Evidence map›Paper›PMID 38348590›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2024

Fast Label-Free Metabolic Profile Recognition Identifies Phenylketonuria and Subtypes.

Haiyang Su, Huiwen Zhang, Jiao Wu, Lin Huang, Mengji Zhang, Wei Xu, Jing Cao, Wanshan Liu, Ning Liu, Hongwei Jiang and 2 more

Open access · goldAbstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

4 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Fast Label-Free Metabolic Profile Recognition Identifies Phenylketonuria and Subtypes.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  4. 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

12 authors at 2 institutions in 1 country.

Haiyang SuHenan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, 471003, P. R. China.
Huiwen ZhangXinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, P. R. China.
Jiao WuState Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Lin HuangCountry Department of Clinical Laboratory Medicine, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Mengji ZhangState Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Wei XuState Key Laboratory for Oncogenes and Related Genes, Division of Cardiology, Renji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200127, P. R. China.
Jing CaoState Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.
Wanshan LiuXinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, P. R. China.
Ning LiuSchool of Electronics Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, P. R. China.
Hongwei JiangHenan Key Laboratory of Rare Diseases, Endocrinology and Metabolism Center, The First Affiliated Hospital, and College of Clinical Medicine of Henan University of Science and Technology, Luoyang, 471003, P. R. China.
Xuefan GuXinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200092, P. R. China.
Kun QianState Key Laboratory of Systems Medicine for Cancer, School of Biomedical Engineering, Institute of Medical Robotics and Shanghai Academy of Experimental Medicine, Shanghai Jiao Tong University, Shanghai, 200030, P. R. China.ORCID 0000-0003-1666-1965
Shanghai Jiao Tong University · CNFirst Affiliated Hospital of Henan University of Science and Technology · CN

Funding

Society for Epidemiologic Research Doctoral Dissertation WorkshopR13TR002021 · NCATS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI HARLOW, BERNARD L · 2017 to 2018
$46k
China Postdoctoral Science Foundation BX2021182Innovative Research Team of High-Level Local Universities in Shanghai SHSMU-ZDCX20210700Medical-Engineering Joint Funds of Shanghai Jiao Tong University YG2021ZD09Medical-Engineering Joint Funds of Shanghai Jiao Tong University YG2022QN107Medical-Engineering Joint Funds of Shanghai Jiao Tong University YG2023ZD08Medical-Engineering Joint Funds of Shanghai Jiao Tong University YG2024ZD07National Key R&D Program of China 2022YFE0103500National Research Center for Translational Medicine Shanghai NRCTM(SH)-2021-06National Research Center for Translational Medicine Shanghai TMSK-2021-124Science and Technology Commission of Shanghai Municipality 20DZ2220400Shanghai Institutions of Higher Learning 2021-01-07-00-02-E00083Shanghai Jiao Tong University Inner Mongolia Research Institute 2022XYJG0001-03-0Shanghai Municipal Education Commission ZXWF082101Shanghai Municipal Health Commission 2019CXJQ03Shanghai Municipal Health Commission 202240361Shanghai Municipal Health Commission 2022JC013
6 · The paper itself

Abstract

Phenylketonuria (PKU) is the most common inherited metabolic disease in humans. Clinical screening of newborn heel blood samples for PKU is costly and time-consuming because it requires multiple procedures, like isotope labeling and derivatization, and PKU subtype identification requires an additional urine sample. Delayed diagnosis of PKU, or subtype identification can result in mental disability. Here, plasmonic silver nanoshells are used for laser desorption/ionization mass spectrometry (MS) detection of PKU with label-free assay by recognizing metabolic profile in dried blood spot (DBS) samples. A total of 1100 subjects are recruited and each DBS sample can be processed in seconds. This platform achieves PKU screening with a sensitivity of 0.985 and specificity of 0.995, which is comparable to existing clinical liquid chromatography MS (LC-MS) methods. This method can process 360 samples per hour, compared with the LC-MS method which processes only 30 samples per hour. Moreover, this assay enables precise identification of PKU subtypes without the need for a urine sample. It is demonstrated that this platform enables high-performance and fast, low-cost PKU screening and subtype identification. This approach might be suitable for the detection of other clinically relevant biomarkers in blood or other clinical samples.

Indexed as

PhenylketonuriasHumansInfant, NewbornLiquid Chromatography-Mass SpectrometryMetabolomediagnosismass spectrometrymetabolic profilephenylketonuriasubtype identification

Identifiers

PMID38348590
PMCPMC11022714
OpenAlexW4391785436

What OpenQuestion holds

Textmetadata
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.