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Martes

Martes is a genus of small to medium-sized mammals known as martens or pine martens.
These carnivorous members of the weasel family are found in forested regions of North America, Europe, and Asia.
Martes species are known for their agility, climbing abilities, and distinctive yellow or cream-colored throats.
They play an important role in their ecosystems as predators and scavengers.
Researchers can use advanced AI tools like Martes and PubCompare.ai to optimize their research protocols, locate the best scientific information from literature, preprints, and patents, and streamline their research process.
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Most cited protocols related to «Martes»

MSTREE, a graphical tool that links allele designations within an MLST database to a minimal spanning tree, was implemented as part of BIONUMERICS V3.5 (Applied Maths BVBA, Sint-Martens-Latem, Belgium). The minimal spanning tree is calculated by Prim's algorithm, modified to choose between otherwise equivalent, alternative subtrees at each step by implementing priority rules that incorporate aspects of the BURST algorithm (Feil and Spratt, 2001 (link)). The highest priority is given to STs with the largest numbers of single locus variants. Any ties were resolved by choosing the ST (or a random ST) with the largest number of isolates. The first node in the network is the ST with the highest priority according to these rules and subsequent links are chosen by a recursive strategy. ST complexes were defined as containing at least three STs, with links of one or two shared alleles. Identical results were obtained by an independent implementation of these rules written in Python (data not shown). The graphical representation displays the quantitative relationships between STs and ST complexes, measured as the number of shared alleles, by lines of different thickness and type (Figs 4B and 6).
Publication 2006
Alleles Figs Martes Python Trees

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Publication 2014
Agar Alleles Ampicillin Antibiotics, Antitubercular Bacteroides thetaiotaomicron Blood Brain Cloning Vectors Equus caballus Erythromycin Escherichia coli Gene Deletion Genome Gentamicin Heart Martes Microbiological Techniques Oligonucleotide Primers Oligonucleotides Reading Frames Serum Strains Tetracycline

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Publication 2014
Corrinoids Culture Media Martes Methionine Oligonucleotides Strains Technique, Dilution
The SSU region was amplified with the primers NS1 and NS4 (White et al. 1990 ), the LSU region with LSU1Fd (Crous et al. 2009b (link)) and LR5 (Vilgalys & Hester 1990 (link)), the ITS region with V9G (De Hoog & Gerrits van den Ende 1998 (link)) and ITS4 (White et al. 1990 ), the GAPDH region with gpd1 and gpd2 (Berbee et al. 1999 ), the RPB2 region with RPB2-5F2 (Sung et al. 2007 (link)) and fRPB2-7cR (Liu et al. 1999 (link)) and the TEF1 gene with the primers EF1-728F and EF1-986R (Carbone & Kohn 1999 ) or EF2 (O’Donnell et al. 1998 (link)). The PCRs were performed in a MyCycler™ Thermal Cycler (Bio-Rad Laboratories B.V., Veenendaal, The Netherlands) in a total volume of 12.5 μL. The SSU and LSU PCR mixtures consisted of 1 μL genomic DNA, 1′ GoTaq® Flexi buffer (Promega, Madison, WI, USA), 2 μM MgCl2, 40 μM of each dNTP, 0.2 μM of each primer and 0.25 Unit GoTaq® Flexi DNA polymerase (Promega). The ITS and GAPDH PCR mixtures differed from the original mix by containing 1 μM MgCl2, the RPB2 and TEF1 PCR mixtures differed from the original mix by containing 2 μL genomic DNA and the RPB2 mixture differed from the original mix by containing 0.5 U instead of 0.25 U GoTaq® Flexi DNA polymerase. Conditions for PCR amplification consisted of an initial denaturation step of 5 min at 94 °C followed by 35 cycles of 30 s at 94 °C, 30 s at 48 °C and 90 s at 72 °C for SSU, LSU, ITS and 40 cycles of 30 s at 94 °C, 30 s at 52 °C / 59 °C and 45 s at 72 °C for TEF1 using respectively EF2 or EF1-986R as reverse primer and a final elongation step of 7 min at 72 °C. The partial RPB2 gene was obtained by using a touchdown PCR protocol of 5 cycles of 45 s at 94 °C, 45 s at 60 °C and 2 min at 72 °C, followed by 5 cycles with a 58 °C annealing temperature and 30 cycles with a 54 °C annealing temperature. The PCR products were sequenced in both directions using the PCR primers and the BigDye Terminator v. 3.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA, USA), according to the manufacturer’s recommendations, and analysed with an ABI Prism 3730XL Sequencer (Applied Biosystems) according to the manufacturer’s instructions. Consensus sequences were computed from forward and reverse sequences using the BioNumerics v. 4.61 software package (Applied Maths, St-Martens-Latem, Belgium). All generated sequences were deposited in GenBank (Table 1).
Publication 2013
Buffers Consensus Sequence DNA-Directed DNA Polymerase GAPDH protein, human Genes Genome Magnesium Chloride Martes Oligonucleotide Primers prisma
Molecular typing data were analyzed with the BioNumerics software (version 6.5; Applied Maths, Sint-Martens-Latem, Belgium) as instructed by the manufacturer. Similarities of spoligotyping and MIRU-VNTR patterns were calculated by using the categorical coefficient. Classification of the Hamburg strain collection in MTBC genotypes was carried out by using the MIRU-VNTRplus database [14] (link), [19] (link). Analysis of sequence data and SNP detection was performed by using SeqScape v2.6 software (Applied Biosystems). Genome sequences of M. tuberculosis H37Rv (http://tuberculist.epfl.ch/) were used as a reference sequence. Calculation of a maximum parsimony phylogenetic tree based on SNP data of the Hamburg strain collection was performed with BioNumerics. A maximum likelihood phylogenetic tree was constructed based on an alignment of SNPs discovered in 26 genes from the reference collection isolates by applying Treefinder software (available at http://www.treefinder.de/) and using the HKY model of DNA substitution. Bootstrap support was calculated based on 1,000 replicates.
More details about procedures for analysis of typing data are described elsewhere [19] (link)–[21] .
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Publication 2012
Genes Genome Genotype Martes Mycobacterium tuberculosis H37Rv Sequence Analysis Single Nucleotide Polymorphism Strains

Most recents protocols related to «Martes»

For lactic acid bacteria enumeration, serial dilutions were prepared and plated on man rogosa sharpe (MRS) agar (VWR, Milano, Italy) containing 0.01% l-Cysteine-HCl (Merck, Darmstadt, Germany), 0.1% fructose (Sigma-Aldrich, Milano, Italy) and 0.1% cycloheximide (Sigma-Aldrich, Milano, Italy). Analyses were performed in triplicate. Plates were incubated anaerobically at 35°C for 72–120 h, the number of colony forming units (CFU) were recorded and counts were made. Around 100 isolated colonies were re-streaked and purified. For long term storage, purified isolates were stored at −80°C with their respective liquid medium containing 20% glycerol. DNA extraction from pure cultures was performed with the Wizard® Genomic DNA Purification Kit (Promega, Madison, WI, USA). Fingerprinting was then obtained using BOX-PCR, as in Gaggìa et al. (2015) . Cluster analysis and grouping BOX profiles was carried out with Bionumerics 7.1 (Applied Maths, Sint-Martens-Latem, Belgium) using Dice’s Coefficient of similarity and the un-weighted pair group method arithmetic averages clustering algorithm (UPGMA). Based on the genotypic grouping, representative isolates were selected, the 16S rRNA gene amplified with primers 8-fw and 1520-rev and sequenced according to Gaggìa et al. (2015) . Sequences were then deposited to GenBank®1 with the following accession number: MT381710-MT381736 and MG649988-MG650060. The obtained 16S rRNA gene sequences were used to generate a phylogenetic tree together with sequences of A. kunkeei retrieved from the National Center for Biotechnology Information (NCBI) Genomes RefSeq database (Supplementary Table 2) especially from Germany, Sweden (Tamarit et al., 2015 (link)), and Switzerland (Crovadore et al., 2021 (link)). The phylogenetic tree was generated with MEGA11 (Tamura et al., 2021 (link)) inferred by using the Maximum Likelihood method (K2 + G substitution model) with rate variation among sites. Lactobacillus melliventris MT53, Lactobacillus apis MT61, and Gilliamella apicola MT1 and MT6 were used as outgroups.
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Publication 2023
Agar Cycloheximide Cysteine Hydrochloride Fructose Genes Genome Genotype Gilliamella apicola Glycerin Lactobacillales Lactobacillus apis Lactobacillus melliventris Martes Oligonucleotide Primers Promega Ribosomal RNA Genes RNA, Ribosomal, 16S Technique, Dilution
PCR-DGGE analyses were performed to investigate lactobacilli populations; for each sampling location, 17 (out of 20) DNA extracted from individual guts were processed. The PCR and subsequent denaturing gradient gel electrophoresis (DGGE) analysis, using the Dcode Universal Mutation Detection System (Bio-Rad Laboratories, Hercules, CA, USA), were performed as described by Alberoni et al. (2018) (link). Denaturing gradient was established at 35–65%. Fingerprinting analyses were carried out using the Bionumerics v 7.1 (Applied Maths, St. Martens-Latem, Belgium) and the UPGMA algorithm based on the Pearson correlation coefficient with an optimization of 1% was applied. Microbial diversity was analyzed with the following parameters: Shannon–Wiener index (H), Simpson index (S), and band evenness (EH), calculated according to Hill et al. (2003) (link). Moreover, principal components analysis (PCA) was carried out by using Bionumerics. Relevant bands were excised from the gels and processed to achieve purified amplicons to be sequenced (Gaggìa et al., 2015 ). Sequencing was carried out by Eurofins Genomics (Ebersberg, Germany) and obtained sequences were assigned to bacterial species using megablast algorithm.2
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Publication 2023
Bacteria Denaturing Gradient Gel Electrophoresis Gels Intestines Lactobacillus Martes Mutation Population Group
Remaking Recess. Remaking Recess is an evidence-based
psychosocial intervention that was designed to support autistic children to
engage socially with their peers at school (Kretzmann et al., 2012 ; Locke et
al., 2019, 2020 (link);
Shih et al.,
2019
). A key characteristic of Remaking Recess is that it is
designed for sustainability—it is focused on training school personnel who
directly support autistic children and their peers day-to-day so that
intervention can be maintained once a schools’ participation in the research
project has ended.
Participating school personnel were individually paired with a “coach” from
the research team with whom they met for didactic and interactive training
in their natural environment (i.e., at school during lunch). Training
sessions lasted for 30 to 45 minutes and occurred 12 times over 6 weeks.
During training sessions, coaches presented information on a target Remaking
Recess skill (i.e., what the skill looks like, how it applies to autistic
children, and why it is important for a child’s development), modeled the
skill, and facilitated a practice session where school personnel tried the
skill while the coach provided in vivo feedback. School personnel were
encouraged to practice skills with students they supported throughout the
rest of the week as homework. Enrolled personnel at allschools received training in Remaking Recess.
Remaking Recess coaching sessions focused on the following skills: (a)
Attending to child engagement on the playground (i.e.,
scanning and circulating the environment for children who may need
additional support and identifying children’s social engagement states; (b)
Transitioning child to an activity (i.e., following
children’s lead, strengths, and interests); (c) Facilitating an
activity
(i.e., providing developmentally- and age-appropriate
activities/games to scaffold children’s engagement with peers and
individualizing the intervention to specific children to help school
personnel generalize the intervention to other students in their care); (d)
Fostering communication (i.e., supporting children’s
social communicative behaviors, including initiations and responses, and
conversations with peers and creating opportunities to facilitate reciprocal
social interactions; (e) Participating in an activity(i.e., sustain children’s engagement within their preferred activities/games
and fading out of an activity/gameing to facilitate student independence);
(f) Providing direct instruction of social skills (i.e.,
coaching children through difficult situations with peers, should they
arise); and (g) Employing peer models (i.e., working with
peers to engage autistic children; Kretzmann et al., 2015 (link); Locke et al.,
2015
).
Remaking Recess with Implementation Support. Schools in this
condition (n = 6) were provided with additional
implementation support from MA- or PhD-level coaches. School principals
identified school administrators, counselors, psychologists, teachers, and
support staff to act as Remaking Recess “champions.” Champions did not
deliver Remaking Recess, but instead received individualized support from
study coaches to address the specific implementation needs of their school.
In the first portion of the support process, coaches facilitated the
identification of implementation needs across schools (e.g., embed Remaking
Recess within the school culture, build internal capacity, improve
implementation climate, and provide tangible support and resources). Then,
school champions identified the needs that were most pertinent to their
school, and coaches worked with champions to develop a plan for
implementation based on the identified topic. School champions also were
tasked with making announcements about Remaking Recess to faculty, staff,
and students, posting visuals of Remaking Recess activities for the week,
and facilitating Remaking Recess with other school members/students who were
not enrolled in the study.
Coaches. Two coaches from the research team were randomly
assigned to provide training in Remaking Recess and Remaking Recess with
implementation support for the assigned schools. The coaches were MA- or
PhD-level professionals with degrees in education and/or psychology. All
coaches were trained in (a) Remaking Recess and (b) the school consultation
process, which included working collaboratively with school personnel to
deliver an intervention to improve student outcomes (Erchul & Martens,
2010). Coaches were trained by a Remaking Recess developer and evaluated for
training and consultation fidelity via a checklist that captured the core
intervention components. Coaches were approved to provide training to school
personnel once they met D > 0.80 fidelity criterion.
Publication 2023
Administrators Autistic Disorder Child Child Development Climate Counselors Faculty Martes Student
In the materials for this study, a total of 322 fecal samples from 6 carnivore species (raccoon (Procyon lotor; n = 65), raccoon dog (Nyctereutes procyonides; n = 87), red fox (Vulpes vulpes; n = 50), European badger (Meles meles; n = 45), pine martens (Martes martes; n = 24), and beech martens (Martes foina; n = 51)) were collected during the period of 2017–2019. All fecal samples were obtained during necropsy from animals shot during a predator control operation or road-killed animals from Ruszów Forestry (51°24′00.1″ N 15°10′12.2″ E), Bory Dolnośląskie, the Lower Silesian District in Poland, where, uniquely, the invasive and native carnivore species co-occur in the same habitat (Figure 1). All samples were kept at −20 °C until further analysis.
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Publication 2023
Animals Autopsy Badgers Beech Carnivora Europeans Feces Martes Nyctereutes Pinus Raccoon Dogs Raccoons Vulpes vulpes
One-way analysis of variance (ANOVA) followed by Fisher least-significant difference (LSD) were applied to analyze data obtained from the real-time PCR using Statistica 12.0 software (StatSoft, Palo Alto, CA, USA).
The Gel Compare II software v 4.6 (Applied Maths, Sint-Martens-Latem, Belgium) was used to analyze the foam DGGE and to convert it into a matching table based on the presence/absence and intensity of bands within each banding pattern, in order to be imported into the freely available PAST 4.03 software for subsequent multivariate statistical analysis [31 ]. Non-metric multidimensional scaling (nMDS) analysis and one-way analysis of similarity (ANOSIM) were performed using the Bray-Curtis distance measure and 9999 permutational tests, in order to visualize the similarity/dissimilarity of bacterial communities hosted in the collected foams in a two-dimensional space and to determine the extent of similarity/dissimilarity according to the different plant species, respectively. The accuracy of the nMDS plot was determined by calculating a 2D stress value. An ANOSIM R value of 1 indicates that the bacterial communities of foam collected from each plant species are more similar to each other than to any sample from another plant species, whereas an R value of 0 indicates that there is as much variation within a group as among the groups being compared. More specifically, 0.5 < R values < 0.75 were interpreted as separated but overlapping [32 (link)].
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Publication 2023
Bacteria Denaturing Gradient Gel Electrophoresis Martes Plants Real-Time Polymerase Chain Reaction

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More about "Martes"

The genus Martes, also known as martens or pine martens, is a group of small to medium-sized carnivorous mammals belonging to the weasel family.
These agile, tree-climbing creatures are found in forested regions of North America, Europe, and Asia, playing a vital role in their ecosystems as predators and scavengers.
Researchers can leverage advanced AI tools like Martes and PubCompare.ai to optimize their research protocols, locate the best scientific information from literature, preprints, and patents, and streamline their research process.
These innovative solutions can help scientists experience the future of protocol optimization today.
Martes species are known for their distinctive yellow or cream-colored throats and impressive climbing abilities.
They are often studied using techniques like CHEF-DR III system, CHEF Mapper system, XbaI, CHEF Mapper, GelCompar II, CHEF-DR II system, SeaKem Gold agarose, and Gel Doc XR system to better understand their biology, behavior, and ecological importance.
By leveraging the insights gained from advanced AI tools and the latest research methodologies, scientists can unlock new discoveries and advance our understanding of these fascinating carnivores.
Expereince the power of protocol optimization and streamlined research with Martes and PubCompare.ai.