Index of cardiac-electrophysiological balance in relapsing-remitting multiple sclerosis patients treated with fingolimod.

BACKGROUND: Fingolimod is indicated for the treatment of relapsing-remitting multiple sclerosis (RRMS) and also targets cardiovascular system due to receptors on cardiomyocytes. Results of previous studies are controversial for the effect of fingolimod in terms of ventricular arrhythmias. Index of cardio-electrophysiological balance (iCEB) is a risk marker for predicting malignant ventricular arrhythmia. There is no evidence on the effect of fingolimod on iCEB in patients with relapsing-remitting multiple sclerosis (RRMS). The aim of this study was to evaluate iCEB in patients with RRMS treated with fingolimod . METHODS: A total of 86 patients with RRMS treated with fingolimod were included in the study. All patients underwent a standard 12-lead surface electrocardiogram at initiation of treatment and 6 h after treatment. Heart rate, RR interval, QRS duration, QT, QTc (heart rate corrected QT), T wave peak-to-end (Tp-e) interval, Tp-e/QT, Tp-e/QTc, iCEB (QT/QRS) and iCEBc (QTc/QRS) ratios were calculated from the electrocardiogram. QT correction for heart rate was performed using both the Bazett and Fridericia formulas. Pre-treatment and post-treatment values were compared. RESULTS: Heart rate was significantly lower after fingolimod treatment (p< 0.001). While the post-treatment values of RR and QT intervals were significantly longer (p< 0.001) and post-treatment iCEB was higher (median [Q1-Q3], 4.23 [3.95-4.50] vs 4.53 [4.18-5.14]; p< 0.001), it was found that there was no statistically significant change in iCEB and other study parameters derived using QT after correcting for heart rate using both of two formulas. CONCLUSIONS: In this study, it was found that fingolimod did not statistically significantly change any of the heart rate-corrected ventricular repolarization parameters, including iCEBc, and it is safe in terms of ventricular arrhythmia.

Receptor modeling for elemental source contributions to fine aerosols in New York State.

Fine atmospheric particulate material was collected at five sites in upstate New York and analyzed for its trace element composition by instrumental neutron activation analysis. Of the 3700 daily samples collected over a 2-yr period, 1459 were analyzed for 39 elements, providing a large and detailed data set. Factor analysis (FA) was used to identify potential pollution sources or source regions and to construct inorganic source profiles for each. Following FA, the method of absolute factor scores-multiple linear regression was used to estimate the absolute elemental contribution of each of the identified sources. Factor analysis identified nine sources impacting the sampling region. Seven of these were found to be present in varying degrees among of the sampling sites. The other two sources had more localized impacts and were observed at only one of the sites each. Regional sources (such as the midwestern United States and eastern Canada) and crustal/soil material accounted for the greatest amount of the trace elements measured in the collected material.

Measurements of SO2, NO X and SPM in an industrial area at the Aegean coast of Turkey.

Data from continuous measurements of SO2 NO x , suspended particulate matter (SPM) and meteorological parameters at seven sites around a highly industrialized region in the Aegean coast of Turkey, between July 15, 1991 to July 31, 1992 were used to evaluate spatial and temporal variations of air quality parameters. Low annual averages and insignificant differences between day and night concentrations were observed at stations far from sources. At stations close to sources, annual average concentrations were high and diurnal patterns were significant. Annual average SO2 and SPM concentrations in all stations used the 'Krigging' technique to assess the impact of industries on air quality in the surrounding airshed. Results have demonstrated that Turkish air quality standards for SO2 were exceeded in a circle with a radius of 4 km and which was centered on the petrochemical complex and refinery. Similarly, standards for SPM were exceeded in a circle with a radius of 1.2 km and which was centered on the ironwork plants. Both SO2 and SPM showed well defined diurnal variations, particularly in stations close to sources. The SO2 concentrations showed a maximum during day-time, while SPM concentrations peaked after midnight. Although annual average SO2 and SPM concentrations were highly variable depending on distances between stations and sources, background concentrations of the same pollutants, calculated by stripping episodes from data, did not change significantly from one station to another. Long range transport and resuspension of local soil were suggested as sources of background SO2 and SPM, respectively. The difference between observed and background concentrations of SO2 and SPM in each station was related to the impact of industries on air quality at that particular site.