Rational construction of a profitable microstructure in carbon-based electromagnetic composites is becoming a promising strategy to reinforce their microwave absorption performance. Herein, the microstructure design is innovatively coupled with a metal–organic frameworks (MOFs)-derived method to produce hollow Co/C microspheres (Co/C-HS). The resultant composites combine the advantages of hollow microstructures and good chemical homogeneity. It is found that the pyrolysis temperature plays an important role in determining the electromagnetic properties of these hollow Co/C microspheres, where high pyrolysis temperature will increase relative complex permittivity and decrease relative complex permeability. When the pyrolysis temperature is 600 °C, the sample (Co/C-HS-600) will show improved impedance matching and good attenuation ability, and thus an excellent microwave absorption performance with strong reflection loss (−66.5 dB at 17.6 GHz) and wide response bandwidth (over −10 dB, 3.7–18.0 GHz) can be achieved. By comparing with Co/C composites derived from conventional ZIF-67, it can be validated that a hollow microstructure is greatly helpful to upgrade the performance by boosting dielectric loss ability and suppressing a negative interaction between the carbon matrix and incident electromagnetic waves, as well as providing multiple reflection behaviors. We believe that this study may open a new avenue to promote the electromagnetic applications of MOFs-derived carbon-based composites.

Carbides/carbon composites are becoming a new kind of microwave absorption (MA) materials with great potential in chemical stability and light weight, as well as enhanced performance. Herein, we design a series of Mo2C/C composites through a simple pyrolysis of Mo-substituted ZIF-8 (Mo/ZIF-8). It is found that the transformation of zeolitic imidazolate frameworks into carbon polyhedrons is accompanied by the in situ formation of ultrasmall Mo2C nanoparticles (Mo2C NPs) less than 5.0 nm. The molar ratio of 2-methylimidazole to molybdic acid (MIM/Mo) presents a significant effect on the relative content of Mo2C NPs but not on their average size. The uniform distribution of Mo2C NPs in carbon polyhedrons overcomes the poor chemical homogeneity in conventional carbides/carbon composites. More importantly, Mo2C NPs modulate the dielectric loss of these composites effectively. On one hand, they moderately weaken the contribution from conductivity loss and dipole orientation polarization; on the other hand, they create considerable interfacial polarization. As a result, these Mo2C/C composites display much better impedance matching than individual carbon polyhedrons. When the MIM/Mo ratio reaches 6.0, the optimized composite, S-Mo2C/C-6.0, displays good MA performance in the frequency range of 2.0–18.0 GHz, including powerful reflection loss and broad qualified bandwidth. Its performance is actually superior to those conventional carbides/carbon composites in previous studies, demonstrating that Mo2C/C composite from this novel strategy may be a promising candidate for high-performance MA materials in the future.

Marital status is an independent prognostic factor for survival in several cancers. To determine if that is also true for pancreatic cancer after surgical treatment, we examined 13,370 cases of pancreatic cancer reported to the Surveillance, Epidemiology, and End Results (SEER) database between 1988 and 2012. We found that patients who were widowed at the time of diagnosis were more likely to be female, a high percentage were elderly, a high ratio were diagnosed in early years, and a high proportion of tumors were located at the head of the pancreas (P < 0.05). Marital status was confirmed to be an independent prognostic factor in both univariate and multivariate analyses (P < 0.05). In those with localized disease, 5-year pancreatic cancer cause-specific survival was 6.5% lower in widowed patients than married ones (38.6% vs. 32.1%), though this difference was not significant in a multivariate analysis (P = 0.084). In those with regional disease or distant metastasis, univariate and multivariate analyses indicated marital status to be an independent prognostic factor (P < 0.05). Thus marital status is an important prognostic factor in pancreatic cancer, and widowed patients are at greater risk of death than others.

Deep learning is a growing trend in medical image analysis. There are limited data of deep learning techniques applied in Chest X-rays. This paper proposed a deep learning algorithm for cardiothoracic ratio (CTR) calculation in chest X-rays. A fully convolutional neural network was employed to segment chest X-ray images and calculate CTR. CTR values derived from the deep learning model were compared with the reference standard using Bland-Altman analysis and linear correlation graphs, and intra-class correlation (ICC) analyses. Diagnostic performance of the model for the detection of heart enlargement was assessed and compared with other deep learning methods and radiologists. CTR values derived from the deep learning method showed excellent agreement with the reference standard, with mean difference 0.0004 ± 0.0133, 95% limits of agreement −0.0256 to 0.0264. Correlation coefficient between deep learning and reference standard was 0.965 (P < 0.001), and ICC coefficient was 0.982 (95% CI 0.978-0.985) (P < 0.001). Measurement time by deep learning was significantly less than that of the manual method [0.69 (0.69-0.70) VS 25.26 (23.49-27.44) seconds, P < 0.001]. Diagnostic accuracy, specificity, and positive predictive value were comparable between the two methods. However, deep learning showed relatively higher sensitivity and negative predictive value (97.2% vs 91.4%, P = 0.004; and 96.0% vs 89.0%, P = 0.006; respectively) compared with the manual method. Performance of this computer-aided technique was demonstrated to be more reliable, time and labor saving than that of the manual method in CTR calculation.

Pancreatic cancer is one of the most malignant tumors that are difficult to diagnose at its early stage and there is no effective therapy. Recent studies uncovered that many non-protein-coding RNAs including the class of long noncoding RNAs (lncRNAs) are differentially expressed in various types of tumors and they are potent regulators of tumor progression and metastasis. LncRNA can mediate tumor initiation, proliferation, migration and metastasis through modulating epigenetic modification, alternative splicing, transcription, and protein translation. In this review, we discuss the molecular mechanism of lncRNAs in the involvement of tumor growth, survival, epithelial-mesenchymal transition, tumor microenvironment, cancer stem cells and chemoresistance in pancreatic ductal adenocarcinoma (PDAC).