2 resultados para composite multiscale entropy
em Massachusetts Institute of Technology
Resumo:
We present a general framework for discriminative estimation based on the maximum entropy principle and its extensions. All calculations involve distributions over structures and/or parameters rather than specific settings and reduce to relative entropy projections. This holds even when the data is not separable within the chosen parametric class, in the context of anomaly detection rather than classification, or when the labels in the training set are uncertain or incomplete. Support vector machines are naturally subsumed under this class and we provide several extensions. We are also able to estimate exactly and efficiently discriminative distributions over tree structures of class-conditional models within this framework. Preliminary experimental results are indicative of the potential in these techniques.
Resumo:
Bone morphogenetic protein-2 (BMP-2) has the ability to induce osteoblast differentiation of undifferentiated cells, resulting in the healing of skeletal defects when delivered with a suitable carrier. We have applied a versatile delivery platform comprising a novel composite of two biomaterials with proven track records – apatite and poly(lactic-co-glycolic acid) (PLGA) – to the delivery of BMP-2. Sustained release of this growth factor was tuned with variables that affect polymer degradation and/or apatite dissolution, such as polymer molecular weight, polymer composition, apatite loading, and apatite particle size. The effect of released BMP-2 on C3H10T1/2 murine pluripotent mesenchymal cells was assessed by tracking the expression of osteoblastic makers, alkaline phosphatase (ALP) and osteocalcin. Release media collected over 100 days induced elevated ALP activity in C3H10T1/2 cells. The expression of osteocalcin was also upregulated significantly. These results demonstrated the potential of apatite-PLGA composite particles for releasing protein in bioactive form over extended periods of time.
