Gene therapy for carcinoma of the breast: Pro-apoptotic gene therapy

The dysregulation of apoptosis contributes in a variety of ways to the malignant phenotype. It is increasingly recognized that the alteration of pro-apoptotic and anti-apoptotic molecules determines not only escape from mechanisms that control cell cycle and DNA damage, but also endows the cancer cells with the capacity to survive in the presence of a metabolically adverse milieu, to resist the attack of the immune system, to locally invade and survive despite a lack of tissue anchorage, and to evade the otherwise lethal insults induced by drugs and radiotherapy. A multitude of apoptosis mediators has been identified in the past decade, and the roles of several of them in breast cancer have been delineated by studying the clinical correlates of pathologically documented abnormalities. Using this information, attempts are being made to correct the fundamental anomalies at the genetic level. Fundamental to this end are the design of more efficient and selective gene transfer systems, and the employment of complex interventions that are tailored to breast cancer and that are aimed concomitantly towards different components of the redundant regulatory pathways. The combination of such genetic modifications is most likely to be effective when combined with conventional treatments, thus robustly activating several pro-apoptotic pathways

The Genealogical Population Dynamics of HIV-1 in a Large Transmission Chain:Bridging within and among Host Evolutionary Rates

Transmission lies at the interface of human immunodeficiency virus type 1 (HIV-1) evolution within and among hosts and separates distinct selective pressures that impose differences in both the mode of diversification and the tempo of evolution. In the absence of comprehensive direct comparative analyses of the evolutionary processes at different biological scales, our understanding of how fast within-host HIV-1 evolutionary rates translate to lower rates at the between host level remains incomplete. Here, we address this by analyzing pol and env data from a large HIV-1 subtype C transmission chain for which both the timing and the direction is known for most transmission events. To this purpose, we develop a new transmission model in a Bayesian genealogical inference framework and demonstrate how to constrain the viral evolutionary history to be compatible with the transmission history while simultaneously inferring the within-host evolutionary and population dynamics. We show that accommodating a transmission bottleneck affords the best fit our data, but the sparse within-host HIV-1 sampling prevents accurate quantification of the concomitant loss in genetic diversity. We draw inference under the transmission model to estimate HIV-1 evolutionary rates among epidemiologically-related patients and demonstrate that they lie in between fast intra-host rates and lower rates among epidemiologically unrelated individuals infected with HIV subtype C. Using a new molecular clock approach, we quantify and find support for a lower evolutionary rate along branches that accommodate a transmission event or branches that represent the entire backbone of transmitted lineages in our transmission history. Finally, we recover the rate differences at the different biological scales for both synonymous and non-synonymous substitution rates, which is only compatible with the 'store and retrieve' hypothesis positing that viruses stored early in latently infected cells preferentially transmit or establish new infections upon reactivation.status: publishe

Lactic Acid Bacterium and Yeast Microbiotas of 19 Sourdoughs Used for Traditional/Typical Italian Breads: Interactions between Ingredients and Microbial Species Diversity

The study of the microbiotas of 19 Italian sourdoughs used for the manufacture of traditional/typical breads allowed the identification, through a culture-dependent approach, of 20 and 4 species of lactic acid bacteria (LAB) and yeasts, respectively. Numerically, the most frequent LAB isolates were Lactobacillus sanfranciscensis (ca. 28% of the total LAB isolates), Lactobacillus plantarum (ca. 16%), and Lactobacillus paralimentarius (ca. 14%). Saccharomyces cerevisiae was identified in 16 sourdoughs. Candida humilis, Kazachstania barnettii, and Kazachstania exigua were also identified. As shown by principal component analysis (PCA), a correlation was found between the ingredients, especially the type of flour, the microbial community, and the biochemical features of sourdoughs. Triticum durum flours were characterized by the high level of maltose, glucose, fructose, and free amino acids (FAA) correlated with the sole or main presence of obligately heterofermentative LAB, the lowest number of facultatively heterofermentative strains, and the low cell density of yeasts in the mature sourdoughs. This study highlighted, through a comprehensive and comparative approach, the dominant microbiotas of 19 Italian sourdoughs, which determined some of the peculiarities of the resulting traditional/typical Italian breads