Different spectrophotometric methods manipulating ratio spectra for the assay of hydrocortisone acetate and clioquinol in their topical preparation

Simple and precise spectrophotometric methods for quantitative assay of a mixture of hydrocortisone acetate (HCA) and clioquinol (CL) were developed and validated through different mathematical manipulation pathways. The developed methods utilized ratio spectra for resolving binary mixtures including absorbance subtraction, ratio subtraction coupled with spectrum subtraction, constant multiplication, constant value, and derivative ratio. The proposed methods were proved to be specific by analysing the laboratory-prepared mixtures and were applied for the assay of topical preparation successfully. The methods were validated using ICH guidelines where accuracy, repeatability and intermediate precision were within the acceptable limits. The linearity range was found to be 2-22 for HCA and 1.5-7 µg/mL for CL in all proposed methods and 2-7 µg/mL for HCA and CL in absorbance subtraction method through using a unified regression equation. The findings were statistically evaluated with respect to the official and reported methods, demonstrating that there was no significant difference.

Phenomenological assessment of proton mechanical properties from deeply virtual Compton scattering

A unique feature of generalised parton distributions is their relation to the QCD energy–momentum tensor. In particular, they provide access to the mechanical properties of the proton i.e. the distributions of pressure and shear stress induced by its quark and gluon structure. In principle the pressure distribution can be experimentally determined in a model-independent way from a dispersive analysis of deeply virtual Compton scattering data through the measurement of the subtraction constant. In practice the kinematic coverage and accuracy of existing experimental data make this endeavour a challenge. Elaborating on recent global fits of deeply virtual Compton scattering measurements using artificial neural networks, our analysis presents the current knowledge on this subtraction constant and assesses the impact of the most frequent systematic assumptions made in this field of research. This study will pave the way for future works when more precise data will become available, e.g. obtained in the foreseen electron-ion colliders EIC and EIcC.