Evidence map›Paper›PMID 39716869›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025

In Vivo Neurodynamics Mapping via High-Speed Two-Photon Fluorescence Lifetime Volumetric Projection Microscopy.

Yanping Li, Xiangcong Xu, Chao Zhang, Xuefeng Sun, Sisi Zhou, Xuan Li, Jiaqing Guo, Rui Hu, Junle Qu, Liwei Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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

10 authors.

Yanping LiState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Xiangcong XuState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Chao ZhangState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Xuefeng SunState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Sisi ZhouState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Xuan LiState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Jiaqing GuoState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Rui HuState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Junle QuState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.
Liwei LiuState Key Laboratory of Radio Frequency Heterogeneous Integration & Key Laboratory of Optoelectronic Devices and Systems, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen, 518060, China.ORCID https://orcid.org/0000-0002-4593-665X

Funding

China Postdoctoral Science Foundation 2023M732347National Natural Science Foundation of China 61935012National Natural Science Foundation of China 62127819National Natural Science Foundation of China 62175163National Natural Science Foundation of China 62225505National Natural Science Foundation of China 62405200Science and Technology Planning Project of Shenzen Municipality ZDSYS20210623092006020Shenzhen Talent Innovation Project RCJC20210706091949022
6 · The paper itself

Abstract

Monitoring the morphological and biochemical information of neurons and glial cells at high temporal resolution in three-dimensional (3D) volumes of in vivo is pivotal for understanding their structure and function, and quantifying the brain microenvironment. Conventional two-photon fluorescence lifetime volumetric imaging speed faces the acquisition speed challenges of slow serial focal tomographic scanning, complex post-processing procedures for lifetime images, and inherent trade-offs among contrast, signal-to-noise ratio, and speed. This study presents a two-photon fluorescence lifetime volumetric projection microscopy using an axially elongated Bessel focus and instant frequency-domain fluorescence lifetime technique, and integrating with a convolutional network to enhance the imaging speed for in vivo neurodynamics mapping. The proposed method is validated by monitoring intracellular Ca

Indexed as

BrainImaging, Three-DimensionalMicroscopy, Fluorescence, MultiphotonNeuronsAnimalsCalciumMiceZebrafishCalciumfrequency‐domain fluorescence lifetime microscopyhigh‐speed volumetric projection imagingin vivo neurodynamics

Identifiers

PMID39716869
PMCPMC11831470

What OpenQuestion holds

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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.