Zero mode in a strongly coupled quark gluon plasma

In connection with massless two-flavour QCD, we analyse the chiral symmetry restoring phase transition using three distinct gluon-quark vertices and two different assumptions about the long-range part of the quark-quark interaction. In each case, we solve the gap equation, locate the transition temperature T_c, and use the maximum entropy method to extract the dressed-quark spectral function at T>T_c. Our best estimate for the chiral transition temperature is T_c=(147 +/- 8)MeV; and the deconfinement transition is coincident. For temperatures markedly above T_c, we find a spectral density that is consistent with those produced using a hard thermal loop expansion, exhibiting both a normal and plasmino mode. On a domain T\in[T_c,T_s], with T_s approximately 1.5T_c, however, with each of the six kernels we considered, the spectral function contains a significant additional feature. Namely, it displays a third peak, associated with a zero mode, which is essentially nonperturbative in origin and dominates the spectral function at T=T_c. We suggest that the existence of this mode is a signal for the formation of a strongly-coupled quark-gluon plasma and that this strongly-interacting state of matter is likely a distinctive feature of the QCD phase transition.Comment: 11 pages, 5 figures, 1 tabl

Survey on the Overwintering of Syrphids in Changbai Mountains and Experiments on Artificial Protection of the Overwintering Syrphid Flies

Originating text in Chinese.Citation: Gao, Junfeng, Zhang, Guangxin, Qin, Yongchun, Yu, Kai, Li, Minghai, Qin, Yi. (1993). Survey on the Overwintering of Syrphids in Changbai Mountains and Experiments on Artificial Protection of the Overwintering Syrphid Flies. Chinese Journal of Biological Control, 9(3), 142-144

Phase diagram and thermal properties of strong-interaction matter

We introduce a novel procedure for computing the (mu,T)-dependent pressure in continuum QCD; and therefrom obtain a complex phase diagram and predictions for thermal properties of the system, providing the in-medium behaviour of the trace anomaly, speed of sound, latent heat and heat capacity.Comment: 6 pages, 4 figures. Minor amendments in the version accepted for publicatio

Identification of a Potentially Functional microRNA-mRNA Regulatory Network in Lung Adenocarcinoma Using a Bioinformatics Analysis

Background Lung adenocarcinoma (LUAD) is a common lung cancer with a high mortality, for which microRNAs (miRNAs) play a vital role in its regulation. Multiple messenger RNAs (mRNAs) may be regulated by miRNAs, involved in LUAD tumorigenesis and progression. However, the miRNA-mRNA regulatory network involved in LUAD has not been fully elucidated. Methods Differentially expressed miRNAs and mRNA were derived from the Cancer Genome Atlas (TCGA) dataset in tissue samples and from our microarray data in plasma (GSE151963). Then, common differentially expressed (Co-DE) miRNAs were obtained through intersected analyses between the above two datasets. An overlap was applied to confirm the Co-DEmRNAs identified both in targeted mRNAs and DEmRNAs in TCGA. A miRNA-mRNA regulatory network was constructed using Cytoscape. The top five miRNA were identified as hub miRNA by degrees in the network. The functions and signaling pathways associated with the hub miRNA-targeted genes were revealed through Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. The key mRNAs in the protein-protein interaction (PPI) network were identified using the STRING database and CytoHubba. Survival analyses were performed using Gene Expression Profiling Interactive Analysis (GEPIA). Results The miRNA-mRNA regulatory network consists of 19 Co-DEmiRNAs and 760 Co-DEmRNAs. The five miRNAs (miR-539-5p, miR-656-3p, miR-2110, let-7b-5p, and miR-92b-3p) in the network were identified as hub miRNAs by degrees (>100). The 677 Co-DEmRNAs were targeted mRNAs from the five hub miRNAs, showing the roles in the functional analyses of the GO analysis and KEGG pathways (inclusion criteria: 836 and 48, respectively). The PPI network and Cytoscape analyses revealed that the top ten key mRNAs were NOTCH1, MMP2, IGF1, KDR, SPP1, FLT1, HGF, TEK, ANGPT1, and PDGFB. SPP1 and HGF emerged as hub genes through survival analysis. A high SPP1 expression indicated a poor survival, whereas HGF positively associated with survival outcomes in LUAD. Conclusion This study investigated a miRNA-mRNA regulatory network associated with LUAD, exploring the hub miRNAs and potential functions of mRNA in the network. These findings contribute to identify new prognostic markers and therapeutic targets for LUAD patients in clinical settings.Peer reviewe