Evidence map›Paper›PMID 29666707›Full record

ReviewJournal of lipids2018

Realm of Thermoalkaline Lipases in Bioprocess Commodities.

Ahmad Firdaus B Lajis

Abstract readReview
In one paragraph

Review in Journal of lipids, 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
–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

5 citing papers in PubMed.

  1. Review
  2. Halobacillus as source of natural products and enzyme factories.Extremophiles : life under extreme conditions · 2025
    Review
  3. Genomic Characterization ofMicroorganisms · 2024
    Article
  4. Article
  5. Article
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

1 author.

Ahmad Firdaus B LajisDepartment of Bioprocess Technology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400 Serdang, Malaysia.ORCID 0000-0003-2766-8986

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For decades, microbial lipases are notably used as biocatalysts and efficiently catalyze various processes in many important industries. Biocatalysts are less corrosive to industrial equipment and due to their substrate specificity and regioselectivity they produced less harmful waste which promotes environmental sustainability. At present, thermostable and alkaline tolerant lipases have gained enormous interest as biocatalyst due to their stability and robustness under high temperature and alkaline environment operation. Several characteristics of the thermostable and alkaline tolerant lipases are discussed. Their molecular weight and resistance towards a range of temperature, pH, metal, and surfactants are compared. Their industrial applications in biodiesel, biodetergents, biodegreasing, and other types of bioconversions are also described. This review also discusses the advance of fermentation process for thermostable and alkaline tolerant lipases production focusing on the process development in microorganism selection and strain improvement, culture medium optimization via several optimization techniques (i.e., one-factor-at-a-time, surface response methodology, and artificial neural network), and other fermentation parameters (i.e., inoculums size, temperature, pH, agitation rate, dissolved oxygen tension (DOT), and aeration rate). Two common fermentation techniques for thermostable and alkaline tolerant lipases production which are solid-state and submerged fermentation methods are compared and discussed. Recent optimization approaches using evolutionary algorithms (i.e., Genetic Algorithm, Differential Evolution, and Particle Swarm Optimization) are also highlighted in this article.

Identifiers

PMID29666707
PMCPMC5832097

What OpenQuestion holds

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LicenceCC BY
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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.