Modulation of N-methyl-N-nitrosourea induced mammary tumors in Sprague–Dawley rats by combination of lysine, proline, arginine, ascorbic acid and green tea extract

INTRODUCTION: The limited ability of current treatments to control metastasis and the proposed antitumor properties of specific nutrients prompted us to examine the effect of a specific formulation (nutrient supplement [NS]) of lysine, proline, arginine, ascorbic acid, and green tea extract in vivo on the development of N-methyl-N-nitrosourea (MNU)-induced mammary tumors in rats. METHODS: A single intraperitoneal dose of MNU was injected into each of 20 female Sprague–Dawley rats (aged 50 days) to induce tumors. Two weeks after MNU treatment, a time by which the animals had recovered from MNU-induced toxicity, the rats were divided into two groups. Rats in group 1 (n = 10) were fed Purina chow diet, whereas those in group 2 (n = 10) were fed the same diet supplemented with 0.5% NS. After a further 24 weeks, the rats were killed and tumors were excised and processed. RESULTS: NS reduced the incidence of MNU-induced mammary tumors and the number of tumors by 68.4%, and the tumor burden by 60.5%. The inhibitory effect of NS was also reflected by decreased tumor weight; the tumor weights per rat and per group were decreased by 41% and 78%, respectively. In addition, 30% of the control rats developed ulcerated tumors, in contrast to 10% in the nutrient supplemented rats. CONCLUSION: These findings suggest that the specific formulation of lysine, proline, arginine, ascorbic acid, and green tea extract tested significantly reduces the incidence and growth of MNU-induced mammary tumors, and therefore has strong potential as a useful therapeutic regimen for inhibiting breast cancer development

Micronutrient synergy—a new tool in effective control of metastasis and other key mechanisms of cancer

Consumption of a plant-based diet has been associated with prevention of the development and progression of cancer. We have developed strategies to inhibit cancer development and its spread by targeting common mechanisms used by all types of cancer cells that decrease stability and integrity of connective tissue. Strengthening of collagen and connective tissue can be achieved naturally through the synergistic effects of selected nutrients, such as lysine, proline, ascorbic acid and green tea extract (NM). This micronutrient mixture has exhibited a potent anticancer activity in vivo and in vitro in a few dozen cancer cell lines. Its anti-cancer effects include inhibition of metastasis, tumor growth, matrix metalloproteinase (MMP) secretion, invasion, angiogenesis, and cell growth as well as induction of apoptosis. Many cancers are often diagnosed at later stages, when metastasis has occurred, which standard treatment has been unable to control. Our studies on NM effects on hepatic and pulmonary metastasis demonstrated profound, significant suppression of metastasis in a murine model. Evaluation of effects of NM on xenografts in murine models demonstrated significant reduction in tumor size and tumor burden in all human cancer cell lines tested. In vitro studies demonstrated that NM was very effective in inhibition of cell proliferation (by MTT assay), MMP secretion (by gelatinase zymography), cell invasion (through Matrigel), cell migration (by scratch test), induction of apoptosis (by live green caspase) and induction of pro-apoptotic genes in many diverse cancer cell lines. Furthermore, in vivo and in vitro studies of effects of individual micronutrients compared to their specific combination demonstrated synergistic effects resulting in improved anticancer potency

Green tea consumption and lung cancer risk: the Ohsaki study

We examined the risk of lung cancer in relation to green tea consumption in a population-based cohort study in Japan among 41 440 men and women, aged 40–79 years, who completed a questionnaire in 1994 regarding green tea consumption and other health-related lifestyle factors. During the follow-up period of 7 years (from 1995 to 2001), 302 cases of lung cancer were identified, and the Cox proportional hazards regression model was used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). The multivariable-adjusted HRs of lung cancer incidence for green tea consumption of 1 or 2, 3 or 4, and 5 or more cups/day as compared to less than 1 cup/day were 1.14 (95% CI: 0.80–1.62), 1.18 (95% CI: 0.83–1.66), and 1.17 (95% CI: 0.85–1.61), respectively (P for trend=0.48). This cohort study has found no evidence that green tea consumption is associated with lung cancer

Effect of Database Generation on Damage Consequences’ Assessment Based on Random Forests

Recently, the application of machine learning has been explored to assess the main damage consequences without employing flooding sensors. This method can be the base of a new generation of onboard decision support systems to help the master during the progressive flooding of the ship. In particular, the application of random forests has been found suitable to assess the final fate of the ship and the damaged compartments’ set and estimate the time-to-flood. Random forests have to be trained using a database of precalculated progressive flooding simulations. In the present work, multiple options for database generation were tested and compared: three based on Monte Carlo (MC) sampling based on different probability distributions of the damage parameters and a parametric one. The methods were tested on a barge geometry to highlight the main effects on the damage consequences’ assessment in order to ease the further development of flooding-sensor-agnostic decision support systems for flooding emergencies

Forecasting large explosions at Bezymianny Volcano using thermal satellite data

Large volcanic explosions pose a severe risk to life and cargo by injecting ash into local and international air traffic routes. Prior to exploding, Bezymianny (Kamchatka) commonly shows an increase in lava extrusion rate, which can be detected by satellites as an increase in thermal radiance. Here we present the first method of forecasting explosive eruptions based solely on satellite data. A pattern recognition algorithm using Advanced Very High Resolution Radiometer (AVHRR) data has been developed based on known precursory trends of increasing radiance prior to 19 explosions at Bezymianny Volcano in 1993–2008. The algorithm retrospectively forecasts 89% of the explosions (100% of the explosions that show precursory increases in thermal radiance), with 71% of alerts issued in the 30 days beforehand. The method also provides the probability of an explosion occurring within a given number of days after an alert is triggered by the algorithm. When applied to independent data, the algorithm correctly provided alerts before the 16 December 2009, 31 May 2010 and 13 April 2011 explosions

Brix refractometry of colostrum from primiparous dairy cows and new-born calf blood serum in the evaluation of failure of passive transfer

Failure of passive transfer (FPT) of immunoglobulins (IgG) is associated with increased morbidity and mortality of calves. In this study we evaluated the digital Brix refractometer usefulness for the assessment of FPT. A number of 16 colostrum samples from the fi rst milking (2-3h post-partum) of Holstein-Friesian dairy heifers and 29 blood sera of 3-6 days old calves were analyzed with a digital Brix refractometer. Total proteins were determined by the biuret reaction. Colostral IgG were determined by radial immunodiffusion (RID), and colostral whey and blood serum ? globulin (composed almost entirely of IgG) were determined by agarose protein gel electrophoresis (APE) and densitometry. Colostral % Brix score was 25.5±3.4%. Concentrations of colostrum IgG and colostral whey ? globulin were 130±33 g/L and 100±24 g/L respectively. The concentration of total proteins in colostral whey was 134±30 g/L. The correlations between Brix values and the concentrations of IgG determined with RID and the concentrations of ? globulin determined with APE were positive and highly signifi cant (P<0.001 and P<0.01). The concentration of serum proteins of new-born calves was 57.75±11.8 g/L, the concentration of ? globulin was 14.4±7.8 g/L, and the Brix score was 8.6±1.0%. FPT (serum ? globulin<10 g/L) was detected in 34.5% (10/29) calves. Brix score correlated with the concentration of blood serum ? globulins in all examined calves. The results have confi rmed that digital Brix refractometry allows the producers to use this technique in order to estimate colostral and calf serum IgG, thereby monitoring both colostrum quality and success of passive transfer