Evidence map›Paper›PMID 31955538›Full record

ArticleZhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences2019

[Effect of genipin pretreatment on type Ⅰ collagen mineralization].

Tianyi Gu, Jing Shuai, Chaoqun Chen, Jianying Feng

Open access · greenAbstract read
In one paragraph

Article in Zhejiang da xue xue bao. Yi xue ban = Journal of Zhejiang University. Medical sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 81% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 1 country.

Tianyi GuSchool of Stomatology, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Jing ShuaiSchool of Stomatology, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Chaoqun ChenDepartment of Stomatology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310003, China.
Jianying FengSchool of Stomatology, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Zhejiang Chinese Medical University · CNFirst Affiliated Hospital Zhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo investigate the effects of bio-crosslinker genipin pretreatment on type Ⅰ collagen mineralization.

methodsType Ⅰ collagen gels were prepared and pretreated with 0.5wt%genipin (experimental group) and deionized water (control group) for 2 h, respectively. The pretreated products were subjected to Fourier transform infrared spectroscopy (FT-IR). Reconstituted collagen fibrils were pretreated with genipin or deionized water for 2 h and were mineralized for 4 h. The collagen density and mineralization degree were examined with transmission electron microscopy (TEM) and analyzed with ImageJ software. Then scanning electron microscopy (SEM) and TEM were used to observe the mineralization of cross-linked demineralized dentin collagen.

resultsFT-IR spectrum showed that the genipin was crosslinked with collagen. TEM observation and ImageJ results showed that after 4 h mineralization, the mineralization effect of 0.5wt% genipin group was significantly better than that of the control group[(73.3±5.3)%vs.(7.4±3.5)%,

conclusionsThe study demonstrates that 0.5 wt% concentration of genipin can significantly promote the mineralization of type Ⅰ collagen.

Indexed as

Collagen Type IIridoidsMicroscopy, Electron, ScanningMicroscopy, Electron, TransmissionSpectroscopy, Fourier Transform InfraredCollagen Type IgenipinIridoids

Identifiers

PMID31955538
PMCPMC8800766
OpenAlexW3005576132

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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.