Evidence map›Paper›PMID 41200975›Full record

ArticleSe pu = Chinese journal of chromatography2025

[Undergraduate innovation training experiment: zooarchaeology by mass spectrometry for species identification of paleontological remnants].

Yang Xu, Li-Yan Jiang, Sha-Sha Yang

Abstract readEnglish Abstract
In one paragraph

Article in Se pu = Chinese journal of chromatography, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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.

Yang XuCollege of Life Sciences,Jilin University,Changchun 130012,China.
Li-Yan JiangCollege of Life Sciences,Jilin University,Changchun 130012,China.
Sha-Sha YangCollege of Life Sciences,Jilin University,Changchun 130012,China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Against the educational backdrop of deep interdisciplinary integration and empowering new models for cultivating composite talents, this innovative training experiment focuses on the hot interdisciplinary field of molecular archaeology, targeting the fragmented state of paleontological remains that do not have morphological identification characteristics and cannot be accurately identified for species. We developed a zooarchaeology by mass spectrometry (ZooMS) method based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), utilizing collagen peptide mass fingerprinting (PMF). This approach was successfully applied to species identification of late pleistocene fragmented paleontological samples. ZooMS offers significant advantages including operational simplicity, high identification accuracy, broad applicability, low testing costs, high-throughput analysis and stringent contamination control, making it highly valuable for species identification and the extraction of "hidden information" from fragmented paleontological remains. Through this innovation training experiment, we enhanced interdisciplinary collaboration between humanities and sciences, stimulated students' scientific thinking, and improved their research competencies, laying a solid foundation for cultivating interdisciplinary and innovative talents.

Indexed as

ArchaeologyFossilsPaleontologySpectrometry, Mass, Matrix-Assisted Laser Desorption-IonizationAnimalsHumansinnovation training experimentmatrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)paleontology remnantsspecies identificationzooarchaeology by mass spectrometry (ZooMS)

Identifiers

PMID41200975
PMCPMC12598550

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.