Evidence map›Paper›PMID 18957310›Full record

ArticleHuman immunology2008

Structurally based epitope analysis of major histocompatibility complex class I-related chain A (MICA) antibody specificity patterns.

Rene J Duquesnoy, Justin Mostecki, Jayasree Hariharan, Ivan Balazs

Abstract read
In one paragraph

Article in Human immunology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.1field-weighted citation impact, top 22% 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

9 citing papers in PubMed, 31 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

4 authors at 1 institution in 1 country.

Rene J DuquesnoyUniversity of Pittsburgh Medical Center, Pittsburgh, PA, USA. duquesnoyr@upmc.edu
Justin Mostecki
Jayasree Hariharan
Ivan Balazs
University of Pittsburgh Medical Center · US

Funding

HLAMatchmaker for Transplantation and TransfusionR01AI055933 · NIAID · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI DUQUESNOY, RENE J · 2003 to 2007
$1.3M
NIAID NIH HHS AI-55933NIAID NIH HHS R01 AI055933
6 · The paper itself

Abstract

Recent studies have suggested a clinical significance to the detection of anti-major histocompatibility complex class I-related chain A (MICA) antibodies in transplantation. We have developed an eplet-based version of the HLAMatchmaker algorithm to assess the epitope specificity of these antibodies. Molecular viewing of the MICA structure and the determination of amino acid sequence differences between MICA alleles has yielded a repertoire of 38 potentially immunogenic MICA eplets. These eplets are based on the functional epitope structure that considers a configuration of amino acids within a 3-Angstrom radius of an antibody-accessible polymorphic residue on the molecular surface. In this study MICA-reactive sera were screened in Luminex assays with single MICA allele panels and analyzed with HLAMatchmaker. We identified reactivity patterns that correspond to eplet-specific antibodies to identify of unacceptable MICA mismatches including those alleles that have not been tested with the serum. In conclusion, HLAMatchmaker is a useful algorithm to analyze the reactivity patterns of anti-MICA antibodies and the determination of MICA mismatch acceptability at the structural level.

Indexed as

AlgorithmsAntibody SpecificityEpitope MappingEpitopesAntigen PresentationGraft RejectionHistocompatibility Antigens Class IHistocompatibility TestingHumansIsoantibodiesOrgan TransplantationPeptidesProtein BindingStructure-Activity RelationshipTransplantation ImmunologyEpitopesHistocompatibility Antigens Class IIsoantibodiesMHC class I-related chain AMICB antigenPeptides

Identifiers

PMID18957310
PMCPMC2636556
OpenAlexW2143428933

What OpenQuestion holds

Textmetadata
LicenceTDM
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.