Expression of LIM kinase 1 is associated with reversible G1/S phase arrest, chromosomal instability and prostate cancer

<p>Abstract</p> <p>Background</p> <p>LIM kinase 1 (LIMK1), a LIM domain containing serine/threonine kinase, modulates actin dynamics through inactivation of the actin depolymerizing protein cofilin. Recent studies have indicated an important role of LIMK1 in growth and invasion of prostate and breast cancer cells; however, the molecular mechanism whereby LIMK1 induces tumor progression is unknown. In this study, we investigated the effects of ectopic expression of LIMK1 on cellular morphology, cell cycle progression and expression profile of LIMK1 in prostate tumors.</p> <p>Results</p> <p>Ectopic expression of LIMK1 in benign prostatic hyperplasia cells (BPH), which naturally express low levels of LIMK1, resulted in appearance of abnormal mitotic spindles, multiple centrosomes and smaller chromosomal masses. Furthermore, a transient G1/S phase arrest and delayed G2/M progression was observed in BPH cells expressing LIMK1. When treated with chemotherapeutic agent Taxol, no metaphase arrest was noted in these cells. We have also noted increased nuclear staining of LIMK1 in tumors with higher Gleason Scores and incidence of metastasis.</p> <p>Conclusion</p> <p>Our results show that increased expression of LIMK1 results in chromosomal abnormalities, aberrant cell cycle progression and alteration of normal cellular response to microtubule stabilizing agent Taxol; and that LIMK1 expression may be associated with cancerous phenotype of the prostate.</p

Automatic data decomposition for message--passing machines

Abstract. The data distribution problem is very complex, because it involves trade-off decisions between minimizing communication and max-imizing parallelism. A common approach towards solving this problem is to break the data mapping into two stages: an alignment stage and a distribution stage. The alignment stage attempts to increase parallelism, while the distribution stage attempts to decrease communication over-head. As opposed to previous approaches, we consider the alignment and distribution problems in a unified framework, and attempt to simultane-ously maximize parallelism and minimize communication overhead. The problem becomes harder if dynamic remapping, multi-dimensional distri-butions, array replications and control flow are taken into account. This paper formulates the full data decomposition problem that addresses all these issues and presents a simple new algorithm to find the optimal solution of the dynamic data distribution problem, given the number of processors and a partitioning of the input program into phases. The al-gorithm runs efficiently for small search spaces (several hundreds of data distributions).