The oral microbiota was compared between Romanian adolescents with a high prevalence of caries and no dental care and Swedish caries-active and caries-free adolescents in caries prevention programs ...and with a low prevalence of caries. Biofilm samples were analyzed by FLX+ pyrosequencing of the V1 to V4 hypervariable regions of the 16S rRNA gene and polymerase chain reaction (PCR)/quantitative PCR (qPCR) for Streptococcus mutans and Streptococcus sobrinus. Sequences obtained blasted to 9 phyla, 66 genera, and 401 human oral taxa (HOT) in the 16S rRNA Human Oral Microbiome Database, of which 295 were represented by ≥20 sequences. The Romanian adolescents had more sequences in Firmicutes and fewer in Actinobacteria phyla and more sequences in the genera Bacteroidetes G-3, Porphyromonas, Abiotrophia, Filifactor, Peptostreptococcaceae 11G-4, Pseudoramibacter, Streptococcus, and Neisseria and fewer in Actinomyces, Selenomonas, Veillonella, Campylobacter, and TM7 G-1 than the Swedish groups. Multivariate modeling employing HOT, S. sobrinus and S. mutans (PCR/qPCR), and sugar snacks separated Romanian from Swedish adolescents. The Romanian adolescents’ microbiota was characterized by a panel of streptococci, including S. mutans, S. sobrinus, and Streptococcus australis, and Alloprevotella, Leptotrichia, Neisseria, Porphyromonas, and Prevotella. The Swedish adolescents were characterized by sweet snacks, and those with caries activity were also characterized by Prevotella, Actinomyces, and Capnocytophaga species and those free of caries by Actinomyces, Prevotella, Selenomonas, Streptococcus, and Mycoplasma. Eight species including Streptococcus mitis and Streptococcus species HOT070 were prevalent in Romanian and Swedish caries-active subjects but not caries-free subjects. In conclusion, S. mutans and S. sobrinus correlated with Romanian adolescents with caries and with limited access to dental care, whereas S. mutans and S. sobrinus were detected infrequently in Swedish adolescents in dental care programs. Swedish caries-active adolescents were typically colonized by Actinomyces, Selenomonas, Prevotella, and Capnocytophaga. Hence, the role of mutans streptococci as a primary caries pathogen appears less pronounced in populations with prevention programs compared to populations lacking caries treatment and prevention strategies.
Abstract The fourth edition of the World Health Organization (WHO) classification of urogenital tumours (WHO “blue book”), published in 2016, contains significant revisions. These revisions were ...performed after consideration by a large international group of pathologists with special expertise in this area. A subgroup of these persons met at the WHO Consensus Conference in Zurich, Switzerland, in 2015 to finalize the revisions. This review summarizes the most significant differences between the newly published classification and the prior version for renal, penile, and testicular tumours. Newly recognized epithelial renal tumours are hereditary leiomyomatosis and renal cell carcinoma (RCC) syndrome–associated RCC, succinate dehydrogenase–deficient RCC, tubulocystic RCC, acquired cystic disease–associated RCC, and clear cell papillary RCC. The WHO/International Society of Urological Pathology renal tumour grading system was recommended, and the definition of renal papillary adenoma was modified. The new WHO classification of penile squamous cell carcinomas is based on the presence of human papillomavirus and defines histologic subtypes accordingly. Germ cell neoplasia in situ (GCNIS) of the testis is the WHO-recommended term for precursor lesions of invasive germ cell tumours, and testicular germ cell tumours are now separated into two fundamentally different groups: those derived from GCNIS and those unrelated to GCNIS. Spermatocytic seminoma has been designated as a spermatocytic tumour and placed within the group of non–GCNIS-related tumours in the 2016 WHO classification. Patient summary The 2016 World Health Organization (WHO) classification contains new renal tumour entities. The classification of penile squamous cell carcinomas is based on the presence of human papillomavirus. Germ cell neoplasia in situ of the testis is the WHO-recommended term for precursor lesions of invasive germ cell tumours.
Aim
Although it is established that peri‐implantitis is a bacterially induced disease, little is known about the bacterial profile of peri‐implant communities in health and disease. The purpose of ...the present investigation was to examine the microbial signatures of the peri‐implant microbiome in health and disease.
Materials and methods
Subgingival and submucosal plaque samples were collected from forty subjects with periodontitis, peri‐implantitis, periodontal and peri‐implant health and analysed using 16S pyrosequencing.
Results
Peri‐implant biofilms demonstrated significantly lower diversity than subgingival biofilms in both health and disease, however, several species, including previously unsuspected and unknown organisms, were unique to this niche. The predominant species in peri‐implant communities belonged to the genera Butyrivibrio, Campylobacter, Eubacterium, Prevotella, Selenomonas, Streptococcus, Actinomyces, Leptotrichia, Propionibacterium, Peptococcus, Lactococcus and Treponema. Peri‐implant disease was associated with lower levels of Prevotella and Leptotrichia and higher levels of Actinomyces, Peptococcus, Campylobacter, non‐mutans Streptococcus, Butyrivibrio and Streptococcus mutans than healthy implants. These communities also demonstrated lower levels of Prevotella, non‐mutans Streptococcus, Lactobacillus, Selenomonas, Leptotrichia, Actinomyces and higher levels of Peptococcus, Mycoplasma, Eubacterium, Campylobacter, Butyrivibrio, S. mutans and Treponema when compared to periodontitis‐associated biofilms.
Conclusion
The peri‐implant microbiome differs significantly from the periodontal community in both health and disease. Peri‐implantitis is a microbially heterogeneous infection with predominantly gram‐negative species, and is less complex than periodontitis.
Raman optical spectroscopy promises label-free bacterial detection, identification, and antibiotic susceptibility testing in a single step. However, achieving clinically relevant speeds and ...accuracies remains challenging due to weak Raman signal from bacterial cells and numerous bacterial species and phenotypes. Here we generate an extensive dataset of bacterial Raman spectra and apply deep learning approaches to accurately identify 30 common bacterial pathogens. Even on low signal-to-noise spectra, we achieve average isolate-level accuracies exceeding 82% and antibiotic treatment identification accuracies of 97.0±0.3%. We also show that this approach distinguishes between methicillin-resistant and -susceptible isolates of Staphylococcus aureus (MRSA and MSSA) with 89±0.1% accuracy. We validate our results on clinical isolates from 50 patients. Using just 10 bacterial spectra from each patient isolate, we achieve treatment identification accuracies of 99.7%. Our approach has potential for culture-free pathogen identification and antibiotic susceptibility testing, and could be readily extended for diagnostics on blood, urine, and sputum.
Background: This study compared the subgingival microbiota of subjects with refractory periodontitis (RP) to those in subjects with treatable periodontitis (GRs = good responders) or periodontal ...health (PH) using the Human Oral Microbe Identification Microarray (HOMIM).
Methods: At baseline, subgingival plaque samples were taken from 47 subjects with periodontitis and 20 individuals with PH and analyzed for the presence of 300 species by HOMIM. The subjects with periodontitis were classified as having RP (n = 17) based on mean attachment loss (AL) and/or more than three sites with AL ≥2.5 mm after scaling and root planing, surgery, and systemically administered amoxicillin and metronidazole or as GRs (n = 30) based on mean attachment gain and no sites with AL ≥2.5 mm after treatment. Significant differences in taxa among the groups were sought using the Kruskal‐Wallis and χ2 tests.
Results: More species were detected in patients with disease (GR or RP) than in those without disease (PH). Subjects with RP were distinguished from GRs or those with PH by a significantly higher frequency of putative periodontal pathogens, such as Parvimonas micra (previously Peptostreptococcus micros or Micromonas micros), Campylobacter gracilis, Eubacterium nodatum, Selenomonas noxia, Tannerella forsythia (previously T. forsythensis), Porphyromonas gingivalis, Prevotella spp., Treponema spp., and Eikenella corrodens, as well as unusual species (Pseudoramibacter alactolyticus, TM7 spp. oral taxon OT 346/356, Bacteroidetes sp. OT 272/274, Solobacterium moorei, Desulfobulbus sp. OT 041, Brevundimonas diminuta, Sphaerocytophaga sp. OT 337, Shuttleworthia satelles, Filifactor alocis, Dialister invisus/pneumosintes, Granulicatella adiacens, Mogibacterium timidum, Veillonella atypica, Mycoplasma salivarium, Synergistes sp. cluster II, and Acidaminococcaceae G‐1 sp. OT 132/150/155/148/135) (P <0.05). Species that were more prevalent in subjects with PH than in patients with periodontitis included Actinomyces sp. OT 170, Actinomyces spp. cluster I, Capnocytophaga sputigena, Cardiobacterium hominis, Haemophilus parainfluenzae, Lautropia mirabilis, Propionibacterium propionicum, Rothia dentocariosa/mucilaginosa, and Streptococcus sanguinis (P <0.05).
Conclusion: As determined by HOMIM, patients with RP presented a distinct microbial profile compared to patients in the GR and PH groups.
Social class in Europe Rose, David; Harrison, Eric; Pevalin, David ...
2009, 2010, 20140404, 2009-10-22, 2014-04-04, 20090101, Letnik:
10
eBook, Book
This timely volume introduces a new social class schema, the European Socio-economic Classification (ESeC), which has been specifically developed and tested for use in EU comparative research. Social ...Class in Europe aims to introduce researchers to the new classification and its research potential. Since socio-economic classifications are so widely used in official and academic research, this collection is essential reading for all users of both government and academic social classifications. While primarily aimed at researchers who will be using the ESeC, the book's contents will also have a wider appeal as it is suitable for students taking substantive courses in European studies or as a supplementary text for undergraduates studying the EU, Sociology and Economics. Because of its inherent methodological interest, the book should prove a valuable tool for undergraduate and graduate courses that discuss how social scientists construct and validate basic measures. It will also be required reading for policy makers and analysts concerned with social inequality and social exclusion across Europe.
Learning the mechanisms of network growth Touwen, Lourens; Bucur, Doina; van der Hofstad, Remco ...
Scientific reports,
2024-May-24, Letnik:
14, Številka:
1
Journal Article
Recenzirano
Odprti dostop
We propose a novel model-selection method for dynamic networks. Our approach involves training a classifier on a large body of synthetic network data. The data is generated by simulating nine ...state-of-the-art random graph models for dynamic networks, with parameter range chosen to ensure exponential growth of the network size in time. We design a conceptually novel type of dynamic features that count new links received by a group of vertices in a particular time interval. The proposed features are easy to compute, analytically tractable, and interpretable. Our approach achieves a near-perfect classification of synthetic networks, exceeding the state-of-the-art by a large margin. Applying our classification method to real-world citation networks gives credibility to the claims in the literature that models with preferential attachment, fitness and aging fit real-world citation networks best, although sometimes, the predicted model does not involve vertex fitness.
Abstract
Genomic maps of DNA G-quadruplexes (G4s) can help elucidate the roles that these secondary structures play in various organisms. Herein, we employ an improved version of a G-quadruplex ...sequencing method (G4-seq) to generate whole genome G4 maps for 12 species that include widely studied model organisms and also pathogens of clinical relevance. We identify G4 structures that form under physiological K+ conditions and also G4s that are stabilized by the G4-targeting small molecule pyridostatin (PDS). We discuss the various structural features of the experimentally observed G-quadruplexes (OQs), highlighting differences in their prevalence and enrichment across species. Our study describes diversity in sequence composition and genomic location for the OQs in the different species and reveals that the enrichment of OQs in gene promoters is particular to mammals such as mouse and human, among the species studied. The multi-species maps have been made publicly available as a resource to the research community. The maps can serve as blueprints for biological experiments in those model organisms, where G4 structures may play a role.
Sequencing in all areas of the tree of life has produced >300,000 cytochrome P450 (CYP) sequences that have been mined and collected. Nomenclature has been assigned to >41,000 CYP sequences and the ...majority of the remainder has been sorted by BLAST searches into clans, families and subfamilies in preparation for naming. The P450 sequence space is being systematically explored and filled in. Well-studied groups like vertebrates are covered in greater depth while new insights are being added into uncharted territories like horseshoe crab (Limulus polyphemus), tardigrades (Hypsibius dujardini), velvet worm (Euperipatoides_rowelli), and basal land plants like hornworts, liverworts and mosses. CYPs from the fungi, one of the most diverse groups, are being explored and organized as nearly 800 fungal species are now sequenced. The CYP clan structure in fungi is emerging with 805 CYP families sorting into 32 CYP clans. >3000 bacterial sequences are named, mostly from terrestrial or freshwater sources. Of 18,379 bacterial sequences downloaded from the CYPED database, all are >43% identical to named CYPs. Therefore, they fit in the 602 named P450 prokaryotic families. Diversity in this group is becoming saturated, however 25% of 3305 seawater bacterial P450s did not match known P450 families, indicating marine bacterial CYPs are not as well sampled as land/freshwater based bacterial CYPs. Future sequencing plans of the Genome 10K project, i5k and GIGA (Global Invertebrate Genomics Alliance) are expected to produce more than one million cytochrome P450 sequences by 2020. This article is part of a Special Issue entitled: Cytochrome P450 biodiversity and biotechnology, edited by Erika Plettner, Gianfranco Gilardi, Luet Wong, Vlada Urlacher, Jared Goldstone.
•~350,000 cytochrome P450 sequences are collected from public and private sources.•P450s from panarthropods horseshoe crab, velvet worm and a tardigrade are analyzed.•The P450s from a first spider genome are named.•Progress is presented on naming P450 clans in fungi.•Methods are described for finding all P450 families in any taxa (gymnosperms, etc.).
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