Colin Barrow, Ph.D.
Chair in Biotechnology, School of Life & Environmental Sciences, Deakin University, Australia
Nano-biotechnology: Omega-3 Oils and Nanofibres
The health benefits of long-chain omega-3 fatty acids are well established, especially for eicosapentaenoic acid (EPA) and docosapentaenoic acid (DHA) from fish and microbial sources. In fact, a billion dollar market exists for these compounds as nutritional supplements, functional foods and pharmaceuticals. This presentation will describe some aspects of our omega-3 biotechnology research that are at the intersection of Nano-biotechnology and oil chemistry. These include the use of lipases for the concentration of omega-3 fats, through immobilization of these lipases on nanoparticles, and the microencapsulation and stabilization of omega-3 oils for functional foods. I will also describe some of our work on the enzymatic production of resolvins using lipoxygenases, and the fermentation of omega-3 oils from marine micro-organisms. Finally, I will describe some of our work on the formation of amyloid fibrils and graphene for various applications in nano-biotechnology.
Deepthy Menon, Ph.D.
Associate Professor, Centre for Nanosciences & Molecular Medicine, Health Sciences Campus, Amrita University, Kochi, India
Nanobioengineering of implant materials for improved cellular response and activity
Deepthy Menon, Divyarani V V, Chandini C Mohan, Manitha B Nair, Krishnaprasad C & Shantikumar V Nair
Abstract
Current trends in biomaterials research and development include the use of surfaces with topographical features at the nanoscale (dimensions < 100 nm), which influence biomolecular or cellular level reactions in vitro and in vivo. Progress in nanotechnology now makes it possible to precisely design and modulate the surface properties of materials used for various applications in medicine at the nanoscale. Nanoengineered surfaces, owing to their close resemblance with extracellular matrix, possess the unique capacity to directly affect protein adsorption that ultimately modulates the cellular adhesion and proliferation at the site of implantation. Taking advantage of this exceptional ability, we have nanoengineered metallic surfaces of Titanium (Ti) and its alloys (Nitinol -NiTi), as well as Stainless Steel (SS) by a simple hydrothermal method for generating non-periodic, homogeneous nanostructures. The bio- and hemocompatibility of these nanotextured metallic surfaces suggest their potential use for orthopedic, dental or vascular implants. The applicability of nanotextured Ti implants for orthopedic use was demonstrated in vivo in rat models, wherein early-stage bone formation at the tissue-implant interface without any fibrous tissue intervention was achieved. This nanoscale topography also was found to critically influence bacterial adhesion in vitro, with decreased adherence of staphylococcus aureus. The same surface nanotopography also was found to provide enhanced proliferation and functionality of vascular endothelial cells, suggesting its prospective use for developing an antithrombotic stent surface for coronary applications. Clinical SS & NiTi stents were also modified based on this strategy, which would offer a suitable solution to reduce the probability of late stent thrombosis associated with bare metallic stents. Thus, we demonstrate that nanotopography on implant surfaces has a critical influence on the fate of cells, which in turn dictates the long term success of the implant.
Acknowledgement: Authors gratefully acknowledge the financial support from Department of Biotechnology, Government of India through the Bioengineering program.
Aditya Murthy, Ph.D.
Associate Professor, Centre For Neuroscience, Indian Institute of Science, Bangalore, India
Since Karl Lashley’s seminal work on the formulation of serial order, numerous models assume simultaneous representation of competitive elements of a sequence, to account for serial order effects in different types of behavior like typing, speech, etc. Such models follow two basic assumptions: (1) more than one plan representation can be simultaneously active in a planning layer; (2) the most active plan is chosen in another layer called the competitive choice layer. Using the oculomotor system I will describe behavioral and neurophysiological experiments that tests the two critical predictions of such queuing models, providing evidence that basal ganglia in monkeys and humans instantiate a form of queuing that transforms parallel movement representations into more serial representations, allowing for the expression of sequential saccadic eye movements.
Seeram Ramakrishna, Ph.D.
Director, Center for Nanofibers & Nanotechnology, National University of Singapore
Biomaterials: Future Perspectives
From the perspective of thousands of years of history, the role of biomaterials in healthcare and wellbeing of humans is at best accidental. However, since 1970s with the introduction of national regulatory frameworks for medical devices, the biomaterials field evolved and reinforced with strong science and engineering understandings. The biomaterials field also flourished on the backdrop of growing need for better medical devices and medical treatments, and sustained investments in research and development. It is estimated that the world market size for medical devices is ~300 billion dollars and for biomaterials it is ~30 billion dollars. Healthcare is now one of the fastest growing sectors worldwide. Legions of scientists, engineers, and clinicians worldwide are attempting to design and develop newer medical treatments involving tissue engineering, regenerative medicine, nanotech enabled drug delivery, and stem cells. They are also engineering ex-vivo tissues and disease models to evaluate therapeutic drugs, biomolecules, and medical treatments. Engineered nanoparticles and nanofiber scaffolds have emerged as important class of biomaterials as many see them as necessary in creating suitable biomimetic micro-environment for engineering and regeneration of various tissues, expansion & differentiation of stem cells, site specific controlled delivery of biomolecules & drugs, and faster & accurate diagnostics. This lecture will capture the progress made thus far in pre-clinical and clinical studies. Further this lecture will discuss the way forward for translation of bench side research into the bed side practice. This lecture also seeks to identify newer opportunities for biomaterials beyond the medical devices.
Manzoor K, Ph.D.
Professor, Centre for Nanoscience & Molecular Medicine, Amrita University
Targeting aberrant cancer kinome using rationally designed nano-polypharmaceutics
Manzoor Koyakutty, Archana Ratnakumary, Parwathy Chandran, Anusha Ashokan, and Shanti Nair
`War on Cancer’ was declared nearly 40 years ago. Since then, we made significant progress on fundamental understanding of cancer and developed novel therapeutics to deal with the most complex disease human race ever faced with. However, even today, cancer remains to be the unconquered `emperor of all maladies’. It is well accepted that meaningful progress in the fight against cancer is possible only with in-depth understanding on the molecular mechanisms that drives its swift and dynamic progression. During the last decade, emerging new technologies such as nanomedicine could offer refreshing life to the `war on cancer’ by way of providing novel methods for molecular diagnosis and therapy.
In the present talk, we discuss our approaches to target critically aberrant cancer kinases using rationally designed polymer-protein and protein-protein core-shell nanomedicines. We have used both genomic and proteomic approaches to identify many intimately cross-linked and complex aberrant protein kinases behind the drug resistance and uncontrolled proliferation of refractory leukemic cells derived from patients. Small molecule inhibitors targeted against oncogenic pathways in these cells were found ineffective due to the involvement of alternative survival pathways. This demands simultaneous inhibition more than one oncogenic kinases using poly-pharmaceutics approach. For this, we have rationally designed core-shell nanomedicines that can deliver several small molecules together for targeting multiple cancer signalling. We have also used combination of small molecules and siRNA for combined gene silencing together with protein kinase inhibition in refractory cancer cells. Optimized nanomedicines were successfully tested in patient samples and found enhanced cytotoxicity and molecular specificity in drug resistant cases.
Nano-polypharmaceutics represents a new generation of nanomedicines that can tackle multiple cancer mechanisms simultaneously. Considering the complexity of the disease, such therapeutic approaches are not simply an advantage, but indispensable.
Acknowledgements:
We thank Dept. of Biotechnology and Dept. Of Science and Technology,Govt. of India for the financial support through `Thematic unit of Excellence in Medical NanoBiotechnology’ and `Nanomedicine- RNAi programs’.
Srisairam Achuthan, Ph.D.
Senior Scientific Programmer, Research Informatics Division, Department of Information Sciences, City of Hope, CA, USA
Applying Machine learning for Automated Identification of Patient Cohorts
Srisairam Achuthan, Mike Chang, Ajay Shah, Joyce Niland
Patient cohorts for a clinical study are typically identified based on specific selection criteria. In most cases considerable time and effort are spent in finding the most relevant criteria that could potentially lead to a successful study. For complex diseases, this process can be more difficult and error prone since relevant features may not be easily identifiable. Additionally, the information captured in clinical notes is in non-coded text format. Our goal is to discover patterns within the coded and non-coded fields and thereby reveal complex relationships between clinical characteristics across different patients that would be difficult to accomplish manually. Towards this, we have applied machine learning techniques such as artificial neural networks and decision trees to determine patients sharing similar characteristics from available medical records. For this proof of concept study, we used coded and non-coded (i.e., clinical notes) patient data from a clinical database. Coded clinical information such as diagnoses, labs, medications and demographics recorded within the database were pooled together with non-coded information from clinical notes including, smoking status, life style (active / inactive) status derived from clinical notes. The non-coded textual information was identified and interpreted using a Natural Language Processing (NLP) tool I2E from Linguamatics.