We defined critical illness as severe sepsis, delivery of mechanical ventilation, or death at any point during hospitalization. We use this definition of critical illness rather than simple admission to an ICU, which can be influenced by emergency department disposition, ICU bed availability, and local practice variation. We used a clinically validated, administrative definition for severe sepsis based on International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnosis codes for a bacterial or fungal infectious process and the presence of acute organ dysfunction.19 (link) Because of changes in coding for sepsis, we also included ICD-9-CM codes 995.91 (systemic inflammatory response syndrome due to infectious process without acute organ dysfunction), 995.92 (severe sepsis), and 785.52 (shock without mention of trauma; septic shock) in our definition. We used the ICD-9-CM procedure code (96.7×) to define the need for mechanical ventilation.20 (link) We defined hospital death using discharge disposition in CHARS. We abstractedout-of-hospital clinical data from the King County EMS database, including dispatch, demographic, physical examination, procedure, and transport data. We evaluated only initial out-of-hospital vital signs, documented by first-arriving EMS personnel.
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Fish
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Salvelinus
Salvelinus
Salvelinus is a genus of freshwater fish belonging to the family Salmonidae.
These fish, commonly known as char or trout, are found in cold, clear waters of the Northern Hemisphere.
Salvelinus species are characterized by the presence of light-colored spots on their dark bodies and a white leading edge on their fins.
They are important food and game fish, with several species being commercially farmed or extensively fished.
Salvelinus research is crucial for understanding the biology, ecology, and conservation of these ecologically and economically significant fish.
PubCompare.ai is an AI-driven platform that can optimize Salvelinus research by helping researchers easily locate relevant protocols from literature, preprints, and patents, and leverage AI-driven comparisons to identify the best protocols and products for their Salvelinus studies.
This can streamline research and unlock new insights to advance the understanding of this important genus of fish.
These fish, commonly known as char or trout, are found in cold, clear waters of the Northern Hemisphere.
Salvelinus species are characterized by the presence of light-colored spots on their dark bodies and a white leading edge on their fins.
They are important food and game fish, with several species being commercially farmed or extensively fished.
Salvelinus research is crucial for understanding the biology, ecology, and conservation of these ecologically and economically significant fish.
PubCompare.ai is an AI-driven platform that can optimize Salvelinus research by helping researchers easily locate relevant protocols from literature, preprints, and patents, and leverage AI-driven comparisons to identify the best protocols and products for their Salvelinus studies.
This can streamline research and unlock new insights to advance the understanding of this important genus of fish.
Most cited protocols related to «Salvelinus»
Bacteria
Critical Illness
Diagnosis
Hospitalization
Infection
Mechanical Ventilation
Mycoses
Obstetric Delivery
Patient Discharge
Physical Examination
Salvelinus
Septicemia
Septic Shock
Severe Sepsis
Shock, Traumatic
Signs, Vital
Systemic Inflammatory Response Syndrome
Carbon content in feedstock (and char) was measured in triplicates on 100-mg samples that were combusted at 1030°C and analyzed in an element analyzer (Perkin-Elmer Optima 5300 DV Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES)). Wood feedstock was analyzed to contain 50.1% C, Eupatorium shrub 40.3% C, and in our parallel project in Tanzania rice husk was analyzed to contain 41.1% C, in accordance with literature values [25 ]. All biochars were characterized for cation exchange capacity by extraction with ammonium acetate at pH 7, both before and after washing with water for those samples where quenching was done with soil, and only after washing for the water-quenched samples [26 ]. Three biochars representing two different kiln types (soil pit kiln and metal cone kiln each 70°—1m50 diameter) and two feedstock (100% Eupatorium and 50:50 Eupatorium: hard wood) were analyzed by a EBC accredited laboratory following the EBC certification program and methods [4 , 27 ]. Five example biochars were further analyzed for 15 individual PAHs by 36-h exhaustive toluene Soxhlet extraction according to published procedures [28 (link), 29 (link)] and surface area by N2 adsorption at 77 K.
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Adsorption
ammonium acetate
Carbon
Eupatorium
Metals
Oryza sativa
Plasma
Polycyclic Hydrocarbons, Aromatic
Retinal Cone
Salvelinus
Toluene
Vision
We modified the phylogenetic matrix compiled by Fischer et al. [34] . We deleted two dental characters (chars. 4 and 5) because examination of the abundant material of Ophthalmosaurus showed that these characters varied during ontogeny. We also deleted character 23 because the states were not clearly defined and proved uninformative. Characters 3 and 34 were slightly modified (see Text S1 ) as were some codings: this is due both to new observations, and because the analysis now incorporates species-level taxa amongst Thunnosauria (character-taxon matrix available in Table S1 and nexus file in Text S2 ). Finally, we added four new characters (chars. 19, 20, 27, 36, see Text S1 ) and two taxa: Ophthalmosaurus natans and Acamptonectes densus. Characters were coded from the literature and personal observations for Temnodontosaurus (IRSNB R122 and IRSNB R123), Platypterygius hercynicus (MHNH 2010.4 and a cast of the holotype held at the SNHM), Sveltonectes insolitus (IRSNB R269), Ophthalmosaurus natans (CM material), Ophthalmosaurus icenicus (NHMUK and GLAHM material) and Acamptonectes densus (GLAHM 132588, SNHM1284-R, NHMUK R11185). We used exact parsimony searches of TNT v1.1 [35] to analyze the character matrix (see supporting information) and calculate the Bremer support and bootstrap values. We generated the phylogenetic tree with unambiguous optimization using Winclada v.0.9 [36] (fast and slow optimizations are available in Figure S1 ). Characters were not weighted and, except for characters 17, 39, and 45, were not ordered.
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ARID1A protein, human
CD3EAP protein, human
Character
Dental Health Services
Nexus
Salvelinus
The starting point for this in silico analysis were the sequences for the two known salmon DNA transposons SALT1 [Genbank:L22865 ] [19 (link)] and Tss [Genbank:L12207 ] [18 (link)], as well as an analysis of the sequence of the T-cell receptor alpha locus of Salmo salar by RepeatMasker [46 ]. These two transposons as well as the RepeatMasker data were used to find faint similarities which were used in turn to find a larger number of each family in approximately 3 Mbp of sequence. The Dotter program [47 (link)] was used extensively to find regions of similar sequence, which were extracted and stored in an SQL database. The length of the transposon sequences was determined by identifying the inverted terminal repeat sequences where possible. Sequence alignments were performed with ClustalW [48 (link)] and phylogenetic trees generated with MEGA3.1 [49 (link)] using the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), pairwise deletion, and a p-distance model. The entire alignment of the sequences was used in the phylogenetic reconstruction. Our salmon EST database was searched for the presence of sequences that are similar to the DNA transposon sequences that we found in salmon.
The following DNA sequences and BAC clones were used in this analysis. The Salmo salar TCRα locus [30 (link)], the major histocompatibility loci MHC class 1a and 1b [29 ], the growth hormone and interleukin loci (manuscripts in preparation), and zoneadhesin-like genes [Genbank:AY785950 ] and the Oncorhynchus mykiss sequences for the metallothionein gene [GENBANK:DQ156151 ], MHC1a [Genbank:AB162342 ] and MHC1b loci [Genbank:AB162343 ], and the IgH.A locus [Genbank:AY872256 ]. Genbank sequence entries were used in this study from a variety of other organisms (table 2 ): Oncorhynchus mykiss, Ictalurus punctatus, Esox lucius, Cyprinus carpio, Salvelinus namaycush, Salvelinus confluentus, Salvelinus fontinalis, Tanichthys albonus, Carassius auratus, Astatotilapia burtoni, Oryzias latipes, Petromyzon marinus, Danio rerio, Xenopus tropicalis, Xenopus laevis, Rana pipens, and Polypterus bichir. Sequences from Schistosoma japonicum EST Genbank data were found for transposon families as follows: DTSsa1 [Genbank:AY915112 , AY809993 ], DTSsa2 [Genbank:AY816058 , AY834394 ], DTSsa3 [Genbank:AY124772 ], DTSsa4 [Genbank:AY812589 , AY915240 ], DTSsa5 [Genbank:AY813498 ], DTSsa6 [Genbank:AY813020 ], DTSsa7 [Genbank:AY813225 , AY915121 ], SSTN1 [Genbank:AY809988 , AY815476 , AY915835 ], Tss [Genbank:AY915400 , AY915891 ], and SALT1 [Genbank:AY223470 , AY915102 ].
Representative sequences from all new families have been deposited in GenBank under accession numbersEF685954 – EF685960 , EF685962 – EF685963 , and EF685966 – EF685967 .
The following DNA sequences and BAC clones were used in this analysis. The Salmo salar TCRα locus [30 (link)], the major histocompatibility loci MHC class 1a and 1b [29 ], the growth hormone and interleukin loci (manuscripts in preparation), and zoneadhesin-like genes [Genbank:
Representative sequences from all new families have been deposited in GenBank under accession numbers
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Catfishes, Channel
Clone Cells
Cyprinus carpio
Deletion Mutation
DNA Transposons
Esox lucius
Genes
Goldfish
Growth Hormone
Interleukins
Inverted Terminal Repeat
Jumping Genes
Metallothionein
Oncorhynchus mykiss
Oryzias latipes
Petromyzon marinus
Rana
Salmo salar
Salvelinus
Schistosoma japonicum
Sequence Alignment
Sequence Analysis
Syncope
T Cell Receptor alpha Chain Genes
Xenopus laevis
Zebrafish
Analyses were largely conducted in R v3.4.1 (75 ). First, a disparity-through-time plot was created for the individual partitions by using the dtt function in the GEIGER R package v2.0.6 (76 (link), 77 (link)). Second, we used BayesTraitsV3 (78 ) to estimate evolutionary rates for the overall skull and its partitions based on PCs accounting for >95% of total shape variation (SI Appendix, Table S3 ). All available evolutionary models were tested, including BM, OU, δ, κ, and λ models. Bayes Factor was used to determine the best-supported evolutionary model. Estimated rates based on the preferred model were used to generate a rate-through-time plot for each partition. Total disparity (Procrustes variance) and mean evolutionary rates under the BM model were calculated within each model and for each landmark and sliding semilandmark by using the morphol.disparity and compare.multi.evol.rates functions in the geomorph R package v.3.0.5 (79 , 80 ), respectively. We simulated shape evolution under BM model by using the sim.char function in GEIGER R package. Ancestral shapes were calculated by using the anc.recon function in the Rphylopars R package v0.2.9 (81 (link)) on extant-only and combined datasets.
The geomorph R package was used to assess allometry, phylogenetic signal, evolutionary allometry, and phylogenetically corrected correlations with ecological and reproductive variables in partition-specific and whole skull-shape data by using the functions procD.allometry, physignal, and procD.pgls (SI Appendix, Tables S6, S9, and S11 ). Because of the proportionately low contribution of (evolutionary) allometric signal, we did not correct for allometry in the datasets for other analyses. To identify cranial modules from partitions, we employed EMMLi (26 (link)), a maximum-likelihood approach, and CR analysis (27 ), which is implemented in geomorph. By using the results output by EMMLi, we further assessed the pattern of integration by comparing estimated within-module correlations (ρwithin) with the estimated between-module correlation (ρbetween) for each pair of partitions (SI Appendix, SI Text ). We applied a subsampling approach to ascertain the robustness of these results by running 100 repetitions of EMMLi with 10% of the total landmark dataset while keeping a minimum of three landmarks + sliding semilandmarks per partition, which consistently returned the same pattern of cranial modules, as did analyses limited to landmarks only (SI Appendix, Fig. S9 ). Results from EMMLi and CR analyses with and without phylogenetic correction yielded largely congruent results (SI Appendix, Tables S7 and S8 ). Least-squares linear regression was conducted on these values to determine any relationships between disparity, mean evolutionary rates, and within-module correlation (SI Appendix, Table S9 ). Integration and macroevolutionary patterns were assessed separately for extant lizards, extant snakes, all extant squamates, and combined extant and extinct squamates.
The geomorph R package was used to assess allometry, phylogenetic signal, evolutionary allometry, and phylogenetically corrected correlations with ecological and reproductive variables in partition-specific and whole skull-shape data by using the functions procD.allometry, physignal, and procD.pgls (
Biological Evolution
Cranium
Extinction, Psychological
Glomus Tumors, Familial, 1
Lizards
Reproduction
Salvelinus
Snakes
Most recents protocols related to «Salvelinus»
First, 0.0875 g of
lignin was suspended in DI water with the Ni–Fe cocatalysts
on magnesium silicate supports in a batch reactor. To study the effect
of temperature on the depolymerization of kraft lignin, the system
was studied at temperatures of 250, 300, and 350 °C. Catalysts
were further loaded at 0.0044 g into the reactor. Subsequently, the
reactor was sealed and purged with N2 to remove any reactive
air and achieve an inert atmosphere until reaching 10 bars of N2. The reactor was operated for 1 h with vertical shaking at
40 rpm.
After completing the reaction, the products were separated
by a centrifuge consisting of solid and liquid phases. The solid phase
was defined as char, while the liquid phase contained lignin-derived
products and residual lignin. Next, the liquid phase was acidified
to a pH of 2.00 with 1 M hydrochloric acid. In this step, the residual
lignin was precipitated out as solids by a centrifuge at 15 °C.
Next, the lignin-derived products were separated using ethyl acetate.
Finally, the samples were characterized and quantified by a gas chromatography
mass spectrometer.
The liquid fraction qualification was analyzed
on a GC–MS
instrument (Shimadzu) equipped with a capillary column (30 m ×
0.32 mm × 0.25 mm). The GC heating ramp was as follows: the oven
temperature program increased from 40 °C (held for 3 min) to
300 °C at a rate of 5 °C/min under a helium atmosphere.
The main products from the depolymerization of kraft lignin are anisole,
phenol, p-cresol, 4-ethylphenol, creosol, catechol,
guaiacol, mequinol, 4-ethylguaiacol, syringol, 4-hydroxybenzaldehyde,
vanillin, 4′-hydroxyacetophenone, 3,4-dimethoxyenzaldehyde,
and vanillic acid. These products were analyzed using the database
from the National Institute of Standards and Technology (NIST) for
comparison of the molecular weight. The yields of each product and
the kraft lignin conversion were calculated using the followingeqs 1 and 2 .
lignin was suspended in DI water with the Ni–Fe cocatalysts
on magnesium silicate supports in a batch reactor. To study the effect
of temperature on the depolymerization of kraft lignin, the system
was studied at temperatures of 250, 300, and 350 °C. Catalysts
were further loaded at 0.0044 g into the reactor. Subsequently, the
reactor was sealed and purged with N2 to remove any reactive
air and achieve an inert atmosphere until reaching 10 bars of N2. The reactor was operated for 1 h with vertical shaking at
40 rpm.
After completing the reaction, the products were separated
by a centrifuge consisting of solid and liquid phases. The solid phase
was defined as char, while the liquid phase contained lignin-derived
products and residual lignin. Next, the liquid phase was acidified
to a pH of 2.00 with 1 M hydrochloric acid. In this step, the residual
lignin was precipitated out as solids by a centrifuge at 15 °C.
Next, the lignin-derived products were separated using ethyl acetate.
Finally, the samples were characterized and quantified by a gas chromatography
mass spectrometer.
The liquid fraction qualification was analyzed
on a GC–MS
instrument (Shimadzu) equipped with a capillary column (30 m ×
0.32 mm × 0.25 mm). The GC heating ramp was as follows: the oven
temperature program increased from 40 °C (held for 3 min) to
300 °C at a rate of 5 °C/min under a helium atmosphere.
The main products from the depolymerization of kraft lignin are anisole,
phenol, p-cresol, 4-ethylphenol, creosol, catechol,
guaiacol, mequinol, 4-ethylguaiacol, syringol, 4-hydroxybenzaldehyde,
vanillin, 4′-hydroxyacetophenone, 3,4-dimethoxyenzaldehyde,
and vanillic acid. These products were analyzed using the database
from the National Institute of Standards and Technology (NIST) for
comparison of the molecular weight. The yields of each product and
the kraft lignin conversion were calculated using the following
4-ethylguaiacol
4-ethylphenol
4-hydroxyacetophenone
4-hydroxybenzaldehyde
anisole
ARID1A protein, human
Atmosphere
Capillaries
Catechols
creosol
ethyl acetate
Guaiacol
Helium
Hydrochloric acid
Kraft lignin
Lignin
Magnesium
mequinol
para-cresol
Phenol
Salvelinus
Silicates
Syringol
Vanillic Acid
vanillin
Lipid storage also plays a key role in reproduction for siscowet lake trout. Surveys of wild lake trout found that siscowet lake trout that skipped spawning had significantly lower energy reserves than those that did not skip (Sitar et al., 2014 (link)). In laboratory settings, muscle lipid concentration prior to parasitism was a significant predictor of ovarian mass and the likelihood of skipping spawning (Firkus et al., 2022 (link)). Therefore, accounting for individual variation and other factors that influence muscle lipid is important for accurately modeling the influence of parasitism. Approaches have been developed to account for differences in lipid storage in a DEB context, but they require the use of simplified models that do not include all of the components of a full DEB model (Martin et al., 2017 (link)).
Lipid storage has no direct analogue in the DEB framework, but is most analogous to the reserve compartment, which primarily consists of polymers and lipids (Kooijman, 2010 (link)). The energy conductance parameter controls the rate of energy mobilization from the reserve. Increasing increases the rate at which reserves are depleted and mobilized for use. We would expect that siscowet lake trout with low muscle lipid storage would mobilize energy from the reserve at a much lower rate to allow lipid to accumulate. Reduced energy mobilization seems especially likely given the functional role of lipid for maintaining neutral buoyancy at the depths siscowet lake trout inhabit (Henderson and Anderson, 2002 ; Goetz et al., 2014 (link)). We implemented changes to the energy conductance parameter so that it is relative to the average muscle lipid concentration in laboratory-raised lake trout that did not skip spawning (Firkus et al., 2022 (link)). As muscle lipid concentration strays from the average (55.58%), energy conductance increases or decreases following the function where “lipid” is the muscle lipid concentration of an individual lake trout (Table 2 ).
Muscle lipid concentration also likely influences reproductive efficiency, represented in the DEB model as . Empirically, low muscle lipid concentration has been associated with an increased likelihood of skipped spawning for siscowet lake trout (Sitar et al., 2014 (link); Firkus et al., 2022 (link)). Because lipid reserves are drawn upon to create reproductive mass, low muscle lipid concentrations could mean there are insufficient resources such as critical amino and fatty acids available for gamete production, and producing gametes in the absence of adequate lipid reserves results in reduced reproductive efficiency. Muscle lipid concentration influencing oocyte maturation and quality is well supported in the literature for a variety of species (Craig et al., 2000 (link); Rodríguez et al., 2004 (link); Ghaedi et al., 2016 (link)). To account for the influence of low muscle lipid concentration on reproductive efficiency, the unstressed value from the base model is modified for lake trout with muscle lipid concentrations below average for siscowet lake charr (55.58%) using the equation: where lipid is the percent muscle lipid concentration of an individual and 55.58% is the average percent muscle lipid concentration of siscowet lake trout used in laboratory sea lamprey parasitism trials (Firkus et al., 2022 (link)). When muscle lipid concentrations are equal or greater than average, remains unchanged. With this function, the further muscle lipid concentration deviates below average, the lower is, but as muscle lipid increases above average, does not increase as reproduction efficiency is rarely greater than 0.95 in DEB applications (Lika et al., 2011b (link)).
Lipid storage has no direct analogue in the DEB framework, but is most analogous to the reserve compartment, which primarily consists of polymers and lipids (Kooijman, 2010 (link)). The energy conductance parameter controls the rate of energy mobilization from the reserve. Increasing increases the rate at which reserves are depleted and mobilized for use. We would expect that siscowet lake trout with low muscle lipid storage would mobilize energy from the reserve at a much lower rate to allow lipid to accumulate. Reduced energy mobilization seems especially likely given the functional role of lipid for maintaining neutral buoyancy at the depths siscowet lake trout inhabit (Henderson and Anderson, 2002 ; Goetz et al., 2014 (link)). We implemented changes to the energy conductance parameter so that it is relative to the average muscle lipid concentration in laboratory-raised lake trout that did not skip spawning (Firkus et al., 2022 (link)). As muscle lipid concentration strays from the average (55.58%), energy conductance increases or decreases following the function where “lipid” is the muscle lipid concentration of an individual lake trout (
Muscle lipid concentration also likely influences reproductive efficiency, represented in the DEB model as . Empirically, low muscle lipid concentration has been associated with an increased likelihood of skipped spawning for siscowet lake trout (Sitar et al., 2014 (link); Firkus et al., 2022 (link)). Because lipid reserves are drawn upon to create reproductive mass, low muscle lipid concentrations could mean there are insufficient resources such as critical amino and fatty acids available for gamete production, and producing gametes in the absence of adequate lipid reserves results in reduced reproductive efficiency. Muscle lipid concentration influencing oocyte maturation and quality is well supported in the literature for a variety of species (Craig et al., 2000 (link); Rodríguez et al., 2004 (link); Ghaedi et al., 2016 (link)). To account for the influence of low muscle lipid concentration on reproductive efficiency, the unstressed value from the base model is modified for lake trout with muscle lipid concentrations below average for siscowet lake charr (55.58%) using the equation: where lipid is the percent muscle lipid concentration of an individual and 55.58% is the average percent muscle lipid concentration of siscowet lake trout used in laboratory sea lamprey parasitism trials (Firkus et al., 2022 (link)). When muscle lipid concentrations are equal or greater than average, remains unchanged. With this function, the further muscle lipid concentration deviates below average, the lower is, but as muscle lipid increases above average, does not increase as reproduction efficiency is rarely greater than 0.95 in DEB applications (Lika et al., 2011b (link)).
Full text: Click here
Fatigue
Fatty Acids
Gametes
Genes, vif
Lipid A
Lipids
Muscle Development
Muscle Tissue
Oocytes
Ovary
Petromyzon marinus
Polymers
Reproduction
Salvelinus
Trout
The optical
thin slices for microscopic
optical analysis were prepared according to GB/T 16773–2008.
The samples were mixed with an epoxy resin in ring-shaped molds. Once
cured, the sample was demoulded, ground, and polished to obtain an
optical thin slice with a surface size of 25 mm × 25 mm. The
sample particle area on the working area should be more than 2/3.
The petrographic analysis of the optical thin slices was performed
using a Zeiss microscope (Axio Scope1&MSO) with reflected light,
50× magnification, and oil immersion. The petrographic composition
of coal and coke based on the microscopic composition was determined
according to the ICCP guidelines.27 (link)−29 (link) According to the classification scheme for the combustion
coal, the morphology of the unburned char was characterized.30 (link) The quantitative studies were carried out using
point counters; the maceral content analysis was carried out on the
surface of the optical thin slices with equal spacing points, and
the effective points of each optical slice were not less than 500.
thin slices for microscopic
optical analysis were prepared according to GB/T 16773–2008.
The samples were mixed with an epoxy resin in ring-shaped molds. Once
cured, the sample was demoulded, ground, and polished to obtain an
optical thin slice with a surface size of 25 mm × 25 mm. The
sample particle area on the working area should be more than 2/3.
The petrographic analysis of the optical thin slices was performed
using a Zeiss microscope (Axio Scope1&MSO) with reflected light,
50× magnification, and oil immersion. The petrographic composition
of coal and coke based on the microscopic composition was determined
according to the ICCP guidelines.27 (link)−29 (link) According to the classification scheme for the combustion
coal, the morphology of the unburned char was characterized.30 (link) The quantitative studies were carried out using
point counters; the maceral content analysis was carried out on the
surface of the optical thin slices with equal spacing points, and
the effective points of each optical slice were not less than 500.
Coal
Cocaine
Epoxy Resins
Fungus, Filamentous
Immersion
Light
Microscopy
Salvelinus
Vision
Chars
from semi-coke and coke breeze were prepared in a drop tube furnace
(DTF) to identify the microscopic optical characteristics of different
single fuels after combustion. The details of the reactor were described
in some studies,26 (link) and the DTF experimental
system is shown inFigure 1 . The reactor was operated at 1000 °C under air atmosphere
(O2/N2 = 1:4) and the powder flow rate was 0.6
g ± 0.05 g/min. The residence time of the fuel in the DTF was
about 2–3 s. The chars were collected by the filter cartridge
for petrographic analysis.
from semi-coke and coke breeze were prepared in a drop tube furnace
(DTF) to identify the microscopic optical characteristics of different
single fuels after combustion. The details of the reactor were described
in some studies,26 (link) and the DTF experimental
system is shown in
(O2/N2 = 1:4) and the powder flow rate was 0.6
g ± 0.05 g/min. The residence time of the fuel in the DTF was
about 2–3 s. The chars were collected by the filter cartridge
for petrographic analysis.
Atmosphere
Cocaine
Light Microscopy
Powder
Salvelinus
Longitudinal Env evolution analyses were performed as described (12 (link)). Briefly, LASSIE (https://github.com/phraber/lassie ) was used to identify amino acid/glycan mutations under selection, using 80% or higher loss of the transmitted virus sequence as the cutoff. The webtool AnalyzeAlign was used to calculate sequence logos (https://www.hiv.lanl.gov/content/sequence/ANALYZEALIGN/analyze_align.html ) that show evolution at such sites. Glycan shield mapping was performed using the Glycan Shield Mapping tool (https://www.hiv.lanl.gov/content/sequence/GLYSHIELDMAP/glyshieldmap.html ) (56 (link)). Hypervariable loops from longitudinal Envs were characterized using alignment-free characteristics (https://www.hiv.lanl.gov/content/sequence/VAR_REG_CHAR/index.html ), such as length, number of glycans, and net charge. Hypervariable loop positions were identified based on HXB2 numbering:132 to 152 for hypervariable V1,185 to 190 for hypervariable V2, 396 to 410 for hypervariable V4, and 460 to 465 for hypervariable V5.
Full text: Click here
Amino Acids
Biological Evolution
Complementarity Determining Regions
Genes, env
Mutation
Polysaccharides
Salvelinus
Virus
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More about "Salvelinus"
Salvelinus, a Genus of Freshwater Char and Trout: Exploring the Biology, Ecology, and Conservation of these Ecologically and Economically Significant Fishes Salvelinus is a captivating genus of freshwater fish belonging to the Salmonidae family, commonly known as char or trout.
These cold-water-loving species are found in the clear, chilly waters of the Northern Hemisphere, including regions such as North America, Europe, and Asia.
Salvelinus species are characterized by their distinctive light-colored spots on their dark bodies and a striking white leading edge on their fins, making them visually appealing to both anglers and researchers.
Salvelinus research is of crucial importance for understanding the biology, ecology, and conservation of these ecologically and economically significant fish.
Advancements in analytical techniques, such as those offered by advanced instruments like the JEM-2100 transmission electron microscope, ASAP 2020 surface area and porosity analyzer, and STA 6000 simultaneous thermal analyzer, have enabled researchers to delve deeper into the physiological processes and environmental adaptations of Salvelinus species.
PubCompare.ai, an AI-driven platform, can further optimize Salvelinus research by helping researchers easily locate relevant protocols from literature, preprints, and patents.
This tool leverages AI-driven comparisons to identify the best protocols and products for Salvelinus studies, streamlining the research process and unlocking new insights to advance the understanding of this important genus of fish.
Whether you're a fisheries biologist, aquaculture specialist, or conservation ecologist, exploring the fascinating world of Salvelinus can provide invaluable insights into the biology, ecology, and management of these remarkable freshwater species.
With the aid of cutting-edge analytical tools and AI-powered research optimization platforms like PubCompare.ai, the future of Salvelinus research holds great promise for unlocking new discoveries and driving sustainable management strategies for these ecologically and economically significant fishes.
OtherTerms: Char, Trout, Salmonidae, Northern Hemisphere, JEM-2100, ASAP 2020, STA 6000, STA449F3, JSM-6610LV, TGA 8000, TM3030, Vario Micro Cube, SU8010, Silica gel 60 F254, Fisheries Biology, Aquaculture, Conservation Ecology
These cold-water-loving species are found in the clear, chilly waters of the Northern Hemisphere, including regions such as North America, Europe, and Asia.
Salvelinus species are characterized by their distinctive light-colored spots on their dark bodies and a striking white leading edge on their fins, making them visually appealing to both anglers and researchers.
Salvelinus research is of crucial importance for understanding the biology, ecology, and conservation of these ecologically and economically significant fish.
Advancements in analytical techniques, such as those offered by advanced instruments like the JEM-2100 transmission electron microscope, ASAP 2020 surface area and porosity analyzer, and STA 6000 simultaneous thermal analyzer, have enabled researchers to delve deeper into the physiological processes and environmental adaptations of Salvelinus species.
PubCompare.ai, an AI-driven platform, can further optimize Salvelinus research by helping researchers easily locate relevant protocols from literature, preprints, and patents.
This tool leverages AI-driven comparisons to identify the best protocols and products for Salvelinus studies, streamlining the research process and unlocking new insights to advance the understanding of this important genus of fish.
Whether you're a fisheries biologist, aquaculture specialist, or conservation ecologist, exploring the fascinating world of Salvelinus can provide invaluable insights into the biology, ecology, and management of these remarkable freshwater species.
With the aid of cutting-edge analytical tools and AI-powered research optimization platforms like PubCompare.ai, the future of Salvelinus research holds great promise for unlocking new discoveries and driving sustainable management strategies for these ecologically and economically significant fishes.
OtherTerms: Char, Trout, Salmonidae, Northern Hemisphere, JEM-2100, ASAP 2020, STA 6000, STA449F3, JSM-6610LV, TGA 8000, TM3030, Vario Micro Cube, SU8010, Silica gel 60 F254, Fisheries Biology, Aquaculture, Conservation Ecology