The administration of exogenous DNA has been proposed as a promising therapeutic approach for a variety of diseases. Unfortunately, exogenous DNA is unable to spontaneously penetrate mammalian cells. Although viral vectors facilitate DNA delivery at high transfection efficiency, they are restricted for in vivo applications as they could potentially induce immunogenicity and mutagenesis. To overcome the clinical challenge of viral delivery, a strategy for the encapsulation of plasmid DNA on the surface of poly(lactide-co-glycolide) nanoparticles (PLGA NPs) is shown. Plasmid green fluorescence protein (pEF-GFP) or piggybac transposon (PBCAG-eGFP) are assembled on the surface of PLGA NPs through layer by layer technique. The assembly of pEF-GFP with biopolyelectrolytes is monitored on a planar support using a quartz crystal microbalance with dissipation. The assembly of the biopolymer multilayers on PLGA NPs is followed by ζ-potential measurements. Encapsulation of plasmid DNA within the multilayers coating is confirmed by gel electrophoresis. Cellular uptake studies on HEK293 cells revealed that PLGA NPs are taken up by cells within the first 5 hr of co-culturing. Intracellular release of cargo is confirmed by GFP expression in HEK293 cells. PLGA NPs encapsulating pEF-GFP on their surface are able to transfect~20% of HEK293 cells, while those encapsulating PBCAG-eGFP can transfect up to 75% of cells after 72 hr, causing minimum to non-cytotoxic effects. K E Y W O R D Sbiomedical applications, drug delivery systems, polyelectrolytes, self-assembly, surfaces and interfaces
Here we report the synthesis of core–satellite nanoparticles to explore tunable SERS hot-spot generation, signal reproducibility and long-term activity.
Gold nanoparticles absorb light energy and convert it to thermal energy that transfers to the surrounding environment, making them potentially useful for the hyperthermic treatments well known as photothermal therapy (PTT). Further, it is well documented that noble metal nanoparticles are capable of significantly enhancing the Raman scattering of molecules attached to their surfaces, a technique which is termed surface-enhanced Raman scattering (SERS). SERS combined with PTT has the ability to locate nanoparticles at depth and trigger heat production, providing an effective methodology to both seek and destroy diseased tissues. While PTT and SERS are often used in tandem and there are several ways of individually measuring SERS and thermal output, there is currently no method available that pre-screens both properties prior to in vitro or in vivo application. In this work, we have designed a 3D printed platform capable of coupling a commercially available Raman probe to a sample cuvette for SERS and heat output to be monitored simultaneously. We have compared the performance of morphologically complex gold nanoparticles, nanostars (AuNSs) and nanoplates (AuNPLs), which are both well utilized in SERS and photothermal experiments; and measured the SERS activity originating from common Raman reporter analytes 4-mercaptobenzoic acid (MBA) and 1,4-benzenedithiol (BDT). We were able to show that the system effectively measures the thermal output and SERS activity of the particles and can evaluate the effect that multiple irradiation cycles have on the SERS signal.
Some medical diagnostic tools, such as urinalysis dipsticks, rely on reading colors accurately for making clinical decisions. Reading color visually can be subject to 1) perceptual differences (inter-observer), 2) environmental factors such as illumination, and 3) target coloring (metamerism), especially among users with limited training and experience. Mobile phone cameras and compact camera modules offer potential low-cost platforms for automated, objective color readouts. However, image colors are a function of camera sensor and illumination characteristics. To restore color fidelity, color correction techniques must be applied to account for systematic deviation. This work aims to provide a quantitative assessment of color correction techniques and reduce variability in color interpretation for urinalysis dipstick results using a low-cost imager. Three color correction methods -linear, polynomial, and root-polynomial regression -were compared for performance in color difference reduction. A standard color checker card was used as reference to compute color correction matrices. A custom imaging system with a low-cost camera module was developed to capture images under controlled illumination. Reference values of the color checker card were obtained with a CM-26d handheld spectrophotometer. The CIE2000 ∆E was used to quantify the color difference between the camera image and the spectrometer to evaluate 3 color correction algorithms. The derived color correction matrices were applied to urinalysis dipstick images and compared to the spectrometer readings. Results indicated that polynomial fitting showed the lowest ∆E during calibration but failed to properly correct urine dipstick colors. Root polynomial offered the best performance in reducing color differences to be below 3 to 4 ∆E. Utilizing L*a*b values for classifying a given dipstick result according to reference concentration levels, it was found that quadratic discriminant analysis (QDA) and k Nearest Neighbor (kNN) classifiers achieved an 82.9% and 97.1% accuracy, respectively.
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