An Affinity Propagation Clustering Algorithm for Mixed Numeric and Categorical Datasets

Clustering has been widely used in different fields of science, technology, social science, and so forth. In real world, numeric as well as categorical features are usually used to describe the data objects. Accordingly, many clustering methods can process datasets that are either numeric or categorical. Recently, algorithms that can handle the mixed data clustering problems have been developed. Affinity propagation (AP) algorithm is an exemplar-based clustering method which has demonstrated good performance on a wide variety of datasets. However, it has limitations on processing mixed datasets. In this paper, we propose a novel similarity measure for mixed type datasets and an adaptive AP clustering algorithm is proposed to cluster the mixed datasets. Several real world datasets are studied to evaluate the performance of the proposed algorithm. Comparisons with other clustering algorithms demonstrate that the proposed method works well not only on mixed datasets but also on pure numeric and categorical datasets

Cross-CBAM: A Lightweight network for Scene Segmentation

Scene parsing is a great challenge for real-time semantic segmentation. Although traditional semantic segmentation networks have made remarkable leap-forwards in semantic accuracy, the performance of inference speed is unsatisfactory. Meanwhile, this progress is achieved with fairly large networks and powerful computational resources. However, it is difficult to run extremely large models on edge computing devices with limited computing power, which poses a huge challenge to the real-time semantic segmentation tasks. In this paper, we present the Cross-CBAM network, a novel lightweight network for real-time semantic segmentation. Specifically, a Squeeze-and-Excitation Atrous Spatial Pyramid Pooling Module(SE-ASPP) is proposed to get variable field-of-view and multiscale information. And we propose a Cross Convolutional Block Attention Module(CCBAM), in which a cross-multiply operation is employed in the CCBAM module to make high-level semantic information guide low-level detail information. Different from previous work, these works use attention to focus on the desired information in the backbone. CCBAM uses cross-attention for feature fusion in the FPN structure. Extensive experiments on the Cityscapes dataset and Camvid dataset demonstrate the effectiveness of the proposed Cross-CBAM model by achieving a promising trade-off between segmentation accuracy and inference speed. On the Cityscapes test set, we achieve 73.4% mIoU with a speed of 240.9FPS and 77.2% mIoU with a speed of 88.6FPS on NVIDIA GTX 1080Ti

Cautious explorers generate more future academic impact

Some scientists are more likely to explore unfamiliar research topics while others tend to exploit existing ones. In previous work, correlations have been found between scientists' topic choices and their career performances. However, literature has yet to untangle the intricate interplay between scientific impact and research topic choices, where scientific exploration and exploitation intertwine. Here we study two metrics that gauge how frequently scientists switch topic areas and how large those jumps are, and discover that 'cautious explorers' who switch topics frequently but do so to 'close' domains have notably better future performance and can be identified at a remarkably early career stage. Cautious explorers who balance exploration and exploitation in their first four career years have up to 19% more citations per future paper. Our results suggest that the proposed metrics depict the scholarly traits of scientists throughout their careers and provide fresh insight, especially for nurturing junior scientists.Comment: 16 pages of main text and 94 pages of supplementary informatio

TGFBI promoter hypermethylation correlating with paclitaxel chemoresistance in ovarian cancer

The purpose of this study is to determine the methylation status of Transforming growth factor-beta-inducible gene-h3 (TGFBI) and its correlation with paclitaxel chemoresistance in ovarian cancer. The methylation status of TGFBI was examined in ovarian cancer and control groups by methylation-specific PCR (MSP) and bisulfite sequencing PCR (BSP). The TGFBI expression and cell viability were compared by Quantitative Real-Time PCR, Western Blotting and MTT assay before and after demethylating agent 5-aza-2'-deoxycytidine (5-aza-dc) treatment in 6 cell lines (SKOV3, SKOV3/TR, SKOV3/DDP, A2780, 2780/TR, OVCAR8). In our results, TGFBI methylation was detected in 29/40 (72.5%) of ovarian cancer and 1/10 (10%) of benign ovarian tumors. No methylation was detected in normal ovarian tissues (P < 0.001). No statistical correlation between RUNX3 methylation and clinicopathological characteristics was observed. A significant correlation between TGFBI methylation and loss of TGFBI mRNA expression was found (P < 0.001). The methylation level of TGFBI was significantly higher in paclitaxel resistant cell lines (SKOV3/TR and 2780/TR) than that in the sensitive pairs (P < 0.001). After 5-aza-dc treatment, the relative expression of TGFBI mRNA and protein increased significantly in SKOV3/TR and A2780/TR cells. However, no statistical differences of relative TGFBI mRNA expression and protein were found in other cells (all P > 0.05), which showed that re-expression of TGFBI could reverse paclitaxel chemoresistance. Our results show that TGFBI is frequently methylated and associated with paclitaxel-resistance in ovarian cancer. TGFBI might be a potential therapeutic target for the enhancement of responses to chemotherapy in ovarian cancer patients

Solution structure of the second bromodomain of Brd2 and its specific interaction with acetylated histone tails

<p>Abstract</p> <p>Background</p> <p>Brd2 is a transcriptional regulator and belongs to BET family, a less characterized novel class of bromodomain-containing proteins. Brd2 contains two tandem bromodomains (BD1 and BD2, 46% sequence identity) in the N-terminus and a conserved motif named ET (extra C-terminal) domain at the C-terminus that is also present in some other bromodomain proteins. The two bromodomains have been shown to bind the acetylated histone H4 and to be responsible for mitotic retention on chromosomes, which is probably a distinctive feature of BET family proteins. Although the crystal structure of Brd2 BD1 is reported, no structure features have been characterized for Brd2 BD2 and its interaction with acetylated histones.</p> <p>Results</p> <p>Here we report the solution structure of human Brd2 BD2 determined by NMR. Although the overall fold resembles the bromodomains from other proteins, significant differences can be found in loop regions, especially in the ZA loop in which a two amino acids insertion is involved in an uncommon <it>π</it>-helix, termed <it>π</it>D. The helix <it>π</it>D forms a portion of the acetyl-lysine binding site, which could be a structural characteristic of Brd2 BD2 and other BET bromodomains. Unlike Brd2 BD1, BD2 is monomeric in solution. With NMR perturbation studies, we have mapped the H4-AcK12 peptide binding interface on Brd2 BD2 and shown that the binding was with low affinity (2.9 mM) and in fast exchange. Using NMR and mutational analysis, we identified several residues important for the Brd2 BD2-H4-AcK12 peptide interaction and probed the potential mechanism for the specific recognition of acetylated histone codes by Brd2 BD2.</p> <p>Conclusion</p> <p>Brd2 BD2 is monomeric in solution and dynamically interacts with H4-AcK12. The additional secondary elements in the long ZA loop may be a common characteristic of BET bromodomains. Surrounding the ligand-binding cavity, five aspartate residues form a negatively charged collar that serves as a secondary binding site for H4-AcK12. We suggest that Brd2 BD1 and BD2 may possess distinctive roles and cooperate to regulate Brd2 functions. The structure basis of Brd2 BD2 will help to further characterize the functions of Brd2 and its BET members.</p

Prediction and Identification of Potential Immunodominant Epitopes in Glycoproteins B, C, E, G, and I of Herpes Simplex Virus Type 2

Twenty B candidate epitopes of glycoproteins B (gB2), C (gC2), E (gE2), G (gG2), and I (gI2) of herpes simplex virus type 2 (HSV-2) were predicted using DNAstar, Biosun, and Antheprot methods combined with the polynomial method. Subsequently, the biological functions of the peptides were tested via experiments in vitro. Among the 20 epitope peptides, 17 could react with the antisera to the corresponding parent proteins in the EIA tests. In particular, five peptides, namely, gB2466–473 (EQDRKPRN), gC2216–223 (GRTDRPSA), gE2483–491 (DPPERPDSP), gG2572–579 (EPPDDDDS), and gI2286-295 (CRRRYRRPRG) had strong reaction with the antisera. All conjugates of the five peptides with the carrier protein BSA could stimulate mice into producing antibodies. The antisera to these peptides reacted strongly with the corresponding parent glycoproteins during the Western Blot tests, and the peptides reacted strongly with the antibodies against the parent glycoproteins during the EIA tests. The antisera against the five peptides could neutralize HSV-2 infection in vitro, which has not been reported until now. These results suggest that the immunodominant epitopes screened using software algorithms may be used for virus diagnosis and vaccine design against HSV-2

Investigation on the amplitude of random telegraph noise (RTN) in nanoscale MOSFETs: Scaling limit of “Hole in the inversion layer” model

In this paper, the widely adopted “hole in the inversion layer” (HIL) model for predicting the amplitude of random telegraph noise (RTN) in nanoscale MOSFETs, is theoretically revisited with focusing on its scaling limit and validation range. It is found that this simple physical model fail to apply on ultra-scaled devices with L&lt;;20nm and/or W&lt;;10nm, due to the non-negligible impact from source/drain and the failure of assumed equivalence to resistor network in ultra-scaled devices. This work provides a deeper understanding to this model and is helpful for accurate prediction of RTN amplitude in nanoscale devices and circuits

AFAP1-AS1 Promotes Epithelial-Mesenchymal Transition and Tumorigenesis Through Wnt/β-Catenin Signaling Pathway in Triple-Negative Breast Cancer

Long non-coding RNA (LncRNA) actin filament-associated protein1-antisense RNA 1 (AFAP1-AS1) is overexpressed in various types of cancers and plays an important role in tumor progression and prognosis. This study investigates the role of AFAP1-AS1 in tumor progression in triple-negative breast cancer (TNBC). We found that AFAP1-AS1 was overexpressed in TNBC tissues and cells. Overexpression of LncRNA AFAP1-AS1 was associated with poor prognosis in TNBC patients. Moreover, we demonstrated that upregulation of AFAP1-AS1 promoted cell proliferation and invasion, and inhibited cell apoptosis in vitro, while overexpression of AFAP1-AS1 promoted tumor growth in vivo. Our results also revealed that upregulation of AFAP1-AS1 activated Wnt/β-catenin pathway to promote tumorigenesis and cell invasion by increasing the expression of C-myc and epithelial-mesenchymal transition-related molecules in TNBC. Collectively, AFAP1-AS1 can be an independent prognostic marker and an effective therapeutic target of triple- negative breast cancer