ArticleTranslational neuroscience2018
Photobiomodulation Optimization for Spinal Cord Injury Rat Phantom Model.
Article in Translational neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled 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.
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, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Review of light parameters and photobiomodulation efficacy: dive into complexity.Journal of biomedical optics · 2018Pooled it
- Therapeutic Potential of Photobiomodulation in Early Recovery After Experimental Spinal Cord Injury in Rats: Histological and Biomechanical Analysis.Journal of biophotonics · 2026Article
- Effects of wavelength and spinal cord injury segment on photobiomodulation efficacy: Monte Carlo simulation in a rat model.Journal of biomedical optics · 2025Article
- Effects of photobiomodulation on different application points and different phases of complex regional pain syndrome type I in the experimental model.The Korean journal of pain · 2021Article
- In vivo, noncontact, real-time, PV[O]H imaging of the immediate local physiological response to spinal cord injury in a rat model.Journal of biomedical optics · 2019Article
- Optimization of photobiomodulation therapy for spinal cord injury: A review.Photochemistry and photobiologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Spinal Cord Injury (SCI) causes interruption along the severed axonal tract(s) resulting in complete or partial loss of sensation and motor function. SCI can cause tetraplegia or paraplegia. Both these conditions can have lifelong excessive medical costs, as well as can reduce life expectancy. Preclinical research showed that Photobiomodulation therapy (PBMT), also known as Low-level laser (light) therapy (LLLT), possesses reparative and regenerative capabilities that have the potential to be used as a complimentary or supplementary SCI therapy. Despite the promising effects of PBMT, there are still no standardized irradiation parameters (i.e. different wavelengths, power, fluence, irradiance, beam type, beam diameters, and irradiation time) and there is also a lack of standardized experimental protocol(s), which makes it difficult to compare different studies. It is, nonetheless, essential to standardize such irradiation parameters in order to provide better PBMTs. The aim of this study, therefore, is to evaluate the delivery of light in a 3D voxelated SCI rat model for PBMT using different irradiation parameters (wavelengths: 660, 810, and 980 nm; beam types: Gaussian and Flat beam; and beam diameters: 0.04-1.2 cm) using Monte Carlo simulation. This study also aids in providing standardization for preclinical research for PBMT, which will eventually translate into clinical standardization upon clinical research studies and results.
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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.