Prediction models and the extrapolation effects for water content of surface dead fuels in the typical stand of the Great Xing'an Mountains of China by one-hour time step.

The water content of surface dead fuels is one of the most important indicators for forecasting fire danger and fire behaviors. We employed the timelag equilibrium water content methods (i.e. Nelson and Simard models) and the meteorological variable regression method to continuously measure the water content of surface dead fuels by one-hour time step from September to October in 2010 under Populus davidiana + Betula platyphylla, Picea koraiensis and the cutover lands (Pinus sylvestris var. mongolica + Betula platyphylla) with different canopy densities in Pangu Forestry Bureau, the Great Xing'an Mountains, Heilongjiang Province, China. We established prediction models and obtained prediction errors. The models were also used to extrapolate the water contents of surface dead fuels under other forest stands and the extrapolation accuracy was analyzed. The results showed that the mean absolute error, the mean relative error and the mean square error root of Nelson model (0.0154, 0.104 and 0.0226) were lower than those of Simard model (0.0185, 0.117 and 0.0256). In terms of extrapolation effects, the mean absolute error, the mean relative error and the mean square error root of meteorological variable regression method (0.0410, 0.0300 and 0.0740) were lower than those of Simard model (0.610, 0.492 and 0.846), but they were higher than those of Nelson model (0.034, 0.021 and 0.0660). Such results indicated that the timelag equilibrium moisture content method by one-hour time step, especially Nelson model, was sui-table for the forest stands in the Great Xing'an Mountains. Although extrapolation could not reduce the prediction errors, it could help improve the prediction accuracy and the efficiency of the present models applied to different forest stands or in a larger scale. The modeling and extrapolation errors were closely related to species identity and canopy densities, thus the appropriate timelag equilibrium moisture content methods should be selected according to different forest stands and locations.

Pharmacokinetic Profiling of Butylidenephthalide and Alisol B in Danggui-Shaoyao-San in Rats.

BACKGROUND AND OBJECTIVE: Danggui-Shaoyao-San (DSS), a famous Chinese formula, has been widely used to treat gynecological disorders since ancient times and has recently showed efficacy in treating Alzheimer's disease. Butylidenephthalide (BDPH) and alisol B (ALI) are recognized as the primary active ingredients of DSS. The objectives of the present study were to evaluate the pharmacokinetic comparative study of BDPH and ALI in herbal extracts and their purified forms. METHOD: A sensitive and specific high-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) methodology was developed to determine the concentration level of BDPH and ALI in rat plasma. This approach enables a real-time pharmacokinetics profiling of BDPH and ALI in DSS extracts as well as their purified forms in rats after oral administration. RESULTS: The validated method showed an evident linearity over a wide range of dosages (r > 0.99) with sensitivity down to 1.0 ng/mL for each analyte. The extraction recovery of the analyte ranged from 80.8 to 99.1%. The pharmacokinetic parameters were significantly different in herbal extracts and their purified forms. The results showed that the absorption of both BDPH and ALI from DSS extracts was significantly greater compared with their purified forms. CONCLUSIONS: A highly specific, sensitive and rapid HPLC-MS/MS method was developed and applied for the determination of BDPH and ALI in rat plasma. It was found that BDPH and ALI had higher bioavailability in the DSS extract compared with their purified forms.

Determination of a novel B-Raf(V600E) and EGFR dual inhibitor in rat plasma by HPLC-MS/MS and its application in a pharmacokinetic study.

The EGFR and B-Raf(V600E) dual inhibition is a promising strategy in treatment of colorectal cancer patients with B-Raf(V600E) mutation. Previously, compound 3 was designed and synthesized as a novel B-Raf(V600E) and EGFR dual inhibitor with highly potency in both kinase and cell based assay. Herein, a sensitive and rapid HPLC-MS/MS quantitative method was developed and validated for the further pharmacokinetic evaluation of compound 3 in rats.

Fractal scaling of particle size distribution and relationships with topsoil properties affected by biological soil crusts.

BACKGROUND: Biological soil crusts are common components of desert ecosystem; they cover ground surface and interact with topsoil that contribute to desertification control and degraded land restoration in arid and semiarid regions. METHODOLOGY/PRINCIPAL FINDINGS: To distinguish the changes in topsoil affected by biological soil crusts, we compared topsoil properties across three types of successional biological soil crusts (algae, lichens, and mosses crust), as well as the referenced sandland in the Mu Us Desert, Northern China. Relationships between fractal dimensions of soil particle size distribution and selected soil properties were discussed as well. The results indicated that biological soil crusts had significant positive effects on soil physical structure (P<0.05); and soil organic carbon and nutrients showed an upward trend across the successional stages of biological soil crusts. Fractal dimensions ranged from 2.1477 to 2.3032, and significantly linear correlated with selected soil properties (R(2) = 0.494∼0.955, P<0.01). CONCLUSIONS/SIGNIFICANCE: Biological soil crusts cause an important increase in soil fertility, and are beneficial to sand fixation, although the process is rather slow. Fractal dimension proves to be a sensitive and useful index for quantifying changes in soil properties that additionally implies desertification. This study will be essential to provide a firm basis for future policy-making on optimal solutions regarding desertification control and assessment, as well as degraded ecosystem restoration in arid and semiarid regions.