Evidence map›Paper›PMID 37041446›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Immune Cell Lineage-Specific Chimerism Testing by Next-Generation Sequencing for Engraftment Monitoring After Allogeneic Hematopoietic Stem Cell Transplantation.

Cassie Wu, Thea Dela Cruz, Jack Lai, Denice Kong, Raja Rajalingam

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2023. 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
–field-weighted citation impact, top 89% 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, 0 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 1 institution in 1 country.

Cassie WuImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California San Francisco, San Francisco, CA, USA.
Thea Dela CruzImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California San Francisco, San Francisco, CA, USA.
Jack LaiImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California San Francisco, San Francisco, CA, USA.
Denice KongImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California San Francisco, San Francisco, CA, USA.
Raja RajalingamImmunogenetics and Transplantation Laboratory, Department of Surgery, University of California San Francisco, San Francisco, CA, USA. Rajalingam.raja@ucsf.edu.
University of California, San Francisco · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chimerism is an unusual state in which a person's body comprises cells from genetically different people. Chimerism testing allows monitoring for the relative proportion of recipient and donor-derived cell subsets in recipient blood and bone marrow. In the bone marrow transplant setting, chimerism testing is the standard diagnostic tool for early detection of graft rejection and the risk of malignant disease relapse. Chimerism testing enables the identification of patients with increased risk for recurrence of the underlying disease. Herein, we describe a step-by-step technical procedure of a novel, commercially available, next-generation sequencing-based chimerism testing method for use in the clinical laboratory.

Indexed as

ChimerismHematopoietic Stem Cell TransplantationBone Marrow TransplantationCell LineageHigh-Throughput Nucleotide SequencingHumansBone marrow transplantationChimerism testingGraft rejectionHematopoietic stem cell transplantationImmune monitoringMixed chimerismNext-generation sequencingPosttransplant engraftment monitoringRelapse

Identifiers

PMID37041446
OpenAlexW4364856104

What OpenQuestion holds

Textmetadata
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.