Determination of opipramol in human plasma by high-performance liquid chromatography with photometric detection using a cyanopropyl column

A high-performance liquid chromatographic method is described for the determination of opipramol in human plasma. Opipramol was extracted into tert.-butylmethyl ether, separated on a cyanopropyl silica column and detected at 254 nm. Imipramine was used as internal standard. The limit of quantitation was 250 pg/ml using 1.5 ml plasma. Precision was better than 9%, inaccuracy less than 8%. The assay is more sensitive than previously published methods, and it has been applied to the analysis of plasma samples from a pharmacokinetic study.     

Skeletal troponin I as a marker of exercise-induced muscle damage

Sorichter, Stephan, Johannes Mair, Arnold Koller, WalterGebert, Daniel Rama, Charles Calzolari, Erika Artner-Dworzak, and BerndPuschendorf. Skeletal troponin I as a marker of exercise-inducedmuscle damage. J. Appl. Physiol.83(4): 1076-1082, 1997.The utility of skeletal troponin I (sTnI)as a plasma marker of skeletal muscle damage after exercise wascompared against creatine kinase (CK), myoglobin (Mb), and myosin heavychain (MHC) fragments. These markers were serially measured in normalphysical education teacher trainees after four different exerciseregimens: 20 min of level or downhill (16% decline) running(intensity: 70% maximal O₂uptake), high-force eccentric contractions (70 repetitions), orhigh-force isokinetic concentric contractions of the quadriceps group(40 repetitions). Eccentrically biased exercise (downhill running andeccentric contractions) promoted greater increases in all parameters.The highest plasma concentration were found after downhill running{median peaks: 309 U/l CK concentration ([CK])}, 466 µg/l Mb concentration([Mb]), 1,021 µU/l MHC concentration ([MHC]),and 27.3 µg/l sTnI concentration ([sTnI]). Level running produced a moderate response (median peaks: 178 U/l [CK],98 µg/l [Mb], 501 µU/l [MHC], and 6.6 µg/l [sTnI]), whereas the concentric contraction protocoldid not elicit significant changes in any of the markers assayed. sTnIincreased and peaked in parallel to CK and stayed elevated (>2.2µg/l) for at least 1-2 days after exercise. In contrast to MHC,sTnI is an initial, specific marker of exercise-induced muscle injury,which may be partly explained by their different intracellularcompartmentation with essentially no (MHC <0.1%) or a small solublepool (sTnI: median 3.4%).

     

Role of the tubulin-microtubule system in lymphocyte activation

The role of the tubulin-microtubule system was examined in human peripheral blood leukocytes after activation with phytohemagglutinin (PHA). Soluble tubulin and microtubules were measured with a [(3)H]colchicine-binding assay. It was found that the tubulin content of PHA-activated lymphocytes was consistently increased relative to total protein content after 36 h of culture. There was no increase in the proportion of total tubulin synthesis which was present as microtubules at 36 h. Nevertheless, as a result of increased tubulin synthesis, there was a two-to three-fold increase in total microtubular mass. Colchicine, which disrupts microtubles, was used to assess the role of microtubule assembly in the sequence of events which follow lymphocyte activation, namely lymphokine release, protein synthesis, RNA synthesis, and DNA synthesis. Colchicine consistently inhibited DNA synthesis but did not inhibit release of the lymphokine, osteoclast activating factor (OAF). Protein and RNA syntheses were inhibited much less than DNA synthesis. The fact that some effects of PHA on lymphocytes appear to require intact microtubules and at least one does not suggest that the microtubule dependent step in PHA-stimulated lymphocyte activation occurs at a stage after propagation of the signal from the membrane to the cell interior.     

Kinetics of binding of bovine trypsin-killikrein inhibitor (K unitz) in which the reactive-site peptide bond Lys-15--Ala-16 is cleaved, to alpha-chymotrypsin and beta-trypsin.

Equilibrium measurements of the binding of reactive-site-cleaved (modified) bovine trypsin-kallikrein inhibitor (Kunitz) to alpha-chymotrypsin and beta-trypsin show a stoichiometric 1:1 association with high binding constants. At least in the case of chymotrypsin much evidence is presented that the reaction with modified inhibitor leads to the same complex as the reaction with virgin inhibitor does. The association rate constant of modified inhibitor with chymotrypsin at pH 7, 22.5 degrees C is 15.8 M-1 S-1. This is about 2 x 10(4) times slower than the binding of virgin inhibitor to that enzyme. In the analogous reaction of modified inhibitor with beta-trypsin, however, the association rate constant (1.2 x 10(4) M-1 s-1 at pH 6.9, 22.5 degrees C) is of about the same order of magnitude as it is in the reaction of virgin inhibitor and trypsin. These and analogous phenomena observed in the reactions of virgin and modified soybean trypsin inhibitor (Kunitz) with alpha-chymotrypsin and beta-trypsin suggest that the specificity of both inhibitors to trypsin is strongly reflected in the association rate constants of the modified forms. The dissociation rate constants of the complexes of trypsin-kallikrein inhibitor with chymotrypsin or with trypsin towards the modified inhibitor are estimated to be unmeasurably slow (half-life times of 45 or 1.5 x 10(4) years, respectively).     

Calories Do Not Explain Extension of Life Span by Dietary Restriction in Drosophila

Dietary restriction (DR) extends life span in diverse organisms, including mammals, and common mechanisms may be at work. DR is often known as calorie restriction, because it has been suggested that reduction of calories, rather than of particular nutrients in the diet, mediates extension of life span in rodents. We here demonstrate that extension of life span by DR in Drosophila is not attributable to the reduction in calorie intake. Reduction of either dietary yeast or sugar can reduce mortality and extend life span, but by an amount that is unrelated to the calorie content of the food, and with yeast having a much greater effect per calorie than does sugar. Calorie intake is therefore not the key factor in the reduction of mortality rate by DR in this species.     

Occupancy versus colonization–extinction models for projecting population trends at different spatial scales

Understanding spatiotemporal population trends and their drivers is a key aim in population ecology. We further need to be able to predict how the dynamics and sizes of populations are affected in the long term by changing landscapes and climate. However, predictions of future population trends are sensitive to a range of modeling assumptions. Deadwood‐dependent fungi are an excellent system for testing the performance of different predictive models of sessile species as these species have different rarity and spatial population dynamics, the populations are structured at different spatial scales, and they utilize distinct substrates. We tested how the projected large‐scale occupancies of species with differing landscape‐scale occupancies are affected over the coming century by different modeling assumptions. We compared projections based on occupancy models against colonization–extinction models, conducting the modeling at alternative spatial scales and using fine‐ or coarse‐resolution deadwood data. We also tested effects of key explanatory variables on species occurrence and colonization–extinction dynamics. The hierarchical Bayesian models applied were fitted to an extensive repeated survey of deadwood and fungi at 174 patches. We projected higher occurrence probabilities and more positive trends using the occupancy models compared to the colonization–extinction models, with greater difference for the species with lower occupancy, colonization rate, and colonization:extinction ratio than for the species with higher estimates of these statistics. The magnitude of future increase in occupancy depended strongly on the spatial modeling scale and resource resolution. We encourage using colonization–extinction models over occupancy models, modeling the process at the finest resource‐unit resolution that is utilizable by the species, and conducting projections for the same spatial scale and resource resolution at which the model fitting is conducted. Further, the models applied should include key variables driving the metapopulation dynamics, such as the availability of suitable resource units, habitat quality, and spatial connectivity.