The golden camellia, Camellia nitidissima Chi., is a well-known ornamental plant that is known as “the queen of camellias” because of its golden yellow flowers. The principal pigments in the flowers are carotenoids and flavonol glycosides. Understanding the biosynthesis of the golden color and its regulation is important in camellia breeding. To obtain a comprehensive understanding of flower development in C. nitidissima, a number of cDNA libraries were independently constructed during flower development. Using the Illumina Hiseq2500 platform, approximately 71.8 million raw reads (about 10.8 gigabase pairs) were obtained and assembled into 583,194 transcripts and 466, 594 unigenes. A differentially expressed genes (DEGs) and co-expression network was constructed to identify unigenes correlated with flower color. The analysis of DEGs and co-expressed network involved in the carotenoid pathway indicated that the biosynthesis of carotenoids is regulated mainly at the transcript level and that phytoene synthase (PSY), β -carotene 3-hydroxylase (CrtZ), and capsanthin synthase (CCS1) exert synergistic effects in carotenoid biosynthesis. The analysis of DEGs and co-expressed network involved in the flavonoid pathway indicated that chalcone synthase (CHS), naringenin 3-dioxygenase (F3H), leucoanthocyanidin dioxygenase(ANS), and flavonol synthase (FLS) play critical roles in regulating the formation of flavonols and anthocyanidin. Based on the gene expression analysis of the carotenoid and flavonoid pathways, and determinations of the pigments, we speculate that the high expression of PSY and CrtZ ensures the production of adequate levels of carotenoids, while the expression of CHS, FLS ensures the production of flavonols. The golden yellow color is then the result of the accumulation of carotenoids and flavonol glucosides in the petals. This study of the mechanism of color formation in golden camellia points the way to breeding strategies that exploit gene technology approaches to increase the content of carotenoids and flavonol glucosides and to decrease anthocyanidin synthesis.

Epigenetic alterations, including 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) and nucleosome positioning (NP), in cell-free DNA (cfDNA) have been widely observed in human diseases, and many available cfDNA-based epigenome-wide profiles exhibit high sensitivity and specificity in disease detection and classification. However, due to the lack of efficient collection, standardized quality control, and analysis procedures, efficiently integrating and reusing these data remain considerable challenges. Here, we introduce CFEA (http://www.bio-data.cn/CFEA), a cell-free epigenome database dedicated to three types of widely adopted epigenetic modifications (5mC, 5hmC and NP) involved in 27 human diseases. We developed bioinformatic pipelines for quality control and standard data processing and an easy-to-use web interface to facilitate the query, visualization and download of these cell-free epigenome data. We also manually curated related biological and clinical information for each profile, allowing users to better browse and compare cfDNA epigenomes at a specific stage (such as early- or metastasis-stage) of cancer development. CFEA provides a comprehensive and timely resource to the scientific community and supports the development of liquid biopsy-based biomarkers for various human diseases.

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Recent findings have demonstrated the superiority and utility of microRNAs (miRNAs) as new biomarkers for cancer diagnosis, therapy, and prognosis. In this study, to explore the prognostic value of immune-related miRNAs in gastric cancer (GC), we analyzed the miRNA-expression profiles of 389 patients with GC, using data deposited in The Cancer Genome Atlas database. Using a forward- and backward-variable selection and multivariate Cox regression analyses model, we identified a nine-miRNA signature (the “ImmiRSig,” consisting of miR-125b-5p, miR-99a-3p, miR-145-3p, miR-328-3p, miR-133a-5p, miR-1292-5p, miR-675-3p, miR-92b-5p, and miR-942-3p) in the training cohort that enabled the division of patients into high- and low-risk groups with significantly different survival rates. The ImmiRSig was successfully validated with an independent test cohort of 193 GC patients. Univariate and multivariate Cox regression analyses indicated that the ImmiRSig would serve as an independent prognostic factor after adjusting for other clinical covariates. Pending further prospective validation, the identified ImmiRSig appears to have significant clinical importance in terms of improving outcome predictions and guiding personalized treatment for patients with GC. Finally, significant associations between the ImmiRSig and the half-maximal inhibitory concentrations of chemotherapeutic agents were observed, suggesting that ImmiRSig may predict the clinical efficacy of chemotherapy.

Poly(vinyl chloride) (PVC)/halloysite nanotubes (HNTs) nanocomposites were synthesized by in situ suspension polymerization of vinyl chloride (VC) in the presence of HNTs. The microstructure, mean particle size, and cold plasticizer absorption (CPA) of these resins and the rheological property, mechanical properties and thermal properties of PVC/HNTs nanocomposites were investigated. The results show that the mean particle size, the degree of porosity, and the CPA of PVC resins decrease with the addition of HNTs. The plasticization time and the equilibrium torque of PVC/HNTs nanocomposites are found to be longer and higher than that for the neat PVC. HNTs are uniformly distributed in the PVC matrix and effective in toughening and stiffening PVC nanocomposites when the addition of HNTs is 4.0 wt% or less. The glass transition temperatures of the PVC/HNTs nanocomposites were nearly identical to that of pure PVC. POLYM. COMPOS.,

The energy reading has been an efficient and attractive measure for collaborative acoustic source localization in practical application due to its cost saving in both energy and computation capability. The maximum likelihood problems by fusing received acoustic energy readings transmitted from local sensors are derived. Aiming to efficiently solve the nonconvex objective of the optimization problem, we present an approximate estimator of the original problem. Then, a direct norm relaxation and semidefinite relaxation, respectively, are utilized to derive the second-order cone programming, semidefinite programming or mixture of them for both cases of sensor self-location and source localization. Furthermore, by taking the colored energy reading noise into account, several minimax optimization problems are formulated, which are also relaxed via the direct norm relaxation and semidefinite relaxation respectively into convex optimization problems. Performance comparison with the existing acoustic energy-based source localization methods is given, where the results show the validity of our proposed methods.

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