Anti-infective therapy of peri-implantitis with adjunctive local drug delivery or photodynamic therapy: 12-month outcomes of a randomized controlled clinical trial

OBJECTIVE: The objective of the study is to compare the clinical, microbiological and host-derived effects in the non-surgical treatment of initial peri-implantitis with either adjunctive local drug delivery (LDD) or adjunctive photodynamic therapy (PDT) after 12 months. MATERIALS AND METHODS: Forty subjects with initial peri-implantitis, that is, pocket probing depths (PPD) 4-6 mm with bleeding on probing (BoP) and radiographic bone loss ≤2 mm, were randomly assigned to two treatment groups. All implants were mechanically debrided with titanium curettes and with a glycine-based powder airpolishing system. Implants in the test group (N = 20) received adjunctive PDT, whereas minocycline microspheres were locally delivered into the peri-implant pockets of control implants (N = 20). At sites with residual BoP, treatment was repeated after 3, 6, 9 and 12 months. The primary outcome variable was the change in the number of peri-implant sites with BoP. Secondary outcome variables included changes in PPD, clinical attachment level (CAL), mucosal recession (REC) and in bacterial counts and crevicular fluid (CF) levels of host-derived biomarkers. RESULTS: After 12 months, the number of BoP-positive sites decreased statistically significantly (P < 0.05) from baseline in both groups (PDT: 4.03 ± 1.66-1.74 ± 1.37, LDD: 4.41 ± 1.47-1.55 ± 1.26). A statistically significant (P < 0.05) decrease in PPD from baseline was observed at PDT-treated sites up to 9 months (4.19 ± 0.55 mm to 3.89 ± 0.68 mm) and up to 12 months at LDD-treated sites (4.39 ± 0.77 mm to 3.83 ± 0.85 mm). Counts of Porphyromonas gingivalis and Tannerella forsythia decreased statistically significantly (P < 0.05) from baseline to 6 months in the PDT and to 12 months in the LDD group, respectively. CF levels of IL-1β decreased statistically significantly (P < 0.05) from baseline to 12 months in both groups. No statistically significant differences (P > 0.05) were observed between groups after 12 months with respect to clinical, microbiological and host-derived parameters. CONCLUSIONS: Non-surgical mechanical debridement with adjunctive PDT was equally effective in the reduction of mucosal inflammation as with adjunctive delivery of minocycline microspheres up to 12 months. Adjunctive PDT may represent an alternative approach to LDD in the non-surgical treatment of initial peri-implantitis.

Temporal trends of extended-spectrum cephalosporin-resistant Escherichia coli and Klebsiella pneumoniae isolates in in- and outpatients in Switzerland, 2004 to 2011

Increasing trends for invasive infections with extended-spectrum cephalosporin-resistant (ESC-R) Enterobacteriaceae have been described in many countries worldwide. However, data on the rates of ESC-R isolates in non-invasive infections and in the outpatient setting are scarce. We used a laboratory-based nationwide surveillance system to compare temporal trends of ESC-R rates in Escherichia coli and Klebsiella pneumoniae for in- and outpatients in Switzerland. Our data showed a significant increase in ESC-R rates from 1% to 5.8% in E. coli (p<0.001) and from 1.1% to 4.4% in K. pneumoniae (p=0.002) during an eight-year period (2004–2011). For E. coli, the increase was significantly higher in inpatients (from 1.2% to 6.6%), in patients residing in eastern Switzerland (from 1.0% to 6.2%), in patients older than 45 years (from 1.2% to 6.7%), and in male patients (from 1.2% to 8.1%). While the increase in inpatients was linear (p<0.001) for E. coli, the increase of ESC R K. pneumoniae isolates was the result of multiple outbreaks in several institutions. Notably, an increasing proportion of ESC-R E. coli was co-resistant to both trimethoprim-sulfamethoxazole and quinolones (42% in 2004 to 49.1% in 2011, p=0.009), further limiting the available oral therapeutic options.

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

Factor structure of the Bern Psychopathology Scale in a sample of patients with schizophrenia spectrum disorders.

BACKGROUND The Bern Psychopathology Scale (BPS) is based on a system-specific approach to classifying the psychopathological symptom pattern of schizophrenia. It consists of subscales for three domains (language, affect and motor behaviour) that are hypothesized to be related to specific brain circuits. The aim of the study was to examine the factor structure of the BPS in patients with schizophrenia spectrum disorders. METHODS One hundred and forty-nine inpatients with schizophrenia spectrum disorders were recruited at the Department of Psychiatry II, Ulm University, Germany (n=100) and at the University Hospital of Psychiatry, Bern, Switzerland (n=49). Psychopathology was assessed with the BPS. The VARCLUS procedure of SAS(®) (a type of oblique component analysis) was used for statistical analysis. RESULTS Six clusters were identified (inhibited language, inhibited motor behaviour, inhibited affect, disinhibited affect, disinhibited language/motor behaviour, inhibited language/motor behaviour) which explained 40.13% of the total variance of the data. A binary division of attributes into an inhibited and disinhibited cluster was appropriate, although an overlap was found between the language and motor behaviour domains. There was a clear distinction between qualitative and quantitative symptoms. CONCLUSIONS The results argue for the validity of the BPS in identifying subsyndromes of schizophrenia spectrum disorders according to a dimensional approach. Future research should address the longitudinal assessment of dimensional psychopathological symptoms and elucidate the underlying neurobiological processes.

Evaluating atmospheric methane inversion model results for Pallas, northern Finland

A state-of-the-art inverse model, CarbonTracker Data Assimilation Shell (CTDAS), was used to optimize estimates of methane (CH4) surface fluxes using atmospheric observations of CH4 as a constraint. The model consists of the latest version of the TM5 atmospheric chemistry-transport model and an ensemble Kalman filter based data assimilation system. The model was constrained by atmospheric methane surface concentrations, obtained from the World Data Centre for Greenhouse Gases (WDCGG). Prior methane emissions were specified for five sources: biosphere, anthropogenic, fire, termites and ocean, of which bio-sphere and anthropogenic emissions were optimized. Atmospheric CH 4 mole fractions for 2007 from northern Finland calculated from prior and optimized emissions were compared with observations. It was found that the root mean squared errors of the posterior esti - mates were more than halved. Furthermore, inclusion of NOAA observations of CH 4 from weekly discrete air samples collected at Pallas improved agreement between posterior CH 4 mole fraction estimates and continuous observations, and resulted in reducing optimized biosphere emissions and their uncertainties in northern Finland.

Robust indoor localization of narrowband signals

Many location-based services target users in indoor environments. Similar to the case of dense urban areas where many obstacles exist, indoor localization techniques suffer from outlying measurements caused by severe multipath propaga??tion and non-line-of-sight (NLOS) reception. Obstructions in the signal path caused by static or mobile objects downgrade localization accuracy. We use robust multipath mitigation techniques to detect and filter out outlying measurements in indoor environments. We validate our approach using a power-based lo??calization system with GSM. We conducted experiments without any prior knowledge of the tracked device's radio settings or the indoor radio environment. We obtained localization errors in the range of 3m even if the sensors had NLOS links to the target device.

Accuracy of tidal breathing measurement of FloRight compared to an ultrasonic flowmeter in infants.

INTRODUCTION Monitoring breathing pattern is especially relevant in infants with lung disease. Recently, a vest-based inductive plethysmograph system (FloRight®) has been developed for tidal breathing measurement in infants. We investigated the accuracy of tidal breathing flow volume loop (TBFVL) measurements in healthy term-born infants and infants with lung disease by the vest-based system in comparison to an ultrasonic flowmeter (USFM) with a face mask. We also investigated whether the system discriminates between healthy infants and those with lung disease. METHODS Floright® measures changes in thoracoabdominal volume during tidal breathing through magnetic field changes generated by current-carrying conductor coils in an elastic vest. Simultaneous TBFVL measurements by the vest-based system and the USFM were performed at 44 weeks corrected postmenstrual age during quiet unsedated sleep. TBFVL parameters derived by both techniques and within both groups were compared. RESULTS We included 19 healthy infants and 18 infants with lung disease. Tidal volume per body weight derived by the vest-based system was significantly lower with a mean difference (95% CI) of -1.33 ml/kg (-1.73; -0.92), P < 0.001. Respiratory rate and ratio of time to peak tidal expiratory flow over total expiratory time (tPTEF/tE) did not differ between the two techniques. Both systems were able to discriminate between healthy infants and those with lung disease using tPTEF/tE. CONCLUSION FloRight® accurately measures time indices and may discriminate between healthy infants and those with lung disease, but demonstrates differences in tidal volume measurements. It may be better suited to monitor breathing pattern than for TBFVL measurements.

Timely Reporting and Interactive Visualization of Animal Health and Slaughterhouse Surveillance Data in Switzerland

The reporting of outputs from health surveillance systems should be done in a near real-time and interactive manner in order to provide decision makers with powerful means to identify, assess, and manage health hazards as early and efficiently as possible. While this is currently rarely the case in veterinary public health surveillance, reporting tools do exist for the visual exploration and interactive interrogation of health data. In this work, we used tools freely available from the Google Maps and Charts library to develop a web application reporting health-related data derived from slaughterhouse surveillance and from a newly established web-based equine surveillance system in Switzerland. Both sets of tools allowed entry-level usage without or with minimal programing skills while being flexible enough to cater for more complex scenarios for users with greater programing skills. In particular, interfaces linking statistical softwares and Google tools provide additional analytical functionality (such as algorithms for the detection of unusually high case occurrences) for inclusion in the reporting process. We show that such powerful approaches could improve timely dissemination and communication of technical information to decision makers and other stakeholders and could foster the early-warning capacity of animal health surveillance systems.