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520A robust numerical algorithm to computationally predict the ability of drug molecules to cross the blood-brain barrier (BBB) is of relevance to basic neuroscience and to the pharmacology of drug design. [1][2][3][4] A molecule can cross the BBB by either active transport or passive diffusion; 4 passive diffusion remains the most important method for the greatest structural diversity of drug molecules. The two most widely recognized principal physical properties that influence passive diffusion across the BBB (with subsequent entry into the brain) are molecular size and lipophilicity. [4][5][6][7] Although equations that quantitatively relate trans-BBB diffusion to these two properties have been proposed, [8][9][10] these models use only one predictor to encode each of the factors of size and lipophilicity.This study endeavours to develop a rigorous theoretical ABSTRACT: Background: Predicting the ability of drugs to enter the brain is a longstanding problem in neuropharmacology. The first step in creating a much-needed computational algorithm for predicting whether a drug will enter brain is to devise a rigorous mathematical model. Methods: Employing two experimental measures of blood-brain barrier (BBB) penetrability (brain/plasma ratio and the brainuptake index) and 14 theoretically derived biophysical predictors, a mathematical model was developed to quantitatively correlate molecular structure with ability to traverse the BBB. Results: This mathematical model employs Stein's hydrogen bonding number and Randic's topological descriptors to correlate structure with ability to cross the BBB. The final model accurately predicts the ability of test molecules to cross the BBB. Conclusions: A mathematical method to predict blood-brain barrier penetrability of drug molecules has been successfully devised. As a result of bioinformatics, chemoinformatics and other informatics-based technologies, the number of small molecules being developed as potential therapeutics is increasing exponentially. A biophysically rigorous method to predict BBB penetrability will be a much-needed tool for the evaluation of these molecules.RÉSUMÉ: Un modèle mathématique pour prédire la diffusion de molécules à travers la barrière hémato-encéphalique. Introduction : En neuropharmacologie, il est difficile de prédire quels médicaments pourront pénétrer dans le cerveau. La première étape dans la création d'un algorithme pour prédire si un médicament pénétrera dans le cerveau est d'élaborer un modèle mathématique rigoureux. Méthodes : Un modèle mathématique a été développé en utilisant deux mesures expérimentales de la perméabilité de la barrière hémato-encéphalique (BHE) [le ratio cerveau/plasma (RCP) et l'indice de captation du cerveau (ICC)] et 14 prédicteurs biophysiques théoriques, afin de corréler quantitativement la structure moléculaire d'une substance et sa capacité à pénétrer la BHE. Ce modèle mathématique utilise le nombre de liaisons hydrogène de Stein et les indices topologiques de Randic pour corréler la structure de la molécul...
520A robust numerical algorithm to computationally predict the ability of drug molecules to cross the blood-brain barrier (BBB) is of relevance to basic neuroscience and to the pharmacology of drug design. [1][2][3][4] A molecule can cross the BBB by either active transport or passive diffusion; 4 passive diffusion remains the most important method for the greatest structural diversity of drug molecules. The two most widely recognized principal physical properties that influence passive diffusion across the BBB (with subsequent entry into the brain) are molecular size and lipophilicity. [4][5][6][7] Although equations that quantitatively relate trans-BBB diffusion to these two properties have been proposed, [8][9][10] these models use only one predictor to encode each of the factors of size and lipophilicity.This study endeavours to develop a rigorous theoretical ABSTRACT: Background: Predicting the ability of drugs to enter the brain is a longstanding problem in neuropharmacology. The first step in creating a much-needed computational algorithm for predicting whether a drug will enter brain is to devise a rigorous mathematical model. Methods: Employing two experimental measures of blood-brain barrier (BBB) penetrability (brain/plasma ratio and the brainuptake index) and 14 theoretically derived biophysical predictors, a mathematical model was developed to quantitatively correlate molecular structure with ability to traverse the BBB. Results: This mathematical model employs Stein's hydrogen bonding number and Randic's topological descriptors to correlate structure with ability to cross the BBB. The final model accurately predicts the ability of test molecules to cross the BBB. Conclusions: A mathematical method to predict blood-brain barrier penetrability of drug molecules has been successfully devised. As a result of bioinformatics, chemoinformatics and other informatics-based technologies, the number of small molecules being developed as potential therapeutics is increasing exponentially. A biophysically rigorous method to predict BBB penetrability will be a much-needed tool for the evaluation of these molecules.RÉSUMÉ: Un modèle mathématique pour prédire la diffusion de molécules à travers la barrière hémato-encéphalique. Introduction : En neuropharmacologie, il est difficile de prédire quels médicaments pourront pénétrer dans le cerveau. La première étape dans la création d'un algorithme pour prédire si un médicament pénétrera dans le cerveau est d'élaborer un modèle mathématique rigoureux. Méthodes : Un modèle mathématique a été développé en utilisant deux mesures expérimentales de la perméabilité de la barrière hémato-encéphalique (BHE) [le ratio cerveau/plasma (RCP) et l'indice de captation du cerveau (ICC)] et 14 prédicteurs biophysiques théoriques, afin de corréler quantitativement la structure moléculaire d'une substance et sa capacité à pénétrer la BHE. Ce modèle mathématique utilise le nombre de liaisons hydrogène de Stein et les indices topologiques de Randic pour corréler la structure de la molécul...
Local CMRGlc values were determined for 13 regions in each hemisphere from tomographs of patients with Alzheimer's, Huntington's, and Parkinson's diseases who were studied using [18F]fluorodeoxyglucose with positron emission computed tomography. Intercorrelations among the 26 regional measures were calculated for each disease state and for normal controls, and were accepted as reliable at p less than 0.01, uncorrected for the number of comparisons. The number of reliable correlations was found to be decreased in Parkinson's and Huntington's diseases, two primarily subcortical disorders, and increased in Alzheimer's disease, a primarily cortical disorder. The changes suggest that one role of the basal ganglia involves coordinating or pacing the ability of cortical brain regions to function as a unit.
Brain bilirubin concentrations are increased by hyperosmolality and hypercarbia, but the mechanism is not known. The same applies to the mechanism for preferential localization of bilirubin to basal ganglia. Young Sprague-Dawley rats were used. Groups were: control (n = 15), hypercarbia (n = 16, pH approximately 6.95), and hyperosmolality (n = 13, serum osmolality approximately 390 mosm/L). Hyperbilirubinemia was induced by a 5-min infusion of 50 mg/kg bilirubin, containing approximately 20 microCi [3H]bilirubin. Rats were killed at 15-min intervals up to 60 min, and the brains were flushed in situ, dissected into seven regions, weighed, and dissolved. Brain bilirubin was determined by scintillation counting. The half-life of bilirubin in brain was calculated by exponential fitting, which also allowed an estimation of brain bilirubin at the end of the bilirubin bolus. The kinetics of bilirubin clearance from brain were first order. The half-life of bilirubin in brain was significantly prolonged in hyperosmolality (38.2 +/- 28.8 min [mean +/- SD]) compared with control (16.1 +/- 7.7 min) and hypercarbia (12.6 +/- 8.6 min) (F = 12.6, p < 0.0001 after log transformation) results. The estimated acute entry of bilirubin into brain was significantly increased in hypercarbia (13.9 +/- 7.4 nmol/g) compared with control (5.6 +/- 2.1 nmol/g) and hyperosmolality (6.5 +/- 2.1 nmol/g) (F = 19.2, p < 0.0001 after log transformation) results. There were no significant differences between brain regions in acute entry or clearance of bilirubin. The kinetics of increased brain bilirubin differ between hypercarbia (increased acute entry) and hyperosmolality (delayed clearance). Preferential localization of bilirubin to basal ganglia is not produced under, and may not be explained by, the conditions investigated.
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