Evidence map›Paper›PMID 36806998›Full record

ArticleThe AAPS journal2023

Novel Cell Quantification Method Using a Single Surrogate Calibration Curve Across Various Biological Samples.

Miyu Nakayama, Syunsuke Yamamoto, Hideki Hirabayashi

Open access · hybridAbstract read
PubMed Publisher
In one paragraph

Article in The AAPS journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 19% 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

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

3 authors at 1 institution in 1 country.

Miyu NakayamaDrug Metabolism and Pharmacokinetics Research Laboratories, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited, 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, Japan. miyu.nakayama@takeda.com.
Syunsuke YamamotoDrug Metabolism and Pharmacokinetics Research Laboratories, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited, 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, Japan.
Hideki HirabayashiDrug Metabolism and Pharmacokinetics Research Laboratories, Preclinical and Translational Sciences, Research, Takeda Pharmaceutical Company Limited, 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, Japan.
Takeda (Japan) · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative polymerase chain reaction (qPCR) is generally used to quantify transplanted cell therapy products in biological samples. As the matrix effects on PCR amplification and variability in DNA recovery from biological samples are well-known limitations that hinder the assay's performance, a calibration curve is conventionally established for each matrix. Droplet digital PCR (ddPCR) is based on the endpoint assay and advantageous in avoiding matrix effects. Moreover, the use of an external control gene may correct assay fluctuations to minimize the effects caused by inconsistent DNA recovery. In this study, we aimed to establish a novel and robust ddPCR method capable of quantifying human cells across various mouse biological samples using a single surrogate calibration curve in combination with an external control gene and DNA recovery normalization. Acceptable accuracy and precision were observed for quality control samples from different tissues, indicating the excellent quantitative and versatile potential of the developed method. Furthermore, the established method enabled the evaluation of human CD8

Indexed as

DNAAnimalsCalibrationHumansMicePolymerase Chain ReactionReal-Time Polymerase Chain ReactionTissue DistributionDNACell quantificationCell therapy productsddPCRLINE1Matrix effect

Identifiers

PMID36806998
OpenAlexW4321187434

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.