Day 2 :
- Biomedical engineering | Cell&Tissue engineering | Bioinformatics | Biophysics | Bio-systems engineering| Biosensors | Bioelectronics | Types of Biosensors | Biosensing Technologies | Nanotechnology in Biosensors | Enzymatic Biosensors | Environmental Biosensors.
Chair
Mahmoud F Almasri.
University of Missouri USA.
Session Introduction
Thanh Duc Nguyen
University of Connecticut, USA
Title: Novel processing of biodegradable and biocompatible polymers at small scales for medical applications
Time : 13:45-14:10
Biography:
Thanh Duc Nguyen has joined the Departments of Mechanical Engineering and Biomedical Engineering at UConn at the beginning of 2016. His research is highly interdisciplinary and at the interface of biomedicine, materials and nano/micro technology. He did his Post-doctoral Fellowship with Dr. Robert Langer at MIT. His Post-doctoral research involved developing a platform technology which can create 3-dimensional microstructures of biomaterials, such as biodegradable and FDA-approved polymers for applications in vaccine/drug delivery and medical implants. In 2013, he obtained his PhD from Princeton University in the Department of Mechanical and Aerospace Engineering. There, he worked with Dr. Michael McAlpine to develop the field of biointerfaced nanopiezoelectrics, which aims to create advanced electromechanical materials/devices at nanoscales that can interface with biological cells/tissues for applications in harvesting, sensing and engineering cellular mechanics. His work has been published in prestigious journals and highlighted in major media such as The New York Times and Nature.
Abstract:
Biodegradable polymers have a significant impact to medical field. The polymers have been extensively used for medical sutures, tissue engineering scaffolds and drug carriers. In this talk, I will present two researches which aim to further fabricate and process the polymers at small scales, enabling their special functions for use in important medical devices. The first part of this talk will be focused on a novel manufacturing technology, which allows creating versatile 3D microstructures of biodegradable polymers for vaccine/drug delivery. The second part of this talk will be emphasized on a novel approach, which enables the polymers to be electromechanically-active for use in an implanted biodegradable force-sensor, which could measure tiny vital bio-physiological forces such as trans-diaphragmatic/trans-pulmonary pressures. The presented works, while significantly enhancing functionality and usefulness of the polymers, do not compromise their excellent biodegradability and biocompatibility for medical use. We anticipate many other applications in health monitoring, drug delivering, tissue engineering etc. will be generated from the presented technology and method.
Zifeng Yang
Wright State University, USA
Title: A novel optical flow method for intravascular blood velocimetry: A validation study
Time : 14:10-14:35
Biography:
Zifeng Yang has completed his PhD and Post-doctoral studies from Iowa State University Department of Aerospace Engineering. He is an Assistant Professor at Wright State University. He has published more than 20 papers in reputed journals and has been serving as an Editorial Board Member of Journal of Coastal Life Medicine.
Abstract:
Intravascular blood velocity map can be obtained by applying optical flow method (OFM) in processing fluoroscopic digital subtracted catheter angiographic images, however, there are still challenges with the accuracy of results from OFM. In the present study, an improved OFM, in which a non-zero divergence of velocity is assumed due to the finite resolution of the image, was explored and applied to the digital subtraction angiography (DSA) x-ray images. The objective of the present study is to examine the applicability and accuracy of the divergence-compensatory optical flow method (DC-OFM) in assessing the velocity of blood flow in vessels. First, an Oseen vortex flow was simulated on the standard particle image to generate an image pair. Then, the DC-OFM was utilized to recover the velocity field for validation from the particle image pair. Second, DSA images of intracranial arteries were used to examine the accuracy of the current method. For each set of images, the first image is the in vivo DSA image, and the second image is generated by superimposing a given flow field. The recovered velocity map from the DC-OFM agrees well with the exact velocity distribution for both the particle images and angiographic images. In comparison with traditional OFM, the present method can provide much more accurate velocity estimation. It is also found that the accuracy of the velocity estimation can also be improved by implementing pre-process techniques including image intensification, Gaussian filter and “image -shift”.
Janet Roveda
University of Arizona, USA
Title: Sleep apnea prognosis for pediatric applications
Time : 14:35-15:00
Biography:
Janet Roveda is a Professor in the Department of Electrical and Computer Engineering and the Department of Biomedical Engineering at the University of Arizona in Tucson. She received her MS and PhD degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 1998 and 2000, respectively. She was a recipient of the NSF Career Award and the Presidential Early Achievement Award for Science and Engineering at White House in 2005 and 2006, respectively. She was the recipient of the 2017 Da Vinci Fellow at the College of Engineering, Univ. of Arizona, the 2008 R Newton Graduate Research Award from the EDA community, the 2007 USS University of Arizona Outstanding Achievement Award. She has over 120 publications.
Abstract:
This children and adult sleep apnea prognosis system employs an IoT application portal, to perform sleep apnea prognosis, to help with sleep apnea diagnosis, to monitor sleep apnea treatment, and to offer personal health education. The core component of the system is a set of machine learning algorithms. Our system allows a couple of low cost sleep apnea devices to reach high accurate sleep apnea monitoring/diagnosis/prognosis results, although we use high end devices such Phillips’ products in the development of our prototype system. We also plan to develop wearable sensors, such as pulse oximeter pulse oximeters, electrocardiogram (ECG) sensors, and electroencephalogram (EEG) sensors to work with our system and to provide optimal care and cost balance. Comparing with other sleep apnea questionnaires, our new system provides personalized questionnaires. The backend data mining program monitors patients’ responses and adjust the contents of the questionnaires in real time. One key application of our new system is pediatric sleep apnea. Most sleep care products are currently focused only on adults. However, sleep apnea also has serious impacts on children's brain development. At least 2% of children have sleep apnea in the US. Most parents, however, never realize that their children have sleep apnea. Compared with adults, children in general have higher oxygen saturation levels, faster heart beats, and very different physiological measurements that change as they age. Sleep apnea among children requires a different set of indexes and thresholds in terms of measurements. With a different set of parameters, features and indices, specifically designed for the pediatric sleep apnea application, our tools can provide accurate diagnosis for children with apnea, and stimulate their patients to seek medical care. Our system employs 3D simulation to monitor sleep quality and apnea treatment results, with real time feedback from treatment devices. Coupled with physiological sensors, the new system can improve the dynamic treatment regimes (DTRs) by using reinforcement learning algorithms.
Richa Kothari
University of Nebraska-Lincoln, USA
Title: H-LCBF - Harvesting of Chlorella sp. with low-cost bio-flocculant: An approach for clean environment with bioprocess engineering
Time : 15:00-15:25
Biography:
Richa Kothari has completed his MPhil and PhD (2005) in the Field of Energy and Environment from Devi Ahilya Unversity, Indore, India. She is working as an Assistant Professor (2008) and Deputy Co-ordinator for MSc -Energy and Environment at Babasaheb Bhimrao Ambedkar University, Lucknow, UP, India. Presently, she is a WARI Fellow, (Department of Biochemistry and Department of Civil Engineering), Robert B Daugherty Water for Food Institute, University of Nebraska-Lincoln, Lincoln,NE, USA under Indo-US Science and Technology Forum. She has published more that 50 papers in reputed journals and book chapters. She has guided research and post-graduate students and has published two books. She has been serving as an Editotrial Board Member of repute in her field.
Abstract:
Harvesting of Chlorella sp. with low-cost bio-flocculant: An approach for clean environment with bioprocess engineering (H-LCBF): In order to use microalgae as a feedstock for biofuels and other bioproducts, optimal conditions must be established for harvesting following growth. Prior to downstream bio-processing including cell disruption, oil extraction and trans-esterification for biodiesel production, the microalga must be harvested, dewatered and dried. The common harvesting methods include chemical flocculation, centrifugation, and pressurized filtration. The application of chemical flocculants is problematic with the algal cell surfaces requiring long incubation times following cell growth that result in increased costs. Various process parameters i.e. pH, temperature, contact time, flocculent dose, mixing rate, ionic strength, and settling time etc. are act an influencing ones during biomass harvesting. To overcome these barriers, the development of a bio-flocculant and its engineering chemistry (zeta (ïº) potential) for harvesting algae was the key objective in this experimental study. Egg-shell materials were developed as an effective bio-flocculant for harvesting different Chlorella sp. Various concentrations of this material (0-100 mg/L) along with differences in contact times (0-50 minutes) were employed to analyze harvesting efficiency. It was found that maximal harvesting (95.6%) was achieved with 100 mg/L of the egg-shell bio-flocculant. Using 100 mg egg-shell bio-flocculant/L, ïº potential analyses were completed to further understand the chemistry leading to maximized harvesting efficiency over a range of pH (2, 4, 8, and 10). These studied defined the influence of pH and in particular demonstrated that maximal harvesting efficiency (99%) was accomplished at a pH of 4. Collectively, these studies found key relationships between the ïº potential and pH that positively impact harvesting efficiency as the first step in bio-processing, which is seen as a boon for a sustainable biofuel economy.
Jae-Hyung Jang
Yonsei University, South Korea
Title: Intelligent electrospun nanofibrous matrices for gene and cell therapy applications
Time : 15:25-15:45
Biography:
Jae-Hyung Jang has completed his PhD from Northwestern University (Evanston, IL) and performed Post-doctoral works at University of California, Berkeley. He is an Associate Professor of Yonsei University, and he has been working on the development of adeno-associated virus-mediated gene delivery tools and biomaterial systems that can be applied for cell delivery vehicles or 3D scaffolds.
Abstract:
Spatial networks of natural extracellular matrix (ECM) fibers are closely related to tissue/organ phenotypes, cellular differentiation and proliferation, soluble factor secretion, and other important biochemical signaling processes. Therefore, the ECM plays key roles in regulating numerous important biological events in the body. Thus, strategies for mimicking the fibrous morphology of the natural ECM can serve as a valuable platform for creating a favorable environment or for constructing an infrastructure that effectively manipulates cellular behaviors. Electrospinning is a representative methodology that can be used to artificially construct fibrous networks; the resulting electrospun fibrous constructs have served as powerful templates in many biomedical fields (e.g., tissue engineering, drug delivery, gene delivery, and cell therapy) to complement the key functions of the natural ECM. Therefore, several high-impact studies have proposed smart technologies that significantly improved the technical aspects of electrospun fibers; such novel structures include hierarchical fibrous structures, three-dimensional fluffy fibrous sponges, spatially patterned fibrous matrices, and multi-layered fibrous constructs. Several powerful electrospun fibrous scaffolds that can be used as delivery vehicles for carrying therapeutic genes or cells will be discussed in this presentation.
Meenakshi Singh
Banaras Hindu University, India
Title: Epitope-imprinted polymers for diagnostics
Time : 15:45-16:10
Biography:
Meenakshi Singh received her PhD from Banaras Hindu University, Varanasi, India in 1995. She has joined as Assistant Professor in Department of Chemistry, MMV, Banaras Hindu University in 2005, later on as Associate Professor in 2012. Her research interests include polyelectrolytes, hydrogels and organogels, molecular imprinting (MIP) and MIP sensors. She is experienced in designing the novel polymeric formats for crafting molecular recognition elements to device sensors for biomolecules/drugs using molecular imprinting. She has published many papers in peer-reviewed reputed international journals and supervised few PhD and Master’s students in the field of Analytical Chemistry.
Abstract:
Epitope sequences are unique combination of amino acids sequence positioned on exposed domains of proteins. Molecular imprinting is a promising technique for creating molecular receptors with recognition and binding sites that are chemically and sterically complementary in shape, size and functionality to the predetermined target molecules in synthetic polymer. This approach creates template-shaped cavities in polymer matrices with memory of template molecules to be used in molecular recognition. Imprinting whole protein denatures the tertiary and quaternary structures of protein in the polymer matrix and complexity and flexibility of its structure cannot be sustained in the polymer matrix. Epitope approach offers a way out of such snags. The epitope-imprinted film revealed high selectivity over the target protein and allow tolerance for even a single amino acid mismatch between the epitope and target protein. Bioinformatics tools were adapted to search epitope sequences of Neisseria meningitides, a human-specific bacterial pathogen which causes bacterial meningitis by invading the meninges of central nervous system. High mortality rate associated with the disease therefore requires proper medical diagnosis and early treatment. Diagnosing bacterial meningitis is currently cumbersome and involves isolating the bacteria from sterile cerebrospinal fluid (CSF) through lumbar puncture followed by observing presence of meningococci under microscope by a neurologist. T-cell epitopes from outer membrane proteins Por B present on the exposed surface of immunogenic loops of Class 3 OMP allele of N. Meningitides as well as another epitope sequence identified from N. meningitides iron acquisition protein viz. an iron regulated outer membrane protein frpB. These epitopes are used for designing a diagnostic tool via molecularly imprinted piezoelectric sensor (MIP-QCM) for N. meningitides strain MC58. The epitope can be simultaneously bound to functional monomer and fitted into the shape-selective cavities. On extraction of epitope sequence from thus grafted polymeric film, shape-selective and sensitive sites were generated on EQCM crystal i.e known as epitope imprinted polymers (EIPs). Imprinting was characterized by atomic force microscopy images. The epitope-imprinted sensor was able to selectively bind Neisseria meningitides proteins present in blood serum of patients suffering from brain fever. Thus fabricated sensors can be used as a diagnostic tool for meningitis disease.