Análise imuno-histoquímica das proteínas RANK, RANKL e OPG em dentes de ratos reimplantados

The RANK / RANKL / OPG sy stem plays an important role in bone formation and resorption . This finding has been regarded as one of the m ost important advances in the understanding of bone biology with respect to osteoclastogenesis. The aim of this study was to investigate the expression of RANKL / RANK / OPG markers in reimplanted t eeth of rats, and to observe the relationship between the expression of these markers and to oth and bone resorption. Thirty male Wistar rats (Rattus norvegicus albinos) had their maxillary right incisors extrac ted , and were divided into 2 groups according to the period that the extracted teeth were kept in dry air before reimplantation : G1 (n = 15) - 5 minutes , and G2 (n = 15) - 60 minutes . After reimplantation, teeth were analyzed at intervals of 1, 3 and 7 da ys. After these experimental periods, the animals were euthanized. Longitudinal sections with 5μm thick were obtained and stained with Hematoxylin and Eosin for histological analysis , while 3μm thick sections were subjected to immunohistochemical analysis of OPG , RANK and RANKL. The results showed that the RANK / RANKL / OPG system actively participates in both the repair process, as well as tooth and bone resorption . Extr a - alveolar time of 60 minutes before replantation caused minor expressions of RANKL a nd OPG, not influencing the expression of RANK; RANKL immunostaining showed higher in both groups when compared to other biomarkers, participating in all phases of bone and tooth resorption; RANKL was associated to both osteoclastogenesis and c ell ular proliferation , and was expressed in both groups.

(Table 2, Page 252) Average chemical composition of 11 manganese nodules and crust from the Pacific Ocean

The ability of the hydrated oxides of manganese and iron to adsorb ions from solution (scavenging) is considered in relation to some problems in marine geology, chemistry, and biology. In the ferruginous sediments of the Pacific Ocean, iron oxides are accompanied by titanium, cobalt, and zirconium in amounts proportional to the iron content. Similarly, copper and nickel are linearly related to the manganese content. These observations are explained on the basis of scavenging. An electrochemical theory for the formation of manganese nodules is presented. Marine sediments are classified on the basis of the geosphere in which the solid phases originate. The distribution of certain ionic species in sea water between the solid and aqueous phases is considered on the basis of scavenging and co-ordination compound theory. The concentration of minor elements by members of the marine biosphere is explained either by the direct uptake of the element or by the uptake of iron or manganese oxides with the accompanying scavenged element.

Comparison of available measurements of the absolute air-fluorescence yield and determination of its global average value

Experimental results of the absolute air-fluorescence yield are given very often in different units (photons/MeV or photons/m) and for different wavelength intervals. In this work we present a comparison of available results normalized to its value in photons/MeV for the 337 nm band at 1013 hPa and 293 K. The conversion of photons/m to photons/MeV requires an accurate determination of the energy deposited by the electrons in the field of view of the experimental set-up. We have calculated the energy deposition for each experiment by means of a detailed Monte Carlo simulation and the results have been compared with those assumed or calculated by the authors. As a result, corrections to the reported fluorescence yields are proposed. These corrections improve the compatibility between measurements in such a way that a reliable average value with uncertainty at the level of 5% is obtained.

Evaluating New Policy Instruments of the Corporate Average Fuel Economy Standards : Footprints, Credit Transferring and Credit Trading

Publisher PDF

Evaluating New Policy Instruments of the Corporate Average Fuel Economy Standards : Footprints, Credit Transferring and Credit Trading

Publisher PDF

Beam Angle Optimization for Automated Coplanar IMRT Lung Plans

Purpose: To investigate the effect of incorporating a beam spreading parameter in a beam angle optimization algorithm and to evaluate its efficacy for creating coplanar IMRT lung plans in conjunction with machine learning generated dose objectives.

Methods: Fifteen anonymized patient cases were each re-planned with ten values over the range of the beam spreading parameter, k, and analyzed with a Wilcoxon signed-rank test to determine whether any particular value resulted in significant improvement over the initially treated plan created by a trained dosimetrist. Dose constraints were generated by a machine learning algorithm and kept constant for each case across all k values. Parameters investigated for potential improvement included mean lung dose, V20 lung, V40 heart, 80% conformity index, and 90% conformity index.

Results: With a confidence level of 5%, treatment plans created with this method resulted in significantly better conformity indices. Dose coverage to the PTV was improved by an average of 12% over the initial plans. At the same time, these treatment plans showed no significant difference in mean lung dose, V20 lung, or V40 heart when compared to the initial plans; however, it should be noted that these results could be influenced by the small sample size of patient cases.

Conclusions: The beam angle optimization algorithm, with the inclusion of the beam spreading parameter k, increases the dose conformity of the automatically generated treatment plans over that of the initial plans without adversely affecting the dose to organs at risk. This parameter can be varied according to physician preference in order to control the tradeoff between dose conformity and OAR sparing without compromising the integrity of the plan.

First evidence of altered sensory quality in a shellfish exposed to decreased pH relevant to ocean acidification

Understanding how seafood will be influenced by coming environmental changes such as ocean acidification is a research priority. One major gap in knowledge relates to the fact that many experiments are not considering relevant end points related directly to production (e.g., size, survival) and product quality (e.g., sensory quality) that can have important repercussions for consumers and the seafood market. The aim of this experiment was to compare the survival and sensory quality of the adult northern shrimp (Pandalus borealis) exposed for 3 wk to a temperature at the extreme of its thermal tolerance (11°C) and 2 pH treatments: pH 8.0 (the current average pH at the sampling site) and pH 7.5 (which is out of the current natural variability and relevant to near-future ocean acidification). Results show that decreased pH increased mortality significantly, by 63%. Sensory quality was assessed through semiqualitative scoring by a panel of 30 local connoisseurs. They were asked to rate 4 shrimp (2 from each pH treatment) for 3 parameters: appearance, texture and taste. Decreased pH reduced the score significantly for appearance and taste, but not texture. As a consequence, shrimp maintained in pH8.0 had a 3.4 times increased probability to be scored as the best shrimp on the plate, whereas shrimp from the pH 7.5 treatment had a 2.6 times more chance to be scored as the least desirable shrimp on the plate. These results help to prove the concept that ocean acidification can modulate sensory quality of the northern shrimp P. borealis. More research is now needed to evaluate impacts on other seafood species, socioeconomic consequences, and potential options.

Average chemical composition of lake ores of Finland and North-Eastern Russia extracted in the late nineteen century

According to Solitander C. P., the extraction of lake ore from Eastern Finland lakes considerably rose in the 1870 - 1880 period in relation with the increasing demand from the ironworks being operated in the region. In St. Petersburg, Nicholas Putiloff, a business tycoon and State Minister owned the Haapakosken, Huutokosken and Oravin ironworks which were using 99% of lake ore for their supply. During this period the biggest production came from lake Sysmäjärvi in the Joroinen county with 3676 tonnes at an average concentration of 35.94% Fe, 4.55% Mn, 0.26% P and 0.04% S. The Värtsilä ironworks used the lake ore coming from 49 lakes, the biggest production coming from lake Loitimojärvi with 14535 tonnes of ore with a medium at concentration of 30.8% Fe. Möhkö ironworks took advantage of the 59 lakes, the largest of which was from lake Koitere with 4301 tonnes at 41.3% Fe. The Karttula ironworks were also significant in the consumption of ferromanganese lake ore.

(Table 1) Average sea surface temperature, average sea surface salinity, C37 concentration, palmitic acid concentration, Uk'37, C37/C38 ratio, dD of water, dD of C37 and dD of palmitic acid of water samples from a transect across the Amazon Plume

The stable hydrogen isotope composition of lipid biomarkers, such as alkenones, is a promising new tool for the improvement of palaeosalinity reconstructions. Laboratory studies confirmed the correlation between lipid biomarker dD composition (dDLipid), water dD composition (dDH2O) and salinity; yet there is limited insight into the applicability of this proxy in oceanic environments. To fill this gap, we test the use of the dD composition of alkenones (dDC37) and palmitic acid (dDPA) as salinity proxies using samples of surface suspended material along the distinct salinity gradient induced by the Amazon Plume. Our results indicate a positive correlation between salinity and dDH2O, while the relationship between dDH2O and dDLipid is more complex: dDPAM correlates strongly with dDH2O (r2 = 0.81) and shows a salinity-dependent isotopic fractionation factor. dDC37 only correlates with dDH2O in a small number (n = 8) of samples with alkenone concentrations > 10 ng L**-1, while there is no correlation if all samples are taken into account. These findings are mirrored by alkenone-based temperature reconstructions, which are inaccurate for samples with low alkenone concentrations. Deviations in dDC37 and temperature are likely to be caused by limited haptophyte algae growth due to low salinity and light limitation imposed by the Amazon Plume. Our study confirms the applicability of dDLipid as a salinity proxy in oceanic environments. But it raises a note of caution concerning regions where low alkenone production can be expected due to low salinity and light limitation, for instance, under strong riverine discharge.

(Table 2, Page 270) Average chemical composition of manganese nodules and crust collected at different localities the Pacific Ocean

Considerable regional variations in the chemical composition of manganese nodules from a wide range of the Pacific Ocean have been observed. These variations can be more exactly expressed in terms of inter-element relationships. In particular, Cu-Mn and Cu-Ni associations reveal that Cu content in pelagic nodules increases rapidly in proportion to those of Mn or Ni. In nodules from continental borderland and hemipelagic areas, even if Mn or Ni contents increase, that of Cu increases only slightly. It is suggested that the considerable chemical differences within individual nodules and between nodules from the same site, at a limited pelagic area where there is no marked change in depositional conditions of nodules, are due to the role of hydrolyzable trace elements in the formation of nodules.

IMPROVING THE PERFORMANCE OF DATABASE-CENTRIC APPLICATIONS THROUGH PROGRAM ANALYSIS

Modern software applications are becoming more dependent on database management systems (DBMSs). DBMSs are usually used as black boxes by software developers. For example, Object-Relational Mapping (ORM) is one of the most popular database abstraction approaches that developers use nowadays. Using ORM, objects in Object-Oriented languages are mapped to records in the database, and object manipulations are automatically translated to SQL queries. As a result of such conceptual abstraction, developers do not need deep knowledge of databases; however, all too often this abstraction leads to inefficient and incorrect database access code. Thus, this thesis proposes a series of approaches to improve the performance of database-centric software applications that are implemented using ORM. Our approaches focus on troubleshooting and detecting inefficient (i.e., performance problems) database accesses in the source code, and we rank the detected problems based on their severity. We first conduct an empirical study on the maintenance of ORM code in both open source and industrial applications. We find that ORM performance-related configurations are rarely tuned in practice, and there is a need for tools that can help improve/tune the performance of ORM-based applications. Thus, we propose approaches along two dimensions to help developers improve the performance of ORM-based applications: 1) helping developers write more performant ORM code; and 2) helping developers configure ORM configurations. To provide tooling support to developers, we first propose static analysis approaches to detect performance anti-patterns in the source code. We automatically rank the detected anti-pattern instances according to their performance impacts. Our study finds that by resolving the detected anti-patterns, the application performance can be improved by 34% on average. We then discuss our experience and lessons learned when integrating our anti-pattern detection tool into industrial practice. We hope our experience can help improve the industrial adoption of future research tools. However, as static analysis approaches are prone to false positives and lack runtime information, we also propose dynamic analysis approaches to further help developers improve the performance of their database access code. We propose automated approaches to detect redundant data access anti-patterns in the database access code, and our study finds that resolving such redundant data access anti-patterns can improve application performance by an average of 17%. Finally, we propose an automated approach to tune performance-related ORM configurations using both static and dynamic analysis. Our study shows that our approach can help improve application throughput by 27--138%. Through our case studies on real-world applications, we show that all of our proposed approaches can provide valuable support to developers and help improve application performance significantly.