Evidence map›Paper›PMID 24086175›Full record

ArticleJournal of biomedical research2013

Preparation and application of polyclonal antibodiesagainst KSHV v-cyclin.

Min Xue, Yuanyuan Guo, Qin Yan, Di Qin, Chun Lu

Open access · hybridAbstract read
In one paragraph

Article in Journal of biomedical research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 33% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors at 3 institutions in 1 country.

Min XueDepartment of Microbiology and Immunology, Nanjing Medical University, Nanjing 210029, P. R. China; ; Department of Physiology, Xuzhou Medical College, Xuzhou, Jiangsu, 221000, P. R. China; Jiangsu 223300, China.
Yuanyuan Guo
Qin Yan
Di Qin
Chun Lu
Nanjing Medical University · CNXuzhou Medical College · CNJiangsu University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We prepared rabbit polyclonal antibodies against Kaposi's sarcoma-associated herpesvirus (KSHV)-encoded v-cyclin (ORF 72) and detected the natural viral protein using these polyclonal antibodies. Three antigenic polypeptides of v-cyclin were designed and synthesized. A fragment of the v-cyclin gene was cloned into a eukaryotic expression vector pEF-MCS-Flag-IRES/Puro to construct a recombinant vector, pEF v-cyclin. Then, pEF v-cyclin was transfected into 293T and EA.hy926 cells to obtain v-cyclin-Flag fusion proteins. Six New Zealand white rabbits were immunized with KLH-conjugated peptides to generate polyclonal antibodies against v-cyclin. The polyclonal antibodies were then characterized by ELISA and Western blotting assays. Finally, the polyclonal antibodies against v-cyclin were used to detect natural viral protein expressed in BCBL-1, BC-3, and JSC-1 cells. The results showed that using the Flag antibody, v-cyclin-Flag fusion protein was detected in 293T and EA.hy926 cells transfected with pEF-v-cyclin. Furthermore, ELISA showed that the titer of the induced polyclonal rabbit anti-v-cyclin antibodies was higher than 1:8,000. In Western blotting assays, the antibodies reacted specifically with the v-cyclin-Flag fusion protein as well as the natural viral protein. The recombinant expression vector pEF-v-cyclin was constructed successfully, and the polyclonal antibodies prepared can be used for various biological tests including ELISA and Western blotting assays.

Indexed as

Kaposi's sarcoma-associated herpesviruspolyclonal antibodysynthesized peptidesv-cyclin

Identifiers

PMID24086175
PMCPMC3783827
OpenAlexW2022333350

What OpenQuestion holds

Textmetadata
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.