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MODIFIED CATECHOL-BASED POLYMERIC BIOMATERIALS FOR ANTIVIRAL, ANTIBACTERIAL, AND HEMOSTATIC APPLICATIONS
No full textThe catechol side chain, a key molecule in mussel adhesive proteins, can be modified with electron-donating (e.g., –OH) or electron-withdrawing (e.g., halogens, –NO₂) groups to control its autoxidation. Electron-donating groups promote catechol oxidation, increasing hydrogen peroxide (H₂O₂) generation, which is useful for developing antimicrobial materials. Conversely, electron-withdrawing groups limit oxidation, leading to enhanced crosslinking, interfacial binding, and intrinsic antibacterial properties. These modifications make catechol-functionalized polymers ideal candidates for hemostatic and infection prevention applications. This dissertation focuses on the development of polymeric biomaterials to address challenges in infection control, hemostasis, and tissue adhesion. The projects explore catechol-based modifications to enhance material functionality for these biomedical applications.
Project 1 develops a novel polymer coating containing 6-hydroxycatechol, which enhances H₂O₂ production on polypropylene (PP) fabric. The addition of an electron-donating –OH group accelerates autoxidation, generating over 3000 μM of H₂O₂ within an hour, significantly more than unmodified catechol. This coating exhibited strong antimicrobial effects against both Gram-positive and Gram-negative bacteria, as well as antiviral activity against human coronavirus 229E and bovine viral diarrhea virus, reducing viral load by 99.7%.
Project 2 introduces 6-chlorocatechol-functionalized gelatin nanoparticles designed for rapid hemorrhage control and infection prevention. These nanoparticles form adhesive films upon hydration, with the addition of an electron-withdrawing –Cl group enhancing crosslinking, mechanical stability, and hemostatic performance. In mouse tail transection and liver hemorrhage models, the nanoparticles achieved rapid bleeding cessation and reduced blood loss. They also demonstrated antibacterial activity against multiple bacterial strains without causing cytotoxicity.
Project 3 investigates the effects of different electron-withdrawing groups (–Br, –Cl, –NO₂) on catechol-functionalized gelatin nanoparticles. These modifications improve mechanical properties, adhesive strength, and antibacterial efficacy by promoting crosslinking and non-covalent interactions. 6-Nitrocatechol showed superior antibacterial performance, though it exhibited reduced cytocompatibility compared to other modifications.
Overall, this body of work provides insights into developing multifunctional biomaterials for infection control, hemostasis, and tissue adhesion, leveraging targeted chemical modifications to enhance their properties and performance
Effects of Spatial Variability on Bearing Capacity of Deep Soil Mixing Columns
No full textThe effects of spatial variability on the bearing capacity of deep soil mixing columns are critical in understanding and improving their performance in soft and weak soils. This study investigates the effects of spatial variability in strength parameters and in column geometry on the bearing capacity of deep soil mixing columns. By employing Monte Carlo simulations and the validated finite volume models, the research analyzes the mechanical response of DSM columns under axial loading. Results reveal that spatial variability in strength parameters reduces the peak bearing capacity of DSM columns by approximately 21%, with average peak stress decreasing from 570 kPa (DSM column with uniform strength parameters) to 450 kPa (DSM with random variability in strength parameters). Additionally, variability in column diameters introduces a 3.8% coefficient of variation, reducing the average ultimate stress to 520 kPa. These findings highlight the significant impact of spatial variability on deep soil mixing column performance, emphasizing the need for quality control during construction to achieve uniform strength distribution and consistent column geometry. Such improvements are essential to enhance the load-bearing capacity, stiffness, and overall reliability of deep soil mixing columns in geotechnical engineering applications
Generating synthetic images for construction machinery data augmentation utilizing context-aware object placement
No full textDataset is an essential factor influencing the accuracy of computer vision (CV) tasks in construction. Although image synthesis methods can automatically generate substantial annotated construction data compared to manual annotation, existing challenges limited the CV task accuracy, such as geometric inconsistency. To efficiently generate high-quality data, a synthesis method of construction data was proposed utilizing Unreal Engine (UE) and PlaceNet. First, the inpainting algorithm was applied to generate pure backgrounds, followed by multi-angle foreground capture within the UE. Then, the Swin Transformer and improved loss functions were integrated into PlaceNet to enhance the feature extraction of construction backgrounds, facilitating object placement accuracy. The generated synthetic dataset achieved a high average accuracy (mAP = 85.2%) in object detection tasks, 2.1% higher than the real dataset. This study offers theoretical and practical insights for synthetic dataset generation in construction, providing a future perspective to enhance CV task performance utilizing image synthesis
The impact of irrigated agriculture on landslide activity: A spatio-temporal analysis in Heifangtai, China
No full textThe Heifangtai loess terrace in Gansu Province (China) suffered from frequent irrigation-induced landslides. In the past 50 years, the perennial channel irrigation has resulted in 210 slope failures within a small area of 9 km2. The landslide activity is particularly linked with the cultivation of vegetables, which need more frequent channel irrigation compared to other crops. In order to reveal the long-term relationship between the recurrent landslides and irrigation intensity variations induced by land use changes, we used remotely sensed images from different sources, covering a period of 59 years, to map land use changes as well as to create a landslide inventory. Based on field surveys, samples of land use and vegetation phenology were studied, which were used in classification using a random forest classifier based on synergy multi-temporal Normalized Difference Vegetation Index (NDVI) for characterizing features during a crop cycle. A landslide inventory was created by visual interpretation of images and comparison of landslide maps from literature. Based on the land use map and crop irrigation frequency, the irrigation intensity of all the crop types was calculated. For studying the interaction of horizontal and vertical water infiltration over long periods, kernel density estimation (KDE) was applied to identify irrigation hotspot areas, which were used to correlate with slope failure hotspots. Furthermore, temporal and spatial relationship was analyzed among the landslide density, land use, and irrigation intensity. The results of this study showed that irrigation intensity varied with changes in land use as well as agriculture technology, which was later correlated with landslide sensitivity. Most of the landslides in Heifangtai (90 %) were loess landslides, which were retrogressive with a small average area and the recurrence was intensified after vegetable cultivation; bedrock landslide occurred a little more frequently before vegetable cultivation initiated and has large average area. This study revealed that the hotspots of recurrent loess landslides were near the hotspot irrigation areas and local groundwater table dome, which were in the concave edges with groundwater seepage in the loess layer. This study is also the first to evaluate the annual irrigation volume and the time for recent Groundwater Table (GWT) distribution, and implies that irrigation water management in arid farming areas was effective and viable for landslide preventing
Spitefulness and envy: The mediating role of justice sensitivity
No full textWe examined the associations that the trait of spitefulness had with the benign and malicious forms of dispositional envy as well as the role that justice sensitivity played in these associations. In Study 1 (N = 901 undergraduate students), trait spitefulness was positively associated with malicious envy even when controlling for basic personality dimensions, whereas it was not associated with benign envy. In Study 2 (N = 356 undergraduate students) and Study 3 (N = 748 community members), the positive association that spitefulness had with malicious envy was mediated by the tendency to view oneself as a victim of injustice as well as a lack of concern about whether one treats others in a fair and just manner. Studies 2 and 3 also revealed that spitefulness had an unexpected indirect association with benign envy through the tendency to view oneself as a victim. Taken together, these results suggest that the connection between spitefulness and dispositional envy – especially the malicious form of envy – may be due, at least in part, to a self-centered view of fairness that is focused on one\u27s own welfare combined with a disregard for whether others are treated in a fair or just manner
Spatio-temporal interpolation of ~530 Ma paleo-DEM to quantify denudation of a terrestrial impact crater
No full textErosion and weathering are two of the several exogenic processes that control the intensity and patterns of landform evolution. Based on previous studies, the varied erosion rates observed in the geological past depends on factors like mean relief (morphology), climate, lithology, and time. Meteorite impact craters have unique geomorphic features, being characterized by both negative relief features (the bowl-shaped depression) and positive features (such as elevated rims; additionally, central elevated areas for complex craters). This makes them a suitable morphologic feature to study both erosion and deposition. This study estimates the long-term erosion of Ramgarh crater in western India, a crater debated on its morphology and erosion rates. This study uses a paleo-digital elevation model (paleo-DEM), a reconstruction of the crater morphology at ⁓528 Ma- the potential upper age of formation of Ramgarh, along with previously established models with suitable modifications to quantify erosion from the final stage to the present day. The type of projectile and its physical characteristics such as diameter and volume were also estimated. Reconstruction of the crater\u27s paleo-position was achieved through GPlates (a GIS-based paleo-reconstruction model), followed by recreating the transient and final crater morphology (including parameters such as crater diameter and true depth, rim height, and thickness of proximal ejecta) for two age limits (528 Ma and 395 Ma). The intermittent morphology of the crater was generated using mathematical equations to depict the sequence of changes through time. The erosion of the crater, quantified in terms of cumulative volume, is between 0.41 and 0.58 km3. This range is based on four conditions pertaining to two different final crater rim heights (mathematically derived) as well as two age limits. Overall, this study provides valuable insights into the long-term morphological evolution of Ramgarh crater and contributes to the understanding of impact crater\u27s erosion processes
A Rhodamine-Based Ratiometric Fluorescent Sensor for Dual-Channel Visible and Near-Infrared Emission Detection of NAD(P)H in Living Cells and Fruit Fly Larvae
No full textThe detection and dynamic monitoring of intracellular NAD(P)H concentrations are crucial for comprehending cellular metabolism, redox biology, and their roles in various physiological and pathological processes. To address this need, we introduce sensor A, a near-infrared ratiometric fluorescent sensor for real-time, quantitative imaging of NAD(P)H fluctuations in live cells. Sensor A combines a 3-quinolinium electron-deficient acceptor with a near-infrared rhodamine dye, offering high sensitivity and specificity for NAD(P)H with superior photophysical properties. In its unbound state, sensor A emits strongly at 650 nm and weakly at 465 nm upon 400 nm excitation. Upon binding to NAD(P)H, it shows a fluorescence increase at 465 nm and a decrease at 650 nm, enabling accurate ratiometric measurements. Sensor A also exhibits ratiometric upconversion fluorescence when excited at 800 or 810 nm, offering additional flexibility for different experimental setups. The sensor’s response relies on the reduction of the 3-quinolinium acceptor by NAD(P)H, forming a 1,4-dihydroquinoline donor that enhances fluorescence at 465 nm and quenches the near-infrared emission at 650 nm through photoinduced electron transfer. This mechanism ensures high sensitivity and reliable quantification of NAD(P)H levels while minimizing interference from sensor concentration, excitation intensity, or environmental factors. Sensor A was validated in HeLa and MD-MB453 cells under various metabolic and pharmacological conditions, including glucose and maltose stimulation and treatments with chemotherapeutic agents. Co-localization with mitochondrial-specific dyes confirmed its mitochondrial targeting, enabling precise tracking of NAD(P)H fluctuations. In vivo imaging of Drosophila larvae under nutrient starvation or chemotherapeutic exposure revealed dose-dependent fluorescence responses, highlighting its potential for tracking NAD(P)H changes in live organisms. Sensor A represents a significant advancement in NAD(P)H imaging, providing a powerful tool for exploring cellular metabolism and redox biology in biomedical research
TRPV4 Dominates High Shear-Induced Initial Traction Response and Long-Term Relaxation Over Piezo1
Get PDFModulation of endothelial traction is critical for the responses of endothelial cells to fluid shear stress (FSS), which has profound implications for vascular health and atherosclerosis. Previously, we demonstrated that under high FSS, endothelial cells rapidly increase traction forces, followed by relaxation, with traction aligning in the flow direction. In contrast, low shear preconditioning induces a modest short-term increase in traction (min), followed by a secondary long-term (\u3e14 hr) rise, with traction/cells aligning perpendicular to the flow. The upstream mechanosensors driving these responses, however, remain unknown. Here, we sought the roles of Piezo1 and TRPV4 ion channels in shear-induced traction modulation. We report that HUVECs with Piezo1 silencing reduced the initial traction rise in half under high FSS compared to those by WT cells, while not affecting the traction modulation in response to low FSS or traction/cell alignment to the flow direction. Conversely, cells with siTRPV4 fully abrogated the initial traction rise, as well as alignment of traction and cells, in response to both high and low FSS conditions. Dual inhibition of Piezo1 and TRPV4 further impaired both initial and long-term traction under high FSS. Interestingly, dual-inhibited cells displayed larger initial traction responses to low FSS compared to control cells, suggesting the involvement of alternative calcium-independent pathways that become dominant when both ion channels are nonfunctional. Additionally, either ion channel inhibition led to secondary long-term traction increase even under high FSS condition. These findings suggest that while both Piezo1 and TRPV4 channels contribute to shear mechanotransduction, TRPV4 plays more dominant role than Piezo1 in mediating the initial traction rise and sustaining long-term relaxation under high or low shear stress, highlighting their critical and distinct contributions to endothelial mechanotransduction and remodeling
Drivers and concerns of adopting Artificial Intelligence in managerial accounting
No full textRecent advancements in Artificial Intelligence (AI) have attracted significant attention within the managerial ac-counting profession. With its transformative capabilities and complexity, AI presents numerous opportunities alongside notable challenges in its adoption. This paper examines the key factors influencing AI adoption in managerial accounting and highlights common concerns faced by companies during this process. Based on inter-views with representatives from 41 companies, we identified a range of factors impacting AI adoption at both institutional and individual levels. These findings offer valuable insights into AI acceptance within the field of managerial accounting
Influence of Particle Morphology on Angle of Repose Derived from Hopper Flow Tests Using 3D DEM Simulations
No full textThe angle of repose holds significant importance within granular systems, serving as a key indicator of material packing and flow behavior. In this work, we investigated the impact of particle morphology on the repose angle (AOR) using a series of numerical simulations and laboratory measurements. For the experiments, granular materials are first loaded into a hopper and then released to fall freely under gravity into a vessel positioned below, and the angle of repose of the resulting pile is measured. Numerical simulations used the bubble pack technique to create clumps of pebbles with varying shapes. The results show that the AOR is strongly influenced by the shape of the clumps used in the simulations, allowing for the use of fewer pebbles to efficiently replicate the behavior of irregular particle shapes. Notably, differences in repose angle values between hopper flow tests and cylinder pull-out tests emphasize the importance of test methods in evaluating particle flowability