Evidence map›Paper›PMID 29101709›Full record

ArticleLasers in medical science2018

Laser-induced autofluorescence-based objective evaluation of burn tissue repair in mice.

Bharath Rathnakar, Bola Sadashiva Satish Rao, Vijendra Prabhu, Subhash Chandra, Krishna Kishore Mahato

Abstract read
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In one paragraph

Article in Lasers in medical science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

2 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
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

5 authors at 1 institution in 1 country.

Bharath RathnakarDepartment of Biophysics, School of Life Sciences, Manipal University, Manipal, Karnataka, 576104, India.
Bola Sadashiva Satish RaoDepartment of Radiation Biology and Toxicology, School of Life Sciences, Manipal University, Manipal, Karnataka, 576104, India.
Vijendra PrabhuDepartment of Biophysics, School of Life Sciences, Manipal University, Manipal, Karnataka, 576104, India.
Subhash ChandraDepartment of Biophysics, School of Life Sciences, Manipal University, Manipal, Karnataka, 576104, India.
Krishna Kishore MahatoDepartment of Biophysics, School of Life Sciences, Manipal University, Manipal, Karnataka, 576104, India. mahato.kk@manipal.edu.
Manipal Academy of Higher Education · IN

Funding

Board of Research in Nuclear Sciences 2012/34/47
6 · The paper itself

Abstract

Management of burn injuries are a growing concern, especially in determining the progression of healing. Several techniques are being practiced in clinics and have been considered all-time standard approaches to determine pre- and post-treatment outcomes of a healthy healing. However, these kinds of methods involve repeated biopsies and thereby hindering tissue repair. In view of this, our perspective was to develop a non-invasive tool in an attempt to provide a solution to determine the progression of healing, in vivo. Hence, the present study was designed to investigate the ability of laser-induced fluorescence (LIF) to monitor the variations in collagen intensity at various time points (0, 2, 6, 12, 18, 24, and 30 days) during burn tissue repair in mice, post low-power laser therapy (LPLT). The spectral findings demonstrated a significant change in collagen intensity as observed on day 24 (p < 0.05) and 30 (p < 0.01), when treated with LPLT (830 nm 3 J/cm

Indexed as

LasersWound HealingAnimalsArea Under CurveBurnsCollagenFemaleMaleMiceSpectrometry, FluorescenceCollagenAutofluorescenceBurnsCollagenLow-power laser therapyWound healing

Identifiers

PMID29101709
OpenAlexW2765511209

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.