Evidence map›Paper›PMID 40645952›Full record

ArticleNature communications2025

Luminescence-enabled three-dimensional temperature bioimaging.

Liyan Ming, Anna Romelli, José Lifante, Patrizia Canton, Ginés Lifante-Pedrola, Daniel Jaque, Erving Ximendes, Riccardo Marin

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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

8 authors.

Liyan MingNanomaterials for Bioimaging Group (nanoBIG), Departamento de Física de Materiales, Facultad de Ciencias, Universidad Autónoma de Madrid, Madrid, Spain.ORCID http://orcid.org/0000-0001-9171-9149
Anna RomelliDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Via Torino 155/b, I-30170, Venice, Italy.
José LifanteNanomaterials for Bioimaging Group (nanoBIG), Departamento de Física de Materiales, Facultad de Ciencias, Universidad Autónoma de Madrid, Madrid, Spain.
Patrizia CantonDepartment of Molecular Sciences and Nanosystems, Ca' Foscari University of Venice, Via Torino 155/b, I-30170, Venice, Italy.ORCID http://orcid.org/0000-0003-1604-5265
Ginés Lifante-PedrolaDepartamento de Física de Materiales, Facultad de Ciencias, Universidad Autónoma de Madrid, 28049, Madrid, Spain.
Daniel JaqueNanomaterials for Bioimaging Group (nanoBIG), Departamento de Física de Materiales, Facultad de Ciencias, Universidad Autónoma de Madrid, Madrid, Spain.ORCID http://orcid.org/0000-0002-3225-0667
Erving XimendesNanomaterials for Bioimaging Group (nanoBIG), Departamento de Física de Materiales, Facultad de Ciencias, Universidad Autónoma de Madrid, Madrid, Spain. erving.ximendes@uam.es.ORCID http://orcid.org/0000-0001-7182-0573
Riccardo MarinNanomaterials for Bioimaging Group (nanoBIG), Departamento de Física de Materiales, Facultad de Ciencias, Universidad Autónoma de Madrid, Madrid, Spain. riccardo.marin@unive.it.ORCID http://orcid.org/0000-0003-3270-892X

Funding

Comunidad de Madrid S2022/BMD-7403 RENIM-CMCSC | Chinese Government Scholarship 202108350018
6 · The paper itself

Abstract

Luminescence thermometry affords remote thermal readouts with high spatial resolution in a minimally invasive way. This technology has advanced our understanding of biological mechanisms and physical processes from the macro- to the submicrometric scale. Yet, current approaches only allow obtaining 2D thermal images. This aspect limits the potential of this technology, given the inherent three-dimensional nature of heat diffusion processes. Despite initial attempts, a credible method that allows extracting 3D thermal images via luminescence is missing. Here, we design such a method combining Ag

Indexed as

Imaging, Three-DimensionalLuminescent MeasurementsThermometryAlgorithmsAnimalsHumansLuminescenceMachine LearningMiceNeural Networks, ComputerTemperature

Identifiers

PMID40645952
PMCPMC12254501

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.