Multiple sclerosis (MS) is an inflammatory neurodegenerative disease of the central nervous system (CNS) which affects mostly aged between 20 and 40 years. MS causes demyelination of the white matter of the brain with this process sometimes extending into the gray matter. The MS patients show white matter with areas of damage name plaques or lesions. The progressive loss of myelin, a lipoprotein that covers the axon of neurons, inhibits the coordinated and rapid transmission of nerve impulses causing various symptoms that characterize all demyelinating diseases in general and MS in particular. MS is a disease not clinically well characterized since it is unpredictable. The type and severity of symptoms can vary greatly according to the affected CNS areas and the extent of the damage. Recent studies show that the biochemical aspect of the lesions may vary between the different MS forms. However, this is not the predominant reason why patients with MS differ in their symptoms.

Uncontrolled cellular proliferation and/or alteration of apoptosis lead to breast cancer, as a consequence of the accumulation of genetic lesions, which give rise to alterations that activate proto-oncogenes and inactivate the tumour suppressor genes. In recent years, strategy in cancer therapy has been the use of high doses of toxic non-specific agents and to investigate a range of new agents that specifically target tumour-related molecules, in a variety of biological pathways. The development of new agents with tumour-specific mechanism of action on molecular targets that are responsible for cells transformation is one of main therapeutic strategies for improving chemotherapeutics. In this context, novel 5-fluorouracil (5-FU) derivatives possessing a broader spectrum of antitumor activity and fewer side effects than 5-FU, have been diligently sought in a number of laboratories. We have shown that benzannelated seven-membered O,N-acetals posses potent antiproliferative (in a micromolar range) and apoptotic activities in breast cancer cells. In order to elucidate its mechanisms of antitumour activity, we studied the effect of new drugs on the expression of molecular markers such cell cycle regulators (cyclin D1, p21, p27, p34,) and apoptosis-related proteins (Bcl-2 and p53) on MCF-7 human breast cancer cells. Our result showed that the high apoptotic activity induced by the novel compounds was due to inhibition of cyclin D or p34 expression, which implied the halting of the cell cycle in Go/G1 or G2 phases respectively and the non-entrance of tumour cells in mitosis. Moreover, DBDFU and 7MDFU compounds inhibited completely bcl-2 expression. In constrast, the most early and potent apoptotic compound DBOFU, increased cyclin D and p34 expression, decreased the members of Cip/Kip family p21 and p27 proteins. This compound had antitumour activity by selective induction of p53 activity in the p53-wild type MCF-7 breast cancer cells. In conclusion, our finding demonstrate the ability of benzannelated seven-membered O,N-acetals to target selective apoptotic or cell cycle checkpoints in breast cancer cells, suggesting its potential application as a new strategy for this type of cancer.

In the last decade progress in diagnostic techniques and treatment has greatly contributed to the survival of cancer patients, however breast cancer is still one of the leading causes of death in women and its incidence in the developing world is on the rise. New therapeutic strategies are required to overcome the limitations of conventional breast cancer treatment. Thus, the use of novel antitumour drugs that are less toxic to normal tissues and more specific to malignant cells combined to suicide gene therapy offers a potential approach to this type of tumour. In this context, we have previously reported that gef gene found in E. coli encodes a small protein related with cell-killing functions, and benzomono and benzodi-heteropinics derivative compounds are regarded as potential anticancer agents. In this study, we analysed whether this novel antitumour drugs combined with gef gene treatment could result in enhanced citotoxicity in human tumour cell cultures. Combined treatment with recombinant retrovirus under the control of the tetracycline responsive element (TRE) expressing gef gene and benzomono and benzodi-heteropinics compounds clearly showed an additive cytotoxic effect on human MCF-7 cells. Doxycicline-induction of gef gene expression in MCF-7 cells combined with low doses of benzomono and benzodi-heteropinics derivatives compounds produced a significant decrease on proliferation rate and arrest cells in the G(0)/G(1) phase of the cell cycle. This inhibition was greater than that obtained using the gene therapy or chemotherapy alone. The combined action was dose-dependent in time. Moreover, Annexin-V-FITC and propidium iodide assays showed the presence of apoptotic and necrotic cell death, which was confirmed by both confocal and scanning electron microscopy. In conclusion, our results suggest that combined therapy with gef gene and new pharmacological derivatives has an important antitumour activity, due to the enhancement in the selective action of the pharmacological compounds by the gef gene expression. This new therapeutic strategy could be useful in the fight against breast cancer.

Stem cells represent an invaluable source of cells for tissue regeneration, thanks to their ability to self-renewal and differentiate into functional cells of the tissues. The studies and results related to stem cell differentiation are diverse and sometimes contradictory due to the different stem cell types and the numerous variables involved in the differentiation process. In this paper a new methodology is proposed in order to select the relevant factors involved in stem cell differentiation into myocardial lineage and forecast its behaviour and response in the differentiation process. We have built a database from the results of experiments regarding cardiomyocytic differentiation of stem cells and using this database we have applied state-of-the-art classification and predictive techniques such as support vector machine and decision trees, as well as several feature selection techniques. The results obtained are very promising and demonstrate that with only a reduced subset of variables high prediction rates are possible.