INVESTIGATE THE INTERACTIONS BETWEEN SILVER NANOPARTICLES AND SPINACH LEAF BY SURFACE ENHANCED RAMAN SPECTROSCOPIC MAPPING

Owing to their increasing application and potential toxicity, engineered nanoparticles (ENPs) have been considered as a potential agricultural contaminant that may pose unknown risk to human beings. However, many techniques require invasive and complicated sample preparation procedures to detect and characterize engineered nanomaterials in complex matrices. In the first part of this thesis, we present a non-destructive and label-free approach based on surface enhanced Raman spectroscopic (SERS) mapping technique to qualitatively detect and characterize gold nanoparticles (AuNPs), on and in spinach leaves in situ. We were able to detect the clearly enhanced signals from AuNPs at 15 to 125 nm on and in spinach leaves. Peak characterizations revealed the aggregation status of Au NPs and their interactions with plant biomolecules, such as chlorophylls and carotenoids. This developed approach will open a new analytical platform for various researches on studying ENPs\u27 adhesion and accumulation. The second part focuses on investigating the interaction between AgNPs and plant leaves using surface enhanced Raman spectroscopy. AgNPs of different surface coating (citrate, CIT and polyvinylpyrrolidone, PVP) and size (40 and 100 nm), were deposited onto spinach leaves. SERS signals produced from all kinds of AgNPs exhibited a unique C-S stretching peak at 650-680 cm-1. In vitro study indicates this peak may originate from the interaction between AgNPs and cysteine-like compounds based on the peak pattern recognition. The interaction between AgNPs and the cysteine-like compounds happened as soon as 0.5 h after AgNPs exposure. The in situ replacement of the CIT with the cysteine-like compounds on the AgNP surfaces was faster compared to that of the PVP. Based on the mapping of the highest C-S peak, we observed the CIT-AgNPs penetrated faster in spinach leaves than the PVP-AgNPs, although the penetration profile for both of them is similar after 48 h (P ˂ 0.05). The 40 nm CIT-AgNPs was able to penetrate deeper (to the depth of 183 ± 38 µm) than the 100 nm CIT-AgNPs (to the depth of 90 ± 51 µm) after 48 h. The results obtained here demonstrate the size of AgNPs is the main factor that affects the penetration depth, and the surface coating mainly affects the initial speed of interaction and penetration. This study helps us to better understand the distribution and biotransformation of AgNPs in plants. In the third part, the removal efficiency of postharvest washing on AgNPs that had accumulated on fresh produce was evaluated. Ten µL commercially available 40 nm citrate coated AgNPs (0.4 mg L-1) were dropped to a (1×1 cm2) spot on spinach leaves, followed by washing with deionized water (DI water), Tsunami® 100 (80 mg L-1) or Clorox® bleach (200 mg L-1). Then, AgNPs removal efficiency of the three treatments was evaluated by surface enhanced Raman spectroscopy (SERS), scanning electron microscopy (SEM)-energy dispersive spectrometer (EDS), and inductively coupled plasma mass spectrometry (ICP-MS). ICP-MS results showed that deionized water removed statistically insignificant amounts of total Ag, whereas Tsunami® 100 and Clorox® bleach yielded 21% and 10% decreases in total Ag, respectively (P \u3c 0.05). The increased removal efficiency resulted from Ag NPs dissolution and Ag+ release upon contact with the oxidizing agents in Tsunami® 100 (peroxyacetic acid, hydrogen peroxide) and Clorox® bleach (sodium hypochlorite). According to the SERS results, the deionized water and Tsunami® 100 treatments removed nonsignificant amounts of AgNPs. Clorox® bleach decreased Ag NPs by more than 90% (P \u3c 0.05), however, SEM-EDS images revealed the formation of large silver chloride (AgCl) crystals (162 ± 51 nm) on the leaf, which explained low total Ag removal from ICP-MS. This study indicates current factory washing methods for fresh produce may not be effective in reducing AgNPs (by water and Tsunami® 100) and total Ag (by all three means). This highlights the necessity to develop an efficient washing method for NP removal from food surfaces in the future

A New Distributed Localization Method for Sensor Networks

This paper studies the problem of determining the sensor locations in a large sensor network using relative distance (range) measurements only. Our work follows from a seminal paper by Khan et al. [1] where a distributed algorithm, known as DILOC, for sensor localization is given using the barycentric coordinate. A main limitation of the DILOC algorithm is that all sensor nodes must be inside the convex hull of the anchor nodes. In this paper, we consider a general sensor network without the convex hull assumption, which incurs challenges in determining the sign pattern of the barycentric coordinate. A criterion is developed to address this issue based on available distance measurements. Also, a new distributed algorithm is proposed to guarantee the asymptotic localization of all localizable sensor nodes

A COMPARISON OF HAZE REMOVAL ALGORITHMS AND THEIR IMPACTS ON CLASSIFICATION ACCURACY FOR LANDSAT IMAGERY

The quality of Landsat images in humid areas is considerably degraded by haze in terms of their spectral response pattern, which limits the possibility of their application in using visible and near-infrared bands. A variety of haze removal algorithms have been proposed to correct these unsatisfactory illumination effects caused by the haze contamination. The purpose of this study was to illustrate the difference of two major algorithms (the improved homomorphic filtering (HF) and the virtual cloud point (VCP)) for their effectiveness in solving spatially varying haze contamination, and to evaluate the impacts of haze removal on land cover classification. A case study with exploiting large quantities of Landsat TM images and climates (clear and haze) in the most humid areas in China proved that these haze removal algorithms both perform well in processing Landsat images contaminated by haze. The outcome of the application of VCP appears to be more similar to the reference images compared to HF. Moreover, the Landsat image with VCP haze removal can improve the classification accuracy effectively in comparison to that without haze removal, especially in the cloudy contaminated area

MicroRNA-30b is a multifunctional regulator of aortic valve interstitial cells

ObjectiveCalcific aortic valve disease is an active process involving a wide range of pathologic changes. Valve interstitial cells are the most prevalent cells in the heart valve and maintain normal valve structure and function. MicroRNAs (miRNAs) are essential posttranscriptional modulators of gene expression, and miRNA-30b is a known repressor of bone morphogenetic protein 2–mediated osteogenesis. We hypothesized that miRNA-30b is a multifunctional regulator of aortic valve interstitial cells during calcification.MethodsTo determine the role of miRNA-30b in calcific aortic valve disease, we evaluated miRNA expression in human calcific aortic valve leaflets obtained intraoperatively. Furthermore, human valve interstitial cells were evaluated with regard to miRNA-30b expression and osteogenesis by quantitative real-time polymerase chain reaction, Western blotting, flow cytometry, and alkaline phosphatase assays.ResultsIn this study, we demonstrated that miRNA-30b attenuates bone morphogenetic protein 2–induced osteoblast differentiation by targeting Runx2, Smad1, and caspase-3. Transfection of a mimic of miRNA-30b led to decreases in alkaline phosphatase activity and expressions of Runx2, Smad1, and caspase-3. Furthermore, dual luciferase reporter assays confirmed that Runx2, Smad1, and caspase-3 are direct targets of miRNA-30b.ConclusionsWe demonstrated a remarkable role of miRNA-30b in calcific aortic valve disease as a regulator of human aortic valvular calcification and apoptosis through direct targeting of Runx2, Smad1, and caspase-3. Targeting of miRNA-30b could serve as a novel therapeutic strategy to limit progressive calcification in aortic stenosis