Evidence map›Paper›PMID 35933376›Full record

ArticleJournal of nanobiotechnology2022

Artificial neural network for cytocompatibility and antibacterial enhancement induced by femtosecond laser micro/nano structures.

Libin Lu, Jiaru Zhang, Kai Guan, Jin Zhou, Fusong Yuan, Yingchun Guan

Open access · goldAbstract read
In one paragraph

Article in Journal of nanobiotechnology, 2022. 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
3.1field-weighted citation impact, top 8% 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

11 citing papers in PubMed, 41 citations in OpenAlex.

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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 at 4 institutions in 1 country.

Libin Lu *Advanced Manufacturing Center, Ningbo Institute of Technology, Beihang University, Ningbo, 315100, China.
Jiaru Zhang *School of Mechanical Engineering & Automation, Beihang University, Beijing, 100083, China.
Kai GuanDepartment of Radiotherapy, The Third Hospital of Zhangzhou City, Zhangzhou, 363005, Fujian, China.
Jin ZhouKey Laboratory for Biomechanics and Mechanobiology of Ministry of Education, School of Biological Science and Medical Engineering, Beihang University, Beijing, 100083, China. jinzhou@buaa.edu.cn.
Fusong YuanNational Center of Stomatology & National Clinical Research Center for Oral Diseases, Beijing, 100081, China.
Yingchun GuanAdvanced Manufacturing Center, Ningbo Institute of Technology, Beihang University, Ningbo, 315100, China. guanyingchun@buaa.edu.cn.
Beihang University · CNNational Clinical Research Center for Digestive Diseases · CNNingbo University of Technology · CNZhangzhou Municipal Hospital of Fujian Province · CN

Funding

National Natural Science Foundation of China 51875313
6 · The paper itself

Abstract

The failure of orthopedic and dental implants is mainly caused by biomaterial-associated infections and poor osseointegration. Surface modification of biomedical materials plays a significant role in enhancing osseointegration and anti-bacterial infection. In this work, a non-linear relationship between the micro/nano surface structures and the femtosecond laser processing parameters was successfully established based on an artificial neural network. Then a controllable functional surface with silver nanoparticles (AgNPs) to was produced to improve the cytocompatibility and antibacterial properties of biomedical titanium alloy. The surface topography, wettability, and Ag

Indexed as

Metal NanoparticlesSilverAnimalsAnti-Bacterial AgentsBiocompatible MaterialsEscherichia coliLasersMiceNeural Networks, ComputerStaphylococcus aureusSurface PropertiesTitaniumAnti-Bacterial AgentsBiocompatible MaterialsSilverTitaniumAntibacterial activityCytocompatibilityFemtosecond laser microprocessingGA-BP neural networkHierarchical micro/nano-structure

Identifiers

PMID35933376
PMCPMC9357338
OpenAlexW4290072542

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.