SeqVISTA: a graphical tool for sequence feature visualization and comparison

BACKGROUND: Many readers will sympathize with the following story. You are viewing a gene sequence in Entrez, and you want to find whether it contains a particular sequence motif. You reach for the browser's "find in page" button, but those darn spaces every 10 bp get in the way. And what if the motif is on the opposite strand? Subsequently, your favorite sequence analysis software informs you that there is an interesting feature at position 13982–14013. By painstakingly counting the 10 bp blocks, you are able to examine the sequence at this location. But now you want to see what other features have been annotated close by, and this information is buried several screenfuls higher up the web page. RESULTS: SeqVISTA presents a holistic, graphical view of features annotated on nucleotide or protein sequences. This interactive tool highlights the residues in the sequence that correspond to features chosen by the user, and allows easy searching for sequence motifs or extraction of particular subsequences. SeqVISTA is able to display results from diverse sequence analysis tools in an integrated fashion, and aims to provide much-needed unity to the bioinformatics resources scattered around the Internet. Our viewer may be launched on a GenBank record by a single click of a button installed in the web browser. CONCLUSION: SeqVISTA allows insights to be gained by viewing the totality of sequence annotations and predictions, which may be more revealing than the sum of their parts. SeqVISTA runs on any operating system with a Java 1.4 virtual machine. It is freely available to academic users at

Discovery of N-arylsulfonyl-3-acylindole benzoyl hydrazone derivatives as anti-HIV-1 agents

The discovery and development of novel inhibitors with activity against variants of human immunodeficiency virus type 1 (HIV-1) is pivotal for overcoming treatment failure. As our ongoing work on research of anti-HIV-1 inhibitors, 32 N-arylsulfonyl-3-acylindole benzoyl hydrazone derivatives were prepared by introduction of the hydrazone fragments on the N-arylsulfonyl-3-acylindolyl skeleton and preliminarily screened in vitro as HIV-1 inhibitors for the first time. Among of all the reported analogues, eight compounds exhibited significant anti-HIV-1 activity, especially N-(3-nitro)phenylsulfonyl-3- acetylindole benzoyl hydrazone (18) and N-(3-nitro)phenylsulfonyl-3-acetyl-6-methylindole benzoyl hydrazone (23) displayed the most potent anti-HIV-1 activity with EC50 values of 0.26 and 0.31 μg/mL, and TI values of >769.23 and >645.16, respectively. It is noteworthy that introduction of R3 as the methyl group and R2 as the hydrogen group could result in more potent compounds. This suggested that introduction of R3 as the methyl group could be taken into account for further preparation of these kinds of compounds as anti-HIV-1 agents

RayMVSNet++: Learning Ray-based 1D Implicit Fields for Accurate Multi-View Stereo

Learning-based multi-view stereo (MVS) has by far centered around 3D convolution on cost volumes. Due to the high computation and memory consumption of 3D CNN, the resolution of output depth is often considerably limited. Different from most existing works dedicated to adaptive refinement of cost volumes, we opt to directly optimize the depth value along each camera ray, mimicking the range finding of a laser scanner. This reduces the MVS problem to ray-based depth optimization which is much more light-weight than full cost volume optimization. In particular, we propose RayMVSNet which learns sequential prediction of a 1D implicit field along each camera ray with the zero-crossing point indicating scene depth. This sequential modeling, conducted based on transformer features, essentially learns the epipolar line search in traditional multi-view stereo. We devise a multi-task learning for better optimization convergence and depth accuracy. We found the monotonicity property of the SDFs along each ray greatly benefits the depth estimation. Our method ranks top on both the DTU and the Tanks & Temples datasets over all previous learning-based methods, achieving an overall reconstruction score of 0.33mm on DTU and an F-score of 59.48% on Tanks & Temples. It is able to produce high-quality depth estimation and point cloud reconstruction in challenging scenarios such as objects/scenes with non-textured surface, severe occlusion, and highly varying depth range. Further, we propose RayMVSNet++ to enhance contextual feature aggregation for each ray through designing an attentional gating unit to select semantically relevant neighboring rays within the local frustum around that ray. RayMVSNet++ achieves state-of-the-art performance on the ScanNet dataset. In particular, it attains an AbsRel of 0.058m and produces accurate results on the two subsets of textureless regions and large depth variation.Comment: IEEE Transactions on Pattern Analysis and Machine Intelligence. arXiv admin note: substantial text overlap with arXiv:2204.0132

Cyclohexadione-aniline conjugate inhibits proliferation of melanoma cells via upregulation of Mek 1/2 kinase activity

Purpose: To investigate the antiproliferative effect of cyclohexadione-aniline conjugate (CHAC) on melanoma cells, and the mechanism of action involved. Methods: Human melanoma cell lines (B16 F1 and A375) were used in this study. The cells were cultured in RPMI 1640 medium supplemented with 10 % fetal bovine serum (FBS) and 1 % penicillin/streptomycin at 37 °C in a humidified atmosphere of 5 % CO2 and 95 % air. After attaining 70 - 80 % confluency, the cells were treated with serum-free medium and graded concentrations of CHAC (10 – 60 μM) for 24 h. Normal cell culture without CHAC served as control group. B16 F1 and A375 cells were used in logarithmic growth phase in this study. Cell viability and apoptosis were assessed using 3-(4, 5-dimethylthiazol-2-yl) 2, 5-diphe¬nyltetrazolium bromide (MTT) and flow cytometric assays, respectively. Western blotting was used to assess the levels of protein expression of X linked inhibitor of apoptosis (XIAP), survivin, p-Erk 1/2, and p-Mek 1/2. Results: Treatment of B16 F1 and A375 cells with CHAC led to significant and concentrationdependent reductions in their viability (p < 0.05). The proliferation of B16 F1 cells decreased from 93.41 to 32.87 %, while that of A375 cells was reduced from 95.23 to 36.50 %. Treatment of B16 F1 cells with CHAC significantly and concentration-dependently increased the population of cells in G0/G1 phase, and significantly reduced cell proportion in S and G2/M phases (p < 0.05). It also significantly and concentration-dependently promoted apoptosis in B16 F1 cells (p < 0.05). CHAC treatment significantly and concentration-dependently down-regulated the expressions of XIAP and survivin proteins (p < 0.05). Exposure of B16 F1 cells to CHAC significantly and concentration-dependently upregulated the expression of p-Mek 1/2, but down-regulated p-Erk 1/2 protein expression (p < 0.05). Densitometric analysis revealed that the expression of p-Mek 1/2 was increased from 12 to 91 %. Conclusion: The results of this study indicate that CHAC inhibits the proliferation of melanoma cells via upregulation of Mek 1/2 kinase activity, and therefore may find application in the management of melanoma

GTC: Guided Training of CTC Towards Efficient and Accurate Scene Text Recognition

Connectionist Temporal Classification (CTC) and attention mechanism are two main approaches used in recent scene text recognition works. Compared with attention-based methods, CTC decoder has a much shorter inference time, yet a lower accuracy. To design an efficient and effective model, we propose the guided training of CTC (GTC), where CTC model learns a better alignment and feature representations from a more powerful attentional guidance. With the benefit of guided training, CTC model achieves robust and accurate prediction for both regular and irregular scene text while maintaining a fast inference speed. Moreover, to further leverage the potential of CTC decoder, a graph convolutional network (GCN) is proposed to learn the local correlations of extracted features. Extensive experiments on standard benchmarks demonstrate that our end-to-end model achieves a new state-of-the-art for regular and irregular scene text recognition and needs 6 times shorter inference time than attentionbased methods.Comment: Accepted by AAAI 202

Expression of miR-126 and its potential function in coronary artery disease

Objective: This study aimed to explore the role of miR-126 in coronary artery disease (CAD) patients and the potential gene targets of miR-126 in atherosclerosis.Methodology: A total of 60 CAD patients and 25 healthy control subjects were recruited in this study. Among the 60 CAD patients, 18 cases were diagnosed of stable angina pectoris (SAP), 20 were diagnosed of unstable angina pectoris (UAP) and 22 were diagnosed of acute myocardial infarction (AMI). Plasma miR-126 levels from both groups of participants were analyzed by real-time quantitative PCR. ELISA was used to measure plasma level of placenta growth factor (PLGF).Results: The results showed that the miR-126 expression was significantly down-regulated in the circulation of CAD patients compared with control subjects (P<0.01). Plasma PLGF level was significantly upregulated in patients with unstable angina pectoris and acute myocardial infarction (AMI) compared with controls (both P<0.01) the miR-126 expression in AMI was significantly associated with PLGF.Conclusion: miR-126 may serve as a novel biomarker for CAD.Keywords: miR-126; PLGF; PCR; coronary artery disease; atherosclerosi

Identification of functional modules that correlate with phenotypic difference: the influence of network topology

A gene set enrichment analysis method for including network topology in the identification of genes involved in phenotypic alterations is described. Classifications: Genome studies, Method

Spin excitations in optimally P-doped BaFe2(As0.7P0.3)2superconductor

We use inelastic neutron scattering to study temperature and energy dependence of spin excitations in optimally P-doped BaFe2(As0.7P0.3)2 superconductor (Tc = 30 K) throughout the Brillouin zone. In the undoped state, spin waves and paramagnetic spin excitations of BaFe2As2 stem from antiferromagnetic (AF) ordering wave vector QAF= (1/-1,0) and peaks near zone boundary at (1/-1,1/-1) around 180 meV. Replacing 30% As by smaller P to induce superconductivity, low-energy spin excitations of BaFe2(As0.7P0.3)2form a resonance in the superconducting state and high-energy spin excitations now peaks around 220 meV near (1/-1,1/-1). These results are consistent with calculations from a combined density functional theory and dynamical mean field theory, and suggest that the decreased average pnictogen height in BaFe2(As0.7P0.3)2 reduces the strength of electron correlations and increases the effective bandwidth of magnetic excitations.Comment: 7 pages, 5 figures, with supplementar

Role of microRNA carried by small extracellular vesicles in urological tumors

Small extracellular vesicles (sEVs) are minute vesicles secreted by various cells that are capable of transporting cargo, including microRNAs, between donor and recipient cells. MicroRNAs (miRNAs), small non-coding RNAs approximately 22 nucleotides in length, have been implicated in a wide array of biological processes, including those involved in tumorigenesis. Emerging evidence highlights the pivotal role of miRNAs encapsulated in sEVs in both the diagnosis and treatment of urological tumors, with potential implications in epithelial-mesenchymal transition, proliferation, metastasis, angiogenesis, tumor microenvironment and drug resistance. This review provides a brief overview of the biogenesis and functional mechanisms of sEVs and miRNAs, followed by a summarization of recent empirical findings on miRNAs encapsulated in sEVs from three archetypal urologic malignancies: prostate cancer, clear cell renal cell carcinoma, and bladder cancer. We conclude by underscoring the potential of sEV-enclosed miRNAs as both biomarkers and therapeutic targets, with a particular focus on their detection and analysis in biological fluids such as urine, plasma, and serum