Periodontitis and systemic diseases:A record of discussions of working group 4 of the Joint EFP/AAP Workshop on Periodontitis and Systemic Diseases

Background There has been an explosion in research into possible associations between periodontitis and various systemic diseases and conditions. Aim To review the evidence for associations between periodontitis and various systemic diseases and conditions, including chronic obstructive pulmonary disease (COPD), pneumonia, chronic kidney disease, rheumatoid arthritis, cognitive impairment, obesity, metabolic syndrome and cancer, and to document headline discussions of the state of each field. Periodontal associations with diabetes, cardiovascular disease and adverse pregnancy outcomes were not discussed by working group 4. Results Working group 4 recognized that the studies performed to date were largely cross-sectional or case-control with few prospective cohort studies and no randomized clinical trials. The best current evidence suggests that periodontitis is characterized by both infection and pro-inflammatory events, which variously manifest within the systemic diseases and disorders discussed. Diseases with at least minimal evidence of an association with periodontitis include COPD, pneumonia, chronic kidney disease, rheumatoid arthritis, cognitive impairment, obesity, metabolic syndrome and cancer. The working group agreed that there is insufficient evidence to date to infer causal relationships with the exception that organisms originating in the oral microbiome can cause lung infections. Conclusions The group was unanimous in their opinion that the reported associations do not imply causality, and establishment of causality will require new studies that fulfil the Bradford Hill or equivalent criteria. Precise and community-agreed case definitions of periodontal disease states must be implemented systematically to enable consistent and clearer interpretations of studies of the relationship to systemic diseases. The members of the working group were unanimous in their opinion that to develop data that best inform clinicians, investigators and the public, studies should focus on robust disease outcomes and avoid surrogate endpoints. It was concluded that because of the relative immaturity of the body of evidence for each of the purported relationships, the field is wide open and the gaps in knowledge are large. © 2013 European Federation of Periodontology and American Academy of Periodontology.

A Tight Upper Bound on Bit Error Rate of Joint OFDM and Multi-Carrier Index Keying

This letter investigates performance enhancement by the concept of multi-carrier index keying in orthogonal frequency division multiplexing (OFDM) systems. For the performance evaluation, a tight closed-form approximation of the bit error rate (BER) is derived introducing the expression for the number of bit errors occurring in both the index domain and the complex domain, in the presence of both imperfect and perfect detection of active multi-carrier indices. The accuracy of the derived BER results for various cases are validated using simulations, which can provide accuracy within 1 dB at favorable channels.

A '3-body' abrasion wear study of bioceramics for total hip joint replacements

The current study focuses on the effect of the material type and the lubricant on the abrasive wear behaviour of two important commercially available ceramic on ceramic prosthetic systems, namely, Biolox(R) forte and Bioloxl(R) delta (CeramTec AG, Germany). A standard microabrasion wear apparatus was used to produce '3-body' abrasive wear scars with three different lubricants: ultrapure water, 25 vol% new-born calf serum solution and 1 wt% carboxymethyl cellulose sodium salt (CMC-Na) solution. 1 mu m alumina particles were used as the abrasive. The morphology of the wear scar was examined in detail using Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM). Subsurface damage accumulation was investigated by Focused Ion Beam (FIB) cross-sectional milling and Transmission Electron Microscopy (TEM). The effect of the lubricant on the '3-body' abrasive wear mechanisms is discussed and the effect of material properties compared. (C) 2009 Elsevier B.V. All rights reserved.

Antimicrobial peptides and proinflammatory cytokines in periprosthetic joint infection

Background: Differentiation between septic and aseptic loosening of joint replacements is essential for successful revision surgery, but reliable markers for the diagnosis of low-grade infection are lacking. The present study was performed to assess intra-articular and systemic levels of antimicrobial peptides and proinflammatory cytokines as diagnostic markers for periprosthetic joint infection. Methods: Fifteen consecutive patients with staphylococcal periprosthetic joint infections and twenty control patients with aseptic loosening of total hip and knee replacements were included in this prospective, single-center, controlled clinical trial. Expression of the antimicrobial peptides human β-defensin-2 (HBD-2), human β-defensin-3 (HBD-3), and cathelicidin LL-37 (LL-37) was determined by ELISA (enzyme-linked immunosorbent assay) in serum and joint aspirates. Proinflammatory cytokines were assessed in serum and joint aspirates with use of cytometric bead arrays. C-reactive protein in serum, microbiology, and histopathology of periprosthetic tissue served as the “gold standard” for the diagnosis of infection. Results: The antimicrobial peptides HBD-3 and LL-37 were significantly elevated in joint aspirates from patients with periprosthetic joint infection compared with patients with aseptic loosening, and the area under the curve (AUC) in a receiver operating characteristic curve analysis was equal to 0.745 and 0.875, respectively. Additionally, significant local increases in the proinflammatory cytokines interleukin (IL)-1β, IL-4, IL-6, IL-17A, interferon (IFN)-γ, and tumor necrosis factor (TNF)-α were observed to be associated with infection. Logistic regression analysis indicated that the combination of an antimicrobial peptide with another synovial fluid biomarker improved diagnostic accuracy; the AUC value was 0.916 for LL-37 and IL-4, 0.895 for LL-37 and IL-6, 0.972 for HBD-3 and IL-4, and 0.849 for HBD-3 and IL-6. In contrast, the only antimicrobial peptides and cytokines in serum that showed a significant systemic increase in association with infection were HBD-2, IL-4, and IL-6 (all of which had an AUC value of <0.75). Conclusions: The present study showed promising results for the use of antimicrobial peptides and other biomarkers in synovial fluid for the diagnosis of periprosthetic joint infection, and analysis of the levels in synovial fluid was more accurate than analysis of serum.

Proactive Relay Selection with Joint Impact of Hardware Impairment and Co-channel Interference

In this paper, we investigate the end-to-end performance of dual-hop proactive decode-and-forward relaying networks with Nth best relay selection in the presence of two practical deleterious effects: i) hardware impairment and ii) cochannel interference. In particular, we derive new exact and asymptotic closed-form expressions for the outage probability and average channel capacity of Nth best partial and opportunistic relay selection schemes over Rayleigh fading channels. Insightful discussions are provided. It is shown that, when the system cannot select the best relay for cooperation, the partial relay selection scheme outperforms the opportunistic method under the impact of the same co-channel interference (CCI). In addition, without CCI but under the effect of hardware impairment, it is shown that both selection strategies have the same asymptotic channel capacity. Monte Carlo simulations are presented to corroborate our analysis.

Interpretable semantic vectors from a joint model of brain-and text-based meaning

Vector space models (VSMs) represent word meanings as points in a high dimensional space. VSMs are typically created using a large text corpora, and so represent word semantics as observed in text. We present a new algorithm (JNNSE) that can incorporate a measure of semantics not previously used to create VSMs: brain activation data recorded while people read words. The resulting model takes advantage of the complementary strengths and weaknesses of corpus and brain activation data to give a more complete representation of semantics. Evaluations show that the model 1) matches a behavioral measure of semantics more closely, 2) can be used to predict corpus data for unseen words and 3) has predictive power that generalizes across brain imaging technologies and across subjects. We believe that the model is thus a more faithful representation of mental vocabularies.

Cross-participant modelling based on joint or disjoint feature selection: an fMRI conceptual decoding study

Multivariate classification techniques have proven to be powerful tools for distinguishing experimental conditions in single sessions of functional magnetic resonance imaging (fMRI) data. But they are vulnerable to a considerable penalty in classification accuracy when applied across sessions or participants, calling into question the degree to which fine-grained encodings are shared across subjects. Here, we introduce joint learning techniques, where feature selection is carried out using a held-out subset of a target dataset, before training a linear classifier on a source dataset. Single trials of functional MRI data from a covert property generation task are classified with regularized regression techniques to predict the semantic class of stimuli. With our selection techniques (joint ranking feature selection (JRFS) and disjoint feature selection (DJFS)), classification performance during cross-session prediction improved greatly, relative to feature selection on the source session data only. Compared with JRFS, DJFS showed significant improvements for cross-participant classification. And when using a groupwise training, DJFS approached the accuracies seen for prediction across different sessions from the same participant. Comparing several feature selection strategies, we found that a simple univariate ANOVA selection technique or a minimal searchlight (one voxel in size) is appropriate, compared with larger searchlights.