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31 pages, 9469 KiB  
Article
Elucidation of Medusozoan (Jellyfish) Venom Constituent Activities Using Constellation Pharmacology
by Angel A. Yanagihara, Matías L. Giglio, Kikiana Hurwitz, Raechel Kadler, Samuel S. Espino, Shrinivasan Raghuraman and Baldomero M. Olivera
Toxins 2024, 16(10), 447; https://doi.org/10.3390/toxins16100447 - 17 Oct 2024
Abstract
Within the phylum Cnidaria, sea anemones (class Anthozoa) express a rich diversity of ion-channel peptide modulators with biomedical applications, but corollary discoveries from jellyfish (subphylum Medusozoa) are lacking. To bridge this gap, bioactivities of previously unexplored proteinaceous and small molecular weight (~15 kDa [...] Read more.
Within the phylum Cnidaria, sea anemones (class Anthozoa) express a rich diversity of ion-channel peptide modulators with biomedical applications, but corollary discoveries from jellyfish (subphylum Medusozoa) are lacking. To bridge this gap, bioactivities of previously unexplored proteinaceous and small molecular weight (~15 kDa to 5 kDa) venom components were assessed in a mouse dorsal root ganglia (DRG) high-content calcium-imaging assay, known as constellation pharmacology. While the addition of crude venom led to nonspecific cell death and Fura-2 signal leakage due to pore-forming activity, purified small molecular weight fractions of venom demonstrated three main, concentration-dependent and reversible effects on defined heterogeneous cell types found in the primary cultures of mouse DRG. These three phenotypic responses are herein referred to as phenotype A, B and C: excitatory amplification (A) or inhibition (B) of KCl-induced calcium signals, and test compound-induced disturbances to baseline calcium levels (C). Most notably, certain Alatina alata venom fractions showed phenotype A effects in all DRG neurons; Physalia physalis and Chironex fleckeri fractions predominantly showed phenotype B effects in small- and medium-diameter neurons. Finally, specific Physalia physalis and Alatina alata venom components induced direct excitatory responses (phenotype C) in glial cells. These findings demonstrate a diversity of neuroactive compounds in jellyfish venom potentially targeting a constellation of ion channels and ligand-gated receptors with broad physiological implications. Full article
(This article belongs to the Section Animal Venoms)
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Figure 1
<p>Biochemical signaling pathways that result in increased intracellular calcium concentration ([Ca<sup>2+</sup>]<sub>i</sub>). Different cell processes can lead to the influx of extracellular Ca<sup>2+</sup> or the release of Ca<sup>2+</sup> from the intracellular stores, both leading to increased [Ca<sup>2+</sup>]<sub>i</sub>. When assessing the effects of venom component toxins by constellation pharmacology using high extracellular potassium [K<sup>+</sup>] pulses (e.g., 25 mM KCl) as a depolarizing stimulus, three different effects could be observed according to the interaction of the venom components to one or more of the mechanistic pathways depicted here: amplification (phenotype A), which augments or prolongs subsequent membrane depolarization duration (e.g., potential mechanisms include blocking voltage-gated potassium channels or delayed inactivation of sodium channels); inhibition (phenotype B), which decreases or shortens the membrane depolarization duration (e.g., potential mechanisms include blocking voltage-gated sodium or calcium channels or activation of hyperpolarizing ion channels including GABA or glycine receptors); and direct effects (phenotype C) on voltage-gated ion channels and ligand-gated ion channels, including G-protein coupled receptors (GPCRs), causing a depolarizing elevation of cytosolic calcium levels. Finally, as with other calcium imaging-based assays, calcium ionophores and cytolytic events involving the loss of cell membrane integrity can result in a transient increase in the intracellular Ca<sup>2+</sup>, which is most often irreversible and leads to cell death with leakage of the Fura-2.</p>
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<p>Output of the constellation pharmacology assay. <b>(A</b>) Representative tracing of two pulses of KCl with the application and incubation with phosphate-buffered saline (PBS) as a control. The application of extracellular KCl causes membrane depolarization, leading to an elevation of intracellular calcium and thus an increase in the Fura-2 signal. Note that the signal peak heights are reproducible and reversible; (<b>B</b>) Representative images of dorsal root ganglia (DRG) cells indicating Fura-2 intensity at the time of PBS incubation (<span class="html-italic">t</span><sub>1</sub>) and during the application of KCl (<span class="html-italic">t</span><sub>2</sub>) from A are shown.</p>
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<p>Representation of the different phenotypes evoked by venom fractions. <span class="html-italic">X</span>-axis is time in minutes and <span class="html-italic">Y</span>-axis represents the ratiometric emission of the Fura-2 excited at 340 nm and 380 nm. (<b>A</b>) Phenotype A: amplification of the KCl-induced Fura-2 signal. This phenotype could be elicited by voltage-gated potassium channel (VGKC) inhibitors, blockers of the voltage-gated sodium channel (VGSC) inhibition, or modulation of ligand-gated receptors; (<b>B</b>) phenotype B: inhibition of the KCl-induced Fura-2 signal. VGSC inhibitors or modulators of ligand-gated receptors are examples that could lead to this phenotype; (<b>C</b>) phenotype C: direct effect consisting of a spontaneous (independent from the depolarization stimulus) increase in [Ca<sup>2+</sup>]<sub>i</sub> upon incubation with the venom fraction. VGSC activators or ligand-gated receptor modulators could directly induce an increase in the influx of Ca<sup>2+</sup>; (<b>D</b>) example of dual effects. Complex venom fractions or isolated compounds could elicit a combination of phenotypes (typically A and C, or B and C) on the same cell. Some VGKC blockers, such as the conotoxin κM-RIIIJ, for instance, could cause both a direct effect and amplification [<a href="#B21-toxins-16-00447" class="html-bibr">21</a>].</p>
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<p>Porin activity of the <span class="html-italic">Alatina alata</span> crude venom using constellation pharmacology: (<b>A</b>) Representative traces of DRG cells exposed to crude venom for 3.5 min (blue and red boxes). The <span class="html-italic">X</span>-axis represents time. The <span class="html-italic">Y</span>-axis represents the ratiometric measurement of Fura-2 at 340 nm and 380 nm. K40 = 10 s pulse with 40 mM KCl; K = 10 s pulse of 25 mM KCl. Untreated crude venom (left) causes an increase in [Ca<sup>2+</sup>]i and sustained high ratiometric values. Crude venom denatured by heating at 100 °C for 10 min showed no effect; (<b>B</b>) comparison of the ratiometric signal (top row) with the deconvoluted signal of Fura-2 excited at 340 nm (middle row) and 380 nm (lower row); (<b>C</b>) bright field images of the DRG cells following 3.5 min treatment with crude or heat-denatured venom before and after the exposure with the crude venom. Scale bar = 100 μm.</p>
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<p>Size fractionation chromatograms of cnidarian venom preparations using size exclusion column high-performance liquid chromatography (SEC-HPLC). Major peaks are labeled: Peak I, molecular weight (MW) of ~250 kDa to 60 kDa comprising large proteins; Peak II MW ~50 kDa to 30 kDa comprising proteins including porins; Peak III MW ~15 kDa to 5 kDa comprising peptides and molecules investigated in this study; Peak IV MW ~3 kDa to 1 kDa. (<b>A</b>) <span class="html-italic">P. physalis</span> venom; (<b>B</b>) <span class="html-italic">C. fleckeri</span> venom; (<b>C</b>) <span class="html-italic">A. alata</span> venom. The fractions highlighted in Peak III were analyzed as subfractions (Peak III A–D) as well as pooled together.</p>
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<p>Overall comparison of the effect of venom Peak III from three medusozoan species using constellation pharmacology: (<b>A</b>) proportion of different neuron responses; (<b>B</b>) profile of representative cells comprising panel A. Two profiles of each neuron class are shown. From top to bottom: large-diameter unlabeled neurons (large gray circle), medium-diameter GFP-positive neurons (peptidergic nociceptors) (green square), medium-diameter IB4-positive neurons (non-peptidergic nociceptors) (orange square), and small-unlabeled neurons (gray triangle). The <span class="html-italic">x</span> axis represents time. The <span class="html-italic">y</span> axis represents the ratiometric measurement of Fura-2 at 340 nm and 380 nm. K = 10-s pulse with 25 mM KCl. Vehicle control: white box = 3.5 min incubation with PBS. The incubation with the venom fractions is represented by the blue (<span class="html-italic">P. physalis</span>), orange (<span class="html-italic">C. fleckeri</span>), and green (<span class="html-italic">A. alata</span>) boxes.</p>
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<p>Effect of the Peak III pooled venom fractions from <span class="html-italic">Physalia physalis</span> on DRG cells: (<b>A</b>) proportion of different cell types responding to the peptide fraction of <span class="html-italic">P. physalis</span> using two different concentrations; (<b>B</b>) representative calcium traces from panel A exposed to the venom fraction for 3.5 min (blue box). Three profiles of each neuron class are shown. From top to bottom: glial cells, large-unlabeled neurons (L1–L4), large-GFP positive neurons (L5–L6), medium-GFP positive neurons (peptidergic nociceptors), medium-size IB4 positive neurons (non-peptidergic nociceptors), and small-unlabeled neurons. The <span class="html-italic">X</span> axis represents time. The <span class="html-italic">Y</span> axis represents the ratiometric measurement of Fura-2 at 340 nm and 380 nm. K = 10 s pulse with 25 mM KCl; A = 10 s pulse of AITC; M = 10 s pulse of menthol; C = 10 s pulse of capsaicin; K40 = 10 sec pulse of 40 mM KCl. Vehicle control: white box = 2.5 min incubation with PBS. Grey box = 3.5 min incubation with the conotoxin κM-RIIIJ.</p>
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<p>Effect of the Peak III pooled venom fraction from <span class="html-italic">Chironex fleckeri</span> on DRG cells: (<b>A</b>) proportion of different cell classes responding to the peptide fraction of <span class="html-italic">C. fleckeri</span> using two different concentrations; (<b>B</b>) profile of representative cells from panel A exposed to the venom fraction for 3.5 min (orange box). Three profiles of each neuron class are shown. From top to bottom: glial cells, large-unlabeled neurons (L1–L4), large-GFP positive neurons (L5–L6), medium-GFP positive neurons (peptidergic nociceptors), medium-size IB4 positive neurons (non-peptidergic nociceptors), and small-unlabeled neurons. The <span class="html-italic">X</span> axis represents time. The <span class="html-italic">Y</span> axis represents the ratiometric measurement of Fura-2 at 340 nm and 380 nm. K = 10 s pulse with 25 mM KCl; A = 10 s pulse of AITC; M = 10 s pulse of menthol; C = 10 s pulse of capsaicin; K40 = 10 s pulse of 40 mM KCl. Vehicle control:white box = 3.5 min incubation with PBS. Grey box = 3.5 min incubation with the conotoxin κM-RIIIJ.</p>
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<p>Effects of Peak III pooled venom fractions from <span class="html-italic">Alatina alata</span> on DRG cells: (<b>A</b>) proportions of responses in different cell classes at two different concentrations; (<b>B</b>) time-course Fura-2 signal intensity response profile of representative cells from panel A exposed to Peak III for 3.5 min (green box). Three profiles of each neuron class are shown. From top to bottom: glial cells, large-unlabeled neurons (L1–L4), large-GFP positive neurons (L5–L6), medium-GFP positive neurons (peptidergic nociceptors), medium-size IB4 positive neurons (non-peptidergic nociceptors), and small-unlabeled neurons. The <span class="html-italic">X</span> axis represents time. The <span class="html-italic">Y</span> axis represents the ratiometric measurement of Fura-2 at 340 nm and 380 nm. K = 10 s pulse with 25 mM KCl; A = 10 s pulse of AITC; M = 10 s pulse of menthol; C = 10 s pulse of capsaicin; K40 = 10 s pulse of 40 mM KCl. Vehicle control: white box = 3.5 min incubation with PBS. Grey box = 3.5 min incubation with the conotoxin κM-RIIIJ.</p>
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<p>Bioactivity-resolution within Peak III of <span class="html-italic">A. alata</span> using constellation pharmacology: (<b>A</b>) chromatogram of individual and pooled fractions comprising Peak III of <span class="html-italic">Alatina alata</span> venom shown in <a href="#toxins-16-00447-f004" class="html-fig">Figure 4</a>. Each shade of green (A–D) represents the different subfractions used for the constellation pharmacology assay; (<b>B</b>) proportion of neurons responding to the different subfractions classified by type of response.</p>
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<p>Venom-derived toxins in paralysis and pain: (<b>A</b>) Motor neuron–muscle synapse and toxin targets. Flaccid paralysis (left): the block of voltage-gated sodium channels (VGSC) inhibits the transmission of the electric signal to the neuronal terminus; the block of the voltage-gated calcium channels (VGCC) prevents the fusion of the synaptic vesicles for the release of the neurotransmitter acetylcholine (ACh). The block of the muscarinic (mAChR) and nicotinic (nAChR) acetylcholine receptors in the postsynaptic membrane inhibits the transduction of the signal into the myocyte. Tetanic paralysis: the block of voltage-gated potassium channels (VGKC) and the activation or activity prolongation of the VGSC result in more neurotransmitter release and overstimulation of the muscle. Modified from Trim and Trim 2013 [<a href="#B75-toxins-16-00447" class="html-bibr">75</a>]; (<b>B</b>) scheme of the pain-related receptors and the pain-signaling transmission to the central nervous system (CNS). Activation of the pain transducer receptors acid-sensing ion channel (ASIC) and transient receptor potential channel ankyrin 1 (TRPA1) and vanilloid 1 (TRPV1) lead to the activation of nociceptive neurons. The inhibition of either of these receptors has been related to analgesia. Additionally, the block of the VGCC at the nociceptor terminal abolishes the signal transduction to the CNS. Modified from Bohlen 2012 [<a href="#B76-toxins-16-00447" class="html-bibr">76</a>].</p>
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<p>Jellyfish collection, intact cnidae recovery and venom preparation, as described in 5.1. From left to right (arrows denote steps in this process), schematic images of <span class="html-italic">Chironex fleckeri</span>, <span class="html-italic">Alatina alata</span> and <span class="html-italic">Physalia physalis</span>; schematic representation of freshly excised tentacles (pink) in chilled 1 M trisodium citrate; spontaneously shed intact cnidae are represented as pink ovals; light micrograph of <span class="html-italic">Alatina alata</span> eurytele [<a href="#B86-toxins-16-00447" class="html-bibr">86</a>] in live replete tentacle (scale bar 65 micron, inset 15 micron); 0.5 mm mesh sieving of citrate solution of tentacles to remove shed intact cnidae from depleted tentacles; pelleted cnidae are then ruptured in a chilled pressure cell disruptor (French Press); complete ruptured slurry is quickly centrifuged to pellet collagenous structural components (capsule walls and tubules), total cnidae content venom (supernatant) is then aliquoted and snap frozen in liquid nitrogen [<a href="#B1-toxins-16-00447" class="html-bibr">1</a>].</p>
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<p>DRG dissection and dissociation protocol. Lumbar DRGs (L1–L6) were removed from the mice and transferred to a petri dish where the nerves were trimmed for cleaning. Individual DRGs were excised to expose the cells. Enzymatic tissue dissociation was performed using a trypsin solution for 20 min at 37 °C. DRGs were then mechanically dissociated by pipetting using Pasteur pipettes with decreasing diameter tips and sieved through a 45-µm cell strainer. Cell suspension was centrifuged and pelleted cells were resuspended in 100 μL of the culture medium. Aliquots of the resuspended solution were plated in 24-well plates within a silicone ring and incubated overnight in a cell culture chamber at 37 °C.</p>
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<p>Workflow to screen for effects of cnidarian venom fractions on dorsal root ganglia (DRG) cells using constellation pharmacology. Primary cultures were plated, as described in the <a href="#sec5-toxins-16-00447" class="html-sec">Section 5</a>. Eighteen hours later, DRG cells were incubated with Fura-2 for 1 h (30 min in culture chamber and 30 min at room temperature). Continuous Fura-2 calcium imaging was conducted during pulse-chase exposure of the cells in the flow cell well to control solutions, depolarizing KCl pulses and the specific pharmacological agents comprising constellation pharmacology. Venom fractions were applied in between successive KCl pulses (blue box). Cell responses (Fura-2 ratiometric intensity over time) were transformed into profiles of individual cells to be analyzed. KCl, potassium chloride 25 mM; AITC, allyl isothiocyanate (agonist of the transient receptor potential ankyrin 1 channel or TRPA1); Men, menthol (agonist of the transient receptor potential melastatin 8 channel or TRPM8); Cap, capsaicin (agonist of the transient receptor potential vanilloid 1 channel or TRPV1).</p>
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17 pages, 1944 KiB  
Article
A Water Level Forecasting Method Based on an Improved Jellyfish Search Algorithm Optimized with an Inverse-Free Extreme Learning Machine and Error Correction
by Qiwei Zhang, Weiwei Shou, Xuefeng Wang, Rongkai Zhao, Rui He and Chu Zhang
Water 2024, 16(20), 2871; https://doi.org/10.3390/w16202871 - 10 Oct 2024
Viewed by 524
Abstract
Precise water level forecasting plays a decisive role in improving the efficiency of flood prevention and disaster reduction, optimizing water resource management, enhancing the safety of waterway transportation, reducing flood risks, and promoting ecological and environmental protection, which is crucial for the sustainable [...] Read more.
Precise water level forecasting plays a decisive role in improving the efficiency of flood prevention and disaster reduction, optimizing water resource management, enhancing the safety of waterway transportation, reducing flood risks, and promoting ecological and environmental protection, which is crucial for the sustainable development of society. This study proposes a hybrid water level forecasting model based on Time-Varying Filter-based Empirical Mode Decomposition (TVFEMD), Inverse-Free Extreme Learning Machine (IFELM), and error correction. Firstly, historical water level data are decomposed into different modes using TVFEMD; secondly, the Improved Jellyfish Search (IJS) algorithm is employed to optimize the IFELM, and subsequently, the optimized IFELM independently forecasts each sub-sequence and obtains the predictive results of each sub-sequence; thirdly, an Online Sequential Extreme Learning Machine (OSELM) model is used to correct data errors, and the initial predictive results and error prediction results are added together to obtain the final prediction for the sub-sequence; and finally, the final prediction for the sub-sequences are added to obtain the prediction results of the entire water level sequence. Taking the daily water level data from 2006 to 2018 in Taihu, China as the research object, this paper compares the proposed model with the ELM, BP, LSTM, IFELM, TVFEMD-IFELM, and TVFEMD-IFELM-OSELM models. The results show that the TVFEMD-IJS-IFELM-OSELM model established in this study has high prediction accuracy and strong stability and is suitable for water level forecasting. Full article
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<p>Flowchart of error correction process.</p>
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<p>A structural diagram of the TVFEMD-IJS-IFELM-OSELM water level prediction model.</p>
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<p>Decomposition components of Taihu’s daily water level time series.</p>
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<p>NSE for different models.</p>
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<p>Daily water level forecasts for Taihu in the 2016–2018 period.</p>
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<p>Comparison of forecast errors for different models.</p>
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<p>A 95% scatter plot for Taihu’s daily water level prediction results.</p>
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16 pages, 4169 KiB  
Article
Massive Outbreak of Aurelia coerulea in Geoje Bay, Korea
by Kyoung Yeon Kim, Seok Hyun Youn, Seo Yeol Choi and Wongyu Park
Water 2024, 16(19), 2846; https://doi.org/10.3390/w16192846 - 7 Oct 2024
Viewed by 367
Abstract
This study was carried out to elucidate the causes of massive outbreaks of Aurelia coerulea in Geoje Bay, Korea, from November 2022 to October 2023. Adult medusae consistently spawn with planulae, and the populations of A. coerulea in Geoje Bay could be [...] Read more.
This study was carried out to elucidate the causes of massive outbreaks of Aurelia coerulea in Geoje Bay, Korea, from November 2022 to October 2023. Adult medusae consistently spawn with planulae, and the populations of A. coerulea in Geoje Bay could be categorized into current-year and overwintering populations. The current-year population began with the emergence of ephyrae in February and grew until October, while the overwintering population comprised a mixture of surviving current-year population and additional individuals that joined during the warm season. The size of the planulae are significantly larger than the annual average during the cold season. These results appear to be the energy accumulation of planulae for polyp formation under low water temperatures. Planulae form polyps within a temperature range of 5–25 °C, suggesting the possibility of year-round polyp recruitment. In Geoje Bay, the highest appearance rate of A. coerulea was in April (8.71 ± 12.5 ind. m−3), with ephyrae experiencing higher growth rates up to the young medusa stage. However, from April, a decline in zooplankton biomass resulted in reduced growth rates in adults, indicating that jellyfish growth was primarily regulated by food availability. Additionally, submersed oyster shells in oyster farms served as the main habitat for jellyfish polyps. A. coerulea populations were also characterized by the continuous spawning of planulae throughout the year. In conclusion, this study suggests that stable polyp habitats, abundant food supply during the initial developmental period of the population, and suitable ranges of water temperature were significant factors inducing the massive outbreak of A. coerulea in Geoje Bay, Korea. Full article
(This article belongs to the Special Issue Aquatic Environmental Pollution and Ecotoxicological Studies)
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<p>Map of the sampling stations in Geoje Bay, Korea (Red dots: Sample and survey locations).</p>
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<p>Average monthly environmental data from November 2022 to October 2023: (<b>a</b>) water temperature and salinity, (<b>b</b>) nutrients (DIN and DIP), (<b>c</b>) total Chl-<span class="html-italic">a</span> concentration, and (<b>d</b>) total abundance of zooplankton.</p>
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<p><span class="html-italic">Aurelia coerulea</span> polyps residing on artificial structures. Polyps attached (<b>a</b>) to submerged oyster lines, where elongated polyps indicate ongoing strobilation; (<b>b</b>) to the surface of <span class="html-italic">Ciona</span> sp.; and (<b>c</b>) to the underside of a pontoon with red tips on polyps indicating strobilation or detecting ephyrae. Red circles are polyp colonies and yellow arrows indicate ongoing strobilation.</p>
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<p>Average monthly density of <span class="html-italic">Aurelia coerulea</span> at different developmental stages. Data are presented as the mean ± S.D.</p>
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<p>Size frequency distribution of <span class="html-italic">Aurelia coerulea</span> in the study area (gray bars: overwintering population; black bars: current-year population).</p>
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<p>Average size–weight relationship of <span class="html-italic">Aurelia coerulea</span> (<span class="html-italic">n</span> = 44).</p>
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<p>Growth rates of <span class="html-italic">Aurelia coerulea</span> and zooplankton biomass. Zooplankton biomass represents the mean values from three sampling points. Data are presented as the mean ± S.D.</p>
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<p>Size distribution of <span class="html-italic">Aurelia coerulea</span> planulae. The boxplots represent the median (line within the box), interquartile range (IQR; box), and potential outliers (points outside the whiskers) of planulae size (µm). The whiskers extend to the lowest and highest values within 1.5 times the IQR from the lower and upper quartiles.</p>
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<p>Cumulative polyp formation rate (%) for <span class="html-italic">Aurelia coerulea</span> planulae at temperature ranging from 5 °C to 25 °C. Data are presented as the mean ± S.D.</p>
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25 pages, 3831 KiB  
Article
Solving Optimal Power Flow Using New Efficient Hybrid Jellyfish Search and Moth Flame Optimization Algorithms
by Chiva Mayouf, Ahmed Salhi, Fanta Haidara, Fatima Zahra Aroua, Ragab A. El-Sehiemy, Djemai Naimi, Chouaib Aya and Cheikh Sidi Ethmane Kane
Algorithms 2024, 17(10), 438; https://doi.org/10.3390/a17100438 - 1 Oct 2024
Viewed by 414
Abstract
This paper presents a new optimization technique based on the hybridization of two meta-heuristic methods, Jellyfish Search (JS) and Moth Flame Optimizer (MFO), to solve the Optimal Power Flow (OPF) problem. The JS algorithm offers good exploration capacity but lacks performance in its [...] Read more.
This paper presents a new optimization technique based on the hybridization of two meta-heuristic methods, Jellyfish Search (JS) and Moth Flame Optimizer (MFO), to solve the Optimal Power Flow (OPF) problem. The JS algorithm offers good exploration capacity but lacks performance in its exploitation mechanism. To improve its efficiency, we combined it with the Moth Flame Optimizer, which has proven its ability to exploit good solutions in the search area. This hybrid algorithm combines the advantages of both algorithms. The performance and precision of the hybrid optimization approach (JS-MFO) were investigated by minimizing well-known mathematical benchmark functions and by solving the complex OPF problem. The OPF problem was solved by optimizing non-convex objective functions such as total fuel cost, total active transmission losses, total gas emission, total voltage deviation, and the voltage stability index. Two test systems, the IEEE 30-bus network and the Mauritanian RIM 27-bus transmission network, were considered for implementing the JS-MFO approach. Experimental tests of the JS, MFO, and JS-MFO algorithms on eight well-known benchmark functions, the IEEE 30-bus, and the Mauritanian RIM 27-bus system were conducted. For the IEEE 30-bus test system, the proposed hybrid approach provides a percent cost saving of 11.4028%, a percent gas emission reduction of 14.38%, and a percent loss saving of 50.60% with respect to the base case. For the RIM 27-bus system, JS-MFO achieved a loss percent saving of 50.67% and percent voltage reduction of 62.44% with reference to the base case. The simulation results using JS-MFO and obtained with the MATLAB 2009b software were compared with those of JS, MFO, and other well-known meta-heuristics cited in the literature. The comparison report proves the superiority of the JS-MFO method over JS, MFO, and other competing meta-heuristics in solving difficult OPF problems. Full article
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<p>Flowchart of the JS-MFO algorithm.</p>
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<p>IEEE 30-bus single-line diagram.</p>
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<p>Convergence curves of JS, MFO and JS-MFO algorithms for case 1.</p>
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<p>Convergence rates of JS, MFO, and JS-MFO algorithms for case 2.</p>
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<p>Convergence rates of JS, MFO, and JS-MFO algorithms for case 3.</p>
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<p>Convergence rates of JS, MFO, and JS-MFO for Case 4.</p>
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<p>Convergence curves of JS, MFO, and JS-MFO algorithms for case 7.</p>
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<p>Single-line diagram of the Mauritanian electric power system 27 bus.</p>
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<p>Convergence characteristics of JS, MFO, and JS-MFO algorithms for case 4.</p>
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<p>Convergence characteristics of JS, MFO, and JS-MFO algorithms for case 5.</p>
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<p>Voltage profile for each RIM 27-bus case using the JS-MFO algorithm.</p>
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14 pages, 2748 KiB  
Article
Identification of New Angiotensin-Converting Enzyme Inhibitory Peptides Isolated from the Hydrolysate of the Venom of Nemopilema nomurai Jellyfish
by Ramachandran Loganathan Mohan Prakash, Deva Asirvatham Ravi, Du Hyeon Hwang, Changkeun Kang and Euikyung Kim
Toxins 2024, 16(9), 410; https://doi.org/10.3390/toxins16090410 - 20 Sep 2024
Viewed by 576
Abstract
Recently, jellyfish venom has gained attention as a promising reservoir of pharmacologically active compounds, with potential applications in new drug development. In this investigation, novel peptides, isolated from the hydrolysates of Nemopilema nomurai jellyfish venom (NnV), demonstrate potent inhibitory activities against angiotensin-converting enzyme [...] Read more.
Recently, jellyfish venom has gained attention as a promising reservoir of pharmacologically active compounds, with potential applications in new drug development. In this investigation, novel peptides, isolated from the hydrolysates of Nemopilema nomurai jellyfish venom (NnV), demonstrate potent inhibitory activities against angiotensin-converting enzyme (ACE). Proteolytic enzymes—specifically, papain and protamex—were utilized for the hydrolysis under optimized enzymatic conditions, determined by assessing the degree of hydrolysis through the ninhydrin test. Comparative analyses revealed that papain treatment exhibited a notably higher degree of NnV hydrolysis compared to protamex treatment. ACE inhibitory activity was quantified using ACE kit-WST, indicating a substantial inhibitory effect of 76.31% for the papain-digested NnV crude hydrolysate, which was validated by captopril as a positive control. The separation of the NnV-hydrolysate using DEAE sepharose weak-anion-exchange chromatography revealed nine peaks under a 0–1 M NaCl stepwise gradient, with peak no. 3 displaying the highest ACE inhibition of 96%. The further purification of peak no. 3 through ODS-C18 column reverse-phase high-performance liquid chromatography resulted in five sub-peaks (3.1, 3.2, 3.3, 3.4, and 3.5), among which 3.2 exhibited the most significant inhibitory activity of 95.74%. The subsequent analysis of the active peak (3.2) using MALDI–TOF/MS identified two peptides with distinct molecular weights of 896.48 and 1227.651. The peptide sequence determined by MS/MS analysis revealed them as IVGRPLANG and IGDEPRHQYL. The docking studies of the two ACE-inhibitory peptides for ACE molecule demonstrated a binding affinity of −51.4 ± 2.5 and −62.3 ± 3.3 using the HADDOCK scoring function. Full article
(This article belongs to the Special Issue Venoms and Drugs)
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<p>Degree of enzyme hydrolysis upon NnV based on the Ninhydrin test and preliminary ACE inhibition. (<b>A</b>) Effect of different temperatures of enzyme incubation upon NnV; (<b>B</b>) Effect of enzyme concentrations on NnV; (<b>C</b>) Effect of reaction time of enzymes upon NnV; (<b>D</b>) Log-inhibitory curve of the percent ACE inhibition of papain-hydrolyzed NnV (positive control: captopril). Red arrow denotes highest hydrolysis condition. Results are expressed as mean ± standard deviation (SD), with significance denoted by * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001.</p>
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<p>Purification of ACE-inhibitory fractions using DEAE sepharose anion-exchange chromatography. (<b>A</b>) Chromatogram of fractions that were isolated from hydrolyzed crude NnV. (<b>B</b>) ACE-inhibitory activity of separated fractions. The red arrows denote the active peak. Results are expressed as mean ± standard deviation (SD), with significance denoted by *** <span class="html-italic">p</span> &lt; 0.001. The numbers 1–9 in (<b>A</b>) denote isolated peaks.</p>
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<p>Further separation of ACE-inhibitory fractions using RP-HPLC. (<b>A</b>) Chromatogram of sub peaks from active peak no. 3 isolated (<b>B</b>) ACE-inhibitory activity. The red arrow marks denote the active peak. Results were expressed as mean ± standard deviation (SD), with significance denoted by *** <span class="html-italic">p</span> &lt; 0.001. The numbers 3.1–3.5 in (<b>A</b>) denotes isolated peaks.</p>
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<p>Mass spectrum of fraction 3.2, obtained using MALDI–TOF/MS.</p>
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<p>Identification of ACE-inhibitory peptide sequence. (<b>A</b>,<b>B</b>) MS/MS peaks of identified peptides IVGRPLANG and IGDEPRHQYL from NnV-hydrolysate.</p>
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<p>Molecular docking simulations of ACE (PDB: 1O8A) protein against the isolated peptides. (<b>A</b>,<b>B</b>) Depicting the optimal docking poses at the active site for IVGRPLANG (red) and IGDEPRHQYL (blue). (<b>C</b>,<b>D</b>) The peptides’ (IVGRPLANG and IGDEPRHQYL) interactions with ACE protein residues.</p>
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30 pages, 3343 KiB  
Review
Typical Marine Ecological Disasters in China Attributed to Marine Organisms and Their Significant Insights
by Lulu Yao, Peimin He, Zhangyi Xia, Jiye Li and Jinlin Liu
Biology 2024, 13(9), 678; https://doi.org/10.3390/biology13090678 - 30 Aug 2024
Viewed by 1788
Abstract
Owing to global climate change or the ever-more frequent human activities in the offshore areas, it is highly probable that an imbalance in the offshore ecosystem has been induced. However, the importance of maintaining and protecting marine ecosystems’ balance cannot be overstated. In [...] Read more.
Owing to global climate change or the ever-more frequent human activities in the offshore areas, it is highly probable that an imbalance in the offshore ecosystem has been induced. However, the importance of maintaining and protecting marine ecosystems’ balance cannot be overstated. In recent years, various marine disasters have occurred frequently, such as harmful algal blooms (green tides and red tides), storm surge disasters, wave disasters, sea ice disasters, and tsunami disasters. Additionally, overpopulation of certain marine organisms (particularly marine faunas) has led to marine disasters, threatening both marine ecosystems and human safety. The marine ecological disaster monitoring system in China primarily focuses on monitoring and controlling the outbreak of green tides (mainly caused by outbreaks of some Ulva species) and red tides (mainly caused by outbreaks of some diatom and dinoflagellate species). Currently, there are outbreaks of Cnidaria (Hydrozoa and Scyphozoa organisms; outbreak species are frequently referred to as jellyfish), Annelida (Urechis unicinctus Drasche, 1880), Mollusca (Philine kinglipini S. Tchang, 1934), Arthropoda (Acetes chinensis Hansen, 1919), and Echinodermata (Asteroidea organisms, Ophiuroidea organisms, and Acaudina molpadioides Semper, 1867) in China. They not only cause significant damage to marine fisheries, tourism, coastal industries, and ship navigation but also have profound impacts on marine ecosystems, especially near nuclear power plants, sea bathing beaches, and infrastructures, posing threats to human lives. Therefore, this review provides a detailed introduction to the marine organisms (especially marine fauna species) causing marine biological disasters in China, the current outbreak situations, and the biological backgrounds of these outbreaks. This review also provides an analysis of the causes of these outbreaks. Furthermore, it presents future prospects for marine biological disasters, proposing corresponding measures and advocating for enhanced resource utilization and fundamental research. It is recommended that future efforts focus on improving the monitoring of marine biological disasters and integrating them into the marine ecological disaster monitoring system. The aim of this review is to offer reference information and constructive suggestions for enhancing future monitoring, early warning systems, and prevention efforts related to marine ecological disasters in support of the healthy development and stable operation of marine ecosystems. Full article
(This article belongs to the Special Issue Biology, Ecology and Management of Aquatic Macrophytes)
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<p>The large-scale outbreak of green tides and red tides occurred in China. (<b>a</b>) A green tide event occurred in the Yellow Sea in July 2019; (<b>b</b>) A red tide event occurred in the East China Sea in June 2019.</p>
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<p>The outbreak of jellyfish occurred in the China Sea. On 21 June 2021, the jellyfish bloom was observed in the offshore waters of the Yellow Sea (<b>a</b>,<b>b</b>); on 26 June 2021 (<b>c</b>) and 3 June 2024 (<b>d</b>), the jellyfish bloom was observed in the East China Sea. The red or white dashed arrows indicate the location of the jellyfish that have been spotted.</p>
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<p>The outbreak of <span class="html-italic">Urechis unicinctus</span> Drasche, 1880; <span class="html-italic">Philine kinglipini</span> S. Tchang, 1934; and <span class="html-italic">Acetes chinensis</span> Hansen, 1919, occurred in China. <span class="html-italic">Urechis unicinctus</span> was discovered in the seafloor habitats of Jiaozhou Bay on 1 August 2019 (<b>a</b>); an outbreak of <span class="html-italic">P. kinglipini</span> occurred in the seawaters of Jiaozhou Bay in 2022 [<a href="#B89-biology-13-00678" class="html-bibr">89</a>] (<b>b</b>); <span class="html-italic">Acetes chinensis</span> were captured in the Southern Yellow Sea in 2024 (<b>c</b>). Among them, the white dashed arrow indicates the sediment collected from the seafloor, and the red dashed arrow indicates <span class="html-italic">U. unicinctus</span>.</p>
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<p>In 2018, an outbreak of <span class="html-italic">Acanthaster planci</span> Linnaeus, 1758, occurred in the sea area of Xisha Islands [<a href="#B140-biology-13-00678" class="html-bibr">140</a>] (<b>a</b>) (Reproduced with permission; Copyright 2021; Science China Press); in 2021, an outbreak of <span class="html-italic">Asterina pectinifera</span> Muller and Troschel, 1842 took place in the sea area near Laopian Island, Dalian [<a href="#B126-biology-13-00678" class="html-bibr">126</a>] (<b>b</b>); on June 22, 2019, the Ophiuroidea species was collected in the East China Sea (<b>c</b>); in May 2017, the population of Ophiuroidea species was observed in the sea area of north Yellow Sea [<a href="#B173-biology-13-00678" class="html-bibr">173</a>]; (<b>d</b>) (Reproduced with permission; Copyright © 2019; Chinese Society for Oceanology and Limnology; Science Press and Springer-Verlag GmbH Germany; part of Springer Natures); and <span class="html-italic">Acaudina molpadioides</span> Semper, 1867 was collected from the East China Sea in 2018 [<a href="#B196-biology-13-00678" class="html-bibr">196</a>] (<b>e</b>). The white dashed arrow indicates the Ophiuroidea species collected from the seafloor sediments.</p>
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<p>Due to their culinary appeal and distinctive flavor, starfish are frequently utilized as accompaniments in Chinese hotpot cuisine (<b>a</b>); some species of jellyfish have edible oral arms, which are commonly prepared as cold shredded jellyfish in China (<b>b</b>).</p>
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14 pages, 3209 KiB  
Article
A Three–Year Comparison of Fluctuations in the Occurrence of the Giant Jellyfish (Nemopilema nomurai)
by Sunyoung Oh, Kyoungyeon Kim, Seokhyun Youn, Sara Lee, Geunchang Park, Wooseok Oh and Kyounghoon Lee
Water 2024, 16(16), 2265; https://doi.org/10.3390/w16162265 - 11 Aug 2024
Viewed by 840
Abstract
In this study, acoustic, sighting, trawl, and marine environmental surveys were used to determine the vertical distribution and density of giant jellyfish that have been observed in Korean waters over the past 3 years. From 2020 to 2022, annual surveys were conducted in [...] Read more.
In this study, acoustic, sighting, trawl, and marine environmental surveys were used to determine the vertical distribution and density of giant jellyfish that have been observed in Korean waters over the past 3 years. From 2020 to 2022, annual surveys were conducted in May and July in the East China Sea and waters adjacent to South Korea. The acoustic data were processed by identifying and eliminating all signals considered as noise while excluding those suspected to be jellyfish signals. Subsequently, a single target detection method was employed. Giant jellyfish are distributed mostly in the middle and low layers. In May 2021, the average population density of giant jellyfish was recorded as 11.6 (ind./ha), which was the highest density. In July 2022, this value decreased to 1.7 (ind./ha), marking the lowest density. The sighting survey, which allows for the identification of jellyfish distributed in the surface layer, exhibited a difference of approximately 0.13 times compared to the acoustic survey conducted in the middle and low layers in 2020. In 2021 and 2022, this difference was approximately 0.11 times and 0.24 times, respectively. The average of this difference was 0.16 times or greater. Full article
(This article belongs to the Section Biodiversity and Functionality of Aquatic Ecosystems)
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<p>A map of the survey station, which has been under investigation for 3 years ((<b>a</b>): East China Sea and (<b>b</b>): coastal waters in Korea).</p>
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<p>Arrangemenz of the jellyfish trawl net used in this study.</p>
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<p>Schematic N. jellyfish Trawl’s Kite.</p>
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<p>Vertical distribution of giant jellyfish over 3 years.</p>
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<p>Vertical distribution of water temperature and salinity in the survey area.</p>
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<p>Acoustic survey distribution density over 3 years.</p>
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<p>Sighting survey distribution density over 3 years.</p>
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<p>Correlation of acoustic survey density and sighting survey density.</p>
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19 pages, 2780 KiB  
Article
Comparative Analysis of Tentacle Extract and Nematocyst Venom: Toxicity, Mechanism, and Potential Intervention in the Giant Jellyfish Nemopilema nomurai
by Xiao-Yu Geng, Ming-Ke Wang, Xiao-Chuan Hou, Zeng-Fa Wang, Yi Wang, Die-Yu Zhang, Blessing Danso, Dun-Biao Wei, Zhao-Yong Shou, Liang Xiao and Ji-Shun Yang
Mar. Drugs 2024, 22(8), 362; https://doi.org/10.3390/md22080362 - 9 Aug 2024
Viewed by 1027
Abstract
The giant jellyfish Nemopilema nomurai sting can cause local and systemic reactions; however, comparative analysis of the tentacle extract (TE) and nematocyst venom extract (NV), and its toxicity, mechanism, and potential intervention are still limited. This study compared venom from TE and NV [...] Read more.
The giant jellyfish Nemopilema nomurai sting can cause local and systemic reactions; however, comparative analysis of the tentacle extract (TE) and nematocyst venom extract (NV), and its toxicity, mechanism, and potential intervention are still limited. This study compared venom from TE and NV for their composition, toxicity, and efficacy in vitro and in vivo used RAW264.7 cells and ICR mice. A total of 239 and 225 toxin proteins were identified in TE and NV by proteomics, respectively. Pathological analysis revealed that TE and NV caused heart and liver damage through apoptosis, necrosis, and inflammation, while TE exhibited higher toxicity ex vivo and in vivo. Biochemical markers indicated TE and NV elevated creatine kinase, lactatedehydrogenase, and aspartate aminotransferase, with the TE group showing a more significant increase. Transcriptomics and Western blotting indicated both venoms increased cytokines expression and MAPK signaling pathways. Additionally, 1 mg/kg PACOCF3 (the phospholipase A2 inhibitor) improved survival from 16.7% to 75% in mice. Our results indicate that different extraction methods impact venom activities, tentacle autolysis preserves toxin proteins and their toxicity, and PACOCF3 is a potential antidote, which establishes a good extraction method of jellyfish venom, expands our understanding of jellyfish toxicity, mechanism, and provides a promising intervention. Full article
(This article belongs to the Special Issue Commemorating the Launch of the Section "Marine Toxins")
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<p>Comparison and toxicity evaluation of toxins in TE and NV. (<b>A</b>) Venn analysis of proteins between TE and NV groups, n = 4. (<b>B</b>) Venn analysis of toxins between TE and NV groups, n = 4. (<b>C</b>) Overview of toxin family distributions and protein number and expression in TE and NV identified in the proteomes. (<b>D</b>) Survival analysis of ICR mice after TE injections, n = 12. (<b>E</b>) Survival analysis of ICR mice after NV injections, n = 12. (<b>F</b>) Viability of RAW264.7 cells exposed to TE, n = 6. (<b>G</b>) Viability of RAW264.7 cells exposed to NV, n = 6. (<b>H</b>) HE analysis of the heart, liver, and kidneys at 400× magnification, n = 4. (<b>I</b>) Evaluation of blood biochemical indices, including creatine kinase (CK) and lactate dehydrogenase (LDH), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine (CREA), and urea nitrogen (UREA), n = 3. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 represent the comparison of the group with the control group, and # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, and ### <span class="html-italic">p</span> &lt; 0.001 represents the comparison of the group with the TE group, with ns representing no significance.</p>
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<p>TE versus NV transcriptome overview and Western blot results. (<b>A</b>) Venn diagram of genes upregulated by TE versus NV in RAW264.7 compared to PBS treatment, n = 4. (<b>B</b>) Bubble plots of KEGG enrichment analysis of DEGs. (<b>C</b>) Protein–protein interaction networks of TE (10.45 μg/mL) and NV (32.34 μg/mL). (<b>D</b>) Comparative analysis of TE and NV co-induced upregulation of inflammatory factors in the transcriptome. All genes were calculated using log2 (fold change) and shown by thermography. (<b>E</b>,<b>F</b>) Relative gene expression of six inflammatory factors including IL-6, TNF-α, Cxcl10, IL1β, Ccl2, and Cxcl2 in RAW264.7 cells treated with TE (10.45 μg/mL) or TE (32.34 μg/mL), n = 3. (<b>G</b>) Western blotting analysis of c-fos, c-Jun, p65, and p38 phosphorylated and non-phosphorylated protein, n = 4. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 represent the comparison of the group with the control group, and # <span class="html-italic">p</span> &lt; 0.05 represents the comparison of the group with the TE group, with ns representing no significance.</p>
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<p>PACOCF3 and verapamil antagonized TE or NV toxicity in vitro. (<b>A</b>,<b>B</b>) Inhibition of TE or NV cytotoxicity in RAW264.7 cells by 10–30 μM EDTA, PACOCF3, and verapamil. n = 6. (<b>C</b>) Relative gene expression levels of three inflammatory factors, namely IL-6, IL1β, and TNF-α, in RAW264.7 cells treated with TE (10.45 μg/mL) or TE combined with PACOCF3 (20 μM) or verapamil (20 μM), n = 3. (<b>D</b>) Western blotting analysis of c-Fos, c-Jun, p65, and p38 phosphorylated and non-phosphorylated proteins, n = 4. * <span class="html-italic">p</span> &lt; 0.05, ** <span class="html-italic">p</span> &lt; 0.01, and *** <span class="html-italic">p</span> &lt; 0.001 represent the comparison of the group with the control group, and # <span class="html-italic">p</span> &lt; 0.05, and ## <span class="html-italic">p</span> &lt; 0.01 represents the comparison of the group with the TE group, with ns representing no significance.</p>
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<p>In vivo interventional effects of different inhibitors on TE. (<b>A</b>) Lethality analysis of TE interfered with PACOCF3, n = 12. (<b>B</b>) Lethality analysis of TE interfered with verapamil, n = 12. (<b>C</b>) Evaluation of blood biochemical parameters including creatine kinase (CK) and lactate dehydrogenase (LDH), aspartate aminotransferase (AST), alanine aminotransferase (ALT), creatinine (CREA), and urea nitrogen (UREA) in mice treated with TE (14 mg/kg) or TE combined with PACOCF3 (1 mg/kg) or verapamil (1 mg/kg), n = 3. (<b>D</b>) Detailed HE-stained analyses of the heart, liver, and kidneys. 400× magnification, n = 4. * <span class="html-italic">p</span> &lt; 0.05, and *** <span class="html-italic">p</span> &lt; 0.001 represent the comparison of the group with the control group, and # <span class="html-italic">p</span> &lt; 0.05, ## <span class="html-italic">p</span> &lt; 0.01, and ### <span class="html-italic">p</span> &lt; 0.001 represents the comparison of the group with the TE group, with ns representing no significance.</p>
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17 pages, 2072 KiB  
Article
Antioxidant and Anti-Atherosclerosis Activities of Hydrolyzed Jellyfish Collagen and Its Conjugate with Black Jelly Mushroom Extract
by Thunwa Binlateh, Pilaiwanwadee Hutamekalin, Soottawat Benjakul and Lalita Chotphruethipong
Foods 2024, 13(15), 2463; https://doi.org/10.3390/foods13152463 - 4 Aug 2024
Viewed by 1098
Abstract
Atherosclerosis, a noncommunicable disease caused by cholesterol plaque, can cause chronic diseases. The antiplatelet medicines used in its treatment can cause complications. Marine collagen peptides can be used as a natural atherosclerosis remedy. The present study investigated the preparation and characterization of hydrolyzed [...] Read more.
Atherosclerosis, a noncommunicable disease caused by cholesterol plaque, can cause chronic diseases. The antiplatelet medicines used in its treatment can cause complications. Marine collagen peptides can be used as a natural atherosclerosis remedy. The present study investigated the preparation and characterization of hydrolyzed collagen (HC) from jellyfish and its conjugation with black jelly mushroom extract (BJME). Their cytotoxicity and ability to prevent cholesterol-induced endothelial cell injury were also examined. HC was prepared using Alcalase or papain hydrolysis (0.2–0.4 units/g of dry matter (DM)). Higher yield, degree of hydrolysis, and antioxidant activities (AAs) were found in the HC obtained from Alcalase, especially at 0.4 units/g DM (A-0.4), compared to other processes (p < 0.05). Thus, A-0.4 was further conjugated with BJME (1–4%, w/w of HC). The HC-2%BJME conjugate showed the highest surface hydrophobicity and AAs compared to other samples. The FTIR spectra and size distribution also confirmed the conjugation between HC and BJME. When EA.hy926 endothelial cells were treated with HC or HC-2%BJME (25–1000 µg/mL), HC-2%BJME had no cytotoxicity, whereas HC at 1000 µg/mL induced cytotoxicity (p < 0.05). Both samples also exhibited protective ability against cholesterol-induced apoptosis and VE-cadherin downregulation of cells. Therefore, HC and conjugate could be natural agents for preventing atherosclerosis. Full article
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<p>Heat map of bioactive compounds in BJME identified by LC-QTOF-MS. The color gradient represents the abundance (×10<sup>5</sup>) of the compounds.</p>
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<p>FTIR spectra in the wavenumber region of 4000–800 cm<sup>−1</sup> (<b>A</b>) and elution profiles of HC and HC-2%BJME conjugate using SephadexTM G-25 gel filtration chromatography (<b>B</b>).</p>
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<p>Endothelial EA.hy962 cell viability as affected by HC (<b>A</b>) and HC-2%BJME (<b>B</b>) at various levels. Nuclear morphology after treatment with HC or HC-2%BJME (arrows indicate apoptotic nuclear morphology; scale bar = 50 µm; magnification = 20×) (<b>C</b>) and cell proliferation of EA.hy962 cells as influenced by HC (<b>D</b>) and HC-2%BJME (<b>E</b>) treatments (25–100 µg/mL) for 24 h, respectively. Values are mean ± SD (<span class="html-italic">n = 3</span>). Different lowercase letters indicate significant differences among the samples tested (<span class="html-italic">p</span> &lt; 0.05). Different uppercase letters indicate significant differences among the levels tested within the same sample group (<span class="html-italic">p</span> &lt; 0.05).</p>
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<p>Effect of cholesterol (25–100 µM) on cell viability after incubation for 24 h (<b>A</b>). Impacts of HC and HC-2%BJME at 50 µg/mL on viability (<b>B</b>), nuclear morphology (arrows indicate apoptotic nuclear morphology; scale bar = 50 µm; magnification = 20×) (<b>C</b>) and VE-cadherin expression level (<b>D</b>) of cells induced by cholesterol at 50 µM. Values are mean ± SD (<span class="html-italic">n =</span> 3). Different lowercase letters indicate significant differences among the samples tested (<span class="html-italic">p</span> &lt; 0.05). Different uppercase letters indicate significant differences among the levels tested within the same sample group (<span class="html-italic">p</span> &lt; 0.05).</p>
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47 pages, 5907 KiB  
Review
Marine Antioxidants from Marine Collagen and Collagen Peptides with Nutraceuticals Applications: A Review
by Emin Cadar, Ana-Maria Pesterau, Irina Prasacu, Ana-Maria Ionescu, Carolina Pascale, Ana-Maria Laura Dragan, Rodica Sirbu and Cezar Laurentiu Tomescu
Antioxidants 2024, 13(8), 919; https://doi.org/10.3390/antiox13080919 - 29 Jul 2024
Viewed by 1113
Abstract
Collagen peptides and marine collagen are enormous resources currently utilized. This review aims to examine the scientific literature to determine which collagen peptides derived from marine sources and which natural active antioxidants from marine collagen have significant biological effects as health-promoting nutraceuticals. Marine [...] Read more.
Collagen peptides and marine collagen are enormous resources currently utilized. This review aims to examine the scientific literature to determine which collagen peptides derived from marine sources and which natural active antioxidants from marine collagen have significant biological effects as health-promoting nutraceuticals. Marine collagen is extracted from both vertebrate and invertebrate marine creatures. For vertebrates, this includes fish skin, bones, scales, fins, and cartilage. For invertebrates, it includes mollusks, echinoderms, crustaceans, and poriferans. The method used involved data analysis to organize information for isolating and identifying marine biocompounds with antioxidant properties. Specifically, amino acids with antioxidant properties were identified, enabling the use of hydrolysates and collagen peptides as natural antioxidant nutraceuticals. The methods of extraction of hydrolyzed collagen and collagen peptides by different treatments are systematized. The structural characteristics of collagen, collagen peptides, and amino acids in fish skin and by-products, as well as in invertebrate organisms (jellyfish, mollusks, and crustaceans), are described. The antioxidant properties of different methods of collagen hydrolysates and collagen peptides are systematized, and the results are comparatively analyzed. Their use as natural antioxidant nutraceuticals expands the range of possibilities for the exploitation of natural resources that have not been widely used until now. Full article
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<p>Marine sources for the preparation of marine collagen.</p>
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<p>Scheme for obtaining marine collagen through (<b>A</b>) acid-soluble collagen method; (<b>B</b>) pepsin-soluble collagen method and (<b>C</b>) collagen peptides.</p>
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<p>Advantages and disadvantages of marine collagen extraction procedures.</p>
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<p>Structure of collagen fibers, collagen fibrils, and amino acid chains. Reprinted with permission from reference [<a href="#B34-antioxidants-13-00919" class="html-bibr">34</a>], 2023, Emin Cadar.</p>
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<p>Amino acids (EAA) in marine-derived collagen and collagen peptides.</p>
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<p>Type of methods used to demonstrate antioxidant activity.</p>
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<p>Diseases treated with antioxidant nutraceuticals that have in their compositions peptides and collagen hydrolysates.</p>
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14 pages, 4811 KiB  
Article
Jellyfish Venom Peptides Targeting Human Potassium Channels Identified through Ligand Screening: Morphometric and Molecular Identification of the Species and Antibiotic Potential
by Edirisinghe Arachchige Hashini Wasthala Edirisinghe, Buddhima Nirmani Athukorala, Minoli Perera, Bothunga Arachchige Shamali Dilhara Abeywardana, Polgahawattage Sachini Tarushika Sigera, Pasindu Eranga, Kavindu Dinuhara Theekshana, Mohamad Boudjelal, Rizwan Ali and Dinithi Champika Peiris
Mar. Drugs 2024, 22(8), 333; https://doi.org/10.3390/md22080333 - 24 Jul 2024
Viewed by 1014
Abstract
The relative lack of marine venom could be attributed to the difficulty in dealing with venomous marine animals. Moreover, the venom of marine animals consists of various bioactive molecules, many of which are proteins with unique properties. In this study, we investigated the [...] Read more.
The relative lack of marine venom could be attributed to the difficulty in dealing with venomous marine animals. Moreover, the venom of marine animals consists of various bioactive molecules, many of which are proteins with unique properties. In this study, we investigated the potential toxic proteins of jellyfish collected for ligand screening to understand the mechanism of the toxic effects of jellyfish. Since taxonomic identification is problematic due to the lack of proper keys, we conducted morphological and molecular mitochondrial DNA sequencing from COI and ITS regions. The venom extract from nematocysts found along the bell margins was used for protein characterization using SDS-gel electrophoresis and nano-liquid chromatography-tandem mass spectrometry. Ligand screening for the most potent toxin and antibacterial and cytotoxicity assays were carried out. The phylogenetic tree showed distinct clustering from other Catostylus sp. The proteomic analysis revealed venom with many bioactive proteins. Only 13 venom proteins were identified with molecular weights ranging from 4318 to 184,923 Da, exhibiting the venom’s complexity. The overall toxin protein composition of Catostylus sp. venom was dominated by potassium channel toxin alpha-KTx. Molecular docking of toxin alpha-KTx 1.13 revealed high specificity towards the human voltage-gated potassium channel Kv3 with a high fitness score and a minimum energy barrier of −17.9 kcal/mol. Disc diffusion and cytotoxicity assays revealed potent antibacterial activity against Klebsiella pneumoniae with no cytotoxicity. Further studies on detailed characterization and therapeutic potentials are warranted. Full article
(This article belongs to the Special Issue Toxins as Marine-Based Drug Discovery, 2nd Edition)
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<p>Bayesian tree of concatenated sequences (<span class="html-italic">COI</span> and <span class="html-italic">ITS1</span>). The studied jellyfish is highlighted in red. Numbers at the nodes indicate posterior probability values.</p>
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<p>Light micrograph of nematocysts after autolysis at 10 × 10 magnification. (A) 4–6 µm, (B) 7–9 µm, (C) 14–16 µm.</p>
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<p><span class="html-italic">Catostylus</span> sp. venom proteins. (<b>A</b>) The spectral counts for proteins from toxins using LC-MS analysis and (<b>B</b>) SDS-PAGE protein profile of venom samples. <b>M</b>—Protein marker, <b>1</b>: 25 μg/mL, and <b>2</b>: 12.5 μg/mL of 20 µL of crude venom samples. Black arrows indicate venom proteins, while blue arrows indicate the potassium channel toxin alpha-KTx 1.13.</p>
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<p>Three-dimensional toxin–potassium complex model from the ClusPro method. (<b>A</b>) Surface model. (<b>B</b>) Cartoon model. (<b>C</b>) Visualization of polar–polar interaction between the toxin–potassium channel complex. (Human voltage-gated potassium channel Kv3.1 (PDB ID-7PHH) is displayed in green, and the potassium channel toxin alpha-KTx 1.13 (UniProtKB—P59944) is displayed in purple, and active residues of the potassium channel are displayed in blue sticks).</p>
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<p>The 2D interaction representation, including hydrogen bonds, salt bridges, and nonbonded interactions between human voltage-gated potassium channel Kv3.1 and potassium channel toxin alpha-KTx 1.13. (Chain A represents the human voltage-gated the potassium channel, and Chain B represents the potassium channel toxin).</p>
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<p>Morphology of jellyfish specimens collected from Beruwala coastal waters. (<b>A</b>) The exumbrella; (<b>B</b>) exumbrella diameter (<span class="html-fig-inline" id="marinedrugs-22-00333-i001"><img alt="Marinedrugs 22 00333 i001" src="/marinedrugs/marinedrugs-22-00333/article_deploy/html/images/marinedrugs-22-00333-i001.png"/></span>); (<b>C</b>) side view; (<b>D</b>) oral arms; (<b>E</b>) subumbrella region (arrow).</p>
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<p>Bovine serum albumin (BSA) microtiter Bradford assay standard curve. The data are fit with the equation y = 0.0097x + 0.72, and the coefficient of determination (R<sup>2</sup>) for this regression model was 0.98, indicating a strong linear relationship between protein concentration and absorbance.</p>
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15 pages, 15251 KiB  
Article
A New Species of Hydrozoan Jellyfish Eutima onahamaensis and New Record of Eutima diademata (Hydrozoa, Leptothecata) from Japan
by Sho Toshino, Rintaro Ishii and Seiichi Mizutani
Hydrobiology 2024, 3(3), 134-148; https://doi.org/10.3390/hydrobiology3030010 - 2 Jul 2024
Viewed by 861
Abstract
The family Eirenidae is one of the major taxa of the order Leptothecata, comprising approximately 80 species from ten genera. In this study, taxonomic investigations, including morphological observations and molecular 16S phylogenetic analyses, were conducted on unknown Eirenidae specimens collected off the coast [...] Read more.
The family Eirenidae is one of the major taxa of the order Leptothecata, comprising approximately 80 species from ten genera. In this study, taxonomic investigations, including morphological observations and molecular 16S phylogenetic analyses, were conducted on unknown Eirenidae specimens collected off the coast of Iwaki, Fukushima Prefecture, eastern Japan, in June 2022. The specimens had the following morphological characteristics: marginal warts and tentacular bulbs with lateral cirri and without adaxial papillae, a mouth with simple lips, four simple radial canals, and eight statocysts common to the genus Eutima. However, this species can be distinguished from other species of Eutima by the number of tentacles, number and shape of marginal warts, position of the gonads, and gastric peduncle length. Moreover, the monophyly of the species was evident in the 16S rRNA phylogenetic tree (as indicated by the high bootstrap value of 100%), thereby supporting the validity of the new species. Based on these results, we describe it as a new species, Eutima onahamaensis, for taxonomic stabilization. We also made detailed observations of the morphology and molecular phylogenetic analyses of one of the species newly recorded in Japan: Eutima diademata. A comparative table of the primary diagnostic characteristics of Eutima has been provided. This study provided taxonomic keys for identifying species in the genus Eutima. Full article
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<p>Key characters for identification and measurement of parts of the <span class="html-italic">Eutima</span>: g = gonad; gp = gastric peduncle; ma = manubrium; mo = mouth; mw = marginal wart; rac = radial canal; ric = ring canal; t = tentacle; tb = tentacle bulb; u = umbrella; UD = umbrella diameter; UH = umbrella height; v = velum.</p>
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<p>Live mature medusa of <span class="html-italic">Eutima onahamaensis</span> sp. n.: (<b>A</b>) lateral, (<b>B</b>) apical view. Scale bars: 1 mm.</p>
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<p>Live mature medusa of <span class="html-italic">Eutima onahamaensis</span> sp. n.: (<b>A</b>) manubrium, (<b>B</b>) mouth, (<b>C</b>) stomach, (<b>D</b>,<b>E</b>) tentacular bulb, (<b>F</b>) tentacle, (<b>G</b>) statocyst, (<b>H</b>) umbrella margin. lc = lateral cirri; mw = marginal wart; st = statocyst. Scale bars: 0.2 mm.</p>
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<p>Nematocysts of <span class="html-italic">Eutima onahamaensis</span> sp. n.: (<b>A</b>) merotrichous isorhiza, (<b>B</b>) basitrichous isorhiza, (<b>C</b>) artichous isorhiza. Scale bars represent 5 µm.</p>
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<p>Fixed mature medusa of <span class="html-italic">Eutima diademata</span>: (<b>A</b>) lateral, (<b>B</b>) oral view, (<b>C</b>) apical view. Scale bars: 5 mm.</p>
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<p>Fixed mature medusa of <span class="html-italic">Eutima diademata</span>: (<b>A</b>) manubrium and gastric peduncle, (<b>B</b>) manubrium, (<b>C</b>) stomach, (<b>D</b>,<b>E</b>) tentacular bulb, (<b>F</b>) tentacle, (<b>G</b>,<b>H</b>) umbrella margin. gp = gastric peduncle; lc = lateral cirri; ma = manubrium; mw = marginal wart; st = statocyst; t = tentacle; v = velum. Scale bars: (<b>A</b>,<b>C</b>) = 1 mm; (<b>B</b>,<b>G</b>) = 0.5 mm; (<b>D</b>,<b>E</b>,<b>H</b>) = 0.2 mm.</p>
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<p>Maximum likelihood tree (under GTR + G + I) for 12 Leptothecata taxa based on the mitochondrial 16S rDNA data set. The scale bar indicates branch length in substitutions per site. Nodal support values are presented as the ML bootstrap value; only values &gt;50% are shown.</p>
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16 pages, 306 KiB  
Review
Hot-Water Immersion (HWI) or Ice-Pack Treatment (IPT) as First Aid for Human Envenomation by Marine Animals? Review of Literature
by Łukasz Niżnik, Karolina Jabłońska, Michał Orczyk, Martyna Orzechowska, Judyta Jasińska, Barbara Smoliniec, Agnieszka Hućko, Piotr Kosowicz, Anna Klocek, Paweł Słoma, Aleksandra Roztoczyńska, Joanna Toporowska-Kaźmierak and Kamil Jurowski
Toxins 2024, 16(6), 273; https://doi.org/10.3390/toxins16060273 - 15 Jun 2024
Viewed by 1246
Abstract
Envenomation by marine animals poses a significant health concern globally, affecting both local residents and tourists in coastal regions. The primary objective of this review is to critically evaluate the existing scientific literature to determine the most effective first-aid treatment for envenomations caused [...] Read more.
Envenomation by marine animals poses a significant health concern globally, affecting both local residents and tourists in coastal regions. The primary objective of this review is to critically evaluate the existing scientific literature to determine the most effective first-aid treatment for envenomations caused by marine animals, specifically whether hot-water immersion (HWI) or ice-pack treatment (IPT) provides the best immediate care. This comprehensive review covers a wide range of marine envenomations, from jellyfish stings to stingray injuries. While our focus is primarily on the efficacy of HWI and IPT, we also explore the role of cold-water treatment as a result of its relevance and similarity to ice-pack applications. In addition, we examine other treatments mentioned in the literature, such as medications or vinegar, and highlight their findings where applicable. To provide a clear and structured overview, we summarised the articles in separate tables. These tables categorise the type of research conducted, the marine species studied, the region of origin of the marine species, and the key findings of each study. Our analysis of the available evidence indicates a general consensus in the scientific community on the effectiveness of HWI or IPT for envenomation by marine animals. However, when treating those injuries, it is crucial to consider all factors since there is no universally superior treatment due to the diverse nature of marine habitats. Full article
(This article belongs to the Section Animal Venoms)
25 pages, 1964 KiB  
Article
Effect of Jellyfish Body Parts and Presentation Form on Consumers Liking, Sensory Perception, Emotions, and Food Pairings
by Chiara Nervo, Claudia Ragazzini and Luisa Torri
Foods 2024, 13(12), 1872; https://doi.org/10.3390/foods13121872 - 14 Jun 2024
Viewed by 770
Abstract
Although jellyfish represent a food source in Asia, limited attention has been devoted to investigating Western consumers’ perception and acceptance. This study explored the role of jellyfish body parts and presentation form in determining consumer perception. A local consumer test with 106 untrained [...] Read more.
Although jellyfish represent a food source in Asia, limited attention has been devoted to investigating Western consumers’ perception and acceptance. This study explored the role of jellyfish body parts and presentation form in determining consumer perception. A local consumer test with 106 untrained subjects (57.5% female, 18–45 years) was performed in Italy over two days on six samples of jellyfish (Rhopilema esculentum Kishinouye) differing in terms of body parts (umbrella and oral arms) and presentation form (minced, striped, and pieced). For each sample, participants expressed their overall liking and, through three check-all-that-apply tests, described their perceived sensory properties and emotions and potential preferred food pairings. The results showed a significant effect of presentation form on liking (with striped and minced samples liked more than pieced samples), 18 sensory properties, four emotions, and five food pairings. Moreover, different drivers of liking and emotions were observed for three clusters of subjects named “In favour of”, “Against”, and “Picky towards” eating jellyfish. In conclusion, this study found that at least one segment of consumers could accept jellyfish as novel food. Moreover, the provided results could be useful for developing innovative jellyfish-based products and dishes that meet consumers’ expectations. Full article
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<p>Image of the six samples of jellyfish differing in terms of body parts (oral arms and umbrellas) and presentation form (pieced, striped, minced).</p>
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<p>Biplot obtained from the principal components analysis applied to the liking data provided by 106 subjects for six samples of jellyfish differing in terms of parts (arms vs. umbrella) and presentation forms (pieced, striped, minced).</p>
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<p>Correspondence analysis ordination diagram showing the associations among the significant sensory attributes and six jellyfish samples differing in terms of parts (arms, umbrella) and presentation form (pieced, striped, minced).</p>
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<p>Results of the penalty analysis applied to the liking data and the occurrences of the sensory attributes from the check-all-that-apply-test: (<b>a</b>) mean impact of the sensory attributes used to describe the six jellyfish samples and (<b>b</b>) sensory attributes with a significant mean impact on liking (mean increases are displayed in dark grey, while mean decreases are displayed in light grey).</p>
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<p>Results of the penalty analysis applied to the liking data and the occurrences of the sensory attributes from the check-all-that-apply test of the three clusters showing the sensory attributes with a significant mean impact on liking. Mean increases are displayed in dark grey, while mean decreases are displayed in light grey. (<b>a</b>) Cluster 1; (<b>b</b>) Cluster 2; and (<b>c</b>) Cluster 3.</p>
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<p>Correspondence analysis ordination diagram showing the association among possible food pairings and the six jellyfish samples differing in parts (umbrella, arms) and presentation form (pieced, striped, minced).</p>
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19 pages, 6327 KiB  
Article
Analysis of the Distribution Characteristics of Jellyfish and Environmental Factors in the Seawater Intake Area of the Haiyang Nuclear Power Plant in China
by Yunpeng Song, Tiantian Wang, Minsi Xiong, Shenglong Yang, Heng Zhang, Jie Ying, Yongchuang Shi, Guoqing Zhao, Xiumei Zhang, Xiaodan Liu, Cankun Lin, Zuli Wu and Yumei Wu
Biology 2024, 13(6), 433; https://doi.org/10.3390/biology13060433 - 12 Jun 2024
Viewed by 950
Abstract
In recent years, there have been frequent jellyfish outbreaks in Chinese coastal waters, significantly impacting the structure, functionality, safety, and economy of nuclear power plant cooling water intake and nearby ecosystems. Therefore, this study focuses on jellyfish outbreaks in Chinese coastal waters, particularly [...] Read more.
In recent years, there have been frequent jellyfish outbreaks in Chinese coastal waters, significantly impacting the structure, functionality, safety, and economy of nuclear power plant cooling water intake and nearby ecosystems. Therefore, this study focuses on jellyfish outbreaks in Chinese coastal waters, particularly near the Shandong Peninsula. By analyzing jellyfish abundance data, a Generalized Additive Model integrating environmental factors reveals that temperature and salinity greatly influence jellyfish density. The results show variations in jellyfish density among years, with higher densities in coastal areas. The model explains 42.2% of the variance, highlighting the positive correlation between temperature (20–26 °C) and jellyfish density, as well as the impact of salinity (27.5–29‰). Additionally, ocean currents play a significant role in nearshore jellyfish aggregation, with a correlation between ocean currents and site coordinates. This study aims to investigate the relationship between jellyfish blooms and environmental factors. The results obtained from the study provide data support for the prevention and control of blockages in nuclear power plant cooling systems, and provide a data basis for the implementation of monitoring measures in nuclear power plants. Full article
(This article belongs to the Section Marine Biology)
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<p>Distribution of jellyfish resource investigation stations in the seawater intake area of the Haiyang Nuclear Power Plant.</p>
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<p>The frequency distribution (<b>a</b>) and its test (<b>b</b>) of ln(abundance) of jellyfish in the southern sea area of Yantai and Weihai, Shandong, from 2010 to 2022.</p>
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<p>Interannual variation in jellyfish resource density in the southern sea areas of Yantai and Weihai, Shandong Province, from 2010 to 2022.</p>
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<p>Density distribution map of jellyfish resources in the sea area around Haiyang Nuclear Power Plant in Shandong Province, China, from 2010 to 2022.</p>
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<p>Box plot of explanatory variables and residuals fitted by the best GAM. (The black dots in the diagram represent outliers in the respective factors).</p>
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<p>The impact of each explanatory variable on the density of jellyfish resources in the southern waters of Yantai and Weihai, Shandong Province, from 2010 to 2022: (<b>a</b>) year; (<b>b</b>) latitude; (<b>c</b>) longitude; (<b>d</b>) SST; and (<b>e</b>) SSS. (The dashed lines in the diagram represent the 95% confidence interval, and the solid lines represent the actual values).</p>
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<p>Overlay map of sea currents and jellyfish resource density in the Shandong Peninsula from 2010 to 2022.</p>
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<p>Overlay map of sea surface temperature (SST) and jellyfish resource density in the Shandong Peninsula from 2010 to 2022.</p>
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<p>Overlay map of SSS and jellyfish resource density in the Shandong Peninsula from 2010 to 2022.</p>
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