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Thoracica

Thoracica is a suborder of marine crustaceans that includes barnacles, goose barnacles, and acorn barnacles.
These sessile organisms attach themselves to various surfaces, such as rocks, ships, and marine animals.
Thoracica play important roles in marine ecosystems, serving as food sources and contributing to the fouling of submerged structures.
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Most cited protocols related to «Thoracica»

Samples were taken and processed according to the standard operating procedures to ensure maximum comparability. In brief, at least three different specimens of each sponge species were collected into sterile bags and species identities were confirmed by microscopic examination of morphological characters following established protocols (for example, as reviewed in ref. 43 ). Specimens were either processed directly or after freezing, depending on logistical constraints of each sampling event. Specimens were cleaned of external growth (for example, barnacles), washed three times with sterile seawater to remove planktonic or loosely associated microorganisms and cut into small pieces from which a random sub-sample of pieces was used for subsequent DNA extraction. Sediment samples were collected under water in close proximity to sponges. Sediments were scooped into sterile containers using sterile spatulas to avoid laboratory contamination. Seawater was drained from the containers on surfacing and prior to freezing. Sponges and sediment samples were immediately frozen and kept on dry ice or at −80 °C until further processing. DNA was extracted from ∼0.25 g of sponge tissue or sediment using the PowerSoil DNA Extraction kit (MoBio) according to the Earth Microbiome Project standard protocols (http://press.igsb.anl.gov/earthmicrobiome/emp-standard-protocols/dna-extraction-protocol/). Microbial communities in seawater were collected by passing 2 l of seawater through 0.2 μm Sterivex filters and DNA was extracted from the filters as previously described13 (link). Samples were extracted at laboratories at the Australian Institute of Marine Sciences (Townsville, Australia), the University of Wuerzburg (Germany) or the Nova Southeastern University (Dania Beach, FL, USA) to minimize shipment of frozen specimens. Aliquots of the specimens and DNA were kept at the three locations (and are available on request) and an aliquot of the extracted DNA was shipped to the University of Colorado, Bolder, CO, USA for sequencing of the 16S rRNA gene using standard procedures of the Earth Microbiome Project (http://www.earthmicrobiome.org/emp-standard-protocols/16s/). Briefly, the V4 region of the 16S rRNA gene was amplified using the primer 515f–806rB and sequenced using the HiSeq2500 platform (Illumina)44 (link).
Publication 2016
Character Dry Ice Freezing Marines Microbial Community Microbiome Microscopy Oligonucleotide Primers Plankton Porifera Ribosomal RNA Genes Sterility, Reproductive Thoracica Tissues
Adult worker bees were obtained from sites across seven countries (Australia, Malaysia, Singapore, Hong Kong, South Korea, United States, and Brazil), mostly between May 2013 and October 2014 (data file S1). Specimens were kept in 100% ethanol or frozen at −80°C for DNA preservation. For a subset of samples, the guts were removed, homogenized, and then frozen in 19% glycerol, allowing for preservation of live bacteria from which strains were later isolated.
Of the approximately nine recognized Apis species, the five most common species were collected. Both the Neotropical and Indo-Malay/Australasia clades of the diverse stingless bees (90 ) were sampled, including species used in commercial meliponiculture such as Heterotrigona itama, Geniotrigona thoracica, and T. carbonaria (91 , 92 ). Bumble bees were collected from sites in the United States (Colorado, New Jersey, Texas, and Utah) and included new samples and samples from the study of Powell et al. (93 (link)). As outgroups for comparative analyses, we obtained specimens of C. atripes [tribe Centridini, a close relative of the corbiculates (94 (link))] and A. abrupta [tribe Anthophorini, which is a more distant outgroup but still belongs to the “Apine line” of subfamily Apinae (95 )]. Where available, sympatric bees were collected at the same time and location.
Bee species were identified by morphology. For most stingless bee samples, the mitochondrial 16S rRNA gene was also sequenced, following Rasmussen and Cameron (90 ). For C. atripes and A. abrupta, the 28S rRNA gene was sequenced, following Martins et al. (94 (link)). Sequences were classified on the basis of the closest BLAST hits in the GenBank nonredundant (nr) database (data file S1). To verify that samples classified as the same species were related, phylogenies based on their sequences were built and inspected in Geneious R9 (Biomatters Ltd.).
Publication 2017
Adult Apis Bacteria Base Sequence Biologic Preservation Ethanol Freezing Genes Genes, Mitochondrial Glycerin Intestines Ribosomal RNA Genes RNA, Ribosomal, 16S RNA, Ribosomal, 28S Strains Sympatry Thoracica Workers
Marine heterotardigrades, Echiniscoides cf. sigismundi, were collected from barnacles in the intertidal zone at Lynæs, Zealand, Denmark (see [57 ]). Specimens of a parthenogenetic population of the eutardigrade, Richtersius cf. coronifer, were sampled from moss growing on limestone in Øland, Sweden (see [76 (link)]). Total RNA was extracted from active stage pools of ∼550 E. cf. sigismundi and ∼200 R. cf. coronifer, respectively, using a RNeasy Plus Universal Mini Kit (Qiagen,Hilden, Germany). RNA quantitation and quality analyses were performed using a NanoDrop ND-1000 (Thermo Scientific, Waltham, Massachusetts, USA) and a Bioanalyzer 2100 (Agilent Technologies, Santa Clara).
Cryptic species complexes are common within Tardigrada and the genus Echiniscoides has an exceptionally large genetic variation [19 (link)]. We therefore analyzed both transcriptomes with respect to the often used barcoding sequence of cytochrome c oxidase subunit I (COXI) using BLASTN searches in the NCBI nucleotide non-redundant database. The transcriptome data revealed tardigrade COXI contigs (CL4672.Contig1_Echiniscoides and CL1502.Contig2_Richtersius), which support that the 550 Echiniscoides and 200 Richtersius specimens each constitute single species. BLASTN searches in GenBank returned a 99% identity to the isolate Echiniscoides cf. sigismundi (voucher ZMUC:TAR Esi1; GenBank Accession number: HM193403.1; [77 (link)]. Similarly, the Richtersius cf. coronifer BLASTN search in GenBank returned a 99% identity to the isolate Richtersius cf. coronifer (GenBank Accession number: EU244606.1).
Publication 2019
CFC1 protein, human Genetic Diversity Limestone Marines Mosses Nucleotides Oxidase, Cytochrome-c Parthenogenesis Protein Subunits PTGS1 protein, human Tardigrada Thoracica Transcriptome
The experiment involved three salinity treatments (6, 15 and 30 PSU), corresponding to the native mean salinities for the three barnacle populations studied (Stockholm, Kiel and Tjärnö, respectively). From each of the four batches obtained per population, two panels with newly settled barnacles (eight days old) were placed in separate aquaria in each of the three salinity treatments, resulting in a split-plot design [51 ]. Three large independent re-circulating systems (370 l each) were used, each consisting of 24 aquaria (6 l each). The flow through each aquarium was 20-25 l/h. Each system had a biological filter (Fluval filter 405) with coral rubble, activated charcoal and nitrifying bacteria added to maintain water quality and avoid build-up of nitrogenous waste products. In addition, water in each system was completely replaced every two weeks, at which time the culture systems were cleaned, drained and treatment combinations were moved to a new system within the same room to avoid confounding the effects of salinity with effects of aquarium location within the room. The experiment was maintained at 20°C and a light regime of 14:10 h (L:D). The different salinities were obtained by mixing filtered deep saltwater (0.2 μm) from the Kosterfjord (30-34 PSU, total alkalinity, AT, of 2186-2290 μmol l-1) with filtered tap water (AT of 369 μmol l-1). Water quality variables including temperature, salinity, AT, NH3 and NH4 were monitored routinely during the experiment (Additional file 1: Table S1). Salinity was adjusted by adding freshwater whenever needed. Barnacles were fed a mixture of microalgae (Skeletonema marinoi and Chaetoceros calcitrans) at ~ 20,000 cells ml-1 and 30,000 cells ml-1, respectively. Algal cell concentrations were checked regularly using a Multisizer™ 3 Coulter Counter (Beckman Coulter) and levels were adjusted to maintain stable concentrations ad libitum throughout the experiment. The algal cell concentration in the systems never reached below 5,000 cells ml-1. Chlorophyll content of the algal cultures and experimental systems were also checked for possible degradation of food quality, assessed by a spectrophotometric trichromatic method [52 ], which showed no signs of degradation. After four weeks, the barnacle diet was complemented with newly hatched Artemia (ca. 3,000 Artemia per aquarium) added every second day. Barnacles were cultured in the experimental systems for a total of nine weeks.
Publication 2014
Alkalies Artemia Bacteria Biopharmaceuticals Cells Charcoal, Activated Chlorophyll Coral Diet Light Microalgae Nitrogen Salinity Spectrophotometry Thoracica
We used two approaches to test whether barnacle geese ‘surf’ along the green wave. One approach was a visualization method to identify correlations between barnacle goose movements during the spring migration and vegetation phenology. For the visualization method, first we divided the study area into three flyways, i.e. Russian, Svalbard and Greenland. Then we used the GPS-tracking data of migrating barnacle geese and related these to the spatio-temporal pattern in GWI (i.e. the vegetation phenology). In this regard, the annual GWI trajectories were stratified for each flyway separately by latitude, plotted along axes of time and latitude, and colored according to GWI value. Thus, each cell in the stratified image represented the average of the actual GWI values in each latitudinal band at a certain time.
The timing of 50% NDVI correlates with the peak in food quality [20] . So, our second approach was to define the date at which the actual GWI value reached 50% of its annual maximum at each of the stopover sites, and compare that to the date on which the geese arrived at that site using regression analysis. To perform the analysis, data from different stopover sites were combined from the three years for each population, leading to 57 stopover sites for the Russian population, 18 for the Svalbard population, and 14 for the Greenland population.
To predict the geese arrival dates from three populations at each stopover site, we used a linear, mixed-effect model, with a fixed effect for the date of 50% GWI, as well as considering the random effect of individual geese within different tracking years and the random effect of each tracking year.
A slope approximately equal to 1 and an intercept near 0 represents surfing the green wave (i.e. where the date of 50% GWI at a given stopover site was also the date on which that stopover was occupied by the geese). The coefficient of determination, R2, was used to assess the strength of the relation.
In addition to regression analysis, we calculated the root-mean-square deviation (RMSD) to measure how well the observed arrival dates at stopover sites fitted with arrival dates predicted from the satellite-derived GWI. We defined RMSD values<10 days as a good fit, 10–15 days as moderate, and >15 days as poor, based on Duriez et al. [48] .
The effect of tracking year and flyway on the actual GWI values was tested using a two-way factorial ANOVA, with year (three levels) and flyways (three levels) as well as their interaction. Where a significant effect was found, we used a Bonferroni correction at p = 0.0167 to compare means within each factor level.
Barnacle geese forage on food patches with the highest grass density [31] and they also forage on agricultural fields in temperate regions [19] , [34] (link). We therefore extracted the actual GWI values only from grassland and cropland land cover types in a 15-km radius around each of the 57, 18, and 14 stopover sites for the Russian, Svalbard, and Greenland populations respectively (Appendix S1). This distance is based on the core foraging range for barnacle geese [49] . In order to do the statistical analysis (i.e. regression and ANOVA), the actual GWI values were extracted from the real stopover site locations.
Publication 2014
Cells Epistropheus Food Geese Movement neuro-oncological ventral antigen 2, human Plant Roots Poaceae Population Group Radius Thoracica

Most recents protocols related to «Thoracica»

We placed all patients on standard non-invasive monitors. Anesthesia was induced according to the standard operating procedures [SOP] of our hospital using 1.5–2.5 mg/kg body weight (BW) Propofol, 0.2–0.5 µg/kg BW Sufentanil and 0.5–0.6 mg/kg ideal body weight (IBW) Atracurium or 0.6 mg/kg IBW Rocuronium at the discretion of the attending anesthesiologist. Maintenance of anesthesia was accomplished using Sevoflurane adjusted to age-corrected mean alveolar concentration. Analgesia was adapted to meet patient individual demands using additional Sufentanil boluses of 5–10 µg. A non-opioid analgetic was administered 30 min before the end of the procedure for early post-operative analgesia.
An arterial cannula was placed in the radial artery for continuous, invasive blood pressure monitoring (Philips IntelliVue MX700, Philips Medizin Systeme GmbH, Boeblingen, Germany). Invasive blood pressure monitoring was calibrated by placing the pressure transducer at the level of the right atrium and venting the transducer to atmospheric pressure for reference. ∆PP was calculated as ΔPP[%]((PPmax-PPmin)/([PPmax+PPmin]/2))×100
where PPmax and PPmin are the maximum and minimum pulse pressure during one respiratory cycle. ΔPP measurements were calculated from beat-to-beat arterial pressure values and reported as the average value of the last 32 s.
Stroke volume was measured by esophageal doppler monitoring (CardioQ-ODM®, Deltex Medical Ltd, Chichester, UK). The tip of the doppler probe was placed in the pars thoracica of esophagus at the level of the descending aorta. Stroke volume was calculated by the product of stroke distance (area of the doppler derived velocity–time waveform) and aortic cross-sectional area [12 (link)].
Patients were mechanically ventilated with a tidal volume ≥ 8 ml/kg IBW using pressure-controlled ventilation. Positive end-exspiratory pressure was kept between 5–8 mbar, respiratory rate was set to 12–16 min−1 and fraction of inspired oxygen (FiO2) was set to keep oxygen saturation above 95% according to departmental standard operating procedures. All settings and target values were continuously adapted to patient characteristics and clinical situation using repetitive blood gas analyses.
In case of possible hypovolemia a fluid bolus of 7 ml/kg IBW was administered at the discretion of the attending anesthesiologist.
Trigger for fluid bolusing were:

Difference in pulse pressure [∆PP] ≥ 9% [13 (link), 14 (link)] and/or

corrected flow time [FTc] ≤ 350 ms [15 (link)]

An increase in stroke volume ≥ 10% following the fluid bolus was considered ‘fluid responsive’.
Publication 2023
Anesthesia Anesthesiologist Aorta Arteries Arteries, Radial Atracurium Atrium, Right Blood Gas Analysis Blood Pressure Body Weight Cannula Cerebrovascular Accident Descending Aorta Esophagus Ideal Body Weight Management, Pain Opioids Oxygen Oxygen Saturation Patient Monitoring Patients Poly(ADP-ribose) Polymerases Precipitating Factors Pressure Propofol Pulse Pressure Respiratory Rate Rocuronium Sevoflurane Stroke Volume Sufentanil Thoracica Tidal Volume Transducers, Pressure
The fossil specimens dealt with herein were discovered at and around a sand quarry in the hinterland of Arcille (Campagnatico, Grosseto Province, Tuscany, central Italy). Arcille is located in the Baccinello–Cinigiano basin (Figure 1A), one of the post-collisional basins of the northern Apennines, whose Neogene infill comprises both continental and marine deposits [14 ]. The sedimentary succession cropping out at this site (Figure 1B) consists of terrigenous deposits dominated by yellowish, fossiliferous, shallow-marine shoreface sandstones with minor fluvial conglomeratic intercalations capped by greyish, open-shelf offshore mudstones [15 (link),16 ] (Figure 2). These sediments have been referred by Dominici et al. [17 (link)] to their S2 Synthem, a lithologically diverse, Lower Pliocene depositional unit that includes fluvial conglomerates, fluvio-deltaic and shoreface sandstones, and shelf mudstones. Biostratigraphic analyses of the planktic foraminiferal assemblage from the mudstone division cropping out at Arcille indicate the lower part of the Zanclean, i.e., the Mediterranean Pliocene (=MPl) zone 2, which has been referred by Lourens et al. [18 ] to the 5.08–4.52 Ma time span [19 (link)].
Palaeontological highlights of the Arcille quarry include: (i) various specimens of Metaxytherium subapenninum, the latest sirenian of the Mediterranean Sea, which on the whole comprise a reference record for reconstructing the osteoanatomy, phylogenetic relationships and palaeoecological habits of this halitheriine dugongid species [15 (link),19 (link)]; (ii) the holotype and referred specimen of Casatia thermophila, which represents one of the geologically oldest monodontid taxa, as well as the first and only representative of this odontocete family in the Mediterranean Basin [21 (link),22 (link)]; (iii) the holotype and referred specimens of Nebriimimus wardi, an idiosyncratic rajiform batoid whose unusual multicuspid tooth morphology is currently unparalleled [23 (link)]; and (iv) some teeth assigned to the extant requiem shark species Carcharhinus limbatus, which represent the first occurrence of the blacktip shark as a fossil from both Europe and the Mediterranean Basin [24 (link)]. Other remarkable vertebrate fossils from the sandy strata exposed at Arcille include two partial skeletons of a marlin (cf. Makaira sp.), as well as abundant and diverse elasmobranch teeth and spines [19 (link),23 (link),25 ,26 (link),27 (link)]. All things considered, the taxonomic composition of the marine vertebrate assemblage from Arcille indicates a warm-water, shallow-marine palaeoenvironment placed close to the coastline. In the same deposits, the remains of macro-invertebrates are also abundant, being dominated by bivalves (mainly pectinids and venerids, including the extinct large-sized clam Pelecyora gigas) with subordinate gastropods, scaphopods, echinoids and corals [25 ]. Given the presence of P. gigas, the molluscan assemblage can be referred to a stock of tropical or near-tropical taxa, categorised as the Mediterranean Pliocene Molluscan Unit (=MPMU) 1, whose most thermophilic members did not survive the cooling episode that affected the Mediterranean region around 3 Ma [28 ,29 (link)].
The three M. subapenninum specimens studied herein (GAMPS 62M, GAMPS 63M and MSNUP I-15892) originate from the highest portion of the sandstone division cropping out at Arcille. Such skeletons were discovered at two different horizons, resting upon as many shell beds [16 ,25 ]. The same stratigraphic intervals have yielded the holotype of N. wardi and the referred specimen of C. thermophila, as well as teeth of C. limbatus and fragmentary postcrania of cf. Makaira sp. [22 (link),23 (link),24 (link)]. The molluscan assemblage includes Glycymeris nummaria, Limopsis aurita, Venus nux, Procardium indicum, Helminthia triplicata, Oligodia spirata, Thetystrombus coronatus and Neverita olla [16 ]; scaphopods, barnacles and solitary corals (flabellids) are also present [25 ]. Macroscopic evidence of bioencrustation and bioerosion of the shell remains is apparently largely absent [25 ].
Publication 2023
Bivalves Clams Coral Elasmobranchii Extinction, Psychological Foraminifera Gastropods Invertebrates Marines Sharks Skeleton Thoracica Tooth Vertebral Column Vertebrates
In 2020, the Ocean Affairs Council in Taiwan announced a “Major Wildlife Habitat of Indo-Pacific Humpback Dolphin” as an area within 1–3 nautical miles offshore from the west coast of Taiwan, from 24°42′ N to 23°26′ N. The major wildlife habitat involves four counties: Miaoli, Taichung, Changhua, and Yunlin. This study focused on two counties located within the central habitat area: Taichung County (24°58′ N~24°11′ N) and Changhua County (24°11′ N~23°51′ N) (Figure 1). The study area included waters from the shoreline to shallow waters with depths < 15 m. Boat-based photo-ID surveys were conducted in 2018 (May to September), 2019 (April to September), and 2021 (April to November) by traveling at an average speed of 6 to 9 knots (13.89 km/h), with an average of 2 to 3 knots (4.63 km/h) when approaching animals using 10~12-meter-long CT-1 fishing boats. Dolphins were photographed using digital single-lens reflex cameras (Canon, Olympus, Pentax, or Nikon with 70–300 mm zoom lenses or 400 mm prime lenses). Every image was cataloged and cut into shape using PhotoImpact 11software, and individuals were further identified from those images by their distinctive scars and markings.
Identified individuals were grouped into five coloration stages based on changes in body color [21 ]: gray and unspotted (calf), gray with some white spotting (mottled), white with lots of black spotting (speckled), white with less black spotting (spotted adult), and white with a pinkish tint and no spotting (unspotted adult) (Figure 2). In this study, markings that possibly resulted from conspecifics or sharks were excluded from the analysis. Injuries were classified into five categories: dorsal fin/fluke mutilation, narrow-spaced linear marks, wide-spaced linear marks, back indentation, and others (Table 1). Skin lesions were classified into seven categories: nodules, hypertrophic scars, barnacles, pale, black patch, red patch, and orange/yellow patch (Table 2).
Publication 2023
Adult Animals Cicatrix Cicatrix, Hypertrophic Dolphins Human Body Injuries Lens, Crystalline Reflex Sharks Skin Sousa Thoracica Trematoda
Aquarium volunteers recorded green turtle observations on the first Saturday of each month (commencing circa October 2012). Although other sea turtle species that occur off the U.S. West Coast have been sighted offshore of California, to date, only green turtles have been recorded within the SGR by professional biologists, CS volunteers, and Aquarium staff overseeing the monitoring sessions. Monitoring sessions lasted for 30 min from 9:00 to 9:30 a.m. A minimum of 2–4 volunteers were assigned to each station, with one volunteer recording data on a paper observation log that included a station diagram (Figure 4). Throughout the monitoring session, volunteers recorded information each time a green turtle surfaced for air, which constitutes a “sighting” (also referred to as a “surfacing”). For each sighting, volunteers recorded location, surfacing time, and relative head size. Head size was reported as large (drawn as a circle, comparable in size to a softball or larger), medium (drawn as a square, comparable in size to a baseball), or small (drawn as a triangle, comparable in size to a golf ball or smaller) [65 ]. The presence of distinctive barnacles (e.g., Chelonibia testudinaria) or other markings visible on the head or body were also used as distinguishing features. Volunteers recorded other information in a notes box on the observation log, including other wildlife sighted (e.g., sea lions or jumping fish), weather patterns, and/or human activity.
Volunteers assigned a numerical number to each sighting based on Aquarium protocols for identifying unique individuals. The purpose of this practice was to gain a general idea of the minimum number of green turtles that may have been present at a given station during a monitoring session. Each presumed individual sea turtle was numbered; a subsequent sighting was not numbered as a new individual unless volunteers could distinguish the sighting as a new individual via a simultaneous sighting (i.e., multiple turtles surfaced at once, meaning that the two surfacings must be separate individuals), a sighting with a different relative head size, or a sighting with a distinct physical feature (presence of barnacles, darker head color, etc.).
Once the 30-min monitoring session concluded, the volunteer responsible for recording the data tallied the total number of sightings and estimated individuals, and delivered the observation log to the Aquarium’s volunteer coordinators overseeing the session. Data from the observation logs was later entered into a spreadsheet managed by Aquarium staff.
Publication 2023
Darkness Fishes Head Human Body Physical Examination Sea Lion Sea Turtles Thoracica Turtle Voluntary Workers
The Geneious v8.0.5 software was used to align with homologous genes from H. thoracica and H. yehi [37 (link)]. The software MEGA v7.0 was used to calculate the A + T content, AT-skew, GC-skew, and relative synonymous codon usage (RSCU) for (PCG) analysis [39 (link)]. The bias of base usage was calculated by AT-skew and GC-skew. The calculation formulas were as follows: AT-skew = (A − T)/(A + T) and GC-skew = (G − C)/(G + C). Tandem repeats in the control regions (CRs) were detected using the Tandem Repeat Finder v4.09 [40 (link)]. Twenty-two tRNAs were identified using tRNA-ScanSE Search Server v1.21 and ARWEN v1.2.3 based on the secondary structures and then were manually proofread according to the codon and tRNA structure [41 (link),42 (link)]. The secondary structures of rrnS and rrnL were predicted by RNA Structure (http://rna.urmc.rochester.edu/RNAstructureWeb/) (accessed on 9 September 2021) and then the Clustal_W v2.1 algorithm in MEGA v7.0 was used to align them and the other available Cucujoid mt genomes [43 (link)]. The nucleotide diversity (Pi) of 13 Helotidae PCGs was assessed using DnaSP v6.0 [44 (link)]. A sliding window of 150 bp in 5 bp steps was performed using the Spider package in R v3.4.4 [45 (link),46 ]. The software MEGA v7.0 [39 (link)] was used to calculate the genetic distances, based on the Kimura-2-parameter model, between the two mt genomes. The ratios of non-synonymous substitutions (Ka)/synonymous substitutions (Ks) for each PCG were measured using KaKs_Calculator v2.0 [47 (link),48 (link)].
Publication 2023
Codon Codon Usage Diet, Formula Genes Genome Nucleotides Reproduction Richards-Rundle syndrome Spiders Tandem Repeat Sequences Thoracica Transfer RNA

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More about "Thoracica"

Thoracica, a suborder of marine crustaceans, encompasses a diverse array of organisms including barnacles, goose barnacles, and acorn barnacles.
These sessile creatures attach themselves to various surfaces such as rocks, ships, and even marine animals, playing crucial roles in marine ecosystems.
As food sources and contributors to the fouling of submerged structures, Thoracica are of great interest to researchers.
To optimize Thoracica research, scientists can utilize the powerful PubCompare.ai tool, which leverages AI-driven reproducibility enhancement.
This tool helps researchers easily locate relevant protocols from literature, preprints, and patents, and provides AI-based comparisons to identify the best protocols and products, ultimately enhancing Thoracica research efforts.
Beyond the PubCompare.ai tool, researchers may also find value in other advanced technologies and equipment.
For instance, the HiSeq 3000 sequencing system, the Coolpix W300 underwater camera, and the InVia confocal Raman microscope can all contribute to the study of Thoracica and their marine environments.
Additionally, common laboratory tools like the Kern Analytical balance, the XMReconstructor software, and the Nanoman nanoparticle characterization system can support various aspects of Thoracica research.
To further enrich their studies, researchers may utilize chemical compounds such as Ampicillin, a widely used antibiotic, and Protease inhibitor cocktail, which helps preserve protein samples.
Bovine serum albumin, a common protein used in cell culture media, may also find applications in Thoracica research.
By incorporating these diverse tools, technologies, and substances, researchers can enhance their understanding of the Thoracica suborder and its role in marine ecosystems, ultimately driving forward the field of Thoracica research.