HCV microelimination in harm reduction centres has benefits beyond HCV cure but is hampered by high reinfection rates

Significant scale-up of treatment among people who inject drugs (PWID) is crucial to achieve WHO HCV elimination targets. We explored the impact of on-site HCV diagnosis and treatment on PWID in an externalised hepatology clinic at the biggest harm reduction centre (HRC) in Barcelona attending to a marginalised PWID population with ongoing high-risk practices.On-site HCV point-of-care testing was performed for diagnosis and treatment delivery. HCV-RNA was assessed at SVR12 (sustained virologic response at 12 weeks) and every 6 months. The programme included behavioural questionnaires at baseline and after treatment.Between 2018 and 2020, 919 individuals were prospectively enrolled. Of these, only 46% accepted HCV screening. HCV-RNA+ prevalence was 55.7% (n = 234). Of the 168 (72%) individuals starting treatment, 48% were foreigners, 32% homeless, 73% unemployed, and 62% had a history of incarceration. At enrolment, 70% injected drugs daily and 30% reported sharing needles or paraphernalia. Intention-to-treat SVR12 was 60%; only 4% were virological failures, the remaining were either early reinfections (20%) or losses to follow-up (16%). The overall reinfection rate during follow-up was 31/100 persons/year. HIV coinfection and daily injection were associated with a higher risk of reinfection. Nonetheless, beyond viral clearance, antiviral therapy was associated with a significant reduction in injection frequency, risk practices, and homelessness.HCV treatment can be successfully delivered to active PWID with high-risk practices and has a significant benefit beyond HCV elimination. However, approaching this difficult spectrum of the PWID population implies significant barriers such as low rate of screening acceptance and high dropout and reinfection rates.People who inject drugs attending harm reduction centres represent the most difficult population to treat for hepatitis C. We show that hepatitis C treatment has a significant benefit beyond viral cure, including improving quality of life, and decreasing injection frequency and risk practices. However, intrinsic barriers and the high reinfection rates hamper the achievement of viral microelimination in this setting.© 2022 The Author(s)

Computer-assisted timber identification based on features extracted from microscopic wood sections

Wood anatomy is one of the most important methods for timber identification. However, training wood anatomy experts is time-consuming, while at the same time the number of senior wood anatomists with broad taxonomic expertise is de- clining. Therefore, we want to explore how a more automated, computer-assisted approach can support accurate wood identification based on microscopic wood anatomy. For our exploratory research, we used an available image dataset that has been applied in several computer vision studies, consisting of 112 — mainly neotropical — tree species representing 20 images of transverse sections for each species. Our study aims to review existing computer vision methods and compare the success of species identification based on (1) several image classifiers based on manually adjusted texture features, and (2) a state-of-the-art approach for image classification based on deep learning, more specifically Convolutional Neural Networks (CNNs). In support of previous studies, a considerable increase of the correct identification is accomplished using deep learning, leading to an accuracy rate up to 95.6%. This remarkably high success rate highlights the fundamental potential of wood anatomy in species identification and motivates us to expand the existing database to an extensive, worldwide reference database with transverse and tangential microscopic images from the most traded timber species and their look-a-likes. This global reference database could serve as a valuable future tool for stakeholders involved in combatting illegal logging and would boost the societal value of wood anatomy along with its collections and experts.Plant sciencesNaturali

Cloud computing for energy management in smart grid - an application survey

The smart grid is the emerging energy system wherein the application of information technology, tools and techniques that make the grid run more efficiently. It possesses demand response capacity to help balance electrical consumption with supply. The challenges and opportunities of emerging and future smart grids can be addressed by cloud computing. To focus on these requirements, we provide an in-depth survey on different cloud computing applications for energy management in the smart grid architecture. In this survey, we present an outline of the current state of research on smart grid development. We also propose a model of cloud based economic power dispatch for smart grid

A proteomic approach for the identification of novel lysine methyltransferase substrates

<p>Abstract</p> <p>Background</p> <p>Signaling via protein lysine methylation has been proposed to play a central role in the regulation of many physiologic and pathologic programs. In contrast to other post-translational modifications such as phosphorylation, proteome-wide approaches to investigate lysine methylation networks do not exist.</p> <p>Results</p> <p>In the current study, we used the ProtoArray^®platform, containing over 9,500 human proteins, and developed and optimized a system for proteome-wide identification of novel methylation events catalyzed by the protein lysine methyltransferase (PKMT) SETD6. This enzyme had previously been shown to methylate the transcription factor RelA, but it was not known whether SETD6 had other substrates. By using two independent detection approaches, we identified novel candidate substrates for SETD6, and verified that all targets tested <it>in vitro </it>and in cells were genuine substrates.</p> <p>Conclusions</p> <p>We describe a novel proteome-wide methodology for the identification of new PKMT substrates. This technological advance may lead to a better understanding of the enzymatic activity and substrate specificity of the large number (more than 50) PKMTs present in the human proteome, most of which are uncharacterized.</p

Pre-formulation and systematic evaluation of amino acid assisted permeability of insulin across in vitro buccal cell layers

The aim of this work was to investigate alternative safe and effective permeation enhancers for buccal peptide delivery. Basic amino acids improved insulin solubility in water while 200 and 400 µg/mL lysine significantly increased insulin solubility in HBSS. Permeability data showed a significant improvement in insulin permeation especially for 10 µg/mL of lysine (p < 0.05) and 10 µg/mL histidine (p < 0.001), 100 µg/mL of glutamic acid (p < 0.05) and 200 µg/mL of glutamic acid and aspartic acid (p < 0.001) without affecting cell integrity; in contrast to sodium deoxycholate which enhanced insulin permeability but was toxic to the cells. It was hypothesized that both amino acids and insulin were ionised at buccal cavity pH and able to form stable ion pairs which penetrated the cells as one entity; while possibly triggering amino acid nutrient transporters on cell surfaces. Evidence of these transport mechanisms was seen with reduction of insulin transport at suboptimal temperatures as well as with basal-to-apical vectoral transport, and confocal imaging of transcellular insulin transport. These results obtained for insulin is the first indication of a possible amino acid mediated transport of insulin via formation of insulin-amino acid neutral complexes by the ion pairing mechanism

Stressful conditions reveal decrease in size, modification of shape but relatively stable asymmetry in bumblebee wings

Human activities can generate a wide variety of direct and indirect effects on animals, which can manifest as environmental and genetic stressors. Several phenotypic markers have been proposed as indicators of these stressful conditions but have displayed contrasting results, depending, among others, on the phenotypic trait measured. Knowing the worldwide decline of multiple bumblebee species, it is important to understand these stressors and link them with the drivers of decline. We assessed the impact of several stressors (i.e. natural toxin-, parasite-, thermic- and inbreeding-stress) on both wing shape and size and their variability as well as their directional and fluctuating asymmetries. The total data set includes 650 individuals of Bombus terrestris (Hymenoptera: Apidae). Overall wing size and shape were affected by all the tested stressors. Except for the sinigrin (e.g. glucosinolate) stress, each stress implies a decrease of wing size. Size variance was affected by several stressors, contrary to shape variance that was affected by none of them. Although wing size directional and fluctuating asymmetries were significantly affected by sinigrin, parasites and high temperatures, neither directional nor fluctuating shape asymmetry was significantly affected by any tested stressor. Parasites and high temperatures led to the strongest phenotype modifications. Overall size and shape were the most sensitive morphological traits, which contrasts with the common view that fluctuating asymmetry is the major phenotypic marker of stress

Deep-sequencing reveals broad subtype-specific HCV resistance mutations associated with treatment failure

A percentage of hepatitis C virus (HCV)-infected patients fail direct acting antiviral (DAA)-based treatment regimens, often because of drug resistance-associated substitutions (RAS). The aim of this study was to characterize the resistance profile of a large cohort of patients failing DAA-based treatments, and investigate the relationship between HCV subtype and failure, as an aid to optimizing management of these patients. A new, standardized HCV-RAS testing protocol based on deep sequencing was designed and applied to 220 previously subtyped samples from patients failing DAA treatment, collected in 39 Spanish hospitals. The majority had received DAA-based interferon (IFN) a-free regimens; 79% had failed sofosbuvir-containing therapy. Genomic regions encoding the nonstructural protein (NS) 3, NS5A, and NS5B (DAA target regions) were analyzed using subtype-specific primers. Viral subtype distribution was as follows: genotype (G) 1, 62.7%; G3a, 21.4%; G4d, 12.3%; G2, 1.8%; and mixed infections 1.8%. Overall, 88.6% of patients carried at least 1 RAS, and 19% carried RAS at frequencies below 20% in the mutant spectrum. There were no differences in RAS selection between treatments with and without ribavirin. Regardless of the treatment received, each HCV subtype showed specific types of RAS. Of note, no RAS were detected in the target proteins of 18.6% of patients failing treatment, and 30.4% of patients had RAS in proteins that were not targets of the inhibitors they received. HCV patients failing DAA therapy showed a high diversity of RAS. Ribavirin use did not influence the type or number of RAS at failure. The subtype-specific pattern of RAS emergence underscores the importance of accurate HCV subtyping. The frequency of “extra-target” RAS suggests the need for RAS screening in all three DAA target regions