Momentum-Resolved Visualization of Electronic Evolution in Doping a Mott Insulator

High temperature superconductivity in cuprates arises from doping a parent Mott insulator by electrons or holes. A central issue is how the Mott gap evolves and the low-energy states emerge with doping. Here we report angle-resolved photoemission spectroscopy measurements on a cuprate parent compound by sequential in situ electron doping. The chemical potential jumps to the bottom of the upper Hubbard band upon a slight electron doping, making it possible to directly visualize the charge transfer band and the full Mott gap region. With increasing doping, the Mott gap rapidly collapses due to the spectral weight transfer from the charge transfer band to the gapped region and the induced low-energy states emerge in a wide energy range inside the Mott gap. These results provide key information on the electronic evolution in doping a Mott insulator and establish a basis for developing microscopic theories for cuprate superconductivity.Comment: 23 pages, 5 figure

Interprovincial migration, regional development and state policy in China, 1985-2010

Internal migration in China occurs as a result of both market forces and government interventions. This paper investigates how indicators of migration have changed over the past quarter of a century using data from successive censuses, with particular attention given to the roles of regional economic development and national policy and the effects of age and education on spatial patterns of migration. The results show a surge in migration throughout the period, an increasing concentration of migration destinations and an improvement of migration efficiency prior to 2000, but a decreased focusing of migration during the first decade of the twenty-first century. Widening regional disparity has been responsible for a sharp increase of migration from the interior to the coast, and different national economic growth poles emerged as major migration destinations at different stages of economic reforms. The analyses of age- and education-specific migration flows indicate that young adults were more mobile and more sensitive than older cohorts to interregional economic differentials, and that educated migrants were more concentrated than less-educated migrants since knowledge-based industries were more concentrated than labour-intensive industries. Our findings suggest that massive eastward migration induced by unbalanced economic development and relaxed migration restrictions still persisted in the 2000s, and that the State's recent efforts to alleviate regional inequalities were far from achieving equilibrium in the migration system

Theoretical analysis of a high performance protein imprint on a nanosensor

The structural details and flexibilities of protein impose significant challenges to develop protein imprint, especially for the selection of functional monomer. Using NAMD, AutoDock 4 and AutoDock Vina, we investigated the formation of a high performance protein imprint on a nanosensor that detected human papillomavirus (HPV) biomarker protein E7 with high sensitivity. According to molecular dynamics, the phenolic oligomers were shown to assemble with the E7 protein and form a complex at specific targeting areas on the protein. Docking analysis efficiently screened chemical compounds by evaluating the binding affinity. A new parameter, i.e., average binding energy (ΔG/contact), was used together with binding energy (ΔG) to screen compounds. The screening went through 189 compounds and identified a subpopulation of 22 compounds showing unique characteristics of binding, and could potentially be used to develop the specific and robust imprint. Accordingly, the study implicated a novel approach to screen functional compounds for rational design of the protein imprint. Keywords: Molecular imprint, Rational design, Nanosensor, Electropolymerization, Biorecognition, Carbon nanotube, Docking, Molecular dynamic

FvMYB79 Positively Regulates Strawberry Fruit Softening via Transcriptional Activation of FvPME38

Strawberry is a soft fruit with short postharvest life, due to a rapid loss of firmness. Pectin methylesterase (PME)-mediated cell wall remodeling is important to determine fruit firmness and softening. Previously, we have verified the essential role of FvPME38 in regulation of PME-mediated strawberry fruit softening. However, the regulatory network involved in PME-mediated fruit softening is still largely unknown. Here, we identified an R2R3-type MYB transcription factor FvMYB79, which activates the expression level of FvPME38, thereby accelerating fruit softening. During fruit development, FvMYB79 co-expressed with FvPME38, and this co-expression pattern was opposite to the change of fruit firmness in the fruit of ‘Ruegen’ which significantly decreased during fruit developmental stages and suddenly became very low after the color turning stage. Via transient transformation, FvMYB79 could significantly increase the transcriptional level of FvPME38, leading to a decrease of firmness and acceleration of fruit ripening. In addition, silencing of FvMYB79 showed an insensitivity to ABA-induced fruit ripening, suggesting a possible involvement of FvMYB79 in the ABA-dependent fruit softening process. Our findings suggest FvMYB79 acts as a novel regulator during strawberry ripening via transcriptional activation of FvPME38, which provides a novel mechanism for improvement of strawberry fruit firmness

Research on the morphological structure of partial fracture healing process in diabetic mice based on synchrotron radiation phase-contrast imaging computed tomography and deep learning

The prevalence of diabetes mellitus has exhibited a notable surge in recent years, thereby augmenting the susceptibility to fractures and impeding the process of fracture healing. The primary objective of this investigation is to employ synchrotron radiation phase-contrast imaging computed tomography (SR-PCI-CT) to examine the morphological and structural attributes of different types of callus in a murine model of diabetic partial fractures. Additionally, a deep learning image segmentation model was utilized to facilitate both qualitative and quantitative analysis of callus during various time intervals. A total of forty male Kunming mice, aged five weeks, were randomly allocated into two groups, each consisting of twenty mice, namely, simple fracture group (SF) and diabetic fracture group (DF). Mice in DF group were intraperitoneally injected 60 mg/kg 1 % streptozotocin(STZ) solution for 5 consecutive days, and the standard for modeling was that the fasting blood glucose level was ≥11.1 mmol /l one week after the last injection of STZ. The right tibias of all mice were observed to have oblique fractures that did not traverse the entire bone. At three, seven, ten and fourteen days after the fracture occurred, the fractured tibias were extracted for SR-PCI-CT imaging and histological analysis. Furthermore, a deep learning image segmentation model was devised to automatically detect, categorize and quantitatively examine different types of callus. Image J software was utilized to measure the grayscale values of different types of callus and perform quantitative analysis. The findings demonstrated that: 1) SR-PCI-CT imaging effectively depicted the morphological attributes of different types of callus of fracture healing. The grayscale values of different types of callus were significantly different(P < 0.01). 2) In comparison to the SF group, the DF group exhibited a significant reduction in the total amount of callus during the same period (P < 0.01). Additionally, the peak of cartilage callus in the hypertrophic phase was delayed. 3) Histology provides the basis for training algorithms for deep learning image segmentation models. The deep-learning image segmentation models achieved accuracies of 0.69, 0.81 and 0.733 for reserve/proliferative cartilage, hypertrophic cartilage and mineralized cartilage, respectively, in the test set. The corresponding Dice values were 0.72, 0.83 and 0.76, respectively.In summary, SR-PCI-CT images are close to the histological level, and a variety of cartilage can be identified on synchrotron radiation CT images compared with histological examination, while artificial intelligence image segmentation model can realize automatic analysis and data generation through deep learning, and further determine the objectivity and accuracy of SR-PCI-CT in identifying various cartilage tissues. Therefore, this imaging technique combined with deep learning image segmentation model can effectively evaluate the effect of diabetes on the morphological and structural changes of callus during fracture healing in mice

Effects of structure and air damping on quality factor under various pressure environments based on experimental research

Conference Name:15th Annual Conference and 4th International Conference of the Chinese Society of Micro-Nano Technology, CSMNT 2013. Conference Address: Tianjin, China. Time:November 3, 2013 - November 6, 2013.This paper presents an analysis about the variation of quality factor (Q-factor) aiming at the complex micro resonator to explore the mechanism of the energy loss under different pressures. To demonstrate the work, a series of resonators are designed, which mainly differs in the squeeze-damping and scale of the beam. According to corresponding structure, the Q-factor is measured at different pressures while the theoretical air damping model combined with Christian's model is also proposed. The air damping models of three types are proved to have 10%~30% relative error compared to experimental results in low vacuum, respectively. And, for the high vacuum, the structural energy loss plays an important role on the Q-factor, which increases with the decrement of comb quantity and the beam width. ? (2014) Trans Tech Publications

Synthetic Tet-inducible artificial microRNAs targeting β-catenin or HIF-1α inhibit malignant phenotypes of bladder cancer cells T24 and 5637

Abstract Ribonucleic acid interference (RNAi) based on microRNA (miRNA) may provide efficient and safe therapeutic opportunities. However, natural microRNAs can not easily be regulated and usually cause few phenotypic changes. Using the engineering principles of synthetic biology, we provided a novel and standard platform for the generation of tetracycline (Tet)-inducible vectors that express artificial microRNAs in a dosage-dependent manner. The vector generates a Pol II promoter-mediated artificial microRNA which was flanked by ribozyme sequences. In order to prove the utility of this platform, we chose β-catenin and HIF-1α as the functional targets and used the bladder cancer cell lines 5637 and T24 as the test models. We found that the Tet-inducible artificial microRNAs can effectively silence the target genes and their downstream genes and induce anti-cancer effects in the two bladder cancer cell lines. These devices can inhibit proliferation, induce apoptosis and suppress migration of the bladder cancer cell lines 5637 and T24. The Tet-inducible synthetic artificial microRNAs may represent a kind of novel therapeutic strategies for treating human bladder cancer

Theophylline controllable RNAi-based genetic switches regulate expression of lncRNA TINCR and malignant phenotypes in bladder cancer cells

Abstract TINCR is a well-known lncRNA which acts as a master regulator in somatic differentiation development. However, it is still unclear whether TINCR is also involved in caner occurrence and progression. In this study, we observed that TINCR was up-regulated in bladder cancer tissues and cells and contributed to oncogenesis and cancer progression. Silencing TINCR expression inhibited cell proliferation and promoted apoptosis in vitro, indicating that TINCR may be the potential therapeutic target for treating bladder urothelial carcinoma. Thus we used the synthetic biology approach to create theophylline controllable RNAi-based genetic switches which silenced TINCR in a dosage-dependent manner. Both RNAi-OFF and ON switches can be used to quantitatively control the expression of TINCR in bladder cancer to suppress the progression of bladder cancer. These findings suggest that lncRNA-TINCR could promote bladder cancer development and progression and artificial control of its expression through inducible RNAi may represent a new kind of therapeutic strategy for treating human bladder cancer