Evidence map›Paper›PMID 39114747›Full record

ReviewBiology methods & protocols2024

The use of droplet-based microfluidic technologies for accelerated selection of

Taras Mika, Martins Kalnins, Kriss Spalvins

Abstract readReview
In one paragraph

Review in Biology methods & protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Taras MikaInstitute of Energy Systems and Environment, Riga Technical University, 12 - K1 Āzene street, Riga, LV-1048, Latvia.ORCID https://orcid.org/0009-0000-2865-782X
Martins KalninsInstitute of Energy Systems and Environment, Riga Technical University, 12 - K1 Āzene street, Riga, LV-1048, Latvia.ORCID https://orcid.org/0009-0003-1974-6523
Kriss SpalvinsInstitute of Energy Systems and Environment, Riga Technical University, 12 - K1 Āzene street, Riga, LV-1048, Latvia.ORCID https://orcid.org/0000-0003-4464-1101

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Microorganisms are widely used for the industrial production of various valuable products, such as pharmaceuticals, food and beverages, biofuels, enzymes, amino acids, vaccines, etc. Research is constantly carried out to improve their properties, mainly to increase their productivity and efficiency and reduce the cost of the processes. The selection of microorganisms with improved qualities takes a lot of time and resources (both human and material); therefore, this process itself needs optimization. In the last two decades, microfluidics technology appeared in bioengineering, which allows for manipulating small particles (from tens of microns to nanometre scale) in the flow of liquid in microchannels. The technology is based on small-volume objects (microdroplets from nano to femtolitres), which are manipulated using a microchip. The chip is made of an optically transparent inert to liquid medium material and contains a series of channels of small size (<1 mm) of certain geometry. Based on the physical and chemical properties of microparticles (like size, weight, optical density, dielectric constant, etc.), they are separated using microsensors. The idea of accelerated selection of microorganisms is the application of microfluidic technologies to separate mutants with improved qualities after mutagenesis. This article discusses the possible application and practical implementation of microfluidic separation of mutants, including yeasts like

Indexed as

microdropletmicrofluidicsmicroorganismsmutagenesisselection

Identifiers

PMID39114747
PMCPMC11303513

What Socratic holds

Textmetadata
LicenceCC BY
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 Socratic graph.