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Knowing cutting force in rotary ultrasonic machining (RUM) can help optimizing input variables. RUM of brittle materials has been investigated both experimentally and theoretically. However, there are no reports on cutting force models for RUM of brittle materials. This paper presents a mechanistic model for cutting force in RUM of brittle materials. Assuming that brittle fracture is the primary mechanism of material removal in RUM of brittle materials, the cutting force model is developed step by step. On the basis of this mechanistic model, relationships between cutting force and input variables (such as spindle speed, feed rate, ultrasonic vibration amplitude, abrasive size, and abrasive concentration) are predicted.

X-inactive specific transcript (XIST), one of the first found cancer-associated long non-coding RNAs (lncRNAs), is involved in the development and progression of many types of tumors. Aberrant expression of XIST has been observed in hepatocellular carcinoma, cervical, breast, ovarian and colorectal cancer. However, the exact effects and molecular mechanisms of XIST in lung cancer progression are still unknown to date. In the present study, we investigated the role of XIST in human lung cancer cell lines and clinical tumor samples in order to determine the function of this molecule. In our research, lncRNA-XIST was specifically upregulated in lung cancer cell lines and promoted lung cancer cell growth through targeting miR-140. Knockdown of XIST inhibited the proliferation and promoted cell apoptosis of human lung cancer cells and suppressed metastasis in vitro and in vivo. In addition, miR-140-dependent inhibitor of apoptosis-stimulating protein of p53 (iASPP) regulation was required in XIST-induced lung cancer cell growth. These findings indicated that XIST may regulate the tumor growth and metastasis via miR-140-dependent iASPP regulation. Taken together, our data indicated that XIST may be an oncogenic lncRNA that promotes the proliferation and metastasis of lung cancer through the regulation of miR-140 and could be regarded as a therapeutic target in human lung cancer.

Aggregating evidences have shown that long non-coding RNAs (lncRNAs) generally play key roles in cellular biological processes such as epigenetic regulation, gene expression regulation at transcriptional and post-transcriptional levels, cell differentiation and others. However, most lncRNAs have not been functionally characterized. There is an urgent need to develop computational approaches for function annotation of increasing available lncRNAs. In this article, we propose a global network-based method, KATZLGO, to predict the functions of human lncRNAs at large scale. A global network is constructed by integrating three heterogeneous networks: lncRNA-lncRNA similarity network, lncRNA-protein association network and proteinprotein interaction network. The KATZ measure is then employed to calculate similarities between lncRNAs and proteins in the global network. We annotate lncRNAs with Gene Ontology (GO) terms of their neighboring protein-coding genes based on the KATZ similarity scores. The performance of KATZLGO is evaluated on a manually annotated lncRNA benchmark and a proteincoding gene benchmark with known function annotations. KATZLGO significantly outperforms state-of-the-art computational method both in maximum F-measure and coverage. Furthermore, we apply KATZLGO to predict functions of human lncRNAs and successfully map 12,318 human lncRNA genes to GO terms.

Glucocorticoids (GCs) are widely used for treating asthma, rheumatoid arthritis, nephrotic syndrome, acute lymphoblastic leukemia and other autoimmune diseases. However, in a subgroup of patients, failure to respond to GCs is known as GC resistance or GC insensitivity. This represents an important barrier to effective treatment and a clinical problem requiring an urgent solution. Genetic variation in the GC pathway is a significant factor in interindividual differences in GC treatment. This article reviews the pharmacogenetics of GCs in diverse diseases based on the GC pathway.

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Tracheobronchial mucormycosis is a rare but severe disease with high mortality because of its nonspecific clinical presentations and variable predisposing factors.