No abstract

A Hb level of 7 g/dL is the transfusion threshold which is being adopted by many hospitals. Institutional culture change to a Hb level of 7 g/dL can be implemented with the right champion when endorsed by upper echelon medical leadership and hospital administration.

In this work, we investigate image registration by mapping one image to another in a variational framework and focus on both model robustness and solver efficiency. We first propose a new variational model with a special regularizer, based on the quasi-conformal theory, which can guarantee that the registration map is diffeomorphic. It is well known that when the deformation is large, many variational models including the popular diffusion model cannot ensure diffeomorphism. One common observation is that the fidelity error appears small while the obtained transform is incorrect by way of mesh folding. However, direct reformulation from the Beltrami framework does not lead to effective models; our new regularizer is constructed based on this framework and added to the diffusion model to get a new model, which can achieve diffeomorphism. However, the idea is applicable to a wide class of models. We then propose an iterative method to solve the resulting nonlinear optimization problem and prove the convergence of the method. Numerical experiments can demonstrate that the new model can not only get a diffeomorphic registration even when the deformation is large, but also possess the accuracy in comparing with the currently best models.

Overexpression of glucosylceramide synthase (GCS) increases multidrug resistance (MDR) in many cancer cells. However, its mechanism is unknown. The aim of the present study is to detect the association of methylation at the GCS gene promoter with its expression and MDR in invasive ductal breast cancer. 40 cases GCS-positive and 40 cases GCS-negative primary breast carcinoma samples, three drug-sensitive breast cancer cell lines and one multidrug-resistant breast cancer cell line were used. Immunohistochemistry, methylation-specific PCR (MSP), quantitative real-time (qPCR), westernblot and cytotoxicity assay techniques were employed. Thwe results revealed that there was a statistically negative correlation between GCS CpG islands methylation and GCS phenotype in patients with breast cancer. GCS CpG islands methylation was negatively associated with high ER, meanwhile positively with high HER-2 status. Similar results were obtained from the analysis of breast cancer cell lines. Treatment with the demethylating agent 5-aza-2′-deoxycytidine (5-Aza-dc) changed the GCS promoter methylation pattern in three sensitive cells and also caused increased drug resistance of them. These results suggested that the changes of DNA methylation status of the GCS promoter correlates with multidrug resistance in breast cancer.