Evidence map›Paper›PMID 35071023›Full record

ArticleFrontiers in oncology2021

High Level of Aristolochic Acid Detected With a Unique Genomic Landscape Predicts Early UTUC Onset After Renal Transplantation in Taiwan.

Hong-Yue Lai, Li-Ching Wu, Po-Hsin Kong, Hsin-Hwa Tsai, Yen-Ta Chen, Yuan-Tso Cheng, Hao-Lun Luo, Chien-Feng Li

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. 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
1.0field-weighted citation impact, top 27% 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

10 citing papers in PubMed, 8 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

8 authors at 3 institutions in 1 country.

Hong-Yue LaiCenter for Precision Medicine, Chi Mei Medical Center, Tainan, Taiwan.
Li-Ching WuCenter for Precision Medicine, Chi Mei Medical Center, Tainan, Taiwan.
Po-Hsin KongCenter for Precision Medicine, Chi Mei Medical Center, Tainan, Taiwan.
Hsin-Hwa TsaiCenter for Precision Medicine, Chi Mei Medical Center, Tainan, Taiwan.
Yen-Ta ChenDepartment of Urology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Yuan-Tso ChengDepartment of Urology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Hao-Lun LuoDepartment of Urology, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung, Taiwan.
Chien-Feng LiCenter for Precision Medicine, Chi Mei Medical Center, Tainan, Taiwan.
Chi Mei Medical Center · TWChang Gung University · TWKaohsiung Chang Gung Memorial Hospital · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe unusual high dialysis prevalence and upper urinary tract urothelial carcinoma (UTUC) incidence in Taiwan may attribute to aristolochic acid (AA), which is nephrotoxic and carcinogenic, exposure. AA can cause a unique mutagenic pattern showing A:T to T:A transversions (mutational Signature 22) analyzed by whole exome sequencing (WES). However, a fast and cost-effective tool is still lacking for clinical practice. To address this issue, we developed an efficient and quantitative platform for the quantitation of AA and tried to link AA detection with clinical outcomes and decipher the genomic landscape of UTUC in Taiwan. PATIENTS AND

methodsWe recruited 61 patients with

resultsWe found that high level of 7-(deoxyadenosin-N

conclusionAccordingly, dA-AL-I detection can provide more direct evidence to AA exposure and serve as a more specific predictive and prognostic biomarker for patients with

Indexed as

aristolochic acidbiomarkerLC-MS/MSmTORrenal transplantationUTUC

Identifiers

PMID35071023
PMCPMC8770835
OpenAlexW4206325119

What OpenQuestion holds

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Registered trials

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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.