Evidence map›Paper›PMID 40074433›Full record

ArticleJournal, genetic engineering & biotechnology2025

Process optimization and extraction of alkaline protease from halotolerant Streptomyces sp. VITGS3 and its use as a contact lens cleaner.

Gargi Sarkar, K Prem Anand, M A Jayasri, K Suthindhiran

Abstract read
In one paragraph

Article in Journal, genetic engineering & biotechnology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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

4 authors.

Gargi SarkarMarine Biotechnology and Bioproducts Laboratory, Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.
K Prem AnandMarine Biotechnology and Bioproducts Laboratory, Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.
M A JayasriMarine Biotechnology and Bioproducts Laboratory, Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.
K SuthindhiranMarine Biotechnology and Bioproducts Laboratory, Department of Biomedical Sciences, School of Biosciences and Technology, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India. Electronic address: ksuthindhiran@vit.ac.in.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Marine halotolerant actinobacteria are robust microbes poorly explored and barely cultivable in nature. They are a trove of various secondary metabolites and enzymes, especially the alkaline proteases withstanding higher temperatures, pH, and salinity, making them an ideal source with versatile commercial and therapeutic values. This study focuses on extracting and optimizing alkaline protease production from Streptomyces sp. VITGS3 isolated from Puthuvypeen, Kerala. The protease production was optimized by Response Surface Methodology (RSM) using the Box-Behnken model, which used rice bran, wheat bran, skim milk, and casein as substrates. The maximum protease was produced (357 U/mL) using wheat bran (5.5 % w/v) as substrate at pH 9 and incubated at 45 °C for 9 days. The Michaelis-Menten model's enzyme kinetics exhibited a K

Indexed as

ActinobacteriaAlkaline ProteaseContact Lens CleanerSDS-PAGEStreptomyces

Identifiers

PMID40074433
PMCPMC11787585

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.