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- Romagnoni, A, et al.
(författare)
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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 10351-
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Tidskriftsartikel (refereegranskat)abstract
- Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers.
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- Ariano, RE, et al.
(författare)
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Pharmacokinetics and pharmacodynamics of meropenern in febrile neutropenic patients with bacteremia
- 2005
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Ingår i: Annals of Pharmacotherapy. - 1060-0280. ; 39:1, s. 32-38
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Tidskriftsartikel (refereegranskat)abstract
- Background: Pharmacodynamic investigations with antimicrobials define the relationship between the infecting organism and achievable drug concentrations with clinical outcome. Objective: To examine this relationship for meropenem in a population of patients who are at high risk of infection-related morbidity and mortality. Methods: The study was a retrospective analysis of a multicenter, randomized, blinded clinical trial. A population-based predictive model was created using data from adults with febrile neutropenia and the nonparametric modeling program, NPEM. Patient age, body weight, and serum creatinine level were covariates in the model used to predict unbound concentrations for each patient. Pathogen susceptibility was estimated using product literature minimum inhibitory concentrations for effectiveness against 50% of microorganisms (MIC50) for specific organisms. The pharmacodynamic index of percent time above MIC (% T>MIC) was analyzed for its association with clinical outcome. Results: A 2-compartment pharmacokinetic model using patient covariates of body weight and renal function best described the pharmacokinetics of meropenem in febrile neutropenic patients. Sixty patients with confirmed gram-positive or -negative bacteremia were studied. An average of 83% T>MIC was identified for the 42 clinical responders compared with 59% T>MIC for the 18 nonresponders (p=0.04). An 80% clinical response rate was evident when the % T>MIC for meropenem exceeded 75% of the dosing interval (p=0.01). Conclusions: To our knowledge, this is the first published report of a relationship between a pharmacodynamic index and clinical outcome in a febrile neutropenic population. Based on this relationship, dosing with intravenous meropenem 500 mg every 6 hours is predicted to be comparable to the currently recommended 1 g every 8 hours for serious infections. Our model provides further justification for a prospective clinical trial to evaluate a pharmacodynamically targeted meropenem dosing schedule as to its ability to improve clinical outcome in these patients.
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- Brioni, JD, et al.
(författare)
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Activation of dopamine D-4 receptors by ABT-724 induces penile erection in rats
- 2004
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : National Academy of Sciences; 1999. - 0027-8424 .- 1091-6490. ; 101:17, s. 6758-6763
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Tidskriftsartikel (refereegranskat)abstract
- Apomorphine, a nonselective dopamine receptor agonist, facilitates penile erection and is effective in patients suffering from erectile dysfunction. The specific dopamine receptor subtype(s) responsible for its erectogenic effect is not known. Here we report that the dopamine D(4) receptor plays a role in the regulation of penile function. ABT-724 is a selective dopamine D(4) receptor agonist that activates human dopamine D(4) receptors with an EC(50) of 12.4 nM and 61% efficacy, with no effect on dopamine D(1), D(2), D(3), or D(5) receptors. ABT-724 dose-dependently facilitates penile erection when given s.c. to conscious rats, an effect that is blocked by haloperidol and clozapine but not by domperidone. A proerectile effect is observed after intracerebroventricular but not intrathecal administration, suggesting a supraspinal site of action. s.c. injections of ABT-724 increase intracavernosal pressure in awake freely moving rats. In the presence of sildenafil, a potentiation of the proerectile effect of ABT-724 is observed in conscious rats. The ability of ABT-724 to facilitate penile erection together with the favorable side-effect profile indicates that ABT-724 could be useful for the treatment of erectile dysfunction.
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