ArticleJournal of ophthalmic & vision research
An
Article in Journal of ophthalmic & vision research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed, 9 citations in OpenAlex.
- Review
- State-of-the-art techniques for imaging the vascular microenvironment in craniofacial bone tissue engineering applications.American journal of physiology. Cell physiology · 2022Review
- Systems Biology Approach for Identification of Essential Growth Factors in Retinal Regeneration.Journal of ophthalmic & vision researchArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeConsidering the significance of retinal disorders and the growing need to employ tissue engineering in this field,
methodsIn this study, a regeneration gene database was used. All 21 protein-coding genes participating in retinal regeneration were considered as a protein-protein interaction (PPI) network via the "STRING App" in "Cytoscape 3.7.2" software. The resultant graph possessed 21 nodes as well as 37 edges. Gene ontology (GO) analysis, as well as the centrality analysis, revealed the most effective proteins in retinal regeneration.
resultsAccording to the biological processes and the role of each protein in different pathways, selecting the correct one is possible through the information that the network provides. Eye development, detection of the visible light, visual perception, photoreceptor cell differentiation, camera-type eye development, eye morphogenesis, and angiogenesis are the major biological processes in retinal regeneration. Based on the GO analysis, SHH, STAT3, FGFR1, OPN4, ITGAV, RAX, and RPE65 are effective in retinal regeneration via the biological processes. In addition, based on the centrality analysis, four proteins have the greatest influence on retinal regeneration: SHH, IGF1, STAT3, and ASCL1.
conclusionWith the intention of applying the most impressive growth factors in retinal engineering, it seems logical to pay attention to SHH, STAT3, and RPE65. Utilizing these proteins can lead to fabricate high efficiency engineered retina via all aforementioned biological processes.
Indexed as
Identifiers
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.