A semi-parametric statistical model for integrating gene expression profiles across different platforms

Determining differentially expressed genes (DEGs) between biological samples is the key to understand how genotype gives rise to phenotype. RNA-seq and microarray are two main technologies for profiling gene expression levels. However, considerable discrepancy has been found between DEGs detected using the two technologies. Integration data across these two platforms has the potential to improve the power and reliability of DEG detection. We propose a rank-based semi-parametric model to determine DEGs using information across different sources and apply it to the integration of RNA-seq and microarray data. By incorporating both the significance of differential expression and the consistency across platforms, our method effectively detects DEGs with moderate but consistent signals. We demonstrate the effectiveness of our method using simulation studies, MAQC/SEQC data and a synthetic microRNA dataset. Our integration method is not only robust to noise and heterogeneity in the data, but also adaptive to the structure of data. In our simulations and real data studies, our approach shows a higher discriminate power and identifies more biologically relevant DEGs than eBayes, DEseq and some commonly used meta-analysis methods.     

Skp2 is over-expressed in breast cancer and promotes breast cancer cell proliferation

The F box protein Skp2 is oncogenic. Skp2 and Skp2B, an isoform of Skp2 are overexpressed in breast cancer. However, little is known regarding the mechanism by which Skp2B promotes the occurrence and development of breast cancer. Here, we determined the expression and clinical outcomes of Skp2 in breast cancer samples and cell lines using breast cancer database, and investigated the role of Skp2 and Skp2B in breast cancer cell growth, apoptosis and cell cycle arrest. We obtained Skp2 is significantly overexpressed in breast cancer samples and cell lines, and high Skp2 expression positively correlated with poor prognosis of breast cancer. Both Skp2 and Skp2B could promote breast cancer cell proliferation, inhibit cell apoptosis, change the cell cycle distribution and induce the increased S phase cells and therefore induce cell proliferation in breast cancer cells. Moreover, the 2 isoforms could both suppress PIG3 expression via independent pathways in the breast cancer cells. Skp2 suppressed p53 and inhibited PIG3-induced apoptosis, while Skp2B attenuated the function of PIG3 by inhibiting PHB. Our results indicate that Skp2 and Skp2B induce breast cancer cell development and progression, making Skp2 and Skp2B potential molecular targets for breast cancer therapy.     

Long non‐coding RNA SNHG6 promotes cell proliferation and migration through sponging miR‐4465 in ovarian clear cell carcinoma

Dysregulation of small nucleolar RNA host gene 6 (SNHG6) exerts critical oncogenic effects and facilitates tumourigenesis in human cancers. However, little information about the expression pattern of SNHG6 in ovarian clear cell carcinoma (OCCC) is available, and the contributions of this long non‐coding RNA to the tumourigenesis and progression of OCCC are unclear. In the present study, we showed via quantitative real‐time PCR that SNHG6 expression was abnormally up‐regulated in OCCC tissues relative to that in unpaired normal ovarian tissues. High SNHG6 expression was correlated with vascular invasion, distant metastasis and poor survival. Further functional experiments demonstrated that knockdown of SNHG6 in OCCC cells inhibited cell proliferation, migration and invasion in vitro as well as tumour growth in vivo. Moreover, SNHG6 functioned as a competing endogenous RNA (ceRNA), effectively acting as a sponge for miR‐4465 and thereby modulating the expression of enhancer of zeste homolog 2 (EZH2). Taken together, our data suggest that SNHG6 is a novel molecule involved in OCCC progression and that targeting the ceRNA network involving SNHG6 may be a treatment strategy in OCCC.     

Synergistic Engineering of Defects and Architecture in Binary Metal Chalcogenide toward Fast and Reliable Lithium–Sulfur Batteries

Lithium–sulfur (Li–S) batteries have great promise to support the next‐generation energy storage if their sluggish redox kinetics and polysulfide shuttling can be addressed. The rational design of sulfur electrodes plays key roles in tacking these problems and achieving high‐efficiency sulfur electrochemistry. Herein, a synergetic defect and architecture engineering strategy to design highly disordered spinel Ni–Co oxide double‐shelled microspheres (NCO‐HS), which consist of defective spinel NiCo₂O_4–x (x = 0.9 if all nickel is Ni²⁺ and cobalt is Co^2.13+), as the multifunctional sulfur host material is reported. The in situ constructed cation and anion defects endow the NCO‐HS with significantly enhanced electronic conductivity and superior polysulfide adsorbability. Meanwhile, the delicate nanoconstruction offers abundant active interfaces and reduced ion diffusion pathways for efficient Li–S chemistry. Attributed to these synergistic features, the sulfur composite electrode achieves excellent rate performance up to 5 C, remarkable cycling stability over 800 cycles and good areal capacity of 6.3 mAh cm^?2 under high sulfur loading. This proposed strategy based on synergy engineering could also inform material engineering in related energy storage and conversion fields.     

Decreases in Both the Seroprevalence of Serum Antibodies and Seroprotection against Japanese Encephalitis Virus among Vaccinated Children

The incidence of Japanese encephalitis(JE) has significantly decreased in China due to JE vaccines. In this study, we investigated the post-JE vaccination seroprevalence and protection provided by vaccinated sera against Japanese encephalitis virus(JEV) to elucidate the persistence and waning of antibodies to JEV among JE-SA14-14-2-vaccinated children. A total of 300 serum samples were collected from vaccinated children aged 3–10 years in Zhaotong, Yunnan,China. The seroprevalence of anti-JEV antibodies was determined by enzyme-linked immune sorbent assay and plaque reduction neutralization test. The highest seropositivity of 82% was observed in vaccinated children during the first0.5–1.5 years after booster vaccination. Then, the seropositivity began to decline and remained lower than the original level observed in the 0.5–1.5-year group. An association was found between the waning of seroprevalence and elapsed time of the post-booster vaccination. Similarly, the neutralizing antibody(nAb) titres gradually decreased over time, and the levels showed a positive correlation with the protective efficacy in mice. This finding suggests that nAbs play an important role in the antiviral process and that the nAb titre is an adequately credible parameter for evaluating the protective efficacy induced by the JE vaccine. Our results provide data that clarify the persistence and waning of antibodies to JEV, which may help elucidate the pathogenesis of JE.     

Combining information from multiple bone turnover markers as diagnostic indices for osteoporosis using support vector machines

Context: Osteoporosis (OP) is a progressive systemic bone disease. Dual-energy X-ray absorptiometry (DXA) is routinely employed and is considered the gold standard method for the diagnosis of OP.

Objective: We aimed to investigate the potential use of combined information from multiple bone turnover markers (BTMs) as a clinical diagnostic tool for OP.

Materials and methods: A total of 9053 Chinese postmenopausal women (2464 primary OP patients and 6589 healthy controls) were recruited. Serum levels of six common BTMs, including BAP, BSP, CTX, OPG, OST and sRANKL were assayed. Models based on support vector machine (SVM) were constructed to explore the efficiency of different combinations of multiple BTMs for OP diagnosis.

Results: Increasing the number of BTMs used in generating the models increased the predictive power of the SVM models for determining the disease status of study subjects. The highest kappa coefficient for the model with one BTM (BAP) compared to DXA was 0.7783. The full model incorporating all six BTMs resulted in a high kappa coefficient of 0.9786.

Conclusion: Our findings showed that although single BTMs were not sufficient for OP diagnosis, appropriate combinations of multiple BTMs incorporated into the SVM models showed almost perfect agreement with the DXA.     

Design and synthesis of novel 1-phenyl-3-(5-(pyrimidin-4-ylthio)-1,3,4-thiadiazol- 2-yl)urea derivatives with potent anti-CML activity throughout PI3K/AKT signaling pathway

In this investigation, a series of 1-phenyl-3-(5-(pyrimidin-4-ylthio)-1,3,4- thiadiazol-2-yl)urea receptor tyrosine kinase inhibitors were synthesized by a simple and efficient structure-based design. Structure-activity relationship (SAR) analysis of these compounds based on cellular assays led to the discovery of a number of compounds that showed potent activity against human chronic myeloid leukemia (CML) cell line K562, but very weak or no cellular toxicity through monitoring the growth kinetics of K562 cell during a period of 72 h using the real-time live-cell imaging. Among these compounds, 1-(5-((6-((3-morpholinopropyl) amino)pyrimidin-4-yl)thio)-1,3,4-thiadiazol-2-yl)-3-(4-(trifluoromethyl)phenyl)urea (7) exhibited the least cellular toxicity and better biological activity in cellular assays (K562, IC₅₀: 0.038 μM). Compound 7 also displayed very good induced-apoptosis effect for human CML cell line K562 and exerted its effect via a significantly reduced protein phosphorylation of PI3K/Akt signal pathway by Human phospho-kinase array analysis. In vitro results indicate that 1-phenyl-3-(5-(pyrimidin-4-ylthio)-1,3,4- thiadiazol-2-yl)urea derivatives are lead molecules for further development as treatment of chronic myeloid leukemia and cancer.