Evidence map›Paper›PMID 42733250›Full record

ArticleJournal of biophotonics2026

Laser Tissue Welding of Esophageal Tissue Assisted by Chitosan-Based Precoating: Process Optimization and Thermal-Mechanical Performance.

Jun Huang, Hui Jiang, Xijing Yan, Mintao Yan, Jincheng Li, Kehong Wang

Abstract read
In one paragraph

Article in Journal of biophotonics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

6 authors.

Jun HuangSchool of Material Science and Technology, Nanjing University of Science and Technology, Nanjing, China.ORCID https://orcid.org/0000-0001-5058-7004
Hui JiangSchool of Material Science and Technology, Nanjing University of Science and Technology, Nanjing, China.
Xijing YanSchool of Material Science and Technology, Nanjing University of Science and Technology, Nanjing, China.
Mintao YanSchool of Material Science and Technology, Nanjing University of Science and Technology, Nanjing, China.
Jincheng LiSchool of Material Science and Technology, Nanjing University of Science and Technology, Nanjing, China.
Kehong WangSchool of Material Science and Technology, Nanjing University of Science and Technology, Nanjing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper investigates the effect of process parameters and chitosan-based precoating on mechanical properties and thermal damage during laser repair of esophageal tissue. The effects of laser power, defocusing amount, and concentrations of indocyanine green (ICG) and carbon nanotubes (CNT) on burst pressure strength, thermal denaturation degree, and microstructure characteristic parameters were investigated. To maximize burst pressure strength and minimize thermal damage, response surface models were constructed to correlate process parameters with burst pressure strength and thermal denaturation degree. The parameters were optimized using a genetic algorithm, and the predicted optimum was validated experimentally. Results show significant linear effects of laser power and defocusing amount on burst pressure, with notable interactions between defocusing amount-ICG and ICG-CNT. Laser power and CNT concentration also exhibit significant linear effects on thermal denaturation. The optimal process parameters were a laser power of 6.90 W, defocusing amount -0.10 mm, ICG 0.03 wt%, CNT 0.01 wt%.

Indexed as

ChitosanEsophagusLasersMechanical PhenomenaTemperatureAnimalsGenetic AlgorithmsIndocyanine GreenNanotubes, CarbonPressureChitosanIndocyanine GreenNanotubes, Carbonesophageal tissuegenetic algorithmlaser repairprocess parameter optimizationresponse surface model

Identifiers

PMID42733250
PMCPMC13572806

What OpenQuestion holds

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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.