Evidence map›Paper›PMID 30460151›Full record

ArticleBiomedical optics express2018

Robot-assisted laser tissue soldering system.

Svetlana Basov, Amit Milstein, Erez Sulimani, Max Platkov, Eli Peretz, Marcel Rattunde, Joachim Wagner, Uri Netz, Abraham Katzir, Ilana Nisky

Abstract read
In one paragraph

Article in Biomedical optics express, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Cyanine-Doped Nanofiber Mats for Laser Tissue Bonding.Nanomaterials (Basel, Switzerland) · 2022
    Article
  8. Article
  9. Article
  10. Article
  11. 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

10 authors.

Svetlana BasovDepartment of Biomedical Engineering, Tel Aviv University, Tel Aviv, 6997801, Israel.
Amit MilsteinDepartment of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, 8410501, Israel.
Erez SulimaniDepartment of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, 8410501, Israel.
Max PlatkovNuclear Research Center Negev, Beer-Sheva, 84190, Israel.
Eli PeretzDepartment of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, 8410501, Israel.
Marcel RattundeFraunhofer-Institut für Angewandte Festkörperphysik, Freiburg, Germany.
Joachim WagnerFraunhofer-Institut für Angewandte Festkörperphysik, Freiburg, Germany.
Uri NetzDepartment of Surgery A, Soroka University Medical Center, Beer-Sheva, 85025, Israel.
Abraham KatzirSchool of Physics & Astronomy, Tel Aviv University, Tel Aviv, 6997801, Israel.
Ilana NiskyDepartment of Biomedical Engineering, Ben-Gurion University of the Negev, Beer-Sheva, 8410501, Israel.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Fast and reliable incision closure is critical in any surgical intervention. Common solutions are sutures and clips or adhesives, but they all present difficulties. These difficulties are especially pronounced in classical and robot-assisted minimally-invasive interventions. Laser soldering methods present a promising alternative, but their reproducibility is limited. We present a system that combines a previously reported laser soldering system with a robotic system, and demonstrate its feasibility on the incision-closure of ex-vivo mice skins. In this demonstration, we measured tearing forces of ~2.5N, 73% of the tearing force of a mouse skin without an incision. This robot-assisted laser soldering technique has the potential to make laser tissue soldering more reproducible and revolutionize surgical tissue bonding.

Identifiers

PMID30460151
PMCPMC6238920

What OpenQuestion holds

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Registered trials

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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.