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Background and purpose: Hyperphosphorylation of Tau is one of the important pathological features of Alzheimer's disease (AD). Therefore, studying the mechanisms behind Tau hyperphosphorylation is crucial in exploring the pathogenesis of neurological damage in AD. Methods: In this study, after the establishment of rat models of AD, quantitative phosphoproteomics and proteomics were performed to identify proteins, showing that phosphorylation of microtubule associated protein 1A (MAP 1A) was lower in the model group. Western blot confirmed the changes of MAP 1A in the SD rats, APP/PS1 transgenic mice and cell AD models. To further study the molecular mechanism of recombinant MAP 1A phosphorylation affecting Tau phosphorylation, interfering siRNA‐MAP 1A and protein immunoprecipitation reaction analysis were performed in AD cell models. Results: Cyclin‐dependent kinase 5 (CDK5) showed reduced binding to MAP 1A and increased binding to Tau, resulting in a decrease in phosphorylated MAP 1A (p‐MAP 1A) and an increase in phosphorylated Tau (p‐Tau), and MAP 1A silencing promoted binding of CDK5‐Tau and increased Tau phosphorylation, thereby reducing the cell survival rate. Conclusions: In summary, we found that p‐MAP 1A downregulation associated with p‐Tau upregulation was due to their altered binding forces to CDK5, and MAP 1A could enhance autophosphorylation by competitive binding to CDK5 and antagonise Tau phosphorylation. This leads to neuronal protection and reducing tissue damage levels in AD, which can help better understand the mechanisms of AD pathogenesis. [ABSTRACT FROM AUTHOR]

Metal coordination compound (MCC) glasses [e.g., metal‐organic framework (MOF) glass, coordination polymer glass, and metal inorganic‐organic complex (MIOC) glass] are emerging members of the hybrid glass family. So far, a limited number of crystalline MCCs can be converted into glasses by melt‐quenching. Here, we report a universal wet‐chemistry method, by which the super‐sized supramolecular MIOC glasses can be synthesized from non‐meltable MOFs. Alcohol and acid were used as agents to inhibit crystallization. The MIOC glasses demonstrate unique features including high transparency, shaping capability, and anisotropic network. Directional photoluminescence with a large polarization ratio (≈47 %) was observed from samples doped with organic dyes. This crystallization‐suppressing approach enables fabrication of super‐sized MCC glasses, which cannot be achieved by conventional vitrification methods, and thus allows for exploring new MCC glasses possessing photonic functionalities. [ABSTRACT FROM AUTHOR]

Constructing 0D–2D mixed‐dimensional van der Waals (MvdW) heterostructures is an effective strategy to improve photovoltaic properties of photovoltaic devices. However, addressing the underlying mechanism on the role of array periodicity of 0D and thickness of 2D components on the photovoltaic properties at the atomic‐level still remains challenging. Herein, the interfacial charge transfer and photovoltaic conversion mechanism in C60/MoS2 0D–2D MvdWs based on the atomic‐bond‐relaxation consideration, Marcus theory, modified‐detailed balance principle, and first‐principles calculations are investigated. Compared with the case of monolayer MoS2, it is found that C60/MoS2 MvdW heterostructures have lower interface reflectivity and type II band alignment, leading to obvious improvement of power conversion efficiency (PCE) from 0.27% to 1.40%. Moreover, the photovoltaic properties can be tuned by changing the array periodicity of the C60 and the thickness of the MoS2, and the optimized PCE can be up to 5.35%. The results reveal that the modification of 0D C60 is an effective strategy to enhance the photovoltaic properties of MoS2‐based solar cells. [ABSTRACT FROM AUTHOR]

Functional network connectivity has been widely acknowledged to characterize brain functions, which can be regarded as "brain fingerprinting" to identify an individual from a pool of subjects. Both common and unique information has been shown to exist in the connectomes across individuals. However, very little is known about whether and how this information can be used to predict the individual variability of the brain. In this paper, we propose to enhance the uniqueness of individual connectome based on an autoencoder network. Specifically, we hypothesize that the common neural activities shared across individuals may reduce the individual identification. By removing contributions from shared activities, inter‐subject variability can be enhanced. Our experimental results on HCP data show that the refined connectomes obtained by utilizing autoencoder with sparse dictionary learning can distinguish an individual from the remaining participants with high accuracy (up to 99.5% for the rest–rest pair). Furthermore, high‐level cognitive behaviors (e.g., fluid intelligence, executive function, and language comprehension) can also be better predicted with the obtained refined connectomes. We also find that high‐order association cortices contribute more to both individual discrimination and behavior prediction. In summary, our proposed framework provides a promising way to leverage functional connectivity networks for cognition and behavior study, in addition to a better understanding of brain functions. [ABSTRACT FROM AUTHOR]

Background: Growing evidences have been revealing that long noncoding RNAs are vital factors in oncogenesis and tumor development. Among them, cancer susceptibility candidate 11 (CASC11) has displayed an impressively essential role in various kinds of cancers including hepatocellular carcinoma (HCC). Nevertheless, its role and potential mechanism in HCC still remain to be fully investigated. Methods: CASC11 expression level was evaluated by real‐time polymerase chain reaction, western blotting, and in situ hybridization staining in HCC patients, and its prognostic effect was analyzed. The role of CASC11 in HCC tumorigenesis and progression was investigated by cell proliferation assay, transwell assay, extracellular acidification rate, western blotting, flow cytometry, and an in vivo xenograft model. The interactions among CASC11, E2F transcription factor 1 (E2F1), and eukaryotic translation initiation factor 4A3 (EIF4A3) were explored by using quantitative reverse transcriptase polymerase chain reaction, western blotting, RNA‐binding protein immunoprecipitation assay, and chromatin immunoprecipitation assays. Results: Upregulation of CASC11 was confirmed in HCC tissues and associated with poor prognosis. Loss of function assays showed inhibition of CASC11 expression suppressed HCC cells proliferation, mobility, and glucose metabolism and promoted apoptosis. E2F1 expression significantly decreased after inhibition of CASC11. Rescue experiments illustrated that E2F1 overexpression alleviated the suppression of CASC11 inhibition on HCC progression in vitro and in vivo. Mechanistically, CASC11 recruited EIF4A3 to enhance the stability of E2F1 mRNA. CASC11 and E2F1 impacted the activation of the NF‐κB signaling and PI3K/AKT/mTOR pathway and further regulated the expression PD‐L1 that is an important target of immunotherapy. In addition, we identified YY1 could modulate CASC11 expression by binding to its promoter. Conclusions: Our data revealed that CASC11 promoted the progression of HCC by means of EIF4A3‐mediated E2F1 upregulation, indicating CASC11 is a promising diagnostic biomarker and therapeutic target for HCC. [ABSTRACT FROM AUTHOR]

Brain functional connectome analysis is commonly based on population‐wise inference. However, in this way precious information provided at the individual subject level may be overlooked. Recently, several studies have shown that individual differences contribute strongly to the functional connectivity patterns. In particular, functional connectomes have been proven to offer a fingerprint measure, which can reliably identify a given individual from a pool of participants. In this work, we propose to refine the standard measure of individual functional connectomes using dictionary learning. More specifically, we rely on the assumption that each functional connectivity is dominated by stable group and individual factors. By subtracting population‐wise contributions from connectivity patterns facilitated by dictionary representation, intersubject variability should be increased within the group. We validate our approach using several types of analyses. For example, we observe that refined connectivity profiles significantly increase subject‐specific identifiability across functional magnetic resonance imaging (fMRI) session combinations. Besides, refined connectomes can also improve the prediction power for cognitive behaviors. In accordance with results from the literature, we find that individual distinctiveness is closely linked with differences in neurocognitive activity within the brain. In summary, our results indicate that individual connectivity analysis benefits from the group‐wise inferences and refined connectomes are indeed desirable for brain mapping. [ABSTRACT FROM AUTHOR]

X‐ray phase‐contrast imaging can substantially enhance image contrast for weakly absorbing samples. The fabrication of dedicated optics remains a major barrier, especially in high‐energy regions (i.e. over 50 keV). Here, the authors perform X‐ray phase‐contrast imaging by using engineered porous materials as random absorption masks, which provides an alternative solution to extend X‐ray phase‐contrast imaging into previously challenging higher energy regions. The authors have measured various samples to demonstrate the feasibility of the proposed engineering materials. This technique could potentially be useful for studying samples across a wide range of applications and disciplines. [ABSTRACT FROM AUTHOR]