Can altered production of interleukin-1β, interleukin-6, transforming growth factor-β and prostaglandin E2 by isolated human subchondral osteoblasts identify two subgroups of osteoarthritic patients

AbstractObjective To determine the capacity of human subchondral osteoarthritic osteoblasts (Ob) to produce interleukin (IL)-1β, IL-6, transforming growth factor-β (TGF-β) and prostaglandin E2 (PGE2), and determine if a relationship exists between IL-1β, TGF-β, PGE2 and IL-6 production.Methods We measured the abundance of IL-1β, IL-6, TGF-β and PGE2 using very sensitive ELISA in conditioned-media of human primary subchondral Ob from normal individuals and osteoarthritic patients. Selective inhibition of IL-6 or IL-6 receptor signaling was performed to determine its effect on PGE2 production whereas the inhibiton of PGE2 production was performed to determine its effect on IL-6 production. The expression of bone cell markers and urokinase plasminogen activator (uPA) activity was also determined.Results Osteoarthritic Ob produced all these factors with greater variability than normal cells. Interestingly, the production of IL-6 and PGE2 by osteoarthritic Ob separated patients into two subgroups, those whose Ob produced levels comparable to normal (low producers) and those whose Ob produced higher levels (high producers). In those cells classified as high osteoarthritic Ob, PGE2 and IL-6 levels were increased two- to three-fold and five- to six-fold, respectively, compared with normal. In contrast, while using their IL-6 and PGE2 production to separate osteoarthritic Ob into low and high producers, we found that IL-1β levels were similar in normal and all osteoarthritic Ob. Using the same criteria, TGF-β levels were increased in all osteoarthritic Ob compared with normal. Reducing PGE2 synthesis by Indomethacin [a cyclo-oxygenase (COX) -1 and -2 inhibitor] reduced IL-6 levels in all osteoarthritic Ob, whereas Naproxen (a more selective COX-2 inhbitor) reduced PGE2 and IL-6 levels only in the high osteoarthritic group. Conversely, PGE2 addition to osteoarthritic Ob enhanced IL-6 production in both groups. Moreover, the addition of parathyroid hormone also stimulated IL-6 production to similar normal levels in both osteoarthritic groups. In contrast, using an antibody against IL-6 or IL-6 receptors did not reduce PGE2 levels in either group. The evaluation of alkaline phosphatase activity, osteocalcin release, collagen type I and uPA activity in osteoarthritic Ob failed to show any differences between these cells regardless to which subgroup they were assigned.Conclusions These results indicate that IL-6 and PGE2 production by subchondral Ob can discriminate two subgroups of osteoarthritic patients that cannot otherwise be separated by their expression of cell markers, and that endogenous PGE2 levels influence IL-6 synthesis in osteoarthritic Ob. Copyright 2002 OsteoArthritis Research Society International. Published by Elsevier Science Ltd. All rights reserved

Can distributed delays perfectly stabilize dynamical networks?

Signal transmission delays tend to destabilize dynamical networks leading to oscillation, but their dispersion contributes oppositely toward stabilization. We analyze an integro-differential equation that describes the collective dynamics of a neural network with distributed signal delays. With the gamma distributed delays less dispersed than exponential distribution, the system exhibits reentrant phenomena, in which the stability is once lost but then recovered as the mean delay is increased. With delays dispersed more highly than exponential, the system never destabilizes.Comment: 4pages 5figure

Power-law persistence and trends in the atmosphere: A detailed study of long temperature records

We use several variants of the detrended fluctuation analysis to study the appearance of long-term persistence in temperature records, obtained at 95 stations all over the globe. Our results basically confirm earlier studies. We find that the persistence, characterized by the correlation C(s) of temperature variations separated by s days, decays for large s as a power law, C(s) ~ s^(-gamma). For continental stations, including stations along the coastlines, we find that gamma is always close to 0.7. For stations on islands, we find that gamma ranges between 0.3 and 0.7, with a maximum at gamma = 0.4. This is consistent with earlier studies of the persistence in sea surface temperature records where gamma is close to 0.4. In all cases, the exponent gamma does not depend on the distance of the stations to the continental coastlines. By varying the degree of detrending in the fluctuation analysis we obtain also information about trends in the temperature records.Comment: 5 pages, 4 including eps figure

ERUPTION TO DOSE: COUPLING A TEPHRA DISPERSAL MODEL WITHIN A PERFORMANCE ASSESSMENT FRAMEWORK

The tephra dispersal model used by the Yucca Mountain Project (YMP) to evaluate the potential consequences of a volcanic eruption through the waste repository must incorporate simplifications in order to function within a large Monte-Carlo style performance assessment framework. That is, the explicit physics of the conduit, vent, and eruption column processes are abstracted to a 2-D, steady-state advection-dispersion model (ASHPLUME) that can be run quickly over thousands of realizations of the overall system model. Given the continuous development of tephra dispersal modeling techniques in the last few years, we evaluated the adequacy of this simplified model for its intended purpose within the YMP total system performance assessment (TSPA) model. We evaluated uncertainties inherent in model simplifications including (1) instantaneous, steady-state vs. unsteady eruption, which affects column height, (2) constant wind conditions, and (3) power-law distribution of the tephra blanket; comparisons were made to other models and published ash distributions. Spatial statistics are useful for evaluating differences in these model output vs. results using more complex wind, column height, and tephra deposition patterns. However, in order to assess the adequacy of the model for its intended use in TSPA, we evaluated the propagation of these uncertainties through FAR, the YMP ash redistribution model, which utilizes ASHPLUME tephra deposition results to calculate the concentration of nuclear waste-contaminated tephra at a dose-receptor population as a result of sedimentary transport and mixing processes on the landscape. Questions we sought to answer include: (1) what conditions of unsteadiness, wind variability, or departure from simplified tephra distribution result in significant effects on waste concentration (related to dose calculated for the receptor population)? (2) What criteria can be established for the adequacy of a tephra dispersal model within the TSPA framework