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Xuechun Wang,1,* Jia Jia,2,* Xuehong Gu,3 Wei-wei Zhao,4 Caiping Chen,5 Wanxin Wu,6 Jiayuan Wang,1 Midie Xu7 1Department of Laboratory, Jiaxing First Hospital, Jiaxing, 314000, People’s Republic of China; 2Shanghai Center for Bioinformation Technology, Shanghai, 201202, People’s Republic of China; 3Department of Nursing, Jiaxing First Hospital, Jiaxing, 314000, People’s Republic of China; 4Department of Rehabilitation Medicine, Jiaxing First Hospital, Jiaxing, 314000, People’s Republic of China; 5Department of Breast Surgery, Jiaxing First Hospital, Jiaxing, 314000, People’s Republic of China; 6Department of Pathology, Jiaxing First Hospital, Jiaxing, 314000, People’s Republic of China; 7Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, 200032, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xuehong GuDepartment of Nursing, Jiaxing First Hospital, No. 1882 of Central South Road, Jiaxing, 314000, People’s Republic of ChinaTel +86 13957368443Fax +86 573-83599079Email guxuehong145@163.comObjective: Breast cancer has become a fatal disease for women world-wide. Its incidence in China has been increasing yearly, and the identification of early-stage biomarkers is urgently required.Methods: ANOVA was carried out in the case of a primary tumor, adjacent normal tissue, and tumor metastasis of breast cancer, and on pan-cancer samples using the genome-wide methylation data of 31 solid tumor Illumina Methylation 450K chips downloaded from The Cancer Genome Atlas (TCGA) website in September 2018. Methylation sites showing a significant difference (P ≤ 0.05) were screened and compared with the whole-genome methylation data of 31 other solid tumor species in the TCGA database using t-tests in order to screen the methylation sites of breast cancer-specific expression. The expression of the screened methylation sites was confirmed through pyrosequencing in 45 cases of breast cancer, lung cancer, gastric cancer, and colorectal cancer.Results: A total of 10 specific breast cancer methylation sites (cg13683194, cg07996594, cg21646032, cg07671949, cg21185686, cg03625109, cg16429070, cg23601468, cg24818566, and cg01240931) were analyzed; nine genes (C9orf125, RARB, ESR1, RUNX3, PCDHGB7, DBC1, PDGFRB, TIMP3, and APC) were involved. The overall effect was excellent; a total of 4 methylation sites (2 in the DBC1 gene [cg03625109 and cg24818566], 1 in the C9orf125 gene [cg13683194], and 1 in the PDGFRB gene [cg16429070]) could effectively distinguish breast cancer from 31 other cancer species. The pyrosequencing results revealed that 7 screened methylation sites could significantly distinguish between breast cancer, lung cancer, gastric cancer, and colorectal cancer samples; these sites could also specifically distinguish between luminal A, luminal B, HER2, and Basal-like types of breast cancer.Conclusion: The 10 breast cancer methylation sites screened in the present study can effectively distinguish breast cancer from 31 other solid tumors, and they are expected to be used as biomarkers for early screening of breast cancer.Keywords: breast cancer, Basal-like breast cancer, methylation, biomarker, TCGA, ANOVA

Additional file 1: Table S1. Protective efficacy of EIAVDLV121 and EIAVFDDV13.

Additional file 2: Figure S1. Replication efficacies of EIAV strains. The growth rates of five EIAV strains (EIAVDLV34, EIAVDLV62, EIAVDLV92, EIAVDLV121 and EIAVFDDV13) in cultivated dMDM for 2, 4, 6, 8 and 10 days were compared by measuring reverse transcriptase (RT) activity. Data were collected from three independent experiments. Figure S2. Stable mutations in Gag (A), Pol (B), gp45 (C), Tat, S2 and Rev (D) generated during different vaccine development stages. The amino acid sequences were deduced from the gene sequences originating from either the proviral genomes or from the directly cloned PCR products after removing sequences containing premature stop codons. The sequences of each gene were aligned to the reference sequence EIAVLN40. The shadowed residues and white background residues are identical to or different from the reference sequence, respectively. Stable mutation sites detected primarily in virus strains adapted to cultivated cells are boxed, whereas those limited in the attenuated strains are marked with red circles. The numbers on the top of the graphs show the positions of stable mutation sites, and those at the left side indicate the sequences applied for the analysis. The downward arrows indicate the direction of the vaccine development process.

The Jiyuan Depression is a frontier area for oil and gas exploration in Henan Province, China. In recent years, oil was discovered in the Deng-2 well in the lower Tertiary, though the tectonics and petroleum geology of the Depression are very complex. A series of experiments on fluid inclusions in the oil-bearing sandstones from the Deng-2 well were made that included measurement of the homogenization temperatures of gas–liquid inclusions and GC–MS analysis of biomarkers either in the sandstone pores or in the fluid inclusions. The Deng-2 oil-reservoir was formed at about 78 °C, corresponding to a burial depth of about 2200 m. The present burial depth is about 700 m because of erosion and fault-block uplift in Oligocene time. Although oil in the sandstone pores is now heavily biodegraded, the biomarkers in the inclusions show slight biodegradation representing a watering and biodegradation process that did not occur before formation of the Deng-2 oil-pool. Having investigated the structural evolution of the Deng-2 trap, it is concluded that the oil discovered in the Tertiary reservoir of Deng-2 well migrated from Mesozoic reservoirs through active faults around the Deng-2 trap. As the oil migrated from the Mesozoic to the Tertiary reservoir, the Deng-2 trap was uplifted close to the depth of active biodegradation (subsurface temperature lower than 80 °C and to a burial depth shallower than 2250 m from the thermal gradient of 3.1 °C/100 m) so that the oil in the inclusions shows a slight biodegradation. Because of the continuous uplift of the Deng-2 trap during the Tertiary and Quaternary, the reservoired oil has been more heavily biodegraded compared to that in the inclusions.

Through-wall-radar imaging (TWRI) has an ability to see the target behind the wall, which is desirable for antiterrorism, rescue and law enforcement. In order to obtain high resolution images, ultra wide band signal and large synthetic aperture should be used, which inevitably increases measuring time. The emerging compressive sensing (CS) technique can recover a sparse signal from incomplete measurements. Due to sparse scene approximation, TWRI is converted into an optimization problem based on CS framework in this paper, which can dramatically reduce measuring time. Furthermore, simulation results are given to demonstrate the potentiality of CS technique for TWRI. (4 pages)