Evidence map›Paper›PMID 36447523›Full record

ArticleOpen medicine (Warsaw, Poland)2022

Amino acid profiles in the tissue and serum of patients with liver cancer.

Da-Hua Liu, Gui-Min Wen, Chang-Liang Song, Li-Jun Ji, Pu Xia

Open access · goldAbstract read
In one paragraph

Article in Open medicine (Warsaw, Poland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.6field-weighted citation impact, top 35% 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

2 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Review
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 2 institutions in 1 country.

Da-Hua LiuBiological Anthropology Institute, Jinzhou Medical University, Jinzhou, Liaoning, P.R. China.
Gui-Min WenDepartment of Basic Nursing, College of Nursing, Jinzhou Medical University, Jinzhou, Liaoning, P.R. China.
Chang-Liang SongDepartment of Radiotherapy, Center Hospital of Handan, Handan, Hebei, P.R. China.
Li-Jun JiOffice of Library, Jinzhou Medical University, Jinzhou, Liaoning, P.R. China.
Pu XiaBiological Anthropology Institute, Jinzhou Medical University, Jinzhou, Liaoning, P.R. China.
Jinzhou Medical University · CNHandan College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Most patients with liver cancer were found late and lost the chance of surgery. Liquid biopsy can monitor the risk of tumor recurrence and metastasis, quickly evaluate the curative effect of tumor treatment, and is conducive to early screening and auxiliary diagnosis of high-risk groups. Amino acid (AA) profiling has been used to the diagnosis and the prognosis for cancers. However, little was known about the profiles of AA of liver cancer. In this study, we used tRNA in Cancer database to analyze the AA levels in liver cancer tissues. Blood samples of patients with liver cancer were collected and analyzed using the automatic AA analyzer. We found that valine, isoleucine, and leucine were decreased significantly both in the plasma and the tumor tissues of patients with liver cancer. However, upregulation of methionine was observed in tissues and plasma of patients with liver cancer. Interestingly, tyrosine, and phenylalanine were decreased in tumor tissue but increased in the plasma of patients with liver cancer. This is the first report provided an overview of AA profile in both plasma and tissue for patients with liver cancer. AA levels can be used as diagnostic and prognostic markers of patients with liver cancer.

Indexed as

amino acidliquid biopsyliver cancermetabolismprognosis

Identifiers

PMID36447523
PMCPMC9675036
OpenAlexW4310595370

What OpenQuestion holds

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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.