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SIMU-RAD programme: a learning tool for radiation (photons and charged particles) interaction

Abstract

Radiation education is necessary for a wide variety of people, such as radiation workers particularly for students of secondary school and higher education institution who learn radiation sciences. The fact that we could not see or feel radiation makes it difficult to understand it. The use of radiation trajectories shown on a personal computer should be useful to overcome this difficulty. In order to understand radiation behaviour inside the material, we have developed a Simu-Rad (Copyright: LY2018002738) by using Monte Carlo simulation programme. One who has no programming knowledge is able to simulate photons in a material through the developed programme. The program could become a computer aided learning tool for radiation related courses. We aim to facilitate lecturer from ‘The Traditional Classroom’ to ‘The Flipped Classroom’ for radiation education concerning in the era of IR 4.0. To validate our radiation simulator, we calculate photon linear attenuation coefficient (µ) of an aluminium material which commonly used as a filter in diagnostic radiology. µ is one of the main characteristics to understand how the radiation attenuated inside the materials. We calculate at energy photon of 662 keV (Cs-137 radiation source) to compare our results of µ with the XCOM database. Consequently, the results from the developed simulator comparable with the database verified our programme to be used for radiation study.

Open access
Diffuse reflectance spectroscopy for identification of carcinogen transformation stages in skin tissue

. Look-up table based Monte Carlo inverse model as a tool to discover liver tumors. Bachelor thesis. Lund University, 2015. [5] Reif R, A’Amar O, Bigio IJ. Analytical model of light reflectance for extraction of the optical properties in small volumes of turbid media. Appl Opt. 2007;(46)29:7317-7328. [6] van Veen RL, Amelink A, Menke-Pluymers M, et al. Optical biopsy of breast tissue using differential path-length spectroscopy. Phys Med Biol. 2005;50(11):2573-2581. [7] Bigio IJ, Mourant JR. Optical Biopsy. In: Encyclopedia of Optical Engineering

Open access
Switching from petro-plastics to microbial polyhydroxyalkanoates (PHA): the biotechnological escape route of choice out of the plastic predicament?

. Braunegg G, Lefebvre G, Renner G, Zeiser A, Haage G, Loidl-Lanthaler K. Kinetics as a tool for polyhydroxyalkanoate production optimization. Can J Microbiol 1995; 41(13): 239-248. 80. Sindhu R, Silviya N, Binod P, Pandey A. Pentose-rich hydrolysate from acid pretreated rice straw as a carbon source for the production of poly-3-hydroxybutyrate. Biochem Eng J 2013; 78: 67-72. 81. Gahlawat G, Srivastava AK. Enhancing the production of polyhydroxyalkanoate biopolymer by Azohydromonas australica using a simple empty and fill bioreactor cultivation strategy. Chem

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Formal- and high-structured kinetic process modelling and footprint area analysis of binary imaged cells: Tools to understand and optimize multistage-continuous PHA biosynthesis

microbial polyhydroxyalkanoate (PHA) biopolyesters in a sustainable manner. New Biotechnol 2017; 37(A): 24-38. 14. Narodoslawsky M, Shazad K, Kollmann R, Schnitzer H. LCA of PHA Production-Identifying the Ecological Potential of Bio-plastic. Chem Biochem Eng Q 2015; 29(2): 299-305. 15. Novak M, Koller M, Braunegg M, Horvat P. Mathematical modelling as a tool for optimized PHA production. Chem Biochem Eng Q 2015; 29(2): 183-220. 16. Kaur G, Roy I. Strategies for large-scale production of polyhydroxyalkanoates. Chem Biochem

Open access
Artificial intelligence used in genome analysis studies

Abstract

Next Generation Sequencing (NGS) or deep sequencing technology enables parallel reading of multiple individual DNA fragments, thereby enabling the identification of millions of base pairs in several hours. Recent research has clearly shown that machine learning technologies can efficiently analyse large sets of genomic data and help to identify novel gene functions and regulation regions. A deep artificial neural network consists of a group of artificial neurons that mimic the properties of living neurons. These mathematical models, termed Artificial Neural Networks (ANN), can be used to solve artificial intelligence engineering problems in several different technological fields (e.g., biology, genomics, proteomics, and metabolomics). In practical terms, neural networks are non-linear statistical structures that are organized as modelling tools and are used to simulate complex genomic relationships between inputs and outputs. To date, Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNN) have been demonstrated to be the best tools for improving performance in problem solving tasks within the genomic field.

Open access
IMRT versus 3D-CRT for thyroid cancer

References Karczmarzyk R, Dabrowski R. [Rules of defining dose in irradiated volume in thyroid cancer external photon and electron beams radiotherapy]. Nowotwory J Oncol. 1994; 44 : 349-355. Polish. Miften MM, Das SK, Su M, Marks LB. A dose-volume-based tool for evaluating and ranking IMRT treatment plans. J Appl Clin Med Phys. 2004; 5 (4): 1-14. Knoos T, Kristensen I, Nilsson P. Volumetric and dosimetric evaluation of radiation treatment plans: Radiation conformity index

Open access
A literature review on multimodality molecular imaging nanoprobes for cancer detection

Abstract

Molecular imaging techniques using nanoparticles have significant potential to be widely used for the detection of various types of cancers. Nowadays, there has been an increased focus on developing novel nanoprobes as molecular imaging contrast enhancement agents in nanobiomedicine. The purpose of this review article is to summarize the use of a variety of nanoprobes and their current achievements in accurate cancer imaging and effective treatment. Nanoprobes are rapidly becoming potential tools for cancer diagnosis by using novel molecular imaging modalities such as Ultrasound (US) imaging, Computerized Tomography (CT), Single Photon Emission Tomography (SPECT) and Positron Emission Tomography (PET), Magnetic Resonance Imaging (MRI), and Optical Imaging. These imaging modalities may facilitate earlier and more accurate diagnosis and staging the most of cancers.

Open access
Advances in biotechnology: Genomics and genome editing

Abstract

Genomics, the study of genes, their functions and related techniques has become a crucial science for developing understanding of life processes and how they evolve. Since the advent of the human genome project, huge strides have been made in developing understanding of DNA and RNA sequence information and how it can be put to good use in the biotechnology sector. Newly derived sequencing and bioinformatics tools have added to the torrent of new insights gained, so that ‘sequence once and query often’ type DNA apps are now becoming reality. Genome editing, using tools such as CRISPR/Cas9 nuclease or Cpf1 nuclease, provide rapid methods for inserting, deleting or modifying DNA sequences in highly precise ways, in virtually any animal, plant or microbial system. Recent international discussions have considered human germline gene editing, amongst other aspects of this technology. Whether or not gene edited plants will be considered as genetically modified remains an important question. This will determine the regulatory processes adopted by different groups of nations and applicability to feeding the world’s ever growing population. Questions surrounding the intellectual property rights associated with gene editing must also be resolved. Mitochondrial replacement therapy leading to ‘3-Parent Babies’ has been successfully carried out in Mexico, by an international team, to correct mother to child mitochondrial disease transmission. The UK has become the first country to legally allow ‘cautious use’ of mitochondrial donation in treatment. Genomics and genome editing will continue to advance what can be achieved technically, whilst society determines whether or not what can be done should be applied.

Open access
Dosimetrical evaluation of Leksell Gamma Knife 4C radiosurgery unit

Dosimetrical evaluation of Leksell Gamma Knife 4C radiosurgery unit

A number of experiments was performed using standard protocols, in order to evaluate the dosimetric accuracy of Leksell Gamma Knife 4C unit. Verification of the beam alignment has been performed for all collimators using solid plastic head phantom and Gafchromic™ type MD-55 films. The study showed a good agreement of Leksell Gammaplan calculated dose profiles with experimentally determined profiles in all three axes. Isocentric accuracy is verified using a specially machined cylindrical aluminium film holder tool made with very narrow geometric tolerances aligned between trunnions of 4 mm collimator. Considering all uncertainties in all three dimensions, the estimated accuracy of the unit was 0.1 mm. Dose rate at the centre point of the unit has been determined according to the IAEA, TRS-398 protocol, using Unidose-E (PTW-Freiburg, Germany) with a 0.125 cc ion chamber, over a period of 6 years. The study showed that the Leksell Gamma Knife 4C unit is excellent radiosurgical equipment with high accuracy and precision, which makes it possible to deliver larger doses of radiation, within the limits defined by national and international guidelines, applicable for stereotactic radiosurgery procedures.

Open access
Effect of electrode contact area on the information content of the recorded electrogastrograms: An analysis based on Rényi entropy and Teager-Kaiser Energy

Abstract

Electrogastrograms (EGG) are electrical signals originating from the digestive system, which are closely correlated with its mechanical activity. Electrogastrography is an efficient non-invasive method for examining the physiological and pathological states of the human digestive system. There are several factors such as fat conductivity, abdominal thickness, change in electrode surface area etc, which affects the quality of the recorded EGG signals. In this work, the effect of variations in the contact area of surface electrodes on the information content of the measured electrogastrograms is analyzed using Rényi entropy and Teager-Kaiser Energy (TKE). Two different circular cutaneous electrodes with approximate contact areas of 201.14 mm2 and 283.64 mm2, have been adopted and EGG signals were acquired using the standard three electrode protocol. Further, the information content of the measured EGG signals were analyzed using the computed values of entropy and energy. Results demonstrate that the information content of the measured EGG signals increases by 6.72% for an increase in the contact area of the surface electrode by 29.09%. Further, it was observed that the average energy increases with increase in the contact surface area. This work appears to be of high clinical significance since the accurate measurement of EGG signals without loss in its information content, is highly useful for the design of diagnostic assistance tools for automated diagnosis and mass screening of digestive disorders.

Open access