Evidence map›Paper›PMID 30740778›Full record

ArticleAdvanced materials (Deerfield Beach, Fla.)2019

Lysosome-Targeted Bioprobes for Sequential Cell Tracking from Macroscopic to Microscopic Scales.

G Kate Park, Jeong Heon Lee, Andrew Levitz, Georges El Fakhri, Nathaniel S Hwang, Maged Henary, Hak Soo Choi

Open access · greenAbstract read
In one paragraph

Article in Advanced materials (Deerfield Beach, Fla.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.7field-weighted citation impact, top 19% 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

13 citing papers in PubMed, 33 citations in OpenAlex.

  1. Review
  2. Lysosome-Targeted Bifunctional Therapeutics Induce Autodynamic Cancer Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  3. Article
  4. Article
  5. Review
  6. Molecular Tuning of IR-786 for Improved Brown Adipose Tissue Imaging.International journal of molecular sciences · 2022
    Article
  7. Article
  8. NIR fluorescence imaging and treatment for cancer immunotherapy.Journal for immunotherapy of cancer · 2022
    Review
  9. Article
  10. Article
  11. Article
  12. Targeted Near-Infrared Fluorescence Imaging for Regenerative Medicine.Tissue engineering and regenerative medicine · 2019
    Review
  13. 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 at 3 institutions in 2 countries.

G Kate ParkGordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
Jeong Heon LeeGordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
Andrew LevitzDepartment of Chemistry, Georgia State University, Atlanta, GA, 30303, USA.
Georges El FakhriGordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.
Nathaniel S HwangInterdisciplinary Program in Bioengineering and School of Chemical and Biological Engineering, Seoul National University, Seoul, 151-742, South Korea.
Maged HenaryDepartment of Chemistry, Georgia State University, Atlanta, GA, 30303, USA.
Hak Soo ChoiGordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, 02114, USA.ORCID https://orcid.org/0000-0002-7982-6483
Harvard University · USGeorgia State University · USSeoul National University · KR

Funding

Image-Guided Drug Delivery for Pancreatic Neuroendocrine Tumor.R01EB022230 · NIBIB · MASSACHUSETTS GENERAL HOSPITAL · PI CHOI, HAK SOO, HENARY, MAGED M · 2017 to 2020
$3.6M
Image-Guided Drug Delivery and Treatment for GISTR21CA223270 · NCI · MASSACHUSETTS GENERAL HOSPITAL · PI CHOI, HAK SOO · 2018 to 2019
$398k
Marine Biotechnology Program 20170263Ministry of Oceans and FisheriesNCI NIH HHS R21 CA223270NIBIB NIH HHS R01 EB022230NIH HHS R01-EB022230NIH HHS R21CA223270)
6 · The paper itself

Abstract

Longitudinal tracking of living cells is crucial to understanding the mechanism of action and toxicity of cell-based therapeutics. To quantify the presence of administered cells in the host tissue without sacrifice of animals, labeling of the target cells with a nontoxic and stable contrast agent is a prerequisite. However, such long-term live cell tracking is currently limited by the lack of fluorophores with steady optical and physicochemical properties in the near-infrared (NIR) window. Herein, for the first time, the design of fixable cell-tracking NIR fluorophores (CTNFs) with high optical properties, excellent cell permeation and retention, and high stability against chemical treatments is reported. Efficient cellular labeling and tracking of CTNFs using intraoperative optical fluorescence imaging by following the fate of NIR-labeled cells from the time of injection into animals to ex vivo cellular analysis after resection of the target tissue is demonstrated. Due to the lipophilic cationicity and primary amine docking group, CTNF126 outperforms the other tested fluorophores with rapid diffusion into the cytoplasmic membrane and sequestration inside the lysosomes, which prevents cellular efflux and improves cellular retention. Thus, CTNF126 will be useful to track cells in living organisms for the mechanism of action at the single cell level.

Indexed as

AnimalsCell TrackingHumansLysosomesMiceMice, Inbred C57BLMolecular ProbesPC-3 CellsSingle-Cell AnalysisMolecular Probesfixable bioprobehistological analysisin vivo cell trackingnear-infrared fluorescenceoptical imaging

Identifiers

PMID30740778
PMCPMC6574216
OpenAlexW2913887401

What OpenQuestion holds

Textmetadata
LicenceTDM
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.