Journal d'informatique et de biologie des systèmes

Biological databases related to medical science, containing pathological, radiological and genetic information of patients is undergoing tremendous growth, beyond our analyzing capability. However such analysis can reveal new findings about the cause and subsequent treatment of any disease. Here the genetic information of Lung Adenocarcinoma, in the form of microarray dataset has been investigated which have five different stages. Rough Set Theory (RST) has been used in analysis with an aim to effectively extract biologically relevant information, as RST is a tool that works well in an environment, heavy with inconsistent and ambiguous data, or with missing data and provides efficient algorithms for finding hidden patterns in data. The investigation has been carried out on the publicly available microarray dataset obtained from the GEO profiles at National Centre for Biotechnology Information (NCBI) website. Cross validation of the generated rule sets shows 100% accuracy. Now to extract the hidden biological dependencies between responsible genes, Decision Tree is used at consecutive two stages of cancer development to identify the main culprit genes for cancer development from one stage to another and that may lead to the drug design. The analysis revealed that hybrid Rough- Decision Tree is able to extract hidden relationships among the various genes which play an important role in causing the disease and also able to provide a unique rule set for automated medical diagnosis. Moreover at the end, the functions of the identified genes are studied and validated from Gene Ontology website DAVID which clearly shows the direct or indirect relation of genes with the cancer. This study highlights the usefulness and efficiency of RST and Decision Tree in the disease diagnosis process and its potential use in inductive learning and as a valuable aid for building more biologically significant expert systems in medical sciences

We discuss how integration of back action into coupled rate equations describing dynamical biophysical processes can lead the identification of optimized structural features. This approach is applied to analyze neural receptor binding and function. In functional receptor studies, the influence of ligand binding to the receptor on free ligand concentration in the synaptic cleft is rarely considered, especially when the number of ligand molecules vastly exceeds the number of receptors. Here we evaluate the role of ligand binding/unbinding to the receptor on ligand concentration and the resulting change in receptor dynamics using the example of glutamate interaction with the AMPA receptor subtype of glutamate receptors. We find a significant difference for AMPA receptor-mediated current between the free diffusion case, where binding/unbinding is neglected, and the case when glutamate binding to AMPA receptors is taken into account for evaluating free ligand concentration. Furthermore, taking into account receptor binding/unbinding reveals new properties of the receptor/neurotransmitter system, and in particular, indicates the existence of an optimum receptor density profile with an optimal radius where the total charge and peak current are maximal, a property that cannot be captured by the free diffusion case. This may provide an explanation for the disposition of AMPA receptors and the synaptic geometry based on the optimization of the receptor-mediated current.

A homeomorphic model of the human eye has been developed to simulate the effect of impact forces on the internal components of the eye. This is the first time a Mass-Spring-Damper (MSD) model has been used to investigate forces and displacements throughout the outer tunic, the vitreous body, and the retina. Whereas most of the existing Finite Element Models (FEM) are extremely complicated in their structure and composition, and takes up to 6-10 hours for a single simulation run, our MSD model, with its inherent computational advantages, completes a single round of simulation within tens of seconds. The model also provides detailed information about the node positions, velocities and force profiles, with a special emphasis on the retina. Moreover, a prediction paradigm was developed to indicate the estimated extent of retinal damage based on the angle and magnitude of the applied forces. Further, a user-friendly GUI was developed to allow additional new investigations into ocular trauma. The results of the model simulations under various force impact conditions were shown to be accurate and consistent with known experimental findings. Thus, our homeomorphic MSD model can be a useful tool for the physician to assess retinal damage non-invasively prior to clinical intervention.

Bovine patella cartilage shows signs of damage and cell death when subjected to a compressive cyclic load of 6 MPa, which results in a shear stress of 5.6 MPa. The aim of this research was to investigate the effect of activities of daily living (descending stairs, bicycling and deep flexion) on the contact stresses in the patellofemoral compartment following an articular chondrocyte implantation (ACI). A finite element (FE) model of the patellar femoral joint was created and dynamic non-linear analyses were carried out for this purpose. A shear stress of 5.6 MPa was used as the threshold that cartilage can tolerate without resulting in damage. The FE model was verified numerically. Our results show that, for a 70 kg individual at 50% recovery, (i) contact stress in the patella is 11% higher than that in the femur; (ii) shear stress in the host cartilage reaches 4.75 MPa at 50° of flexion; (iii) shear stress in the patella host cartilage is twice that in a healthy cartilage during deep flexion approaching 70°; (iv) maximum shear stress value was 2.75 MPa during cycling at 60% load; (v) stress shielding still occurs through the host cartilage even when the implanted cartilage reaches 97.5% the Young’s modulus of a healthy cartilage. Based on these results, (i) using an exercise bicycle is recommended for rehabilitation; (ii) deep knee flexion should be avoided; (iii) obese people with a BMI of over 42 kg/m2 should not undertake vigorous weight-bearing exercises involving deep knee flexion.

The orthognathic surgery is the standard treatment for the correction of dentofacial deformities, in order to get a stable dental occlusion and facial harmony. The advancement of technology and the evolution of the concepts involved in the diagnosis and treatment plan in this area have been immeasurable, leading to the development of new methods, such as computer-aided jaw surgery system by a three-dimensional (3D) virtual surgical planning. The advent of the cone-beam computed tomography (CBCT) allows the acquisition of 3D images of the patient’s craniofacial complex and eliminates the ambiguity that can occur with two-dimensional (2D) images. Surgical simulation in 3D may benefit patients by providing a more accurate treatment plan and streamlined surgery, especially for patients with complex dentofacial deformities. The breakthrough of software tools for the diagnosis and treatment planning allows the construction of 3D surface models, dynamic cephalometry, semi-automatic mirroring in cases of asymmetry, interactive cutting of bone, bony segment repositioning, 3D splint manufacturing, bone reconstruction and visualization and prediction of the changes in hard and soft tissues of the face. The aim of this study was to report a case where the computed-assisted surgical planning predicts the possibility in achieving balance between aesthetic and function. Alterations in the virtual planning allow overcoming obstacles in actual surgery. Considering all possible details, the process provides greater predictability, practicality and precision in surgical planning.