Evidence map›Paper›PMID 22514034›Full record

ArticleMicroscopy research and technique2012

Measurement of distance with the nanoscale precise imaging by rapid beam oscillation method.

Luca Lanzano, Enrico Gratton

Open access · greenAbstract read
In one paragraph

Article in Microscopy research and technique, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 29% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

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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

2 authors at 2 institutions in 1 country.

Luca LanzanoDepartment of Biomedical Engineering, Laboratory for Fluorescence Dynamics, University of California, Irvine, California 92697, USA.
Enrico Gratton
Fluor (United States) · USUniversity of California, Irvine · US

Funding

Univ.of Calif., Irvine Cancer Center Support GrantP30CA062203 · NCI · UNIVERSITY OF CALIFORNIA-IRVINE · PI Christine Hui · 1994 to 2026
$57.9M
TRD4: Phasor analysisP41GM103540 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI GRATTON, ENRICO · 2012 to 2020
$12.5M
Regulation of Renal Phosphate Transport by LipidsR01DK066029 · NIDDK · UNIVERSITY OF COLORADO DENVER · PI LEVI, MOSHE · 2005 to 2013
$3.2M
NCI NIH HHS P30 CA062203NIDDK NIH HHS R01 DK066029NIGMS NIH HHS 8P41 GM103540NIGMS NIH HHS P41 GM103540
6 · The paper itself

Abstract

We discuss here the principles of a novel optical method in which the scanning of a laser spot around a fluorescent object is used to determine its shape, orientation, and fluorophore distribution. The scanning pattern is adapted to the shape of the object according to a feedback principle based on intensity modulation measurements. The modulation of the intensity with respect to the angular coordinate is used to keep the orbit centered on the object. The modulation induced by rapid oscillations of the orbit radius is used to measure the local distance from the surface with nanometer precision. We provide a model to describe the fundamental relationship between modulation and distance and discuss the range of validity of several approximate expressions. According to this model, the distance can be measured with a precision dependent on the steepness of the point spread function and the total number of detected photons. To test our findings, we performed experiments with one or two channels on fluorescent spheres of known size and characterized the modulation function of our microscope setup. We conclude that the method can be used to measure distances in the range 10-200 nm between two surfaces labeled with two different probes.

Identifiers

PMID22514034
PMCPMC3426651
OpenAlexW2130321507

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.