Evidence map›Paper›PMID 40167821›Full record

ArticleBiodegradation2025

A comparative study using response surface methodology and artificial neural network for modeling the bio-reduction of hexavalent chromium (Cr⁶⁺) by immobilized cells of Paenibacillus taichungensis strain MAHA in an alginate-gellan gum matrix.

Maha Obaid Al-Osaimi, Mohd Izuan Effendi Halmi, Siti Salwa Abd Gani, Khairil Mahmud, Mohd Yunus Abd Shukor

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Biodegradation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

5 authors.

Maha Obaid Al-OsaimiDepartment of Land Management, Faculty of Agriculture, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia.
Mohd Izuan Effendi HalmiDepartment of Land Management, Faculty of Agriculture, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia. m_izuaneffendi@upm.edu.my.
Siti Salwa Abd GaniDepartment of Agricultural Technology, Faculty of Agriculture, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia.
Khairil MahmudDepartment of Crop Science, Agricultural Technology, Faculty of Agriculture, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia.
Mohd Yunus Abd ShukorDepartment of Biochemistry, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chromium (Cr⁶⁺) waste poses a hazard as it leads to imbalanced ecosystems and severe health issues. Although, it is widely associated with many industries. Chromium (Cr⁶⁺) reduction by the immobilized cells of Paenibacillus taitungensis strain MAHA-MIE was optimized using response surface methodology (RSM) and artificial neural networks (ANN). The RSM-Box-Behnken Design (BBD) was selected to investigate the effects of chromium (Cr⁶⁺) concentration, alginate concentration, gellan gum concentration, bead size, and the number of beads on chromium (Cr⁶⁺) reduction rate. Experimental data from the BBD was used to train a feed-forward, multilayer artificial neural network (ANN). Results show that the ANN model outperformed the response surface methodology (RSM) based on actual and predicted data, with lower errors and a higher R

Indexed as

AlginatesChromiumNeural Networks, ComputerPaenibacillusPolysaccharides, BacterialBiodegradation, EnvironmentalCells, ImmobilizedGlucuronic AcidHexuronic AcidsAlginatesChromiumchromium hexavalent iongellan gumGlucuronic AcidHexuronic AcidsPolysaccharides, BacterialAlginate-gellan gum matrixBio-reductionHexavalent chromiumImmobilized cellsModeling

Identifiers

PMID40167821

What OpenQuestion holds

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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.