Implementing Professional Skills Training in STEM: A Review of the Literature

Background: Project management and other professional skill training is often lacking in graduate student education, typically as a result of limited resources, lack of faculty buy-in, and narrow focus on thesis research. To address this need and with support from NSF, we are developing the Graduates for Advancing Professional Skills (GAPS) program at Iowa State University. To aid the initial development of this program, we conducted a literature review to understand the current context of the development and implementation of professional skills in higher education curricula, with specific interest in STEM fields. Purpose: The purpose of our study was to identify best practices related to implementing professional development skills into an academic curriculum. The goal was to utilize this information in the development, planning, implementation, and assessment of our GAPS program. Design: We engaged in a systematic literature review. We focused on the curricular and pedagogical approaches to implementing these skills, results of the initiatives, and methodologies used to assess their effectiveness. Results: Our literature review uncovered the “messiness” of teaching and learning of skills such as project management. There is often not one approach or definition of project management – it may change based on scope of project and context. Successful implementation requires adaptability, mentorship, problem solving, creativity, and communication. Additionally, project management has been referred to as a “threshold concept” and requires a certain level of intuition that cannot necessarily be gained through traditional classroom education. Conclusions: There appears to be an agreement on the importance of implementing project management skills at the postsecondary level. Our work illustrates the difficulty associated with undertaking this endeavor and provides guidance on approaches that can make these initiatives more beneficial. Although this literature was conducted to aid in the planning for our specific project, the synthesis of the extant works can inform other faculty and industry leaders who are interested in teaching and applying project management techniques in their courses or companies

A Community of Practice Approach to Integrating Professional Skills Training with Graduate Thesis Research

Background. It is well recognized that current graduate education is too narrowly focused on thesis research. Graduate students have a strong desire to gain skills for their future career success beyond thesis research. This obvious gap in professional skill training in current graduate study also leads to the common student perception that professional skills beyond academic knowledge should only be gained after completion of thesis research. Purpose. A new program is being developed to rigorously integrate professional skills training with thesis research. The approach is to establish learning communities of Graduates for Advancing Professional Skills (GAPS) to incorporate project management skill training from industry into academic research. The GAPS program seeks to address two fundamental education research questions: How can project management skill training be integrated with thesis research in graduate education? What is the role/value of learning communities in enhancing the training and retention of professional skills and the effectiveness of thesis research? Our proposed solution is that graduate student learning communities engaging in a blended online and classroom approach will promote learning of professional skills such as project and time management in thesis research activities. The purpose of this session is to establish the connection between project management and thesis research, and demonstrate the beginning progress of the GAPS program towards. Methodology/approach. The following progress is being made to establish GAPS learning communities through which to teach and practice professional skills. A website has been developed to introduce the program, recruit participants, provide information on the online modules, and survey results of participants’ current levels of knowledge and skills related to project management. A new course, “Introduction of Project Management for Thesis Research”, has been added to the course catalog and open to enrollment for students from different majors. In addition, learning modules including project charter, scheduling, communication, teamwork, critical path method, and lean concept are developed. Case studies and examples have been developed to help students learn how to utilize project management skills in their thesis research. Conclusions. The concept of integrating professional skills training with thesis research through learning communities has been demonstrated. There are multiple advantages of this approach, including efficient utilization of the current resources, and faculty buy-in. Preliminary data from the first cohort are being collected and analyzed to identify students’ needs, benefits of the program, and areas of improvement for future cohort iterations. Implications. The GAPS program will improve professional skill training for graduate students through communities of practice. This new learning model has the potential to fundamentally change the culture of graduate education. We believe the method demonstrated here can be broadly applied to different engineering majors, and even broadly to all thesis research

Experimental Tools to Study Molecular Recognition within the Nanoparticle Corona

Advancements in optical nanosensor development have enabled the design of sensors using synthetic molecular recognition elements through a recently developed method called Corona Phase Molecular Recognition (CoPhMoRe). The synthetic sensors resulting from these design principles are highly selective for specific analytes, and demonstrate remarkable stability for use under a variety of conditions. An essential element of nanosensor development hinges on the ability to understand the interface between nanoparticles and the associated corona phase surrounding the nanosensor, an environment outside of the range of traditional characterization tools, such as NMR. This review discusses the need for new strategies and instrumentation to study the nanoparticle corona, operating in both in vitro and in vivo environments. Approaches to instrumentation must have the capacity to concurrently monitor nanosensor operation and the molecular changes in the corona phase. A detailed overview of new tools for the understanding of CoPhMoRe mechanisms is provided for future applications

Experimental Tools to Study Molecular Recognition within the Nanoparticle Corona

Advancements in optical nanosensor development have enabled the design of sensors using synthetic molecular recognition elements through a recently developed method called Corona Phase Molecular Recognition (CoPhMoRe). The synthetic sensors resulting from these design principles are highly selective for specific analytes, and demonstrate remarkable stability for use under a variety of conditions. An essential element of nanosensor development hinges on the ability to understand the interface between nanoparticles and the associated corona phase surrounding the nanosensor, an environment outside of the range of traditional characterization tools, such as NMR. This review discusses the need for new strategies and instrumentation to study the nanoparticle corona, operating in both in vitro and in vivo environments. Approaches to instrumentation must have the capacity to concurrently monitor nanosensor operation and the molecular changes in the corona phase. A detailed overview of new tools for the understanding of CoPhMoRe mechanisms is provided for future applications.Juvenile Diabetes Research Foundation InternationalMcGovern Institute for Brain Research at MIT. Neurotechnology (MINT) ProgramNational Science Foundation (U.S.) (Postdoctoral Research Fellowship Award DBI-1306229)Burroughs Wellcome Fund (Grant Award 1013994)German Science Foundatio

Towards Wireless Characterization of Solvated Ions with Uncoated Resonant Sensors

Uncoated resonant sensors are presented here for wireless monitoring of solvated ions, with progress made toward monitoring nitrates in agricultural runoff. The sensor, an open-circuit Archimedean coil, is wirelessly interrogated by a portable vector network analyzer (VNA) that monitors the scattering parameter response to varying ionic concentrations. The sensor response is defined in terms of the resonant frequency and the peak-to-peak amplitude of the transmission scattering parameter profile (|S21|). Potassium chloride (KCl) solutions with concentrations in the range of 100 nM – 4.58 M were tested on nine resonators having different length and pitch sizes to study the effect of sensor geometry on its response to ion concentration. The resonant sensors demonstrated an ion-specific response, caused by the variations in the relative permittivity of the solution, which was also a function of the resonator geometry. A lumped circuit model, which fit the experimental data well, confirms signal transduction via change in solution permittivity. Also, a ternary ionic mixture (composed of potassium nitrate (KNO3), ammonium nitrate (NH4NO3), and ammonium phosphate (NH4H2PO4)) response surface was constructed by testing 21 mixture variations on three different sensor geometries and the phase and magnitude of scattering parameters were monitored. It was determined that the orthogonal responses presented by resonant sensor arrays can be used for quantifying levels of target ions in ternary mixtures. Applications of these arrays include measuring the concentration of key ions in bioreactors, human sweat, and agricultural waters. Preliminary results are shown for calibration standards and real waterway samples in Iowa, USA

A graphene-based physiometer array for the analysis of single biological cells

A significant advantage of a graphene biosensor is that it inherently represents a continuum of independent and aligned sensor-units. We demonstrate a nanoscale version of a micro-physiometer – a device that measures cellular metabolic activity from the local acidification rate. Graphene functions as a matrix of independent pH sensors enabling subcellular detection of proton excretion. Raman spectroscopy shows that aqueous protons p-dope graphene – in agreement with established doping trajectories, and that graphene displays two distinct pKa values (2.9 and 14.2), corresponding to dopants physi- and chemisorbing to graphene respectively. The graphene physiometer allows micron spatial resolution and can differentiate immunoglobulin (IgG)-producing human embryonic kidney (HEK) cells from non-IgG-producing control cells. Population-based analyses allow mapping of phenotypic diversity, variances in metabolic activity, and cellular adhesion. Finally we show this platform can be extended to the detection of other analytes, e.g. dopamine. This work motivates the application of graphene as a unique biosensor for (sub)cellular interrogation.National Cancer Institute (U.S.) (Cancer Center Support (Core) Grant P30-CA14051)U.S. Army Research LaboratoryUnited States. Army Research Office. Institute for Soldier Nanotechnologies (Contract W911NF-13-D-0001)National Institute for Biomedical Imaging and Bioengineering (U.S.) (Grant P41EB015871-27)Skolkovo Institute of Science and Technolog

In vivo biosensing via tissue-localizable near-infrared-fluorescent single-walled carbon nanotubes

Single-walled carbon nanotubes are particularly attractive for biomedical applications, because they exhibit a fluorescent signal in a spectral region where there is minimal interference from biological media. Although single-walled carbon nanotubes have been used as highly sensitive detectors for various compounds, their use as in vivo biomarkers requires the simultaneous optimization of various parameters, including biocompatibility, molecular recognition, high fluorescence quantum efficiency and signal transduction. Here we show that a polyethylene glycol ligated copolymer stabilizes near-infrared-fluorescent single-walled carbon nanotubes sensors in solution, enabling intravenous injection into mice and the selective detection of local nitric oxide concentration with a detection limit of 1 µM. The half-life for liver retention is 4 h, with sensors clearing the lungs within 2 h after injection, thus avoiding a dominant route of in vivo nanotoxicology. After localization within the liver, it is possible to follow the transient inflammation using nitric oxide as a marker and signalling molecule. To this end, we also report a spatial-spectral imaging algorithm to deconvolute fluorescence intensity and spatial information from measurements. Finally, we demonstrate that alginate-encapsulated single-walled carbon nanotubes can function as implantable inflammation sensors for nitric oxide detection, with no intrinsic immune reactivity or other adverse response for more than 400 days.National Institutes of Health (U.S.) (T32 Training Grant in Environmental Toxicology ES007020)National Cancer Institute (U.S.) (Grant P01 CA26731)National Institute of Environmental Health Sciences (Grant P30 ES002109)Arnold and Mabel Beckman Foundation (Young Investigator Award)National Science Foundation (U.S.). Presidential Early Career Award for Scientists and EngineersScientific and Technological Research Council of Turkey (TUBITAK 2211 Research Fellowship Programme)Scientific and Technological Research Council of Turkey (TUBITAK 2214 Research Fellowship Programme)Middle East Technical University. Faculty Development ProgrammeSanofi Aventis (Firm) (Biomedical Innovation Grant

Neurotransmitter Detection Using Corona Phase Molecular Recognition on Fluorescent Single-Walled Carbon Nanotube Sensors

ABSTRACT: Temporal and spatial changes in neurotransmitter concentrations are central to information processing in neural networks. Therefore, biosensors for neurotransmitters are essential tools for neuroscience. In this work, we applied a new technique, corona phase molecular recognition (CoPhMoRe), to identify adsorbed polymer phases on fluorescent single-walled carbon nanotubes (SWCNTs) that allow for the selective detection of specific neurotransmitters, including dopamine. We functionalized and suspended SWCNTs with a library of different polymers (n = 30) containing phospholipids, nucleic acids, and amphiphilic polymers to study how neurotransmitters modulate the resulting band gap, near-infrared (nIR) fluorescence of the SWCNT. We identified several corona phases that enable the selective detection of neurotransmitters. Catecholamines such as dopamine increased the fluorescence of specific single-stranded DNA- and RNA-wrapped SWCNTs by 58−80 % upon addition of 100 μM dopamine depending on the SWCNT chirality (n,m). In solution, the limit of detection was 11 nM [Kd = 433 nM for (GT)15 DNA-wrapped SWCNTs]. Mechanistic studies revealed that this turn-on response is due to an increase in fluorescence quantum yield and not covalent modification of the SWCNT or scavenging o

Label-free carbon nanotube sensors for glycan and protein detection

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Chemical Engineering, June 2014.Cataloged from PDF version of thesis.Includes bibliographical references.Nanoengineered glycan sensors may help realize the long-held goal of accurate and rapid glycoprotein profiling without labeling or glycan liberation steps. Current methods of profiling oligosaccharides displayed on protein surfaces, such as liquid chromatography, mass spectrometry, capillary electrophoresis, and microarray methods, are limited by sample pretreatment and quantitative accuracy. Microarrayed platforms can be improved with methods that better estimate kinetic parameters rather than simply reporting relative binding information. These quantitative glycan sensors are enabled by an emerging class of nanoengineered materials that differ in their mode of signal transduction from traditional methods. Platforms that respond to mass changes include a quartz crystal microbalance and cantilever sensors. Electronic response can be detected from electrochemical, field effect transistor, and pore impedance sensors. Optical methods include fluorescent frontal affinity chromatography, surface plasmon resonance methods, and fluorescent single walled carbon nanotubes-(SWNT). Advantages of carbon nanotube sensors include their sensitivity and ability to multiplex. The focus of this work has been to develop carbon nanotube-based sensors for glycans and proteins. Before detailing the development of these new sensors, the thesis will begin with a very brief primer on glycobiology, its connection to medicine, and the advantages and limitations of existing tools for glycan analysis. In the second chapter we model the use of quantitative nanosensors in a weak affinity dynamic microarray (WADM) to simulate practical uses of these sensors in bioprocessing and clinical diagnostics. There is significant interest in developing new detection platforms for characterizing glycosylated proteins, despite the lack of easily synthesized model glycans or high affinity receptors for this analytical problem. In the third chapter we experimentally demonstrate 'proof of concept' of carbon nanotubebased glycan sensors. This is done with a sensor array employing recombinant lectins as glycan recognition sites tethered via Histidine tags to Ni2l complexes that act as fluorescent quenchers for SWNT embedded in a chitosan hydrogel spot to measure binding kinetics of model glycans. We examine as model glycans both free and streptavidin-tethered biotinylated monosaccharides. Two higher-affined glycan-lectin pairs are explored: fucose (Fuc) to PA-IIL and N-acetylglucosamine (GlcNAc) to GafD. The dissociation constants (KD) for these pairs as free glycans (106 and 19 [mu]M respectively) and streptavidin-tethered (142 and 50 [mu]M respectively) were found. The absolute detection limit for the first-generation platform was found to be 2 pg of glycosylated protein or 100 ng of free glycan to 20 pg of lectin. Glycan detection (GlcNAc-streptavidin at 10 [mu]M) is demonstrated at the single nanotube level as well by monitoring the fluorescence from individual SWNT sensors tethered to GafD lectin. Over a population of 1000 nanotubes, 289 of the SWNT sensors had signals strong enough to yield kinetic information (KD of 250 ± 10 [mu]M). We are also able to identify the locations of "strong-transducers" on the basis of dissociation constant (4 sensors with KD 5% quench response). We report the key finding that the brightest SWNT are not the best transducers of glycan binding. SWNT ranging in intensity between 50 and 75% of the maximum show the greatest response. The ability to pinpoint strong-binding, single sensors is promising to build a nanoarray of glycan-lectin transducers as a high throughput method to profile glycans without protein labeling or glycan liberation pretreatment steps. In the fourth chapter we move from detection of model glycoproteins (streptavidin with biotinylated glycans) to a more applied problem: detection of antibodies and their glycosylation. We do this with a second generation array of SWNT nanosensors in an array format. It is widely recognized that an array of addressable sensors can be multiplexed for the label-free detection of a library of analytes. However, such arrays have useful properties that emerge from the ensemble, even when monofunctionalized. As examples, we show that an array of nanosensors can estimate the mean and variance of the observed dissociation constant (KD), using three different examples of binding IgG with Protein-A as the recognition site, including polyclonal human IgG (KD [mu] = 19 [mu]M, [sigma]2 = 1000 [mu]M2 ). murine IgG (KD = 4.3 [mu]M, 2= 3 [mu]M 2), and human IgG from CHO cells (KD [mu] = 2.5 nM, [sigma]F2 = 0.01 RM2). Second, we show that an array of nanosensors can uniquely monitor weakly-affined analyte interactions via the increased number of observed interactions. One application involves monitoring the metabolically-induced hypermannosylation of human IgG from CHO using PSA-lectin conjugated sensor arrays where temporal glycosylation patterns are measured and compared. Finally, the array of sensors can also spatially map the local production of an analyte from cellular biosynthesis. As an example we rank productivity of IgG-producing HEK colonies cultured directly on the array of nanosensors itself. One great limitation to these practical applications, common to other new sensor developments, are the constraints of large, bulky, and capital-intensive excitation sources, optics, and detectors. In the fifth chapter we detail the design of a lightweight, field-portable detection platform for SWNT based sensors using stock parts with a total cost below $3000. The portable detector is demonstrated with antibody detection in our lab and onsite at a commercial facility 3700 miles away with complex production samples. Along the course of developing these sensors, there was a need to analyze noisy data sets from signal nanotubes (Chapter 3) to determine distinct binding states. NoRSE was developed to analyze highfrequency data sets collected from multi-state, dynamic experiments, such as molecular adsorption and desorption onto carbon nanotubes. As technology improves sampling frequency, these stochastic data sets become increasingly large with faster dynamic events. More efficient algorithms are needed to accurately locate the unique states in each time trace. NoRSE adapts and optimizes a previously published noise reduction algorithm (Chung et al., 1991) and uses a custom peak flagging routine to rapidly identify unique event states. The algorithm is explained using experimental data from our lab and its fitting accuracy and efficiency are then shown with a generalized model of stochastic data sets. The algorithm is compared to another recently published state finding algorithm and is found to be 27 times faster and more accurate over 55% of the generalized experimental space. This work is detailed in Chapter 6. Future uses of these sensors include in vivo reporters of protein biomarkers. In Chapter 7, three-dimensional tracking of single walled carbon nanotubes (SWNT) with an orbital tracking microscope is demonstrated for this purpose. We determine the viscosity regime (above 250 cP) at which the rotational diffusion coefficient can be used for length estimation. We also demonstrate SWNT tracking within live HeLa cells and use these findings to spatially map corral volumes (0.27-1.32 Im 3), determine an active transport velocity (455 nm/s), and calculate local viscosities (54-179 cP) within the cell. With respect to the future use of SWNTs as sensors in living cells, we conclude that the sensor must change the fluorescence signal by at least 4-13% to allow separation of the sensor signal from fluctuations due to rotation of the SWNT when measuring with a time resolution of 32 ms. In the final chapter we draw conclusions from the development of this carbon nanotube-based sensor for glycan analysis and show the start of future work with arrays of SWNT sensors for glycoprofiling.by Nigel F. Reuel.Ph. D

Advancements in Airborne Viral Nucleic Acid Detection with Wearable Devices

Abstract Wearable health sensors for an expanding range of physiological parameters have experienced rapid development in recent years and are poised to disrupt the way healthcare is tracked and administered. The monitoring of environmental contaminants with wearable technologies is an additional layer of personal and public healthcare and is also receiving increased focus. Wearable sensors that detect exposure to airborne viruses can alert wearers of viral exposure and prompt proactive testing and minimization of viral spread, benefitting their own health and decreasing community risk. With the high levels of asymptomatic spread of Coronavirus Disease 2019 (COVID‐19) observed during the pandemic, such devices can dramatically enhance the pandemic response capabilities in the future. To facilitate advancements in this area, this review summarizes recent research on airborne viral detection using wearable sensing devices, as well as technologies suitable for wearables. Since the low concentration of viral particles in the air poses significant challenges to detection, methods for airborne viral particle collection and viral sensing are discussed in detail. A special focus is placed on nucleic acid‐based viral sensing mechanisms due to their enhanced ability to discriminate between viral subtypes. Important considerations for integrating airborne viral collection and sensing on a single wearable device are also discussed