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Herpes simplex virus-2 genital tract shedding is not predictable over months or years in infected persons.

Dhankani V, Kutz JN, Schiffer JT - PLoS Comput. Biol. (2014)

Bottom Line: Empirical and model-derived, time-series data gathered over >30 days consists of multiple complex episodes that could not be reduced to a manageable number of descriptive features with PCA and SVD.However, single HSV-2 shedding episodes, even those with prolonged duration and complex morphologies consisting of multiple erratic peaks, were consistently described using a maximum of four dominant features.These findings suggest that HSV-2 shedding patterns within an individual are impossible to predict over weeks or months, and that even highly complex single HSV-2 episodes can only be partially predicted based on spatial distribution of immune cell density.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.

ABSTRACT
Herpes simplex virus-2 (HSV-2) is a chronic reactivating infection that leads to recurrent shedding episodes in the genital tract. A minority of episodes are prolonged, and associated with development of painful ulcers. However, currently, available tools poorly predict viral trajectories and timing of reactivations in infected individuals. We employed principal components analysis (PCA) and singular value decomposition (SVD) to interpret HSV-2 genital tract shedding time series data, as well as simulation output from a stochastic spatial mathematical model. Empirical and model-derived, time-series data gathered over >30 days consists of multiple complex episodes that could not be reduced to a manageable number of descriptive features with PCA and SVD. However, single HSV-2 shedding episodes, even those with prolonged duration and complex morphologies consisting of multiple erratic peaks, were consistently described using a maximum of four dominant features. Modeled and clinical episodes had equivalent distributions of dominant features, implying similar dynamics in real and simulated episodes. We applied linear discriminant analysis (LDA) to simulation output and identified that local immune cell density at the viral reactivation site had a predictive effect on episode duration, though longer term shedding suggested chaotic dynamics and could not be predicted based on spatial patterns of immune cell density. These findings suggest that HSV-2 shedding patterns within an individual are impossible to predict over weeks or months, and that even highly complex single HSV-2 episodes can only be partially predicted based on spatial distribution of immune cell density.

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Linear Discriminant Analysis.(a) x-axis is T-cell density in the region of episode initiation (T0), (b) x-axis (xi) is the scalar projection value of ith initial condition <T1i; T2i; T3i; T4i; T5i; T6i> obtained by projecting onto vector w1 that maximizes Fisher criterion. In both (a) and (b), Class A (0–2 days) of initial T-cell densities showed maximum separation from the other three classes, indicating strong correlation between initial T-cell densities and episode severity only for episodes that last for 0–2 days.
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pcbi-1003922-g006: Linear Discriminant Analysis.(a) x-axis is T-cell density in the region of episode initiation (T0), (b) x-axis (xi) is the scalar projection value of ith initial condition <T1i; T2i; T3i; T4i; T5i; T6i> obtained by projecting onto vector w1 that maximizes Fisher criterion. In both (a) and (b), Class A (0–2 days) of initial T-cell densities showed maximum separation from the other three classes, indicating strong correlation between initial T-cell densities and episode severity only for episodes that last for 0–2 days.

Mentions: In stochastic model simulations, episodes randomly initiate in one of 300 regions, each of which has a certain density of CD8+ T-cells and is surrounded by six other regions with separate densities. We attempted to correlate these regional densities with episode trajectory. Probability density curves of T-cell density in the region of episode initiation (T0) showed significant separation between Class A and the other three classes. Class A demonstrated comparatively higher T-cell densities while Classes B, C, and D showed considerable overlap in their ranges (Figure 6a). Class C and D were superimposed.


Herpes simplex virus-2 genital tract shedding is not predictable over months or years in infected persons.

Dhankani V, Kutz JN, Schiffer JT - PLoS Comput. Biol. (2014)

Linear Discriminant Analysis.(a) x-axis is T-cell density in the region of episode initiation (T0), (b) x-axis (xi) is the scalar projection value of ith initial condition <T1i; T2i; T3i; T4i; T5i; T6i> obtained by projecting onto vector w1 that maximizes Fisher criterion. In both (a) and (b), Class A (0–2 days) of initial T-cell densities showed maximum separation from the other three classes, indicating strong correlation between initial T-cell densities and episode severity only for episodes that last for 0–2 days.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4222642&req=5

pcbi-1003922-g006: Linear Discriminant Analysis.(a) x-axis is T-cell density in the region of episode initiation (T0), (b) x-axis (xi) is the scalar projection value of ith initial condition <T1i; T2i; T3i; T4i; T5i; T6i> obtained by projecting onto vector w1 that maximizes Fisher criterion. In both (a) and (b), Class A (0–2 days) of initial T-cell densities showed maximum separation from the other three classes, indicating strong correlation between initial T-cell densities and episode severity only for episodes that last for 0–2 days.
Mentions: In stochastic model simulations, episodes randomly initiate in one of 300 regions, each of which has a certain density of CD8+ T-cells and is surrounded by six other regions with separate densities. We attempted to correlate these regional densities with episode trajectory. Probability density curves of T-cell density in the region of episode initiation (T0) showed significant separation between Class A and the other three classes. Class A demonstrated comparatively higher T-cell densities while Classes B, C, and D showed considerable overlap in their ranges (Figure 6a). Class C and D were superimposed.

Bottom Line: Empirical and model-derived, time-series data gathered over >30 days consists of multiple complex episodes that could not be reduced to a manageable number of descriptive features with PCA and SVD.However, single HSV-2 shedding episodes, even those with prolonged duration and complex morphologies consisting of multiple erratic peaks, were consistently described using a maximum of four dominant features.These findings suggest that HSV-2 shedding patterns within an individual are impossible to predict over weeks or months, and that even highly complex single HSV-2 episodes can only be partially predicted based on spatial distribution of immune cell density.

View Article: PubMed Central - PubMed

Affiliation: Department of Applied Mathematics, University of Washington, Seattle, Washington, United States of America.

ABSTRACT
Herpes simplex virus-2 (HSV-2) is a chronic reactivating infection that leads to recurrent shedding episodes in the genital tract. A minority of episodes are prolonged, and associated with development of painful ulcers. However, currently, available tools poorly predict viral trajectories and timing of reactivations in infected individuals. We employed principal components analysis (PCA) and singular value decomposition (SVD) to interpret HSV-2 genital tract shedding time series data, as well as simulation output from a stochastic spatial mathematical model. Empirical and model-derived, time-series data gathered over >30 days consists of multiple complex episodes that could not be reduced to a manageable number of descriptive features with PCA and SVD. However, single HSV-2 shedding episodes, even those with prolonged duration and complex morphologies consisting of multiple erratic peaks, were consistently described using a maximum of four dominant features. Modeled and clinical episodes had equivalent distributions of dominant features, implying similar dynamics in real and simulated episodes. We applied linear discriminant analysis (LDA) to simulation output and identified that local immune cell density at the viral reactivation site had a predictive effect on episode duration, though longer term shedding suggested chaotic dynamics and could not be predicted based on spatial patterns of immune cell density. These findings suggest that HSV-2 shedding patterns within an individual are impossible to predict over weeks or months, and that even highly complex single HSV-2 episodes can only be partially predicted based on spatial distribution of immune cell density.

Show MeSH
Related in: MedlinePlus