Evidence map›Paper›PMID 40951363›Full record

ArticleMaterials today. Bio2025

NIR/pH-responsive arginine-ε-polylysine/black phosphorus nanocomposites for synergistic therapy of bacterial infections.

Qian Gao, Ranran Fu, Mengting Li, Dongbo Guo, Bingcheng Gan, Tao Wang, Maohua Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Materials today. Bio, 2025. 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
–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

2 citing papers in PubMed.

  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

7 authors.

Qian GaoLaboratory of Digital Medical Engineering, Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, 572025, China.
Ranran FuLaboratory of Digital Medical Engineering, Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, 572025, China.
Mengting LiHainan Provincial Fine Chemical Engineering Research Center, School of Chemical Engineering and Technology, Hainan University, Haikou, 570228, China.
Dongbo GuoLaboratory of Digital Medical Engineering, Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, 572025, China.
Bingcheng GanInstitute of Urban Agriculture, Chinese Academy of Agricultural Sciences, Chengdu National Agricultural Science &Technology Center, Chengdu, 610213, China.
Tao WangInstitute of Urban Agriculture, Chinese Academy of Agricultural Sciences, Chengdu National Agricultural Science &Technology Center, Chengdu, 610213, China.
Maohua ChenLaboratory of Digital Medical Engineering, Sanya Research Institute of Hainan University, School of Biomedical Engineering, Hainan University, Sanya, 572025, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The escalating global burden of drug-resistant bacterial infections demands urgent innovation in highly effective, non-invasive antimicrobial strategies. Herein, we developed a multimodal near infrared (NIR) light-responsive bactericidal nanoplatform (BP@EPL-LA) with surface charge adaptability by loading black phosphorus nanosheets with L-Arg-grafted ε-poly(L-lysine) for targeted combinatorial therapy of subcutaneous abscesses. Under physiological conditions, BP@EPL-LA remained a neutral surface charge and demonstrated excellent biosafety both

Indexed as

Black phosphorus nanosheetsNitric oxide gas therapyPhotodynamic therapySynergistic antibacterial effectε-Polylysine

Identifiers

PMID40951363
PMCPMC12423699

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.