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Theoretical biology medical modelling [journal]
- Quantitative indices of autophagy activity from minimal models. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 Jul 6; 11(1):31.
A number of cellular- and molecular-level studies of autophagy assessment have been carried out with the help of various biochemical and morphological indices. Still there exists ambiguity for the assessment of the autophagy status and of the causal relationship between autophagy and related cellular changes. To circumvent such difficulties, we probe new quantitative indices of autophagy which are important for defining autophagy activation and further assessing its roles associated with different physiopathological states.Our approach is based on the minimal autophagy model that allows us to understand underlying dynamics of autophagy from biological experiments. Specifically, based on the model, we reconstruct the experimental context-specific autophagy profiles from the target autophagy system, and two quantitative indices are defined from the model-driven profiles. The indices are then applied to the simulation-based analysis, for the specific and quantitative interpretation of the system.Two quantitative indices measuring autophagy activities in the induction of sequestration fluxes and in the selective degradation are proposed, based on the model-driven autophagy profiles such as the time evolution of autophagy fluxes, levels of autophagosomes/autolysosomes, and corresponding cellular changes. Further, with the help of the indices, those biological experiments of the target autophagy system have been successfully analyzed, implying that the indices are useful not only for defining autophagy activation but also for assessing its role in a specific and quantitative manner.Such quantitative autophagy indices in conjunction with the computer-aided analysis should provide new opportunities to characterize the causal relationship between autophagy activity and the corresponding cellular change, based on the system-level understanding of the autophagic process at good time resolution, complementing the current in vivo and in vitro assays.
- Comparative analysis of human and mouse immunoglobulin variable heavy regions from IMGT/LIGM-DB with IMGT/HighV-QUEST. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 Jul 3; 11(1):30.
Immunoglobulin (IG) complementarity determining region (CDR) includes VH CDR1, VH CDR2, VH CDR3, VL CDR1, VL CDR2 and VL CDR3. Of these, VH CDR3 plays a dominant role in recognizing and binding antigens. Three major mechanisms are involved in the formation of the VH repertoire: germline gene rearrangement, junctional diversity and somatic hypermutation. Features of the generation mechanisms of VH repertoire in humans and mice share similarities while VH CDR3 amino acid (AA) composition differs. Previous studies have mainly focused on germline gene rearrangement and the composition and structure of the CDR3 AA in humans and mice. However the number of AA changes due to somatic hypermutation and analysis of the junctional mechanism have been ignored.Here we analyzed 9,340 human and 6,657 murine unique productive sequences of immunoglobulin (IG) variable heavy (VH) domains derived from IMGT/LIGM-DB database to understand how VH CDR3 AA compositions significantly differed between human and mouse. These sequences were identified and analyzed by IMGT/HighV-QUEST (http://www.imgt.org), including gene usage, number of AA changes due to somatic hypermutation, AA length distribution of VH CDR3, AA composition, and junctional diversity.Analyses of human and murine IG repertoires showed significant differences. A higher number of AA changes due to somatic hypermutation and more abundant N-region addition were found in human compared to mouse, which might be an important factor leading to differences in VH CDR3 amino acid composition.These findings are a benchmark for understanding VH repertoires and can be used to characterize the VH repertoire during immune responses. The study will allow standardized comparison for high throughput results obtained by IMGT/HighV-QUEST, the reference portal for NGS repertoire.
- A model of immunohistochemical differences between invasive breast cancers and DCIS lesions tested on a consecutive case series of 1248 patients. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 Jun 11; 11(1):29.
A previous theoretic model (Tumour Biol 2013;34:1-7.) that breast tumor types differ in the relative rate of tissue invasion was elaborated and developed on a consecutive case series.Histologic data of 68 ductal breast cancer in situ (DCIS) and 1180 invasive ductal cancer (IDC) patients were collected and analyzed.ER+PgR- phenotype was more common in Luminal B2 than among the pooled Luminal A&B1 (p = 0.0002), and more frequent in Luminal B1 than in Luminal A (p = 0.0167). The same phenotype was associated with the age older than 54 years in Luminal B1 and in B2 patients. HER2 type cancers were more frequent in older patients (p = 0.0038).Tumor progression from DCIS to IDC was found 39% faster than the average in Luminal B1 tumors, supporting the clinical importance of this tumor type. A rare combination of low Ki-67 in HER2 type cancers (only 14% of HER2 type cancers) showed very slow transition to IDC (occurring at only 53.55% of average progression rate), while triple-negative cancers progressed faster than the average, despite Ki-67 value (104.63% for low and 114.27% for high Ki-67 tumors).In three tumor types with positive steroid receptors the ER+PgR- phenotype showed slower IDC transition than the ER+PgR+ phenotype of the same tumor type (difference in progression rate was 38% for Luminal A, 46% for Luminal B1 and 67% for Luminal B2 with Ki67 > 14%).Triple-negative tumors in younger patients exceeded the expected average progression rate by 24%, while in HER2 type tumors, the rate of tissue invasion was in younger patients 20% lower than the expected value.The relative rate of tissue invasion differed substantialy among our patients. Differences depended on tumor types, steroid expression phenotypes and age. The dysfunctional ERs in the ER+PgR- phenotype showed slower rates of tissue invasion, suggesting that ligand binding to functional breast tumor ERs, beside promoting the PgR expression, possibly also promotes tumor transition to the invasive phase.In triple-negative tumors, an age dependent premenopausal mechanism possibly acted as an accelerator of tissue invasion, while faster tissue invasion by HER2-overexpressed tumors in older patients possibly depended on an unidentified mechanism that takes more time to be acquired, so it was less present in premenopausal patients.
- A new flexible plug and play scheme for modeling, simulating, and predicting gastric emptying. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 Jun 10; 11(1):28.
In-silico models that attempt to capture and describe the physiological behavior of biological organisms, including humans, are intrinsically complex and time consuming to build and simulate in a computing environment. The level of detail of description incorporated in the model depends on the knowledge of the system's behavior at that level. This knowledge is gathered from the literature and/or improved by knowledge obtained from new experiments. Thus model development is an iterative developmental procedure. The objective of this paper is to describe a new plug and play scheme that offers increased flexibility and ease-of-use for modeling and simulating physiological behavior of biological organisms.This scheme requires the modeler (user) first to supply the structure of the interacting components and experimental data in a tabular format. The behavior of the components described in a mathematical form, also provided by the modeler, is externally linked during simulation. The advantage of the plug and play scheme for modeling is that it requires less programming effort and can be quickly adapted to newer modeling requirements while also paving the way for dynamic model building.As an illustration, the paper models the dynamics of gastric emptying behavior experienced by humans. The flexibility to adapt the model to predict the gastric emptying behavior under varying types of nutrient infusion in the intestine (ileum) is demonstrated. The predictions were verified with a human intervention study. The error in predicting the half emptying time was found to be less than 6%.A new plug-and-play scheme for biological systems modeling was developed that allows changes to the modeled structure and behavior with reduced programming effort, by abstracting the biological system into a network of smaller sub-systems with independent behavior. In the new scheme, the modeling and simulation becomes an automatic machine readable and executable task.
- Herpes B virus gD interaction with its human receptor - an in silico analysis approach. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 Jun 6; 11(1):27.
The glycoprotein D (gD) is essential for Herpes B virus (BV) entry into mammalian cells. Nectin-1, an HSV-1 gD receptor, is found to be the receptor which mediated BV induced cell-cell fusion, while HVEM does not mediate fusion by BV glycoprotein. However, the specific sequence and structural requirements of the BV gD for the recognition of and binding to Nectin-1 are unknown. Moreover, the 3D structures of BV gD and the BV gD-receptor complex have not been determined. In this study, we propose a reliable model of the interaction of the BV gD with receptor using bioinformatics tools.The three-dimensional structures of two BV gD-receptor complexes were constructed using homology modelling and docking strategy. Based on the models of these complexes, the BV gD receptor interaction patterns were calculated. The results showed that the interface between the BV gD and nectin-1 molecule is not geometrically complementary. The computed molecular interactions indicated that two terminal extensions were the main region of BV gD that binds to nectin-1 and that hydrophobic contacts between the two molecules play key roles in their recognition and binding. The constructed BV gD-HVEM complex model showed that this complex had a lower shape complementarity value and a smaller interface area compared with the HSV-1 gD-HVEM complex, and the number of intermolecular interactions between BV gD-HVEM were fewer than that of HSV-1 gD-HVEM complex. These results could explain why HVEM does not function as a receptor for BV gD.In this study, we present structural model for the BV gD in a complex with its receptor. Some features predicted by this model can explain previously reported experimental data. This complex model may lead to a better understanding of the function of BV gD and its interaction with receptor and will improve our understanding of the activation of the BV fusion and entry process.
- On the origins of the mitotic shift in proliferating cell layers. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 May 27; 11(1):26.
During plant and animal development, monolayer cell sheets display a stereotyped distribution of polygonal cell shapes. In interphase cells these shapes range from quadrilaterals to decagons, with a robust average of six sides per cell. In contrast, the subset of cells in mitosis exhibits a distinct distribution with an average of seven sides. It remains unclear whether this 'mitotic shift' reflects a causal relationship between increased polygonal sidedness and increased division likelihood, or alternatively, a passive effect of local proliferation on cell shape.We use a combination of probabilistic analysis and mathematical modeling to predict the geometry of mitotic polygonal cells in a proliferating cell layer. To test these predictions experimentally, we use Flp-Out stochastic labeling in the Drosophila wing disc to induce single cell clones, and confocal imaging to quantify the polygonal topologies of these clones as a function of cellular age. For a more generic test in an idealized cell layer, we model epithelial sheet proliferation in a finite element framework, which yields a computationally robust, emergent prediction of the mitotic cell shape distribution.Using both mathematical and experimental approaches, we show that the mitotic shift derives primarily from passive, non-autonomous effects of mitoses in neighboring cells on each cell's geometry over the course of the cell cycle. Computationally, we predict that interphase cells should passively gain sides over time, such that cells at more advanced stages of the cell cycle will tend to have a larger number of neighbors than those at earlier stages. Validating this prediction, experimental analysis of randomly labeled epithelial cells in the Drosophila wing disc demonstrates that labeled cells exhibit an age-dependent increase in polygonal sidedness. Reinforcing these data, finite element simulations of epithelial sheet proliferation demonstrate in a generic framework that passive side-gaining is sufficient to generate a mitotic shift.Taken together, our results strongly suggest that the mitotic shift reflects a time-dependent accumulation of shared cellular interfaces over the course of the cell cycle. These results uncover fundamental constraints on the relationship between cell shape and cell division that should be general in adherent, polarized cell layers.
- Comparison of calculated and experimental power in maximal lactate-steady state during cycling. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 May 27; 11(1):25.
The purpose of this study was the comparison of the calculated (MLSSC) and experimental power (MLSSE) in maximal lactate steady-state (MLSS) during cycling.13 male subjects (24.2 +/- 4.76 years, 72.9 +/- 6.9 kg, 178.5 +/- 5.9 cm, V O2max: 60.4 +/- 8.6 ml min-1 kg-1, V Lamax: 0.9 +/- 0.19 mmol l-1 s-1) performed a ramp-test for determining the V O2maxand a 15 s sprint-test for measuring the maximal glycolytic rate (V Lamax). All tests were performed on a Lode-Cycle-Ergometer. V O2max and V Lamax were used to calculate MLSSC. For the determination of MLSSE several 30 min constant load tests were performed. MLSSE was defined as the highest workload that can be maintained without an increase of blood-lactate-concentration (BLC) of more than 0.05 mmol l-1 min-1 during the last 20 min. Power in following constant-load test was set higher or lower depending on BLC.MLSSE and MLSSC were measured respectively at 217 +/- 51 W and 229 +/- 47 W, while mean difference was -12 +/- 20 W. Orthogonal regression was calculated with r = 0.92 (p < 0.001).The difference of 12 W can be explained by the biological variability of V O2max and V Lamax. The knowledge of both parameters, as well as their individual influence on MLSS, could be important for establishing training recommendations, which could lead to either an improvement in V O2max or V Lamax by performing high intensity or low intensity exercise training, respectively. Furthermore the validity of V Lamax -test should be focused in further studies.
- A combined model of human erythropoiesis and granulopoiesis under growth factor and chemotherapy treatment. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 May 26; 11(1):24.
Haematotoxicity of conventional chemotherapies often results in delays of treatment or reduction of chemotherapy dose. To ameliorate these side-effects, patients are routinely treated with blood transfusions or haematopoietic growth factors such as erythropoietin (EPO) or granulocyte colony-stimulating factor (G-CSF). For the latter ones, pharmaceutical derivatives are available, which differ in absorption kinetics, pharmacokinetic and -dynamic properties. Due to the complex interaction of cytotoxic effects of chemotherapy and the stimulating effects of different growth factor derivatives, optimal treatment is a non-trivial task. In the past, we developed mathematical models of thrombopoiesis, granulopoiesis and erythropoiesis under chemotherapy and growth-factor applications which can be used to perform clinically relevant predictions regarding the feasibility of chemotherapy schedules and cytopenia prophylaxis with haematopoietic growth factors. However, interactions of lineages and growth-factors were ignored so far.To close this gap, we constructed a hybrid model of human granulopoiesis and erythropoiesis under conventional chemotherapy, G-CSF and EPO applications. This was achieved by combining our single lineage models of human erythropoiesis and granulopoiesis with a common stem cell model. G-CSF effects on erythropoiesis were also implemented. Pharmacodynamic models are based on ordinary differential equations describing proliferation and maturation of haematopoietic cells. The system is regulated by feedback loops partly mediated by endogenous and exogenous EPO and G-CSF. Chemotherapy is modelled by depletion of cells. Unknown model parameters were determined by fitting the model predictions to time series data of blood counts and cytokine profiles. Data were extracted from literature or received from cooperating clinical study groups. Our model explains dynamics of mature blood cells and cytokines after growth-factor applications in healthy volunteers. Moreover, we modelled 15 different chemotherapeutic drugs by estimating their bone marrow toxicity. Taking into account different growth-factor schedules, this adds up to 33 different chemotherapy regimens explained by the model.We conclude that we established a comprehensive biomathematical model to explain the dynamics of granulopoiesis and erythropoiesis under combined chemotherapy, G-CSF, and EPO applications. We demonstrate how it can be used to make predictions regarding haematotoxicity of yet untested chemotherapy and growth-factor schedules.
- Surface aggregation patterns of LDL receptors near coated pits III: potential effects of combined retrograde membrane flow-diffusion and a polarized-insertion mechanism. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 May 22; 11(1):23.
Although the process of endocytosis of the low density lipoprotein (LDL) macromolecule and its receptor have been the subject of intense experimental research and modeling, there are still conflicting hypotheses and even conflicting data regarding the way receptors are transported to coated pits, the manner by which receptors are inserted before they aggregate in coated pits, and the display of receptors on the cell surface. At first it was considered that LDL receptors in human fibroblasts are inserted at random locations and then transported by diffusion toward coated pits. But experiments have not ruled out the possibility that the true rate of accumulation of LDL receptors in coated pits might be faster than predicted on the basis of pure diffusion and uniform reinsertion over the entire cell surface. It has been claimed that recycled LDL receptors are inserted preferentially in regions where coated pits form, with display occurring predominantly as groups of loosely associated units. Another mechanism that has been proposed by experimental cell biologists which might affect the accumulation of receptors in coated pits is a retrograde membrane flow. This is essentially linked to a polarized receptor insertion mode and also to the capping phenomenon, characterized by the formation of large patches of proteins that passively flow away from the regions of membrane exocytosis. In this contribution we calculate the mean travel time of LDL receptors to coated pits as determined by the ratio of flow strength to diffusion-coefficient, as well as by polarized-receptor insertion. We also project the resulting display of unbound receptors on the cell membrane. We found forms of polarized insertion that could potentially reduce the mean capture time of LDL receptors by coated pits which is controlled by diffusion and uniform insertion. Our results show that, in spite of its efficiency as a possible device for enhancement of the rate of receptor trapping, polarized insertion nevertheless fails to induce the formation of steady-state clusters of receptor on the cell membrane. Moreover, for appropriate values of the flow strength-diffusion ratio, the predicted steady-state distribution of receptors on the surface was found to be consistent with the phenomenon of capping.
- Improving the estimation of the death rate of infected cells from time course data during the acute phase of virus infections: application to acute HIV-1 infection in a humanized mouse model. [JOURNAL ARTICLE]
- Theor Biol Med Model 2014 May 21; 11(1):22.
Mathematical modeling of virus dynamics has provided quantitative insights into viral infections such as influenza, the simian immunodeficiency virus/human immunodeficiency virus, hepatitis B, and hepatitis C. Through modeling, we can estimate the half-life of infected cells, the exponential growth rate, and the basic reproduction number (R0). To calculate R0 from virus load data, the death rate of productively infected cells is required. This can be readily estimated from treatment data collected during the chronic phase, but is difficult to determine from acute infection data. Here, we propose two new models that can reliably estimate the average life span of infected cells from acute-phase data, and apply both methods to experimental data from humanized mice infected with HIV-1.Both new models, called as the reduced quasi-steady state (RQS) model and the piece-wise regression (PWR) model, are derived by simplification of a standard model for the acute-phase dynamics of target cells, viruses and infected cells. By having only a limited number of parameters, both models allow us to reliably estimate the death rate of productively infected cells. Simulated datasets with plausible parameter values are generated with the standard model to compare the performance of the new models with that of the major previous model (i.e., the simple exponential model). Finally, we fit models to time course data from HIV-1 infected humanized mice to estimate the several important parameters characterizing their acute infection.Results and conclusions: The new models provided much better estimates than the previous model because they more precisely capture the de novo infection process. Both models describe the acute phase of HIV-1 infected humanized mice reasonably well, and we estimated an average death rate of infected cells of 0.61 and 0.61, an average exponential growth rate of 0.69 and 0.76, and an average basic reproduction number of 2.30 and 2.38 in the RQS model and the PWR model, respectively. These estimates are fairly close to those obtained in humans.