IgG4-related lung disease as a differential diagnosis of a lymphoproliferative disease: atypical presentation of an atypical disease.

IgG4-related disease (IgG4-RD) is an immunomodulated inflammatory disease that usually affects the pancreas and parotid glands. Although lung involvement is rare, it has been recently reported and could mimic various other diagnoses. We present a case of IgG4-RD whose symptoms and images raised the suspicion of a malignant lymphoproliferative lung neoplasm.

Finding the fixed points of a Boolean network from a positive feedback vertex set.

Motivation: In the modeling of biological systems by Boolean networks, a key problem is finding the set of fixed points of a given network. Some constructed algorithms consider certain structural properties of the regulatory graph like those proposed by Akutsu et al. and Zhang et al.

Cancer Health Impact Program (CHIP): Identifying Social and Demographic Associations of mHealth Access and Cancer Screening Behaviors Among Brooklyn, New York, Residents.

Background: The Bedford-Stuyvesant (BS) and Bushwick (BW) communities of central Brooklyn, New York, are located within the 50-mile core radius of Memorial Sloan Kettering's main catchment area. Cancer is the second leading cause of death among the predominantly African American and Hispanic neighborhoods, with BS and BW having higher prostate cancer and colorectal mortality rates than New York City as a whole. There is significant opportunity to design cancer interventions that leverage the accessibility and acceptability of mobile health (mHealth) tools among the BS and BW communities.

Enumeration and extension of non-equivalent deterministic update schedules in Boolean networks.

Motivation: Boolean networks (BNs) are commonly used to model genetic regulatory networks (GRNs). Due to the sensibility of the dynamical behavior to changes in the updating scheme (order in which the nodes of a network update their state values), it is increasingly common to use different updating rules in the modeling of GRNs to better capture an observed biological phenomenon and thus to obtain more realistic models.In Aracena et al.

On circuit functionality in Boolean networks.

It has been proved, for several classes of continuous and discrete dynamical systems, that the presence of a positive (resp. negative) circuit in the interaction graph of a system is a necessary condition for the presence of multiple stable states (resp. a cyclic attractor).

On the number of different dynamics in Boolean networks with deterministic update schedules.

Deterministic Boolean networks are a type of discrete dynamical systems widely used in the modeling of genetic networks. The dynamics of such systems is characterized by the local activation functions and the update schedule, i.e.

On the robustness of update schedules in Boolean networks.

Deterministic Boolean networks have been used as models of gene regulation and other biological networks. One key element in these models is the update schedule, which indicates the order in which states are to be updated. We study the robustness of the dynamical behavior of a Boolean network with respect to different update schedules (synchronous, block-sequential, sequential), which can provide modelers with a better understanding of the consequences of changes in this aspect of the model.

Maximum number of fixed points in regulatory Boolean networks.

Boolean networks (BNs) have been extensively used as mathematical models of genetic regulatory networks. The number of fixed points of a BN is a key feature of its dynamical behavior. Here, we study the maximum number of fixed points in a particular class of BNs called regulatory Boolean networks, where each interaction between the elements of the network is either an activation or an inhibition.

Mathematical modeling in genetic networks: relationships between the genetic expression and both chromosomic breakage and positive circuits.

The human genome with its 23 pairs of chromosomes, is the result of evolution. This evolution has been ruled by the mutation process and also by the physiological and pathological reorganization of the genomic material inside or between the chromosomes, which are conditioning the genomic variability. This reorganization is starting at singular points on the short or long chromosomic arms, called crossing-over, or translocations, insertions, break points.

A discrete mathematical model applied to genetic regulation and metabolic networks.

This paper describes the use of a discrete mathematical model to represent the basic mechanisms of regulation of the bacteria E. coli in batch fermentation. The specific phenomena studied were the changes in metabolism and genetic regulation when the bacteria use three different carbon substrates (glucose, glycerol, and acetate).

Regulatory network for cell shape changes during Drosophila ventral furrow formation.

Rapid and sequential cell shape changes take place during the formation of the ventral furrow (VF) at the beginning of Drosophila gastrulation. At the cellular level, this morphogenetic event demands close coordination of the proteins involved in actin cytoskeletal reorganization. In order to construct a regulatory network that describes these cell shape changes, we have used published genetic and molecular data for 18 genes encoding transcriptional regulators and signaling pathway components.

Mathematical methods for inferring regulatory networks interactions: application to genetic regulation.

This paper deals with the problem of reconstruction of the intergenic interaction graph from the raw data of genetic co-expression coming with new technologies of bio-arrays (DMA-arrays, protein-arrays, etc.). These new imaging devices in general only give information about the asymptotical part (fixed configurations of co-expression or limit cycles of such configurations) of the dynamical evolution of the regulatory networks (genetic and/or proteic) underlying the functioning of living systems.

Positive and negative circuits in discrete neural networks.

We study the relationships between the positive and negative circuits of the connection graph and the fixed points of discrete neural networks (DNNs). As main results, we give necessary conditions and sufficient conditions for the existence of fixed points in a DNN. Moreover, we exhibit an upper bound for the number of fixed points in terms of the structure and number of positive circuits in the connection graph.

Genetic regulation networks: circuits, regulons and attractors.

We deal in this paper with the concept of genetic regulation network. The genes expression observed through the bio-array imaging allows the geneticist to obtain the intergenic interaction matrix W of the network. The interaction graph G associated to W presents in general interesting features like connected components, gardens of Eden, positive and negative circuits (or loops), and minimal components having 1 positive and 1 negative loop called regulons.