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Authors: Azar Kordbacheh, Robert L. Wallace, Elizabeth J. Walsh
Summary: Sample collection and cultureAquatic plant samples were collected from habitats across the USA and a sediment sample from Australia (Tables S1.1, S1.2). Limnias melicerta and L. ceratophylli were identified and isolated from rehydrated sediments or by removing a piece of vegetation to which they were attached. Species identification was based on tube structure, shape of corona, antennae length, and the number of dorsal nodules [1]. Clonal lineages initiated from single females were cultured in modified MBL media [2] and fed a mixture of the algae Chlorella vulgaris Berijerinck, 1890 (The UTEX Culture Collection of Algae at the University of Texas at Austin [UTEX] strain 30) and Chlamydomonasreinhardtii Dangeard, 1888 (UTEX strain 90). Rotifers in this genus produce tubes of hardened secretions [3]; we added powdered carmine (Alfa Aesar, UK) to lab cultures to provide a supplementary matrix to aid tube construction and to increase their visibility in culture. Voucher specimens were deposited in the UTEP Biodiversity Collections at The University of Texas at El Paso (L. melicerta: UTEP:Zoo:43, 105-134; L. ceratophylli: UTEP:Zoo:32-42, UTEP:Zoo:52-61).Deposited specimens included approximately 10 individuals from each population preserved in 95% ethanol and 10 clonal individuals preserved in 4% buffered formalin for molecular analyses and identification, respectively. DNA Extraction and gene amplificationDNA was extracted from one individual of each clonal lineage by adding 13 µl Chelex®-100 (Bio-Rad Laboratories, CA, USA) and incubating at 100°C for 10 min. DNA templates were stored at -80°C until used for amplification. Number of clonal lineages examined from each population is given in Tables S1.1 and S1.2.An approximate 630 bp portion of the cytochrome c oxidase subunit I (COI) gene was amplified using the primers LCO1490: 5' -GGTCAACAAATCATAAAGATATTGG-3' and HCO2198: 5'-TAAACTTCAGGGTGACCAAAAAATCA-3' [4]. The entire nuclear internal transcribed spacer region (ITS) was amplified using the primers ITS4: 5'-TCCTCCGCTTATTGATATGC-3' and ITS5: 5'-GGAAGTAAAAGTCGTAACAAGG-3' [5], and 865 bp of the 18S rRNA gene was amplified using primers 3F: 5’-GTTCGATTCCGGAGAGGG-3’ as modified by Giribet et al. [6] and primer 18Sbi: 5’-CTAGAGTCTCGTTCGTTATCGG-3’ as modified by Whiting et al. [7].PCR reactions contained 10 µl of genomic DNA, 1 µl of each primer (500 ng/ µl), 22 µl HPLC grade sterile water, 1 µl GoTaq® G2 DNA Polymerase (Promega), 10 µl 5X PCR buffer B (10 mM MgCl2, pH 8.5) or 5X PCR buffer A (7.5 mM MgCl2, pH 8.5), followed by adding 5 µl dNTP mix (2.5 mM each of dATP, dCTP, dGTP, dTTP) at 80ºC. PCR cycles were run on a thermocycler (TECHNE TC-412) and consisted of an initial denaturation at 94ºC for 1 min, followed by denaturation at 94ºC for 1 min, annealing at 48ºC for 2 min and extension at 72ºC for 3 min for 35 cycles, and a final extension step at 72ºC for 7 min. To verify the size of amplification products we used electrophoresis, and we purified them using GENECLEAN® kits (MP Biomedicals, LLC) before sequencing. Sequencing was done at UTEP’s BBRC Genomic Analysis Core Facility on an Applied Biosystems 3130xl Genetic Analyzer using BigDye Terminator v3.1 Cycle Sequencing Kits (Applied Biosystems). GenBank accession numbers for all sequences obtained are given in Tables S1.1 (L. melicerta) and S1.2 (L. ceratophylli). The COI gene sequences of L. melicerta (accession number, KT870155.1) and L. ceratophylli(KT870157.1) from GenBank are not included in our analyses for two reasons. 1) The COI sequence of L. melicerta KT870155.1 is 330 bp, which was much shorter than COI sequences obtained in this study (623 bp). 2) The COI sequence of L. ceratophylli KT870157.1 grouped with cryptic species M of L. melicerta in phylogenetic analyses. Additional 18S rRNA sequences (L. melicerta: KM873599.1, L. ceratophylli: KM873598.1) and a COI sequence from L. melicerta (KT870154.1) were included from GenBank. Sinantherina socialis(Linneaus, 1758) and Ptygura pilula (Cubitt, 1872) were included as outgroups in phylogenetic analyses for the COI gene. Floscularia conifera (Hudson, 1886) andPtygura brachiata (Hudson, 1886) were used as outgroup taxa in phylogenetic analyses based on ITS region. For analysis of 18S rRNA sequences, we used Collotheca campanulata as the outgroup (Table S1.1).Genetic DiversityFinchTV v 1.4.0 [8] was used to check sequences manually, especially for potential double peaks in the ITS region sequences. The ITS region alignment was uploaded to the SeqPhase online tool (http://seqphase.mpg.de/seqphase/) to phase the sequences as described by Flot [9]. Contigs for all sequences were made using CAP 3 [10] and were aligned using MAFFT v 7 [11]. Mesquite v 3.2 [12] was used to manually check the alignments and to translate COI gene sequences to proteins. To measure substitution saturation, we used DAMBE v 6 [13]. Number of polymorphic sites, number of parsimony informative sites, number of haplotypes, haplotype diversity (h), and nucleotide diversity (π) were calculated using DnaSp v 5.10.01 [14], and uncorrected pairwise sequences distances ("p") were calculated in Mega v 7.0 [15]. A haplotype network was constructed using the median joining method in Network v 5.0.3 [16]. Species delimitation Models for sequence evolution were TPM2uF+I+G for the COI gene, TPM1uF+I for the ITS region, and JC for the 18S rRNA gene as determined using Jmodeltest2 [17,18] available at the Cipres Science Gateway 3.3 [19]. To construct the phylogenetic trees, Bayesian analysis was run for 107 generations with two parallel runs and a 25% burn in period using MrBayes v 3.2.6 on XSEDE high-throughput computing resources available at Cipres Science Gateway [19]. Phylogenetic analyses were implemented in BEAST and *BEAST [20] using GTR+I+G model of sequence evolution for the COI gene and GTR+I model for the ITS region. TPM2uF and TPM1uF models are not available in BEAST. However, both of these models are classified under the GTR model. Thus GTR was used in both instances.To determine the number of evolutionary entities (putative cryptic species), we used Generalized Mixed Yule Coalescent (GMYC, [21]), Poisson Tree Process (PTP, [22]), Automatic Barcoding Gap Discovery (ABGD, [23]), *BEAST v 1.8.3 [20], and Bayesian Species Delimitation (BSD) implemented in Bayesian Phylogenetics and Phylogeography software (BPP v 3.1, [24–26]). We used BEAST v 1.8.3 [20] to construct ultrametric trees and *BEAST v 1.8.3 [20] for species delimitation. Both analyses were run for the COI gene and ITS region sequences separately for 107 generations, with sampling every 1,000 generations. Tracer v 1.6.0 [27] was used to check the effective sample size (ESS>200) and to verify convergence. Consensus trees were obtained using TreeAnnotator v 1.8.3 with a 25% burn in. Ultrametric trees were used for species delimitation in single threshold and multiple threshold GMYC [28] (http://species.h-its.org/gmyc/, accessed June 12, 2018), Bayesian GMYC (bGMYC) [29] and PTP methods. bGMYC was run using the R package bGMYC v 1.0.2 for 100,000 iterations with sampling every 1,000 iterations. We ran PTP by uploading the ultrametric trees to the online tool available at http://species.h-its.org/ptp/(accessed June 12, 2018) andused default settings. ABGD delimitation was done by uploading the sequence alignment to the online tool available at wwwabi.snv.jussieu.fr/public/abgd/ under the default settings (accessed June 12, 2018).*BEAST v 1.8.3 [20] was run under assumptions regarding the number of species for both the COI gene and ITS region sequences. Lineages having posterior probabilities > 0.90 were retained in *BEAST analyses. To run BSD, the phylogenetic tree based on Bayesian inference was used as the guide tree, and we used the joint species delimitation and tree estimation method (unguided species delimitation) that does not rely on the topology of the guide tree.Isolation by Distance Geographic distance matrices were constructed using Geographic Distance Matrix Generator v 1.2.3 [30]. To test the correlation between genetic variation and geographic distances (log transformed; km) among populations, Mantel tests with 10,000 permutations were run using the R package ecodist v 1.2.9 [31]. Trophi morphologyTrophi were prepared for scanning electron microscopy (SEM) by dissolving rotifer tissue in ~5% sodium hypochlorite, rinsing with deionized water 10-15 times, and air-drying on circular cover slips at room temperature [32]. Trophi were coated with gold/palladium using a Gatan 682 PECS sputter coater. SEM images were obtained at 20 kV using a Hitachi S-4800 system. Trophi were prepared for individuals from one clonal lineage from each examined population. We used a geometric morphometric approach to study variation in the shape and size of 92 trophi for L. melicerta and 60 trophi for L. ceratophylli among putative cryptic species. This method uses Cartesian coordinates for a set of anatomical landmarks [33]. SEM images were obtained from caudal and frontal views of the trophi. Using TPS series software [34], nine landmarks on the caudal view and 10 on the frontal view of the trophi were digitized (Fig 1). Configuration of landmarks were analyzed using Generalized Procrustes Analysis [33]. Trophi size was calculated as Centroid Size (CS): i.e., the square root of the sum of squared distances between landmarks and their centroid [35]. Variation in the shape of trophi based on landmarks was examined using Discriminant Analysis in SPSS v 24 [36]. Because trophi centroid size was not normally distributed, variation in size among putative cryptic species was tested using a non-parametric Kruskal-Wallis test, and between the two morphospecies using a non-parametric Man-Whitney U test implemented in SPSS v 24 [36]. References1. Wallace RL, Kordbacheh A, Walsh EJ. Key to the currently recognized species of Limnias Schrank, 1803 (Rotifera, Monogononta, Gnesiotrocha, Flosculariidae). Zootaxa. 2018;4442: 307–318. doi.org/10.11646/zootaxa.4442.2.7.2. Stemberger RS. A general approach to the culture of planktonic rotifers. Can J Fish Aquat Sci. 1981;38: 721–724. doi:10.1139/f81-095.3. Wallace RL, Nogrady T, Snell TW, Ricci C. Rotifera 1: Biology, ecology and systematics. 2nd ed. Nogrady T, editor. Kenobi Productions, 2006, 293 pp. 4. Folmer O, Black M, Hoeh W, Lutz R, Vrijenhoek R. DNA primers for amplification of mitochondrial cytochrome coxidase subunit I from diverse metazoan invertebrates. Mol Mar Biol Biotechnol. 1994;3: 294–299. doi:10.1371/journal.pone.0013102.5. White T, Bruns T, Lee S, Taylor J. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: Innis M, Gelfand D, Shinsky J, White T, editors. PCR Protocols: A guide to methods and applications. Academic Press, 1990, pp. 315–322. citeulike-article-id:671166.6. Giribet G, Carranza S, Baguna J, Riutort M, Ribera C. First molecular evidence for the existence of a Tardigrada + Arthropoda clade. Mol Biol Evol. 1996;13: 76–84. 7. Whiting MF, Carpenter JC, Wheeler QD, Wheeler WC. The Strepsiptera problem: phylogeny of the holometabolous insect orders inferred from 18S and 28S ribosomal DNA sequences and morphology. Syst Biol. 1997;46: 1–68. 8. Geospiza.com. FinchTV. Seattle, WA; 2014: http://www.geospiza.com/Products/finchtv.shtml.9. Flot JF. seqphase: a web tool for interconverting phase input/output files and fasta sequence alignments. Mol Ecol Resour. 2010;10: 162–166. doi:10.1111/j.1755-0998.2009.02732.x.10. Huang X, Madan A. CAP3: A DNA sequence assembly program. Genome Res. 1999;9: 868–877. 11. Katoh K, Standley DM. MAFFT. Multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30: 772–780. doi:10.1093/molbev/mst010.12. Maddison WP, Maddidon DR. Mesquite: a modular system for evolutionary analysis. 2017: Version 3.2. http://mesquiteproject.org. 13. Xia X. DAMBE6: New tools for microbial genomics, phylogenetics and molecular evolution. J Hered. 2017;108: 431–437. 14. Librado P, Rozas J. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics. 2009;25: 1451–1452. doi:10.1093/bioinformatics/btp187.15. Kumar S, Stecher G, Tamura K. MEGA7: Molecular Evolutionary Genetics Analysis version 7.0 for bigger datasets. Mol Biol Evol. 2015;33: 1870-4. doi:10.1093/molbev/mst197.16. Bandelt HJ, Forster P, Rohl A. Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol. 1999;16: 37–48. 17. Darriba D, Taboada GL, Doallo R, Posada D. jModelTest 2: more models, new heuristics and parallel computing. Nat Methods. 2012;9: 772. http://dx.doi.org/10.1038/nmeth.2109.18. Guindon S, Gascuel O. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 2003;52: 696–704. doi:10.1080/10635150390235520.19. Miller MA, Pfeiffer W, Schwartz T. Creating the CIPRES science gateway for inference of large phylogenetic trees. 2010. Gateway Computing Environments Workshop, 2010, pp. 1–8. doi:10.1109/GCE.2010.5676129.20. Drummond AJ, Suchard MA, Xie D, Rambaut A. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol. 2012;29: 1969–1973. doi:10.1093/molbev/mss075.21. Pons J, Barraclough TG, Gomez-Zurita J, Cardoso A, Duran DP, Hazell S, et al. Sequence-based species delimitation for the DNA taxonomy of undescribed insects. Syst Biol. 2006;55: 595–609. doi:10.1080/10635150600852011.22. Zhang J, Kapli P, Pavlidis P, Stamatakis A. A general species delimitation method with applications to phylogenetic placements. Bioinformatics. 2013;29: 2869–76. doi:10.1093/bioinformatics/btt499.23. Puillandre N, Lambert A, Brouillet S, Achaz G. ABGD, Automatic Barcode Gap Discovery for primary species delimitation. Mol Ecol. 2012;21: 1864–1877. doi:10.1111/j.1365-294X.2011.05239.x.24. Rannala B, Yang Z. Bayes estimation of species divergence times and ancestral population sizes using DNA sequences from multiple loci. Genetics. 2003;164: 1645–56. doi:10.1073/pnas.0913022107.25. Yang Z, Rannala B. Bayesian species delimitation using multilocus sequence data. Proc Natl Acad Sci. 2010;107: 9264–9269. doi:10.1073/pnas.0913022107.26. Yang Z, Rannala B. Unguided species delimitation using DNA sequence data from multiple loci. Mol Biol Evol. 2014;31: 3125–3135. doi:10.1093/molbev/msu279.27. Rambaut A, Suchard MA, Xie D, Drummond AJ. Tracer v1.6. http://beast.bio.ed.ac.uk/Tracer. citeulike-article-id:13604975.28. Fujisawa T, Barraclough TG. Delimiting species using single-locus data and the generalized mixed yule coalescent approach: a revised method and evaluation on simulated data sets. Syst Biol. 2013; 62: 707–724. doi:10.1093/sysbio/syt033.29. Reid NM, Carstens BC. Phylogenetic estimation error can decrease the accuracy of species delimitation: a Bayesian implementation of the general mixed yule coalescent model. BMC Evol Biol. 2012;12: 196. doi:10.1186/1471-2148-12-196.30. Ersts PJ. Geographic distance matrix generator version 1.2.3. Nat Hist. 2006; http://biodiversityinformatics.amnh.org/open_source/gdmg/documentation.php.31. Goslee SC, Urban DL. The ecodist package for dissimilarity-based analysis of ecological data. J Stat Software. 2007;22: 1–19. https://www.jstatsoft.org/v022/i07.32. Segers H. Rotifera of some lakes in the floodplain of the River Niger (Imo State, Nigeria). New species and other taxonomic considerations. Hydrobiologia. 1993;250: 39–61. doi:10.1007/BF00007494.33. Adams DC, Rohlf FJ, Slice DE. Geometric morphometrics: Ten years of progress following the revolution. Ital J Zool. 2004;71: 5–16. doi:10.1080/11250000409356545.34. Rohlf FJ. The tps series of software. Hystrix. 2015;26: 1–4. doi:10.4404/hystrix-26.1-11264.35. Cavalcanti MJ, Monteiro LR, Lopes PRD. Landmark-based morphometric analysis in selected species of serranid fishes (Perciformes: Teleostei). Zool Stud. 1999;38: 287–294. 36. IBM Corp. IBM SPSS statistics for windows, version 24.0. IBM Corp. 2016.

Proper citation: Azar Kordbacheh, Robert L. Wallace, Elizabeth J. Walsh 2018. Protocol used in Evidence supporting cryptic species complexes within two sessile microinvertebrates, Limnias melicerta and L. ceratophylli (Rotifera, Gnesiotrocha). protocols.io https://dx.doi.org/10.17504/protocols.io.tppemmn Copy   

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Authors: Faezah Mohd Salleh, Jazmin Ramos-Madrigal, Fernando Penaloza, Shanlin Liu, Mikkel-Holger S Sinding, Riddhi P Patel, Renata Martins, Dorina Lenz, Jorns Fickel, Christian Roos, Mohd Shahir Shamsir, Mohammad Shahfiz Azman, Burton K Lim, Stephen J Rossiter, Andreas Wilting, M Thomas P Gilbert
Group: GigaScience Press
Summary: This protocol allows for adequate DNA extraction from archival samples.

Proper citation: Faezah Mohd Salleh, Jazmin Ramos-Madrigal, Fernando Penaloza, Shanlin Liu, Mikkel-Holger S Sinding, Riddhi P Patel, Renata Martins, Dorina Lenz, Jorns Fickel, Christian Roos, Mohd Shahir Shamsir, Mohammad Shahfiz Azman, Burton K Lim, Stephen J Rossiter, Andreas Wilting, M Thomas P Gilbert 2017. Extraction Method D (PRP and RM). protocols.io https://dx.doi.org/10.17504/protocols.io.indcda6 Copy   

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Authors: Eva Feldman
Group: Diabetic Complications Consortium
Summary: The Tail Flick assay is a pain receptive assay in which a mouse is placed within a restraining tube with its tail protruding. The tail is placed on a level surface, a radiant heat is applied to the tail and the latency of the mouse to remove its tail from the heat is recorded. This latency is used as a measure to indicate neurological pathology.Diabetic Complication:

Proper citation: Eva Feldman 2019. Tail Flick. protocols.io https://dx.doi.org/10.17504/protocols.io.7thhnj6 Copy   

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Authors: Ahmed O.Abass, Gamal Mehaisen

Proper citation: Ahmed O.Abass, Gamal Mehaisen 2019. Lymphocyte proliferation in poultry species. protocols.io https://dx.doi.org/10.17504/protocols.io.xjpfkmn Copy   

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Authors: matt , Eugene Joseph, Arun Manoharan Arunprimediscoveriescom
Group: Coronavirus Method Development Community, XPRIZE Rapid Covid Testing, Prime Discoveries

Proper citation: matt , Eugene Joseph, Arun Manoharan Arunprimediscoveriescom 2020. COVID19 RTLAMP Assay. protocols.io https://dx.doi.org/10.17504/protocols.io.bkx6kxre Copy   

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Authors: Miriam Schalamun, Benjamin Schwessinger
Group: High molecular weight DNA extraction from all kingdoms, Plantae
Summary: Extraction of high quality DNA for long read sequencing e.g. the Oxford Nanopore Optimized for DNA extraction from eucalyptus grandis and eucalyptus pauciflora. This protocol contains an optional Chloroform clean up step which is necessary for eucalyptus but might not be for other tissue. For long DNA fragments don't vortex the DNA sample. 

Proper citation: Miriam Schalamun, Benjamin Schwessinger 2017. High molecular weight gDNA extraction after Mayjonade et al. optimised for eucalyptus for nanopore sequencing. protocols.io https://dx.doi.org/10.17504/protocols.io.khkct4w Copy   

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Authors: Renata Alitto, Michela Borges, Letícia Dias de Oliveira, Karin Regina Seger, Luciana Bolsoni Lourenço
Summary: This test adds Bayesian support (BS) values to the nodes of the input tree and delimit species based on the Phylogenetic Species Concept. Higher BS values indicate all descendants from the node are more likely to be from one species

Proper citation: Renata Alitto, Michela Borges, Letícia Dias de Oliveira, Karin Regina Seger, Luciana Bolsoni Lourenço 2019. Species delimitation of Ophiothrix using bPTP. protocols.io https://dx.doi.org/10.17504/protocols.io.t2jeqcn Copy   

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Authors: Kelsey Miller
Group: BioLegend

Proper citation: Kelsey Miller 2016. Intracellular Staining With True-Phos™ Perm Buffer in Whole Blood. protocols.io https://dx.doi.org/10.17504/protocols.io.e2dbga6 Copy   

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Authors: Jiarong Guo, Dean Vik, Akbar Adjie Pratama, Simon Roux, Matthew Sullivan
Group: Sullivan Lab, iVirus
Summary: This protocol shows how to use VirSorter2, checkV, DRAMv and some manual curation criteria for viral sequence identification.

Proper citation: Jiarong Guo, Dean Vik, Akbar Adjie Pratama, Simon Roux, Matthew Sullivan 2021. Viral sequence identification SOP with VirSorter2. protocols.io https://dx.doi.org/10.17504/protocols.io.btv8nn9w Copy   

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Authors: Mitchell Finger, Michael Lyon, Judy Northill, Ian Mackay
Group: Public Health Virology, Forensic and Scientific Services
Summary: This real-time TaqMan-MGB RT-PCR protocol aimed to amplify measles virus (MeV) strains and not other viruses.Michael Lyon and Mitchell Finger designed the assay in 2009 using Primer Express software.The method was later published by Greg Smith in 2010 (see below).The assay targets the fusion (F) gene region and is designed as a qualitative test for investigating MeV infection of humans.This was a past assay that we no longer in use. For our favoured Measles virus TaqMan test, please refer to the MeV N TaqMan protocol.

Proper citation: Mitchell Finger, Michael Lyon, Judy Northill, Ian Mackay 2019. Measles virus TaqMan RT-PCR (F gene; no longer in regular use; see Guidelines). protocols.io https://dx.doi.org/10.17504/protocols.io.8b9hsr6 Copy   

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Authors: Adriana C. Vargas, Angela A. Gravena, Rosana R. Rosseto, Luciano Andrade, João R.N Vissoci, Marcia E.L. Consolaro, Maria Dalva B.C. Carvalho, Sandra M. Pelloso
Summary: The aim of this study was to analyze the trend in mortality from uterine neoplasms and their risk factors, specified by the International Classification of Diseases - 10th Edition (ICD-10): C53, C54 and C55. This is an ecological study of a cross-sectional cohort and time series of deaths from uterine cancer that were recorded on the death certificates of 147 women residing in Maringá-PR from 2004 to 2014. Deaths attributed to malignant neoplasms of the cervix, unspecified (C53.9) were the most common among these women. There was an increasing trend in mortality rates from cancer of the uterus. The behavior of age groups showed an increase in women over 65 years of age. Overall, 71.5% of the women had less than 8 years of education, and 60.5% had no partner. It was also found that the health unit in Vardelina had the highest number of deaths, corresponding to 0.73% of the population. The percentage of the total deaths in the city was 0.15%. These data indicate that women in lower social strata have less access to health services and less information regarding primary prevention and the effective treatment of uterine cancer.

Proper citation: Adriana C. Vargas, Angela A. Gravena, Rosana R. Rosseto, Luciano Andrade, João R.N Vissoci, Marcia E.L. Consolaro, Maria Dalva B.C. Carvalho, Sandra M. Pelloso 2017. TENDENCY OF UTERINE NEOPLASM MORTALITY IN WOMEN IN SOUTHERN BRAZIL. protocols.io https://dx.doi.org/10.17504/protocols.io.jz2cp8e Copy   

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Authors: Steven Wilhelm
Group: The Aquatic Microbial Ecology Research Group - AMERG (The Buchan, Zinser and Wilhelm labs), Samantha R Coy's Protocols
Summary: Please contact Dr. Steven Wilhelm ([email protected]) for additional information regarding this protocol.

Proper citation: Steven Wilhelm 2017. Guava Flow Cytometer - Troubleshooting "Tray Hold Off State". protocols.io https://dx.doi.org/10.17504/protocols.io.iv9ce96 Copy   

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Authors: Gabriel Magalhães Nunes Guimarães
Summary: Protocolos da equipe de anestesiologia do Instituto Castro e Santos (Distrito Federal)

Proper citation: Gabriel Magalhães Nunes Guimarães 2018. Protocolos da anestesiologia do ICS. protocols.io https://dx.doi.org/10.17504/protocols.io.vgie3ue Copy   

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Authors: Soham Adla, Neeraj Rai, K Sri Harsha, Shivam Tripathi, Markus Disse, Saket Pande

Proper citation: Soham Adla, Neeraj Rai, K Sri Harsha, Shivam Tripathi, Markus Disse, Saket Pande 2019. Laboratory calibration of soil moisture sensors in porous media (repacked soils). protocols.io https://dx.doi.org/10.17504/protocols.io.swnefde Copy   

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Authors: Stemcell Technologies
Group: STEMCELL Technologies
Summary: Multipotent neural progenitor cells (NPCs) generate the major cell types of the central nervous system (CNS): neurons, astrocytes and oligodendrocytes. Human pluripotent stem cells (hPSCs), including embryonic stem (ES) cells and induced pluripotent stem (iPS) cells, can be directed to differentiate into NPCs using a variety of methods. This process, known as ‘neural induction’, must be efficient and reliable, in order to generate high-quality NPCs for downstream applications. Although neural induction of hPSCs using embryoid body (EB) formation allows for visual assessment of induction success via the formation of neural rosettes, the whole process can take anywhere between 16 and 19 days to get single-cell neural progenitor cells (NPCs). As a result, monolayer culture-based neural induction methods have recently gained popularity, since they enable single-cell NPCs to be obtained in as few as six days. Here we describe a procedure for neural induction using STEMdiff™ Neural Induction Medium in a monolayer culture-based system to efficiently generate PAX6-positive NPCs.

Proper citation: Stemcell Technologies 2019. A Monolayer Culture Method for Neural Induction of Human Pluripotent Stem Cells. protocols.io https://dx.doi.org/10.17504/protocols.io.4uagwse Copy   

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Authors: Joshua Welsh, Sean Cook, Jennifer Jones
Group: Translational Nanobiology Section
Summary: This is collection contains the protocols required for each step in the mpapass software pipeline for performing stitched multiplex analysis. This is one of a number of protocols in the pipeline for using the mpapass software package and is applicable to the latest release of the software.

Proper citation: Joshua Welsh, Sean Cook, Jennifer Jones 2020. MPAPASS Software Collection. protocols.io https://dx.doi.org/10.17504/protocols.io.bm3gk8jw Copy   

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Authors: Kathryn Kauffman, Martin Polz
Summary: This protocol simplifies current approaches for agar overlay plaque assays by eliminating the use of tubes for premixing of agar, hosts, and viruses, in favor of pipetting each of these directly onto the bottom agar. The benefits of this approach include simplified experimental set-up, and reductions in preparation and clean-up times and material requirements. In addition, by eliminating tube-based steps, the duration of exposure of cells and viruses to heat is reduced and the need for potentially damaging vortexing or agitation of virus-host mixtures is also eliminated. We note that Hershey et al. [1] mentioned the possibility of such an approach in their 1943 description of the tube-based overlay procedure, stating: “A further slight improvement may be made by mixing the sample directly on the phage with only 3 ml 0.7 per cent agar, but the mixing is difficult.” By using a lower percentage agar, which is advantageous for other reasons (see Additional Information section in the associated publication), we find that this approach works very well with as low as 2 ml of top agar.Using this streamlined, tube-free, plating method, >45 samples can readily be plated per hour from a common or pre-prepared virus stock, without the need for individual tubes of molten agar or multiple transfers of bacteria and virus. When deployed for isolation of novel viruses, or quantification of environmental viruses, this translates to a potential for screening hundreds of potential host strains per day using a single bottle of molten agar rather than hundreds of tubes. When used for routine bench assays, a single bottle of top agar can be used over multiple days by simply re-microwaving.[1] A. Hershey, G. Kalmanson, J. Bronfenbrenner "Quantitative methods in the study of the phage-antiphage reaction" J. Immunol., 46 (1943), pp. 267-279

Proper citation: Kathryn Kauffman, Martin Polz 2018. Tube-free Agar Overlays: rapid plaque assays with fewer steps and materials. protocols.io https://dx.doi.org/10.17504/protocols.io.j8ncrve Copy   

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Authors: Molly Moynihan

Proper citation: Molly Moynihan 2021. 15N2 label preparation (dissolved method). protocols.io https:// Copy   

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Authors: Addgene The Nonprofit Plasmid Repository
Summary: This protocol describes ddPCR titration of AAV vectors. To see the full abstract and additional resources, visit https://www.addgene.org/protocols/aav-ddpcr-titration/.Sample Data: When analyzing data there should be a clear distinction between negative droplets (black) and positive droplets (blue).The no template control (NTC) should be close to zero (B08). At Addgene, runs with an NTC >5 are invalid.To reduce NTC values, we recommend wiping down all pipettes and equipment with 10% bleach prior to use and keeping all reagents and samples on ice or pre-chilled 96-well freezer blocks during use.In this protocol, a dilution series is prepared for each AAV sample and the 3 final dilutions are assayed. The samples that are assayed are diluted 2-fold serially therefore, the concentration obtained by ddPCR should decrease by a factor of 2 across the dilutions. In the example below, 2-fold serial dilutions of a sample were loaded in wells A04, A05 and A06. As shown in the image and table below, the concentration of positive droplets decreases by a factor of ~2.To increase the accuracy of the titer, calculate an average of several dilutions. For additional tips on AAV titering using ddPCR, read our blog post.

Proper citation: Addgene The Nonprofit Plasmid Repository 2020. ddPCR titration of AAV vectors. protocols.io https://dx.doi.org/10.17504/protocols.io.bqifmubn Copy   

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Authors: Chris Ockenhouse, Chris Gast, Renee Holt, Jorge Flores
Group: Coronavirus Method Development Community
Summary: This is Part 2 of "Phase 3 randomized, double-blinded, placebo-controlled trial to evaluate the safety, immunogenicity, and efficacy of Vaccine Candidate against COVID-19 in adults > 18 years of age"This generic Phase 3 protocol was developed by the PATH team with support of the Bill and Melinda Gates Foundation. The aim of the collection is to share recommended best practices in designing and implementing a Phase 3 study of a COVID-19 vaccine candidate. As Phase 3 trials of different Vaccine Candidates proceed around the world, following the same protocols will ensure consistency and comparability of the Phase 3 trial results.Please note that this is an evolving document, to be versioned and updated, based on community feedback and new data.

Proper citation: Chris Ockenhouse, Chris Gast, Renee Holt, Jorge Flores 2020. Hypotheses, Objectives, Endpoints, and Case Definitions (Part 2 of Phase 3 study of Vaccine Candidate for COVID-19). protocols.io https://dx.doi.org/10.17504/protocols.io.bj5vkq66 Copy   

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