Evidence map›Paper›PMID 22916318›Full record

ArticleProceedings of SPIE--the International Society for Optical Engineering2010

3D single molecule tracking of quantum-dot labeled antibody molecules using multifocal plane microscopy.

Sripad Ram, Prashant Prabhat, Jerry Chao, E Sally Ward, Raimund J Ober

Abstract read
In one paragraph

Article in Proceedings of SPIE--the International Society for Optical Engineering, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

5 authors.

Sripad RamDepartment of Immunology, University of Texas Southwestern Medical Center, Dallas, TX, 75390.
Prashant Prabhat
Jerry Chao
E Sally Ward
Raimund J Ober

Funding

STRUCTURE/FUNCTION STUDIES OF HUMAN FCRNR01AI039167 · NIAID · UT SOUTHWESTERN MEDICAL CENTER · PI WARD, ELIZABETH SALLY · 1995 to 2008
$2.8M
High accuracy quantum dot tracking in live cellsR01GM085575 · NIGMS · UNIVERSITY OF TEXAS DALLAS · PI OBER, RAIMUND J · 2008 to 2016
$2.5M
NIAID NIH HHS R01 AI039167NIGMS NIH HHS R01 GM085575
6 · The paper itself

Abstract

Single molecule tracking in three dimensions (3D) in a live cell environment promises to reveal important new insights into cell biological mechanisms. However, classical microscopy techniques suffer from poor depth discrimination which severely limits single molecule tracking in 3D with high temporal and spatial resolution. We introduced a novel imaging modality, multifocal plane microscopy (MUM) for the study of subcellular dynamics in 3D. We have shown that MUM provides a powerful approach with which single molecules can be tracked in 3D in live cells. MUM allows for the simultaneous imaging at different focal planes, thereby ensuring that trajectories can be imaged continuously at high temporal resolution. A critical requirement for 3D single molecule tracking as well as localization based 3D super-resolution imaging is high 3D localization accuracy. MUM overcomes the depth discrimination problem of classical microscopy based approaches and supports high accuracy 3D localization of singe molecule/particles. In this way, MUM opens the way for high precision 3D single molecule tracking and 3D super-resolution imaging within a live cell environment. We have used MUM to reveal complex intracellular pathways that could not be imaged with classical approaches. In particular we have tracked quantum dot labeled antibody molecules in the exo/endocytic pathway from the cell interior to the plasma membrane at the single molecule level. Here, we present a brief review of these results.

Identifiers

PMID22916318
PMCPMC3423200

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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.