Evidence map›Paper›PMID 37689821›Full record

ArticleCommunications biology2023

Smart-Plexer: a breakthrough workflow for hybrid development of multiplex PCR assays.

Luca Miglietta, Yuwen Chen, Zhi Luo, Ke Xu, Ning Ding, Tianyi Peng, Ahmad Moniri, Louis Kreitmann, Miguel Cacho-Soblechero, Alison Holmes and 2 more

Abstract read
In one paragraph

Article in Communications biology, 2023. 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
–field-weighted citation impact
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.

  1. Article
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  6. Review
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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

12 authors.

Luca MigliettaDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-6652-4785
Yuwen Chen *Department of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK.
Zhi Luo *Department of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK.ORCID http://orcid.org/0000-0002-7567-1082
Ke XuDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK.
Ning DingDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK.
Tianyi PengDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK.
Ahmad MoniriDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK.
Louis KreitmannDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK.
Miguel Cacho-SoblecheroDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK.
Alison HolmesDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK.
Pantelis GeorgiouDepartment of Electrical and Electronic Engineering, Faculty of Engineering, Imperial College London, London, UK.
Jesus Rodriguez-ManzanoDepartment of Infectious Disease, Faculty of Medicine, Imperial College London, London, UK. j.rodriguez-manzano@imperial.ac.uk.ORCID http://orcid.org/0000-0002-2583-8366

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing multiplex PCR assays requires extensive experimental testing, the number of which exponentially increases by the number of multiplexed targets. Dedicated efforts must be devoted to the design of optimal multiplex assays ensuring specific and sensitive identification of multiple analytes in a single well reaction. Inspired by data-driven approaches, we reinvent the process of developing and designing multiplex assays using a hybrid, simple workflow, named Smart-Plexer, which couples empirical testing of singleplex assays and computer simulation to develop optimised multiplex combinations. The Smart-Plexer analyses kinetic inter-target distances between amplification curves to generate optimal multiplex PCR primer sets for accurate multi-pathogen identification. In this study, the Smart-Plexer method is applied and evaluated for seven respiratory infection target detection using an optimised multiplexed PCR assay. Single-channel multiplex assays, together with the recently published data-driven methodology, Amplification Curve Analysis (ACA), were demonstrated to be capable of classifying the presence of desired targets in a single test for seven common respiratory infection pathogens.

Indexed as

Biological AssayMultiplex Polymerase Chain ReactionComputer SimulationKineticsWorkflow

Identifiers

PMID37689821
PMCPMC10492832

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.