The VLT-FLAMES Tarantula Survey XI. A census of the hot luminous stars and their feedback in 30 Doradus

Context. The VLT-FLAMES Tarantula Survey has an extensive view of the copious number of massive stars in the 30 Doradus (30 Dor) star forming region of the Large Magellanic Cloud. These stars play a crucial role in our understanding of the stellar feedback in more distant, unresolved star forming regions. Aims. The first comprehensive census of hot luminous stars in 30 Dor is compiled within a 10 arcmin (150 pc) radius of its central cluster, R136. We investigate the stellar content and spectroscopic completeness of the early type stars. Estimates were made for both the integrated ionising luminosity and stellar wind luminosity. These values were used to re-assess the star formation rate (SFR) of the region and determine the ionising photon escape fraction. Methods. Stars were selected photometrically and combined with the latest spectral classifications. Spectral types were estimated for stars lacking spectroscopy and corrections were made for binary systems, where possible. Stellar calibrations were applied to obtain their physical parameters and wind properties. Their integrated properties were then compared to global observations from ultraviolet (UV) to far-infrared (FIR) imaging as well as the population synthesis code, Starburst99. Results. Our census identified 1145 candidate hot luminous stars within 150 pc of R136 of which >700 were considered to be genuine early type stars and contribute to feedback. We assess the survey to be spectroscopically complete to 85% in the outer regions (>5 pc) but only 35% complete in the region of the R136 cluster, giving a total of 500 hot luminous stars in the census which had spectroscopy. Only 31 were found to be Wolf-Rayet (W-R) or Of/WN stars, but their contribution to the integrated ionising luminosity and wind luminosity was ~ 40% and ~ 50%, respectively. Similarly, stars with M > 100 M (mostly H-rich WN stars) also showed high contributions to the global feedback, ~ 25% in both cases. Such massive stars are not accounted for by the current Starburst99 code, which was found to underestimate the integrated ionising luminosity of R136 by a factor ~ 2 and the wind luminosity by a factor ~ 9. The census inferred a SFR for 30 Dor of 0.073 ± 0.04 M yr . This was generally higher than that obtained from some popular SFR calibrations but still showed good consistency with the far-UV luminosity tracer as well as the combined Hα and mid-infrared tracer, but only after correcting for Hα extinction. The global ionising output was also found to exceed that measured from the associated gas and dust, suggesting that ~6 % of the ionising photons escape the region. Conclusions. When studying the most luminous star forming regions, it is essential to include their most massive stars if one is to determine a reliable energy budget. Photon leakage becomes more likely after including their large contributions to the ionising output. If 30 Dor is typical of other massive star forming regions, estimates of the SFR will be underpredicted if this escape fraction is not accounted for.

Isotretinoin therapy changes the expression of antimicrobial peptides in acne vulgaris

In acne vulgaris, antimicrobial peptides (AMPs) could play a dual role; i.e., protective by acting against Propionibacterium acnes, pro-inflammatory by acting as signalling molecules. The cutaneous expression of 15 different AMPs was investigated in acne patients; furthermore, the impact of isotretinoin therapy on AMP expression was analysed in skin biopsies from 13 patients with acne vulgaris taken before, during and after a 6-month treatment cycle with isotretinoin using quantitative real-time polymerase chain reaction. Cutaneous expression of the AMPs cathelicidin, human β-defensin-2 (HBD-2), lactoferrin, lysozyme, psoriasin (S100A7), koebnerisin (S100A15), and RNase 7 was upregulated in untreated acne vulgaris, whereas α-defensin-1 (HNP-1) was downregulated compared to controls. While relative expression levels of cathelicidin, HBD-2, lactoferrin, psoriasin (S100A7), and koebnerisin (S100A15) decreased during isotretinoin treatment, only those of cathelicidin and koebnerisin returned to normal after 6 months of isotretinoin therapy. The increased expression of lysozyme and RNase 7 remained unaffected by isotretinoin treatment. The levels of granulysin, RANTES (CCL5), perforin, CXCL9, substance P, chromogranin B, and dermcidin were not regulated in untreated acne patients and isotretinoin had no effect on these AMPs. In conclusion, the expression of various AMPs is altered in acne vulgaris. Isotretinoin therapy normalizes the cutaneous production of distinct AMPs while the expression of others is still increased in healing acne. Considering the antimicrobial and pro-inflammatory role of AMPs, these molecules could serve as specific targets for acne therapy and maintenance of clinical remission.

COD and NH4-N Estimation in the Inflow of Wastewater Treatment Plants using Machine Learning Techniques

The in-line measurement of COD and NH4-N in the WWTP inflow is crucial for the timely monitoring of biological wastewater treatment processes and for the development of advanced control strategies for optimized WWTP operation. As a direct measurement of COD and NH4-N requires expensive and high maintenance in-line probes or analyzers, an approach estimating COD and NH4-N based on standard and spectroscopic in-line inflow measurement systems using Machine Learning Techniques is presented in this paper. The results show that COD estimation using Radom Forest Regression with a normalized MSE of 0.3, which is sufficiently accurate for practical applications, can be achieved using only standard in-line measurements. In the case of NH4-N, a good estimation using Partial Least Squares Regression with a normalized MSE of 0.16 is only possible based on a combination of standard and spectroscopic in-line measurements. Furthermore, the comparison of regression and classification methods shows that both methods perform equally well in most cases.

The PREDICTS database: a global database of how local terrestrial biodiversity responds to human impacts

Biodiversity continues to decline in the face of increasing anthropogenic pressures such as habitat destruction, exploitation, pollution and introduction of alien species. Existing global databases of species' threat status or population time series are dominated by charismatic species. The collation of datasets with broad taxonomic and biogeographic extents, and that support computation of a range of biodiversity indicators, is necessary to enable better understanding of historical declines and to project - and avert - future declines. We describe and assess a new database of more than 1.6 million samples from 78 countries representing over 28,000 species, collated from existing spatial comparisons of local-scale biodiversity exposed to different intensities and types of anthropogenic pressures, from terrestrial sites around the world. The database contains measurements taken in 208 (of 814) ecoregions, 13 (of 14) biomes, 25 (of 35) biodiversity hotspots and 16 (of 17) megadiverse countries. The database contains more than 1% of the total number of all species described, and more than 1% of the described species within many taxonomic groups - including flowering plants, gymnosperms, birds, mammals, reptiles, amphibians, beetles, lepidopterans and hymenopterans. The dataset, which is still being added to, is therefore already considerably larger and more representative than those used by previous quantitative models of biodiversity trends and responses. The database is being assembled as part of the PREDICTS project (Projecting Responses of Ecological Diversity In Changing Terrestrial Systems - http://www.predicts.org.uk). We make site-level summary data available alongside this article. The full database will be publicly available in 2015.