Adsorption kinetics of β-lactoglobulin on a polyclonal immunochromatographic support

β-Lactoglobulin is one of the main components of whey proteins. Among other reasons, its allergenicity makes its determination in hypoallergenic foods and bio-pharmaceutical products necessary. Immunoaffinity chromatography is a widely accepted technique for purification and analysis of proteins. Knowledge of the apparent kinetics of the adsorption of b-lactoglobulin onto the anti-b-lactoglobulin immunochromatographic column is important to optimize the analytical process. High-performance frontal affinity chromatography was used to study the apparent kinetics of the adsorption process. Langmuir and bi-Langmuir kinetic models, assuming one and two kinds of binding sites, respectively, were used to characterize the adsorption kinetics of b-lactoglobulin B on a polyclonal immunoadsorbent. Very good fits were obtained with the bi-Langmuir model for two different concentrations of b-lactoglobulin and this allowed us to calculate the apparent adsorption rate constants and the column capacities for both kinds of sites. Experimental results indicate the possibility that the adsorption process is not irreversible. The values of the apparent dissociation rate constants leading to the best fit were estimated and the affinity constants were calculated. Ó 2002 Elsevier Science B.V. All rights reserved.A.P. acknowledges the Spanish Ministry of Sci-ence and Technology for a predoctoral grant. This work has been supported by CICYT (project AGL2000-1480). Collaboration between our labora-tories has been possible thanks to French–Spanish Cooperation between CNRS and CSIC (project 7954, 2000).Peer reviewe

Frontal analysis for characterizing the adsorption-desorption behavior of beta-lactoglobulin on immunoadsorbents

High-performance frontal affinity chromatography was employed to study the adsorption–desorption kinetics characterizing the retention of Beta-lactoglobulin (Beta-LG) onto polyclonal anti-Beta-lactoglobulin (anti-Beta-LG) chromatographic supports. The adsorption and desorption processes were studied by analyzing two different elution fronts separated by a relatively long rinsing step. The method consists in performing two successive frontal injections of the protein. In between, the column was rinsed with a given volume of mobile phase (buffer alone). During this rinsing stage, a partial desorption may occur and a novel amount of protein could be adsorbed in the second frontal injection step. The whole process (first adsorption, possible desorption, and second adsorption) was simulated by a numerical procedure, in which the column was divided into a large number of slices. A model based on bi-Langmuir type kinetics was used to describe the adsorption of the protein on the support. The model assumes a non-uniform adsorbent with two types of binding sites. At equilibrium the adsorption isotherm is of the bi-Langmuir type. A global adsorption effect was considered which includes the effective binding process and the mass transfer resistances due to the transport to the binding site. Therefore, the column capacity and the kinetic parameters of the model (apparent adsorption and desorption rate constants) were determined from the best fit of the first and second adsorption fronts to the experimental ones. The other parameters of the model are the saturation capacities for the adsorption on each type of sites. The equilibrium affinity constants were estimated in a single experiment from the ratio of the apparent adsorption and desorption rate constants. The high values found (around 108 M−1) reveal a strong interaction of -LG with the immunoadsorbent. Kinetic measurements were carried out at different flow rates. Both the apparent adsorption and desorption kinetics were faster at larger flow rates, indicating an important contribution of the mass transfer resistance in the stagnant fluid at the particle boundary. However, as expected, close values were found for the resulting equilibrium constants calculated from the ratio of the apparent adsorption and desorption rate constant determined at various flow rates.A.P. acknowledges Spanish Ministry of Science and Tech- nology for a predoctoral grant. This work has been supported by Spanish CICYT (Project TIC2003-01906) and Foundation Ramon Areces. Collaboration between laboratories has been possible thanks to French-Spanish Cooperation between CNRS and CSIC.Peer reviewe

Multicentre analysis of intensity of care at the end-of-life in patients with advanced cancer, combining health administrative data with hospital records: variations in practice call for routine quality evaluation

Abstract Background Accessible indicators of aggressiveness of care at the end-of-life are useful to monitor implementation of early integrated palliative care practice. To determine the intensity of end-of-life care from exhaustive data combining administrative databases and hospital clinical records, to evaluate its variability across hospital facilities and associations with timely introduction of palliative care (PC). Methods For this study designed as a decedent series nested in multicentre cohort of advanced cancer patients, we selected 997 decedents from a cohort of patients hospitalised in 2009–2010, with a diagnosis of metastatic cancer in 3 academic medical centres and 2 comprehensive cancer centres in the Paris area. Hospital data was combined with nationwide mortality databases. Complete data were collected and checked from clinical records, including first referral to PC, chemotherapy within 14 days of death, ≥1 intensive care unit (ICU) admission, ≥2 emergency department visits (ED), and ≥ 2 hospitalizations, all within 30 days of death. Results Overall (min-max) indicator values as reported by facility providing care rather than the place of death, were: 16% (8–25%) patients received chemotherapy within 14 days of death, 16% (6–32%) had ≥2 admissions to acute care, 6% (0–15%) had ≥2 emergency visits and 18% (4–35%) had ≥1 intensive care unit admission(s). Only 53% of these patients met the PC team, and the median (min-max) time between the first intervention of the PC team and death was 41 (17–112) days. The introduction of PC > 30 days before death was independently associated with lower intensity of care. Conclusions Aggressiveness of end-of-life cancer care is highly variable across centres. This validates the use of indicators to monitor integrated PC in oncology. Disseminating a quality audit-feedback cycle should contribute to a shared view of appropriate end-of-life care objectives, and foster action for improvement among care providers

Aide à la décision de transfert ou non transfert en réanimation d’un patient atteint de cancer

Référentiel inter régional en soins oncologiques de support, AFSOS et Réseau Espace Santé - Cancer Rhône-Alpes (RRCRA), 201