This paper presents a new supervised method for vessel segmentation in retinal images. This method remolds the task of segmentation as a problem of cross-modality data transformation from retinal image to vessel map. A wide and deep neural network with strong induction ability is proposed to model the transformation, and an efficient training strategy is presented. Instead of a single label of the center pixel, the network can output the label map of all pixels for a given image patch. Our approach outperforms reported state-of-the-art methods in terms of sensitivity, specificity and accuracy. The result of cross-training evaluation indicates its robustness to the training set. The approach needs no artificially designed feature and no preprocessing step, reducing the impact of subjective factors. The proposed method has the potential for application in image diagnosis of ophthalmologic diseases, and it may provide a new, general, high-performance computing framework for image segmentation.
Although highly active anti-retroviral therapy has resulted in remarkable decline in the morbidity and mortality in AIDS patients, inadequately low delivery of anti-retroviral drugs across the blood-brain barrier results in virus persistence. The capability of high-efficacytargeted drug delivery and on-demand release remains a formidable task. Here we report an in vitro study to demonstrate the on-demand release of azidothymidine 5 0 -triphosphate, an anti-human immunodeficiency virus drug, from 30 nm CoFe 2 O 4 @BaTiO 3 magneto-electric nanoparticles by applying a low alternating current magnetic field. Magneto-electric nanoparticles as field-controlled drug carriers offer a unique capability of field-triggered release after crossing the blood-brain barrier. Owing to the intrinsic magnetoelectricity, these nanoparticles can couple external magnetic fields with the electric forces in drug-carrier bonds to enable remotely controlled delivery without exploiting heat. Functional and structural integrity of the drug after the release was confirmed in in vitro experiments with human immunodeficiency virus-infected cells and through atomic force microscopy, spectrophotometry, Fourier transform infrared and mass spectrometry studies.
The nanotechnology capable of high-specificity targeted delivery of anti-neoplastic drugs would be a significant breakthrough in Cancer in general and Ovarian Cancer in particular. We addressed this challenge through a new physical concept that exploited (i) the difference in the membrane electric properties between the tumor and healthy cells and (ii) the capability of magneto-electric nanoparticles (MENs) to serve as nanosized converters of remote magnetic field energy into the MENs' intrinsic electric field energy. This capability allows to remotely control the membrane electric fields and consequently trigger high-specificity drug uptake through creation of localized nano-electroporation sites. In in-vitro studies on human ovarian carcinoma cell (SKOV-3) and healthy cell (HOMEC) lines, we applied a 30-Oe d.c. field to trigger high-specificity uptake of paclitaxel loaded on 30-nm CoFe2O4@BaTiO3 MENs. The drug penetrated through the membrane and completely eradicated the tumor within 24 hours without affecting the normal cells.
Aim:The in vivo study on imprinting control region mice aims to show that magnetoelectric nanoparticles may directly couple the intrinsic neural activityinduced electric fields with external magnetic fields. Methods: Approximately 10 μg of CoFe 2 O 4 -BaTiO 3 30-nm nanoparticles have been intravenously administrated through a tail vein and forced to cross the blood-brain barrier via a d.c. field gradient of 3000 Oe/cm. A surgically attached two-channel electroencephalography headmount has directly measured the modulation of intrinsic electric waveforms by an external a.c. 100-Oe magnetic field in a frequency range of 0-20 Hz. Results: The modulated signal has reached the strength comparable to that due the regular neural activity. Conclusion:The study opens a pathway to use multifunctional nanoparticles to control intrinsic fields deep in the brain.
It is a challenge to eradicate tumor cells while sparing normal cells. We used magnetoelectric nanoparticles (MENs) to control drug delivery and release. The physics is due to electric-field interactions (i) between MENs and a drug and (ii) between drug-loaded MENs and cells. MENs distinguish cancer cells from normal cells through the membrane’s electric properties; cancer cells have a significantly smaller threshold field to induce electroporation. In vitro and in vivo studies (nude mice with SKOV-3 xenografts) showed that (i) drug (paclitaxel (PTX)) could be attached to MENs (30-nm CoFe2O4@BaTiO3 nanostructures) through surface functionalization to avoid its premature release, (ii) drug-loaded MENs could be delivered into cancer cells via application of a d.c. field (~100 Oe), and (iii) the drug could be released off MENs on demand via application of an a.c. field (~50 Oe, 100 Hz). The cell lysate content was measured with scanning probe microscopy and spectrophotometry. MENs and control ferromagnetic and polymer nanoparticles conjugated with HER2-neu antibodies, all loaded with PTX were weekly administrated intravenously. Only the mice treated with PTX-loaded MENs (15/200 μg) in a field for three months were completely cured, as confirmed through infrared imaging and post-euthanasia histology studies via energy-dispersive spectroscopy and immunohistochemistry.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.