High specificity of line-immunoassay based algorithms for recent HIV-1 infection independent of viral subtype and stage of disease

ABSTRACT: BACKGROUND: Serologic testing algorithms for recent HIV seroconversion (STARHS) provide important information for HIV surveillance. We have shown that a patient's antibody reaction in a confirmatory line immunoassay (INNO-LIATM HIV I/II Score, Innogenetics) provides information on the duration of infection. Here, we sought to further investigate the diagnostic specificity of various Inno-Lia algorithms and to identify factors affecting it. METHODS: Plasma samples of 714 selected patients of the Swiss HIV Cohort Study infected for longer than 12 months and representing all viral clades and stages of chronic HIV-1 infection were tested blindly by Inno-Lia and classified as either incident (up to 12 m) or older infection by 24 different algorithms. Of the total, 524 patients received HAART, 308 had HIV-1 RNA below 50 copies/mL, and 620 were infected by a HIV-1 non-B clade. Using logistic regression analysis we evaluated factors that might affect the specificity of these algorithms. RESULTS: HIV-1 RNA <50 copies/mL was associated with significantly lower reactivity to all five HIV-1 antigens of the Inno-Lia and impaired specificity of most algorithms. Among 412 patients either untreated or with HIV-1 RNA ≥50 copies/mL despite HAART, the median specificity of the algorithms was 96.5% (range 92.0-100%). The only factor that significantly promoted false-incident results in this group was age, with false-incident results increasing by a few percent per additional year. HIV-1 clade, HIV-1 RNA, CD4 percentage, sex, disease stage, and testing modalities exhibited no significance. Results were similar among 190 untreated patients. CONCLUSIONS: The specificity of most Inno-Lia algorithms was high and not affected by HIV-1 variability, advanced disease and other factors promoting false-recent results in other STARHS. Specificity should be good in any group of untreated HIV-1 patients

TRY plant trait database – enhanced coverage and open access

Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants - determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits - almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Osteoclast formation within a human co-culture system on bone material as an in vitro model for bone remodeling processes

Bone remodeling can be mimicked in vitro by co-culture models. Based on bone cells, such co-cultures help to study synergistic morphological changes and the impact of materials and applied substances. Hence, we examined the formation of osteoclasts on bovine bone materials to prove the bone resorption functionality of the osteoclasts in three different co-culture set-ups using human monocytes (hMCs) and (I) human mesenchymal stem cells (hMSCs), (II) osteogenic differentiated hMSCs (hOBs), and (III) hOBs in addition of soluble monocyte-colony stimulating factor (M-CSF) and cytokine receptor activator of NFκB ligand (RANKL). We detected osteoclast-specific actin morphology, as well as the expression of cathepsin K and CD51/61 in single cells in set-up II and in numerous cells in set-up III. Resorption pits on bone material as characteristic proof of functional osteoclasts were not found in set-up I and II, but we detected such resorption pits in set–up III. We conclude in co-culture models without M-CSF and RANKL that monocytes can differentiate into osteoclasts that show the characteristic actin structures and protein expression. However, to receive functional bone resorbing osteoclasts in vitro, the addition of M-CSF and RANKL is needed. Moreover, we suggest the use of bone or bone-like materials for future studies evaluating osteoclastogenesis