ArticleMethodsX2018
Development of tensile strength methodology for murine skin wound healing.
Article in MethodsX, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- AI-Guided 4D Printing of Carnivorous Plants-Inspired Microneedles for Accelerated Wound Healing.Advanced materials (Deerfield Beach, Fla.) · 2026Article
- A Novel Murine Model for Studying Impaired Wound Healing in Diabetes.International wound journal · 2026Article
- Bioactive nanomaterials kickstart early repair processes and potentiate temporally modulated healing of healthy and diabetic wounds.Biomaterials · 2024Article
- Bigel Formulations of Nanoencapsulated St. John's Wort Extract-An Approach for Enhanced Wound Healing.Gels (Basel, Switzerland) · 2023Article
- Combined injury: irradiation with skin or bone wounds in rodent models.Journal of radiological protection : official journal of the Society for Radiological Protection · 2021Article
- Wound healing after excision of subcutaneous tumors treated with near-infrared photoimmunotherapy.Cancer medicine · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
In this study, a methodology was evaluated and improved to quickly measure the tensile strength of murine skin in a biomechanical assay for an incisional wound healing model. The aim was to streamline and enhance the wound model, skin specimen preparation, and tensile test so that large numbers of fresh tissue could be tested reliably and rapidly. Linear incisions of 25-mm length were made in the dorsal skin of mice along the spine and metallic staples were used to close the wound. After 20 days, the mice were sacrificed, and a square-shaped section of skin containing the linear incision was excised. Two metallic punches were fabricated and used to punch 15-mm long strips of skin of 2 mm width whose length was orthogonal to the direction of incision. The tensiometer configuration was modified to expedite tensile measurements on fresh skin, and load-to-failure was measured for each strip of skin from the cephalad to the caudal region. We evaluated sources of error in the animal model and the testing protocol and developed procedures to maximize speed and reproducibility in tensile strength measurements. This report provides guidance for efficient and reproducible tensile strength measurement of large numbers of skin specimens from freshly sacrificed animals. •Tattoo placement to identify the two ends of the healing incisional wound assisted in decreasing error in the position and orientation of tensile strips.•Custom-made punches to prepare skin strips for tensile testing helped conduct tensile tests of fresh tissue rapidly.•Alteration of the manual grips of the tensile tester enabled specimens to be gripped rapidly to significantly accelerate testing for each skin strip.
Indexed as
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What OpenQuestion holds
Registered trials
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.