Evidence map›Paper›PMID 30211977›Full record

ReviewCytometry. Part A : the journal of the International Society for Analytical Cytology2018

Microfluidic Based Optical Microscopes on Chip.

Petra Paiè, Rebeca Martínez Vázquez, Roberto Osellame, Francesca Bragheri, Andrea Bassi

Abstract readReview
In one paragraph

Review in Cytometry. Part A : the journal of the International Society for Analytical Cytology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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  9. Artificial intelligence in imaging flow cytometry.Frontiers in bioinformatics · 2023
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  12. Article
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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

5 authors.

Petra PaièIstituto di Fotonica e Nanotecnologie, Consiglio Nazionale dell Ricerche, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
Rebeca Martínez VázquezIstituto di Fotonica e Nanotecnologie, Consiglio Nazionale dell Ricerche, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
Roberto OsellameIstituto di Fotonica e Nanotecnologie, Consiglio Nazionale dell Ricerche, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
Francesca BragheriIstituto di Fotonica e Nanotecnologie, Consiglio Nazionale dell Ricerche, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.
Andrea BassiIstituto di Fotonica e Nanotecnologie, Consiglio Nazionale dell Ricerche, Piazza Leonardo da Vinci 32, 20133 Milan, Italy.ORCID 0000-0002-5017-0775

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Last decade's advancements in optofluidics allowed obtaining an ever increasing integration of different functionalities in lab on chip devices to culture, analyze, and manipulate single cells and entire biological specimens. Despite the importance of optical imaging for biological sample monitoring in microfluidics, imaging is traditionally achieved by placing microfluidics channels in standard bench-top optical microscopes. Recently, the development of either integrated optical elements or lensless imaging methods allowed optical imaging techniques to be implemented in lab on chip systems, thus increasing their automation, compactness, and portability. In this review, we discuss known solutions to implement microscopes on chip that exploit different optical methods such as bright-field, phase contrast, holographic, and fluorescence microscopy.

Indexed as

AutomationHolographyHumansLab-On-A-Chip DevicesMicrofluidic Analytical TechniquesMicrofluidicsMicroscopyOptical Imagingbrightfieldfluorescencelab on chipoptical microscopyoptofluidics

Identifiers

PMID30211977
PMCPMC6220811

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.