Symphysis
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB44108 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR5690973_1.fastq.gz | Fastqsanger.gz | |||
| ERR5690973_2.fastq.gz | Fastqsanger.gz | |||
| ERR5690974_1.fastq.gz | Fastqsanger.gz | |||
| ERR5690974_2.fastq.gz | Fastqsanger.gz |
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Similar Datasets
Project description:This a model from the article:
A mathematical model of bone remodeling dynamics for normal bone cell populations and myeloma bone disease
Bruce P Ayati, Claire M Edwards, Glenn F Webb and John P Wikswo.
Biology Direct2010 Apr 20;5(28).
20406449,
Abstract:
BACKGROUND:
Multiple myeloma is a hematologic malignancy associated with the development of a destructive osteolytic bone disease.
RESULTS:
Mathematical models are developed for normal bone remodeling and for the dysregulated bone remodeling that occurs in myeloma bone disease. The models examine the critical signaling between osteoclasts (bone resorption) and osteoblasts (bone formation). The interactions of osteoclasts and osteoblasts are modeled as a system of differential equations for these cell populations, which exhibit stable oscillations in the normal case and unstable oscillations in the myeloma case. In the case of untreated myeloma, osteoclasts increase and osteoblasts decrease, with net bone loss as the tumor grows. The therapeutic effects of targeting both myeloma cells and cells of the bone marrow microenvironment on these dynamics are examined.
CONCLUSIONS:
The current model accurately reflects myeloma bone disease and illustrates how treatment approaches may be investigated using such computational approaches.
Note:
The paper describes three models 1) Zero-dimensional Bone Model without Tumour, 2) Zero-dimensional Bone Model with Tumour and 3) Zero-dimensional Bone Model with Tumour and Drug Treatment. This model corresponds to the Zero-dimensional Bone Model without Tumour.
Typos in the publication:
Equation (4): The first term should be (β1/α1)^(g12/Γ) and not (β2/α2)^(g12/Γ)
Equation (14): The first term should be (β1/α1)^(((g12/(1+r12))/Γ) and not (β2/α2)^(((g12/(1+r12))/Γ)
Equation (13): The first term should be (β1/α1)^((1-g22+r22)/Γ) and not (β1/α1)^((1-g22-r22)/Γ)
All these corrections has been implemented in the model, with the authors agreement.
Beyond these, there are several mismatches between the equation numbers that are mentioned in for each equation and the reference that has been made to these equations in the figure legend.
2024-09-02 | BIOMD0000000401 | BioModels
Project description:This a model from the article:
A mathematical model of bone remodeling dynamics for normal bone cell populations and myeloma bone disease
Bruce P Ayati, Claire M Edwards, Glenn F Webb and John P Wikswo.
Biology Direct2010 Apr 20;5(28).
20406449,
Abstract:
BACKGROUND:
Multiple myeloma is a hematologic malignancy associated with the development of a destructive osteolytic bone disease.
RESULTS:
Mathematical models are developed for normal bone remodeling and for the dysregulated bone remodeling that occurs in myeloma bone disease. The models examine the critical signaling between osteoclasts (bone resorption) and osteoblasts (bone formation). The interactions of osteoclasts and osteoblasts are modeled as a system of differential equations for these cell populations, which exhibit stable oscillations in the normal case and unstable oscillations in the myeloma case. In the case of untreated myeloma, osteoclasts increase and osteoblasts decrease, with net bone loss as the tumor grows. The therapeutic effects of targeting both myeloma cells and cells of the bone marrow microenvironment on these dynamics are examined.
CONCLUSIONS:
The current model accurately reflects myeloma bone disease and illustrates how treatment approaches may be investigated using such computational approaches.
Note:
The paper describes three models 1) Zero-dimensional Bone Model without Tumour, 2) Zero-dimensional Bone Model with Tumour and 3) Zero-dimensional Bone Model with Tumour and Drug Treatment. This model corresponds to the Zero-dimensional Bone Model with Tumour.
Typos in the publication:
Equation (4): The first term should be (β1/α1)^(g12/Γ) and not (β2/α2)^(g12/Γ)
Equation (14): The first term should be (β1/α1)^(((g12/(1+r12))/Γ) and not (β2/α2)^(((g12/(1+r12))/Γ)
Equation (13): The first term should be (β1/α1)^((1-g22+r22)/Γ) and not (β1/α1)^((1-g22-r22)/Γ)
All these corrections has been implemented in the model, with the authors agreement.
Beyond these, there are several mismatches between the equation numbers that are mentioned in for each equation and the reference that has been made to these equations in the figure legend.
2024-09-02 | BIOMD0000000402 | BioModels
Project description:This a model from the article:
A mathematical model of bone remodeling dynamics for normal bone cell populations and myeloma bone disease
Bruce P Ayati, Claire M Edwards, Glenn F Webb and John P Wikswo.
Biology Direct2010 Apr 20;5(28).
20406449,
Abstract:
BACKGROUND:
Multiple myeloma is a hematologic malignancy associated with the development of a destructive osteolytic bone disease.
RESULTS:
Mathematical models are developed for normal bone remodeling and for the dysregulated bone remodeling that occurs in myeloma bone disease. The models examine the critical signaling between osteoclasts (bone resorption) and osteoblasts (bone formation). The interactions of osteoclasts and osteoblasts are modeled as a system of differential equations for these cell populations, which exhibit stable oscillations in the normal case and unstable oscillations in the myeloma case. In the case of untreated myeloma, osteoclasts increase and osteoblasts decrease, with net bone loss as the tumor grows. The therapeutic effects of targeting both myeloma cells and cells of the bone marrow microenvironment on these dynamics are examined.
CONCLUSIONS:
The current model accurately reflects myeloma bone disease and illustrates how treatment approaches may be investigated using such computational approaches.
Note:
The paper describes three models 1) Zero-dimensional Bone Model without Tumou
r, 2) Zero-dimensional Bone Model with Tumour and 3) Zero-dimensional Bone Model with Tumour and Drug Treatment. This model corresponds to the Zero-dimensional Bo
ne Model with Tumour and Drug Treatment.
Typos in the publication:
Equation (4): The first term should be (β1/α1)^(g12/Γ) and not (β2/α2)^(g12/Γ)
Equation (14): The first term should be (β1/α1)^(((g12/(1+r12))/Γ) and not (β2/α2)^(((g12/(1+r12))/Γ)
Equation (13): The first term should be (β1/α1)^((1-g22+r22)/Γ) and not (β1/α1)^((1-g22-r22)/Γ)
All these corrections has been implemented in the model, with the authors agreement.
Beyond these, there are several mismatches between the equation numbers that are mentioned in for each equation and the reference that has been made to these equations in the figure legend.
2024-09-02 | BIOMD0000000403 | BioModels
Project description:Jason M. Graham, Bruce P. Ayati, Sarah A. Holstein & James A. Martin. The role of osteocytes in targeted bone remodeling: a mathematical model. PLoS ONE 8, 5 (2013).
Until recently many studies of bone remodeling at the cellular level have focused on the behavior of mature osteoblasts and osteoclasts, and their respective precursor cells, with the role of osteocytes and bone lining cells left largely unexplored. This is particularly true with respect to the mathematical modeling of bone remodeling. However, there is increasing evidence that osteocytes play important roles in the cycle of targeted bone remodeling, in serving as a significant source of RANKL to support osteoclastogenesis, and in secreting the bone formation inhibitor sclerostin. Moreover, there is also increasing interest in sclerostin, an osteocyte-secreted bone formation inhibitor, and its role in regulating local response to changes in the bone microenvironment. Here we develop a cell population model of bone remodeling that includes the role of osteocytes, sclerostin, and allows for the possibility of RANKL expression by osteocyte cell populations. We have aimed to give a simple, yet still tractable, model that remains faithful to the underlying system based on the known literature. This model extends and complements many of the existing mathematical models for bone remodeling, but can be used to explore aspects of the process of bone remodeling that were previously beyond the scope of prior modeling work. Through numerical simulations we demonstrate that our model can be used to explore theoretically many of the qualitative features of the role of osteocytes in bone biology as presented in recent literature.
2024-09-02 | BIOMD0000000721 | BioModels
Project description:Primary outcome(s): To investigate the variations of bone mineral densities (DEXA) and bone turnover markers (NTX and BAP) between baseline and 16 weeks after.
| 2626430 | ecrin-mdr-crc
Project description:This a model from the article:
Mathematical model of paracrine interactions between osteoclasts and osteoblasts predicts anabolic action of parathyroid hormone on bone.
Komarova SV.
Endocrinology.2005 Aug;146(8):3589-95.
15860557,
Abstract:
To restore falling plasma calcium levels, PTH promotes calcium liberation from bone. PTH targets bone-forming cells, osteoblasts, to increase expression of the cytokine receptor activator of nuclear factor kappaB ligand (RANKL), which then stimulates osteoclastic bone resorption. Intriguingly, whereas continuous administration of PTH decreases bone mass, intermittent PTH has an anabolic effect on bone, which was proposed to arise from direct effects of PTH on osteoblastic bone formation. However, antiresorptive therapies impair the ability of PTH to increase bone mass, indicating a complex role for osteoclasts in the process. We developed a mathematical model that describes the actions of PTH at a single site of bone remodeling, where osteoclasts and osteoblasts are regulated by local autocrine and paracrine factors. It was assumed that PTH acts only to increase the production of RANKL by osteoblasts. As a result, PTH stimulated osteoclasts upon application, followed by compensatory osteoblast activation due to the coupling of osteoblasts to osteoclasts through local paracrine factors. Continuous PTH administration resulted in net bone loss, because bone resorption preceded bone formation at all times. In contrast, over a wide range of model parameters, short application of PTH resulted in a net increase in bone mass, because osteoclasts were rapidly removed upon PTH withdrawal, enabling osteoblasts to rebuild the bone. In excellent agreement with experimental findings, increase in the rate of osteoclast death abolished the anabolic effect of PTH on bone. This study presents an original concept for the regulation of bone remodeling by PTH, currently the only approved anabolic treatment for osteoporosis.
The model reproduces Figures 1B and 2A of the reference publication. To obtain the figures 1B, the parameter g21 needs changes. To obtain the figures 1A, the parameters g21, g12 and k2 need to changed. For details look at the curation tab.
The initial concentration of Osteoclasts (x1) is corrected to 1.06066 from 10.06066.
This model was taken from the
CellML repository and automatically converted to SBML.
The original model was:
CellMLdetails
The original CellML model was created by:
Lloyd, Catherine, May
c.lloyd@auckland.ac.nz
The University of Auckland
The Bioengineering Institute
This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
For more information see the terms of use.
To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.
2024-09-02 | BIOMD0000000279 | BioModels
Project description:Background
This work focuses on the computational modelling of osteomyelitis, a bone pathology caused by bacteria infection (mostly Staphylococcus aureus). The infection alters the RANK/RANKL/OPG signalling dynamics that regulates osteoblasts and osteoclasts behaviour in bone remodelling, i.e. the resorption and mineralization activity. The infection rapidly leads to severe bone loss, necrosis of the affected portion, and it may even spread to other parts of the body. On the other hand, osteoporosis is not a bacterial infection but similarly is a defective bone pathology arising due to imbalances in the RANK/RANKL/OPG molecular pathway, and due to the progressive weakening of bone structure.
Results
Since both osteoporosis and osteomyelitis cause loss of bone mass, we focused on comparing the dynamics of these diseases by means of computational models. Firstly, we performed meta-analysis on a gene expression data of normal, osteoporotic and osteomyelitis bone conditions. We mainly focused on RANKL/OPG signalling, the TNF and TNF receptor superfamilies and the NF-kB pathway. Using information from the gene expression data we estimated parameters for a novel model of osteoporosis and of osteomyelitis. Our models could be seen as a hybrid ODE and probabilistic verification modelling framework which aims at investigating the dynamics of the effects of the infection in bone remodelling. Finally we discuss different diagnostic estimators defined by formal verification techniques, in order to assess different bone pathologies (osteopenia, osteoporosis and osteomyelitis) in an effective way.
Conclusions
We present a modeling framework able to reproduce aspects of the different bone remodeling defective dynamics of osteomyelitis and osteoporosis. We report that the verification-based estimators are meaningful in the light of a feed forward between computational medicine and clinical bioinformatics
Model is encoded by Ruby and submitted and curated to BioModels by Ahmad Zyoud
2024-09-02 | BIOMD0000000923 | BioModels
Project description:Peterson2010 - integrated calcium homeostasis
and bone remodelling
This model is described in the article:
A physiologically based
mathematical model of integrated calcium homeostasis and bone
remodeling.
Peterson MC, Riggs MM.
Bone 2010 Jan; 46(1): 49-63
Abstract:
Bone biology is physiologically complex and intimately
linked to calcium homeostasis. The literature provides a wealth
of qualitative and/or quantitative descriptions of cellular
mechanisms, bone dynamics, associated organ dynamics, related
disease sequela, and results of therapeutic interventions. We
present a physiologically based mathematical model of
integrated calcium homeostasis and bone biology constructed
from literature data. The model includes relevant cellular
aspects with major controlling mechanisms for bone remodeling
and calcium homeostasis and appropriately describes a broad
range of clinical and therapeutic conditions. These include
changes in plasma parathyroid hormone (PTH), calcitriol,
calcium and phosphate (PO4), and bone-remodeling markers as
manifested by hypoparathyroidism and hyperparathyroidism, renal
insufficiency, daily PTH 1-34 administration, and receptor
activator of NF-kappaB ligand (RANKL) inhibition. This model
highlights the utility of systems approaches to physiologic
modeling in the bone field. The presented bone and calcium
homeostasis model provides an integrated mathematical construct
to conduct hypothesis testing of influential system aspects, to
visualize elements of this complex endocrine system, and to
continue to build upon iteratively with the results of ongoing
scientific research.
This model is hosted on
BioModels Database
and identified by:
BIOMD0000000613.
To cite BioModels Database, please use:
BioModels Database:
An enhanced, curated and annotated resource for published
quantitative kinetic models.
To the extent possible under law, all copyright and related or
neighbouring rights to this encoded model have been dedicated to
the public domain worldwide. Please refer to
CC0
Public Domain Dedication for more information.
2024-09-02 | BIOMD0000000613 | BioModels
Project description:This trial compares cryoablation combined with stereotactic body radiation therapy to stereotactic body radiation therapy alone to see how well they work in treating patients with pain from cancer that has spread to the bones (bone metastases). Bone is a common site of metastasis in advanced cancer, and bone metastases often result in debilitating cancer-related pain. The current standard of care to treat painful bone metastases is radiation therapy alone. However, many patients do not get adequate pain relief from radiation therapy alone. Another type of therapy that may be used to provide pain relief from bone metastases is cryoablation. Cryoablation is a procedure in which special needles are inserted into the tumor site. These needles grow ice balls at their tips to freeze and kill cancer cells. The goal of this trial is to compare how well cryoablation in combination with radiation therapy works to radiation therapy alone when given to cancer patients to provide pain relief from bone metastases.
| 2362665 | ecrin-mdr-crc
Project description:This a model from the article:
Mathematical model predicts a critical role for osteoclast autocrine regulation in the control of bone remodeling.
Komarova SV, Smith RJ, Dixon SJ, Sims SM, Wahl LM Bone2003 Aug;33(2):206-15 14499354,
Abstract:
Bone remodeling occurs asynchronously at multiple sites in the adult skeleton and involves resorption by osteoclasts, followed by formation of new bone by osteoblasts. Disruptions in bone remodeling contribute to the pathogenesis of disorderssuch as osteoporosis, osteoarthritis, and Paget's disease. Interactions among cells of osteoblast and osteoclast lineages are critical in the regulation of bone remodeling. We constructed a mathematical model of autocrine and paracrine interactions among osteoblasts and osteoclasts that allowed us to calculate cell population dynamics and changes in bone mass at a discrete site of bone remodeling. Themodel predicted different modes of dynamic behavior: a single remodeling cycle in response to an external stimulus, a series of internally regulated cycles of bone remodeling, or unstable behavior similar to pathological bone remodeling in Paget's disease. Parametric analysis demonstrated that the mode of dynamic behaviorin the system depends strongly on the regulation of osteoclasts by autocrine factors, such as transforming growth factor beta. Moreover, simulations demonstratedthat nonlinear dynamics of the system may explain the differing effects of immunosuppressants on bone remodeling in vitro and in vivo. In conclusion, the mathematical model revealed that interactions among osteoblasts and osteoclasts result in complex, nonlinear system behavior, which cannot be deduced from studies of each cell type alone. The model will be useful in future studies assessing the impact of cytokines, growth factors, and potential therapies on the overall process ofremodeling in normal bone and in pathological conditions such as osteoporosis and Paget's disease.
The model reproduces Fig 2A and Fig 2B of the paper. Note that the Y-axis scale is not right, the osteoblast steadystate is approximatley 212 and not 0 as depicted in the figure. Also, there is atypo in the equation for x2_bar which has been corrected here. Model successfully tested on MathSBML.
This model originates from BioModels Database: A Database of Annotated Published Models. It is copyright (c) 2005-2009 The BioModels Team.For more information see the terms of use.To cite BioModels Database, please use Le Novère N., Bornstein B., Broicher A., Courtot M., Donizelli M., Dharuri H., Li L., Sauro H., Schilstra M., Shapiro B., Snoep J.L., Hucka M. (2006) BioModels Database: A Free, Centralized Database of Curated, Published, Quantitative Kinetic Models of Biochemical and Cellular Systems Nucleic Acids Res., 34: D689-D691.
2024-09-02 | BIOMD0000000148 | BioModels