In situ examination of the time-course for secondary mineralization of Haversian bone using synchrotron Fourier transform infrared microspectroscopy.

At the tissue level it is well established that the rate of remodeling is related to the degree of mineralization. However, it is unknown how long it takes for an individual bone structural unit (BSU) to become fully mineralized during secondary mineralization. Using synchrotron Fourier transform infrared microspectroscopy (FTIRM) we examined the time required for newly formed bone matrix to reach a physiological mineralization limit. Twenty-six, four-month old female New Zealand white rabbits were administered up to four different fluorochrome labels at specific time points to evaluate the chemical composition of labeled osteons from the tibial diaphysis that had mineralized for 1, 8, 18, 35, 70, 105, 140, 175, 210, 245, 280, 315, 350, and 385 days. Interstitial bone from 505 day old rabbits was used as a reference value for the physiological limit to which bone mineralizes. Using synchrotron FTIRM, area integrations were carried out on protein (Amide I: 1688-1623 cm(-1)), carbonate (v(2)CO(3)(2-): 905-825 cm(-1)), and phosphate (v(4)PO(4)(3-): 650-500 cm(-1)) IR bands. IR spectral data are presented as ratios of phosphate/protein (overall matrix mineralization) and carbonate/protein. The rate of mineralization of osteonal bone proceeded rapidly between day 1 and 18, reaching 67% of interstitial bone levels. This was followed by a slower, more progressive accumulation of mineral up to day 350. By 350 days the rate of increase plateaued. The ratio of carbonate/protein also increased rapidly during the first 18 days, reaching 73% of interstitial bone levels. The ratio of carbonate/protein plateaued by day 315, reaching levels not significantly different to interstitial bone levels. In conclusion, our data demonstrate that bone accumulates mineral rapidly during the first 18 days (primary mineralization), followed by a more gradual increase in the accumulation of mineral (secondary mineralization) which we found to be completed in 350 days.     

Identification of 96 single nucleotide polymorphisms in eight genes involved in iron metabolism: efficiency of bioinformatic extraction compared with a systematic sequencing approach

Single nucleotide polymorphisms (SNPs) can significantly contribute to the characterization of the genes predisposing to iron overloads or deficiencies. We report an SNP survey of coding and non-coding regions of eight genes involved in iron metabolism, by two successive methods. First, we made use of the public domain sequence data, by using assembled expressed sequence tags, non-redundant sequences, and SNP database screening. We extracted 77 potential SNPs of which only 31 could be further validated by sequencing DNA from 44 unrelated multi-ethnic individuals. Our results indicate that a bioinformatic approach may be effective only in those cases where candidate SNPs are extracted from two different data sources or in cases of experimentally confirmed SNPs. Second, additional systematic sequencing of DNA from 24 unrelated Breton subjects increased the number of SNPs over a total length of 86 kb to 96. The average distance between the SNPs and minor allele frequencies were higher than reported by others authors; this discrepancy may reflect the nature of the genes studied and the ethnic homogeneity of our test population.     

Defects in TLR3 expression and RNase L activation lead to decreased MnSOD expression and insulin resistance in muscle cells of obese people

Obesity is associated with chronic low-grade inflammation and oxidative stress that blunt insulin response in its target tissues, leading to insulin resistance (IR). IR is a characteristic feature of type 2 diabetes. Skeletal muscle is responsible for 75% of total insulin-dependent glucose uptake; consequently, skeletal muscle IR is considered to be the primary defect of systemic IR development. Interestingly, some obese people stay insulin-sensitive and metabolically healthy. With the aim of understanding this difference and identifying the mechanisms responsible for insulin sensitivity maintenance/IR development during obesity, we explored the role of the latent endoribonuclease (RNase L) in skeletal muscle cells. RNase L is a regulator of innate immunity, of double-stranded RNA sensors and of toll-like receptor (TLR) 4 signaling. It is regulated during inflammation by interferons and its activity is dependent on its binding to 2-5A, an oligoadenylate synthesized by oligoadenylate synthetases (OAS). Increased expression of RNase L or downregulation of its inhibitor (RLI) improved insulin response in mouse myogenic C2C12 cells and in primary human myotubes from normal-weight subjects treated with palmitate, a saturated free fatty acid (FFA) known to induce inflammation and oxidative stress via TLR4 activation. While RNase L and RLI levels remained unchanged, OAS level was decreased in primary myotubes from insulin-resistant obese subjects (OB-IR) compared with myotubes from insulin-sensitive obese subjects (OB-IS). TLR3 and mitochondrial manganese superoxide dismutase (MnSOD) were also underexpressed in OB-IR myotubes. Activation of RNase L by 2-5A transfection allowed to restore insulin response, OAS, MnSOD and TLR3 expression in OB-IR myotubes. Due to low expression of OAS, OB-IR myotubes present a defect in RNase L activation and TLR3 regulation. Consequently, MnSOD level is low and insulin sensitivity is reduced. These results support that RNase L activity limits FFA/obesity-induced impairment of insulin response in muscle cells via TLR3 and MnSOD expression.     

Learning to reach by reinforcement learning using a receptive field based function approximation approach with continuous actions

Reinforcement learning methods can be used in robotics applications especially for specific target-oriented problems, for example the reward-based recalibration of goal directed actions. To this end still relatively large and continuous state-action spaces need to be efficiently handled. The goal of this paper is, thus, to develop a novel, rather simple method which uses reinforcement learning with function approximation in conjunction with different reward-strategies for solving such problems. For the testing of our method, we use a four degree-of-freedom reaching problem in 3D-space simulated by a two-joint robot arm system with two DOF each. Function approximation is based on 4D, overlapping kernels (receptive fields) and the state-action space contains about 10,000 of these. Different types of reward structures are being compared, for example, reward-on- touching-only against reward-on-approach. Furthermore, forbidden joint configurations are punished. A continuous action space is used. In spite of a rather large number of states and the continuous action space these reward/punishment strategies allow the system to find a good solution usually within about 20 trials. The efficiency of our method demonstrated in this test scenario suggests that it might be possible to use it on a real robot for problems where mixed rewards can be defined in situations where other types of learning might be difficult. This work was supported by EU-Grant PACO-PLUS.     

Relative Impacts of Elephant and Fire on Large Trees in a Savanna Ecosystem

Elephant and fire are considered to be among the most important agents that can modify the African savanna ecosystem. Although the synergistic relationship between these two key ecological drivers is well documented, it has proved much more difficult to establish the relative effects they have on savanna vegetation structure at a fine-scale over time. In this study, we explore the comparative impacts of fire and elephant on 2,522 individually identified large trees (≥5 m in height) in the Kruger National Park, South Africa. Data were collected from 21 transects first surveyed in April 2006 and resurveyed in November 2008, to determine the relative importance of past damage by these agents on subsequent impacts and mortality. The occurrence of fire or elephant damage in 2006 affected the amount of tree volume subsequently removed by both these agents; elephant removed more tree volume from previously burned trees and the impact of subsequent fire was higher on previously burned or elephant-utilized trees than on undamaged trees. Mortality was also affected by an interaction between previous and recent damage, as the probability of mortality was highest for trees that suffered from fire or elephant utilization after being pushed over. Subsequent fire damage, but not elephant utilization, on debarked trees also increased the probability of mortality. Mortality was twice (4.6% per annum) that of trees progressing into the ≥5 m height class, suggesting an overall decline in large tree density during the 30-month study period. The responses of large trees were species and landscape-specific in terms of sensitivity to elephant and fire impacts, as well as for levels of mortality and progression into the ≥5 m height class. These results emphasize the need for fine-scale site-specific knowledge for effective landscape level understanding of savanna dynamics.