Keynote Abstracts
Materials Research
A sustainable future through lignocellulosic biorefineries: bioprocesses and bio-based products as tools for changing the world
Prof. Dr. Silvio Silverio da Silva, Lorena School of Engineering, University of São Paulo (USP)
Lignocellulosic biorefineries play a pivotal role in sustainable development by utilizing renewable resources and green technologies to produce a diverse range of bio-based products. These innovative facilities employ efficient bioprocesses to convert non-edible plant materials into biofuels, bio-based chemicals, and biomaterials, all of which contribute to a greener and more sustainable future. By reducing reliance on fossil fuels and minimizing greenhouse gas emissions, these biorefineries promote environmental preservation and resource efficiency. The production of bio-based products in lignocellulosic biorefineries not only offers opportunities for sustainable economic growth but also fosters the development of a circular economy. Through their technological advancements, these biotechnological platforms demonstrate their transformative potential in revolutionizing industries and reducing the environmental impact. The analysis of their technological advancements, environmental benefits, and socio-economic implications underscores the significant role of lignocellulosic biorefineries in shaping a better world. Ultimately, these biorefineries hold immense promise in realizing sustainable development goals and creating a prosperous future driven by bio-based products. In this presentation, we will describe some biotechnological applications and challenges in the utilization of agroindustrial residues (lignocellulosic biomass) for the production of biobased products. Among the examples, we highlight second-generation ethanol, xylitol, biosurfactants, biopigments, biobinders for transportation, among others, in the context of biorefineries and sustainability.
Prof. Dr. Silvio Silverio da Silva, Lorena School of Engineering, University of São Paulo (USP)
Lignocellulosic biorefineries play a pivotal role in sustainable development by utilizing renewable resources and green technologies to produce a diverse range of bio-based products. These innovative facilities employ efficient bioprocesses to convert non-edible plant materials into biofuels, bio-based chemicals, and biomaterials, all of which contribute to a greener and more sustainable future. By reducing reliance on fossil fuels and minimizing greenhouse gas emissions, these biorefineries promote environmental preservation and resource efficiency. The production of bio-based products in lignocellulosic biorefineries not only offers opportunities for sustainable economic growth but also fosters the development of a circular economy. Through their technological advancements, these biotechnological platforms demonstrate their transformative potential in revolutionizing industries and reducing the environmental impact. The analysis of their technological advancements, environmental benefits, and socio-economic implications underscores the significant role of lignocellulosic biorefineries in shaping a better world. Ultimately, these biorefineries hold immense promise in realizing sustainable development goals and creating a prosperous future driven by bio-based products. In this presentation, we will describe some biotechnological applications and challenges in the utilization of agroindustrial residues (lignocellulosic biomass) for the production of biobased products. Among the examples, we highlight second-generation ethanol, xylitol, biosurfactants, biopigments, biobinders for transportation, among others, in the context of biorefineries and sustainability.
Environmental Biotechnology
"Why doesn't the grass die after a killing frost?"; the answer reveals biotech innovations
Dr. Virginia K. Walker, Queen’s University Kingston, Ontario
The plant pathogen, Pseudomonas syringae, comes to fight as a bookie favorite. It is armed with multiple weapons including beta-solenoid ice nucleating protein sabers that organize ice crystal growth when temperatures drop just below freezing. How can cereals fight against these? The low temperature defence strategy includes the transcription of antifreeze protein (AFP) genes, which protect plant membranes as well as “spoil” the bacterium's ~120 kDa protein sabers. Another domain of these AFP genes attenuates an energetically costly immune response the pathogen's flagella peptides. Indeed, microbiome analysis shows that the relative abundance of P. syringae DNA decreases from 8% to 0% after plant cold acclimation in concert with an increase in beneficial bacteria. Thus, although faced with a formidable opponent, cereal AFP gene products restrict ice growth, inhibit ice nucleation, and reduce energetically costly pattern-triggered immune responses in a remarkable “jab-cross-hook” combination that defies pathogen and freezing conditions alike. Taken together, this knowledge offers the prospect of improved cereal protection using synthetic microbial communities armed with this technology.
Dr. Virginia K. Walker, Queen’s University Kingston, Ontario
The plant pathogen, Pseudomonas syringae, comes to fight as a bookie favorite. It is armed with multiple weapons including beta-solenoid ice nucleating protein sabers that organize ice crystal growth when temperatures drop just below freezing. How can cereals fight against these? The low temperature defence strategy includes the transcription of antifreeze protein (AFP) genes, which protect plant membranes as well as “spoil” the bacterium's ~120 kDa protein sabers. Another domain of these AFP genes attenuates an energetically costly immune response the pathogen's flagella peptides. Indeed, microbiome analysis shows that the relative abundance of P. syringae DNA decreases from 8% to 0% after plant cold acclimation in concert with an increase in beneficial bacteria. Thus, although faced with a formidable opponent, cereal AFP gene products restrict ice growth, inhibit ice nucleation, and reduce energetically costly pattern-triggered immune responses in a remarkable “jab-cross-hook” combination that defies pathogen and freezing conditions alike. Taken together, this knowledge offers the prospect of improved cereal protection using synthetic microbial communities armed with this technology.
Rhodosporidium toruloides as a workhorse: Decoding its benefits and burdens in biorefinery
Dr. Satinder Kaur Brar, Department of Civil Engineering, Lassonde School of Engineering, York University
With an ever-growing population, global energy demand increases, thereby contributing to the depletion of fossil resources and their limited reserves. Thereby, to lessen the environmental damage caused by fossil fuels, there has been a surge of interest in developing and producing biofuels from renewable feedstocks, such as microbial lipids. Typically, they are derived via a biochemical process using liquid hydrolysates obtained from several residues such food lignocellulosic biomass or industrial residues as a substrate. However, microbial lipid production using hydrolysates presents numerous challenges, including the need for a strain that can accumulate high lipid titers, consume five-carbon sugars (xylose and arabinose), and tolerate inhibitory compounds such as furans, phenols, and organic acids, among others. Out of several microorganisms, Rhodosporidium toruloides, an oleaginous yeast, could be a potential alternative to produce lipids. It is known that R. toruloides can accumulate lipids up to 70% of its dry cell weight, use different carbon sources, and tolerate a wide range of inhibitory compounds. However, in several studies has been reported that R. toruloides shows low lipid productivity due to culture conditions, fermentation strategies, type of substrate and presence of inhibitory compounds.
During the last decade, the exploitation of the oleaginous yeast Rhodosporidium toruloides has been increasing. This fact has generated a large amount of information related to various parameters involved mainly in the yeast performance as well as the different products obtained through its use as a biocatalyst. However, the research using R. toruloides is scattered and on development, mainly focused on metabolomics, proteomics and in silico analysis-modeling to understand the complexity of its metabolic pathway. Furthermore, there are questions regarding which substrates, methods, of cultivation strategies, are the best suited to improve their performance and increase the final yield of target products. In this sense, the current work analyzes the effect of cultivation conditions and type of substrate over the lipid and carotenoid biosynthesis capacity of Rhodosporidium toruloides using a critical meta-analysis approach. The meta-analysis is focused on the statistical assessment of the literature data using inferential and multivariate statistics with the aim to identify and predict the best working conditions and substrate in which R. toruloides can accumulate and produce microbial lipids and carotenoids.
Dr. Satinder Kaur Brar, Department of Civil Engineering, Lassonde School of Engineering, York University
With an ever-growing population, global energy demand increases, thereby contributing to the depletion of fossil resources and their limited reserves. Thereby, to lessen the environmental damage caused by fossil fuels, there has been a surge of interest in developing and producing biofuels from renewable feedstocks, such as microbial lipids. Typically, they are derived via a biochemical process using liquid hydrolysates obtained from several residues such food lignocellulosic biomass or industrial residues as a substrate. However, microbial lipid production using hydrolysates presents numerous challenges, including the need for a strain that can accumulate high lipid titers, consume five-carbon sugars (xylose and arabinose), and tolerate inhibitory compounds such as furans, phenols, and organic acids, among others. Out of several microorganisms, Rhodosporidium toruloides, an oleaginous yeast, could be a potential alternative to produce lipids. It is known that R. toruloides can accumulate lipids up to 70% of its dry cell weight, use different carbon sources, and tolerate a wide range of inhibitory compounds. However, in several studies has been reported that R. toruloides shows low lipid productivity due to culture conditions, fermentation strategies, type of substrate and presence of inhibitory compounds.
During the last decade, the exploitation of the oleaginous yeast Rhodosporidium toruloides has been increasing. This fact has generated a large amount of information related to various parameters involved mainly in the yeast performance as well as the different products obtained through its use as a biocatalyst. However, the research using R. toruloides is scattered and on development, mainly focused on metabolomics, proteomics and in silico analysis-modeling to understand the complexity of its metabolic pathway. Furthermore, there are questions regarding which substrates, methods, of cultivation strategies, are the best suited to improve their performance and increase the final yield of target products. In this sense, the current work analyzes the effect of cultivation conditions and type of substrate over the lipid and carotenoid biosynthesis capacity of Rhodosporidium toruloides using a critical meta-analysis approach. The meta-analysis is focused on the statistical assessment of the literature data using inferential and multivariate statistics with the aim to identify and predict the best working conditions and substrate in which R. toruloides can accumulate and produce microbial lipids and carotenoids.
Bio-inspired Engineering
Deciphering the Fluid Dynamics of Biological Locomotion: A Computational Framework for Advancing Bio-Inspired Flow Systems
Dr. Chengyu Li, Assistant Professor of Mechanical Engineering, Villanova University
Biology serves as a fertile ground for innovative engineering solutions, yet the intricate geometries and dynamic boundaries of biological locomotion pose significant challenges to numerical modeling in fluid dynamics. This seminar presents a cutting-edge, image-based computational approach to unravel the complex flow physics governing such biological systems, focusing on the aerodynamics of flapping flight and the hydrodynamics of metachronal swimming. Utilizing high-speed photogrammetry, we reconstruct accurate 3D geometries and dynamic motions with unprecedented detail. We then employ a specialized, in-house Cartesian-grid-based Computational Fluid Dynamics (CFD) solver to simulate intricate 3D viscous incompressible flows. The presentation will showcase examples from both previous and current projects, concluding with an insightful discussion on future directions for physics-based modeling in the development of bio-inspired aerial and underwater robotics.
Dr. Chengyu Li, Assistant Professor of Mechanical Engineering, Villanova University
Biology serves as a fertile ground for innovative engineering solutions, yet the intricate geometries and dynamic boundaries of biological locomotion pose significant challenges to numerical modeling in fluid dynamics. This seminar presents a cutting-edge, image-based computational approach to unravel the complex flow physics governing such biological systems, focusing on the aerodynamics of flapping flight and the hydrodynamics of metachronal swimming. Utilizing high-speed photogrammetry, we reconstruct accurate 3D geometries and dynamic motions with unprecedented detail. We then employ a specialized, in-house Cartesian-grid-based Computational Fluid Dynamics (CFD) solver to simulate intricate 3D viscous incompressible flows. The presentation will showcase examples from both previous and current projects, concluding with an insightful discussion on future directions for physics-based modeling in the development of bio-inspired aerial and underwater robotics.
Medical Innovations
Peptides: Transforming Natural Ligands into Therapeutics and Imaging Agents
Dr. Len Luyt, Professor, Departments of Chemistry, Oncology, Medical Imaging, Western University;Senior Scientist, London Regional Cancer Program, Lawson Health Research Institute
Peptides are becoming increasingly important targeting molecules for the discovery of cancer drugs, imaging agents and theranostics. Peptide hormones that bind to G protein-coupled receptors (GPCRs) are starting points in this development pathway and modifications are required for a natural peptide to become useful as a pharmaceutical product. In this seminar, we will explore the path taken for developing peptide drugs, such as the diabetes drug semaglutide, peptide imaging agents for cancer and peptide theranostic agents. One focus of our research is the peptide ghrelin, which is the endogenous ligand for the growth-hormone secretagogue receptor (GHSR), also referred to as the ghrelin receptor. While the primary role of ghrelin relates to appetite regulation, there is increasing evidence for the cancer associated implications of the presence of the GHSR. We have discovered a variety of fluorine-containing and metal-complexed ghrelin analogues for the purpose of molecular imaging of the GHSR and as potential diagnostic-therapeutic pairs. Through discussing the multifaceted potential of peptides for the development of drugs, imaging agents and theranostic approaches, this seminar sheds light on the promising future of peptide-based pharmaceuticals.
Dr. Len Luyt, Professor, Departments of Chemistry, Oncology, Medical Imaging, Western University;Senior Scientist, London Regional Cancer Program, Lawson Health Research Institute
Peptides are becoming increasingly important targeting molecules for the discovery of cancer drugs, imaging agents and theranostics. Peptide hormones that bind to G protein-coupled receptors (GPCRs) are starting points in this development pathway and modifications are required for a natural peptide to become useful as a pharmaceutical product. In this seminar, we will explore the path taken for developing peptide drugs, such as the diabetes drug semaglutide, peptide imaging agents for cancer and peptide theranostic agents. One focus of our research is the peptide ghrelin, which is the endogenous ligand for the growth-hormone secretagogue receptor (GHSR), also referred to as the ghrelin receptor. While the primary role of ghrelin relates to appetite regulation, there is increasing evidence for the cancer associated implications of the presence of the GHSR. We have discovered a variety of fluorine-containing and metal-complexed ghrelin analogues for the purpose of molecular imaging of the GHSR and as potential diagnostic-therapeutic pairs. Through discussing the multifaceted potential of peptides for the development of drugs, imaging agents and theranostic approaches, this seminar sheds light on the promising future of peptide-based pharmaceuticals.
A hybrid complex-valued neural network framework with applications to electroencephalograms (EEG)
Dr. Steven X. Wang, York University, Toronto, Canada
OBJECTIVES: We present a new EEG signal classification framework by integrating the complex-valued and real-valued Convolutional Neural Network (CNN) with discrete Fourier transform (DFT). Our method drastically reduces the number of parameters used and improves accuracy when compared with the existing methods in classifying benchmark seizure EEG dataset, and significantly improves performance in classifying simulated EEG signals.
METHOD: The proposed neural network architecture consists of only one complex-valued convolutional layer, real-valued convolutional layers, and fully connected layers. Our method can efficiently utilize the phase information contained in the DFT. We validate our approach using two simulated EEG signals and two benchmark datasets and compare it with some widely used frameworks.
RESULTS: If desired, the results could be reported using a line or a bar graph, preferably according to the APA formatting style. Aside from the descriptive statistics, if inferential analyses were involved the value of test statistic, degrees of freedom, and effect sizes should be reported.
CONCLUSION/IMPLICATION: We proposed a novel neural network architecture that can capture the phase information in signals by using a complex-valued convolutional layer at the very beginning. In simulations, our framework significantly improves the classification performance com-pared with other methods; furthermore, our method can reduce the number of parameters and improve the accuracy simultaneously in the experiments for the real-world dataset. Besides, our framework can be used to build a more efficient hybrid complex-valued neural network structure. It can also be applied to find proper complex-valued filters on the frequency domain without prior knowledge, which is usually tricky. Currently, all the input signals to our neural network are relatively short. In the future, we plan to improve our method such that it can be applied to classify long-term EEG signals.
Dr. Steven X. Wang, York University, Toronto, Canada
OBJECTIVES: We present a new EEG signal classification framework by integrating the complex-valued and real-valued Convolutional Neural Network (CNN) with discrete Fourier transform (DFT). Our method drastically reduces the number of parameters used and improves accuracy when compared with the existing methods in classifying benchmark seizure EEG dataset, and significantly improves performance in classifying simulated EEG signals.
METHOD: The proposed neural network architecture consists of only one complex-valued convolutional layer, real-valued convolutional layers, and fully connected layers. Our method can efficiently utilize the phase information contained in the DFT. We validate our approach using two simulated EEG signals and two benchmark datasets and compare it with some widely used frameworks.
RESULTS: If desired, the results could be reported using a line or a bar graph, preferably according to the APA formatting style. Aside from the descriptive statistics, if inferential analyses were involved the value of test statistic, degrees of freedom, and effect sizes should be reported.
CONCLUSION/IMPLICATION: We proposed a novel neural network architecture that can capture the phase information in signals by using a complex-valued convolutional layer at the very beginning. In simulations, our framework significantly improves the classification performance com-pared with other methods; furthermore, our method can reduce the number of parameters and improve the accuracy simultaneously in the experiments for the real-world dataset. Besides, our framework can be used to build a more efficient hybrid complex-valued neural network structure. It can also be applied to find proper complex-valued filters on the frequency domain without prior knowledge, which is usually tricky. Currently, all the input signals to our neural network are relatively short. In the future, we plan to improve our method such that it can be applied to classify long-term EEG signals.
Biotechnology at Lakehead University
Biotechnology is a field of study that uses living organisms or cellular and bio-molecular processes to make new products, solve problems, or provide new methods of production. Biotechnology has existed since the beginning of civilization with the domestication of plants, animals and the discovery of fermentation.
The start of the Biotechnology PhD program in 2007 strengthened Lakehead's involvement in biotechnology initiatives in Northwestern Ontario, providing opportunities for a broad range of industry partnerships. By successfully combining the focus and expertise of faculty in sciences and engineering into two interdisciplinary areas of biotechnology: Environmental Biotechnology and Medical Biotechnology, Lakehead placed itself at the forefront of cutting-edge biotechnology research in the Thunder Bay area. The Ph.D. in Biotechnology at Lakehead is a research-based, interdisciplinary graduate program focused on the professional development of scientists in theses two areas.
Scientific and technological advances have transformed biotechnology techniques, opening the door to a variety of applications in areas such as health care, the environment, forestry, and industrial processes. Lakehead is a comprehensive university with a reputation for innovative programs and relevant research.
The start of the Biotechnology PhD program in 2007 strengthened Lakehead's involvement in biotechnology initiatives in Northwestern Ontario, providing opportunities for a broad range of industry partnerships. By successfully combining the focus and expertise of faculty in sciences and engineering into two interdisciplinary areas of biotechnology: Environmental Biotechnology and Medical Biotechnology, Lakehead placed itself at the forefront of cutting-edge biotechnology research in the Thunder Bay area. The Ph.D. in Biotechnology at Lakehead is a research-based, interdisciplinary graduate program focused on the professional development of scientists in theses two areas.
Scientific and technological advances have transformed biotechnology techniques, opening the door to a variety of applications in areas such as health care, the environment, forestry, and industrial processes. Lakehead is a comprehensive university with a reputation for innovative programs and relevant research.