Evidence map›Paper›PMID 40387375›Full record

ArticleMicrobiology spectrum2025

Study on

Chen Chen, Tianyu Guo, Di Wu, Jingyan Shu, Ningwei Huang, Huaixiang Tian, Haiyan Yu, Chang Ge

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Microbiology spectrum, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  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

8 authors.

Chen ChenSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, Shanghai, China.
Tianyu GuoSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, Shanghai, China.ORCID 0009-0007-0309-0514
Di WuSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, Shanghai, China.
Jingyan ShuSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, Shanghai, China.
Ningwei HuangSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, Shanghai, China.
Huaixiang TianSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, Shanghai, China.ORCID 0000-0002-6097-809X
Haiyan YuSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, Shanghai, China.
Chang GeSchool of Perfume and Aroma Technology, Shanghai Institute of Technology, Shanghai, Shanghai, China.ORCID 0009-0000-5858-5644

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study enhanced the production efficiency of Lacticaseibacillus casei TCS by optimizing medium composition and fermentation conditions for high-density culture. Initially, single-factor and orthogonal experimental designs and the response surface methodology were used to determine the optimal concentrations of medium. Subsequently, we applied the artificial neural network-genetic algorithm optimization method, which significantly increased the viable bacterial count. Fermentation kinetics were modeled using logistic growth and Luedeking-Piret models, which accurately predicted cell growth. Amberlite IRA 67, an anion exchange resin, effectively adsorbed lactic acid and maintained pH levels. Furthermore, the combined use of fed-batch fermentation and ion exchange alleviated the effects of acid inhibition, salt stress, and substrate limitation, resulting in a maximum cell density of 10.01 lg CFU/mL, a 9.3-fold increase over the basal medium. This study develops a robust and cost-effective strategy for the industrial production of

Indexed as

FermentationLacticaseibacillus caseiAlgorithmsBatch Cell Culture TechniquesCulture MediaKineticsLactic AcidNeural Networks, ComputerProbioticsCulture MediaLactic AcidANN-GAfed-batch fermentationhigh-density fermentationion exchange resinLacticaseibacillus casei TCSmedium optimization

Identifiers

PMID40387375
PMCPMC12210951

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.