p73-deficient mice have neurological, pheromonal and inflammatory defects but lack spontaneous tumours

p73 (ref. 1) has high homology with the tumour suppressor p53 (refs 2-4), as well as with p63, a gene implicated in the maintenance of epithelial stem cells. Despite the localization of the p73 gene to chromosome 1p36.3, a region of frequent aberration in a wide range of human cancers, and the ability of p73 to transactivate p53 target genes, it is unclear whether p73 functions as a tumour suppressor. Here we show that mice functionally deficient for all p73 isoforms exhibit profound defects, including hippocampal dysgenesis, hydrocephalus, chronic infections and inflammation, as well as abnormalities in pheromone sensory pathways. In contrast to p53-deficient mice, however, those lacking p73 show no increased susceptibility to spontaneous tumorigenesis. We report the mechanistic basis of the hippocampal dysgenesis and the loss of pheromone responses, and show that new, potentially dominant-negative, p73 variants are the predominant expression products of this gene in developing and adult tissues. Our data suggest that there is a marked divergence in the physiological functions of the p53 family members, and reveal unique roles for p73 in neurogenesis, sensory pathways and homeostatic control.     

A multiple intelligent agent system for credit risk prediction via an optimization of localized generalization error with diversity

Company bankruptcies cost billions of dollars in losses to banks each year. Thus credit risk prediction is a critical part of a bank＇s loan approval decision process. Traditional financial models for credit risk prediction are no longer adequate for describing today＇s complex relationship between the financial health and potential bankruptcy of a company. In this work, a multiple classifier system （embedded in a multiple intelligent agent system） is proposed to predict the financial health of a company. In our model, each individual agent （classifier） makes a prediction on the likelihood of credit risk based on only partial information of the company. Each of the agents is an expert, but has limited knowledge （represented by features） about the company. The decisions of all agents are combined together to form a final credit risk prediction. Experiments show that our model out-performs other existing methods using the benchmarking Compustat American Corporations dataset.     

Field trial of an HTS filter system on a CDMA base station

This paper presents the field trial results of a high temperature superconductor filter system (HTSFS) in a code division multiple access (CDMA) mobile communication base station (BTS) in Tangshan, China. The center frequency of the HTSFS is 830 MHz with 1.4% fractional bandwidth. The noise figure (NF) of the HTSFS, including connectors and cables, is 0.8 dB. The field trial results show that after the HTSFS was installed in the receiver front-end of a CDMA base station, the transmitting power of handset was decreased by 3.1 dB on average. Up to now, the HTSFS has been running steadily in the base station for more than 22 months, demonstrating the reliability and stability of the system.