Evidence map›Paper›PMID 30326577›Full record

ArticleMetabolites2018

The Effect of High-Intensity Ultraviolet Light to Elicit Microalgal Cell Lysis and Enhance Lipid Extraction.

Thomas Sydney, Jo-Ann Marshall-Thompson, Rahul Vijay Kapoore, Seetharaman Vaidyanathan, Jagroop Pandhal, J Patrick A Fairclough

Open access · goldAbstract read
In one paragraph

Article in Metabolites, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

5 citing papers in PubMed, 27 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
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

6 authors at 2 institutions in 1 country.

Thomas SydneyDepartment of Chemistry, The University of Sheffield, Sheffield S3 7HF, UK. thomas_sydney@hotmail.co.uk.
Jo-Ann Marshall-ThompsonDepartment of Chemical and Biological Engineering, ChELSI Institute, Advanced Biomanufacturing Centre, The University of Sheffield, Sheffield S1 3JD, UK. jo-ann.marshall@svgcc.vc.ORCID 0000-0003-2966-9421
Rahul Vijay KapooreDepartment of Chemical and Biological Engineering, ChELSI Institute, Advanced Biomanufacturing Centre, The University of Sheffield, Sheffield S1 3JD, UK. R.V.Kapoore@swansea.ac.uk.ORCID 0000-0002-2287-0619
Seetharaman VaidyanathanDepartment of Chemical and Biological Engineering, ChELSI Institute, Advanced Biomanufacturing Centre, The University of Sheffield, Sheffield S1 3JD, UK. s.vaidyanathan@sheffield.ac.uk.ORCID 0000-0003-4137-1230
Jagroop PandhalDepartment of Chemical and Biological Engineering, ChELSI Institute, Advanced Biomanufacturing Centre, The University of Sheffield, Sheffield S1 3JD, UK. j.pandhal@sheffield.ac.uk.
J Patrick A FaircloughDepartment of Mechanical Engineering, The University of Sheffield, Sheffield S3 7HQ, UK. p.fairclough@sheffield.ac.uk.ORCID 0000-0002-1675-5219
University of Sheffield · GBSwansea University · GB

Funding

University of Sheffield 310957
6 · The paper itself

Abstract

Currently, the energy required to produce biofuel from algae is 1.38 times the energy available from the fuel. Current methods do not deliver scalable, commercially viable cell wall disruption, which creates a bottleneck on downstream processing. This is primarily due to the methods depositing energy within the water as opposed to within the algae. This study investigates ultraviolet B (UVB) as a disruption method for the green algae

Indexed as

biodieselcell disruptionChlamydomonas reinhardtiiDunaliella salinaMicractinium inermummicroalgaeultraviolet light

Identifiers

PMID30326577
PMCPMC6315748
OpenAlexW2896938538

What OpenQuestion 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 OpenQuestion graph.