PubMed · 51414
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1975-09-27. Beta-blockade withdrawal.. https://pubmed.ncbi.nlm.nih.gov/51414/
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Five potent, lipophilic beta-adrenoceptor antagonists (carvedilol, pindolol, toliprolol and fluorinated analogs of bupranolol and penbutolol) were labeled with either carbon-11 or fluorine-18 and evaluated for cerebral beta-adrenoceptor imaging in experimental animals. The standard radioligand for autoradiography of beta-adrenoceptors, [125I]-iodocyanopindolol, was also included in this survey. All compounds showed either very low uptake in rat brain or a regional distribution that was not related to beta-adrenoceptors, whereas some ligands did display specific binding in heart and lungs. Apparently, the criteria of a high affinity and a moderately high lipophilicity were insufficient to predict the suitability of beta-adrenergic antagonists for visualization of beta-adrenoceptors in the central nervous system.
BACKGROUND: There is concern that care provided in the Veterans Health Administration (VA) may be of poorer quality than non-VA health care. We compared use of medications after acute myocardial infarction in the VA with that in non-VA healthcare settings under fee-for-service (FFS) Medicare financing. METHODS AND RESULTS: We used clinical data from 2486 VA and 29 249 FFS men >65 years old discharged with a confirmed diagnosis of acute myocardial infarction from 81 VA hospitals and 1530 non-VA hospitals. We reported odds ratios (ORs) for use of thrombolytics, beta-blockers, ACE inhibitors, or aspirin among ideal candidates adjusted for age, sample design (hospital academic affiliation, availability of cardiac procedures, and volume), and within-hospital clustering. Ideal VA candidates were more likely to undergo thrombolytic therapy at arrival (OR [VA relative to Medicare] 1.40 [1.05, 1.74]) or to receive ACE inhibitors (OR 1.67 [1.12, 2.45]) or aspirin (OR 2.32 [1.81, 3.01]) at discharge and equally likely to receive beta-blockers (OR 1.09 [1.03, 1.40]) at discharge. CONCLUSIONS: Ideal candidates in VA were at least as likely as those in FFS to receive medical therapies of known benefit for acute myocardial infarction.
Models to predict binding affinities to human serum albumin (HSA) should be very useful in the pharmaceutical industry to speed up the design of new compounds, especially as far as pharmacokinetics is concerned. We have experimentally determined through high-performance affinity chromatography the binding affinities to HSA of 95 diverse drugs and druglike compounds. These data have allowed us the derivation of quantitative structure-activity relationship models to predict binding affinities to HSA of new compounds on the basis of their structure. Simple linear, one-variable models have been derived for specific families of compounds (r(2) > or = 0.80; q(2) > or = 0.62): beta-adrenergic antagonists, steroids, COX inhibitors, and tricyclic antidepressants. Also, global models have been derived to be applicable to the whole medicinal chemical space by using the full database of HSA binding constants described above. For this aim, a genetic algorithm has been used to exhaustively search and select for multivariate and nonlinear equations, starting from a large pool of molecular descriptors. The resulting models display good fits to the experimental data (r(2) > or = 0.78; LOF < or = 0.12). In addition, both internal (cross validation and randomization) and external validation tests have demonstrated that these models have good predictive power (q(2) > or = 0.73; PRESS/SSY < or = 0.23; r(2) > or = 0.82 for the external set). Statistical analysis of the equation populations indicates that hydrophobicity (as measured by the ClogP) is the most important variable determining the binding extent to HSA. In addition, structural factors (especially the topological (6)chi(ring) index and some Jurs descriptors) also frequently appear as descriptors in the best equations. Therefore, binding to HSA turns out to be determined by a combination of hydrophobic forces together with some modulating shape factors. This agrees with X-ray structures of HSA alone or bound to ligands, where the binding pockets of both sites I and II are composed mainly of hydrophobic residues.