ABSTRACT
Metal-Organic Framework (MOF) membranes act as selective layers have offered unprecedented opportunities for energy-efficient and cost-effective gas separation. Searching for the green and sustainable synthesis method of dense MOF membrane has received huge attention in both academia and industry. In this work, we demonstrate an in situ electrochemical potential-induced synthesis strategy to aqueously fabricate Metal Azolate Framework-4 (MAF-4) membranes on polypropylene (PP) support. The constant potential can induce the heterogeneous nucleation and growth of MAF-4, resulting an ultrathin membrane with the thickness of only 390 nm. This high-quality membrane exhibits a high H2/CO2 separation performance with the H2 permeance as high as 1565.75 GPU and selectivity of 11.6. The deployment of this environment friendly one-step fabrication method under mild reaction conditions, such as low-cost polymer substrate, water instead of organic solvent, room temperature and ambient pressure shows great promise for the scale-up of MOF membranes.
ABSTRACT
OBJECTIVES: To develop algorithms of locating patients with primary aldosteronism (PA) using insurance reimbursement data and to validate the algorithms using medical charts. STUDY DESIGN AND SETTING: We extracted National Health Insurance (NHI) reimbursement data and medical charts in seven enrolled hospitals and analyzed diagnosis-related information for 1999-2010. The NHI codes PA as 255.1x, using the International Classification of Diseases, Ninth Revision, Clinical Modification. Confirmation of PA was based on suppression tests. RESULTS: We reviewed medical charts for 1,094 cases with at least one PA diagnosis. PA was confirmed for 563 cases. Compared with patients with essential hypertension, PA patients had higher systolic blood pressure, higher aldosterone, lower renin activity, and lower potassium level (all P-values <0.05). An algorithm based on PA diagnosis reported in at least one hospital stay or three outpatient visits had modest performance (sensitivity = 0.94 and specificity = 0.20). The best additional condition for the algorithm was use of mineralocorticoid receptor antagonist (MRA; sensitivity = 0.89 and specificity = 0.88). CONCLUSION: Using information on PA diagnosis and MRA prescription reported in insurance claims data can precisely locate PA patients in high-risk groups. This algorithm can construct a reliable PA sample for conducting research in various fields, including epidemiology and clinical practice.
