Trypsin IV or mesotrypsin and p23 cleave protease-activated receptors 1 and 2 to induce inflammation and hyperalgesia

Although principally produced by the pancreas to degrade dietary proteins in the intestine, trypsins are also expressed in the nervous system and in epithelial tissues, where they have diverse actions that could be mediated by protease-activated receptors (PARs). We examined the biological actions of human trypsin IV (or mesotrypsin) and rat p23, inhibitor-resistant forms of trypsin. The zymogens trypsinogen IV and pro-p23 were expressed in Escherichia coli and purified to apparent homogeneity. Enteropeptidase cleaved both zymogens, liberating active trypsin IV and p23, which were resistant to soybean trypsin inhibitor and aprotinin. Trypsin IV cleaved N-terminal fragments of PAR(1), PAR(2), and PAR(4) at sites that would expose the tethered ligand (PAR(1) = PAR(4) > PAR(2)). Trypsin IV increased [Ca(2+)](i) in transfected cells expressing human PAR(1) and PAR(2) with similar potencies (PAR(1), 0.5 microm; PAR(2), 0.6 microm). p23 also cleaved fragments of PAR(1) and PAR(2) and signaled to cells expressing these receptors. Trypsin IV and p23 increased [Ca(2+)](i) in rat dorsal root ganglion neurons that responded to capsaicin and which thus mediate neurogenic inflammation and nociception. Intraplantar injection of trypsin IV and p23 in mice induced edema and granulocyte infiltration, which were not observed in PAR (-/-)(1)(trypsin IV) and PAR (-/-)(2) (trypsin IV and p23) mice. Trypsin IV and p23 caused thermal hyperalgesia and mechanical allodynia and hyperalgesia in mice, and these effects were absent in PAR (-/-)(2) mice but maintained in PAR (-/-)(1) mice. Thus, trypsin IV and p23 are inhibitor-resistant trypsins that can cleave and activate PARs, causing PAR(1)- and PAR(2)-dependent inflammation and PAR(2)-dependent hyperalgesia.

Peroxidative bromination and oxygenation of organic compounds: synthesis, X-ray crystal structure and catalytic implications of mononuclear and binuclear oxovanadium(V) complexes containing Schiffbase ligands

Treatment of of (R,R)-N,N-salicylidene cyclohexane 1,2-diamine(H(2)L(1)) in methanol with aqueous NH(4)VO(3) solution in perchloric acid medium affords the mononuclear oxovanadium(V) complex [VOL(1)(MeOH)]-ClO(4) (1) as deep blue solid while the treatment of same solution of (R,R)-N,N-salicylidene cyclohexane 1,2-diamine(H(2)L(1)) with aqueous solution of VOSO(4) leads to the formation of di-(mu-oxo) bridged vanadium(V) complex [VO(2)L(2)](2) (2) as green solid where HL(2) = (R,R)-N-salicylidene cyclohexane 1,2-diamine. The ligand HL(2) is generated in situ by the hydrolysis of one of the imine bonds of HL(1) ligand during the course of formation of complex [VO(2)L(2)](2) (2). Both the compounds have been characterized by single crystal X-ray diffraction as well as spectroscopic methods. Compounds 1 and 2 are to act as catalyst for the catalytic bromide oxidation and C-H bond oxidation in presence of hydrogen peroxide. The representative substrates 2,4-dimethoxy benzoic acid and para-hydroxy benzoic acids are brominated in presence of H(2)O(2) and KBr in acid medium using the above compounds as catalyst. The complexes are also used as catalyst for C-H bond activation of the representative hydrocarbons toluene, ethylbenzene and cyclohexane where hydrogen peroxide acts as terminal oxidant. The yield percentage and turnover number are also quite good for the above catalytic reaction. The oxidized products of hydrocarbons have been characterized by GC Analysis while the brominated products have been characterized by (1)H NMR spectroscopic studies.

The Joint UK Land Environment Simulator (JULES), model description – part 1: energy and water fluxes

This manuscript describes the energy and water components of a new community land surface model called the Joint UK Land Environment Simulator (JULES). This is developed from the Met Office Surface Exchange Scheme (MOSES). It can be used as a stand alone land surface model driven by observed forcing data, or coupled to an atmospheric global circulation model. The JULES model has been coupled to the Met Office Unified Model (UM) and as such provides a unique opportunity for the research community to contribute their research to improve both world-leading operational weather forecasting and climate change prediction systems. In addition JULES, and its forerunner MOSES, have been the basis for a number of very high-profile papers concerning the land-surface and climate over the last decade. JULES has a modular structure aligned to physical processes, providing the basis for a flexible modelling platform.

The potential of 1 h refractivity changes from an operational C-band magnetron-based radar for numerical weather prediction validation and data assimilation

Refractivity changes (ΔN) derived from radar ground clutter returns serve as a proxy for near-surface humidity changes (1 N unit ≡ 1% relative humidity at 20 °C). Previous studies have indicated that better humidity observations should improve forecasts of convection initiation. A preliminary assessment of the potential of refractivity retrievals from an operational magnetron-based C-band radar is presented. The increased phase noise at shorter wavelengths, exacerbated by the unknown position of the target within the 300 m gate, make it difficult to obtain absolute refractivity values, so we consider the information in 1 h changes. These have been derived to a range of 30 km with a spatial resolution of ∼4 km; the consistency of the individual estimates (within each 4 km × 4 km area) indicates that ΔN errors are about 1 N unit, in agreement with in situ observations. Measurements from an instrumented tower on summer days show that the 1 h refractivity changes up to a height of 100 m remain well correlated with near-surface values. The analysis of refractivity as represented in the operational Met Office Unified Model at 1.5, 4 and 12 km grid lengths demonstrates that, as model resolution increases, the spatial scales of the refractivity structures improve. It is shown that the magnitude of refractivity changes is progressively underestimated at larger grid lengths during summer. However, the daily time series of 1 h refractivity changes reveal that, whereas the radar-derived values are very well correlated with the in situ observations, the high-resolution model runs have little skill in getting the right values of ΔN in the right place at the right time. This suggests that the assimilation of these radar refractivity observations could benefit forecasts of the initiation of convection.

Fat composition of organic and conventional retail milk in northeast England

This study of UK retail milk identified highly significant variations in fat composition. The survey, conducted over 2 yr replicating summer and winter, sampled 22 brands, 10 of which indicated organic production systems. Results corroborate earlier farm-based findings considering fat composition of milk produced under conventional and organic management. Organic milk had higher concentrations of beneficial fatty acids (FA) than conventional milk, including total polyunsaturated fatty acids (PUFA; 39.4 vs. 31.8 g/kg of total FA), conjugated linoleic acid cis-9,trans-11 (CLA9; 7.4 v 5.6 g/kg of FA), and α-linolenic acid (α-LN; 6.9 vs. 4.4 g/kg of FA). As expected, purchase season had a strong effect on fat composition: compared with milk purchased in winter, summer milk had a lower concentration of saturated fatty acids (682 vs. 725 g/kg of FA) and higher concentrations of PUFA (37.6 vs. 32.8 g/kg of FA), CLA9 (8.1 vs. 4.7 g/kg of FA), and α-LN (6.5 vs. 4.6 g/kg of FA). Differences identified between sampling years were more surprising: compared with that in yr 2, milk purchased in year 1 had higher concentrations of PUFA (37.5 vs. 32.9 g/kg of FA), α-LN (6.0 vs. 5.1 g/kg of FA), and linoleic acid (19.9 vs. 17.5 g/kg of FA) and lower concentrations of C16:0 and C14:0 (332 vs. 357 and 110 vs. 118 g/kg of FA, respectively). Strong interactions were identified between management and season as well as between season and year of the study. As in the earlier farm studies, differences in fat composition between systems were greater for summer compared with winter milk. Large between-year differences may be due to changes in weather influencing milk composition through forage availability, quality, and intake. If climate change predictions materialize, both forage and dairy management may have to adapt to maintain current milk quality. Considerable variation existed in milk fat composition between brands.