Intermediate Megavoltage Photon Beams for Improved Lung Cancer Treatments

The goal of this study is to evaluate the effects of intermediate megavoltage (3-MV) photon beams on SBRT lung cancer treatments. To start with, a 3-MV virtual beam was commissioned on a commercial treatment planning system based on Monte Carlo simulations. Three optimized plans (6-MV, 3-MV and dual energy of 3- and 6-MV) were generated for 31 lung cancer patients with identical beam configuration and optimization constraints for each patient. Dosimetric metrics were evaluated and compared among the three plans. Overall, planned dose conformity was comparable among three plans for all 31 patients. For 21 thin patients with average short effective path length (< 10 cm), the 3-MV plans showed better target coverage and homogeneity with dose spillage index R_50% = 4.68±0.83 and homogeneity index = 1.26±0.06, as compared to 4.95±1.01 and 1.31±0.08 in the 6-MV plans (p < 0.001). Correspondingly, the average/maximum reductions of lung volumes receiving 20 Gy (V_20Gy), 5 Gy (V_5Gy), and mean lung dose (MLD) were 7%/20%, 9%/30% and 5%/10%, respectively in the 3-MV plans (p < 0.05). The doses to 5% volumes of the cord, esophagus, trachea and heart were reduced by 9.0%, 10.6%, 11.4% and 7.4%, respectively (p < 0.05). For 10 thick patients, dual energy plans can bring dosimetric benefits with comparable target coverage, integral dose and reduced dose to the critical structures, as compared to the 6-MV plans. In conclusion, our study indicated that 3-MV photon beams have potential dosimetric benefits in treating lung tumors in terms of improved tumor coverage and reduced doses to the adjacent critical structures, in comparison to 6-MV photon beams. Intermediate megavoltage photon beams (< 6-MV) may be considered and added into current treatment approaches to reduce the adjacent normal tissue doses while maintaining sufficient tumor dose coverage in lung cancer radiotherapy.     

Physical Constraint Finite Element Model for Medical Image Registration

Due to being derived from linear assumption, most elastic body based non-rigid image registration algorithms are facing challenges for soft tissues with complex nonlinear behavior and with large deformations. To take into account the geometric nonlinearity of soft tissues, we propose a registration algorithm on the basis of Newtonian differential equation. The material behavior of soft tissues is modeled as St. Venant-Kirchhoff elasticity, and the nonlinearity of the continuum represents the quadratic term of the deformation gradient under the Green- St.Venant strain. In our algorithm, the elastic force is formulated as the derivative of the deformation energy with respect to the nodal displacement vectors of the finite element; the external force is determined by the registration similarity gradient flow which drives the floating image deforming to the equilibrium condition. We compared our approach to three other models: 1) the conventional linear elastic finite element model (FEM); 2) the dynamic elastic FEM; 3) the robust block matching (RBM) method. The registration accuracy was measured using three similarities: MSD (Mean Square Difference), NC (Normalized Correlation) and NMI (Normalized Mutual Information), and was also measured using the mean and max distance between the ground seeds and corresponding ones after registration. We validated our method on 60 image pairs including 30 medical image pairs with artificial deformation and 30 clinical image pairs for both the chest chemotherapy treatment in different periods and brain MRI normalization. Our method achieved a distance error of 0.320±0.138 mm in x direction and 0.326±0.111 mm in y direction, MSD of 41.96±13.74, NC of 0.9958±0.0019, NMI of 1.2962±0.0114 for images with large artificial deformations; and average NC of 0.9622±0.008 and NMI of 1.2764±0.0089 for the real clinical cases. Student’s t-test demonstrated that our model statistically outperformed the other methods in comparison (p-values <0.05).     

基于长时间序列landsat数据的科尔沁沙地土地利用演变分析

以科尔沁沙地沙丘-草甸过渡带区域主要土地覆被类型为研究对象，以1987-2017年多时相Landsat TM/OLI遥感影像解译分类为基础，参考生态学植被演替研究方法，系统分析研究区30年来的土地利用/覆被动态演变规律，研究结果表明：（1）决策树法在复杂下垫面不同覆被类型的同步识别效果较好，所有影像分类精度均达到88%以上，分类效果较好，其中2017年分类精度最高为95.24%，达到了分类研究的要求；（2）研究区存在着"半灌丛-草甸地-灌丛"的植被结构特征，且整体表现为"南进北退"的变化趋势。结合土地利用动态度分析结果表明人类活动干涉下，研究区整体上遵循了半干旱区植被条件改善的一般规律，侧面反映该研究区域生态环境的持续不稳定性和脆弱性；（3）研究区覆被类型发生变化的总面积达到2623.59 hm²，总变化强度为63.76%。其中正向演替的比例为52.61%，以半灌丛面积的持续减小与沙地草甸面积的持续扩张为主要变化特征。但同时，半灌丛转为沙地的面积为184.95 hm²，表明以放牧为主的研究区同时发生着局部的逆行演变；（4）质心迁移结果反映了1987-2017年间，除人为影响较大的林地、草地以及耕地向北迁移外，其他植被类型的质心都有很明显的南迁，主要植被类型重心迁移距离依次由大到小为耕地 > 半灌丛 > 灌丛 > 沙地草甸 > 湿地草甸 > 林地。研究通过记录科尔沁沙地连续扩展的时空模式，展示了遥感-生态和时间序列影像在30 m分辨率下跟踪土地利用/覆被变化的潜力，为提高干旱半干旱区土地利用情况的动态监测效率，开展土地利用/覆被动态演变研究提供参考。     

Variation of phenotype,ploidy level,and organogenic potential of in vitro regenerated polyploids of <Emphasis Type="Italic">Pyrus communis</Emphasis>

A wide range of phenotypic variation was observed among neopolyploids obtained from the diploid pear cultivar ‘Fertility’ by in vitro colchicine treatment. The variant plantlets had alterations in leaf characteristics. Neopolyploids had significantly different ratios of leaf length to leaf width compared to the diploid control. Shoot regeneration from leaf explants and rooting ability from in vitro shoots of neopolyploids was examined. Regeneration frequencies of shoots from leaf explants of seven of the nine neopolyploids were significantly decreased compared to the diploid control. The organogenic potential of neopolyploids was highly genotype-dependent for both shoots and roots. Tetraploid clone 4x − 4 failed to regenerate shoots from leaf explants and the pentaploid clone 5x − 2 failed to root from in vitro shoots. The results suggest that polyploidization caused the decrease in or loss of in vitro organogenic potential. Regenerated shoots derived from neopolyploids showed different phenotypes, depending on the ploidy of the donor plant.     

Agnogene Deletion in a Novel Pathogenic JC Virus Isolate Impairs VP1 Expression and Virion Production

Infection of glial cells by the human polyomavirus JC (JCV) causes progressive multifocal leukoencephalopathy (PML). JCV Encephalopathy (JCVE) is a newly identified disease characterized by JCV infection of cortical pyramidal neurons. The virus JCV_CPN associated with JCVE contains a unique 143 base pair deletion in the agnogene. Contrary to most JCV brain isolates, JCV_CPN has an archetype-like regulatory region (RR) usually found in kidney strains. This provided us with the unique opportunity to determine for the first time how each of these regions contributed to the phenotype of JCV_CPN. We characterized the replication of JCV_CPN compared to the prototype virus JCV_Mad-1 in kidney, glial and neuronal cell lines. We found that JCV_CPN is capable of replicating viral DNA in all cell lines tested, but is unable to establish persistent infection seen with JCV_Mad-1. JCV_CPN does not have an increased ability to replicate in the neuronal cell line tested. To determine whether this phenotype results from the archetype-like RR or the agnogene deletion, we generated chimeric viruses between JCV_CPN of JCV_Mad-1. We found that the deletion in the agnogene is the predominant cause of the inability of the virus to maintain a persistent infection, with the introduction of a full length agnogene, either with or without agnoprotein expression, rescues the replication of JCV_CPN. Studying this naturally occurring pathogenic variant of JCV provides a valuable tool for understanding the functions of the agnogene and RR form in JCV replication.     

基于InVEST模型的疏勒河流域碳储量时空变化研究

研究区域土地利用方式与生态系统服务碳储量的关系，对于区域生态系统保护及经济社会可持续发展具有重要意义。利用InVEST模型碳储量模块和CA-Markov模型，探究并预测疏勒河流域1990-2015及2015-2040年流域生态系统碳储量时空变化特征及其与土地利用方式之间的关系。结果表明：疏勒河流域1990、1995、2000、2005、2010、2015年碳储量分别为7.994×10⁸、7.996×10⁸、7.998×10⁸、8.038×10⁸、8.064×10⁸、8.071×10⁸t，呈逐年增加趋势，累计增加7.7×10⁶t。土地利用类型变化是导致生态系统碳储量变化的主要因素，未利用地向耕地和草地转化有利于碳储量增加，而草地向耕地和未利用地的转化则导致碳储量减少。疏勒河流域碳储量存在显著的空间格局，碳储量较高区域呈现"北部点状-中部带状-南部点状片状"特征，这种分布格局与流域土地利用类型紧密联系。预测表明至2040年疏勒河流域碳储量为9.128×10⁸t，较2015年增加13.1%，主要原因是草地、耕地和林地面积较大幅度增长，提高了流域内的碳储量。