Evidence map›Paper›PMID 33572335›Full record

ArticleBiology2021

Modeling of Old Scars: Histopathological, Biochemical and Thermal Analysis of the Scar Tissue Maturation.

Alexey Fayzullin, Natalia Ignatieva, Olga Zakharkina, Mark Tokarev, Daniil Mudryak, Yana Khristidis, Maxim Balyasin, Alexandr Kurkov, Semyon Churbanov, Tatyana Dyuzheva and 3 more

Abstract read
In one paragraph

Article in Biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

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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

13 authors.

Alexey FayzullinLaboratory of Experimental Morphology, Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.
Natalia IgnatievaChemistry Department, Lomonosov Moscow State University, Leninskiye Gory 1-3, Moscow 119991, Russia.
Olga ZakharkinaInstitute of Photon Technologies, Federal Scientific Research Centre "Crystallography and Photonics" of Russian Academy of Sciences, 2 Pionerskaya st., Troitsk, Moscow 142190, Russia.
Mark TokarevSklifosovsky Institute for Clinical Medicine, Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.
Daniil MudryakSklifosovsky Institute for Clinical Medicine, Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.ORCID 0000-0002-6570-3909
Yana KhristidisWorld-Class Research Center "Digital Biodesign and Personalized Healthcare", Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.
Maxim BalyasinLaboratory of Experimental Morphology, Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.
Alexandr KurkovLaboratory of Experimental Morphology, Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.
Semyon ChurbanovInstitute of Photon Technologies, Federal Scientific Research Centre "Crystallography and Photonics" of Russian Academy of Sciences, 2 Pionerskaya st., Troitsk, Moscow 142190, Russia.ORCID 0000-0003-3549-5683
Tatyana DyuzhevaSklifosovsky Institute for Clinical Medicine, Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.
Peter TimashevChemistry Department, Lomonosov Moscow State University, Leninskiye Gory 1-3, Moscow 119991, Russia.
Anna GullerLaboratory of Experimental Morphology, Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.ORCID 0000-0002-8866-9838
Anatoly ShekhterLaboratory of Experimental Morphology, Institute for Regenerative Medicine, Sechenov First Moscow State Medical University (Sechenov University), 8-2 Trubetskaya st., Moscow 119991, Russia.

Funding

A STATE ASSIGNMENT 0082-2019-0012 State registration number АААА-А20-120021190043-7RUSSIAN ACADEMIC SCIENCE EXCELLENCE PROJECT "5-100"Russian Foundation for Basic Research 19-315-90058THE SCHOLARSHIP OF THE PRESIDENT OF THE RUSSIAN FEDERATION (awardee: A. Fayzullin)
6 · The paper itself

Abstract

Mature hypertrophic scars (HSs) remain a challenging clinical problem, particularly due to the absence of biologically relevant experimental models as a standard rabbit ear HS model only reflects an early stage of scarring. The current study aims to adapt this animal model for simulation of mature HS by validating the time of the scar stabilization using qualitative and quantitative criteria. The full-thickness skin and perichondrium excision wounds were created on the ventral side of the rabbit ears. The tissue samples were studied on post-operation days (PODs) 30, 60, 90 and 120. The histopathological examination and morphometry were applied in parallel with biochemical analysis of protein and glycosaminoglycans (GAGs) content and amino acid composition. The supramolecular organization of collagen was explored by differential scanning calorimetry. Four stages of the rabbit ear HS maturation were delineated and attributed with the histolomorphometrical and physicochemical parameters of the tissue. The experimental scars formed in 30 days but stabilized structurally and biochemically only on POD 90-120. This evidence-based model can be used for the studies and testing of new treatments of the mature HSs.

Indexed as

animal modelcollagenhypertrophic scarquantitative histopathologyscar maturationscarring

Identifiers

PMID33572335
PMCPMC7916157

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.