Evidence map›Paper›PMID 41863963›Full record

ArticleUltrasonics sonochemistry2026

Ultrasonic-assisted extraction, purification, identification, and bioactivity evaluation of phlorotannins from Sargassum fusiforme: A comparative study of RSM and SVM-GA.

Weibin He, Qimiao Kong, Haoran Li, Yuhan Wu, Runyan Huang, Li Yu, Shanshan Shen, Chaojian Xu, Yuehua Han, Yuting Ai and 1 more

Abstract readComparative Study
In one paragraph

Article in Ultrasonics sonochemistry, 2026. 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. Article
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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

11 authors.

Weibin HeDepartment of Pharmacy, School of Medicine, Hangzhou City University, Hangzhou 310015, China; College of Pharmaceutical Sciences, Zhejiang University, Hangzhou 310058, China.
Qimiao KongSchool of Medicine, Huaqiao University, Quanzhou 362021, China.
Haoran LiDepartment of Pharmacy, School of Medicine, Hangzhou City University, Hangzhou 310015, China.
Yuhan WuDepartment of Pharmacy, School of Medicine, Hangzhou City University, Hangzhou 310015, China.
Runyan HuangDepartment of Pharmacy, School of Medicine, Hangzhou City University, Hangzhou 310015, China.
Li YuSchool of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou 310053, China.
Shanshan ShenDepartment of Pharmacy, School of Medicine, Hangzhou City University, Hangzhou 310015, China.
Chaojian XuDepartment of Pharmacy, School of Medicine, Hangzhou City University, Hangzhou 310015, China.
Yuehua HanDepartment of Gastroenterology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou 310000, China.
Yuting AiZhejiang Shiyuan Jinniu Biological Technology Co., Ltd., Wenzhou 325700, China.
Jianping JiangDepartment of Pharmacy, School of Medicine, Hangzhou City University, Hangzhou 310015, China; Hangzhou Lin'an Traditional Chinese Medicine Hospital, Affiliated Hospital, Hangzhou City University, Hangzhou 311300, China. Electronic address: jiangjp@hzcu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sargassum fusiforme is a medicinal and edible species present in China, Korea, and Japan, and its phlorotannins are considered valuable bioactive components. Response surface methodology (RSM) and a support vector machine integrated with a genetic algorithm (SVM-GA) were used in this study to optimize ultrasonic-assisted extraction (UAE) of S. fusiforme phlorotannins (SFP), to compare its efficiency with convenient water bath extraction and ultrasonic-assisted enzymatic extraction, and to conduct pilot-scale experiments. Furthermore, this study explored the effect of ultrasound treatment on the adsorption and desorption efficiency of SFP using macroporous resins. The findings indicated that the optimization performance of the SVM-GA model was superior to that of RSM, and the following optimal UAE conditions were identified: 75 min extraction time, 70 ℃ extraction temperature, 20 mL/g liquid-solid ratio, 30% ethanol concentration, and 320 W ultrasonic power. Under these conditions, a total phlorotannin content of 0.52 ± 0.021 mg phloroglucinol equivalents/g and a total phenolic content of 3.42 ± 0.071 mg gallic acid equivalents/g were obtained. Macroporous adsorption resin purification experiments revealed that HPD600 was one of the most effective resins for SFP purification. At the selected ultrasonic intensity of 65 W, ultrasound enhanced the adsorption and desorption capacities of SFP on HPD600 resin owing to increased hydrogen bond formation on the resin surface and surface roughness. Furthermore, the adsorption of SFP could be well described using the pseudo-second-order model and the Freundlich model. Conventional shaking-assisted HPD600-purified sample (SFP-SA) and ultrasonic-assisted HPD600-purified sample (SFP-UA) were selected to investigate the antioxidant and anti-neuroinflammatory activities. In addition, a total of 8 types of phlorotannin tentatively identified by ultra-performance liquid chromatography-quadrupole time-of-flight tandem mass spectrometry (UPLC-Q-TOF-MS/MS). This method is expected to be effective for extracting and purifying SFP, and the findings highlight its promising antioxidant and anti-neuroinflammatory properties, suggesting broad applications across the functional food industry.

Indexed as

Chemical FractionationSargassumSupport Vector MachineTanninsUltrasonic WavesAdsorptionAntioxidantsEdible SeaweedsGenetic AlgorithmsAntioxidantsTanninsAnti-neuroinflammatoryMacroporous adsorption resinsSargassum fusiforme phlorotanninsSVM–GAUltrasonic-assisted purification

Identifiers

PMID41863963
PMCPMC13022700

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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.