scholarly journals A mechanistic latent variable model for estimating drug concentrations in the male genital tract: A case study in drug kinetics

2008 ◽  
Vol 27 (14) ◽  
pp. 2697-2714
Author(s):  
Leena Choi ◽  
Brian Caffo ◽  
Charles Rohde ◽  
Themba T. Ndovi ◽  
Craig W. Hendrix
AIDS ◽  
2001 ◽  
Vol 15 (15) ◽  
pp. 2051-2053 ◽  
Author(s):  
Stephen Taylor ◽  
Helen Reynolds ◽  
Caroline A. Sabin ◽  
Susan M. Drake ◽  
David J. White ◽  
...  

2020 ◽  
Vol 75 (6) ◽  
pp. 1611-1617
Author(s):  
Charlotte Charpentier ◽  
Gilles Peytavin ◽  
François Raffi ◽  
Charles Burdet ◽  
Roland Landman ◽  
...  

Abstract Objectives To describe plasma residual HIV viraemia, cellular HIV reservoir size, blood plasma drug concentrations and their male genital tract penetration during the maintenance dual therapy dolutegravir + lamivudine. Patients and methods ANRS167 LAMIDOL enrolled 104 virologically suppressed patients to switch to dolutegravir + lamivudine. In this pharmacovirological substudy, ultrasensitive plasma viral load (USpVL) and plasma drug concentrations were measured at Day 0 (D0), Week 24 (W24) and W48 of dolutegravir + lamivudine, and HIV-DNA was measured at W−8 and W48. Semen samples were collected at D0 and W24 from 18 participants. Total and unbound blood and seminal plasma drug concentrations were measured using UPLC–MS/MS. Results Median HIV-DNA was 2.5 log10 copies/106 PBMC (IQR = 2.2–3.0, n = 100) at W−8 and 2.4 log10 copies/106 PBMC (IQR = 2.1–2.9, n = 100) at W48 (P = 0.17). The proportion of patients with undetected USpVL was 38% (n = 98), 43% (n = 98) and 49% (n = 97) at D0, W24 and W48, respectively (P = 0.08). Total and unbound plasma dolutegravir concentrations were stable between timepoints (P = 0.13) and all total plasma dolutegravir concentrations except one were adequate. Median free fraction of dolutegravir in plasma was 0.21%. Median blood plasma and seminal plasma concentrations of total dolutegravir at 24 h were 1812 ng/mL and 206 ng/mL, respectively. Median seminal plasma/blood plasma total concentration ratios were 11.6% and 2478% for dolutegravir and lamivudine, respectively. HIV-RNA (365 to 475 copies/mL) was detected in seminal plasma of one patient at D0 (5.9%) and of two patients at W24 (11.8%). Conclusions These findings add further important information regarding the effectiveness of dolutegravir + lamivudine maintenance dual therapy in terms of plasma residual viraemia, cellular reservoir size and drug penetration in the male genital tract.


2021 ◽  
Vol 421 ◽  
pp. 244-259
Author(s):  
Hao Xiong ◽  
Yuan Yan Tang ◽  
Fionn Murtagh ◽  
Leszek Rutkowski ◽  
Shlomo Berkovsky

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3137
Author(s):  
Amine Tadjer ◽  
Reider B. Bratvold ◽  
Remus G. Hanea

Production forecasting is the basis for decision making in the oil and gas industry, and can be quite challenging, especially in terms of complex geological modeling of the subsurface. To help solve this problem, assisted history matching built on ensemble-based analysis such as the ensemble smoother and ensemble Kalman filter is useful in estimating models that preserve geological realism and have predictive capabilities. These methods tend, however, to be computationally demanding, as they require a large ensemble size for stable convergence. In this paper, we propose a novel method of uncertainty quantification and reservoir model calibration with much-reduced computation time. This approach is based on a sequential combination of nonlinear dimensionality reduction techniques: t-distributed stochastic neighbor embedding or the Gaussian process latent variable model and clustering K-means, along with the data assimilation method ensemble smoother with multiple data assimilation. The cluster analysis with t-distributed stochastic neighbor embedding and Gaussian process latent variable model is used to reduce the number of initial geostatistical realizations and select a set of optimal reservoir models that have similar production performance to the reference model. We then apply ensemble smoother with multiple data assimilation for providing reliable assimilation results. Experimental results based on the Brugge field case data verify the efficiency of the proposed approach.


2021 ◽  
Vol 11 (2) ◽  
pp. 624
Author(s):  
In-su Jo ◽  
Dong-bin Choi ◽  
Young B. Park

Chinese characters in ancient books have many corrupted characters, and there are cases in which objects are mixed in the process of extracting the characters into images. To use this incomplete image as accurate data, we use image completion technology, which removes unnecessary objects and restores corrupted images. In this paper, we propose a variational autoencoder with classification (VAE-C) model. This model is characterized by using classification areas and a class activation map (CAM). Through the classification area, the data distribution is disentangled, and then the node to be adjusted is tracked using CAM. Through the latent variable, with which the determined node value is reduced, an image from which unnecessary objects have been removed is created. The VAE-C model can be utilized not only to eliminate unnecessary objects but also to restore corrupted images. By comparing the performance of removing unnecessary objects with mask regions with convolutional neural networks (Mask R-CNN), one of the prevalent object detection technologies, and also comparing the image restoration performance with the partial convolution model (PConv) and the gated convolution model (GConv), which are image inpainting technologies, our model is proven to perform excellently in terms of removing objects and restoring corrupted areas.


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