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Euphausiacea

Euphausiacea, also known as krill, are a group of small, shrimp-like crustaceans that play a critical role in marine ecosystems.
These planktonic organisms serve as a key food source for a variety of predators, including whales, seals, and seabirds.
Euphausiids are found in all the world's oceans and are particularly abundant in polar and temperate regions.
Their complex life cycle and sensitivity to environmental changes make them important indicators of ecosystem health.
Researchers studying Euphausiacea face the challenge of optimizing research protocols to ensure reproducibility and accuracy.
PubCompate.ai leverages artificial intelligence to help scientists locate the most effective methods and products, enhancing Euphausiacea research and advancing our understanding of these fascinating marine creatures.

Most cited protocols related to «Euphausiacea»

Designing Blocking Primers for Predator Diet Analysis

Cited 29 times

Primers applied in analysing of gut content of predators should ideally target short sequences of multiple-copy DNA because of the degraded nature of the prey derived sequences [13 (link),16 (link),17 ,36 (link)]. The ribosomal DNA is therefore often used as a target for PCR amplification in diet studies because ribosomal DNA (rDNA) genes are repeated tandemly in high copy numbers and are highly conserved within species [37 (link)]. We designed 'universal' PCR primers that amplify a short, but fairly variable region of the 28S rDNA from all eukaryotes tested. We also designed three blocking primers intended to bind to the Euphausia superba sequence amplified by the universal primers. The primers used in this study are given in Table 1 and shown aligned with the krill sequence in Figure 2.
The blocking primer, 'Short28SR-blkKrill3'c3' overlapped with the 3' end of the reverse universal primer, but extended into krill-specific sequence and was modified with a C3 spacer at the 3'-end (Figure 2). We needed a modification which was 100% synthesized (i.e. no oligos missing it) and which was stable (i.e. no degradation or enzymatic removing of the modification after synthesis). Even if just a small percentage of the blocking primers were to prime amplification of predator DNA as a result of not having the 3' modification, this would render the procedure unworkable. C3 spacer (3 hydrocarbons) CPG is a standard primer modification available from most suppliers of custom oligonucleotides. Adding this modification to the 3'-end of an oligonucleotide prevents elongation during a PCR without noticeably influencing its annealing properties. Because oligos are synthesized from a 3' to 5' direction, all molecules will be modified with the 3' modification. Modifying the 3'- end with a phosphate group (as chosen by Liles et al. [35 (link)]), a phosphate ester, or using an inverted 3'-3' linkage would also prevent elongation. However, side reactions during deprotection of the oligonucleotide or enzymatic impurities may free the 3'-hydroxyl group to a small extent, and these methods are not so effective in blocking as C3 spacers CPG [38 (link),39 (link)].
Because finding an appropriate binding site for a species specific primer next to a binding site of a universal primer is often difficult, a krill specific blocking primer, Short28SF-DPO-blkKrill overlapping with the 3'end of the forward universal primer and having an internal modification of five deoxyinosine (dI) molecules in addition to the C3 spacer modification was also designed (Figure 2). Very long conventional oligonucleotides often do not work. In general, primers longer than 25 bases are rarely used since their Tms can be over 70°C, which is too high for effective PCR cycling [40 (link)]. Long primers also often generate many non-specific bands resulting from non-specific annealing. A dual priming oligonucleotide (DPO) [41 (link)] contains two separate priming regions joined by a polydeoxyinosine linker. DPOs does not suffer from the limitations of a high Tm since the linker assumes a bubble-like structure resulting in two primer segments with distinct annealing properties. Furthermore, the bubble-like structure of linker efficiently prevents primer-dimer and hairpin structure formation [41 (link)].
The Short28SR-blkKrill3'c3 and the Short28SF-DPO-blkKrill blocking primers were both designed to prevent annealing of the unmodified version of the universal primer on krill sequences. Further a third krill specific blocking primer situated between the two universal primers was tested (Figure 2). This was an "elongation arrest" primer ([42 (link)]; Figure 1) and also had a C3 spacer at its 3' end.

Vestheim H, & Jarman S.N. (2008). Blocking primers to enhance PCR amplification of rare sequences in mixed samples – a case study on prey DNA in Antarctic krill stomachs. Frontiers in Zoology, 5, 12.

Publication 2008

2',5'-oligoadenylate Binding Sites Cardiac Arrest deoxyinosine Diet DNA, Ribosomal Enzymes Esters Eukaryota Euphausia Euphausiacea Genes Hydrocarbons Hydroxyl Radical Oligonucleotides Phosphates

Depression Risk Factors in Aging Chinese

Cited 7 times

The data used in this study came from the follow-up survey of the CHARLS targeting the middle-aged and older population (45+) in China. The CHARLS is an ongoing national longitudinal study administered by the National School for Development (China Center for Economic Research), with exams performed every 2 years for a total of 3 waves from 2011 to 2015. The first national baseline survey of the CHARLS was fielded between June 2011 and March 2012 and involved 17,705 respondents who were chosen randomly with a probability proportional to scale (PPS) in 450 villages/resident committees, 150 counties/districts and 28 provinces. The respondents were interviewed face-to-face in their homes via computer-assisted personal interviewing (CAPI) technology. Physical parameters, such as the respondents’ standing height, weight and waist circumference (WC), were measured by the trained investigators with standardized equipment (Index: height; Equipment: SecaTM213 Stadiometer Manufacturer/source: China Seca (Hangzhou) Co., Ltd. Index: weight; Equipment: OmronTMHN-286Scale Manufacturer/source: Krill Technology (Yangzhou) Co., Ltd. Index: waist circumference; Equipment: Soft Tape Measure Manufacturer/source: None.). The medical ethics committee approved the CHARLS study, and all interviewees were required to sign informed consent, Ethics approval for the data collection in CHARLS was obtained from the Biomedical Ethics Review Committee of Peking University (IRB00001052–11015). Ethics approval for the use of CHARLS data was obtained from the University of Newcastle Human Research Ethics Committee (H-2015-0290).
This study used the baseline data from 2011 and follow-up data from 2013 and 2015. To research the association between BMI (WC) and the onset of depression, we limited the samples to respondents who had no depression symptoms in 2011 and had received physical examinations in each of the three surveys. A total of 3337 subjects were included.

Luo H., Li J., Zhang Q., Cao P., Ren X., Fang A., Liao H, & Liu L. (2018). Obesity and the onset of depressive symptoms among middle-aged and older adults in China: evidence from the CHARLS. BMC Public Health, 18, 909.

Publication 2018

Depressive Symptoms Ethics Committees Ethics Committees, Research Euphausiacea Face Homo sapiens Physical Examination Waist Circumference

Efficient Cloning and Sequencing of Krill Microbiome

Cited 6 times

After determining the most efficient blocking primer mixture, PCR was performed on krill stomach isolates. PCRs were prepared using UV sterilized equipment and consumables and negative (no-template) controls were always run alongside the samples. The PCR reactions were carried out on a MJ Research DNA engine Gradient Cycler (eq. Chromo 4) and sequencing was performed on a 3730 xl DNA analyzer (Applied Biosystems). PCR products were checked by electrophoresis on a 1.3% agarose gel stained with SYBR^®Safe DNA gel stain (Invitrogen). Visible bands were cut out and purified with Bio-Rad Quantum Prep Freeze'N Squeeze DNA Gel Extraction Spin Columns.
The PCR products were thereafter reincubated for 10 min at 72°C with 20 μL reaction volume containing 2 μL 10×, 1 μL Mg²⁺, 0.2 μL Biotaq TM DNA Polymerase (Bioline) and 0.2 μL dNTP to add 3' adenines and cloned using the TOPO TA Cloning system competent cells (Invitrogen). Transformants were picked for PCR and amplification was performed with the TOPO_F and TOPO_R primers as 25 μL reactions with 0.25 μL of each oligo (10 μM), 0.25 μL dNTP, 2.5 μL 10×, 0.1 μL Platinum Taq DNA Polymerase High Fidelity (Invitrogen) 5 U^. μL^-1and 1 μL Mg²⁺. PCR thermal cycling conditions were: 2 min at 94°C; 40 cycles of 10 s at 94°C, 30 s at 65°C, 30 s at 68°C; and finally 5 min at 72°C.
Sequences were generated from these PCR products with the M13 forward primer and BigDye Terminator v3.1 sequencing reactions (ABI).
Amplification for sequencing of species not yet available in GenBank were performed as 25 μL reactions with 0.25 μL of each of the universal 28S rDNA primers Short28SseqF and Short28SseqR (10 μM) (Table 1) designed to cover a larger area than the Short28SF/Short28SR primers, including their primer binding sites, 0.25 μL dNTP, 2.5 μL 10×, 0.1 μL Platinum Taq DNA Polymerase High Fidelity (Invitrogen) 5 U^. μL^-1and 1 μL Mg²⁺. PCR thermal cycling conditions were unmodified except for increasing the elongation step to 60 s.

Publication 2008

Adenine Binding Sites Cardiac Arrest Clone Cells DNA, Ribosomal DNA-Directed DNA Polymerase Electrophoresis Euphausiacea Oligonucleotide Primers Oligonucleotides Platinum Sepharose Stains Stomach Taq Polymerase Topotecan

Baleen Isotope Prey Comparison Protocol

Cited 5 times

Measured baleen isotope values were compared to literature-derived estimates of three distinct prey sources (combining prey type and feeding location). The three estimates are presented in Table 2 together with corresponding references [42 –47 ]. Literature averages represent data accumulated across a range of years, so that temporal variability was at least partially accounted for. We included the standard deviation of all values in the defined prey isotope ranges to account for possible taxonomic and sub-regional variations in δ¹³C and δ¹⁵N (Table 2).
In all cases, literature-derived prey estimates were adjusted to account for trophic fractionation and represent the baleen isotopic values of whales consuming these prey (S2 Table). The adjusted estimates are calculated as follow:

δ X_{B} = {T F}_{x} + δ X_{P} \pm {SD}_{P}

Where δX = δ¹³C or δ¹⁵N values, B is baleen, P is prey, X = ¹³C or ¹⁵N, TF is the trophic enrichment factor, and SD is the standard deviation. Two sets of TF estimates were initially compared (S2 Table, Fig 2). The first set corresponds to generic estimates of +3.4‰ for nitrogen and 0.5‰ for carbon. Although δ¹³C TEF values are known to range from 0.5–1.5‰ [48 , 56 ], the generic estimates given here are the most commonly used for species with unknown TFs. Because a recent study on krill-feeding northern hemisphere fin whales reported TFs of +2.77‰ for nitrogen isotopes and +2.26‰ for carbon isotopes in baleen plates [57 (link)], this TF set was also included in the preliminary analysis (Fig 2).
The isotopic values from the known diet of SH humpback whales aligned more closely with fin whale-specific TF estimates (+2.77‰ per trophic level for nitrogen and +2.26‰ for carbon) than generic estimates (+3.4‰ per trophic level for nitrogen and +0.5‰ for carbon; Fig 2). The fin whale specific TF set was thus used in our interpretations. As the estimates do not overlap in δ¹³C or δ¹⁵N, they provide distinct isotopic zones specific to the consumption of that prey (Fig 2).

Eisenmann P., Fry B., Holyoake C., Coughran D., Nicol S, & Bengtson Nash S. (2016). Isotopic Evidence of a Wide Spectrum of Feeding Strategies in Southern Hemisphere Humpback Whale Baleen Records. PLoS ONE, 11(5), e0156698.

Publication 2016

Balaenoptera physalus Carbon Carbon Isotopes Cetacea Diet Euphausiacea Fractionation, Chemical Generic Drugs Isotopes Megaptera novaeangliae Nitrogen Nitrogen Isotopes

Evaluating Blocking Primer Efficiency

Cited 5 times

To evaluate the efficiency of the different types and different amounts of blocking primers, artificial rDNA mixtures were created. First PCR amplification were performed on krill and Pyramimonas DNA with the universal 28S rDNA primers Short28SF and Short28SR (Table 1) as 25 μL reactions with 0.25 μL of each oligo (10 μM), 0.25 μL dNTP, 2.5 μL 10×, 0.1 μL Platinum Taq DNA Polymerase High Fidelity (Invitrogen) 5 U^. μL^-1, 1 μL Mg²⁺and 5 μL DNA (~10 ng^. μL^-1).
The PCR products were then cloned using the TOPO TA Cloning system competent cells (Invitrogen). Transformants were screened using blue/white selection on LB-agar containing X-Gal and 10 mg^.mL^-1ampicillin or kanamycin. White or light blue colonies were picked for plasmid isolation, reincubated overnight in LB medium containing antibiotics and plasmids were then extracted using the Ultraclean miniplasmid extraction kit (Mo Bio, Carlsbad, CA, USA). Plasmids were linearized using HindIII restriction enzyme and the yield quantified using Picofluor 8000-004 (Turner Designs) and samples stained with Quant-iT PicoGreen ds DNA reagent (Molecular Probes).
Samples were thus mixed to contain a 100-fold and a 1000-fold excess of target rDNAs (krill 28SrDNA) compared with nontarget rDNAs (Pyramimonas sp.). A sample containing only krill DNA was used as a control.
Amplification with blocking primers were performed as 25 μL reactions with 0.25 μL of each of the universal 28S rDNA primers Short28SF(10 μM) and Short28SR(10 μM), 0.25 μL dNTP, 2.5 μL 10×, 0.1 μL Platinum Taq DNA Polymerase High Fidelity (Invitrogen) 5 U^. μL^-1, 1 μL Mg²⁺and a variable amount of blocking primer and rDNA. PCR thermal cycling conditions were: 2 min at 94°C; 40 cycles of 10 s at 94°C, 30 s at 59°C, 30 s at 68°C; and finally 5 min at 72°C.
Blocking efficiency was assessed by fragment analysis of the fluorescently labelled PCR products. Fragment analysis separates a mixture of DNA fragments according to their sizes and is much more sensitive than standard gel electrophoresis. The analysis was performed on an Applied Biosystems 3130 xl Capillary Electrophoresis (CE) Genetic Analyser and results were analyzed with Peak Scanner Software 1.0 (Applied Biosystems).

Publication 2008

5-bromo-4-chloro-3-indolyl beta-galactoside Agar Ampicillin Antibiotics, Antitubercular Clone Cells DNA, A-Form DNA, Double-Stranded DNA, Ribosomal DNA Primers DNA Restriction Enzymes Electrophoresis Electrophoresis, Capillary Euphausiacea isolation Kanamycin Light Molecular Probes Oligonucleotide Primers Oligonucleotides PicoGreen Plasmids Platinum Reproduction Taq Polymerase Topotecan

Most recents protocols related to «Euphausiacea»

Supercritical CO2 Extraction of Krill Meal

Not available on PMC !

Example 6

Fresh krill was pumped from the harvesting trawl directly into an indirect steam cooker, and heated to 90 C. Water and a small amount of oil were removed in a screw press before ethoxyquin (antioxidant) was added and the denatured meal was dried under vacuum at a temperature not exceeding 80 C. After 19 months storage in room temperature, a sample of the denatured meal was extracted in two steps with supercritical CO₂in laboratory scale at a flow rate of 2 ml/min at 100 C and a pressure of 7500 psi. In the second step 20% ethanol was added to the CO₂. The two fractions collected were combined and analyzed by HPLC using ELS detection. The phosphatidylcholine was measured to 42.22% whereas the partly decomposed phosphatidylcholine was 1.68%. This data strongly contrasts the data obtained by analysis of a krill oil sample in the marketplace that showed a content of 9.05% of phosphatidylcholine and 4.60% of partly decomposed phosphatidylcholine.

US11865143B2. Bioeffective krill oil compositions (2024-01-09). AKER BIOMARINE ANTARCTIC AS [NO]. Inventors: Inge Bruheim [NO], Snorre Tilseth [NO], Daniele Mancinelli [NO].

Patent 2024

Antioxidants Contrast Media Ethanol Ethoxyquin Euphausiacea High-Performance Liquid Chromatographies Phosphatidylcholines Pressure Steam Vacuum

Krill Herd Optimization Algorithm

The KHO algorithm simulated the krill behavior whereas every individual of the KH created their contribution with the process of moving [26 ]. The best solution is acquired when the krill individuals identify the food center. The KHO algorithm is according to the lagrangian as well as krill individual’s evolution behavior with the capability to do exploitation and exploration in the optimization issues. In this KHO algorithm, the random value performs an important role. The time-dependent position of the individual’s krill is calculated on the basis of three actions and they are; random diffusion, foraging activity and the movement induction of the krill individual. The KHO algorithm adopts the d-dimensional search space lagrangian design and it is expressed in the below equation;

\frac{\partial Z_{j}}{\partial t} = O κ_{j} + G κ_{j} + E κ_{j}

Here, the terms

O κ_{j}

G κ_{j}

and

E κ_{j}

indicates search agent’s movement induction, foraging behavior and random diffusion, respectively. The optimization commences by initializing the parameters such as maximum diffusion speed

E_{MAX}

, krill position

Z_{j}

, maximal foraging speed

ν_{g}

, maximal induced speed

o^{MAX}

, the maximal number of iterations

J_{MAX}

and numbers of krill

O

. Compute the movement for every krill. The communal effects between krill individuals lead to movements and they attempt to conserve the higher density.

σ_{j}

denote the motion induction direction and which is evaluated with the local target and the density of the repulsive swarm. Then it is expressed as;

O κ_{j}^{NEW} = o^{MAX} σ_{j} + x_{o} O κ_{j}^{old}

The inertia weight is represented by

x_{o}

, the last motion is denoted by

O κ_{j}^{OLD}

and maximal induced speed is represented as

o^{MAX}

σ_{j} = σ_{j}^{LO} + σ_{j}^{τ}

σ_{j}^{LO} = \sum_{k = 1}^{Oo} {\hat{κ}}_{j, k} {\hat{Y}}_{j, k}

{\hat{Y}}_{j, k} = \frac{Y_{k} - Y_{j}}{∥Y_{k} - Y_{j}∥ + a}

{\hat{κ}}_{j, k} = \frac{κ_{j} - κ_{k}}{κ^{WO} - κ^{BEST}}

The worst and best krill individuals are represented by

κ^{BEST}

and

κ^{WO}

. The smaller positive number is represented by

a

. The numbers of neighbors are denoted by

O_{o}

. Also, the terms

σ_{j}^{τ}

and

σ_{j}^{LO}

denote target direction effect and local effect offered by neighbors, respectively;

κ_{j}

and

κ_{k}

depicts fitness function of

j th

krill and

k th

neighbor, respectively;

Y_{k}

and

Y_{j}

indicates the corresponding positions of

j th

krill and

k th

neighbor, respectively.

σ_{j}^{τ} = D^{BEST} {\hat{κ}}_{j, BEST} {\hat{Y}}_{j, BEST}

D^{BEST}

represents the krill individual efficient individual through best fitness is expressed in the below equation;

D^{BEST} = 2 (ℜ + \frac{J}{J_{MAX}})

E_{t, j} = \frac{1}{5 O} \sum_{k = 1}^{O} Y_{j} - Y_{k}

where

ℜ

depicts random value which lies in the range [0,1],

J

signifies current iteration,

E_{t, j}

indicates sensing distance.
The foraging movement is defined as which is according to food location and previous experiences with the food location. Then it is expressed as;

G κ_{j} = ν_{g} η_{j} + x_{g} G κ_{j}^{OLD}

Inertia weight with foraging movement is represented by

x_{g}

η_{j}

signifies fitness value of

j th

krill and the krill best objective is represented by

η_{j}^{BEST}

η_{j} = η_{j}^{FOOD} + η_{j}^{BEST}

η_{j}^{FOOD} = D^{FOOD} {\hat{κ}}_{j, FOOD} {\hat{Y}}_{j, FOOD}

The food coefficients are represented by

D^{FOOD}

and it is expressed as;

D^{FOOD} = 2 (1 - \frac{J}{J_{MAX}})

The

j th

krill individual best objectives are determined by

η_{j}^{BEST}

and it is expressed in the below equation

η_{j}^{BEST} = {\hat{κ}}_{j, j BEST} {\hat{Y}}_{j, j BEST}

The food centers for iterations are computed and it is expressed as;

Y^{FOOD} = \frac{\sum_{j = 1}^{O} \frac{1}{κ_{j}} Y_{j}}{\sum_{j = 1}^{O} \frac{1}{κ_{j}}}

The physical diffusion movement is described on the basis of the diffusion speed for maximum and the random direction vectors are expressed in the below equation;

E κ_{j} = E^{MAX} (1 - \frac{J}{J_{MAX}}) Φ

The random direction vector is represented by

Φ

which lies between − 1 and 1.
To enhance the performance of KHO, the genetic reproduction mechanisms mutation and crossover are merged through KHO.
The below expression represents the crossover function of

Y_{j}' s n th

component,

Y_{j, n} = \{\begin{matrix} Y_{s, n}, & ℜ_{j, n} < c_{o} \\ Y_{j, n}, & else \end{matrix})

Then, crossover probability

c_{o} = 0.2 {\hat{κ}}_{j, j BEST}

Y_{j, n} = \{\begin{matrix} Y_{h BEST, n} + ν (Y_{q, n} - Y_{r, n}) & ℜ_{j, n} < Nu \\ Y_{j, n} & else \end{matrix})

The mutation probability is denoted by

N_{u}

and it is set to

N_{u} = 0.05 / {\hat{κ}}_{j, j BEST}

.
The krill’s position vector in the interval

|t + Δ t|

is found using below expression,

Y_{j} (t + Δ t) = Y_{j} (t) + Δ t \frac{\partial Y_{J}}{\partial t}

Sivamohan S, & Sridhar S.S. (2023). An optimized model for network intrusion detection systems in industry 4.0 using XAI based Bi-LSTM framework. Neural Computing & Applications, 35(15), 11459-11475.

Publication 2023

Biological Evolution Cloning Vectors Diffusion Disgust Euphausiacea Food Movement Mutation Physical Examination

Explainable AI for Industrial Intrusion Detection

This section provides a detailed description of the proposed Bidirectional Long Short-Term Memory based Explainable Artificial Intelligence (BiLSTM-XAI) framework for accurate detection of industrial network intrusions. The intrusion detection system is comprised of three phases, namely pre-processing, feature selection and classification. In pre-processing, the data are cleaned and normalized and thus increasing the quality of data. Then the significant data features are extracted by means of feature selection process using the krill herd optimization (KHO) algorithm. Finally, the classification is carried out using the BiLSTM-XAI approach which classifies the data and detects the presence of intrusions accurately. These procedures are described elaborately in the following sub-sections. Figure 1 portrays the block diagram of the proposed intrusion detection system.Fig. 1

Block diagram of the proposed intrusion detection system

Publication 2023

Euphausiacea Memory, Short-Term

Krill Herd Optimization for Feature Selection

As a frequent practice to select significant feature subsets, the feature selection process is gaining more attention [25 (link)]. Due to large dimensional and multiple featured data, the intrusion detection accuracy of model gets affected. The data features belonging to various classes contain different attributes and insignificant features that might cause the classifier to misclassify. The feature selection process minimizes data complexities by removing insignificant features from the dataset. It not only extracts redundant data but also reduces false positive rates in detecting intrusion. Moreover, it increases detection speed with a reduction in computation payload. Thus, the feature selection process creates more impact on detection accuracy and generalization capability of the model. Therefore, in this paper, we introduced the krill herd optimization (KHO) algorithm for feature selection which effectively selects the feature subsets by reducing data dimension and increasing detection accuracy and detection speed of intrusion detection system. A brief description of this KHO algorithm is modeled as follows.

Publication 2023

Attention Euphausiacea Generalization, Psychological

Abundance of Antarctic Krill Estimation

The abundance of krill was studied with a Simrad EK80 research echosounder with six frequencies. For this study, we focused on the 38 kHz frequency. It was scrutinized with the Large Scale Survey System (LSSS) software version 2.5.0^{68 (link)}. During the campaign, we used two transducers: one on the drop-keel (3 m from the hull when down) and one hull-mounted. The latter was used in ice-covered areas, with low impact on the detection of krill swarms^{15 (link)}. The density of krill was calculated as nautical area scattering coefficient (NASC)^{69 (link)}.
Krill swarms were sampled with a Macroplankton trawl at two locations within the bloom region (the positions of the two trawling stations are indicated in Fig. 4a). The trawl is a fine-meshed plankton trawl with a 36 m² mouth-opening and 3 × 3 mm diamond shaped mesh (7 mm stretched) from mouth to rear. Towing speed was normally 2.5–3 knots. The velocity of the trawl through water and depth of the trawl were monitored by a depth sensor (SCANMAR) attached to the headline. From each trawl, a subsample of approximately 150 individuals of Euphausia superba was taken, and the length of the individual krill was measured (±1 mm) from the anterior margin of the eye to tip of telson excluding the setae. Sex and maturity stages of E. superba were determined using the classification methods according to Makarov and Denis⁷⁰.

Moreau S., Hattermann T., de Steur L., Kauko H.M., Ahonen H., Ardelan M., Assmy P., Chierici M., Descamps S., Dinter T., Falkenhaug T., Fransson A., Grønningsæter E., Hallfredsson E.H., Huhn O., Lebrun A., Lowther A., Lübcker N., Monteiro P., Peeken I., Roychoudhury A., Różańska M., Ryan-Keogh T., Sanchez N., Singh A., Simonsen J.H., Steiger N., Thomalla S.J., van Tonder A., Wiktor J.M, & Steen H. (2023). Wind-driven upwelling of iron sustains dense blooms and food webs in the eastern Weddell Gyre. Nature Communications, 14, 1303.

Publication 2023

Diamond Euphausia Euphausiacea Oral Cavity Plankton Setae Transducers

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What are the different types or variations of Euphausiacea?

Euphausiacea, commonly known as krill, are a diverse group of small, shrimp-like crustaceans. While there are over 80 known species of Euphausiacea, some of the most common and well-studied include the Antarctic krill (Euphausia superba), North Pacific krill (Euphausia pacifica), and Californian krill (Euphausia pacifica). These species can vary in size, habitat, and specific ecological roles within marine ecosystems.

What are the key challenges researchers face when studying Euphausiacea?

Researchers studying Euphausiacea face several challenges, including optimizing research protocols to ensure reproducibility and accuracy. The complex life cycle and sensitivity of these planktonic organisms to environmental changes can make it difficult to develop standardized experimental methods. Additionaly, the vast geographic distribution of Euphausiacea across polar and temperate regions adds complexity to research efforts.

How can PubCompare.ai assist with Euphausiacea research?

PubCompare.ai can greatly enhance Euphausacea research by leveraging artificial intelligence to help scientists locate the most effective methods and products. The platfom allows researchers to efficiently screen protocl literature, and its AI-driven analysis can highkight key differences in protocol effectiveness. This enables researchers to choose the best option for their specific research goals, improving reproducibility and accuracy in their Euphausiacea studies.

What are some common applications of Euphausiacea in research and industry?

Euphausiacea, or krill, have a variety of applications in research and industry due to their critical role in marine ecosystems. In research, Euphausiacea are often used as model organisms to study topics like plankton dynamics, ocean acidification, and the effects of climate change on marine food webs. In industry, krill are harvested as a source of omega-3 fatty acids and used in dietary supplements, as well as in aquaculture feed for farmed fish and shellfish.

More about "Euphausiacea"

Euphausiacea, also known as krill, are a group of small, shrimp-like crustaceans that play a crucial role in marine ecosystems.
These planktonic organisms, found in all the world's oceans and particularly abundant in polar and temperate regions, serve as a key food source for a variety of predators, including whales, seals, and seabirds.
Euphausiids, with their complex life cycle and sensitivity to environmental changes, are important indicators of ecosystem health.
Researchers studying Euphausiacea face the challenge of optimizing research protocols to ensure reproducibility and accuracy.
PubCompare.ai, a powerful AI-driven platform, can help scientists locate the most effective methods and products, enhancing Euphausiacea research and advancing our understanding of these fascinating marine creatures.
When conducting Euphausiacea studies, researchers may utilize various analytical techniques and equipment, such as the Varioskan Flash multimode reader, which can be used for fluorescence, absorbance, and luminescence measurements.
Solvents like acetonitrile, n-hexane, methanol, and chloroform may be employed for sample preparation and extraction.
Reagents such as sodium hydroxide and triethylamine may also be employed in the research process.
Additionally, molecular biology techniques, such as the use of the FastDNA SPIN Kit for Soil and the TRIzol reagent, can be valuable for DNA and RNA extraction from Euphausiacea samples, enabling advanced genetic and genomic analyses.
By leveraging the power of PubCompare.ai, researchers can optimize their Euphausiacea studies, ensuring reproducibility, accuracy, and the identification of the most effective methods and products.
This, in turn, can lead to a deeper understanding of these critical marine organisms and their role in the ecosystem.