Molecular Selection, Modification and Development of Therapeutic Oligonucleotide Aptamers.

Monoclonal antibodies are the dominant agents used in inhibition of biological target molecules for disease therapeutics, but there are concerns of immunogenicity, production, cost and stability. Oligonucleotide aptamers have comparable affinity and specificity to targets with monoclonal antibodies whilst they have minimal immunogenicity, high production, low cost and high stability, thus are promising inhibitors to rival antibodies for disease therapy. In this review, we will compare the detailed advantages and disadvantages of antibodies and aptamers in therapeutic applications and summarize recent progress in aptamer selection and modification approaches. We will present therapeutic oligonucleotide aptamers in preclinical studies for skeletal diseases and further discuss oligonucleotide aptamers in different stages of clinical evaluation for various disease therapies including macular degeneration, cancer, inflammation and coagulation to highlight the bright commercial future and potential challenges of therapeutic oligonucleotide aptamers.

A novel, fast, HMM-with-Duration implementation - for application with a new, pattern recognition informed, nanopore detector.

BACKGROUND: Hidden Markov Models (HMMs) provide an excellent means for structure identification and feature extraction on stochastic sequential data. An HMM-with-Duration (HMMwD) is an HMM that can also exactly model the hidden-label length (recurrence) distributions - while the regular HMM will impose a best-fit geometric distribution in its modeling/representation. RESULTS: A Novel, Fast, HMM-with-Duration (HMMwD) Implementation is presented, and experimental results are shown that demonstrate its performance on two-state synthetic data designed to model Nanopore Detector Data. The HMMwD experimental results are compared to (i) the ideal model and to (ii) the conventional HMM. Its accuracy is clearly an improvement over the standard HMM, and matches that of the ideal solution in many cases where the standard HMM does not. Computationally, the new HMMwD has all the speed advantages of the conventional (simpler) HMM implementation. In preliminary work shown here, HMM feature extraction is then used to establish the first pattern recognition-informed (PRI) sampling control of a Nanopore Detector Device (on a "live" data-stream). CONCLUSION: The improved accuracy of the new HMMwD implementation, at the same order of computational cost as the standard HMM, is an important augmentation for applications in gene structure identification and channel current analysis, especially PRI sampling control, for example, where speed is essential. The PRI experiment was designed to inherit the high accuracy of the well characterized and distinctive blockades of the DNA hairpin molecules used as controls (or blockade "test-probes"). For this test set, the accuracy inherited is 99.9%.