飯塚 成志

Background: Mycobacterium bovis bacillus Calmette Guerin (BCG) vaccine, which has been inoculated to more than one billion people world-wide, has significant effect in preventing tuberculous meningitis and miliary tuberculosis (TB) in neonate and early childhood. However, BCG fails to adequately protect against pulmonary TB and reactivation of latent infections in adults. To overcome this problem, adequate booster is urgently desired in adult who received prior BCG vaccination, and appropriate animal models that substitute human cases would be highly valuable for further experimentation. Findings: The booster effect of the synthesized CpG oligomer (Oligo-B) on aged mice which had been primarily vaccinated with BCG at the age of 4-week old. The specific Th1 type reaction, production of interferon-gamma, in response to TB antigens, purified protein derivatives (PPD) and protection against challenge with Mycobacterium tuberculosis (MTB) H(37)Rv decreased with increasing age and were not observed in 89-week old mice. In order to rejuvenate the Th1 type response against PPD and protection activity against MTB infection, Oligo-B, which is known to augment Th1 responses, was administered as a booster to 81-90-week old mice (late 50's in human equivalent) vaccinated with BCG at 4-week old. The boosting with Oligo-B increased the number of CD4(+)CD44(high) CD62L(high), central memory type T cell. Furthermore, the Oligo-B boosting rejuvenated the ability of mice to protect against infection with MTB H(37)Rv. Conclusions: Th1-adjuvant CpG oligo DNA, such as Oligo-B, may be a promising booster when coupled with BCG priming.

Aims Acceleration and deceleration capacity (AC and DC) for beat-to-beat short-term heart rate dynamics are powerful predictors of mortality after acute myocardial infarction (AMI). We examined if AC and DC for minute-order long-term heart rate dynamics also have independent predictive value. Methods and results We studied 24-hr Hotter electrcardiograms in 708 post-AMI patients who were followed up for up to 30 months thereafter. Acceleration capacity and DC was calculated with the time scales of T (window size defining heart rate) and s (wavelet scale) from 1 to 500 s and compared their prognostic values with conventional measures (AC(conv) and DCconv) that were calculated with (T,s) = [1,2 (beat)]. During the follow-up, 47 patients died. Both increased AC(conv) and decreased DCconv predicted mortality (C statistic, 0.792 and 0.797). Concordantly, sharp peaks of C statistics were observed at (T,s) = [2,7 (sec)] for both increased AC and decreased DC (0.762 and 0.768), but there were larger peaks of C statistics at around [30,60 (sec)] for both (0.783 and 0.796). The C statistic was greater for DC than AC at (30,60) (P = 0.0012). Deceleration capacity at (30,60) was a significant predictor even after adjusted for AC(conv) (P = 0.020) and DCconv (P = 0.028), but the predictive power of AC at (30,60) was no longer significant. Conclusion A decrease in DC for minute-order long-term heart rate dynamics is a strong predictor for post-AMI mortality and the predictive power is independent of AC(conv) and DCconv for beat-to-beat short-term heart rate dynamics.

Background and objectives Nonlinear measures of heart rate variability (HRV) have gained recent interest as powerful risk predictors in various clinical settings. This study examined whether they improve risk stratification in hemodialysis patients. Design, setting, participants, & measurements To assess heart rate turbulence, deceleration capacity, fractal scaling exponent (alpha(1)), and other conventional HRV measures, 281 hemodialysis patients underwent 24-hour electrocardiography between January 2002 and May 2004 and were subsequently followed up. Results During a median 87-month follow-up, 77 patients (27%) died. Age, left ventricular ejection fraction, serum albumin, C-reactive protein, and calcium X phosphate independently predicted mortality. Whereas all nonlinear HRV measures predicted mortality, only decreased scaling exponent alpha(1) remained significant after adjusting for clinical risk factors (hazard ratio per a 0.25 decrement, 1.46; 95% confidence interval [95% CI], 1.16-1.85). The inclusion of alpha(1) into a prediction model composed of clinical risk factors increased the C statistic from 0.84 to 0.87 (P=0.03), with 50.8% (95% CI, 20.2-83.7) continuous net reclassification improvement for 5-year mortality. The predictive power of a1 showed an interaction with age (P=0.02) and was particularly strong in patients aged <70 years (n=208; hazard ratio, 1.87; 95% CI, 1.38-2.53), among whom alpha(1) increased the C statistic from 0.85 to 0.89 (P=0.01), with a 93.1% (95% CI, 59.3-142.0) continuous net reclassification improvement. Conclusions Scaling exponent alpha(1) that reflects fractal organization of short-term HRV improves risk stratification for mortality when added to the prediction model by conventional risk factors in hemodialysis patients, particularly those aged <70 years. Clin J Am Soc Nephrol 7: 1454-1460, 2012. doi: 10.2215/CJN.09430911