PubMed · 14250038
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J R LEWIS. 1964. MAMMAPLASTY--A CURRENT EVALUATION.. https://pubmed.ncbi.nlm.nih.gov/14250038/
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Microarrays have been extensively used to investigate genome-wide expression patterns. Although this technology has been tremendously successful, it has suffered from suboptimal individual measurement precision. Significant improvements in this respect have been recently made. In an effort to further explore the underlying variability, we have attempted to globally assess the accuracy of individual probe sequences used to query gene expression. For mammalian Affymetrix microarrays, we identify an unexpectedly large number of probes (greater than 19% of the probes on each platform) that do not correspond to their appropriate mRNA reference sequence (RefSeq). Compared with data derived from inaccurate probes, we find that data derived from sequence-verified probes show 1) increased precision in technical replicates, 2) increased accuracy translating data from one generation microarray to another, 3) increased accuracy translating data from oligonucleotide to cDNA microarrays, and 4) improved capture of biological information in human clinical specimens. The logical conclusion of this work is that probes containing the most reliable sequence information provide the most accurate results. Our data reveal that the identification and removal of inaccurate probes can significantly improve this technology.
The patients seeking our help for breast reduction are very often young and probably planning to have children later in their lives. Therefore it is most important to offer them a method of reduction mammaplasty that leaves as little scars and as much physiological function as possible. The vertical reduction mammaplasty as we perform it is a method that leaves normal sensibility in almost all cases, the possibility of lactation, little scarring and a pleasant form. The method can be used in all cases, ranging from mastopexy to reduction weights of over 2 kg of each breast. The vertical technique developed by Claude Lassus [1,2] and Madeleine Lejour [3,4,5,6] is a contemporary method of reduction that leaves few scars and conserves a maximum of physiological function. The method needs surgical skill and therefore it is not suitable for beginners in breast surgery. It is difficult to teach because it uses no patterns such as those of Strömbeck [7] or McKissock [8] but it gives the breasts a new form based on the anatomical circumstances and wishes of the patients. Due to some unfavorable results in the early beginning often caused by too long a caudal part of the breast or a dog-ear at the end of the vertical scar, we have added some modifications to the method. We've heard of the same problems from several colleagues who no longer perform this method in major reduction plasties. We have been using this technique in all cases of breast reductions or mastopexies for the past 8 years.
Cancer derived microarray data sets are routinely produced by various platforms that are either commercially available or manufactured by academic groups. The fundamental difference in their probe selection strategies holds the promise that identical observations produced by more than one platform prove to be more robust when validated by biology. However, cross-platform comparison requires matching corresponding probe sets. We are introducing here sequence-based matching of probes instead of gene identifier-based matching. We analyzed breast cancer cell line derived RNA aliquots using Agilent cDNA and Affymetrix oligonucleotide microarray platforms to assess the advantage of this method. We show, that at different levels of the analysis, including gene expression ratios and difference calls, cross-platform consistency is significantly improved by sequence- based matching. We also present evidence that sequence-based probe matching produces more consistent results when comparing similar biological data sets obtained by different microarray platforms. This strategy allowed a more efficient transfer of classification of breast cancer samples between data sets produced by cDNA microarray and Affymetrix gene-chip platforms.