Periodontal disease in the Mycenean (1450–1150 BC) population of Aghia Triada, W. Peloponnese, Greece

This study investigates the incidence of periodontitis in a Mycenaean population unearthed at the cemetery of Aghia Triada (West Peloponnese, Greece) during the 1989–1997 field season. The material consists of 172 dry skulls. Demographic parameters of sex and age were difficult to be assigned due to the bad state of preservation of the skeletal material. The ratio was 50 males, 48 females, 65 unidentified and 9 children, and we estimated an average age of 38 years. In this work we used traditional and modern methods to determine the incidence of periodontitis in the archeological human dental bone. We also recorded other dental diseases, such as ante mortem tooth loss, caries and attrition. The results showed that periodontitis has affected 35% of the jaws. A notable percentage of the individuals — 24% — lost three or more teeth during their lifetime and a total 53% of the population had extracted teeth before death. This paper points out that the ancient jaws present a high proportion of ante-mortem tooth loss, attrition and deep caries, whereas the frequency of periodontitis does not seem to differ from that of other prehistoric samples.     

Oligodendrocyte-specific FADD deletion protects mice from autoimmune-mediated demyelination

Apoptosis of oligodendrocytes (ODCs), the myelin-producing glial cells in the CNS, plays a central role in demyelinating diseases such as multiple sclerosis and experimental autoimmune encephalomyelitis (EAE), an animal model of multiple sclerosis. To investigate the mechanism behind ODC apoptosis in EAE, we made use of conditional knockout mice lacking the adaptor protein FADD specifically in ODCs (FADD(ODC-KO)). FADD mediates apoptosis by coupling death receptors with downstream caspase activation. In line with this, ODCs from FADD(ODC-KO) mice were completely resistant to death receptor-induced apoptosis in vitro. In the EAE model, FADD(ODC-KO) mice followed an ameliorated clinical disease course in comparison with control littermates. Lymphocyte and macrophage infiltration into the spinal cord parenchyma was significantly reduced, as was the extent of demyelination and proinflammatory gene expression. Collectively, our data show that FADD is critical for ODC apoptosis and the development of autoimmune demyelinating disease.     

RNA folding with soft constraints: reconciliation of probing data and thermodynamic secondary structure prediction

Thermodynamic folding algorithms and structure probing experiments are commonly used to determine the secondary structure of RNAs. Here we propose a formal framework to reconcile information from both prediction algorithms and probing experiments. The thermodynamic energy parameters are adjusted using 'pseudo-energies' to minimize the discrepancy between prediction and experiment. Our framework differs from related approaches that used pseudo-energies in several key aspects. (i) The energy model is only changed when necessary and no adjustments are made if prediction and experiment are consistent. (ii) Pseudo-energies remain biophysically interpretable and hold positional information where experiment and model disagree. (iii) The whole thermodynamic ensemble of structures is considered thus allowing to reconstruct mixtures of suboptimal structures from seemingly contradicting data. (iv) The noise of the energy model and the experimental data is explicitly modeled leading to an intuitive weighting factor through which the problem can be seen as folding with 'soft' constraints of different strength. We present an efficient algorithm to iteratively calculate pseudo-energies within this framework and demonstrate how this approach can be used in combination with SHAPE chemical probing data to improve secondary structure prediction. We further demonstrate that the pseudo-energies correlate with biophysical effects that are known to affect RNA folding such as chemical nucleotide modifications and protein binding.     

Performance and scalability of discriminative metrics for comparative gene identification in 12 Drosophila genomes

Comparative genomics of multiple related species is a powerful methodology for the discovery of functional genomic elements, and its power should increase with the number of species compared. Here, we use 12 Drosophila genomes to study the power of comparative genomics metrics to distinguish between protein-coding and non-coding regions. First, we study the relative power of different comparative metrics and their relationship to single-species metrics. We find that even relatively simple multi-species metrics robustly outperform advanced single-species metrics, especially for shorter exons (≤240 nt), which are common in animal genomes. Moreover, the two capture largely independent features of protein-coding genes, with different sensitivity/specificity trade-offs, such that their combinations lead to even greater discriminatory power. In addition, we study how discovery power scales with the number and phylogenetic distance of the genomes compared. We find that species at a broad range of distances are comparably effective informants for pairwise comparative gene identification, but that these are surpassed by multi-species comparisons at similar evolutionary divergence. In particular, while pairwise discovery power plateaued at larger distances and never outperformed the most advanced single-species metrics, multi-species comparisons continued to benefit even from the most distant species with no apparent saturation. Last, we find that genes in functional categories typically considered fast-evolving can nonetheless be recovered at very high rates using comparative methods. Our results have implications for comparative genomics analyses in any species, including the human.