VTechWorks staff will be away for the winter holidays starting Tuesday, December 24, 2024, through Wednesday, January 1, 2025, and will not be replying to requests during this time. Thank you for your patience, and happy holidays!

Virginia Tech Carilion (VTC)

Permanent URI for this community

https://hdl.handle.net/10919/23198

Browse

Browsing Virginia Tech Carilion (VTC) by Department "Chemical Engineering"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Fabrication and characterization of PLGA nanoparticles encapsulating large CRISPR–Cas9 plasmid
    Jo, Ami; Ringel-Scaia, Veronica M.; McDaniel, Dylan K.; Thomas, Cassidy A.; Zhang, Rui; Riffle, Judy S.; Allen, Irving C.; Davis, Richey M. (2020-01-20)
    Background The clustered regularly interspaced short palindromic repeats (CRISPR) and Cas9 protein system is a revolutionary tool for gene therapy. Despite promising reports of the utility of CRISPR–Cas9 for in vivo gene editing, a principal problem in implementing this new process is delivery of high molecular weight DNA into cells. Results Using poly(lactic-co-glycolic acid) (PLGA), a nanoparticle carrier was designed to deliver a model CRISPR–Cas9 plasmid into primary bone marrow derived macrophages. The engineered PLGA-based carriers were approximately 160 nm and fluorescently labeled by encapsulation of the fluorophore 6,13-bis(triisopropylsilylethynyl) pentacene (TIPS pentacene). An amine-end capped PLGA encapsulated 1.6 wt% DNA, with an encapsulation efficiency of 80%. Release studies revealed that most of the DNA was released within the first 24 h and corresponded to ~ 2–3 plasmid copies released per nanoparticle. In vitro experiments conducted with murine bone marrow derived macrophages demonstrated that after 24 h of treatment with the PLGA-encapsulated CRISPR plasmids, the majority of cells were positive for TIPS pentacene and the protein Cas9 was detectable within the cells. Conclusions In this work, plasmids for the CRISPR–Cas9 system were encapsulated in nanoparticles comprised of PLGA and were shown to induce expression of bacterial Cas9 in murine bone marrow derived macrophages in vitro. These results suggest that this nanoparticle-based plasmid delivery method can be effective for future in vivo applications of the CRISPR–Cas9 system.
  • Thumbnail Image
    The Rametrix (TM) PRO Toolbox v1.0 for MATLAB (R)
    Senger, Ryan S.; Robertson, John L. (2020-01-06)
    Background. Existing tools for chemometric analysis of vibrational spectroscopy data have enabled characterization of materials and biologicals by their broad molecular composition. The Rametrix (TM) LITE Toolbox v1.0 for MATLAB (R) is one such tool available publicly. It applies discriminant analysis of principal components (DAPC) to spectral data to classify spectra into user-defined groups. However, additional functionality is needed to better evaluate the predictive capabilities of these models when "unknown" samples are introduced. Here, the Rametrix (TM) PRO Toolbox v1.0 is introduced to provide this capability. Methods. The Rametrix (TM) PRO Toolbox v1.0 was constructed for MATLAB (R) and works with the Rametrix (TM) LITE Toolbox v1.0. It performs leave-one-out analysis of chemometric DAPC models and reports predictive capabilities in terms of accuracy, sensitivity (true-positives), and specificity (true-negatives). Rametrix (TM) PRO is available publicly through GitHub under license agreement at: https://github.com/SengerLab/RametrixPROToolbox. Rametrix (TM) PRO was used to validate Rametrix (TM) LITE models used to detect chronic kidney disease (CKD) in spectra of urine obtained by Raman spectroscopy. The dataset included Raman spectra of urine from 20 healthy individuals and 31 patients undergoing peritoneal dialysis treatment for CKD. Results. The number of spectral principal components (PCs) used in building the DAPC model impacted the model accuracy, sensitivity, and specificity in leave-one-out analyses. For the dataset in this study, using 35 PCs in the DAPC model resulted in 100% accuracy, sensitivity, and specificity in classifying an unknown Raman spectrum of urine as belonging to a CKD patient or a healthy volunteer. Models built with fewer or greater number of PCs showed inferior performance, which demonstrated the value of Rametrix (TM) PRO in evaluating chemometric models constructed with Rametrix (TM) LITE.
  • Thumbnail Image
    Spectral characteristics of urine specimens from healthy human volunteers analyzed using Raman chemometric urinalysis (Rametrix)
    Senger, Ryan S.; Kavuru, Varun; Sullivan, Meaghan; Gouldin, Austin; Lundgren, Stephanie; Merrifield, Kristen; Steen, Caitlin; Baker, Emily; Vu, Tommy; Agnor, Ben; Martinez, Gabrielle; Coogan, Hannah; Carswell, William; Karageorge, Lampros; Dev, Devasmita; Du, Pang; Sklar, Allan; Orlando, Giuseppe; Pirkle, James, Jr.; Robertson, John L. (PLOS, 2019-09-27)
    Raman chemometric urinalysis (Rametrix™) was used to analyze 235 urine specimens from healthy individuals. The purpose of this study was to establish the “range of normal” for Raman spectra of urine specimens from healthy individuals. Ultimately, spectra falling outside of this range will be correlated with kidney and urinary tract disease. Rametrix™ analysis includes direct comparisons of Raman spectra but also principal component analysis (PCA), discriminant analysis of principal components (DAPC) models, multivariate statistics, and it is available through GitHub as the Rametrix™ LITE Toolbox for MATLAB®. Results showed consistently overlapping Raman spectra of urine specimens with significantly larger variances in Raman shifts, found by PCA, corresponding to urea, creatinine, and glucose concentrations. A 2-way ANOVA test found that age of the urine specimen donor was statistically significant (p < 0.001) and donor sex (female or male identification) was less so (p = 0.0526). With DAPC models and blind leave-one-out build/test routines using the Rametrix™ PRO Toolbox (also available through GitHub), an accuracy of 71% (sensitivity = 72%; specificity = 70%) was obtained when predicting whether a urine specimen from a healthy unknown individual was from a female or male donor. Finally, from female and male donors (n = 4) who contributed first morning void urine specimens each day for 30 days, the co-occurrence of menstruation was found statistically insignificant to Rametrix™ results (p = 0.695). In addition, Rametrix™ PRO was able to link urine specimens with the individual donor with an average of 78% accuracy. Taken together, this study established the range of Raman spectra that could be expected when obtaining urine specimens from healthy individuals and analyzed by Rametrix™ and provides the methodology for linking results with donor characteristics.