Periodontitis is a complex chronic inflammatory noncommunicable disease, initiated by the development of a dysbiotic microbial plaque biofilm below the gingival margin. Whilst the pathogenic biofilm ...is a “necessary cause” of periodontitis, it is insufficient on its own to cause the disease, and a destructive immune‐inflammatory response is a key to the translation of risk to destructive events. Other exposures or “component causes” include individual genetic predisposition, lifestyle (including smoking and nutrition), and environmental factors. Dietary nutrients are essential for life as they provide crucial energy sources in the form of macronutrients, as well as important cofactors in the form of micronutrients, which regulate the functionality of enzymes during the regulation of anabolic and catabolic processes in human cells. Moreover, micronutrients can regulate gene transcription factors, such as the proinflammatory nuclear factor kappa B and the anti‐inflammatory nuclear factor (erythroid‐derived 2)‐like 2. This review focuses on the role of vitamins (vitamin A, carotenoids, the vitamin B complex, vitamins C, D, and E, and coenzyme Q10) and minerals (calcium, magnesium, iron, zinc, potassium, copper, manganese, and selenium) in human physiology and the impact of their deficiencies upon periodontal health and disease.
Interactive volume rendering in its standard formulation has become an increasingly important tool in many application domains. In recent years several advanced volumetric illumination techniques to ...be used in interactive scenarios have been proposed. These techniques claim to have perceptual benefits as well as being capable of producing more realistic volume rendered images. Naturally, they cover a wide spectrum of illumination effects, including varying shading and scattering effects. In this survey, we review and classify the existing techniques for advanced volumetric illumination. The classification will be conducted based on their technical realization, their performance behaviour as well as their perceptual capabilities. Based on the limitations revealed in this review, we will define future challenges in the area of interactive advanced volumetric illumination.
Interactive volume rendering in its standard formulation has become an increasingly important tool in many application domains. In recent years several advanced volumetric illumination techniques to be used in interactive scenarios have been proposed. These techniques claim to have perceptual benefits as well as being capable of producing more realistic volume rendered images. Naturally, they cover a wide spectrum of illumination effects, including varying shading and scattering effects. In this survey, we review and classify the existing techniques for advanced volumetric illumination. The classification will be conducted based on their technical realization, their performance behavior as well as their perceptual capabilities.
Objective
To evaluate the influence of implant and prosthetic components on peri‐implant tissue health. A further aim was to evaluate peri‐implant soft‐tissue changes following surgical ...peri‐implantitis treatment.
Materials and methods
Group discussions based on two systematic reviews (SR) and one critical review (CR) addressed (i) the influence of implant material and surface characteristics on the incidence and progression of peri‐implantitis, (ii) implant and restorative design elements and the associated risk for peri‐implant diseases, and (iii) peri‐implant soft‐tissue level changes and patient‐reported outcomes following peri‐implantitis treatment. Consensus statements, clinical recommendations, and implications for future research were discussed within the group and approved during plenary sessions.
Results
Data from preclinical in vivo studies demonstrated significantly greater radiographic bone loss and increased area of inflammatory infiltrate at modified compared to non‐modified surface implants. Limited clinical data did not show differences between modified and non‐modified implant surfaces in incidence or progression of peri‐implantitis (SR). There is some evidence that restricted accessibility for oral hygiene and an emergence angle of >30 combined with a convex emergence profile of the abutment/prosthesis are associated with an increased risk for peri‐implantitis (CR). Reconstructive therapy for peri‐implantitis resulted in significantly less soft‐tissue recession, when compared with access flap. Implantoplasty or the adjunctive use of a barrier membrane had no influence on the extent of peri‐implant mucosal recession following peri‐implantitis treatment (SR).
Conclusions
Prosthesis overcontouring and impaired access to oral hygiene procedures increases risk for peri‐implantitis. When indicated, reconstructive peri‐implantitis treatment may facilitate the maintenance of post‐operative peri‐implant soft‐tissue levels.
Using body mass index (BMI) as a proxy, previous Mendelian randomization (MR) studies found total causal effects of general obesity on polycystic ovarian syndrome (PCOS). Hitherto, total and direct ...causal effects of general- and central obesity on PCOS have not been comprehensively analyzed.
To investigate the causality of central- and general obesity on PCOS using surrogate anthropometric markers.
Summary GWAS data of female-only, large-sample cohorts of European ancestry were retrieved for anthropometric markers of central obesity (waist circumference (WC), hip circumference (HC), waist-to-hip ratio (WHR)) and general obesity (BMI and its constituent variables-weight and height), from the IEU Open GWAS Project. As the outcome, we acquired summary data from a large-sample GWAS (118870 samples; 642 cases and 118228 controls) within the FinnGen cohort. Total causal effects were assessed via univariable two-sample Mendelian randomization (2SMR). Genetic architectures underlying causal associations were explored. Direct causal effects were analyzed by multivariable MR modelling.
Instrumental variables demonstrated no weak instrument bias (F > 10). Four anthropometric exposures, namely, weight (2.69-77.05), BMI (OR: 2.90-4.06), WC (OR: 6.22-20.27), and HC (OR: 6.22-20.27) demonstrated total causal effects as per univariable 2SMR models. We uncovered shared and non-shared genetic architectures underlying causal associations. Direct causal effects of WC and HC on PCOS were revealed by two multivariable MR models containing exclusively the anthropometric markers of central obesity. Other multivariable MR models containing anthropometric markers of both central- and general obesity showed no direct causal effects on PCOS.
Both and general- and central obesity yield total causal effects on PCOS. Findings also indicated potential direct causal effects of normal weight-central obesity and more complex causal mechanisms when both central- and general obesity are present. Results underscore the importance of addressing both central- and general obesity for optimizing PCOS care.
To identify predictors of prediabetes using feature selection and machine learning on a nationally representative sample of the US population.
We analyzed n = 6346 men and women enrolled in the ...National Health and Nutrition Examination Survey 2013-2014. Prediabetes was defined using American Diabetes Association guidelines. The sample was randomly partitioned to training (n = 3174) and internal validation (n = 3172) sets. Feature selection algorithms were run on training data containing 156 preselected exposure variables. Four machine learning algorithms were applied on 46 exposure variables in original and resampled training datasets built using 4 resampling methods. Predictive models were tested on internal validation data (n = 3172) and external validation data (n = 3000) prepared from National Health and Nutrition Examination Survey 2011-2012. Model performance was evaluated using area under the receiver operating characteristic curve (AUROC). Predictors were assessed by odds ratios in logistic models and variable importance in others. The Centers for Disease Control (CDC) prediabetes screening tool was the benchmark to compare model performance.
Prediabetes prevalence was 23.43%. The CDC prediabetes screening tool produced 64.40% AUROC. Seven optimal (≥ 70% AUROC) models identified 25 predictors including 4 potentially novel associations; 20 by both logistic and other nonlinear/ensemble models and 5 solely by the latter. All optimal models outperformed the CDC prediabetes screening tool (P < 0.05).
Combined use of feature selection and machine learning increased predictive performance outperforming the recommended screening tool. A range of predictors of prediabetes was identified.
This work demonstrated the value of combining feature selection with machine learning to identify a wide range of predictors that could enhance prediabetes prediction and clinical decision-making.
We present a method for interactive global illumination of both static and time-varying volumetric data based on reduction of the overhead associated with re-computation of photon maps. Our method ...uses the identification of photon traces invariant to changes of visual parameters such as the transfer function (TF), or data changes between time-steps in a 4D volume. This lets us operate on a variant subset of the entire photon distribution. The amount of computation required in the two stages of the photon mapping process, namely tracing and gathering, can thus be reduced to the subset that are affected by a data or visual parameter change. We rely on two different types of information from the original data to identify the regions that have changed. A low resolution uniform grid containing the minimum and maximum data values of the original data is derived for each time step. Similarly, for two consecutive time-steps, a low resolution grid containing the difference between the overlapping data is used. We show that this compact metadata can be combined with the transfer function to identify the regions that have changed. Each photon traverses the low-resolution grid to identify if it can be directly transferred to the next photon distribution state or if it needs to be recomputed. An efficient representation of the photon distribution is presented leading to an order of magnitude improved performance of the raycasting step. The utility of the method is demonstrated in several examples that show visual fidelity, as well as performance. The examples show that visual quality can be retained when the fraction of retraced photons is as low as 40%-50%.
The complexity of today's visualization applications demands specific visualization systems tailored for the development of these applications. Frequently, such systems utilize levels of abstraction ...to improve the application development process, for instance by providing a data flow network editor. Unfortunately, these abstractions result in several issues, which need to be circumvented through an abstraction-centered system design. Often, a high level of abstraction hides low level details, which makes it difficult to directly access the underlying computing platform, which would be important to achieve an optimal performance. Therefore, we propose a layer structure developed for modern and sustainable visualization systems allowing developers to interact with all contained abstraction levels. We refer to this interaction capabilities as usage abstraction levels, since we target application developers with various levels of experience. We formulate the requirements for such a system, derive the desired architecture, and present how the concepts have been exemplary realized within the Inviwo visualization system. Furthermore, we address several specific challenges that arise during the realization of such a layered architecture, such as communication between different computing platforms, performance centered encapsulation, as well as layer-independent development by supporting cross layer documentation and debugging capabilities.
Using a nationally-representative, cross-sectional cohort, we examined nutritional markers of undiagnosed type 2 diabetes in adults via machine learning.
A total of 16429 men and non-pregnant women ≥ ...20 years of age were analysed from five consecutive cycles of the National Health and Nutrition Examination Survey. Cohorts from years 2013-2016 (n = 6673) was used for external validation. Undiagnosed type 2 diabetes was determined by a negative response to the question "Have you ever been told by a doctor that you have diabetes?" and a positive glycaemic response to one or more of the three diagnostic tests (HbA1c > 6.4% or FPG >125 mg/dl or 2-hr post-OGTT glucose > 200mg/dl). Following comprehensive literature search, 114 potential nutritional markers were modelled with 13 behavioural and 12 socio-economic variables. We tested three machine learning algorithms on original and resampled training datasets built using three resampling methods. From this, the derived 12 predictive models were validated on internal- and external validation cohorts. Magnitudes of associations were gauged through odds ratios in logistic models and variable importance in others. Models were benchmarked against the ADA diabetes risk test.
The prevalence of undiagnosed type 2 diabetes was 5.26%. Four best-performing models (AUROC range: 74.9%-75.7%) classified 39 markers of undiagnosed type 2 diabetes; 28 via one or more of the three best-performing non-linear/ensemble models and 11 uniquely by the logistic model. They comprised 14 nutrient-based, 12 anthropometry-based, 9 socio-behavioural, and 4 diet-associated markers. AUROC of all models were on a par with ADA diabetes risk test on both internal and external validation cohorts (p>0.05).
Models performed comparably to the chosen benchmark. Novel behavioural markers such as the number of meals not prepared from home were revealed. This approach may be useful in nutritional epidemiology to unravel new associations with type 2 diabetes.
The primary aim of this current systematic review and meta-analysis was to evaluate the potential microbiological effect of probiotics on the implant microbiota. The secondary aim was to evaluate if ...probiotics have any effect as an adjunct to non-surgical peri-implant treatment in reducing peri-implant mucositis and peri-implantitis clinical parameters-bleeding on probing, modified Gingival Index, and pocket depth.
The research focus questions were constructed in accordance with the Participants, Intervention, Comparison, and Outcomes (PICO) criteria, and a PROSPERO protocol was registered. A comprehensive systematic search in MEDLINE
the PubMed, Scopus, and Web of Science Core Collection databases was conducted. Two independent reviewers screened the reports based on the PICO criteria-inclusion and exclusion criteria.
In total, 467 records were identified, and ultimately, 7 papers were included: 3 papers in the qualitative synthesis of microbiological effect and 4 in the meta-analysis synthesis on pocket depth. The data synthesis showed that probiotics had no detectable effect on the implant microflora, and in the following data synthesis, no clinical peri-implantitis variable showed a significantly beneficial effect from probiotics in the test group compared to the control group.
Within the limitations of this review, the oral implant microflora is not affected by probiotics nor do probiotics add any effect to the conventional non-surgical treatment of peri-implant mucositis and peri-implantitis.
In this work we present a volume exploration method designed to be used by novice users and visitors to science centers and museums. The volumetric digitalization of artifacts in museums is of ...rapidly increasing interest as enhanced user experience through interactive data visualization can be achieved. This is, however, a challenging task since the vast majority of visitors are not familiar with the concepts commonly used in data exploration, such as mapping of visual properties from values in the data domain using transfer functions. Interacting in the data domain is an effective way to filter away undesired information but it is difficult to predict where the values lie in the spatial domain. In this work we make extensive use of dynamic previews instantly generated as the user explores the data domain. The previews allow the user to predict what effect changes in the data domain will have on the rendered image without being aware that visual parameters are set in the data domain. Each preview represents a subrange of the data domain where overview and details are given on demand through zooming and panning. The method has been designed with touch interfaces as the target platform for interaction. We provide a qualitative evaluation performed with visitors to a science center to show the utility of the approach.
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