Cost and cost-effectiveness of a real-world HCV treatment program among HIV-infected individuals in Myanmar

Introduction Over half of those hepatitis C virus (HCV)/HIV coinfected live in low-income and middle-income countries, and many remain undiagnosed or untreated. In 2016, Médecins Sans Frontières (MSF) established a direct-acting antiviral (DAA) treatment programme for people HCV/HIV coinfected in Myanmar. The purpose of our study was to evaluate the real-world cost and cost-effectiveness of this programme, and potential cost-effectiveness if implemented by the Ministry of Health (MoH). Methods Costs (patient-level microcosting) and treatment outcomes were collected from the MSF prospective cohort study in Dawei, Myanmar. A Markov model was used to assess cost-effectiveness of the programme compared with no HCV treatment from a health provider perspective. Estimated lifetime and healthcare costs (in 2017 US$) and health outcomes (in disability-adjusted life-years (DALYs)) were simulated to calculate the incremental cost-effectiveness ratio (ICER), compared with a willingness-to-pay threshold of per capita Gross Domestic Product in Myanmar ($1250). We evaluated cost-effectiveness with updated quality-assured generic DAA prices and potential cost-effectiveness of a proposed simplified treatment protocol with updated DAA prices if implemented by the MoH. Results From November 2016 to October 2017, 122 with HIV/HCV-coinfected patients were treated with DAAs (46% with cirrhosis), 96% (n=117) achieved sustained virological response. Mean treatment costs were $1229 (without cirrhosis) and$1971 (with cirrhosis), with DAA drugs being the largest contributor to cost. Compared with no treatment, the program was cost-effective (ICER $634/DALY averted); more so with updated prices for quality-assured generic DAAs (ICER$488/DALY averted). A simplified treatment protocol delivered by the MoH could be cost-effective if associated with similar outcomes (ICER $316/DALY averted). Conclusions Using MSF programme data, the DAA treatment programme for HCV among HIV-coinfected individuals is cost-effective in Myanmar, and even more so with updated DAA prices. A simplified treatment protocol could enhance cost-effectiveness if further rollout demonstrates it is not associated with worse treatment outcomes

Synergistic NGF/B27 Gradients Position Synapses Heterogeneously in 3D Micropatterned Neural Cultures

Native functional brain circuits show different numbers of synapses (synaptic densities) in the cerebral cortex. Until now, different synaptic densities could not be studied in vitro using current cell culture methods for primary neurons. Herein, we present a novel microfluidic based cell culture method that combines 3D micropatterning of hydrogel layers with linear chemical gradient formation. Micropatterned hydrogels were used to encapsulate dissociated cortical neurons in laminar cell layers and neurotrophic factors NGF and B27 were added to influence the formation of synapses. Neurotrophic gradients allowed for the positioning of distinguishable synaptic densities throughout a 3D micropatterned neural culture. NGF and B27 gradients were maintained in the microfluidic device for over two weeks without perfusion pumps by utilizing a refilling procedure. Spatial distribution of synapses was examined with a pre-synaptic marker to determine synaptic densities. From our experiments, we observed that (1) cortical neurons responded only to synergistic NGF/B27 gradients, (2) synaptic density increased proportionally to synergistic NGF/B27 gradients; (3) homogeneous distribution of B27 disturbed cortical neurons in sensing NGF gradients and (4) the cell layer position significantly impacted spatial distribution of synapses

Normalization of transcranial magnetic stimulation points by means of atlas registration

peer reviewe

Image segmentation with dynamic artifacts detection and bias correction

Region-based image segmentation is well-addressed by the ChanVese (CV) model. However, this approach fails when images are affected by artifacts (outliers) and illumination bias that outweigh the actual image contrast. Here, we introduce a model for segmenting such images. In a single energy functional, we introduce 1) a dynamic artifact class preventing intensity outliers from skewing the segmentation, and 2), in Retinex-fashion, we decompose the image into a piecewise-constant structural part and a smooth bias part. The CV-segmentation terms then only act on the structure, and only in regions not identified as artifacts. The segmentation is parameterized using a phase-field, and efficiently minimized using threshold dynamics. We demonstrate the proposed model on a series of sample images from diverse modalities exhibiting artifacts and/or bias. Our algorithm typically converges within 10-50 iterations and takes fractions of a second on standard equipment to produce meaningful results. We expect our method to be useful for damaged images, and anticipate use in applications where artifacts and bias are actual features of interest, such as lesion detection and bias field correction in medical imaging, e.g., in magnetic resonance imaging (MRI)

Whole-soil warming decreases abundance and modifies the community structure of microorganisms in the subsoil but not in surface soil

International audienceAbstract. The microbial community composition in subsoils remains understudied, and it is largely unknown whether subsoil microorganisms show a similar response to global warming as microorganisms at the soil surface do. Since microorganisms are the key drivers of soil organic carbon decomposition, this knowledge gap causes uncertainty in the predictions of future carbon cycling in the subsoil carbon pool (> 50 % of the soil organic carbon stocks are below 30 cm soil depth). In the Blodgett Forest field warming experiment (California, USA) we investigated how +4 ∘C warming in the whole-soil profile to 100 cm soil depth for 4.5 years has affected the abundance and community structure of microorganisms. We used proxies for bulk microbial biomass carbon (MBC) and functional microbial groups based on lipid biomarkers, such as phospholipid fatty acids (PLFAs) and branched glycerol dialkyl glycerol tetraethers (brGDGTs). With depth, the microbial biomass decreased and the community composition changed. Our results show that the concentration of PLFAs decreased with warming in the subsoil (below 30 cm) by 28 % but was not affected in the topsoil. Phospholipid fatty acid concentrations changed in concert with soil organic carbon. The microbial community response to warming was depth dependent. The relative abundance of Actinobacteria increased in warmed subsoil, and Gram+ bacteria in subsoils adapted their cell membrane structure to warming-induced stress, as indicated by the ratio of anteiso to iso branched PLFAs. Our results show for the first time that subsoil microorganisms can be more affected by warming compared to topsoil microorganisms. These microbial responses could be explained by the observed decrease in subsoil organic carbon concentrations in the warmed plots. A decrease in microbial abundance in warmed subsoils might reduce the magnitude of the respiration response over time. The shift in the subsoil microbial community towards more Actinobacteria might disproportionately enhance the degradation of previously stable subsoil carbon, as this group is able to metabolize complex carbon sources

A geometric model of brightness perception and its application to color images correction

Human perception involves many features like contours, shapes, textures, and colors to name a few. Whereas several geometric models for contours, shapes and textures perception have been proposed, the geometry of color perception has received very little attention, possibly due to the fact that our perception of colors is still not fully understood. Nonetheless, there exists a class of mathematical models, gathered under the name Retinex, that aim at modeling the color perception of an image, that are inspired by psychophysical/physiological knowledge about color perception, and that can geometrically be viewed as the averaging of perceptual distances between image pixels. Some of the Retinex models turn out to be associated to an efficient image processing technique for the correction of camera output images. The aim of this paper is to show that this image processing technique can be improved by including more properties of the human visual system. To that purpose, we first present a generalization of the perceptual distance between image pixels by considering the parallel transport map associated to a covariant derivative on a vector bundle, and from which can be derived a new image processing model for color images correction. Then, we show that the family of covariant derivatives constructed in [T. Batard and N. Sochen, J. Math. Imaging Vision, 48(3) (2014), pp. 517-543] can model some color appearance phenomena related to brightness perception. Finally, we conduct experiments in which we show that the image processing techniques induced by these covariant derivatives outperform the original approach.This work was supported by the European Research Council, Starting Grant ref. 306337, by the Spanish government and FEDER Fund, grant ref. TIN2015-71537-P (MINECO/FEDER,UE), and by the Icrea Academia Award

Two-Dimensional Compact Variational Mode Decomposition

Decomposing multidimensional signals, such as images, into spatially compact, potentially overlapping modes of essentially wavelike nature makes these components accessible for further downstream analysis. This decomposition enables space–frequency analysis, demodulation, estimation of local orientation, edge and corner detection, texture analysis, denoising, inpainting, or curvature estimation. Our model decomposes the input signal into modes with narrow Fourier bandwidth; to cope with sharp region boundaries, incompatible with narrow bandwidth, we introduce binary support functions that act as masks on the narrow-band mode for image recomposition. L1 and TV terms promote sparsity and spatial compactness. Constraining the support functions to partitions of the signal domain, we effectively get an image segmentation model based on spectral homogeneity. By coupling several submodes together with a single support function, we are able to decompose an image into several crystal grains. Our efficient algorithm is based on variable splitting and alternate direction optimization; we employ Merriman–Bence–Osher-like threshold dynamics to handle efficiently the motion by mean curvature of the support function boundaries under the sparsity promoting terms. The versatility and effectiveness of our proposed model is demonstrated on a broad variety of example images from different modalities. These demonstrations include the decomposition of images into overlapping modes with smooth or sharp boundaries, segmentation of images of crystal grains, and inpainting of damaged image regions through artifact detection