferative and cell migration effects on HDFs, we employed the XTT cell proliferation assay and TAS-TOS commercial kits. The XTT assay revealed that CA displayed a proliferative effect within the concentration range of 75-250 µM (P <0.01), and at a concentration of 125 µM, TAS levels increased significantly (P<0.05). The scratch assay demonstrated that HDF cell migration increased at 12 h, with substantial closure of the wound area at 24 h when treated with CA concentrations between 75-125 µM. The results demonstrate that pure chlorogenic acid extracted from plants exhibits dose-dependent effects on cell proliferation, antioxidant, and cell migration

Background. - Precision medicine, which looks for high efficacy and low toxicity in therapies, has increased in popularity with omics technology. This work aims to discover novel and low-toxicity therapy options by examining the complex relationship between silodosin-induced side effects and the metabolomic profiles associated with its administration. Materials and methods. - The plasma samples of the control group and silodosin-treated rats were analyzed by LC-Q-TOF-MS/MS. Employing XCMS and MetaboAnalyst software, MS/MS data processed to detect compounds and investigate metabolic pathways. MATLAB 2019b was used for data categorization and multivariate analysis. A thorough comparison of METLIN and HMDB databases revealed 41 m/z values with significant differences between the drug-treated and control groups ( p < 0.01 and fold analysis > 1.5). Results. - According to multivariate data analysis, 17-,e-estradiol, taurocholic acid, Lkynurenine, N-formylkynurenine, D-glutamine, L-arginine, prostaglandin H2, prostaglandine G2, 15-keto-prostaglandin E2, calcidiol, thromboxane A2, 5'-methylthioadenosine, L-methionine and S-adenosylmethionine levels changed significantly compared to the control group. Differences in the metabolisms of glycerophospholipid, tyrosine, phenylalanine, arachidonic acid, cysteine and methionine, and biosynthesis of phenylalanine, tyrosine, and tryptophan, and aminoacyl-tRNA have been successfully demonstrated by metabolic pathway analysis. According to this study, vitamin D, D-glutamine, and L-arginine supplements can be recommended to prevent side effects such as fatigue, intraoperative floppy iris syndrome, blurred vision, and dizziness in the treatment of silodosin. Silodosin treatment negatively affected the immune system by affecting the kynurenine and tryptophan metabolism pathways. Conclusions. - The study is a guide for silodosin treatments that offer low side effects and high therapeutic effect within the scope of precision medicine. (c) 2024 Academie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Objective: The goal of the present work was to investigate the antioxidant properties of the extracts of Hippophae rhamnoides L. and to determine their effects on liver toxicity in rats. Material and Method: Metal chelation, reducing power and DPPH radical scavenging methods were used in the antioxidant activity analysis of extracts. The total phenolic content was determined using the folin-ciocalteu reagent. Plant extracts were administered orally to the rats at doses of 500 µg/kg for 2 days. Each animal group was composed of six female Albino Wistar rats with an average weight of 250 g. Microscopic examination was carried out to observe any pathological changes in the rat livers. Result and Discussion: Water extract showed the highest radical scavenging activity (48.65%), reducing power (0.291 absorbance at 700 nm) and metal chelating (35.40%) at 1 mg/ml concentration. Histopathological studies showed that especially water extract reduced the severity of CCl4-induced intoxication. Hippophae rhamnoides L. extracts were found to have antioxidant activity, and also Hippophae rhamnoides L. water extract was shown to be particularly effective in preventing liver damage.

In the present study, the electroanalytical behavior of 17β-estradiol was investigated using cyclic voltammetry. The procedure was based on 17β-estradiol being electrochemically oxidized at a platinum electrode in non-aqueous solutions. At 1.47 V, the oxidation peak was noted. It was discovered that 17β-estradiol's oxidation was diffusion-controlled. Additionally, a quick and easy square wave voltammetry method was developed and validated in this work to determine 17β-estradiol in pharmaceutical preparations. The calibration curve was linear at 5 and 30 µg/mL concentrations. The precision was given by relative standard deviation and was less than 3.36%. Accuracy was given with relative error and did not exceed 2.54%. In pharmaceutical preparations, 17β-estradiol had an average recovery of 100.3%. Under the chosen experimental conditions, no interference was found. The suggested method is highly accurate and precise. Therefore, the method applies to measuring 17β-estradiol in pharmaceutical formulations.

This study's goal was to determine the amounts of lead in schoolchildren's deciduous teeth from Turkey's Erzurum, Tuncbilek, Yatagan, and Didim. 50 girls and 54 boys aged 7 to 11 had their 104 deciduous teeth collected. Atomic absorption spectrometry was used to measure the lead amounts. Limits for detection and quantification have also been estimated, along with the method's linearity, precision, and accuracy. A linear response was seen for lead concentrations ranging from 10 to 1000 ng/mL. Repeatability of the method gave Relative Standard Deviation (RSD) of ≤ 3.87 %. Tuncbilek and Yatagan are suburban areas that have thermo electrical centrals. The mean levels of lead in Tuncbilek and Yatagan were found as 12.44 ± 4.53 μg/g and 8.48 ± 3.53 μg/g, respectively. Erzurum is an urban area by heavy traffic and air pollution and the mean level of lead in this area was found as 7.49 ± 2.71 μg/g. Didim is a suburban area. The mean level of lead was found as 9.49 ± 3.54 μg/g.

It was aimed to develop and validate the UV spectroscopic, the first-order derivative spectroscopy, and the HPLC method for determination of cefuroxime axetil in bulk and tablets and also in spiked human plasma samples by UV spectroscopy method. In the spectroscopic analyses, the maximum absorbance of cefuroxime axetil in acetonitrile was obtained at 277 nm wavelength in the spectra. In first-order derivative spectroscopy method, two peaks were observed in spectra, a maximum at 258 nm and a minimum at 298 nm. 298 nm wavelength was used in the study. In HPLC-UV study, parameters were chosen as follows: C18 column, 0.1% acetic acid-acetonitrile (30:70; v/v) for mobile phase, 1.0 mL/min of flow rate, 280 nm of wavelength, 10 μL of injection volume and etodolac (2.5 μg/mL) as internal standard. Accuracy, precision, recovery, linearity and sensitivity parameters were determined for each of the three methods. Developed and validated methods were successfully applied on 4 tablets which are named as Cefaks, Cefurol, Aksef ve Enfexia. As a result, it is claimed that proposed method is sensitive, precise, accurate, and successfully used in quality control studies in the drug industry.

The determination of progesterone in pure and capsule form was accomplished in this work using new, simple and quick procedures by UV spectrophotometry, first-order derivative spectrophotometry and gas chromatography. To increase the sensitivity of the suggested methods, it was necessary to optimize the solvent system, the detection wavelength, and the chromatographic conditions. The linear regression equations for the UV spectrophotometry, first-order derivative spectrophotometry and gas chromatography were y=0.0536x+0.0002, y=0.1362x+0.0014, and y=1.8217x-1.239, respectively, as determined by the least square regression approach. Under the chosen experimental conditions, no interference was found. The suggested methods are extremely accurate and precise. When the suggested methods' findings were compared to those of two published reference methods, there was statistically no discernible difference. Therefore, the methods are applicable to the measurement of progesterone in pharmaceutical formulations.

Background. - The understanding of precision medicine, which aims for high efficacy and low toxicity in treatments, has gained more importance with omics technologies. In this study, it was aimed to reach new suggestions for low-toxicity treatment by clarifying the relationship between tamsulosin side effects and metabolome profiles. Materials and methods. - Plasma samples of control and tamsulosin-treated rats were ana-lyzed by LC-Q-TOF/MS/MS. MS/MS data was processed in XCMS software for the identification of metabolite and metabolic pathway analysis. Data were classified with MATLAB 2019b for multivariate data analysis. 34m/z values were found to be significantly different between the drug and control groups (P < 0.01 and fold analysis >= 1.5) and identified by comparing METLIN and HMDB databases. Results. - According to multivariate data analysis, ce-Linolenic Acid, Thiamine, Retinoic acid, 1.25-Dihydroxyvitamin D3-26.23-Lactone, L-Glutamine, L-Serine, Retinaldehyde, Sphingosine 1-phosphate, L-Lysine, 23S.25-Dihydroxyvitamin D3, Sphinganine, L-Cysteine, Uridine 5'-diphosphate, Calcidiol, L-Tryptophan, L-Alanine levels changed significantly compared to the control group. Differences in the metabolisms of Retinol, Sphingolipid, Alanine-Aspartate-Glutamate, Glutathione, Fatty Acid, Tryptophan, and biosynthesis of Aminoacyl-tRNA, and Unsaturated Fatty Acid have been successfully demonstrated by metabolic pathway analysis. According to our study, vitamin A and D supplements can be recommended to prevent side effects such as asthenia, rhinitis, nasal congestion, dizziness and IFIS in the treatment of tam-sulosin. Alteration of aminoacyl-tRNA biosynthesis and sphingolipid metabolism pathways during tamsulosin treatment is effective in the occurrence of nasal congestion. Conclusions. - Our study provides important information for tamsulosin therapy with high effi-cacy and low side effects in precision medicine. (c) 2022 Academie Nationale de Pharmacie. Published by Elsevier Masson SAS. All rights reserved.