Theory of doped Mott insulators: duality between pairing and magnetism

By bosonizing the electronic t-J model exactly on any two-dimensional (2D) lattices, and integrating out the gauge fluctuations combined to slave particles beyond mean fields, we get a theory in terms of physical Cooper pair and spin condensates. In the sense of mutual Berry phase they turns out to be dual to each other. The mutual-duality is the missing key in the resonant-valance-bond idea\cite{rvb} to work as a paradigm of doped 2D Mott insulators. We argue that essential aspects of high-$T_c$ phenomenology find natural solutions in the theory. We also provide interesting predictions for systems on hexagonal lattices.Comment: 4 pages, no figures, Submitted to Phys. Rev. Let

Screen key genes associated with distraction-induced osteogenesis of stem cells using bioinformatics methods

Background: Applying mesenchymal stem cells (MSCs), together with the distraction osteogenesis (DO) process, displayed enhanced bone quality and shorter treatment periods. The DO guides the differentiation of MSCs by providing mechanical clues. However, the underlying key genes and pathways are largely unknown. The aim of this study was to screen and identify hub genes involved in distraction-induced osteogenesis of MSCs and potential molecular mechanisms. Material and Methods: The datasets were downloaded from the ArrayExpress database. Three samples of negative control and two samples subjected to 5% cyclic sinusoidal distraction at 0.25 Hz for 6 h were selected for screening differentially expressed genes (DEGs) and then analysed via bioinformatics methods. The Gene Ontology (GO) terms and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment were investigated. The protein–protein interaction (PPI) network was visualised through the Cytoscape software. Gene set enrichment analysis (GSEA) was conducted to verify the enrichment of a self-defined osteogenic gene sets collection and identify osteogenic hub genes. Results: Three hub genes (IL6, MMP2, and EP300) that were highly associated with distraction-induced osteogenesis of MSCs were identified via the Venn diagram. These hub genes could provide a new understanding of distraction-induced osteogenic differentiation of MSCs and serve as potential gene targets for optimising DO via targeted therapies

Physiological, behavioral and subjective sadness reactivity in frontotemporal dementia subtypes.

Frontotemporal dementia (FTD), a neurodegenerative disease broadly characterized by socioemotional impairments, includes three clinical subtypes: behavioral variant FTD (bvFTD), semantic variant primary progressive aphasia (svPPA) and non-fluent variant primary progressive aphasia (nfvPPA). Emerging evidence has shown emotional reactivity impairments in bvFTD and svPPA, whereas emotional reactivity in nfvPPA is far less studied. In 105 patients with FTD (49 bvFTD, 31 svPPA and 25 nfvPPA) and 27 healthy controls, we examined three aspects of emotional reactivity (physiology, facial behavior and subjective experience) in response to a sad film. In a subset of the sample, we also examined the neural correlates of diminished aspects of reactivity using voxel-based morphometry. Results indicated that all three subtypes of FTD showed diminished physiological responding in respiration rate and diastolic blood pressure; patients with bvFTD and svPPA also showed diminished subjective experience, and no subtypes showed diminished facial behavior. Moreover, there were differences among the clinical subtypes in brain regions where smaller volumes were associated with diminished sadness reactivity. These results show that emotion impairments extend to sadness reactivity in FTD and underscore the importance of considering different aspects of sadness reactivity in multiple clinical subtypes for characterizing emotional deficits and associated neurodegeneration in FTD

Long-term dynamic compression enhancement TGF-β3-induced chondrogenesis in bovine stem cells: a gene expression analysis

Abstract: Background: Bioengineering has demonstrated the potential of utilising mesenchymal stem cells (MSCs), growth factors, and mechanical stimuli to treat cartilage defects. However, the underlying genes and pathways are largely unclear. This is the first study on screening and identifying the hub genes involved in mechanically enhanced chondrogenesis and their potential molecular mechanisms. Methods: The datasets were downloaded from the Gene Expression Omnibus (GEO) database and contain six transforming growth factor-beta-3 (TGF-β3) induced bovine bone marrow-derived MSCs specimens and six TGF-β3/dynamic-compression-induced specimens at day 42. Screening differentially expressed genes (DEGs) was performed and then analysed via bioinformatics methods. The Database for Annotation, Visualisation, and Integrated Discovery (DAVID) online analysis was utilised to obtain the Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment. The protein-protein interaction (PPI) network of the DEGs was constructed based on data from the STRING database and visualised through the Cytoscape software. The functional modules were extracted from the PPI network for further analysis. Results: The top 10 hub genes ranked by their connection degrees were IL6, UBE2C, TOP2A, MCM4, PLK2, SMC2, BMP2, LMO7, TRIM36, and MAPK8. Multiple signalling pathways (including the PI3K-Akt signalling pathway, the toll-like receptor signalling pathway, the TNF signalling pathway, and the MAPK pathway) may impact the sensation, transduction, and reaction of external mechanical stimuli. Conclusions: This study provides a theoretical finding showing that gene UBE2C, IL6, and MAPK8, and multiple signalling pathways may play pivotal roles in dynamic compression-enhanced chondrogenesis

N-Jettiness Subtractions for gg→Hgg\to H at Subleading Power

$N$-jettiness subtractions provide a general approach for performing fully-differential next-to-next-to-leading order (NNLO) calculations. Since they are based on the physical resolution variable $N$-jettiness, $\mathcal{T}_N$, subleading power corrections in $\tau=\mathcal{T}_N/Q$, with $Q$ a hard interaction scale, can also be systematically computed. We study the structure of power corrections for $0$-jettiness, $\mathcal{T}_0$, for the $gg\to H$ process. Using the soft-collinear effective theory we analytically compute the leading power corrections $\alpha_s \tau \ln\tau$ and $\alpha_s^2 \tau \ln^3\tau$ (finding partial agreement with a previous result in the literature), and perform a detailed numerical study of the power corrections in the $gg$, $gq$, and $q\bar q$ channels. This includes a numerical extraction of the $\alpha_s\tau$ and $\alpha_s^2 \tau \ln^2\tau$ corrections, and a study of the dependence on the $\mathcal{T}_0$ definition. Including such power suppressed logarithms significantly reduces the size of missing power corrections, and hence improves the numerical efficiency of the subtraction method. Having a more detailed understanding of the power corrections for both $q\bar q$ and $gg$ initiated processes also provides insight into their universality, and hence their behavior in more complicated processes where they have not yet been analytically calculated.Comment: 16 pages, 12 figure

Measuring Significance of Community Structure in Complex Networks

Many complex systems can be represented as networks and separating a network into communities could simplify the functional analysis considerably. Recently, many approaches have been proposed for finding communities, but none of them can evaluate the communities found are significant or trivial definitely. In this paper, we propose an index to evaluate the significance of communities in networks. The index is based on comparing the similarity between the original community structure in network and the community structure of the network after perturbed, and is defined by integrating all the similarities. Many artificial networks and real-world networks are tested. The results show that the index is independent from the size of network and the number of communities. Moreover, we find the clear communities always exist in social networks, but don't find significative communities in proteins interaction networks and metabolic networks.Comment: 6 pages, 4 figures, 1 tabl