Molecular Dynamics and Docking Investigations of Several Zoanthamine- Type Marine Alkaloids as Matrix Metaloproteinase-1 Inhibitors

Zoanthamine-type alkaloids display a wide spectrum of biological effects. This study aimed to examine the inhibitory effects of norzoanthamine and its ten homologues of zoanthamine class on human fibroblast collagenase by modeling a three-dimensional structure of the ligands at collagenase using energy minimization, docking, molecular dynamics simulation and MM-PB/GBSA binding free energy calculations. The results showed that zoanthamide, zooxathellamine and enol-iminium form of norzoanthamine, with lower binding free energies than other compounds, are potent inhibitors of collagenase. However, the enol-iminium form of norzoanthamine showed a more inhibitory activity against collagenase than its keto form. This suggests that it can be used for treatment of many diseases such as osteoporosis, autoimmune diseases, and cancer. Zinc-binding residues such as His 118, His 122 and His 128 for hydrogen bonds and Leu 81, Tyr 110, Val 115, Leu 126, Pro 138, Ser 139 for hydrophobic interactions should be considered for designing an inhibitor for collagenase. Our theoretical results and MM/GBSA binding free energy calculations are consistent with experimental studies. Abbreviation MD: Molecular dynamics; RMSD: Root mean square deviation; MM-PB/GBSA: Molecular mechanics Poisson-Boltzmann/General Born surface area, DFT: density functional theory, B3LYP: Becke, three-parameter, Lee-Yang-Parr, RESP: Restrained electrostatic surfacepotentia

Column Generation-Based Techniques for Intensity-Modulated Radiation Therapy (IMRT) and Volumetric Modulated Arc Therapy (VMAT) Treatment Planning

RÉSUMÉ: Les statistiques ont estimé à environ 14,1 millions le nombre de cas de cancer en 2018 dans le monde, et qui devrait passer à 24 millions d’ici 2035. La radiothérapie est l’une des premières méthodes de traitement du cancer, qu’environ 50% des patients reçoivent au cours de leur maladie. Cette méthode endommage le matériel génétique des cellules cancéreuses, détruisant ainsi leur capacité de reproduction. Cependant, les cellules normales sont également affectées par le rayonnement ; par conséquent, le traitement doit être effectué de manière à maximiser la dose de rayonnement aux tumeurs, tout en minimisant les effets néfastes des radiations sur les tissus sains. Les techniques d’optimisation sont utilisées afin de déterminer la dose et la position du rayonnement à administrer au corps du patient. Ce projet aborde la radiothérapie externe à travers la radiothérapie par modulation d’intensité (IMRT), ainsi qu’une nouvelle forme appelée modulation d’intensité volumétrique par thérapie par arcs (VMAT). En IMRT, un nombre fini de directions sont déterminées pour le rayonnement du faisceau, tandis qu’en VMAT l’accélérateur linéaire tourne autour du corps du patient alors que le faisceau est allumé. Cette technologie permet de modifier dynamiquement la forme du faisceau et le débit de dose pendant le traitement. Le problème de planification du traitement consiste à choisir une séquence de distribution des formes de faisceaux, à optimiser le dé bit de dose du faisceau et à déterminer la vitesse de rotation du portique, si nécessaire. Cette recherche tire profit de la méthode de génération de colonnes, en tant que méthode d’optimisation efficace en particulier pour les problèmes à grande échelle. Cette technique permet d’améliorer le temps de traitement et les objectifs cliniques non linéaires et non convexes, dans la planification de traitement en VMAT. Un nouveau modèle multi-objectif de génération de colonnes pour l’IMRT est également développé. Dans le premier essai, nous développons un nouvel algorithme de génération de colonnes qui optimise le compromis entre le temps et la qualité du traitement délivré pour la planification de traitement en VMAT. Pour ce faire, une génération simultanée de colonnes et de rangées est développée, afin de relier les colonnes, contenant la configuration des ouvertures de faisceaux, aux rangées du modèle, représentant la restriction de temps de traitement. De plus, nous proposons une technique de regroupement par grappe modifiée, afin d’agréger des éléments de volume similaires du corps du patient, et de réduire efficacement le nombre de contraintes dans le modèle. Les résultats de calcul montrent qu’il est possible d’obtenir un traitement de haute qualité sur quatre processeurs en parallèle. Dans le deuxième essai, nous développons une approche de planification automatique intégrant les critères de l’histogramme dose-volume (DVH). Les DVH sont la représentation de dose la plus courante pour l’évaluation de la qualité de traitement en technologie VMAT. Nous profitons de la procédure itérative de génération de colonnes pour ajuster les paramètres du modèle lors de la génération d’ouverture, et répondre aux critères DVH non linéaires, sans tenir compte des contraintes dures dans le modèle. Les résultats sur les cas cliniques montrent que notre méthodologie a été significativement améliorée, pour obtenir des plans cliniquement acceptables sans intervention humaine par rapport à une simple optimisation VMAT. De plus, la comparaison avec un système de planification de traitement commercial existant montre que la qualité des plans obtenus à partir de la méthode proposée, en particulier pour les tissus sains, est largement meilleure alors que le temps de calcul est moindre. Dans le troisième essai, nous abordons la planification de traitement en IMRT, qui est formulée comme un problème d’optimisation convexe à grande échelle, avec un espace de faisabilité simplex. Nous intégrons d’abord une nouvelle approche de solution basée sur la méthode Frank-Wolfe, appelée Blended Conditional Gradients, dans la génération de colonnes, pour améliorer les performances de calcul de la méthode. Nous proposons ensuite une technique de génération de colonnes multi-objectif, pour obtenir directement des ouvertures qui se rapprochent d’un ensemble efficace de plans de traitement non dominés. A cette fin, nous trouvons les limites inférieure et supérieure du front de Pareto, et générons une colonne avec un vecteur de poids des objectifs pré-assigné ou nouveau, réduisant la distance maximale de deux bornes. Nous prouvons que cet algorithme converge vers le front de Pareto. Les résultats de recherche d’un bon compromis de traitement entre la destruction des volumes cibles et la protection des structures saines dans un espace objectif bidimensionnel, montrent l’efficacité de l’algorithme dans l’approche du front de Pareto, avec des plans de traitement livrables en 3 minutes environ, et évitant un grand nombre de colonnes. Cette méthode s’applique également à d’autres classes de problèmes d’optimisation convexe, faisant appel à la fois à une génération de colonnes et à une optimisation multi-objectifs.----------ABSTRACT: The statistics have estimated about 18.1 million cancer cases in 2018 around the world, which is expected to increase to 24 million by 2035. Radiation therapy is one of the most important cancer treatment methods, which about 50% of patients receive during their illness. This method works by damaging the genetic material within cancerous cells and destroying their ability to reproduce. However, normal cells are also affected by radiation; therefore, the treatment should be performed in such a way that it maximizes the dose of radiation to tumors, while simultaneously minimizing the adverse effects of radiations to healthy tissues. The optimization techniques are useful to determine where and how much radiation should be delivered to patient’s body. In this project, we address the intensity-modulated radiation therapy (IMRT) as a widelyused external radiotherapy method and also a novel form called volumetric modulated arc therapy (VMAT). In IMRT, a finite number of directions are determined for the beam radiation, while in VMAT, the linear accelerator rotates around the patient’s body while the beam is on. These technologies give us the ability of changing the beam shape and the dose rate dynamically during the treatment. The treatment planning problem consists of selecting a delivery sequence of beam shapes, optimizing the dose rate of the beam, and determining the rotation speed of the gantry, if required. In this research, we take advantages of the column generation technique, as a leading optimization method specifically for large-scale problems, to improve the treatment time and non-linear non-convex clinical objectives in VMAT treatment planning, and also develop a new multi-objective column generation framework for IMRT. In the first essay, we develop a novel column generation algorithm optimizing the trade-off between delivery time and treatment quality for VMAT treatment planning. To this end, simultaneous column-and-row generation is developed to relate the configuration of beam apertures in columns to the treatment time restriction in the rows of the model. Moreover, we propose a modified clustering technique to aggregate similar volume elements of the patient’s body and efficiently reduce the number of constraints in the model. The computational results show that a high-quality treatment is achievable using a four-thread CPU. In the second essay, we develop an automatic planning approach integrating dose-volume histogram (DVH) criteria, the most common method of treatment evaluation in practice, for VMAT treatment planning. We take advantage of the iterative procedure of column generation to adjust the model parameters during aperture generation and meet nonlinear DVH criteria without considering hard constraints in the model. The results on clinical cases show that our methodology had significant improvement to obtain clinically acceptable plans without human intervention in comparison to simple VMAT optimization. In addition, the comparison to an existing commercial treatment planning system shows the quality of the obtained plans from the proposed method, especially for the healthy tissues, is significantly better while the computational time is less. In the third essay, we address the IMRT treatment planning, which is formulated as a large scale convex optimization problem with simplex feasibility space. We first integrate a novel Frank-Wolfe-based solution approach, so-called Blended Conditional Gradients, into the column generation to improve the computational performance for the method. We then propose a multi-objective column generation technique to directly obtain apertures that approximate an efficient non-dominated set of treatment plans. To this end, we find lower and upper bounds for the Pareto front and generate a column with a pre-assigned or new weight-vector of the objectives, reducing the maximum distance of two bounds. We prove this algorithm converges to the Pareto front. The results in a two-dimensional objective space to find the trade-off plans between the treat of target volumes and sparing the healthy structures show the efficiency of the algorithm to approximate the Pareto front with deliverable treatment plans in about 3 minutes, avoiding a large number of columns. This method is also applicable for other classes of convex optimization problems requiring both column generation and multi-objective optimization

In silico designing and creation a new generation of reteplase with more fibrin specificity

Introduction: Reteplase is a fibrin-specific thrombolytic drug and non-glycosylated modified recombinant form of human tissue plasminogen activator (t-PA). It is containing kringle-2 and serine protease domains but the epidermal growth factor and fibronectin finger domains are absent. The lack of finger domain in reteplase cause decrease fibrin specificity. Since the enhancing fibrin specificity is one of the aim for development new thrombolytic drug, due to decreasing side effect such as hemorrhage, also reteplase is non-glycosylated and can be produced in bacterial system at low cost, in this study a new generation of reteplase designed with more fibrin specificity.  Methods and Results: According to the sequence of protein drugswith more fibrin specificity, mutations in reteplase sequence consist of substitution mutation in Kringle 2 domains and adding sequence of mutated finger domain to reteplase sequence. 3D structure of this new reteplase was created by Modeller9.17 software and then simulated by Gromacs 5 software for 20 ns. Docking simulation was performed between new and wild reteplase with fibrin by HADDOCK server separately. The results showed that new reteplase has better interaction with fibrin compared with wild type (table1). Parameter Wild reteplase New  reteplase HADDOCK score* -35.8 +/- 8.3 -43.2 +/- 21.3             *More negative score is better score  Conclusions: In this study a new generation of reteplase with more fibrin specificity was designed in silico. Since the production of reteplase has low cost compared with tPA, improvement its structure to desirable features such as increasing fibrin specificity, can be a way to achieve a favorable thrombolytic drug

The first attempt on fabrication of a nano-biosensing platform and exploiting first-order advantage from impedimetric data: application to simultaneous biosensing of doxorubicin, daunorubicin and idarubicin

In this work, for the first time, we have developed a novel and very interesting electroanalytical methodology assisted by first-order multivariate calibration (MVC) for simultaneous determination of doxorubicin (DX), daunorubicin (DN) and idarubicin (ID) as three chemotherapeutic drugs at simulated physiological conditions. A sever overlapping was observed among signals of the three drugs which hindered us for simultaneous determination of them by conventional electroanalytical techniques. Therefore, we had to assist our method by chemometric approaches to develop a novel method for simultaneous determination of DX, DN and ID. Among the existing electroanalytical methods, electrochemical impedance spectroscopy (EIS) due to its high sensitivity was chosen. After individual calibration of the three drugs with the EIS data, a set of calibration samples was designed which was used to develop several first-order MVC models by partial least squares (PLS), continuum power regression (CPR), radial basis function-partial least squares (RBF-PLS), RBF-artificial neural network (RBF-ANN) and least squares-support vector machines (LS-SVM) as linear and non-linear chemometric algorithms. Then, performance of the developed MVC models in predicting concentrations of DX, DN and ID in synthetic samples was compared to choose the best model for the analysis of real samples. Our records confirmed more superiority of RBF-PLS algorithm than the other developed models which motivated us to choose it for the analysis of real samples. Fortunately, the results of the RBF-PLS in the analysis of real samples towards simultaneous determination DX, DN and ID was acceptable.Fil: Soleimani, Shokoufeh. Kermanshah University Of Medical Sciences; IránFil: Arkan, Elham. Kermanshah University Of Medical Sciences; IránFil: Farshadnia, Tooraj. Kermanshah University Of Medical Sciences; IránFil: Mahnam, Zahra. Kermanshah University Of Medical Sciences; IránFil: Jalili, Faramarz. Kermanshah University Of Medical Sciences; IránFil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Bioquímica y Ciencias Biológicas. Laboratorio de Desarrollo Analítico y Quimiometría; ArgentinaFil: Jalalvand, Ali R.. Kermanshah University Of Medical Sciences; Irá

Conditioning electrical impedance mammography system

A multi-frequency Electrical Impedance Mammography (EIM) system has been developed to evaluate the conductivity and permittivity spectrums of breast tissues, which aims to improve early detection of breast cancer as a non-invasive, relatively low cost and label-free screening (or pre-screening) method. Multi-frequency EIM systems typically employ current excitations and measure differential potentials from the subject under test. Both the output impedance and system performance (SNR and accuracy) depend on the total output resistance, stray and output capacitances, capacitance at the electrode level, crosstalk at the chip and PCB levels. This makes the system design highly complex due to the impact of the unwanted capacitive effects, which substantially reduce the output impedance of stable current sources and bandwidth of the data that can be acquired. To overcome these difficulties, we present new methods to design a high performance, wide bandwidth EIM system using novel second generation current conveyor operational amplifiers based on a gyrator (OCCII-GIC) combination with different current excitation systems to cancel unwanted capacitive effects from the whole system. We reconstructed tomography images using a planar E-phantom consisting of an RSC circuit model, which represents the resistance of extra-cellular (R), intra-cellular (S) and membrane capacitance (C) of the breast tissues to validate the performance of the system. The experimental results demonstrated that an EIM system with the new design achieved a high output impedance of 10MΩ at 1MHz to at least 3MΩ at 3MHz frequency, with an average SNR and modelling accuracy of over 80dB and 99%, respectively

Evaluation of a low-cost and low-noise active dry electrode for long-term biopotential recording

Wet Ag/AgCl electrodes, although very popular in clinical diagnosis, are not appropriate for expanding applications of wearable biopotential recording systems which are used repetitively and for a long time. Here, the development of a low-cost and low-noise active dry electrode is presented. The performance of the new electrodes was assessed for recording electrocardiogram (ECG) and electroencephalogram (EEG) in comparison with that of typical gel-based electrodes in a series of long-term recording experiments. The ECG signal recorded by these electrodes was well comparable with usual Ag/AgCl electrodes with a correlation up to 99.5% and mean power line noise below 6.0 μVRMS. The active electrodes were also used to measure alpha wave and steady state visual evoked potential by recording EEG. The recorded signals were comparable in quality with signals recorded by standard gel electrodes, suggesting that the designed electrodes can be employed in EEG-based rehabilitation systems and brain-computer interface applications. The mean power line noise in EEG signals recorded by the active electrodes (1.3 μVRMS) was statistically lower than when conventional gold cup electrodes were used (2.0 μVRMS) with a significant level of 0.05, and the new electrodes appeared to be more resistant to the electromagnetic interferences. These results suggest that the developed low-cost electrodes can be used to develop wearable monitoring systems for long-term biopotential recording

Development of a Assistive Human-Computer device Based On Electro-Oculogram for Disabled People

Objective: In the study, a novel wearable miniaturized human computer interface system was designed and implemented. It allowed disabled people, who are not able to move their limbs voluntarily and speech overtly, to express their intentions and feelings just by moving their eyes. Materials & Methods: The developed system that is installed on a pair of glasses, records the electrooculogram signal and transfers the digitized data wirelessly to a laptop. Realtime analysis of the signals allows users to utilize two high performance graphical user interfaces a keypad and a game, just by their eye movements. The performance of the developed system was tested on six normal people, who typed a total number of 1071 characters successfully, to evaluate accuracy and rate of typing. It was also tested by four people with quadriplegia and cerebral palsy who performed a computer game by using their eye movements. Results: According to results of the experiments on normal people, the accuracy of recognizing the user's intention was obtained 94.1% and the average rate of communication was 7.72 characters per minute. Evaluating the usability of the system for disabled people showed that they were able to perform the computer game using their eyes. The percentage of success was evaluated as an average of 58.7%. Conclusion: The proposed system recorded and processed elecrooculogram signals with appropriate quality. The final prototype of the system was 2.6 cm× 4.5 cm in size and weighted only 15 grams. The total power consumption was measured as 123 mW. The designed keypad provided selection of each character by minimum eye movements. The system assures high performance for communication as well as high level of mobility and comfort for everyday use

Molecular dynamics and docking investigations of several zoanthamine-type marine alkaloids as matrix metaloproteinase-1 inhibitors

Zoanthamine-type alkaloids display a wide spectrum of biological effects. This study aimed to examine the inhibitory effects of norzoanthamine and its ten homologues of zoanthamine class on human fibroblast collagenase by modeling a three-dimensional structure of the ligands at collagenase using energy minimization, docking, molecular dynamics simulation and MM-PB/GBSA binding free energy calculations. The results showed that zoanthamide, zooxathellamine and enol-iminium form of norzoanthamine, with lower binding free energies than other compounds, are potent inhibitors of collagenase. However, the enol-iminium form of norzoanthamine showed a more inhibitory activity against collagenase than its keto form. This suggests that it can be used for treatment of many diseases such as osteoporosis, autoimmune diseases, and cancer. Zinc-binding residues such as His 118, His 122 and His 128 for hydrogen bonds and Leu 81, Tyr 110, Val 115, Leu 126, Pro 138, Ser 139 for hydrophobic interactions should be considered for designing an inhibitor for collagenase. Our theoretical results and MM/GBSA binding free energy calculations are consistent with experimental studies

The Impact of Task-Based Language Teaching on the Development of Iranian EFL Learners’ ESP Reading Comprehension Skills

The present study primarily aimed at investigating the effect of Task-Based Language Teaching (TBLT) on development of the Iranian EFL learners’ ESP Reading Comprehension Skills. Moreover, it was aimed at investigating the probable difference between the TBLT-instructed students of Law and Mechanical Engineering with respect to their ESP reading skills, on the one hand, and the probable difference between TBLT-instructed males and females, on the other. In so doing, four groups of 25 participants (including two experimental groups and two control ones) were selected through cluster random sampling from among ESP students majoring in Law and Mechanical Engineering. After a four-week instruction treatment, the post-test was conducted to the participants. The results of the data analysis revealed that the experimental groups significantly performed better than the control groups in the post-test with respect to their reading comprehension scores. Furthermore, the results of independent samples t-test indicated that TBLT has been more effective on the Mechanical Engineering students than the Law students. Finally, the findings of the study were indicative of the fact that TBLT was more effective on females’ reading comprehension rather than on males’. Consequently, it can be concluded that TBLT can have a positive effect on students’ ESP reading ability. The findings of this study can be employed in different areas of second/foreign language teaching and learning to facilitate and improve the process of language learning.