Baseline (T0) Study Population Characteristics.

<p>Abbreviations: T0, time of first viral load result using the ultrasensitive Taqman assay (study entry); TND, target not detected; NNRTI, non-nucleoside reverse transcriptase inhibitor.</p>a<p>4 missing values, N = 774.</p>b<p>Number and percent within T0 viral load group.</p>c<p>Includes protease inhibitor, integrase inhibitor-based and other regimens.</p>d<p>Includes 180 subjects with VL <48 copies, and 360 subjects with undetectable VL propensity score-matched to the <48 group.</p>e<p>Mean CD4 counts were identical after propensity matching.</p

Multivariable Results from Cox Proportional Hazards Regression Analyses of Predictors of Virologic Rebound.

<p>Abbreviations: HR, hazard ratio; CI, confidence interval; T0, time of first viral load result using the ultrasensitive Taqman assay (study entry); NNRTI, non-nucleoside reverse transcriptase inhibitor; ART, antiretroviral therapy.</p>a<p>N = 773 (5 cases with missing demographic or laboratory values).</p>b<p>Significant association, P<0.05.</p>c<p>N = 540, including 180 subjects with VL <48 copies, and 360 subjects with undetectable VL propensity score-matched to the <48 group. Only effects of the T0 VL group were compared as propensity score-matching adjusted for baseline differences between cohorts.</p

Clinical outcomes associated with coadministration of lopinavir/ritonavir-based ART and rifampicin-containing TB treatment.

<p>T-test, Chi-square, and Fisher’s tests used for comparisons, * p<0.05.</p

Baseline characteristics of patients at initiation of lopinavir/ritonavir-based second line ART, according to treatment group.

<p>Baseline characteristics of patients at initiation of lopinavir/ritonavir-based second line ART, according to treatment group.</p

Kaplan-Meier survival curve for the impact of lopinavir/ritonavir dosing strategy among patients with HIV/TB coinfection on time until treatment discontinuation.

<p>Kaplan-Meier survival curve for the impact of lopinavir/ritonavir dosing strategy among patients with HIV/TB coinfection on time until treatment discontinuation.</p

Comparison of the viral load decay rates during treatment with or without RAL.

<p>Rows represent each phase of decay and columns the estimates for each treatment using two methodologies: a heuristic multi-exponential model (two columns on the left) and the SRI model in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006478#ppat.1006478.g002" target="_blank">Fig 2B</a> and Eq (<b><a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006478#ppat.1006478.e008" target="_blank">1</a></b>) (two columns on the right). The estimation of the rate for phase 1b is only applicable in the case of treatment with RAL. All values are in units of day^-1. For the SRI model, we also indicate the parameter combination defining the decay rate of each phase.</p

Schematics of the models.

<p>(A) The standard model with pre- and post-integration phases of infection. We follow two types of target cells that after infection will be short-lived, , or long-lived, . Target cells, , are infected by infectious virus, <i>V_i</i>, at rate . The infection can be blocked by the activity of RTIs with effectiveness <i>η</i>. These infected cells, <i>I</i>₁, are lost at rate <i>δ</i>₁, or can undergo provirus integration at rate <i>k</i> and become productively infected cells <i>I</i>₂. InSTIs block integration with efficacy <i>ω</i>. Cells with integrated provirus, <i>I</i>₂, are lost at rate <i>δ</i>₂. Virions are produced by these cells at rate <i>p</i> per cell and are cleared from the circulation at rate <i>c</i> per virion. Protease inhibitors block the production of infectious virus <i>V</i>_<i>Ii</i>, and lead to production of non-infectious virus <i>V</i>_<i>Ini</i>, with efficacy <i>ε</i>. The subscripts <i>I</i> and <i>M</i> are used to distinguish virions produced by short-lived and long-lived infected cells, respectively. The dynamics of long-lived cells are similar, but possibly with different rates as indicated. (B) The slow and rapid integration (SRI) model. The SRI model proposes that both short-lived cells with fast integration (<i>I</i>₁) and long-lived cells with slow integration (<i>M</i>₁) generate productively infected cells that die quickly (<i>I</i>₂) (i.e. <i>δ</i>₂ = <i>δ</i>_{<b><i>M</i>2</b>}<b>)</b>.</p

Representative individual fits for the three datasets.

<p>Blue, red and green circles represent HIV RNA measurements for the quad-based-, RAL-combination- and RAL-mono therapy, respectively. Solid black lines represent best fits from the SRI model using the mixed-effects approach. Parameter estimates for each individual are presented in Table E in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006478#ppat.1006478.s001" target="_blank">S1 Text</a>.</p

Nanoplasmonic Quantitative Detection of Intact Viruses from Unprocessed Whole Blood

Infectious diseases such as HIV and hepatitis B pose an omnipresent threat to global health. Reliable, fast, accurate, and sensitive platforms that can be deployed at the point-of-care (POC) in multiple settings, such as airports and offices, for detection of infectious pathogens are essential for the management of epidemics and possible biological attacks. To the best of our knowledge, no viral load technology adaptable to the POC settings exists today due to critical technical and biological challenges. Here, we present for the first time a broadly applicable technology for quantitative, nanoplasmonic-based intact virus detection at clinically relevant concentrations. The sensing platform is based on unique nanoplasmonic properties of nanoparticles utilizing immobilized antibodies to selectively capture rapidly evolving viral subtypes. We demonstrate the capture, detection, and quantification of multiple HIV subtypes (A, B, C, D, E, G, and subtype panel) with high repeatability, sensitivity, and specificity down to 98 ± 39 copies/mL (<i>i.e</i>., HIV subtype D) using spiked whole blood samples and clinical discarded HIV-infected patient whole blood samples validated by the gold standard, <i>i</i>.<i>e</i>., RT-qPCR. This platform technology offers an assay time of 1 h and 10 min (1 h for capture, 10 min for detection and data analysis). The presented platform is also able to capture intact viruses at high efficiency using immuno-surface chemistry approaches directly from whole blood samples without any sample preprocessing steps such as spin-down or sorting. Evidence is presented showing the system to be accurate, repeatable, and reliable. Additionally, the presented platform technology can be broadly adapted to detect other pathogens having reasonably well-described biomarkers by adapting the surface chemistry. Thus, this broadly applicable detection platform holds great promise to be implemented at POC settings, hospitals, and primary care settings

Predicted viral load decay for the quad and RAL-combination treatments using the best fit of the SRI model (Eq (1) when <i>δ</i>₂ = <i>δ</i>_<i>M</i>2) to the data.

<p>The estimated population parameters for each treatment group where used to plot the viral load decline under the effect of RAL+RTI (red) and quad therapy (blue). The dotted blue and red lines show the analytical approximation for the second phase of decay for quad therapy and RAL-combination therapy, respectively (see equation S.14 in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006478#ppat.1006478.s001" target="_blank">S1 Text</a>). The shadowed section highlights phase 1b for RAL-combination therapy. The viral load at the start of phase 2 in patients under RAL-based therapy is reduced with respect to the corresponding level in RAL-free therapy by a factor of . We fixed the values of the following parameters (see text for details): <i>V</i>_<i>I</i>(0)/<i>V</i>(0) = 0.98, <i>δ</i>_<i>M</i>1 = 0.02 day^-1, <i>k</i> = 2.6 day^-1 and <i>c</i> = 23 day^-1 based on previous studies [<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006478#ppat.1006478.ref014" target="_blank">14</a>,<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006478#ppat.1006478.ref016" target="_blank">16</a>,<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006478#ppat.1006478.ref039" target="_blank">39</a>]. In addition, for RAL combination we used <i>η</i> = 0.95, <i>ε</i> = 0 and <i>ω</i> = 0.94, and for the quad therapy <i>η</i> = <i>ε</i> = 0.95 and <i>ω</i> = 0 [<a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1006478#ppat.1006478.ref014" target="_blank">14</a>]. The estimated best-fit population parameters are (estimated standard deviation in parenthesis): <i>δ</i>₁ = 0.23 (0.04) day^-1, <i>k</i>₁ = 0.017 (0.01) day^-1, <i>δ</i>₂ = 0.85 (0.07) day^-1 and <i>V</i>(0) = 4.8 (0.07).</p