| 1. |
- Li, Sirui, et al.
(författare)
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Glioma grading, molecular feature classification, and microstructural characterization using MR diffusional variance decomposition (DIVIDE) imaging
- 2021
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Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 31:11, s. 8197-8207
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To evaluate the potential of diffusional variance decomposition (DIVIDE) for grading, molecular feature classification, and microstructural characterization of gliomas. Materials and methods: Participants with suspected gliomas underwent DIVIDE imaging, yielding parameter maps of fractional anisotropy (FA), mean diffusivity (MD), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), total mean kurtosis (MKT), MKA/MKT, and microscopic fractional anisotropy (μFA). Tumor type and grade, isocitrate dehydrogenase (IDH) 1/2 mutant status, and the Ki-67 labeling index (Ki-67 LI) were determined after surgery. Statistical analysis included 33 high-grade gliomas (HGG) and 17 low-grade gliomas (LGG). Tumor diffusion metrics were compared between HGG and LGG, among grades, and between wild and mutated IDH types using appropriate tests according to normality assessment results. Receiver operating characteristic and Spearman correlation analysis were also used for statistical evaluations. Results: FA, MD, MKA, MKI, MKT, μFA, and MKA/MKT differed between HGG and LGG (FA: p = 0.047; MD: p = 0.037, others p < 0.001), and among glioma grade II, III, and IV (FA: p = 0.048; MD: p = 0.038, others p < 0.001). All diffusion metrics differed between wild-type and mutated IDH tumors (MKI: p = 0.003; others: p < 0.001). The metrics that best discriminated between HGG and LGGs and between wild-type and mutated IDH tumors were MKT and FA respectively (area under the curve 0.866 and 0.881). All diffusion metrics except FA showed significant correlation with Ki-67 LI, and MKI had the highest correlation coefficient (rs = 0.618). Conclusion: DIVIDE is a promising technique for glioma characterization and diagnosis. Key Points: • DIVIDE metrics MKIis related to cell density heterogeneity while MKAand μFA are related to cell eccentricity. • DIVIDE metrics can effectively differentiate LGG from HGG and IDH mutation from wild-type tumor, and showed significant correlation with the Ki-67 labeling index. • MKIwas larger than MKAwhich indicates predominant cell density heterogeneity in gliomas. • MKAand MKIincreased with grade or degree of malignancy, however with a relatively larger increase in the cell eccentricity metric MKAin relation to the cell density heterogeneity metric MKI.
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| 2. |
- Sun, Wenbo, et al.
(författare)
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Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI
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Ingår i: Magnetic Resonance Materials in Physics, Biology and Medicine. - 0968-5243.
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To assess the performance of hybrid multi-dimensional magnetic resonance imaging (HM-MRI) in quantifying hematoxylin and eosin (H&E) staining results, grading and predicting isocitrate dehydrogenase (IDH) mutation status of gliomas. Materials and methods: Included were 71 glioma patients (mean age, 50.17 ± 13.38 years; 35 men). HM-MRI images were collected at five different echo times (80–200 ms) with seven b-values (0–3000 s/mm2). A modified three-compartment model with very-slow, slow and fast diffusion components was applied to calculate HM-MRI metrics, including fractions, diffusion coefficients and T2 values of each component. Pearson correlation analysis was performed between HM-MRI derived fractions and H&E staining derived percentages. HM-MRI metrics were compared between high-grade and low-grade gliomas, and between IDH-wild and IDH-mutant gliomas. Using receiver operational characteristic (ROC) analysis, the diagnostic performance of HM-MRI in grading and genotyping was compared with mono-exponential models. Results: HM-MRI metrics FDvery-slow and FDslow demonstrated a significant correlation with the H&E staining results (p <.05). Besides, FDvery-slow showed the highest area under ROC curve (AUC = 0.854) for grading, while Dslow showed the highest AUC (0.845) for genotyping. Furthermore, a combination of HM-MRI metrics FDvery-slow and T2Dslow improved the diagnostic performance for grading (AUC = 0.876). Discussion: HM-MRI can aid in non-invasive diagnosis of gliomas.
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| 3. |
- Feng, Haibo, et al.
(författare)
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China’s VAT Reform, Enterprises Tax Burden and Innovation
- 2022
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- The impact of China’s VAT reform on enterprise innovation is the result of the combination of tax cuts and endogenous incentives. We find evidence that China’ VAT reform generally reduced the tax burden of firms but had a different impact on the manufacturing and the service industry. The tax burden of the manufacturing dropped significantly, but that of the service industry did not change markedly. Furthermore, we show that China’s VAT reform had also a significant positive impact on corporate innovation for both the service industry and the manufacturing. However, these effects were significantly greater in the manufacturing. Meanwhile, China’s VAT reform did not alleviate the tax burden of all the enterprises. For the enterprises facing the increased burden of tax, the reform can still stimulate the enterprise innovation if it has sufficient own capital, whereas the impact coefficient and significant level reduced significantly compared with the enterprises that the burden of tax reduced. If the enterprise’s own capital is insufficient, VAT reform has little effect on enterprise innovation. Finally, we show that China’s VAT reform exerted different influences on the innovative behavior of heterogeneous enterprises.
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| 4. |
- Li, Xiansheng, et al.
(författare)
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A Multifunctional Small-Molecule Hole- Transporting Material Enables Perovskite QLEDs with EQE Exceeding 20%
- 2023
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Ingår i: ACS Energy Letters. - : AMER CHEMICAL SOC. - 2380-8195. ; 8:3, s. 1445-1454
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Tidskriftsartikel (refereegranskat)abstract
- Hole-transporting materials (HTMs) play critical roles in the device performance and stability of perovskite quantum dot light-emitting diodes (Pe-QLEDs). However, the development of small-molecule HTMs for achieving high-performance Pe-QLEDs has proven to be very challenging because of their low hole mobility and poor solvent resistance. Herein, we tailor-made a multifunc-tional small-molecule HTM, termed X10, with methoxy as the substituents, for application in Pe-QLEDs. X10 features high hole mobility, good film-forming ability, and strong solvent resistance ability as well as defect passivation effect. Subsequently, Pe-QLEDs employing X10 as HTM presented a promising external quantum efficiency (EQE) of 20.18%, which is 7-fold higher than that of the reference HTM-TCTA-based ones (EQE approximate to 2.88%). To the best of our knowledge, this is the first case in which a small-molecule HTM displays a high EQE over 20% in Pe-QLEDs. Our work provides important guidance for the rational design of multifunctional small-molecule HTMs for high-performance Pe-QLEDs.
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| 5. |
- Shao, Wen-Ze, et al.
(författare)
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On potentials of regularized Wasserstein generative adversarial networks for realistic hallucination of tiny faces
- 2019
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Ingår i: Neurocomputing. - : ELSEVIER. - 0925-2312 .- 1872-8286. ; 364, s. 1-15
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Tidskriftsartikel (refereegranskat)abstract
- Super-resolution of facial images, a.k.a. face hallucination, has been intensively studied in the past decades due to the increasingly emerging analysis demands in video surveillance, e.g., face detection, verification, identification. However, the actual performance of most previous hallucination approaches will drop dramatically when a very low-res tiny face is provided, due to the challenging multimodality of the problem as well as lack of an informative prior as a strong semantic guidance. Inspired by the latest progress in deep unsupervised learning, this paper focuses on tiny faces of size 16 x 16 pixels, hallucinating them to their 8 x upsampling versions by exploring the potentials of Wasserstein generative adversarial networks (WGAN). Besides a pixel-wise L2 regularization term imposed to the generative model, it is found that our advocated autoencoding generator with both residual and skip connections is a critical component for WGAN representing the facial contour and semantic content to a reasonable precision. With the additional Lipschitz penalty and architectural considerations for the critic in WGAN, the proposed approach finally achieves state-of-the-art hallucination performance in terms of both visual perception and objective assessment. The cropped CelebA face dataset is primarily used to aid the tuning and analysis of the new method, termed as tfh-WGAN. Experimental results demonstrate that the proposed approach not only achieves realistic hallucination of tiny faces, but also adapts to pose, expression, illuminance and occluded variations to a great degree.
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| 6. |
- Xie, Shipeng, et al.
(författare)
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Artifact Removal Using GAN Network for Limited-Angle CT Reconstruction
- 2019
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Ingår i: 2019 9th International Conference on Image Processing Theory, Tools and Applications, IPTA 2019.
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Konferensbidrag (refereegranskat)abstract
- Computed tomography (CT) plays an increasingly important role in clinical diagnosis. However, in practical applications of CT, physical limitations on acquisition lead to some blind regions where data cannot be sampled. CT image reconstruction from limited-angle would enable a rapid scanning with a reduced x-ray dose delivered to the patient. As it is known, Generative Adversarial Networks (GAN) can keep the original information and details of the sample very well. In this paper, we propose an end-to-end Generative Adversarial Networks model used for removing artifacts from limited-angle CT reconstruction images. The proposed GAN is based on the conditional GAN with the joint loss function, which .can remove the artifacts while retaining the complete details and sharp edges. The intensity of reconstruction using the proposed method is very close to the full-view projective reconstructed image. Compared to several other classic methods, our GAN model shows better consequent, in terms of artifact reduction, feature preservation, and computational efficiency for limited-angle CT reconstruction.
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| 7. |
- Xiong, Yan, et al.
(författare)
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Small molecule Z363 co-regulates TAF10 and MYC via the E3 ligase TRIP12 to suppress tumour growth
- 2023
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Ingår i: CLINICAL AND TRANSLATIONAL MEDICINE. - : JOHN WILEY & SONS LTD. - 2001-1326. ; 13:1
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundThe MYC oncoprotein, also known as the master regulator of genes, is a transcription factor that regulates numerous physiological processes, including cell cycle control, apoptosis, protein synthesis and cell adhesion, among others. MYC is overexpressed in approximately 70% of human cancers. Given its pervasive role in cancer biology, MYC down-regulation has become an attractive cancer treatment strategy. MethodsThe CRISPR/Cas9 method was used to produce KO cell models. Western blot was used to analyzed the expressions of MYC and TATA-binding proteinassociated factors 10 (TAF10) in cancer cells (MCF7, A549, HepG2 cells) Cell culture studies were performed to determine the mechanisms by which small molecules (Z363119456, Z363) affects MYC and TAF10 expressions and functions. Mouse studies were carried out to investigate the impact of Z363 regulation on tumor growth. ResultsZ363 activate Thyroid hormone Receptor-interacting Protein 12 (TRIP12), which phosphorylates MYC at Thr58, resulting in MYC ubiquitination and degradation and thereby regulating MYC target genes. Importantly, TRIP12 also induces TAF10 degradation, which reduces MYC protein levels. TRIP12, an E3 ligase, controls MYC levels both directly and indirectly by inhibiting MYC or TAF10 activity. ConclusionsIn summary,these results demonstrate the anti-cancer properties of Z363, a small molecule that is co-regulated by TAF10 and MYC.
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| 8. |
- Xu, Xiaoran, et al.
(författare)
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Applications of Boron Cluster Supramolecular Frameworks as Metal-Free Chemodynamic Therapy Agents for Melanoma
- 2023
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Ingår i: Small. - : WILEY-V C H VERLAG GMBH. - 1613-6810 .- 1613-6829.
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Tidskriftsartikel (refereegranskat)abstract
- Chemodynamic therapy (CDT) is a highly targeted approach to treat cancer since it converts hydrogen peroxide into harmful hydroxyl radicals (OH & BULL;) through Fenton or Fenton-like reactions. However, the systemic toxicity of metal-based CDT agents has limited their clinical applications. Herein, a metal-free CDT agent: 2,4,6-tri(4-pyridyl)-1,3,5-triazine (TPT)/ [closo-B12H12]2-(TPT@ B12H12) is reported. Compared to the traditional metal-based CDT agents, TPT@B12H12 is free of metal avoiding cumulative toxicity during long-term therapy. Density functional theory (DFT) calculation revealed that TPT@B12H12 decreased the activation barrier more than 3.5 times being a more effective catalyst than the Fe2+ ion (the Fenton reaction), which decreases the barrier about twice. Mechanismly, the theory calculation indicated that both [B12H12]-& BULL; and [TPT-H]2+ have the capacity to decompose hydrogen into 1O2, OH & BULL;, and O2-& BULL;. With electron paramagnetic resonance and fluorescent probes, it is confirmed that TPT@B12H12 increases the levels of 1O2, OH & BULL;, and O2-& BULL;. More importantly, TPT@B12H12 effectively suppress the melanoma growth both in vitro and in vivo through 1O2, OH & BULL;, and O2-& BULL; generation. This study specifically highlights the great clinical translational potential of TPT@B12H12 as a CDT reagent. 2,4,6-Tri(4-pyridyl)-1,3,5-triazine (TPT)/ [closo-B12H12]2-(TPT@B12H12), a metal-free chemodynamic therapy (CDT) agent, decreases the activation barrier more than 3.5 times being a more effective catalyst than the Fe2+ ion (the Fenton reaction), which decreases the barrier about twice. More importantly, TPT@B12H12 effectively suppress the melanoma growth both in vitro and in vivo through 1O2, OH & BULL;, and O2-& BULL; generation. image
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| 9. |
- Xu, Xiaoran, et al.
(författare)
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Synthesis of iron-boride/carbon-nitride composites and their applications in chemodynamic therapy
- 2024
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Ingår i: Journal of Colloid and Interface Science. - : Elsevier. - 0021-9797 .- 1095-7103. ; 658, s. 276-285
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Tidskriftsartikel (refereegranskat)abstract
- Chemodynamic therapy (CDT) is an emerging treatment strategy that inhibits tumor growth by catalyzing the generation of reactive oxygen species (ROS), such as hydroxyl radicals (center dot OH), using specific nanomaterials. Herein, we have developed a new class of iron-based nanomaterials, i.e., iron-based borides (FeB), using the superchaotropic effect of a boron cluster (closo-[B12H1212-) and organic ligands, followed by high-temperature calcination. Experimental data and theoretical calculations revealed that FeB nanoparticles exhibit a Fentonlike effect, efficiently decomposing hydrogen peroxide into center dot OH and thus increasing the concentration of ROS. FeB nanomaterials demonstrate excellent catalytic performance, efficiently generate ROS, and exert significant antitumor effects in cell experiments and animal models. Therefore, FeB nanomaterials have
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| 10. |
- Yan, Jingjie, et al.
(författare)
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Sparse Kernel Reduced-Rank Regression for Bimodal Emotion Recognition From Facial Expression and Speech
- 2016
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Ingår i: IEEE transactions on multimedia. - 1520-9210 .- 1941-0077. ; 18:7, s. 1319-1329
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Tidskriftsartikel (refereegranskat)abstract
- A novel bimodal emotion recognition approach from facial expression and speech based on the sparse kernel reduced-rank regression (SKRRR) fusion method is proposed in this paper. In this method, we use the openSMILE feature extractor and the scale invariant feature transform feature descriptor to respectively extract effective features from speech modality and facial expression modality, and then propose the SKRRR fusion approach to fuse the emotion features of two modalities. The proposed SKRRR method is a nonlinear extension of the traditional reduced-rank regression (RRR), where both predictor and response feature vectors in RRR are kernelized by being mapped onto two high-dimensional feature space via two nonlinear mappings, respectively. To solve the SKRRR problem, we propose a sparse representation (SR)-based approach to find the optimal solution of the coefficient matrices of SKRRR, where the introduction of the SR technique aims to fully consider the different contributions of training data samples to the derivation of optimal solution of SKRRR. Finally, we utilize the eNTERFACE '05 and AFEW4.0 bimodal emotion database to conduct the experiments of monomodal emotion recognition and bimodal emotion recognition, and the results indicate that our presented approach acquires the highest or comparable bimodal emotion recognition rate among some state-of-the-art approaches.
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