Self-assemblies of bioactively natural compounds into supramolecular hydrogels without structural modifications are of interest to improve their sustained releases and bioavailabilities in vivo. However, it is still a formidable challenge to dig out such a naturally small molecule with a meticulous structure which can be self-assembled to form a hydrogel for biomedical applications. Here, a new hydrogel consisting only of gallic acid (GA) via 𝝅-𝝅 stacking and hydrogen bond interactions, whereas none of GA analogues can form the similar supramolecular hydrogels, is reported. This interesting phenomenon is intriguing to further investigate the potential applications of GA hydrogels in wound healing. Notably, this GA hydrogel has rod-like structures with lengths varying from 10 to 100 μm. The biocompatibility and antibacterial tests prove that this well-assembled GA hydrogel has no cytotoxicity and excellent antibacterial activities against Escherichia coli and Staphylococcus aureus. Moreover, the GA hydrogel can significantly accelerate the process of wound healing with or without bacterial infections by mediation of inflammation signaling pathways. It is believed that the current study may shed a new light on the design of a supramolecular hydrogel based on self-assemblies of naturally small molecules to improve their bioavailabilities and diversify their uses in biomedical applications.

The maintenance of a timely, reliable and accurate spatial database on current forest ecosystem conditions and changes is essential to characterize and assess forest resources and support sustainable forest management. Information for such a database can be obtained only through a continuous forest inventory. The National Forest Continuous Inventory (NFCI) is the first level of China's three-tiered inventory system. The NFCI is administered by the State Forestry Administration; data are acquired by five inventory institutions around the country. Several important components of the database include land type, forest classification and ageclass/ age-group. The NFCI database in China is constructed based on 5-year inventory periods, resulting in some of the data not being timely when reports are issued. To address this problem, a forest growth simulation model has been developed to update the database for years between the periodic inventories. In order to aid in forest plan design and management, a three-dimensional virtual reality system of forest landscapes for selected units in the database (compartment or sub-compartment) has also been developed based on Virtual Reality Modeling Language. In addition, a transparent internet publishing system for a spatial database based on open source WebGIS (UMN Map Server) has been designed and utilized to enhance public understanding and encourage free participation of interested parties in the development, implementation, and planning of sustainable forest management.

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Monitoring the dynamics of forest biomass at various spatial scales is important for better understanding the terrestrial carbon cycle as well as improving the effectiveness of forest policies and forest management activities. In this article, field data and Landsat image data acquired in 1999 and 2007 were utilized to quantify spatiotemporal changes of forest biomass for Dongsheng Forestry Farm in Changbai Mountain region of northeastern China. We found that Landsat TM band 4 and Difference Vegetation Index with a 3 × 3 window size were the best predictors associated with forest biomass estimations in the study area. The inverse regression model with Landsat TM band 4 predictor was found to be the best model. The total forest biomass in the study area decreased slightly from 2.77 × 10(6) Mg in 1999 to 2.73 × 10(6) Mg in 2007, which agreed closely with field-based model estimates. The area of forested land increased from 17.9 × 10(3) ha in 1999 to 18.1 × 10(3) ha in 2007. The stabilization of forest biomass and the slight increase of forested land occurred in the period following implementations of national forest policies in China in 1999. The pattern of changes in both forest biomass and biomass density was altered due to different management regimes adopted in light of those policies. This study reveals the usefulness of the remote sensing-based approach for detecting and monitoring quantitative changes in forest biomass at a landscape scale.

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