Ternary heterogeneous MWCNT@TiO 2-C wave absorbent was firstly prepared, using glucose, MWCNT, and titanium isopropoxide as raw materials, through the solvothermal process followed by post-heat treatment. Afterwards, MWCNT@TiO 2-C/silicone rubber wave-absorbing composites were fabricated via solution casting and subsequent curing process. XRD, Raman, XPS, and TEM analyses demonstrated the MWCNT@TiO 2-C fillers were successfully synthesized with TiO 2 and amorphous carbon coated on the surface of MWCNT. When the MWCNT@TiO 2-C/silicone rubber wave-absorbing composites contained 25 wt% MWCNT@TiO 2-C fillers and with the thickness of 2.5 mm, it displayed the minimum reflection loss of-53.2 dB and an effective absorption bandwidth of 3.1 GHz. Remarkable wave-absorbing performances for MWCNT@TiO 2-C/silicone rubber composites could be attributed to the synergetic effect of interfacial polarization loss and conduction loss.

PurposeINHBA, which encodes a member of the TGF-beta superfamily of proteins, has been identified to play a critical role in different types of cancer. However, its clinical significance in esophageal squamous cell carcinoma (ESCC) has never been reported.Patients and methodsIn this study, we collected 239 ESCC paraffin-embedded specimens and measured the expression of INHBA with immunohistochemistry (IHC). The clinical and prognostic significance of INHBA expression was statistically analyzed. What is more, we conducted a meta-analysis to study the prognostic value of INHBA expression in multiple types of solid tumors.ResultsThe results showed that INHBA expression was observed predominantly in the cytoplasm of cells in the ESCC specimens. INHBA expression was closely correlated with N categories (P=0.026). Kaplan–Meier analysis showed that ESCC patients in the low INHBA expression subgroup had significantly better prognosis than those with high INHBA level. Subgroup analysis revealed that INHBA distinguished the disease-free survival (DFS) and overall survival (OS) when patients were stratified by TNM stage status and N status. Multivariate analysis results suggested that INHBA expression was an independent factor that affected OS (HR =1.679, P=0.022) and DFS (HR =1.715, P=0.017). In the meta-analysis, six papers with 1321 patients were included and patients with high INHBA level had worse prognosis than patients with low INHBA level (HR 2.50, 95% CI 1.75–3.57, P<0.0001).ConclusionHigh INHBA level predicts poor prognosis in ESCC and other solid tumors. More studies are required to elucidate the role of INHBA and its clinical application in cancer settings.

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Nowadays online users prefer to join multiple social media for the purpose of socialized online service. The problem anchor link prediction is formalized to link user data with the common ground on user profile, content and network structure across social networks. Most of the traditional works concentrated on learning matching function with explicit or implicit features on observed user data. However, the low quality of observed user data confuses the judgment on anchor links, resulting in the matching collision problem in practice. In this paper, we explore local structure consistency and then construct a matching graph in order to circumvent matching collisions. Furthermore, we propose graph convolution networks with mini-batch strategy, efficiently solving anchor link prediction on matching graph. The experimental results on three real application scenarios show the great potentials of our proposed method in both prediction accuracy and efficiency. In addition, the visualization of learned embeddings provides us a qualitative way to understand the inference of anchor links on the matching graph.