Short-term and long-term effectiveness of acupuncture and Tuina on knee osteoarthritis: study protocol for a randomized controlled trial.

Background: The effectiveness of acupuncture and tuina in treating knee osteoarthritis (KOA) is still controversial, which limits their clinical application in practice. This study aims to evaluate the short-term and long-term effectiveness of acupuncture and tuina on KOA.

Methods/design: This parallel-group, multicenter randomized clinical trial (RCT) will be conducted at the outpatient clinic of five traditional Chinese medicine hospitals in China.

VSMP: a novel variable selection and modeling method based on the prediction.

The use of numerous descriptors that are indicative of molecular structure and topology is becoming more common in quantitative structure-activity relationship (QSAR). How to choose the adequate descriptors for QSAR studies is important but difficult because there are no absolute rules to govern this choice. A variety of variable selection techniques including stepwise, partial least squares/principal component analysis (PLS/PCA), neural network, and evolutionary algorithm such as genetic algorithm have been applied to this common problem.

Combined MEDV-GA-MLR method for QSAR of three panels of steroids, dipeptides, and COX-2 inhibitors.

The MEDV-13, molecular electronegativity distance vector based on 13 atomic types, has at best 91 descriptors. It is impossible to indirectly use multiple linear regression (MLR) to derive a quantitative structure-activity relationship (QSAR) model. Although principal component regression (PCR) or partial least-squares regression (PLSR) can be employed to develop a latent QSAR model, it is still difficult how to determine the principal components (PCs) and depict the physical meaning of the PCs.