Change in soil organic carbon between 1981 and 2011 in croplands of Heilongjiang Province, northeast China.

BACKGROUND: Soil organic carbon (SOC) is fundamental for mitigating climate change as well as improving soil fertility. Databases of SOC obtained from soil surveys in 1981 and 2011 were used to assess SOC change (0-20 cm) in croplands of Heilongjiang Province in northeast China. Three counties (Lindian, Hailun and Baoqing) were selected as typical croplands representing major soil types and land use types in the region. RESULTS: The changes in SOC density (SOCD) between 1981 and 2001 were -6.6, -14.7 and 5.7 Mg C ha(-1) in Lindian, Hailun and Baoqing Counties respectively. The total SOC storage (SOCS) changes were estimated to be -11.3, -19.1 and 16.5% of those in 1981 in the respective counties. The results showed 22-550% increases in SOCS in rice (Oryza sativa L.) paddies in the three counties, but 28-33% decreases in dry cropland in Lindian and Hailun Counties. In addition, an increase of 11.4 Mg C ha(-1) in SOCD was observed in state-owned farms (P < 0.05), whereas no significant change was observed in family-owned farms. CONCLUSION: Soil C:N ratio and initial SOCD related to soil groups were important determinants of SOCD changes. Land use and residue returning greatly affected SOC changes in the study region. To increase the topsoil SOCD, the results suggest the conversion of dry croplands to rice paddies and returning of crop residue to soils.

The RTEL1 rs6010620 polymorphism and glioma risk: a meta-analysis based on 12 case-control studies.

BACKGROUND: The association between the RTEL1 rs6010620 single nucleotide polymorphism (SNP) and glioma risk has been extensively studied. However, the results remain inconclusive. To further examine this association, we performed a meta-analysis. MATERIALS AND METHODS: A computerized search of the PubMed and Embase databases for publications regarding the RTEL1 rs6010620 polymorphism and glioma cancer risk was performed. Genotype data were analyzed in a meta-analysis. Odds ratios (ORs) with 95% confidence intervals (CIs) were estimated to assess the association. Sensitivity analyses, tests of heterogeneity, cumulative meta-analyses, and assessments of bias were performed in our meta-analysis. RESULTS: Our meta-analysis confirmed that risk with allele A is lower than with allele G for glioma. The A allele of rs6010620 in RTEL1 decreased the risk of developing glioma in the 12 case-control studies for all genetic models: the allele model (OR=0.752, 95%CI: 0.715-0.792), the dominant model (OR=0.729, 95%CI: 0.685-0.776), the recessive model (OR=0.647, 95%CI: 0.569-0.734), the homozygote comparison (OR=0.528, 95%CI: 0.456-0.612), and the heterozygote comparison (OR=0.761, 95%CI: 0.713-0.812). CONCLUSIONS: In all genetic models, the association between the RTEL1 rs6010620 polymorphism and glioma risk was significant. This meta-analysis suggests that the RTEL1 rs6010620 polymorphism may be a risk factor for glioma. Further functional studies evaluating this polymorphism and glioma risk are warranted.

RTEL1 and TERT polymorphisms are associated with astrocytoma risk in the Chinese Han population.

Common variants of multiple genes play a role in glioma onset. However, research related to astrocytoma, the most common primary brain neoplasm, is rare. In this study, we chose 21 tagging SNPs (tSNPs), previously reported to be associated with glioma risk in a Chinese case-control study from Xi'an, China, and identified their contributions to astrocytoma susceptibility. We found an association with astrocytoma susceptibility for two tSNPs (rs6010620 and rs2853676) in two different genes: regulator of telomere elongation helicase 1 (RTEL1) and telomerase reverse transcriptase (TERT), respectively. We confirmed our results using recessive, dominant, and additive models. In the recessive model, we found two tSNPs (rs2297440 and rs6010620) associated with increased astrocytoma risk. In the dominant model, we found that rs2853676 was associated with increased astrocytoma risk. In the additive model, all three tSNPs (rs2297440, rs2853676, and rs6010620) were associated with increased astrocytoma risk. Our results demonstrate, for the first time, the potential roles of RTEL1 and TERT in astrocytoma development.

[Simulation of Larix gmelinii tree volume growth based on random effect].

Based on the stem analysis data of 80 sample trees in dahurian larch (Larix gmelinii) plantations of Daqingchuan Forest Farm, Dailing Forest Bureau in Heilongjiang Province and the Logistic growth model, the NLME procedure of S-PLUS software was adopted to fit the nonlinear tree volume growth models, with consideration of individual tree effect and plot effect, and the evaluation statistics such as AIC, BIC, Log Likelihood, and likelihood ratio test were used to compare the prediction precisions of the models. The results showed that the random effect models with parameters b1, b2, and b3 (representing the random parameters for progressive, scale, and shape in Logistic model, respectively) had the best performance when considering individual tree effect, while the models with parameter b1 had the best performance when considering plot effect. The models considering both individual tree effect and plot effect provided better model fitting than the basic model (Logistic growth model), and the models considering individual tree effect showed more precision, as compared with those considering plot effect. The model validation indicated that random effect models not only showed the mean variation trend of individual tree volume growth, but also showed the differences among the individuals. In addition, the prediction precision of the models could be further improved through the calibration of random parameters.