Astrophysics in 2006

The fastest pulsar and the slowest nova; the oldest galaxies and the youngest stars; the weirdest life forms and the commonest dwarfs; the highest energy particles and the lowest energy photons. These were some of the extremes of Astrophysics 2006. We attempt also to bring you updates on things of which there is currently only one (habitable planets, the Sun, and the universe) and others of which there are always many, like meteors and molecules, black holes and binaries.Comment: 244 pages, no figure

Terminus-driven retreat of a major southwest Greenland tidewater glacier during the early 19th century : insights from glacier reconstructions and numerical modelling

Peer reviewedPublisher PD

Dansk i Amerika: Status og perspektiv

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A bioinformatic approach to identify new potential resistance relevant amino acid substitutions (AAS) in HIV-1 protease (H1P)

Background: Predicting potential drug resistance mutations are important when evaluating protein-drug interactions of potential new antiviral drugs. Here we used evolutionary data from the Retroviral Aspartyl Protease (RVP) family (PF00077, 54135 sequences) to estimate plausible PI resistant-associated AAS within the H1P. Methods: Using a Hidden Markov Model (HMM) of the RVP family probabilities were extracted for each possible AAS limited to the 38 positions reported in the IAS drug resistance listing for H1P (December 2008 version). The HMM is a dynamic Bayesian network, modeling sequences of amino acids. The HMM is based on curated and representative sequences from the RVP family. Results: Theoretically 760 AAS (20 × 38) are possible for the 38 evaluated positions within the H1P. Of these, the RVP-HMM detected a total of 229 AAS (30.1%) with a probability above 1/20 (0.05). Of the 229 AAS, 51 (70%) were among the 73 AAS included in the IAS listing as PI-resistant mutations, leaving 178 AAS with P > 0.05 as evolutionary plausible. Conclusion: Based on exploration of the RVP family by HMM, 70% of the established PI-resistant associated AAS could be predicted to occur. Additional 178 AAS was identified as evolutionary plausible and potentially could allow for drug-resistance. In conclusion, we provide a probability landscape of plausible/unfavorable AAS based on inherited structure through evolution and genetic distance, which could prove useful for future drug design

Missing sea level rise in southeastern Greenland during and since the Little Ice Age

The Greenland Ice Sheet has been losing mass at an accelerating rate over the past 2 decades. Understanding ice mass and glacier changes during the preceding several hundred years prior to geodetic measurements is more difficult because evidence of past ice extent in many places was later overridden. Salt marshes provide the only continuous records of relative sea level (RSL) from close to the Greenland Ice Sheet that span the period of time during and since the Little Ice Age (LIA) and can be used to reconstruct ice mass gain and loss over recent centuries. Salt marsh sediments collected at the mouth of Dronning Marie Dal, close to the Greenland Ice Sheet margin in southeastern Greenland, record RSL changes over the past ca. 300 years through changing sediment and diatom stratigraphy. These RSL changes record a combination of processes that are dominated by local and regional changes in Greenland Ice Sheet mass balance during this critical period that spans the maximum of the LIA and 20th-century warming. In the early part of the record (1725–1762 CE) the rate of RSL rise is higher than reconstructed from the closest isolation basin at Timmiarmiut, but between 1762 and 1880 CE the RSL rate is within the error range of the rate of RSL change recorded in the isolation basin. RSL begins to slowly fall around 1880 CE, with a total amount of RSL fall of 0.09±0.1 m in the last 140 years. Modelled RSL, which takes into account contributions from post-LIA Greenland Ice Sheet glacio-isostatic adjustment (GIA), ongoing deglacial GIA, the global non-ice sheet glacial melt fingerprint, contributions from thermosteric effects, the Antarctic mass loss sea level fingerprint and terrestrial water storage, overpredicts the amount of RSL fall since the end of the LIA by at least 0.5 m. The GIA signal caused by post-LIA Greenland Ice Sheet mass loss is by far the largest contributor to this modelled RSL, and error in its calculation has a large impact on RSL predictions at Dronning Marie Dal. We cannot reconcile the modelled RSL and the salt marsh observations, even when moving the termination of the LIA to 1700 CE and reducing the post-LIA Greenland mass loss signal by 30 %, and a “budget residual” of  mm yr−1 since the end of the LIA remains unexplained. This new RSL record backs up other studies that suggest that there are significant regional differences in the timing and magnitude of the response of the Greenland Ice Sheet to the climate shift from the LIA into the 20th century