In vitro differentiation of murine hematopoietic progenitor cells toward the myeloid lineage occurs in response to Staphylococcus aureus and yeast species

We have studied the effect of inactivated microbial stimuli (Candida albicans, Candida glabrata, Saccharomyces boulardii, and Staphylococcus aureus) on the in vitro differentiation of lineage negative (Lin−) hematopoietic progenitor mouse cells. Purified Lin− progenitors were co-cultured for 7 days with the stimuli, and cell differentiation was determined by flow cytometry analysis. All the stimuli assayed caused differentiation toward the myeloid lineage. S. boulardii and particularly C. glabrata were the stimuli that induced in a minor extent differentiation of Lin− cells, as the major population of differentiated cells corresponded to monocytes, whereas C. albicans and S. aureus induced differentiation beyond monocytes: to monocyte-derived dendritic cells and macrophages, respectively. Interestingly, signaling through TLR2 by its pure ligand Pam3CSK4 directed differentiation of Lin− cells almost exclusively to macrophages. These data support the notion that hematopoiesis can be modulated in response to microbial stimuli in a pathogen-dependent manner, being determined by the pathogen-associated molecular patterns and the pattern-recognition receptors involved, in order to generate the populations of mature cells required to deal with the pathogen.

Chebanov law and Vakar formula in mathematical models of complex systems

Ecological models written in a mathematical language L(M) or model language, with a given style or methodology can be considered as a text. It is possible to apply statistical linguistic laws and the experimental results demonstrate that the behaviour of a mathematical model is the same of any literary text of any natural language. A text has the following characteristics: (a) the variables, its transformed functions and parameters are the lexic units or LUN of ecological models; (b) the syllables are constituted by a LUN, or a chain of them, separated by operating or ordering LUNs; (c) the flow equations are words; and (d) the distribution of words (LUM and CLUN) according to their lengths is based on a Poisson distribution, the Chebanov's law. It is founded on Vakar's formula, that is calculated likewise the linguistic entropy for L(M). We will apply these ideas over practical examples using MARIOLA model. In this paper it will be studied the problem of the lengths of the simple lexic units composed lexic units and words of text models, expressing these lengths in number of the primitive symbols, and syllables. The use of these linguistic laws renders it possible to indicate the degree of information given by an ecological model.