Rift Valley fever virus Gn V5-epitope tagged virus enables identification of UBR4 as a Gn interacting protein that facilitates Rift Valley fever virus production

Rift Valley fever virus (RVFV) is an arbovirus that was first reported in the Rift Valley of Kenya which causes significant disease in humans and livestock. RVFV is a tri-segmented, negative-sense RNA virus consisting of a L, M, and S segments with the M segment encoding the glycoproteins Gn and Gc. Host factors that interact with Gn are largely unknown.
To this end, two viruses containing an epitope tag (V5) on the Gn protein in position 105 or 229 (V5Gn105 and V5Gn229) were generated using the RVFV MP-12 vaccine strain as a backbone.
The V5-tag insertion minimally impacted Gn functionality as measured by replication kinetics, Gn localization, and antibody neutralization assays.
A proteomics-based approach was used to identify novel Gn-binding host proteins, including the E3 ubiquitin-protein ligase, UBR4. Depletion of UBR4 resulted in a significant decrease in RVFV titers and a reduction in viral RNA production.

The Dual Histone Deacetylase-Proteasome Inhibitor RTS-V5 Acts Synergistically With Ritonavir to Induce Endoplasmic Reticulum Stress in Bladder Cancer Cells

Background/aim: Simultaneous inhibition of histone deacetylase and proteasomes induces endoplasmic reticulum (ER) stress efficiently. RTS-V5 is the first dual histone deacetylase-proteasome inhibitor, and we anticipated that combining it with the cytochrome P450 family 3 subfamily A member 4 inhibitor ritonavir would enhance its activity in bladder cancer cells.
Materials and methods: Using bladder cancer cells (human T-24, J-82, murine MBT-2), we evaluated the ability and mechanism by which the combination of RTS-V5 and ritonavir induced ER stress and killed cancer cells.
Results: The combination of RTS-V5 and ritonavir triggered robust apoptosis and inhibited bladder cancer growth effectively in vitro and in vivo.
It caused ubiquitinated protein accumulation and induced ER stress synergistically. The combination inhibited the mammalian target of rapamycin pathway by increasing the expression of AMP-activated protein kinase. We also found that the combination caused histone and tubulin hyperacetylation.
Conclusion: Ritonavir enhances the ability of RTS-V5 to cause ER stress in bladder cancer cells.
Keywords: Histone deacetylase; endoplasmic reticulum stress; proteasome; ritonavir.

Ischemic ST-Segment Depression Maximal in V1-V4 (Versus V5-V6) of Any Amplitude Is Specific for Occlusion Myocardial Infarction (Versus Nonocclusive Ischemia)

Background Occlusion myocardial infarctions (OMIs) of the posterolateral walls are commonly missed by ST-segment-elevation myocardial infarction (STEMI) criteria, with >50% of patients with circumflex occlusion not receiving emergent reperfusion and experiencing increased mortality. ST-segment depression maximal in leads V1-V4 (STDmaxV1-4) has been suggested as an indicator of posterior OMI.
Methods and Results We retrospectively reviewed a high-risk population with acute coronary syndrome. OMI was defined from prior studies as a culprit lesion with TIMI (Thrombolysis in Myocardial Infarction) 0 to 2 flow or TIMI 3 flow plus peak troponin T >1.0 ng/mL or troponin I >10 ng/mL. STEMI was defined by the Fourth Universal Definition of Myocardial Infarction. ECGs were interpreted blinded to outcomes. Among 808 patients, there were 265 OMIs, 108 (41%) meeting STEMI criteria. A total of 118 (15%) patients had “suspected ischemic” STDmaxV1-4, of whom 106 (90%) had an acute culprit lesion, 99 (84%) had OMI, and 95 (81%) underwent percutaneous coronary intervention.
Suspected ischemic STDmaxV1-4 had 97% specificity and 37% sensitivity for OMI. Of the 99 OMIs detected by STDmaxV1-4, 34% had <1 mm ST-segment depression, and only 47 (47%) had accompanying STEMI criteria, of which 17 (36%) were identified a median 1.00 hour earlier by STDmaxV1-4 than STEMI criteria. Despite similar infarct size, TIMI flow, and coronary interventions, patients with STEMI(-) OMI and STDmaxV1-4 were less likely than STEMI(+) patients to undergo catheterization within 90 minutes (46% versus 68%; P=0.028).
Conclusions Among patients with high-risk acute coronary syndrome, the specificity of ischemic STDmaxV1-4 was 97% for OMI and 96% for OMI requiring emergent percutaneous coronary intervention. STEMI criteria missed half of OMIs detected by STDmaxV1-4. Ischemic STDmaxV1-V4 in acute coronary syndrome should be considered OMI until proven otherwise.

PhylomeDB V5: an expanding repository for genome-wide catalogues of annotated gene phylogenies

PhylomeDB is a unique knowledge base providing public access to minable and browsable catalogues of pre-computed genome-wide collections of annotated sequences, alignments and phylogenies (i.e. phylomes) of homologous genes, as well as to their corresponding phylogeny-based orthology and paralogy relationships.
In addition, PhylomeDB trees and alignments can be downloaded for further processing to detect and date gene duplication events, infer past events of inter-species hybridization and horizontal gene transfer, as well as to uncover footprints of selection, introgression, gene conversion, or other relevant evolutionary processes in the genes and organisms of interest. Here, we describe the latest evolution of PhylomeDB (version 5).
This new version includes a newly implemented web interface and several new functionalities such as optimized searching procedures, the possibility to create user-defined phylome collections, and a fully redesigned data structure.
This release also represents a significant core data expansion, with the database providing access to 534 phylomes, comprising over 8 million trees, and homology relationships for genes in over 6000 species.
This makes PhylomeDB the largest and most comprehensive public repository of gene phylogenies. PhylomeDB is available at http://www.phylomedb.org.
Application of local fully Convolutional Neural Network combined with YOLO v5 algorithm in small target detection of remote sensing image
This exploration primarily aims to jointly apply the local FCN (fully convolution neural network) and YOLO-v5 (You Only Look Once-v5) to the detection of small targets in remote sensing images.
Firstly, the application effects of R-CNN (Region-Convolutional Neural Network), FRCN (Fast Region-Convolutional Neural Network), and R-FCN (Region-Based-Fully Convolutional Network) in image feature extraction are analyzed after introducing the relevant region proposal network.
Secondly, YOLO-v5 algorithm is established on the basis of YOLO algorithm. Besides, the multi-scale anchor mechanism of Faster R-CNN is utilized to improve the detection ability of YOLO-v5 algorithm for small targets in the image in the process of image detection, and realize the high adaptability of YOLO-v5 algorithm to different sizes of images.
Finally, the proposed detection method YOLO-v5 algorithm + R-FCN is compared with other algorithms in NWPU VHR-10 data set and Vaihingen data set.
\The experimental results show that the YOLO-v5 + R-FCN detection method has the optimal detection ability among many algorithms, especially for small targets in remote sensing images such as tennis courts, vehicles, and storage tanks. Moreover, the YOLO-v5 + R-FCN detection method can achieve high recall rates for different types of small targets.

V5 (clone V5,E10)

AS15-3027 Agrisera AB 50 µg 259 EUR


MBS9217295-005mL MyBiosource 0.05mL 210 EUR


MBS9217295-02mL MyBiosource 0.2mL 430 EUR


MBS9217295-5x02mL MyBiosource 5x0.2mL 1910 EUR

V5 Antibody

20-abx118003 Abbexa
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V5 antibody

10R-10453 Fitzgerald 100 ug 451 EUR

V5 antibody

10R-10454 Fitzgerald 100 ug 451 EUR

V5 antibody

10R-10455 Fitzgerald 100 ug 451 EUR

V5 tag

E8ET1605-41 EnoGene 100ul 275 EUR


E8M1008-2 EnoGene 200ul 275 EUR

V5 Antibody

GWB-13B361 GenWay Biotech 0.1 mg Ask for price


PC-300 Kamiya Biomedical Company Polyclonal Ask for price


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T16805-10mg TargetMol Chemicals 10mg Ask for price
Furthermore, due to the deeper network architecture, the YOL v5 + R-FCN detection method has a stronger ability to extract the characteristics of image targets in the detection of remote sensing images.
Meanwhile, it can achieve more accurate feature recognition and detection performance for the densely arranged target images in remote sensing images. This research can provide reference for the application of remote sensing technology in China, and promote the application of satellites for target detection tasks in related fields.