Spatial and temporal variations of Cocconeis placentula var. euglypta (Ehrenb.) 1854 Grunow, 1884 in drift and periphyton

Spatial and temporal variations of Cocconeis placentula var. euglypta in drift and periphyton were studied in mountain streams of the Córdoba Province (Argentina). The sampling program was conducted in study sites located on a confluence between different order streams during an annual cycle. Samples were also taken every two hours during the daylight period in high and low water conditions. The relationship between drift and cellular reproduction was evaluated by valve length biometrics analysis. C. placentula var. euglypta drift was continuous; its density was not always dependent on periphyton density in each locality. C. placentula var. euglypta drift could be related to abiotic factors such as temperature and flow during the annual cycle. There were significant differences between periphyton and drift valve lengths. Moreover, drift can be associated with cellular reproduction because density was higher when valve lengths were shorter at different hours of the day. C. placentula var. euglypta epiphytims on Cladophora glomerata also influenced drift density and size distribution, modifying the relationship between periphyton and drift during the late spring when C. placentula var. euglypta was detached from senescent mats

Spatial and temporal variations of Cocconeis placentula var. euglypta (Ehrenb.) 1854 Grunow, 1884 in drift and periphyton

Spatial and temporal variations of Cocconeis placentula var. euglypta in drift and periphyton were studied in mountain streams of the Córdoba Province (Argentina). The sampling program was conducted in study sites located on a confluence between different order streams during an annual cycle. Samples were also taken every two hours during the daylight period in high and low water conditions. The relationship between drift and cellular reproduction was evaluated by valve length biometrics analysis. C. placentula var. euglypta drift was continuous; its density was not always dependent on periphyton density in each locality. C. placentula var. euglypta drift could be related to abiotic factors such as temperature and flow during the annual cycle. There were significant differences between periphyton and drift valve lengths. Moreover, drift can be associated with cellular reproduction because density was higher when valve lengths were shorter at different hours of the day. C. placentula var. euglypta epiphytims on Cladophora glomerata also influenced drift density and size distribution, modifying the relationship between periphyton and drift during the late spring when C. placentula var. euglypta was detached from senescent mats

Selecting a differential equation cell cycle model for simulating leukemia treatment

This work studies three differential equation models of the leukemia cell cycle: a population balance model (PBM) using intracellular protein expression levels as state variables representing phase progress; a delay differential equation model (DDE) with temporal phase durations as delays; and an ordinary differential equation model (ODE) of phase-to-phase progression. In each type of model, global sensitivity analysis determines the most significant parameters while parameter estimation fits experimental data. To compare models based on the output of their structural properties, an expected behavior was defined, and each model was coupled to a pharmacokinetic/pharmacodynamic model of chemotherapy delivery. Results suggest that the particular cell cycle model chosen highly affects the simulated treatment outcome, given the same steady state kinetic parameters and drug dosage/scheduling. The manuscript shows how cell cycle models should be selected according to the complexity, sensitivity, and parameter availability of the application envisioned

An Integrated Platform for the Study of Leukaemia

Leukemia is a severe cancer of the blood and the most common treatment for acute myeloid leukemia (AML), a severe and aggressive type of leukemia, is intensive chemotherapy. The latter involves exposure of the patient to cytotoxic drugs which interact with highly proliferative cells. More specifically, only cells that are in specific phases of the cell cycle will be eliminated. Since healthy cells also proliferate in order to renew the cellular material. Therefore, “closing the loop” from in vivo to in vitro and in silico is a first step towards optimization and personalization of chemotherapy treatment. Clinical treatment protocols ignore the mechanisms behind drug action on the normal and abnormal populations. The main models are pharmacokinetics (PK), which describes the elimination of the drug by the organs, and pharmacodynamics (PD), which accounts for the effects of the drug on the cells in the bone marrow, which is the location of the tumor generation

Towards unravelling the kinetics of an acute myeloid leukaemia model system under oxidative and starvation stress: a comparison between two- and three-dimensional cultures.

A great challenge when conducting ex vivo studies of leukaemia is the construction of an appropriate experimental platform that would recapitulate the bone marrow (BM) environment. Such a 3D scaffold system has been previously developed in our group [1]. Additionally to the BM architectural characteristics, parameters such as oxygen and glucose concentration are crucial as their value could differ between patients as well as within the same patient at different stages of treatment, consequently affecting the resistance of leukaemia to chemotherapy. The effect of oxidative and glucose stress-at levels close to human physiologic ones-on the proliferation and metabolic evolution of an AML model system (K-562 cell line) in conventional 2D cultures as well as in 3D scaffolds were studied. We observed that the K-562 cell line can proliferate and remain alive for 2 weeks in medium with glucose close to physiological levels both in 20 and 5% O2. We report interesting differences on the cellular response to the environmental, i.e., oxidative and/or nutritional stress stimuli in 2D and 3D. Higher adaptation to oxidative stress under non-starving conditions is observed in the 3D system. The glucose level in the medium has more impact on the cellular proliferation in the 3D compared to the 2D system. These differences can be of significant importance both when applying chemotherapy in vitro and also when constructing mathematical tools for optimisation of disease treatment

Towards unravelling the kinetics of an acute myeloid leukaemia model system under oxidative and starvation stress: a comparison between two- and three-dimensional cultures

A great challenge when conducting ex vivo studies of leukaemia is the construction of an appropriate experimental platform that would recapitulate the bone marrow (BM) environment. Such a 3D scaffold system has been previously developed in our group [1]. Additionally to the BM architectural characteristics, parameters such as oxygen and glucose concentration are crucial as their value could differ between patients as well as within the same patient at different stages of treatment, consequently affecting the resistance of leukaemia to chemotherapy. The effect of oxidative and glucose stress—at levels close to human physiologic ones—on the proliferation and metabolic evolution of an AML model system (K-562 cell line) in conventional 2D cultures as well as in 3D scaffolds were studied. We observed that the K-562 cell line can proliferate and remain alive for 2 weeks in medium with glucose close to physiological levels both in 20 and 5 % O2. We report interesting differences on the cellular response to the environmental, i.e., oxidative and/or nutritional stress stimuli in 2D and 3D. Higher adaptation to oxidative stress under non-starving conditions is observed in the 3D system. The glucose level in the medium has more impact on the cellular proliferation in the 3D compared to the 2D system. These differences can be of significant importance both when applying chemotherapy in vitro and also when constructing mathematical tools for optimisation of disease treatment