Using this device to isolate breast cancer cells from spiked blood samples, we achieved an enrichment factor of 1500×, and a high processing throughput of 9.6 mL/min with 90% capture yield and more than 50% capture purity at cell concentration 102 cells/mL.
For AD samples we achieved 100% positive agreement and for NDC samples a 92% negative agreement (Fig. 3d).
For ∼10 markers and ∼10 samples, we achieve ∼10 20 min, in contrast with ∼400 h, i.e. ∼17 days for a single CPU.
By designing the antimonide-to-arsenide interfaces in sample II, we achieved exact lattice matching of the active region to the substrate.
By using our classifier that was derived from large, integrated microarray sample datasets, we achieved high accuracy, sensitivity, and specificity in the classification of an independent test dataset.
With the sample size we achieved (over 280 per group), we would have had 80% power to detect a difference of 9% six month tobacco product use quitting, assuming a base rate of quitting of 11%.
We continued sampling until we achieved saturation in the codes and themes identified during data analysis.
Here we describe miRNA profiles for 13 HB tumour samples, which we achieved by using a combination of three platforms for miRNA detection.
Despite this modification, we were unable to meet targeted sample size in Nampula/Nacala; nevertheless, we achieved sample stability on all key variables.
To demonstrate the performance of our Glass software system at identifying " difficult" samples, we also imaged and evaluated HIV RDTs activated with highly diluted positive control samples, such that we achieved dilutions of 2-, 3-, 4-, 5-, and 6-fold by adding phosphate buffer solution (PBS) to the manufacturer-provided reagent solution used for activating the HIV RDTs.
