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1.
In this short report, the genome-wide homologous recombination events were re-evaluated for classical swine fever virus (CSFV) strain . We challenged a previous study which suggested only one recombination event in AF407339 based on 25 CSFV genomes. Through our re-analysis on the 25 genomes in the previous study and the 41 genomes used in the present study, we argued that there should be possibly at least two clear recombination events happening in AF407339 through genome-wide scanning. The reasons for identifying only one recombination event in the previous study might be due to the limited number of available CSFV genome sequences at that time and the limited usage of detection methods. In contrast, as identified by most detection methods using all available CSFV genome sequences, two major recombination events were found at the starting and ending zones of the genome AF407339, respectively. The first one has two parents AF407339 (minor) and AF333000 (major) with beginning and ending breakpoints located at 19 and 607 nt of the genome respectively. The second one has two parents AY554397 (minor) and AF531433 (major) with beginning and ending breakpoints at 8397 and 11,078 nt of the genome respectively. Phylogenetic incongruence analysis using neighbor-joining algorithm with 1000 bootstrapping replicates further supported the existence of these two recombination events. In addition, we also identified additional 18 recombination events on the available CSFV strains. Some of them may be trivial and can be ignored. In conclusion, CSFV might have relatively high frequency of homologous recombination events. Genome-wide scanning of identifying recombination events should utilize multiple detection methods so as to reduce the risk of misidentification. GQ902941相似文献
2.
In Vivo Fitness Cost of the M184V Mutation in Multidrug-Resistant Human Immunodeficiency Virus Type 1 in the Absence of Lamivudine 总被引:1,自引:0,他引:1
Roger Paredes Manish Sagar Vincent C. Marconi Rebecca Hoh Jeffrey N. Martin Neil T. Parkin Christos J. Petropoulos Steven G. Deeks Daniel R. Kuritzkes 《Journal of virology》2009,83(4):2038-2043
3.
We analyzed the temporal and spatial diversity of the microbiota in a low-usage and a high-usage hospital tap. We identified a tap-specific colonization pattern, with potential human pathogens being overrepresented in the low-usage tap. We propose that founder effects and local adaptation caused the tap-specific colonization patterns. Our conclusion is that tap-specific colonization represents a potential challenge for water safety.Humans are exposed to and consume large amounts of tap water in their everyday life, with the tap water microbiota representing a potent reservoir for pathogens (8). Despite the potential impact, our knowledge about the ecological diversification processes of the tap water microbiota is limited (4, 11).The aim of the present work was to determine the temporal and spatial distribution patterns of the planktonic tap water microbiota. We compared the summer and winter microbiota from two hospital taps supplied from the same water source. We analyzed 16S rRNA gene clone libraries by using a novel alignment-independent approach for operational taxonomic unit (OTU) designation (6), while established OTU diversity and richness estimators were used for the ecological interpretations.Tap water samples (1 liter) from a high-usage kitchen and a low-usage toilet cold-water tap in Akershus University Hospital, Lørenskog, Norway, were collected in January and July 2006. The total DNA was isolated and the 16S rRNA gene PCR amplified and sequenced. Based on the sequences, we estimated the species richness and diversity, we calculated the distances between the communities, and trees were constructed to reflect the relatedness of the microbiota in the samples analyzed. Details about these analytical approaches are given in the materials and methods section in the supplemental material.Our initial analysis of species composition was done using the RDPII hierarchical classifier. We found that the majority of pathogen-related bacteria in our data set belonged to the class Gammaproteobacteria. The genera encompassed Legionella, Pseudomonas, and Vibrio (Table (Table1).1). We found a significant overrepresentation of pathogen-related bacteria in the toilet tap (P = 0.04), while there were no significant differences between summer and winter samples. Legionella showed the highest relative abundance for the pathogen-related bacteria. With respect to the total diversity, we found that Proteobacteria dominated the tap water microbiota (representing 86% of the taxa) (see Table S1 in the supplemental material). There was, however, a large portion (56%) of the taxa that could not be assigned to the genus level using this classifier.
TABLE 1.
Cloned sequences related to human pathogensaOpen in a separate windowaThe relatedness between the cloned sequences and potential pathogens was determined by BLAST searches of the NCBI database, carried out using default settings.To obtain a better resolution of the uncharacterized microbiota, we analyzed the data using a clustering approach that is not dependent on a predefined bacterial group (see the materials and methods section in the supplemental material for details). These analyses showed that there were three relatively tightly clustered groups in our data set (Fig. (Fig.1A).1A). The largest group (n = 590) was only distantly related to characterized betaproteobacteria within the order Rhodocyclales. We also identified another large betaproteocaterial group (n = 320) related to Polynucleobacter. Finally, a tight group (n = 145) related to the alphaproteobacterium Sphingomonas was identified.Open in a separate windowFIG. 1.Tap water microbiota diversity, determined by use of a principal component analysis coordinate system. (A) Each bacterium is classified by coordinates, with the following color code: brown squares, kitchen summer; red diamonds, toilet summer; green triangles, kitchen winter; and green circles, toilet winter. (B and C) Each square represents a 1 × 1 (B) or 5 × 5 (C) OTU. PC1, first principal component; PC2, second principal component.The tap-specific distributions of the bacterial groups were investigated using density distribution analyses. A dominant population related to Polynucleobacter was identified for the toilet summer samples, while for the winter samples there was a dominance of the Rhodocyclales-related bacteria. The kitchen summer samples revealed a dominance of Sphingomonas. The corresponding winter samples did not reveal distinct high-density bacterial populations (see Table S2 in the supplemental material).Hierarchical clustering for the 1 × 1 OTU density distribution confirmed the relatively low overlap for the microbiota in the samples analyzed (Fig. (Fig.2).2). We found that the microbiota clustered according to tap and not season.Open in a separate windowFIG. 2.Hierarchical clustering for the density distribution of the tap water microbiota. The density of 1 × 1 OTUs was used as a pseudospecies for hierarchical clustering. The tree for the Cord distance matrix is presented, while the distances calculated using the three distance matrices Cord, Brad Curtis, and Sneath Sokal, respectively, are shown for each branch.We have described the species diversity and richness of the microbiota in Table S3 in the supplemental material. For the low taxonomic level, these analyses showed that the diversity and species richness were greater for the winter samples than for the summer samples. Comparing the two taps, the diversity and richness were greater in the kitchen tap than in the toilet tap. In particular, the winter sample from the kitchen showed great richness and diversity. The high taxonomic level, however, did not reveal the same clear differences as did the low level, and the distributions were more even. Rarefaction analyses for the low taxonomic level confirmed the richness and diversity estimates (see Fig. S1 in the supplemental material).Our final analyses sought to fit the species rank distributions to common rank abundance curves. Generally, the rank abundance curves were best fitted to log series or truncated log normal distributions (see Table S4 in the supplemental material). The log series distribution could be fit to all of the samples except the kitchen summer samples at the low taxonomic level, while the truncated log normal distribution could not be fit to the kitchen samples at the high taxonomic level. Interestingly, however, the kitchen winter sample was best fit to a geometric curve at both the high and the low taxonomic level.Diversifying, adaptive biofilm barriers have been documented for tap water bacteria (7), and it is known that planktonic bacteria can interact with biofilms in an adaptive manner (3). On the other hand, tap usage leads to water flowthrough and replacement of the global with the local water population by stochastic founder effects (1).Therefore, we propose that parts of the local diversity observed can be explained by local adaptation (10) and parts by founder effects (9).Most prokaryote diversity measures assume log normal or log series OTU dominance density distributions (5). The kitchen winter sample, however, showed deviations from these patterns by being correlated to geometric distributions (in addition to the log series and truncated log normal distributions for the high taxonomic level). This sample also showed a much greater species richness than the other samples. A possible explanation is that the species richness of the tap water microbiota can be linked to usage and that the kitchen tap is driven toward a founder microbiota by high usage.Since our work indicates an overrepresentation of Legionella in the low-usage tap, it would be of high interest to determine whether the processes for local Legionella colonization can be related to tap usage. Understanding the ecological forces affecting Legionella and other pathogens are of great importance for human health. At the Akerhus University Hospital, this was exemplified by a Pseudomonas aeruginosa outbreak in an intensive care unit, where the outbreak could be traced back to a single tap (2). 相似文献4.
Derek M. Shore Gemma L. Baillie Dow H. Hurst Frank Navas III Herbert H. Seltzman Jahan P. Marcu Mary E. Abood Ruth A. Ross Patricia H. Reggio 《The Journal of biological chemistry》2014,289(9):5828-5845
The cannabinoid 1 (CB1) allosteric modulator, 5-chloro-3-ethyl-1H-indole-2-carboxylic acid [2-(4-piperidin-1-yl-phenyl)-ethyl]-amide) (), has the paradoxical effect of increasing the equilibrium binding of [3H](−)-3-[2-hydroxyl-4-(1,1-dimethylheptyl)phenyl]-4-[3-hydroxylpropyl]cyclohexan-1-ol (CP55,940, an orthosteric agonist) while at the same time decreasing its efficacy (in G protein-mediated signaling). ORG27569 also decreases basal signaling, acting as an inverse agonist for the G protein-mediated signaling pathway. In ligand displacement assays, ORG27569 can displace the CB1 antagonist/inverse agonist, N-(piperidiny-1-yl)-5-(4-chlorophenyl)-1-(2,4-dichlorophenyl)-4-methyl-1H-pyrazole-3-carboxamide(SR141716A). The goal of this work was to identify the binding site of ORG27569 at CB1. To this end, we used computation, synthesis, mutation, and functional studies to identify the ORG27569-binding site in the CB1 TMH3-6-7 region. This site is consistent with the results of K3.28192A, F3.36200A, W5.43279A, W6.48356A, and F3.25189A mutation studies, which revealed the ORG27569-binding site overlaps with our previously determined binding site of SR141716A but extends extracellularly. Additionally, we identified a key electrostatic interaction between the ORG27569 piperidine ring nitrogen and K3.28192 that is important for ORG27569 to act as an inverse agonist. At this allosteric site, ORG27569 promotes an intermediate conformation of the CB1 receptor, explaining ORG27569''s ability to increase equilibrium binding of CP55,940. This site also explains ORG27569''s ability to antagonize the efficacy of CP55,940 in three complementary ways. 1) ORG27569 sterically blocks movements of the second extracellular loop that have been linked to receptor activation. 2) ORG27569 sterically blocks a key electrostatic interaction between the third extracellular loop residue Lys-373 and D2.63176. 3) ORG27569 packs against TMH6, sterically hindering movements of this helix that have been shown to be important for receptor activation. ORG27569相似文献
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6.
Lavanya Rishishwar Lee S. Katz Nitya V. Sharma Lori Rowe Michael Frace Jennifer Dolan Thomas Brian H. Harcourt Leonard W. Mayer I. King Jordan 《Journal of bacteriology》2012,194(20):5649-5656
Containment strategies for outbreaks of invasive Neisseria meningitidis disease are informed by serogroup assays that characterize the polysaccharide capsule. We sought to uncover the genomic basis of conflicting serogroup assay results for an isolate () from a patient with acute meningococcal disease. To this end, we characterized the complete genome sequence of the M16917 isolate and performed a variety of comparative sequence analyses against N. meningitidis reference genome sequences of known serogroups. Multilocus sequence typing and whole-genome sequence comparison revealed that M16917 is a member of the ST-11 sequence group, which is most often associated with serogroup C. However, sequence similarity comparisons and phylogenetic analysis showed that the serogroup diagnostic capsule polymerase gene (synD) of M16917 belongs to serogroup B. These results suggest that a capsule-switching event occurred based on homologous recombination at or around the capsule locus of M16917. Detailed analysis of this locus uncovered the locations of recombination breakpoints in the M16917 genome sequence, which led to the introduction of an ∼2-kb serogroup B sequence cassette into the serogroup C genomic background. Since there is no currently available vaccine for serogroup B strains of N. meningitidis, this kind capsule-switching event could have public health relevance as a vaccine escape mutant. M16917相似文献
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8.
damo Davi Digenes Siena Isabela Ichihara de Barros Camila Baldin Storti Carlos Alberto Oliveira de Biagi Júnior Larissa Anastacio da Costa Carvalho Silvya Stuchi MariaEngler Josane de Freitas Sousa Wilson Araújo Silva Jr 《Journal of cellular and molecular medicine》2022,26(3):671
Our previous work using a melanoma progression model composed of melanocytic cells (melanocytes, primary and metastatic melanoma samples) demonstrated various deregulated genes, including a few known lncRNAs. Further analysis was conducted to discover novel lncRNAs associated with melanoma, and candidates were prioritized for their potential association with invasiveness or other metastasis‐related processes. In this sense, we found the intergenic lncRNA (ENSG00000230454) and decided to explore its effects in melanoma. For that, we silenced the lncRNA U73166 expression using shRNAs in a melanoma cell line. Next, we experimentally investigated its functions and found that migration and invasion had significantly decreased in knockdown cells, indicating an essential association of lncRNA U73166 for cancer processes. Additionally, using naïve and vemurafenib‐resistant cell lines and data from a patient before and after resistance, we found that vemurafenib‐resistant samples had a higher expression of lncRNA U73166. Also, we retrieved data from the literature that indicates lncRNA U73166 may act as a mediator of RNA processing and cell invasion, probably inducing a more aggressive phenotype. Therefore, our results suggest a relevant role of lncRNA U73166 in metastasis development. We also pointed herein the lncRNA U73166 as a new possible biomarker or target to help overcome clinical vemurafenib resistance. U73166相似文献
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11.
The purpose of this table is to provide the community with a citable record of publications of ongoing genome sequencing projects that have led to a publication in the scientific literature. While our goal is to make the list complete, there is no guarantee that we may have omitted one or more publications appearing in this time frame. Readers and authors who wish to have publications added to subsequent versions of this list are invited to provide the bibliographic data for such references to the SIGS editorial office.
Phylum Euryarchaeota
- Halococcus hamelinensis, sequence accession PRJNA80845 [1]
- “Methanocella conradii” HZ254, sequence accession [ CP0032432]
- Thermococcus litoralis NS-C, sequence accession [ AHVB000000003]
Phylum Crenarchaeota
- Candidatus Nitrosopumilus salaria” BD31, sequence accession [ AEXL000000004]
- Candidatus Nitrosoarchaeum limnia, sequence accession [ AHJG000000005]
Phylum Deinococcus-Thermus
- Deinococcus gobiensis, sequence accession [ CP0025366]
Phylum Proteobacteria
- Aggregatibacter actinomycetemcomitans strain ANH9381, sequence accession [ CP0030997]
- Alishewanella jeotgali, sequence accession [ AHTH000000008]
- Enterobacter aerogenes KCTC 2190, sequence accession [ CP0028249]
- Escherichia coli O104:H4, sequence accession [ AFOB0200009210]
- Helicobacter pylori strains 17874, sequence accession PRJNA76569 [11]
- Helicobacter pylori strains P79, sequence accession PRJNA76567 [11]
- Janthinobacterium sp. Strain PAMC 25724, sequence accession [ AHHB0000000012]
- Klebsiella oxytoca KCTC 1686, sequence accession [ CP00321813]
- Klebsiella pneumoniae subsp. pneumoniae HS11286, sequence accession (chromosome), CP003200 (plasmid pKPHS1), CP003223 (plasmid pKPHS2), CP003224 (plasmid pKPHS3), CP003225 (plasmid pKPHS4), CP003226 (plasmid pKPHS5), CP003227 (plasmid pKPHS6) [ CP00322814]
- Oceanimonas sp. GK1, sequence accession [ CP00317115]
- “Pseudogulbenkiania ferrooxidans” Strain 2002, sequence accession [ NZ_ACIS0100000016]
- Pseudomonas extremaustralis 14-3b, sequence accession [ AHIP0000000017]
- Pseudomonas sp. Strain PAMC 25886, sequence accession [ AHHC0000000018]
- Psychrobacter, sequence accession [ AHVZ0000000019]
- Rahnella sp. Strain Y9602, sequence accession [ CP00250520]
- Rhizobium sp. Strain PDO1-076, sequence accession [ AHZC0000000021]
- Rhodospirillum photometricum DSM122, sequence accession [ HE66349322]
- “Rickettsia sibirica sibirica”, sequence accession [ AHIZ0000000023]
- Rickettsia sibirica subsp. mongolitimonae strain HA-91, sequence accession [ AHZB0000000024]
- Salmonella enterica subsp. enterica Serotype Enteritidis Strain LA5, sequence accession [25]
- Salmonella enterica subsp. enterica Serotype Senftenberg Strain SS209, sequence accession [ CAGQ0000000026]
- Salmonella enterica subsp. enterica Serovar Typhi P-stx-12, sequence accession (chromosome) and CP003278 (plasmid) [ CP00327927]
- Sphingomonas echinoides ATCC 14820, sequence accession [ AHIR0000000028]
- Strain HIMB55, sequence accession [ AGIF0000000029]
- Vibrio harveyi CAIM 1792, sequence accession [ AHHQ0000000030]
- Wolbachia Strain wAlbB, sequence accession [ CAGB01000001 to CAGB0100016531]
- Xanthomonas axonopodis pv. punicae Strain LMG 859, sequence accession [ CAGJ01000001 to CAGJ0100021732]
Phylum Tenericutes
- Mycoplasma hyorhinis Strain GDL-1, sequence accession [ CP00323133]
Phylum Firmicutes
- Bacillus subtilis, sequence accession BGSCID 3A27 through BGSCID 28A4 [34]
- Clostridium difficile Strain CD37, sequence accession [ AHJJ0000000035]
- Clostridium perfringens, sequence accession [ AFES0000000036]
- Lactobacillus fructivorans KCTC 3543, sequence accession [ AEQY0000000037]
- Lactococcus lactis IO-1, sequence accession [ AP01228138]
- Lactobacillus plantarum strain NC8, sequence accession [ AGRI0000000039]
- Paenibacillus dendritiformis C454, sequence accession [ AHKH0000000040]
- Paenibacillus sp. Strain Aloe-11, sequence accession [ AGFI0000000041]
- “Peptoniphilus rhinitidis” 1-13T, sequence accession [ BAEW01000001 to BAEW0100005642]
- Streptococcus macedonicus ACA-DC 198, sequence accession and HE613569 [ HE61357043]
- Staphylococcus aureus VC40, sequence accession [ CP00303344]
- Streptococcus infantarius subsp. infantarius Strain CJ18, sequence accession (chromosome), CP003295 (plasmid) [ CP00329645]
- Streptococcus macedonicus ACA-DC 198, sequence accession (chromosome), HE613569 (plasmid pSMA198) [ HE61357046]
Phylum Actinobacteria
- Actinoplanes sp. SE50/110, sequence accession [ CP00317047]
- Amycolatopsis sp. Strain ATCC 39116, sequence accession [48]
- Nocardia cyriacigeorgica GUH-2, sequence accession [ FO08284349]
- Salinibacterium sp., sequence accession [ AHWA0000000050]
- Streptomyces acidiscabies 84-104, sequence accession [ AHBF0000000051]
Non-Bacterial genomes
- Bluetongue Virus Serotype 2, sequence accession (Seg-6) and AJ783905 (Seg-1), JQ681257 (Seg-1), JQ681257 (Seg-2), JQ681258 (Seg-3), JQ681259 (Seg-4), JQ681260 (Seg-5), JQ681261 (Seg-7), JQ6812563 (Seg-8), JQ6812564 (Seg-9), to JQ681262 (Seg-10) [ JQ68126552]
- Virus Serotype 1, sequence accession (Seg-2), AJ585111 (Seg-6), AJ586659 (Seg-1), JQ282770 (Seg-3), JQ282771 (Seg-4), JQ282772 (Seg-5), JQ282773 (Seg-7), JQ282774 (Seg-8), JQ282775 (Seg-9), and JQ282776 (Seg-10) [ JQ28277752]
- Chloroplast genome of Erycina pusilla, sequence accession JF_746994 [53]
- Danio rerio, sequence accession [ JQ43410154]
- Enterococcal Bacteriophage SAP6, sequence accession [ JF73112855]
- Eubenangee virus, sequence accession through JQ070376 [ JQ07038556]
- Fujian/411-like viruses, sequence accession [ CY087969 to CY08856857]
- Hantavirus Variant of Rio Mamoré Virus, Maripa Virus, sequence accession (segment S), JQ611712 (segment M), and JQ611713 (segment L) [ JQ61171458]
- Pata virus, sequence accession through JQ070386 [ JQ07039559]
- Porcine Circovirus 2, sequence accession [ JQ41380860]
- Porcine Reproductive and Respiratory Syndrome Virus, sequence accession [ JQ32627161]
- Streptococcus mutans Phage M102AD, sequence accession [ DQ38616262]
- Tilligery virus, sequence accession through JQ070366 [ JQ07037563]
12.
L. Pilloni P. Bianco C. Manieli G. Senes P. Coni L. Atzori N. Aste G. Faa 《European journal of histochemistry : EJH》2009,53(2)
Basal cell carcinoma (BCC) is a very common malignant skin tumor that rarely metastatizes, but is often locally aggressive. Several factors, like large size (more than 3 cm), exposure to ultraviolet rays, histological variants, level of infiltration and perineural or perivascular invasion, are associated with a more aggressive clinical course. These morphological features seem to be more determinant in mideface localized BCC, which frequently show a significantly higher recurrence rate. An immunohistochemical profile, characterized by reactivity of tumor cells for p53, Ki67 and alpha-SMA has been associated with a more aggressive behaviour in large BCCs. The aim of this study was to verify if also little (<3 cm) basal cell carcinomas can express immunohistochemical markers typical for an aggressive behaviour.Basal cell carcinoma (BCC) is a very common malignant skin tumor that rarely metastatizes, even If Is often locally aggressive. Several factors, like large size (more than 3 cm), face localization, exposure to ultraviolet rays, histological variants, infiltration level and perineural or perivascular invasion, are associated with a more aggressive clinical course. In particular, the incidence of metastasis and/or death correlates with tumors greater than 3 cm in diameter in which setting patients are said to have 1–2 % risk of metastases that increases to 20–25% in lesions greater than 5 cm and to 50% in lesions greater than 10 cm in diameter (Snow et al., 1994). Histologically morpheiform, keratotic types and infiltrative growth of BCC are also considered features of the most aggressive course (Crowson, 2006). This can be explained by the fact that both the superficial and nodular variants of BCC are surrounded by a continuous basement membrane zone comprising collagens type IV and V admixed with laminin, while the aggressive growth variants (i.e. morpheiform, metatypical, and infiltrative growth subtypes) manifest the absence of basement membrane (Barsky et al., 1987).The molecular markers which characterize aggressive BCC include: increased expression of stromolysin (MMP-3) and collagenase-1 (MMP-1) (Cribier et al., 2001), decreased expression of syndecan-1 proteoglycan (Bayer-Garner et al., 2000) and of anti-apoptotic protein bcl-2 (Ramdial et al., 2000; Staibano et al., 2001).C-ras , c-fos (Urabe et al., 1994; Van der Schroeff et al., 1990) and p53 tumor supressor gene mutations (Auepemikiate et al., 2002) are indicative of an aggressive course.Focusing upon bcl-2 and p53 expression in BCC, there have been numerous studies documenting the utility of bcl-2 as a marker of favourable clinical behaviour while p53 expression may be a feature of a more aggressive outcome (Ramdial et al., 2000; Staibano et al., 2001; Bozdogan et al., 2002).An increased expression of cytoskeletal microfilaments like α–smooth muscle actin, frequently found in invasive BCC subtypes (Jones JCR et al., 1989), may explain an enhanced tumor mobility and deep tissue invasion through the stroma. (Cristian et al., 2001; Law et al., 2003). The aim of this preliminary study was to verify if also little (<3 cm) basal cell carcinomas may express aggressive immunohistochemical markers like p53, Ki67 and alpha-SMA. We used 31 excisional BCCs with tumor size less than 2 cm (ranging from 2 up to 20 mm) and with different skin localization (19 in the face, 6 in the trunk and 6 in the body extremities). All cases were immunostained for p53, BCL2, Ki67 and alpha-smooth muscle actin (α-SMA) (Age Sex Location Hystotype Max.Dim Depth Ulc Ess Inf p53 Bcl-2 Ki67 AML 1 61 M Extr Keratotic 10×8 1 No +++ URD +++ + + - 2 61 M Face Adenoid 10×9 4 No + URD +++ - - - 3 64 M Extr Sup mult 11×13 0.8 No + DRD + - - - 4 73 M Face Nodular 10×8 2 Yes + DRD +++ + ++ +++ 5 84 M Face Nodular 9×12 2 Yes + DRD - - - - 6 84 M Face Adenoid 5 0.8 No + URD +++ - - - 7 84 M Extr Nodular 13×10 3 No + DRD +++ + + - 8 52 F Face Nodular 4 0.8 No + URD + + + - 9 76 F Face Adenoid 10×4 4 No + DRD +++ - ++ - 10 77 F Face Morph 8×6 1 Yes +++ DRD +++ - - - 11 86 M Face Morph 8 1 Yes + DRD +++ - + + 12 63 F Face Adenoid 4 1 No + URD ++ + + + 13 76 F Face Nodular 7 1.5 No + DRD +++ + ++ - 14 84 M Face Nodular 11 4 Yes +++ DRD + - - + 15 63 F Face Keratotic 10×6 1.8 No ++ DRD - + ++ - 16 68 F Trunk Sup mult 10×6 0.7 No ++ URD + + - - 17 67 M Face Sup mult 12×6 0.4 No + URD + - + - 18 67 M Extr Sup mult 4×3 0.3 No + URD + +++ + - 19 32 F Extr Sup mult 1×3 0.4 No + URD + + + - 20 45 M Trunk Nodular 7×5 2 Yes +++ URD + + + - 21 62 M Trunk Sup mult 11×7 0.9 No ++ URD - ++ - ++ 22 65 M Trunk Adenoid 7×6 1.5 No + URD +++ + + - 23 72 M Trunk Nodular 12×6 1 No + URD +++ - + + 24 86 F Face Keratotic 20×11 3.1 No ++ DRD + + + - 25 85 M Face Nodular 0.5 1.3 No ++ DRD ++ + + - 26 74 F Extr Nodular 4×4 0.9 No + URD - - + - 27 71 M Face Nodular 6×12 1.7 No + DRD - - + - 28 64 F Trunk Sup mult 1.3×1.5 0.4 No ++ URD +++ - - - 29 78 F Face Nodular 4×3 1.5 No ++ DRD ++ + - +++ 30 80 M Face Keratotic 4×4 1.6 Yes + DRD - - + +++