A comprehensive two-dimensional (2D) retention time alignment algorithm was developed using a novel indexing scheme. The algorithm is termed comprehensive because it functions to correct the entire chromatogram in both dimensions and it preserves the separation information in both dimensions. Although the algorithm is demonstrated by correcting comprehensive two-dimensional gas chromatography (GC x GC) data, the algorithm is designed to correct shifting in all forms of 2D separations, such as LC x LC, LC x CE, CE x CE, and LC x GC. This 2D alignment algorithm was applied to three different data sets composed of replicate GC x GC separations of (1) three 22-component control mixtures, (2) three gasoline samples, and (3) three diesel samples. The three data sets were collected using slightly different temperature or pressure programs to engender significant retention time shifting in the raw data and then demonstrate subsequent corrections of that shifting upon comprehensive 2D alignment of the data sets. Thirty 12-min GC x GC separations from three 22-component control mixtures were used to evaluate the 2D alignment performance (10 runs/mixture). The average standard deviation of first column retention time improved 5-fold from 0.020 min (before alignment) to 0.004 min (after alignment). Concurrently, the average standard deviation of second column retention time improved 4-fold from 3.5 ms (before alignment) to 0.8 ms (after alignment). Alignment of the 30 control mixture chromatograms took 20 min. The quantitative integrity of the GC x GC data following 2D alignment was also investigated. The mean integrated signal was determined for all components in the three 22-component mixtures for all 30 replicates. The average percent difference in the integrated signal for each component before and after alignment was 2.6%. Singular value decomposition (SVD) was applied to the 22-component control mixture data before and after alignment to show the restoration of trilinearity to the data, since trilinearity benefits chemometric analysis. By applying comprehensive 2D retention time alignment to all three data sets (control mixtures, gasoline samples, and diesel samples), classification by principal component analysis (PCA) substantially improved, resulting in 100% accurate scores clustering.

Summary The global spread of human immunodeficiency virus (HIV) is dependent on the ability of this virus to efficiently cross from one host to the next by traversing a mucosal membrane. Unraveling how mucosal exposure of HIV results in systemic infection is critical for the development of effective therapeutic strategies. This review focuses on understanding the immune events associated with the oral route of transmission (via breastfeeding or sexual oral intercourse), which occurs across the oral and/or gastrointestinal mucosa. Studies in both humans and simian immunodeficiency virus (SIV) monkey models have identified viral changes and immune events associated with oral HIV/SIV exposure. This review covers our current knowledge of HIV oral transmission in both infants and adults, the use of SIV models in understanding early immune events, oral immune factors that modulate HIV/SIV susceptibility (including mucosal inflammation), and interventions that may impact oral HIV transmission rates. Understanding the factors that influence oral HIV transmission will provide the foundation for developing immune therapeutic and vaccine strategies that can protect both infants and adults from oral HIV transmission.