Developing Children's Oral Health Assessment Toolkits Using Machine Learning Algorithm.

ObjectivesEvaluating children's oral health status and treatment needs is challenging. We aim to build oral health assessment toolkits to predict Children's Oral Health Status Index (COHSI) score and referral for treatment needs (RFTN) of oral health. Parent and Child toolkits consist of short-form survey items (12 for children and 8 for parents) with and without children's demographic information (7 questions) to predict the child's oral health status and need for treatment.MethodsData were collected from 12 dental practices in Los Angeles County from 2015 to 2016. We predicted COHSI score and RFTN using random Bootstrap samples with manually introduced Gaussian noise together with machine learning algorithms, such as Extreme Gradient Boosting and Naive Bayesian algorithms (using R). The toolkits predicted the probability of treatment needs and the COHSI score with percentile (ranking). The performance of the toolkits was evaluated internally and externally by residual mean square error (RMSE), correlation, sensitivity and specificity.ResultsThe toolkits were developed based on survey responses from 545 families with children aged 2 to 17 y. The sensitivity and specificity for predicting RFTN were 93% and 49% respectively with the external data. The correlation(s) between predicted and clinically determined COHSI was 0.88 (and 0.91 for its percentile). The RMSEs of the COHSI toolkit were 4.2 for COHSI (and 1.3 for its percentile).ConclusionsSurvey responses from children and their parents/guardians are predictive for clinical outcomes. The toolkits can be used by oral health programs at baseline among school populations. The toolkits can also be used to quantify differences between pre- and post-dental care program implementation. The toolkits' predicted oral health scores can be used to stratify samples in oral health research.Knowledge transfer statementThis study creates the oral health toolkits that combine self- and proxy- reported short forms with children's demographic characteristics to predict children's oral health and treatment needs using Machine Learning algorithms. The toolkits can be used by oral health programs at baseline among school populations to quantify differences between pre and post dental care program implementation. The toolkits can also be used to stratify samples according to the treatment needs and oral health status

Developing a Standard Set of Patient-centred Outcomes for Adult Oral Health - An International, Cross-disciplinary Consensus.

OBJECTIVE: To develop a minimum Adult Oral Health Standard Set (AOHSS) for use in clinical practice, research, advocacy and population health. MATERIALS AND METHODS: An international oral health working group (OHWG) was established, of patient advocates, researchers, clinicians and public health experts to develop an AOHSS. PubMed was searched for oral health clinical and patient-reported measures and case-mix variables related to caries and periodontal disease. The selected patient-reported outcome measures focused on general oral health, and oral health-related quality of life tools. A consensus was reached via Delphi with parallel consultation of subject matter content experts. Finally, comments and input were elicited from oral health stakeholders globally, including patients/consumers. RESULTS: The literature search yielded 1,453 results. After inclusion/exclusion criteria, 959 abstracts generated potential outcomes and case-mix variables. Delphi rounds resulted in a consensus-based selection of 80 individual items capturing 31 outcome and case-mix concepts. Global reviews generated 347 responses from 87 countries, and the patient/consumer validation survey elicited 129 responses. This AOHSS includes 25 items directed towards patients (including demographics, the impact of their oral health on oral function, a record of pain and oral hygiene practices, and financial implications of care) and items for clinicians to complete, including medical history, a record of caries and periodontal disease activity, and types of dental treatment delivered. CONCLUSION: In conclusion, utilising a robust methodology, a standardised core set of oral health outcome measures for adults, with a particular emphasis on caries and periodontal disease, was developed

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Genetic aspects of dental disorders

The document attached has been archived with permission from the Australian Dental Association. An external link to the publisher’s copy is included.This paper reviews past and present applications of quantitative and molecular genetics to dental disorders. Examples are given relating to craniofacial development (including malocclusion), oral supporting tissues (including periodontal diseases) and dental hard tissues (including defects of enamel and dentine as well as dental caries). Future developments and applications to clinical dentistry are discussed. Early investigations confirmed genetic bases to dental caries, periodontal diseases and malocclusion, but research findings have had little impact on clinical practice. The complex multifactorial aetiologies of these conditions, together with methodological problems, have limited progress until recently. Present studies are clarifying previously unrecognized genetic and phenotypic heterogeneities and attempting to unravel the complex interactions between genes and environment by applying new statistical modelling approaches to twin and family data. linkage studies using highly polymorphic DNA markers are providing a means of locating candidate genes, including quantitative trait loci (QTL). In future, as knowledge increases: it should be possible to implement preventive strategies for those genetically-predisposed individuals who are identified-predisposed individuals who are identified to be at risk.Grant C. Townsend, Michael J. Aldred and P. Mark Bartol

Foraging in an unsteady world: bumblebee flight performance in field-realistic turbulence

Natural environments are characterized by variable wind that can pose significant challenges for flying animals and robots. However, our understanding of the flow conditions that animals experience outdoors and how these impact flight performance remains limited. Here, we combine laboratory and field experiments to characterize wind conditions encountered by foraging bumblebees in outdoor environments and test the effects of these conditions on flight. We used radio-frequency tags to track foraging activity of uniquely identified bumblebee (Bombus impatiens) workers, while simultaneously recording local wind flows. Despite being subjected to a wide range of speeds and turbulence intensities, we find that bees do not avoid foraging in windy conditions. We then examined the impacts of turbulence on bumblebee flight in a wind tunnel. Rolling instabilities increased in turbulence, but only at higher wind speeds. Bees displayed higher mean wingbeat frequency and stroke amplitude in these conditions, as well as increased asymmetry in stroke amplitude-suggesting that bees employ an array of active responses to enable flight in turbulence, which may increase the energetic cost of flight. Our results provide the first direct evidence that moderate, environmentally relevant turbulence affects insect flight performance, and suggest that flying insects use diverse mechanisms to cope with these instabilities