Etilefrine 5mg tablets

A highly ultrasensitive sensor that relied on Cr/ZnO-NPs was developed to detect etilefrine hydrochloride (ETF) in different matrices via a particular green voltammetric technique. The X-ray diffraction pattern showed the nanomaterials of the polycrystalline hexagonal structure. The energy-dispersive X-ray spectrum approved the presence of Cr3+ inside the host zinc oxide framework. The morphological and topological characteristics were visualized using transmission electron microscopy and atomic force microscopy micrographs describing the nanoparticles in spherical-like shape with large-surface area. The energy gap (Eg) was evaluated from transmittance (T %) and reflectance (R %) spectra within the visible region. The optimization study indicated that the Cr/ZnO-NP/CPE sensor has high sensitivity, thanks to the distinctive physical and chemical properties of the fabricated electrode. A new approach showed a great selectivity for determining ETF in different matrices in the presence of other interferents like levodopa. Under optimal circumstances, the square-wave voltammetry revealed a linear response to ETF from 0.01 to 10 μmol L-1 (r = 0.9996) with quantification and detection limits of 9.11 and 2.97 nmol L-1, respectively. Finally, the proposed approach was effectively applied to estimate ETF in pharmaceutical dosage forms and biological fluids using simple, accurate, and selective electrochemical electrode. The greenness profile assessment of the developed method was performed using the Eco-Scale and green analytical procedure index. These tools indicated that the proposed method is an eco-friendly technique for the determination of ETF in different matrices.

Abstract licence: CC BY-NC-ND

ObjectiveParkinson's disease (PD) is a chronic neurodegenerative disorder characterized pathologically by the progressive loss of dopaminergic neurons in the substantia nigra pars compacta, leading to a significant decline in striatal dopamine levels. This study aims to systematically analyze alterations in striatal metabolites across different stages of PD to identify potential biomarkers, elucidate pathological mechanisms, and explore therapeutic targets.MethodsA total of 72 mice were divided into six groups, including one control group and five PD model groups (W1-W5, representing distinct stages based on the duration of 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine/probenecid induction). Striatal tissues were comprehensively collected, and small-molecule metabolites were detected using metabolomics techniques. Potential differential metabolite biomarkers were screened through variable importance in projection values from orthogonal partial least squares-discriminant analysis (OPLS-DA) and coefficient values from LASSO ordinal logistic regression.ResultsThirteen potential differential metabolites were identified, including Ergocalciferol, Glutaric acid, Etilefrine, and Guanine, among others. Pathway enrichment analysis revealed that purine metabolism emerged as the most significantly perturbed pathway. Additionally, receiver operating characteristic curve analysis demonstrated that the biomarker panel composed of these 13 metabolites effectively distinguished different stages of PD.ConclusionThe striatum exhibits distinct metabolic profiles at different stages of PD, with purine metabolism showing the most pronounced alterations. The characteristic metabolites and metabolic pathways identified in this study contribute to elucidating the pathophysiological features of PD and may guide precision therapy.

Abstract licence: CC BY-NC-ND