Dietary fat modifies the in vivo mutagenicity of some food-borne carcinogens

Female BALB/c mice were fed a low fat diet (1% safflower oil, by weight) or one supplemented with 25% (by weight) of beef fat or olive oil. The abilities of these diets to modify the in vitro and in vivo hepatic conversion of the dietary carcinogens aflatoxin B1, 2-amino-3, 4-dimethylimidazo[4,5-f]quinoline (MeIQ) and 3-amino-1-methyl-5H-pyrido[4,3-b]indole (Trp-P-2) to bacterial mutagens was evaluated. Dietary olive oil appeared to increase the metabolism of both MeIQ and Trp-P-2 to bacterial mutagens in vivo using the intrasanguineous host-mediated assay. Feeding mice either of the high-fat diets increased hepatic conversion of these two compounds to bacterial mutagens in vitro. Dietary fat had no effect on the metabolism of aflatoxin B1. Subsequent experiments suggested that the in vivo effects of dietary olive oil on MeIQ and Trp-P-2 mutagenesis were due to the induction of hepatic enzyme activities rather than to increased rates of uptake of the carcinogen from the gut-lumen.     

Interactions among oscillatory pathways in NF-kappa B signaling

Background  

Sustained stimulation with tumour necrosis factor alpha (TNF-alpha) induces substantial oscillations—observed at both the single cell and population levels—in the nuclear factor kappa B (NF-kappa B) system. Although the mechanism has not yet been elucidated fully, a core system has been identified consisting of a negative feedback loop involving NF-kappa B (RelA:p50 hetero-dimer) and its inhibitor I-kappa B-alpha. Many authors have suggested that this core oscillator should couple to other oscillatory pathways.     

Physiological determinants of three-kilometer running performance in experienced triathletes

The present investigation examined the physiological parameters that contribute to 3-km running performance. Following 2 familiarization sessions, 16 experienced male triathletes (Vo(2)max = 55.7 +/- 4.9 ml.kg(-1).min(-1), age = 31.3 +/- 11.7 years) performed a 3-km time trial (3kmTT) and were assessed for selected physiological and anthropometrical characteristics. Stepwise multiple regression and correlation analysis was used to determine the variables that significantly related to 3kmTT. The analysis revealed that 82.3% of the adjusted variance in 3kmTT performance could be explained by peak treadmill running velocity during a Vo(2)max test (Vmax) alone. The addition of the running velocity at lactate threshold (LT(vel)) and peak lactate concentration ([BLa(-)](peak)) to the prediction equation allowed for 93.6% of the adjusted variance in 3kmTT to be predicted (Y = -13.64 Vmax - 25.61 LT(vel) - 5.40 [BLa(-)](peak) + 1358.5). Correlation analysis revealed that Vmax (r = -0.91), LT(vel) (r = -0.90), and Vo(2)max (r = -0.80) were significantly related to running performance. These results show that Vmax was the single best predictor of 3-km running performance in experienced male triathletes and that both aerobic and anaerobic abilities are related to improved 3kmTT performance. Since the assessment of Vmax is relatively simple to implement, we suggest that determining Vmax may be a practical method for monitoring performance changes in short-term endurance running events.