Adenovirus early gene products may control viral mRNA accumulation and translation in vivo

The mechanisms controlling early adenovirus gene expression in vivo have been studied using inhibitors of protein synthesis. When inhibitors were added shortly before or at the onset of infection, viral mRNA from all early regions was transcribed, spliced and accumulated over a 7 hr period. After longer pretreatment, accumulation of several early mRNAs were suppressed. Addition of inhibitors 1 hr after infection enhanced the accumulation of viral mRNA in the cytoplasm. Translation of early mRNA selected on adenovirus DNA in a cell-free system reflected the amount of viral mRNA present. A viral coded product may therefore control accumulation of viral mRNA.A different pattern emerged when inhibitors of protein synthesis were removed at 5 hr postinfection and cells were pulse-labeled in vivo. If inhibitors were introduced at or before infection, early viral proteins were synthesized only after a lag of 1–3 hr. However, if treatment was introduced 1 hr post-infection, reversion of the protein synthesis block was instantaneous. It appears that protein synthesis inhibitors reveal an in vivo translational block for viral mRNA. This block could be overcome by preinfection with a related virus. Furthermore, no block was observed in a virus-transformed human embryonic kidney cell line (293) which expresses early region 1 of the viral genome. Viral gene product(s) encoded in early region 1 may control translation of early adenovirus messenger RNA in vivo.     

Synchrotron X-ray imaging via ultra-small-angle scattering: principles of quantitative analysis and application in studying bone integration to synthetic grafting materials

Optimized experimental conditions for extracting accurate information at subpixel length scales from analyzer-based X-ray imaging were obtained and applied to investigate bone regeneration by means of synthetic β-TCP grafting materials in a rat calvaria model. The results showed a 30% growth in the particulate size due to bone ongrowth/ingrowth within the critical size defect over a 1-month healing period.     

Identifying essential genes in bacterial metabolic networks with machine learning methods

Background  

Identifying essential genes in bacteria supports to identify potential drug targets and an understanding of minimal requirements for a synthetic cell. However, experimentally assaying the essentiality of their coding genes is resource intensive and not feasible for all bacterial organisms, in particular if they are infective.     

Modelling biome shifts and tree cover change for 2050 in West Africa

Aim Africa is expected to face severe changes in climatic conditions. Our objectives are: (1) to model trends and the extent of future biome shifts that may occur by 2050, (2) to model a trend in tree cover change, while accounting for human impact, and (3) to evaluate uncertainty in future climate projections. Location West Africa. Methods We modelled the potential future spatial distribution of desert, grassland, savanna, deciduous and evergreen forest in West Africa using six bioclimatic models. Future tree cover change was analysed with generalized additive models (GAMs). We used climate data from 17 general circulation models (GCMs) and included human population density and fire intensity to model tree cover. Consensus projections were derived via weighted averages to: (1) reduce inter‐model variability, and (2) describe trends extracted from different GCM projections. Results The strongest predicted effect of climate change was on desert and grasslands, where the bioclimatic envelope of grassland is projected to expand into the desert by an area of 2 million km². While savannas are predicted to contract in the south (by 54 ± 22 × 10⁴ km²), deciduous and evergreen forest biomes are expected to expand (64 ± 13 × 10⁴ km² and 77 ± 26 × 10⁴ km²). However, uncertainty due to different GCMs was particularly high for the grassland and the evergreen biome shift. Increasing tree cover (1–10%) was projected for large parts of Benin, Burkina Faso, Côte d’Ivoire, Ghana and Togo, but a decrease was projected for coastal areas (1–20%). Furthermore, human impact negatively affected tree cover and partly changed the direction of the projected change from increase to decrease. Main conclusions Considering climate change alone, the model results of potential vegetation (biomes) show a ‘greening’ trend by 2050. However, the modelled effects of human impact suggest future forest degradation. Thus, it is essential to consider both climate change and human impact in order to generate realistic future tree cover projections.     

The likelihood of persistent arthritis increases with the level of anti-citrullinated peptide antibody and immunoglobulin M rheumatoid factor: a longitudinal study of 376 patients with very early undifferentiated arthritis

Introduction  

We wanted to assess the importance of the levels of anti-citrullinated peptide antibody (anti-CCP) and immunoglobulin M (IgM) rheumatoid factor (RF) in predicting development of persistent arthritis from undifferentiated arthritis (UA), and to investigate whether there is an added predictive value for persistent arthritis in testing for both anti-CCP and IgM RF.