Population biology of Propionibacterium acnes and Pseudomonas aeruginosa in ophthalmic infections and the development of novel diagnostic tools

Bacterial keratitis and bacterial endophthalmitis are two of the most devastating sight threatening eye infections. It is currently unclear whether the organisms isolated from these infections represent specialised members of these species or whether all strains are equally likely to cause infection. One method of differentiating strains genotypically is by a typing technique known as multilocus sequence typing (MLST). Using this technique, a better understanding of the molecular epidemiology of eye infections can be achieved. Propionibacterium acnes (P. acnes) is an important anaerobic organism causing several types of eye infections. Although it is now beginning to be recognised as a serious opportunistic pathogen, few studies have been done to investigate the population biology of P. acnes at the molecular level. Our continuing inability to distinguish between strains of P. acnes means that we still do not fully understand how antibiotic-resistant strains spread, nor whether certain strains, or clonal complexes, of P. acnes are associated with certain infections. These are key issues that can now be understood with our development of an MLST system for P. acnes. A diverse culture collection of 125 P. acnes isolates have been analysed using the MLST scheme developed. Sequence analysis shows that there are phylogenetically distinct groups within P. acnes and identified a novel cluster not previously described. Analysis of recombination using several methods suggests that frequent recombination occurs within these subgroups. There appears to be no association between these subgroups and clinical manifestation of P. acnes infection or geographical location. The P. acnes MLST scheme was validated against 16S rRNA gene and complete recA gene typing as well as immunofluorescence microscopy (IFM) and random amplification of polymorphic DNA (RAPD) analysis. P. acnes is a slow growing organism and is difficult to culture from ocular samples. A real-time PCR assay was developed in order to overcome the low culture positive rate and delay associated with conventional culture methods. Primers targeting one of the seven housekeeping genes used in the MLST scheme (gmk), specific for P. acnes were selected. The real-time PCR assay was both specific to P. acnes and highly sensitive. Pseudomonas aeruginosa (P. aeruginosa) is another important organism in the development of serious eye infections, and is the commonest cause of contact lens related microbial keratitis. Infections with this organism can lead to rapid deterioration of vision and possible blindness. A previously developed MLST scheme has been applied to 117 eye isolates from around the UK and China. This typing data was compared to 166 P. aeruginosa isolates from other clinical and environmental sources. Overall, MLST data supports previous findings that P. aeruginosa has a nonclonal population with epidemic clones. Sequence analysis showed that eye isolates do not cluster away from isolates from other clinical infection sites

Constitutively active transforming growth factor β receptor 1 in the mouse ovary promotes tumorigenesis

Despite the well-established tumor suppressive role of TGFβ proteins, depletion of key TGFβ signaling components in the mouse ovary does not induce a growth advantage. To define the role of TGFβ signaling in ovarian tumorigenesis, we created a mouse model expressing a constitutively active TGFβ receptor 1 (TGFBR1) in ovarian somatic cells using conditional gain-of-function approach. Remarkably, these mice developed ovarian sex cord-stromal tumors with complete penetrance, leading to reproductive failure and mortality. The tumors expressed multiple granulosa cell markers and caused elevated serum inhibin and estradiol levels, reminiscent of granulosa cell tumors. Consistent with the tumorigenic effect, overactivation of TGFBR1 altered tumor microenvironment by promoting angiogenesis and enhanced ovarian cell proliferation, accompanied by impaired cell differentiation and dysregulated expression of critical genes in ovarian function. By further exploiting complementary genetic models, we substantiated our finding that constitutively active TGFBR1 is a potent oncogenic switch in mouse granulosa cells. In summary, overactivation of TGFBR1 drives gonadal tumor development. The TGFBR1 constitutively active mouse model phenocopies a number of morphological, hormonal, and molecular features of human granulosa cell tumors and are potentially valuable for preclinical testing of targeted therapies to treat granulosa cell tumors, a class of poorly defined ovarian malignancies

novoBreak: local assembly for breakpoint detection in cancer genomes.

We present novoBreak, a genome-wide local assembly algorithm that discovers somatic and germline structural variation breakpoints in whole-genome sequencing data. novoBreak consistently outperformed existing algorithms on real cancer genome data and on synthetic tumors in the ICGC-TCGA DREAM 8.5 Somatic Mutation Calling Challenge primarily because it more effectively utilized reads spanning breakpoints. novoBreak also demonstrated great sensitivity in identifying short insertions and deletions

Studying discrete dynamical systems trough differential equations

In this paper we consider dynamical systems generated by a diffeomorphism F defined on U an open subset of R^n, and give conditions over F which imply that their dynamics can be understood by studying the flow of an associated differential equation, $\dot x=X(x),$ also defined on U. In particular the case where F has n-1 functionally independent first integrals is considered. In this case X is constructed by imposing that it shares with $F$ the same set of first integrals and that the functional equation $\mu(F(x))=\det((DF(x))\mu(x),$ for x in U has some non-zero solution. Several examples for n=2,3 are presented, most of them coming from several well-known difference equations.Comment: 22 pages; 3 Figure

An expanded multilocus sequence typing scheme for propionibacterium acnes : investigation of 'pathogenic', 'commensal' and antibiotic resistant strains

The Gram-positive bacterium Propionibacterium acnes is a member of the normal human skin microbiota and is associated with various infections and clinical conditions. There is tentative evidence to suggest that certain lineages may be associated with disease and others with health. We recently described a multilocus sequence typing scheme (MLST) for P. acnes based on seven housekeeping genes (http://pubmlst.org/pacnes). We now describe an expanded eight gene version based on six housekeeping genes and two ‘putative virulence’ genes (eMLST) that provides improved high resolution typing (91eSTs from 285 isolates), and generates phylogenies congruent with those based on whole genome analysis. When compared with the nine gene MLST scheme developed at the University of Bath, UK, and utilised by researchers at Aarhus University, Denmark, the eMLST method offers greater resolution. Using the scheme, we examined 208 isolates from disparate clinical sources, and 77 isolates from healthy skin. Acne was predominately associated with type IA1 clonal complexes CC1, CC3 and CC4; with eST1 and eST3 lineages being highly represented. In contrast, type IA2 strains were recovered at a rate similar to type IB and II organisms. Ophthalmic infections were predominately associated with type IA1 and IA2 strains, while type IB and II were more frequently recovered from soft tissue and retrieved medical devices. Strains with rRNA mutations conferring resistance to antibiotics used in acne treatment were dominated by eST3, with some evidence for intercontinental spread. In contrast, despite its high association with acne, only a small number of resistant CC1 eSTs were identified. A number of eSTs were only recovered from healthy skin, particularly eSTs representing CC72 (type II) and CC77 (type III). Collectively our data lends support to the view that pathogenic versus truly commensal lineages of P. acnes may exist. This is likely to have important therapeutic and diagnostic implications

Tree-Values: selective inference for regression trees

We consider conducting inference on the output of the Classification and Regression Tree (CART) [Breiman et al., 1984] algorithm. A naive approach to inference that does not account for the fact that the tree was estimated from the data will not achieve standard guarantees, such as Type 1 error rate control and nominal coverage. Thus, we propose a selective inference framework for conducting inference on a fitted CART tree. In a nutshell, we condition on the fact that the tree was estimated from the data. We propose a test for the difference in the mean response between a pair of terminal nodes that controls the selective Type 1 error rate, and a confidence interval for the mean response within a single terminal node that attains the nominal selective coverage. Efficient algorithms for computing the necessary conditioning sets are provided. We apply these methods in simulation and to a dataset involving the association between portion control interventions and caloric intake

Data thinning for convolution-closed distributions

We propose data thinning, an approach for splitting an observation into two or more independent parts that sum to the original observation, and that follow the same distribution as the original observation, up to a (known) scaling of a parameter. This very general proposal is applicable to any convolution-closed distribution, a class that includes the Gaussian, Poisson, negative binomial, gamma, and binomial distributions, among others. Data thinning has a number of applications to model selection, evaluation, and inference. For instance, cross-validation via data thinning provides an attractive alternative to the usual approach of cross-validation via sample splitting, especially in unsupervised settings in which the latter is not applicable. In simulations and in an application to single-cell RNA-sequencing data, we show that data thinning can be used to validate the results of unsupervised learning approaches, such as k-means clustering and principal components analysis

Population biology of Propionibacterium acnes and Pseudomonas aeruginosa in ophthalmic infections and the development of novel diagnostic tools

Bacterial keratitis and bacterial endophthalmitis are two of the most devastating sight threatening eye infections. It is currently unclear whether the organisms isolated from these infections represent specialised members of these species or whether all strains are equally likely to cause infection. One method of differentiating strains genotypically is by a typing technique known as multilocus sequence typing (MLST). Using this technique, a better understanding of the molecular epidemiology of eye infections can be achieved. Propionibacterium acnes (P. acnes) is an important anaerobic organism causing several types of eye infections. Although it is now beginning to be recognised as a serious opportunistic pathogen, few studies have been done to investigate the population biology of P. acnes at the molecular level. Our continuing inability to distinguish between strains of P. acnes means that we still do not fully understand how antibiotic-resistant strains spread, nor whether certain strains, or clonal complexes, of P. acnes are associated with certain infections. These are key issues that can now be understood with our development of an MLST system for P. acnes. A diverse culture collection of 125 P. acnes isolates have been analysed using the MLST scheme developed. Sequence analysis shows that there are phylogenetically distinct groups within P. acnes and identified a novel cluster not previously described. Analysis of recombination using several methods suggests that frequent recombination occurs within these subgroups. There appears to be no association between these subgroups and clinical manifestation of P. acnes infection or geographical location. The P. acnes MLST scheme was validated against 16S rRNA gene and complete recA gene typing as well as immunofluorescence microscopy (IFM) and random amplification of polymorphic DNA (RAPD) analysis. P. acnes is a slow growing organism and is difficult to culture from ocular samples. A real-time PCR assay was developed in order to overcome the low culture positive rate and delay associated with conventional culture methods. Primers targeting one of the seven housekeeping genes used in the MLST scheme (gmk), specific for P. acnes were selected. The real-time PCR assay was both specific to P. acnes and highly sensitive. Pseudomonas aeruginosa (P. aeruginosa) is another important organism in the development of serious eye infections, and is the commonest cause of contact lens related microbial keratitis. Infections with this organism can lead to rapid deterioration of vision and possible blindness. A previously developed MLST scheme has been applied to 117 eye isolates from around the UK and China. This typing data was compared to 166 P. aeruginosa isolates from other clinical and environmental sources. Overall, MLST data supports previous findings that P. aeruginosa has a nonclonal population with epidemic clones. Sequence analysis showed that eye isolates do not cluster away from isolates from other clinical infection sites.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

LEGAL BASIS FOR THE DEVELOPMENT OF AN INDUSTRIAL INTERNET PLATFORM IN THE CONTEXT OF DIGITAL TRANSFORMATION

Objective: The purpose of this study is to analyze the experience of using industrial Internet platforms in China and its impact on the regulation of production services of enterprises. The study analyzes the concept of global value chains and examines the distribution of benefits among participating countries as a result of the deepening of the international division of labor.Methods: A combination of research methods, including factorial, comparative, and structural analysis, was used to achieve the research objectives. The main research material consisted of Russian and international statistical data, Russian and international legal frameworks, and comparative legal analysis.Results: Industrial Internet platforms not only promote cooperation between the production party and upstream and downstream enterprises in the value chain but also increase the added value of the production party and smoothen the smile curve.Conclusion: The article combines the concept of proactive artificial intelligence and suggests an innovative direction for the industrial Internet. The development of industrial Internet platforms plays a crucial role in the digital transformation of production processes. This requires a comprehensive legal and regulatory framework to ensure data confidentiality, intellectual property protection, and secure cross-border data transfer