Size-regulated group separation of CoFe2O4 nanoparticles using centrifuge and their magnetic resonance contrast properties

Magnetic nanoparticle (MNP)-based magnetic resonance imaging (MRI) contrast agents (CAs) have been the subject of extensive research over recent decades. The particle size of MNPs varies widely and is known to influence their physicochemical and pharmacokinetic properties. There are two commonly used methods for synthesizing MNPs, organometallic and aqueous solution coprecipitation. The former has the advantage of being able to control the particle size more effectively; however, the resulting particles require a hydrophilic coating in order to be rendered water soluble. The MNPs produced using the latter method are intrinsically water soluble, but they have a relatively wide particle size distribution. Size-controlled water-soluble MNPs have great potential as MRI CAs and in cell sorting and labeling applications. In the present study, we synthesized CoFe(2)O(4) MNPs using an aqueous solution coprecipitation method. The MNPs were subsequently separated into four groups depending on size, by the use of centrifugation at different speeds. The crystal shapes and size distributions of the particles in the four groups were measured and confirmed by transmission electron microscopy and dynamic light scattering. Using X-ray diffraction analysis, the MNPs were found to have an inverse spinel structure. Four MNP groups with well-selected semi-Gaussian-like diameter distributions were obtained, with measured T(2) relaxivities (r(2)) at 4.7 T and room temperature in the range of 60 to 300 mM(−1)s(−1), depending on the particle size. This size regulation method has great promise for applications that require homogeneous-sized MNPs made by an aqueous solution coprecipitation method. Any group of the CoFe(2)O(4) MNPs could be used as initial base cores of MRI T(2) CAs, with almost unique T(2) relaxivity owing to size regulation. The methodology reported here opens up many possibilities for biosensing applications and disease diagnosis. PACS: 75.75.Fk, 78.67.Bf, 61.46.D

MR Assessment of Acute Pathologic Process after Myocardial Infarction in a Permanent Ligation Mouse Model: Role of Magnetic Nanoparticle-Contrasted MRI

We evaluated the relationship between myocardial infarct size and inflammatory response using cardiac magnetic resonance imaging (CMR) in an acute myocardial infarction (AMI) mouse model. Myocardial infarction (MI) was induced in 14 mice by permanent ligation of the left anterior descending artery. Late gadolinium enhancement (LGE), manganese-enhanced MRI (MEMRI), and magnetofluorescent nanoparticle MRI (MNP-MRI) were performed 1, 2, and 3 days after MI, respectively. The size of the enhanced lesion was quantitatively determined using Otsu’s thresholding method in area-based and sector-based approaches and was compared statistically. Linear correlation between the enhanced lesion sizes was evaluated by Pearson’s correlation coefficients. Differences were compared using Bland-Altman analysis. The size of the inflammatory area determined by MNP-MRI (57.1 ± 10.1%) was significantly larger than that of the infarct area measured by LGE (40.8 ± 11.7%, P<0.0001) and MEMRI (44.1 ± 14.9%, P<0.0001). There were significant correlations between the sizes of the infarct and inflammatory lesions (MNP-MRI versus LGE: r=0.3418, P=0.0099; MNP-MRI versus MEMRI: r=0.4764, P=0.0002). MNP-MRI provides information about inflammatory responses in a mouse model of AMI. Thus, MNP-MRI associated with LGE and MEMRI may play an important role in monitoring the disease progression in MI

Kernel Estimation Using Total Variation Guided GAN for Image Super-Resolution

Various super-resolution (SR) kernels in the degradation model deteriorate the performance of the SR algorithms, showing unpleasant artifacts in the output images. Hence, SR kernel estimation has been studied to improve the SR performance in several ways for more than a decade. In particular, a conventional research named KernelGAN has recently been proposed. To estimate the SR kernel from a single image, KernelGAN introduces generative adversarial networks(GANs) that utilize the recurrence of similar structures across scales. Subsequently, an enhanced version of KernelGAN, named E-KernelGAN, was proposed to consider image sharpness and edge thickness. Although it is stable compared to the earlier method, it still encounters challenges in estimating sizable and anisotropic kernels because the structural information of an input image is not sufficiently considered. In this paper, we propose a kernel estimation algorithm called Total Variation Guided KernelGAN (TVG-KernelGAN), which efficiently enables networks to focus on the structural information of an input image. The experimental results show that the proposed algorithm accurately and stably estimates kernels, particularly sizable and anisotropic kernels, both qualitatively and quantitatively. In addition, we compared the results of the non-blind SR methods, using SR kernel estimation techniques. The results indicate that the performance of the SR algorithms was improved using our proposed method

Unexpected Collision Avoidance Driving Strategy Using Deep Reinforcement Learning

In this paper, we generated intelligent self-driving policies that minimize the injury severity in unexpected traffic signal violation scenarios at an intersection using the deep reinforcement learning. We provided guidance on reward engineering in terms of the multiplicity of objective function. We used a deep deterministic policy gradient method in the simulated environment to train self-driving agents. We designed two agents, one with a single-objective reward function of collision avoidance and the other with a multi-objective reward function of both collision avoidance and goal-approaching. We evaluated their performances by comparing the percentages of collision avoidance and the average injury severity against those of human drivers and an autonomous emergency braking (AEB) system. The percentage of collision avoidance of our agents were 78.89% higher than human drivers and 84.70% higher than the AEB system. The average injury severity score of our agents were only 8.92% of human drivers and 6.25% of the AEB system

A Preliminary Application of Magnetic Resonance Spectroscopy for Quantitatively Assessing Hepatic Fat and the Efficacy of Anti-obesity Therapy

Alcoholic and non-alcoholic fatty liver diseases cause insulin resistance and may develop into metabolic diseases such as steatohepatitis or type II diabetes. Standard histopathological examinations are routinely used to measure hepatic fat in order to assess and treat liver diseases, but this method is invasive, complicated, and time-consuming. Here, we present a noninvasive technique, localized magnetic resonance spectroscopy (MRS), for quantitatively measuring hepatic fat in vivo and in situ. This method allowed us to create a relatively high-resolution time series from the same mouse. Further, it enabled us to examine the efficacy of cryptotanshinone (Ct) treatment in male mice with non-alcoholic fatty liver disease; MRS clearly showed that mice treated with Ct experienced a dramatic reduction in hepatic fat content compared with control mice. Thus, the localized MRS technique shows promise as a tool for in vivo assessments of drug efficacy against liver fat diseases and for early-stage disease preventio

Inkjet printed electronics using copper nanoparticle ink

Inkjet printing of electrode using copper nanoparticle ink is presented. Electrode was printed on a flexible glass epoxy composite substrate using drop on demand piezoelectric dispenser and was sintered at 200 °C of low temperature in N2 gas condition. The printed electrodes were made with various widths and thickness. In order to control the thickness of the printed electrode, number of printing was varied. Resistivity of printed electrode was calculated from the cross-sectional area measured by a profilometer and resistance measured by a digital multimeter. Surface morphology of electrode was analyzed using scanning electron microscope (SEM) and atomic force microscope (AFM). From the study, it was found that 10 times printed electrode has the most stable grain structure and low resistivity of 36.7 nΩ m

Cu²⁺-Responsive Bimodal (Optical/MRI) Contrast Agent for Cellular Imaging

A water-soluble T₁ magnetic resonance imaging contrast agent (<b>1</b>) has been synthesized. The bimodal contrast agent <b>1</b> responds to the Cu²⁺ ion in living cells by enhancing the MRI modality signal whereas the optical signal gradually drops. This dual modality probe response depends on the cellular free copper ions in RAW 264.7 cells even at the micromolar level