We quantify the effect of spatial autocorrelation on the effective sample size for various search methods, to reveal potential type I statistical error, for a sample of 557 plots of the Norwegian National Forest Inventory located in the Hedmark Country. Our results show that spatial autocorrelation mostly appears when competitors are selected within short search radii (3-4) m of the subject tree. However, when simultaneously accounting for the impact of spatial autocorrelation on the effective sample size between individual tree
growth at breast height and competition, the effect appears to be neglect-able. This result is verified by testing if the change in the effective check details degrees of freedom in the Spearman rank correlation t-test for the Clifford et al. correction and a spatial bootstrap method, relative to the classical t-test effective degrees of freedom, are correlated with different measures of stand structure. This ratio showed no systematic variation across measures of plot micro and macro-scale 4EGI-1 cost variation like Loreys mean height, the Gini-coefficient of tree basal area or volume per hectare. The conclusion seems indifferent to plot edge bias correction. A linear mixed model with spatial covariance structure confirmed that sample overlap does not cause serious spatial dependence. Moreover, a median based statistical
test revealed a significant smoothing effect, with increasing search radii of competitors, which causes loss of variation. However, the smoothing does not decrease the ability of the competition indices to correlate with individual tree growth at breast height within search radii of 12 m, and thus it does not represent any problem for prediction. (C) 2013 Elsevier B.V. All rights reserved.”
“Purpose: To investigate the association between genetic polymorphisms of growth factor-related genes and prognosis in patients with advanced esophageal squamous cell carcinoma (ESCC). Patients and Methods: A total of 334 ESCC patients with advanced tumor stages (stages IIB, III and IV) were enrolled
in the study. The genotypes of 14 candidate single nucleotide polymorphisms (SNPs) involved in growth factor-related functions were analyzed using iPLEX Gold technology from the genomic DNA of peripheral leukocytes, and were correlated with the clinical outcome of patients. Serum levels of growth factors were Dorsomorphin inhibitor examined by enzyme-linked immunosorbent assay (ELISA). Results: The genetic polymorphisms of EGF:rs4444903, EGF:rs2237051 and VEGF:rs2010963 showed significant associations with overall survival (OS) of advanced ESCC patients (A/A+ A/G vs. GG, [HR = 0.77, 95% CI = 0.60-0.99, P = 0.039 for rs4444903; A/G+ G/G vs. A/A, [HR = 0.74, 95% CI = 0.58-0.95, P = 0.019 for rs2237051; G/G+ G/C vs. C/C, [HR] inves = 0.69, 95% CI = 0.50-0.95, P = 0.023 for rs2010963). EGFR:rs2227983 and 3 SNPs of PIK3CA also showed borderline significant correlation with OS of advanced ESCC patients (P = 0.058 for rs2227983; P = 0.069, 0.091 and 0.