[Plus Tree Selection of Litsea mollis by Principal Component Analysis].

Objective: To establish a principal component analysis( PCA) method for selecting Litsea mollis,to determine the selection criteria, in order to provide a theoretical basis for the early excellenting, selective breeding of Litsea mollis. Methods: The seedling origin of Litsea mollis plantion in Wanzhou district of Chongqing province were used as the research object,72 plus trees were selected by using 5 dominant comparative method. Its growth and economic traits were observed and analyzed by variance analysis and PCA method. Results: The variatice analysis result showed that the traits existed rich genetic differences. The PCA analysis result showed that in rotated component matrix, tree height, crown area, east-west crown, north-south crown, diameter at breast height were used as the selection optimal criteria of Litsea mollis. Four plants with superior integrated economical were selected, which namely Y12-4,Y12,Y11-3and Y10. Conclusion: The rich variability of Litsea mollis provide the prerequisite condition for plus tree selection. The results conform to the phenotypic and indicate that the optimization methods are scientific and feasible.

Relationship between plasma lipoprotein (a), apolipoprotein (a) phenotypes, and other coronary heart disease risk factors in a Melbourne South Asian population.

BACKGROUND: High plasma lipoprotein(a) [Lp(a)] level is a strong and important risk factor for cardiovascular disease (CVD). Small-sized apolipoprotein(a) [apo(a)] isoforms (F, B, S1, and S2) are inversely correlated with the high levels of Lp(a) in plasma and significantly associated with CVD. Although the effects of apo(a) phenotypes and various risk factors on Lp(a) status in South Asian population may have been studied in other countries, there are no reports involving these risk factors in Australia. METHODS AND RESULTS: Factors contributing to variation in Lp(a) were surveyed in 402 (216 males and 186 females) South Asian Melburnians. There was a negative relationship between low alcohol beer per day and Lp(a) in men (P < 0.05). Approximately 21% of the variance of Lp(a) concentration in men and 6% in women were explained by age. Age was positively associated with Lp(a) concentrations in men but negatively in women. The most commonly occurring phenotype was apo(a) S3. In this phenotype, Lp(a) concentrations ranged from non-detectable to 811 mg/l. After adjusting for age, an inverse correlation was observed between Lp(a) concentration and apo(a) phenotypes (P < 0.01). CONCLUSIONS: Although Lp(a) has been reported to be genetically determined, there are clearly other factors contributing to variations in Lp(a) concentrations in a South Asian population.