Empirical maximum lifespan of earthworms is twice that of mice

We considered a Gompertzian model for the population dynamics of Eisenia andrei case-cohorts in artificial OECD soil under strictly controlled conditions. The earthworm culture was kept between 18 and 22°C at a constant pH of 5.0. In all, 77 lumbricids were carefully followed for almost 9 years, until the oldest died. The Eisenia median longevity is 4.25 years and the oldest specimen was 8.73 years. Eisenia cocoons were hand-sorted every 3 weeks, washed in distilled water, placed in Petri dishes, and counted. Regular removal did not reduce breeding. Each fertile cocoon contained on average two or three embryos. The failure rates (mortality and infertility percentages) are smooth power functions where the rate at time (n + 1) captured most of the phenomenology of the previous rate at time n, as expected by the considered law, but not at both the beginning and the end of this long-term laboratory study

Interplay between distribution of live cells and growth dynamics of solid tumours

Experiments show that simple diffusion of nutrients and waste molecules is not sufficient to explain the typical multilayered structure of solid tumours, where an outer rim of proliferating cells surrounds a layer of quiescent but viable cells and a central necrotic region. These experiments challenge models of tumour growth based exclusively on diffusion. Here we propose a model of tumour growth that incorporates the volume dynamics and the distribution of cells within the viable cell rim. The model is suggested by in silico experiments and is validated using in vitro data. The results correlate with in vivo data as well, and the model can be used to support experimental and clinical oncology

Predicting Outcomes of Prostate Cancer Immunotherapy by Personalized Mathematical Models

Therapeutic vaccination against disseminated prostate cancer (PCa) is partially effective in some PCa patients. We hypothesized that the efficacy of treatment will be enhanced by individualized vaccination regimens tailored by simple mathematical models.We developed a general mathematical model encompassing the basic interactions of a vaccine, immune system and PCa cells, and validated it by the results of a clinical trial testing an allogeneic PCa whole-cell vaccine. For model validation in the absence of any other pertinent marker, we used the clinically measured changes in prostate-specific antigen (PSA) levels as a correlate of tumor burden. Up to 26 PSA levels measured per patient were divided into each patient's training set and his validation set. The training set, used for model personalization, contained the patient's initial sequence of PSA levels; the validation set contained his subsequent PSA data points. Personalized models were simulated to predict changes in tumor burden and PSA levels and predictions were compared to the validation set. The model accurately predicted PSA levels over the entire measured period in 12 of the 15 vaccination-responsive patients (the coefficient of determination between the predicted and observed PSA values was R(2) = 0.972). The model could not account for the inconsistent changes in PSA levels in 3 of the 15 responsive patients at the end of treatment. Each validated personalized model was simulated under many hypothetical immunotherapy protocols to suggest alternative vaccination regimens. Personalized regimens predicted to enhance the effects of therapy differed among the patients.Using a few initial measurements, we constructed robust patient-specific models of PCa immunotherapy, which were retrospectively validated by clinical trial results. Our results emphasize the potential value and feasibility of individualized model-suggested immunotherapy protocols

Computational Modeling of PI3K/AKT and MAPK Signaling Pathways in Melanoma Cancer

Background Malignant melanoma is an aggressive tumor of the skin and seems to be resistant to current therapeutic approaches. Melanocytic transformation is thought to occur by sequential accumulation of genetic and molecular alterations able to activate the Ras/Raf/MEK/ERK (MAPK) and/or the PI3K/AKT (AKT) signalling pathways. Specifically, mutations of B-RAF activate MAPK pathway resulting in cell cycle progression and apoptosis prevention. According to these findings, MAPK and AKT pathways may represent promising therapeutic targets for an otherwise devastating disease. Result Here we show a computational model able to simulate the main biochemical and metabolic interactions in the PI3K/AKT and MAPK pathways potentially involved in melanoma development. Overall, this computational approach may accelerate the drug discovery process and encourages the identification of novel pathway activators with consequent development of novel antioncogenic compounds to overcome tumor cell resistance to conventional therapeutic agents. The source code of the various versions of the model are available as S1 Archive

Effect of macromolecular crowding on the rate of diffusion-limited enzymatic reaction

The cytoplasm of a living cell is crowded with several macromolecules of different shapes and sizes. Molecular diffusion in such a medium becomes anomalous due to the presence of macromolecules and diffusivity is expected to decrease with increase in macromolecular crowding. Moreover, many cellular processes are dependent on molecular diffusion in the cell cytosol. The enzymatic reaction rate has been shown to be affected by the presence of such macromolecules. A simple numerical model is proposed here based on percolation and diffusion in disordered systems to study the effect of macromolecular crowding on the enzymatic reaction rates. The model explains qualitatively some of the experimental observations.Comment: 6 pages, 4 figure

Antibiotic resistance determinants in the interplay between food and gut microbiota

A complex and heterogeneous microflora performs sugar and lactic acid fermentations in food products. Depending on the fermentable food matrix (dairy, meat, vegetable etc.) as well as on the species composition of the microbiota, specific combinations of molecules are produced that confer unique flavor, texture, and taste to each product. Bacterial populations within such “fermented food microbiota” are often of environmental origin, they persist alive in foods ready for consumption, eventually reaching the gastro-intestinal tract where they can interact with the resident gut microbiota of the host. Although this interaction is mostly of transient nature, it can greatly contribute to human health, as several species within the food microbiota also display probiotic properties. Such an interplay between food and gut microbiota underlines the importance of the microbiological quality of fermented foods, as the crowded environment of the gut is also an ideal site for genetic exchanges among bacteria. Selection and spreading of antibiotic resistance genes in foodborne bacteria has gained increasing interest in the past decade, especially in light of the potential transferability of antibiotic resistance determinants to opportunistic pathogens, natural inhabitants of the human gut but capable of acquiring virulence in immunocompromised individuals. This review aims at describing major findings and future prospects in the field, especially after the use of antibiotics as growth promoters was totally banned in Europe, with special emphasis on the application of genomic technologies to improve quality and safety of fermented foods

Translational research into gut microbiota: new horizons on obesity treatment: updated 2014

Obesity is currently a pandemic of worldwide proportions affecting millions of people. Recent studies have proposed the hypothesis that mechanisms not directly related to the human genome could be involved in the genesis of obesity, due to the fact that, when a population undergoes the same nutritional stress, not all individuals present weight gain related to the diet or become hyperglycemic. The human intestine is colonized by millions of bacteria which form the intestinal flora, known as gut flora. Studies show that lean and overweight human may present a difference in the composition of their intestinal flora; these studies suggest that the intestinal flora could be involved in the development of obesity. Several mechanisms explain the correlation between intestinal flora and obesity. The intestinal flora would increase the energetic extraction of non-digestible polysaccharides. In addition, the lipopolysaccharide from intestinal flora bacteria could trigger a chronic sub-clinical inflammatory process, leading to obesity and diabetes. Another mechanism through which the intestinal flora could lead to obesity would be through the regulation of genes of the host involved in energy storage and expenditure. In the past five years data coming from different sources established causal effects between intestinal microbiota and obesity/insulin resistance, and it is clear that this area will open new avenues of therapeutic to obesity, insulin resistance and DM2

The Human Intestinal Microbiome: A New Frontier of Human Biology

To analyze the vast number and variety of microorganisms inhabiting the human intestine, emerging metagenomic technologies are extremely powerful. The intestinal microbes are taxonomically complex and constitute an ecologically dynamic community (microbiota) that has long been believed to possess a strong impact on human physiology. Furthermore, they are heavily involved in the maturation and proliferation of human intestinal cells, helping to maintain their homeostasis and can be causative of various diseases, such as inflammatory bowel disease and obesity. A simplified animal model system has provided the mechanistic basis for the molecular interactions that occur at the interface between such microbes and host intestinal epithelia. Through metagenomic analysis, it is now possible to comprehensively explore the genetic nature of the intestinal microbiome, the mutually interacting system comprising the host cells and the residing microbial community. The human microbiome project was recently launched as an international collaborative research effort to further promote this newly developing field and to pave the way to a new frontier of human biology, which will provide new strategies for the maintenance of human health

Chemotherapy in conjoint aging-tumor systems: some simple models for addressing coupled aging-cancer dynamics

Background In this paper we consider two approaches to examining the complex dynamics of conjoint aging-cancer cellular systems undergoing chemotherapeutic intervention. In particular, we focus on the effect of cells growing conjointly in a culture plate as a precursor to considering the larger multi-dimensional models of such systems. Tumor cell growth is considered from both the logistic and the Gompertzian case, while normal cell growth of fibroblasts (WI-38 human diploid fibroblasts) is considered as logistic only. Results We demonstrate, in a simple approach, how the interdependency of different cell types in a tumor, together with specifications of for treatment, can lead to different evolutionary patterns for normal and tumor cells during a course of therapy. Conclusions These results have significance for understanding appropriate pharmacotherapy for elderly patients who are also undergoing chemotherapy