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Moso bamboo extensively distributes in southeast and south Asia, and plays an important role in global carbon budget. However, its spatial distribution and heterogeneity are poorly understood. This research uses geostatistics theory to examine the spatial heterogeneity of aboveground biomass (AGB) of moso bamboo, and uses a point kriging interpolation method to estimate and map its spatial distribution. Results showed that (1) spatial heterogeneity and spatial pattern of moso bamboo's AGB can be revealed by an exponential semivariance model. The analysis of the model structure indicating that the AGB spatial heterogeneity is mainly composed of spatial autocorrelation components, and spatial autocorrelation range is from 360 to 41,220 m; (2) kriging standard deviation map showing the level of the model errors indicates that the AGB spatial distribution by point kriging interpolation method is reliable; (3) the average AGB of moso bamboo in Anji County is 44.228 Mg hm -2 , and carbon density is 20.297 Mg C hm -2 . The total AGB of moso bamboo accounts for 16.97% of the total forest-stand biomass in Zhejiang province. The total carbon storage of moso bamboo in China is 68.3993 Tg C, accounting for 1.6286% of the total forest carbon storage. This implies the important contribution of moso bamboo in regional or national carbon budget.

T-cell recognition of somatic mutation-derived cancer neoepitopes can lead to tumor regression. Due to the difficulty to identify effective neoepitopes, constructing a database for sharing experimentally validated cancer neoantigens will be beneficial to precise cancer immunotherapy. Meanwhile, the routine neoepitope prediction in silico is important but laborious for clinical use. Here we present NEPdb, a database that contains more than 17,000 validated human immunogenic neoantigens and ineffective neoepitopes within human leukocyte antigens (HLAs) via curating published literature with our semi-automatic pipeline. Furthermore, NEPdb also provides pan-cancer level predicted HLA-I neoepitopes derived from 16,745 shared cancer somatic mutations, using state-of-the-art predictors. With a well-designed search engine and visualization modes, this database would enhance the efficiency of neoantigen-based cancer studies and treatments. NEPdb is freely available at http://nep.whu.edu.cn/.