ArticleMembranes2022
Characterization of Electrospun Poly(ε-caprolactone) Nano/Micro Fibrous Membrane as Scaffolds in Tissue Engineering: Effects of the Type of Collector Used.
Article in Membranes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
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
Electrospinning is an electrohydrodynamic technique that transforms a polymer solution into nano/microscopic diameter fibers under the influence of a high-voltage electric field. Its use in the fabrication of nano/micro fibrous membranes as scaffolds for tissue engineering has increased rapidly in recent years due to its efficiency and reproducibility. The objective of this study is to show how the use of the same polymeric solution (polycaprolactone 9%
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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.