Potential of helical tomotherapy for sparing critical organs in a patient with AIDS who was treated for Hodgkin lymphoma.
Potential of helical tomotherapy for sparing critical organs in a patient with AIDS who was treated for Hodgkin lymphoma.
复制标题
螺旋断层放疗对于接受霍奇金淋巴瘤治疗的艾滋病患者来说具有保护重要器官的潜力。
DOI：
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发表时间：
2009
影响因子：
11.8
通讯作者：
Y. Kirova
中科院分区：
文献类型：
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作者：
C. Chargari;S. Zefkili;Y. Kirova
致编辑-在最近发表的一篇文章中，Hirsch等人[1]回顾了临床实践中使用的HIV耐药性测定，并描述了一种“虚拟表型”，该表型将候选基因的血浆HIV-1 RNA的基因型数据与配对表型和基因型的大型数据库相关联。虽然作者引用了其他生物信息学系统，产生了计算的倍数变化（FC），我们的评论是特定的病毒型HIV-1。Hirsch et al. [1]指出，虚拟表型耐药解释受到依赖于基于预选密码子而不是整个核苷酸序列的匹配的方法的限制，并且“预测能力取决于可用的匹配数据集的数量”[1，第274页]，对于具有较小数据集的新药具有高变异性。我们要注意的是，在他们的文章中用于计算FC的匹配系统不再是Virco检测所使用的方法。自2006年7月以来，Virco的生物信息学引擎已被用于通过以下方法计算给定样品的FC [2]。首先，定期进行线性回归建模以分析Virco相关数据库中基因型和表型之间的关系，迄今为止，Virco相关数据库具有153，000个具有配对基因型和表型数据的样本。确定影响对每种药物表型敏感性的显著突变和突变对，并通过耐药权重因子量化其对FC的负面或正面影响。第二，将样本基因型中的所有突变在逐个药物的基础上与该药物的耐药权重因子的当前列表进行比较。然后通过计算样品基因型中鉴定的所有抗性权重因子的值的总和来产生FC评分。这种方法与第一代虚拟表型不同，第一代虚拟表型试图鉴定与具有非常相似突变谱的病毒的匹配。使用当前的线性建模引擎，无论数据库中是否存在具有相似突变谱的病毒，都可以报告准确的FC值。
To the Editor—In a recently published article, Hirsch et al. [1] reviewed HIV drug resistance assays used in clinical practice and described a “virtual phenotype” that correlates genotypic data on the plasma HIV-1 RNA of a candidate gene with a large database of paired phenotypes and genotypes. Although the authors cite other bioinformatics systems that generate a calculated fold change (FC), our comments are specific to the Virco Type HIV-1. Hirsch et al. [1] state that virtual phenotype resistance interpretations are limited by a methodology that relies on matches that are based on preselected codons and not on the entire nucleotide sequence and that the “predictive power depends on the number of matched datasets available” [1, p. 274], with high variation for newer drugs with smaller datasets. We would like to note that the matching system used to calculate the FC in their article is no longer the methodology used by the Virco assay. Since July 2006, Virco’s bioinformatics engine has been used to calculate the FC for a given sample by the following method [2]. First, linear regression modeling is performed periodically to analyze the relationship between genotype and phenotype in the Virco correlative database, which to date, has 153,000 samples with paired genotypic and phenotypic data. Significant mutations and mutation pairs that affect phenotypic susceptibility to each drug are identified, and their negative or positive impact on the FC is quantified by a resistance weight factor. Second, all of the mutations in a sample genotype are compared on a drug-by-drug basis to the current list of resistance weight factors for the drug. An FC score is then generated by calculating the sum of the values for all resistance weight factors identified in the sample genotype. This methodology is unlike the first generation of the virtual phenotype, which sought to identify matches to viruses with very similar mutational profiles. With the current linear modeling engine, accurate FC values can be reported regardless of whether there are viruses with similar mutational profiles in the database.
影响因子：
3.8
作者：
MACKIE, TR;HOLMES, T;KINSELLA, T
通讯作者：
KINSELLA, T