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Abstract

Type
Preface
Copyright
Copyright © Materials Research Society 2015 

Symposium I focused on the translational applications of 1D and 2D nanomaterials in health care and disease management. Nanomaterials have been proposed as key components in biosensing, imaging, and drug delivery schemes since they confer distinctive advantages over conventional approaches. In particular, the characteristic electronic and optical properties of nano carbon materials are potentially significant in diagnostic sensing and imaging in vitro and in vivo. The unique chemical and physical properties of graphene and carbon nanotubes offer opportunities to functionalize and modify developing protein transducers, therapeutic drug delivery vehicles, gene delivery systems, and microbial diagnostics (bacteria and viruses) for use in both in vitro and in vivo modes. Carbon- and non-carbon-based nanomaterials have unique properties, including the potential for transduction mechanisms that make them extremely interesting for in vitro and in vivo sensor developments in health care. Translational clinical applications include continuous monitoring of biomarkers from body fluids, which are signatures of diseases, in static and dynamic modes for home, physician’s office, and hospital use which are wirelessly transmittable by wearable devices, for example, the smart watch. The same principles can be extended to genome sequencing with major adaptation.

The complexities of managing patients with chronic diseases increasingly require a balance between care in the home and care in a clinical setting. Diabetes is just one example in which self-monitoring has been shown to be practically achievable by patients in a home setting. Glucometers are point-of-care (POC) devices that have become standard equipment at home and in clinical settings. Similarly, many other POC biosensors have also been developed [Reference Wang, Esfahani, Gurkan, Inci, Kuritzkes and Demirci1Reference Lissandrello, Inci, Francom, Paul, Demirci and Ekinci5]. Target enzymes, as disease-specific biomarkers, are often used as diagnostic indicators in such sensors because of their specificity, signal amplification, and the resulting reaction which can be electrochemically transduced or charge transfer detected by field-effect transistor (FET) for the measurement of the specific target biomarker. When these target enzymes (proteins) are immobilized on an electronically active substrate, the enzymatic reactions can be transduced by direct electron transport. This includes modifying enzymes for improved performance, developing methods to conjugate them to the nanomaterial surface, incorporating the functionalized graphene on a field-effect transistor, and integrating the process into a microfluidic device suitable for home, physician’s office, and hospital use.

Point-of-care (POC) devices [Reference Martinez, Phillips, Whitesides and Carrilho6Reference Stoot, Cairns, Cull, Taylor, Jeffrey, Morin, Mandelman, Clark and Cooke11], continuous biomedical monitoring systems, implantable devices, and non-invasive monitoring systems have significantly improved over the last twenty years. A good example is glucose sensors, which have been developed and refined significantly. However, even with substantial effort, there continue to be several challenges related to accuracy and reliability[Reference Krouwer12, Reference Klonoff and Reyes13]. Under an international standard, glucometers are required to produce results within a 20 percent margin of error, and the U.S. Food and Drug Administration (FDA) is contemplating more stringent standards [Reference Freckmann, Schmid, Baumstark, Pleus, Link and Haug14]. For this reason, coupled with knowledge gained from the previous research on glucose measurement, the ability to combine the exceptional electrical properties of emerging nanomaterials, both carbon and non-carbon-based, with the stereospecific functionality of biological macromolecules offers promising new avenues in diagnosis and treatment.

Graphene protein sensors combine the remarkable electrical properties of graphene and the selectivity of proteins with the processing power of nano-electronics and fabrication to offer new powerful diagnostic tools with much greater precision in medical science. Protein- carbon nanotube (CNT) sensors are on average several orders of magnitude greater in their sensitivity. Integrated, highly efficient, lab-on-a-chip devices based on graphene protein FET sensors that will measure clinically relevant analytes from a few μl of blood would have broad applications in bedside monitoring of patients. The nano-dimensions of graphene and its electronic properties make it an ideal candidate for anchoring the protein substrates for biochemical sensing.

Research and development for clinical diagnostic systems based on lab-on-a-chip technologies have proliferated significantly. Miniaturization can save reagents, enable rapid and inexpensive assays, and reduce the need for skilled personnel. These characteristics are important for monitoring patients at home. Home-based diagnostics and therapy monitoring simply cannot require large samples of blood plasma.

Lab-on-a-chip microfluidic devices [Reference Martinez, Phillips, Whitesides and Carrilho6Reference Issadore and Westervelt9, Reference Silva, Santhiago, Barragana and Kubota15] designed by integrating graphene and other emerging nanomaterials with improved target proteins can exploit the full potential of proteins in acting as nanosensors and nanofilters. The excellent electrical properties of graphene auger well for the next generation of handheld, ultra-portable devices for personal health-care monitoring by the patient. One could envision that with the revolution in wireless-based mobile multi-media, these hand held devices might be able to transmit the information to the physician or hospital for timely intervention. For instance, early detection of infections in patients via home monitoring could minimize chronic cases and allow those infections to be addressed early at an acute phase. This type of monitoring would minimize costs and hospitalizations, resulting in overall savings for the economy. Another potential application is screening tests for early detection of cancer biomarkers [Reference Herceg and Hainaut16]; such detection could enable treatment prior to metastasis, increasing the odds of survival.

In general, proteins and biological macromolecules offer extreme stereo-specificity and sensitivity, and can be incorporated into cutting-edge, protein-based microfluidic devices [Reference Gervais, De Rooij and Delamarche17, Reference Gervais and Delamarche18], allowing the possibility of using them for any pathological/metabolic disorder that has enzyme detection or assay titration as the basis for diagnosing, monitoring and treating diseases. This could include comprehensive metabolic panels such as liver enzymes [Reference Fallatah19], microRNA [Reference Hayes, Paolo Peruzzi and Lawler20], aspartate aminotransferase [Reference Krishnamurthy, Korenblat and Scott21], alanine aminotransferase [Reference Liu, Que, Xu and Peng22] (AST/ALT), blood urea nitrogen/creatinine [Reference Udy, O’Donoghue, D’Intini, Healy and Lipman23], blood ketone testing [Reference Charles, Bee, Eng and Goh24], cardiac biomarkers [Reference Kim, Wook Oh, Cheol Hong, Joon Mok and Choi25], prostate cancer specific biomarker PSA [Reference Barbosa, Castanheira, Edwards and Reis26], thyroid function tests [Reference Yazawa, Oonishi, Watanabe, Shiratori, Funaoka and Fukushima27] and urinary biomarkers [Reference Warrena, Kwonga, Woodc, Lin and Bhatia28] – the prospects are endless. Saliva [Reference Wong29], as well as other intra and intercellular bodily fluids, could be explored for health and disease surveillance; modifying approaches described here for salivary diagnostics, which would be especially useful in pediatrics.

The dawn of personalized medicine will herald a paradigm shift in our lives [Reference Hamburg and Collins30], just as the Internet and personal computers transformed information collection and as a result, many aspects of our professional and personal lives have been changed forever. We are moving from the inefficient medicine of today towards the data-driven medicine of tomorrow. Soon, diagnosis, prognosis, treatment, and most importantly, prevention will be tailored to individuals’ genetic and phenotypic information.

During the second decade of the 21st century, investments in molecular biology, bioinformatics, structural biology of biological macromolecules, disease management and the unraveling of the human genome [Reference Biesecker and Green31] will converge and finally bear fruit. Personalized medicine promises to revolutionize the practice of medicine, transform the global healthcare industry, and ultimately lead to longer and affordable healthier lives. Miniaturization of genome sequencing by emerging technologies such as nanopore sequencing [Reference Laszlo, Derrington, Ross, Brinkerhoff, Adey, Nova and Craig32] are contributing towards rapid genome sequencing, which will accelerate the development of personalized medicine.

Recent years have witnessed the advancement of nanotechnology within healthcare, and it pervades many aspects of a new era aptly labeled ‘nanomedicine.’ Equally, it has generated safety concerns among the scientific community. Novel properties that differentiate nanomaterials from bulk materials generally develop at a length scale of ∼100 nm. However, the size at which materials display different properties to the bulk material is material dependent. From the biological point of view, nanomaterials match the typical size of naturally occurring functional units or components of living organisms, and for this reason, enable more effective interaction with biological systems. The application of nanomaterials in medicine which may enhance quality of life can be understood from state-of-the-art knowledge on nanoscale features of biological systems in order to learn how to design nanodevices for biomedical uses. Nanomaterials have a large surface area and therefore are more chemically reactive. In addition, the nano-scale has a marked effect on the strength and electrical properties as the quantum effects dominate the behavior of materials with respect to their optical, electrical, and magnetic properties. Basically, nanomaterials fall into three categories: one-, two-, and three-dimensional. Three-dimensional nanomaterials like carbon nanotubes (CNTs) have generated considerable interest, and a significant amount of research has been done during the past decade on their potential biomedical applications. Boron nitride nanotubes (BNNT) have generated immense curiosity in view of their piezo-electric properties through which they are able to acquire an electric charge on exposure to ultrasound and polarized light.

Clinical translational research includes two areas of translation. One is the process of applying discoveries made in the laboratory (e.g., in test tubes or in animals) to the development of clinical studies using human subjects. The second area of translation refers to research intended to discover how best to apply the clinical findings to the community.

This symposium has brought together frontline researchers in a single forum.

April 2015

Acknowledgments

We would like to thank Boston Scientific Corporation International, Anarghya Innovation Pvt. Lt., and Asylum Research for financial support. We wish to thank Mr. Gurusaran Manickam of the Indian Institute of Science, Bangalore, India for his help in the preparation of the preface.

References

Wang, ShuQi, Esfahani, Matin, Gurkan, Umut A., Inci, Fatih, Kuritzkes, Daniel R., and Demirci, Utkan. “Efficient on-chip isolation of HIV subtypes.” Lab on a Chip 12, no. 8 (2012): 15081515.CrossRefGoogle ScholarPubMed
Tokel, Onur, Inci, Fatih, and Demirci, Utkan. “Advances in Plasmonic Technologies for Point of Care Applications.” Chemical reviews (2014).CrossRefGoogle ScholarPubMed
Inci, Fatih, Tokel, Onur, Wang, ShuQi, Gurkan, Umut Atakan, Tasoglu, Savas, Kuritzkes, Daniel R., and Demirci, Utkan. “Nanoplasmonic quantitative detection of intact viruses from unprocessed whole blood.” ACS nano 7, no. 6 (2013): 47334745.CrossRefGoogle ScholarPubMed
Shafiee, Hadi, Jahangir, Muntasir, Inci, Fatih, Wang, ShuQi, Willenbrecht, Remington, Giguel, Francoise F., Tsibris, Athe, Kuritzkes, Daniel R., and Demirci, Utkan. “Acute On‐Chip HIV Detection Through Label‐Free Electrical Sensing of Viral Nano‐Lysate.” Small 9, no. 15 (2013): 25532563.CrossRefGoogle ScholarPubMed
Lissandrello, C., Inci, F., Francom, M., Paul, M. R., Demirci, U., and Ekinci, K. L.. “Nanomechanical motion of Escherichia coli adhered to a surface.” Applied physics letters 105, no. 11 (2014): 113701.CrossRefGoogle ScholarPubMed
Martinez, Andres W., Phillips, Scott T., Whitesides, George M., and Carrilho, Emanuel. “Diagnostics for the developing world: microfluidic paper-based analytical devices.” Analytical chemistry 82, no. 1 (2009): 310.CrossRefGoogle Scholar
Viswanathan, Sowmya, Li, Pingzuo, Choi, Wonbong, Filipek, Slawomir, Balasubramaniam, T. A., and Renugopalakrishnan, V.. Protein–Carbon Nanotube Sensors: Single Platform Integrated Micro Clinical Lab for Monitoring Blood Analytes: In Düzgüneş, Nejat, editor: Methods in Enzymology, Vol. 509, Academic Press, 2012, pp. 165–19.Google Scholar
Viswanathan, Sowmya, Narayanan, Tharangattu N., Aran, Kiana, Fink, Kathryn D., Paredes, Jacobo, Ajayan, Pulickel M., Filipek, Slawomir, Miszta, Przemyslaw, Gurusaran, M., Cumhur Tekin, H., Inci, Fatih, Demirci, Utkan, Li, Pingzuo, Bolotin, Kirill I., Liepmann, Dorian, and Renugopalakrishanan, V.. Graphene-Protein Field Effect Biosensors: Glucose Sensing, Materials Today (revision) Google Scholar
Issadore, David, Westervelt, Robert (Eds.), Point-of-Care Diagnostics on a Chip, Series: Biological and Medical Physics, Biomedical Engineering, 2013, Springer4 CrossRefGoogle Scholar
Gerbers, Roman, Foellscher, Wilke, Chen, Hong, Anagnostopoulos, Constantine, and Faghri, Mohammad. “A new paper-based platform technology for point-of-care diagnostics.” Lab on a Chip 14, no. 20 (2014): 40424049.CrossRefGoogle ScholarPubMed
Stoot, Lauren J., Cairns, Nicholas A., Cull, Felicia, Taylor, Jessica J., Jeffrey, Jennifer D., Morin, Félix, Mandelman, John W., Clark, Timothy D., and Cooke, Steven J.. Use of portable blood physiology point-of-care devices for basic and applied research on vertebrates: a review. Conservation Physiology 2, no. 1 (2014): cou011.CrossRefGoogle ScholarPubMed
Krouwer, Jan S. “Evaluation of the Analytical Performance of the Coulometry-Based Optium Omega Blood Glucose Meter: What Do Such Evaluations Show?Journal of Diabetes Science and Technology 5, no. 6 (2011): 1618.CrossRefGoogle Scholar
Klonoff, David C., and Reyes, Juliet S.. “Do currently available blood glucose monitors meet regulatory standards? 1-day public meeting in Arlington, Virginia.” Journal of diabetes science and technology 7, no. 4 (2013): 10711083.CrossRefGoogle ScholarPubMed
Freckmann, Guido, Schmid, Christina, Baumstark, Annette, Pleus, Stefan, Link, Manuela, and Haug, Cornelia. “System accuracy evaluation of 43 blood glucose monitoring systems for self-monitoring of blood glucose according to DIN EN ISO 15197.” Journal of diabetes science and technology 6, no. 5 (2012): 10601075.CrossRefGoogle ScholarPubMed
Silva, E. T. S. G., Santhiago, M., Barragana, J. T. C. and Kubota, L. T., Construction of a new versatile point-of-care testing device with electrochemical detection employing paper as a microfluidic platform. Anal. Methods, 2014, 6, 61336136.CrossRefGoogle Scholar
Herceg, Zdenko, and Hainaut, Pierre. “Genetic and epigenetic alterations as biomarkers for cancer detection, diagnosis and prognosis.” Molecular oncology 1, no. 1 (2007): 2641.CrossRefGoogle ScholarPubMed
Gervais, Luc, De Rooij, Nico, and Delamarche, Emmanuel. “Microfluidic Chips for Point‐of‐Care Immunodiagnostics.” Advanced Materials 23, no. 24 (2011): H151H176.CrossRefGoogle ScholarPubMed
Gervais, Luc, and Delamarche, Emmanuel. “Toward one-step point-of-care immunodiagnostics using capillary-driven microfluidics and PDMS substrates.” Lab on a Chip 9, no. 23 (2009): 33303337.CrossRefGoogle ScholarPubMed
Fallatah, Hind I. “Noninvasive Biomarkers of Liver Fibrosis: An Overview.” Advances in Hepatology 2014 (2014).CrossRefGoogle Scholar
Hayes, Josie, Paolo Peruzzi, Pier, and Lawler, Sean. “MicroRNAs in cancer: biomarkers, functions and therapy.” Trends in molecular medicine 20, no. 8 (2014): 460469.CrossRefGoogle ScholarPubMed
Krishnamurthy, Smita, Korenblat, Kevin M., and Scott, Mitchell G.. “Persistent increase in aspartate aminotransferase in an asymptomatic patient.” Clinical chemistry 55, no. 8 (2009): 15731575.CrossRefGoogle Scholar
Liu, Zhengtao, Que, Shuping, Xu, Jing, and Peng, Tao. “Alanine aminotransferase-old biomarker and new concept: a review.” International journal of medical sciences 11, no. 9 (2014): 925.CrossRefGoogle ScholarPubMed
Udy, A., O’Donoghue, S., D’Intini, V., Healy, H., and Lipman, J.. “Point of care measurement of plasma creatinine in critically ill patients with acute kidney injury.” Anaesthesia 64, no. 4 (2009): 403407.CrossRefGoogle ScholarPubMed
Charles, R. A., Bee, Y. M., Eng, P. H., and Goh, S. Y.. “Point-of-care blood ketone testing: screening for diabetic ketoacidosis at the emergency department.” Singapore medical journal 48, no. 11 (2007): 986989.Google ScholarPubMed
Kim, Tae Kyum, Wook Oh, Sang, Cheol Hong, Soon, Joon Mok, Young, and Choi, Eui Yul. “Point‐of‐Care Fluorescence Immunoassay for Cardiac Panel Biomarkers.” Journal of clinical laboratory analysis (2014).CrossRefGoogle ScholarPubMed
Barbosa, Ana I., Castanheira, Ana P., Edwards, Alexander D., and Reis, Nuno M.. “A lab-in-a-briefcase for rapid prostate specific antigen (PSA) screening from whole blood.” Lab on a Chip 14, no. 16 (2014): 29182928.CrossRefGoogle ScholarPubMed
Yazawa, Yoshiaki, Oonishi, Tadashi, Watanabe, Kazuki, Shiratori, Akiko, Funaoka, Sohei, and Fukushima, Masao. “System-on-fluidics immunoassay device integrating wireless radio-frequency-identification sensor chips.” Journal of bioscience and bioengineering (2014).CrossRefGoogle ScholarPubMed
Warrena, A. D., Kwonga, G. A., D, Woodc, K., K, Lin, Y. and Bhatia, S. N.. Point-of-care diagnostics for noncommunicable diseases using synthetic urinary biomarkers and paper microfluidics. PNAS 2014, 111, 3671–3676 CrossRefGoogle Scholar
Wong, David T. “Salivary diagnostics powered by nanotechnologies, proteomics and genomics.” Journal of the American Dental Association (1939) 137, no. 3(2006): 313321.CrossRefGoogle Scholar
Hamburg, Margaret A., and Collins, Francis S.. “The path to personalized medicine.” New England Journal of Medicine 363, no. 4 (2010): 301304.CrossRefGoogle ScholarPubMed
Biesecker, Leslie G., and Green, Robert C.. “Diagnostic clinical genome and exome sequencing.” New England Journal of Medicine 370, no. 25 (2014): 24182425.CrossRefGoogle ScholarPubMed
Laszlo, Andrew H., Derrington, Ian M., Ross, Brian C., Brinkerhoff, Henry, Adey, Andrew, Nova, Ian C., Craig, Jonathan M. et al. . “Decoding long nanopore sequencing reads of natural DNA.” Nature biotechnology (2014).CrossRefGoogle ScholarPubMed