Increased B Cell ADAM10 in Allergic Patients and Th2 Prone Mice

ADAM10, as the sheddase of the low affinity IgE receptor (CD23), promotes IgE production and thus is a unique target for attenuating allergic disease. Herein, we describe that B cell levels of ADAM10, specifically, are increased in allergic patients and Th2 prone WT mouse strains (Balb/c and A/J). While T cell help augments ADAM10 expression, Balb WT B cells exhibit increased ADAM10 in the naïve state and even more dramatically increased ADAM10 after anti-CD40/IL4 stimulation compared C57 (Th1 prone) WT B cells. Furthermore, ADAM17 and TNF are reduced in allergic patients and Th2 prone mouse strains (Balb/c and A/J) compared to Th1 prone controls. To further understand this regulation, ADAM17 and TNF were studied in C57Bl/6 and Balb/c mice deficient in ADAM10. C57-ADAM10B-/- were more adept at increasing ADAM17 levels and thus TNF cleavage resulting in excess follicular TNF levels and abnormal secondary lymphoid tissue architecture not noted in Balb-ADAM10B-/-. Moreover, the level of B cell ADAM10 as well as Th context is critical for determining IgE production potential. Using a murine house dust mite airway hypersensitivity model, we describe that high B cell ADAM10 level in a Th2 context (Balb/c WT) is optimal for disease induction including bronchoconstriction, goblet cell metaplasia, mucus, inflammatory cellular infiltration, and IgE production. Balb/c mice deficient in B cell ADAM10 have attenuated lung and airway symptoms compared to Balb WT and are actually most similar to C57 WT (Th1 prone). C57-ADAM10B-/- have even further reduced symptomology. Taken together, it is critical to consider both innate B cell levels of ADAM10 and ADAM17 as well as Th context when determining host susceptibility to allergic disease. High B cell ADAM10 and low ADAM17 levels would help diagnostically in predicting Th2 disease susceptibility; and, we provide support for the use ADAM10 inhibitors in treating Th2 disease

Coupling of CFD and semiempirical methods for designing three-phase condensate separator: case study and experimental validation

This study presents an approach to determine the dimensions of three-phase separators. First, we designed different vessel configurations based on the fluid properties of an Iranian gas condensate field. We then used a comprehensive computational fluid dynamic (CFD) method for analyzing the three-phase separation phenomena. For simulation purposes, the combined volume of fluid–discrete particle method (DPM) approach was used. The discrete random walk (DRW) model was used to include the effect of arbitrary particle movement due to variations caused by turbulence. In addition, the comparison of experimental and simulated results was generated using different turbulence models, i.e., standard k–ε, standard k–ω, and Reynolds stress model. The results of numerical calculations in terms of fluid profiles, separation performance and DPM particle behavior were used to choose the optimum vessel configuration. No difference between the dimensions of the optimum vessel and the existing separator was found. Also, simulation data were compared with experimental data pertaining to a similar existing separator. A reasonable agreement between the results of numerical calculation and experimental data was observed. These results showed that the used CFD model is well capable of investigating the performance of a three-phase separator

Quantitative characterization of metabolism and metabolic shifts during growth of the new human cell line AGE1.HN using time resolved metabolic flux analysis

For the improved production of vaccines and therapeutic proteins, a detailed understanding of the metabolic dynamics during batch or fed-batch production is requested. To study the new human cell line AGE1.HN, a flexible metabolic flux analysis method was developed that is considering dynamic changes in growth and metabolism during cultivation. This method comprises analysis of formation of cellular components as well as conversion of major substrates and products, spline fitting of dynamic data and flux estimation using metabolite balancing. During batch cultivation of AGE1.HN three distinct phases were observed, an initial one with consumption of pyruvate and high glycolytic activity, a second characterized by a highly efficient metabolism with very little energy spilling waste production and a third with glutamine limitation and decreasing viability. Main events triggering changes in cellular metabolism were depletion of pyruvate and glutamine. Potential targets for the improvement identified from the analysis are (i) reduction of overflow metabolism in the beginning of cultivation, e.g. accomplished by reduction of pyruvate content in the medium and (ii) prolongation of phase 2 with its highly efficient energy metabolism applying e.g. specific feeding strategies. The method presented allows fast and reliable metabolic flux analysis during the development of producer cells and production processes from microtiter plate to large scale reactors with moderate analytical and computational effort. It seems well suited to guide media optimization and genetic engineering of producing cell lines

Induction of Erythroid Differentiation in Human Erythroleukemia Cells by Depletion of Malic Enzyme 2

Malic enzyme 2 (ME2) is a mitochondrial enzyme that catalyzes the conversion of malate to pyruvate and CO2 and uses NAD as a cofactor. Higher expression of this enzyme correlates with the degree of cell de-differentiation. We found that ME2 is expressed in K562 erythroleukemia cells, in which a number of agents have been found to induce differentiation either along the erythroid or the myeloid lineage. We found that knockdown of ME2 led to diminished proliferation of tumor cells and increased apoptosis in vitro. These findings were accompanied by differentiation of K562 cells along the erythroid lineage, as confirmed by staining for glycophorin A and hemoglobin production. ME2 knockdown also totally abolished growth of K562 cells in nude mice. Increased ROS levels, likely reflecting increased mitochondrial production, and a decreased NADPH/NADP+ ratio were noted but use of a free radical scavenger to decrease inhibition of ROS levels did not reverse the differentiation or apoptotic phenotype, suggesting that ROS production is not causally involved in the resultant phenotype. As might be expected, depletion of ME2 induced an increase in the NAD+/NADH ratio and ATP levels fell significantly. Inhibition of the malate-aspartate shuttle was insufficient to induce K562 differentiation. We also examined several intracellular signaling pathways and expression of transcription factors and intermediate filament proteins whose expression is known to be modulated during erythroid differentiation in K562 cells. We found that silencing of ME2 leads to phospho-ERK1/2 inhibition, phospho-AKT activation, increased GATA-1 expression and diminished vimentin expression. Metabolomic analysis, conducted to gain insight into intermediary metabolic pathways that ME2 knockdown might affect, showed that ME2 depletion resulted in high orotate levels, suggesting potential impairment of pyrimidine metabolism. Collectively our data point to ME2 as a potentially novel metabolic target for leukemia therapy

Concepts for the development of person-centred, digitally-enabled, Artificial Intelligence-assisted ARIA care pathways (ARIA 2024)

The traditional healthcare model is focused on diseases (medicine and natural science) and does not acknowledge patients' resources and abilities to be experts in their own life based on their lived experiences. Improving healthcare safety, quality and coordination, as well as quality of life, are important aims in the care of patients with chronic conditions. Person-centred care needs to ensure that people's values and preferences guide clinical decisions. This paper reviews current knowledge to develop (i) digital care pathways for rhinitis and asthma multimorbidity and (ii) digitally-enabled person-centred care (1). It combines all relevant research evidence, including the so-called real-world evidence, with the ultimate goal to develop digitally-enabled, patient-centred care. The paper includes (i) Allergic Rhinitis and its Impact on Asthma (ARIA), a two-decade journey, (ii) Grading of Recommendations, Assessment, Development and Evaluation (GRADE), the evidence-based model of guidelines in airway diseases, (iii) mHealth impact on airway diseases, (iv) from guidelines to digital care pathways, (v) embedding Planetary Health, (vi) novel classification of rhinitis and asthma, (vi) embedding real-life data with population-based studies, (vii) the ARIA-EAACI strategy for the management of airway diseases using digital biomarkers, (viii) Artificial Intelligence, (ix) the development of digitally-enabled ARIA Person-Centred Care and (x) the political agenda. The ultimate goal is to propose ARIA 2024 guidelines centred around the patient in order to make them more applicable and sustainable