Evidence map›Paper›PMID 41104234›Full record

ArticleIranian journal of pharmaceutical research : IJPR

Enhanced Hyaluronic Acid Production in

Kamand Hedayat, Delaram Doroud, Naser Mohamadpour Dounighi, Mohammad Ali Shokrgozar, Maryam Shahali, Mohammad Hassan Houshdar Tehrani

Abstract read
In one paragraph

Article in Iranian journal of pharmaceutical research : IJPR. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Kamand HedayatDepartment of Biotechnology, Production and Research Complex, Pasteur Institute of Iran, Tehran, Iran.
Delaram DoroudDepartment of Immunotherapy and Leishmania Vaccine Research, Pasteur Institute of Iran, Tehran, Iran.ORCID https://orcid.org/0000-0003-4167-9921
Naser Mohamadpour DounighiDepartment of Human Vaccines and Serum, Razi Vaccine and Sera Research Institute, Karaj, Iran.
Mohammad Ali ShokrgozarDepartment of Cell Bank, Pasteur Institute of Iran, Tehran, Iran.
Maryam ShahaliResearch and Production Complex, Pasteur Institute of Iran, Tehran, Iran.
Mohammad Hassan Houshdar TehraniDepartment of Medicinal Chemistry, School of Pharmacy, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Objectives: This study focuses on strain optimization and the purification of HA. The key goals include reducing hyaluronidase activity, which degrades HA, eliminating beta-hemolytic traits, and developing a purification process that significantly minimizes organic solvent consumption to lower costs and reduce environmental impact. Methods: UV-induced physical mutagenesis and chemical mutagenesis utilizing nitrous acid and N-methyl-N'-nitro-N-nitrosoguanidine (NTG) were employed to generate mutant strains with diminished hyaluronidase activity and beta-hemolytic properties. Following strain optimization, an efficient downstream process was implemented, focusing on pre-treatment methods involving pH and temperature adjustments, followed by ultrafiltration and phenol acetate treatment. Results: The selected mutant, designated as Conclusions: The study presents an integrated approach to HA production, encompassing strain improvement and purification. It addresses key challenges in the manufacturing of streptococcal HA and contributes to the development of more efficient and environmentally friendly purification methods, ultimately resulting in high-purity HA.

Indexed as

Hyaluronic AcidPurificationRandom MutagenesisStrain OptimizationStreptococcusequi subsp. S. zooepidemicus

Identifiers

PMID41104234
PMCPMC12523987

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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.