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Owing to the increasing prevalence of diabetic mellitus, diabetic kidney disease (DKD) is presently the leading cause of chronic kidney disease and end‐stage renal disease worldwide. Early identification and disease interception is of paramount clinical importance for DKD management. However, current diagnostic, disease monitoring and prognostic tools are not satisfactory, due to their low sensitivity, low specificity, or invasiveness. Magnetic resonance imaging (MRI) is noninvasive and offers a host of contrast mechanisms that are sensitive to pathophysiological changes and risk factors associated with DKD. MRI tissue characterization involves structural and functional information including renal morphology (kidney volume (TKV) and parenchyma thickness using T1‐ or T2‐weighted MRI), renal microstructure (diffusion weighted imaging, DWI), renal tissue oxygenation (blood oxygenation level dependent MRI, BOLD), renal hemodynamics (arterial spin labeling and phase contrast MRI), fibrosis (DWI) and abdominal or perirenal fat fraction (Dixon MRI). Recent (pre)clinical studies demonstrated the feasibility and potential value of DKD evaluation with MRI. Recognizing this opportunity, this review outlines key concepts and current trends in renal MRI technology for furthering our understanding of the mechanisms underlying DKD and for supplementing clinical decision‐making in DKD. Progress in preclinical MRI of DKD is surveyed, and challenges for clinical translation of renal MRI are discussed. Future directions of DKD assessment and renal tissue characterization with (multi)parametric MRI are explored. Opportunities for discovery and clinical break‐through are discussed including biological validation of the MRI findings, large‐scale population studies, standardization of DKD protocols, the synergistic connection with data science to advance comprehensive texture analysis, and the development of smart and automatic data analysis and data visualization tools to further the concepts of virtual biopsy and personalized DKD precision medicine. We hope that this review will convey this vision and inspire the reader to become pioneers in noninvasive assessment and management of DKD with MRI. Level of Evidence: 1 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

Summary: Exogenous enzymes, accompanied by a function of assisting digestion, can be employed in therapeutic application which supplement the daily diet for the patients suffering from gastrointestinal diseases. To prevent the degradation of the enzymes in gastric fluid, papain was encapsulated into alginate microspheres with the external wrap of chitin nanocrystals. The protective effect of the assembled alginate microspheres (PAM‐ChNC) on papain was studied and compared with traditional chitosan‐coated alginate microspheres (PAM‐Ch). Scanning electron microscopy results showed that ChNC could form a dense structure on the surface of alginate microspheres. The swelling rate of PAM‐ChNC was lower than that of PAM‐Ch at pH 1.2. The effect of papain (encapsulated in microspheres) on the digestion of myofibrillar protein gels (MP) was investigated by in vitro digestion. The results showed that the degree of hydrolysis of MP + PAM‐ChNC was significantly higher than that of MP+ PAM‐Ch, indicating that PAM‐ChNC was expected to become a controlled release system for oral exogenous enzymes that assist digestion. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the feasibility of two‐dimensional (2D) navigated, interleaved multishot echo‐planar imaging (EPI) to enhance kidney diffusion‐weighted imaging (DWI) in rats at 7.0 T. Fully sampled interleaved four‐shot EPI with 2D navigators was tailored for kidney DWI (Sprague–Dawley rats, n = 7) on a 7.0‐T small bore preclinical scanner. The image quality of four‐shot EPI was compared with T2‐weighted rapid acquisition with relaxation enhancement (RARE) (reference) and single‐shot EPI (ss‐EPI) without and with parallel imaging (PI). The contrast‐to‐noise ratio (CNR) was examined to assess the image quality for the EPI approaches. The Dice similarity coefficient and the Hausdorff distance were used for evaluation of image distortion. Mean diffusivity (MD) and fractional anisotropy (FA) were calculated for renal cortex and medulla for all DWI approaches. The corticomedullary difference of MD and FA were assessed by Wilcoxon signed‐rank test. Four‐shot EPI showed the highest CNR among the three EPI variants and lowest geometric distortion versus T2‐weighted RARE (mean Dice: 0.77 for ss‐EPI without PI, 0.88 for ss‐EPI with twofold undersampling, and 0.92 for four‐shot EPI). The FA map derived from four‐shot EPI clearly identified a highly anisotropic region corresponding to the inner stripe of the outer medulla. Four‐shot EPI successfully discerned differences in both MD and FA between renal cortex and medulla. In conclusion, 2D navigated, interleaved multishot EPI facilitates high‐quality rat kidney DWI with clearly depicted intralayer and interlayer structure and substantially reduced image distortion. This approach enables the anatomic integrity of DWI‐MRI in small rodents and has the potential to benefit the characterization of renal microstructure in preclinical studies. [ABSTRACT FROM AUTHOR]

Metal phosphides have triggered growing interest for their exotic structures and striking properties. Hence, within advanced structure search and first‐principle calculations, several unprecedented Y−P compounds (e. g., Y3P, Y2P, Y3P2, Y2P3, YP2, and YP3) were identified under compression. Interestingly, as phosphorus content increases, P atoms exhibit diverse behaviors corresponding to standalone anion, dumbbell, zigzag chain, planar sheet, crossing chain‐like network, buckled layer, three‐dimensional framework, and wrinkled layer. Particularly, Fd‐3m YP2 can be viewed as assemblage of diamond‐like Y structure and rare vertex‐sharing tetrahedral P4 units. Impressively, electron‐phonon coupling (EPC) calculations elucidate that Pm‐3m Y3P possesses the highest superconducting critical temperature Tc of 10.2 K among binary transition metal phosphides. Remarkably, the EPC of Pm‐3m Y3P mainly arises from the contribution of low‐frequency soft phonon modes, whereas mid‐frequency phonon modes of Fd‐3m YP2 dominate. These results strengthen knowledge of metal phosphides and pave a way for seeking superconductive transition metal phosphides. [ABSTRACT FROM AUTHOR]

Aim: Kidney diseases constitute a major health challenge, which requires noninvasive imaging to complement conventional approaches to diagnosis and monitoring. Several renal pathologies are associated with changes in kidney size, offering an opportunity for magnetic resonance imaging (MRI) biomarkers of disease. This work uses dynamic MRI and an automated bean‐shaped model (ABSM) for longitudinal quantification of pathophysiologically relevant changes in kidney size. Methods: A geometry‐based ABSM was developed for kidney size measurements in rats using parametric MRI (T2, T2* mapping). The ABSM approach was applied to longitudinal renal size quantification using occlusion of the (a) suprarenal aorta or (b) the renal vein, (c) increase in renal pelvis and intratubular pressure and (d) injection of an X‐ray contrast medium into the thoracic aorta to induce pathophysiologically relevant changes in kidney size. Results: The ABSM yielded renal size measurements with accuracy and precision equivalent to the manual segmentation, with >70‐fold time savings. The automated method could detect a ~7% reduction (aortic occlusion) and a ~5%, a ~2% and a ~6% increase in kidney size (venous occlusion, pelvis and intratubular pressure increase and injection of X‐ray contrast medium, respectively). These measurements were not affected by reduced image quality following administration of ferumoxytol. Conclusion: Dynamic MRI in conjunction with renal segmentation using an ABSM supports longitudinal quantification of changes in kidney size in pathophysiologically relevant experimental setups mimicking realistic clinical scenarios. This can potentially be instrumental for developing MRI‐based diagnostic tools for various kidney disorders and for gaining new insight into mechanisms of renal pathophysiology. [ABSTRACT FROM AUTHOR]

Purpose: Examine the feasibility of characterizing the regulation of renal oxygenation using high‐temporal‐resolution monitoring of the T2∗ response to a step‐like oxygenation stimulus. Methods: For T2∗ mapping, multi‐echo gradient‐echo imaging was used (temporal resolution = 9 seconds). A step‐like renal oxygenation challenge was applied involving sequential exposure to hyperoxia (100% O2), hypoxia (10% O2 + 90% N2), and hyperoxia (100% O2). In vivo experiments were performed in healthy rats (N = 10) and in rats with bilateral ischemia‐reperfusion injury (N = 4). To assess the step response of renal oxygenation, a second‐order exponential model was used (model parameters: amplitude [A], time delay [Δt], damping constant [D], and period of the oscillation [T]) for renal cortex, outer stripe of the outer medulla, inner stripe of the outer medulla, and inner medulla. Results: The second‐order exponential model permitted us to model the exponential T2∗ recovery and the superimposed T2∗ oscillation following renal oxygenation stimulus. The in vivo experiments revealed a difference in Douter medulla between healthy controls (D < 1, indicating oscillatory recovery) and ischemia‐reperfusion injury (D > 1, reflecting aperiodic recovery). The increase in Douter medulla by a factor of 3.7 (outer stripe of the outer medulla) and 10.0 (inner stripe of the outer medulla) suggests that this parameter might be rather sensitive to (patho)physiological oxygenation changes. Conclusion: This study demonstrates the feasibility of monitoring the dynamic oxygenation response of renal tissues to a step‐like oxygenation challenge using high‐temporal‐resolution T2∗ mapping. Our results suggest that the implemented system analysis approach may help to unlock questions regarding regulation of renal oxygenation, with the ultimate goal of providing imaging means for diagnostics and therapy of renal diseases. [ABSTRACT FROM AUTHOR]

Bimetallic hollow nanomaterials which are composed of two different metal/metal oxide materials show great potentials owing to their unique structural features. Here, the second metal ions were introduced into the surface of ZIF‐67 by ultrasonication to form bimetallic hollow complexes, and the coordination between the second metal ions and ZIF‐67 colloidal crystals are further investigated. A series of bimetallic complexes has been synthesized by incorporating FeIII, CuII and NiII into the coordinating block of ZIF‐67. After calcination in oxygen, these as‐prepared transformed to Fe/Cu/Ni doped Co3O4 hollow nanoboxes. We found a facile and general method to form bimetallic complexes by complexing the second metal ions with ZIF‐67 surface ligands and calcining to form bimetallic hollow nanoboxes. [ABSTRACT FROM AUTHOR]

Purpose: To develop a machine learning approach using convolutional neural network for reducing MRI Gibbs‐ringing artifact. Theory and Methods: Gibbs‐ringing artifact in MR images is caused by insufficient sampling of the high frequency data. Existing methods exploit smooth constraints to reduce intensity oscillations near sharp edges at the cost of blurring details. In this work, we developed a machine learning approach for removing the Gibbs‐ringing artifact from MR images. The ringing artifact was extracted from the original image using a deep convolutional neural network and then subtracted from the original image to obtain the artifact‐free image. Finally, its low‐frequency k‐space data were replaced with measured counterparts to enforce data fidelity further. We trained the convolutional neural network using 17,532 T2‐weighted (T2W) normal brain images and evaluated its performance on T2W images of normal and tumor brains, diffusion‐weighted brain images, and T2W knee images. Results: The proposed method effectively removed the ringing artifact without noticeable smoothing in T2W and diffusion‐weighted images. Quantitatively, images produced by the proposed method were closer to the fully‐sampled reference images in terms of the root‐mean‐square error, peak signal‐to‐noise ratio, and structural similarity index, compared with current state‐of‐the‐art methods. Conclusion: The proposed method presents a novel and effective approach for Gibbs‐ringing reduction in MRI. The convolutional neural network‐based approach is simple, computationally efficient, and highly applicable in routine clinical MRI. [ABSTRACT FROM AUTHOR]