免疫细胞浸润在非小细胞肺癌诊断与预后中的应用

免疫细胞浸润对癌症的诊断与预后有着重要意义。文中收集TCGA数据库已收录的非小细胞肺癌肿瘤与正常组织基因表达数据,利用CIBERSORT工具得到22种免疫细胞占比来评估免疫细胞浸润情况。以22种免疫细胞占比为特征,用机器学习方法构建了非小细胞肺癌肿瘤与正常组织的分类模型,其中随机森林方法构建的模型分类效果AUC=0.987、敏感性0.98及特异性0.84。并且用随机森林方法构建的肺腺癌和肺鳞癌肿瘤组织分类模型效果AUC=0.827、敏感性0.75及特异性0.77。用LASSO回归筛选22种免疫细胞特征,保留8种强相关特征组成的免疫细胞评分结合临床特征构建了非小细胞肺癌预后模型。经评估及验证,预后模型C-index=0.71并且3年和5年的校准曲线拟合良好,可以对预后风险度进行准确预测。本研究基于免疫细胞浸润所构建的分类模型与预后模型,旨在对非小细胞肺癌的诊断与预后研究提供新的策略。     

Canopy closure estimation in a temperate forest using airborne LiDAR and LANDSAT ETM+ data

Aims　Forest canopy closure is one of the essential factors in forest survey, and plays an important role in forest ecosystem management. It is of great significance to study how to apply LiDAR (light detection and ranging) data efficiently in remote sensing estimation of forest canopy closure. LiDAR can be used to obtain data fast and accurately and therefore be used as training and validation data to estimate forest canopy closure in large spatial scale. It can compensate for the insufficiency (e.g. labor-intensive, time-consuming) of conventional ground survey, and provide foundations to forest inventory.Methods　In this study, we estimated canopy closure of a temperate forest in Genhe forest of Da Hinggan Ling area, Nei Mongol, China, using LiDAR and LANDSAT ETM+ data. Firstly, we calculated the canopy closure from ALS (Airborne Laser Scanning) high density point cloud data. Then, the estimated canopy closure from ALS data was used as training and validation data to modeling and inversion from eight vegetation indices computed from LANDSAT ETM+ data. Three approaches, multi-variable stepwise regression (MSR), random forest (RF) and Cubist, were developed and tested to estimate canopy closure from these vegetation indices, respectively.Important findings The validation results showed that the Cubist model yielded the highest accuracy compared to the other two models (determination coefficient (R²) = 0.722, root mean square error (RMSE) = 0.126, relative root mean square error (rRMSE) = 0.209, estimation accuracy (EA) = 79.883%). The combination of LiDAR data and LANDSAT ETM+ showed great potential to accurately estimate the canopy closure of the temperate forest. However, the model prediction capability needs to be further improved in order to be applied in larger spatial scale. More independent variables from other remotely sensed datasets, e.g. topographic data, texture information from high-resolution imagery, should be added into the model. These variables can help to reduce the influence of optical image, vegetation indices, terrain and shadow and so on. Moreover, the accuracy of the LiDAR-derived canopy closure needs to be further validated in future studies.     

华裔科学家研究新型免疫疗法？有望两年内攻克癌症

据英国《每日电讯报》9月20日报道，美国维克森林大学医学院的崔征博士近日在剑桥大学举行的抗衰老会议上公布了他在免疫细胞研究方面的新发现。即在不同人身上提取的免疫细胞在抗癌方面的能力大不相同，疗效可以相差近50倍。[第一段]     

关于"南亚热带鹤山主要人工林生态系统C、N累积及分配格局的模拟研究"一文中两个问题的讨论

植声:不同系统的C、N分配格局对群落演替的影响应进一步说明。变化的数量如何能够发挥这种作用,应深入一步,如马占相思作为外来种被其它本地阳性种取代的可能,但实际上模拟的结果100年仍然是马占相思本身,这如何解释,希望在讨论中加以说明。申卫军:审者指出了一个非常重要的研究课题:森林生态系统的C、N分配格局变化如何影响生态系统的演替进程。这实质上是生态系统的结构和功能/过程研究如何耦合的问题。本文只考虑了叶,因为冠层是影响透光率的主要生态系统部分,而光因子     

华北地区针叶林下凋落物层化学性质的研究

森林凋落物中贮积了大量的有机、无机养分物质,它是森林土壤自然肥力的重要来源之一。在森林生态系统中,养分物质的内部循环主要是通过凋落物来实现的。在分解、转化过     

气候变化和人类活动对中国北方旱区植被变绿的定量贡献

气候变化和大规模的生态恢复使中国北方旱区植被发生了显著变化，量化气候变化和人类活动对植被动态的相对贡献，对于旱区生态系统管理和应对未来气候变化具有重要意义。目前，中国北方旱区植被变化影响因素的时间动态（2000年大规模生态恢复工程实施前后）和空间异质性（沿干旱梯度）仍需进一步的定量研究。基于多源数据，采用趋势分析、偏相关分析和随机森林模型等方法，分析了1981-2018年中国北方旱区气候和植被的时空变化规律，量化了2000年前后气候变化和人类活动对植被动态的相对贡献并分析其在干旱梯度上的空间差异性。结果表明：（1）1981-2018年期间，中国北方旱区的叶面积指数（LAI）平均增加速率为（0.0037±0.0443） a^-1，且增加速率沿干旱梯度增大。2000年前仅10.46%（P<0.05）的地区显著变绿，而2000年后达到36.84%，且植被变绿主要归因于非树木植被。（2）2000年后降水对植被变绿的正效应在不同干旱梯度均增加，而在半干旱区和亚湿润干旱区，温度对植被变绿由正向促进转为负向抑制，而辐射在干旱区由负效应转向正效应。（3）2000年前后，气候变化均主导着植被的动态，贡献率分别为96.07%和73.72%，人类活动的贡献在2000年后进一步增强（从3.93%增加到26.28%），且沿着干旱梯度而增加，其中人类活动对植被变绿的贡献在半干旱地区增加最显著（+0.0289 m² m^-2 a^-1，P<0.05）。研究结果可为未来气候变化下中国北方旱区的植被恢复和可持续发展提供科学依据。     

Scale-dependent spatial patterns of species diversity in the tropical montane rain forest in Jianfengling,Hainan Island,China

Aims Spatial distribution patterns and formation mechanisms of species diversity are fundamental issues in community ecology. The objectives of this study are to assess the species diversity patterns at the different spatial scales in Jianfengling, Hainan Island, China.
Methods Based on the dataset from the 60 hm² plot in the tropical montane rain forest in Jianfengling, Hainan Island, the spatial distribution patterns of species richness, species abundance, Shannon-Wiener, Simpson and Pielou’s evenness indices were analyzed at six spatial scales, including 5 m × 5 m, 10 m × 10 m, 20 m × 20 m, 40 m × 40 m, 100 m × 100 m, and 200 m × 200 m, respectively.Important findings
Results showed that spatial distribution patterns of species richness, species abundance and Shannon-Wiener index were much more obviously changed with the spatial scales than Simpson and Pielou’s evenness indices. Change of variance of the species richness with the increase of spatial scales was unimodal, which had the maximum value at the 20 m × 20 m scale. Variance of the species abundance showed a linear relationship with the increase of spatial scales. The positive relationship between species richness and abundance gradually decreased and even disappeared with the increase of sampling scales, which may be correlated with the increase of habitat heterogeneity. The effects of spatial scales on Shannon-Wiener, Simpson, and Pielou’s evenness indices may be also correlated with the composition of rare species in the plot.