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In the bacteria species Enterococcus faecalis, transfer of plasmid pCF10 by conjugation between donor cells that possess sets of genes conferring drug resistance and recipient cells leads to the spread of this resistance in a population. A complex signaling molecule network is responsible for communication between recipient and donor cells. Up to this point, the nature of these signaling molecules has been modeled deterministically from the point of view of an “average” cell. While this view has been cured slightly by stochastic treatments, a model is needed that better accounts for the individual nature of each cell, each cell’s interactions with other cells, and each cell’s distinct effect on the population’s environment. To this end, a population balance model has been formulated that considers these features. Of interest is the distribution of protein PrgB, a membrane-bound protein that indicates the degree to which conjugation has been initiated. As a result of the interactions between cells and the signaling molecules, two steady state levels of protein concentration exist, one for an “off” state of conjugation and one for an “on” state. While the single-cell approach predicts a bimodal distribution of protein resulting from this bistability, the population balance approach demonstrates that a bistable system such as that of plasmid pCF10 can give rise to a unimodal stationary distribution. While there is still much work to be done on understanding conjugation in Enterococcus faecalis, this study has delineated two important concepts associated with this complex phenomenon (i.e. bistability versus bimodality).

Vincristine is a vinca alkaloid, a commonly used chemotherapy drug for treating leukemia, lymphoma, multiple myeloma and some pediatric cancers. Its major dose-limiting side effect is peripheral neuropathy. The current dosing of “standard-dose-for-all” ignores the genetic and phenotypic variations among different patients, and causes severe neuropathy in some patients while ineffectively treats the others. In the present study, we aim to discover novel biomarkers involved in vincristine-induced neuropathy and identify patients with varied metabolic characteristics. Thus treatment can be tailored accordingly to improve outcomes of vincristine treatment. Pre-dose and post-dose serum samples were collected from two groups of patients (low and high toxicity groups) at the beginning of treatment and at the end of treatments. Liquid chromatography–mass spectrometry (LC-MS) was used to identify and quantify metabolites in the samples. Metabolomics data analysis tools were utilized to analyze the raw spectrum obtained from LC-MS. From statistical analysis and modeling, we identified 27 compounds that showed a difference in intensity between low toxicity and high toxicity patients at the beginning of the treatment. Further verification against database and validation are needed to confirm the biomarkers to be able to be useful in clinics. . Successful validation of the biomarkers will enable the clinicians to treat the patients according to their characteristics which will ultimately improve the survival and quality-of-life of cancer patients.