Three New Ranidae Mitogenomes and the Evolution of Mitochondrial Gene Rearrangements among Ranidae Species

Various types of gene rearrangements have been discovered in the mitogenoes of the frog family Ranidae. In this study, we determined the complete mitogenome sequence of three Rana frogs. By combining the available mitogenomic data sets from GenBank, we evaluated the phylogenetic relationships of Ranidae at the mitogenome level and analyzed mitogenome rearrangement cases within Ranidae. The three frogs shared an identical mitogenome organization that was extremely similar to the typical Neobatrachian-type arrangement. Except for the genus Babina, the monophyly of each genus was well supported. The genus Amnirana occupied the most basal position among the Ranidae. The [Lithobates + Rana] was the closest sister group of Odorrana. The diversity of mitochondrial gene arrangements in ranid species was unexpectedly high, with 47 mitogenomes from 40 ranids being classified into 10 different gene rearrangement types. Some taxa owned their unique gene rearrangement characteristics, which had significant implication for their phylogeny analysis. All rearrangement events discovered in the Ranidae mitogenomes can be explained by the duplication and random loss model

NMI inhibits cancer stem cell traits by downregulating hTERT in breast cancer.

N-myc and STAT interactor (NMI) has been proved to bind to different transcription factors to regulate a variety of signaling mechanisms including DNA damage, cell cycle and epithelial-mesenchymal transition. However, the role of NMI in the regulation of cancer stem cells (CSCs) remains poorly understood. In this study, we investigated the regulation of NMI on CSCs traits in breast cancer and uncovered the underlying molecular mechanisms. We found that NMI was lowly expressed in breast cancer stem cells (BCSCs)-enriched populations. Knockdown of NMI promoted CSCs traits while its overexpression inhibited CSCs traits, including the expression of CSC-related markers, the number of CD44+CD24- cell populations and the ability of mammospheres formation. We also found that NMI-mediated regulation of BCSCs traits was at least partially realized through the modulation of hTERT signaling. NMI knockdown upregulated hTERT expression while its overexpression downregulated hTERT in breast cancer cells, and the changes in CSCs traits and cell invasion ability mediated by NMI were rescued by hTERT. The in vivo study also validated that NMI knockdown promoted breast cancer growth by upregulating hTERT signaling in a mouse model. Moreover, further analyses for the clinical samples demonstrated that NMI expression was negatively correlated with hTERT expression and the low NMI/high hTERT expression was associated with the worse status of clinical TNM stages in breast cancer patients. Furthermore, we demonstrated that the interaction of YY1 protein with NMI and its involvement in NMI-mediated transcriptional regulation of hTERT in breast cancer cells. Collectively, our results provide new insights into understanding the regulatory mechanism of CSCs and suggest that the NMI-YY1-hTERT signaling axis may be a potential therapeutic target for breast cancers

Thermophoretic deposition of particles in fully developed mixed convection flow in a parallel-plate vertical channel: the full analytical solution

In a recent paper (Grosan et al. in Heat Mass Transf 45:503-509, 2009) a mostly numerical approach to the title problem has been reported. In the present paper the full analytical solution is given. Several new features emerging from this approach are discussed in detai

Hurricanes Substantially Reduce the Nutrients in Tropical Forested Watersheds in Puerto Rico

Because nutrients including nitrogen and phosphorus are generally limited in tropical forest ecosystems in Puerto Rico, a quantitative understanding of the nutrient budget at a watershed scale is required to assess vegetation growth and predict forest carbon dynamics. Hurricanes are the most frequent disturbance in Puerto Rico and play an important role in regulating lateral nitrogen and phosphorus exports from the forested watershed. In this study, we selected seven watersheds in Puerto Rico to examine the immediate and lagged effects of hurricanes on nitrogen and phosphorous exports. Our results suggest that immediate surges of heavy precipitation associated with hurricanes accelerate nitrogen and phosphorus exports as much as 297 ± 113 and 306 ± 70 times than the long-term average, respectively. In addition, we estimated that it requires approximately one year for post-hurricane riverine nitrogen and phosphorus concentrations to recover to pre-hurricane levels. During the recovery period, the riverine nitrogen and phosphorus concentrations are 30 ± 6% and 28 ± 5% higher than the pre-hurricane concentrations on average

Carbon Nanotube Mode-Locked Fiber Laser Generating Cylindrical Vector Beams with a Two-Mode Fiber Bragg Grating

We propose and demonstrate a compact all-fiber laser generating cylindrical vector beam (CVB) using carbon nanotubes as the saturable absorber for mode-locking and a two-mode fiber Bragg grating (TM-FBG) as the mode discriminator. Both radially and azimuthally polarized beams with a polarization purity of 90% were obtained by simply adjusting the polarization controllers. The CVB mode-locked fiber laser operates at 1552.9 nm with a 3-dB line width of less than 0.02 nm, generating ns CVB pulses. The all-fiber CVB laser may have potential applications from fundamental research to practical applications, such as particle capture, high-resolution measurement and material processing

Highlights of the 2nd International Symposium on Tribbles and Diseases: Tribbles tremble in therapeutics for immunity, metabolism, fundamental cell biology and cancer

The Tribbles (TRIB) family of pseudokinase proteins has been shown to play key roles in cell cycle, metabolic diseases, chronic inflammatory disease, and cancer development. A better understanding of the mechanisms of TRIB pseudokinases could provide new insights for disease development and help promote TRIB proteins as novel therapeutic targets for drug discovery. At the 2nd International Symposium on Tribbles and Diseases held on May 7‒9, 2018 in Beijing, China, a group of leading Tribbles scientists reported their findings and ongoing studies about the effects of the different TRIB proteins in the areas of immunity, metabolism, fundamental cell biology and cancer. Here, we summarize important and insightful overviews from 4 keynote lectures, 13 plenary lectures and 8 short talks that took place during this meeting. These findings may offer new insights for the understanding of the roles of TRIB pseudokinases in the development of various diseases

Online predicting conformance of business process with recurrent neural networks

Conformance Checking is a problem to detect and describe the differences between a given process model representing the expected behaviour of a business process and an event log recording its actual execution by the Process-aware Information System (PAIS). However, such existing conformance checking techniques are offline and mainly applied for the completely executed process instances, which cannot provide the real-time conformance-oriented process monitoring for an on-going process instance. Therefore, in this paper, we propose three approaches for online conformance prediction by constructing a classification model automatically based on the historical event log and the existing reference process model. By utilizing Recurrent Neural Networks, these approaches can capture the features that have a decisive effect on the conformance for an executed case to build a prediction model and then use this model to predict the conformance of a running case. The experimental results on two real datasets show that our approaches outperform the state-of-the-art ones in terms of prediction accuracy and time performance.</p

Occlusion-Aware Deep Convolutional Neural Network via Homogeneous Tanh-transforms for Face Parsing

Face parsing infers a pixel-wise label map for each semantic facial component. Previous methods generally work well for uncovered faces, however, they overlook facial occlusion and ignore some contextual areas outside a single face, especially when facial occlusion has become a common situation during the COVID-19 epidemic. Inspired by the lighting phenomena in everyday life, where illumination from four distinct lamps provides a more uniform distribution than a single central light source, we propose a novel homogeneous tanh-transform for image preprocessing, which is made up of four tanh-transforms. These transforms fuse the central vision and the peripheral vision together. Our proposed method addresses the dilemma of face parsing under occlusion and compresses more information from the surrounding context. Based on homogeneous tanh-transforms, we propose an occlusion-aware convolutional neural network for occluded face parsing. It combines information in both Tanh-polar space and Tanh-Cartesian space, capable of enhancing receptive fields. Furthermore, we introduce an occlusion-aware loss to focus on the boundaries of occluded regions. The network is simple, flexible, and can be trained end-to-end. To facilitate future research of occluded face parsing, we also contribute a new cleaned face parsing dataset. This dataset is manually purified from several academic or industrial datasets, including CelebAMask-HQ, Short-video Face Parsing, and the Helen dataset, and will be made public. Experiments demonstrate that our method surpasses state-of-the-art methods in face parsing under occlusion