Constraining neutron-star matter with microscopic and macroscopic collisions.

Interpreting high-energy, astrophysical phenomena, such as supernova explosions or neutron-star collisions, requires a robust understanding of matter at supranuclear densities. However, our knowledge about dense matter explored in the cores of neutron stars remains limited. Fortunately, dense matter is not probed only in astrophysical observations, but also in terrestrial heavy-ion collision experiments. Here we use Bayesian inference to combine data from astrophysical multi-messenger observations of neutron stars1-9 and from heavy-ion collisions of gold nuclei at relativistic energies10,11 with microscopic nuclear theory calculations12-17 to improve our understanding of dense matter. We find that the inclusion of heavy-ion collision data indicates an increase in the pressure in dense matter relative to previous analyses, shifting neutron-star radii towards larger values, consistent with recent observations by the Neutron Star Interior Composition Explorer mission5-8,18. Our findings show that constraints from heavy-ion collision experiments show a remarkable consistency with multi-messenger observations and provide complementary information on nuclear matter at intermediate densities. This work combines nuclear theory, nuclear experiment and astrophysical observations, and shows how joint analyses can shed light on the properties of neutron-rich supranuclear matter over the density range probed in neutron stars.

Quantifying methionine sulfoxide in therapeutic protein formulation excipients as sensitive oxidation marker.

Methionine is a common excipient used in therapeutic protein liquid formulations as stabilizer and antioxidant. The oxidation of methionine to methionine sulfoxide can be regarded as a sensitive marker of oxidative stress for drug product storage conditions. In this study, a sensitive HPLC method for the quantification of methionine sulfoxide in formulated protein product was developed and qualified according to regulatory requirements using a SIELC® Primesep 100 column with UV detection. The separation involves a mixed-mode mechanism including reversed phase and cationic exchange modalities. The operating range of the method was established between 1 µM and 35 µM of methionine sulfoxide. In this testing range, the method was shown to be linear (R2 > 0.99), accurate (Recovery 92.9 - 103.6%, average recovery = 99.8 ± 1.4%) and precise (intermediate precision at LoQ, CV = 2.9%). The developed test system was successfully applied to study the effects of temperature and storage conditions on methionine sulfoxide formation in complex therapeutic antibody formulations.

Comprehensive Multidimensional Liquid Chromatography-Mass Spectrometry for the Characterization of Charge Variants of a Bispecific Antibody.

Identification and further characterization of antibody charge variants is a crucial step during biopharmaceutical drug development, particularly with regard to the increasing complexity of novel antibody formats. As a standard analytical approach, manual offline fractionation of charge variants by cation-exchange chromatography followed by comprehensive analytical testing is applied. These conventional workflows are time-consuming and labor-intensive and overall reach their limits in terms of chromatographic separation of enhanced structural heterogeneities raised from new antibody formats. For these reasons, we aimed to develop an alternative online characterization strategy for charge variant characterization of a therapeutic bispecific antibody by online mD-LC-MS at middle-up (2D-LC-MS) and bottom-up (4D-LC-MS) level. Using the implemented online mD-LC-MS approach, all medium- and even low-abundant product variants previously identified by offline fraction experiments and liquid chromatography mass spectrometry could be monitored. The herein reported automated online mD-LC-MS methodology therefore represents a complementary and in part alternative approach for analytical method validation including multiattribute monitoring (MAM) strategies by mass spectrometry, offering various benefits including increased throughput and reduced sample handling and combined protein information at intact protein and peptide level.