Evidence map›Paper›PMID 39609450›Full record

ArticleScientific reports2024

Artificial intelligence-based optimization for extracellular L-glutaminase free L-asparaginase production by Streptomyces violaceoruber under solid state fermentation conditions.

Noura El-Ahmady El-Naggar, Ragaa A Hamouda, Naglaa Elshafey

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Article in Scientific reports, 2024. 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
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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

3 authors.

Noura El-Ahmady El-NaggarDepartment of Bioprocess Development, Genetic Engineering and Biotechnology Research Institute, City of Scientific Research and Technological Applications (SRTA-City), New Borg El-Arab City, 21934, Alexandria, Egypt. nouraalahmady@yahoo.com.ORCID 0000-0001-8493-9194
Ragaa A HamoudaMicrobial Biotechnology Department, Genetic Engineering and Biotechnology Research Institute, University of Sadat City, Sadat City, Egypt.
Naglaa ElshafeyBotany and Microbiology Department, Faculty of Science, Arish University, Al-Arish, 45511, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The bacterial L-asparaginase is a highly effective chemotherapeutic drug and a cornerstone of treatment protocols used for treatment the acute lymphoblastic leukemia in pediatric oncology. A potential actinomycete isolate, Streptomyces sp. strain NEAE-99, produces glutaminase-free L-asparaginase was isolated from a soil sample. This potential strain was identified as S. violaceoruber strain NEAE-99. The central composite design (CCD) approach was utilized for finding the optimal values for four variables including the mixture of soybean and wheat bran in a 1:1 ratio (w/w), the concentrations of dextrose, L-asparagine, and potassium nitrate under solid state fermentation conditions. Through the use of an artificial neural network (ANN), the production of L-asparaginase by S. violaceoruber has been investigated, validated, and predicted in comparison to CCD. It was found that the optimal predicted conditions for maximum L-asparaginase production (216.19 U/gds) were 8.46 g/250 mL Erlenmeyer flask of soybean and wheat bran mixture in a 1:1 ratio (w/w), 2.2 g/L of dextrose, 18.97 g/L of L-asparagine, and 1.34 g/L of KNO

Indexed as

AsparaginaseFermentationGlutaminaseStreptomycesAsparagineNeural Networks, ComputerAsparaginaseAsparagineGlutaminaseArtificial neural networkCentral composite designL-asparaginase; Streptomyces; IdentificationOptimization

Identifiers

PMID39609450
PMCPMC11604706

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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.