Debridement of contaminated implants using air-polishing coupled with pH-responsive maximin H5-embedded metal-organic frameworks

The primary goal of peri-implantitis treatments remains the decontamination of implant surfaces exposed to polymicrobial biofilms and renders biocompatibility. In this study, we reported a synergistic strategy for the debridement and re-osteogenesis of contaminated titanium by using erythritol air abrasion (AA) coupled with an as-synthesized pH-responsive antimicrobial agent. Here, the anionic antibacterial peptide Maximin H5 C-terminally deaminated isoform (MH5C) was introduced into the Zeolitic Imidazolate Frameworks (ZIF-8) via a one-pot synthesis process. The formed MH5C@ZIF-8 nanoparticles (NPs) not only possessed suitable stability, but also guarantee the slow-release effect of MH5C. Antibacterial experiments revealed that MH5C@ZIF-8 NPs exhibited excellent antimicrobial abilities toward pathogenic bacteria of peri-implantitis, confirming ZIF-8 NPs as efficient nanoplatforms for delivering antibacterial peptide. To evaluate the comprehensive debridement efficiency, single-species as well as mixed-species biofilms were successively established on commercially used titanium surfaces and decontaminated with different methods: removed only by erythritol air abrasion, treated merely with MH5C@ZIF-8 NPs, or received both managements. The results demonstrated that only erythritol air abrasion accompanied with MH5C@ZIF-8 NPs at high concentrations eliminated almost all retained bacteria and impeded biofilm rehabilitation, while neither erythritol air abrasion nor MH5C@ZIF-8 NPs alone could achieve this. Subsequently, we evaluated the re-osteogenesis on previously contaminated surfaces which were treated with different debridement methods afterwards. We found that cell growth and osteogenic differentiation of bone marrow–derived mesenchymal stem cells (BMSCs) in the group received both treatments (AA + MH5C@ZIF-8) were higher than those in other groups. Our work emphasized the great potential of the synergistic therapy as a credible alternative for removing microorganisms and rendering re-osseointegration on contaminated implant surfaces, boding well for the comprehensive applications in peri-implantitis treatments

Relevant domains, core outcome sets and measurements for implant dentistry clinical trials: The Implant Dentistry Core Outcome Set and Measurement (ID-COSM) international consensus report

AIM: Lack of consistently reported outcomes limits progress in evidence-based implant dentistry and quality of care. The objective of this initiative was to develop a core outcome set (COS) and measurements for implant dentistry clinical trials (ID-COSM). MATERIALS AND METHODS: This Core Outcome Measures in Effectiveness Trials (COMET)-registered international initiative comprised six steps over 24 months: (i) systematic reviews of outcomes reported in the last 10 years; (ii) international patient focus groups; (iii) a Delphi project with a broad range of stakeholders (care providers, clinical researchers, methodologists, patients and industry representatives); (iv) expert group discussions organizing the outcomes in domains using a theoretical framework and identifying the COSs; (v) identification of valid measurement systems to capture the different domains and (vi) final consensus and formal approval involving experts and patients. The methods were modified from the best practice approach following the Outcome Measures in Rheumatoid Arthritis Clinical Trial and COMET manuals. RESULTS: The systematic reviews and patient focus groups identified 754 (665 + 89, respectively) relevant outcome measures. After elimination of redundancies and duplicates, 111 were formally assessed in the Delphi project. By applying pre-specified filters, the Delphi process identified 22 essential outcomes. These were reduced to 13 after aggregating alternative assessments of the same features. The expert committee organized them into four core outcome areas: (i) pathophysiology, (ii) implant/prosthesis lifespan, (iii) life impact and (iv) access to care. In each area, core outcomes were identified to capture both the benefits and harms of therapy. Mandatory outcome domains included assessment of surgical morbidity and complications, peri-implant tissue health status, intervention-related adverse events, complication-free survival and overall patient satisfaction and comfort. Outcomes deemed mandatory in specific circumstances comprised function (mastication, speech, aesthetics and denture retention), quality of life, effort for treatment and maintenance and cost effectiveness. Specialized COSs were identified for bone and soft-tissue augmentation procedures. The validity of measurement instruments ranged from international consensus (peri-implant tissue health status) to early identification of important outcomes (patient-reported outcomes identified by the focus groups). CONCLUSIONS: The ID-COSM initiative reached a consensus on a core set of mandatory outcomes for clinical trials in implant dentistry and/or soft tissue/bone augmentation. Adoption in future protocols and reporting on the respective domain areas by currently ongoing trials will contribute to improving evidence-informed implant dentistry and quality of care

Relevant domains, core outcome sets and measurements for implant dentistry clinical trials: The Implant Dentistry Core Outcome Set and Measurement (ID-COSM) international consensus report

AimLack of consistently reported outcomes limits progress in evidence‐based implant dentistry and quality of care. The objective of this initiative was to develop a core outcome set (COS) and measurements for implant dentistry clinical trials (ID‐COSM).Materials and MethodsThis Core Outcome Measures in Effectiveness Trials (COMET)‐registered international initiative comprised six steps over 24 months: (i) systematic reviews of outcomes reported in the last 10 years; (ii) international patient focus groups; (iii) a Delphi project with a broad range of stakeholders (care providers, clinical researchers, methodologists, patients and industry representatives); (iv) expert group discussions organizing the outcomes in domains using a theoretical framework and identifying the COSs; (v) identification of valid measurement systems to capture the different domains and (vi) final consensus and formal approval involving experts and patients. The methods were modified from the best practice approach following the Outcome Measures in Rheumatoid Arthritis Clinical Trial and COMET manuals.ResultsThe systematic reviews and patient focus groups identified 754 (665 + 89, respectively) relevant outcome measures. After elimination of redundancies and duplicates, 111 were formally assessed in the Delphi project. By applying pre‐specified filters, the Delphi process identified 22 essential outcomes. These were reduced to 13 after aggregating alternative assessments of the same features. The expert committee organized them into four core outcome areas: (i) pathophysiology, (ii) implant/prosthesis lifespan, (iii) life impact and (iv) access to care. In each area, core outcomes were identified to capture both the benefits and harms of therapy. Mandatory outcome domains included assessment of surgical morbidity and complications, peri‐implant tissue health status, intervention‐related adverse events, complication‐free survival and overall patient satisfaction and comfort. Outcomes deemed mandatory in specific circumstances comprised function (mastication, speech, aesthetics and denture retention), quality of life, effort for treatment and maintenance and cost effectiveness. Specialized COSs were identified for bone and soft‐tissue augmentation procedures. The validity of measurement instruments ranged from international consensus (peri‐implant tissue health status) to early identification of important outcomes (patient‐reported outcomes identified by the focus groups).ConclusionsThe ID‐COSM initiative reached a consensus on a core set of mandatory outcomes for clinical trials in implant dentistry and/or soft tissue/bone augmentation. Adoption in future protocols and reporting on the respective domain areas by currently ongoing trials will contribute to improving evidence‐informed implant dentistry and quality of care

Smart Bacteria-Responsive Drug Delivery Systems in Medical Implants

With the rapid development of implantable biomaterials, the rising risk of bacterial infections has drawn widespread concern. Due to the high recurrence rate of bacterial infections and the issue of antibiotic resistance, the common treatments of peri-implant infections cannot meet the demand. In this context, stimuli-responsive biomaterials have attracted attention because of their great potential to spontaneously modulate the drug releasing rate. Numerous smart bacteria-responsive drug delivery systems (DDSs) have, therefore, been designed to temporally and spatially release antibacterial agents from the implants in an autonomous manner at the infected sites. In this review, we summarized recent advances in bacteria-responsive DDSs used for combating bacterial infections, mainly according to the different trigger modes, including physical stimuli-responsive, virulence-factor-responsive, host-immune-response responsive and their combinations. It is believed that the smart bacteria-responsive DDSs will become the next generation of mainstream antibacterial therapies

The l2,1-Norm Stacked Robust Autoencoders for Domain Adaptation

Recently, deep learning methods that employ stacked denoising autoencoders (SDAs) have been successfully applied in domain adaptation. Remarkable performance in multi-domain sentiment analysis datasets has been reported, making deep learning a promising approach to domain adaptation problems. SDAs are distinguished by learning robust data representations for recovering the original features that have been artificially corrupted with noise. The idea has been further exploited to marginalize out the random corruptions by a state-of-the-art method called mSDA. In this paper, a deep learning method for domain adaptation called l2,1-norm stacked robust autoencoders (l2,1-SRA) is proposed to learn useful representations for domain adaptation tasks. Each layer of l2,1-SRA contains two steps: a robust linear reconstruction step which is based on l2,1 robust regression and a non-linear squashing transformation step. The experimental results demonstrate that the proposed method is very effective in multiple cross domain classification datasets which include Amazon review dataset, spam dataset from ECML/PKDD discovery challenge 2006 and 20 newsgroups dataset

Infestation of Platypodine Beetles (Coleoptera: Curculionidae) on Rubber Trees in China

Lai, Shengchang, Wang, Jianguo, Fu, Yueguan, Duan, Bo, Hongchang, A, Zhang, Ling, Tarno, Hagus (2020): Infestation of Platypodine Beetles (Coleoptera: Curculionidae) on Rubber Trees in China. The Coleopterists Bulletin 74 (3): 626-631, DOI: 10.1649/0010-065X-74.3.626, URL: http://dx.doi.org/10.1649/0010-065x-74.3.62