Doubly stochastic Poisson distribution of platelet adhesion on material surfaces and its implication on fluorescence image analysis.

An image based assay has been developed to quantify platelet adhesion on material surfaces. Briefly, citrated platelet rich plasma (PRP) is incubated with materials for 2 h to allow platelet adhesion on the surface, followed by fluorescence labeling of platelets with Celltracker Green. Multiple images are acquired by an automatic fluorescence microscope, IN Cell Analyzer 1000. Platelets are identified and counted by an automatic image analysis algorithm. We have observed that the variance of the counts is considerably greater than expected from simple distribution laws. Statistical analysis of that difference shows that these measurements will often follow a doubly stochastic Poisson process in which the variance is inherently very large. To overcome this, multiple images (n > or = 8 images/well, about 3% of total area) are necessary to achieve accurate counting. This method has been compared to the commonly used enzyme based platelet adhesion assay, lactate dehydrogenase (LDH) assay. It is concluded that the present method is only effective in quantifying adherent platelets when a large number of samples are used. However, this method does provide additional information on platelet morphology and spatial distribution, which is lacking in the LDH assay.

Development of combinatorial chemistry methods for coatings: high-throughput weathering evaluation and scale-up of combinatorial leads.

Combinatorial screening of materials formulations followed by the scale-up of combinatorial leads has been applied for the development of high-performance coating materials for automotive applications. We replaced labor-intensive coating formulation, testing, and measurement with a "combinatorial factory" that includes robotic formulation of coatings, their deposition as 48 coatings on a 9x12-cm plastic substrate, accelerated performance testing, and automated spectroscopic and image analysis of resulting performance. This high-throughput (HT) performance testing and measurement of the resulting properties provided a powerful set of tools for the 10-fold accelerated discovery of these coating materials. Performance of coatings is evaluated with respect to their weathering, because this parameter is one of the primary considerations in end-use automotive applications. Our HT screening strategy provides previously unavailable capabilities of (1) high speed and reproducibility of testing by using robotic automation and (2) improved quantification by using optical spectroscopic analysis of discoloration of coating-substrate structure and automatic imaging of the integrity loss of coatings. Upon testing, the coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Using our HT methodology, we have developed several cost-competitive coatings leads that match the performance of more costly coatings. These HT screening results for the best coating compositions have been validated on the traditional scales of coating formulation and weathering testing. These validation results have confirmed the improved weathering performance of combinatorially developed coatings over conventional coatings on the traditional scale.

Efficient discovery of nonlinear dependencies in a combinatorial catalyst data set.

Exploration of a complex catalyst system using Genetic Algorithm methods and combinatorial experimentation efficiently removes noncontributing elements and generates data that can be used to model the remaining system. In particular the combined methods effectively navigate and optimize systems with highly nonlinear dependencies (3-way and higher interactions).

Development of combinatorial chemistry methods for coatings: high-throughput adhesion evaluation and scale-up of combinatorial leads.

Coupling of combinatorial chemistry methods with high-throughput (HT) performance testing and measurements of resulting properties has provided a powerful set of tools for the 10-fold accelerated discovery of new high-performance coating materials for automotive applications. Our approach replaces labor-intensive steps with automated systems for evaluation of adhesion of 8 x 6 arrays of coating elements that are discretely deposited on a single 9 x 12 cm plastic substrate. Performance of coatings is evaluated with respect to their resistance to adhesion loss, because this parameter is one of the primary considerations in end-use automotive applications. Our HT adhesion evaluation provides previously unavailable capabilities of high speed and reproducibility of testing by using a robotic automation, an expanded range of types of tested coatings by using the coating tagging strategy, and an improved quantitation by using high signal-to-noise automatic imaging. Upon testing, the coatings undergo changes that are impossible to quantitatively predict using existing knowledge. Using our HT methodology, we have developed several coatings leads. These HT screening results for the best coating compositions have been validated on the traditional scales of coating formulation and adhesion loss testing. These validation results have confirmed the superb performance of combinatorially developed coatings over conventional coatings on the traditional scale.