We propose and analyze a mathematical model of hematopoietic stem cell dynamics. This model takes into account a finite number of stages in blood production, characterized by cell maturity levels, which enhance the difference, in the hematopoiesis process, between dividing cells that differentiate (by going to the next stage) and dividing cells that keep the same maturity level (by staying in the same stage). It is described by a system of n nonlinear differential equations with n delays. We study some fundamental properties of the solutions, such as boundedness and positivity, and we investigate the existence of steady states. We determine some conditions for the local asymptotic stability of the trivial steady state, and obtain a sufficient condition for its global asymptotic stability by using a Lyapunov functional. Then we prove the instability of axial steady states. We study the asymptotic behavior of the unique positive steady state and obtain the existence of a stability area depending on all the time delays. We give a numerical illustration of this result for a system of four equations.

We consider a size structured cell population model where a mother cell gives birth to two daughter cells. We know that the asymptotic behavior of the density of cells is given by the solution to an eigenproblem. The eigenvector gives the asymptotic shape and the eigenvalue gives the exponential growth rate and so the Maltusian parameter. The Maltusian parameter depends on the division rule for the mother cell, i.e., symmetric (the two daughter cells have the same size) or asymmetric. We use a min-max principle and a differentiation principle to find the variation of the first eigenvalue with respect to a parameter of asymmetry of the cell division. We prove that the symmetrical division is not always the best fitted division, i.e., the Maltusian parameter may be not optimal.

We review the basic pathology of cyclical neutropenia in both humans and the grey collie, and examine the role that mathematical modeling of hematopoietic cell production has played in our understanding of the origins of this fascinating dynamical disease.

Neutropenia is a significant dose-limiting toxicity of cancer chemotherapy, especially in dose-intensified regimens. It is widely treated by injections of Granulocyte Colony-Stimulating Factor (G-CSF). However, optimal schedules of G-CSF administration are still not determined. In order to aid in identifying more efficacious and less neutropenic treatment protocols, we studied a detailed physiologically-based computer model of granulopoiesis, as affected by different treatment schedules of doxorubicin and/or Granulocyte Colony-Stimulating Factor (G-CSF). We validated the model as evident from accurate prediction of clinical data on human granulopoiesis in healthy individuals and in doxorubicin-treated cancer patients, with or without G-CSF support. Based on our model, we suggest new G-CSF administration regimens. These regimens include reduced G-CSF doses, optimally timed post-chemotherapy. Application of these regimens can lead to minimization of G-CSF side effects, as well as more cost-effective and less myelotoxic protocols. Currently clinical trials are being designed in order to test these new treatment regimens.

In this work, we introduce a new software created to study hematopoiesis at the cell population level with the individually based approach. It can be used as an interface between theoretical works on population dynamics and experimental observations. We show that this software can be useful to study some features of normal hematopoiesis as well as some blood diseases such as myelogenous leukemia. It is also possible to simulate cell communication and the formation of cell colonies in the bone marrow.

Patients with acute myeloblastic leukemia (AML) are divided according to the French American British (FAB) classification into eight subgroups (M0 to M7) on the basis of their degree of maturation/differentiation. However, even if immunophenotypical characterization by flow cytometry is routinely used to distinguish between AML and acute lymphoblastic leukemia (ALL), it is not yet well established for the identification within the AML subgroups. Here we show that certain subgroups of AML can be identified with a good accuracy (80% of the patients we analyzed) by means of the expression of specific markers.

Spatial dynamics of fibrin clot formation in non-stirred system activated by glass surface was studied as a function of FIX activity. Haemophilia B plasma was obtained from untreated patients with different levels of FIX deficiency and from severe haemophilia B patient treated with FIX concentrate (Ahemphil B) during its clearance with half-life t1/2=12 hours. As reported previously (Ataullakhanov et al. Biochim Biophys Acta 1998; 1425: 453-468), clot growth in space showed two distinct phases: activation and propagation. The activation phase is characterized by the time required to start clot growth from the activator, while the characteristic parameter of the propagation phase is the clot elongation rate. This rate reaches steady state in approximately ten minutes after the beginning of growth. In haemophilia B plasma, clot formation is substantially impaired: clot starts to grow from the activating surface later than in healthy donor plasma, and its propagation rate is considerably lower. The most significant abnormalities in clot growth kinetics are observed at FIX activity below 10% of normal. Simulation of these experiments was performed theoretically using a detailed biochemical model (Panteleev et al. Biophys J 2006; 90: 1489-1500) adapted for experimental conditions used. Suitability of the assumptions used to describe triggering contact activation was verified.