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

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

1323-1333

Abstract. MMP-2 and MMP-9 secretion is elevated in several types of human cancers and their elevated expression has been associated with poor prognosis. Expression of MMPs is highly regulated by cytokines and signal transducation pathways, including those activated by phorbol 12-myristate 13-acetate (PMA). The aim of this study was to examine the effect of PMA on MMP-2 and MMP-9 secretion in 42 different human cancer cell lines, selected on the basis of their organ malignancies. They were cultured in the recommended media supplemented with 10% FBS and antibiotics in 24-well tissue culture plates. At near confluence, the cells were washed with PBS, 0.5 ml of medium was added, and the cultures were incubated. Parallel sets of cultures were also treated with PMA for induction of enzymes. After 24 h the media were collected and MMP-2 and MMP-9 levels were assayed by gelatinase zymography. Based on MMP-2 and MMP-9 secretion without and with PMA treatment, the various human cancer cell lines fell into one of two major groups. The first group characterized by low basal MMP-9 secretion fell into three different categories of susceptibility to PMA induction of MMP-9 expression: resistant, moderately susceptible and highly susceptible. High basal MMP-9 levels responsive to PMA induction characterized the second group. Most cancer cell lines examined exhibited basal levels of MMP-2, MMP-9 or both. MMP-2 secretion was not induced by PMA in any of the cancer cells examined

Right Scaling for Right Pricing: A Case Study on Total Cost of Ownership Measurement for Cloud Migration

Cloud computing promises traditional enterprises and independent software vendors a myriad of advantages over on-premise installations including cost, operational and organizational efficiencies. The decision to migrate software configured for on-premise delivery to the cloud requires careful technical consideration and planning. In this chapter, we discuss the impact of right-scaling on the cost modelling for migration decision making and price setting of software for commercial resale. An integrated process is presented for measuring total cost of ownership, taking in to account IaaS/PaaS resource consumption based on forecast SaaS usage levels. The process is illustrated with a real world case study

Social Internet of Things and New Generation Computing -- A Survey

Social Internet of Things (SIoT) tries to overcome the challenges of Internet of Things (IoT) such as scalability, trust and discovery of resources, by inspiration from social computing. This survey aims to investigate the research done on SIoT from two perspectives including application domain and the integration to the new computing models. For this, a two-dimensional framework is proposed and the projects are investigated, accordingly. The first dimension considers and classifies available research from the application domain perspective and the second dimension performs the same from the integration to new computing models standpoint. The aim is to technically describe SIoT, to classify related research, to foster the dissemination of state-of-the-art, and to discuss open research directions in this field.Comment: IoT, Social computing, Surve

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified