120 research outputs found
Assessment of the In Vivo Toxicity of Gold Nanoparticles
The environmental impact of nanoparticles is evident; however, their toxicity due to their nanosize is rarely discussed. Gold nanoparticles (GNPs) may serve as a promising model to address the size-dependent biological response to nanoparticles because they show good biocompatibility and their size can be controlled with great precision during their chemical synthesis. Naked GNPs ranging from 3 to 100 nm were injected intraperitoneally into BALB/C mice at a dose of 8 mg/kg/week. GNPs of 3, 5, 50, and 100 nm did not show harmful effects; however, GNPs ranging from 8 to 37 nm induced severe sickness in mice. Mice injected with GNPs in this range showed fatigue, loss of appetite, change of fur color, and weight loss. Starting from day 14, mice in this group exhibited a camel-like back and crooked spine. The majority of mice in these groups died within 21 days. Injection of 5 and 3 nm GNPs, however, did not induce sickness or lethality in mice. Pathological examination of the major organs of the mice in the diseased groups indicated an increase of Kupffer cells in the liver, loss of structural integrity in the lungs, and diffusion of white pulp in the spleen. The pathological abnormality was associated with the presence of gold particles at the diseased sites, which were verified by ex vivo Coherent anti-Stoke Raman scattering microscopy. Modifying the surface of the GNPs by incorporating immunogenic peptides ameliorated their toxicity. This reduction in the toxicity is associated with an increase in the ability to induce antibody response. The toxicity of GNPs may be a fundamental determinant of the environmental toxicity of nanoparticles
Concentration-Dependent, Size-Independent Toxicity of Citrate Capped AuNPs in Drosophila melanogaster
The expected potential benefits promised by nanotechnology in various fields have led to a rapid increase of the presence of engineered nanomaterials in a high number of commercial goods. This is generating increasing questions about possible risks for human health and environment, due to the lack of an in-depth assessment of the physical/chemical factors responsible for their toxic effects. In this work, we evaluated the toxicity of monodisperse citrate-capped gold nanoparticles (AuNPs) of different sizes (5, 15, 40, and 80 nm) in the model organism Drosophila melanogaster, upon ingestion. To properly evaluate and distinguish the possible dose- and/or size-dependent toxicity of the AuNPs, we performed a thorough assessment of their biological effects, using two different dose-metrics. In the first approach, we kept constant the total surface area of the differently sized AuNPs (Total Exposed Surface area approach, TES), while, in the second approach, we used the same number concentration of the four different sizes of AuNPs (Total Number of Nanoparticles approach, TNN). We observed a significant AuNPs-induced toxicity in vivo, namely a strong reduction of Drosophila lifespan and fertility performance, presence of DNA fragmentation, as well as a significant modification in the expression levels of genes involved in stress responses, DNA damage recognition and apoptosis pathway. Interestingly, we found that, within the investigated experimental conditions, the toxic effects in the exposed organisms were directly related to the concentration of the AuNPs administered, irrespective of their size
Designing Nanoconjugates to Effectively Target Pancreatic Cancer Cells In Vitro and In Vivo
Pancreatic cancer is the fourth leading cause of cancer related deaths in America. Monoclonal antibodies are a viable treatment option for inhibiting cancer growth. Tumor specific drug delivery could be achieved utilizing these monoclonal antibodies as targeting agents. This type of designer therapeutic is evolving and with the use of gold nanoparticles it is a promising approach to selectively deliver chemotherapeutics to malignant cells. Gold nanoparticles (GNPs) are showing extreme promise in current medicinal research. GNPs have been shown to non-invasively kill tumor cells by hyperthermia using radiofrequency. They have also been implemented as early detection agents due to their unique X-ray contrast properties; success was revealed with clear delineation of blood capillaries in a preclinical model by CT (computer tomography). The fundamental parameters for intelligent design of nanoconjugates are on the forefront. The goal of this study is to define the necessary design parameters to successfully target pancreatic cancer cells.The nanoconjugates described in this study were characterized with various physico-chemical techniques. We demonstrate that the number of cetuximab molecules (targeting agent) on a GNP, the hydrodynamic size of the nanoconjugates, available reactive surface area and the ability of the nanoconjugates to sequester EGFR (epidermal growth factor receptor), all play critical roles in effectively targeting tumor cells in vitro and in vivo in an orthotopic model of pancreatic cancer.Our results suggest the specific targeting of tumor cells depends on a number of crucial components 1) targeting agent to nanoparticle ratio 2) availability of reactive surface area on the nanoparticle 3) ability of the nanoconjugate to bind the target and 4) hydrodynamic diameter of the nanoconjugate. We believe this study will help define the design parameters for formulating better strategies for specifically targeting tumors with nanoparticle conjugates
Toxicity and cellular uptake of gold nanoparticles: what we have learned so far?
Gold nanoparticles have attracted enormous scientific and technological interest due to their ease of synthesis, chemical stability, and unique optical properties. Proof-of-concept studies demonstrate their biomedical applications in chemical sensing, biological imaging, drug delivery, and cancer treatment. Knowledge about their potential toxicity and health impact is essential before these nanomaterials can be used in real clinical settings. Furthermore, the underlying interactions of these nanomaterials with physiological fluids is a key feature of understanding their biological impact, and these interactions can perhaps be exploited to mitigate unwanted toxic effects. In this Perspective we discuss recent results that address the toxicity of gold nanoparticles both in vitro and in vivo, and we provide some experimental recommendations for future research at the interface of nanotechnology and biological systems
In vivo uptake and cellular distribution of gold nanoshells in a preclinical model of xenografted human renal cancer
Anti-lymphangiogenic properties of mTOR inhibitors in head and neck squamous cell carcinoma experimental models
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Development and deployment of a generative model-based framework for text to photorealistic image generation
The task of generating photorealistic images from their textual descriptions is quite challenging. Most existing tasks in this domain are focused on the generation of images such as flowers or birds from their textual description, especially for validating the generative models based on Generative Adversarial Network (GAN) variants and for recreational purposes. However, such work is limited in the domain of photorealistic face image generation and the results obtained have not been satisfactory. This is partly due to the absence of concrete data in this domain and a large number of highly specific features/attributes involved in face generation compared to birds or flowers. In this paper, we propose an Attention Generative Adversarial Network (AttnGAN) for a fine-grained text-to-face generation that enables attention-driven multi-stage refinement by employing Deep Attentional Multimodal Similarity Model (DAMSM). Through extensive experimentation on the CelebA dataset, we evaluated our approach using the Frechet Inception Distance (FID) score. The output files for the Face2Text Dataset are also compare with that of the T2F Github project. According to the visual comparison, AttnGAN generated higher-quality images than T2F. Additionally, we compare our methodology with existing approaches with a specific focus on CelebA dataset and demonstrate that our approach generates a better FID score facilitating more realistic image generation. The application of such an approach can be found in criminal identification, where faces are generated from the textual description from an eyewitness. Such a method can bring consistency and eliminate the individual biases of an artist drawing the faces from the description given by the eyewitness. Finally, we discuss the deployment of the models on a Raspberry Pi to test how effective the models would be on a standalone device to facilitate portability and timely task completion
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