Towards a New Spatial Representation of Bone Remodeling

Irregular bone remodeling is associated with a number of bone diseases such as osteoporosis and multiple myeloma. Computational and mathematical modeling can aid in therapy and treatment as well as understanding fundamental biology. Different approaches to modeling give insight into different aspects of a phenomena so it is useful to have an arsenal of various computational and mathematical models. Here we develop a mathematical representation of bone remodeling that can effectively describe many aspects of the complicated geometries and spatial behavior observed. There is a sharp interface between bone and marrow regions. Also the surface of bone moves in and out, i.e. in the normal direction, due to remodeling. Based on these observations we employ the use of a level-set function to represent the spatial behavior of remodeling. We elaborate on a temporal model for osteoclast and osteoblast population dynamics to determine the change in bone mass which influences how the interface between bone and marrow changes. We exhibit simulations based on our computational model that show the motion of the interface between bone and marrow as a consequence of bone remodeling. The simulations show that it is possible to capture spatial behavior of bone remodeling in complicated geometries as they occur \emph{in vitro} and \emph{in vivo}. By employing the level set approach it is possible to develop computational and mathematical representations of the spatial behavior of bone remodeling. By including in this formalism further details, such as more complex cytokine interactions and accurate parameter values, it is possible to obtain simulations of phenomena related to bone remodeling with spatial behavior much as \emph{in vitro} and \emph{in vivo}. This makes it possible to perform \emph{in silica} experiments more closely resembling experimental observations.Comment: Math. Biosci. Eng., 9(2), 201

An automated carotid pulse assessment approach using Doppler ultrasound

During cardiac arrest emergencies, lay rescuers are required to manually check the patient's carotid pulse after the delivery of defibrillation shocks to assess the cardiac resuscitation progress of the patient. As a more automated way of monitoring the resuscitation progress, a new Doppler-ultrasound-based carotid pulse assessment approach is presented in this paper. The method works by analyzing the temporal aperiodicity of Doppler shifts seen in the ultrasound echoes returned from the patient's carotid arteries. As a quantitative investigation with this method, we derived a new measure called the pulselessness indicator to assess whether a carotid pulse is absent based on the given Doppler information. To study the performance of the new carotid pulse checking method, we built a multi-channel CW Doppler prototype device to acquire Doppler data in vivo during cardiac arrest experiments conducted on five different swines and computed pulselessness indicator estimates with these data. Our results indicated that the Doppler-based pulse checking approach has good sensitivity and specificity: it had a pulselessness detection rate greater than 0.9 for a given false alarm rate of 0.05. As a further analysis, the prototype device was applied to other experiments where the swine had suffered cardiac arrest for over five minutes. It showed a consistent assessment performance on the monitoring of the swine's resuscitation progress after defibrillation and chest compressions. © 2006 IEEE.published_or_final_versio

Modeling and Simulation of the Effects of Cyclic Loading on Articular Cartilage Lesion Formation

We present a model of articular cartilage lesion formation to simulate the effects of cyclic loading. This model extends and modifies the reaction-diffusion-delay model by Graham et al. 2012 for the spread of a lesion formed though a single traumatic event. Our model represents "implicitly" the effects of loading, meaning through a cyclic sink term in the equations for live cells. Our model forms the basis for in silico studies of cartilage damage relevant to questions in osteoarthritis, for example, that may not be easily answered through in vivo or in vitro studies. Computational results are presented that indicate the impact of differing levels of EPO on articular cartilage lesion abatement

Performance evaluation of a digital electrical impedance tomography system

Performance evaluation of a portable digital multi-frequency electrical impedance tomography system is presented. The instrumentation hardware and image reconstruction are assessed according to a systematic methodology using a practical phantom. The phantom is equipped with eight electrodes in a ring configuration and a sinusoidal current of constant amplitude is injected using an adjacent current injection protocol. Artificial anomalies are introduced as inhomogeneity targets and the boundary potential data is collected. The images are reconstructed from the boundary data using Comsol Multiphysics and Matlab. Signal to noise ratio (SNR) and accuracy of the measurements are calculated. The limits of detectability and distinguishability of contrasts are measured from the collected potential data set for single and double inhomogeneities. The conductivity of the targets is successfully reconstructed from the potential data measurements. The detectability value is found to be high when a single target is close to the electrodes, while the values are less for the target in the centre. Also, the value of distinguishability increases when the targets move further away from each other

Investigating learning theories in social networks; providing a theoretical framework for curriculum design

Background and Objectives: To use social media effectively, we need to identify and apply the implications of supportive theories using social media. Different learning theories provide a variety of interpretations of learning. Different learning theories lead to diverse orientations and outcomes in curriculum planning. Therefore, learning theories serve as a framework for guiding decisions during the design and implementation of the curriculum. The aim of this study was to identify the types of learning theories that support the use of social networks and to analyze learning theories on social networks in order to provide a theoretical basis for designing curricula. Methods: For this study, qualitative content analysis method was used. The statistical population of this study consists of all valid documents related to the subject- supportive theories of learning in social networks- from 1995 to 2018 (n=30) selected based on purposeful sampling. The content of 30 documents were analyzed.  The analysis unit is the theme. To analyze the findings, the main and sub-classes were extracted after open coding. To ensure the validity of the research, the methods of review by members, triangulation of data sources and review by colleagues were used, and to ensure reliability, the agreement method between the two coders was used. Findings: The findings showed a variety of context-based, community-based, and person-centered theories that support learning on social media. The findings also include four main categories: It showed the dimensions of social networks, network interactions, types of learning, and curriculum elements. It was shown that network communication in social networks includes social interaction, interpersonal communication and interactive communication with admin and teacher-student communication, which is broad and based on community sharing, central agreement and based on sharing ideas. Types of learning on social networks include; network learning, situational learning, problem-based learning, personal learning, and indirect learning. Elements of the curriculum include; network objectives, network content, network learning environment, network inclusiveness, and network evaluation. Network Objectives; features such as unpredictability, divergence, unpredictability, variability, nonlinearity, flexibility, value, reproductive and interactive. Network content has some features such as distributed knowledge, multiplicity of resources, reliable resources, accessibility, context-based knowledge, shared knowledge, inclusive knowledge, self-centered information, voluntary knowledge creation, interchangeable content. The network environment includes technical and educational features. Among the technical features of this environment, we can mention the diversity of language, the existence of communication tools, the possibility of customizing the message and simulating communication. The educational features of this environment also include; being rich is one of the tools of knowledge management, situational awareness, personalized information, open and flexible environment. The network learner is knowledgeable and up-to-date, independent and active, able to do several things together. The network learner is an actor, and social agent who processes, publishes, and manages knowledge on a regular basis. Evaluation on social media is a nonlinear process, formative, conscious, and continuous that is accompanied by the elimination of standard rankings and tests. Conclusion: Based on the research results, it is suggested that those in charge of education use the coordinates of social network-based curriculum elements to design a curriculum based on social networks. For further research it is suggested that researchers implement the findings in an experimental environment to take a positive step towards the optimal use of social networks to learners’ learning outcome.   ===================================================================================== COPYRIGHTS  ©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================

Association of RS4784227-casc16 (Loc643714 locus) and RS4782447-ACSF3 polymorphisms and their association with breast cancer risk among iranian population

Peer reviewedPublisher PD

ELF3 is an antagonist of oncogenic-signalling-induced expression of EMT-TF ZEB1

Background: Epithelial-to-mesenchymal transition (EMT) is a key step in the transformation of epithelial cells into migratory and invasive tumour cells. Intricate positive and negative regulatory processes regulate EMT. Many oncogenic signalling pathways can induce EMT, but the specific mechanisms of how this occurs, and how this process is controlled are not fully understood. Methods: RNA-Seq analysis, computational analysis of protein networks and large-scale cancer genomics datasets were used to identify ELF3 as a negative regulator of the expression of EMT markers. Western blotting coupled to siRNA as well as analysis of tumour/normal colorectal cancer panels was used to investigate the expression and function of ELF3. Results: RNA-Seq analysis of colorectal cancer cells expressing mutant and wild-type β-catenin and analysis of colorectal cancer cells expressing inducible mutant RAS showed that ELF3 expression is reduced in response to oncogenic signalling and antagonizes Wnt and RAS oncogenic signalling pathways. Analysis of gene-expression patterns across The Cancer Genome Atlas (TCGA) and protein localization in colorectal cancer tumour panels showed that ELF3 expression is anti-correlated with β-catenin and markers of EMT and correlates with better clinical prognosis. Conclusions: ELF3 is a negative regulator of the EMT transcription factor (EMT-TF) ZEB1 through its function as an antagonist of oncogenic signalling