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Complex oxide heterointerfaces and heterostructures have demonstrated enormous emergent phenomena over the last decades, attributed to the reconstructions of mis‐matched crystalline structure, polarity, and spin ordering across the heterointerfaces. This work employs the heterostructures of La0.7Sr0.3MnO3 and CaFeO2.5 as model system to demonstrate an interface‐specific oxygen migration/reconstruction across the interfaces due to the mismatched chemical potential, which dramatically influences the ferromagnetic and electronic states of La0.7Sr0.3MnO3 layer. Specifically, the alternative stacking of octahedral (Oh) and tetrahedral (Td) layers in CaFeO2.5 are used to form two distinct heterointerfaces, namely the Oh‐Td and the Oh‐Oh interfaces with the adjacent La0.7Sr0.3MnO3 layer. Interestingly, the oxygen ion migrates toward opposite directions across the interface for these two cases, in which the CaFeO2.5 layer acts as an "oxygen pump" and manipulates the oxygen contents of its adjacent La0.7Sr0.3MnO3 layers. Such manipulation leads to a dramatically changed ferromagnetic transition temperature for the heterostructure with the Oh‐Td and Oh‐Oh interface. This work establishes a feasible and efficient strategy to control the oxygen ionic distribution through atomic‐scale interface design and opens up new opportunities to exploit emergent states at the complex oxide heterostructures through selective oxygen ion evolution. [ABSTRACT FROM AUTHOR]

Chemical reduction in oxides plays a crucial role in engineering the material properties through structural transformation and electron filling. Controlling the reduction at nanoscale forms a promising pathway to harvest functionalities, which however is of great challenge for conventional methods (e.g., thermal treatment and chemical reaction). Here, we demonstrate a convenient pathway to achieve nanoscale chemical reduction for vanadium dioxide through the electron-beam illumination. The electron beam induces both surface oxygen desorption through radiolytic process and positively charged background through secondary electrons, which contribute cooperatively to facilitate the vacancy migration from the surface toward the sample bulk. Consequently, the VO2 transforms into a reduced V2O3 phase, which is associated with a distinct insulator to metal transition at room temperature. Furthermore, this process shows an interesting facet-dependence with the pronounced transformation observed for the c-facet VO2 as compared with the a-facet, which is attributed to the intrinsically different oxygen vacancy formation energy between these facets. Remarkably, we readily achieve a lateral resolution of tens nanometer for the controlled structural transformation with a commercial scanning electron microscope. This work provides a feasible strategy to manipulate the nanoscale chemical reduction in complex oxides for exploiting functionalities. The authors demonstrate a nanoscale chemical reduction for VO2 into V2O3 through electron-beam illumination, showcasing potential for nanoscale manipulation of oxygen ionic evolution for advanced harvesting functionalities. [ABSTRACT FROM AUTHOR]

Background: Reduced signal on fluorodeoxyglucose-positron emission tomography (FDG-PET) is a valid proxy for neurodegeneration in Alzheimer's disease (AD). Perivascular space (PVS) is believed to be associated with AD pathology and cognitive decline.Objective: This study aimed to investigate the associations of PVS with FDG-PET and cognitive performance based on the burden of amyloid pathology.Methods: We used magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI). MRI-visible PVS in basal ganglia (BG) and centrum semi-oval (CSO) were visually classified as: none/mild, moderate or frequent/severe. The association of PVS with brain FDG-PET was explored based on the burden of amyloid pathology, where a cerebrospinal fluid (CSF) t-tau/Aβ42 with the ratio≥0.27 was defined as high amyloid pathology. Moreover, the relationships between PVS and cognitive performance variables (ADNI-MEM and ADNI-EF) were studied.Results: For participants with higher tau/Aβ42 ratio, CSO-PVS severity was independently associated with lower FDG-PET. There were significant interaction effects between moderate or frequent/severe CSO-PVS and time on FDG decline in people with high amyloid pathology. The interaction between CSO-PVS and time (follow-up) was consistently associated with ADNI-MEM and ADNI-EF decline in individuals with high amyloid pathology.Conclusion: The study established the differential utility of PVS in BG and CSO for predicting brain metabolism. These findings suggest that CSO-PVS serves as a contributing factor to brain metabolism and cognitive decline associated with amyloid pathology. [ABSTRACT FROM AUTHOR]

This article was to explore the adoption value of deep learning combined with computed tomography (CT) imaging omics in the prediction of metastatic lymph nodes of nasopharyngeal carcinoma (NPC). An end‐to‐end neural network architecture was designed based on the fully convolutional neural network (FCNN), which was applied to the CT image analysis of 52 patients with lymphatic metastasis and 36 patients without lymphatic metastasis. Patient's lymph node volume (V), the largest cross‐sectional shortest diameter (d‐value), and other macro characteristics were recorded. The microscopic features of its CT imaging omics were extracted. Moreover, receiver operating characteristic (ROC) curve was utilized to analyse the prediction performance (accuracy, area under the curve [AUC], and Youden index) of each feature for lymphatic metastasis. The results showed that the lymph node volume (4.37 ± 0.67) and the shortest diameter of the largest cross section (12.35 ± 2.31) of patients with lymph node metastasis were greatly larger than those without lymph node metastasis (1.84 ± 0.65, 7.98 ± 2.04) (P < 0.05). There were five features that met the conditions of AUC > 0.7 and Yoden index>0.5, including lymph node volume (AUC area 0.945, Youden index 0.597), the shortest diameter of the largest cross section (AUC area 0.746, Youden index 0.539), Surface Area Density (AUC area 0.809, Youden index 0.552), Compactness1 (AUC area 0.751, Youden index 0.537), and Convex Hull Volume (AUC area 0.751, Youden index 0.537). The AUC of V+ Surface Area Density + Compactness1 + Convex Hull Volume was 0.876, and the prediction accuracy was 92.11%. In short, the prediction model composed of the macroscopic features of CT images and some imaging omics features based on deep learning showed high accuracy and AUC for the prediction of NPC metastatic lymph nodes. Moreover, V + Surface Area Density + Compactness1 + Convex Hull Volume can be used as the optimal feature combination model for predicting NPC lymphatic metastasis. [ABSTRACT FROM AUTHOR]

Chemical reduction in oxides plays a crucial role in engineering the material properties through structural transformation and electron filling. Controlling the reduction at nanoscale forms a promising pathway to harvest functionalities, which however is of great challenge for conventional methods (e.g., thermal treatment and chemical reaction). Here, we demonstrate a convenient pathway to achieve nanoscale chemical reduction for vanadium dioxide through the electron-beam illumination. The electron beam induces both surface oxygen desorption through radiolytic process and positively charged background through secondary electrons, which contribute cooperatively to facilitate the vacancy migration from the surface toward the sample bulk. Consequently, the VO 2 transforms into a reduced V 2 O 3 phase, which is associated with a distinct insulator to metal transition at room temperature. Furthermore, this process shows an interesting facet-dependence with the pronounced transformation observed for the c-facet VO 2 as compared with the a-facet, which is attributed to the intrinsically different oxygen vacancy formation energy between these facets. Remarkably, we readily achieve a lateral resolution of tens nanometer for the controlled structural transformation with a commercial scanning electron microscope. This work provides a feasible strategy to manipulate the nanoscale chemical reduction in complex oxides for exploiting functionalities., (© 2023. The Author(s).)