Dehydration assessment via a portable, single sided magnetic resonance sensor.

PURPOSE: Undiagnosed dehydration compromises health outcomes across many populations. Existing dehydration diagnostics require invasive bodily fluid sampling or are easily confounded by fluid and electrolyte intake, environment, and physical activity limiting widespread adoption. We present a portable MR sensor designed to measure intramuscular fluid shifts to identify volume depletion. METHODS: Fluid loss is induced via a mouse model of thermal dehydration (37°C; 15-20% relative humidity). We demonstrate quantification of fluid loss induced by hyperosmotic dehydration with multicomponent T2 relaxometry using both a benchtop NMR system and MRI localized to skeletal muscle tissue. We then describe a miniaturized (~1000 cm3 ) portable (~4 kg) MR sensor (0.28 T) designed to identify dehydration-induced fluid loss. T2 relaxometry measurements were performed using a Carr-Purcell-Meiboom-Gill pulse sequence in ~4 min. RESULTS: T2 values from the portable MR sensor exhibited strong (R2 = 0.996) agreement with benchtop NMR spectrometer. Thermal dehydration induced weight loss of 4 to 11% over 5 to 10 h. Fluid loss induced by thermal dehydration was accurately identified via whole-animal NMR and skeletal muscle. The portable MR sensor accurately identified dehydration via multicomponent T2 relaxometry. CONCLUSION: Performing multicomponent T2 relaxometry localized to the skeletal muscle with a miniaturized MR sensor provides a noninvasive, physiologically relevant measure of dehydration induced fluid loss in a mouse model. This approach offers sensor portability, reduced system complexity, fully automated operation, and low cost compared with MRI. This approach may serve as a versatile and portable point of care technique for dehydration monitoring.

Silica-coated gold nanoplates as stable photoacoustic contrast agents for sentinel lymph node imaging.

A biopsy of the first lymph node to which a tumor drains-the sentinel lymph node (SLN)-is commonly performed to identify micrometastases. Image guidance of the SLN biopsy procedure has the potential to improve its accuracy and decrease its morbidity. We have developed a new stable contrast agent for photoacoustic image-guided SLN biopsy: silica-coated gold nanoplates (Si-AuNPs). The Si-AuNPs exhibit high photothermal stability when exposed to pulsed and continuous wave laser irradiation. This makes them well suited for in vivo photoacoustic imaging. Furthermore, Si-AuNPs are shown to have low cytotoxicity. We tested the Si-AuNPs for SLN mapping in a mouse model where they exhibited a strong, sustained photoacoustic signal. Real-time ultrasound and photoacoustic imaging revealed that the Si-AuNPs quickly drain to the SLN, gradually spreading throughout a large portion of the node.

Machine-learning aided in situ drug sensitivity screening predicts treatment outcomes in ovarian PDX tumors.

Long-term treatment outcomes for patients with high grade ovarian cancers have not changed despite innovations in therapies. There is no recommended assay for predicting patient response to second-line therapy, thus clinicians must make treatment decisions based on each individual patient. Patient-derived xenograft (PDX) tumors have been shown to predict drug sensitivity in ovarian cancer patients, but the time frame for intraperitoneal (IP) tumor generation, expansion, and drug screening is beyond that for tumor recurrence and platinum resistance to occur, thus results do not have clinical utility. We describe a drug sensitivity screening assay using a drug delivery microdevice implanted for 24 h in subcutaneous (SQ) ovarian PDX tumors to predict treatment outcomes in matched IP PDX tumors in a clinically relevant time frame. The SQ tumor response to local microdose drug exposure was found to be predictive of the growth of matched IP tumors after multi-week systemic therapy using significantly fewer animals (10 SQ vs 206 IP). Multiplexed immunofluorescence image analysis of phenotypic tumor response combined with a machine learning classifier could predict IP treatment outcomes against three second-line cytotoxic therapies with an average AUC of 0.91.

A portable single-sided magnetic-resonance sensor for the grading of liver steatosis and fibrosis.

Low-cost non-invasive diagnostic tools for staging the progression of non-alcoholic chronic liver failure from fatty liver disease to steatohepatitis are unavailable. Here, we describe the development and performance of a portable single-sided magnetic-resonance sensor for grading liver steatosis and fibrosis using diffusion-weighted multicomponent T2 relaxometry. In a diet-induced mouse model of non-alcoholic fatty liver disease, the sensor achieved overall accuracies of 92% (Cohen's kappa, κ = 0.89) and 86% (κ = 0.78) in the ex vivo grading of steatosis and fibrosis, respectively. Localization of the measurements in living mice through frequency-dependent spatial encoding led to an overall accuracy of 87% (κ = 0.81) for the grading of steatosis. In human liver samples, the sensor graded steatosis with an overall accuracy of 93% (κ = 0.88). The use of T2 relaxometry as a sensitive measure in fully automated low-cost magnetic-resonance devices at the point of care would alleviate the accessibility and cost limits of magnetic-resonance imaging for diagnosing liver disease and assessing liver health before liver transplantation.

Curative in vivo hematopoietic stem cell gene therapy of murine thalassemia using large regulatory elements.

Recently, we demonstrated that hematopoietic stem/progenitor cell (HSPC) mobilization followed by intravenous injection of integrating, helper-dependent adenovirus HDAd5/35++ vectors resulted in efficient transduction of long-term repopulating cells and disease amelioration in mouse models after in vivo selection of transduced HSPCs. Acute innate toxicity associated with HDAd5/35++ injection was controlled by appropriate prophylaxis, making this approach feasible for clinical translation. Our ultimate goal is to use this technically simple in vivo HSPC transduction approach for gene therapy of thalassemia major or sickle cell disease. A cure of these diseases requires high expression levels of the therapeutic protein (γ- or ß-globin), which is difficult to achieve with lentivirus vectors because of their genome size limitation not allowing larger regulatory elements to be accommodated. Here, we capitalized on the 35 kb insert capacity of HDAd5/35++ vectors to demonstrate that transcriptional regulatory regions of the ß-globin locus with a total length of 29 kb can efficiently be transferred into HSPCs. The in vivo HSPC transduction resulted in stable γ-globin levels in erythroid cells that conferred a complete cure of murine thalassemia intermedia. Notably, this was achieved with a minimal in vivo HSPC selection regimen.

Computationally Guided Intracerebral Drug Delivery via Chronically Implanted Microdevices.

Treatments for neurologic diseases are often limited in efficacy due to poor spatial and temporal control over their delivery. Intracerebral delivery partially overcomes this by directly infusing therapeutics to the brain. Brain structures, however, are nonuniform and irregularly shaped, precluding complete target coverage by a single bolus without significant off-target effects and possible toxicity. Nearly complete coverage is crucial for effective modulation of these structures. We present a framework with computational mapping algorithms for neural drug delivery (COMMAND) to guide multi-bolus targeting of brain structures that maximizes coverage and minimizes off-target leakage. Custom-fabricated chronic neural implants leverage rational fluidic design to achieve multi-bolus delivery in rodents through a single infusion of radioactive tracer (Cu-64). The resulting spatial distributions replicate computed spatial coverage with 5% error in vivo, as detected by positron emission tomography. COMMAND potentially enables accurate, efficacious targeting of discrete brain regions.

Design and experimental validation of Unilateral Linear Halbach magnet arrays for single-sided magnetic resonance.

Single-sided NMR has the potential for broad utility and has found applications in healthcare, materials analysis, food quality assurance, and the oil and gas industry. These sensors require a remote, strong, uniform magnetic field to perform high sensitivity measurements. We demonstrate a new permanent magnet geometry, the Unilateral Linear Halbach, that combines design principles from "sweet-spot" and linear Halbach magnets to achieve this goal through more efficient use of magnetic flux. We perform sensitivity analysis using numerical simulations to produce a framework for Unilateral Linear Halbach design and assess tradeoffs between design parameters. Additionally, the use of hundreds of small, discrete magnets within the assembly allows for a tunable design, improved robustness to variability in magnetization strength, and increased safety during construction. Experimental validation using a prototype magnet shows close agreement with the simulated magnetic field. The Unilateral Linear Halbach magnet increases the sensitivity, portability, and versatility of single-sided NMR.

Evaluating disparities in the U.S. technology transfer ecosystem to improve bench to business translation.

Background: A large number of highly impactful technologies originated from academic research, and the transfer of inventions from academic institutions to private industry is a major driver of economic growth, and a catalyst for further discovery. However, there are significant inefficiencies in academic technology transfer. In this work, we conducted a data-driven assessment of translational activity across United States (U.S.) institutions to better understand how effective universities are in facilitating the transfer of new technologies into the marketplace. From this analysis, we provide recommendations to guide technology transfer policy making at both the university and national level. Methods: Using data from the Association of University Technology Managers U.S. Licensing Activity Survey, we defined a commercialization pipeline that reflects the typical path intellectual property takes; from initial research funding to startup formation and gross income. We use this pipeline to quantify the performance of academic institutions at each step of the process, as well as overall, and identify the top performing institutions via mean reciprocal rank. The corresponding distributions were visualized and disparities quantified using the Gini coefficient. Results: We found significant discrepancies in commercialization activity between institutions; a small number of institutions contribute to the vast majority of total commercialization activity. By examining select top performing institutions, we suggest improvements universities and technology transfer offices could implement to emulate the environment at these high-performing institutions. Conclusion: Significant disparities in technology transfer performance exist in which a select set of institutions produce a majority share of the total technology transfer activity. This disparity points to missed commercialization opportunities, and thus, further investigation into the distribution of technology transfer effectiveness across institutions and studies of policy changes that would improve the effectiveness of the commercialization pipeline is warranted.