Evidence map›Paper›PMID 23484120›Full record

ArticleBioMed research international2013

Conformation-dependent high-affinity potent ricin-neutralizing monoclonal antibodies.

Wei-Gang Hu, Junfei Yin, Damon Chau, Charles Chen Hu, Dustin Lillico, Justin Yu, Laurel M Negrych, John W Cherwonogrodzky

Open access · hybridAbstract read
In one paragraph

Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

10 citing papers in PubMed, 18 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Wei-Gang HuDefence Research and Development Canada-Suffield, P.O. Box 4000, Station Main, Medicine Hat, AB, Canada T1A 8K6. wei-gang.hu@drdc-rddc.gc.ca
Junfei Yin
Damon Chau
Charles Chen Hu
Dustin Lillico
Justin Yu
Laurel M Negrych
John W Cherwonogrodzky
Defence Research and Development Canada · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ricin is a potential biothreat agent with no approved antidote available for ricin poisoning. The aim of this study was to develop potent antibody-based antiricin antidotes. Four strong ricin resistant hybridoma clones secreting antiricin monoclonal antibodies (mAbs) were developed. All four mAbs are bound to conformational epitopes of ricin toxin B (RTB) with high affinity (KD values from 2.55 to 36.27 nM). RTB not only triggers cellular uptake of ricin, but also facilitates transport of the ricin toxin A (RTA) from the endoplasmic reticulum to the cytosol, where RTA exerts its toxic activity. The four mAbs were found to have potent ricin-neutralizing capacities and synergistic effects among them as determined by an in vitro neutralization assay. In vivo protection assay demonstrated that all four mAbs had strong efficacy against ricin challenges. D9 was found to be exceptionally effective. Intraperitoneal (i.p.) administration of D9, at a dose of 5 μ g, 6 weeks before or 6 hours after an i.p. challenge with 5 × LD50 of ricin was able to protect or rescue 100% of the mice, indicating that mAb D9 is an excellent candidate to be developed as a potent antidote against ricin poisoning for both prophylactic and therapeutic purposes.

Indexed as

Antibody AffinityAnimalsAntibodies, Monoclonal, Murine-DerivedAntibodies, NeutralizingAntitoxinsEpitopesFemaleMiceMice, Inbred BALB CProtein Structure, TertiaryRicinAntibodies, Monoclonal, Murine-DerivedAntibodies, NeutralizingAntitoxinsEpitopesRicin

Identifiers

PMID23484120
PMCPMC3591125
OpenAlexW1991173050

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.