Evidence map›Paper›PMID 39318477›Full record

ArticleClinical, cosmetic and investigational dermatology2024

Efficacy of 1060 nm Diode Laser for Non-Invasive Subcutaneous Fat Reduction in Mini-Pigs.

Yea-Jin Lee, Namgue Hong, Eun Seo Choi, Sun-Hyang Choi, Eun Young Kim, Hyeong Ju Park, Jin-Chul Ahn

Abstract read
In one paragraph

Article in Clinical, cosmetic and investigational dermatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

7 authors.

Yea-Jin LeeDepartment of Medicine, Dankook University, Cheonan-si, 31116, Republic of Korea.
Namgue HongMedical Laser Research Center, Graduate School of Medicine, Dankook University, Cheonan-si, 31116, Republic of Korea.
Eun Seo ChoiDepartment of Physics, Chosun University, Gwangju, 61452, Republic of Korea.
Sun-Hyang ChoiMedical Laser Research Center, Graduate School of Medicine, Dankook University, Cheonan-si, 31116, Republic of Korea.
Eun Young KimMedical Laser Research Center, Graduate School of Medicine, Dankook University, Cheonan-si, 31116, Republic of Korea.
Hyeong Ju ParkBio&Health Photonics Research Center, Korea Photonics Technology Institute, Gwangju, 61007, Republic of Korea.
Jin-Chul AhnDepartment of Medicine, Dankook University, Cheonan-si, 31116, Republic of Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: To evaluate the efficacy and safety of abdominal fat reduction in mini-pigs, utilizing at 1060 nm diode laser with a wavelength of 1060 nm. Patients and Methods: The laser system non-invasively disrupts adipose tissue; its effectiveness and safety were evaluated by ultrasound imaging and histological analysis. Laser irradiation was performed with various powers, and the cooling function was activated to prevent skin surface damage. Results: The dermal tissue temperature increased to at least 43°C during laser exposure, leading to a decrease in abdominal fat thickness after 30 days. Blood tests revealed no significant changes in kidney and liver function but showed increased blood levels of nonessential free acids (NEFAs), likely due to the release of fatty tissue-derived free fatty acids. Histological evaluation demonstrated rapid transformation of adipose tissue into collagen, muscle fibers, and intracellular fibrous tissue. Conclusion: The 1060 nm laser showed promise as a non-invasive and safe tool for reducing abdominal fat.

Indexed as

abdominaldiode laserfatnon-invasivepreclinical

Identifiers

PMID39318477
PMCPMC11421435

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.