Evidence map›Paper›PMID 40663602›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

A gentle palette of plasma membrane dyes.

Jing Ling, Yitong Liu, Alexandre Dumoulin, Danli Sheng, Yunzhe Fu, Shuzhang Liu, Ling Ding, Lulu Huang, Peng Xi, Hongyun Tang and 2 more

Abstract read
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 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. Review
  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

12 authors.

Jing Ling *Peking-Tsinghua Center for Life Science, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.ORCID 0000-0003-4620-9507
Yitong Liu *Peking-Tsinghua Center for Life Science, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.ORCID 0009-0008-7073-564X
Alexandre Dumoulin *Department of Molecular Life Sciences, University of Zurich, Zurich 8057, Switzerland.ORCID 0000-0002-2420-6877
Danli ShengSchool of Life Sciences, Westlake University, Hangzhou 310030, China.
Yunzhe FuDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China.
Shuzhang LiuCollege of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center, Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China.
Ling DingCenter for Reproductive Medicine, Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China.
Lulu HuangPeking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.
Peng XiDepartment of Biomedical Engineering, College of Future Technology, Peking University, Beijing 100871, China.ORCID 0000-0001-6626-4840
Hongyun TangSchool of Life Sciences, Westlake University, Hangzhou 310030, China.ORCID 0000-0002-7550-2860
Esther T StoeckliDepartment of Molecular Life Sciences, University of Zurich, Zurich 8057, Switzerland.ORCID 0000-0002-8485-0648
Zhixing ChenPeking-Tsinghua Center for Life Science, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China.ORCID 0000-0001-5962-7359

Funding

CAS | ICCAS | Beijing National Laboratory for Molecular Sciences (BNLMS) BNLMS202407MOST | National Key Research and Development Program of China (NKPs) 2021YFF0502904MOST | National Natural Science Foundation of China (NSFC) 32350015Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (SNF) P00P3_170681 and 310030_220012
6 · The paper itself

Abstract

Plasma membrane (PM) stains are important organelle markers for monitoring membrane morphology and dynamics. The state-of-the-art PM stains are bright, specific, fluorogenic, and compatible with superresolution imaging. However, when recording membrane dynamics using advanced fluorescence microscopes, PM is prone to photodynamic damage introduced by dyes due to its phospholipid bilayer nature. Here, we introduce PK Mem dyes tailored for time-lapse fluorescence imaging. By integrating triplet-state quenchers into the MemBright dyes featuring cyanine chromophores and amphiphilic zwitterion anchors, PK Mem dyes exhibited a three-fold reduction in phototoxicity and a more than four-fold improvement in photostability in imaging experiments compared to MemBright prototypes. These dyes enable 2D and 3D imaging of live or fixed cancer cell lines and a wide range of primary cells, at the same time pair well with various fluorescent markers. PK Mem dyes can be applied to neuronal imaging in brain slices and in vivo two-photon imaging. The gentle nature of PK Mem palette enables ultralong-term recording of cell migration, cardiomyocyte beating, spermiogenesis, and axonal growth cone dynamics, which are prohibitively challenging using traditional PM dyes. Notably, PK Mem dyes are optically compatible with STED/SIM imaging, which can handily upgrade the routine of time-lapse neuronal imaging, such as growth cone tracking and mitochondrial transportations, into nanoscopic resolutions.

Indexed as

Cell MembraneFluorescent DyesAnimalsCarbocyaninesCell Line, TumorHumansMiceMicroscopy, FluorescenceTime-Lapse ImagingCarbocyaninesFluorescent Dyeslong-term imagingmembrane dyesneuronal imagingphototoxicitysuper-resolution imaging

Identifiers

PMID40663602
PMCPMC12304895

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.