Learn More
Sparsity or parsimony of statistical models is crucial for their proper interpretations, as in sciences and social sciences. Model selection is a commonly used method to find such models, but usually involves a computationally heavy combinatorial search. Lasso (Tibshirani, 1996) is now being used as a computationally feasible alternative to model selection.(More)
Extracting useful information from high-dimensional data is an important focus of today’s statistical research and practice. Penalized loss function minimization has been shown to be effective for this task both theoretically and empirically. With the virtues of both regularization and sparsity, the L1-penalized squared error minimization method Lasso has(More)
Recently much attention has been devoted to model selection through regularization methods in regression and classification where features are selected by use of a penalty function (e.g. Lasso in Tibshirani, 1996). While the resulting sparsity leads to more interpretable models, one may want to further incorporate natural groupings or hierarchical(More)
Many patients with traumatic spinal cord injury (SCI) report pain that persists indefinitely and is resistant to available therapeutic approaches. We recently showed that microglia become activated after experimental SCI and dynamically maintain hyperresponsiveness of spinal cord nociceptive neurons and pain-related behaviors. Mechanisms of signaling(More)
Spinal cord injury (SCI) results in the generation and amplification of pain caused in part by injury-induced changes in neuronal excitability at multiple levels along the sensory neuraxis. We have previously shown that activated microglia, through an ERK (extracellular signal-regulated kinase)-regulated PGE(2) (prostaglandin E(2)) signaling mechanism,(More)
Developed for multimedia and game applications, as well as other numerically intensive workloads, the CELL processor provides support both for highly parallel codes, which have high computation and memory requirements, and for scalar codes, which require fast response time and a full-featured programming environment. This first generation CELL processor(More)
the concept of separate memories by allocating SPE program data in system memory and having the compiler automatically manage the movement of this data between its home location and a temporary location in the local store. A naı̈ve compiler inserts an explicit DMA transfer for each access to shared memory, which is likely to debilitate performance. Our(More)
MicroRNAs (miRNAs) are small noncoding RNA molecules that regulate protein expression by cleaving or repressing the translation of target mRNAs. In mammal animals, their function mainly represses the target mRNAs transcripts via imperfectly complementary to the 3' UTR of target mRNAs. Several miRNAs have been recently reported to be involved in modulation(More)
CONTEXT In response to a meal, glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic peptide (GIP) are released and modulate glycemic control. Normally these incretins are rapidly degraded by dipeptidyl peptidase-4 (DPP-4). DPP-4 inhibitors are a novel class of oral antihyperglycemic agents in development for the treatment of type 2 diabetes.(More)
Transplantation of mesenchymal stem cells (MSCs) derived from bone marrow has been shown to improve functional outcome in spinal cord injury (SCI). We transplanted MSCs derived from human bone marrow (hMSCs) to study their potential therapeutic effect in SCI in the rat. In addition to hMSCs, we used gene-modified hMSCs to secrete brain-derived neurotrophic(More)