|Antibacterial Activity of Silver Nanoparticles Obtained by Electrochemical Synthesis in Poly(Amide-Hydroxyurethane) Media|
Melnig Viorel, Stefan Marius, Hritcu Lucian, Mihasan Marius, Gostin Irina, Pricop Daniela
Due to the outbreak of the infectious diseases caused by pathogenic bacteria, inorganic nanoparticles (NPs) have emerged up as novel antimicrobial agents.
|Nanoliter Volume Pin Tool Transfers as Measured by a Dual-Dye Absorbance Method|
Duong T. Chau; Patrick H. Cleveland, Ph.D. (V & P Scientific); John Thomas Bradshaw, Ph.D. (ARTEL)
This poster compares the volumes of sample solutions delivered by an array of stainless steel and hydrophobic-coated pins as measured by a fluorescent-dye approach versus a dual-dye absorbance approach.
|Ion Chromatography ICP-Q-MS for the Detection of Arsenic Species in Apple Juice|
Daniel Kutscher, Shona McSheehy-Ducos, Julian Wills and Detlef Jensen
Interest in the determination of Arsenic species in fruit juices has been triggered by recent media reports in the United States claiming that some apple juices may contain high amounts of Arsenic. Inorganic forms of Arsenic (As3+ and As5+) are highly toxic, whereas the organic forms (e.g. arsenobetaine) are not considered toxic. A robust IC-ICP-MS system was developed and shown to be a highly selective and sensitive technique for determination of trace element species.
|High Content Analysis of Neural Stem Cell Expansion and Differentiation|
Oksana Sirenko, Allan C. Powe, Steven L. Stice, Karen Cook, Nick Callamaras, Jayne Hesley, Xin Jiang and Evan F. Cromwell
Automated assay methods for monitoring neural stem cell expansion and differentiation using stem cell derived neural cell lines and high content imaging systems have been described.
|Modeling Disposition of Sotalol following Intravenous and Oral Administration in Healthy Adult Subjects|
S. Ray Chaudhuri, V. Lukacova and W. S. Woltosz
Sotalol is a non specific adrenergic beta-antagonist that is used in the treatment of life-threatening arrhythmia. Its absorption, distribution and systemic PK or, collectively, ‘disposition’ was modeled and simulated using GastroPlus™ v7.0. Biopharmaceutical properties were obtained from in silico predictions and in vitro measurements.
|Predicting hERG Potassium Channel Affinity with Artificial Neural Network Ensembles|
Adam C. Lee, GrazynaFraczkiewicz, Robert Fraczkiewicz, Robert D. Clark and Walter S. Woltosz
Modeling hERG inhibition has gained significant popularity since 2005, when the FDA recognized the correlation between hERG inhibition and a prolonged QT interval by issuing guidance for the evaluation of new non-antiarrythmic drugs against the hERG channel.Long QT syndrome or LQTS is a risk factor for ventricular tachyarrhythmias and sudden death.
|Predicting Sites of Metabolism with Artificial Neural Network Ensembles|
Marvin Waldman, Robert Fraczkiewicz, JinhuaZhang, Robert D. Clark and Walter S. Woltosz
Hepatic first-pass metabolism of many drugs and pro drugs plays a key role in their oral bioavailability. The human cytochrome P450 enzymes are responsible for the metabolism of most drugs. Knowledge of likely sites of metabolic attack in a drug molecule can aid in designing out unwanted metabolic liabilities early on in the drug discovery process, as well as in the design of pro drugs where metabolic transformation is desired.
|Hot Start Amplification using OligoBeads via Gradual Release of Bound Primers|
Dr. Nam Ngo, Dr. Laurent Jacquinod
OligoBeads provide a mean to store normalized primers used in performing enzymatic reactions including PCR. Primer bound beads eliminate the potential for pipeting errors and reduce contamination thus yielding lower repeat rates and less reagent wastage. The primers bound to the OligoBeads can be stored over a period of a few months without degradation in a nuclease free environment.
|Novel colorimetric detection method for the cost-effective identification of influenza on a low-density microarray|
The presented work explores the use of ampliPHOX, a rapid, cost-effective, field-amenable colorimetric detection method, combined with the FluChip low-density microarray for screening and surveillance of influenza viruses, particularly in resource-limited settings. Analysis of microarray data from over 100 influenza samples confirmed the ability to easily distinguish influenza A and B and produce unique array patterns for a wide variety of influenza A subtypes.