A SERINE KINASE REGULATES INTRACELLULAR-LOCALIZATION OF SPLICING FACTORS IN THE CELL CYCLE

Small nuclear ribonucleoprotein particles (snRNPs) and non-snRNP splicing factors containing a serine/arginine-rich domain (SR proteins) concentrate in 'speckles' in the nucleus of interphase cells(1). It is believed that nuclear speckles act as storage sites for splicing factors while splicing occurs on nascent transcripts(2). Splicing factors redistribute in response to transcription inhibition(3,4) or viral infection(5), and nuclear speckles break down and reform as cells progress through mitosis(6). We have now identified and cloned a kinase, SRPK1, which is regulated by the cell cycle and is specific for SR proteins; this kinase is related to a Caenorhabditis elegans kinase and to the fission yeast kinase Dsk1 (ref. 7). SRPK1 specifically induces the disassembly of nuclear speckles, and a high level of SRPK1 inhibits splicing in vitro. Our results indicate that SRPK1 mag have a central role in the regulatory network for splicing, controlling the intranuclear distribution of splicing factors in interphase cells, and the reorganization of nuclear speckles during mitosis.

Wear resistance of reaction sintered alumina/mullite composites

Alumina and alumina/mullite composites with mullite content of 0.96-8.72 vol.% were subjected to an abrasive wear test under loads of 0.1-2.0 N with a ball-on-disc apparatus. The wear rate and area fraction of pullout f(po) on the worn surfaces were measured. The wear resistances of the alumina/mullite composites were better by a factor of 1-2 than that of pure alumina. The main wear mechanism of alumina is fracture wear, and for alumina/mullite composites, fracture wear and plastic wear mechanisms work together. The influence of mechanical properties on wear resistance was estimated by Evans' method. It was found that the wear rate depends on f(po), and the primary reason for the better wear resistance of alumina/mullite composites is the reduction off, induced by fracture mode transition. (c) 2007 Elsevier B.V. All rights reserved.

An Automatic Classification Method of Metabolic Cycle Based on Biomimetic Pattern Recognition

Correct classification of different metabolic cycle stages to identification cell cycle is significant in both human development and clinical diagnostics. However, it has no perfect method has been reached in classification of metabolic cycle yet. This paper exploringly puts forward an automatic classification method of metabolic cycle based on Biomimetic pattern recognition (BPR). As to the three phases of yeast metabolic cycle, the correct classification rate reaches 90%, 100% and 100% respectively.