Evidence map›Paper›PMID 26677068›Full record

ArticleJournal of biomedical optics2015

Quantitative Raman spectral changes of the differentiation of mesenchymal stem cells into islet-like cells by biochemical component analysis and multiple peak fitting.

Xin Su, Shaoyin Fang, Daosen Zhang, Qinnan Zhang, Yingtian He, Xiaoxu Lu, Shengde Liu, Liyun Zhong

Open access · bronzeAbstract read
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In one paragraph

Article in Journal of biomedical optics, 2015. 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
0.3field-weighted citation impact, top 36% 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, 4 citations in OpenAlex.

  1. Review
  2. 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

8 authors at 1 institution in 1 country.

Xin Su
Shaoyin Fang
Daosen Zhang
Qinnan Zhang
Yingtian He
Xiaoxu Lu
Shengde Liu
Liyun Zhong
South China Normal University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mesenchymal stem cells (MSCs) differentiate into islet-like cells, providing a possible solution for type I diabetes treatment. To search for the precise molecular mechanism of the directional differentiation of MSC-derived islet-like cells, biomolecular composition, and structural conformation information during MSC differentiation, is required. Because islet-like cells lack specific surface markers, the commonly employed immunostaining technique is not suitable for their identification, physical separation, and enrichment. Combining Raman spectroscopic data, a fitting accuracy-improved biochemical component analysis, and multiple peaks fitting approach, we identified the quantitative biochemical and intensity change of Raman peaks that show the differentiation of MSCs into islet-like cells. Along with increases in protein and glycogen content, and decreases in deoxyribonucleic acid and ribonucleic acid content, in islet-like cells relative to MSCs, it was found that a characteristic peak of insulin (665  cm-1) has twice the intensity in islet-like cells relative to MSCs, indicating differentiation of MSCs into islet-like cells was successful. Importantly, these Raman signatures provide useful information on the structural and pathological states during MSC differentiation and help to develop noninvasive and label-free Raman sorting methods for stem cells and their lineages.

Indexed as

Spectrum Analysis, RamanCell DifferentiationCell LineageCell MembraneDNAGlycogenHumansImage Processing, Computer-AssistedInfant, NewbornInsulinIslets of LangerhansMesenchymal Stem CellsReproducibility of ResultsRNASoftwareUmbilical CordDNAGlycogenInsulinRNA

Identifiers

PMID26677068
OpenAlexW2204813387

What OpenQuestion holds

Textmetadata
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.