Evidence map›Paper›PMID 28531156›Full record

ReviewSensors (Basel, Switzerland)2017

Molecular Techniques for the Detection of Organisms in Aquatic Environments, with Emphasis on Harmful Algal Bloom Species.

Linda K Medlin, Jahir Orozco

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing 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

19 citing papers in PubMed.

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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.

Linda K MedlinMarine Biological Association of the UK, The Citadel, Plymouth PL1 2PB, UK. lkm@mba.ac.uk.
Jahir OrozcoMax Planck Tandem Group in Nanobioengineering, Universidad de Antioquia, Complejo Ruta N, Calle 67, N° 52-20, Medellín 050010, Colombia. grupotandem.nanobioe@udea.edu.co.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Molecular techniques to detect organisms in aquatic ecosystems are being gradually considered as an attractive alternative to standard laboratory methods. They offer faster and more accurate means of detecting and monitoring species, with respect to their traditional homologues based on culture and microscopic counting. Molecular techniques are particularly attractive when multiple species need to be detected and/or are in very low abundance. This paper reviews molecular techniques based on whole cells, such as microscope-based enumeration and Fluorescence In-Situ Hybridization (FISH) and molecular cell-free formats, such as sandwich hybridization assay (SHA), biosensors, microarrays, quantitative polymerase chain reaction (qPCR) and real time PCR (RT-PCR). Those that combine one or several laboratory functions into a single integrated system (lab-on-a-chip) and techniques that generate a much higher throughput data, such as next-generation systems (NGS), were also reviewed. We also included some other approaches that enhance the performance of molecular techniques. For instance, nano-bioengineered probes and platforms, pre-concentration and magnetic separation systems, and solid-phase hybridization offer highly pre-concentration capabilities. Isothermal amplification and hybridization chain reaction (HCR) improve hybridization and amplification techniques. Finally, we presented a study case of field remote sensing of harmful algal blooms (HABs), the only example of real time monitoring, and close the discussion with future directions and concluding remarks.

Indexed as

Harmful Algal BloomBiosensing TechniquesEcosystemEnvironmental MonitoringNucleic Acid Hybridizationaquatic ecosystemsFISHharmful algae bloomhybridization chain reactionisothermal amplificationlab-on-a-chipmolecular techniquesnext generation systemPCRsandwich hybridization assay

Identifiers

PMID28531156
PMCPMC5470929

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Registered trials

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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.