Comparative study on the extraction efficiency, characterization, and bioactivities of Bletilla striata polysaccharides using response surface methodology (RSM) and genetic algorithm-artificial neural network (GA-ANN)

Chen, Haoying; Wang, Bin; Li, Jinpeng; Xu, Jun; Zeng, Jinsong; Gao, Wenhua; Chen, Kefu

doi:10.1016/j.ijbiomac.2022.12.017

Cited by 27 publications

(8 citation statements)

References 85 publications

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“…Some of recent studies reported that advanced glycation end products (AGEs), accumulated in the diabetic patient, were effective oxidants to promote the production of excessive ROS and were considered a risk factor for injury and chronic ulcers . Chen et al found that BSP inhibited the formation of advanced glycation end products (AGEs) after 15 days of incubation in the BSA glucose system . Therefore, the inhibition of BSP on AGEs may also be one of the mechanisms of the hydrogel to heal diabetic wounds.…”

Section: Resultsmentioning

confidence: 99%

“…66 Chen et al found that BSP inhibited the formation of advanced glycation end products (AGEs) after 15 days of incubation in the BSA glucose system. 67 Therefore, the inhibition of BSP on AGEs may also be one of the mechanisms of the hydrogel to heal diabetic wounds. In addition to above, the disruption of M1 to M2 macrophage transition is a significant factor in the excessive and prolonged inflammation and delayed healing of diabetic wounds.…”

Section: Water Content and Swellingmentioning

confidence: 99%

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Bletilla striata Polysaccharide-/Chitosan-Based Self-Healing Hydrogel with Enhanced Photothermal Effect for Rapid Healing of Diabetic Infected Wounds via the Regulation of Microenvironment

Zhao,

Hu,

Chen

et al. 2024

Biomacromolecules

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The management of diabetic ulcers poses a significant challenge worldwide, and persistent hyperglycemia makes patients susceptible to bacterial infections. Unfortunately, the overuse of antibiotics may lead to drug resistance and prolonged infections, contributing to chronic inflammation and hindering the healing process. To address these issues, a photothermal therapy technique was incorporated in the preparation of wound dressings. This innovative solution involved the formulation of a self-healing and injectable hydrogel matrix based on the Schiff base structure formed between the oxidized Bletilla striata polysaccharide (BSP) and hydroxypropyltrimethylammonium chloride chitosan. Furthermore, the introduction of CuO nanoparticles encapsulated in polydopamine imparted excellent photothermal properties to the hydrogel, which promoted the release of berberine (BER) loaded on the nanoparticles and boosted the antibacterial performance. In addition to providing a reliable physical protection to the wound, the developed hydrogel, which integrated the herbal components of BSP and BER, effectively accelerated wound closure via microenvironment regulation, including alleviated inflammatory reaction, stimulated reepithelialization, and reduced oxidative stress based on the promising results from cell and animal experiments. These impressive outcomes highlighted their clinical potential in safeguarding the wound against bacterial intrusion and managing diabetic ulcers.

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Section: Resultsmentioning

confidence: 99%

Section: Water Content and Swellingmentioning

confidence: 99%

Bletilla striata Polysaccharide-/Chitosan-Based Self-Healing Hydrogel with Enhanced Photothermal Effect for Rapid Healing of Diabetic Infected Wounds via the Regulation of Microenvironment

Zhao,

Hu,

Chen

et al. 2024

Biomacromolecules

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“…Consequently, by designing a lesser number of experimental groups, one can effectively explore the influence of factor interactions on the response value while employing multivariate quadratic polynomials to represent the constructed model [81]. However, the limitations of simple binary equations for accurately elucidating the intricate mechanisms involved in microbial fermentation necessitate the utilization of ANN, which possess the capability to construct more sophisticated models and generally outperform RSM when confronted with such challenges [39,[82][83][84][85].…”

Section: Discussionmentioning

confidence: 99%

Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by Streptomyces parvus Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm

Yu,

Fu,

Wang

2024

Fermentation

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4′-N-demethyl-vicenistatin is a vicenistatin analogue that has better antitumor activity with promising applications in the pharmaceuticals industry. The harnessing of the complete potential of this compound necessitates a systematic optimization of the culture medium to enable the cost-effective production of 4′-N-demethyl-vicenistatin by Streptomyces parvus SCSIO Mla-L010/ΔvicG. Therefore, in this study, a sequential approach was employed to screen the significant medium compositions, as follows: one-factor-at-a-time (OFAT) and Plackett–Burman designs (PBD) were initially utilized. Cassava starch, glycerol, and seawater salt were identified as the pivotal components influencing 4′-N-demethyl-vicenistatin production. To further investigate the direct and interactive effects of these key components, a three-factor, five-level central composite design (CCD) was implemented. Finally, response surface methodology (RSM) and an artificial-neural-network-genetic-algorithm (ANN-GA) were employed for the modeling and optimization of the medium components to enhance efficient 4′-N-demethyl-vicenistatin production. The ANN-GA model showed superior reliability, achieving the most 4′-N-demethyl-vicenistatin, at 0.1921 g/L, which was 17% and 283% higher than the RSM-optimized and initial medium approaches, respectively. This study represents pioneering work on statistically guided optimization strategies for enhancing 4′-N-demethyl-vicenistatin production through medium optimization.

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“…2.2.2. Algorithm Structure of GA-ANN GA originated from computer simulation studies conducted on biological systems is a stochastic global search optimization method [16]. It simulates phenomena such as replication, crossover, and variation occurring in natural selection and inheritance [11].…”

Section: Data Collectionmentioning

confidence: 99%

“…The goal of these algorithms is to improve their performance and prediction accuracy by modifying the weights and structure of the neural network. Using GA to optimize ANN can not only enhance their performance and generalization ability but also improve their global search ability and interpretability [16]. GA can also improve scalability, which means they can be extended to multi-objective optimization and multiple types of ANN structure and weight parameter optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Advancing Concrete Mix Proportion through Hybrid Intelligence: A Multi-Objective Optimization Approach

Chen,

Xu,

Wen

et al. 2023

Materials

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Concrete mixture design has been a key focus in concrete research. This study presents a new method for concrete mixture design by combining artificial neural networks (ANN), genetic algorithms (GA), and Scipy libraries for hybrid intelligent modeling. This method enables the prediction of concrete mechanical properties and the optimization of mix proportions with single or multi-objective goals. The GA is used to optimize the structure and weight parameters of ANN to improve prediction accuracy and generalization ability (R2 > 0.95, RMSE and MAE < 10). Then, the Scipy library combined with GA-ANN is used for the multi-objective optimization of concrete mix proportions to balance the compressive strength and costs of concrete. Moreover, an AI-based concrete mix proportion design system is developed, utilizing a user-friendly GUI to meet specific strength requirements and adapt to practical needs. This system enhances optimization design capabilities and sets the stage for future advancements. Overall, this study focuses on optimizing concrete mixture design using hybrid intelligent modeling and multi-objective optimization, which contributes to providing a novel and practical solution for improving the efficiency and accuracy of concrete mixture design in the construction industry.

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Comparative study on the extraction efficiency, characterization, and bioactivities of Bletilla striata polysaccharides using response surface methodology (RSM) and genetic algorithm-artificial neural network (GA-ANN)

Cited by 27 publications

References 85 publications

Bletilla striata Polysaccharide-/Chitosan-Based Self-Healing Hydrogel with Enhanced Photothermal Effect for Rapid Healing of Diabetic Infected Wounds via the Regulation of Microenvironment

Bletilla striata Polysaccharide-/Chitosan-Based Self-Healing Hydrogel with Enhanced Photothermal Effect for Rapid Healing of Diabetic Infected Wounds via the Regulation of Microenvironment

Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by Streptomyces parvus Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm

Advancing Concrete Mix Proportion through Hybrid Intelligence: A Multi-Objective Optimization Approach

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