Regional climate model simulations for Europe at 6 and 0.2 k BP: sensitivity to changes in anthropogenic deforestation

This study aims to evaluate the direct effects of anthropogenic deforestation on simulated climate at two contrasting periods in the Holocene, ~6 and ~0.2 k BP in Europe. We apply We apply the Rossby Centre regional climate model RCA3, a regional climate model with 50 km spatial resolution, for both time periods, considering three alternative descriptions of the past vegetation: (i) potential natural vegetation (V) simulated by the dynamic vegetation model LPJ-GUESS, (ii) potential vegetation with anthropogenic land use (deforestation) from the HYDE3.1 (History Database of the Global Environment) scenario (V + H3.1), and (iii) potential vegetation with anthropogenic land use from the KK10 scenario (V + KK10). The climate model results show that the simulated effects of deforestation depend on both local/regional climate and vegetation characteristics. At ~6 k BP the extent of simulated deforestation in Europe is generally small, but there are areas where deforestation is large enough to produce significant differences in summer temperatures of 0.5–1 °C. At ~0.2 k BP, extensive deforestation, particularly according to the KK10 model, leads to significant temperature differences in large parts of Europe in both winter and summer. In winter, deforestation leads to lower temperatures because of the differences in albedo between forested and unforested areas, particularly in the snow-covered regions. In summer, deforestation leads to higher temperatures in central and eastern Europe because evapotranspiration from unforested areas is lower than from forests. Summer evaporation is already limited in the southernmost parts of Europe under potential vegetation conditions and, therefore, cannot become much lower. Accordingly, the albedo effect dominates in southern Europe also in summer, which implies that deforestation causes a decrease in temperatures. Differences in summer temperature due to deforestation range from −1 °C in south-western Europe to +1 °C in eastern Europe. The choice of anthropogenic land-cover scenario has a significant influence on the simulated climate, but uncertainties in palaeoclimate proxy data for the two time periods do not allow for a definitive discrimination among climate model results.

Observation of Associated Near-Side and Away-Side Long-Range Correlations in √sNN=5.02 TeV Proton-Lead Collisions with the ATLAS Detector

Two-particle correlations in relative azimuthal angle (Delta phi) and pseudorapidity (Delta eta) are measured in root S-NN = 5.02 TeV p + Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1 mu b(-1) of data as a function of transverse momentum (p(T)) and the transverse energy (Sigma E-T(Pb)) summed over 3.1 < eta < 4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2 < vertical bar Delta eta vertical bar < 5) "near-side" (Delta phi similar to 0) correlation that grows rapidly with increasing Sigma E-T(Pb). A long-range "away-side" (Delta phi similar to pi) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small Sigma E-T(Pb), is found to match the near-side correlation in magnitude, shape (in Delta eta and Delta phi) and Sigma E-T(Pb) dependence. The resultant Delta phi correlation is approximately symmetric about pi/2, and is consistent with a dominant cos2 Delta phi modulation for all Sigma E-T(Pb) ranges and particle p(T).

Real-time quantitative broad-range PCR assay for detection of the 16S rRNA gene followed by sequencing for species identification

Here we determined the analytical sensitivities of broad-range real-time PCR-based assays employing one of three different genomic DNA extraction protocols in combination with one of three different primer pairs targeting the 16S rRNA gene to detect a panel of 22 bacterial species. DNA extraction protocol III, using lysozyme, lysostaphin, and proteinase K, followed by PCR with the primer pair Bak11W/Bak2, giving amplicons of 796 bp in length, showed the best overall sensitivity, detecting DNA of 82% of the strains investigated at concentrations of < or =10(2) CFU in water per reaction. DNA extraction protocols I and II, using less enzyme treatment, combined with other primer pairs giving shorter amplicons of 466 bp and 342 or 346 bp, respectively, were slightly more sensitive for the detection of gram-negative but less sensitive for the detection of gram-positive bacteria. The obstacle of detecting background DNA in blood samples spiked with bacteria was circumvented by introducing a broad-range hybridization probe, and this preserved the minimal detection limits observed in samples devoid of blood. Finally, sequencing of the amplicons generated using the primer pair Bak11W/Bak2 allowed species identification of the detected bacterial DNA. Thus, broad-spectrum PCR targeting the 16S rRNA gene in the quantitative real-time format can achieve an analytical sensitivity of 1 to 10 CFU per reaction in water, avoid detection of background DNA with the introduction of a broad-range probe, and generate amplicons that allow species identification of the detected bacterial DNA by sequencing. These prerequisites are important for its application to blood-containing patient samples.

Highly potent 4-amino-indolo[2,3-c]azepin-3-one-containing somatostatin mimetics with a range of sst receptor selectivities

The synthesis, biological evaluation, and conformational analysis of 4-amino-indolo[2,3-c]azepin-3-one (Aia)-containing SRIF mimetics are reported. Different subtype selectivities are observed depending on the N- and C-terminal substituents of the D-Aia-Lys dipeptide mimetic. An sst(5)-selective analogue with subnanomolar binding affinity was obtained that is the most potent agonist reported to date. A nonselective mimetic with high potency was also identified. This study allows a better definition of the bioactive conformation of the essential D-Trp side chain in the somatostatin pharmacophore.

The dust environment of comet 67P/Churyumov-Gerasimenko from Rosetta OSIRIS and VLT observations in the 4.5 to 2.9 AU heliocentric distance range inbound

Context. The ESA Rosetta spacecraft, currently orbiting around cornet 67P/Churyumov-Gerasimenko, has already provided in situ measurements of the dust grain properties from several instruments, particularly OSIRIS and GIADA. We propose adding value to those measurements by combining them with ground-based observations of the dust tail to monitor the overall, time-dependent dust-production rate and size distribution. Aims. To constrain the dust grain properties, we take Rosetta OSIRIS and GIADA results into account, and combine OSIRIS data during the approach phase (from late April to early June 2014) with a large data set of ground-based images that were acquired with the ESO Very Large Telescope (VLT) from February to November 2014. Methods. A Monte Carlo dust tail code, which has already been used to characterise the dust environments of several comets and active asteroids, has been applied to retrieve the dust parameters. Key properties of the grains (density, velocity, and size distribution) were obtained from. Rosetta observations: these parameters were used as input of the code to considerably reduce the number of free parameters. In this way, the overall dust mass-loss rate and its dependence on the heliocentric distance could be obtained accurately. Results. The dust parameters derived from the inner coma measurements by OSIRIS and GIADA and from distant imaging using VLT data are consistent, except for the power index of the size-distribution function, which is alpha = -3, instead of alpha = -2, for grains smaller than 1 mm. This is possibly linked to the presence of fluffy aggregates in the coma. The onset of cometary activity occurs at approximately 4.3 AU, with a dust production rate of 0.5 kg/s, increasing up to 15 kg/s at 2.9 AU. This implies a dust-to-gas mass ratio varying between 3.8 and 6.5 for the best-fit model when combined with water-production rates from the MIRO experiment.